# Presentation: 060024

## DRAINMOD 6.0: A Field-Scale Model for Simulating Hydrology and Water Quality for Shallow Water Table Soils

**By**
**M.A. Youssef, R.W. Skaggs, G.M. Chescheir,    C. Tian, and D.M. Amatya**

## OUTLINE

**Hydrology**
**Carbon and Nitrogen Cycles**
**Model Inputs/Outputs**
**Model Testing and Applications**
**Ongoing and Future Research**

**OUTLINE**

## BACKGROUND

## Background

- The model uses the water balance approach with functional relationships to describe the main hydrologic processes and predict subsurface drainage, surface runoff, infiltration, water table depth, soil water content and evapotranspiration in response to given climatological conditions, soil and crop properties, and drainage and irrigation management.

**Background**

## Background

- Crop response to planting date delays, excessive and deficit soil-water conditions, and soil salinity has been incorporated into the model (Skaggs et al., 1982; Seymour et al., 1992; Kandil et al., 1995).
- Luo et al. (2000) modified the model for cold conditions (freezing and thawing, snow accumulation and melt); the modified model simulates heat flow using finite difference solution to the heat equation.

**Background**

## Background

- McCarthy et al. (1992) and Amatya et al. (1997) further extended the model to simulate the hydrology of drained forested lands on both the field and watershed scale.
- Kandil et al. (1995) developed a version of the model for irrigated arid land (DRAINMOD-S) that predicts soil salinity as affected by irrigation water quality and drainage system design.

**Background**

## Background

- Youssef et al. (2005) developed DRAINMOD-N II as a major extension and upgrade of the original nitrogen model. The model simulates a more complete N cycle, adds a carbon cycle, and considers a range of farming practices.

**Background**

## HYDROLOGY

## DRAINMOD performs water balance on a soil column midway between the drains using approximate methods to quantify hydrologic processes.

## Water Balance Equations

**Water Balance Equations**

- *V**a* = *D* + *ET* + *DS* - *F*

- where  *v**a* is the change in water-free pore space, cm; *D* is drainage/subirrigation, cm; *ET* is evapotranspiration, cm; *F* is infiltration, cm.

- A water balance is also conducted at the soil surface,

*P *= *F* + *S*+ *RO*

- where  *P* is precipitation, cm;  *S* is change in water volume stored on the surface, cm; and *RO* is runoff, cm.

## Hydrologic Processes

*Infiltration: *is simulated using a modified form of the Green and Ampt (1911) equation.
- Surface Drainage: is characterized by identifying a depressional storage that must be filled with water before runoff can begin.

**Hydrologic Processes**

## Hydrologic Processes

*Soil Water Distribution in the unsaturated zone: *is conducted assuming a drained-to-equilibrium profile; that is, the pressure head distribution above the water table is essentially static.

**Hydrologic Processes**

## CARBON AND NITROGEN CYCLES

## DRAINMOD-N II

**DRAINMOD-N II**

- is a field-scale, process-based model that simulates C and N dynamics in drained agricultural lands for a wide range of     soil types, climatic conditions,               and farming practices.

## Nitrogen Cycle

## Carbon Cycle

**Carbon Cycle**

## C and N Processes

- The fertilizer component of the model simulates short-term processes that follow fertilizer application, including urea hydrolysis and pH change induced by the application of                           urea and anhydrous NH3.
***DRAINMOD-N***** II** simulates the effects of tillage on C and N dynamics using a tillage intensity factor that reflects the level of soil disturbance caused by tillage operations.

**C and N Processes**

## C and N Processes

***DRAINMOD-N II*** simulates nitrification, denitrification, and urea hydrolysis using Michaelis-Menten kinetics.
- It simulates *N* mineralization/immobilization processes as a consequence of *C* cycling in the system during OC decomposition, which is assumed to follow 1st-order rate kinetics.
- The model uses an empirical approach to simulate N plant uptake during crop growing season.

**C and N Processes**

## MODEL INPUTS/OUTPUTS

## Model Inputs

- Soil Properties: hydraulic conductivity, soil water characteristic or θ = θ(h), soil texture, bulk density, soil pH.
- Crop and Management: planting and harvesting, tillage, fertilization, manure application, yield inputs, N uptake and rooting depth functions.
- C and N processes: rate coefficients for C decomposition and other N processes, rate modifiers due to environmental conditions.

**Model Inputs**

## Model Output

- Crop relative yield as affected by planting date delays, soil water related stresses, and soil salinity;
- Daily, monthly, and annual rates of simulated N processes;
- NO3-N and NHx-N concentrations in soil solution and drain flow;
- OC content of the top 20 cm soil layer.

**Model Output**

## MODEL TESTING AND APPLICATION

## Field Testing of the original version of DRAINMOD

- Results have generally shown that DRAINMOD can be used to reliably predict water table fluctuations and drainage volumes.

