Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Nonpoint-Source Pollution, in 

Irondequoit Creek Basin, Monroe and Ontario Counties, New York—Application of a Precipitation-Runoff Model

Coon SIR 2005-5070
Effects of Land-Use Changes and 

Stormflow-Detention Basins on Flooding 

and Nonpoint-Source Pollution, in 

Irondequoit Creek Basin, Monroe and 

Ontario Counties, New York—Application 

of a Precipitation-Runoff Model

By William F. Coon and Mark S. Johnson

In cooperation with the

Irondequoit Creek Watershed Collaborative

Scientific Investigations Report 2005-5070

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

Gale A. Norton, Secretary

U.S. Geological Survey

Charle G. Groat, Director

U.S. Geological Survey, Reston, Virginia: 2005

For sale by U.S. Geological Survey, Information Services

Box 25286, Denver Federal Center

Denver, CO 80225

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Telephone: 1-888-ASK-USGS

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Any use of trade, product, or firm names in this publication 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.
iii

Contents

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

Introduction ................................................................................................ 1

Purpose and Scope ................................................................................. 3

Previous Studies .................................................................................... 3

Study Area ................................................................................................ 4

Climate ................................................................................................ 4

Geology and Topography ........................................................................... 4

Soils ................................................................................................ 4

Land Use and Land Cover ........................................................................ 7

Hydrology .......................................................................................... 7

Surface Water ................................................................................. 7

Wetland Areas ................................................................................. 7

New York State Erie (Barge) Canal ......................................................... 7

Runoff from Rochester ........................................................................ 10

Ground Water ................................................................................. 10

Effects of Urbanization ..................................................................... 12

Stream-Water Quality .............................................................................. 12

Precipitation-Runoff Model .............................................................................. 14

Model Selection .................................................................................... 14

Model Description ................................................................................. 14

Input and Calibration Data ........................................................................ 16

Meteorological Data ........................................................................ 16

Streamflow Data .............................................................................. 16

Water-Temperature Data ..................................................................... 16

Stream-Water-Quality Data .................................................................. 18

Atmospheric-Deposition-Quality Data ...................................................... 19

Bed-Material Particle-Size Data ............................................................ 19

Basin Representation .............................................................................. 20

Hydrologic-Response Units .................................................................. 22

Pervious Land Segments (PERLNDs) ................................................ 22

Impervious Land Segments (IMPLNDs) ............................................. 24

Hydrologic Response Unit (HRU) Summary .......................................... 25

Stream Reaches .............................................................................. 25

Simulation Complexities ........................................................................... 27

Wetlands ....................................................................................... 27

Ground-Water Flow Out of the Basin ...................................................... 27

Surface-Water Losses to Fractured Bedrock ............................................. 28

Hydrologic Connections with the NYS Erie (Barge) Canal .............................. 28

Diversions from the Erie (Barge) Canal ................................................... 28

Diversions to Golf Courses in Allen Creek Subbasin .................................... 30

Ground-Water Recharge Sites ............................................................ 30

Excess Stormflow in White Brook ......................................................... 30
iv

Jefferson Road Stormwater-Management Facility ....................................... 30

Runoff from the City of Rochester ......................................................... 31

Areas of Severe Streambank Erosion ...................................................... 32

Hypothetical Stormflow-Detention Basins ................................................ 32

Model Calibration and Performance ............................................................ 32

Hydrologic Component of Model ............................................................ 32

Model Performance ..................................................................... 33

Model Sensitivity to Parameter Values ............................................. 36

Model Uncertainty ..................................................................... 36

Water-Quality Components of Model ...................................................... 42

Water Temperature ..................................................................... 42

Sediment Loads ........................................................................ 42

Nutrient Loads ........................................................................... 45

Phosphorus Constituents ......................................................... 45

Nitrogen Constituents ............................................................ 45

Model Applications ....................................................................................... 53

Land-Use Changes ................................................................................. 53

Effects on Streamflow ........................................................................ 53

Effects on Stream-Water Quality ............................................................ 53

Stormflow-Detention Basin ........................................................................ 53

Effects on Streamflow ........................................................................ 56

Effects on Stream-Water Quality ............................................................ 56

Flood-Frequency Analysis ........................................................................ 56

Summary ................................................................................................... 57

Acknowledgments ....................................................................................... 59

References ................................................................................................ 60

Appendix—Sources of Data

Geographic Information System Coverages ................................................... 67

Miscellaneous Data ................................................................................. 67

Computer Programs ................................................................................. 67

Figures

 1–5. Maps Showing—

1. Location of the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y., 

 including towns, major streams, and data-collection sites. ........................ 2

2. Generalized geologic maps of the Irondequoit Creek basin, Monroe and 

 Ontario Counties, N.Y.: (A.) Bedrock. (B.) Surficial geology. ........................ 5

3. Generalized maps of (A.) land-surface elevation and (B.) thickness of 

 unconsolidated deposits in the Irondequoit Creek basin, Monroe and 

 Ontario Counties, N.Y. .................................................................. 6

4A. Land use and land cover in the Irondequoit Creek basin, Monroe and 

 Ontario Counties, N.Y. .................................................................. 8

4B. Land use and land cover in each of seven subbasins, as percentage of total ... 9
v

5. Hydrology of the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y. ... 11

6. Graphs showing relation between cumulative precipitation and cumulative runoff 

at selected streamflow monitoring sites, Irondequoit Creek basin, Monroe and 

Ontario Counties, N.Y.: (A.) Midbasin and downstream sites showing stable 

relation between precipitation and runoff. (B.) Urbanized basin showing 

changing relation between precipitation and runoff .................................... 13

 7–9. Maps Showing—

7. Segmentation of the Irondequoit Creek basin, Monroe County, N.Y., 

 based on proximity to the National Weather Service precipitation stations, 

 the data from which were input to the Hydrological Simulation Program—

 FORTRAN model ........................................................................ 20

8. Subbasin boundaries and locations of existing or hypothetical stormflow-

 detention basins in the Irondequoit Creek basin, Monroe and Ontario 

 Counties, N.Y. .............................................................................. 21

9. Data used in development of hydrologic-response units for precipitation-

 runoff model of Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.: 

 (A.) Soil permeability. (B.) Land-surface slope. (C.) Land use and land cover. ... 23

 10–20. Graphs Showing—

10. Daily and monthly observed and simulated flows at five calibration sites in the 

 Irondequoit Creek basin, Monroe and Ontario Counties, N.Y. ..................... 39

 11. Flow-duration plots of observed and simulated flows at five calibration sites ... 41

12. Daily observed and simulated water temperatures at five calibration sites ...... 43

13. Monthly observed total suspended solids (TSS) and simulated sediment 

 loads at five calibration sites ............................................................ 46

14. Monthly observed and simulated orthophosphate loads at five calibration sites 48

15. Monthly observed and simulated total phosphorus loads at five calibration sites 49

16. Monthly observed and simulated ammonia loads at five calibration sites ...... 50

17. Monthly observed and simulated ammonia-plus-organic nitrogen loads 

 at five calibration sites .................................................................. 51

18. Monthly observed and simulated nitrate-plus-nitrite loads at five calibration 

 sites ....................................................................................... 52

 19. Effects of hypothetical land-use changes and stormflow detention on 

 streamflow in subbasin T5 of Irondequoit Creek basin, Monroe and Ontario 

 Counties, N.Y.: (A.) Flow duration. (B.) Hydrograph for storm of July 4–10, 1998 55

 20. Flood frequencies for observed and simulated annual peak flows at two 

 sites in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.: 

 (A.) Flood frequencies for observed and simulated peak discharges. 

 (B.) Changes in flood frequencies resulting from detention basins ............... 58
vi

Tables

1. Land use and land cover in the Irondequoit Creek basin, Monroe and 

Ontario Counties, N.Y., 1991–92, as calculated by two methods ........................ 10

2. Structure of Hydrological Simulation Program—FORTRAN (HSPF) for simulation 

of hydrologic and water-quality processes in the Irondequoit Creek basin, 

Monroe and Ontario Counties, N.Y. ......................................................... 15

3. Data-collection sites in the Irondequoit Creek basin, Monroe and Ontario 

Counties, N.Y. . ................................................................................. 17

4. Published estimated annual loading rates for nonpoint-source constituents, by 

land use ....................................................................................... 18

5. Percentages of residential or commercial areas assigned to pervious or 

impervious categories in the precipitation-runoff model of the Irondequoit Creek 

basin, Monroe and Ontario Counties, N.Y. ................................................ 24

6. Hydrologic-response units used in the precipitation-runoff model of the 

Irondequoit Creek basin, Monroe and Ontario Counties, N.Y. ........................... 26

7. Seepage investigation of Allen Creek subbasin, Monroe County, N.Y., 

July 3 and 6, 2001 .............................................................................. 29

8. Published removal efficiency values for selected constituents for three types 

of stormwater-detention basins. ............................................................ 31

9. Calibration criteria and errors for simulated streamflow at five streamflowmonitoring sites in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y. 34

10. Selected criteria for evaluating Hydrological Simulation Program—FORTRAN 

(HSPF) model performance .................................................................. 36

11. Model-performance statistics for simulated streamflow at five monitoring sites 

in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y. ..................... 37

12. Published model-performance results for streamflow simulated by Hydrological 

Simulation Program—FORTRAN models. ................................................... 38

13. Model-performance statistics for monthly simulated water temperature, 

sediment loads, and chemical loads at five water-quality monitoring sites in the 

Irondequoit Creek basin, Monroe and Ontario Counties, N.Y. ........................... 44

14. Observed and simulated annual loading rates for selected constituents at five 

water-quality monitoring sites in the Irondequoit Creek basin, Monroe and 

Ontario Counties, N.Y., 1991–98 ............................................................ 47

15. Changes in peak flows resulting from land-use-change and stormflow-detention 

scenarios in a subbasin of Irondequoit Creek basin, Monroe and Ontario 

Counties, N.Y. . ................................................................................. 54

16. Changes in chemical loads resulting from land-use-change and stormflowdetention scenarios in a subbasin of the Irondequoit Creek basin, Monroe and 

Ontario Counties, N.Y. . ........................................................................ 54

17. Changes in flood frequency of annual peak flows resulting from one existing and 

nine hypothetical stormflow-detention basins at two sites in the Irondequoit Creek 

basin, Monroe and Ontario Counties, N.Y. . ................................................ 59
vii

Conversion Factors, Datums, Abbreviations, and Acronyms

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

Area

acre 0.4047 hectare (ha)

square foot (ft2) 0.09290 square meter (m2)

square mile (mi2) 2.590 square kilometer (km2) 

Volume

cubic foot (ft3) 0.02832 cubic meter (m3) 

acre-foot (acre-ft) 1,233 cubic meter (m3)

Flow rate

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

Mass

ounce, avoirdupois (oz) 28.35 gram (g) 

pound, avoirdupois (lb) 0.4536 kilogram (kg) 

ton, short (2,000 lb) 0.9072 megagram (Mg) 

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

 °C=(°F-32)/1.8

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) 

or micrograms per liter (μg/L).

Vertical coordinate information is referenced to the National Geodetic Vertical Datum of 1929 

(NGVD), a geodetic datum derived from a general adjustment of the first-order level nets of both 

the United States and Canada, formerly called Sea Level Datum of 1929.

Horizontal coordinate information is referenced to the North American Datum of 1927 (NAD 27).

ACRONYMS AND ADDITIONAL ABBREVIATIONS USED IN THIS REPORT:

BMP Best-management practice

BOD Biochemical oxygen demand

DO Dissolved oxygen

ET Evapotranspiration

GIS Geographic Information System

HSPF Hydrologic Simulation Program - Fortran

HSPEXP Hydrologic Simulation Program - Fortran EXPert system

IMPLND Impervious land segment

NURP Nationwide Urban Runoff Program

NYSEBC New York State Erie (Barge) Canal

PERLND Pervious land segment

RCHRES Stream reach or reservoir

UCI User control input 

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey

Abstract

Urbanization of the 150-square-mile Irondequoit Creek 

basin in Monroe and Ontario Counties, N.Y., continues to 

spread southward and eastward from the City of Rochester, 

on the shore of Lake Ontario. Conversion of forested land to 

other uses over the past 40 years has increased to the extent 

that more than 50 percent of the basin is now developed. This 

expansion has increased flooding and impaired stream-water 

quality in the northern (downstream) half of the basin.

A precipitation-runoff model of the Irondequoit Creek 

basin was developed with the model code HSPF (Hydrological 

Simulation Program—FORTRAN) to simulate the effects of 

land-use changes and stormflow-detention basins on flooding 

and nonpoint-source pollution on the basin. Model performance was evaluated through a combination of graphical comparisons and statistical tests, and indicated “very good” agreement (mean error less than 10 percent) between observed and 

simulated daily and monthly streamflows, between observed 

and simulated monthly water temperatures, and between 

observed total suspended solids loads and simulated sediment 

loads. Agreement between monthly observed and simulated 

nutrient loads was “very good” (mean error less than 15 percent) or “good” (mean error between 15 and 25 percent).

Results of model simulations indicated that peak flows 

and loads of sediment and total phosphorus would increase in 

a rural subbasin, where 10 percent of the basin was converted 

from forest and grassland to pervious and impervious 

developed areas. Subsequent simulation of a stormflowdetention basin at the mouth of this subbasin indicated that 

peak flows and constituent loads would decrease below those 

that were generated by the land-use-change scenario, and, in 

some cases, below those that were simulated by the original 

land-use scenario. Other results from model simulations of 

peak flows over a 30-year period (1970–2000), with and 

without simulation of 50-percent flow reductions at one 

existing and nine hypothetical stormflow-detention basins, 

indicated that stormflow-detention basins would likely 

decrease peak flows 14 to 17 percent on Allen Creek and 17 to 

18 percent on Irondequoit Creek at Blossom Road.

The model is intended as a management tool that waterresource managers can use to guide decisions regarding 

future development in the basin. The model and associated 

files are designed to permit (1) creation of scenarios that 

represent planned or hypothetical development in the basin, 

and (2) assessment of the flooding and chemical loads that 

are likely to result. Instream stormflow-detention basins 

can be simulated in separate scenarios to assess their effect 

on flooding and chemical loads. This report (1) provides 

examples of how the model can be applied to address these 

issues, (2) discusses the model revisions required to simulate 

land-use changes and detention basins, and (3) describes the 

analytical steps necessary to evaluate the model results.

Introduction

Urbanization, which is partly characterized by an 

increase in impervious surfaces, decreases the rate of infiltration through the disturbance of soils (through mixing, removal, 

or replacement with fill) or through compaction (Natural 

Resources Conservation Service, 1986) and increases the rate 

at which stormwater moves from land surfaces to a drainage 

system. These changes affect the timing of peak flows from 

different parts of the basin and thereby can change the degree 

and frequency of local flooding. Urbanization also increases 

the use of fertilizer, pesticides, and herbicides that can be 

applied to and the number and quantity of airborne contaminants from industries and automobiles that can accumulate 

on the land surface and be washed into streams, ditches, and 

culverts. The net result is a substantial increase in the chemical 

loads carried by storm runoff to ground water and streams.

