Prepared by the U.S. Geological Survey,

Office of Ground Water, Ground-Water Resources Program

Chapter 17 of

Section A, Ground Water, of

Book 6, Modeling Techniques

U.S. Department of the Interior

U.S. Geological Survey

Techniques and Methods 6–A17

User Guide for the Farm Process (FMP1) for the

U.S. Geological Survey’s Modular Three-Dimensional 

Finite-Difference Ground-Water Flow Model, MODFLOW-2000 
User Guide for the Farm Process (FMP1) 

for the U.S. Geological Survey’s Modular 

Three-Dimensional Finite-Difference 

Ground-Water Flow Model, MODFLOW-2000 

By Wolfgang Schmid1, R.T. Hanson, Thomas Maddock III2, and S.A. Leake

Prepared by the U.S. Geological Survey, 

Office of Ground Water, Ground-Water Resources Program

Techniques and Methods 6–A17

U.S. Department of the Interior

U.S. Geological Survey

1

Research Hydrologist, Department of Hydrology and Water Resources, 

University of Arizona 2

Professor and Department Head, Department of Hydrology and Water Resources, 

University of Arizona
U.S. Department of the Interior

P. Lynn Scarlett, Acting Secretary

U.S. Geological Survey

P. Patrick Leahy, Acting Director

U.S. Geological Survey, Reston, Virginia: 2006

For product and ordering information:

World Wide Web: http://www.usgs.gov/pubprod

Telephone: 1-888-ASK-USGS

For more information on the USGS--the Federal source for science about the Earth, its natural and living resources, 

natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted materials contained within this report.

Suggested citation:

Schmid, Wolfgang, Hanson, R.T., Maddock, Thomas, III, Leake, S.A., 2006, User guide for the farm process (FMP1) 

for the U.S. Geological Survey’s modular three-dimensional finite-difference ground-water flow model, MODFLOW2000: U.S. Geological Survey Techniques and Methods 6-A17, 127 p.
iii

Preface

This report presents a computer program for simulating the consumption and redistribution of surface water and ground water from farming in the U.S. Geological Survey (USGS) 

ground-water model, MODFLOW. The performance of this computer program has been tested 

in models of hypothetical ground-water flow systems; however, future applications of the programs could reveal errors that were not detected in the test simulations. Users are requested to 

notify the USGS if errors are found in the report or in the computer program. Correspondence 

regarding the report or program should be sent to: 

U.S. Geological Survey

Water Resources Discipline

4165 Spruance Road, Suite 200

San Diego, CA 92101

Attention: Randall T. Hanson

Although this program has been used by the USGS, no warranty, expressed or implied, is 

made by the authors, the USGS, or the United States Government as to the accuracy and functioning of the program and related program material. Nor shall the fact of distribution constitute 

any such warranty, and no responsibility is assumed by the authors or the USGS in connection 

therewith.

The computer program described herein consists in part of copyrighted scientific methodologies obtained from the copyright holder (Schmid, 2004). The copyright holder has granted 

full quotation, copy and use of these methods to the USGS and to the public. Requests for 

modification of copyrighted methods and for publication of such can be made to the copyright 

holder or to the address listed above.

The computer program documented in this report is part of the MODFLOW-2000 groundwater flow model. These and other ground-water programs are available from the USGS at 

World Wide Web address:

http://h2o.usgs.gov/software/

or by anonymous ftp file transfer from directory: 

/pub/software/ground_water/modflow at Internet address h2o.usgs.gov
iv

Contents

Abstract ..........................................................................................................................................................1

Introduction ....................................................................................................................................................2

Irrigation Water Demand and Supply ...............................................................................................4

Previous Simulation of Crop Demand and Irrigation Water Supply .............................................7

Modeling Agricultural Irrigation Supply and Demand....................................................................8

Purpose and Scope ..............................................................................................................................8

Acknowledgements..............................................................................................................................8

Farm Process Capabilities............................................................................................................................8

Consumptive Use ................................................................................................................................10

Transpiration for Water Levels between Ground Surface and Bottom of Root Zone ....11

Consumptive-Use Concept 1...........................................................................................11

Consumptive-Use Concept 2...........................................................................................14

Transpiration for Water Levels between Bottom of the Root Zone and the 

Extinction Depth ...........................................................................................................15

Evaporation for Water Levels between Ground Surface and Extinction Depth..............16

Head-Dependent Transpiration from Precipitation..............................................................16

Head-Dependent Crop Irrigation Requirement.....................................................................16

Surface-Water Supply .......................................................................................................................17

Ground-Water Supply ........................................................................................................................19

Net Recharge.......................................................................................................................................20

Water-Rights Allocation.....................................................................................................................22

Equal Appropriation with Specified Canal Diversions.........................................................22

Prior Appropriation with Simulated Canal Diversion...........................................................23

No Senior Farm Downstream of the Farm of Interest on the Same Canal..............26

Senior Farm Exists Downstream of the Farm of Interest on the Same Canal.........26

No Senior Farms Exist on Downstream Diverting Canal (Case A)............................27

Senior Farms Exist on Downstream Diversion Canal (Case B) .................................27

Modification of Prior Appropriation System for Surface-Water Surplus.............. 28

Drought Scenario Alternatives.........................................................................................................30

Update of Source Term Flow Rates ...............................................................................30

Applicability and Limitations.............................................................................................................33

General Data Requirements.......................................................................................................................33

Arrays and Lists of Spatially Distributed Data ...............................................................................33

Two-Dimensional Arrays ..........................................................................................................34

Ground-Surface Elevation...............................................................................................34

Identification Arrays.........................................................................................................34

Multi-Dimensional Attribute Lists ...........................................................................................35

Farm Wells .........................................................................................................................35

Stream Segments and Reaches.....................................................................................35

Data Requirements for Entire Simulation .......................................................................................36

Farm-Wells Data ........................................................................................................................36

Farm Data....................................................................................................................................40
v

Farm Irrigation Efficiency ................................................................................................40

Soil-Type Data ............................................................................................................................42

Crop-Type Data (Natural)..........................................................................................................44

Root-Zone Depth...............................................................................................................44

Fraction of Transpiration and Evaporation of Consumptive Use...............................44

Fraction of Inefficiency Losses to Surface-Water Runoff .........................................46

Root-Uptake Coefficients for Stress Response Function...........................................46

Specific Crop Coefficients...............................................................................................47

Climate Data................................................................................................................................48

Crop-Type Data (Agro-Economic)...........................................................................................49

Crop-Type-Related Fallow Flags.....................................................................................49

Crop-Type Benefits Data..................................................................................................49

Water-Cost Coefficients...................................................................................................51

Surface-Water Data ..................................................................................................................53

Nonrouted Deliveries .......................................................................................................53

Routed Deliveries..............................................................................................................53

Semi-Routed Deliveries ...................................................................................................53

Fully-Routed Deliveries....................................................................................................54

Stream-Reach Data..........................................................................................................54

Data Requirements for each Stress-Period ...................................................................................54

Farm-Wells Data ........................................................................................................................55

Nonparameter or Parameter Farm-Wells Lists............................................................55

Farm Irrigation Efficiencies......................................................................................................56

Crop-Type Arrays and Data (Natural Attributes)..................................................................56

Crop-Type Identification Array .......................................................................................56

Crop-Type Data..................................................................................................................57

Climate Data................................................................................................................................58

Precipitation Array ...........................................................................................................58

Crop-Type Data (Agro-Economic)...........................................................................................58

Crop-Type Benefits Data..................................................................................................58

Water-Cost Coefficients............................................................................................................59

Surface-Water Data ..................................................................................................................59

Nonrouted Surface-Water Deliveries ...........................................................................59

Routed Surface-Water Deliveries..................................................................................61

Water-Rights Data ............................................................................................................63

Data Input Instructions ...............................................................................................................................64

Input Data for the FMP1.....................................................................................................................65

Data for each Simulation..........................................................................................................65

Data for each Stress Period.....................................................................................................66

Input Structure of Array and List Reading Utility Modules..........................................................67

Control-Record Item a...............................................................................................................67

Control-Record Item b...............................................................................................................68

Explanation of Fields Used in the Input Instructions ....................................................................69

Dimensions and Flags (item 2).................................................................................................69

Parameter Dimensions (item 2) ......................................................................................69
vi

Farm-Well Related Variables (items 3, 4, 22, 23)...................................................................74

Farm Well Parameter Definition (item 3):......................................................................74

Two-Dimensional Arrays (items 5, 6, 8, 10, 25, 30)................................................................75

Farm Related Data Lists (items 7, 19, 20, 24, 32, 33, 34, 36)..................................................75

Soil Type Related Data List (item 9).........................................................................................75

Crop-Type-Related Data List (Natural Crop Growth Parameters) (items 11−15, 25−29)76

Climate-Related Data (items 16, 30)........................................................................................76

Climate Time Series (item 16):.........................................................................................76

Precipitation Array (item 30): ..........................................................................................77

Crop-Type-Related Data Lists (Agro-Economic Parameters) (items 17, 18, 31) ..............77

Fallow List (item 17): .........................................................................................................77

Water Cost Coefficients (items 19, 32)....................................................................................77

Ground-Water Cost Coefficients: ...................................................................................77

Surface-Water Cost Coefficients: ..................................................................................77

Nonrouted Surface-Water Deliveries–Farm-Related Data List (item 33).........................77

Semi-Routed Surface-Water Deliveries–Farm-Related Data List (items 20, 34).............78

Surface-Water Allotment (items 35, 36).................................................................................78

Equal Appropriation:.........................................................................................................78

Prior Appropriation:..........................................................................................................78

Ouput Data for Farm Process ...........................................................................................................78

Farm-Well Budget......................................................................................................................79

Farm Net-Recharge Budget.....................................................................................................79

Farm Supply and Demand Budget ..........................................................................................79

Optimized Flow Rates and Optimized Acreage of Farms ....................................................80

Budgets at Points of Canal Diversion and Farm Diversion ................................................81

Example Problems .......................................................................................................................................82

References Cited........................................................................................................................................102

Appendix......................................................................................................................................................105
vii

Figures

Figure 1. Diagram showing supply and demand components and relations to potential 

 applications of MODFLOW-2000 with the FMP1...............................................................2

Figure 2. Diagram showing supply and demand components and connections to other 

 models and packages by the FMP1....................................................................................3

Figure 3. Diagram showing flow chart of the flow of water into and out of the Farm 

 Budget as simulated by the FMP1 ......................................................................................5

Figure 4. Diagram showing cases of sufficiency and insufficiency of irrigation water 

 supply in a surface-water dominated irrigation setting..................................................9

Figure 5. Graph showing transient course of root uptake and flux across the water 

 table or different depths to water table ...........................................................................13

Figure 6. Graph showing variation of actual root uptake from ground water, and of 

 maximum actual root uptake from ground water and irrigation, with 

 changing water level ..........................................................................................................13

Figure 7. Graph showing linear approximation of pseudo-steady-state root uptake 

 from ground water and maximum actual root uptake from ground water and 

 irrigation water.....................................................................................................................14

Figure 8. Graphs showing crop specific stress response function, and analytical

 function fitting the vertical pressure head distribution over depth ............................15

Figure 9. Diagrams showing two conceptual approximations to change of crop 

 consumptive-use components with varying head ........................................................16

Figure 10. Diagram showing numerical procedure for determining the diversion 

 rate to a canal for farms subject to a water-rights allocation hierarchy...................24

Figure 11. Graphs showing concept of Deficit Irrigation Policy ....................................................29

Figure 12. Graphs showing concept of Water-Stacking Policy .....................................................29

Figure 13. Flowchart showing the updating of source-term flow-rates depending on 

 the drought-response policy chosen ...............................................................................32

Figure 14. Map showing streamflow-routing segment-numbering scheme in 

 relation to direction of flow and model grid ....................................................................36

Figure 15. Diagram showing transpiratory and evaporative fractions of 

 consumptive use..................................................................................................................45

Figure 16. Diagram showing model domain and boundary conditions and initial heads 

 for the FMP1 example problems .......................................................................................83

Figure 17. Diagrams showing model domain with farms and related wells for example 

 problems 1 and 2 and crops and soils for both problems .............................................84

Figure 18. Graphs showing irrigation demand and surface- and ground-water supply for 

 Farms 1, 2, 3, and 4 for example problem 1......................................................................86

Figure 19. Graphs showing irrigation demand and surface- and ground-water supply 

 for Farms 1, 2, 3, and 4 for example problem 2 ...............................................................88

Figure 20. Graph showing spatial distribution of fractions of crop acreage for farm 

 cells in example problem 2 ..............................................................................................101
viii

Tables

Table 1. Summary of variably saturated flow equations and soil-water constitutive 

functions used in HYDRUS2D to develop unsaturated-flow approximations

incorporated in the FMP1..........................................................................................................12

Table 2. Example of soil-type attributes associated with the Soil-Type ID......................................42

Table 3. Summary of Farm Budget Components...................................................................................80

Table 4. Farm Demand and Supply (FDS.OUT), Farm Budget Output for Example Problem 1.......92

Table 5. Farm Demand and Supply (FDS.OUT), Farm Budget Output for Example Problem 2.......96
ix

Multiply By To obtain

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

foot (ft) 0.3048 meter (m)

square foot (ft2) 929.0 square centimeter (cm2)

square foot (ft2) 0.09290 square meter (m2)

pound, avoirdupois (lb) 0.4536 kilogram (kg) 

pound per square foot (lb/ft2) 0.04788 kilopascal (kPa) 

SI/Pound

Multiply By To obtain

centimeter (cm) 0.3937 inch (in)

meter (m) 3.281 foot (ft) 

meter (m) 1.094 yard (yd) 

cubic meter per day (m3/d) 0.000811 acre-foot per day (acre-ft/d)

square meter (m2) 0.0002471 acre 

square centimeter (cm2) 0.001076 square foot (ft2)

square meter (m2) 10.76 square foot (ft2) 

square centimeter (cm2) 0.1550 square inch (ft2) 

hectare (ha) 0.003861 square mile (mi2) 

kilogram (kg) 2.205 pound avoirdupois (lb)

kilogram per cubic meter (kg/m3) 0.06242 pound per cubic foot (lb/ft3) 

kilograms per hectare (kg/ha) 0.8921 pounds per acre (lb/acre)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as 

follows:

°F=(1.8×°C)+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as 

follows:

°C=(°F-32)/1.8

Elevation as used in this report, refers to distance above the vertical datum.

*Transmissivity: The standard unit for transmissivity is cubic foot per day per square foot 

times foot of aquifer thickness [(ft3/d)/ft2]ft. In this report, the mathematically reduced form, foot 

squared per day (ft2/d), is used for convenience.

NOTE TO USGS USERS: Use of hectare (ha) as an alternative name for square hectometer 

(hm2) is restricted to the measurement of small land or water areas. Use of liter (L) as a special 

name for cubic decimeter (dm3) is restricted to the measurement of liquids and gases. No prefix 

other than milli should be used with liter. Metric ton (t) as a name for megagram (Mg) should be 

restricted to commercial usage, and no prefixes should be used with it.

Conversions, Datum, Abbreviations, Acronyms, 

and Variable Definitions

Pound/SI
x

Abbreviations, Acronyms, and Variable Definitions

a(ψ) = dimensionless water stress response function [-]; ∀ 0 ≤ a ≤ 1

ψ = pressure head [L]

[-] = signifies dimensionless units

AI = average available irrigation per cell, in case of irrigation insufficiency [L3/T]

AVI = actual available irrigation per cell, in case of irrigation insufficiency [L3/T]

ARUmax = maximum actual root uptake = Tc-act-max [L/T]·[L2]

ASR = aquifer storage-and-recovery

AZ = depth of anoxia zone [L]

CIR = crop irrigation requirement per cell (CIR = Ei + Ti) [L/T]·[L2]

CU = consumptive use per unit area [L/T], or per cell [L/T]·[L2]

DELact = actual surface-water delivery from a head gate at a canal to a farm [L3/T]

DELpot = potential surface-water delivery to a farm’s head gate [L3/T]

DRZ = depth of depleted root zone = part of root zone at which pressure heads ψ

increase with depth from a minimum pressure head ψ4 to 0 (∀ψ4 < ψ < 0). [L]

Ec-act = actual evaporative consumptive use per cell [L/T]·[L2]

Ec-pot = potential evaporative consumptive use per cell = (1-Kt) ⋅ ETc-pot [L/T]·[L2]

Egw-act = actual evaporation uptake from ground water per cell [L/T]·[L2]

Egw-act-max = maximum evaporation uptake from ground water per cell [L/T]·[L2]

Ei = evaporation requirement from irrigation = Ti · (Ke

i

/Kt), ∀ 0≤ Ke

i

<1, 0<Kt≤ 1 [L/T]·[L2]

Ep = evaporation from precipitation per cell [L/T]·[L2]

Ep-act = actual evaporation from precipitation per cell [L/T]·[L2]

Ep-pot = potential evaporation from precipitation per cell [L/T]·[L2]

ET = evapotranspiration

ETc-act = actual crop evapotranspiration = actual crop consumptive use [L/T]·[L2] 

ETc-pot = potential crop evapotranspiration = potential crop consumptive use [L/T]·[L2]

ETgw = evapotranspiration from ground water per cell [L/T]·[L2]

ETp = evaporation and transpiration from precipitation per cell [L/T]·[L2]

FMP = Farm Process

GDD(d) = Growing Degree Days for a certain crop and a certain day d [°F or °C]

GSE = ground surface elevation [L]

h = aquifer head; potentiometric head [L]

I = applied irrigation per cell [L3/T]

 [sufficiency case: I = TDR or insufficiency case: I = AVI ]

IEsw

I = fraction of inefficient losses to surface-water runoff related to irrigation [-]

IEsw

P = fraction of inefficient losses to surface-water runoff related to precipitation [-]

IGSM = Integrated Ground-Water and Surface-Water Model

IWFM = Integrated Water-Flow Model

Ke

i = evaporative fraction of consumptive use related to irrigation [-]

Ke

p = evaporative fraction of consumptive use related to preciptiation [-]

Kt = transpiratory fraction of consumptive use [-]

MF2K = MODFLOW-2000

MNW = Multi-Node Well Package

n = sinuosity coefficient, expressing curvature of the vertical pressure head configuration over the depth of the root zone in analytical solution [-] 

(unless n does not represent a dimension or numbering index)

NRDf,t

act = actually used nonrouted delivery of type t to farm f [L3

]

NRDf,t

pot =

 potentially available nonrouted delivery of type t to farm f [L3

]

NRDf,t

use =

 binary “NRDuse-Flag” of a nonrouted delivery type t to a farm f
xi

OFE = on-farm efficiency (fraction of applied irrigation, which is needed for evapotranspiration by the crop to avoid undesirable water stress) [-]

P = precipitation per unit area [L/T], or per cell [L/T]·[L2]

QAVF = average required discharge per farm well = QREQ/number of wells in a farm [L3/T]

Qi

max = maximum capacity of each well i = QMAX [L3

/T]

Qdiversion = diversion applied in simulation [L3/T]

Qspec-div = user-specified diversion inflow into first reach of diversion segment [L3/T]

Qstream-inflow = stream-inflow into the last reach of an upstream segment [L3/T]

Qspec-max = user-specified maximum streamflow for last reach of upstream segment [L3/T]

QMAXF = cumulative maximum capacity of all farm wells in a farm [L3/T]

QREQ = a farm’s ground water pumping requirement = TFDR–DELact [L3/T]

RD(d) = root depth for a specific crop and a certain day d [L]

SFR1 = Streamflow Routing Package

Tc-act = actual transpiratory consumptive use per cell [L/T]·[L2]

Tc-act-max = maximum actual transpiratory consumptive use per cell = 

Tc-pot ⋅ [1-AZ/TRZ] [L/T]·[L2]

Tc-pot = potential transpiratory consumptive use per cell = Kt ⋅ ETc-pot [L/T]·[L2]

TDR = total irrigation delivery requirement per cell (TDR = CIR/OFE) [L3/T]

TFDR = total farm irrigation delivery requirement of any one farm [L3/T]

Tgw-act = actual transpiration uptake from ground water per cell [L/T]·[L2]

Tgw-act-max = maximum actual transpiration uptake from ground water per cell =

 Tc-pot ⋅ [1-(AZ+WZ)/TRZ] [L/T]·[L2]

Ti = transpiration requirement from irrigation per cell = Tc-act–Tgw-act–Tp-act [L/T]·[L2]

TNRDf = total of all types of actually used nonrouted deliveries to farm f

Tp = transpiration from precipitation per cell [L/T]·[L2]

Tp-act = actual transpiration from precipitation per cell [L/T]·[L2]

Tp-pot = potential transpiration from precipitation per cell [L/T]·[L2]

TRZ = depth of total root zone [L]

WZ = depth of wilting zone [L]

Organizations

CADWR California Department of Water Resources

USGS U.S. Geological Survey
xii
User Guide for the Farm Process (FMP1) for the 

U.S. Geological Survey’s Modular Three-Dimensional 

Finite-Difference Ground-Water Flow Model, 

MODFLOW-2000 

By Wolfgang Schmid1, R.T. Hanson, Thomas Maddock III2, and S.A. Leake

Abstract 

There is a need to estimate dynamically integrated supply-and-demand components of irrigated agriculture as part of the 

simulation of surface-water and ground-water flow. To meet this need, a computer program called the Farm Process (FMP1) 

was developed for the U.S. Geological Survey three-dimensional finite-difference modular ground-water flow model, MODFLOW-2000 (MF2K). The FMP1 allows MF2K users to simulate conjunctive use of surface- and ground water for irrigated 

agriculture for historical and future simulations, water-rights issues and operational decisions, nondrought and drought scenarios. By dynamically integrating farm delivery requirement, surface- and ground-water delivery, as well as irrigation-return 

flow, the FMP1 allows for the estimation of supplemental well pumpage. While farm delivery requirement and irrigation return 

flow are simulated by the FMP1, the surface-water delivery to the farm can be simulated optionally by coupling the FMP1 with 

the Streamflow Routing Package (SFR1) and the farm well pumping can be simulated optionally by coupling the FMP1 to the 

Multi-Node Well (MNW) Package. In addition, semi-routed deliveries can be specified that are associated with points of diversion in the SFR1 stream network. Nonrouted surface-water deliveries can be specified independently of any stream network. The 

FMP1 maintains a dual mass balance of a farm budget and as part of the ground-water budget.

Irrigation demand, supply, and return flow are in part subject to head-dependent sources and sinks such as evapotranspiration from ground water and leakage between the conveyance system and the aquifer. Farm well discharge and farm net recharge 

are source/sink terms in the FMP1, which depend on transpiration uptake from ground water and other head dependent consumptive use components. For heads rising above the bottom of the root zone, the actual transpiration is taken to vary proportionally with the depth of the active root zone, which can be restricted by anoxia or wilting. Depths corresponding to anoxia- or 

wilting-related pressure heads within the root zone are found using analytical solutions of a vertical pseudo steady-state pressure-head distribution over the depth of the total root zone (Consumptive Use Concept 1). Alternatively, a simpler, conceptual 

model is available, which defines how consumptive use (CU) components vary with changing head (CU Concept 2). 

Subtracting the ground water and precipitation transpiration components from the total transpiration yields a transpiratory 

irrigation requirement for each cell. The total farm delivery requirement (TFDR) then is determined as cumulative transpiratory 

and evaporative irrigation requirements of all farm cells and increased sufficiently to compensate for inefficient use from irrigation with respect to plant consumption. The TFDR subsequently is satisfied with surface- and ground-water delivery, respectively constrained by allotments, water rights, or maximum capacities. 

Five economic and noneconomic drought response policies can be applied optionally, if the potential supply of surface 

water and ground water is insufficient to meet the crop demand: acreage-optimization with or without a water conservation pool, 

deficit irrigation with or without water-stacking, and zero policy. 

1

Research Hydrologist, Department of Hydrology and Water Resources, University of Arizona

2

Professor and Department Head, Department of Hydrology and Water Resources, University of Arizona
Introduction 

The estimation of irrigation demand from a combination of surface water and ground water is a fundamental requirement 

that is a widely needed feature of ground-water models, such as MODFLOW (fig. 1). The current simulation capability of irrigation demand and irrigation water supply in MODFLOW, however, has required prior estimation of the fundamental components 

of irrigation that may include plant consumption, evaporation, effective precipitation, surface-water delivery, supplemental 

pumpage of ground water, irrigation runoff, and deep percolation through the partially saturated root zone of excess applied 

irrigation. Conjunctive use of surface water and ground water commonly is complex for most modern agricultural settings. Typically conjunctive use is complicated by the fact that ground-water pumpage is not always metered and estimation of pumpage 

is required for simulation of ground-water flow in agricultural areas. The integrated estimation of plant and soil consumption of 

precipitation, as well as applied surface- and ground-water deliveries, is needed to estimate a complete farm budget and related 

inflow and outflow components that are connected to the surface- and ground-water flow systems. In addition, it is critical that 

the farm budget be implicitly linked to these systems through head-dependent relations that allow the consumptive requirements 

of the crops and the natural evaporation of the soils to be dependent on the water-level in the uppermost aquifer. Heads in aquifers below the irrigated agriculture, therefore, are coupled to the evaporation and transpiration that occurs in the root zone of the 

soils on a cell-by-cell basis. The simulation of inflows and outflows to the farm and ground-water systems also should represent 

fallow or noncultivated regions, as well as urban irrigation located within the modeling domain. 

Operational Drought

response

Legal

Issues

Simulating

the past

Model

calibration

Simulating

the future

Link to climate-

 predictions

Appropriations

Water-rights

Water-transfers

Farm Delivery Requirement

NonSW

d

elivery

pumping

Requirement

ro

uted

de

SW

livery

Routed Ground-water

DEMAND

SUPPLY

Water Appropriations

Sustainable Management Using

FMP1 Farm Budget:

-Forecast of future 

 supply and demand

-Analysis of impact of

 farming on surface

 water and ground

 water

Resolving or defining 

appropriations for:

 -Individual farms

 -Irrigation districts

 -Transboundary 

 setting

-Estimation of water allocations

 prior to the growing season

-Assess impact of availability 

 of water through water

 transfers, leases, or futures

-Assess operation of aquifer-storage-

 and recovery systems

Conjunctive Management Using

FMP1 Drought Response Policies

Historical Simulations Future Forecasts

-Acreage optimization

-Water-stacking on priority crops

-Deficit irrigation

Balance supply 

and demand

Sustainable/optimal

management

Unconstrained

supply

and demand

Water budgets

conjunctive-use

allocations

Water Budgets:

-Well pumpage estimated

 when not metered

-Model calibration assessments

 of surface-water or ground-water 

 use for adjudications

-Storage change

 analysis

-Ground-water/

 surface-water

 interactions

-Conservation/

 efficiency analysis

Figure 1. Supply and demand components and relations to potential applications of MODFLOW-2000 with the FMP1.

2 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
The Farm Process (FMP1) described in this user’s manual is designed to simulate demand components representing crop 

irrigation requirement and on-farm inefficiency losses, and the supply components representing surface-water deliveries and supplemental ground-water pumpage, as well as additional head-dependent inflows and outflows such as canal losses/gains, surface 

runoff, surface-water return flows, and deep percolation of excess water (fig. 2). Data input requirements for these components 

are discussed in more detail in the section “General Data Requirements.” In addition, the FMP1 also has the capability to estimate economically optimal allocations through acreage optimization of water supplied by surface- and ground-water deliveries 

when demand exceeds supply. Other noneconomic drought-response scenarios also are available, such as deficit irrigation and 

water stacking.

drawdown

data

data

data

related

related

data

data

related

Soil type

Farm

Crop type

Climate

pumping

capacities

of farm

wells

Economic

Head

Maximum

constraints

Maximum

DEMAND

SUPPLY

Farm-Delivery Requirement

Ground- Water Pumping

Requiremen

S

t

urface-Water

Delivery

Streamflow Routing

Package (SFR1)

Regional climate data or

global climate and land-use models Economic models

Other streamflow-routing approaches Other well packages

Multi-node

Well Package (MNW)

Farm Process (FMP1)

Farm Process (FMP1)

Farm

Process

(FMP1

F

)

arm

Process (FMP1)

Fully-routed deliveries

allotments

Surfacewater

deliveries

Stream parameters

N

o

n-ro

uted

d

eliveries

Semi-routed

Diversion rates

v

olu

m

es

of

release

diversion

Types

a

nd

inflow

of

River

Point

Figure 2. Supply and demand components, data requirements, and connections to other models and packages by the FMP1.

Introduction 3
As part of the U.S. Geological Survey’s ground-water modeling program MODFLOW-2000 (MF2K) (Harbaugh and others, 

2000), the FMP1 provides four objectives for determining the major supply and demand components (fig. 2):

Estimation of consumptive use;

Simulation of surface-water supply distribution;

Simulation and estimation of ground-water pumpage supplemental to surface-water supply, to meet the irrigation water 

demand of each farm unit; 

Identify whether irrigation water supply to a farm unit from surface water and ground water is sufficient to meet the 

farm’s irrigation water demand or else to apply a user-specified drought3 response policy.

Combined with other MODFLOW-2000 packages such as the streamflow routing (SFR1) and multi-node well (MNW) 

packages, the FMP1 helps to transform MF2K from a predominantly ground-water-flow model to a more complete hydrologic 

model that simulates the hydrologic components of land-use as well as surface-water and ground-water-flow processes. In addition to linkage with other packages, FMP1 facilitates more direct linkage with other models such as Global Climate models (also 

referred to as General Circulation Models) for potential projections of future conditions, economic models for assessment of 

additional economic aspects of water policy and water projects as well as other surface-water routing approaches such as reservoir models and other ground-water sources such as springs or aquifer-and-storage facilities (fig. 2).

The FMP1 integrates various components of supply and demand data that can be variously specified over the different time 

frames of time steps, stress periods, or held constant for the entire simulation (fig. 2). The Farm Delivery Requirement requires 

soil, crop, and climate data to compute consumptive use. In addition, if drought policy scenarios are invoked to estimate the 

adjustments needed to balance demand with reduced supplies, economic data are also used to estimate the reduced consumptive 

use (fig. 2). Similarly, the water supply requires surface-water delivery and farm-well data to estimate the routed and nonrouted 

surface-water deliveries and the ground-water pumping requirements, respectively (fig. 2). Data input requirements for these 

components are discussed in more detail in the section “General Data Requirements.” 

The FMP1 dynamically simulates these supply and demand features for a farm unit within MF2K by integrating the 

following computational features (fig. 3):

(1) Total farm delivery requirement (irrigation demand), which depends on changing climate (evapotranspiration and precipitation) and variable aquifer head (fig. 3: 1);

(2) Actual surface-water delivery to the farm, which may be driven by irrigation demand, but limited to canal stream 

inflow at the farm’s diversion head gate, or limited by allotments or by semi- or nonrouted deliveries (fig. 3 : 2);

(3) Supplemental ground-water pumpage, which is estimated as the irrigation demand minus the actual surface-water 

delivery, but limited by a specified maximum farm well-pumping capacity (fig. 3: 3); 

(4) Net recharge to ground water, which is taken to be the excess irrigation plus excess precipitation minus surface-water 

runoff minus the evapotranspiration from ground water (fig. 3: 4); and

(5) Identification of the irrigation water supply insufficiency and application of a user-specified drought response policy 

(not shown in fig. 3).

The FMP1 dynamically links the demanded and actually supplied flow rates and related aquifer head (fig. 3). 

Irrigation Water Demand and Supply 

The ability to simulate allocations of surface-water and ground-water flow rates to a farm is desirable for incorporating 

legal requirements such as stream or ground-water adjudications into simulations, drought management, and for agro-economic 

decision making ahead of the cropping season (fig. 1). The need to specify these flow rates applies to simulation of historic and 

future periods. Estimation of these allocations may be necessary during periods when irrigation water supply is sufficient or 

insufficient to meet the irrigation water demand (fig. 1). Since well pumpage is not always metered in regional aquifer systems 

such as the areas of the southwestern and southeastern United States, it is of great advantage to simulate historical pumpage 

instead of estimating pumpage indirectly from power records or land-use maps (fig. 1). This approach was driven by the context 

of water use and water law from the western United States that is derived from the prior appropriation history of the Spanish. 

The application of the FMP1 to riparian water law and policies derived from the English that are more prevalent in the eastern United States, can still use the FMP1 by not employing any farm wells. Future versions of FMP1 will allow for more user 

options regarding the order of use of supply and demand components that also could facilitate urban use over agricultural use 

and ground-water use over surface-water supplies.

3

For the purposes of this study, the definition of degrees of “drought” is operational, not climatic, and is defined as: first-degree drought = insufficiency of 

surface-water supply; second-degree drought = insufficiency of surface-water and ground-water supply.

•

•

•

•

4 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Drain flow

Conveyance Losses

Return Flow Inefficient losses 

from irrigation and precipitation

Ground-water pumping

Effective precip.

Diversion into canals and laterals

Drain Flow

Runoff return flow

DELpot

TFDR

DEL pot TFDR

CIR = Crop irrigation required

Flux from atmosphere

Net recharge, on farm

 (simulated by FMP1)

Actual surface-water delivery (minimum 

 of TFDR and potential available

 surface-water delivery) (DELpot)

(simulated by FMP1)

Total farm delivery requirement (TFDR)

(simulated by FMP1)

EXPLANATION

Flux to atmosphere

Flux out of stream

Flux into stream

Flux out of aquifer

Flux into aquifer

Flux related to atmosphere

Flux related to stream-channel

Flux related to aquifer

Example of operational decision making

Computational features

If surface-water budget between supply

 (Surface-Water Delivery) 

 and demand (Total Farm Irrigation 

 Delivery Requirement) is negative,

 then supplemental ground-water

 pumping is required

OFF FARM

ON FARM

Stream

2

1

2

1

Off-farm leakage between stream-

 canal-drain network and aquifer

 (simulated by SFR1)

Supplemental well pumpage from 

 farm wells (on or off farm)

 (simulated by FMP1)

3

4

5

Figure 3.

Evapotranspiration from ground water

On farm evapo- transpiraton

Farm

precipitation

Stream

Leakage

3

4

5

5

5

5

Aquifer

Vadose Zone

Return

Flow

Atmosphere

Diversion Dam

Deep percolation

Figure 3. Flow chart of the flow of water into and out of the farm budget as simulated by the FMP1.

Introduction 5
The core concept of estimating crop irrigation requirement and the potentially related ground-water pumpage is based on a 

simple farm irrigation water budget (herein referred to as the farm budget). The FMP1 estimates budget components of (1) farm 

irrigation demand, and (2) water supply from surface-water and ground-water sources. The FMP1 does not account for water 

storage in a farm or water storage in the unsaturated zone.

(1) Irrigation water demand is simulated by the FMP1 as part of the farm budget. The FMP1 estimates the Total Farm 

Delivery Requirement (TFDR) as the sum of the Crop Irrigation Requirements (CIR) of all finite difference cells in any 

farm divided by the On-Farm Irrigation Efficiency (OFE). Each farm’s TFDR (fig. 3) includes all crop transpiratory and 

evaporative needs from irrigation in a farm, and accounts in addition for the level of efficiency of water use. Subtracting the 

transpiration components that are supplied by uptake from ground water and by precipitation from the total transpiration 

yields a transpiratory irrigation requirement for each cell. The total farm delivery requirement (TFDR) then is determined as 

cumulative transpiratory and evaporative irrigation requirements (Ti and Ei) of all finite difference cells in a farm, increased 

sufficiently to compensate for inefficient use. The TFDR subsequently is satisfied with surface- and ground-water delivery, 

respectively constrained by allotments, water rights, or maximum capacities. The TFDR is simulated for each farm unit by 

FMP1 as:

( / ),

Farm

TFDR CIR OFE = ∑ (EQ.1)

with

where

CIR = Crop Irrigation Requirement of any model cell in a farm

Ti = Transpiration supplied by irrigation (Ti = Tc-act – Tgw-act – Tp-act)

Tc-act = Actual crop transpiration requirement at steady state

Tgw-act = Portion of actual transpiration supplied by ground water at steady state

Tp-act = Portion of actual transpiration supplied by precipitation at steady state

Ei = Evaporation losses from irrigation (Ei is an estimate of the compensation needed for surface-evaporative losses, and defined to 

vary proportionally to Ti), and

OFE = On-Farm Irrigation Efficiency, defined as fraction of beneficially applied irrigation water to the field (OFE is specified by the 

user).

The CIR is the supplemental irrigation requirement needed to supply crop transpiration after water supplied from effective precipitation and uptake of ground water. The transpiration and evaporation components, Tc-act, Tgw-act

, Tp-act, and Ei, 

are assumed to occur at steady state for each model time step, and are dependent on climatic factors and aquifer head.

(2) Irrigation water supply is simulated by the FMP1 as part of the farm budget, which estimates additional water supplied by two potential components: surface-water deliveries and ground water. Surface-water supplies can be simulated 

as routed, semi-routed, and nonrouted deliveries. Ground water can be supplied through ground-water pumpage. The 

FMP1 can be used to simulate supplies that include any one or any combination of these supply components. Surfacewater supplies that are fully or semi-routed can be simulated in combination with the SFR1 package (Niswonger and 

others, 2005). The streamflow network can represent any combination of natural or artificial channels that are capable 

of conveying surface water to the adjacent farms. These deliveries are simulated as diversions onto a farm from a headgate adjacent to a farm for fully routed deliveries or from a remote specified point of diversion for semi-routed deliveries.

CIR = Ti + Ei

6 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Previous Simulation of Crop Demand and Irrigation Water Supply

Numerous regional ground-water flow models have used estimates of crop demand and irrigation water supply. However, 

most of these models simulated the components of irrigated agriculture through a priori estimates of supply and demand with 

related inflows and outflows. Previous ground-water simulations required estimating the consumptive use supplied by groundwater pumpage and the related irrigation efficiencies that collectively represent the amount of applied water supplied with 

ground water. Since most agricultural areas do not have metered pumpage, typically these estimates of ground-water pumpage 

were made through indirect estimates from other types of data. For example, Williamson and others (1989) used electrical power 

records to make detailed estimates of ground-water pumpage for the Central Valley, California. In other areas where many of 

the pumps are powered by diesel or gasoline engines in combination with electrical power, indirect estimates of ground-water 

pumpage have been derived from land-use maps for selected periods of time using crop-specific consumptive use estimates and 

assumed irrigation efficiencies (for example, Hanson and others, 2003). In yet other regions, reporting pumpage may be required 

as a basis for taxation. In these settings, the reported pumpage can provide a first-order validation of the pumpage estimated by 

FMP.

Perkins and Sophocleous provided a comprehensive large-watershed basin model, which links an agriculturally based 

watershed model, SWAT, to MODFLOW (McDonald and Harbaugh, 1988; Perkins and Sophocleous, 1999a,b). This linkage of 

SWAT and MODFLOW is also known as SWATMOD (Sophocleous and others, 1999). SWATMOD allows the spatial disaggregation and temporal aggregation of hydrologic flows yielded by SWAT from larger watershed subbasins to smaller MODFLOW 

model cells and from daily time steps to longer MODFLOW time steps (Sophocleous and Perkins, 2000). The SWAT model 

applies lumped, analytical models to represent ground water elevation and percolation out of the root zone, which are of limited 

use in representing the ground water and stream-aquifer hydraulics (Arnold and others, 1994; Neitsch and others, 2002a, b). 

SWAT as a stand-alone model does not have the ability to simulate how root uptake and capillary rise from ground water dynamically influence crop-water and irrigation-water demand and use, and soil-water storage. When the linked model, SWATMOD is 

used, it simulates a soil-water budget and allows the simulation of a “quasi root-uptake” by cumulating cell-by-cell evapotranspiration (ET) from shallow aquifers. This ET component is calculated by the ET package of MODFLOW over a subbasin, and 

by applying the corresponding evapotranspiration depth as capillary uptake into the soil profile. However, this procedure may 

widely overestimate root uptake from ground water due to the conceptual simplicity of the ET package of MODFLOW and, 

therefore, may underestimate irrigation demand. In addition, the simplicity of applying a uniform capillary uptake over a subbasin may result in additional estimation errors, since phreatophytic uptake often occurs only locally. While SWATMOD does 

return a basin-wide hydrologic balance, it does not allow for a water budget on the scale of individual water accounting units, 

such as farms or irrigation districts, for the components of irrigation demand, surface water and ground water supply, and net 

recharge. In addition, SWATMOD models are limited to watersheds boundaries. Constraints on surface-water and ground-water 

supply are present in SWATMOD, but it does not account for constraints from water-rights ranking in the sense of water-rights 

seniority, or account for maximum pumping capacity or head-constraints imposed on well pumpage.

Further advances in the simulation of irrigated agriculture resulted in a limited inclusion of the supply and demand components into ground-water flow models that represent decoupled sources of ground-water pumpage and deep percolation of excess 

applied water. For example, in a finite-element model, Integrated Ground-water/Surface-water Model (IGSM) (Montgomery 

Watson, 1993), flows between agricultural demand and surface-water supply, as well as ground water, were not fully coupled. 

Another finite-element model, the Integrated Water Flow Model (IWFM) (California Department of Water Resources, 2005a, b) 

provides full coupling between agricultural demand and the surface-water supply with flow from the root zone to ground water. 

A more dynamic linkage was provided with MODFLOW with the MODRIGHT Package (McCurry, 2000), which simulates 

surface-water diversions based upon Colorado water rights delivered to farm areas and the subsequent simulation of consumptive 

use, deep percolation, and irrigation return flow to the surface-water system. While these flows estimated consumptive use on 

the basis of user-specified agricultural properties, these components were not linked to the ground-water or surface-water-flow 

systems through head-dependent relations. In addition, this approach delivered an allotment to the farm equal to the full water 

right not bounded by crop demand. Thus, few models have been capable of dynamically integrating these supply and demand 

components based on actual crop demand in a head-dependent context of regional ground-water and surface-water flow.

Introduction 7
Modeling Agricultural Irrigation Supply and Demand

There are three main classes of problems that are facilitated in the simulation of conjunctively managed surface water and 

ground water supply and demand components for irrigated agriculture. The FMP1 allows MF2K users to simulate conjunctive use of surface water and ground water for simulation and estimation of irrigated agriculture for historic and future periods, 

for analysis of water-rights issues and operational decisions, and for analysis of nondrought and drought situations (fig. 1). By 

dynamically integrating farm delivery requirement, surface- and ground-water delivery, and irrigation return flow, the FMP1 

allows the direct estimation of supplemental ground-water pumping. While the farm delivery requirement and irrigation return 

flow are simulated by the FMP1, the surface-water delivery to the farm can optionally be simulated by coupling the FMP1 with 

the Streamflow Routing Package (SFR1) and the farm ground-water pumping can be simulated optionally by coupling the FMP1 

to the Multi-Node Well (MNW) Package. One of the most significant contributions of the FMP1 is the ability to dynamically 

estimate the amount of unmetered ground-water pumpage through the coupling of supply and demand water-resource components.

Purpose and Scope

The purpose of this report is to describe the organization, structure, and use of the FMP1, a head-dependent package for use 

with the ground-water/surface-water flow model, MF2K. The scope includes a brief description of the theory and implementation of the FMP1 that are derived from the more detailed documentation of the development and the basic procedures (Schmid, 

2004). Additional description of newer features, such as nonrouted and semi-routed surface-water deliveries, head-dependent 

irrigation efficiencies, water-rights allocations, and connection to the Multi-Node Well Package, also are provided. The purpose 

of this package is to provide MF2K with the additional capability of simulating cell-by-cell crop demand for every user-specified 

farm and the related supply components. The estimated crop demand is supplied from surface-water and ground-water deliveries 

to each farm and, as such, the FMP1 also maintains an additional farm budget independent from the ground-water budget. An 

additional purpose of this package is to provide a means to potentially balance demand and supply components by estimating a 

limited demand through acreage optimization, water stacking, or deficit irrigation.

Acknowledgements

The development of the FMP1 initially was supported by SAHRA (Sustainability of semi-Arid Hydrology and Riparian 

Areas) under the STC Program of the National Science Foundation, Agreement No. EAR-9876800, and from funding provided 

by the U.S. Geological Survey (USGS). This final version of the FMP1 and additional development was supported from the 

USGS Central Valley RASA project of the Ground-Water Resources Program (CADWR). We also acknowledge additional collaboration during the development of the FMP1 with Phil King and Sue Tillery (New Mexico State University), as well as David 

Prudic, Charles Brush, Claudia Faunt, and Ken Belitz (USGS).

Farm Process Capabilities

The FMP1 was developed to simulate, within MF2K (Harbaugh and others, 2000), the surface water and ground water 

inflows and outflows required to sustain irrigated agriculture. For the purposes of this report, the farm represents the basic unit 

of water consumption. Each farm can include one or more model cells in model layer 1. On the basis of cell-by-cell estimations 

for each farm, the FMP1 first calculates crop water demand as the transpiration from plant-water consumption and the related 

evaporation. The FMP1 then determines a residual crop water demand that cannot be satisfied by crop-effective precipitation or 

by root uptake from ground water. The FMP1 then equates this residual crop water demand with the crop irrigation requirement. 

This amount is then increased by accounting for evaporative losses from irrigation and other inefficiency losses to yield a final 

‘total farm delivery requirement.’ The FMP1 then attempts to satisfy the total farm delivery requirement with first priority by the 

nonrouted supply components and, with second priority, by the semi- and fully routed deliveries. If the supply components are 

constrained by a water-rights allocation hierarchy, the supply components are adjusted accordingly. Lastly, by third priority, the 

FMP1 determines the amount of supplemental ground-water pumping necessary to satisfy the total farm delivery requirement. 

The FMP1 then calculates the amount of excess water from irrigation or precipitation that is not effectively used for crop growth, 

which becomes either overland runoff or ground-water recharge. All of the supply and demand components are then tabulated 

into a farm budget that compliments the ground-water-flow budget. Finally, the FMP1 allows for user-specified scenarios that 

can estimate optimal distributions of supply components if the irrigation demand exceeds the supply components (fig. 4).

8 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
When using MF2K with the FMP1, this process dynamically integrates the following terms for a farm unit (fig. 3):

Farm irrigation delivery requirement (irrigation demand), which depends on changing climate (evapotranspiration and 

precipitation) and variable aquifer head;

Actual surface-water delivery to the farm, which is driven by irrigation demand, but limited to canal stream inflow at the 

farm’s diversion head gate, limited by water-rights allotments, or nonrouted deliveries;

Supplemental ground-water pumpage, which is the difference between the irrigation demand and the actual surface-water 

delivery, but limited by a specified maximum capacity for all of the wells associated with a farm; and

Net recharge to ground water, which is the excess of irrigation and of precipitation minus surface-water runoff and minus 

evapotranspiration from ground water.

In general, the FMP1 provides four improvements compared to previous approaches of integrated surface-water/groundwater modeling:

Dynamic dependency of crop water demand on changing climate and variable aquifer head;

Analytical steady state approximation of unsaturated flow (confirmed with HYDRUS2D simulations for several typical 

soil types) underlying the derivation of crop water demand and in-excess farm net recharge;

Allocation of surface-water and ground-water supply driven dynamically by crop water demand, and allowing for the 

estimation of historic and future ground-water pumping supplemental to surface-water supply; and

Inclusion of response policies to irrigation insufficiency (drought) to preserve mass balance.

•

•

•

•

•

•

•

•

Demand

Total farm delivery

requirement

SW sufficiency SW insufficiency

GW sufficiency GW insufficiency

Acreageoptimization

Waterstacking

DeficitirrigationZero

scenario

GW pumping

requirement =

SW Supply minus Demand

GW Supply

Maximum well

capacities No Yes

?

? SW supply

lesser of potential SW

delivery or SW allotment No Yes

Total farm delivery 

requirements

Actual SW delivery Farm pumping

requirement

Farm net recharge Stream and canal

leakage

Ground-water

well pumpage

Update head-dependent flow terms at each iteration

Add head-dependent inflow/outflow terms at each iteration

Figure 4

Figure 4. Cases of sufficiency and insufficiency of irrigation water supply in a surface-water dominated irrigation setting.

Farm Process Capabilities 9
Consumptive Use

Consumptive use is commonly defined as actual evapotranspiration (ET), which includes both plant transpiration and 

evaporation in an agricultural area (Colorado’s Decision Support Systems, 1995; Gelt and others, 1999; European Environment 

Agency, 2004). The purpose of estimating the consumptive use is to estimate evapotranspiration and its components. Two of its 

components are the transpiratory irrigation requirement and the evaporation losses from irrigation, which is the major portion of 

the farm irrigation requirement. In addition, the estimation of farm net recharge requires estimates of both of these irrigation and 

ground-water components and ET as a whole. In addition, the FMP1 can be used to estimate components of consumptive use for 

non-farm applications where transpiration accounts for riparian or natural vegetation or for urban vegetation. The FMP1 also can 

be used for applications with zero transpiration, such as aquifer storage-and-recovery (ASR) systems or urban-land use settings.