**Field Testing of the original version of DRAINMOD**

## Recent Field Testing and Application of DRAINMOD-N II

**Recent Field Testing and Application of DRAINMOD-N II**

| Location | Eastern North Carolina |
| --- | --- |
| No. of Years | 6 |
| Soil | Portsmouth sandy loam |
| Crop and Management | Corn-Wheat-soybean, convention tillage and no till, mineral N fertilizer |
| Drainage System | Conventional vs. Controlled drainage, spacing=23 m, depth=1.2m
 |
| Reference | Youssef et al. (2006) |

## Recent Field Testing and Application of DRAINMOD-N II

| Location | North Eastern Germany |
| --- | --- |
| No. of Years | 12 |
| Soil | Fluvi-Dystric Gleysol (FAO Classification) |
| Crop and Management | Rye grass receiving mineral N fertilizer and cattle manure |
| Drainage System | Conventional drainage, spacing=12-18 m, depth=0.95-1.3m
 |
| Reference | Bechtold et al. (2007) |

## Recent Field Testing and Application of DRAINMOD-N II

| Location | Embarras River Watershed (48,000 ha), East-Central Illinois |
| --- | --- |
| No. of Years | 10 |
| Soil | Drummer silty clay loam |
| Crop and Management | Corn-soybean rotation, corn receiving mineral N fertilizer |
| Drainage System | Conventional drainage, irregular spacing, depth=1.0-1.5m
 |
| Reference | David et al. (2008), In review |

## Recent Field Testing and Application of DRAINMOD-N II

| Location | South-eastern Sweden |
| --- | --- |
| No. of Years | 4 |
| Soil | Aquic Hapludolls, Loam Sand |
| Crop and Management | Winter wheat-sugar beet-barly-barly rotation, conventional tillage, mineral N fertilizer and pig manure |
| Drainage System | Conventional and controlled drainage, spacing=9.0m, depth=0.8-1.0m
 |
| Reference | Salazar et al. (2008), In review |

## ONGOING AND FUTURE RESEARCH

## Ongoing and future Research

-  Linking DRAINMOD-N II to DRAINMOD-Based watershed-scale models.
- Developing a more comprehensive plant component of the model.
- Extending the model to simulate the fate and transport of phosphorus, pesticides, and bacteria.

**Ongoing and future Research**

## THANK YOU!

## A quick summary of 3-PG

| Attribute | Comments |
| --- | --- |
| Model type  | Dynamic; process-based & empirical relationships, stand-level  |
| Time frame | Monthly |
| Processes | NPP, biomass allocation, water usage & soil water balance, stem mortality, litterfall & root turnover |
| Inputs | Monthly climate data, soil texture & water capacity, fertility |
| Outputs | Biomass pools, stocking, available soil water, NPP & ET, DBH & standard stand attributes, and others |
| Strengths | Fully dynamic, can be adapted for range of species, provides management-related outputs  |
| Weaknesses | Naive treatment of soil nutrition, allocation based largely on size, poor predictor of canopy development & of mortality |

## 3-PG model 

- 3-PG model

## A quick summary of PnETii

| Attribute | Comments |
| --- | --- |
| Model type  | Lump-parameter, canopy to stand-level model |
| Time frame | Monthly |
| Processes | NPP, biomass allocation, soil water balance, litterfall & root turnover |
| Inputs | Monthly climate data, soil water capacity, Lat, etc. |
| Outputs | NPP & ET, net carbon balance, NEP and drainage and yearly NPP allocated to L,R and S.   |
| Strengths | Simple and can be used in large scales. adapted for range of species |
| Weaknesses | Do not consider effect of age, nutrients status, empirical allocation function, No litterfall output. |

## Carbon cycling in PnET-ii

- N: nitrogen content in leaf               Pmax: maximum photosynthesis rate
- Pg: Gross photosynthesis rate

## A quick summary of Forest-BGC

| Attribute | Comments |
| --- | --- |
| Model type  | Process-based, biogeochemical and stand level model |
| Time frame | Daily |
| Processes | NPP, biomass allocation, soil water balance, litter fall & root turnover,  |
| Inputs | Monthly climate data, soil texture & water capacity, fertility |
| Outputs | Year litter fall and root turnover. NPP. LAI and biomass etc. |
| Strengths | More dynamic and process-based,  |
| Weaknesses | Did not consider disturbance like thinning and fertilization, the effect of age and nutrients.   |

## Slide 36

## NPP Simulation Equation

- AB1=0.03191DBH1.89823H0.89868

- AB2=1.019*EXP (Ln (DBH*2.391)-2.413)

- Equation 2

- Equation 3

- AB3=0.0194(DBH2H)0.99

- Equation 1

- (IPCC recommended)

## NPP Simulation Results

- NPP Simulation Results

## Simulation results

**3-PG **

- R=0.07(0.5), E=-0.22(0.16)

## Simulation results

**Simulation results**

- R=-0.17, E=-1.49

## Simulation results

**Forest-BGC**

- R=-0.14, E=-2.02

## Simulation results

**Simulation results**

## Simulation results

**LAI results from 3-PG**

**Simulation results**