The Irondequoit Creek basin (fig. 1) has undergone 

rapid development during the past 40 years, and recent 

(1999) property-tax classifications indicate that more than 

50 percent of the basin is now residential, commercial, 

or industrial (B. Houston, Monroe County Department of 

Planning and Development, written commun., 1999). The 

U.S. Geological Survey (USGS), in cooperation with Monroe 

County, has monitored streamflows and stream-water quality 

Effects of Land-Use Changes and Stormflow-Detention 

Basins on Flooding and Nonpoint-Source Pollution, in 

Irondequoit Creek Basin, Monroe and Ontario Counties, 

New York—Application of a Precipitation-Runoff Model

By William F. Coon and Mark S. Johnson
Figure 1. Location of the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y., including towns, major streams, and datacollection sites.

2 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.

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at one site in the Irondequoit Creek basin since 1960, and at 

many sites since 1980. These data have documented flood 

discharges and allowed calculation of nutrient loads and 

assessment of water-quality trends in the basin (Johnston 

and Sherwood, 1996; Sherwood, 1999, 2001, and 2003; 

Coon and others, 2000; Coon, 2004). The changes in the 

hydrology and water quality of Irondequoit Creek and its 

major tributaries have prompted several measures to mitigate 

the adverse effects of urbanization. Among these measures 

are (1) a wastewater-interceptor system, which, since 1978, 

has diverted effluent from 14 wastewater-treatment facilities 

out of the basin to a tertiary-treatment plant at the north end 

of Rochester; (2) a bedrock-tunnel system that, since 1991, 

permits subsurface storage of stormwater and decreases the 

frequency of combined-sewer overflows from the City of 

Rochester into the creek; (3) local zoning and development 

ordinances, which, along with onsite controls of erosion 

and storm runoff at new developments, and expanded 

use of multipurpose stormflow-detention basins, serve to 

decrease peak streamflows and their associated chemical 

loads; (4) conversion of dry stormflow-detention basins in 

older developments to wet basins to promote the removal 

of nutrients in stormwater through increased biological 

uptake; and (5) rip-rap reinforcement of erodable banks along 

Irondequoit Creek and one of its tributaries, Allen Creek, to 

decrease sediment loads. Additionally, during 1997, Monroe 

County modified the flow patterns in the Ellison Park wetland 

at the mouth of Irondequoit Creek, and installed a flow-control 

structure to increase dispersion and detention of stormflows 

in the wetland. These measures, along with the diversion of 

wastewater out of the basin, have decreased the nutrient loads 

to Irondequoit Bay (Coon and others, 2000; Coon, 2004) and 

have improved its trophic status (C. Knauf, Monroe County 

Department of Health, written commun., 2001).

The measure that has been most widely used to decrease 

peak discharges and their associated chemical loads is the use 

of stormwater-detention basins because they are relatively 

inexpensive to construct, can fit a wide variety of sites and 

outflow requirements, can be incorporated into a proposed 

development plan, and can be constructed in flood-prone areas 

that are limited in their development potential. In addition, 

detention basins have the potential to improve stream-water 

quality. Any impoundment will do this to a degree by allowing the settling and removal of sediment, particulate constituents, organic matter, and their adherent chemical loads, but a 

detention basin that is specifically designed for water-quality 

improvement provides extended detention time, which can 

further decrease contaminant loads through biological and 

chemical processes.

Many of the mitigative steps listed above have been 

done on a site-specific or town-wide basis, but flooding and 

water-quality issues in downstream areas can rarely be solved 

without the cooperation of upstream landowners and governmental agencies. Therefore, basinwide coordination of 

efforts is needed. A basinwide precipitation-runoff model was 

envisioned as a tool to help water-resource managers to (1) 

understand the relation between development and the hydrologic and water-quality changes within the basin; (2) predict 

the probable effects of future development on peak flows and 

chemical loads; (3) analyze the potential effects of instream 

stormflow-detention basins to mitigate flooding and contamination; and (4) provide guidance as to the location and design 

of proposed detention basins.

During 2000–03, the USGS, in cooperation with the 

Irondequoit Creek Watershed Collaborative (IWC), a consortium representing the counties, towns, and municipalities 

that lie within the basin, conducted a project to (1) develop a 

precipitation-runoff model to simulate streamflows and water 

quality in the Irondequoit Creek basin; (2) use the model to 

assess the effects of (a) a hypothetical increase in urbanization 

in the basin, and (b) 10 hypothetical instream detention basins; 

and (3) instruct representatives of the IWC on the use of the 

model to create and compare results from a variety of land-use 

or detention-basin scenarios.

Purpose and Scope

This report (1) documents the development of the precipitation-runoff model and its water-quality component, and 

(2) presents examples of how the model might be used to 

assess the effects of future urbanization and instream detention basins on flooding and nonpoint-source pollution loads. 

Instruction of the IWC on scenario creation and analysis was 

provided in an earlier report by Coon (2003).

Previous Studies

The water resources of the Rochester area were 

summarized by Grossman and Yarger (1953). The hydrologic 

characteristics of the Irondequoit Creek basin were described 

by Dunn (1965) and studied extensively during 1979–81 as 

part of the Nationwide Urban Runoff Program (NURP) (U.S. 

Environmental Protection Agency, 1983; O’Brien and Gere, 

1983; Zarriello and others, 1985; Kappel and others, 1986). 

The NURP study identified the heavily developed areas of the 

basin as the major sources of chemical loads and noted that 

snowmelt and spring runoff carried a disproportionate amount 

of the annual loads. The glacial history and geohydrology 

of the basin were described by Kappel and Young (1989). 

Ground-water resources were studied by Yager and others 

(1985). Also studied were the effects of stormwater-detention 

basins on the chemical quality of runoff from a small 

residential development (Zarriello and Sherwood, 1993) and 

on peak flows and water quality of major streams (Zarriello 

and Surface, 1989; Zarriello, 1996). The hydrology and waterquality effects of the Ellison Park wetland at the mouth of 

Irondequoit Creek were documented by Coon (1997; 2004) 

and Coon and others (2000).

Introduction 3
Study Area

The Irondequoit Creek basin encompasses 151 mi2 in 

parts of eight townships and two counties, and drains into the 

southern end of Irondequoit Bay (fig. 1). Most (78 percent) 

of the basin lies in Monroe County; 22 percent is in Ontario 

County. The City of Rochester occupies 7 percent of the basin. 

Climate

Average annual precipitation (1961–90) in the Rochester 

area is 31.96 in., including an average snowfall of about 

90 in., as recorded by the National Weather Service station at 

the Greater Rochester International Airport (fig. 1; Northeast 

Regional Climate Center, 2003). Precipitation is fairly evenly 

distributed throughout the year; monthly 30-year mean quantities range from 2.08 in. for January to 3.40 in. for August. 

Spatial variation in precipitation across the study area can be 

substantial, however. Annual totals vary by an average of 

2.7 in. and by as much as 7.2 in. between the Rochester Airport, just northwest of the study area, and a National Weather 

Service station at Victor, southeast of the study area (fig. 1). 

Heavy rains fall infrequently in the Rochester area and generally are caused by (1) slowly moving thunderstorms that usually occur from May through September, (2) slowly moving 

or stalled major low-pressure systems, or (3) hurricanes and 

tropical storms that move inland (National Climatic Data Center, 1996). On average, the basin receives measurable precipitation on 159 days per year and precipitation in excess of 1 in. 

on 4 days per year. Lake Ontario affects the distribution and 

quantity of snowfall, which is substantially greater and more 

variable along the shore than inland; the lake also modifies air 

temperatures in the Rochester area and inhibits the extreme 

temperature fluctuations that are recorded further inland. Daily 

mean temperature (1961–90) ranges from 23.6 °F in January 

to 70.2 °F in July; the annual mean temperature is 47.6 °F 

(Northeast Regional Climate Center, 2003).

Geology and Topography

The basin is underlain by sedimentary rock (limestone, 

dolostone, sandstone, and shale) that dips gently to the southsouthwest (Rickard and Fisher, 1970; Kappel and Young, 

1989). The bedrock surface in the central and northern parts 

of the basin (fig. 2) contains a north-south-trending, V-shaped 

depression caused by preferential scouring of a preglacial 

river channel (Irondogenesee River) during one or more ice 

advances during the last glacial period (Young, 1983). Sandand-gravel outwash partly fills the buried preglacial Irondogenesee River valley and forms the present-day Irondogenessee aquifer (Olcott, 1995; Kappel and Young, 1989).

The bedrock is overlain by glacial deposits throughout 

most of the basin. Till is exposed at the land surface in 

44 percent of the basin. Thick till and ice-contact deposits 

are present at glacial-retreat stagnation points across the 

northern end of the basin and discontinuously across the 

southern half (fig. 2). Lacustrine deposits (sand, silt, and 

clay), which are exposed in 32 percent of the basin, are 

present where proglacial lakes once stood. Alluvium is found 

along the Irondequoit Creek channel and flood plain from its 

mouth to just north of the New York State Thruway (fig. 2). 

Irondequoit Creek incised the glacial deposits in the northern 

third of the basin; southern migration of channel incision was 

impeded by a bedrock outcrop just downstream of USGS 

streamflow-monitoring station 04232047 (fig. 1). Isostatic 

uplift of the Lake Ontario area, which has progressed at a 

faster rate at the lake’s mouth than elsewhere, caused the 

lake-surface elevation to rise to its present level, forming 

embayments at the mouths of Lake Ontario tributaries (Clark 

and Persoage, 1970; Larsen, 1985; Young, 1998), one of which 

is Irondequoit Bay and the expansive cattail marsh (Ellison 

Park wetland) at the mouth of Irondequoit Creek.

The thickness of unconsolidated deposits ranges from 0 

to more than 400 ft (fig. 3) and is greatest in the buried Irondogenesee River valley, and in topographically high areas in the 

southeastern part of the basin near the Monroe-Ontario County 

boundary and along the southern boundary of the basin in 

Ontario County. Thickness is least where bedrock is near the 

surface in the northwestern and northeastern parts of the basin. 

Basin topography is the result of glacial scouring and 

deposition followed by stream erosion of the glacial deposits. 

Land-surface elevations range from about 250 ft at the northern end of the basin to more than 1,100 ft at the southern end 

(fig. 3). The high points in the southern half of the basin correspond to thick layers of kame and lacustrine deposits. Relief 

is greatest in the south, where small headwater valleys contain 

large elevation differences, and in the north, where incised 

tributaries to Irondequoit and Allen Creeks have eroded lacustrine sand and silt deposits. 

Soils

All soils in the basin are derived from glacial deposits 

(fig. 2) and can be grouped according to the dominant parent 

material (Heffner and Goodman, 1973; Pearson and Cline, 

1958). Soils that formed on kame deposits and outwash 

sand and gravel are highly permeable and, except during 

intense rainfall, generate negligible surface runoff. Soils that 

formed on lacustrine silt and fine sand have low to moderate 

permeability; percolation can be impeded by underlying 

lenses of silt or clay (Waller and Finch, 1982). These soils 

can be prone to erosion on steep slopes, where the vegetation 

cover has been removed. In contrast, soils that developed on 

lacustrine silt and clay deposits have low permeability and are 

subject to seasonal wetness. Soils that formed on till generally 

have extremely low permeability (less than 0.6 in/h). Till 

layers impede downward percolation from overlying deposits, 

regardless of their origin, and result in saturated soil conditions 

or shallow interflow along the till surface boundary. Another 

cause of decreased permeability is land development, which 

has locally decreased the water-infiltration characteristics of 

the soil through compaction. 

4 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
Figure 2. Generalized geologic maps of the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.: (A.) Bedrock. (B.) Surficial geology.

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Study Area 5
6 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y. Figure 3. Generalized map s of (A) land-surface elevation and (B) thickness of unconsolidated deposits in the Irondequoit Creek basin, Monroe and Ontario

Counties, N.Y.

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Land Use and Land Cover

Virtually all of the Irondequoit Creek basin has been 

affected by human activity. Most of the land in the Irondequoit 

Creek and Allen Creek valleys was either cleared in the 19th 

century for farming (Hosley, 1993) or was heavily logged; 

as many as 19 saw mills were in operation along the banks 

of Irondequoit Creek during the mid-1800s (F.W. Pugsley, 

Town of Pittsford Historian, written commun., 1942). The 

large tracts of forests found in the basin today—mainly in 

steep-sloped rural areas—are second-growth forests that have 

grown since the 19th century. Urbanization increases from the 

southern part of the basin to the northwestern corner, which 

includes part of the City of Rochester (fig. 4A). 

Land use and land cover can be classified by two methods—the NLCD (National Land Cover Data) method (U.S. 

Geological Survey, 1999), which is based on 30-meter satellite 

thematic mapper data, and the PTC (property-type classification) method (New York State Office of Real Property Services, 1996), which is used by county tax offices. Both methods indicate that more than 50 percent of the basin is in some 

form of developed condition, including residential (18.8 and 

43.6 percent by NLCD and PTC, respectively), commercial, 

industrial, and transportation (5.0 and 10.2 percent by NLCD 

and PTC, respectively), agricultural (40.8 to 15.8 percent by 

NLCD and PTC, respectively), and public or recreational areas 

(8.1 to 11.8 percent by NLCD and PTC, respectively). The 

land-use and land-cover percentages obtained by both methods, and a “final” value that represents the percentages used in 

this study, are given in table 1. Discrepancies in this table are 

discussed in detail in the “Basin Representation” part of the 

“Precipitation-Runoff Model” section of this report.

The southern third of the basin is predominantly rural 

and agricultural and consists mostly of pasture, row crops, and 

forests; only a few areas in the Towns of Mendon and Victor 

are classified as residential or commercial (fig. 4A). Areas 

along the major transportation corridors have been subject to 

the pressures of development, however, and strip malls and 

business parks line most of New York State Route 96, which 

parallels Interstate Highway 490 across the basin (fig. 4A). 

Suburban development increases northward across the 

basin and occupies large parts of the Towns of Henrietta, Pittsford, Perinton, and Penfield (fig. 4A), and the area north of the 

Erie (Barge) Canal (EBC) is mostly urban. Allen Creek and 

its main tributaries—East Branch Allen Creek and Buckland 

Creek—flow through suburban areas with moderate-density 

housing and commercial services and businesses. Similarly, 

Thomas Creek flows through areas that are increasingly undergoing suburban growth. The northwestern corner of the basin 

contains the Town of Brighton and City of Rochester, which 

consist of high-density residential, commercial, and industrial 

land. Land uses and covers for major subbasins in the Irondequoit Creek basin, and changes in the land-use-land-cover 

composition of the basin from upstream rural to downstream 

developed areas are shown in figure 4B.