The FMP1 establishes the demand for water by estimating the consumptive use as ET from the crop water demand and 

related bare-soil evaporation of water. At steady state, ET is composed of the transpiratory and evaporative components from 

three sources: ground water, precipitation, and irrigation (eq. 1), where the CIR represents the components from irrigation. In 

the FMP, the CIR has been formulated to be head dependent and can vary with changing, ground-water levels within each model 

cell of each farm. All transpiratory and evaporative outflows are assumed to occur at steady state and, therefore, the soil moisture 

content (storage) does not change with time.

The irrigation demand (herein referred to as the total farm delivery requirement, TFDR) depends on the head-dependent component CIR. As long as the water supply is sufficient, the surface- or ground-water supply is driven by the irrigation 

demand. Therefore, the irrigation water supplied by surface water or by ground-water pumping depends indirectly on the headdependent CIR. In addition, the farm net recharge return flow, as described in the section “Farm Net Recharge,” depends directly 

on consumptive use components of CIR, Tp, Ep, Tgw-act, Egw-act, which are partly head-dependent. Hence, farm well discharge and 

farm net recharge are source/sink terms in the FMP1 that are dynamically dependent on the aquifer head.

In the case where the water table rises above the bottom of the root zone, the actual transpiration is taken to vary proportionally with the active root zone, which can be restricted by anoxia or wilting. Depths corresponding to anoxia- or wiltingrelated pressure heads within the root zone are found using analytical solutions of a vertical pseudo-steady-state pressure head 

distribution over the depth of the total root zone (CU Concept 1). Alternatively, a simpler conceptual model is available, which 

defines how consumptive use components vary with changing head (CU Concept 2).

The variation of transpiration fluxes with changing ground-water level, which includes the actual transpiration from ground 

water Tgw-act as part of the total actual crop transpiration Tc-act, is linearly approximated in the FMP1. Transient model runs of 

variably saturated flow soil column models simulated with HYDRUS2D (Simunek and others, 1999) yielded, for different 

ground-water levels, transpiration fluxes approaching a steady state. In the FMP1, these approximations of transpiration under 

variably saturated soil conditions (eq. 2) were derived for three typical soil types: sandy loam, silt, and silty clay. 

The variably saturated flow model, HYDRUS2D (Simunek and others, 1999), is based on the nonlinear form of the 

Richards’ equation governing flow in the unsaturated zone, given isothermal Darcian flow of water in a variably saturated rigid 

porous medium, and assuming that the air phase plays an insignificant role in the liquid flow process. The general nonlinear 

form of Richards’ equation (eq. 2) using Einstein’s notation can be described as follows, with the initial condition given by the 

pressure head distribution:

∂

∂

∂

∂















 +

∂

∂

+ =

∂

x ∂

K

x

K

x

S

t i

ij

j

iz

i

( ) ( ) ( ) θ ψ θ θ θ

 (EQ.2)

where 

z = 2 for two dimensional and 

z = 3 for three dimensional and using indices summation notation.

The solution of the Richards equation (eq. 2) requires the specification of soil-water constitutive functions such as the 

water-retention function ψ(θ) or θ(ψ) and the hydraulic conductivity function K(θ) or K(ψ). Coefficients of the water retention 

function can be determined from experimental data of ψ versus θ using nonlinear regression techniques (van Genuchten and 

others, 1991). Since the measurement of unsaturated hydraulic conductivity for a fixed water content is difficult, ψ(θ) or θ(ψ) 

and the saturated hydraulic conductivity Ks are customarily used in conjunction with theoretical models (for example, Mualem, 

1976; van Genuchten, 1980) to obtain K(θ) (Ravi and Williams, 1998).

10 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
The root uptake sink term in HYDRUS2D can be determined by the product S(ψ) of a “Feddes”-type water stress response 

function a(ψ) and a potential water uptake rate Sp that is assumed to be equally distributed over the root zone (Feddes and others, 

1978). The stress response needs to be specified as 0.0 for the wilting point and water-entry pressure heads, and as 1.0 for two 

values between which the water uptake is considered optimal. The potential water uptake is dependent on the root zone geometry and the potential transpiration rate (Simunek and others, 1999). 

Soil-water constitutive functions that can be used in HYDRUS2D are those developed by Brooks and Corey (1964), 

Mualem (1976), and van Genuchten (1980). The van Genuchten-Mualem approach probably is used most widely. This approach 

used variably saturated soil column simulations with HYDRUS2D to develop analytical approximations in the FMP1. This 

approximation simulates the reduction of transpiration proportionally to the reduction of the root zone by changes in the zones 

of anoxia and wilting. These were incorporated into the FMP1 using the relations given in table 1. The parameters α, n, and l are 

empirical coefficients affecting the shape of the hydraulic functions (Simunek and others, 1999). The selection of a soil type in 

HYDRUS2D implicitly assumes a set of empirical parameters that define the soil-type-specific hydraulic functions that further 

define the water-retention and the hydraulic-conductivity function.

The HYDRUS2D simulations of unsaturated flow demonstrate how the resulting fluxes of the actual transpiration from 

ground water (root uptake from ground water as the only source) and fluxes across the water table merge when approaching 

steady state (fig. 5). These steady state values were plotted for various depths to the ground-water table for sandy loam and silt 

soils (fig. 6) with the corresponding linear approximation (fig. 7). In addition, the variation of a maximum possible actual transpiration (with root uptake from sources ground water and irrigation) with changing ‘depths to water’ was determined 

(figs. 5 and 6), along with its linear approximation (fig. 7). Since at steady state the output transpiratory flux equals the flux 

across the water table (plus the irrigation flux, if applied) for the HYDRUS2D models, changes in storage in the unsaturated 

zone are assumed to be negligible in the FMP1. 

Transpiration for Water Levels between Ground Surface and Bottom of Root Zone

In the FMP1, both crop-consumptive-use concepts (Concepts 1 and 2) assume a linear decrease in transpiration as the 

ground-water level rises above the bottom of the root zone. Hypothetically, the potential ‘maximum possible transpiration’ for 

ground-water levels between ground surface and the bottom of root zone is taken to vary linearly through the active root zone 

(dotted line in fig. 7), as it is reduced to zero by ground-water levels rising from the bottom of the root zone up to the groundsurface elevation. This hypothesis holds, given the following assumptions:

(1) The actual transpiration can at maximum be equal to the potential transpiration;

(2) The potential transpiration is at maximum, if the entire root zone is available for uptake as active root zone; and

(3) The potential transpiration is distributed equally over the root zone.

Consumptive-Use Concept 1

Consumptive-use concept 1 represents a step-wise linear approximation of transpiration for ground-water levels between 

the bottom of the root zone and the ground surface. The potential ‘maximum possible transpiration’ is not quite reached by the 

results from the soil column HYDRUS2D simulations. For a ground-water level equal to the bottom of the root zone (when the 

transpiration is found to be at maximum), the ‘maximum actual transpiration’ (Tc-act-max, in fig. 7 called ‘maximum actual root 

uptake,’ ARUmax) is reduced as the active root zone is restricted by conditions of anoxia or wilting. In the FMP1, the depths 

within the root zone which correspond to user-specified, crop-specific anoxia- or wilting-related pressure heads (fig. 8A), are 

found using analytical solutions of a vertical steady state pressure head distribution over the depth of the total root zone (fig. 8B). 

This was carried out for ground-water levels located at the bottom of the root zone, where the ‘total actual crop transpiration’

(Tc-act) and its component, the ‘actual transpiration from ground water (Tgw-act), reach a maximum (Tc-act-max , Tgw-act-max). As the 

ground-water level rises above the bottom of the root zone, the anoxia fringe does not change but is shifted upward until it equals 

the ground-surface elevation. The vertical range over which pressure heads are lower than the wilting-point pressure head, is 

found by assuming ground water to be the only source for transpiration. Such a “too-dry-zone” in the upper part of the root zone 

decreases linearly as the ground-water level rises above the bottom of the root zone. This approximation of how transpiration is 

taken to vary for ground-water levels between the bottom of the root zone and ground surface is the most important feature of 

what is referred to as CU concept 1 (fig. 9) of the consumptive-use approximation in the FMP1.

Farm Process Capabilities 11
12 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000

HYDRUS 2D

[from Simunek and others, 1999] 

Dimension 2D

∂ t

∂ θ

by replacing h with ψ + z, and replacing K with K(KA

), where K = K(ψ,x,z)

and using Einstein’s Notation for 2D, we get:

S x K(K

x

A

iz

j

A

ij

i

+ − ∂

∂

∂

∂ = ∂

∂ θ ψ

where: S = a(ψ)Sp; and S p = (L tTpot)/(LxL z)

Water retention function: 

≥

+ < s

1+

1−( 1−S

θ

ψ ψ

s ψ ψ

αψ

θ−θ

θ

θ(ψ)=

s

n m

s r

r

( )

Hydraulic conductivity function:

[ 2

1/m m

e

l

s ψ

< = = 1

αψ ψ -1/α

ψ < -1/α

θ − θ

θ − θ

−n

s r e S Se after Brooks and Corey (1964)

List of Parameters and Functions in Table 1: 

unsaturated hydraulic conductivity [L/T]

hydraulic conductivity tensor [L/T]

Kij components of hydraulic conductivity tensor K [L/T]

K

A

dimensionless anisotropy tensor for the unsaturated

 hydraulic conductivity K [-]

KA

ij components of dimensionless anisotropy tensor KA K [-]

s saturated hydraulic conductivity [L/T]

pore-connectivity parameter [-]

Lt

Lx width of root zone [L]

Lz depth of root zone [L]

HYDRUS2D models using soil-water constitutive functions after van Genuchten (1980) and Mualem (1976): 

Governing

equation

Soil-water

constitutive

functions

t

K )

=∇⋅(K∇h)−S

K( )=KS S ) ] with: m=1/n, n >1,

a dimensionless water stress response function [-]

K

K

l

width of soil surface associated with transpiration [L]

Table 1. Summary of variably saturated flow equations and soil-water constitutive functions used in HYDRUS2D to develop

unsaturated-flow approximations incorporated in the FMP1.

n empirical exponent in soil water retention function [-]

S sink term – root uptake [1/T]

Se effective water content [-]

Sp spatial distribution of the potential transpiration rate [1/T]

Tpot potential transpiration rate [L/T]

α inverse of air-entry value in water retention function [1/L]

θ volumetric water content [L3

/L3]

θs saturated soil water content [L3

/L3

]

θ r residual soil water content [L3

/L3]

ψs air-entry pressure head [L]
Figure 5-6.

0

50

100

150

200

250

300

0.5 1 1.5 2

FLUX, IN CENTIMETERS PER DAY

FLUX, IN CENTIMETERS PER DAY

DEPTH TO WATER LEVEL, IN CENTIMETERS

Sandy loam (Actual root uptake)

Sandy loam (constant head boundary - flux)

Silt (actual root uptake)

Silt (constant head boundary - flux)

Maximum possible transpiration

Sandy Loam (maximum actual root uptake from

groundwater and irrigation without causing recharge)

Silt (maximum actual root uptake from groundwater

and irrigation without causing recharge)

Depth to water level = 120 cm

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0 10 20 30 40 50

DAYS

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Depth to water level = 30 cm

Depth to water level = 60 cm

Depth to water level

= 180 cm

Specified irrigation flux

(maximum irrigation applicable

without causing recharge)

+

Upward flux across

the water table

 (= Constant head boundary)

=

Maximum possible

actual root uptake

Actual root water uptake

 (from ground-water)

Actual root water uptake

 (from ground-water and

 from irrigation)

Constant boundary flux

Figure 5 (left). Transient course of root 

uptake and flux across the water table for 

different depths to water table. (Soil type: 

silt; root zone depth = 120 cm; potential crop 

transpiration Tc-pot = 2 cm/day)

Figure 6 (right). Variation of actual root uptake from ground water (at 

steady state), and of maximum actual root uptake from ground water and 

irrigation (at steady state), with changing water level (root zone depth = 

120 cm; potential crop transpiration Tc-pot = 2 cm/day).

Farm Process Capabilities 13
The maximum ‘total actual crop transpiration’ Tc-act-max is defined as: 

Tc-act-max = Tc-pot • [1 – AZ/TRZ] 

The maximum ‘actual transpiration from ground water’ Tgw-act-max is defined as:

Tgw-act-max = Tc-pot • [1 – (AZ+WZ)/TRZ] 

where

Tc-pot is the potential crop transpiration, 

Tc-act-max is the maximum actual crop transpiration,

TRZ is the total root zone thickness, 

AZ is the thickness of the anoxia zone, and

WZ is the thickness of the wilting zone.

Consumptive-Use Concept 2

Alternatively, a simpler, conceptual model, CU concept 2 (fig. 9) simply assumes, for a ground-water level equal to the bottom of the root zone, the maximum actual crop transpiration Tc-act-max and the maximum actual transpiration from ground water 

Tgw-act-max are equal to the potential crop transpiration Tc-pot:

 Tc-act-max = Tgw-act-max = Tc-pot

Sandy loam (Actual root uptake (ARU) flux)

Silt (ARU flux)

Maximum possible transpiration

Sandy Loam (ARUmax from

ground water and irrigation without present recharge)

Silt (ARUmax from ground water & irrigation

without present recharge)

Linear approximation of silt

(ARUmax from ground water and irrigation 

without present recharge)

Linear approximation of silt

(ARU flux from ground water)

Linear approximation of sandy loam

(ARUmax from ground water and irrigation

without present recharge)

Linear approximation of sandy loam

(ARU flux from ground water) 0 0.5 1.0 1.5 2.0

0

50

100

150

250

300

200

FLUX, IN CENTIMETERS PER DAY

DEPTH TO WATER LEVEL, IN CENTIMETERS

Figure 7

Tgw-act-max

Tgw-act-max

Figure 7. Linear approximation of pseudo-steady-state root uptake from ground water and maximum actual root uptake (ARU) from 

ground water and irrigation water.

14 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Transpiration for Water Levels between Bottom of the Root Zone and the Extinction Depth

Transpiration is simulated for ground-water levels between the bottom of the root zone and the extinction depth for both 

crop CU concepts (fig. 9) and is assumed to decrease linearly with depth. All of the head-dependent variables are specified in 

red in this section and subsequent sections of this report. As the ground-water level drops below the bottom of root zone, the 

actual transpiration from ground water Tgw-act is assumed to decrease linearly from the respective maximum actual transpiration from ground water, Tgw-act-max , at the bottom of the root zone to a transpiration-extinction depth (defined to be equal to the 

capillary fringe) below the bottom of the root zone. For a ground-water level below the bottom of the root zone, the total actual 

transpiration Tc-act is assumed to remain constant at the maximum actual transpiration Tc-act-max (fig. 9).

Figure 8. (A) crop specific stress response function a( ψ ), and (B) analytical function d( ψ ) fitting the 

vertical pressure head distribution over depth. 

0

1

SOIL WATER PRESSURE HEAD [ln (| |)] Y

Figure 8a and b

 user specified

 simplified in

 the FMP1

|Y| |Y| |Y| |Y|

ln (| | at steady state) Y

d (| |) Y

A

B

hydrostatic

pressure head

pressure head

distribution at

steady state

Zone

below

tolerance

against

wilting

(WZ)

Zone

of

anoxia

(AZ)

Active

Root

Zone

DRZ

10,000 1,000 100 10 1

Zero uptake Full uptake

Wilting

Anoxia

n

Farm Process Capabilities 15
Evaporation for Water Levels between Ground Surface and Extinction Depth

Evaporation from ground water is simulated for ground-water level between the ground surface and the extinction depth 

(fig. 9). The ‘maximum actual evaporation from ground water’ Egw-act-max is assumed to equal the portion of the saturation water 

vapor pressure deficit over exposed no crop areas (potential evaporation Ec-pot), which is not compensated by evaporating precipitation (Ep

), where Egw-act-max = Ec-pot – Ep. For both crop consumptive use concepts, the extinction of evaporation from ground 

water is likely to occur when the highest point of the capillary fringe is below the ground surface (Robinson, 1958). Thus, evaporation from ground water Egw-act is assumed to decrease linearly with the ground-water level from the ‘maximum actual evaporation from ground water’ Egw-act-max at the ground surface to an ‘evaporation-from-ground water extinction depth’ (defined to be 

equal to the capillary fringe) below ground surface.

Head-Dependent Transpiration from Precipitation

Head-dependent transpiration from precipitation (fig. 9) also is simulated by the FMP1. As the transpiration from ground 

water increases with rising ground-water level, the amount of ‘actual transpiration provided by precipitation’ Tp-act

4

 decreases as 

long as it is less than the available ‘potential transpiration from precipitation’ that is needed:

Tp-act = Tc-act – Tgw-act ; if Tp-pot > Tc-act – Tgw-act (head-dependent case)

Tp-act = Tp-pot ; if Tp-pot ≤ Tc-act – Tgw-act (nonhead-dependent case)

Head-Dependent Crop Irrigation Requirement

The head-dependent transpiratory irrigation requirement for each model cell (Ti) (fig. 9) is simulated by subtracting the 

actual transpiration from ground water Tgw-act and the actual transpiration from precipitation Tp-act from the total transpiration. 

After adding the evaporative irrigation needs (Ei), which are to compensate surface-evaporative losses from irrigation, this yields 

the estimate of the crop-irrigation requirement, CIR.

4

The actual transpiration from precipitation commonly is defined as the so-called crop-“effective precipitation” (Doorenbos and Pruitt, 1977; Dastane, 1978; 

Brouwer and others, 1985; and Brouwer and Heibloem, 1986)

Figure 9.

Tgw-pot

Extinction

E P

E GW

CONCEPT 1

T

GW

Capillary

fringe

T c-pot Ec-pot

Root

zone

E p-pot

E T i i Tp-pot

Tp-act

T

gw-act

E

gw-act

Egw-pot

Extinction

Egw-pot

Extinction

Capillary

Fringe

E P

E GW

CONCEPT 2

T GW

Ec-pot Tc-pot

T

gw-act

E T i i

Flux

Tp-pot

E p-pot

E

gw-act

T gw-act-max

T c-act-max

Ground surface Ground surface

Ti Ti

Egw-act Egw-act

Tgw-act

Ep-pot Ep-pot

Tp-pot E Tp-pot i Ei

Capillary

fringe

Tgw-pot

Extinction

Capillary

fringe

Root

zone

Tgw-act

Tp-act

Figure 9. Two conceptual approximations to change of crop consumptive-use components with varying head. 

16 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Surface-Water Supply

Surface-water supply as deliveries to a farm or flow of water away from any farm can be simulated for each farm as 

nonrouted surface water, or simulated as conveyance from diversions or to drainage canals with the SFR1 package (Prudic and 

others, 2004). The simulation of surface-water conveyance to and from farms can include any combination of nonrouted and 

routed transfers that, in turn, can represent a variety of conveyance mechanisms from natural rivers to manmade canals and pipelines. Simulation of surface-water deliveries is not required, if the simulated irrigation of a farm is based solely on ground-water 

pumped from local wells.

Nonrouted surface-water deliveries, herein referred to as water transfers, represent the ability to move water to or from 

a farm without simulating the actual process of conveyance. Any farm can have any number of separate water transfers from 

multiple sources. Thus, multiple water transfers can represent deliveries of water from private, county, state, federal, or international sources of water. When water transfers are specified as deliveries, they are the first water-supply components that are used 

to satisfy the demand representing the total farm delivery requirement (TFDR)(eq. 1). In addition, when a user specifies water 

transfers, they are assumed to occur during a specified period of time and are not subject to any prior appropriation hierarchy. 

Water transfers also can be flagged to equate only to the TFDR or can be flagged to allow deliveries in excess of the TFDR. 

Water transfers can be specified as a positive quantity to represent the delivery of water to the farm (importation). Water transfers 

also can be specified as a negative quantity to represent the delivery of surface water or ground water away from a farm (exportation). A water export could be an additional water demand that may represent a transfer of water in lieu of farming or could be 

an addition to any potential TFDR. If, for example, the farm land is fallow then the negative water transfer would be manifested 

as additional ground-water pumpage or a redirection of surface-water deliveries. This combination of features also allows the 

simulation of ponds and wells that are part of aquifer-storage-and-recovery (ASR) operations. Thus, excess water transfers could 

be applied to fallow land that represents infiltration ponds or injection wells where water is returned to the ground-water system. 

Model cells of infiltration ponds as well as injection wells could be represented by “farm wells.” Alternatively, the excess water 

transfers also could be returned to the surface water system through the farm canal. Subsequently, later negative transfers can 

represent additional pump back from the same “farm wells.”

A stated above, each farm may receive nonrouted deliveries from several sources. A farm-specific ranking of these random 

delivery types is necessary to determine which type of potentially available nonrouted delivery is not used in its entirety if the 

sum of all types of nonrouted deliveries exceeds the farm’s total delivery requirement (TFDRf). The ranking scheme assumes 

a lower number to be of higher priority. The user may specify not only to use the amount sufficient to meet TFDR but to apply 

the entire amount of an available nonrouted delivery type. In this case, an NRDuse-Flag is set to a positive number indicating the 

target to which the excess or unneeded delivery will be sent. The NRDuse-Flag is set to “1” if the surplus from a certain delivery 

type is to be delivered to a canal. This feature may be useful for simulating the actions of farmers that make local water transfers. Similarly, the NRDuse-Flag is set to “2” if the surplus from a certain delivery type is to be injected into the farm’s wells. 

This feature may be useful if the farm represents an aquifer storage and recovery system (ASR) or where recharge credits are 

needed. The total of all nonrouted deliveries, TNRDf, equals the sum of all types of actually used nonrouted deliveries to farm f 

is determined as follows:

NRD

TFDR NRD t t t NRD

act

f t

f

pot

f t

tot u use

f

,

,

=

− 						∀	 - = ;	and	if	 ,t t( ) t

t

t t

tot u

tot u

= −

=

− −

∑ = 0

1

1

0																																									∀ > 	 - ;	and	if	 = 	0 > − t t t NRD

NRD

tot u use

f t t t tot u , ( )

pot

f t t t

tot u tot u t t t , ( ≥ − )

																					∀ ≥ 	 - ;	and	if	NRDuse

f t t t tot u , ( ≥ − ) =



















1	or	2

Farm Process Capabilities 17

TNRD NRD NRD NRD f

act

f t

pot

f t

act

f t

t t t

t

t

t

tot u

tot tot

= = + = = −

−

∑ , , ,

1

t

t

tact u −

=

∑ ∑

1

1

and:

(EQ. 3)
where

f = 1,2,..., number of farms;

t = 1,2,..., t

act, ... , ttot ; (lower type t = higher priority rank)

t

act = number of actually used ranked types of nonrouted deliveries;

t

tot = total number of available ranked types of nonrouted deliveries;

t

u = number of types of nonrouted deliveries unnecessary to meet TFDRf

;

NRDf,t

pot = potentially available nonrouted delivery of type t to farm f

NRDf,t

act = actually used nonrouted delivery of type t to farm f

TNRDf = total of all types of actually used nonrouted deliveries to farm f

NRDf,t

use = binary “NRDuse-Flag” of a nonrouted delivery type t to a farm f:

if 0: only the amount sufficient is used to meet the farm’s demand,

if 1: the absolute amount available is used; surplus recharged into canal at farm’s head gate,

if 2: the absolute amount available is used; surplus injected into farm wells attributed to farm ID.

Routed deliveries can be simulated as fully or semi-routed deliveries. Fully routed streamflow deliveries are linked to the 

streamflow routing package (SFR1, Prudic and others, 2004) in MF2K, if the simulation of surface-water supply to farms is 

desired. The estimation of streamflow at the farm’s head gate6, which potentially is available for delivery to the farm, is accomplished by routing streamflow through a network of channels (including streams and canals) to the respective head gate of a 

farm. To simulate semi-routed deliveries, the user specifies a diversion point from the streamflow-routing network for each farm. 

The distribution of surface water to the model cells within the farm unit is subject to additional on-farm transmission losses that 

implicitly are accounted for by the on-farm efficiency. While a simulation with multiple farms can contain a mixture of fully and 

semi-routed deliveries, each farm only can receive either a fully or semi-routed delivery. However, any farm can receive nonrouted deliveries as well as one fully or semi-routed delivery.

The potential surface-water delivery to the farm’s head gate starts with the simulation of routed streamflow using the SFR1 

package (Prudic and others, 2004). The stream inflow into the farm’s head-gate reach7 (potentially deliverable surface-water supply, DELpot), is determined by the SFR1 routing scheme moving downstream, which updates each reach’s streamflow by changes 

in inflows and outflows. The calculation of inflows and outflows is constrained by a mass-balance assumption for each reach 

(Σinflows = Σoutflows), assuming no changes in stream-channel storage. 

The SFR1 package has four options for simulating water diversions from the last reach of an upstream segment into the first 

reach of a diversion segments are (with: Qspec-div = user-specified diversion flow; Qspec-max = user-specified maximum streamflow) 

(Hanson and others, 2003; Prudic and others, 2004):

(1) if Qspec-div ≤ Qstream-inflow, then Qdiversion = Qspec-div,

 

if Qspec-div > Qstream-inflow, then Qdiversion = Qstream-inflow, 

(2) if Qspec-div ≤ Qstream-inflow, then Qdiversion = Qspec-div,

if Qspec-div > Qstream-inflow, then Qdiversion = 0

(3) Qdiversion = specified fraction of Qstream-inflow between 0 and 1

(4) if Qspec-max < Qstream-inflow, then Qdiversion = Qstream-inflow – Qspec-max (“Flood Control”

  type diversion )

if Qspec-max ≥ Qstream-inflow, then Qdiversion = 0 

5

The SFR1 package computes leakage rates between the stream and the aquifer as source/sink terms for MF2K.

6

The farm’s head gate is the point of diversion with respect to the canal or lateral reach where water enters the farm unit.

7

A stream reach, including head-gate reaches, is a section of a stream that is associated with a particular model cell.

18 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
These streamflow-diversion options can be used to specify the method for calculating diversions from a stream or canal to a 

diversion canal leading to a farm or to a set of farms. Such a ‘canal diversion’ is simulated only by the SFR1. It is different from 

a ‘farm diversion’ of delivered surface water from any reach along a canal-diversion segment onto a farm that is simulated by a 

link to the SFR1 from the FMP. The ‘farm diversion’ is established as the ‘actual surface-water delivery’ either from a remote 

point of diversion (semi-routed delivery) or from the farm’s head gate (fully routed delivery). For fully routed deliveries, the 

FMP1 automatically determines the most upstream reach along a canal-diversion segment that is adjacent to a farm.

The actual surface-water delivery, DELf

act, (eq. 4) from a canal to farm f is equal to the portion of the total delivery requirement of farm f, TFDRf

, that cannot be supplied by the sum of all types of actually used nonrouted deliveries to farm f, NRDf,t

act. 

However, DELf

act cannot exceed the potentially available stream inflow, DELr,fpot, into the canal reach at the farm’s headgate (for 

“fully routed deliveries”), or at a point of diversion from the river or from a canal (for “semi-routed deliveries”). In addition, the 

actual delivery (eq. 4) also cannot exceed a delivery constraint, Qf

constr, associated with a water-rights system:

 

DEL T act FDR NRD DEL Q f f

act

f t

pot

r f

constr

f

t

= min( −∑ , , ) , ,

[L3/T] (EQ. 4)

where

f = 1,2,..., number of farms;

r = 1,2,..., number of stream reaches;

t = 1,2,..., number of ranked types of actually used nonrouted deliveries.

Ground-Water Supply

The ground water supplied to each farm is simulated by a series of user-specified, single-aquifer “farm wells” or through 

user-specified associations with multi-aquifer wells simulated with the MNW package (Halford and Hanson, 2002). Groundwater pumpage requirements are estimated by the FMP1 after the TFDR is estimated and surface-water imports and exports 

from routed and nonrouted deliveries have been subtracted from the TFDR. If the TFDR is satisfied by the surface-water deliveries, then no ground-water pumpage will be estimated. Conversely, if no surface-water is available for supply, then ground-water 

from farm wells will be used to attempt to satisfy the demand estimated as the TFDR.

Ground-water pumping depends indirectly on consumptive use components. The ground-water pumping (eq. 5) of each 

farm (Q) equals either the farm’s pumping requirement (QREQ), which is reflected as residual farm delivery requirement by 

farm’s irrigation demand (TFDR) minus the total nonrouted delivery (TNRD) minus the actual surface-water supply (DELact), or 

the cumulative maximum pumping capacity, whichever is less (fig. 3):

Q = min(TFDR-TNRD-DELact, QMAXF) ⇒ Q = min(QREQ, QMAXF) (EQ. 5)

The algorithm to calculate the pumping rate for each well in any one farm is as follows:

If TFDR-TNRD > DELact, then

If wells do not exist in farm, apply drought policy scenario (condition 1a).

If wells do exist, then:

(1) If TFDR-TNRD- DELact >∑ −

i

i Qmax capacity , then

(a) Apply drought policy scenario, so that

TFDR ≥ TNRD + DELact +∑

i

i Qmax

if TFDR-TNRD- DELact <∑ −

i

i Qmax capacity , then

update net-recharge, DELact, and update QREQ by going to (condition 2)

if TFDR-TNRD- DELact =∑ −

i

i Qmax capacity , then

update net-recharge, and

(b) Pump wells i with Qi = Qi

max

Farm Process Capabilities 19
 (2) If TFDR-TNRD- DELact < ∑ −

i

i Qmax capacity , then

Pump wells on average with QAVF = (TFDR-TNRD-DELact)/n

 (a) If Qi

max ≤ QAVF:

pump well i with Qi = Qi

max

(b) If Qi

max > QAVF:

 

 pump well i with QAVF + sum of deficiencies (QAVF-Qj

max) of these wells (j) where 

 Qi

max < QAVF, prorated to the wells (k) where Qimax < QAVF

 Qi = ( ) ( )

∑( ) ∑ −

−  ∗



 





+ −

k

k

i

j

j

Q QAVF

Q QAVF QAVF QAVF Q

max

max

max

where 

i = 1,2,...,n (number of wells per farm)

j = 1,2,...,l (number of wells with Qtot/n > Qj

max) and

k = 1,2,...,m (number of wells with Qtot/n < Qk

max)

The link between the FMP1 and MNW package can be specified individually for any single- or multi-aquifer well. This 

link allows the simulation of an actual pumping rate based on (a) the desired ground-water pumping rate, Qi, as determined by 

the above algorithm in FMP1, (b) the respective aquifer productivity found by the MNW, and (c) head- or drawdown constraints 

specified in the MNW data input file. If the actual pumping rate calculated by the MNW is less than Qi, then the actual pumping 

rate is used as a simulated QMAX of a well, which replaces the default QMAX (= Qi

max of well i, in the above algorithm) of the 

FMP1. In this case, the cumulative QMAXF (eq. 5) may be composed of both simulated and non-simulated maximum capacities 

of wells linked or not linked to the MNW package.

Net Recharge

For each model cell in a farm, net recharge is defined as “(1) inefficiency losses due to excess irrigation and excess precipitation, reduced by (2) the fraction inefficiency losses to surface-water runoff, and reduced by (3) evapotranspiration from ground 

water.” The following definitions relate to any finite-difference cell in the uppermost active model layer (the model-cell indices 

(i,j,k) have been omitted):

 (1) Inefficiency losses to runoff and deep percolation as a result of excess irrigation and excess precipitation are 

defined as:

 (I-CIR) + (P-ETp),

where

• Excess irrigation (I-CIR) equal to applied irrigation (I) in excess of the crop irrigation requirement (CIR), plus

• Excess precipitation (P-ETp) equal to precipitation (P) in excess of the evapotranspiration from precipitation (ETp).

20 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
In a sufficiency situation, the applied irrigation (I) is driven by the crop irrigation demand and the demand for compensating 

inefficient water use (TDR = CIR/OFE). In an insufficiency situation, the available irrigation per cell (AVI), depends on the total 

available supplies and by the reduction scheme or pro-rating scheme of the user-selected deficiency scenario.

(2) The fraction of inefficiency losses to surface-water runoff depends on whether it is related to irrigation (IEI

sw) or to precipitation (IEP

sw). IEIsw depends on different irrigation methods, which, in turn, often depend on the crop type. For basin-level irrigation, IEI

sw generally is zero. In the FMP1, the user may specify IEIsw and IEPsw as estimates between 0.0 and 1.0. Alternatively, 

the FMP1 can calculate internally the slope as rise-run, and equate both IEI

sw and IEPsw to the slope. Therefore, in the FMP1, deep 

percolation can be defined as inefficiency losses to runoff and deep percolation minus the fraction of inefficiency losses to surface-water runoff respectively due to irrigation or precipitation: 

 (I-CIR) (1-IEI

sw) + (P-ETp

) (1-IEP

sw). 

In the FMP1, deep percolation is taken to be equal to recharge.

(3) Evapotranspiration from ground water (even for irrigated areas) is subtracted from the potential net downward flux to 

the ground-water system. The net recharge to the uppermost active model cell is therefore equal to ‘recharge’ as defined in (2) 

minus the evapotranspiration from ground water as: 

 (I-CIR) (1-IEI

sw) + (P-ETp

) (1-IEP

sw).

Hence, net recharge to ground-water, Rn (eq. 6), can be defined for each uppermost active model cell in each farm by means 

of user-specified and head-dependent parameters, which are specified in red as functions of head (h) as:

 Rn(h) = [I (h) – CIR(h)] (1-IEI

sw) + [P – Ep

–Tp(h)](1-IEP

sw) – Tgw-act

(h) – Egw-act(h), (EQ. 6)

where

I(h) = Applied Irrigation (head-dependent)

 For sufficiency cases: I(h) = TDR(h)

 For insufficiency cases: I(h) = AVI(h),

TDR(h) = Total Delivery Requirement (head-dependent) = CIR(h)/OFE(h),

AVI(h) = Available Irrigation (head-dependent),

CIR(h) = Crop Irrigation Requirement (head-dependent) = (Tc-act – Tgw-act – Tp-act) (1 + Ke

i

/Kt), 

OFE(h) = On-Farm Efficiency (optionally head-dependent for IEBFL = 2 and IEBFL = 3), 

P = Precipitation,

Ep = Evaporation from precipitation,

Tp(h) = Transpiration from precipitation (head-dependent),

IEsw

I = Fraction of inefficiency losses to surface-water runoff from irrigation,

IEsw

P = Fraction of inefficiency losses to surface-water runoff from precipitation,

Tgw-act(h) = Actual transpiration from ground water, and

Egw-act(h) = Actual evaporation from ground water.

This definition of net recharge is physically valid, given the following assumptions:

(1) Deep percolation beyond the active root zone is equal to ground-water recharge,

(2) Recharge is simulated without delay and represents an instantaneous source pulse into ground-water flow, and

(3) Evapotranspiration from ground water equals an instantaneous sink pulse out of ground-water flow.

Farm Process Capabilities 21
Water-Rights Allocation

Allocation constraints representing water-rights hierarchies can be imposed as surface-water allotments. These surfacewater allotments may be introduced into a model as a lumped equal appropriation allotment height for any stress period in units 

of [L/T] for all farms within the modeling domain or as water rights calls per stress period in units of [L] for a prior appropriation system for individual farms or irrigation regions. Equal appropriation means that all farms receive an equal amount of water 

from routed or semi-routed surface-water deliveries weighted by the respective area of the farm. The simulation of surface-water 

deliveries constrained by equal appropriation allotments requires specification of canal diversions in the SFR1 package input 

file. Simulating surface-water deliveries regulated by a prior appropriation system, requires that diversions from a river into 

canals serving the farms be simulated by the FMP1. Both equal and prior appropriation water rights may constrain the surfacewater delivery at a farm’s head gate (for fully routed deliveries) or at a specified point of diversion (for semi-routed deliveries). 

In this report, the phrase “inflow into, or delivery to a farm’s head gate” represents either an ‘adjacent’ head gate for fully routed 

deliveries or a point of diversion conceived as a ‘remote’ head gate for semi-routed deliveries. Water-rights allocations that represent the prior appropriation of water can be applied to individual farms or to groups of farms when this group is simulated as a 

“virtual model farm.” Thus, ranked appropriations of entire irrigation districts, or irrigated regions in transboundary settings, can 

be simulated by MF2K with the FMP1. 

Equal Appropriation with Specified Canal Diversions

The potential delivery, DELt,k

potf

 (eq. 7A), of equally appropriated surface water to farms through a ‘river to canal’ conveyance network is equal to the iteratively updated network inflow into the farm’s head gate reach , such that:

DEL Q pot

t,k

in

t,k

f r,f = [L3

/T] (EQ. 7A)

where

t = time step;

k = iteration step;

f = 1,2,..., number of farms; and

r = 1,2,..., number of stream reaches.

For equally appropriated farms, not only the streamflow but also the farm allotment rate [L3/T] constrain the actual amount 

of surface-water delivered. The farm allotment rate, Qt

allotf

, is the product of an equal appropriation allotment flux, qallot [L/T], and 

the respective farm area, Af (eq.7B). The FMP1 converts the allotment height internally into an allotment flux [L/T] by dividing 

the height by the duration of the respective stress period [T].

Q q constr A Q t

allot

t

f allot

t

f f = ⋅ 	 	 = [L3

/T] (EQ. 7B)

For an equal appropriation system in the FMP1, the actual delivery (eq. 4) takes on the form:

 

DEL m act in(TFDR TNRD Q Q t,k

f

t,k

f

t,k

in

t,k

allot

t

f r,f f = − ,	 ,	 )

 

(EQ. 7C)

The inflow into the farm’s head gate reach, , depends on:

a specified inflow into a river (for example, release from reservoir);

a specified diversion from the river into a diversion canal;

upstream river and canal conveyance losses and gains; and

upstream diversions from a diversion canal into upstream farms.

•

•

•

•

22 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Prior Appropriation with Simulated Canal Diversion

Prior appropriation can be simulated with canal diversion as conveyance of surface water to downstream senior water rights 

in the FMP1. By maintaining a minimum streamflow at any upstream farm with junior rights, the minimum streamflow accounts 

for the downstream senior demand (senior right) and the conveyance losses to that senior farm. However, satisfying the senior 

demand also is dependent on the river streamflow, and on maintaining diversions to other even more senior farms that may exist 

on canals diverting water farther downstream.

For a prior appropriation system, the potential delivery, (eq. 8A), through a “river to canal” network is equal to the 

network inflow into the head gate reach of the farm of interest, , minus a minimum streamflow, , which accounts 

for the senior demand of a farm downstream of the same canal and the canal conveyance losses to that farm:

DEL Q pot Q t,k

in

t,k

C-min

t,k

f r,f r,f = − [L3

/T] (EQ. 8A)

where

t = time step;

k = iteration step;

f = 1,2,..., number of farms; and

r = 1,2,..., number of stream reaches.

For a ranked prior appropriation water-rights system, each farm is assigned a certain water right or water-rights call, which 

the respective farm can receive as a maximum:

 Qt

constr, f

 = Qt

call, f

 [L3/T]. (EQ. 8B)

Other approaches to simulate farm diversions in the recent past have implemented prior appropriation water rights systems into conjunctive surface-water and ground-water modeling programs. The main concept of a water-rights package, called 

MODRIGHT for MODFLOW-96 (McCurry, 2000), was to satisfy a farm’s water rights call as an irrigation demand exists, and, 

if so, then to send the entire call in a model to a point of main diversion from the river. This addresses a situation, where a farm 

or an irrigation setting would use its entire right. In some states or regions, this procedure might apply to common practices. In 

general, however, it could lead to oversupply. Thus, the FMP1’s concept is to deliver only the simulated demand, but not more 

than a specified water rights call.

For the implementation of the prior appropriation system in the FMP1, the actual delivery (eq. 4) takes on the following 

form:

 

DEL min(TFDR TNRD Q Q (EQ. 8C) act

t,k

f

t,k

f

t,k

in

t,k

C-min

t,k

f r,f r,f = − ,	 − 	 , Q ) call

t

f

 

Both the inflow into a respective farm’s head gate reach, , and the required minimum streamflow to preserve the delivery to a downstream senior farm, , depend on:

A specified inflow into a river (for example, release from reservoir);

Upstream river conveyance losses and gains;

A potential diversion from the river into a diversion canal, which accounts for the

o Irrigation water demand of all farms on a canal sequentially according to their water rights rank; 

o Canal conveyance losses and gains from the point of canal diversion from the river to these farms; and

An actual diversion from the river into a diversion canal, which might be equal to a potential diversion accounting for all 

the deliveries on one main diversion canal or be restricted by the river streamflow.

•

•

•

•

•

•

Farm Process Capabilities 23
s=2 s=2

Canal diversion

Canal diversion

Qt

SRs=1

Qt,n

S-minf=3

Qt,mCD-sens=2

PDIVt,n+1

for Farms 1+3 s=2

s=2

Q < TDFR

t,n+1

− TNRDt,n+1

+Qt,n+1

inr,f=3 f=3 C-minr,f=3 f=3

t,n

FA

RM 3

RDEL at head gate of Farm 3 = t,k

r,f=3

f=3 f=3 C-minr,f=3

TFDR − TNRDtk + Qtk t,k

No convergence for Farm 3:

Q in

t,k-1

r,f=3 r,f=3

RDEL > - t,k E

f=3 f=3 TFDRt,n+1

-TNRDt,n+1

QC-minr,f=3

t,m-1

FA

RM 1

FA

RM 4 FA

R

Q

M 2

inr,f=1

t,k-1

RDEL at head gate of Farm 1 = t,k

TFDR − TNRDt,k t,k

r,f=1

f=1 f=1

Convergence for Farm 1 until:

RDEL < - - t,k E r,f=1

Qin

t,4 Qinr,f=1

t,m-1 TFDR − TNRD t,m

f=1

t,m

f=1 ~~

Qin

t,1 Qin

t,0 Qin

t,2 Qin

t,3

HIERARCHY RIGHTS TER A W Senior farm Junior farm

FA

RM 1

FA

RM 2

FA

RM 3

FA

RM 4

s=4 PDIV t,n+2

for Farms 2 + 4

s=4 ADIVt,n+2 for Farms 2+4 (zero for Farm 4)

s=4 s=4 ADIVt,n =PDIVt,n for Farm 2

Qinr,f=4

t,n+1

QC-minr,f=4

t,n-1 Qinr,f=4

t,n-1 TFDR − TNRD t,n

f=2

t,n

f=2 ~~

TFDR t,n+2 − TNRDt,n+2

f=4 f=4

SEGMENT 4

SEGMENT 2

QCD-sens=4

t,n

ADIVt,n+1 for Farms 1+3

ADIVt,m =PDIVt,m for Farm 1

Iterations of head-gate inflow estimates

Figure 10. Numerical procedure for determining the diversion rate to a canal for farms subject to a water-rights allocation hierarchy.

24 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Diversion into canal for senior farm on canal

Stream release into river segment s (specified per stress period and constant over time step t)

Actual diversion = potential diversion

actual diversion from river into canal segment s at time step t, and at iteration step k

potential diversion from river into canal segment s at time step t, and at iteration step k

Iterative approach of determining the canal diversion for a farm (here: starting with an initial )

Simulation of a potential diversion for a junior farm exceeding the actual diversion

Minimum canal streamflow not available for farm f at its head gate, necessary to account for senior farm on same canal

Inflow into head gate reach of farm f, at reach r, at time step t, and at iteration step k

Total farm delivery requirement of farm f, at time step t, and at iteration step k

Total non-routed deliveriy to farm f, at time step t, and at iteration step k =

Delivery requirement into head gate reach of farm f, at reach r, at time step t, and at iteration step k

Error tolerance (convergence criterion)

Stream segment (group of reaches specified in streamflow routing package SFR1)

Farm identifier (farm number): lower farm ID = higher water rights ranking

Time step (diagram displayed within one particular time step)

Iteration step

Reach number: reach = section of stream segment associated with finite-difference cell

types

type act TNRD = ∑ (NRD )

s

r

f

t

k

m

n

−

=

Minimum river streamflow that is not available for diversion to farm f, necessary to account for the

demand and for related conveyance losses to a downstream senior farm located at a downstream

diverting canal

= sum of all types of actually used non-routed deliveries

Qt,k

S-minf

Qt,k

CD-sens

TFDRt,k

f

TNDRt,k

f

RDELt,k

r,f

Qt,k

inr,f

Qt,n Qt,m-1

C-minr,f=3 C-minr,f=3

Qt,n-1

C-minr,f= 4

Qt,m+1

inr,f= 4

t,k

r,f

t,k

f

t,k

f

Qt,k

C-minr,f

Qt

SRs

PDIVt, k

S

ADIVt, k

S

RDEL Qt,0

CD-sens

=0

E

Number of iterations to reach a “convergence solution” for farm 1:

- solving for actual diversion from river into canal to satisfy the delivery requirement for farm 1, and

- determination of minimum canal stream flow at farm 3 to account for demand of downstream farm 1.

Number of iterations to reach a “convergence solution” for farm 1 (m iterations) + number of iterations to

reach a “convergence solution” for farm 2:

- solving for actual diversion from river into canal to satisfy the delivery requirement for farm 2, and

- determination of minimum river stream flow at upstream canal to account for demand of farm 2, and

- determination of minimum canal stream flow at farm 4 to account for demand of downstream farm 2.

n+1 Number of iterations to reach an “exceedance solution” for farm 3:

- potentially necessary diversion (PDIV) exceeds ADIV at first iteration after convergence solution for farm 2:

(delivery to head gate reach is less than RDEL and equal to: )

n+2 Number of Iterations to reach an “exceedance solution” for farm 4:

(delivery to head gate reach is zero, since: )

- potentially necessary diversion (PDIV) exceeds ADIV at first iteration after exceedance solution for farm 3:

EXPLANATION (figure 10)

Farm Process Capabilities 25
The numerical objective is to satisfy a farm’s residual irrigation delivery requirement that is not yet supplied by nonrouted 

deliveries (TFDR−TNRD) by sufficiently diverting water from a river into a canal to account for the canal’s conveyance losses 

to that farm, and for the surface-water inflow into the farm’s head gate reach to meet the farm’s delivery requirement. Depending 

on an estimated diversion from the river into the canal and the conveyance losses or gains, the inflow into the farm’s head gate 

reach will be either sufficient or insufficient to satisfy the residual delivery requirement, TFDR-TNRD. Although canals generally will be ‘losing channels,’ the algorithms also hold for canals that are ‘gaining channels.’ A schematic (fig. 10) illustrates 

how the diversion rate for a canal is determined. The farm identification numbering scheme is inversely proportional to its rank 

(water-right seniority).

No Senior Farm Downstream of the Farm of Interest on the Same Canal

For the hypothetical example farm 1 (fig. 10) is the most senior water-right farm in the model, and is not constrained by 

more senior water rights of any downstream farms. “Downstream farms” in this context stands for farms downstream on the 

same canal where the farm of interest is located and for farms on canals diverting from the river on downstream locations. If 

no senior farm exists downstream on the same canal, the delivery requirement (eq. 9) to the head gate reach of farm 1, RDELrf,, 

simply equates to the total farm delivery requirement, minus the total nonrouted delivery, TFDRf – TNRDf:

 RDELr,f = TFDRf – TNRDf (EQ. 9)

where

f = 1,2,..., number of farms;

r = 1,2,..., number of stream reaches; and

s = 1,2,..., number of segments (in text).

The iterative algorithm determines the ‘unsatisfied increment’ between the reach delivery requirement, , at a current iteration (k) and the actual inflow into the farm’s head gate reach, , resulting from a diversion rate specified or estimated at the previous iteration (k-1).

The initial potential diversion rate t,0 PDIVs , into a certain canal segment (s) is specified by the user in the SFR1 input file 

and can be any arbitrary number (for example, zero). The ‘unsatisfied increment’, , then is added to the initial 

potential diversion rate, t,0 PDIVs , and is applied as the new potential diversion rate, t,1 PDIVs . The program passes on this 

temporary potential diversion rate to SFR1, where it is used as an actual diversion rate. Before solving the ground-water-flow 

equation in MF2K, SFR1 generates the resulting canal streamflow and streambed leakage rates. Due to these conveyance losses 

or gains, the inflow at the farm’s head gate, , again might not be sufficient to satisfy the delivery requirement exactly. During the following iteration, the algorithm then recomputes again the ‘unsatisfied increment, , and adds it to the 

previous potential diversion rate, t,1 PDIVs . 