Hydrology

Irondequoit Creek has a total length of about 32.6 mi and 

descends 525 ft from an elevation of 770 ft (above NGVD of 

1929) at its head in Ontario County to 245 ft (mean elevation) at Irondequoit Bay. The creek flows northward down the 

approximate center of the basin with the Allen Creek subbasin 

to the west and the Thomas Creek subbasin to the east (fig. 5).

Surface Water

Allen Creek drains 20 percent of the Irondequoit Creek 

basin; of this, 8.7 percent is drained by East Branch Allen 

Creek and 3.4 percent by Buckland Creek. Thomas Creek 

drains 19 percent of the basin; of this, 9.5 percent is drained 

by its tributary, White Brook. The stream network in the basin 

is incised in glacial deposits; in only a few locations does the 

bedrock control channel shape and slope. 

Wetland Areas

Almost 7 percent of the basin area consists of wetlands, 

lakes, and ponds (fig. 5). The headwater areas contain large 

lacustrine wetlands around Mendon Ponds. Extensive emergent wetlands, the largest of which is Thousand Acre Swamp, 

are found in the northeastern part of the basin, and collectively 

cover almost 11 percent of the Thomas Creek and White 

Brook subbasins on the eastern side of the basin. Riverine 

wetlands are found along much of Irondequoit Creek in the 

southern half of the basin and along many of its tributaries, 

and an extensive palustrine marsh lies at the mouth of Irondequoit Creek in Ellison Park (fig. 5). 

New York State Erie (Barge) Canal

The Erie (Barge) Canal cuts across the basin and divides 

it into a northern section and a southern section. During the 

navigation season, generally May through November, water 

in the canal flows eastward from the at-grade confluence 

of the canal with the Genesee River toward the canalized 

Clyde River, east of the Irondequoit Creek basin. During the 

non-navigation season (December through April), a gate to 

the east of the Genesee River prevents the eastward flow of 

water, and the canal is allowed to drain to the east. The canal 

was constructed in or above the Vernon Shale Formation 

and, the southward bend in the canal in the central part of 

the basin between Pittsford and Fairport (fig. 1) follows the 

bedrock contact between the resistant Lockport dolostone and 

the relatively soft Vernon shale. (See fig. 2.) The canal was 

constructed in native material for most of its length across the 

basin, except for the Great Embankment, a 2-mi concrete-lined 

section from just east of Pittsford to Bushnell Basin (fig. 1). 

The canal crosses Irondequoit Creek along this section. 

Study Area 7
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Figure 4A. Land use and land cover in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y. 

8 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
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Figure 4B. Land use and land cover in each of seven subbasins, as percentage of total. (Locations are shown in fig. 1.)

Study Area 9
The canal complicates the hydrology of the basin in several ways. Storm runoff enters the canal from adjacent areas 

along its entire length, and also from large areas around Pittsford, Fairport, and near the junction of the town boundaries 

of Henrietta, Brighton, and Penfield (fig. 1). Presumably little 

if any ground water enters the canal, except possibly from 

adjacent areas along the sections that are at grade with the 

surrounding area and built in native materials. Ground-water 

recharge from the canal is possible along its entire length and 

through cracks or seams in the concrete-lined section. The 

interaction between surface water and ground water has not 

been studied, nor have rates of ground-water discharge or 

recharge been estimated. 

During the navigation season, canal water is diverted to 

the natural drainage system at four locations—Allen Creek, 

East Branch Allen Creek, Cartersville, and Fairport. Water 

is siphoned from the canal where it crosses Allen Creek and 

East Branch Allen Creek (sites A and B, fig. 1) for low-flow 

augmentation and golf-course water demands. Water also 

leaks around flood-control waste gates at Cartersville (east of 

Pittsford) and Fairport (sites C and D, fig. 1) and contributes to 

flows in Irondequoit and Thomas Creeks, respectively. Flows 

at these canal-diversion points are periodically measured, 

and water samples collected, by Monroe County. No leakage 

occurs at a third set of flood-control gates near the PittsfordPerinton town lines and west of Bushnell Basin (fig. 1). 

Parts of the canal can be isolated by locks and gates 

and dewatered to Irondequoit Creek or its tributaries through 

ports in the canal bottom during the navigation season, but 

dewatering is done rarely and only for maintenance purposes. 

These ports can be opened during the non-navigation season to 

permit drainage of runoff from adjacent areas and from small 

streams that flow into the canal. Leakage, seasonal drainage, 

or intentional releases from these ports are not measured. 

Runoff from Rochester

Storm runoff within the city boundaries is controlled by a 

centralized sewer system. Runoff from the western part of the 

city that lies within the Irondequoit Creek basin is routed to an 

underground bedrock-tunnel system, which permits subsurface 

storage and subsequent routing to a wastewater-treatment plant 

that discharges to Lake Ontario. Runoff from the eastern part 

of the city that lies within the Irondequoit Creek basin is discharged to Irondequoit Creek through storm sewers between 

Blossom Road and Irondequoit Bay. 

Ground Water

The Irondogenesee aquifer underlies the present-day 

Irondequoit Creek valley north of the Erie (Barge) Canal 

(Olcott, 1995) and presumably provides a ground-water 

flowpath from upgradient recharge areas in the southern part 

of the basin toward Irondequoit Creek north of East Rochester 

(Waller and Finch, 1982). The areal extent and hydraulic 

connectivity of the Irondogenesee aquifer are unknown, 

however (Kappel and Young, 1989). The aquifer probably also 

receives recharge through highly fractured near-surface bedrock, which is capable of transmitting substantial volumes of 

ground water (Yager and others, 1985), in addition to permeable deposits overlying and adjacent to the buried-valley walls. 

Table 1. Land use and land cover in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y., 1991–92, as 

calculated by two methods.

[Values are percentages of entire basin. --, category not used by this classification method]

Land use and land cover National Land Cover 

Data classification1

Property-type 

classification2

Irondequoit 

Creek model 

Forest 25.7 -- 21.5

Agriculture3 40.8 15.8 10.5

Former agriculture -- 18.6 0

Open and(or) rural grass -- -- 27.0

Urban and(or) recreational grass 8.1 -- 8.0

Public land -- 11.8 0

Residential 18.8 43.6 17.9

Commercial, industrial, transportation, or high-density residential 5.0 -- 8.3

Developed -- 10.2 0

Wetland or water 1.5 -- 6.8

1

U.S. Geological Survey, 1999.

2

Christopher Sciacca, Monroe County Planning Board, written commun., 1998.

3

“Agriculture” includes row crops, pasture, and hay for the National Land Cover Data and Property-type classifications, and only row 

crops for the Irondequoit Creek model.

10 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
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Figure 5. Hydrology of the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.

Study Area 11
Local ground-water flow generally is toward nearby 

streams, but regional movement is northward, toward Lake 

Ontario (Yager and others, 1985). Ground water generally 

follows the pattern of surface-water drainage, except where 

permeable deposits are hydraulically connected to the underlying Irondogenesee aquifer, in which case shallow ground 

water may travel vertically to deeper permeable units. The 

ground-water divide for most of the basin generally parallels 

the surface-water divide (fig. 5), except (1) along the eastern 

side of the basin, where it lies west of the surface-water divide, 

such that ground water in most of the White Brook subbasin 

and part of the Thomas Creek subbasin drains eastward, away 

from the Irondequoit Creek basin; (2) along the southwestern 

edge of the basin in the Town of Mendon, where the groundwater divide lies east of the surface-water divide and ground 

water in this area flows westward out of the basin; and (3) at 

the southern tip of the basin, where the ground-water divide 

extends south of the surface-water divide and encompasses 

an area where ground water presumably moves northward 

into the Irondequoit Creek basin (Yager and others, 1985). 

The delineated ground-water divide may change seasonally, 

depending on climatic conditions; but is considered representative of the average location of the divide in the basin. 

All assessments of ground-water movement in relation to the 

surface-water basin for purposes of model development were 

based on these conclusions.

Effects of Urbanization

The hydrologic effects of urbanization in a basin include 

changes in the relation between precipitation and runoff. Ordinarily this relation, when plotted to show cumulative runoff 

as a function of cumulative precipitation forms a straight line 

under stable precipitation-runoff conditions. This relation is 

illustrated in figure 6A, which represents a midbasin site (station 04232034 in fig. 1) whose drainage area has not undergone substantial urbanization, and a site at the downstream 

end of the basin (station 0423205010 in fig. 1), which represents a composite of all factors that can affect the hydrology 

in the basin. Both examples indicate a stable relation since the 

early 1980s. The relocation of the midbasin streamflow-monitoring site in 1991 is seen as a break in the straight-line relation; yet, the 1980s and 1990s line segments indicate generally 

stable relations. 

The plot for a third site (fig. 6B), near the downstream 

end of the heavily urbanized Allen Creek subbasin (station 

04232050 in fig. 1), covers a period twice as long as the other 

two sites and shows deviations from a stable precipitation-torunoff relation. The pre-1970 period shows a gradual increase 

in runoff relative to precipitation—a result of the increase in 

impervious area. The slope of the plot stabilizes during 1970–

79, either because the impervious area no longer increased 

during these years, or more likely runoff from new developments was controlled to maintain predevelopment levels. After 

1980, a new equilibrium condition was reached, in which 

runoff decreased in relation to precipitation. This decrease 

coincided with the construction of a wastewater-interceptor 

system in the Irondequoit Creek basin during 1978–79 and 

the subsequent routing of a small percentage of storm runoff 

out of the basin, but it, as well as the apparent stability of the 

precipitation-runoff relation shown for the downstream site in 

figure 6A, might also reflect the efforts of the towns and counties to control storm runoff in response to the findings of the 

1980–81 NURP study (U.S. Environmental Protection Agency, 

1983; O’Brien and Gere, 1983; Kappel and others, 1986).

Stream-Water Quality

The quality of stream water in the Irondequoit Creek 

basin reflects the effects of human activities, such as agriculture and urban development. The drainage area of the most 

upstream water-quality-monitoring site (Railroad Mills; station 04232034 in fig. 1) is 31 percent forest, 42 percent and 

grass and shrubs, and more than 14 percent agriculture. Data 

collected at this site during 1991–2000 indicate that this rural 

subbasin annually generates, on average, 0.37 and 5.17 lb/acre 

of total phosphorus and total nitrogen, respectively, and 

0.28 ton/acre of total suspended solids. The Allen Creek subbasin, which is 42 percent urbanized, annually generates, on 

average, 0.50 and 6.30 lb/acre of total phosphorus and total 

nitrogen, respectively, and 0.24 tons/acre of total suspended 

solids. The highest loading rates generally were in the East 

Branch Allen Creek subbasin, which represents about 

32 percent of the Allen Creek basin. On average, the East 

Branch Allen Creek subbasin generates 0.61 and 9.32 lb/acre 

of total phosphorus and total nitrogen per year, respectively. 

In addition to being the smallest monitored subbasin in the 

Irondequoit Creek basin, with the smallest potential for dilution, East Branch Allen Creek has the highest percentage of 

agricultural land (19 percent). These loading rates are biased, 

however, because they include chemical loads carried by summer low-flow diversions from the EBC. The highest measured 

annual loading rates of total phosphorus and total suspended 

solids were near the downstream end of the basin (Irondequoit 

Creek at Blossom Road; station 0423205010 in fig. 1)—

0.67 lb/acre of total phosphorus and 0.32 tons/acre of total 

suspended solids were measured. These loading rates may be 

biased to an unknown degree, however, by sediment from two 

points of severe streambank erosion less than 3 mi upstream—

one on Irondequoit Creek, and one on Allen Creek; these areas 

presumably contributed large loads of sediment (Young and 

Burton, 1993) and associated constituents during 1991–2000. 

12 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
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Figure 6. Relation between cumulative precipitation and cumulative runoff at selected streamflow monitoring sites, Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.: (A.) Midbasin and downstream 

sites showing stable relation between precipitation and runoff. (B.) Urbanized basin showing changing relation between precipitation and runoff. (Site locations are shown in fig. 1.)

Study Area 13
Precipitation-Runoff Model

A precipitation-runoff model was selected, developed 

for Irondequoit Creek basin, and calibrated and validated 

with data from five USGS streamflow- and water-qualitymonitoring sites. Meteorological data were obtained from two 

National Weather Service stations. Geographical information 

system (GIS) coverages of hydrology, geology, soils, and land 

use and land cover were analyzed to assess the hydrologic and 

water-quality characteristics of the Irondequoit Creek basin 

and were consolidated for input to the model. The basin was 

divided into 82 subbasins and, within subbasins, into land 

segments, each of which was assumed to show consistent 

hydrologic and water-quality responses to precipitation and 

other meteorological factors. Model performance was assessed 

by graphical and statistical methods, and parameter sensitivity 

and model uncertainty were analyzed.

Model Selection

The model selected for simulation of runoff and chemical 

loads in response to precipitation was the Hydrological Simulation Program—FORTRAN (version 12; Bicknell and others, 

1997), hereafter referred to as HSPF. HSPF, jointly developed 

by U.S. Environmental Protection Agency and USGS, is a 

mathematical model designed to simulate hydrologic and 

water-quality processes in natural and manmade water systems 

and is one of the most comprehensive and flexible models of 

watershed hydrology and water quality available (Donigian 

and Huber, 1991). 

HSPF has been used extensively to simulate basin hydrology (Dinicola, 1990, 1997, and 2001; Flippo and Madden, 

1994; Berris, 1995; Duncker and others, 1995; Mastin, 1996; 

Raines, 1996; Jacomino and Fields, 1997; Srinivasan and others, 1998; Duncker and Melching, 1998; and Zarriello, 1999), 

and nonpoint-source water-quality processes (Reddy and others, 1999; Bergman and Donnangelo, 2000; Martin and others, 

2001; Wicklein and Schiffer, 2002; and Senior and Koerkle, 

2003). HSPF also has been used to (1) simulate sediment 

transport (Fontaine and Jacomino, 1997) and atrazine transport 

(Laroche and others, 1996; DeGloria and others, 1999; Bergman and others, 2002); (2) estimate total maximum daily loads 

(TMDL) (Yagow and others, 2001); (3) evaluate the probable 

effects of hypothetical land-use changes (Bohman and others, 

1995; Lohani and others, 2001; Wicklein and Schiffer, 2002) 

or instream detention basins (Donigian and others 1997) on 

flooding and water-quality conditions; (4) analyze surfacewater and ground-water interactions (Zarriello and Reis, 

2000); (5) evaluate the effects of best-management practices 

on agricultural and urban nonpoint-sources of pollution 

(Donigian and Love, 2002), and the effects of wetland restoration on runoff (Jones and Winterstein, 2000). 

HSPF was selected for this study on the basis of its widespread and varied use by the scientific community, and for its 

ability to simulate (1) snowmelt processes; (2) all streamflow 

components (surface runoff, interflow, and base flow) and 

their chemical contributions; (3) individual storms at a less 

than daily time step; (4) concentrations and loads of nitrogen 

and phosphorus; and (5) the effects of land-use changes and 

stormflow-detention basins on flooding and nonpoint-source 

pollution. Interflow, in the context of HSPF, refers to shallow, 

subsurface flow, and represents a flow component that has a 

faster response than ground-water flow, but slower response 

than surface runoff. Along with pre- and post-processing 

software that have been developed to provide interactive capabilities for model-input development and manipulation, data 

storage and data analysis, and model-output analysis (Flynn 

and others, 1995; Kittle and others, 1998; Lumb and others, 

1994), an HSPF model provides a basinwide management tool 

that county and town personnel can use to help make future 

water-resource decisions.

Model Description

HSPF is a lumped-parameter, semidistributed, continuous-simulation, conceptual precipitation-runoff model 

(Duncker and Melching, 1998; Zarriello and Ries, 2000; 

Martin and others, 2001). Many model parameters are not 

physically measurable and their respective values must be 

obtained through calibration. HSPF is set up in a modular format; each module controls the simulation of specific processes 

within the model.

In HSPF, the land surface is divided into hydrologic 

response units (HRUs), and the surface-water bodies (streams 

and lakes) are divided into reaches or reservoirs (RCHRESs). 

HRUs are assumed to exhibit consistent hydrologic and waterquality responses to precipitation, potential evapotranspiration, 

and other meteorological factors on the basis of their land 

use, soil characteristics, subsurface geology, and other factors 

that control the hydrologic and water-quality processes in the 

basin. HRUs are categorized as either pervious land segments (PERLNDs) or impervious land segments (IMPLNDs). 

Hydrologic and water-quality processes that occur in these 

land segments are simulated by different sections of the HSPF 

modules, PERLND and IMPLND, respectively; those that are 

pertinent to the Irondequoit Creek model are listed in table 2. 

Overland flows, subsurface flows, and chemical loads from 

PERLNDs, and overland flows and chemical loads from 

IMPLNDs, are routed to RCHRESs (or to other PERLNDs) 

by means of linkages defined in the NETWORK module 

or jointly in the SCHEMATIC and MASS-LINK modules. 

Hydraulic and water-quality processes within a RCHRES 

are simulated by the RCHRES module (table 2); flows and 

chemical loads are routed downstream from reach to reach 

by storage-routing (kinematic-wave) methods (Bicknell and 

others, 1997). For each RCHRES, a relation between water 

depth, surface area, storage volume, and outflow (discharge) is 

defined in a user-supplied function table (FTABLE module).

Two main mechanisms of surface-runoff generation have 

been identified—infiltration excess and saturation excess. 

14 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
Infiltration-excess runoff occurs when the precipitation rate 

exceeds the soil infiltration rate, whereas saturation-excess 

runoff occurs when the soil becomes saturated and additional 

precipitation cannot infiltrate. Both mechanisms may occur 

within a basin during a storm (Wood and others, 1990). HSPF 

simulates surface runoff primarily as an infiltration-excess 

process, whereby moisture inputs (precipitation and snowmelt) 

are separated into infiltrating and noninfiltrating fractions. 

Saturation-excess overland flow can be simulated, if needed, 

through adjustment of the exponent used in the infiltration 

equation (INFEXP), as well as the infiltration-capacity index 

and soil-moisture storage parameters (Berris, 1995). These 

adjustments allow inhibition of simulated overland flow during 

dry seasons, and generation of substantial runoff during wet 

periods. A comparison of HSPF with Soil Moisture Routing 

(Frankenberger and others, 1999), a saturation-excess overland 

flow model, in the upper part of the Irondequoit Creek basin, 

found saturation-excess flow to be the major flow mechanism, 

particularly in hillslope-dominated areas where vertical percolation was retarded by bedrock or a shallow, poorly permeable 

soil layer (Johnson and others, 2003). Despite the differences 

in structure and representation of hydrologic processes, the 

two models simulated streamflow with almost equal accuracy.

HSPF permits input of precipitation and meteorological data from many sources, depending on the availability of 

data. It also allows application of atmospheric deposition to 

selected HRUs, and routing of diversions and point-source 

chemical loads to appropriate RCHRESs. Hourly or daily time 

series of data required by HSPF are stored in a Watershed 

Data Management (WDM) file and input to the model through 

the EXT SOURCES module. Output type and storage locations in the WDM are identified through the EXT TARGETS 

module. Data time series can be input directly to a WDM 

through IOWDM (U.S. Geological Survey, 1998) and ANNIE 

(Flynn and others, 1995), or can be computed and automatically stored in a WDM through ANNIE or WDMUtil (U.S. 

Environmental Protection Agency, 1999). GenScn (Kittle and 

others, 1998), a graphical user interface that has many of the 

features of ANNIE and WDMUtil, has an improved capability 

to generate and analyze model scenarios and compare model 

results. WDMUtil or GenScn can also be used to check for and 

correct missing or erroneous data.

Table 2. Structure of Hydrological Simulation Program—FORTRAN (HSPF) for simulation of hydrologic and 

water-quality processes in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.

Model Section Process simulated by HSPF

PERLND Module for simulating processes of a pervious land segment

PWATER Water budget (overland and subsurface flows)

SNOW Accumulation and melting of snow and ice

SEDMNT Production and removal of sediment

PSTEMP Soil temperatures

PWTGAS Water temperature and dissolved-gas concentrations in overland flow, interflow, and ground water

PQUAL Generation of chemical constituents 

IMPLND Module for simulating processes of an impervious land segment

IWATER Water budget (overland flow)

SNOW Accumulation and melting of snow and ice

SOLIDS Accumulation and removal of solids

IWTGAS Water temperature and dissolved-gas concentrations

IQUAL Generation of chemical constituents 

RCHRES Module for simulating processes of a reach or reservoir

HYDR Hydraulic behavior

HTRCH Heat exchange with atmosphere and bed, and water temperature.

SEDTRN Behavior of inorganic sediment

RQUAL

OXRX

NUTRX

PLANK

Constituents involved in biochemical transformations

Dissolved oxygen and biochemical oxygen demand 

Inorganic nitrogen and phosphorus balances

Plankton populations (organic nitrogen, phosphorus, and carbon) 

SPEC-ACTIONS Module for simulating unique or variable conditions

BMPRAC Decrease in chemical-load resulting from best-management practice

Precipitation-Runoff Model 15
Input and Calibration Data

Simulation of streamflow by HSPF requires hourly or 

daily records of precipitation and potential evapotranspiration; 

simulation of snowmelt processes requires additional records 

of air and dewpoint temperatures, wind speed, and solar radiation. Information on diversions into and out of a basin, and 

their estimated flows and chemical loads, are also needed. 

Some of the instream water-quality processes simulated by 

HSPF also require water-temperature data, which can either 

be input from a recorded time series or generated by HSPF. 

The accumulation of chemical constituents on the land surface 

through either estimation of an accumulation rate or input of 

atmospheric-deposition data if available, can be simulated by 

HSPF. Observed streamflows, water temperatures, and chemical concentrations and loads are used to calibrate and validate 

the model. All model-input data must be entered at the same 

time step as the model-simulation run (hourly), either directly 

from a data file or by a conversion factor stipulated in the usercontrol input (UCI) file. 

Meteorological Data

Meteorological data for the model were obtained from 

two National Weather Service (NWS) stations (fig. 1; table 3). 

Meteorological data for 1970–2000, including hourly precipitation, air temperature, dewpoint temperature, wind speed, and 

percentage of cloud cover, were obtained from the station at 

the Greater Rochester International Airport. Estimates of solar 

radiation and potential evapotranspiration were calculated 

from data collected at the Rochester Airport by the methods contained in WDMUtil (U.S. Environmental Protection 

Agency, 1999). A second record of hourly precipitation was 

obtained from the NWS observation station at Victor, N.Y. for 

1986–2000.

A major source of parameter-estimation error in a precipitation-runoff model is the undocumented spatial variability 

in precipitation quantity within a basin (Chaubey and others, 

1999; Straub and Bednar, 2000; Troutman, 1983). The two 

weather stations that provided data for the Irondequoit Creek 

model are located outside the Irondequoit Creek basin. Several 

county- or town-operated stations within the basin had missing 

or erroneous data and only short periods of record, and, therefore, could not be used. 

Streamflow Data

Streamflow records were obtained from eight USGS 

streamflow-monitoring stations (fig. 1; table 3). These data 

sets were reviewed, and any missing or erroneous hourly 

values, such as occurred during days of ice-affected or estimated daily discharges, were identified and corrected through 

WDMUtil (U.S. Environmental Protection Agency, 1999) or 

GenScn (Kittle and others, 1998). Three of these stations were 

operated during the 1980s, and their data were used to calibrate a preliminary model that approximated the hydrologic 

characteristics of that decade. The data from one of these stations, Thomas Creek at Fairport, confirmed the loss of ground 

water from the White Brook and Thomas Creek subbasins, 

as discussed previously and were used to define the relations 

between surface water and ground water in these subbasins. 

The remaining five streamflow stations were operated during 

the simulated period and were used to calibrate and validate 

the model. 

During the navigation season, water is diverted from the 

EBC to the local surface-water network at four locations—as 

siphoned flow to Allen Creek and East Branch Allen Creek 

(fig. 1, sites A and B) for low-flow augmentation and golfcourse irrigation, and as leakage through flood-control waste 

gates to Irondequoit Creek at Cartersville and to Thomas 

Creek at Fairport (fig. 1, sites C and D) (table 3). Discharges 

at these points have been measured occasionally by Monroe 

County and were used to estimate daily diversions into the 

basin. The withdrawals from Allen Creek and East Branch 

Allen Creek for golf-course irrigation were estimated from 

the Allen Creek hydrograph, which indicated the occurrence 

of otherwise unexplainable decreases in flow. The estimated 

withdrawals were tested for two criteria—they did not exceed 

the combined estimated inflow from the two siphoning points 

and did not decrease flows at the Allen Creek monitoring 

site (station 04232050) below an acceptable low-flow limit 

of about 2 ft3/s. The diversion estimates are considered poor, 

however, because (1) measurement of canal diversions was 

inconsistent during the 1991–2000 simulation period (from 

zero to 15 measurements in any one season) and (2) no records 

of golf-course withdrawals were available.

Water-Temperature Data

Records of surface-water temperatures measured every 

15 minutes were available from the five USGS monitoring 

stations that were in operation from November 1994 

through 2000 (table 3). Temperatures were measured with 

thermistors anchored near the stream bottom at each site. The 

accuracy of the recorded temperatures was checked by field 

measurements. These records were used to calibrate simulated 

water temperatures. 

Initially, an attempt was made to use the recorded temperatures, rather than simulated temperatures, as input to the 

model as was done in the final version of the model. Periods 

of missing record at three sites precluded the use of all five 

data sets, but the data were sufficient for construction of 

three representative time series for water temperatures in 

(1) rural headwater reaches with cool temperatures (Irondequoit Creek at Railroad Mills record), (2) developed headwater reaches with warm temperatures (East Branch Allen Creek 

record), and (3) downstream reaches with varied development 

that receive water from a combination of land uses and with 

intermediate temperatures (records from Allen Creek and 

Irondequoit Creek at Blossom Road that exhibited similar 

daily and seasonal patterns and ranges in water temperature). 

16 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
Table 3. Data-collection sites in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.

[Site locations are shown in figure 1. mi2, square miles]

Site 

(and subbasin identifier in model, where applicable)

Site-identification number

Drainage 

area 

(mi2)

Data type Period of 

record

National Weather Service meteorological-data collection sites

Greater Rochester International Airport Precipitation, air and dew-point temperatures, windspeed, and cloud cover 1/70–12/00

Observation station at Victor, N.Y. Precipitation 1/86–12/00

U.S. Geological Survey streamflow, water-quality, and water-temperature-data collection sites

Irondequoit Creek at Railroad Mills (IC6) 04232034 39.2 Streamflow 

Water quality

Water temperature

 7/91–9/00

 7/91–9/99

 2/95–9/00

Irondequoit Creek near Pittsford (IC9) 04232040 44.4 Streamflow and water quality 3/80–5/91

Thomas Creek at Fairport (TC5) 04232046 28.5 Streamflow and water quality 3/80–2/90

Irondequoit Creek at Linden Avenue (IC14) 04232047 101 Streamflow and water quality 8/73–3/89

East Branch Allen Creek at Pittsford (EB4) 0423204920 9.50 Streamflow

Water quality

Water temperature

 4/90–9/00

 4/90–9/99

 11/94–9/00

Allen Creek near Rochester (AC5) 04232050 30.1 Streamflow

Water quality

Water temperature

 11/59–9/00

 10/83–9/99

 11/94–9/00

Irondequoit Creek at Blossom Road (IC16) 0423205010 142 Streamflow and water quality

Water temperature

 12/80–9/00

 11/94–9/00

Irondequoit Creek at Empire Boulevard (IC19) 0423205025 151 Streamflow and water quality

Water temperature

 6/90–9/00

 11/94–9/00

Atmospheric-deposition collection sites

Mendon Ponds 1 Water quality 10/83–9/00

Empire Boulevard (Ellison Park wetland) 2a Water quality 10/92–6/97

Indian Landing School 2b Water quality 10/97–9/00

New York State Erie (Barge) Canal diversion sites

Allen Creek below Erie Canal siphon near Rochester A Streamflow and water quality 10/88–9/00

East Branch Allen Creek below Erie Canal siphon 

near Pittsford

 B Streamflow and water quality 10/88–9/00

Cartersville waste channel at Pittsford C Streamflow and water quality 10/88–9/00

Fairport waste channel at Fairport D Streamflow and water quality 10/88–9/00

Precipitation-Runoff Model 17
The qualifying terms—cool and warm—refer to the general 

relation of a given temperature record to the other two and do 

not imply a particular temperature or temperature range. The 

option of directly inputting these temperature records to the 

model was abandoned because the simulation period would 

have been limited to the water-temperature-recording period— 

since November 1994—which would have precluded the use 

of earlier data for calibration purposes (table 3).

Ground-water temperatures have been measured as part 

of a Monroe County monitoring program since 1984. Selected 

temperature profiles were used to make initial estimates of 

monthly soil-water temperatures for the surface, upper, and 

lower soil layers, and for shallow ground water, as required by 

HSPF in the PERLND module PSTEMP (table 2).