The algorithm repeats (eq. 10, fig. 10) the computation of the “unsatisfied increment,” RDELt,k
Qt,k
1

r,f inr,f , until convergence 

is reached within a user-specified tolerance (| | ≤ ε).

PDIVs PDIV RDEL Q t,k t,k

r, f

t,k

in

t,k

r,f

= + s − -1 -1 	( 	 ) (eq. 10)

 (indices t, k, s, r, f , fig. 10)

Senior Farm Exists Downstream of the Farm of Interest on the Same Canal

As long as the potential diversion is less than the available river streamflow, the same procedure (eq. 9) is repeated for 

the next more junior water-right farm along the same canal, starting with the PDIV value from the previously processed senior 

water-right farm. If the junior water-right farm is further upstream along the canal (see farm 3, fig. 10), then it has to guarantee 

a minimum canal streamflow, , which accounts for the conveyance losses and the downstream senior-right demand. The 

delivery requirement into the farm’s head gate reach, RDEL is, therefore, equal to the TFDRf of farm 3 minus the total nonrouted 

delivery, TNDRf, plus the minimum streamflow, , required to sustain the delivery to farm 1 and not available for 

farm 3. If a senior farm exists downstream on the canal, the delivery requirement (eq. 11) is estimated as:

 RDELr,f = TFDRf – TNRDf + (eq. 11)

26 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
After having determined a cumulative potential diversion, PDIV, from the river for a certain farm and all farms senior to 

that farm along a canal (farm 3 + farm 1 in fig. 10), the FMP1 passes PDIV on to the SFR1 and to the MF2K main program. 

PDIV is compared with the current value of the actual river streamflow at the point of diversion into the canal before the groundwater-flow equation is solved. If PDIV (± in fig. 10), exceeds the actual possible diversion, then ADIV ( × in fig. 10), as indicated by the dashed line in figure 10, only an insufficient stream inflow can be used for the demanded delivery of the current 

farm.

No Senior Farms Exist on Downstream Diverting Canal (Case A)

If no senior farms exist on a diverting canal located downstream of the canal under consideration (not shown in fig. 10), 

then the farms along the canal are supplied sequentially, according to their rank, until the diversion into the canal is restricted 

or ceases owing to limited available streamflow. At that point, a farm junior to the already sufficiently supplied farms will not 

receive enough water. In this case, the actual diversion from the river reach into the canal segment, ADIVs, is constrained by 

the stream inflow, , into the river stream reach, r. ADIV needs to have already provided the diversion necessary for the 

delivery to senior farms along the same canal segment, s, and the canal conveyance losses to such senior farms (QCD-sens). The 

only amount of a limited river streamflow that is available for the supply to a junior farm and the related conveyance losses, is 

the outflow, outr QS- , out of the reach from which the canal diverts (eq. 12):

Case A: No senior farms exist on downstream diverting canal (not shown in fig. 10).

ADIVs = P DIV , s when PDIVs S < Q -inr

 (eq. 12) ADIVs = QS -inr = QCD-sens + QS -outr PDIVs QS-inr , when £

Senior Farms Exist on Downstream Diversion Canal (Case B)

If higher-ranking farms divert from downstream canals, then a minimum river streamflow, f QS-min , is maintained at the 

point of diversion into an upstream canal. This minimum streamflow is not available for diversion to farm f, which is served 

by the upstream diverting canal. f QS-min must include downstream canal diversions from the river to downstream senior farms 

and for downstream river and canal conveyance losses (fig. 10). Therefore, as apposed to Case A, the actual diversion into the 

upstream diversion canal is limited not only by the river streamflow, but also by a limiting minimum streamflow. The minimum 

streamflow, QS-min, is the difference between the river streamflow downstream from the point of the upstream diversion canal and 

streamflow from the point of the downstream diversion canal. This difference accounts for the conveyance losses and the downstream diversion necessary to supply the downstream senior farm located on the downstream diverting canal.

In this case (Case B), the actual diversion from the river reach into the canal segment, ADIV, is equal to the inflow into the 

river stream reach minus the minimum streamflow that is not available for diversion to farm f, f QS-min . As before in Case A, 

ADIV needs to have already provided the diversion necessary for the delivery to senior farms along the same canal and the canal 

conveyance losses to such senior farms ( ). The only amount of a limited river streamflow available for an insufficiently 

supplied junior farm is:

The outflow from the river reach from which the canal diverts, r QS-out , 

minus

The minimum streamflow, f QS-min , that is not available for diversion to farm f, necessary to guarantee downstream 

canal diversions from the river to downstream senior farms and to compensate for downstream conveyance losses 

(eq. 13):

Case B: Senior farms exist on downstream diversion canal (farm 2, fig. 10).

ADIVs = PDIVs when PDIVs S Q Q -in S r -minf< -

ADIV Q Q S -inr S -min Q Q CD-sen S-out Q P S -min DIVs f s r f s = - = + - when 3 - Q Q S -inr S -minf 

(eq. 13)

•

•

•

Farm Process Capabilities 27
The lesser of the residual farm delivery requirement that is not yet supplied by nonrouted deliveries, TFDR - TNRD, or the 

available streamflow from the farm’s head gate reach, Qin - QC-min, or of a water rights constrained maximum allowable flow rate 

(commonly called a “call,” Qcall), will be diverted from the farm’s head gate reach into the farm (eq. 8C). Supplying the residual 

farm delivery requirement to the most junior farm would require that the cumulative potential delivery from the river into the 

canal be less than the river streamflow (Case A), or less than the river streamflow minus a minimum required streamflow to 

account for downstream senior-rights-driven canal diversions (Case B). If those canal diversions are restricted, as formulated 

by equations (12) and (13), then the junior rights farm will receive a reduced stream inflow at the farm’s head gate. The surface 

water available to the junior farm equals this stream inflow minus further streamflow restrictions for downstream senior farms 

along the same canal.

A flow rate in the amount of a water rights call will be diverted only if the available streamflow exceeds the call. Again, 

that available streamflow could be either sufficient or insufficient to satisfy the farm’s residual delivery requirement. The FMP1 

uses only water rights calls to stipulate a limitation on the farm. Other approaches may result in an oversupply to any farm (for 

example, McCurry, 2000).

Modification of Prior Appropriation System for Surface-Water Surplus

Surplus deliveries owing to the (1) absolute use of nonrouted deliveries, or to (2) a reduced TFDR after invoking a drought 

response policy, may modify the rules of a prior appropriation system as follows:

(1) Nonrouted deliveries that exceed the farm’s delivery requirement of an upstream farm may be specified to supply surplus water into the conveyance system (NRDuse-Flag = 1) to benefit downstream users through a local water transfer. The downstream farm’s diversion requirement from the river accordingly can be replaced in part or fully by supplying surplus water into 

the canal at an upstream farm. This concept assumes a replacement of the rate of surface-water delivery, which a downstream 

farm would have received to satisfy its demand and the according conveyance losses. 

(2) After invoking a drought response policy (for example, water-stacking or acreage-optimization), the farm’s delivery 

requirement may be reduced to be less than the limited surface-water supply. This could be the result of a reduced demand from 

priority crops (in the case of water-stacking), or owing to a reduction of the cropped acreage that would force the demand to 

be even smaller than the limited supply. The latter may occur in situations where surface-water irrigation is unprofitable for a 

particular cropping pattern.

There are several important assumptions in the FMP1 regarding surplus delivery cases 1 and 2:

Assumptions for case 1:

Surplus due to excess nonrouted deliveries supplied to the canal at a certain junior upstream farm can increase the available 

supply to a senior downstream farm. Under such conditions, the junior farm, formerly restricted by the demand of senior farms 

under the prior appropriation system, now has the potential to supply water to senior downstream farms. Such a scenario might 

occur if water is traded between farms along the same canal. However, the concept of a prior appropriation water rights system 

would not be strictly maintained. The FMP1’s farm budget would account for these additional credited deliveries.

The flow-rate portion of the diversion from the river is potentially necessary to account for the demand of the senior farm and 

the conveyance losses to that farm.

• Assumption 1a: When the surplus is smaller than the minimum streamflow requirement, the delivery of surface water 

is reduced by the rate gained by the surplus supplied at the upstream farm and is additionally reduced by any potential canal 

losses for the upstream farm. That is, the remaining diversion from the river plus the surplus supplied at an upstream farm 

compensate fully for the downstream farm’s demand. No water will remain in the canal downstream of the downstream 

farm.

• Assumption 1b: When the surplus is greater than the minimum streamflow requirement, the delivery of surface water 

is reduced to zero, That is, the downstream farm’s demand and the conveyance losses between the upstream and downstream farm is compensated fully by supplying the surplus at the upstream farm into the canal. The excess surplus (that is, 

surplus in excess of minimum streamflow requirement) also is supplied to the canal. Therefore, more water will arrive at the 

downstream farm than what is needed to satisfy this farm’s demand.

28 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Total surface-water (SW) + 

ground-water (GW) supply

farm-area

Prorated excess- supply to cells with 

supply deficiencies (weighted by

their original irrigation requirement)

Actual available irrigation

rate per cell=

Total SW + GW Supply x

Actual available irrigation rate per priority crop cell =

TDR > AI if any TDR < AI

Crop

EXPLANATION

EXPLANATION

1

2

3

4

Crop

1-Priority crop

2-Non-priority crop

3-Non-priority crop

4-Priority crop

all priority-crop cells’ TDR > AI

as long as:

if any priority-crop cells’ TDR< AI

but if:

Average available

 irrigation (AI)

Actual available irrigation (AVI)

Excess supply

Prorated excess supply

Average available

 irrigation (AI)

Actual available irrigation (AVI)

Actual available irrigation rate per non-priority crop cell = 0

WATER-STACKING = STACK LIMITED SUPPLY ON PRIORITY CROPS

(Priority crops are crops which generally are not fallowed)

Prorated excess-supply to priority-crop cells 

with supply deficiencies

(weighted by their original irrigation requirement) 

Priority farm-area Cell-area of priority crops +

Total delivery requirement 

per cell (TDR) =

Crop irrigation requirement 

(CIR)/irrigation efficiency

Excess supply

Prorated excess supply

Total delivery requirement 

per cell (TDR) =

Crop irrigation requirement 

(CIR)/irrigation efficiency

Figure 12.

Figure 11.

Total supply bDemand of priority crops Total supply Demand of priority crops

Recompute new farm-demand,

new surface-water delivery,

and new ground-water requirement

 ̈ ̈  ̈ ̈

x cell-area +

DEFICIT IRRIGATION = APPLY LIMITED SUPPLY TO ALL CROPS

Figure 11. Concept of Deficit Irrigation Policy.

Figure 12. Concept of Water-Stacking Policy (Legend see figure 11).

Farm Process Capabilities 29
Assumption for case 2:

Using less routed surface-water than what was formerly available as limited supply also implies that a lesser flow rate is needed 

for diversion from the river into the canal to account for this new demand and associated conveyance losses. Such a lesser 

diversion consequently leads to excess streamflow in the river downstream of the diversion, which is in contrast to invoking the 

drought scenario where the downstream junior farm(s) located along a downstream diverting canal will benefit from the reduced 

diversion. If this benefit exceeds the demand of the downstream junior farm then such a farm will not need to reduce its demand 

anymore and the drought-policy scenario may not be invoked for the downstream junior farm(s).

Drought Scenario Alternatives

If the potential supply of surface water and ground water is insufficient to meet the crop demand, three options of economic 

and noneconomic drought response policies can be applied: acreage-optimization (eq. 14), deficit irrigation (fig. 11), or deficit 

irrigation with water-stacking (fig. 12).

If the desired response to insufficient irrigation supplies is to reduce crop acreage through an optimization routine, then the 

optimized total farm irrigation demand must be equal to or less than the available supply of nonrouted, and (semi-)routed surface 

water as well as ground water (TFDR ≤ TNRD + DELact + QMAXF). The objective function describes a linear optimization 

scheme, where the objective is to maximize the farm’s overall profit associated with the surface water irrigated acreage and with 

the ground-water-irrigated acreage of all farm cells.

The optimization of surface- and ground-water irrigated cell acreages (equals the optimization variables) is subject to 

resource and area constraints: the farm’s irrigation demand from nonrouted surface water, (semi-) routed surface water, and 

ground water should not be greater than the respective available water resources (TNRD, DELact, QMAXF). The area of each 

cell’s acreage should be bound by an initial maximum acreage and a minimum allowed acreage, which usually is zero. The ratio 

between the optimum cell acreage and the initial maximum cell acreage is applied as a reduction factor to the cell’s net recharge 

calculation before the net-recharge term is added to the left-hand side and right-hand side of the finite-difference flow equation.

The economic value or net profit per unit area associated with the irrigation of a specific water type and with a certain crop 

type can be determined for each cell by subtracting the respective costs of applying either irrigation of a certain water type to a 

unit area of the model cell from the crop benefit per unit area. As opposed to the crop benefit per unit area (b), which enters the 

objective function directly as user-specified parameters, the water costs per unit area irrigated with a certain water type are calculated by the FMP1 in the objective function (eq. 14) as the product of water costs per unit water volume (cgw, csw) associated 

with a user-specified water-type multiplied by the required model-cell specific crop irrigation flux (q).

Update of Source Term Flow Rates

After a drought policy has been applied, the source-term flow rates are updated regardless of whether the supplies are (A) 

greater than or equal to or (B) less than the adjusted irrigation demand (fig. 13). 

(A) If after applying a drought policy scenario, the total irrigation demand is still greater than or equal to the total supply, 

that is,

If TFDR ≥ TNRD + DELact + QMAXF ⇒ then for the following drought policies

deficit irrigation (in general),

water stacking (if reduced farm delivery requirement of priority crops > total supply),

acreage-optimization (if demand was forced to equal the total supply), then the flow rates are updated as follows:

(1) For all scenarios: apply “pre-policy” surface-water supply TNRD + DELact and 

 ground-water pumping at maximum capacity QMAXF.

(2) For all scenarios: apply reduced available irrigation (AVI) to cells, which

 do not receive the originally required total delivery requirement TDR = CIR/OFE 

 (for AVI > CIR); irrigation related losses are: (AVI - CIR) instead of (TDR – CIR).

(B) If, after applying a drought policy scenario, the total irrigation demand is less than the total supply, that is, 

If TFDR < TNRD + DELact + QMAXF ⇒ then for the following drought policies:

water stacking (reduced farm delivery requirement of priority crops < total supply)

acreage-optimization (demand of low profitable crops even < total supply) flow rates are updated as follows:

•

•

•

•

•

30 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Objective Function: ∑∑( × )

×

× ×

×

×

= − i t

t

i i

t

i i max Z b c q x (EQ. 14)

subject to: notations:

gw ground water.

rsw routed surface water,

nrd nonrouted delivery,

nrd, rsw, gw;

1 2 number of cellsin a farm;

- minimum possible acreage of cell (taken to be zero);

-initial / maximum possible acreage of cell;

- acreage per cell irrigated with water type ;

- crop irrigation flux required for a cell

=

=

=

=

=

−

−

t

i , ,...,

x

x

x t

q (CIR ) ;

i min

i max

t

i

i i

notations (cont.):

- on-farm irrigation efficiency.

cumulative maximum capacity of all wells in a farm

actual surface-water delivery to a farm ;

total nonrouted delivery to a farm ;

- water supply resource of type t :

OFE

WR (QMAXF )

WR (DEL )

WR (TNRD )

WR

gw

act

rsw

nrd

t

=

=

=

c t.

y a ET b

A

$ b

W

$

p A

W b y

t

i

c

i

costs of water type

with : (water production function).

crop benefit from expected yield and crop market price : ;

−

= +





 



 =



 



 



 



 −

[ ]

[ ]

[ ]

[ ]

[L] L c

L

L c

L

L c

L

$ c

c c c c c

c

c L

L

L L

$ c

L

$ c

c c c c

c

L

$ c

gw DEL

i

gw SHL

i

gw WHL

F

gw BASE

gw DEL

i

gw SHL

i

gw WHL

F

gw gw BASE

i

gw

i

rsw DEL

i

rsw SHL

i

rsw FP

rsw DEL

i

rsw SHL

i

rsw rsw FP

i

rsw

i

nrd

i

unit delivery costs effectivedistance from cell to well

unit pumping costs surface head lift from"effectivewell" to cell

unit pumping costs effectivewell head lift of allfarm wells

with : pumping base maintenance costs

ground-water costs:

unit delivery costs distance of cell to nearest reach

unit pumping costs surface head lift from nearest canalreach to cell

with : fixed price of surface water

surface-water costs:

nonrouted-delivery costs

3

3

3

3

3

3

3





 =





 =





 =





 



 =

= + + +

−





 =







× L ×L

$

3 





× ×L

$ 





× ×L

$ 





× × L

$ 









 =





 



 =

= + +

−





 



 −

−

−

−

−

− − − −

−

−

−

− − −

x x ( )

x x

q x WR OFE

i min

t

t

i

i max

t

t

i

i

t t

i i

≥ = 0

≤

≤

−

−

∑

∑

∑

(EQ. 14)

Farm Process Capabilities 31
(1) For water stacking: recompute TNRD, DELact for priority crops, and supplemental QREQ 

 (here < QMAXF) for priority crops.

(2) For acreage optimization: apply resulting profitable amount of nonrouted delivery (≤ initial TNRD), 

 surface-water (≤ initial DELact) and ground-water pumping (≤ QMAXF).

(3) For both scenarios: apply reduced available irrigation (AVI) to cells, which do not receive the originally required

 total delivery requirement TDR = CIR/OFE (for AVI > CIR); irrigation related losses are:

 (AVI - CIR) instead of (TDR - CIR).

For cases (A) and (B), if in any cell the available irrigation is smaller than the CIR (AVI < CIR), then all available irrigation is 

used, and no irrigation related losses occur.

EXPLANATION

Test for sufficiency, demand > supply?

= <

<

Farm net

recharge

UPDATE AT EACH ITERATION

ADD TO FINITE-DIFFERENCE EQUATIONS ADD TO FINITE-DIFFERENCE EQUATIONS

UPDATE AT EACH ITERATION

>?

>?

Yes No

recompute

Farm net

recharge

recompute

New SW delivery 

and stream/canal 

leakage

recompute

New required 

well pumpage 

(QREQ)

recompute

SW delivery and 

stream/canal

leakage

“pre-policy”

Well pumpage + 

max. capacities 

(QMAX)

“pre-policy”

Figure 13.

WATER STACKING ACREAGE OPTIMIZATION

Demand:

Total farm delivery

requirement

of priority crops

Supply:

Total supply =

SW delivery +

GW well capacities

Insufficiency for

priority crops:

use available supply

Sufficiency for

priority crops:

use new supply

for priority crops

Demand:

Delivery Requirement 

of crops related to 

optimized acreage

Supply:

Total supply =

SW delivery +

GW well capacities

Supply sufficient for

optimized demand:

use available supply

Available supply not

optimally profitable:

use new supply for

profitable crops

SW

GW

Less than

Surface water

Ground water

Figure 13. Updating of source-term flow-rates depending on the drought-response policy chosen.

32 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Applicability and Limitations

The FMP1 facilitates the estimation of water consumption from irrigated agriculture from precipitation, surface water, and 

ground water. The types of approximations made by the FMP1 can be used to simulate a wide variety of irrigation settings that 

span the spectrum from flooded fields, to drip irrigation of truck crops and orchards. In addition, this process can be used for a 

wide variety of applications that include consumption of water by vegetation in nonirrigated agriculture, fallow fields, natural 

vegetation, and urban landscape settings. 

While the FMP1 can simulate a wide variety of settings for consumption of water by vegetation and evaporation, a number 

of basic assumptions are required to facilitate these simulations. These approximations represent limitations that may preclude 

the application of the process to certain types of problems. The limitations include:

(1) The steady-state analytical approximation for changes in flow in the unsaturated part of the root zone does not include

 any changes in storage in the unsaturated zone;

(2) The potential transpiration is assumed to be equally distributed over the entire active root zone;

(3) There is no delay in the infiltration of irrigation and precipitation. Therefore, runoff from the soil surface is subtracted

 after infiltration and evapotranspiration are estimated;

(4) Deep percolation beyond the active root zone is taken to be recharge;

(5) Recharge is assumed to be an instantaneous source pulse into ground water;

(6) Evapotranspiration from ground water is taken to be an instantaneous sink pulse out of ground water;

(7) The farm wells are assumed to be single-aquifer wells. However, multi-aquifer wells entered through Multi-Node 

 Well package also can be linked to FMP1; 

(8) The nonrouted surface-water deliveries are assumed to be exempt from water-rights allocations and are accounted 

 for first with respect to satisfying the TFDR; and

(9) With respect to satisfying the TFDR during sufficiency, nonrouted deliveries are accounted for by first priority, 

 semi- or fully routed surface-water deliveries by second priority, and ground-water pumpage by third priority.

General Data Requirements

A review of general data requirements will assist the user with the compilation of the data required to use the FMP1 with 

MF2K. The items reviewed in this section generally follow the sequence of the data input items as described in the “Data Input 

Instructions” section of this report. In particular, the data requirements described in the “Data Input Instructions” section of this 

report discuss data requirements for the entire simulation and then data requirements for each stress period. To facilitate understanding of these data requirements, two-dimensional data arrays and multi-dimensional data lists, which could be retrieved from 

Geographic Information System (GIS) coverages, are summarized. 

Input parameters, or parameters from which input parameters are derived, generally are kept in italic. Some parameters, 

parameter arrays, or parameter lists are read only once when related option flags are specified by the user. The flags are capitalized and in parentheses. These flags are defined in detail in the following section of this report (Data Input Instructions in the 

“Explanation of Fields used in the Input Instructions” subsection of this report).

Arrays and Lists of Spatially Distributed Data

Two-dimensional arrays of spatially continuous features (for example, polygons) and multi-dimensional lists for line or 

point features are required mostly for the entire simulation, but in some cases also are required for every stress period. The compilation of these data may be supported through the use of a GIS. Two-dimensional arrays of farm, soil-type, or crop-type identifiers relate only to a single identifier (ID) variable and, therefore, are not discussed again in the following sections. Multi-dimensional attribute lists contain several parameters attributed to one multi-dimensional variable. They, therefore, are, discussed in 

more detail in the following sections of this report: “Data requirements for the entire simulation” and “Data requirements for 

each stress period.”

General Data Requirements 33
Two-Dimensional Arrays

In MODFLOW, the model domain is discretized into a mesh of blocks called cells, the locations of which are described 

in terms of rows, column, and layers with an i,j,k indexing system (Harbaugh and others, 2000). A two-dimensional (2D) array 

refers to a 2D-matrix of a model variable, x(i,j), that contains a value for each cell, that is applied at the center of the cell. Each 

value of the model variables, x(i,j), is held constant during either each stress period or for the entire period of simulation. Spatially distributed model variables, such as 2D-arrays of real or integer variables, can be generated by a GIS preprocessor using 

the same boundaries and discretization as specified in the input file for the Basic Package (BAS6) or in the Discretization File 

(DIS) (Harbaugh and others, 2000).

Ground-Surface Elevation

A two-dimensional (2D) real array of ground-surface elevation is required for the entire simulation. This array may be 

obtained optionally by converting Digital Elevation Model (DEM) data into a GIS raster data grid of different resolution, or from 

a point feature class or polygon feature class that is sampled at the cell centers (where it may represent the mean, median, or 

minimum land-surface elevation).

Identification Arrays

Every farm, soil type, and crop type must have an integer number identifier (ID). Each respective ID grid array can be 

obtained optionally by converting the ID attribute of a GIS polygon feature class into a GIS raster grid coverage. Alternatively, 

a point feature class with MF2K cell center coordinates and an attributed ID can be created by overlaying the ID attribute of a 

polygon feature class onto a point feature class, which contains coordinates of the MF2K model cell centers. If these features are 

at a smaller resolution or more detailed than the user-specified model-grid discretization, these features may need to be simplified to average values for each model cell. Other farm, soil type, or crop type attributes are not represented as a 2D-array, but as 

data lists related to their respective IDs. While the ID arrays are mostly required only for the entire simulation, the Crop-Type 

Identification also may be read for each stress period, if crop rotation is desired. The sequence of each respective farm, soil type, 

or crop type must run from 1 to the total number of farms, soil types, or crop types.

Farm Identification—A 2-D integer array of Farm Identification (Farm-ID) is required for the entire simulation. The 

spatial distribution of the Farm-ID may be random as long as there is no water-rights allocation ranking associated with 

the Farm-ID (IALLOT < 2). Non farm-active mode cells must be given an identifier of zero. If the prior appropriation 

option is selected (IALLOT ≥ 2), then the sequence of the Farm-ID numbering scheme has to follow the farms’ waterrights ranking (water-right seniority). That is, the Farm-ID equal to one is the farm with the most senior water rights and 

the larger Farm-ID numbers indicate a lower (that is, more junior) water-rights ranking.

Soil-Type Identification—A 2-D integer array of Soil-Type Identification (Soil-ID) is required for the entire simulation. 

The spatial distribution of the Soil-ID may be random. Soil types outside the farms can be given a zero identifier. Soil 

types within farms must have an identifier greater than zero. Spatial estimates of soils can be simplified from sources 

such as the State Soil Geographic Database STATSGO (U.S. Department of Agriculture, 2005a) or the more detailed Soil 

Survey Geographic Database (SSURGO) (U.S. Department of Agriculture, 2005b).

Crop-Type Identification—A 2-D integer array of Crop-Type Identification (Crop-ID) is required for the entire simulation if the distribution of crop types is considered permanent throughout the simulation (IROTFL ≥ 0). If the spatial 

distribution of crop types changes temporally (that is, crop rotation; IROTFL = -1), then the Crop-ID array must be read 

for each stress period. The sequence and spatial distribution of the Crop-ID may be random. Crop types outside the farms 

can be given a zero identifier. Crop types within farms must have an identifier greater than zero. Polygons of fallowed 

areas are identified by a Crop-ID of -1. In addition, fallowed areas combined with nonrouted deliveries can be used to 

simulate Aquifer-Storage and Recovery (ASR) infiltration ponds.

•

•

•

34 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Multi-Dimensional Attribute Lists

Multiple attributes that relate to the same identification (ID) of a multi-dimensional variable can be represented in form of 

a “multi-dimensional attribute list,” x(m,n). The list contains a value for each variable number, n, and attribute number, m. The 

variable ID is equal to the variable number, n. An attribute list also may contain layer, row, and column number associated with 

the variable ID. For instance, layer, row, and column number could be represented as x(1,n), x(2,n), and x(3,n). Other integer or 

real parameters attributed to each variable number, n, then would be represented as x(m,n), where m = 4,5,..., total number of 

attributes. GIS coverages can display the delineation of features associated with an ID and other attributed parameters. Such a 

coverage can provide the data input variables needed for an attribute list such as GIS point-feature coverages representing farm 

wells or GIS-arcs representing stream segments. In addition, GIS polygon-feature coverages or GIS grids can provide the location of a variable ID such as model cells representing stream reaches or farm wells.

Farm Wells

Farm well attributes of “parameter” farm wells must be defined for the entire simulation if “parameter” farm wells exist 

(MXL > 0) that can be used to scale maximum well capacities with a multiplier. For FMP1, the word “parameter” stands for this 

“multiplier-parameter.” These simple multipliers are not part of the MF2K parameter-estimation process that requires observations. The list of attributes for “parameter” farm wells is described fully in a later section (“Data Requirements for the Entire 

Simulation”). A parameter name is given for each such list that contains a scaled parameter-factor assigned to a certain attribute, 

which, for farm wells, is the maximum capacity of farm wells. 

Farm well attributes of “nonparameter” farm wells can also be defined for each stress period if “nonparameter” farm wells 

exist during a stress period (ITMP > 0). They are described in the “Data Requirements for Each Stress Period” section of this 

report as data input variables of the attributes list for “nonparameter” farm wells. A GIS point- or polygon-feature coverage of 

Farm-Well IDs and other farm-well attributes can provide the input variables needed for the attributes list for farm wells. The list 

of attributes associated with each farm well includes the layer number of the screened aquifer, horizontal location coordinates, 

the farm well ID, the farm ID and the maximum capacity. This list also may include wells whose discharge rates are simulated 

by the Multi-Node Well (MNW) Package (Halford and Hanson, 2002).

The pumping requirement of a farm well in the FMP1 can be limited to maximum well capacity, that is, to a ‘volumetric 

rate’ constraint. A farm well alternately can be designated in the FMP1 attributes list to be a multiple-aquifer well that straddles 

several model layers and the pumpage is simulated as an MNW farm well. For MNW farm wells, the pumping requirement also 

can be constrained indirectly by a defined aquifer head elevation or by a specified maximum drawdown through the optional 

constraints of the MNW package.

For “multi-layer” wells, an additional advantage of linking an FMP1 well to the MNW package is that the lesser of the 

simulated pumping requirement or the initially specified maximum capacity of the well can be reapportioned to several productive aquifer layers. Depending on the aquifer productivity of each respective aquifer, the total actual pumping rate simulated in 

the MNW package may be equal to or less than the originally desired pumping requirement and the distribution of pumpage 

between model layers may change as heads change between aquifer layers. This actual pumping rate acts as a simulated ‘maximum capacity.’ It replaces the initially specified ‘maximum capacity’ during the second and following iterations when compared 

to the iteratively changing well pumping requirement.

Stream Segments and Reaches

The definition of stream segments and reaches is needed only if routed surface-water deliveries to a farm and drain return 

flows away from a farm are simulated by using the SFR1 package (Prudic and others, 2004) jointly with the FMP1. Surfacewater deliveries can be semi-routed or fully routed to farms by selecting FMP1 options ISRDFL=1 or IRDFL=1. In this case, the 

FMP1 needs information to be entered as SFR1 data input about the stream segments and reaches that represent the conveyance 

network that transports water to a specified point of diversion (for semi-routed deliveries), or directly to a farm’s head gate (for 

fully routed deliveries). In addition, the FMP1 needs information to be entered as SFR1 data input about the drains that deliver 

excess water away from the farm. In the SFR1 package, the numbering scheme and sequence of segments and reaches remain 

the same throughout the simulation. Additional attributes of stream segments are defined as SFR1 input data for each stress 

period.

General Data Requirements 35
Stream Segments—Every segment requires an integer identification number (Stream-Segment ID). The ID sequence is 

not random but must maintain a downstream order similar to the rest of the streamflow network (fig. 14). The segment 

number increases sequentially from upstream to downstream. For instance, diversion segments have a higher segment 

number than the upstream stream segment, from which water is diverted. Tributary segments merge into a downstream 

stream segment with a higher segment number. In general, stream segment parameters are defined for each stress period. 

They are input variables of the attributes list for stream segments. The only stream segment-related attribute that does 

not change throughout the simulation is the Stream-Segment ID. A GIS arcs coverage of Stream-Segment IDs and other 

stream segment attributes can provide the input variables needed for the attributes list for stream segments. The conversion of a GIS arc coverage of Stream Segments into a grid yields a segment ID and reach length associated with a 

stream reach in a finite-difference cell. Both stream reach attributes enter the attributes list for stream reaches among 

other reach-specific parameters (see “Data Input Instructions“ section of this report). The discretization of segments into 

reaches and the resulting respective reach length depends, in part, on the discretization of the model domain as defined in 

the Discretization File (DIS) of MF2K.

Stream Reaches—Attributes of stream reaches are defined for the entire simulation. They are data input variables of 

the stream reaches-related data attribute. A GIS grid coverage of Stream-Reach IDs and other stream reach attributes 

can provide the input variables needed for the stream reaches data list. These attributes can be derived from various GIS 

sources.

Data Requirements for Entire Simulation

The data requirement items in this section generally follow the sequence of the data input items for the entire simulation 

in the section “Data Input Instructions.” However, for better understanding, 2-D data arrays, which could be retrieved from GIS 

coverages (for example, Farm-ID, Soil-ID, Crop-ID), are explained separately in a section called “Arrays and Lists of Spatially 

Distributed Data” prior to this section. Note that at the beginning, the FMP1 input file can contain text comments that start with #.

Farm-Wells Data

Farm wells can be specified as either parameter or nonparameter wells. Farm well attributes of “parameter” farm wells must 

be defined for the entire simulation if “parameter” farm wells exist (MXL > 0). Attributes of “nonparamter” farm wells are only 

defined for each stress period and are described in section “Data Requirements for each Stress Period.”

•

•

Figure 14. 

COLUMNS

ROWS

Segment 1

Segment 2

Segment 3

Segment 4

Segment 5

Segment 6

Segment 7

Inflow

Inflow

Outflow

Diversion

Diversion point

(semi-routed

delivery)

Pipeline

Canal

Segment junction

Flow direction

Figure 14. Streamflow-routing segment-numbering scheme in relation to direction of flow and model grid (Prudic and others, 2004).

36 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
The following data input is required only for the entire simulation, if farm-well parameters exist (NPFWL > 0). The only 

parameters that are estimated as multipliers with the FMP1 farm wells are used to change the Maximum Capacity of farm wells 

(QMAXfact).

General Information

Number of farm-well parameters (that is, multipliers to QMAXfact).

Maximum number of parameter farm wells.

Data entry block for the QMAX-multiplier parameter

Parameter name for list of parameter-farm wells related to the current multiplier parameter. This can be invoked at any 

stress period.

Parameter type: QMAXfact is the only allowed parameter type in the FMP1.

Parameter value: multiplier applied to QMAXfact of parameter farm wells.

Number of parameter farm wells specific for the current parameter.

Read Parameter-Farm Wells List 

Read list from external file, if cross-referenced to file name containing the list, or

Read list directly from FMP-input file.

Repeat the above data entry block for all other multiplier parameters with a specific parameter name and the attribute list of farm 

wells, for which QMAXfact the respective multiplier is to be applied. Lists of parameter-farm-wells specific for certain QMAXfact-multiplier parameters can be invoked at any stress period by reading the respective ‘parameter name.’

List of Farm-Wells Related Attributes—All attributes of farm-irrigation wells are taken to be constant with time. Note that 

time series of actual well discharge and water-level hydrographs are potentially important information for model calibration. 

However, they are not included in the data input, since the ‘unknown’ farm-well discharge is the main estimation parameter of 

the program. Input variables that represent attributes of a farm well are as follows:

-Layer

-Location (Row, Column)

-Farm-Well ID

-Farm ID associated with Farm Well

-Maximum Well Capacity, which can be varied by changing the parameter value

-[Auxiliary Attribute QMAXRESET or other Auxiliary Attributes].

Layer—In many cases, farm wells are pumping from an uppermost unconfined alluvial aquifer. However, since some 

wells may pump from deeper aquifers, it is necessary to assign to each well the model layers that coincide with the well 

screens. In the attributes list of farm wells that is read for the entire simulation, only one layer can be attributed uniquely 

to a farm-well ID. Alternatively, the FMP1 may be linked to the multi-node well package (MNW) (Halford and Hanson, 

2002), where pumpage across multi-aquifer screen intervals can be reapportioned and estimated by the MNW package. 

Layers of wells that contain screens in multiple aquifer model layers are defined in the MNW package input file. When 

MNW farm wells are linked to the MNW Package by specifying a “negative” farm-well ID in the farm-well attributes list 

of the FMP1 input file, the specification of layers is defined externally in the MNW data input file. Thus, for multi-layer 

MNW farm wells, the layer number is specified as zero as a flag within the FMP1 to specify that the well is a MNW 

well with it’s range of model layers specified in the MNW package. In addition, the list of farm-well attributes may 

also contain single-layer wells, whose discharge rate and maximum capacities are simulated by the MNW package. For 

single-layer MNW farm wells, the user may specify the respective layer number in both the list of farm-well attributes in 

the FMP1 and in the MNW data input file.

•

•

•

•

•

•

•

•

•

General Data Requirements 37
Location—The location of a farm well is designated with the model cell row and column coordinates. Farm wells associated with a specific farm do not necessarily have to be located within the model cells that coincide with that farm. Thus, 

farm wells for any farm also can be located beyond the farm’s boundary. The FMP1 may require a relatively finer resolution to account for crop distribution and well locations associated with each farm if cost optimization features are used. 

For example, this is important especially if the user takes into account that the distance of each farm well to a model cell 

has an impact on the costs of the applied ground water, which is specified in the acreage-optimization case deficiency 

scenario. In the FMP1, each well is associated with a certain Farm ID. Thus, different wells that are associated with different farms can be located within the same model cell (that is, same row and column coordinates). However, this is not 

the case for wells that are designated as MNW wells (negative Farm-well ID). Since the MNW package does not recognize Farm IDs associated with wells, the identification of MNW farm wells is established between the FMP1 and MNW 

package through the same row and column coordinates. Therefore, only the horizontal location of one farm well can be 

identified uniquely through row and column coordinates for MNW farm wells.

Farm-Well ID—The FMP1 simulates pumping from or injection into a well as a point sink or source term associated 

with the center node of a finite-difference cell that is defined by layer, row, and column. In the FMP1, each such point 

sink or source is considered an individual “well.” In reality, such “wells” may represent well intervals screened over one 

aquifer layer. In the attributes list each such “well” has to be attributed uniquely to a Farm-well ID. For a well, which 

produces for different farms, the predominantly receiving farm has to be identified or, alternatively, it needs to be split 

into several ‘virtual’ wells located in the same model cell. Because of the association with the Farm-ID, the farm wells 

that are associated with a specific farm do not need to be located within that farm, but may be located anywhere in the 

active model-cell domain (that is, beyond the farm’s boundary). While the sequence of the Farm-ID must run from 1 to 

the total number of farms, the Farm-well ID can be random. Farm wells that are screened over multiple aquifer layers are 

designated in the FMP1 by a “negative” Farm-well ID which is used by the FMP1 to establish a link to the MNW package. 

Farm ID—Each farm-irrigation well is associated with a certain farm and, therefore, uniquely attributed to a specific 

farm identification (Farm ID). Multiple “single-layer” farm wells that possess equal row and column coordinates can be 

related to different wells and, therefore, must be attributed to different Farm-well IDs. They can be attributed to the same 

Farm ID or to different Farm IDs, as long as they are located horizontally next to each other. This may be especially 

important for coarse-resolution models with large cell sizes. Multiple screened well intervals that relate to the exact same 

multi-layer well cannot be associated in the FMP1 input file with the same Farm-well ID and, therefore, not with the 

same Farm ID. As opposed to “single-layer” farm wells, multiple “multi-layer” MNW farm wells cannot possess equal 

row and column coordinates. Therefore, only one multi-layer well can be simulated by the MNW package for one row 

and column coordinate regardless of Farm IDs. For models that contain many multi-layer wells, the model resolution 

should be fine enough to facilitate MNW package farm wells in separate model cells. To simulate a well that produces 

for more than one farm, the predominantly receiving farm has to be identified. Alternatively, a “single-layer” well can be 

split into several ‘virtual’ wells that have equal row and column coordinate but are attributed to different Farm IDs. Each 

such virtual well must be assigned a unique maximum well capacity that is a portion of the overall maximum well capacity of the real farm well. 

Maximum Well Capacity—Even though the Maximum Well Capacity (QMAX) [L3/T] may be a difficult input parameter to estimate, it is very important to assign a good estimate. Even if a value for QMAX may not be readily available, 

drilling records or pumping tests may allow the estimation of such data. For example, a step-drawdown test (SDT) or 

constant-discharge test (CDT) may have been carried out to test the well or aquifer performance, respectively. If so, then 

those tests easily could give evidence about a maximum well capacity. In addition, wells of similar construction screened 

over similar parts of the aquifer also may have similar hydraulic properties. So, even if not all wells are associated with 

an individually determined QMAX, wells without an individually determined QMAX still may be assigned a value 

extrapolated from other wells. Aside from physically or technically defined maximum capacity, alternatively, allotment 

rules may provide policy constraints, which may serve as a limitation of the well discharge to a maximum flow rate as 

well. For parameter farm wells, QMAX is calculated as the product of a maximum capacity factor, QMAXfact and a 

specific-parameter multiplier, which are read for the entire simulation. Using this method, various sets of QMAX rates 

can be saved for the same or for different wells under a “parameter name” that can be selected at any stress period. Thus 

the determined “default” QMAX rate may be replaced by a rate simulated by a well-specific link between the FMP1 and 

the Mult-Node Well package (MNW). The QMAX simulated by the MNW can only be equal or less than the desired 

pumping rate, which, in turn, can only be less than the default QMAX rate of the FMP1. This could lead to a “self-limiting process,” where the simulated QMAX of a new time step could only be equal or less than the simulated QMAX of a 

previous time step. Hence, in the FMP1, the MNW1-simulated QMAX rate is reset to the FMP1-determined QMAX rate 

•

•

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•

38 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
by default at the beginning of each stress period. However, in the FMP1, an optional flag can be set to reset the simulated 

QMAX to the default QMAX rate at the beginning of each time step (see below in “Auxiliary Attribute QMAXRESET” 

and see section “Data Input Instructions/Explanations and fields Used in the Input Instructions/Dimensions and Flags/

Optional Flags). By resetting the simulated QMAX at each time step, the MNW package can calculate the hydraulically 

maximum possible rate not limited to a simulated QMAX of a previous time step, but bounded only by the FMP1-determined rates of the desired pumping rate and the default QMAX rate of the FMP1.

Auxiliary Attribute QMAXRESET—The specification of the option flag “AUX QMAXREST” as an auxiliary attribute 

will prompt the FMP1 to reset QMAX as simulated by the MNW package to the default QMAX as defined by FMP1 at 

the beginning of each time step. The optional flag “AUX QMAXRESET” tells FMP1 to read an auxiliary integer variable 

in column 7 of the farm wells list after the QMAXfact of QMAX variable. If a “1” is read in column 7 of the farm wells 

list, then the MNW-simulated QMAX is reset to the default QMAX in the first iteration of each time-step.

Auxiliary Attribute (in general)—As many as five auxiliary attributes optionally can be specified to the right of the mandatory farm-well attributes. These values will be read after the QMAXfact or QMAX variable. The auxiliary attribute 

variables will be printed together with the simulated farm well pumping rate to the listing file or to a binary file, where 

they then could be used to facilitate post processing or future linkages to the FMP1.

Model Calibration Data—Observed discharge rates along with water-level measurements or water-level hydrographs of 

some of the farm wells are necessary and valuable to calibrate the simulated farm well discharge rates. Therefore, while 

known discharge rates of farm well are not needed as data input, these data can be used to calibrate the simulated farmwell pumpage. Layer, location, and discharge rates of nonfarm-related wells, such as municipal or industrial use within 

the study area, also may be necessary data input that would be specified separately with the WELL package of MODFLOW-2000 (Harbaugh and others, 2000) or the MNW package (Halford and Hanson, 2002).

•

•

•

General Data Requirements 39

Layer Row Column Farm Well ID Farm ID QMAXfact

[L3/T]

1 1

2 1

0 5 6 
3 1 1000

4 2

5 2

Q-required for farm-well 3 = 800

Example of a Well List for the Multi-Node Well Package:

Layer Row Column Q-desired

[L3/T]

Other

nonfarmrelated

data

Hlim =

limiting

water level,

or

limiting

drawdown

[L]

Other

nonfarm

related

data

1 5 6 50

2 5 6 50

4 5 6

Q-req. or QMAX passed

on from FMP1 and reapportioned to each layer 50

(The well list for the MNW package is read for each simulation)

Cross-Reference and Link from FMP1 well to MNW well

Example of a Farm-Well List for the FMP1:
Farm Data

Farm data consist of farm identifiers and on-farm-irrigation efficiencies. The farm identifiers are a 2-D integer array of 

Farm Identification numbers (Farm ID) that is required for the entire simulation with a nonzero integer number identifier for 

every farm. Nonfarm-active model cells must be given an identifier of zero, similar to the IBOUND arrays for MF2K. The 

sequence and spatial distribution of the Farm ID may have any order as long as no water-rights ranking is associated with the 

Farm ID (IALLOT < 2). However, if the prior appropriation option is selected (IALLOT ≥2), then the sequence of the Farm ID

numbering scheme has to follow the farms’ water-rights ranking (water right seniority). That is, the larger Farm ID numbers 

indicate a lower water-rights ranking.

Farm Irrigation Efficiency

The On-Farm-Efficiency (OFE) is related to each farm through association with every Farm ID and is represented as a 

fractional real number between 0 and 1 (0. < OFE ≤ 1.). This user-specified irrigation efficiency is either constant for each farm 

for the entire simulation period (IEFFL = 1) or user-specified for each stress period (IEFFL = 2). In addition, the user also can 

specify head-dependent irrigation efficiencies that are coupled to the simulated ground-water levels on a cell-by-cell basis. The 

user can distinguish between two conservative irrigation practices (herein referred to as “efficiency behavior”) where an additional flag IEBFL is set. The user can specify two forms of conservative behavior that represent a constant irrigation efficiency 

over each time step (IEBFL = 1) or a constant delivery over each time step (IEBFL = 2 and 3). For conservative management 

practices that seek to maintain a certain constant delivery, a varying on-farm efficiency still could occur owing to natural conditions, such as a fluctuating shallow ground-water level, along with which the beneficially used CIR changes. For IEBFL = 2 and 

3, the FMP1 uses the user-specified on-farm efficiency, OFEspec, to calculate an initially demanded TFDR at the beginning of 

each stress period (IEBFL = 2) or at the beginning of each time step (IEBFL = 3) and calculates subsequently an on-farm efficiency, OFE, for the current time step prior to enacting any deficiency scenario as a head-dependent parameter.

Indices and parameters used in the sections below (summations follow Einstein notation if not indicated otherwise):

t = time step;

k = iteration step;

f = number of farm (farm-ID);

n = number of finite-difference cells in a farm;

r = reach of canal segment;

h = aquifer head;

OFE = on-farm efficiency (OFEspec = specified on-farm efficiency);

CIR = crop irrigation requirement per cell n;

TDR = total delivery requirement per cell n; and

TFDR = total farm delivery requirement per farm f.

The On-Farm Efficiency (OFEspec) for each farm can be specified for either the entire simulation (IEFFL = 1) or for each 

stress period (IEFFL = 2). Every Farm ID is associated with a real number fraction of on-farm efficiency between 0 and 1 (0. 

<OFEspec ≤1.) as follows:

Farm ID OFEspec

1

2

3

The FMP1 simulates for each model cell in a farm a CIR that dynamically depends on an iteratively changing aquifer head. 

Conservative assumptions may imply either farm-specific on-farm efficiencies to be constant during a model time step (IEBFL =

1) or the total applied delivery to be constant (IEBFL = 2,3). In both cases, the parameter assumed constant acts as a proportionality factor for CIR when simulating the other one (IEBFL = 1, 2, 3):

40 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
• Constant Efficiency Over Time Step (Case 1, IEBFL = 1)—An iteratively changing, head-dependent total cell 

 delivery requirement is calculated by:

o an iteratively changing, head-dependent CIR; and

o an on-farm efficiency constant during time step ‘t’, acting as proportionality factor for CIR.

The on-farm efficiency is specified as a constant value for the entire simulation or for each stress period and, therefore, is 

constant during all time steps, t, for the given stress period. This case applies to the assumption that the farmer knows by experience how efficient or inefficient he can operate. To compensate for inefficient use, the CIR must be increased to the total delivery 

requirement by a proportionality factor equal to the inverse of the predefined efficiency. For each model cell, n, in a farm, f, the 

total delivery requirement (TDR) (eq. 15) is estimated as:

( ) ( ) t

spec, f

t ,k

n

t ,k

f ,n

k

n

t ,k TDRf ,n h CIR h OFE −1 −1 = (eq. 15)

The total for the entire farm, f, is summed:

= ∑n

t ,k

f ,n

t ,k TFDRf TDR

Accumulating the TDR of all model cells in a farm yields the total farm delivery requirement, TFDR, reflected in the Farm 

Budget output file. In contrast with cases 2.1 and 2.2, this option (case 1) does not cause any model output of ‘computed’ efficiencies, since on-farm efficiency is considered to remain equal to its input value. However, for reference, the specified values of 

on-farm efficiencies are reflected in the Farm Budget output file “FDS.OUT” in column 5, labeled “OFE.”

• Constant Delivery Over Time Step (Case 2, IEBFL = 2, 3) — An iteratively changing, head-dependent on-farm 

 efficiency is calculated by:

o an iteratively changing, head-dependent CIR; and

o a total applied delivery, constant over time step ‘t,’ acting as proportionality factor for CIR.