Stream-Water-Quality Data

Calibration of the water-quality component of the 

model required measured or estimated loading rates of 

nonpoint-source constituents, as well as the concentrations 

or loads of these constituents in streamflow. In this report, 

the term “loading rate” refers to the average annual mass of a 

constituent that is removed from an acre of land, transported 

to a stream, and carried past the nearest downstream waterquality-monitoring site, where it is measured and subsequently 

included in load calculations. Loading rates are highly 

variable and depend on local physiographic and climatic 

characteristics, including land use, soil texture, slope, distance 

of overland flow, precipitation (quantity and intensity), and 

runoff rate (Beaulac and Reckhow, 1982). Loading rates can 

be strongly affected by agricultural and urban nonpoint-source 

contaminants and by best-management practices. Loading 

rates that are calculated for the basin of interest are the most 

reliable, but loading rates measured at locations outside the 

basin can be used as guides in calibrating simulated loads in 

a basin of interest. Loading rates for various land uses in the 

Irondequoit Creek basin were estimated by Kappel and others 

(1986; table 4) in the Nationwide Urban Runoff Program 

(U.S. Environmental Protection Agency, 1983). The annual 

loading rates for total phosphorus, as estimated from land-use 

and land-cover data, range from 0.1 lb/acre from forested land 

and 0.5 lb/acre from agricultural land to as much as 3.6 lb/acre 

for commercial-industrial areas. Total nitrogen loading rates 

range from 2.1 lb/acre from forested land and 6.8 lb/acre from 

agricultural land to 12.0 lb/acre for urban areas.

Table 4. Published estimated annual loading rates for nonpoint-source constituents, by land use.

[Values are in pounds per acre unless otherwise noted. SE, standard error. Dashes indicate no data] 

Land use and land cover Sediment1

(tons/acre)

Total suspended 

solids2

(tons/acre)

Total phosphorus Total nitrogen3

Ammonia

-plusorganic nitrogen2

Pervious land segments

Forest 0.05–0.4 -- 30.1 (SE 0.03) 2.1 (SE 0.4) --

Pasture or hay .3–1.8 -- -- -- --

Agriculture 4.5–7.0 -- 3.5 (SE 0.13) 6.8 (SE 2.0) --

Mixed rural5 -- 0.02–0.13 2.18–0.26 -- 1.78–2.25

Open .5–2.0 -- -- -- --

Urban .2–1.0 -- 31.5 (SE 0.2) 12.0 (SE 2.3) --

Mixed urban6 -- .14 2.48 -- 4.47

Residential -- .11 2.61 -- 4.46

Low density .05–0.5 -- -- -- --

Medium density .05–0.2 -- -- -- --

Commercial, industrial, transportation, 

or high-density residential

 .1–0.2 .26–0.83 2.67–3.6 -- 4.92–21.2

Impervious land segments

Residential 0.1–0.5 -- -- -- --

Low density

Medium density .1–0.5 -- -- -- --

Commercial .2–0.5 -- -- -- --

1

Donigian and others (1997); or Aqua Terra Consultants, HSPF training notes on Sediment Processes (2002).

2

Data from Kappel and others (1986).

3

Data from Frink (1991) in Donigian (2002).

4

Crop dependent.

5

High percentage of forest, pasture, and agricultural uses.

6

High percentage of residential and commercial uses; also includes forest, pasture, and agricultural uses.

18 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
Water-quality data were obtained from the five sites 

at which streamflow was measured during the simulation 

period (fig. 1; table 3). Automated samplers that extracted 

water samples from the channel (near the centroid of flow) 

hourly and stored them in refrigerated bottles were maintained 

by the Monroe County Environmental Health Laboratory 

(MCEHL). Samples were retrieved twice weekly and delivered 

to MCEHL. Sampling periods were divided on the basis of 

three flow conditions—base or steady flow, and the rising and 

falling phases of a storm hydrograph. If base- or steady-flow 

conditions prevailed during the entire sampling cycle (3 to

4 days), equal volumes of water from all samples collected 

during that cycle were composited for a single analysis. During storms, samples collected during the rising phase were 

composited separately from those collected during the falling 

phase. Samples collected at or near the peak might have been 

separately composited and analyzed. Equal volumes of water 

from all samples collected during a given phase were composited for a single analysis. Laboratory analyses were done by 

MCEHL, which participated in the USGS quality-assurance 

program for cooperating analytical laboratories (U.S. Geological Survey, 2005).

Monthly loads for each analyzed constituent—orthophosphate, total phosphorus, ammonia, ammonia-plus-organic 

nitrogen, nitrate-plus-nitrite nitrogen, total suspended solids—

were calculated from measured streamflows and composited 

constituent concentrations through the USGS program, ESTIMATOR (G. Baier, T. Cohn, and E. Gilroy, U.S. Geological 

Survey, written commun., 1995). The resulting data were used 

to calibrate monthly simulated loads of total suspended solids, 

total nitrogen, and total phosphorus. 

Samples of canal-diversion water were collected 

periodically at the siphon and flood-control waste-gate 

locations during the navigation season. Frequency of sample 

collection at a given site ranged from 0 to 19 times per year. 

Missing concentrations were interpolated from measured data 

or represented by concentration data collected at a nearby 

diversion point. Loads of total suspended solids, ammonia, 

organic nitrogen, nitrate-plus-nitrite nitrogen, orthophosphate, 

and organic phosphorus were estimated from measured 

concentrations and flows at the four sites, and were input to 

the model as point sources of chemical loads. The estimates 

for these loads are considered to be poor, however, because 

few data were available.

Ground-water quality in the Irondequoit Creek basin has 

been monitored by Monroe County since 1984. Concentrations 

of chemicals in ground water were reviewed in an attempt 

to use these data as direct input to the model (interflow and 

ground-water concentrations in the PQUAL section of the 

PERLND module). The initial estimates of nitrate, ammonia, 

and phosphate concentrations required adjustment because 

they reflected integration of many land uses and could not be 

directly associated with specific PERLNDs. Final concentrations were selected through calibration to base flow concentrations and loads.

Atmospheric-Deposition-Quality Data

Monthly samples of dryfall and wetfall were collected 

from three monitoring sites—one in the southern part of the 

basin at Mendon Ponds, the other two in the northern part near 

Blossom Road at Ellison Park (fig. 1, table 3). The southern 

site provided atmospheric-deposition data for the entire simulation period. The combined data from the two northern sites 

provided a single nearly continuous record of atmospheric 

deposition. The original collection site was in the Ellison 

Park wetland near Empire Boulevard and was operated from 

October 1992 through June 1997, after which a replacement 

site at Indian Landing School was operated from October 1997 

through September 2000. 

The atmospheric-deposition data represented the mass 

of monthly dryfall and the mean concentration of monthly 

wetfall of selected constituents. Monthly dryfall mass (lb/acre) 

was divided into hourly quantities for model input; whereas 

the monthly wetfall concentrations (mg/L) were input “as is”, 

because HSPF combines the concentrations with precipitation 

quantities to compute the chemical loads in wetfall. Loads of 

ammonia, organic nitrogen, nitrate-plus-nitrite nitrogen, orthophosphate, and organic phosphorus were available for model 

input but were not used because they overestimated the quantities of nutrients that would be available for washoff from the 

land surface, and prevented calibration of the water-quality 

components of the model. Therefore, atmospheric deposition 

of selected constituents was simulated through adjustment 

of parameters within the PQUAL and IQUAL sections of the 

PERLND and IMPLND modules, respectively.

Bed-Material Particle-Size Data

HSPF requires information on the composition of the 

bed material in the RCHRESs to simulate sediment transport 

in the basin. Each reach within the basin was inspected at 

several locations to identify the dominant bed material and to 

estimate or measure the mean particle size (D50). Gravel and 

other coarse-grained material were described by visual inspection, and a representative D50 value was selected on that basis. 

For sand and fine-grained bed material, a representative sample of the material was collected, and the D50 was calculated 

from a sieve particle-size analysis. The D50 for reaches where 

bed-material sizes were estimated or measured at several locations within a given RCHRES was calculated as the mean for 

that RCHRES.

HSPF also requires estimates of the sand, silt, and clay 

percentages in bed material of each RCHRES. The sand 

fraction in reaches that were dominated by gravel or larger 

particles was assumed to be the major component of the sand, 

silt, and clay material; therefore, sand, silt, and clay were 

assigned values of 90, 5, and 5 percent, respectively. The sand 

percentage for reaches that were dominated by sand (greater 

than 80 percent of all bed material) was computed directly 

from the sieve analyses. The remaining material was assumed 

Precipitation-Runoff Model 19
to contain equal amounts of silt and clay. The sand percentage 

for fine-grained reaches, where sand constituted less than 

80 percent of all bed material, was calculated directly from the 

sieve analysis, and the remaining amount was assumed to be 

about 80 percent silt and 20 percent clay. These latter percentages were estimated from detailed particle-size analyses of 

fine-grained bed-material samples collected in the Ellison Park 

wetland (Coon, 1997; Coon and others, 2000).

Bed-material porosity was estimated from the dominant 

particle size in a RCHRES and the corresponding average 

porosity values given in Fetter (1980), Davis and DeWiest (1966), and Freeze and Cherry (1979). Porosities of 45, 

40, and 35 percent were used for stream channels where the 

D50 was silt sized, fine-sand sized, and coarse-sand sized, 

respectively. A porosity of 30 percent was used for gravel and 

coarser bed material.

Basin Representation

Primary segmentation of the basin, that is, delineation of 

subbasins, was based on the spatial distribution of precipitation; two areas were approximately defined by a Thiessen 

(1911) line generated for the two meteorological stations at the 

Rochester Airport and at Victor (fig. 7), whose precipitation 

records (recorded hourly) covered the calibration and validation periods and were assumed to be error free. This segmentation placed all of the Irondequoit Creek basin south of the 

EBC, as well as the Thomas Creek and White Brook subbasins, into the Victor precipitation area, and placed the Allen 

Creek subbasin, and its tributary, East Branch Allen Creek, 

into the Rochester Airport precipitation area. All other meteorological data that were input to the model were obtained 

directly from, or derived from data collected at, the Rochester 

Airport station, regardless of the precipitation source.

Further segmentation of the basin was based on seven 

other factors: (1) the confluences of major tributaries; (2) an 

approximation of reach length, such that flow time through an 

average RCHRES under mean flow conditions would approximate the simulation time step; (3) an arbitrary size limit 

that subbasins not exceed 3 percent of the total basin area; 

(4) locations of large changes in channel slope and bed-material type that would affect the storage-to-discharge relation and 

sediment-transport processes in a RCHRES; (5) locations of 

calibration sites; (6) locations at which simulated discharge or 

chemical-load data were desired; and (7) locations of proposed 

stormflow-detention basins (fig. 8). This step resulted in division of the basin into 82 subbasins, each of which represented 

less than 2.8 percent of the total basin area (about 2,700 acres).

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Figure 7. Segmentation of the Irondequoit Creek basin, Monroe County, N.Y., based on proximity to the National 

Weather Service precipitation stations, the data from which were input to the Hydrological Simulation Program—

FORTRAN model.

20 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
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Figure 8. Subbasin boundaries and locations of existing or hypothetical stormflow-detention basins in the Irondequoit Creek basin, 

Monroe and Ontario Counties, N.Y.

Precipitation-Runoff Model 21
Hydrologic-Response Units

The HRUs into which the basin was divided were 

assumed to show homogeneous hydrologic and water-quality 

responses to precipitation and other meteorological factors. 

Each HRU was designated as pervious land (PERLND) or 

impervious land (IMPLND). The basin characteristics that 

were initially expected to affect the hydrologic and waterquality responses of the pervious land segments were type 

of surficial material, soil permeability, land-surface slope, 

land use and land cover, and depth to fractured bedrock, as 

described below. 

Pervious Land Segments (PERLNDs)

Surficial material (fig. 2) was initially considered to 

be a factor that would reflect the infiltration and percolation 

characteristics of the basin. Glacial material was assumed to 

have certain rates of infiltration and percolation; for example, 

outwash would have high rates, and till would have low rates. 

Comparison of specific glacial-deposit locations with the soil 

permeability indicated on soil-survey maps of those locations 

yielded inconsistent results, however. Therefore, surficial geology was not used in the development of PERLND HRUs.

Soil permeability varies widely and affects the rate at 

which water infiltrates the surface layer and percolates to the 

water table. Rate of surface infiltration depends upon many 

factors, including soil moisture and temperature, density of 

vegetation, slope, soil porosity, grain-size distribution and 

cohesion, intensity and duration of rainfall (Waller and others, 

1982), and degree of soil compaction. Rate of percolation to 

the water table depends on many of these factors, as well as 

the presence or absence of a water-impeding layer or fragipan, depth to seasonal high-water table, and depth to bedrock. 

Permeability can vary through the soil profile; the factor that 

is generally used for modeling purposes is whichever factor is 

the most restrictive. 

Permeability, as defined by the U.S. Department of 

Agriculture in county soil surveys (Heffner and Goodman, 

1973; Pearson and Cline, 1958), was used to delineate HRUs 

because it provided a means to evaluate soil conditions regardless of surficial material or bedrock type. Permeability values 

were obtained from a generalized map of infiltration rates 

that represented the rate of vertical water movement in the B 

horizon, which is generally between 10 and 40 in. below land 

surface. Areas of equal infiltration rates were digitized from 

published data (Yager and others, 1985, plate 3), which were 

based on original data from soil surveys of Monroe County 

(Heffner and Goodman, 1973), Ontario County (Pearson and 

Cline, 1958), and Wayne County (Higgins and Neeley, 1978). 

Permeability values for areas classified in those reports as 

“urban with no permeability classification” were estimated 

from a generalized map of water-infiltration potential (Waller 

and others, 1982; Waller and Finch, 1982), which in turn was 

derived from data in Sweet and others (1938). The basin was 

divided into areas of low and high permeability—2 in/h or 

less, and greater than 2 in/h, respectively. Sixty-three percent 

of the basin had soils with low permeability, and the remaining 

37 percent had highly permeable soils where the permeability 

ranged from 2 to more than 6 in/h (fig. 9). 

Land-surface slope was selected for HRU delineation 

because it strongly affects erosion processes and the timing 

of storm runoff. A GIS grid of land-surface slope was derived 

from Digital Elevation Models (DEMs) of the basin through 

ArcView (Environmental Systems Research Institute, 1992). 

The basin was divided into low-slope areas (6 percent slope 

or less) and high-slope areas (greater than 6 percent) (fig. 9) 

from a histogram of grid slopes. The 6-percent demarcation 

was an arbitrary value that divided the basin into areas of slow 

and fast hydrologic responses, as well as into minor and major 

sources of sediment and chemicals relative to a given land use 

or land cover. The low-slope area encompassed 67 percent of 

the basin, and the high-slope area, which included slopes as 

high as 127 percent, encompassed the remaining 33 percent.

Land use and land cover were selected as a basis for 

HRU development because they strongly affect evapotranspiration rates and runoff and water-quality processes. The 

primary source of land-use and land-cover data was National 

Land Cover Data (NLCD) (U.S. Geological Survey, 1999) 

that were collected around 1992; an additional source was 

tax-related property-type classifications (PTC) (New York 

State Office of Real Property Services, 1996). Comparison of 

the two groups showed discrepancies; specifically the NLCD 

indicated greater percentages of forested and agricultural areas 

than the PTC, whereas the PTC identified larger percentages 

of residential and developed areas than the NLCD (table 1). 