The total delivery requirement is assumed to be equal to the total applied delivery and to remain constant over a time step 

‘t.’ By taking the TDR to be equal to the actual applied delivery implies that the demand can be supplied fully and that there is 

no existing deficiency for the model cell. Thus, case 2 (IEBFL = 2, 3) cannot be used in conjunction with deficiency scenarios 

(that is, IDEFFL ≠ 0 when IEBFL = 2, or 3). Since TDR is assumed to be constant throughout a time step, its initially determined value does not change iteratively as a function of changing aquifer head. However, the initial value of TDR evaluated 

during the first iteration (k = 1) of time step ‘t’ depends on the aquifer head of the solution of the previous time step (t-1). This 

case represents a conservative behavior of a farmer who chooses to maintain an initially determined rate of delivery, regardless 

of whether a changing ground-water level influences the CIR. For instance, a rising ground-water level could cause uptake from 

ground water to contribute to the crop water demand, which, in turn, would lower the CIR. To maintain the same rate of water 

application while CIR decreases would mean that the on-farm efficiency decreases. For each finite-difference cell in a farm, the 

head-dependent efficiency (eq. 16) is estimated as:

OFE h CIR h TDR h f n

t k

n

t k

f n

t k

n

t k

f n

t k

n

t

,

, ,

,

, ,

,

− − , = − ( ) = ( ) ( ) 1 1 1 1 ,	for	 	 k t >	1	and	 	>	1	

for any farm:

OFE C f IR TDR t k

f n

t k

n

f n

t k

n

,

,

,

,

, = ∑ ∑ =1

with evaluation of TDR at first iteration of first time step of stress period (IEBFL=2), or evaluation of TDR at first iteration of 

each time step (IEBFL=3) as:

TDR h CIR h OFE k f n

t k

n

t

f n

t k

n

t

spec f

t

,

,

,

,

, , = − = − ( ) = ( ) = 1 1 1 1 	for	 	 	1,	t = 	1	(IEBFL=2)

 for k =- 1, for all t (IEBFL=3)

and evaluation of TDR at first iteration of second and following time steps as:

TDR h CIR h OFE h k f n

t k

n

t

f n

t k

n

t

f

t

n

t

,

,

,

, , = − = − − − ( ) = ( ) ( ) 1 1 1 1 1 1 	for	 	 = > 	1,	t 	1	(IEBFL=2)

(eq. 16)

General Data Requirements 41
The initial value of TDR is a function of CIR, which depends on the aquifer-head of the last iteration of the previous time 

step. In addition, the initial TDR may be either a function of a specified efficiency (for k = 1, t = 1 when IEBFL = 2, or for k = 1 

of all time steps when IEBFL = 3) or a head-dependent efficiency evaluated during the last iteration of a previous time step 

(for k = 1, t > 1 when IEBFL = 2).

The user can specify, whether efficiency is reset to the specified efficiency only at the beginning of the first time step of 

each stress period (case 2.1; IEBFL = 2), or at the beginning of the each time step (case 2.2; IEBFL = 3). The latter option is 

especially useful when the CIR changes rapidly within a stress period from time step to time step (for ICUFL = 3, or IRTFL = 3, 

or IPFL = 3). In this case, a constant TDR over a time step may be evaluated solely based on the time step-specific CIR and userspecified efficiency. The use of the head-dependent efficiency of a previous time step may not be appropriate for the calculation 

of an initial TDR value of a current time step. For instance, if a very high consumptive use in a certain time step causes the water 

level to drop heavily, then the CIR may increase and approach a TDR constant over that time step, that is, the efficiency could 

reach 100 percent. Then, if in a following time step, the water level recovers and the CIR decreases, accordingly, then the initial 

TDR would be equal to CIR based on 100-percent efficiency calculated at the end of the previous time step.

Within each time step, the head-dependent efficiency needs to approach beyond a preset 1 percent closure criterion between 

the value of the solution iteration and the value of the second last iteration. Closure, however, is determined by head convergence. Therefore, if head convergence is achieved without sufficient efficiency convergence, the program will output the following message to the screen, asking the user to lower the head closure criterion:

“HCLOSE MUST BE SMALLER FOR HEAD-DEP. EFFICIENCY OF FARM ?? TO CONVERGE!”

For Cases 2.1 and 2.2, the FMP1 will yield a time series of head-dependent efficiencies, which is included in the Farm Budget output file , “FDS.OUT” in column 5, labeled “OFE.”

Soil-Type Data

Soil-type data consisting of a 2-D integer array of Soil Type Identification (Soil-Type ID) and of soil type-related attributes 

is read once and used for the entire simulation. The Soil-Type ID can have any user-specified distribution and sequence that is 

independent of the farms IDs. A data list of soil-type attributes related to each soil type is associated with the Soil-Type ID 

(table 2). Capillary fringe and/or coefficients for an analytical solution that approximates transpiration uptake (Concept 1) are 

variables attributed to each Soil-Type ID for the entire simulation as:

Capillary Fringe,

Coefficients for Analytical Solution (a, b, c, d, e), Soil-Type ‘Word’ (SANDYLOAM, SILT, or SILTYCLAY) 

(if Consumptive-Use Concept 1 is chosen with ICCFL = 1).

Soil-Type ID if ICCFL = 1

if ICCFL = 2

DRZ = f(Tpot, TRZ)

Coefficients for n = f(DRZ) Capillary

Fringe [L] a b c d e

Soil Type in

Words1

1 0.201 -0.195 3.083 3.201 -3.903 SANDY LOAM

2 0.320 -0.329 2.852 1.303 -2.042 SILT

3 0.348 -0.327 1.731 0.530 -0.377 SILTY CLAY

1.

Table 2. Example of soil-type attributes associated with the Soil-Type ID.

The user either specifies numeric coefficients or the word for the soil types for these predefined soil types.

Coefficients for

The soil-type specific capillary fringe is needed along with root zone depths for each crop type (table 2) to linearly approximate transpiration uptake (fig. 7). The user-specified capillary fringe values must be greater than zero. Coefficients a, b, c, d, and 

e are used to define parameters DRZ and n of an analytical solution, which describes a vertical pressure head distribution (eq. 

17) that is reached at steady state in soils with root uptake from ground water as the only source (fig. 8B) (absolute value of the 

pressure head |ψ| over the depth d of the total root zone):

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•

42 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
ψ

ψ

ψ

ψ

= ⋅



 



 + −

−

−





 





DRZ

DRZ

d DRZ

d

DRZ

n

4

1

1

(| |)

(| |) (eq. 17)

Since this analytical function cannot be solved explicitly, it can be solved iteratively for depth d(|ψ|) by the Bisection 

Method in the FMP1. A reduction of the linearly-approximated transpiration by conditions of anoxia or wilting is proportional 

to a reduction of the total root zone by ranges of pressure heads within the vertical pressure head distribution that are typical for 

anoxia or wilting. Such ranges of pressure heads, at which uptake is zero due to anoxia or wilting, are described below as “Root 

Uptake Coefficients” for specific crop type (fig. 8A). Therefore, the parameters “DRZ” and “n” allow the fitting of a vertical, 

pseudo, steady-state pressure head distribution. 

Parameters DRZ and n in equation 17 are defined as follows:

(1) The Depleted Root Zone (DRZ) (eq. 17A) is a function of the potential Transpiration and the Total Root Zone. 

It is defined as the lower part of the root zone at which the pressure head increases with depth from the minimum (negative) pressure head (defined as ψ4

 in stress response function, see below) to zero at the bottom of 

the root zone (fig. 8B) as:

[a Tpot b TRZ c] DRZ e ⋅ + ⋅ + = ln( ) ln( ) (eq. 17A)

(2) The Sinuosity Coefficient (n) (eq. 17B) expresses the curvature of the vertical pressure head configuration over 

depth (fig. 8B), which increases with increasing DRZ as:

n = d ⋅ ln(DRZ) + e (eq. 17B)

Coefficients a to e for three different soil types (Schmid, 2004) are predefined in the FMP1 for three soil types. 

The user has the option to either enter key words for the predefined soil types or the numeric values for user-defined 

approximations of the DRZ and sinuosity coefficient, n.

Example for using Concept 1 along with Soil Type ‘Words’

Soil-type 

ID

Capillary fringe 

[L]

if ICCFL = 1, and if using Soil Type ‘Word’

1 SANDYLOAM

2 SILT

3 SILTYCLAY

Predefined Coefficients a,b,c,d,e that are used FMP1 internally, when using Soil Type ‘Words’

Coefficients for DRZ = f(Tc-pot, TRZ) Coefficients for n = f(DRZ) Soil Type in Words

a b c d e

0.201 -0.195 3.083 3.201 -3.903 SANDYLOAM

0.320 -0.329 2.852 1.303 -2.042 SILT

0.348 -0.327 1.731 0.530 -0.377 SILTYCLAY

Example for using Concept 1 along with user-defined approximations of DRZ and n.

Soil-type

 ID

Capillary 

fringe 

[L]

if ICCFL = 1

Coefficients for DRZ = f(Tc-pot, TRZ) Coefficients for n = f(DRZ)

a b c d e

1

2

3

General Data Requirements 43
Crop-Type Data (Natural)

Crop-type data consist of a 2-D array of Crop-Type Identifications (Crop-Type ID) and related attributes, which are constant 

throughout the entire simulation. If no crop rotation is specified (IROTFL ≥ 0), then there is no change in the spatial distribution 

of the crop type with time and only one set of Crop-Type IDs are needed for the entire simulation. However, if rotating crops are 

being simulated (IROTFL = -1), then the crop distribution (Crop-Type IDs) is specified for each stress period. The Crop-Type ID

is an integer number with any user-specified distribution. Model cells representing fallowed areas are identified by a Crop-Type 

ID of -1. Crop-type attributes that are grouped as “natural” crop variables (as opposed “agro-economic,”) and related to each 

Crop-Type ID are: 

Root zone depths (constant throughout the entire simulation);

Fractions of transpiration and evaporation of consumptive use8 (constant throughout the entire simulation);

Fractions of inefficiency losses to surface-water runoff (constant throughout the entire simulation);

Root Uptake Coefficients for Stress Response Function (constant throughout the entire simulation);

Coefficients to calculate time series of cumulative growing degree day values (CGDD), crop coefficients (Kc), potential 

crop evapotranspiration (ETc-pot), and root-zone depth.

Root-Zone Depth

The root-zone depth can be specified for each crop for the entire simulation (IRTFL = 1) or specified for each stress period 

(IRTFL 12 10 = 2), or calculated for time-step averages (IRTFL = 3) from climate-data time series and a list of crop-specific 

coefficients. The root-zone depths always must be greater than zero.

For IRTFL = 1, the user specifies the root-zone depth (ROOT in data input instructions), as a lumped parameter that is constant during the entire simulation as:

Crop ID Root depth [L]

1

2

3

Fraction of Transpiration and Evaporation of Consumptive Use

The transpiratory and evaporative fractions are defined as fractions of consumptive use for the entire simulation 

(IFTEFL = 1) or for each stress period (IFTEFL = 2). Consumptive use is specified by the user as constant potential cropevapotranspiration, ETc-pot during a stress period (ICUFL = 2), or it is derived internally by the FMP1 as time series, based on 

crop coefficients, Kc, and reference evapotranspiration, ETo (ICUFL = 3). The ETc-pot is defined as:

 ETc-pot = (Kt + Ke) ⋅ ETc-pot = (Kt + Ke) ⋅ Kc ⋅ ETo

The transpiratory and evaporative fractions of consumptive use are taken to vary linearly with the respective area occupied by 

crops and the respective area open to soil-evaporation (fig. 15). If the cropped area and the exposed, wetted area amount to the 

entire area, then Kt + Ke = 1, and Ke = 1- Kt, therefore:

 Tc-pot = Kt ⋅ ETc-pot

 Ec-pot = (1-Kt) ⋅ ETc-pot

8

Consumptive use is defined commonly as crop evapotranspiration, which includes transpiration and evaporation in a cropped agricultural area (Colorado’s 

Decision Support System, 1995; Gelt and others, 1999; European Environment Agency, 2004).

•

•

•

•

•

44 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Figure 15. Transpiratory (Kt

) and Evaporative (Ke) Fractions of Consumptive Use.

Figure 15.

Wetted area (crop-covered)

EXPLANATION

Wetted area (exposed)

Non wetted area (exposed)

Total area

Fraction of area available for:

Evaporation related to irrigation

Transpiration

Evaporation related to precipitation

Example 1: Orchards

Example 2: Row crops

Kt = 0.7

Ke

p = 0.3

Ke

i = 0.13

Kt = 0.6

Ke

p = 0.4

Ke

i = 0.4

Scale for orchards (for example 200 m)

Scale for row crops (for example 2 m)

1

Ke

i

Ke

p

Kt

1

Ke

i

Ke

p Kt

1

Ke

i

Ke

p Kt

General Data Requirements 45
The transpiratory fraction of consumptive use, Kt (FTR in data input instructions), is assumed to be independent of whether the 

transpiratory consumptive use is satisfied by irrigation, precipitation, or ground-water uptake.

The FMP1 assumes that evaporation from precipitation occurs over the entire exposed area because all noncrop-covered 

area will be wetted such that the fraction of evaporation from precipitation (FEP) is Ke

p = 1 -Kt

, or Kt + Ke

p = 1. If the wetted 

portion of the exposed area does not extend to the entire exposed area–as is possible for irrigation–then Ke can be restricted such 

that the fraction of evaporation from irrigation (FEI in data input instructions) is Ke

i <1 -Kt

. Different irrigation methods can 

lead to different lateral extent of the wetted area, with Ke

i ≤1 -Kt

, or Kt + Ke

i ≤1. For basin flood irrigation, however, a complete 

inundation of the noncovered area is expected and, thus: Ke

i = 1 – Kt., or Kt + Kei = 1.

For precipitation as source for evaporation: Ec-pot = Ke

p ⋅ ETc-pot = (1-Kt

) ⋅ ETc-pot

For irrigation as source for evaporation: Ec-pot = Ke

i ⋅ ETc-pot

Which fraction of the consumptive use is transpiratory (FTR) or evaporative (FEP and FEI) also depends highly on type of crop 

and growth stage, which is why Kt and Ke can also be specified for each stress period. If the vegetation cover reaches close to a 

100 percent, then Kt = 1 and Ke = 0.

Each crop may be associated with lumped or constant values of a transpiratory (Kt) and evaporative fraction of consumptive use 

(Ke

p

 - related to precipitation, Ke

i

 - related to irrigation) during the entire simulation (changes during the growing season from 

stress period to stress period would be ignored). Thus, for IFTEFL = 1, Kt + Ke

p = 1 and Kt + Kei ≤ 1, and these are listed for each 

crop type as follows:

Crop ID Kt

(0 < Kt ≤ 1)

Ke

p

(0 ≤ Ke

p ≤ 1)

Ke

i

(0 ≤ Ke

i < 1)

1

2

3

In the FMP1, the evaporation losses from irrigation, Ei, are defined to vary proportionally to Ti, and it is assumed that there is 

equality between Ei/Ti and Ke

i

/ Kt. Therefore, Ei = Ti × (Kei/Kt) and Kt must not be zero.

Fraction of Inefficiency Losses to Surface-Water Runoff

The fraction of inefficiency losses to surface-water runoff can be specified for the entire simulation (IIESWFL = 1), for 

each stress period (IIEWSFL = 2), or related to slope calculated internally as rise-run (IIESWFL = 0). For IIESWFL = 1, each 

crop may be associated with lumped and constant values of fractions of inefficiency losses to surface-water runoff that are 

related to precipitation or irrigation during the entire simulation, as follows:

Crop ID IEsw

p

(0 ≤ IEsw

p ≤ 1)

IEsw

i

(0 ≤ IEsw

i ≤ 1)

1

2

3

Root-Uptake Coefficients for Stress Response Function

The root-uptake coefficients for the stress response function are specified when Consumptive Use Concept 1 is chosen 

(ICCFL = 1) and Concept 2 (ICCFL = 2) is not chosen. Each crop is associated with root uptake parameters equal to the absolute 

values of four different negative pressure heads at which uptake is zero (ψ1-Anoxia, ψ4-Wilting Point) and optimal (ψ2, ψ3) as 

follows:

Crop ID |ψ1 | [L] |ψ2 | [L] |ψ3 | [L] |ψ4

| [L]

1

2

3

46 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Specific Crop Coefficients

Coefficients to calculate Growing Degree Days (GDD), Cumulative Growing Degree Days (CGDD), Crop Coefficients 

(Kc), Crop Evapotranspiration (ETc), and Root Depths are user-specified if Consumptive Use (ETc) or Root Depth of each crop 

are to be calculated as time-step averages (ICUFL = 3 or IRTFL = 3). The calculation of growing degree days (GDD), and other 

time-variable parameters that depend on GDD rests on empiric equations, which take into account daily minimum and maximum 

temperatures and crop-specific minimum and maximum cutoffs and base temperatures. For using the option to calculate time 

series of crop evapotranspiration (ICUFL = 3) and root depths (IRTFL = 3) FMP-internally, the time-series steps must be entered 

in ‘days’. To select daily time-series steps, the time unit of all model data must be ’days’ in the Discretization File (ITMUNI = 

3) (Harbaugh and others, 2000). The program considers it a conceptual mistake if the user specifies ICUFL = 3 or IRTFL = 3 

and, at the same time, a time unit different from days. In that case, the program will stop and the user will be informed about the 

problem on the screen. 

Growing Degree Days (GDD) and Cumulative Growing Degree Days (CGDD) for a specific crop and a certain day d of 

the time series are calculated by the program in conjunction with climate time series of daily minimum and maximum 

temperature (Tmin, Tmax), using the following crop-specific parameters specified by the user:

o Base-Temperature = Tbase

o Minimum-Cutoff-Temperature = Tmin-cut

o Maximum-Cutoff-Temperature = Tmax-cut

( )

( )

( )

( )













+ − ∀ < ∀ >

+ − ∀ < ∀ ≤

+ − ∀ ≥ ∀ >

+ − ∀ ≥ ∀ ≤

=

− −

− − −

− − −

− − − −

max min base max max cut min min cut

max min cut base max max cut min min cut

max cut min base max max cut min min cut

max cut min cut base max max cut min min cut

T T / T T T ; T T

T T / T T T ; T T

T T / T T T ; T T

T T / T T T ; T T

GDD( d )

2 										

2 							

2 							

2 			

 ∑==

d

t

CGDD( d ) CDD(t );

1

with: t = 1,2,...,d; ∀ 1≤ d ≤ D,

where D = total number of days in time series.

Crop Coefficient (Kc) and potential Crop-Evapotranspiration (ETc-pot): The calculation of a crop coefficient Kc as a thirddegree polynomial of a cumulative growing degree day value for a day d requires four polynomial coefficients specified 

by the user:

o Polynomial Coefficients to describe a CGDD-Kc functionality

Kc(d) = C0 + C1 ⋅ CGDD(d) + C2 ⋅ CGDD(d)2 + C3 ⋅ CGDD(d)3

The potential crop-evapotranspiration (ETc) is calculated by the program as:

ETc(d) = Kc(d) ⋅ ETo(d);

with: ETo(d) = Reference-ET at day d of climate-data time series.

Root Depths: The root depth for a specific crop and a certain day d is calculated as a linear function of a cumulative 

growing degree day, using the following crop specific parameters specified by the user:

o Beginning Root Depth = RDbeg

o Maximum Root Depth = RDmax

o Root Growth Coefficient = RGC











∀ ⋅ >

⋅ ∀ ≤ ⋅ ≤

∀ ⋅ <

=

( )

( ) ( )

( )

( )

max max

max

RD RGC CGDD d RD

RGC CGDD d RD RGC CGDD d RD

RD RGC CGDD d RD

RD d beg

beg beg

•

•

•

General Data Requirements 47
Specific crop coefficient are entered by the user for the entire simulation, if ICUFL = 3 or if IRTFL = 3, as follows: 

Coefficients for GDD calculation Polynomial coefficients for 

CGDD-Kc-function Coefficients for root-depth calculation

Crop ID Basetemperature

Minimum

cutofftemperature

Maximum

cutofftemperatureC0 C1 C2 C3

Maximum

root depth

Root growth 

coefficient

Beginning 

root depth

1

2

3

As long as the temperature units are used consistently, either °C or °F can be used in the FMP1 to calculate the Crop Coefficient 

Kc. If, however, the polynomial coefficients retrieved from the literature (for example, Sammis and others, 1985) were derived 

from a CGDD-Kc functionality with GDDs in °F, but the GDD calculation in MODFLOW-FMP1 is based on read-in temperatures, in °C, then the polynomial coefficients need to be converted ahead of reading them into the FMP-input file, as follows:

C1

°C = (9/5) ⋅ C1°F,

C2

°C = (9/5)2 ⋅ C2°F,

C3

°C = (9/5)3 ⋅ C3°F,

In general, a Crop Factor Kc calculated with CGDD based on °C, and with polynomial coefficients based on °F, can be formulated as follows:

Kc = C0 + (9/5) ⋅ C1

°F ⋅ CGDD°C + (9/5)2 ⋅ C2°F ⋅ (CGDD°C)2

 + (9/5)3 ⋅ C3

°F ⋅ (CGDD°C)3

Also, if Root Growth Coefficients (RCG) are available only in inch/°F , but the program is run in metric units, and then a conversion from inch/°F to m/°C has to be carried out in the following way: 

RGC

RGC

m C

in F

/

/ .

°

° = ⋅ ⋅ − 



 



 



 



 9  1

0 024

32

Climate Data

Climate data can be read as constants for each stress period or can be read as time series throughout the duration of the 

entire simulation. The attributes that are read for the entire simulation for each time-series step (for example, day) include 

time series of daily minimum- and maximum-temperature, precipitation, and reference evapotranspiration. These climate data 

are necessary only if one of the following three parameters is to be calculated as averages during each time step (for example, 

weekly) (ICUFL = 3, or IRTFL = 3, or IPFL = 3):

Consumptive Use (potential crop evapotranspiration)

Root Depth

Precipitation

When the precipitation data are used directly to build time-step averages, the reference evapotranspiration and the minimum- and maximum-temperature data are used in conjunction with crop-specific coefficients, to calculate the potential crop ET 

and the crop specific depth of the root zone. Most commonly, the Penman-Monteith estimate of potential evapotranspiration is 

used as a reference evapotranspiration. For more information on the calculation of the Penman-Monteith reference evapotranspiration, the reader is referred to the FAO publications 24 and 56 (Doorenbos and Pruitt, 1977; Allen and others, 1998) or to 

Hoffman and others (1992).

Time-Series Steps Max-Temperature Min-Temperature Precipitation Reference ET

1

2

3

•

•

•

48 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
The calculation of growing degree days is based on empiric equations, which take into account daily minimum and maximum temperatures and crop-specific minimum-cutoff, maximum-cutoff and base temperatures. For using the option to calculate 

time series of crop evapotranspiration and root depths FMP-internally, the time-series steps must be specified in days. To select 

daily time-series steps, the time unit of all model data must be ’days’ in the Discretization File (ITMUNI = 3) (Harbaugh and 

others, 2000). The total number of days in a time series then is equal to the length of the simulation LENSIM. Hence, for a 

period of a 1-year simulation, a data record with 365 time-series steps will be read, if the climate data are available in daily timeseries steps. 

However, if the option to build averages during each time step is chosen only for time series of precipitation, then other 

time units are possible (in this case: columns of Tmax, Tmin, and ETo are zero or remain empty). For instance, if the simulation 

encompasses 100 years, and precipitation is available only as yearly means, then averages can be built for 5 yearly time steps. In 

this case, the time unit must be chosen to be years in the Discretization file (ITMUNI = 4) of MF2K, and the FMP1 would read 

a record with 100 time-series steps. Another example would be that if the duration of the simulation is 1 year, and the precipitation comes in hourly values, then averages could be built for weekly time steps. In this case, the time unit must be hours in the 

Discretization file (ITMUNI = 2), and the FMP1 would read a record with 8,760 time-series steps.

The option to build averages from preexisting time series over MF2K time steps should be handled with care as memory 

insufficiency might occur. As described above, for precipitation only, the user could use units that are consistent with the MF2K 

time units of yearly, daily, and hourly time-series steps. Theoretically, one also could use minutes (ITMUNI = 2) or seconds 

(ITMUNI = 1) as time units. However, the allocation of memory for very short time units and long periods of simulation could 

exceed computer memory (for example, seconds and 1-year simulation would cause the allocation of 31,536,000 elements). 

In addition, precipitation recorded at every second or minute is very unlikely. For that reason, the program always will issue a 

warning on the screen, as soon as IPFL = 3 and ITMUNI = 1 or = 2.

Crop-Type Data (Agro-Economic)

A crop-type related data list is a list of attributes related to each crop type. The fallow flag and crop benefit attributes are 

“agro-economic” crop variables (as opposed “natural” crop-type data) that are attributed to each crop-type identifier. 

Crop-Type-Related Fallow Flags

The fallow flag attribute is required if stacking water on priority or nonfallowable crops (“water-stacking”) is desired as a 

deficiency scenario (IDEFFL = -2). Input parameter of the Fallow List for the entire simulation:

• Fallow-Flag: 

o 1 = Crop type fallowed (for example, onions)

o 0 = Crop type not fallowed (for example, pecan trees)

Crop ID Fallow flag

1

2

3

Crop-Type Benefits Data

Crop benefits are derived from crop specific water production functions and from the crop’s market price if Acreage-Optimization is chosen as the deficiency scenario (IDEFFL > 0). The crop benefit minus the irrigation costs associated with irrigated 

areas assigns an economic value (profit) to the optimization variables “ground water- and surface-water irrigation area” for each 

model cell. Water production functions and a crop’s market price may be specified for each crop type either for the entire simulation (IBEN = 1) or for each stress period (IBEN = 2).

General Data Requirements 49
A water-production function is a linear relation between the ‘water beneficially used for crop production’ [length] and the 

‘expected yield’ [weight/area]. For a linear relation between the water used and the yield, the ‘water beneficially used’ is taken 

to be equal to the crop evapotranspiration. The FMP1 allows the user to apply selected water production functions from the literature (for example, Doorenbos and Kassam, 1979; New Mexico State University Climate Center, 1996). These water production functions do not take into account micro-scale conditions other than evapotranspiration and yield. For instance, a groundwater elevation close to ground surface can cause local anoxia and a reduction of yield. Therefore, yield, as derived by means of 

a water production function, is independent of head. As a result, acreage optimization simulations with the FMP1 generally are 

limited to conditions in which the ground-water elevation is such that the yield and, consequently, the benefit are not affected. 

The crop evapotranspiration entering the water production function either is specified by the user or calculated by the program. 

The user has the option to either specify crop evapotranspiration (ETc) as a constant consumptive use for each stress period or to 

simulate time series of ETc. The monetary crop benefit per unit area can be obtained by multiplying yield with the crop’s market 

price [value/weight]. Slope and intercept of the water production function and the market-price per crop are required data input 

parameters.

Input Parameters of the Crop Benefits Data

Each crop type may be associated with the following parameters constant during the entire simulation (only if IDEFFL > 0, 

and for the entire simulation if IBEN = 1):

Coefficients of crop-specific Water-Production Function (Yield vs. ETc):

Slope

Intercept

Market-price per crop

Crop ID Calculation of crop benefit

Water production function Crop market price

Slope (a) Intercept (b)

YIELD = a × ET + b, where: YIELD in [weight/area], and ET in [length] [value/weight]

1

2

3

The FMP1 computes a crop-yield from a water-production-function specified in consistent units. The length units are the 

units specified in the discretization file (*.DIS) of MF2K, that is, feet for LENUNI = 1, centimeter for LENUNI = 2, and meter 

for LENUNI = 3. Generally, the weight units will be pounds for English length units (the only possible English length unit in 

discretization file is feet), and kilograms for International units (centimeters or meters). However, the choice of the weight unit 

depends on the user’s preference. It is the user’s responsibility to keep consistently the same weight unit for the output-yield of 

the water-production-function and for the crop-market-price. In many cases, the user will be able to retrieve water-productionfunctions from the literature, available in form A or form B:

(A) Yield [lb/acre] = alit ⋅ ETc [inch] + blit

(B) Yield [kg/hectar] = alit ⋅ ETc [cm] + blit

where alit, blit = coefficients of water production function as retrieved from the literature

This report provides assistance in converting water-production-functions of form A into a form using pound and feet or 

kilograms and centimeters or meters, and of form B into a form using kilograms and meters or centimeters.

Converting form A into pounds and feet:

Yield [lb/ft2] = (alit ⋅ 12/43560) ⋅ ETc [ft] + (blit / 43560)

the coefficients a and b entering the water production function are:

 a = alit ⋅ 12/43560

 b = blit /43560

•

•

•

•

50 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Converting form A into kilogram and centimeter or meter:

Yield [kg/cm2] = [alit ⋅ 2.47/(2.54⋅2.2⋅109)]⋅ ETc [cm] + [blit ⋅ 2.47/(2.2⋅109)]

 the coefficients the coefficients a and b entering the water production function are:

 a = alit ⋅ 2.47/(2.54⋅2.2⋅109)

 b = blit ⋅ 2.47/(2.2⋅109)

Yield [kg/m2] = [alit ⋅ 2.47/(2.54⋅2.2⋅102)]⋅ ETc [cm] + [blit ⋅ 2.47/(2.2⋅104)]

 the coefficients the coefficients a and b entering the water production function are:

 a = alit ⋅ 2.47/(2.54⋅2.2⋅102)

 b = blit ⋅ 2.47/(2.2⋅104)

Converting form B into kilogram and centimeter or meter:

Yield [kg/cm2] = (alit /109) ⋅ ETc [cm] + (blit /109)

 the coefficients the coefficients a and b entering the water production function are:

 a = alit / 109

 b = blit / 109

Yield [kg/m2] = (alit /102) ⋅ ETc [m] + (blit /104)

 the coefficients the coefficients a and b entering the water production function are:

 a = alit / 102

 b = bllt / 10 4

Converting form B into pounds and feet:

 Yield [lb/ft2] = [alit ⋅ 2.54⋅12⋅2.2/(2.47⋅43560)] ⋅ ETc [ft] + [blit ⋅ 2.2/(2.47⋅43560)]

 the coefficients a and b entering the water production function are:

a = alit ⋅ 2.54⋅12⋅2.2/(2.47⋅43560)

b = blit ⋅ 2.2/(2.47⋅43560)

Water-Cost Coefficients

Water-cost coefficients are implemented if acreage-optimization as deficiency scenario is chosen (IDEFFL > 0). As 

opposed to the crop benefit per unit area, which enters the objective function directly, the water costs per unit of ground-water or 

surface-water irrigated area are calculated implicitly in the objective function as the product of ground-water- or surface-waterspecific water costs, per unit water volume, multiplied by the required model-cell specific crop irrigation flux. 

For ground water and surface water, the respective water costs, per unit volume, can be expressed by different cost coefficients that are independent or dependent of head or distance. Base maintenance costs for ground-water pumping, a fixed price 

for (semi-) routed surface water9, and a fixed price for nonrouted surface-water deliveries are specified directly by the user as 

costs per unit volume. Head- or distance-dependent costs are calculated by the FMP1 by multiplying user-specified costs per 

unit volume and unit head lift or unit distance multiplied by the respective actual vertical head lift or horizontal distance to the 

cell. Note that distance-dependent costs only occur, if the increasing distance is proportional to increasing costs, caused, for 

example, by pipe-friction.

9 Routed surface-water delivery: Surface water routed through a ‘river to canal’ network to a farm head-gate directly adjacent to the farm. Semirouted 

surface-water delivery: Surface water routed through a ‘river-to-canal’ network to a point of diversion from where water is delivered in a nonrouted form (for 

example, by way of pipeline) to a remote farm that is not adjacent to the canal.

General Data Requirements 51
Ground-water and surface-water cost coefficients determine the cost of ground water or surface water per unit water volume. Multiplied with a model-cell specific irrigation flux, we get the cost of applying ground water or surface water to the area 

of a model cell. By subtracting this number from the crop-benefit of a model cell, the net profit of ground-water or surface-water 

irrigation of a certain crop can be computed in that model cell. Four ground-water cost coefficients and four surface-water cost 

coefficients are required as data input. They may be specified for the entire simulation either as lumped coefficients for all farms, 

or for each farm. The latter requires the input of a farm-related list of coefficients that, alternatively, can be specified for each 

stress period.

Ground water base maintenance costs per unit volume [$/L3]

Ground water costs for pumping in well per unit volume per unit of lift [$/(L3⋅L)]

 Pumping costs are dependent on the head-lift per farm well. The FMP1 calculates an effective head lift per farm, 

 weighted by the maximum capacities of the respective farm wells. Multiplying the pumping costs per unit volume 

 and unit lift by the ‘effective head lift’ in a farm results in the effective well-pumping costs per unit applied 

 volume specific for a certain farm.

Ground-water costs for vertical lift from well to cell per unit volume per unit of lift [$/(L3⋅L)]

 For nonhorizontal surfaces, an additional head-lift from the well to the respective model cell may occur. The FMP1 

 calculates an effective elevation of a ‘virtual well location’ as average of all farm well elevation, weighted by their 

 maximum capacities. If the ground elevation of a respective (irrigated) model cell is higher than the effective elevation, 

 then the difference represents the additional surface-head-lift needed to be overcome to pump the ground water 

 uphill. Multiplying the Well-to-Cell-Lift Costs per unit volume and unit lift by the ‘surface head lift’ yields 

 Effective Well-to-Cell Pumping costs per unit applied volume.

Ground-water delivery costs per unit volume, per unit distance [$/(L3⋅L)]

 The FMP1 calculates an effective distance of each model cell in a farm to a virtual location of a ground water 

 source by weighting the distances of each well to the model cell by their respective maximum capacities. Multiplying

 the ground water delivery costs by that ‘effective distance’ yields Effective Ground water Delivery Costs per unit 

 volume to each model cell.

Fixed Price of (Semi-) Routed Surface Water per unit volume [$/L3]

Costs for Vertical Lift of (Semi-) Routed Surface Water from Canal to Cell, per unit volume per unit lift [$/(L3⋅L)]

 For nonhorizontal surfaces, an additional head lift from the nearest canal reach to the respective model cell also 

 may occur. The FMP1 determines the elevation of stream head in the nearest reach (for routed deliveries) or in the 

 reach specified (for semi-routed deliveries), and calculates the difference between the elevation of the stream-head 

 and the elevation of the model cell if the latter is higher than the former. This difference represents the actual surface-

 water lift. Multiplying the surface-water lift costs per unit volume and unit lift by the actual lift yields the Surface-

 Water Lift Costs per unit-applied volume.

Delivery Costs of (Semi-) Routed Surface Water per unit volume, per unit distance [$/(L3⋅L)]

 The FMP1 calculates the distance of each model cell in a farm to the nearest canal-reach (for routed deliveries) or 

 in the reach specified (for semi-routed deliveries). Multiplying the surface-water delivery costs by that nearest 

 distance yields Surface Water Delivery Costs per unit volume to each model cell from its respective nearest reach.

Fixed Price of Nonrouted Surface Water per unit volume [$/L3]

Lumped Water Cost Coefficients for all Farms

The data input of lumped Water Cost Coefficients does not require a data list but simply eight lumped real constants for the 

entire simulation and for all farms of the entire model area (if IDEFFL > 0, and ICOST = 0) as follows:

•

•

•

•

•

•

•

•

52 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Ground water pumping base costs [$/L3

] Value

Well-Pumping costs [$/(L3⋅L)] Value

Well-to-Cell lift costs [$/(L3⋅L)] Value

Ground-water delivery costs [$/(L3⋅L)] Value

Fixed price of (Semi-)Routed Surface Water [$/L3] Value

Reach to Cell lift costs of (Semi-)Routed Surface Water [$/(L3⋅L)] Value

Reach to Cell delivery costs of (Semi-)Routed Surface Water [$/(L3⋅L)] Value

Fixed price of Nonrouted Surface Water [$/L3] Value

Farm-Related Water Cost Coefficients

Each farm may be associated with ground-water and surface-water cost coefficients constant during the entire simulation 

(if IDEFFL > 0, and ICOST = 1) as follows:

Farm ID

Ground-water 

pumping

base costs

Well 

Pumping

costs

Well-toCell lift

costs

Groundwater 

delivery

costs

Fixed Price 

of (semi-) 

routed surface water

Reach to Cell 

lift costs of 

(semi-) routed 

surface water

Reach to Cell 

delivery costs 

of (semi-) 

routed surface 

water

Fixed Price 

of nonrouted 

surface 

water

[$/L3] [$/(L3⋅L)] [$/(L3⋅L)] [$/(L3⋅L)] [$/L3] [$/(L3⋅L)] [$/(L3⋅L)] [$/L3]

1

2

3

Surface-Water Data

Surface-water data are required if surface water is allocated as either “nonrouted,” as “semi-routed,” or as “fully routed” 

delivery to a farm

Nonrouted Deliveries

Nonrouted deliveries or extractions are volumes of water allocated to or extracted from a farm that are independent of any 

simulated delivery or conveyance mechanism (if nonrouted surface-water delivery flag INRDFL = 1). In the FMP1, nonrouted 

deliveries are assumed to change from stress period to stress period and, therefore, can not be specified for the entire simulation.

Routed Deliveries

The streamflow routing is facilitated by a link of the FMP1 to the SFR1 package for routing surface water through a conveyance network either to a specified, remote point of diversion (if “semi-routed” is selected), or directly to a head gate adjacent 

to a farm (if “fully routed” is selected).’

Semi-Routed Deliveries

Semi-routed surface water is defined as surface water routed through a “river-to-canal” network to a point of diversion from 

where water is delivered in a nonrouted form (for example, by pipeline) to a remote farm not adjacent to the canal (for the entire 

simulation if semi-routed surface-water delivery flag ISRDFL = 1). Such a farm only can receive “semi-routed” but not “fully 

routed” deliveries. Each farm may be associated with a point of diversion for the entire simulation as:

– Farm ID

– Row

– Column

– Segment number

– Reach number

General Data Requirements 53
Example for specifying farm specific points of diversion for semi-routed deliveries: 

Farm ID Row Column Segment number Reach number

1

2

3

The user may optionally specify the diversion point by (1) a full set of information consisting of model cell coordinates, 

stream segment number, and reach number (row, column, segment, reach), or (2) by just the model cell coordinates and a 

stream segment number (row, column, segment), or (3) by just the model cell coordinates (row, column), or alternatively (4) by 

the number of a stream segment and the number of a reach, or (5) simply by the reach number, which, in any case is uniquely 

associated with a segment number. Option (3) does not require any data information from the SFR1 package but is possible only 

if a unique identification of a reach is not necessary. Such a unique identification is important if more than several stream segments pass through one model cell. If a farm is adjacent to a canal and can divert “routed” deliveries from a head-gate, then this 

farm cannot receive “semi-routed” deliveries at the same time. If coordinates of a point of diversion are entered mistakenly for a 

semirouted delivery, then the program exits and prints an error message that asks the user to set the coordinates for that farm to 

zero.

Fully-Routed Deliveries

Fully routed deliveries can be described as surface water routed to a farm by a “river-to-canal” conveyance network (if 

routed delivery flag IRDFL = 1). For this option, the farm has to be adjacent to the canal/lateral. Such a farm only can receive 

“fully routed” but not “semi-routed” deliveries. “Adjacent” in this context means that there must be no model cell in between at 

least one cell containing a canal reach and at least one cell of a particular farm. By setting IRDFL=1, the user has the option to 

let the FMP1 automatically generate head gates at the most upstream located canal reach for a farm, where canal reach cells are 

adjacent to a section of the farm boundary. Clearly, the setup of the Farm ID array and the specification of stream reach locations 

(row, column) in the SFR1 (see “Stream-Reach Data” below) decides whether fully routed deliveries to farms can be simulated 

or not. For farms, where canal reach cells are separated from farm cells by one or more model cells, the user may specify remote 

points of diversion for farms for semi-routed deliveries (ISRDFL > 0). 

Stream-Reach Data

A list that specifies stream reach data is required for the entire simulation (as defined by the SFR1 package input instructions), if the semi-routed delivery flag ISRDFL = 1 or if the fully routed delivery flag IRDFL = 1. The user should refer to the 

input instructions for the SFR1 package (Prudic and others, 2004) if the SFR1 package and the FMP1 are used jointly. Attributes 

of stream reaches are defined as data SFR1 data input for the entire simulation and described below. The reaches in the list must 

be sorted sequentially by segment numbers.

Attributes of stream segments (in other words, inflow, roughness, vertical hydraulic conductivity, thickness, and elevation 

of top of streambed) are defined for each stress period in section “Data Requirements for Each Stress Period”) 

Stream reach related data:

– Layer number of the cell containing the stream reach.

– Row number of the cell containing the stream reach.

– Column number of the cell containing the stream reach.

– Number of Stream Segment in which the stream is located (sequentially ordered).

– Sequential number of this reach within a stream segment.

– Length of channel of the stream within this model cell.

Data Requirements for each Stress-Period

The data-requirement items used for each stress period that are briefly described in this section of the report generally 

follow the sequence of the data-input items for each stress period described in the subsequent section of this report “Data Input 

Instructions.” The data items reviewed here represent the additional or different specifications for the entire simulation that was 

described in the previous section of this report.

54 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Farm-Wells Data

Farm well attributes of “nonparameter” farm wells must be defined for each stress period if “nonparameter” farm wells 

exist during a stress period (ITMP > 0). In FMP1, the word “parameter” stands for a “multiplier-parameter” (herein referred to 

as “parameter wells”). This term is used during a stress period to modify a parameter factor assigned to certain attributes for the 

entire simulation. The maximum capacity of farm wells is the only attribute that currently is available in the FMP1 for parameter 

scaling and this feature does not currently include parameter estimation.

Nonparameter or Parameter Farm-Wells Lists

A Flag (ITMP) is read at the beginning of each stress period that is either equal to the number of nonparameter farm wells, 

or—if such a nonparameter farm wells list was used in one stress period—that specifies to reuse the list. If only parameter farm 

wells are used, and their list already was read for the entire simulation, then that flag always is zero. Another flag is read in the 

same line indicating the number of parameters in use during the current stress period (NP). 

If parameter farm wells exist for the current stress period (NP ≥ 1) a lists of parameter farm wells that are specific for a certain QMAX-fact multiplier parameter can be invoked simply by reading the respective “parameter name,” which was predefined 

for the entire simulation. The FMP1 will read NP parameter names NP times during one stress period. That is, the user has 

several choices, depending on whether one or several multiplier parameters were prespecified, which apply either to a selection 

or all of the farm wells. For instance, one parameter name representing a group of farm wells could be repeated for every stress 

period, whereas, by choosing different parameter names for other groups of farm wells, the wells could experience a change in 

their maximum capacities from stress period to stress period, representing respectively changing QMAX-fact multipliers. To 

apply changing multipliers to a group of farm wells most effectively would require to cross-reference to a file name containing 

that respective list, so the list doesn’t need to be repeated in the input file.

The simplest advantage of using parameter farm wells versus nonparameter farm wells seems to be the following: If the list 

of farm-well variables, including the maximum capacities, does not change during the entire simulation, then the same parameter name representing that list simply can be reread at any stress period. It may be preferable to specify for the entire simulation 

a list of farm-well variables that have been constant during the entire simulation than to put that list into the section for the first 

stress period as a nonparameter farm-wells list, and to repeat it by setting ITMP = -1.

If nonparameter farm-wells exist for the current stress period (if ITMP > 0), then a similar list of farm-well attributes as 

outlined for the entire simulation (for parameter farm wells) can be specified and read for nonparameter farm wells at each 

stress period either directly from the FMP1 input file or from an external file containing the list. Nonparameter maximum well 

capacity values that are read for each stress period remain constant for the entire stress period. In contrast, maximum well capacity parameters that are specified for the entire simulation can be modified by stress period-specific multipliers. The reuse of 

Nonparameter Farm-Well List from the previous stress period is specified by ITMP of current stress period = -1, and if ITMP of 

previous stress period > 0. Input variables, that represent attributes of a farm well, are as follows:

– Layer

– Row

– Column

– Farm Well ID

– Farm ID associated with Farm Well

– Maximum Well Capacity

– [Auxiliary Attributes]

Similarly to parameter farm-wells, an attributes list of nonparameter farm wells can, as well, include attributes of farm wells 

that are simulated by the MNW Package. A “negative” farm-well ID designates that a link to the MNW package is established. 

A “zero” layer number indicates that the well linked to the MNW package is a “multi-layer” well, and that the layers associated 

with the respective screened aquifers are defined in the MNW package input file. A detailed explanation of input variables for 

nonparameter farm wells and how to establish a link of an FMP1 well to a MNW package well can be obtained from the section 

describing the input variables of parameter farm wells. The only difference between a parameter farm-wells list and a nonparameter farm-wells list is that the maximum capacity factor, QMAXfact, is replaced by the maximum capacity, QMAX.

General Data Requirements 55
Farm Irrigation Efficiencies

On-farm efficiency can be specified as a constant or on a farm-by-farm basis either for the entire simulation or for each 

stress period. Variable efficiencies in FMP1 can be chosen to depend on the aquifer head (IEBFL = 2 or 3). The user-specified 

values, OFEspec are either held constant (IEBFL = 1) or employed as initial guess at the beginning of each time step when calculating variable efficiency for each time step (IEBFL = 2 or 3).

Example list of farm irrigation efficiencies:

Farm ID OFEspec

1

2

3

Crop-Type Arrays and Data (Natural Attributes)

An array of Crop-Type IDs only is required for each stress period if a change of the spatial distribution of crops throughout 

time is desired. These changes could represent crop rotation, urbanization, or other changes in agricultural land use. Crop-typerelated data lists specified for each stress period contain attributes, which are constant throughout each stress period.

Crop-Type Identification Array

If changes in crop distribution are specified for each stress period (IROTFL = -1), then the new set of Crop-Type IDs are 

specified for that stress period. Fallowed areas are identified by a Crop-Type-ID of -1. 

56 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000

Layer Row Column Farm Well ID Farm ID QMAXfact

[L3/T]

1 1

2 1

0 5 6 
3 1 1000

4 2

5 2

Q-required for farm-well 3 = 800

Example of a Well List for the Multi-Node Well Package:

Layer Row Column Q-desired

[L3/T]

Other

nonfarmrelated

data

Hlim =

limiting

water level,

or

limiting

drawdown

[L]

Other

nonfarm

related

data

1 5 6 50

2 5 6 50

4 5 6

Q-req. or QMAX passed

on from FMP1 and reapportioned to each layer 50

(The well list for the MNW package is read for each simulation)

Cross-Reference and Link from FMP1 well to MNW well

Example of Farm-Well List for the FMP1:
Crop-Type Data

Crop-type-related data lists specified for each stress period contain attributes that are constant throughout each stress 

period, such as:

(1) Root-zone depths constant throughout each stress period;

(2) Consumptive-use constant throughout each stress period;

(3) Fractions of transpiration and evaporation of consumptive-use constant throughout each stress period;

(4) Fractions of inefficiency losses to surface-water runoff constant throughout each stress period.

Root Depth [L] :

The root depth for each crop is user-specified for each stress period (IRTFL = 2) or calculated as time-step averages (IRTFL = 3) 

from Climate-Data Time Series and a List of Crop-Specific Coefficients. If root depth is specified for each stress period

(IRTFL = 2), then

(1) Root depth may be read optionally as a constant throughout a stress period for all crops.

(2) Each crop may be associated optionally with a spatially lumped Root Depth value constant for each Stress Period 

(S-PER) as follows:

Example for a specific stress period:

Crop ID Root Depth [L] per S-PER

1

2

3

Consumptive-Use Flux [L/T] :

 The consumptive-use flux for each crop is user-specified for each stress period (ICUFL = 2) or calculated as time-step

 averages (ICUFL = 3) from Climate Data Time Series and a List of Crop-Specific Coefficients. Consumptive use is

 defined commonly as crop evapotranspiration, which includes transpiration and evaporation in a cropped agricultural

 area (Colorado’s Decision Support Systems, 1995; Gelt and others, 1999; European Environment Agency, 2004). Each

 crop may be associated with a spatially lumped consumptive use value constant for each Stress Period (S-PER) as 

 follows:

Example for a specific stress period:

Crop ID Consumptive Use [L/T] per S-PER

1

2

3

Fractions of Transpiration and Evaporation of Crop Consumptive Use:

 The fractions of transpiration and evaporation for each crop are user-specified for each stress period (IFTEFL = 2). Each

 crop may be associated with spatially lumped values of a transpiratory (Kt) and evaporative fraction of consumptive use

 (Ke

p

 - related to precipitation, Ke

i

 - related to irrigation), which is constant throughout each stress period (allowing

 changes throughout the growing season between stress periods) as follows:

Example for a specific stress period: 

Crop ID Kt

(0 < Kt ≤1)

Ke

p

(0 ≤ Ke

p ≤ 1)

Ke

i

(0 ≤ Ke

i < 1)

1

2

3

In the FMP1, the evaporation losses from irrigation, Ei, are defined to vary proportionally to Ti. Equality between Ei/Ti and 

Ke

i

/ Kt , therefore, evaporation is assumed to be:

Ei = Ti × (Kei/Kt). 