These discrepancies resulted because the NLCD were developed from Landsat thematic mapper (TM) data (30-meter grid 

size) that were acquired by multiresolution land characterization and, therefore, classified the land primarily by land cover, 

whereas PTC classified the land primarily by land use for 

tax-assessment purposes.

The NLCD is considered to be an acceptable general 

land-cover-classification product for large regions; although 

some small-scale inaccuracies can be expected. Inaccuracies 

were identified, and three revisions to the NLCD were made to 

improve the land-use and land-cover data for the Irondequoit 

Creek model. 

 (1) The NLCD identified 40.8 percent of the basin as 

agricultural, that is, used for row crops and pasture or hay, 

whereas county PTC maps showed only 15.8 percent as agricultural (table 1). The PTC were assumed to correctly identify 

current agricultural land, and only those areas were classified 

as agricultural in the model. The remaining NLCD agricultural 

areas were reclassified as “open and(or) grass.” 

 (2) The NLCD erroneously identified many emergent 

wetlands as row-crop land. Therefore, a separate wetland GIS 

coverage was generated that included all wetlands identified 

in the National Wetland Inventory (U.S. Fish and Wildlife 

Service, 2000) and freshwater wetlands regulated by the New 

York State Department of Environmental Conservation (New 

York State Department of Environmental Conservation, 2000), 

22 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
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Figure 9. Data used in development of hydrologic-response units for precipitation-runoff model of Irondequoit Creek basin, Monroe 

and Ontario Counties, N.Y.: (A.) Soil permeability. (B.) Land-surface slope. (C.) Land use and land cover.

Precipitation-Runoff Model 23
as well as those identified by municipalities in the Irondequoit 

Creek basin. This new wetland coverage was digitally incorporated into the NLCD coverage. 

 (3) Two large gravel pits near the southern boundary of 

the basin, classified by NLCD as commercial, were reclassified as low-slope, highly permeable, open and(or) grass areas. 

Similarly, two large golf courses in the southern part of the 

basin, which were classified as agricultural, were reclassified 

as urban and(or) recreational grass. 

Impervious Land Segments (IMPLNDs)

The NLCD did not provide the amount of detail needed 

for the model in the developed areas of the basin. The NLCD 

contained only the following three categories of developed 

land uses: 

 (1) low-density residential, defined as areas with mostly 

single family housing where constructed materials (primarily 

buildings and pavement) account for 30 to 80 percent of the 

total area; 

 (2) high-density residential, defined as heavily built-up 

urban centers in which people reside; vegetation covers less 

than 20 percent of the total area, and constructed materials 

cover 80 to 100 percent of the area; and 

 (3) commercial-industrial-transportation, defined as all 

highly developed lands not classified as high-density residential. 

Any developed area in which the land surface has been 

covered to some extent by constructed materials generally 

contains some amount of pervious land. A drainage study 

by the Monroe County Planning Council (1964) estimated 

that vegetated areas account for an average of 75 percent of a 

basin, even under conditions of maximum development, and 

that an urban environment containing pervious areas (cemeteries, golf courses, parks) in addition to its large impervious 

(commercially developed) areas can have approximately the 

same hydrologic characteristics as residential areas. Additionally, the modeling of impervious areas should distinguish 

between “effective” impervious areas—those that are hydraulically connected to the natural drainage system through 

ditches, culverts, and(or) a storm-sewer system—and “ineffective” impervious areas—those that are not hydraulically 

connected to the natural drainage system and drain to adjacent 

pervious areas. 

A literature review (Alley and Veenhuis, 1983; Natural 

Resources Conservation Service, 1986; Dinicola, 1990; Berris, 

1995; Zarriello, 1999; Zarriello and Reis, 2000; Lohani and 

others, 2001; Prisloe and others, 2000; and Center for Watershed Protection, 2001) indicated that most precipitation-runoff 

modelers, when modeling urban basins, attempted to develop 

a relation between average parcel or lot size and the percentage of the total or effective impervious areas of a basin. These 

studies had diverse objectives, but they all addressed simulation of urban runoff or the effects of urbanization on basin 

hydrology and nonpoint-source pollution, and many of them 

used HSPF. Only a few of these studies (Alley and Veenhuis, 

1983; Lohani and others, 2001; Prisloe and other, 2000; Center 

for Watershed Protection, 2001) included actual measurements 

of total impervious area, but all the studies that presented 

effective-impervious-area values used estimated, and not 

measured, values, and gave widely differing relations between 

average lot size and effective impervious area. The data from 

these studies provided a basis for development of a relation 

between average lot size and effective impervious area for the 

Irondequoit Creek basin, however (table 5).

The detail of the areas classified as residential by NLCD 

was refined, and the amount of impervious area in the developed areas of the basin was estimated from county tax-parcel 

maps and associated parcel codes, which identified parcels 

that contained a “structure.” Some (3.4 percent) of the parcels 

were classified as commercial, including apartment buildings, 0.56 percent were classified as community and public 

services, and 0.36 percent as industrial (manufacturing and 

processing), but most (95.6 percent) of the parcels were classified as residential. The combined acreage of these parcels 

was divided by the number of parcels to obtain an average lot 

size (AVGLOTSIZE), which was used as an approximation of 

housing density and the degree of development within a given 

subbasin. This value, and the relation between average lot size 

and effective impervious area that was developed from the 

published data (table 5), were used to estimate the percentage 

of the area classified as residential or commercial that could 

be assumed to be effectively impervious. The acreage thus 

computed was placed in one of the IMPLND categories; the 

remaining area was assigned to a corresponding PERLND category. This method of impervious-area estimation resulted in 

paired relations between residential PERLNDs and IMPLNDs 

and between commercial PERLNDs and IMPLNDs.

Table 5. Percentages of residential or commercial areas 

assigned to pervious or impervious categories in the precipitation-runoff model of the Irondequoit Creek basin, Monroe and 

Ontario Counties, N.Y.

[PERLND, pervious land area; IMPLND, impervious land area; <, less than; 

>, greater than. Values are in percent] 

Average residential 

lot (parcel) size 

in subbasin

Residential land use Commercial land use

Acres per parcel PERLND IMPLND PERLND IMPLND 

> 1.5 100 0 100 0

0.751 to 1.5 95 5 60 40

0.55 to 0.75 86 14 14 86

0.21 to 0.54 80 20 14 86

< 0.21 52 48 14 86

24 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
were assumed to have a hydrologic response similar to that 

of another PERLND or IMPLND, or because the distinctions between low and high slopes and(or) permeability were 

considered inconsequential for modeling a particular HRU. 

This consolidation resulted in a final set of 16 PERLNDs 

and 3 IMPLNDs (table 6). This set of HRUs was duplicated 

such that one set (PERLNDs 1–16 and IMPLNDs 1–3) was 

associated with the precipitation station at Victor; the other set 

(PERLNDs 21–36 and IMPLNDs 21–23) was associated with 

the National Weather Service station at the Greater Rochester 

International Airport (fig. 7). Each of these sets had an additional PERLND that was uniquely designed to simulate either 

a ground-water recharge site (infiltration basin; PERLND 20) 

or the Ellison Park wetland at the mouth of Irondequoit Creek 

(PERLND 38). Development of each of these PERLNDs is 

discussed in detail further on.

Thin soils underlain by fractured bedrock presented a 

unique hydrologic condition in the basin. Preliminary calibration of the model indicated a substantial difference between 

the hydrologic response of the Allen Creek subbasin and that 

of the upper Irondequoit Creek subbasin—a difference that the 

original set of HRUs failed to adequately simulate. This difference was attributed to large areas in the Allen Creek subbasin 

(and elsewhere in the northern half of the Irondequoit Creek 

basin) in which thin soils are underlain by fractured dolostone; 

this fracturing affects the water-storage and interflow and 

ground-water-flow characteristics, and increases ground-water 

loss from the subbasin. Therefore, a third set of PERLNDs 

was created for areas in which at least 50 percent of a subbasin contains 30 ft or less of overburden and is underlain by 

fractured dolostone, to permit simulation of flows in these 

“thin-soil” areas (fig. 3B). This set of PERLNDs (numbers 

41–56) was associated with the precipitation record from the 

Greater Rochester International Airport (table 6).

Stream Reaches

Basin hydrography was obtained from digital line graphs 

(DLGs) of the stream network; this GIS coverage was a 

reproduction of the ‘blue-line’ hydrography shown on USGS 

topographic maps of the basin (on file in the USGS office, 

Troy, N.Y.). Stream reaches (RCHRESs) were delineated 

as part of the basin-segmentation process, and their lengths, 

change in elevation from upstream to downstream end, and 

median bed-material size (DB50) were calculated. RCHRES 

lengths were either extracted from the hydraulic data used for 

Federal Emergency Management Agency (FEMA) floodinsurance studies (Federal Emergency Management Agency, 

1979, 1980a, 1980b, 1981, 1982, 1983, 1984, 1992a, 1992b) 

or measured with an ArcView (Environmental Systems 

Research Institute, 1992) graphic tool. The change in channel 

elevation was computed from FEMA flood-insurance crosssectional data, DEM elevations, or contour elevations on 

USGS topographic maps. The DB50 was estimated by field 

inspection of channels where the median particle size was 

obviously gravel or larger, or computed from sieve particleHydrologic Response Unit (HRU) Summary

The final classification of land use and land cover in 

the basin resulted in seven PERLND categories and three 

IMPLND categories (table 6). The seven PERLND categories 

were as follows:

 (1) Forest—21.5 percent of the basin is covered with 

deciduous, evergreen, and mixed forests and orchards. Of this, 

evergreen trees were estimated to cover only 13 percent of the 

forested area. 

 (2) Agriculture—10.5 percent of the basin was estimated 

to be in active agricultural use, including row crops, pasture, 

and hay fields. This value was a result of the adjustments to 

the NLCD classification as described previously. Most agricultural land is south of the EBC. 

 (3) Open and(or) rural grass—27.0 percent of the basin 

is covered by nonforested rural areas that include abandoned 

agricultural fields and those areas classified by NLCD as pasture or hay fields that were not classified as “agricultural” by 

the county property-tax data. 

 (4) Urban and(or) recreational grass covers 8.0 percent 

of the basin and includes golf courses, public parks, and large 

expanses of residential lawns. 

 (5) Residential—17.9 percent of the basin is classified 

as residential, which includes low- and moderate-density residential areas. Of this amount, a calculated percentage of areas 

classified by NLCD as low-density residential was considered 

pervious; the remainder was considered impervious. 

 (6) Commercial uses, including commercial, industrial, 

transportation, and high-density residential uses, cover 8.3 percent of the basin. Of this amount, a calculated percentage of 

the commercial areas was considered pervious; the remainder 

was considered impervious. 

 (7) Wetlands and(or) water bodies (lakes and ponds) 

cover 6.8 percent of the basin. Wetlands include riverine, 

lacustrine, palustrine, open-water, emergent, scrub-shrub, and 

forested wetlands as classified by the National Wetland Inventory (U.S. Fish and Wildlife Service, 2000), regulatory freshwater wetlands (New York State Department of Environmental 

Conservation, 2000), and wetlands identified by town planning 

departments. 

The final land-use and land-cover classification of the 

basin included two IMPLND categories—residential and commercial—which together represented the calculated effectiveimpervious portion of land classified by NLCD as residential 

and commercial.

These land-cover and land-use categories were further 

divided into low- and high-slope areas (6 percent or less and 

greater than 6 percent, respectively), and poorly and highly 

permeable areas (infiltration rate in the B soil horizon of 

2 in/h or less and greater than 2 in/h, respectively). Theoretically, this division of the basin would have resulted in 28 

PERLNDs (7 land covers or land uses × 2 slope classes × 2 

permeability classes) and 4 IMPLNDs (2 land uses × 2 slope 

classes). Some categories were combined, however, because 

they either represented less than 1 percent of the basin or 

Precipitation-Runoff Model 25
Table 6. Hydrologic-response units used in the precipitation-runoff model of the Irondequoit Creek basin, Monroe 

and Ontario Counties, N.Y.

[PERLND, pervious land segment; IMPLND, impervious land segment. Dashes indicate that the hydrologic response unit did not require 

division according to this basin characteristic or that a HRU number was not required] 

HRU number in model

Hydrologic response unit (HRU) Thick-soil1

 subbasin in indicated 

precipitation-record area

Thin-soil1 subbasin 

in Rochester 

Land use or land cover Slope2 Permeability3 Victor Rochester precipitation area

Undeveloped PERLNDs

Forest Low Low 1 21 41

Forest Low High 2 22 42

Forest High Low 3 23 43

Forest High High 4 24 44

Agriculture Low Low 5 25 45

Agriculture Low High 6 26 46

Agriculture High -- 7 27 47

Open and(or) rural grass Low Low 8 28 48

Open and(or) rural grass Low High 9 29 49

Open and(or) rural grass High Low 10 30 50

Open and(or) rural grass High High 11 31 51

Urban or recreational grass -- -- 12 32 52

Upland wetland and water -- -- 13 33 53

Ground-water infiltration basin -- -- 20 -- --

At-mouth wetland -- -- -- 38 --

Developed PERLNDs

Residential Low -- 14 34 54

Residential High -- 15 35 55

Commercial -- -- 16 36 56

IMPLNDs

Residential Low -- 1 21 21

Residential High -- 2 22 22

Commercial -- -- 3 23 23

1

Thin soil = 30 feet or less; thick soil = greater than 30 feet.

2

Slope is average land-surface slope; low is 6 percent or less; high is greater than 6 percent. 

3

Permeability is average infiltration rate of the B soil horizon; low is 2 inches per hour or less; high is greater than 2 inches per hour.

26 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
size analyses of samples collected from several cross sections 

along the reach. The DB50 was used by HSPF for calculation 

of bed shear stress and shear velocity, as well as for sandload computations. 

Each RCHRES requires a function table (Ftable) that 

defines the relations between channel-storage volume and 

water depth, stream-surface area, and discharge. The depth-todischarge relation is usually defined by the hydraulic properties at the downstream end of the reach, whereas the relation 

among surface area, volume, and discharge is a function of the 

hydraulic properties of the entire reach. Surface area and storage were calculated from cross-sectional data that was either 

collected for FEMA flood-insurance studies (FIS) or extracted 

from DEMs and modified by field measurements of channel top widths and depths. Relations between stage and top 

width, cross-sectional area, and discharge were calculated by 

the Channel Geometry Analysis Program (CGAP) (Regan and 

Schaffranek, 1985). Energy gradients, which were required for 

calculation of discharge, were estimated from water-surface 

slopes of 100-year flows given in the FIS or from channel 

slopes measured from topographic maps or computed from 

the DEM data. Roughness coefficients were taken from FIS 

or estimated during site visits. CGAP discharges were calibrated to high flows given in the FIS and to stage-to-discharge 

relations developed at USGS streamflow-monitoring stations. 