This is why Kt must not be zero.

•

•

•

General Data Requirements 57
Fractions of Inefficiency Losses to Surface-Water Runoff:

 Fractions of inefficiency losses to surface-water runoff for each crop are user-specified for each stress period 

 (IIESWFL = 2) or, if related to slope, calculated internally as “rise-over-run” (delta-elevation/delta-lateral distance) 

 (IIESWFL = 0). For IIESWFL = 2, each crop may be associated with spatially lumped values of fractions of in-efficient 

 losses to surface-water runoff related to precipitation or irrigation, which is constant throughout each stress period 

 as follows:

Example for a specific stress period: 

Crop ID IEsw

p

(0 ≤ IEsw

p ≤ 1)

IEsw

i

(0 ≤ IEsw

i ≤ 1)

1

2

3

Climate Data

Climate-related data may be specified as constants for each stress period, as opposed to climate data that are read as time 

series throughout the duration of the entire simulation. The only climate variable that may be specified for each stress period is 

precipitation. Although consumptive use depends on climate (among other factors), it is considered a crop-specific parameter 

and, therefore, is listed in the “Crop-Type Arrays and Data” section of this report.

Precipitation Array

Changed precipitation distributions can be user-specified for each stress period (IPFL = 2) as a lumped average value or a 

spatially distributed array of values, if not specified as daily time series for the entire simulation (IPFL = 3), which would allow 

the calculation of time-step averages.

Lumped Average Precipitation Value [L] :

 A spatially lumped precipitation value for entire domain averaged throughout a stress period.

Distributed Average Precipitation Values [L] :

 Precipitation is user-specified as a 2D-array of spatially distributed precipitation averaged throughout a stress period. 

 Depending on whether the temporal or spatial variability of precipitation is greater, the user should decide if daily time

 series are read in (IPFL = 3) while accepting that the data are lumped spatially or if a spatially distributed 2D array is

 read in while averaging the temporal data for each polygon or cell throughout the duration of one stress period 

 (IPFL = 2; with cross-reference to file containing the 2D array). However, minimal impact of precipitation on the 

 overall water budget would be expected in (semi-) arid areas such as the southwestern United States. In this type of 

 climatic setting a spatially lumped precipitation value averaged throughout a stress period usually should be sufficient

 (IPFL = 2; with value read in as constant for entire domain).

Crop-Type Data (Agro-Economic)

Crop benefits are derived from crop-specific water production functions and from the crop’s market price if Acreage-Optimization is chosen as deficiency scenario (IDEFFL > 0). Water production functions and a crop’s market price also can be userspecified for each crop type for each stress period (IBEN = 2).

Crop-Type Benefits Data

Crop benefits can be user-specified for each stress period if IDEFFL > 0 and IBEN = 2. Each crop type may be associated 

with the following parameters constant over each stress period:

Coefficients of crop-specific Water-Production Function (Yield vs. ETc):

 o Slope

 o Intercept

Market-price per crop:

•

•

•

•

•

58 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Crop ID Calculation of Crop Benefit

Water Production Function Crop Market Price

Slope (a) Intercept (b)

YIELD = a × ET + b, where: YIELD in [weight/area], and ET in [length] [value/weight]

1

2

3

Water-Cost Coefficients

Four ground-water cost coefficients and four surface-water cost coefficients are user-specified for each farm for each stress 

period (ICOST = 2) if Acreage-Optimization is desired as a deficiency scenario (if IDEFFL > 0). These cost coefficients are 

user-specified for each farm and may be associated with ground-water and surface-water cost coefficients that remain constant 

over each stress period as follows:

Farm ID Groundwater 

pumping

base costs

Wellpumping

costs

Well-tocell 

lift

costs

Groundwater 

delivery

costs

Fixed price 

of (semi-) 

routed 

surface 

water

Reach to cell 

lift costs of 

(semi-) routed 

surface water

Reach to cell 

delivery costs 

of (semi-) 

routed surface 

water

Fixed price 

of nonrouted 

surface 

wat er

[$/L3] [$/(L3⋅L)] [$/(L3⋅L)] [$/(L3⋅L)] [$/L3] [$/(L3⋅L)] [$/(L3⋅L)] [$/L3]

1

2

3

Surface-Water Data

Surface-water data are required if surface water is allocated as either “nonrouted,” as “semi-routed,” or as “fully routed” 

delivery to a farm.

Nonrouted Surface-Water Deliveries

Nonrouted surface-water deliveries are user-specified for each stress period if surface-water delivery flag INRDFL = 1. 

Importation schemes for surface-water delivery from outside the modeling domain such as water transfers or complex deliveries can be simulated as nonrouted deliveries independent of a river or canal network from the SFR1 package. The scheme for 

simulation of nonrouted deliveries is presented in the section ‘Surface-water Delivery’ (eq. 3).

Although there are no data required for the entire simulation, a list containing rates, ranks, NRDuse-flags of random, 

unranked types of nonrouted surface-water deliveries (t

u

) may be associated with each farm and is read for each stress period:

– Farm ID

– Farm specific Nonrouted Delivery

– Farm specific Rank of Nonrouted Delivery

– Farm specific Binary NRDuse-flag, which (if 0) tells to use only the amount sufficient to meet the farm’s demand, or (if 1) 

tells to use the absolute amount available, and to recharge surplus from a certain delivery type back into the canal at a 

farm’s head gate, or (if 2) tells to use the absolute amount available, and to inject surplus from a certain delivery type 

into the farm wells attributed to a certain farm ID.

General Data Requirements 59
Example of a list of nonrouted deliveries for each farm for a specific stress period.

Farm ID Unranked

Nonrouted Delivery Type 1

Unranked

Nonrouted Delivery Type 2

Unranked

NRD Type tu

Nonrouted

Delivery 

[L3]

Priority

Rank of

 NRD 

NRDuse-Flag of 

‘sufficient’ or 

‘absolute’

use of NRD

Nonrouted

Delivery 

[L3]

Priority

Rank of

NRD

NRDuse-Flag of 

‘sufficient’ or 

‘absolute’

use of NRD

...

1

2

3

The following two examples show for one specific stress period and one specific farm, how particular settings of the 

NRDuse-flags for four water transfer types t (NRDuse

t = 1,2,3,4) can influence, what the total nonrouted delivery the example farm 

amounts to, whether only the sufficient or the absolute amount of a nonrouted delivery in excess of the TFDR is used, and 

whether excess nonrouted delivery is recharged back into the canal or injected into farm-wells.

Example 1–Potential Oversupply by Non-Routed Deliveries (4 different scenarios):

Input data set for four scenarios of NRD use-flag settings for example farm 1 and for a specific stress period 

(here: Rank No. = Type No.)

Farm 

ID

NRD Type 1 NRD Type 2 NRD Type 3 NRD Type 4

Volume Rank Use-flag Volume Rank Use-flag Volume Rank Use-flag Volume Rank Use-flag

Scenario 1:

1 5 1 0 or 1 or 2 3 2 0 or 1 or 2 3 3 0 4 4 0

Scenario 2:

1 5 1 0 or 1 or 2 3 2 0 or 1 or 2 3 3 1 or 2 4 4 0

Scenario 3:

1 5 1 0 or 1 or 2 3 2 0 or 1 or 2 3 3 0 4 4 1 or 2

Scenario 4:

1 5 1 0 or 1 or 2 3 2 0 or 1 or 2 3 3 1 or 2 4 4 1 or 2 Scenario

TFDR = 10 units NRDpot

1 NRDpot2 NRDpot3 NRDpot4 Results

5 3 3 4

NRDuse

1 NRDuse2 NRDuse3 NRDuse4 NRDact1 NRDact2 NRDact3 NRDact4 Insufficiency (I) 

Sufficiency (S)

Oversupply (O)

1 0 or 1 or 2 0 or 1 or 2 0 0 5 3 2 0 10 units used

= TFDR (S)

Sufficiency

2a

2b

0 or 1 or 2

0 or 1 or 2

0 or 1 or 2

0 or 1 or 2

1

2

0

0

5 3 3 0 11 units used

> TFDR (O)

1 to canal

1 to wells

3a

3b

0 or 1 or 2

0 or 1 or 2

0 or 1 or 2

0 or 1 or 2

0

0

1

2

5 3 2 4 14 units used

> TFDR (O)

4 to canal

4 to wells

4a

4b

4c

4d

0 or 1 or 2

0 or 1 or 2

0 or 1 or 2

0 or 1 or 2

0 or 1 or 2

0 or 1 or 2

0 or 1 or 2

0 or 1 or 2

1

2

1

2

1

1

2

2

5 3 3 4 15 units used

> TFDR (O)

5 to canal

1 to well, 4 to canal

1 to canal, 4 to well

5 to wells

∑=

4

t 1

t NRDact

60 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Example 2 – Insufficiency of Nonrouted Deliveries:

Input data set for any scenarios of NRD use-flag settings for example farm 1 and for a specific stress period

Farm 

ID

NRD type 1 NRD type 2 NRD type 3 NRD type 4

Volume Rank UseflagVolume Rank UseflagVolume Rank UseflagVolume Rank Useflag

1 3 Any Any 1 Any Any 3 Any Any 2 Any Any Scenario

TFDR = 10 units NRDpot

1 NRDpot2 NRDpot3 NRDpot4 Results

3 1 3 2

NRDuse

1 NRDuse2 NRDuse3 NRDuse4 NRDact1 NRDact2 NRDact3 NRDact4

∑=

4

t 1

t NRDact

Insufficiency (I) 

Sufficiency (S)

Oversupply (O)

All For all NRDuse-flags settings 3 1 3 2 9 units used

< TFDR (I)

Insufficiency case

If supply through nonrouted deliveries is found to be insufficient, as demonstrated in Example 2, then the FMP1 checks on 

whether the remaining demand can be supplemented by (semi-) routed deliveries, or by farm well pumping.

Routed Surface-Water Deliveries

The streamflow routing is facilitated by a link of the FMP1 to the SFR1 package for routing surface water through a conveyance network either to a specified, remote point of diversion (if “semi-routed” is selected), or directly to a head gate adjacent 

to a farm (in “fully routed” is selected).

‘Semi-Routed’ Delivery

If semi-routed deliveries are user specified for each stress period, the surface-water delivery flag ISRDFL = 2. Routing 

surface-water along a river or major canal, and diverting nonrouted deliveries from a point of diversion along such a river or 

major canal is defined in the FMP1 as ‘semi-routed’ surface-water delivery. In this case, the SFR1 package is used only to rout 

streamflow along a river or major canal. Aside from the attributes list for stream segments, a list of farms-related data has to be 

specified for each stress period containing the respective coordinates (row, column) from which location along a river or major 

canal the delivery is diverted: 

- Farm ID

- Row

- Column

- Segment number

- Reach number

 

Farm ID Row Column Segment number Reach number

1

2

3

The user may optionally specify the diversion point by (1) a full set of information consisting of model cell coordinates, stream 

segment number, and reach number (row, column, segment, reach), or (2) by just the model cell coordinates and a stream segment number (row, column, segment), or (3) by just the model cell coordinates (row, column), or alternatively (4) by the number 

of a stream segment and the number of a reach, or (5) simply by the reach number, which in any case is uniquely associated 

with a segment number. Option (3) does not require any data information from the SFR1 package but is only possible if a unique 

identification of a reach is not necessary. Such a unique identification is important if more than several stream segments pass 

through one model cell. Farms that are adjacent to a canal and therefore can divert “routed” deliveries from a head-gate cannot 

receive “semi-routed” deliveries at the same time. If coordinates of a point of diversion mistakenly are entered for a semi-routed 

delivery, then the program exits and prints an error message that asks the user to set the coordinates for that farm to zero.

General Data Requirements 61
‘Fully-Routed’ Deliveries 

Fully-routed deliveries represent surface-water deliveries routed through a conveyance network to a farm. If fully routed 

streamflow deliveries are user-specified for each stress period, the ‘routed-delivery flag,’ IRDFL, must be equal to 1. Applying 

the SFR1 package jointly with the FMP1 facilitates the routing of streamflow by way of a ‘river to canal’ conveyance network 

directly to a farm’s head gate reach. The data requirements can be obtained below.

Stream-Segment Data

A list that specifies stream segment data is required for each stress period (as defined by the SFR1 package input requirements), if the semi-routed delivery flag ISRDFL = 1 or 2 or if the fully routed delivery flag IRDFL = 1. The user should refer 

to the input instructions for the SFR1 package (Prudic and others, 2004) if the SFR1 package and the FMP1 are used together. 

Attributes of stream segments are defined for each stress period. They are described below as input variables of the stream 

segments list. The parameters attributed to stream segments in the following list are a suggestion as to which parameters are 

required at minimum if the SFR1 package is used jointly with the FMP1. 

Parameters for the entire segment:

 − Segment Number (ID)

 − ICALC: option for stream stage calculation (see below)

 − Downstream tributary segment number

 − Upstream segment number from which diversion occurs (no record if segment is not a diversion segment)

 − IPRIOR: type of diversion (see below)

 − Inflow rate into segment (for example, first reach of headwaters or diversion segments)

 − Specified losses and gains are optional10: overland runoff, stream evaporation, stream precipitation

 − Streambed Roughness (Manning’s n; if Manning’s formula is chosen as an option for computing stream stage)

Parameters for the upstream and downstream end of the segment:

 − Vertical Hydraulic Conductivity of Streambed

 − Thickness of Streambed

 − Elevation of Top of Streambed

 − Stream Width (if assuming rectangular channel)

The description of input requirements for the SFR1 in conjunction with the FMP1 are limited here to suggestions for the following two: SFR1 options for stream-stage calculation (ICALC) and for diverting water out of a stream for irrigation purposes 

(IPRIOR). However, the user should be advised that the SFR1 offers numerous other options, which are described in the SFR1 

user guide (Prudic and others, 2004).

Suggested option for stream-stage calculation:

 Manning’s formula using a rectangular channel (flag in SFR1: ICALC = 1)

Suggested option for diversions:

 Fixed water right type diversion, meaning diversion is reduced to available streamflow, if specified diversion is 

 greater than streamflow (Hanson and others, 2003) (flag in SFR1: IPRIOR = 0). 

For most irrigation networks, the upstream and downstream parameters for the vertical hydraulic conductivity and the 

thickness of the streambed are specified, as well as for the stream width which may be assumed to remain equal or unequal. 

The stream-segment parameter, which typically takes different values at the upstream and downstream end of the segment, 

is the elevation of the top of the streambed. The elevation of the top of the streambed at the upstream and downstream end of a 

segment is used to calculate the elevation of the midpoint of a stream reach in two different ways, depending on the settings of 

IRDFLG flag in the SFR1 data input file (Prudic and others, 2004).

10When using the SFR1 together with the FMP1 for a conjunctive surface-water/ground-water model in (semi-)arid areas, those fluxes typically have a negligible impact on the overall ground-water budget if related to canal segment.

•

•

•

•

62 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
If IRDFLG = 0: The elevation of the top of the streambed of all segments is interpolated between the elevation of the 

 upstream and downstream ends of the segments, as specified in SFR1 input file.

If IRDFLG = 1: The elevation of the top of the streambed of all segments that are not diversion segments is interpolated

 between the elevation of the upstream and downstream ends of the segments, as specified in SFR 

 input file.

 The elevation of the top of the streambed of diversion segments (canals/laterals) follows the slope of 

 ground surface at a depth defined by the interpolation of:

 (1) the difference between the ground surface elevation and the elevation of the upstream end of a 

 diversion segment, as specified in the SFR input file; and

 (2) the difference between the ground surface elevation and the elevation of the downstream end 

 of a diversion segment, as specified in the SFR input file.

 Note limitation: IRDFLG = 1 cannot be chosen if the number of the diversion segment is equal to the 

 total number of segments.

 Note that the IRDFLG flag in SFR1 also serves as a print flag, which tells to print input data for a stress

 period when IRDFLG = 0, and not to print input data for a stress period when IRDFLG > 0 

 (Prudic and others, 2004).

Water-Rights Data

Surface-water allotments may be introduced into a model as a lumped equal appropriation allotment height for any stress 

period in units of [L] for an entire irrigation district (IALLOT = 1) or as water rights calls per stress period in units of [L3/T] for 

a prior appropriation system of ranked individual farms or irrigation regions (IALLOT > 1). The simulation of surface-water 

deliveries constrained by equal appropriation allotments heights requires the specification of a routing network in the SFR1 input 

file. However, when simulating surface-water deliveries regulated by a prior appropriation system, then diversions from a river 

into canals serving the farms will be simulated by the FMP1.

Equal Appropriation

Water rights are set to equal appropriation by specifying IALLOT = 1. The simulation of the actual delivery to the farm in 

general (eq. 4), and for equal appropriation water rights (eq. 7C) is presented earlier in this report.

The actual delivery to a farm in general (eq. 4) is derived in the ‘Surface-Water Delivery’ section:

DEL m act in TFDR TNRD DEL Q t,k

f

t,k

f

t,k

pot

t,k

constr

t

f f f = ( − ,	 ,	 )

 

The actual delivery to a farm for equal appropriation water rights (eq. 7C) is derived in the “Water Rights Allocations” 

section:

DEL m act in TFDR TNRD Q Q t,k

f

t,k

f

t,k

in

t,k

allot

t

f r,f f = ( − ,	 ,	 ) 

For equally appropriated farms,

o the potential delivery to a farm’s head gate, , is equal to the inflow into the head gate reach, :

DEL Q pot

t,k

in

t,k

f r,f = , and

o the water rights system specific delivery constraint, t

f Qconstr , is equal to the a farm allotment rate, Qallot

f

: 

Q q constr A Q t

allot

t

f allot

t

f f = ⋅ 	 	 = .

The farm allotment rate, Qallotf , is the product of an equal appropriation allotment flux, qt

allot [L/T], and the respective farm 

area, Af.

Equal Appropriation Allotment Height [L]

The only input parameter required for equal appropriation is a spatially lumped value of an allotment height [L] for the 

entire domain and for a stress period. The FMP1 converts the allotment height internally into an allotment flux, qt

allot [L/T] by 

dividing the height by the duration of the respective stress period.

•

General Data Requirements 63
Prior Appropriation

Water rights are set to prior appropriation by specifying IALLOT > 1. The simulation of the actual delivery to the farm in 

general (eq. 4), and for a prior appropriation water rights system (eq. 8C) is presented earlier in this report:

The actual delivery to a farm in general (eq. 4) is derived in the “Surface-Water Delivery” section:

 DEL m act in TFDR TNRD DEL Q t,k

f

t,k

f

t,k

pot

t,k

constr

t

f f f = ( − ,	 ,	 )

The actual delivery to a farm for prior appropriation water rights (eq. 8C) is derived in the “Water-Rights Allotments” section:

DEL m act in TFDR TNRD Q Q t,k

f

t,k

f

t,k

in

t,k

C-min

t,k

f r,f r,f = ( − ,	 	 − ,	 ) Qcall

t

f

For a prior appropriation water rights system,

o the potential delivery to a farm’s head gate, , is equal to the inflow into the head gate reach, 

 minus a minimum canal streamflow, : 

 

DEL Q pot

t,k

in

t,k

f r,f = , and

o the water rights system specific delivery constraint, t

f Qconstr , is equal to user-specified Water Rights Calls:

 Q Q constr

t

call

t

f f = .

Prior Appropriation with Water Rights Calls:

 If the user specifies IALLOT = 2, then a farm-related list of Water Rights Calls [L3/T] is required as data input for 

 each stress period:

Farm ID Call [L3/T] per S-PER

1

2

3

Prior Appropriation without Water Rights Calls:

 If the user specifies IALLOT = 3, then the prior appropriation system is implemented only based on a water 

 rights ranking of all farms represented by the 2D array of farm IDs, where a lower farm ID indicates a higher water 

 rights rank. There is not data input required for this option.

Data Input Instructions

Data input for the FMP1 is read from the file designated as type “FMP” in the name file. The chapter ‘data input instructions’ contains three sections. The first section describes the data input requirements for each input item. An input item can 

consist of a comment, of flags, or of scalar-, list- or array-variables. Optional variables and optional flags are shown in brackets, 

[ ], and curly braces, { }, respectively. Two-dimensional arrays are listed together with their array dimensions (NCOL, NROW). 

Data lists or arrays, which are read by MF2K or FMP1 utility modules are indicated by “read* ” and by a footnote that explains, 

which utility array readers are used, respectively. The second section explains the input structure of the array and list reading 

utility modules, and instructs how to apply scale factor multipliers to the variables. The third section provides an explanation of 

the fields itemized in the input instructions in the first section.

•

•

64 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Input Data for the FMP1

Data for each Simulation

Item No. Input instruction for each item

0 [#Text] read if ‘#’ is specified (can be repeated multiple times)

1 [PARAMETER NPFWL MXL] read if word ‘PARAMETER’ is specified

2 MXACTW NFARMS NCROPS NSOILS IRTFL ICUFL IPFL IFTEFL IIESWFL IEFFL IEBFL IROTFL IDEFFL {IBEN} 

{ICOST} ICCFL INRDFL {MXNRDT}, ISRDFL IRDFL IALLOT {PCLOSE} IFWLCB IFNRCB ISDPFL {IOPFL} 

{IPAPFL} {Option} read

3 [PARNAM PARTYP PARVAL NLST] read if NPFWL > 0 Repeat items 3 + 4 NPIWL times

4 [Layer Row Column Farm-Well-ID Farm-ID QMAXfact] [xyz] Repeat items 3 + 4 NPIWL times

 read* NLST times with [3] if NPFWL > 0

5 GSURF(NCOL,NROW) read* with [2]

6 FID(NCOL,NROW) read* with [1]

7 [Farm-ID OFE] read* NFARMS times with [5] ] if IEFFL = 1

8 SID(NCOL,NROW) read* with [1]

9 Soil-ID CapFringe [A-Coeff B-Coeff C-Coeff D-Coeff E-Coeff, or 

Soil-ID CapFringe [Soil-Type] (parameters in brackets only if ICCFL = 1) read* NSOILS times with [6]

10 [CID(NCOL,NROW)] read* with [1] if IROTFL >= 0

11 [Crop-ID ROOT] read* NCROPS times with [4] if IRTFL = 1

12 [Crop-ID FTR FEP FEI] read* NCROPS times with [5] if IFTEFL = 1

13 [Crop-ID FIESWP FIESWI] read* NCROPS times with [5] if IIESWFL = 1

14 [Crop-ID PSI(1) PSI(2) PSI(3) PSI(4)] read* NCROPS times with [5] if ICCFL = 1

15 [Crop-ID BaseT MinCutT MaxCutT C0 C1 C2 C3 BegRootD MaxRootD RootGC]

 read* NCROPS times with [5] if IRTFL = 3, or ICUFL = 3, or IPFL = 3

16 [TimeSeriesStep MaxT MinT Precip ETref]

read* LENSIM times with [5] if IRTFL = 3, or ICUFL = 3, or IPFL = 3

(LENSIM = length of simulation expressed as total number of time-series steps; length of time-series step defined by ITMUNI 

in the Discretization File)

17 [Crop-ID IFALLOW] read* NCROPS times with [7] if IDEFFL = -2

18 [Crop-ID WPF-Slope WPF-Int Crop-Price] read* NCROPS times with [5] if IDEFFL > 0 and if IBEN = 1

19 Farm-ID GWcost1 GWcost2 GWcost3 GWcost4 SWcost1 SWcost2 SWcost3 SWcost4] read* NFARMS times with [5] if 

IDEFFL > 0 and ICOST = 1

20 [Farm-ID Row Column Segment Reach] read* NFARMS times with [7] if ISRDFL = 1

Data Input Instructions 65
Data for each Stress Period

Item

No.

Input instruction for each item

21 ITMP NP read

22 [Layer Row Column Farm-Well-ID Farm-ID QMAX] [xyz] read* ITMP times with [3] if ITMP > 0

23 [Pname] read NP times if NP > 0

24 [Farm-ID OFE] if IEFFL = read* NFARMS times with [5] if IEFFL = 2

25 [CID(NCOL,NROW)] read* with [1] if IROTFL = -1

26 [Crop-ID ROOT] read* NCROPS times with [4] if IRTFL = 2

27 [Crop-ID CU] read* NCROPS times with [4] if ICUFL = 2

28 [Crop-ID FTR FEP FEI] read* NCROPS times with [5] if IFTEFL = 2

29 [Crop-ID FIESWP FIESWI] read* NCROPS times with [5] if IIESWFL = 2

30 [PFLX(NROW,NCOL)] read* with [2] if IPFL = 2

31 [Crop-ID WPF-Slope WPF-Int Crop-Price]

read* NCROPS times with [5] if IDEFFL > 0 and if IBEN = 2.

32 [Farm-ID GWcost1 GWcost2 GWcost3 GWcost4 SWcost1 SWcost2 SWcost3 SWcost4] read* NFARMS times with [5] if 

IDEFFL > 0 and ICOST = 2.

33 [Farm-ID (NRDV NRDR NRDU)Type1, ( )Type2, ... , ( ) TypeMXNRDT] read* NFARMS times with [5] if INRDFL = 1. A 

maximum number of MXNRDT types of nonrouted deliveries is read for each farm. One set of variables NRDV, NRDR, and 

NRDU is read for a certain unranked type t

u

 of a nonrouted delivery by ( )Type tu .

34 [Farm-ID Row Column Segment Reach] read* NFARMS times with [7] if ISRDFL = 2

35 [ALLOT] read if IALLOT = 1

36 [Farm-ID CALL] read* NFARMS times with [5] if IALLOT = 2

Explanation of the use of Array-Reading Utility Modules 

* In order to keep the structure of the FMP-data-input-file simple, it is recommended to specify for each respective line of the FMP-inputfile, from which a utility module reads, one of the following:

	Name of a file or cross-reference to a file, from which the utility module will read the data array or list records (see use of the 

keywords “OPEN/CLOSE” and “EXTERNAL” below),

	Constant(s), in case 2D-arrays or lists may be lumped together.

Utility-Module FREE-FORMAT CONTROL RECORD options

CONSTANT INTERNAL EXTERNAL OPEN/CLOSE

[1] U2DINT ⊗ x x ⊗

[2] U2DREL ⊗ x x ⊗

[3] FMP1WELRD x x ⊗

[4] FMP1LSTRD ⊗ x x ⊗

[5] FMP1DPLSTRD ⊗ x x ⊗

[6] FMP1DPWDLSTRD ⊗ x x ⊗

[7] FMP1INTLSTRD ⊗ x x ⊗

⊗ Constants or file-names are recommended in order to maintain a line-by-line FMP1 input file structure for each input item.

x Internal arrays or unit numbers for external files are technically possible, but the user has to define such unit numbers in the 

Name File. However, if data are desired to be read from the same file for multiple stress periods, then cross-referenced 

“external” files are of advantage, since they remain open.

66 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Input Structure of Array and List Reading Utility Modules

A control record item “a” is read from the FMP1 input file by all utility modules. A keyword signals whether to use a 

lumped constant value for 2D-arrays or data lists, or whether to read 2D-data arrays and data lists internally from the FMP1 

input file or externally from a data file. For 2D-data arrays read by standard MF2K utility modules, a “Multiplier Constant” can 

be applied to scale any input data array.

For data lists read by FMP-embedded list reading utility modules, a second control record item “b” is optionally read if the 

use of scale factor multipliers is desired. If item b is included, the respective line must begin with “SFAC.” For internal data lists, 

this control record item b is read from the next line of the FMP1 input file. For external lists, item b is read from the first line of 

the external data file.

Control-Record Item a

Module Keyword Constant(s) or

cross-reference

Multiplier

constant

Read

format

Print

flag

For the use of Standard MODFLOW 2D-array reading Utility Modules:

[1] CONSTANT Integer Scalar

INTERNAL 1* (FREE) ** –1***

OPEN/CLOSE FILENAME 1* (FREE) ** –1***

EXTERNAL Nunit 1* (FREE) ** –1***

[2] CONSTANT Real Scalar

INTERNAL Real Scalar (FREE) ** –1***

OPEN/CLOSE FILENAME Real Scalar (FREE) ** –1***

EXTERNAL Nunit Real Scalar (FREE) ** –1***

For the use of list reading Utility Modules embedded in the FMP1:

[3],[4],[5],[6], [7] CONSTANT Real [3],[4] or 

Double Precision [5],[6], 

or Integer [7] Scalar(s)

INTERNAL

OPEN/CLOSE FILENAME

EXTERNAL Nunit

* It is not recommended to “scale” 2D integer arrays of identifiers (such as farm-ID, crop-ID, or soil-ID). 

** Since the FMP1 allows the use of free format, the user is advised to read 2D data arrays by the standard MODFLOW 

 utilitymodules as well in free format.

*** It is not recommended to reprint known input data in order to avoid a very large listing file, where results are to be 

 printed. 

Keywords:

The keyword “CONSTANT” indicates that the scalar, which follows the keyword, represents a lumped value for 2Darrays or for data lists with only one attribute. For data lists with multiple attributes, as many constants must be entered after the 

keyword “CONSTANT,” as fields are attributed to the multi-dimensional variable, while omitting the identifier attribute in the 

first field. Distributed data may be read as 2D arrays or as data lists either internally in the FMP1 input file, as indicated by the 

keyword “INTERNAL,” or externally from a file.

External data can be read by using a keyword of “OPEN/CLOSE” and thereafter specifying a filename directly in the FMP1 

input file. The obvious advantage of using “OPEN/CLOSE” is that no further referencing of the file name in the Name File is 

necessary. However, each file will be closed after reading and no further use of that file for future stress periods is possible.

Alternatively, data can be read by using a keyword of “EXTERNAL” and specifying a file unit number, Nunit, in the FMP1 

input file that cross-references to a file name contained in the name file and the key term “DATA.” The advantage of using 

“EXTERNAL” is that the file, from which a respective module reads, will not be closed and data for future stress periods can 

continuously be read from the same file.

Data Input Instructions 67
Read Format:

The read format for the Standard MODFLOW 2D-array reading utility modules, [1] and [2], must either be a standard 

Fortran format that is enclosed in parenthesis, or “(FREE)” which indicates free format, or “(BINARY)” which indicates binary 

(unformatted) data. A suggested print flag of –1 indicates that an array should not be printed to the listing file after it has been 

read. For further instructions on use of array readers, print flags and associated codes, refer to Harbaugh and others (2000, p. 86) 

and Schmid (2004, p. 159).

The read format for the list reading utility modules embedded in the FMP1, [3],[4],[5], [6], and [7] is by standard in free 

format and therefore not required to be specified. The farm-wells list reading utility module [3] prints the read variables including auxiliary variables to the listing file in integer and scientific notation unless “NOPRINT” is not specified for {option} in 

item 2. The other, less complex, list reading modules, [4], [5], [6], and [7] do not re-print the read input data to the listing file.

Control-Record Item b

If item “b” is included, it must begin with the keyword “SFAC.” The keyword “SFAC” indicates whether a scale factor is to 

be multiplied with parameter values of a designated attribute or a range of attributes. Alternatively, a list of scale factors can be 

read from yet another external data file. If the control-record item “b” is not included, the Scale is 1.0.

Module Keyword 1 Constant or keyword 2 Cross-reference

For the use of list reading Utility Modules embedded in the FMP1:

[3],[4],[5],[6] SFAC Real ([3],[4]) or Double Precision ([5],[6]) Scalar(s)

[5] SFAC OPEN/CLOSE FILENAME

SFAC EXTERNAL Nunit

Constant Scale Factor:

A scale factor can be applied to all lists read by the utility modules embedded in the FMP1, [3], [4], [5], and [6]. For each 

item, a constant real or double precision scalar may be multiplied by the parameter value(s) associated with the following 

respective attribute or range of attributes:

Item SFAC applies to parameter(s) Read by module

4. QMAXfact [3]

7. OFE [5]

9. CapFringe [6]

11. ROOT [4]

12. FTR,FEP,FEI [5]

13. FIESWP, FIESWI [5]

14. PSI(1), PSI(2), PSI(3), PSI(4) [5]

19. GWcost1, GWcost2, GWcost3, GWcost4, 

SWcost1, SWcost2, SWcost3, SWcost4

[5]

22. QMAX [3]

24. OFE [5]

26. ROOT [4]

27. CU [4]

28. FTR, FEP, FEI [5]

29. FIESWP, FIESWI [5]

32. GWcost1, GWcost2, GWcost3, GWcost4, 

SWcost1, SWcost2, SWcost3, SWcost4

[5]

36. CALL [5]

For items 4 and 22, the values of the list variables that are automatically printed to the listing file include the effect of the 

Scale.

68 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
List of Scale Factors:

A list of scale factors can be applied to parameters of a data list that requires different multipliers for each parameter. This 

option is available only for lists read by utility module [5]. As before, item b must begin with the first keyword “SFAC.” A second control record keyword indicates whether the file containing the list of scale factors is specified directly by its file name, or 

by a file unit number, that cross-references to a file name contained in the Name File.

The first column in a list of scale factors contains the attribute or field number of a data list. The second column contains 

the individual scale factor for each respective attribute. For example, multiple scale factors for the three different attributes 

(1: WPF-Slope, 2: WPF-Int, 3: Crop-Price) in item 18 could be defined as follows:

Attribute Scale factor

1 1.0

2 2.0

3 1.0

4 10.0

The first attribute always defines an ID, which is why the scale factor always must be 1.0. Parameters related to any other 

attribute that is not to be scaled, must also be equipped with a scale factor of one. In the example, the slope of the water-production function was multiplied by 2.0, and the crop market price per unit weight was multiplied by 10. 

Explanation of Fields Used in the Input Instructions

Dimensions and Flags (item 2)

Parameter Dimensions (item 2)

NPFWL Number of farm well parameters (changeable parameter is a multiplier of the maximum capacity)

MXL Maximum number of parameter farm wells. 

MXACTFW Maximum number of active farm wells including parameter and nonparameter farm wells. Nonparameter farm 

wells are wells, whose maximum capacity is different for each stress period. In this case, each well-list (layer, 

location, farm-well farm ID, max. capacity) would have to be read for each stress period. However, since the 

maximum capacity in most cases is thought to be constant for the entire simulation, usually the maximum 

number of nonparameter farm-wells will be zero, that is, MXL = MXACTFW.

NFARMS Number of farms

NCROPS Number of crop types

NSOILS Number of soil types

‘When-to-Read-Flags’ (item 2):

When-to-Read-Flags indicate, when to read or calculate a variable:

1 = specified for the entire simulation

2 = specified for each stress period

3 = calculated as average for each time step from time series

IRTFL Root depth flag (1,2,3 possible)

ICUFL Consumptive use flag (2,3 possible)

IPFL Precipitation flag (2,3 possible)

IFTEFL Fraction-of-transpiration-and-evaporation-of-crop-consumptive-use flag (1,2 possible)

Data Input Instructions 69
IIESWFL Fraction-of-inefficiency-losses-to-SW-runoff flag (0,1,2 possible)

 (0 = The fraction of inefficiency losses to surface-water runoff is proportional to the slope of ground surface. 

 The slope is estimated by the FMP1 by a third order finite difference method using all eight outer points of

 the 3 × 3 kernel surrounding the cell. The slope is not calculated at cells directly adjacent to the boundary of

 the grid domain. Thus, farm boundaries must not reach the model boundary if IIESWFL is zero. There is no

 data input required for FIESWP and FIESWI if IIESWFL is zero.)

IEFFL Efficiency Flag (1, 2 possible)

Water Policy Flags (item 2):

IEBFL Efficiency Behavior Flag

1 = Conservative Behavior – Constant Efficiency over Time Step

2 = Conservative Behavior – Constant Delivery over Time Step with evaluation of initial total delivery 

 requirement (TDR) per cell at first iteration of first time step of each stress period.

3 = Conservative Behavior – Constant Delivery over Time Step with evaluation of initial total delivery 

 requirement (TDR) per cell at first iteration of each time step.

IROTFL Crop rotation flag:

< 0 Crop Type changes temporally and spatially at every stress period (CID 2D array is read for each 

 stress period)

= 0 No crop rotation (CID 2D array is read for the entire simulation)

> 0 No crop rotation (CID 2D array is read for the entire simulation), and

 IROTFL = Stress period that is equal to Non-Irrigation Season

IDEFFL Deficiency Scenario flag:

-2 = Water Stacking

-1 = Deficit Irrigation

 0 = “Zero Scenario” where no policy is applied and if demand exceeds supply, it is assumed to be supplied 

 by other imported sources

 1 = Acreage-Optimization

 2 = Acreage-Optimization with Water Conservation Pool

(only if SFR1 is specified in Name File, if a diversion from a river segment into a canal segment is 

specified (IALLOT = 1), and if routed or semi-routed deliveries from such a canal into farms occur 

(IRDFL = 0; ISRDFL = 1).

IBEN Crop-Benefits Flag (only to specify if IDEFFL > 0):

1 = crop benefits list read for the entire simulation

2 = crop benefits list read for each stress period

ICOST Water-Cost Coefficients Flag (only to specify if IDEFFL > 0):

0 = lumped water cost coefficients for the entire simulation

1 = water cost coefficients for each farm for the entire simulation

2 = water cost coefficients for each farm for each stress period

Crop Consumptive-Use Flag (item 2):

ICCFL Concept used for the approximation of ET-fluxes with changing head:

 1 − for consumptive use Concept 1 = plant-and soil-specific pseudo steady state transpiration approximated 

 by analytical solution:

 A restriction of active root zone corresponding to anoxia- or wilting-related pressure heads is 

 determined by the FMP1 by using analytical solutions of a vertical pseudo steady state pressure 

 head distribution over the depth of the total root zone.

 2 − for consumptive use Concept 2 = nonplant- and nonsoil-specific simplification of Concept 1

70 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Surface-Water Flags (item 2):

INRDFL Nonrouted Surface-Water Delivery Flag:

 0 = no Nonrouted Surface-Water Delivery exists.

 1 = Nonrouted Surface-Water Deliveries exist. A farm related list of Volumes, Ranks, and Use-Flags of Nonrouted 

Surface-Water Delivery will be read.

MXNRDT Maximum number of nonrouted delivery types (read if INRDFL = 1).

ISRDFL Semi-Routed Surface-Water Delivery Flag:

 0 = no Semi-Routed Surface-Water Delivery exists

 1 or 2 = Semi-Routed Surface-Water Deliveries exist. (Routing surface-water along a river or major canal, and 

allocating nonrouted deliveries from a point of diversion). A farm related list of Row- and Columncoordinates for a point of diversion will be read (only if SFR1 is specified in Name File).

 1 = List of Row- and Column-coordinates is read for the entire simulation.

 2 = List of Row- and Column-coordinates is read for each stress period.

IRDFL Routed Surface-Water Delivery Flag:

0 = no surface-water delivery exists.

1 = routed surface-water delivery using SFR1 exist. Streamflow routed through a conveyance network to a 

farm (only if SFR1 is specified in Name File). 

IRDFLG A flag of the SFR1, which, if positive, is used to define the method of calculation for the elevation of the

 midpoint of a diversion segment reach. The choice between IRDFLG = 0 and IRDFLG = 1 is an addendum to

 the SFR1 code and, therefore, is only described here and not in the SFR1 input instructions (Prudic and

 others, 2004, p.49). The user is referred to the SFR1 input instructions regarding the location of the IRDFLG

 flag, which is part of the SFR1 data input block that is read for each stress period.

0 = Elevation of top of streambed of diversion segments (canals/laterals) is interpolated between elevation 

 of upstream and downstream ends of segments, as specified in SFR input file (SFR1 input data for a stress

 period are printed to the list file).

1 = Streamflow Routed through a Conveyance Network to a Farm (only if SFR is specified in Name File).

 Elevation of top of streambed of all segments that are not diversion segments is interpolated between 

 the elevation of the upstream and downstream ends of the segments, as specified in SFR input file. 

 Elevation of top of streambed of diversion segments (canals/laterals) follows the slope of ground 

 surface at a depth defined by the interpolation of:

(1) the difference between the ground surface elevation and the elevation of the upstream end 

of a diversion segment, as specified in the SFR input file; and

(2) the difference between the ground surface elevation and the elevation of the downstream end 

of a diversion segment, as specified in the SFR input file.

Note limitation: IRDFLG = 1 cannot be chosen if the number of the diversion segment is equal to the 

 total number of segments (SFR1 input data for a stress period are not printed to a list file).

IALLOT Surface-water allotment flag

 0–No surface-water allotment specified,

 1–Equally appropriated surface-water allotment height [L] specified per stress period (specification of 

 diversions from a river into canals in SFR1 input file required if ISRDFL = 1 or 2, or IRDFL = 1).

 2–Prior appropriation system with Water Rights Calls [L3/T] (diversion rates from a river into canals are 

 simulated 

 if ISRDFL = 1 or 2, or IRDFL = 1; specification of a farm-specific water rights calls list required 

 for each stress period).

 3–Prior appropriation system without Water Rights Calls [L3/T] (diversion rates from a river into canals are

 simulated

 if ISRDFL = 1 or 2, or IRDFL = 1).

PCLOSE User specified closure criterion for simulated canal diversions if prior appropriation is chosen [L3/T]

 (only to specify if IALLOT > 1) 

Data Input Instructions 71
Mandatory Print Flags (item 2):

IFWLCB Farm well budget print flags

 < 0 A list (farm-well ID, farm ID, layer, row, column, farm-well flow rate) is printed to list file for time 

steps, for which in Output Control “Save Budget” is specified (using words) or ICBCFL is not zero 

(using numeric codes)

 = 0 farm-well flow rates not written

 = 1 A list (farm-well ID, farm ID, layer, row, column, farm-well flow rate) is saved on ASCII file 

“FWELLS.OUT” for all time steps

 > 1 if “Compact Budget” is not specified in Output Control:

 A cell-by-cell 2D-array of farm-well flow rates will be saved as binary file on a unit number specified in the Name File for time steps, for which in Output Control “Save Budget” is specified (using 

words) or ICBCFL is not zero (using numeric codes).

 if “Compact Budget” is specified in Output Control:

 A list (node, farm-well flow rate) will be saved as binary file on a unit number specified in the 

Name File for time steps, for which in Output Control “Save Budget” is specified (using words) or 

ICBCFL is not zero (using numeric codes).

IFNRCB Farm net recharge budget print flags

 < 0 A cell-by-cell 2D-array of farm net recharge flow rates is printed to list file for time steps, for which in 

Output Control “Save Budget” is specified (using words) or ICBCFL is not zero (using numeric codes)

 = 0 farm net reacharge flow rates not written

 = 1 A cell-by-cell 2D-array of farm net recharge flow rates is saved on ASCII file “FNRCH_ARRAY.OUT” 

for all time steps

 = 2 A list (stress period, time step, total time, farm ID, cumulative farm net recharge flow rates) will be 

saved as ASCII file “FNRCH_LIST.OUT” 

 = 3 A list (stress period, time step, total time, farm ID, cumulative farm net recharge flow rates) will be 

saved as binary file “FNRCH_LIST_BIN.OUT” for all time steps

 > 3 if “Compact Budget” is not specified in Output Control:

 A list (farm ID, cumulative farm net recharge flow rates) will be saved as binary file on a unit 

number specified in the Name File for time steps, for which in Output Control “Save Budget” is 

specified (using words) or ICBCFL is not zero (using numeric codes).

 if “Compact Budget” is specified in Output Control:

 if number of model layers = 1:

 A cell-by-cell 2D-array of farm net recharge flow rates will be saved as binary file on a unit 

 number specified in the Name File for time steps, for which in Output Control “Save 

 Budget” is specified (using words) or ICBCFL is not zero (using numeric codes)

 if number of model layers > 1:

 A 2D integer-array of each cells uppermost active layer, and a 2D real-array of each cell’s farm 

 net recharge flow rate will be saved as binary file on a unit number specified in the Name File 

 for time steps, for which in Output Control “Save Budget” is specified (using words) or 

 ICBCFL is not zero (using numeric codes)

ISDPFL Farm supply and demand print flags

 = -3 A list (A) of current demand and supply flow rates will be printed to the list file at each iteration, and a 

list (B) of final demand and supply flow rates will be printed to the list file for each time step:

 List (A): (FID, OFE, TFDR, NR-SWD, R-SWD, QREQ);

 List (B): (FID, OFE, TFDR, NR-SWD, R-SWD, QREQ, Q,[COMMENTS])

 = -2 A list of final demand and supply flow rates will be printed to the list file for each time step:

 List: (FID, OFE, TFDR, NR-SWD, R-SWD, QREQ, Q, [COMMENTS])

 = -1 A list of final demand and supply flow rates will be printed to the list file for time steps, for which in 

Output Control “Save Budget” is specified (using words) or ICBCFL is not zero (using numeric codes):

 List: (FID, OFE, TFDR, NR-SWD, R-SWD, QREQ, Q, [COMMENTS])

 = 0 farm demand and supply flow rates not written

 = 1 A list of initial demand and supply flow rates and of final demand & supply flow rates after the application of a deficiency scenario will be saved on ASCII file “FDS.OUT” for all time steps:

72 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
 List: (PER, TSTP, TIME, FID, OFE,

 TFDR-INI, NR-SWD-INI, R-SWD-INI, QREQ,

 TFDR-FIN, NR-SWD-FIN, R-SWD-FIN, QREQ, Q, DEF-FLAG)

 > 1 if “Compact Budget” is not specified in Output Control:

 A list of initial demand & supply flow rates and of final demand and supply flow rates after the 

application of a deficiency scenario will be saved as binary file on a unit number specified in the 

Name File for all time steps

 List: list attributes are equal to ISDPFL = 1

 if “Compact Budget” is specified in Output Control:

 A list of initial demand & supply flow rates and of final demand & supply flow rates after the 

application of a deficiency scenario will be saved as binary file on a unit number specified in the 

Name File for time steps, for which in Output Control “Save Budget” is specified (using words) or 

ICBCFL is not zero (using numeric codes)

 List: list attributes are equal to ISDPFL = 1

Optional Print Flags (item 2):

IOPFL Optional print settings if Acreage-Optimization is chosen (if IDEFFL > 0)

 = -4 A tableaux matrix will be printed to the list file for iterations, during which optimization occurs.

 = -3 Original and optimized flow rates of resource constraints and a list of fractions of optimized cell areas 

 will be printed to the list file for any farm and iteration that are subject to optimization: 

List: (Row, Column, Crop ID, A-tot-opt/ A-gw-opt/ A-sw-opt/ A-nr-opt/

A-tot-max, A-tot-opt, A-tot-opt, A-tot-opt )

 = -2 Original and optimized flow rates of resource constraints will be printed to the list file for any farm and 

iteration that are subject to optimization

 = -1 A cell-by-cell 2D-array of fractions of active cell acreage will be printed to the list file for all time steps.

 = 0 No original & optimized flow rates, and no optimized cell areas are written.

 = 1 A cell-by-cell 2D-array of fractions of active cell acreage is saved on ASCII file “ACR_OPT.OUT” for all 

time steps.

 = 2 Original and optimized flow rates of resource constraints are saved on ASCII file “ACR_OPT.OUT” for 

any farm and iteration that are subject to optimization.

 = 3 Original and optimized flow rates of resource constraints and a list of fractions of optimized cell areas is 

saved on ASCII file “ACR_OPT.OUT” for any farm and iteration that are subject to optimization:

List: (Row, Column, Crop ID, A-tot-opt/ A-gw-opt/ A-sw-opt/ A-nr-opt/

A-tot-max, A-tot-opt, A-tot-opt, A-tot-opt )

 = 4 A tableaux matrix is saved on ASCII file “ACR_OPT.OUT” for iterations, during which optimization 

occurs.

IPAPFL Optional print settings if Prior Appropriation is chosen (if IALLOT >1)

 = -1 A budget at the point of canal-diverions from the river and a budget at the point of a farm-diversion from 

the canal will be printed to the list file for all iterations.

 = 1 A budget at the point of canal-diverions from the river and a budget at the point of a farm-diversion from 

the canal will be saved on ASCII file “PRIOR.OUT” for all iterations. 

Optional Flags (item 2):

AUX “abc” Defines an auxilliary variable, “abc”, which will be read for each farm-well as part of items 4 and 22. Up to 

five auxilliary attributes “abc” can optionally be specified, each of which must be preceeded by “AUX.” These 

values will be read after the QMAXfact or QMAX variable of item 4 or item 22, respectively.