Calibration entailed adjusting the energy gradients and(or) 

roughness coefficients, which were assumed to change with 

flow depth and with the number of flow-constricting bridges 

and culverts in the reach. Ftables that could be input directly 

to the model were generated by GENFTBL (R.S. Regan, U.S. 

Geological Survey, written commun., 1992), which used the 

top widths and cross-sectional areas computed by CGAP to 

compute water-surface area and channel-storage volume for 

each RCHRES.

Simulation Complexities

The Irondequoit Creek basin contains several complex 

hydrologic conditions, which required special handling for 

simulation by the model. Each of these complex conditions is 

described below.

Wetlands

As mentioned previously, lacustrine, palustrine, and 

riverine wetlands cover large percentages of some subbasins. 

These wetlands were simulated by a high infiltration value, 

large storage values for lower- and upper-soil zones, low slope, 

short overland-flow length, a large interflow quantity, high 

interflow- and ground-water-recession rates, and high evapotranspiration rates for active-ground-water and lower-zone 

storages. Collectively, this setup simulated retention and slow 

release of surface runoff, a high water table, and the removal 

of ground water through wetland-plant transpiration.

Upland wetlands (PERLNDs 13, 33, 53) function differently from the Ellison Park wetland at the mouth of Irondequoit Creek in three ways: (1) They are assumed to be regional 

ground-water recharge points, although they can become local 

ground-water discharge points; (2) their inflow and discharge 

are dominated by precipitation and evapotranspiration, 

respectively; and (3) they provide storm runoff storage. The 

Ellison Park wetland (PERLND 38), which has been studied 

in detail since 1990 by Coon (1997 and 2004) and Coon and 

others (2000), is, in combination with Irondequoit Bay, part of 

a regional ground-water-discharge area, although this function 

can vary seasonally (M. Traynor and R. Schneider, Department of Natural Resources, Cornell University, Ithaca, N.Y., 

written commun., 2002). Unlike the upland wetlands, flow 

patterns in the Ellison Park wetland are dominated by creek 

inflows, and water levels are seasonally controlled, not by 

surface inflow and evapotranspiration, but by the water-surface 

elevation of Irondequoit Bay and Lake Ontario. The Ellison 

Park wetland also provides peak-flow attenuation and particulate chemical load decreases through sedimentation (Coon and 

others, 2000). These characteristics were simulated by larger 

lower- and upper-zone storage values, a lower slope, larger 

interflow quantity, and higher interflow-recession rate in the 

Ellison Park wetland than the upland wetlands. The processes 

of sedimentation and nutrient retention and generation that 

occur in the wetland were, at least partly, simulated through 

adjustments of selected parameter values that are pertinent to 

these processes and are found in the model sections SEDMNT 

and PQUAL for PERLND 38 and in SEDTRN, NUTRX, and 

PLANK for the wetland RCHRESs (nos. 770 and 800). Additional adjustments were made through a separate mass-link 

(No. 19), which controlled the loads that were passed from 

reach to reach through the wetland.

Ground-Water Flow Out of the Basin

The eastern boundary of the ground-water divide for the 

Irondequoit Creek basin lies west of the surface-water divide 

(Yager and others, 1985), such that ground water in parts of 

the Thomas Creek and White Brook subbasins flows eastward 

out of the basin (fig. 5). A preliminary version of the model 

simulated runoff for part of the period for which streamflow 

records for Thomas Creek were available, September 1986 

through March 1989. The resulting simulated total runoff at 

the Thomas Creek calibration point was more than 100 percent 

greater than the observed total runoff, but averaged only 

25 percent greater at other calibration points. Therefore, a 

separate mass-link (No. 7) was established so that overland 

flow, interflow, and only 25 percent of ground-water flow 

(changed to 20 percent during calibration of the 1990–98 

period) from the PERLNDs in the affected subbasins were 

routed to the appropriate RCHRESs. The remaining groundwater flow was routed out of the basin. (An alternative 

approach to simulating this condition might have been to 

duplicate the PERLNDs found in these subbasins and set the 

fraction of ground water that becomes “inactive” (DEEPFR) 

equal to 0.80.)

Precipitation-Runoff Model 27
Surface-Water Losses to Fractured Bedrock

Seepage investigations in the Allen Creek and East 

Branch Allen Creek subbasins (table 7; Hornlein and others, 2002) indicated that base flows, as much as 1.8 ft3

/s, 

were lost from Allen Creek through fractures in the Lockport 

dolostone formation (dolomite and shale beds) and entered 

the ground-water system. This loss, which at times during 

July 2001 represented the total flow in the creek, presumably 

occurred through solution cavities and along bedding planes of 

the dolostone, and the water reentered the channel at springs 

along the creek about 0.4 mi downstream. Similar losses were 

not detected in East Branch Allen Creek. No revisions to the 

model were made to simulate this condition, however, because 

the channel losses and gains were within the boundaries of a 

single RCHRES (No. 580), and the overall water balance in 

the Allen Creek subbasin was unaffected.

Hydrologic Connections with the NYS Erie 

(Barge) Canal

The canal was excavated from native materials for most 

of its length, except for a 2-mi section (within subbasin CN3, 

fig. 8) starting at the Cartersville flood-control waste gate east 

of the Village of Pittsford and extending eastward to where 

Interstate Highway 490 crosses the canal just east of Bushnell 

Basin (fig. 1; T. Lippa, New York State Canal Corporation, 

Buffalo, N.Y., oral commun., 2001). This section of the canal, 

called the Great Embankment, is concrete lined where it 

crosses the Irondequoit Creek valley, and the only connection 

between the canal and the ground-water system in this area 

consists of leakage from the canal. Elsewhere, the canal is 

at grade with the surrounding area, such that a complete 

connection between the canal and the local ground-water 

system is possible.

The canal receives surface runoff from the adjacent 

areas, and the Villages of Pittsford and Fairport, as well as 

from several small subbasins between Allen Creek and East 

Branch Allen Creek. These contributing areas represent about 

5,300 acres or 5.5 percent of the basin. Surface flow and 

interflow from these areas were routed to the canal, as was 

done with other PERLNDs and IMPLNDs (mass-link 11). 

Routing of the ground-water component of flow was 

handled one of two ways: 

 (1) If most of the contributing area was drained by overland flow directly to the canal, as in subbasin CN3 (fig. 8), 

or short sewered segments, as in the Village of Fairport area 

(subbasin CN4), ground-water flow was routed to downgradient channels of the natural drainage system on the assumption 

that at least as much canal water was recharging ground water 

on the downgradient side of the canal as was entering the canal 

from the upgradient side (mass-link 6). The canal’s contribution to ground water might be substantially more than assumed 

(M. Brewster, Town of Pittsford, and R. Cass, Town of Perinton, oral commun., 2001), but estimation of that quantity was 

beyond the scope of the study. 

 (2) If a large part of the contributing area was drained 

by a perennial stream, as subbasin CN1 between Allen Creek 

and East Branch Allen Creek, and subbasin CN2 in and south 

of the Village of Pittsford (fig. 8), then 20 percent of groundwater flow was routed to the canal as a base flow contribution to perennial streams (mass-link 14), and the remaining 

80 percent was routed to downgradient channels as described 

in (1) (mass-link 15). The 20–80 percent split in ground-water 

contribution was estimated through calibration of the model 

to the observed streamflow records of Allen Creek and East 

Branch Allen Creek.

Diversions from the Erie (Barge) Canal

Variable amounts of water and chemical loads are 

diverted from the canal to nearby streams at four locations 

(fig. 1): two are siphoned withdrawals permitted by the New 

York State Canal Corporation, and two are points of leakage 

through or around canal flood-control waste gates. The siphoning points—one where the canal crosses Allen Creek, and 

the other where it crosses East Branch Allen Creek—maintain base flows in the stream channels and permit local golf 

courses to remove water for irrigation during the summer. The 

waste gates—one in the Village of Fairport, and the other at 

the Cartersville guard gate just east of the Village of Pittsford—were originally designed to permit discharge of excess 

water to relieve flooding eastward along the canalized-river 

part of the canal, but they have not been used for this purpose 

during recent years. A third flood-control gate in the GreatEmbankment section of the canal near Bushnell Basin, has had 

no reported leakage. 

Another potential point of canal-water discharge is a 

manhole in the bottom of the canal between Bushnell Basin 

and Fairport (fig. 1). The manhole cover can be removed during the nonnavigation season to dewater this section of the 

canal for maintenance activities to be performed. Manhole 

discharges occur only during the nonnavigation season, when 

the canal is drained of all but local inflow, whereas siphoning and leakage occur during the navigation season, when the 

canal is full.

Discharges at the siphoning and waste-gate leakage 

points were periodically measured by the Monroe County 

Environmental Health Laboratory. These measurements, as 

well as hydrographic comparison of observed and simulated 

flows at the calibration points, were used to estimate time 

series of daily flows at each location. Water samples from the 

canal diversions were collected and analyzed for chemical 

concentrations. Time series of ammonia, nitrate-plus-nitrite 

nitrogen, organic nitrogen, orthophosphate, and organic 

phosphorus loads were estimated and input to the model as 

point sources of contaminants. Discharges through the manhole between Bushnell Basin and Fairport was not simulated 

because (1) the contributing area to this point is unknown, 

(2) no flow data were available, and (3) such discharges, 

although possible during any given year, were observed only 

during the winter of 1998–99 (C. Knauf, Monroe County 

Environmental Health Laboratory, oral commun., 2001).

28 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
Table 7. Seepage investigation of Allen Creek subbasin, Monroe County, N.Y., July 3 and 6, 2001.

[Values are in cubic feet per second. no., number; NYS, New York State; USGS station, U.S. Geological Survey streamflow-monitoring station; 

na, not applicable. Dashes indicate no data]

Site no. Site

July 3, 2001 July 6, 2001

Measurement 

accuracy1

Discharge Gain (+) or 

loss (-) Discharge Gain (+) or loss (-)

1 Allen Creek above NYS Barge Canal -- -- 0.18 -- fair

2 Allen Creek below NYS Barge Canal -- -- 21.31 +1.13 good

3 Allen Creek at Columbus Way 1.69 -- -- -- good

4 Allen Creek at Edgewood Avenue 1.84 +0.15 -- -- good

5 Allen Creek at Allens Creek Road 1.58 -.26 -- -- good

6 Allen Creek at Allendale Columbia School Drive 0 -1.58 0 -1.13 na

7 Allen Creek above Woodbury Place .04 +.04 -- -- good

8a Spring 1 below Woodbury Place 1.71 -- -- -- fair

8b Spring 2 below Woodbury Place 3.50 -- -- -- na

9 Allen Creek abover Buckland Creek 

(Sum of flow at Sites 7, 8a, and 8b.)

 2.25 +2.21 -- -- na

10 Buckland Creek at mouth at Allens Creek Road .09 -- -- -- fair

Allen Creek below Buckland Creek 

(Sum of flow at Sites 9 and 10.)

 2.34 +.09 -- -- na

11 Allen Creek above East Branch Allen Creek 

at Knollwood Drive

 3.62 +1.28 -- -- fair

12 East Branch Allen Creek at Tobey Road -- -- .04 -- fair

13 East Branch Allen Creek below NYS Barge Canal -- -- 22.17 +2.13 good

14 West Brook at Tobey Road -- -- .20 -- good

15 West Brook at West Brook Road -- -- .21 -- fair

East Branch Allen Creek below confluence with 

West Brook (Sum of flow at Sites 13 and 15.)

-- -- 2.38 -- na

16 East Branch Allen Creek at USGS station 42.39 -- 42.39 -- na

17 East Branch Allen Creek at mouth at Knollwood Dr. 3.29 -- -- -- fair

Allen Creek below East Branch Allen Creek 

(Sum of flow at Sites 11 and 17.)

 6.91 -- -- -- na

18 Allen Creek at USGS station 46.70 -- -- -- na

18 Allen Creek at USGS station -- -- 3.65 -- poor

1

Accuracy ratings of “good”, “fair”, and “poor” imply that the measured discharge is expected to be within 5 percent, within 8 percent, and 

greater than 8 percent, respectively, of the actual discharge.

2

Mainly low-flow augmentation from New York State Erie (Barge) Canal siphons.

3

Estimated value.

4

From established stage-to-discharge relation.

Precipitation-Runoff Model 29
Diversions to Golf Courses in Allen Creek 

Subbasin

As described above, siphoned flows from the canal into 

Allen Creek and East Branch Allen Creek were subsequently 

diverted to golf courses in the Allen Creek subbasin for irrigation. No records of irrigation withdrawals were available; 

therefore, diversion flows were estimated through a comparison of flows siphoned from the canal and those observed 

at the streamflow-monitoring sites downstream. Daily time 

series of flows were generated and input to the model in the 

EXT SOURCES module, then were removed through second exits that simulated withdrawals along RCHRES 580 of 

Allen Creek and RCHRESs 670 and 680 of East Branch Allen 

Creek. As with the siphoned flows, these diversion estimates 

were considered poor. Removal of chemical loads was simulated automatically with the diverted flows. 

Ground-Water Recharge Sites

Two areas in the basin were identified as ground-water 

recharge sites. The first is associated with a large shopping 

mall east of Interstate Highway 490, in the northern part of the 

Town of Victor (fig. 4; labeled GWR1 in fig. 8). Stormwater 

from about 250 acres of commercial land is routed to two infiltration basins in depressions bounded on the east by the mall 

and on the west by the highway embankment (mass-links 4, 5, 

and 9). These ponds, which have no surface outflow (masslink 6), were collectively simulated as a unique PERLND 

(No. 20) with high storage values for upper- and lower-soil 

zones, high rates of infiltration and ground-water recession, 

low slope, a long overland-flow length, and low interflow 

value and recession rate; all of which were selected to maximize infiltration and ground-water processes. 

The second ground-water recharge area, which is in the 

Town of Pittsford (GWR2 in fig. 8), was identified by town 

personnel as one with highly permeable soils and an ephemeral stream (M. Brewster, Town of Pittsford, oral commun., 

2001). The surface flow from IMPLNDs within subbasin 

GWR2 was routed to the low-slope, highly permeable forest 

and open-grass PERLNDs in the subbasin (mass-links 16 and 

17). Parameter values that generally were set to reflect high 

infiltration rates elsewhere in the basin were considered applicable to this area as well; no unique parameter values specific 

to this area were required.