Data Input Instructions 73
AUX QMAXRESET The specification of the optional flag “AUX QMAXRESET” for {option} in item 2 will prompt 

 the FMP1 to reset QMAX as simulated by the MNW package to the default QMAX as defined by 

 FMP1 at the beginning of each time step. The optional flag “AUX QMAXRESET requires FMP1 

 to read an auxiliary variable in column 7 of the farm wells list in items 4 or 22. If a “1” is read in 

 column 7 of the farm wells ist, then the MNW-simulated QMAX is reset to the default QMAX in 

 the first iteraiton of each time step.

CBC Indicates that memory should be allocated to store cell-by-cell flow for each well to make these 

 flows available for use in other processs.

NOPRINT Indicates that a list of specified farm well attributes will not be printed to the list file

Farm-Well Related Variables (items 3, 4, 22, 23)

Farm Well Parameter Definition (item 3):

PARNAM Parameter name for list of parameter farm-wells (called for each stress period to activate a list of parameter 

wells). This name can consist of 1 to 10 characters and is not case sensitive.

PARTYP Parameter type (the only allowed parameter type is QMAX, which defines values of the volumetric maximum 

well capacity).

PARVAL Parameter value (multiplier applied to parameter-wells).

Farm-Wells List (items 4, 22):

Layer Layer number of cell containing the farm-well (for farm-wells linked to multi-layer wells defined in the MultiNode Well package: Layer No. = 0)

Row Row number of cell containing the farm well

Column Column number of cell containing the farm well

Farm-Well-ID Farm-well identity associated with the farm well (to establish a link of a farm-well to a well defined in the 

Multi-Node Well package: use “negative” Farm-Well-ID)

Farm-ID Farm identity to which the farm-well is attributed

QMAXfact Maximum Well Capacity factor (QMAXfact×PARVAL = QMAX) [L3/T].

QMAX Maximum Well Capacity [L3/T]

(positive value = maximum possible discharge rate)

[xyz] Represents any auxiliary variables for a farm-well that have been defined in item 2. The auxilliary variables must be present in each repetition of items 4 and 22. If the optional flag 

for {Option} in item 2 is set to “AUX QMAXRESET,” then the auxiliary variable for 

[xyz] in column 7 of the farm wells list is defined to be a binary parameter that tells when to reset the 

MNW-simulated QMAX rate to the FMP1-defined default QMAX rate. The parameter in column 7 of the 

well list is ignored, if the option flag “AUX QMAXRESET” is not specified.

0 = The MNW-simulated QMAX is reset at the beginning of each stress period.

1 = The MNW-simulated QMAX is reset at the beginning of each time step.

Farm-Well Flags and Dimensions for each Stress Period (items 4, 22, 23):

NLST Number of parameter farm-wells included in the parameter-well-list related to one parameter.

ITMP flag and counter

> 0 ITMP = number of nonparameter farm-wells read for the current stress period.

= 0 no nonparameter farm-wells are read for the current stress period.

< 0 nonparameter farm-well data from the last stress period will be reused.

NP Number of multiplier parameters in use in the current stress period.

Pname Name of multiplier parameter that is being used in the current stress period. NP parameter names will be read.

74 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Two-Dimensional Arrays (items 5, 6, 8, 10, 25, 30)

GSURF Ground-surface elevation

FID Farm identity

SID Soil type identity

CID Crop type identity

PFLX Precipitation flux (see climate related data) [L/T]

Farm Related Data Lists (items 7, 19, 20, 24, 32, 33, 34, 36)

Farm-ID Farm identity to which the parameters below are attributed

OFE On-farm Efficiency per farm (real number between 0 and 1; 0. < OFE ≤ 1.)

GWcost1,2,3,4

SWcost1,2,3,4  definitions see “Water Cost Coefficients” below

NRDV

NRDR  definitions see “Nonrouted Surface-Water Deliveries” below

NRDU

Row

Column

Segment  definitions see “Semi-Routed Surface-Water Deliveries” below

Reach

CALL definitions see “Surface-Water Allotment\Prior Appropriation”

Soil Type Related Data List (item 9)

Soil-ID Soil type identity to which the parameters below are attributed

CapFringe Capillary Fringe [L]

The following parameters are only needed if ICCFL = 1:

Either:

A-Coeff, B-Coeff, C-Coeff Coefficients a, b, c for function DRZ = f(Tc-pot, TRZ)

D-Coeff, E-Coeff Coefficients d, e for function n = f(DRZ)

Or:

Soil-Type Soil type in words:

3 options are available:

SANDYLOAM, SILT, and SILTYCLAY (not case-sensitive).

(For these three options, the FMP1 code contains intrinsic soil type specific coefficients a,b,c and d,e for 

the functionalities DRZ = f(Tc-pot, TRZ) and n = f(DRZ). If a soil type is entered as a word, then a,b,c,d,e are 

not read).

The intrinsic coefficients in the program are as follows (Schmid, 2004):

Soil type a b c d e

SANDYLOAM 0.201 -0.195 3.083 3.201 -3.903

SILT 0.320 -0.329 2.852 1.303 -2.042

SILTYCLAY 0.348 -0.327 1.731 0.530 -0.377

The parameters DRZ and n allow the fitting of a vertical pseudo steady state pressure head distribution over the total root zone:

Data Input Instructions 75
(3) The Depleted Root Zone (DRZ) is a function of the potential Transpiration and the Total Root Zone. It is defined as the 

 lower part of the root zone at which the pressure head increases with depth from the minimum (negative) pressure 

 head (defined as ψ4 in stress response function, see below) to zero at the bottom of the root zone.

 DRZ=[exp(a⋅ln(TRZ⋅MLT)+b⋅ln(TPOT⋅MLT)+c)]

(4) The Sinuosity Coefficient (n) expresses the curvature of the vertical pressure head configuration over depth, which 

 increases with increasing DRZ.

 NEXP=d⋅ln(DRZ)+e

Although the intrinsic parameters a,b,c,d,e were derived based on CENTIMETER length units, multipliers in the program (MLT) 

can adjust the equations accordingly to length units of METER or FEET, if so chosen as LENUNI = 2 or = 1 in the Discretization file (Harbaugh and others, 2000).

Crop-Type-Related Data List (Natural Crop Growth Parameters) (items 11−15, 25−29)

Crop-ID Crop type identity, to which the parameters below are attributed

ROOT Depth of root zone [L]

CU Consumptive use flux [L/T]

FTR Transpiratory fraction of consumptive use (0 < FTR ≤ 1)

FEP Evaporative fraction of consumptive use related to precipitation (0 ≤ FEP ≤ 1)

FEI Evaporative fraction of consumptive use related to irrigation (0 ≤ FEI < 1)

FIESWP Fraction of in-efficient losses to surface-water related to precipitation (0 ≤ FIESWP ≤ 1)

FIESWI Fraction of in-efficient losses to surface-water related to irrigation (0 ≤ FIESWI ≤ 1)

PSI(1) Absolute value of negative pressure head, at which root uptake becomes zero due to anoxia 

 (absolute value > 0) [L]

PSI(2), PSI(3) Absolute values of negative pressure heads, between which root uptake is optimal 

 (absolute value > 0) [L]

PSI(4) Absolute values of negative pressure head, at which root uptake becomes zero due to wilting 

 (absolute value > 0) [L]

BaseT Base temperature

MinCutT Minimum cutoff temperature

MaxCutT Maximum cutoff temperature

C0,C1,C2,C3 Polynomial coefficients for CGDD – Kc functionality (see Chapter “General Data Requirements”)

BegRootD Beginning root depth [L]

MaxRootD Maximum root depth [L]

RootGC Root growth coefficient

Climate-Related Data (items 16, 30)

Climate Time Series (item 16):

TimeSeriesStep Time-step in climate time series. The length of a time series time step must consistently be equal to the 

 MODFLOW time unit chosen in the Discretization File (ITMUNI).

 For ICUFL = 3 or IRTFL = 3, the MODFLOW time unit must be days (ITMUNI = 4). For IPFL = 3 (while

 ICUFL ≠ 3, and IRTFL ≠ 3), all MODFLOW time units are possible (seconds, minutes, hours, days, years;

 ITMUNI = 1, 2, 3, 4, 5). However, ITMUNI = 1 or 2 for units of seconds or minutes should be avoided 

 for very long periods of simulation due to the possibility of insufficient computer memory.

Precip Precipitation flux [L/T]

76 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
MaxT Maximum temperature

MinT Minimum temperature

ETref Reference Evapotranspiration flux [L/T]

LENSIM Total number of steps in a time series = length of the simulation.

Precipitation Array (item 30):

PFLX Precipitation Flux Array or Constant [L/T]

Crop-Type-Related Data Lists (Agro-Economic Parameters) (items 17, 18, 31)

Fallow List (item 17):

Crop-ID Crop-type identity to which the parameter below is attributed.

IFallow Fallow-Flag: 

 1 = Crop type fallowed

 0 = Crop type not fallowed (for example, pecan trees)

Crop Benefits List (items 18, 19):

Crop-ID Crop-type identity to which the parameters below are attributed.

WPF-Slope Slope of crop-specific water-production function (yield vs. ETcrop)

WPF-Int Intercept of crop-specific water-production function (yield vs. ETcrop) (can be zero).

Crop-Price Market-price per crop [value/weight]

Water Cost Coefficients (items 19, 32)

Farm-ID Farm identity to which the cost coefficients below are attributed.

Ground-Water Cost Coefficients:

GWcost1 Ground water Base Maintenance Costs per unit volume [$/L3]

GWcost2 Ground water Costs for Pumping in Well per unit volume, per unit lift [$/(L3⋅L)]

GWcost3 Ground water Costs for Vertical Lift from Well to Cell per unit volume, per unit lift [$/(L3⋅L)]

GWcost4 Ground water Delivery Costs per unit volume, per unit distance [$/(L3⋅L)]

Surface-Water Cost Coefficients:

SWcost1 Fixed Price of (Semi-) Routed Surface-Water per unit volume [$/L3

]

SWcost2 Costs for Vertical Lift of (Semi-)Routed Surface-Water from Reach to Cell per unit volume, 

 per unit lift [$/(L3⋅L)]

SWcost3 Delivery Costs of (Semi-)Routed Surface-Water per unit volume, per unit distance [$/(L3⋅L)]

SWcost4 Fixed Price of Nonrouted Surface-Water per unit volume [$/L3]

Nonrouted Surface-Water Deliveries–Farm-Related Data List (item 33)

Farm-ID Farm identity to which the parameter below are attributed

NRDV Volume of Nonrouted Delivery Type [L3]

NRDR Rank of Nonrouted Delivery Type

NRDU Binary “NRDuse-Flag” of Nonrouted Delivery Type:

 if 0: only the amount sufficient is used to meet the farm’s demand,

 if 1: the absolute amount available is used; surplus recharged into canal at farm’s head gate.

 if 2: the absolute amount available is used; surplus injected into farm wells attributed to farm ID.

Data Input Instructions 77
Semi-Routed Surface-Water Deliveries–Farm-Related Data List (items 20, 34)

Farm-ID Farm identity to which the parameter below are attributed

Row Row number of point of diversion

Column Column number of point of diversion

Segment Number of stream segment in which the diversion reach is located (must be equal to the number of the identical stream reach specified in the SFR1 input file)

Reach Number of reach from which diversion occurs (must be equal to the number of the identical reach specified in 

the SFR1 input file)

Five options of data input (marked by x) are available in order to uniquely identify the point of diversion within a cell:

Row Column Segment Reach Comments

x x x x full set of information is available (maximum information)

x x x 0/- if more than one segment pass through the cell (user prefers identification of location by 

coordinates) x x 0/- 0/- if just one segment passes through the cell

0 0 x x if more than one segment pass through the cell user prefers identification of location by 

reach number

0 0 0 x if more than one reach are within one cell (minimum information)

Surface-Water Allotment (items 35, 36)

Equal Appropriation:

ALLOT Surface-water allotment height [L] for a stress period.

Prior Appropriation:

Farm-ID Farm identity to which the parameter below is attributed

CALL Water Rights Call attributed to a farm [L3/T]

Ouput Data for Farm Process

Simulation results from the FMP1 can be reported to five auxiliary data sets in addition to the main MF2K listing and 

global files. These data sets consist of the following components. Various options to either print these data to the MF2K listing 

file or to save them to ASCII or binary files are controlled by the associated flags in parenthesis:

(1) Farm-well budget (IFWLCB);

(2) Farm net-recharge budget (IFNRCB);

(3) Farm supply and demand budget (ISDPFL);

(4) Optimized flow rates and optimized acreage of farms that experience a deficiency (IOPFL); only if acreageoptimization is chosen as a deficiency scenario (IDEFFL > 0);

(5) Budget at the point of canal-diverions from the river and a budget at the point of a farm-diversion from the 

canal (IPAPFL); only if prior appropriation is chosen as surface-water rights option (IALLOT > 1).

78 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Farm-Well Budget

The simulated farm-well flow rates can either be printed for each well location identified by layer, row, and column to the 

list file or saved to an ASCII file named “FWELLS.OUT.” In addition, farm-well flow rates can be saved to a binary file for each 

well location identified by the reseptive model node, or as a 2D-array for each cell.

Farm Net-Recharge Budget

Simulated farm net recharge flow rates can be printed as a 2D-array for each cell to the list file or to an ASCII file named 

“FNRCH_ARRAY.OUT.” Alternatively, a list of the cumulative farm net recharge for each farm can be saved to either an ASCII 

file named “FNRCH_LIST.OUT” or to a binary file named “FNRCH_LIST_BIN.OUT.” In addition, a list of cumulative farm 

net-recharge flow rates or a 2D-array of cell-by-cell farm net recharge flow rates can optionally be saved to binary files on a unit 

number specified in the Name File.

Farm Supply and Demand Budget

The simulated components of farm irrigation demand and supply of any current stage of solution during a time step (per 

iteration) and of the final demand and supply rates at the end of time steps or stress periods may be printed to list file:

Lists of current (iterative) and final farm demand and supply flow rates consist of the following parameters:

(1) FID farm ID

(2) OFE on-farm efficiency

(3) TFDR total farm delivery requirement

(4) NR-SWD non-routed surface-water delivery

(5) R-SWD (semi-)routed surface-water delivery

(6) QREQ ground-water pumping requirement

(7) (Q-FIN) ground-water pumping (only available for list of final rates)

Notice, that the list of “current” rates is iteratively updated within a present time step and does not yet contain a final supply 

flow rate from ground-water pumping, Q-FIN, which is available the end of a time step and therefore included into the list of 

final rates. For cases of irrigation water supply insufficiency, a comment is printed at the end of each record, informing about a 

possible imbalance of the farm demand and supply budget.

If the final supply exceeds the original or optimized demand by a certain flow rate X, then the following messages will be 

printed:

For Deficit Irrigation or Zero Scenario (IDEFFL = -1 or 0):

• “QREQ exceeds QMAXF by” X

For Deficit Irrigation with Water-Stacking (IDEFFL = -2): 

• “Original QREQ exceeded QMAXF by” X

• “QREQ of priority crops still exceeds QMAXF by” X

If, for Acreage-Optimization (IDEFFL > 0), the optimized demand is actually less than the original constrained 

surface-water or ground water resource (by a flow rate of X), then the following messages will be printed:

• “Surface-Water Demand falls behind original Surface-Water Supply by” X

• “Ground Water Demand falls behind original QMAXF by” X

Another, more comprehensive form of saving initial and final farm demand and supply budget is to save the according flow 

rates to an ASCII file named “FDS.OUT” for all time steps or alternatively to a binary file either for all or for selected time 

steps. Final rates only differ from intial ones, if either water-stacking or acreage-optimization was applied as deficiency scenario.

A list of inital and final farm demand and supply flow rates for all time steps consists of the following parameters (table 3):

Data Input Instructions 79
Optimized Flow Rates and Optimized Acreage of Farms

The user has various options of saving different data of interest, if acreage-optimization was chosen as a deficiency scenario 

(IDEFFL > 0). Fractions of active cell acreage will be printed as a 2D array either to the list file or saved to an ASCII file named 

“ACR_OPT.OUT” for all time steps. Alternatively, original and optimized flow rates of resource constraints may either be saved 

for each farm by themselves or in conjunction with a list of fractions of active cell acreage. This option will save the according 

data either to the list file or to an ASCII file named “ACR_OPT.OUT” for any farm and any iteration that are subject to optimization. For each cell (row, column) within an optimized farm, the list of fractions of cell acreage consists of the following 

parameters:

• A-tot-opt/A-tot-max fraction of total optimized acreage on total maximum acreage;

• A-gw-opt/A-tot-opt fraction of optimized ground-water irrigated acreage on total 

 optimized acreage;

• A-sw-opt/A-tot-opt fraction of optimized (semi-)routed surface-water irrigated 

acreage on total optimized acreage;

• A-nr-opt/A-tot-opt fraction of optimized nonrouted surface-water irrigated 

 acreage on total optimized acreage;

Users with specifc interest in the definition of the linear optimization tableaux matrix may save this matrix either to the list 

file or to an ASCII file named “ACR_OPT.OUT.” The number of columns in the tableaux matrix equals the number of optimization variables + 1. The number of rows in the matrix equals the number of constraints + 1.

General Information:

(1) PER: Stress period

(2) STP: Time step

(3) TIME [UNIT]: Elapsed time (in units chosen in discretization file)

(4) FID: Farm identification

(5) OFE: Specified or calculated on-farm efficiency

Initial flow rates before invoking a deficiency scenario:

(1) TFDR-INI: Initial Total Farm Delivery Requirement

(2) NR-SWD-INI: Initial Nonrouted Surface-Water Delivery

(3) R-SWD-INI: Initial (Semi-) Routed Surface-Water Delivery

(4) QREQ-INI: Initial Pumping Requirement

Final flow rates of a solution found by means a deficiency scenario:

(1) TFDR-FIN: Final Total Farm Delivery Requirement

(2) NR-SWD-FIN: Final Nonrouted Surface-Water Delivery

(3) R-SWD-FIN: Final (Semi-) Routed Surface-Water Delivery

(4) QREQ-FIN: Final Pumping Requirement

(5) Q-FIN: Final Pumping Rate

(6) DEF-FLAG: Deficiency Scenario Flag

Table 3. Summary of Farm Budget Components.

80 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Budgets at Points of Canal Diversion and Farm Diversion 

A budget at the point of canal-diverions from the river and a budget at the point of a farm-diversion from the canal are 

printed to the list file or to an ASCII file named “PRIOR.OUT” if Prior Appropriation is chosen as surface-water allotment 

option (IALLOT > 1). The “Prior Appropriation Subroutine” in FMP1 solves (1) for the delivery to a farm from a canal and (2) 

for the diversion into the respective canal from a river. Solutions for (1) and (2) are found iteratively. The budgets for both points 

of diversion are therefore printed for any farm on an iterative basis. However, after having found solutions for (1) and for (2) for 

a certain farm, those solutions are not iterated anymore within a current time step. The output budgets for both points of diversion also informs whether a “convergence solution” or “exceedance solution” was found. A “convergence solution” is found if 

the surface-water delivery to the farm “convergences” to the delivery requirement from the farms’s head-gate reach. An “exceedance solution” is found if the necessary diverison from the river into the respective canal “exceeds” the river streamflow and 

consequently the diversion from the canal into a junior water rights farm will be insufficient to satisfy the delivery requirement 

from that farm’s head-gate reach.

The output data set for each farm consists of three blocks of information:

Information about routing system during current iteration:

• Farm-ID;

• Head-gate reach number;

• Canal segment number;

• River segment number.

Budget at Point of Canal-Diversion from River:

• Qstr-in Inflow to point of diversion at the end of current stream segment;

• Qstr-out Outflow from point of diversion past the end of current stream segment;

• Qstr-min Minimum river-streamflow requirement at point of diversion from stream that is not available 

 for diversion to the current farm (necessary to account for the demand and for related conveyance 

 losses to a downstream farm senior farm located at a downstream diverting canal);

• ADIV Actual diversion rate from stream into current canal segment;

• PDIV Potential diversion rate from stream into current canal segement.

Budget at Point of Farm Diversion from Canal:

• RDEL-req Delivery requirment from current head-gate reach;

• Qcn-in Inflow to point of diversion from current canal at beginning of current 

head-gate reach;

• Qcn-out Outflow from point of diversion from current canal past the beginning of 

 current head-gate reach;

• Qcn-min Minimum canal-streamflow requirement at point of diversion from canal that 

 is not available for farm “f” at its head-gate (necessary to account for senior 

 farm on the same canal);

• DELIVERY surface-water delivery to current farm from current head-gate reach at 

 present iteration.

Comments:

Stage:

A record (in quotes) is printed informing about the current 

stage of the “prior appropriation” algorithm; three different 

stages are possible.

Result:

A record (in quotes) is printed informing about the action taken 

at a certain stage of the algorithm; three different results are possible at two different stages.

“Initial values” (initial values at beginning of algorithm 

are printed)

“Cumulate PDIV” (values are printed after cumulating 

PDIV by the unsatisfied increment [RDELreq. – Qcn-in] )

“Exit and apply new PDIV rates” (exit MF2K and solve with 

incremented PDIV)

“SOLUTION” (final values are printed once a solution was 

found)

“Convergence Solution”

“Exceedance Solution”

Data Input Instructions 81
82 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000

Example Problems

Two hypothetical example problems were simulated with MF2K using the FMP1 jointly with the SFR1 package. The first 

problem demonstrates the case of equal appropriation of surface water deliveries and the second problem invokes prior appropriation to surface-water deliveries and includes a simple example of a deficiency scenario that used acreage optimization to 

balance demands with supplies of water. While not all features of the FMP1 are included in these two examples, they illustrate 

many of the fundamental features needed for many regional hydrologic models that include simulations of supply and demand 

related to irrigated agriculture.

The two example problems are based on a common hydrologic framework with a single aquifer represented with a single 

model layer and with areally constant hydraulic properties (fig. 16, Appendix). Identical hydraulic properties, no-flow boundaries on the eastern and western boundaries, general-head boundaries on the northern and southern boundaries, and a common 

streamflow and canal network are used for both problems (fig. 16). The model domain consists of an alluvial valley with a slight 

inclination from west to east, so that the streamflow in canals can follow down the sloped land surface due to gravity (fig. 16). 

A predevelopment steady state simulation with a general-head boundary and a stream-canal-drain network was used to estimate 

initial heads (fig. 16). A development transient-state simulation with the FMP1 then included the farms with crops for the two 

example problems. The development simulations span a period of 1 year with four 3-month stress periods and weekly time 

steps. Data sets for the two example problems, including input for all model packages, are given in the Appendix.

The examples include four farms (figs. 17A, B), with three types of crops (alfalfa, pecans, and onions) with no crop rotation 

or fallow periods (fig. 17C), three soil types (silt, silty clay, and sandy loam) (fig. 17D), and a total of ten farm wells 

(figs. 17A, B). Some of the farm wells are coincident with the farms and several are located in areas not coincident with the 

farms. Note that farm 1 in example problem 1 does not extend to the irrigation canal to facilitate a semi-routed surface-water 

delivery not adjacent to the diversion canal (fig. 17A). In addition, the farms are sequentially numbered in downstream order for 

example problem 1, but are reordered to reflect surface-water water-rights rankings for example problem 2. Both problems use 

the consumptive use concept 1 with the three specified soil types that refer to internally stored analytical solutions specific for 

these soil types and are cross referenced to the soil-ID map (fig. 17D). Both problems use fully routed surface-water deliveries 

with the slopes of the diversion canals interpolated from the endpoints of the canal segments. Both problems have a river/canal 

system composed of 11 segments that use a constant river streamflow into the problem area of 50,000 m3/d (fig. 16). A total 

number of ten farm wells have different maximum pumping capacities (figs. 17 A,B). In example problem 1, the cumulative 

maximum capacities of all farm wells in a farm are 6,000 m3/d for three farms (farms 1, 2, and 3 in example problem 1; farms 

1, 3, 4 in example problem 2) and 8,000 m3/d for one farm (farm 4 in example problem 1; farm 2 in example problem 2). Both 

problems also simulate four types of nonrouted deliveries with some of these deliveries representing interstate or international 

water transfers for example problem 2.

In the first example problem with equal surface-water appropriation, many of the crop, climate, and farm attributes are 

allowed to vary. For example, the root depths, crop consumptive uses, precipitation, fractions of transpiration and evaporation 

from consumptive use, and farm irrigation efficiency are specified for each stress period. The fractions of losses to inefficient 

surface-water runoff are chosen to be proportional to the slope of the ground surface, and the farm irrigation efficiency behavior is considered conservative with efficiency being constant over a time step. There are up to four types of nonrouted delivery 

sources to each farm. In addition to fully routed surface-water deliveries, this problem also has one semi-routed delivery to farm 

1 (fig. 17A) with diversion model coordinates (row, column) = (3, 5) (surface-water routed along a canal; non-surface-water 

routed by pipeline). For eight out of ten farm wells, a parameter factor is assigned to the maximum well capacity. Two additional wells (9 and 10 from farms 3 and 4) (fig. 17B) have maximum pumping capacities that are held constant.

In the second example problem with prior appropriation of surface-water deliveries and acreage optimization for a deficiency scenario, many of the crop and climate attributes are now allowed to vary from time-series data that result in average 

values for each time step, as opposed to user specified values for each stress period as was used in problem 1. Thus, the values 

for root depth, crop consumptive use, and precipitation are now varied for each time step. There are no semi-routed surfacewater deliveries and the crop benefit and cost attributes for the acreage optimization are held constant for the entire simulation. 

For all of the ten farm wells, a parameter-factor is assigned to the maximum well pumping capacity. With additional political 

boundaries between the four farms in example problem 2 (fig. 17B), some of the four types of specified nonrouted deliveries 

could represent interstate and international water transfers.
Figure 16. Model domain and boundary conditions and initial heads for the FMP1 example problems.

Data Input Instructions 83

Regional ground-water

flow direction

ROWS

COLUMNS

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

23

22

21

20

19

18

17

16

15

14

13

12

11

10

9

8

7

6

5

4

3

2

1

Figure 16.

Canal (15 meters ,

 Kv = 0.001 meters per day)

No flow boundary

EXPLANATION

General head boundary

Specified inflow into stream

 (50,000 cubic meters per day)

Diversion into canal

 Example 1: Specified diversion

 (20,000 cubic meters per day)

 Example 2: Simulated diversion

Active model cell

 (500 X 500 meters,

 K = 5 meters per day)

Stream (30 meters , 

 Kv = 0.06 meters per day)

Drain (10 meters ,

Kv = 0.1 meters per day))

Kv Vertical hydraulic conductivity 

 Stream, canal, or drain channel width

1 3 7 5 9

COLUMNS

11 13 15 17 19

HEAD ELEVATION GROUND-SURFACE ELEVATION

299.0

299.0

299.0

299.0

277.0

277.0

293.5

288.0

282.5

277.0

299.0

293.5

288.0

282.5

277.0

299.0

277.0

23

1 5 9 13

ROWS

ROWS

17

23

21

1 5 9 13 17 21

1 3 5 7 9

COLUMNS

11 13 15 17 19
84 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000

Figure 17. Model domain with farms and related wells for example problems 1 and 2 and crops and soils for both problems.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

23

22

21

20

19

18

17

16

15

14

13

12

11

10

9

8

7

6

5

4

3

2

1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

23

22

21

20

19

18

17

16

15

14

13

12

11

10

9

8

7

6

5

4

3

2

1

Farm 1 (efficiency = 70%)

Farm 2 (efficiency = 70%)

Farm 3 (efficiency = 80%)

Farm 4 (efficiency = 80%)

Wells of Farm 1

Wells of Farm 2

Wells of Farm 3

Wells of Farm 4

Maximum pumping 

capacity [m3/d]

Pipeline to Farm 1

(semi-routed delivery)

5,000

500 500

3,000

2,000

1,000

2,000

4,000

3,000

5,000

1,000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

23

22

21

20

19

18

17

16

15

14

13

12

11

10

9

8

7

6

5

4

3

2

1

Crop 1 (alfalfa)

Crop 2 (pecan)

Crop 3 (onion)

C. Model domain with crop types for example problems 1 and 2. D. Model domain with soil types.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

23

22

21

20

19

18

17

16

15

14

13

12

11

10

9

8

7

6

5

4

3

2

1

Soil type 1 (silt)

Soil type 2 (sandy loam)

Soil type 3 (silty clay)

Model domain of example problems, specified and simulated boundary conditions, hydraulic conductivities (K) of aquifers, 

conductivities and widths (∅) for beds of stream, canals and drains (see figure 16 for explanation)

5,000

500 500

3,000

2,000

1,000

2,000

4,000

3,000

5,000

B. Example 2: Distribution of farms or irrigation settings according to 

their prior appropriation ranking (lower ID (farm number) = higher rank) 

with attributed on-farm efficiencies, and farm wells with their 

respective maximum pumping capacities.

Farm 1 (efficiency = 70 %)

Farm 2 (efficiency = 80 %)

Farm 3 (efficiency = 70 %)

Farm 4 (efficiency = 80 %)

Wells of Farm 1

Wells of Farm 2

Wells of Farm 3

Wells of Farm 4

Maximum capacity [m3/d]

State border

International border

2

3

4

1

1,000

A. Example 1: Distribution of equally appropriated farms with attributed

on-farm efficiencies, and farm wells with their respective maximum 

pumping capacities.

Figure 17

COLUMNS

ROWS
The time series (delta-t = 1 week) of irrigation delivery requirements for each farm and surface-water and ground-water 

supply were plotted to demonstrate the demand and supply components (figs. 18 and 19) along with the farm demand and supply 

(FDS) files (tables 4 and 5) for example problems 1 and 2, respectively. For each farm note that the maximum pumping capacity 

for the sum of all farm wells remains constant for the entire simulation for both example problems. 

In example problem 1, the TFDR varies across the four seasonal stress periods for each farm (figs. 18A–D). The TFDR is 

satisfied for each farm by a combination of surface-water deliveries and ground-water pumpage throughout the entire simulation. 

For farm 1 (fig. 18A), there is no TFDR for the first stress period (weeks 1–13). The semirouted surface-water delivery 

[(S)R-SWD-FIN] plus the nonrouted surface-water delivery (NR-SWD-FIN) satisfy the TFDR for the second stress period 

(weeks 14–26). Additional ground-water pumpage (QREQ-FIN) is needed to supplement the reduced surface-water deliveries 

in the third stress period (weeks 27–39), when surface-water delivery is constrained by a low allotment, and then the pumpage 

is not needed for the fourth stress period (weeks 40–52) where the reduced TFDR is again sufficiently satisfied by the semirouted and nonrouted surface-water deliveries. Similarly for farm 2 (fig. 18B), the TFDR is supplied by fully routed surface-water 

deliveries in the second stress period, requires a small supplement of ground-water pumpage in the third stress period, and the 

reduced TFDR is only supplied by nonrouted deliveries in the fourth stress period. The demand and supply history for farm 3 

(fig. 18C) is similar to farm 1, but shows less ground-water pumpage needed to help satisfy the TFDR in the third stress period 

because the nonrouted deliveries are larger. In contrast, farm 4 (fig. 18D) is heavily dependent upon supply from ground-water 

pumpage to satisfy the TFDR demand. The ground-water pumpage is estimated for the total pumpage for a set of wells associated with each farm (figs. 18 A–D) as well as for each individual farm, as printed into the listing file as follows:

FARM WELLS PERIOD 3 STEP 13 10 FARMS WELLS ELAPSED TIME 274.00 DAYS

FARM-WELL ID FARM ID LAYER ROW COL RATE

9 3 1 21 3 -4000.00

10 4 1 21 19 -5000.00

1 1 1 5 6 -5000.00

2 2 1 5 9 -182.339

3 2 1 6 10 -182.339

4 2 1 7 11 -182.339

5 1 1 8 6 -500.00

6 1 1 8 9 -500.00

7 3 1 18 3 -2000.00

8 4 1 18 19 -3000.00

Note that the wells of farm 2 did not reach their maximum well capacities.

Farm net recharge to and from the ground water system also is estimated on a cell by cell basis, and printed to the listing 

file. The net recharge represents the difference between outflows as evapotranspiration from ground water and inflows as deep 

percolation to ground water of water that is in excess of the crop irrigation requirement. Therefore, negative numbers represent 

a net outflow from the ground-water system and positive numbers represent net inflow to the ground-water system. In example 

problem 1 for the stress-period 3/time-step 13, net outflow occurred over western parts of farms 1and 3 and over the northern 

part of farm 2. Net inflow occurred over the eastern parts of farms 1 and 3, over the southeastern part of farm 2, and over the 

entire farm 4. 

Example Problems 85
25,000

20,000

15,000

10,000

5,000

0

A Farm 1

8,000

1 4 8 12 16 20 24

TIME STEP, IN WEEKS

28 32 36 40 44 48 52

7,000

6,000

5,000

4,000

3,000

2,000

1,000

0

B Farm 2

Figure 18. FLOW RATE, IN CUBIC METERS PER DAY

TFDR-INI

NR-SWD-INI

(S)R-SWD-INI

QREQ-INI

TFDR-FIN

NR-SWD-FIN

(S)R-SWD-FIN

QREQ-FIN

Q-FIN

EXPLANATION

(Please see Table 3 for

abbreviation descriptions)

Total well

pumping capacity

(QMAXF)

Surface-water

allotment rate

(ALLOT-RATE)

Figure 18. Irrigation Demand and Surface- and Ground-Water Supply for Farms (A) 1, (B) 2, (C) 3, and (D) 4 for Example Problem 1.

86 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
25,000

20,000

15,000

10,000

5,000

0

C Farm 3

30,000

TIME STEP, IN WEEKS

FLOW RATE, IN CUBIC METERS PER DAY 25,000

20,000

15,000

10,000

5,000

0

D Farm 4

Figure 18 cont.

Total well

pumping capacity

(QMAXF)

TFDR-INI

NR-SWD-INI

(S)R-SWD-INI

QREQ-INI

TFDR-FIN

NR-SWD-FIN

(S)R-SWD-FIN

QREQ-FIN

Q-FIN

Surface-water

allotment rate

(ALLOT-RATE)

EXPLANATION

(Please see Table 3 for

abbreviation descriptions)

1 4 8 12 16 20 24 28 32 36 40 44 48 52

Figure 18.—Continued.

Example Problems 87
18,000

16,000

14,000

12,000

10,000

8,000

6,000

4,000

2,000

0

A Farm 1

40,000

35,000

30,000

25,000

20,000

15,000

10,000

5,000

0

B Farm 2

Figure 19.

FLOW RATE, IN CUBIC METERS PER DAY

TIME STEP, IN WEEKS

1 4 8 12 16 20 24 28 32 36 40 44 48 52

TFDR-INI

NR-SWD-INI

(S)R-SWD-INI

QREQ-INI

TFDR-FIN

NR-SWD-FIN

(S)R-SWD-FIN

QREQ-FIN

Q-FIN

EXPLANATION

(Please see Table 3 for

abbreviation descriptions)

Total well

pumping capacity

(QMAXF)

Figure 19. Irrigation demand and surface- and ground-water supply for farms (A) 1, (B), 2, (C) 3, and (D) 4 for example problem 2.

88 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
50,000

60,000

40,000

30,000

20,000

10,000

0

C

35,000

TIME STEP, IN WEEKS

FLOW RATE, IN CUBIC METERS PER DAY

25,000

30,000

20,000

15,000

10,000

5,000

-5,000

-10,000

0

Farm 4

Farm 3

D

Figure 19. cont.

1 4 8 12 16 20 24 28 32 36 40 44 48 52

TFDR-INI

NR-SWD-INI

(S)R-SWD-INI

QREQ-INI

TFDR-FIN

NR-SWD-FIN

(S)R-SWD-FIN

QREQ-FIN

Q-FIN

EXPLANATION

(Please see Table 3 for

abbreviation descriptions)

Total well

pumping capacity

(QMAXF)

Figure 19.—Continued.

Example Problems 89
FARM NET RECH. PERIOD 3 STEP 13, 20 COLUMNS, 23 ROWS, 1 LAYERS ELAPSED TIME 274.00 DAYS

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 27.92 -0.5207 -3.304 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 100.5 4.205 -0.3998 0 0 0 0 0 0 0 0 0 0

0 0 0 0 -100.6 62.5 165.5 67.55 3.362 4.409 0 0 0 0 0 0 0 0 0 0

0 0 0 0 -168.8 -86.24 50.64 8.891 4.408 4.408 0 0 0 0 0 0 0 0 0 0

0 0 0 0 -218.6 -124.3 -31.23 383.3 4.408 4.408 0 0 0 0 0 0 0 0 0 0

0 0 0 0 -294.1 -239.3 312.5 336.4 4.408 4.408 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 -384.4 -31.86 -27.35 -24.64 84.93 216.2 224.7 248.6 20.19 20.19 20.19 0 0 0 0

0 0 0 0 0 0 -334.2 -11.16 -22.44 70.83 67.98 215 244.3 20.19 20.19 20.19 0 0 0 0

0 0 0 0 0 0 -323.5 -322 -16.33 82.85 91.56 114.4 268.3 20.19 20.19 20.19 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

The total volumetric budget from MF2K demonstrates several features related to the FMP1 for example problem 1. The 

rate of inflow as ground-water recharge is greater than the outflows related to evapotranspiration from the ground water for this 

stress period following the excess irrigation from intensive irrgiation with surface water and ground water during stress-period 

3. However, the cumulative outflow for the first three stress periods is greater than the inflow which is mainly a result of the 

fact, that, during the first stress period, two out of four farms did not require any irrigation and were entirely supplied by uptake 

from ground water and precipitation. Other components of the volumetric budget are ground-water pumpage from farm wells, 

a smaller downward leakage from the stream-canal network to the ground-water system as opposed to a higher upward leakage 

from the aquifer into the stream network, and inflow from the general-head boundaries. In addition to the farm budget

(tables 4 and 5), the ground-water volumetric budget also lists the FMP1 farm wells as “FARM WELLS” and farm net recharge 

as “FARM NET RECH” in both the inflow and outflow portions of the volumetric summary as follows:

90 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
VOLUMETRIC BUDGET FOR ENTIRE MODEL AT END OF TIME STEP 13 IN STRESS PERIOD 3

CUMULATIVE VOLUMES L**3 RATES FOR THIS TIME STEP L**3/T

 IN: IN:

STORAGE = 3490324.0000 STORAGE = 16709.5488

CONSTANT HEAD = 0.0000 CONSTANT HEAD = 0.0000

HEAD DEP BOUNDS = 10468919.0000 HEAD DEP BOUNDS = 38937.4297

STREAM LEAKAGE = 614329.1250 STREAM LEAKAGE = 3415.2991

FARM WELLS = 0.0000 FARM WELLS = 0.0000

FARM NET RECH. = 1150043.3750 FARM NET RECH. = 3665.5386

TOTAL IN = 15723615.0000 TOTAL IN = 62727.8164

OUT: OUT:

STORAGE = 165089.4219 STORAGE = 0.0000

CONSTANT HEAD = 0.0000 CONSTANT HEAD = 0.0000 

HEAD DEP BOUNDS = 8052081.5000 HEAD DEP BOUNDS = 28685.1523

STREAM LEAKAGE = 3629270.0000 STREAM LEAKAGE = 10739.3281

FARM WELLS = 2587317.2500 FARM WELLS = 20547.0156

FARM NET RECH. = 1291158.6250 FARM NET RECH. = 2765.2747

TOTAL OUT = 15724917.0000 TOTAL OUT = 62736.7695

IN - OUT = -1302.0000 IN - OUT = -8.9531

PERCENT DISCREPANCY = -0.01 PERCENT DISCREPANCY = -0.01

In example problem 2, the TFDR varies across the four seasonal stress periods for each farm (figs. 19A–D). The TFDR 

is reduced through acreage reduction because the various components of supply cannot always satisfy the demand for some of 

the farms with junior water-rights. This is most pronounced for farms 3 and 4, which have the most junior water rights where 

ground-water pumpage and reduced TFDR are simulated for these farms. In contrast, farm 4 also may have water available for 

export in stress periods 1, 2 and 4. For example, farm 4 is simulated to have surface-water return flows in stress-period 2/timesteps 7 and 8 of -4,841 and -2,636 m3

/d, respectively (table 5). These return flows from farm 4 into the adjacent canal are a 

result of surface-water surplus originating from two reasons. Firstly, nonrouted and routed deliveries were reduced close to 

zero, because their use was estimated to be unprofitable as a result of the acreage optimization scenario. However, secondly, 

nonrouted deliveries were specifed to be used absolutely in case they are not needed and by majority to be recharged back into 

the adjacent canal. Because of the water-rights ranking to the surface-water deliveries, the reductions of some farms also may 

help to increase the potential supply at other farms. For example, in stress-period 3/time-step 1 (table 5) the TFDR for farm 3 is 

reduced, which makes additional water available for the junior-rights at farm 4 that originally received no routed surface-water. 

In this case an additional 682 m3/d of surface-water was supplied because of the retirement of 2,728 m3/d from farm 3. Even 

with additional surface-water supply at farm 4, the supply remains insufficient. Thus, a secondary acreage optimization was 

carried out, which reduced the additional 2,724 m3/d (2.728 m3/d minus 4 m3/d of conveyance losses) to the profitable amount of 

about 682 m3/d.

For stress-period 2/time-step 13, the spatial distribution of fractions of active cell acreage is saved as a 2D-array to output 

file ‘ACR_OPT.OUT’ and illustrated in figure 20. While farm 1 and farm 2 do not show any acreage reduction, the farm land in 

farm 3 and farm 4 are partially retired. The acreage of cells in green are reduced to zero. One cell experiences a partial reduction 

to 53 percent of the original cell acreage (row, column = 9,9). Although of lowest surface-water rights rank, farm 4 still can sustain the irrigation of a relatively high consumptive pecan-orchard on the east side of the farm. This is not the case for farm 3 due 

to a lower total rate of nonrouted deliveries and ground water pumping, as compared to farm 4 (farm 3: 2,000 m3/d in nonrouted 

deliveries and 6,000 m3/d in ground water pumping; farm 4: 5,000 m3/d in nonrouted deliveries and 6,000 m3/d in ground water 

pumping).

The penalty of each cell’s acreage reduction depends foremost on the availability of water resources. For a prior appropriation system as in example 2, farm 3 and farm 4 are almost completely retired because of partial or total lack of routed surface 

water (fig. 20). Another factor that plays an important role is the question “by how much a cell’s acreage is reduced, is the net 

profit that can be expected from irrigating a cell’s acreage.” This net profit is equal to market dependent benefits of irrigating a 

certain crop’s acreage minus the costs associated with using certain water types to satisfy the cell’s irrigation. 

Example Problems 91
PER STP DAYS FID OFE TFDR-INI NR-SWDINI

(S)R-SWDINIQREQ-INI TFDR-FIN NR-SWDFIN(S)R-SWDFINQREQ-FIN Q-FIN DEFFLAG

1 1 7 1 0.49 0 0 0 0 0 0 0 0 0 0

1 1 7 2 0.49 0 0 0 0 0 0 0 0 0 0

1 1 7 3 0.56 1046 1046 0 0 1046 1046 0 0 0 0

1 1 7 4 0.56 2234 0 2234 0 2234 0 2234 0 0 0

1 2 14 1 0.49 0 0 0 0 0 0 0 0 0 0

1 2 14 2 0.49 0 0 0 0 0 0 0 0 0 0

1 2 14 3 0.56 1098 1098 0 0 1098 1098 0 0 0 0

1 2 14 4 0.56 2234 0 2234 0 2234 0 2234 0 0 0

1 3 21 1 0.49 0 0 0 0 0 0 0 0 0 0

1 3 21 2 0.49 0 0 0 0 0 0 0 0 0 0

1 3 21 3 0.56 1142 1142 0 0 1142 1142 0 0 0 0

1 3 21 4 0.56 2235 0 2235 0 2235 0 2235 0 0 0

1 4 28 1 0.49 0 0 0 0 0 0 0 0 0 0

1 4 28 2 0.49 0 0 0 0 0 0 0 0 0 0

1 4 28 3 0.56 1180 1180 0 0 1180 1180 0 0 0 0

1 4 28 4 0.56 2237 0 2237 0 2237 0 2237 0 0 0

1 5 35 1 0.49 0 0 0 0 0 0 0 0 0 0

1 5 35 2 0.49 0 0 0 0 0 0 0 0 0 0

1 5 35 3 0.56 1213 1213 0 0 1213 1213 0 0 0 0

1 5 35 4 0.56 2239 0 2239 0 2239 0 2239 0 0 0

1 6 42 1 0.49 0 0 0 0 0 0 0 0 0 0

1 6 42 2 0.49 0 0 0 0 0 0 0 0 0 0

1 6 42 3 0.56 1243 1243 0 0 1243 1243 0 0 0 0

1 6 42 4 0.56 2241 0 2241 0 2241 0 2241 0 0 0

1 7 49 1 0.49 0 0 0 0 0 0 0 0 0 0

1 7 49 2 0.49 0 0 0 0 0 0 0 0 0 0

1 7 49 3 0.56 1272 1272 0 0 1272 1272 0 0 0 0

1 7 49 4 0.56 2244 0 2244 0 2244 0 2244 0 0 0

1 8 56 1 0.49 0 0 0 0 0 0 0 0 0 0

1 8 56 2 0.49 0 0 0 0 0 0 0 0 0 0

1 8 56 3 0.56 1298 1298 0 0 1298 1298 0 0 0 0

1 8 56 4 0.56 2248 0 2248 0 2248 0 2248 0 0 0

1 9 63 1 0.49 0 0 0 0 0 0 0 0 0 0

1 9 63 2 0.49 0 0 0 0 0 0 0 0 0 0

1 9 63 3 0.56 1323 1323 0 0 1323 1323 0 0 0 0

1 9 63 4 0.56 2251 0 2251 0 2251 0 2251 0 0 0

1 10 70 1 0.49 0 0 0 0 0 0 0 0 0 0

1 10 70 2 0.49 0 0 0 0 0 0 0 0 0 0

1 10 70 3 0.56 1345 1345 0 0 1345 1345 0 0 0 0

1 10 70 4 0.56 2255 0 2255 0 2255 0 2255 0 0 0

1 11 77 1 0.49 0 0 0 0 0 0 0 0 0 0

1 11 77 2 0.49 0 0 0 0 0 0 0 0 0 0

1 11 77 3 0.56 1364 1364 0 0 1364 1364 0 0 0 0

1 11 77 4 0.56 2259 0 2259 0 2259 0 2259 0 0 0

1 12 84 1 0.49 0 0 0 0 0 0 0 0 0 0

1 12 84 2 0.49 0 0 0 0 0 0 0 0 0 0

1 12 84 3 0.56 1382 1382 0 0 1382 1382 0 0 0 0

1 12 84 4 0.56 2263 0 2263 0 2263 0 2263 0 0 0

1 13 91 1 0.49 0 0 0 0 0 0 0 0 0 0

1 13 91 2 0.49 0 0 0 0 0 0 0 0 0 0

1 13 91 3 0.56 1400 1400 0 0 1400 1400 0 0 0 0

1 13 91 4 0.56 2266 0 2266 0 2266 0 2266 0 0 0

Table 4. Farm Demand and Supply (FDS.OUT), Farm Budget Output for Example Problem 1. 

[see table 3 for explanation of abbreviations]

Stress Period 1 

92 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
PER STP DAYS FID OFE TFDR-INI NR-SWDINI

(S)R-SWDINIQREQ-INI TFDR-FIN NR-SWDFIN(S)R-SWDFINQREQ-FIN Q-FIN DEFFLAG

2 1 98 1 0.63 16118 2000 14118 0 16118 2000 14118 0 0 0

2 1 98 2 0.63 5393 2000 3393 0 5393 2000 3393 0 0 0

2 1 98 3 0.72 17882 5000 12882 0 17882 5000 12882 0 0 0

2 1 98 4 0.72 24773 0 7008 17765 24773 0 7008 17765 8000 0

2 2 105 1 0.63 16451 2000 14451 0 16451 2000 14451 0 0 0

2 2 105 2 0.63 5418 2000 3418 0 5418 2000 3418 0 0 0

2 2 105 3 0.72 17907 5000 12907 0 17907 5000 12907 0 0 0

2 2 105 4 0.72 23976 0 6982 16994 23976 0 6982 16994 8000 0

2 3 112 1 0.63 16632 2000 14632 0 16632 2000 14632 0 0 0

2 3 112 2 0.63 5431 2000 3431 0 5431 2000 3431 0 0 0

2 3 112 3 0.72 17906 5000 12906 0 17906 5000 12906 0 0 0

2 3 112 4 0.72 23484 0 6982 16502 23484 0 6982 16502 8000 0

2 4 119 1 0.63 16743 2000 14743 0 16743 2000 14743 0 0 0

2 4 119 2 0.63 5439 2000 3439 0 5439 2000 3439 0 0 0

2 4 119 3 0.72 17899 5000 12899 0 17899 5000 12899 0 0 0

2 4 119 4 0.72 23225 0 6983 16241 23225 0 6983 16241 8000 0

2 5 126 1 0.63 16817 2000 14817 0 16817 2000 14817 0 0 0

2 5 126 2 0.63 5445 2000 3445 0 5445 2000 3445 0 0 0

2 5 126 3 0.72 17892 5000 12892 0 17892 5000 12892 0 0 0

2 5 126 4 0.72 23103 0 6990 16113 23103 0 6990 16113 8000 0

2 6 133 1 0.63 16872 2000 14872 0 16872 2000 14872 0 0 0

2 6 133 2 0.63 5451 2000 3451 0 5451 2000 3451 0 0 0

2 6 133 3 0.72 17887 5000 12887 0 17887 5000 12887 0 0 0

2 6 133 4 0.72 23065 0 6997 16068 23065 0 6997 16068 8000 0

2 7 140 1 0.63 16915 2000 14915 0 16915 2000 14915 0 0 0

2 7 140 2 0.63 5457 2000 3457 0 5457 2000 3457 0 0 0

2 7 140 3 0.72 17883 5000 12883 0 17883 5000 12883 0 0 0

2 7 140 4 0.72 23078 0 7003 16076 23078 0 7003 16076 8000 0

2 8 147 1 0.63 16952 2000 14952 0 16952 2000 14952 0 0 0

2 8 147 2 0.63 5463 2000 3463 0 5463 2000 3463 0 0 0

2 8 147 3 0.72 17882 5000 12882 0 17882 5000 12882 0 0 0

2 8 147 4 0.72 23116 0 7006 16110 23116 0 7006 16110 8000 0

2 9 154 1 0.63 16984 2000 14984 0 16984 2000 14984 0 0 0

2 9 154 2 0.63 5469 2000 3469 0 5469 2000 3469 0 0 0

2 9 154 3 0.72 17884 5000 12884 0 17884 5000 12884 0 0 0

2 9 154 4 0.72 23163 0 7007 16156 23163 0 7007 16156 8000 0

2 10 161 1 0.63 17013 2000 15013 0 17013 2000 15013 0 0 0

2 10 161 2 0.63 5476 2000 3476 0 5476 2000 3476 0 0 0

2 10 161 3 0.72 17888 5000 12888 0 17888 5000 12888 0 0 0

2 10 161 4 0.72 23224 0 7005 16219 23224 0 7005 16219 8000 0

2 11 168 1 0.63 17040 2000 15040 0 17040 2000 15040 0 0 0

2 11 168 2 0.63 5482 2000 3482 0 5482 2000 3482 0 0 0

2 11 168 3 0.72 17894 5000 12894 0 17894 5000 12894 0 0 0

2 11 168 4 0.72 23295 0 7001 16294 23295 0 7001 16294 8000 0

2 12 175 1 0.63 17065 2000 15065 0 17065 2000 15065 0 0 0

2 12 175 2 0.63 5489 2000 3489 0 5489 2000 3489 0 0 0

2 12 175 3 0.72 17902 5000 12902 0 17902 5000 12902 0 0 0

2 12 175 4 0.72 23371 0 6995 16376 23371 0 6995 16376 8000 0

2 13 182 1 0.63 17089 2000 15089 0 17089 2000 15089 0 0 0

2 13 182 2 0.63 5496 2000 3496 0 5496 2000 3496 0 0 0

2 13 182 3 0.72 17911 5000 12911 0 17911 5000 12911 0 0 0

2 13 182 4 0.72 23451 0 6988 16463 23451 0 6988 16463 8000 0

Table 4. Farm Demand and Supply (FDS.OUT), Farm Budget Output for Example Problem 1—Continued. 

[see table 3 for explanation of abbreviations]

Stress Period 2 

Example Problems 93
PER STP DAYS FID OFE TFDR-INI NR-SWDINI

(S)R-SWDINIQREQ-INI TFDR-FIN NR-SWDFIN(S)R-SWDFINQREQ-FIN Q-FIN DEFFLAG

3 1 189 1 0.70 16293 2000 5707 8586 16293 2000 5707 8586 6000 0

3 1 189 2 0.70 3913 2000 1913 0 3913 2000 1913 0 0 0

3 1 189 3 0.80 17613 5000 4348 8266 17613 5000 4348 8266 6000 0

3 1 189 4 0.80 12077 0 4076 8000 12077 0 4076 8000 8000 0

3 2 196 1 0.70 17035 2000 5707 9329 17035 2000 5707 9329 6000 0

3 2 196 2 0.70 4089 2000 2089 0 4089 2000 2089 0 0 0

3 2 196 3 0.80 17877 5000 4348 8530 17877 5000 4348 8530 6000 0

3 2 196 4 0.80 12265 0 4076 8189 12265 0 4076 8189 8000 0

3 3 203 1 0.70 17588 2000 5707 9882 17588 2000 5707 9882 6000 0

3 3 203 2 0.70 4239 2000 2239 0 4239 2000 2239 0 0 0

3 3 203 3 0.80 18088 5000 4348 8740 18088 5000 4348 8740 6000 0

3 3 203 4 0.80 12388 0 4076 8311 12388 0 4076 8311 8000 0

3 4 210 1 0.70 18014 2000 5707 10307 18014 2000 5707 10307 6000 0

3 4 210 2 0.70 4364 2000 2364 0 4364 2000 2364 0 0 0

3 4 210 3 0.80 18271 5000 4348 8923 18271 5000 4348 8923 6000 0

3 4 210 4 0.80 12468 0 4076 8392 12468 0 4076 8392 8000 0

3 5 217 1 0.70 18347 2000 5707 10640 18347 2000 5707 10640 6000 0

3 5 217 2 0.70 4467 2000 2446 21 4467 2000 2446 21 21 0

3 5 217 3 0.80 18436 5000 4348 9088 18436 5000 4348 9088 6000 0

3 5 217 4 0.80 12531 0 4076 8455 12531 0 4076 8455 8000 0

3 6 224 1 0.70 18615 2000 5707 10909 18615 2000 5707 10909 6000 0

3 6 224 2 0.70 4553 2000 2446 107 4553 2000 2446 107 107 0

3 6 224 3 0.80 18590 5000 4348 9242 18590 5000 4348 9242 6000 0

3 6 224 4 0.80 12588 0 4076 8512 12588 0 4076 8512 8000 0

3 7 232 1 0.70 18839 2000 5707 11132 18839 2000 5707 11132 6000 0

3 7 232 2 0.70 4629 2000 2446 183 4629 2000 2446 183 183 0

3 7 232 3 0.80 18736 5000 4348 9388 18736 5000 4348 9388 6000 0

3 7 232 4 0.80 12640 0 4076 8564 12640 0 4076 8564 8000 0

3 8 239 1 0.70 19029 2000 5707 11323 19029 2000 5707 11323 6000 0

3 8 239 2 0.70 4696 2000 2446 251 4696 2000 2446 251 251 0

3 8 239 3 0.80 18876 5000 4348 9528 18876 5000 4348 9528 6000 0

3 8 239 4 0.80 12688 0 4076 8612 12688 0 4076 8612 8000 0

3 9 246 1 0.70 19195 2000 5707 11488 19195 2000 5707 11488 6000 0

3 9 246 2 0.70 4762 2000 2446 316 4762 2000 2446 316 316 0

3 9 246 3 0.80 19011 5000 4348 9663 19011 5000 4348 9663 6000 0

3 9 246 4 0.80 12732 0 4076 8656 12732 0 4076 8656 8000 0

3 10 253 1 0.70 19342 2000 5707 11636 19342 2000 5707 11636 6000 0

3 10 253 2 0.70 4822 2000 2446 376 4822 2000 2446 376 376 0

3 10 253 3 0.80 19142 5000 4348 9794 19142 5000 4348 9794 6000 0

3 10 253 4 0.80 12775 0 4076 8698 12775 0 4076 8698 8000 0

3 11 260 1 0.70 19475 2000 5707 11769 19475 2000 5707 11769 6000 0

3 11 260 2 0.70 4881 2000 2446 436 4881 2000 2446 436 436 0

3 11 260 3 0.80 19269 5000 4348 9921 19269 5000 4348 9921 6000 0

3 11 260 4 0.80 12814 0 4076 8738 12814 0 4076 8738 8000 0

3 12 267 1 0.70 19597 2000 5707 11890 19597 2000 5707 11890 6000 0

3 12 267 2 0.70 4938 2000 2446 492 4938 2000 2446 492 492 0

3 12 267 3 0.80 19392 5000 4348 10044 19392 5000 4348 10044 6000 0

3 12 267 4 0.80 12852 0 4076 8776 12852 0 4076 8776 8000 0

3 13 274 1 0.70 19709 2000 5707 12003 19709 2000 5707 12003 6000 0

3 13 274 2 0.70 4993 2000 2446 547 4993 2000 2446 547 547 0

3 13 274 3 0.80 19512 5000 4348 10164 19512 5000 4348 10164 6000 0

3 13 274 4 0.80 12888 0 4076 8812 12888 0 4076 8812 8000 0

Table 4. Farm Demand and Supply (FDS.OUT), Farm Budget Output for Example Problem 1—Continued. 

[see table 3 for explanation of abbreviations]

Stress Period 3

94 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
PER STP DAYS FID OFE TFDR-INI NR-SWDINI

(S)R-SWDINIQREQ-INI TFDR-FIN NR-SWDFIN(S)R-SWDFINQREQ-FIN Q-FIN DEFFLAG

4 1 281 1 0.63 3314 2000 1314 0 3314 2000 1314 0 0 0

4 1 281 2 0.63 1107 1107 0 0 1107 1107 0 0 0 0

4 1 281 3 0.72 3420 3420 0 0 3420 3420 0 0 0 0

4 1 281 4 0.72 4331 0 2060 2271 4331 0 2060 2271 2271 0

4 2 288 1 0.63 3162 2000 1162 0 3162 2000 1162 0 0 0

4 2 288 2 0.63 1019 1019 0 0 1019 1019 0 0 0 0

4 2 288 3 0.72 3448 3448 0 0 3448 3448 0 0 0 0

4 2 288 4 0.72 4360 0 2060 2299 4360 0 2060 2299 2299 0

4 3 295 1 0.63 2990 2000 990 0 2990 2000 990 0 0 0

4 3 295 2 0.63 924 924 0 0 924 924 0 0 0 0

4 3 295 3 0.72 3462 3462 0 0 3462 3462 0 0 0 0

4 3 295 4 0.72 4376 0 2060 2315 4376 0 2060 2315 2315 0

4 4 302 1 0.63 2832 2000 832 0 2832 2000 832 0 0 0

4 4 302 2 0.63 839 839 0 0 839 839 0 0 0 0

4 4 302 3 0.72 3471 3471 0 0 3471 3471 0 0 0 0

4 4 302 4 0.72 4385 0 2060 2325 4385 0 2060 2325 2325 0

4 5 309 1 0.63 2697 2000 697 0 2697 2000 697 0 0 0

4 5 309 2 0.63 767 767 0 0 767 767 0 0 0 0

4 5 309 3 0.72 3476 3476 0 0 3476 3476 0 0 0 0

4 5 309 4 0.72 4391 0 2060 2330 4391 0 2060 2330 2330 0

4 6 316 1 0.63 2582 2000 582 0 2582 2000 582 0 0 0

4 6 316 2 0.63 707 707 0 0 707 707 0 0 0 0

4 6 316 3 0.72 3478 3478 0 0 3478 3478 0 0 0 0

4 6 316 4 0.72 4394 0 2060 2333 4394 0 2060 2333 2333 0

4 7 323 1 0.63 2486 2000 486 0 2486 2000 486 0 0 0

4 7 323 2 0.63 657 657 0 0 657 657 0 0 0 0

4 7 323 3 0.72 3479 3479 0 0 3479 3479 0 0 0 0

4 7 323 4 0.72 4395 0 2060 2335 4395 0 2060 2335 2335 0

4 8 330 1 0.63 2404 2000 404 0 2404 2000 404 0 0 0

4 8 330 2 0.63 614 614 0 0 614 614 0 0 0 0

4 8 330 3 0.72 3478 3478 0 0 3478 3478 0 0 0 0

4 8 330 4 0.72 4395 0 2060 2334 4395 0 2060 2334 2334 0

4 9 337 1 0.63 2334 2000 334 0 2334 2000 334 0 0 0

4 9 337 2 0.63 578 578 0 0 578 578 0 0 0 0

4 9 337 3 0.72 3476 3476 0 0 3476 3476 0 0 0 0

4 9 337 4 0.72 4393 0 2060 2332 4393 0 2060 2332 2332 0

4 10 344 1 0.63 2274 2000 274 0 2274 2000 274 0 0 0

4 10 344 2 0.63 546 546 0 0 546 546 0 0 0 0

4 10 344 3 0.72 3472 3472 0 0 3472 3472 0 0 0 0

4 10 344 4 0.72 4390 0 2060 2330 4390 0 2060 2330 2330 0

4 11 351 1 0.63 2222 2000 222 0 2222 2000 222 0 0 0

4 11 351 2 0.63 519 519 0 0 519 519 0 0 0 0

4 11 351 3 0.72 3468 3468 0 0 3468 3468 0 0 0 0

4 11 351 4 0.72 4386 0 2060 2326 4386 0 2060 2326 2326 0

4 12 358 1 0.63 2176 2000 176 0 2176 2000 176 0 0 0

4 12 358 2 0.63 494 494 0 0 494 494 0 0 0 0

4 12 358 3 0.72 3463 3463 0 0 3463 3463 0 0 0 0

4 12 358 4 0.72 4382 0 2060 2321 4382 0 2060 2321 2321 0

4 13 365 1 0.63 2135 2000 135 0 2135 2000 135 0 0 0

4 13 365 2 0.63 472 472 0 0 472 472 0 0 0 0

4 13 365 3 0.72 3457 3457 0 0 3457 3457 0 0 0 0

4 13 365 4 0.72 4377 0 2060 2316 4377 0 2060 2316 2316 0

Table 4. Farm Demand and Supply (FDS.OUT), Farm Budget Output for Example Problem 1—Continued. 

[see table 3 for explanation of abbreviations]

Stress Period 4

Example Problems 95
PER STP DAYS FID OFE TFDR-INI NR-SWDINI

(S)R-SWDINIQREQ-INI TFDR-FIN NR-SWDFIN(S)R-SWDFINQREQ-FIN Q-FIN DEFFLAG

1 1 7 1 0.70 0 0 0 0 0 0 0 0 0 1

1 1 7 2 0.80 0 0 0 0 0 0 0 0 0 1

1 1 7 3 0.70 0 0 0 0 0 0 0 0 0 1

1 1 7 4 0.80 0 5000 -4500 -500 0 5000 -4500 -500 -500 1

1 2 14 1 0.70 75 75 0 0 75 75 0 0 0 1

1 2 14 2 0.80 2417 0 2417 0 2417 0 2417 0 0 1

1 2 14 3 0.70 314 314 0 0 314 314 0 0 0 1

1 2 14 4 0.80 1183 5000 -3317 -500 1183 5000 -3317 -500 -500 1

1 3 21 1 0.70 92 92 0 0 92 92 0 0 0 1

1 3 21 2 0.80 2619 0 2619 0 2619 0 2619 0 0 1

1 3 21 3 0.70 382 382 0 0 382 382 0 0 0 1

1 3 21 4 0.80 1413 5000 -3087 -500 1413 5000 -3087 -500 -500 1

1 4 28 1 0.70 110 110 0 0 110 110 0 0 0 1

1 4 28 2 0.80 2883 0 2883 0 2883 0 2883 0 0 1

1 4 28 3 0.70 459 459 0 0 459 459 0 0 0 1

1 4 28 4 0.80 1701 5000 -2799 -500 1701 5000 -2799 -500 -500 1

1 5 35 1 0.70 128 128 0 0 128 128 0 0 0 1

1 5 35 2 0.80 3148 0 3148 0 3148 0 3148 0 0 1

1 5 35 3 0.70 536 536 0 0 536 536 0 0 0 1

1 5 35 4 0.80 1982 5000 -2518 -500 1982 5000 -2518 -500 -500 1

1 6 42 1 0.70 0 0 0 0 0 0 0 0 0 1

1 6 42 2 0.80 266 0 266 0 266 0 266 0 0 1

1 6 42 3 0.70 0 0 0 0 0 0 0 0 0 1

1 6 42 4 0.80 175 5000 -4325 -500 175 5000 -4325 -500 -500 1

1 7 49 1 0.70 0 0 0 0 0 0 0 0 0 1

1 7 49 2 0.80 1524 0 1524 0 1524 0 1524 0 0 1

1 7 49 3 0.70 55 55 0 0 55 55 0 0 0 1

1 7 49 4 0.80 981 5000 -3519 -500 981 5000 -3519 -500 -500 1

1 8 56 1 0.70 174 174 0 0 174 174 0 0 0 1

1 8 56 2 0.80 4045 0 4045 0 4045 0 4045 0 0 1

1 8 56 3 0.70 738 738 0 0 738 738 0 0 0 1

1 8 56 4 0.80 2806 5000 -1694 -500 2806 5000 -1694 -500 -500 1

1 9 63 1 0.70 0 0 0 0 0 0 0 0 0 1

1 9 63 2 0.80 0 0 0 0 0 0 0 0 0 1

1 9 63 3 0.70 0 0 0 0 0 0 0 0 0 1

1 9 63 4 0.80 0 5000 -4500 -500 0 5000 -4500 -500 -500 1

1 10 70 1 0.70 142 142 0 0 142 142 0 0 0 1

1 10 70 2 0.80 4761 0 4761 0 4761 0 4761 0 0 1

1 10 70 3 0.70 699 699 0 0 699 699 0 0 0 1

1 10 70 4 0.80 3188 5000 -1312 -500 3188 5000 -1312 -500 -500 1

1 11 77 1 0.70 0 0 0 0 0 0 0 0 0 1

1 11 77 2 0.80 817 0 817 0 817 0 817 0 0 1

1 11 77 3 0.70 0 0 0 0 0 0 0 0 0 1

1 11 77 4 0.80 636 5000 -3864 -500 636 5000 -3864 -500 -500 1

1 12 84 1 0.70 240 240 0 0 240 240 0 0 0 1

1 12 84 2 0.80 7287 0 7287 0 7287 0 7287 0 0 1

1 12 84 3 0.70 1280 1280 0 0 1280 1280 0 0 0 1

1 12 84 4 0.80 5104 5000 104 0 5104 5000 104 0 0 1

1 13 91 1 0.70 285 285 0 0 285 285 0 0 0 1

1 13 91 2 0.80 7844 0 7844 0 7844 0 7844 0 0 1

1 13 91 3 0.70 2063 2000 63 0 2063 2000 63 0 0 1

1 13 91 4 0.80 5733 5000 733 0 5733 5000 733 0 0 1

Table 5. Farm Demand and Supply (FDS.OUT), Farm Budget Output for Example Problem 2. 

[see table 3 for explanation of abbreviations]

Stress Period 1

96 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
PER STP DAYS FID OFE TFDR-INI NR-SWDINI

(S)R-SWDINIQREQ-INI TFDR-FIN NR-SWDFIN(S)R-SWDFINQREQ-FIN Q-FIN DEFFLAG

2 1 98 1 0.70 224 224 0 0 224 224 0 0 0 1

2 1 98 2 0.80 8272 0 8272 0 8272 0 8272 0 0 1

2 1 98 3 0.70 4686 2000 2686 0 4686 2000 2686 0 0 1

2 1 98 4 0.80 6964 5000 1964 0 6964 5000 1964 0 0 1

2 2 105 1 0.70 0 0 0 0 0 0 0 0 0 1

2 2 105 2 0.80 9330 0 9330 0 9330 0 9330 0 0 1

2 2 105 3 0.70 5509 2000 3509 0 5509 2000 3509 0 0 1

2 2 105 4 0.80 7924 5000 2924 0 7924 5000 2924 0 0 1

2 3 112 1 0.70 447 447 0 0 447 447 0 0 0 1

2 3 112 2 0.80 11329 0 11329 0 11329 0 11329 0 0 1

2 3 112 3 0.70 8914 2000 6914 0 8914 2000 6914 0 0 1

2 3 112 4 0.80 9966 5000 4966 0 9966 5000 4966 0 0 1

2 4 119 1 0.70 23 23 0 0 23 23 0 0 0 1

2 4 119 2 0.80 10421 0 10421 0 10421 0 10421 0 0 1

2 4 119 3 0.70 7071 2000 5071 0 7071 2000 5071 0 0 1

2 4 119 4 0.80 8920 5000 3920 0 8920 5000 3920 0 0 1

2 5 126 1 0.70 716 716 0 0 716 716 0 0 0 1

2 5 126 2 0.80 16355 0 16355 0 16355 0 16355 0 0 1

2 5 126 3 0.70 14738 2000 12738 0 14738 2000 12738 0 0 1

2 5 126 4 0.80 14542 5000 9542 0 14542 5000 9542 0 0 1

2 6 133 1 0.70 879 879 0 0 879 879 0 0 0 1

2 6 133 2 0.80 18547 0 18547 0 18547 0 18547 0 0 1

2 6 133 3 0.70 17250 2000 15250 0 17250 2000 15250 0 0 1

2 6 133 4 0.80 16464 5000 11464 0 16464 5000 11464 0 0 1

2 7 140 1 0.70 7341 2000 5341 0 7341 2000 5341 0 0 1

2 7 140 2 0.80 20669 0 20669 0 20669 0 20669 0 0 1

2 7 140 3 0.70 21641 2000 19641 0 21641 2000 19641 0 0 1

2 7 140 4 0.80 14358 5000 2711 6648 6159 5000 -4841 6000 6000 1

2 8 147 1 0.70 9791 2000 7791 0 9791 2000 7791 0 0 1

2 8 147 2 0.80 25800 0 25800 0 25800 0 25800 0 0 1

2 8 147 3 0.70 29096 2000 14700 12396 22700 2000 14700 6000 6000 1

2 8 147 4 0.80 18204 5000 0 13204 8364 5000 -2636 6000 6000 1

2 9 154 1 0.70 12553 2000 10553 0 12553 2000 10553 0 0 1

2 9 154 2 0.80 31844 0 31844 0 31844 0 31844 0 0 1

2 9 154 3 0.70 38841 2000 5836 31005 13836 2000 5836 6000 6000 1

2 9 154 4 0.80 23230 5000 0 18230 11000 5000 0 6000 6000 1

2 10 161 1 0.70 8068 2000 6068 0 8068 2000 6068 0 0 1

2 10 161 2 0.80 23859 0 23859 0 23859 0 23859 0 0 1

2 10 161 3 0.70 25497 2000 18256 5241 25497 2000 18256 5241 5241 1

2 10 161 4 0.80 16192 5000 0 11192 7456 5000 -3543 5999 5999 1

2 11 168 1 0.70 13909 2000 11909 0 13909 2000 11909 0 0 1

2 11 168 2 0.80 33838 0 33838 0 33838 0 33838 0 0 1

2 11 168 3 0.70 44145 2000 2369 39776 10369 2000 2369 6000 6000 1

2 11 168 4 0.80 25905 5000 0 20905 11000 5000 0 6000 6000 1

2 12 175 1 0.70 14668 2000 12668 0 14668 2000 12668 0 0 1

2 12 175 2 0.80 35306 0 35306 0 35306 0 35306 0 0 1

2 12 175 3 0.70 47659 2000 74 45585 8074 2000 74 6000 6000 1

2 12 175 4 0.80 28231 5000 0 23231 11000 5000 0 6000 6000 1

2 13 182 1 0.70 15482 2000 13482 0 15482 2000 13482 0 0 1

2 13 182 2 0.80 37122 0 34528 2594 37122 0 34528 2594 2594 1

2 13 182 3 0.70 52770 2000 0 50770 8000 2000 0 6000 6000 1

2 13 182 4 0.80 31747 5000 0 26747 11000 5000 0 6000 6000 1

Table 5. Farm Demand and Supply (FDS.OUT), Farm Budget Output for Example Problem 2—Continued. 

[see table 3 for explanation of abbreviations]

Stress Period 2

Example Problems 97
PER STP DAYS FID OFE TFDR-INI NR-SWDINI

(S)R-SWDINIQREQ-INI TFDR-FIN NR-SWDFIN(S)R-SWDFINQREQ-FIN Q-FIN DEFFLAG

3 1 189 1 0.70 8387 2000 6387 0 8387 2000 6387 0 0 1

3 1 189 2 0.80 21855 0 21855 0 21855 0 21855 0 0 1

3 1 189 3 0.70 32181 2000 19707 10474 24979 2000 16979 6000 6000 1

3 1 189 4 0.80 20472 5000 0 15472 11682 5000 682 6000 6000 1

3 2 196 1 0.70 11378 2000 9378 0 11378 2000 9378 0 0 1

3 2 196 2 0.80 26764 0 26764 0 26764 0 26764 0 0 1

3 2 196 3 0.70 47812 2000 11757 34055 19757 2000 11757 6000 6000 1

3 2 196 4 0.80 30327 5000 0 25327 11000 5000 0 6000 6000 1

3 3 203 1 0.70 3103 2000 1103 0 3103 2000 1103 0 0 1

3 3 203 2 0.80 8879 0 8879 0 8879 0 8879 0 0 1

3 3 203 3 0.70 19912 2000 17912 0 19912 2000 17912 0 0 1

3 3 203 4 0.80 15109 5000 10109 0 15109 5000 10109 0 0 1

3 4 210 1 0.70 4281 2000 2281 0 4281 2000 2281 0 0 1

3 4 210 2 0.80 10736 0 10736 0 10736 0 10736 0 0 1

3 4 210 3 0.70 26378 2000 24378 0 26378 2000 24378 0 0 1

3 4 210 4 0.80 19735 5000 10439 4296 19735 5000 10439 4296 4296 1

3 5 217 1 0.70 4061 2000 2061 0 4061 2000 2061 0 0 1

3 5 217 2 0.80 10700 0 10700 0 10700 0 10700 0 0 1

3 5 217 3 0.70 22622 2000 20622 0 22622 2000 20622 0 0 1

3 5 217 4 0.80 17582 5000 12582 0 17582 5000 12582 0 0 1

3 6 224 1 0.70 6038 2000 4038 0 6038 2000 4038 0 0 1

3 6 224 2 0.80 14570 0 14570 0 14570 0 14570 0 0 1

3 6 224 3 0.70 34144 2000 29114 3030 34144 2000 29114 3030 3030 1

3 6 224 4 0.80 25470 5000 0 20470 11000 5000 0 6000 6000 1

3 7 232 1 0.70 4783 2000 2783 0 4783 2000 2783 0 0 1

3 7 232 2 0.80 12162 0 12162 0 12162 0 12162 0 0 1

3 7 232 3 0.70 24237 2000 22237 0 24237 2000 22237 0 0 1

3 7 232 4 0.80 18267 5000 10495 2771 18267 5000 10495 2771 2771 1

3 8 239 1 0.70 5380 2000 3380 0 5380 2000 3380 0 0 1

3 8 239 2 0.80 13273 0 13273 0 13273 0 13273 0 0 1

3 8 239 3 0.70 26764 2000 24764 0 26764 2000 24764 0 0 1

3 8 239 4 0.80 20101 5000 6211 8891 14073 5000 3073 6000 6000 1

3 9 246 1 0.70 4948 2000 2948 0 4948 2000 2948 0 0 1

3 9 246 2 0.80 12172 0 12172 0 12172 0 12172 0 0 1

3 9 246 3 0.70 24049 2000 22049 0 24049 2000 22049 0 0 1

3 9 246 4 0.80 18173 5000 10427 2746 18173 5000 10427 2746 2746 1

3 10 253 1 0.70 5661 2000 3661 0 5661 2000 3661 0 0 1

3 10 253 2 0.80 13736 0 13736 0 13736 0 13736 0 0 1

3 10 253 3 0.70 26153 2000 24153 0 26153 2000 24153 0 0 1

3 10 253 4 0.80 19647 5000 5999 8648 14307 5000 3307 6000 6000 1

3 11 260 1 0.70 5901 2000 3901 0 5901 2000 3901 0 0 1

3 11 260 2 0.80 14234 0 14234 0 14234 0 14234 0 0 1

3 11 260 3 0.70 26117 2000 24117 0 26117 2000 24117 0 0 1

3 11 260 4 0.80 19548 5000 5272 9276 14573 5000 3573 6000 6000 1

3 12 267 1 0.70 4791 2000 2791 0 4791 2000 2791 0 0 1

3 12 267 2 0.80 11817 0 11817 0 11817 0 11817 0 0 1

3 12 267 3 0.70 20054 2000 18054 0 20054 2000 18054 0 0 1

3 12 267 4 0.80 15311 5000 10311 0 15311 5000 10311 0 0 1

3 13 274 1 0.70 4385 2000 2385 0 4385 2000 2385 0 0 1

3 13 274 2 0.80 10932 0 10932 0 10932 0 10932 0 0 1

3 13 274 3 0.70 17347 2000 15347 0 17347 2000 15347 0 0 1

3 13 274 4 0.80 13383 5000 8383 0 13383 5000 8383 0 0 1

Table 5. Farm Demand and Supply (FDS.OUT), Farm Budget Output for Example Problem 2—Continued. 

[see table 3 for explanation of abbreviations]

Stress Period 3

98 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
PER STP DAYS FID OFE TFDR-INI NR-SWDINI

(S)R-SWDINIQREQ-INI TFDR-FIN NR-SWDFIN(S)R-SWDFINQREQ-FIN Q-FIN DEFFLAG

4 1 281 1 0.70 4250 2000 2250 0 4250 2000 2250 0 0 1

4 1 281 2 0.80 10939 0 10939 0 10939 0 10939 0 0 1

4 1 281 3 0.70 16196 2000 14196 0 16196 2000 14196 0 0 1

4 1 281 4 0.80 12662 5000 7662 0 12662 5000 7662 0 0 1

4 2 288 1 0.70 3990 2000 1990 0 3990 2000 1990 0 0 1

4 2 288 2 0.80 10406 0 10406 0 10406 0 10406 0 0 1

4 2 288 3 0.70 14818 2000 12818 0 14818 2000 12818 0 0 1

4 2 288 4 0.80 11572 5000 6572 0 11572 5000 6572 0 0 1

4 3 295 1 0.70 0 0 0 0 0 0 0 0 0 1

4 3 295 2 0.80 0 0 0 0 0 0 0 0 0 1

4 3 295 3 0.70 0 0 0 0 0 0 0 0 0 1

4 3 295 4 0.80 0 5000 -4500 -500 0 5000 -4500 -500 -500 1

4 4 302 1 0.70 0 0 0 0 0 0 0 0 0 1

4 4 302 2 0.80 0 0 0 0 0 0 0 0 0 1

4 4 302 3 0.70 0 0 0 0 0 0 0 0 0 1

4 4 302 4 0.80 0 5000 -4500 -500 0 5000 -4500 -500 -500 1

4 5 309 1 0.70 1007 1007 0 0 1007 1007 0 0 0 1

4 5 309 2 0.80 4879 0 4879 0 4879 0 4879 0 0 1

4 5 309 3 0.70 4010 2000 2010 0 4010 2000 2010 0 0 1

4 5 309 4 0.80 4135 5000 -365 -500 4135 5000 -365 -500 -500 1

4 6 316 1 0.70 1454 1454 0 0 1454 1454 0 0 0 1

4 6 316 2 0.80 5675 0 5675 0 5675 0 5675 0 0 1

4 6 316 3 0.70 5304 2000 3304 0 5304 2000 3304 0 0 1

4 6 316 4 0.80 5078 5000 78 0 5078 5000 78 0 0 1

4 7 323 1 0.70 1467 1467 0 0 1467 1467 0 0 0 1

4 7 323 2 0.80 5534 0 5534 0 5534 0 5534 0 0 1

4 7 323 3 0.70 5265 2000 3265 0 5265 2000 3265 0 0 1

4 7 323 4 0.80 4879 5000 0 -121 4879 5000 0 -121 -121 1

4 8 330 1 0.70 1478 1478 0 0 1478 1478 0 0 0 1

4 8 330 2 0.80 5349 0 5349 0 5349 0 5349 0 0 1

4 8 330 3 0.70 5394 2000 3394 0 5394 2000 3394 0 0 1

4 8 330 4 0.80 4899 5000 0 -101 4899 5000 0 -101 -101 1

4 9 337 1 0.70 0 0 0 0 0 0 0 0 0 1

4 9 337 2 0.80 0 0 0 0 0 0 0 0 0 1

4 9 337 3 0.70 0 0 0 0 0 0 0 0 0 1

4 9 337 4 0.80 0 5000 -4500 -500 0 5000 -4500 -500 -500 1

4 10 344 1 0.70 1029 1029 0 0 1029 1029 0 0 0 1

4 10 344 2 0.80 4089 0 4089 0 4089 0 4089 0 0 1

4 10 344 3 0.70 3802 2000 1802 0 3802 2000 1802 0 0 1

4 10 344 4 0.80 3634 5000 -866 -500 3634 5000 -866 -500 -500 1

4 11 351 1 0.70 1150 1150 0 0 1150 1150 0 0 0 1

4 11 351 2 0.80 4482 0 4482 0 4482 0 4482 0 0 1

4 11 351 3 0.70 4208 2000 2208 0 4208 2000 2208 0 0 1

4 11 351 4 0.80 3980 5000 -520 -500 3980 5000 -520 -500 -500 1

4 12 358 1 0.70 967 967 0 0 967 967 0 0 0 1

4 12 358 2 0.80 3943 0 3943 0 3943 0 3943 0 0 1

4 12 358 3 0.70 3513 2000 1513 0 3513 2000 1513 0 0 1

4 12 358 4 0.80 3396 5000 -1104 -500 3396 5000 -1104 -500 -500 1

4 13 365 1 0.70 1175 1175 0 0 1175 1175 0 0 0 1

4 13 365 2 0.80 4392 0 4392 0 4392 0 4392 0 0 1

4 13 365 3 0.70 4194 2000 2194 0 4194 2000 2194 0 0 1

4 13 365 4 0.80 3868 5000 -632 -500 3868 5000 -632 -500 -500 1

Table 5. Farm Demand and Supply (FDS.OUT), Farm Budget Output for Example Problem 2—Continued. 

[see table 3 for explanation of abbreviations]

Stress Period 4

Example Problems 99
Benefits not only depend on the market price of the crop but also depend directly on the yield, or in other words on the 

actual consumptive use. Irrigation costs may be related to both the ground water or surface-water head-lift and to the irrigation 

needed, which is equal to a “residual consumptive use” that cannot be satisfied by precipitation or uptake from ground water. In 

turn, the uptake from ground water rests on the soil type, on the depth of the total root zone, on the capillary fringe, and on the 

depth to the water table.

In summary, all of the factors mentioned (in italic) play some role on the question which cell’s acreage is reduced and by 

what percentage. At this point, one could only speculate about the significance of certain factors for this hypothetical example. 

For instance, ground-water head-lift might be of importance, since the eastern parts of farm 3 and farm 4 are of lower elevation 

and, hence, are more cost-effective for ground-water pumping. Viewing the situation by crop type, the acreage of onions appears 

to be left almost within the original extent of crops, while the alfalfa acreage is reduced to zero (fig. 20). The reason for this 

outcome could be that alfalfa got penalized 100 percent during the end of stress period 2, which represents the end of the peak 

irrigation season. Although onions also experience highest consumption during the peak irrigation season, they might have taken 

up a considerable portion from a higher ground-water level. That is, the irrigation flux needed for onions might be less and, 

therefore, the irrigation costs for onions are not as high as for alfalfa. The fact that the pecan orchards of farm 3 are completely 

reduced while they are not at all retired in farm 4 might have something to do with the fact that onions in farm 3 were economically preferred over pecans, while they do not exist in farm 4.

Overall in example 2, the surface-water water-rights ranking results in farm 1 always receiving its surface-water delivery 

while the lesser ranked farms do not always receive the full surface-water deliveries (fig. 19A). Similarly, farm 2 always meets 

its TFDR but has to supplement the surface-water deliveries with ground-water pumpage for a couple of weeks in stress period 3 

during the peak demand (fig. 19B). Overall, the water-rights for surface-water deliveries require additional ground-water pumpage and additional reduction in demand to balance with reduced supplies. For example, in an attempt to supply water to farm 3, 

ground water was pumped at its maximum capacity and demand was reduced through acreage reduction in stress periods 2 and 

3 (fig. 19C). In contrast, the most junior farm, farm 4 is simulated with the largest nonrouted deliveries to sustain some farming, 

which is then supplemented with periodic surface-water deliveries when available and ground-water pumpage (fig. 19D).

100 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

1.00

0.75

0.50

0.25

0.00

No Farm Cell

Fraction of Crop Acreage

grown in each farm cell 

COLUMNS

ROWS

Farm 3

Farm 1

Farm 4 Farm 2

Alfalfa Pecans Onions

Alfalfa Pecans Onions

Figure 20

Figure 20. Spatial distribution of fractions of crop acreage for farm cells in example problem 2. 

References Cited 101
References Cited

Allen, R.G., Pereira, L.S., Raes, D., and Smith, M., 1998, Crop evapotranspiration - Guidelines for computing crop water 

requirements: Food and Agriculture Organization of the United Nations, Irrigation and Drainage Paper 56, 300 p.

Arnold, J.G., Williams, J.R., Srinivasan, R., King, K.W., and Griggs, R.H., 1994, SWAT (Soil and Water Assessment Tool) 

User’s Manual. Temple, Texas: USDA, Agricultural Research Service, Grassland, Soil, and Water Research Laboratory, http://

www.brc.tamus.edu/swat/, accessed December 13, 2005.

Brooks, R.H. and Corey, A.T., 1964, Hydraulic properties of porous media: Colorado State University, Hydrology paper 3, 

p. 22-27.

Brouwer, C., Goffeau, A., and Heibloem, M., 1985, Introduction into irrigation: Food and Agriculture Organization of the 

United Nations, Land and Water Development Division, Irrigation Water Management: Training manual No. 1, http://www.

fao.org/docrep/R4082E/R4082E00.htm, accessed September 2005.

Brouwer, C. and Heibloem, M., 1986, Irrigation water needs: Food and Agriculture Organization of the United Nations, Land 

and Water Development Division, Irrigation Water Management: Training manual No. 3, http://www.fao.org/docrep/S2022E/

S2022E00.htm, accessed September 2005.

California Department of Water Resources, 2005a, Integrated Water Flow Model (IWFM v2.3): Theoretical documentation. 

Hydrol. Development Unit, Modeling Support Branch, Bay-Delta Office, Sacramento, various pagination, http://modeling.

water.ca.gov/hydro/model/iwfm/documentation.html, last accessed December 16, 2005. , last accessed December 16, 2005.

California Department of Water Resources, 2005b, Integrated Water Flow Model (IWFM v2.3): User’s manual. Hydrol. Development Unit, Modeling Support Branch, Bay-Delta Office, Sacramento, various pagination, http://modeling.water.ca.gov/

hydro/model/iwfm/documentation.html, last accessed December 16, 2005. , last accessed December 16, 2005.

Colorado’s Decision Support Systems, 1995, http://cdss.state.co.us/develop/taskmemo/1-19/01.14-08.pdf, accessed September 

2005.

Dastane, N.G., 1978, Effective rainfall in irrigated agriculture: Food and Agriculture Organization of the United Nations, Irrigation and Drainage Paper No. 25, 61 p.

Doorenbos, J. and Kassam, A.H., 1979, Yield response to water: Irrigation and drainage: Food and Agriculture Organization of 

the United Nations, Irrigation and Drainage Paper No. 33, 193 p.

Doorenbos, J. and Pruitt, W.O., 1977, Guidelines for predicting crop water requirements: Food and Agriculture Organization of 

the United Nations, Irrigation and Drainage Paper No. 24, (revised) 144 p.

European Environment Agency, 2004, EEA multilingual environmental glossary: http://glossary.eea.eu.int/EEAGlossary/C/consumptive_use_of_water, accessed September 2005.

Feddes, R.A., Kowalik, P.J., and Zaradny, H., 1978, Field test of a modified numerical model for water uptake by root systems: 

Water Resources Research, vol. 10, no. 6, p. 1199-1206.

Gelt, J., Henderson, J., Seesholes, K., Tellman, B., and Woodard, G., 1999, Water in the Tucson Area: Seeking Sustainability

—A status report prepared by the Water Resources Research Center: College of Agriculture, The University of Arizona. Issue 

Paper No. 20, 155 p.

Halford, K.J. and Hanson, R.T., 2002, User guide for the drawdown-limited, Multi-Node Well (MNW) Package for the U.S. 

Geological Survey’s modular three-dimensional finite-difference ground-water flow model, versions MODFLOW-96 and 

MODFLOW-2000: U.S. Geological Survey Open-File Report 02-293, 33 p. (http://water.usgs.gov/pubs/of/2002/ofr02293/)

Hanson, R.T., Martin, Peter, and Koczot, K.M., 2003, Simulation of ground-water/surface-water flow in the Santa Clara-Calleguas Basin, California: U.S. Geological Survey Water-Resources Investigation Report 02-4136, 214 p. (http://water.usgs.

gov/pubs/wri/wri024136/)

102 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Harbaugh, A.W., Banta, E.R., Hill, M.C., and McDonald, M.G., 2000, MODFLOW-2000, the U.S. Geological Survey modular 

ground-water model—User guide to modularization concepts and the ground-water flow process: U.S. Geological Survey 

Open-File Report 00-92, 121 p.

Hoffman, G.J., Howell, T.A., and Solomon, K.H., eds., 1992, Management of farm irrigation systems: American Society of 

Agricultural Engineers, Monograph no. 9, 1040 p.

McCurry, G.N., 2000, Modeling the effects of climate change on the hydrology and water rights of a semi-arid irrigated 

watershed. Dissertation. University of Colorado at Boulder, 361 p.

McDonald, M.G., and Harbaugh, A.W., 1988, A modular three-dimensional finite-difference ground-water flow model: U.S. 

Geological Survey Techniques of Water Resources Investigations, Book 6, chap. A1, 586 p.

Montgomery Watson, 1993, Integrated Groundwater and Surface Water Model Documentation and User Manual, 

various pagination.

Mualem, Y., 1976, A new model for predicting the hydraulic conductivity of unsaturated porous media: Water Resources 

Research, vol. 12, no. 3, p. 513-522.

Neitsch, S.L., Arnold, J.G., Kiniry, J.R., Williams, J.R., and King, K.W., 2002, Soil and Water Assessment Tool, Theoretical 

Documentation, Version 2000, Grassland, Soil and Water Research Laboratory, USDA-ARS, Temple, Texas. Published by 

Texas Water Resources Institute, College Station, Texas: TWRI Report TR-191, http://www.brc.tamus.edu/swat/downloads/

doc/swat2000theory.pdf, accessed December 13, 2005.

New Mexico State University Climate Center, 1996, http://weather.nmsu.edu/cropinfo.htm, accessed September 2005.

Perkins, S.P., and Sophocleous, M.A., 1999a, Development of a comprehensive watershed model applied to study stream yield 

under drought conditions: Ground Water, vol. 37, no. 3, p. 418-426.

Perkins, S.P., and Sophocleous, M.A., 1999b, Documentation of a combined watershed and stream-aquifer modeling program 

based on SWAT and MODFLOW. vol. 1. User’s manual: Kansas Geological Survey, Open-File Report 99-24, 120 p. 

Prudic, D.E., Konikow, L.F., and Banta, E.A., 2004, A new Streamflow-Routing (SFR1) Package to simulate stream-aquifer 

interaction with MODFLOW-2000: U.S. Geological Survey Open-File Report 04-1042, 95 p.

Ravi, V. and Williams, J.R., 1998, Estimation of infiltration rate in the vadose zone (vol. 1): Compilation of simple mathematical 

models: U.S. Environmental Protection Agency, Subsurface Protection and Remediation Devision, National Risk 

Management Research Laboratory, Ada, Oklahoma, 74820 (EPA/600/R-97/128a), 26 pages of paginated text, 50 pages 

unpaginated appendices .

Robinson, T.W., 1958, Phreatophytes: U.S. Geological Survey Water-Supply Paper 1423, 84 p.

Sammis T.W., Mapel, C.L., Lugg, D.G., Lansford, R.R., and McGuckin, J.T., 1985, Evapotranspiration Crop Coefficients 

Predicted Using Growing Degree Days: ASAE, vol. 28, no. 3, p.773–780.

Schmid, W., 2004, A Farm Package for MODFLOW-2000: Simulation of Irrigation Demand and Conjunctively Managed 

Surface-Water and Ground-Water Supply; PhD Dissertation: Department of Hydrology and Water Resources, The University 

of Arizona, 278 p. 

Simunek, J., Sejna, M., and van Genuchten, M.Th., 1999, HYDRUS-2D/MESHGEN-2D. Simulating water flow and solute 

transport in two-dimensional variably saturated media.- Handbook, International Groundwater Modeling Center – TPS 53C, 

Version 2.0, Colorado School of Mines, 227 p.

Sophocleous, M.A., Koelliker, J.K., Govindaraju, R.S., Birdie, T., Ramireddygari, S.R., Perkins, S.P., 1999, Integrated Numerical Modeling for Basin-wide Water Management—The Case of the Rattlesnake Creek Basin in South-central Kansas: Journal 

of Hydrology, vol. 214, no. 1–4, p. 179–196.

Sophocleous, M.A., and Perkins, S.P., 2000, Methodology and application of combined watershed and ground-water models in 

Kansas: Journal of Hydrology, vol. 236, no. 3–4, p. 185–201.

References Cited 103
104 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000

U.S. Department of Agriculture Natural Resources Conserva­tion Service, 2005a, State Soil Geographic (STATSGO) Database: 

USDA Natural Resources Conservation Service, accessed September 12, 2005, at http://www.ncgc.nrcs.usda.gov/products/

datasets/statsgo/

U.S. Department of Agriculture Natural Resources Conserva­tion Service, 2005b, Soil Survey Geographic (SSURGO) Database: 

USDA Natural Resources Conservation Service, accessed September 12, 2005, at http://www.ncgc.nrcs.usda.gov/products/

datasets/ssurgo/

van Genuchten, M.Th., 1980, A closed-form equation for predicting the hydraulic conductivity of unsaturated soils: Soil Science 

Society of America Journal, vol. 44, p. 892-898.

van Genuchten, M.T., Leij, F.J., and Yates, S.R., 1991, The RETC code for quantifying the hydraulic functions of unsaturated 

soils: U.S. Environmental Protection Agency, Robert S. Kerr Environmental Research Laboratory, EPA/600/S2-9/065.

Williamson, A. K., Prudic, D. P., Swain, L.W., 1989, Ground-water Flow in the Central Valley, California: U.S.

Geological Survey Professional Paper 1401-D, 127 p. 
Appendix

Appendix 105
Appendix: Input Data for Example Problems

The test problem illustrates basic features of the Farm Process (FMP1). Details of the test problem and results are discussed 

in the section titled “Example Problem 1” and “Example Problem 2.” If data sets only are used for a particular example problem, 

they are noted as such.

Name File Input Data Sets

Example Problem 1:

list 6 ex1.lst

bcf6 9 ex1tr.bc6

bas6 10 ex1tr.ba6

dis 11 ex1tr.dis

fmp 12 example1.fmp

sfr 14 ex1tr-reuse.sfr

ghb 16 ex1tr.ghb

pcg 18 ex1.pcg

oc 19 ex1tr.oc

data 22 ex1.hed

data 20 OFE.in

data 30 ROOT.IN

data 40 CU.in

data 50 FTE.in

data 60 NRDV.in

Example Problem 2:

list 6 ex2.lst

bcf6 9 ex2tr.bc6

bas6 10 ex2tr.ba6

dis 11 ex2tr.dis

fmp 12 example2.fmp

sfr 14 ex2tr-reuse.sfr

ghb 16 ex2tr.ghb

pcg 18 ex2.pcg

oc 19 ex2tr.oc

data 22 ex2.hed

data 50 FTE.in

data 60 NRDV.in

106 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Basic (BAS) Package Input Data Set

# Example models 1 and 2

free

constant 1

-999

internal 1. (free) -1

297.99 296.88 295.76 294.64 293.52 292.40 291.27 290.16 289.04 287.94 286.84 285.76 284.69 283.64 282.60 281.57 280.56 279.57 278.58 277.61

297.99 296.88 295.76 294.64 293.52 292.39 291.27 290.14 289.03 287.92 286.83 285.74 284.67 283.62 282.58 281.56 280.55 279.55 278.57 277.60

297.99 296.88 295.77 294.64 293.51 292.38 291.25 290.12 289.00 287.89 286.79 285.71 284.63 283.58 282.54 281.52 280.51 279.52 278.54 277.57

298.00 296.88 295.76 294.63 293.50 292.36 291.22 290.09 288.96 287.84 286.74 285.65 284.58 283.52 282.49 281.47 280.46 279.47 278.49 277.52

298.00 296.89 295.77 294.63 293.49 292.34 291.19 290.04 288.90 287.77 286.66 285.57 284.49 283.44 282.41 281.39 280.40 279.41 278.43 277.47

298.01 296.90 295.77 294.63 293.47 292.31 291.14 289.98 288.82 287.68 286.55 285.46 284.38 283.34 282.31 281.30 280.31 279.33 278.36 277.40

298.03 296.91 295.78 294.63 293.46 292.28 291.10 289.91 288.72 287.56 286.42 285.31 284.24 283.21 282.19 281.19 280.21 279.24 278.28 277.32

298.05 296.94 295.80 294.64 293.46 292.26 291.05 289.82 288.60 287.40 286.24 285.13 284.07 283.05 282.05 281.07 280.10 279.13 278.18 277.23

298.09 296.97 295.83 294.66 293.47 292.25 291.00 289.73 288.46 287.21 286.01 284.88 283.86 282.87 281.89 280.92 279.97 279.02 278.07 277.13

298.14 297.03 295.89 294.71 293.50 292.26 290.97 289.64 288.30 286.97 285.69 284.52 283.60 282.66 281.72 280.77 279.83 278.89 277.96 277.03

298.21 297.10 295.96 294.79 293.57 292.30 290.98 289.63 288.26 286.90 285.57 284.25 283.38 282.46 281.54 280.61 279.68 278.76 277.85 276.93

298.29 297.19 296.07 294.90 293.69 292.39 291.03 289.63 288.21 286.81 285.43 284.05 283.19 282.28 281.36 280.44 279.52 278.63 277.73 276.83

298.38 297.30 296.20 295.07 293.87 292.54 291.11 289.64 288.15 286.68 285.27 284.04 283.04 282.10 281.17 280.26 279.35 278.49 277.63 276.75

298.30 297.20 296.07 294.92 293.71 292.42 291.07 289.70 288.31 286.95 285.65 284.44 283.36 282.33 281.34 280.35 279.33 278.53 277.67 276.78

298.22 297.11 295.98 294.81 293.61 292.36 291.06 289.75 288.45 287.16 285.91 284.73 283.61 282.53 281.50 280.48 279.46 278.62 277.75 276.84

298.15 297.04 295.90 294.74 293.55 292.32 291.06 289.80 288.55 287.32 286.11 284.94 283.80 282.70 281.63 280.59 279.63 278.75 277.84 276.93

298.10 296.99 295.85 294.70 293.52 292.32 291.10 289.87 288.66 287.46 286.27 285.12 283.99 282.90 281.84 280.81 279.83 278.89 277.95 277.02

298.06 296.95 295.82 294.67 293.51 292.32 291.13 289.93 288.74 287.57 286.40 285.26 284.15 283.06 282.00 280.98 279.98 279.01 278.06 277.12

298.04 296.92 295.79 294.65 293.50 292.33 291.16 289.98 288.81 287.65 286.51 285.38 284.28 283.19 282.14 281.11 280.10 279.12 278.15 277.20

298.02 296.90 295.78 294.64 293.50 292.34 291.18 290.02 288.87 287.72 286.59 285.47 284.37 283.29 282.24 281.21 280.20 279.20 278.23 277.27

298.00 296.89 295.77 294.63 293.49 292.35 291.20 290.05 288.91 287.77 286.64 285.53 284.44 283.36 282.31 281.28 280.26 279.27 278.29 277.32

298.00 296.88 295.76 294.63 293.49 292.35 291.21 290.07 288.93 287.80 286.68 285.57 284.48 283.41 282.35 281.32 280.30 279.31 278.33 277.36

297.99 296.88 295.76 294.63 293.49 292.36 291.22 290.08 288.94 287.81 286.70 285.59 284.50 283.43 282.38 281.34 280.33 279.33 278.34 277.38

Discretization File (DIS) Input Data Set

# Example Problem 1 transient discretization file

1 23 20 4 4 2

0

constant 500

constant 500

OPEN/CLOSE GSE.IN 1.0 (FREE) -1

constant 0

91 13 1 TR

91 13 1 TR

92 13 1 TR

91 13 1 TR

Block-Centered Flow (BCF) Package Input Data Set

-1 2222 0 0 0 0 0

1 0 UNCONFINED

constant 1.0 TRPY

constant 0.05 SF1 SPECIFIC YIELD IF TRANSIENT/UNCONFINED

constant 5. HY OF LAYER 1 

PCG2 Package Input Data Set

1000 10 1 NPCOND 1 - mod. incomplete, 2 - polynomial

Appendix: Input Data for Example Problems 107
0.008 10 1. 2 1 1 0 HCLOSE(head),RCLOSE(FLOWRATE: should be relatively higher for m3

/day)

Output Control (OC) Package Input Data Set

head print format -3

head save format (20F8.2) label

head save unit 22

period 1 step 13

print head

print budget

save head

save budget

period 2 step 13

print head

print budget

save head

save budget

period 3 step 13

print head

print budget

save head

save budget

period 4 step 13

print head

print budget

save head

save budget

Streamflow Routing (SFR1) Package Input Data Set

# Farm Process Example 1 -- SFR1 (acronyms used in explanations: GSE = Ground-surface elevation, ss = Steady-State)

88 11 0 0 86400 0.0001 -1 0 NSTRM NSS NSTRPAR NPARSEG CONST DLEAK ISTCB1 ISTCB2 

1 13 1 1 1 500 KRCH IRCH JRCH ISTRM4 ISTRM5 RCHLEN

1 13 2 1 2 500

1 13 3 1 3 500

1 12 3 2 1 500

1 11 3 2 2 500

1 10 3 2 3 500

1 9 3 2 4 500

1 8 3 2 5 500

1 7 3 2 6 500

1 6 3 2 7 500

1 5 3 2 8 500

1 4 3 2 9 500

108 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
1 3 3 2 10 500

1 3 4 2 11 500

1 3 5 2 12 500

1 3 6 2 13 500

1 3 7 2 14 500

1 3 8 2 15 500

1 3 9 2 16 500

1 3 10 2 17 500

1 3 11 2 18 500

1 3 12 2 19 500

1 4 12 2 20 500

1 5 12 2 21 500

1 6 12 2 22 500

1 7 12 2 23 500

1 8 12 2 24 500

1 9 12 2 25 500

1 10 7 3 1 500

1 10 8 3 2 500

1 10 9 3 3 500

1 10 10 3 4 500

1 10 11 3 5 500

1 10 12 4 1 500

1 11 12 4 2 500

1 12 12 4 3 500

1 13 4 5 1 500

1 13 5 5 2 500

1 14 5 6 1 500

1 15 5 6 2 500

1 16 5 6 3 500

1 17 5 6 4 500

1 18 5 6 5 500

1 19 5 6 6 500

1 20 5 6 7 500

1 20 6 6 8 500

1 20 7 6 9 500

1 20 8 6 10 500

Appendix: Input Data for Example Problems 109
1 20 9 6 11 500

1 20 10 6 12 500

1 20 11 6 13 500

1 20 12 6 14 500

1 20 13 6 15 500

1 20 14 6 16 500

1 20 15 6 17 500

1 20 16 6 18 500

1 20 17 6 19 500

1 19 17 6 20 500

1 18 17 6 21 500

1 17 17 6 22 500

1 16 7 7 1 500

1 16 8 7 2 500

1 16 9 7 3 500

1 16 10 7 4 500

1 16 11 7 5 500

1 16 12 7 6 500

1 16 13 7 7 500

1 16 14 7 8 500

1 16 15 7 9 500

1 16 16 7 10 500

1 16 17 8 1 500

1 15 17 8 2 500

1 14 17 8 3 500

1 13 6 9 1 500

1 13 7 9 2 500

1 13 8 9 3 500

1 13 9 9 4 500

1 13 10 9 5 500

1 13 11 9 6 500

1 13 12 10 1 500

1 13 13 10 2 500

1 13 14 10 3 500

1 13 15 10 4 500

1 13 16 10 5 500

1 13 17 11 1 500

1 13 18 11 2 500

1 13 19 11 3 500

1 13 20 11 4 500

11 1 0 ITMP IRDFLG IPTFLG

1 1 5 0 50000. 0. 0. 0. 0.03 NSEG ICALC OUTSEG IUPSEG FLOW RUNOFF ETSW PPTSW 

0.06 1. 298.5 30. HCOND1 THICKM1 ELEVUP WIDTH1 (DEPTH1) 

0.06 1. 295.5 30. HCOND2 THICKM2 ELEVDN WIDTH2 (DEPTH2)

2 1 4 1 0 20000. 0. 0. 0. 0.03 fifth place: IPRIOR

0.001 1. 296.55 15. GSE = 296.55 

0.001 1. 286.98 15. GSE = 286.98; ss head = 286.65

3 1 4 0 0. 0. 0. 0. 0.03

0.1 1. 291.70 10. GSE = 292.40; ss head = 291.30

0.1 1. 284.00 10. ss head = 287.65

4 1 10 0 0. 0. 0. 0. 0.03

0.1 1. 284.00 15.

0.1 1. 282.3 15. 

5 1 9 0 0. 0. 0. 0. 0.03

0.06 1. 295.5 30.

0.06 1. 293.5 30.

110 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
6 1 8 5 0 20000. 0. 0. 0. 0.03

0.001 1. 294.61 15. GSE = 294.61

0.001 1. 281.67 15. GSE = 281.67; ss head = 280.25

7 1 8 0 0. 0. 0. 0. 0.03

0.1 1. 291.50 10. GSE = 292.42; ss head = 291.26

0.1 1. 279.50 10. ss head = 281.10

8 1 11 0 0. 0. 0. 0. 0.03

0.1 1. 279.50 15.

0.1 1. 278.30 15.

9 1 10 0 0. 0. 0. 0. 0.03

0.06 1. 293.5 30.

0.06 1. 282.7 30.

10 1 11 0 0. 0. 0. 0. 0.03

0.06 1. 282.7 30.

0.06 1. 278.7 30.

11 1 0 0 0. 0. 0. 0. 0.03

0.06 1. 278.7 30.

0.06 1. 275.5 30.

-1 0 0

-1 0 0

-1 0 0

General-Head Boundary (GHB) Package Input Data Set

46 -1

46

1 1 1 320.1469851 74.4975

1 2 1 320.1469851 74.4975

1 3 1 320.146314 74.4975

1 4 1 320.1532886 74.5

1 5 1 320.1475168 74.5

1 6 1 320.1440223 74.5025

1 7 1 320.1491155 74.5075

1 8 1 320.1389113 74.5125

1 9 1 320.1368986 74.5225

1 10 1 320.1289985 74.535

1 11 1 320.1309282 74.5525

1 12 1 320.1237859 74.5725

1 13 1 320.1149688 74.595

1 14 1 320.1280925 74.575

1 15 1 320.1309382 74.555

1 16 1 320.1354436 74.5375

1 17 1 320.1313989 74.525

1 18 1 320.132737 74.515

1 19 1 320.1430734 74.51

1 20 1 320.1481793 74.505

1 21 1 320.1416107 74.5

1 22 1 320.1548993 74.5

1 23 1 320.1417501 74.4975

1 1 20 258.4039195 69.4025

1 2 20 258.4110951 69.4

1 3 20 258.4051047 69.3925

1 4 20 258.3953243 69.38

1 5 20 258.3931989 69.3675

1 6 20 258.3959625 69.35

1 7 20 258.3836088 69.33

1 8 20 258.3836991 69.3075

Appendix: Input Data for Example Problems 111
1 9 20 258.3736041 69.2825

1 10 20 258.3689164 69.2575

1 11 20 258.3723862 69.2325

1 12 20 258.3626374 69.2075

1 13 20 258.3615628 69.1875

1 14 20 258.3555474 69.195

1 15 20 258.3556769 69.21

1 16 20 258.3696418 69.2325

1 17 20 258.3712382 69.255

1 18 20 258.375918 69.28

1 19 20 258.3809524 69.3

1 20 20 258.3838601 69.3175

1 21 20 258.3864936 69.33

1 22 20 258.3917277 69.34

1 23 20 258.3893013 69.345

-1 0

-1 0

-1 0

Farm Process (FMP1) Input Data Sets

Example Problem 1:

# Farm Process: example 1 -- ZERO SCENARIO / EQUAL APPROPRIATION

PARAMETER 1 10

10 4 3 3 2 2 2 2 0 2 1 0 0 1 1 4 1 1 1 -1 -1 1

WELLS1 QMAX 1.0 8

OPEN/CLOSE WELLS.IN FREE -1

OPEN/CLOSE GSE.IN 1.0 (FREE) -1

OPEN/CLOSE FID.IN 1 (FREE) -1

OPEN/CLOSE SID.IN 1 (FREE) -1

OPEN/CLOSE SOILLIST.IN

OPEN/CLOSE CID.IN 1 (FREE) -1

OPEN/CLOSE PSI.IN

OPEN/CLOSE SRD.IN

2 1

OPEN/CLOSE WELLSNON.IN

WELLS1

EXTERNAL 20 OFE.IN

EXTERNAL 30 ROOT.IN

EXTERNAL 40 CU.IN

EXTERNAL 50 FTE.IN

CONSTANT 0.000519

EXTERNAL 60 NRDV.IN

0.2

2 1

OPEN/CLOSE WELLSNON.IN

WELLS1

EXTERNAL 20 OFE.IN

EXTERNAL 30 ROOT.IN

EXTERNAL 40 CU.IN

EXTERNAL 50 FTE.IN

CONSTANT 0.000179

EXTERNAL 60 NRDV.IN

0.3

2 1

OPEN/CLOSE WELLSNON.IN

WELLS1

112 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
EXTERNAL 20 OFE.IN

EXTERNAL 30 ROOT.IN

EXTERNAL 40 CU.IN

EXTERNAL 50 FTE.IN

CONSTANT 0.000482

EXTERNAL 60 NRDV.IN

0.1

2 1

OPEN/CLOSE WELLSNON.IN

WELLS1

EXTERNAL 20 OFE.IN

EXTERNAL 30 ROOT.IN

EXTERNAL 40 CU.IN

EXTERNAL 50 FTE.IN

CONSTANT 0.001107

EXTERNAL 60 NRDV.IN

0.05

Example Problem 2:

# Farm Process: example problem 2 -- ACREAGE-OPTIMIZATION / PRIOR APPROPRIATION

PARAMETER 1 10

10 4 3 3 3 3 3 2 1 1 1 0 1 1 1 1 1 4 0 1 3 1e-2 -1 -1 1 1 1

WELLS1 QMAX 1.0 10

OPEN/CLOSE WELLS.IN

OPEN/CLOSE GSE.IN 1.0 (FREE) -1

OPEN/CLOSE FID.IN 1 (FREE) -1

OPEN/CLOSE OFE.IN

OPEN/CLOSE SID.IN 1 (FREE) -1

OPEN/CLOSE SOILLIST.IN

OPEN/CLOSE CID.IN 1 (FREE) -1

OPEN/CLOSE INEFFSW.IN

OPEN/CLOSE PSI.IN

OPEN/CLOSE CROPLIST.IN

OPEN/CLOSE CLIMATE.IN

OPEN/CLOSE CROPBEN.IN

CONSTANT 0.1 0.04 0.08 0. 0.28 0. 0. 0.28

0 1

WELLS1

EXTERNAL 50 FTE.IN

EXTERNAL 60 NRDV.IN

0 1

WELLS1

EXTERNAL 50 FTE.IN

EXTERNAL 60 NRDV.IN

0 1

WELLS1

EXTERNAL 50 FTE.IN

EXTERNAL 60 NRDV.IN

0 1

WELLS1

EXTERNAL 50 FTE.IN

EXTERNAL 60 NRDV.IN

Farm Process (FMP1) Ancillary Input Data Sets

Example Problems 1 and 2:

Farm Wells – WELLS.IN (parameter wells for problem 1 only)

Appendix: Input Data for Example Problems 113
1 5 6 1 1 5000

1 5 9 2 2 3000

1 6 10 3 2 2000

1 7 11 4 2 1000

1 8 6 5 1 500

1 8 9 6 1 500

1 18 3 7 3 2000

1 18 19 8 4 3000

Farm Wells – WELLSNON.IN (non parameter wells for problem 1 only)

1 21 3 9 3 4000

1 21 19 10 4 5000

Farm Wells – WELLS.IN (parameter wells for problem 2 only)

1 5 6 1 3 5000

1 5 9 2 1 3000

1 6 10 3 1 2000

1 7 11 4 1 1000

1 8 6 5 3 500

1 8 9 6 3 500

1 18 3 7 4 2000

1 18 19 8 2 3000

1 21 3 9 4 4000

1 21 19 10 2 5000

Ground-Surface Elevation – GSE.IN

298.50 297.53 296.55 295.58 294.61 293.63 292.66 291.68 290.71 289.74 288.76 287.79 286.82 285.84 284.87 283.89 282.92 281.95 280.97 280.00

298.50 297.53 296.55 295.58 294.61 293.62 292.63 291.64 290.65 289.66 288.68 287.69 286.70 285.71 284.72 283.74 282.75 281.76 280.77 279.78

298.50 297.53 296.55 295.58 294.61 293.60 292.60 291.60 290.59 289.59 288.59 287.59 286.58 285.58 284.58 283.58 282.57 281.57 280.57 279.57

298.50 297.53 296.55 295.58 294.61 293.59 292.57 291.55 290.54 289.52 288.50 287.49 286.47 285.45 284.44 283.42 282.40 281.38 280.37 279.35

298.50 297.53 296.55 295.58 294.61 293.57 292.54 291.51 290.48 289.45 288.42 287.39 286.35 285.32 284.29 283.26 282.23 281.20 280.16 279.13

298.50 297.53 296.55 295.58 294.61 293.56 292.51 291.47 290.42 289.38 288.33 287.28 286.24 285.19 284.15 283.10 282.05 281.01 279.96 278.92

298.50 297.53 296.55 295.58 294.61 293.54 292.48 291.42 290.36 289.30 288.24 287.18 286.12 285.06 284.00 282.94 281.88 280.82 279.76 278.70

298.50 297.53 296.55 295.58 294.61 293.53 292.46 291.38 290.31 289.23 288.16 287.08 286.01 284.93 283.86 282.78 281.71 280.63 279.56 278.48

298.50 297.53 296.55 295.58 294.61 293.52 292.43 291.34 290.25 289.16 288.07 286.98 285.89 284.80 283.71 282.62 281.53 280.45 279.36 278.27

298.50 297.53 296.55 295.58 294.61 293.50 292.40 291.29 290.19 289.09 287.98 286.88 285.78 284.67 283.57 282.46 281.36 280.26 279.15 278.05

298.50 297.53 296.55 295.58 294.61 293.49 292.37 291.25 290.13 289.01 287.90 286.78 285.66 284.54 283.42 282.31 281.19 280.07 278.95 277.83

298.50 297.53 296.55 295.58 294.61 293.47 292.34 291.21 290.07 288.94 287.81 286.68 285.54 284.41 283.28 282.15 281.01 279.88 278.75 277.62

298.50 297.53 296.55 295.58 294.61 293.46 292.31 291.16 290.02 288.87 287.72 286.58 285.43 284.28 283.14 281.99 280.84 279.69 278.55 277.4

298.50 297.53 296.55 295.58 294.61 293.48 292.35 291.22 290.09 288.96 287.83 286.70 285.57 284.44 283.31 282.18 281.05 279.92 278.79 277.66

298.50 297.53 296.55 295.58 294.61 293.49 292.38 291.27 290.16 289.04 287.93 286.82 285.71 284.59 283.48 282.37 281.26 280.14 279.03 277.92

298.50 297.53 296.55 295.58 294.61 293.51 292.42 291.32 290.23 289.13 288.04 286.94 285.85 284.75 283.66 282.56 281.47 280.37 279.28 278.18

298.50 297.53 296.55 295.58 294.61 293.53 292.45 291.37 290.29 289.22 288.14 287.06 285.98 284.91 283.83 282.75 281.67 280.60 279.52 278.44

298.50 297.53 296.55 295.58 294.61 293.54 292.48 291.42 290.36 289.30 288.24 287.18 286.12 285.06 284.00 282.94 281.88 280.82 279.76 278.70

298.50 297.53 296.55 295.58 294.61 293.56 292.52 291.48 290.43 289.39 288.35 287.30 286.26 285.22 284.18 283.13 282.09 281.05 280.00 278.96

298.50 297.53 296.55 295.58 294.61 293.58 292.55 291.53 290.50 289.48 288.45 287.43 286.40 285.37 284.35 283.32 282.30 281.27 280.25 279.22

298.50 297.53 296.55 295.58 294.61 293.60 292.59 291.58 290.57 289.56 288.56 287.55 286.54 285.53 284.52 283.51 282.51 281.50 280.49 279.48

298.50 297.53 296.55 295.58 294.61 293.61 292.62 291.63 290.64 289.65 288.66 287.67 286.68 285.69 284.70 283.70 282.71 281.72 280.73 279.74

298.50 297.53 296.55 295.58 294.61 293.63 292.66 291.68 290.71 289.74 288.76 287.79 286.82 285.84 284.87 283.89 282.92 281.95 280.97 280.00

114 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Farm-IDs – FID.IN(problem 1 only)

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 2 2 2 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 2 2 2 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 1 2 2 2 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 3 3 3 3 3 3 4 4 4 4 4 0 0 0 0

 0 0 0 0 0 0 3 3 3 3 3 4 4 4 4 4 0 0 0 0

 0 0 0 0 0 0 3 3 3 3 3 4 4 4 4 4 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Farm-IDs – FID.IN(problem 2 only)

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 3 3 3 1 1 1 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 3 3 3 1 1 1 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 3 3 3 1 1 1 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 3 3 3 3 3 3 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 3 3 3 3 3 3 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 3 3 3 3 3 3 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 4 4 4 4 4 4 2 2 2 2 2 0 0 0 0

 0 0 0 0 0 0 4 4 4 4 4 2 2 2 2 2 0 0 0 0

 0 0 0 0 0 0 4 4 4 4 4 2 2 2 2 2 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Appendix: Input Data for Example Problems 115
Soil-IDs – SID.IN

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 1 1 1 2 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 1 1 2 2 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 1 2 2 2 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 2 2 2 2 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 1 2 2 2 2 3 3 3 3 3 3 0 0 0 0

 0 0 0 0 0 0 1 2 2 2 2 3 3 3 3 3 0 0 0 0

 0 0 0 0 0 0 1 1 2 2 2 2 3 3 3 3 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Soil-Type List – SOILLIST.IN (problem 1 only)

1 1.8 SILT

2 1.3 SANDYLOAM

3 1.5 SILTYCLAY

Soil-Type List – SOILLIST.IN (problem 2 only)

SFAC 0.5

1 3.6 SILT

2 2.6 SANDYLOAM

3 3.0 SILTYCLAY

Crop-IDs – CID.IN

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 2 2 3 3 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 2 2 3 3 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 2 2 3 3 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 2 2 3 3 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 2 2 3 3 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 1 1 2 2 3 3 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

116 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 1 1 1 1 2 2 2 2 3 3 3 0 0 0 0

 0 0 0 0 0 0 1 1 1 2 2 2 2 3 3 3 0 0 0 0

 0 0 0 0 0 0 1 1 1 2 2 2 2 3 3 3 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Unsaturated-Zone Pressure Heads – PSI.IN

 1 0.15 0.3 15. 80.

 2 0.15 0.3 5.5 80.

 3 0.15 0.3 5. 80.

Semi-Routed Deliveries – SRD.IN (problem 1 only)

1 3 5

2 0 0

3 0 0

4 0 0

Farm Irrigation Efficiency – OFE.IN (problem 1 only)

SFAC 0.7

1 0.7

2 0.7

3 0.8

4 0.8

SFAC 0.9

1 0.7

2 0.7

3 0.8

4 0.8

SFAC 1.0

1 0.7

2 0.7

3 0.8

4 0.8

SFAC 0.9

1 0.7

2 0.7

3 0.8

4 0.8

Appendix: Input Data for Example Problems 117
Farm Irrigation Efficiency – OFE.IN (problem 2 only)

1 0.7

2 0.8

3 0.7

4 0.8

Root-Zone Depths – ROOT.IN

1 1.524

2 1.219

3 0.1016

1 1.524

2 1.219

3 0.2892

1 1.524

2 1.219

3 0.4572

1 1.524

2 1.219

3 0.4572

Crop Consumptive Uses – CU.IN (problem 1 only)

SFAC 0.3048

1 0.00787

2 0.00308

3 0.00692

SFAC 0.3048

1 0.02904

2 0.01329

3 0.02533

SFAC 0.3048

1 0.02103

2 0.02966

3 0.00338

SFAC 0.3048

1 0.00220

2 0.01407

3 0.00000

118 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
Fractions of Crop Consumptive Uses as Transpiration and Evaporation – FTE.IN

1 0.4 0.6 0.5

2 0.7 0.3 0.2

3 0.5 0.5 0.5

1 0.6 0.4 0.3

2 0.8 0.2 0.1

3 0.5 0.5 0.5

1 0.8 0.2 0.1

2 0.9 0.1 0.0

3 0.5 0.5 0.5

1 0.4 0.6 0.5

2 0.7 0.3 0.2

3 0.5 0.5 0.5

Nonrouted Surface-water Deliveries – NRDV.IN (problem 1 only)

1 45500 1 0 45500 2 0 45500 3 0 45500 4 0

2 45500 4 0 45500 1 0 45500 3 0 45500 2 0

3 318500 1 0 45500 2 0 45500 3 0 45500 4 0

4 0 1 0 0 2 0 0 3 0 0 4 0

1 45500 1 0 45500 2 0 45500 3 0 45500 4 0

2 45500 4 0 45500 1 0 45500 3 0 45500 2 0

3 318500 1 0 45500 2 0 45500 3 0 45500 4 0

4 0 1 0 0 2 0 0 3 0 0 4 0

SFAC OPEN/CLOSE NRDFAC.IN

1 45500 1 0 45500 2 0 45500 3 0 45500 4 0

2 45500 4 0 45500 1 0 45500 3 0 45500 2 0

3 318500 1 0 45500 2 0 45500 3 0 45500 4 0

4 0 1 0 0 2 0 0 3 0 0 4 0

1 45500 1 0 45500 2 0 45500 3 0 45500 4 0

2 45500 4 0 45500 1 0 45500 3 0 45500 2 0

3 318500 1 0 45500 2 0 45500 3 0 45500 4 0

4 0 1 0 0 2 0 0 3 0 0 4 0

Nonrouted Surface-water Deliveries – NRDV.IN (problem 2 only)

1 45500 4 0 45500 1 0 45500 3 0 45500 2 0

2 0 1 0 0 2 0 0 3 0 0 4 0

3 45500 1 0 45500 2 0 45500 3 0 45500 4 0

4 318500 1 1 45500 2 1 45500 3 1 45500 4 2

1 45500 4 0 45500 1 0 45500 3 0 45500 2 0

2 0 1 0 0 2 0 0 3 0 0 4 0

3 45500 1 0 45500 2 0 45500 3 0 45500 4 0

4 318500 1 1 45500 2 1 45500 3 1 45500 4 2

SFAC OPEN/CLOSE NRDFAC.IN

1 45500 4 0 45500 1 0 45500 3 0 45500 2 0

2 0 1 0 0 2 0 0 3 0 0 4 0

3 45500 1 0 45500 2 0 45500 3 0 45500 4 0

4 318500 1 1 45500 2 1 45500 3 1 45500 4 2

1 45500 4 0 45500 1 0 45500 3 0 45500 2 0

2 0 1 0 0 2 0 0 3 0 0 4 0

3 45500 1 0 45500 2 0 45500 3 0 45500 4 0

4 318500 1 1 45500 2 1 45500 3 1 45500 4 2

Appendix: Input Data for Example Problems 119
Scaling for Nonrouted Surface-water Deliveries for stress period 3–NRDFAC.IN

1 1.

 2 1.010989011

 3 1.

 4 1.

 5 1.010989011

 6 1.

 7 1.

 8 1.010989011

 9 1.

10 1.

11 1.010989011

12 1.

13 1.

Additional Data Sets for Example Problem 2:

Fraction of Losses to Inefficient Surface-water Runoff–INEFFSW.IN

1 0.6 0.4

2 0.5 0.5

3 0.4 0.6

Crop List – CROPLIST.IN

 1 5 -999 999 0.405 0.0011088 -4.2444E-07 3.55752E-11 1.524 0.001166707 1.524

 2 15.55555556 -999 999 0.229 0.0015516 -2.41056E-07 -2.01787E-10 1.2192 0.000460947 1.2192

 3 4.444444444 4.444444444 21.11111111 0.522353 -0.000648 1.9764E-06 -8.748E-10 0.4572 0.000460947 0.1016

Climate Time-series Data – CLIMATE.IN

 1 16.11111111 -1.666666667 0 0.002286

 2 17.77777778 -2.222222222 0 0.00254

 3 18.33333333 1.666666667 0 0.00254

 4 14.44444444 2.222222222 0.00508 0.001016

120 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
 5 12.77777778 1.111111111 0 0.001778

 6 10 -2.222222222 0 0.002794

 7 11.11111111 -1.666666667 0 0.00254

 8 12.77777778 -3.888888889 0 0.002794

 9 15.55555556 -3.888888889 0 0.003048

 10 16.11111111 0.555555556 0 0.003048

 11 15 3.333333333 0 0.003048

 12 17.22222222 -2.777777778 0 0.003048

 13 15.55555556 -0.555555556 0 0.00254

 14 13.88888889 -1.111111111 0 0.003048

 15 14.44444444 -3.888888889 0 0.003048

 16 18.88888889 0.555555556 0 0.003302

 17 20.55555556 -0.555555556 0 0.003556

 18 20 0 0 0.003048

 19 21.66666667 -0.555555556 0 0.003556

 20 16.66666667 3.333333333 0 0.003302

 21 15 3.333333333 0 0.00254

 22 14.44444444 -0.555555556 0 0.002794

 23 16.66666667 -2.777777778 0 0.003048

 24 17.22222222 -1.666666667 0 0.003048

 25 18.33333333 1.666666667 0 0.004064

 26 18.33333333 0.555555556 0 0.00381

 27 19.44444444 -2.777777778 0 0.003302

 28 21.11111111 -1.666666667 0 0.004318

 29 19.44444444 -1.666666667 0 0.003302

 30 17.77777778 -1.111111111 0 0.004064

 31 16.11111111 -1.111111111 0 0.003302

 32 16.66666667 0 0 0.003556

 33 18.88888889 -3.333333333 0 0.003556

 34 20.55555556 0.555555556 0 0.00508

 35 13.88888889 3.888888889 0 0.003302

 36 13.33333333 1.666666667 0 0.003556

 37 16.66666667 -3.333333333 0 0.003302

 38 17.22222222 0.555555556 0 0.004064

 39 18.88888889 3.888888889 0 0.004318

 40 12.77777778 4.444444444 0.004318 0.002032

 41 14.44444444 -0.555555556 0 0.003302

 42 14.44444444 0 0 0.003556

 43 13.88888889 2.222222222 0 0.004064

 44 15.55555556 -2.222222222 0 0.003048

 45 16.66666667 5 0 0.00254

 46 10.55555556 3.888888889 0.000762 0.00127

 47 10.55555556 0.555555556 0 0.004318

 48 13.33333333 -1.666666667 0.000762 0.003302

 49 11.66666667 2.222222222 0 0.003048

 50 13.88888889 -2.222222222 0 0.003556

 51 15 1.111111111 0 0.002794

 52 15.55555556 3.333333333 0 0.00381

 53 17.77777778 3.888888889 0 0.00508

 54 21.11111111 2.777777778 0 0.004826

 55 24.44444444 2.222222222 0 0.00635

 56 12.22222222 2.777777778 0 0.004318

Appendix: Input Data for Example Problems 121
 57 12.22222222 1.111111111 0.004318 0.004572

 58 11.66666667 0 0 0.004064

 59 11.66666667 -2.777777778 0 0.004572

 60 13.88888889 -3.888888889 0 0.004572

 61 16.66666667 -1.111111111 0 0.004572

 62 22.22222222 -0.555555556 0 0.005334

 63 22.22222222 1.666666667 0.025146 0.005842

 64 21.11111111 2.777777778 0 0.00508

 65 20 8.333333333 0 0.00381

 66 11.66666667 1.666666667 0 0.004572

 67 13.88888889 -2.777777778 0 0.004064

 68 17.22222222 -2.222222222 0 0.004826

 69 17.77777778 0 0 0.00508

 70 18.88888889 0.555555556 0 0.006096

 71 17.22222222 0.555555556 0 0.004826

 72 22.22222222 2.222222222 0 0.004826

 73 23.33333333 7.222222222 0 0.004826

 74 15.55555556 5.555555556 0.006604 0.004064

 75 17.77777778 2.777777778 0 0.004318

 76 17.77777778 7.777777778 0 0.004826

 77 19.44444444 4.722222222 0.000254 0.004318

 78 17.77777778 1.666666667 0 0.005334

 79 21.11111111 2.222222222 0 0.005334

 80 22.77777778 6.666666667 0 0.005588

 81 27.22222222 5.555555556 0 0.006604

 82 27.77777778 6.666666667 0 0.006096

 83 28.88888889 6.666666667 0 0.007112

 84 28.33333333 7.222222222 0 0.006858

 85 23.33333333 7.222222222 0 0.006096

 86 17.22222222 5.555555556 0 0.005842

 87 25 3.333333333 0 0.007112

 88 20 7.222222222 0 0.006604

 89 10 3.333333333 0 0.004826

 90 17.22222222 1.111111111 0 0.005842

 91 22.22222222 ]\0 0 0.006604

 92 14.44444444 3.333333333 0.000762 0.00635

 93 21.11111111 0.555555556 0 0.006096

 94 25.55555556 2.777777778 0 0.007112

 95 23.88888889 5.555555556 0 0.006604

 96 17.77777778 7.222222222 0 0.005842

 97 17.22222222 2.777777778 0 0.00635

 98 19.44444444 2.222222222 0 0.00635

 99 23.33333333 1.666666667 0 0.00635

 100 26.66666667 4.444444444 0 0.007112

 101 29.44444444 7.222222222 0 0.00889

 102 23.33333333 10 0 0.008636

 103 23.88888889 5.555555556 0 0.007366

 104 25 5 0.003556 0.008128

 105 18.88888889 3.888888889 0 0.006858

 106 16.11111111 6.111111111 0 0.006604

 107 17.77777778 2.222222222 0 0.00635

 108 21.66666667 2.777777778 0 0.006096

 109 23.88888889 5 0 0.006858

 110 26.66666667 6.666666667 0 0.008128

 111 23.88888889 8.333333333 0 0.007366

 112 27.22222222 8.333333333 0 0.007874

122 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
 113 31.11111111 10.55555556 0 0.00762

 114 29.44444444 13.33333333 0 0.009398

 115 27.77777778 12.22222222 0 0.008382

 116 20 7.777777778 0 0.00635

 117 20 5 0 0.005334

 118 23.33333333 5.555555556 0.00381 0.007112

 119 23.88888889 10 0 0.006604

 120 27.22222222 8.333333333 0 0.007112

 121 29.44444444 9.444444444 0 0.008128

 122 30.55555556 9.444444444 0 0.007874

 123 30.55555556 8.888888889 0 0.008636

 124 30.55555556 11.11111111 0 0.00889

 125 29.44444444 10 0 0.008636

 126 27.77777778 10 0 0.008382

 127 28.88888889 8.888888889 0 0.008128

 128 23.88888889 10.55555556 0 0.008382

 129 27.77777778 7.222222222 0 0.007874

 130 31.11111111 8.888888889 0 0.00889

 131 28.88888889 10.55555556 0 0.00889

 132 29.44444444 10 0 0.008636

 133 30 10 0 0.00889

 134 26.11111111 12.22222222 0 0.00635

 135 26.66666667 7.222222222 0 0.007874

 136 33.33333333 8.333333333 0 0.008636

 137 33.33333333 17.22222222 0 0.00635

 138 35 15 0 0.00762

 139 33.88888889 16.11111111 0 0.006604

 140 34.44444444 13.33333333 0 0.00635

 141 31.66666667 18.33333333 0 0.005334

 142 30 15 0 0.007366

 143 31.11111111 13.33333333 0 0.00889

 144 31.66666667 12.22222222 0 0.008636

 145 31.66666667 16.11111111 0 0.008382

 146 32.22222222 11.66666667 0 0.008636

 147 33.33333333 12.77777778 0 0.00889

 148 35 12.77777778 0 0.008636

 149 35 12.22222222 0 0.009144

 150 34.44444444 13.33333333 0 0.008636

 151 35 13.88888889 0 0.00889

 152 37.77777778 13.88888889 0 0.009652

 153 38.33333333 15.55555556 0 0.009652

 154 36.11111111 17.22222222 0 0.01016

 155 29.44444444 16.66666667 0 0.009906

 156 31.11111111 11.66666667 0 0.009144

 157 31.11111111 10.55555556 0 0.009144

 158 33.88888889 20.55555556 0 0.01016

 159 31.11111111 13.33333333 0 0.009144

 160 30.55555556 13.88888889 0 0.006604

 161 23.88888889 12.77777778 0.007366 0.002032

 162 27.77777778 10 0 0.006858

 163 32.77777778 13.88888889 0 0.00762

 164 34.44444444 19.44444444 0 0.009906

 165 32.22222222 14.44444444 0 0.010414

 166 33.88888889 14.44444444 0 0.009144

 167 35 15.55555556 0 0.009906

 168 33.88888889 16.66666667 0 0.010668

Appendix: Input Data for Example Problems 123
 169 35.55555556 13.88888889 0 0.009398

 170 38.33333333 14.44444444 0 0.009906

 171 37.77777778 15 0 0.009652

 172 37.22222222 16.66666667 0 0.009906

 173 37.22222222 15.55555556 0 0.009652

 174 37.77777778 16.66666667 0 0.009398

 175 39.44444444 16.66666667 0 0.00889

 176 39.44444444 7.77777778 0 0.009398

 177 39.44444444 18.88888889 0 0.010414

 178 40.55555556 16.11111111 0 0.009906

 179 41.11111111 17.22222222 0 0.010414

 180 41.11111111 20 0 0.009906

 181 40.55555556 22.22222222 0.000508 0.010922

 182 40 22.77777778 0.000254 0.011176

 183 41.11111111 19.44444444 0.000254 0.00635

 184 34.44444444 20.55555556 0 0.007874

 185 35.55555556 22.22222222 0.000254 0.006858

 186 34.44444444 20.55555556 0 0.007874

 187 33.88888889 21.11111111 0 0.00762

 188 33.33333333 19.44444444 0 0.00635

 189 35 18.88888889 0.003048 0.007112

 190 33.33333333 19.44444444 0 0.006604

 191 37.22222222 21.11111111 0 0.008382

 192 39.44444444 23.88888889 0 0.00889

 193 41.66666667 24.44444444 0 0.009398

 194 40.55555556 23.88888889 0 0.010414

 195 41.11111111 22.77777778 0 0.009906

 196 38.33333333 21.11111111 0 0.009144

 197 33.88888889 22.77777778 0 0.007874

 198 34.44444444 20 0 0.004572

 199 35.55555556 20 0 0.007366

 200 36.66666667 21.11111111 0 0.00889

 201 36.11111111 21.11111111 0.01524 0.008382

 202 33.88888889 18.33333333 0 0.008128

 203 33.33333333 21.11111111 0.000508 0.00762

 204 30.55555556 20.55555556 0.002032 0.004572

 205 31.11111111 20 0 0.005842

 206 32.22222222 18.88888889 0 0.007366

 207 33.88888889 20.55555556 0.00127 0.007112

 208 32.22222222 21.66666667 0 0.004318

 209 35.55555556 22.77777778 0 0.008636

 210 36.66666667 20.55555556 0 0.007874

 211 35 21.66666667 0.00254 0.007112

 212 33.33333333 20.55555556 0 0.006858

 213 32.22222222 20.55555556 0 0.007366

 214 33.33333333 21.66666667 0 0.005588

 215 35.55555556 21.11111111 0.001524 0.00762

 216 33.88888889 18.33333333 0.005334 0.00762

 217 30 15.55555556 0 0.006858

 218 31.11111111 17.77777778 0 0.007112

 219 33.88888889 17.77777778 0 0.007874

 220 36.11111111 18.33333333 0 0.008128

 221 35 19.44444444 0 0.006604

 222 36.11111111 19.44444444 0 0.00762

 223 36.66666667 19.44444444 0 0.008636

 224 35 20 0.000762 0.007874

124 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
 225 30.55555556 18.33333333 0.008382 0.006096

 226 33.33333333 18.88888889 0 0.006858

 227 33.88888889 17.77777778 0 0.007366

 228 34.44444444 18.88888889 0 0.007874

 229 35 18.88888889 0 0.007874

 230 33.33333333 20.55555556 0 0.006858

 231 35.55555556 20.55555556 0 0.007366

 232 31.66666667 21.11111111 0 0.006604

 233 32.22222222 20.55555556 0 0.007366

 234 33.33333333 19.44444444 0 0.006858

 235 33.88888889 20 0 0.007112

 236 36.11111111 20 0 0.00762

 237 36.66666667 20 0.002794 0.00762

 238 35 20.55555556 0 0.006604

 239 34.44444444 21.66666667 0.000508 0.00635

 240 33.33333333 22.22222222 0 0.004826

 241 32.77777778 20.55555556 0 0.006096

 242 32.77777778 17.77777778 0 0.007366

 243 33.33333333 16.66666667 0 0.007112

 244 33.33333333 18.33333333 0 0.007366

 245 32.77777778 20 0 0.007366

 246 28.33333333 20 0 0.002794

 247 30 20 0.000254 0.003302

 248 33.88888889 20 0 0.007112

 249 33.88888889 17.77777778 0 0.007874

 250 33.88888889 17.77777778 0 0.007874

 251 33.88888889 16.66666667 0 0.007366

 252 33.33333333 18.33333333 0 0.007874

 253 32.77777778 19.44444444 0 0.007112

 254 33.33333333 20 0 0.007366

 255 32.22222222 16.66666667 0 0.006604

 256 36.11111111 16.11111111 0 0.006604

 257 37.77777778 21.66666667 0 0.00889

 258 34.44444444 21.66666667 0 0.008128

 259 31.11111111 20 0 0.006604

 260 31.66666667 18.88888889 0 0.00635

 26 33.33333333 17.22222222 0 0.00635

 262 35 16.66666667 0 0.00635

 263 32.22222222 18.33333333 0 0.00508

 264 33.33333333 17.77777778 0 0.005588

 265 33.33333333 15 0 0.00635

 266 33.88888889 22.77777778 0 0.007112

 267 35 17.77777778 0 0.00635

 268 33.88888889 20 0.000254 0.00635

 269 33.33333333 15.55555556 0 0.00635

 270 34.44444444 12.77777778 0 0.00635

 271 35 16.66666667 0 0.006858

 272 34.44444444 20.55555556 0 0.005842

 273 32.77777778 18.33333333 0 0.005334

 274 30 16.66666667 0 0.004318

 275 29.44444444 12.22222222 0 0.006604

 276 30 10.55555556 0 0.00635

 277 29.44444444 19.44444444 0 0.00635

 278 22.77777778 10 0 0.00635

 279 23.88888889 4.444444444 0 0.005588

 280 26.11111111 6.666666667 0 0.005842

Appendix: Input Data for Example Problems 125
 281 28.33333333 7.777777778 0 0.005588

 282 31.11111111 9.444444444 0 0.005842

 283 31.11111111 10.55555556 0 0.005842

 284 31.66666667 10 0 0.006096

 285 32.22222222 12.22222222 0 0.00635

 286 31.11111111 13.33333333 0 0.005588

 287 31.66666667 12.22222222 0 0.005588

 288 30 12.77777778 0 0.006096

 289 26.66666667 10 0 0.005842

 290 21.66666667 7.777777778 0 0.005842

 291 24.44444444 7.222222222 0.000254 0.006096

 292 23.33333333 15 0.007112 0.003556

 293 16.66666667 10.55555556 0.02286 0.000508

 294 15 10.55555556 0.003556 0.001016

 295 14.44444444 11.11111111 0.000508 0.000508

 296 17.22222222 11.11111111 0 0.001524

 297 21.66666667 13.33333333 0 0.002032

 298 27.22222222 11.66666667 0 0.004318

 299 27.22222222 16.11111111 0.000508 0.004064

 300 17.77777778 10 0.042164 0.00127

 301 22.22222222 6.111111111 0.000254 0.003302

 302 3.33333333 6.666666667 0 0.003556

 303 25.55555556 9.444444444 0.000508 0.003302

 304 18.88888889 8.333333333 0.001778 0.003302

 305 20 5 0 0.003302

 306 21.11111111 5.555555556 0 0.00381

 307 21.66666667 3.888888889 0 0.00381

 308 19.44444444 3.888888889 0 0.003302

 309 17.77777778 5 0 0.003302

 310 20.55555556 5 0 0.00381

 311 20 7.222222222 0 0.004064

 312 22.22222222 3.333333333 0 0.003556

 313 20 7.777777778 0 0.004572

 314 14.44444444 1.666666667 0 0.003556

 315 19.44444444 0 0 0.003302

 316 20.55555556 7.222222222 0.000762 0.002794

 317 19.44444444 6.111111111 0.000762 0.003048

 318 22.77777778 4.444444444 0 0.00381

 319 22.77777778 3.888888889 0 0.003556

 320 24.44444444 2.777777778 0 0.003556

 321 23.88888889 2.777777778 0 0.003556

 322 23.88888889 5.555555556 0 0.00381

 323 22.22222222 4.444444444 0 0.003556

 324 14.44444444 4.444444444 0 0.001778

 325 18.88888889 2.222222222 0 0.003556

 326 21.66666667 -1.111111111 0 0.003302

 327 23.88888889 1.111111111 0 0.003556

 328 23.33333333 3.888888889 0 0.003556

 329 23.61111111 3.611111111 0 0.003683

 330 23.88888889 3.333333333 0 0.00381

 331 23.88888889 3.333333333 0 0.003302

 332 18.88888889 4.444444444 0.004953 0.002921

 333 13.88888889 5.555555556 0.009906 0.00254

 334 17.22222222 1.666666667 0 0.002794

 335 18.88888889 2.777777778 0 0.00254

 336 13.88888889 7.222222222 0.00381 0.000508

126 User Guide for the Farm Process (FMP1) for the U.S. Geological Survey’s MODFLOW-2000
 337 15 3.888888889 0 0.002286

 338 18.88888889 3.333333333 0 0.00254

 339 19.44444444 2.222222222 0 0.003556

 340 10 1.666666667 0 0.002794

 341 8.333333333 -1.666666667 0 0.00254

 342 9.444444444 -3.333333333 0 0.00254

 343 13.33333333 -4.444444444 0 0.002794

 344 8.333333333 1.111111111 0 0.00127

 345 10.55555556 -2.777777778 0 0.002286

 346 12.22222222 -5 0 0.002286

 347 15.55555556 -3.888888889 0 0.00254

 348 15.55555556 -2.777777778 0 0.00254

 349 18.33333333 1.111111111 0 0.003556

 350 19.44444444 2.777777778 0 0.003302

 351 17.77777778 1.666666667 0 0.003048

 352 16.66666667 6.111111111 0.001016 0.002794

 353 15 2.222222222 0 0.002032

 354 20.55555556 1.111111111 0 0.00381

 355 17.22222222 1.666666667 0 0.003556

 356 7.222222222 -2.222222222 0 0.002286

 357 11.11111111 -4.444444444 0 0.001778

 358 11.11111111 -1.666666667 0 0.002032

 359 14.44444444 -3.333333333 0 0.002794

 360 15.55555556 -3.333333333 0 0.002794

 361 19.44444444 -1.111111111 0 0.003048

 362 20 -1.666666667 0 0.003048

 363 21.11111111 2.222222222 0 0.003302

 364 17.77777778 2.222222222 0 0.002032

 365 17.77777778 2.222222222 0 0.002032

Crop Benefit List – CROPBEN.IN

 1 1.2000 0 0.1

 2 0.2230 0 2.5

 3 5.0000 0 0.5

Appendix: Input Data for Example Problems 127