Excess Stormflow in White Brook

A flood-insurance study for the Town of Perinton (Federal Emergency Management Agency, 1992a) indicated that 

high flows in Thomas Creek caused backwater on the five 4-ftdiameter culverts that convey the flows of White Brook under 

the EBC. An overflow structure on the southern embankment 

of the canal about 6,700 ft upstream from the culverts permits 

about 90 percent of the 100-year discharge in White Brook to 

be diverted to the canal, and only 10 percent to pass downstream to Thomas Creek. Excess flows that enter the canal exit 

the basin at this point. This diversion was simulated by including a second outflow exit for RCHRES 420 (subbasin WB3; 

fig. 8). The outflow from this exit to the canal begins when the 

water-surface elevation in White Brook exceeds the full-pool 

elevation of the canal, about 462.4 ft (Todd Lippa, New York 

State Canal Corporation, Buffalo, N.Y., oral commun., 2000), 

or the RCHRES depth exceeds 3 ft at this location. 

Jefferson Road Stormwater-Management 

Facility

A stormwater-management facility was constructed on 

East Branch Allen Creek between Jefferson Road and the 

EBC in the Town of Pittsford (subbasin EB3; fig 8) in 1995. 

This facility was designed primarily to control flooding and 

secondarily to improve water quality (Sherwood, 2004). 

A “front pond,” upstream from the main storage area, 

was designed to dissipate the energy of stormflows and to 

promote settling of suspended material. Water passes from 

the detention basin through a 30-in. pipe to a weir box at 

the bottom of an outlet control structure. High flows that are 

generated by low-frequency storms are controlled by a V-notch 

weir. When the water level in the basin falls below the apex of 

the weir, outflow is controlled by a 12-in. valve at the bottom 

of the weir box. This valve can be regulated to manipulate 

storage volume in the basin and to maintain summertime base 

flows (D. Anderson, ENSR International, Rochester, N.Y., 

written commun., 2001). Valve changes were not recorded 

during the study.

Three discharge relations were developed to represent 

flow conditions from the basin—a precontrol relation, and two 

postcontrol relations. The first postcontrol relation represented 

flows when the weir-box valve was closed, and, in general, 

gave better calibration results than a relation based on the 

weir-box valve in fully open position; this relation was used 

during most of the postcontrol period. The second postcontrol 

relation, which represented additional low-flow detention, was 

developed to resolve discrepancies that arose during three periods within the calibration period. A column-indicator file was 

created and stored in the WDM (DSN 6400) to permit switching from one discharge relation to another as desired. The initial switch from the precontrol to postcontrol relation occurred 

over a 10-day period during mid-August 1995, when the facility became operational (M. Brewster, Town of Pittsford, oral 

commun., 2001). Switches from one relation to another during 

the postcontrol period were determined through comparison of 

observed and simulated flows at the East Branch Allen Creek 

streamflow-monitoring station. 

The stormwater-management facility had a substantial 

effect on loads of particulate constituents (Sherwood, 2004). 

Load data from the East Branch Allen Creek water-quality 

monitoring site, about 1.4 mi downstream from the facility, 

indicated a 22-percent decrease in total suspended solids 

30 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
(TSS) and 10-percent decreases in ammonia-plus-organic 

nitrogen (TKN) and nitrate-plus-nitrite nitrogen (NOx). 

Median concentrations of TKN and NOx decreased by 23 and 

36 percent, respectively. No statistically significant changes 

in total phosphorus (TP) loads or concentrations were noted. 

These removal rates were low—especially for TP, which has 

a close relation with sediment—compared to those measured 

at other detention basins (table 8), and might reflect the 

differences between removal efficiencies for instream and 

off-channel detention basins, as well as the contributions of 

constituent loads from canal discharges and the urbanized area 

between the Jefferson Road detention basin and the waterquality monitoring site. As a result of these differences, the 

removal rates were increased slightly from those computed 

by Sherwood (2004) to improve the match between simulated 

and observed loads at the East Branch Allen Creek site. In the 

UCI file, this stormwater-management facility was simulated 

as a best-management practice with the BMPRAC module 

of HSPF, which allows simulation of the effects of bestmanagement practices by applying simple “removal” fractions 

to each constituent being simulated. Precontrol removal rates 

were set to zero in BMPRAC, and then were changed to the 

calibrated removal rates through the SPECIAL ACTIONS 

module beginning on August 15, 1995, and continuing though 

the postcontrol period.

Runoff from the City of Rochester

Two subbasins lie within the boundaries of the City of 

Rochester. Surface runoff in the western subbasin (R1; 

fig. 8) is conveyed by storm sewers to a bedrock-tunnel 

storage system under the city and has no connection with the 

rest of the Irondequoit Creek basin. A hypothetical Ftable was 

created to permit gradual depletion of water routed to tunnel 

storage. Surface runoff from the eastern subbasin (R2; fig. 8) 

was routed to Irondequoit Creek by means of mass-link 8. In 

both areas, interflow and ground-water flow were routed to a 

downgradient RCHRES because no direct connection exists 

between subsurface flow and flow in the culverts; mass-link 9 

was used for this purpose. 

Table 8. Published removal efficiency values for selected constituents for three types of stormwater-detention basins.

[Values are percents of total load that is removed. USEPA, U.S. Environmental Protection Agency. Dashes indicate no data]

Reference Number of 

basins

Total suspended 

solids

Total 

phosphorus

Total 

nitrogen

Ammonia

-plusorganic 

nitrogen

Nitrate

-plusnitrite 

nitrogen

Dry pond with or without extended detention

USEPA, 1993 4–6 45 25 30 -- --

USEPA, 2001 15 47–61 19–20 25–31 -- -2–4

Simulated analyses (Donigian and others, 1997) 6 16–63 -- -- -- --

Wet pond (basin with permanent water pool)

Nationwide Urban Runoff Program 

(USEPA, 1983)

 14 90 65 -- 50 50

Strecker and others, 1992 1–3 39–91 21–78 17–85 14 54–55

USEPA, 1993 9–18 60 45 35 -- --

USEPA, 2001 71 79–80 49–51 32–33 -- 36–43

Simulated analyses (Donigian and others, 1997) 6 20–68 -- -- -- --

Irondequoit Creek basin, simulated analyses 

(Zarriello and Surface, 1989)

 4 28–53 -- -- -- --

Jefferson Road Stormwater Management Facility, 

Town of Pittsford, N.Y. (Sherwood, 2004)

 1 22 3 10 10 10

Wet pond with extended detention

USEPA, 1993 1–3 80 65 55 -- --

USEPA, 2001 14 80 55 35 -- 63

Simulated analyses (Donigian and others, 1997) 6 31–92 -- -- -- --

Irondequoit Creek basin, simulated analyses 

(Zarriello and Surface, 1989)

 4 33–60 -- -- -- --

Precipitation-Runoff Model 31
Areas of Severe Streambank Erosion

Severe streambank erosion of sand-and-silt bluffs along 

Irondequoit and Allen Creeks (RCHRESs 510 and 700, 

respectively) contributes large loads of sediment and associated constituents. These sites, which are about a mile above 

the confluence of Allen and Irondequoit Creeks, were estimated to contribute more than 50 percent of the sediment load 

measured in Irondequoit Creek at Blossom Road (Young and 

Burton, 1993). Stabilization of these streambanks was completed during 1999 and 2000, which is beyond the simulation 

period covered in this study. The estimated increases in sediment and particulate constituent loadings that were attributed 

to these sources were simulated through an adjustment of the 

pertinent multiplication factors assigned to these RCHRESs in 

mass-link 18.

Hypothetical Stormflow-Detention Basins

Nine hypothetical stormflow-detention basins of various 

sizes and contributing areas (fig. 8) were identified by members of the IWC and incorporated into the Irondequoit Creek 

model as alternative simulations of their respective RCHRESs 

and to assist in creation of scenarios that would illustrate the 

potential benefits of detention basins for controlling flooding and chemical loads. The hydrologic effects of a detention 

basin can be simulated by HSPF either through a separate 

“off-channel” RCHRES to which runoff from a part of the 

subbasin can be directed before discharging into the mainchannel RCHRES, or as an instream detention basin. An offchannel detention basin permits flexibility in simulating the 

flow and water-quality effects of the basin, and might include 

the following modifications: 

 (1) the point of outflow might be raised in the RCHRES’s 

Ftable to simulate permanent storage and extended detention 

time; 

 (2) sediment-transport and shear-stress values for scour 

and deposition might be increased to decrease sediment scour 

or to limit it to periods of extremely high discharges and 

velocities; and 

 (3) silt- and clay-settling velocities might be increased to 

simulate enhanced sedimentation (Donigian and others, 1997). 

In contrast, an instream detention basin might be simulated with the following:

 (1) permanent storage and extended detention time,

 (2) increased storage volume, and(or) 

 (3) decreased outflow rate. 

Detention simulated by either method could represent a single 

basin within a subbasin, or the aggregate effect of a number 

of small basins elsewhere in the subbasin, in which case, the 

Ftable for the detention basin would reflect the combined surface area and volume capacity of the several small basins. 

All nine hypothetical detention basins were simulated as 

instream basins. Relations between channel-storage volume 

and water depth, surface area, and discharge relations (Ftables) 

were computed for each site on the basis of current conditions. 

A second table, in which the outflow rates and storage volumes could be adjusted to simulate various degrees of detention, was added to the UCI file for each respective RCHRES. 

Steps to make these revisions are described by Coon (2003). 

To a limited degree, these Ftable revisions will also simulate 

the water-quality effects of a detention basin; however, these 

effects can be simulated more precisely through the BMPRAC 

module of HSPF. Therefore, the Ftable revisions were 

included in the model to simulate the hydrologic effects of the 

detention basins, whereas the BMPRAC module was used to 

simulate the water-quality effects of the basins.

Removal efficiencies that were reported in studies of 

various types of detention basins (table 8) were evaluated to 

select representative values for the removal rates required in 

BMPRAC. These values were generally higher than those 

reported by Sherwood (2004) for the Jefferson Road stormwater-management facility and probably reflected the effects 

of off-stream basins that were specifically designed to optimize water-quality benefits. Removal efficiencies of TSS, TP, 

and total nitrogen (TN) for wet ponds with permanent water 

pools, which might be considered most similar in function to 

instream detention basins, were about 50, 50, and 40 percent, 

respectively. On the basis of these values, the removal rates 

used to simulate the water-quality effects of the Irondequoit 

Creek detention basins were 100, 50, and 10 percent for sand, 

silt, and clay, respectively; 100, 50, and 10 percent for ammonia and phosphate adsorbed to sand, silt, and clay particles, 

respectively; 50 percent for NOx, organic phosphorus, and 

organic carbon; and 30 percent for organic nitrogen.

The model was set up to enable simulation of the waterquality effects of eight of the nine hypothetical detention 

basins as described above. The ninth detention basin was in 

a RCHRES (No. 420) that was simulated with two exits, and 

HSPF does not support the use of BMPRAC for multiple 

outflows. Therefore, a unique mass-link (No. 22) was used to 

generate results for this basin that would be similar to those 

obtained for the other detention basins through BMPRAC. The 

limitation of this method of simulation is that outflow loads 

cannot be directly output to a WDM file; instead, the modeler 

will have to estimate the effect of the detention basin by comparing loads from the receiving RCHRES (No. 440) before 

and after simulating the detention-basin scenario.

Model Calibration and Performance

The hydrologic component of the Irondequoit Creek 

model was calibrated and validated first. After acceptable 

results were obtained, the model was calibrated to match 

observed water temperatures, and sediment and nutrient loads. 

Hydrologic Component of Model

The hydrologic component of the model was calibrated 

to streamflow records collected from five sites (table 3; fig. 1) 

from October 1, 1991, through September 30, 1998; and was 

32 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
validated through comparison with records from October 1, 

1998, through September 30, 2000. The precipitation-to-runoff 

relation was considered stable throughout the basin during this 

period (1991–2000; fig. 6); this stability was presumed on the 

basis of the following explanations: 

 (1) a subbasin was sufficiently developed by 1991 that 

subsequent changes in land use during this period had no 

detectable effect on the precipitation-to-runoff relation (as is 

likely to be the case in the northwestern part of the basin); 

 (2) the hydrologic effects of new developments were mitigated through adherence to zoning ordinances or construction 

of flow-attenuating measures, such as detention basins; or 

 (3) minimal development occurred during this period (as 

in the southern part of the basin). 

The hydrologic component of the model was calibrated 

through HSPEXP (Lumb and others, 1994), an expert system 

for calibration of HSPF, and guidance provided by U.S. Environmental Protection Agency (2000) and Donigian and others 

(1984). Parameter values were adjusted through HSPEXP in a 

stepwise manner to obtain acceptable (1) annual mass balance, (2) low-flow volume and recession rates, (3) stormflow 

volume and peak discharges, and (4) seasonal flow volumes. 

During each step of the calibration process, a different set 

of parameters was evaluated through a comparison of simulated streamflow with observed streamflow. When calibration 

results indicated that a specific parameter value should be 

adjusted, reasonable replacement values were selected from 

models for basins with similar soil types, land uses, climatic 

zones, and drainage-basin size that were found in a HSPF 

parameter database, HSPFParm (Donigian and others, 1999), 

or in published reports. HSPEXP generated statistics that 

were used to evaluate the changes made in the model and the 

remaining error. Adjustment continued until the percent error 

between simulated and observed flows was minimized, or at 

least fell below a predefined acceptable limit for errors in total 

volume, low-flow recession rate, the 50-percent lowest flows, 

the 10-percent highest flows, storm volume, seasonal volume, 

and summer-storm volume. 

The Irondequoit Creek model contained three sets of 

duplicate HRUs—one associated with the Victor precipitation 

record, one associated with the Rochester Airport precipitation 

record, and one associated with thin-soil areas underlain by 

fractured bedrock. Although values for some key parameters 

have been found to vary from one basin to another, even in the 

same geographic area (Donigian and others, 1983; Laroche 

and others, 1996; Carrubba, 2000), the parameter values 

assigned to a given HRU in the Irondequoit Creek model were 

assumed to be constant regardless of the precipitation record 

to which the HRU was related. If the basin characteristics that 

dominate the overland and within-channel flow processes were 

correctly identified, as was assumed, then no reason could be 

offered to justify changes to parameter values solely on the 

basis of a different precipitation record. In contrast, values for 

parameters that affect infiltration and subsurface flow can be 

and were modified for the HRUs in the thin-soiled, fracturedbedrock subbasins. Adherence to the guideline of consistent 

application of parameter values during the calibration process 

limited the precision of calibration that could be achieved at 

any given streamflow-monitoring site in the basin, and meant 

that, even though the best combination of parameter values at 

one calibration point might not have been the best at another, 

the values that were used in the final version of the model 

were those that collectively gave the best results and minimized the differences between observed and simulated values 

on a basinwide basis.

The percent errors of the calibrated model fell within 

the predefined default limits of HSPEXP at all five calibration sites and for all calibration criteria (table 9). Total volume 

error did not exceed 5.6 percent at any of the sites during the 

calibration period. Similarly, low-flow and high-flow errors 

were less than 5.9 percent. The error in storm volume did not 

exceed 7.2 percent at any site except the downstream site, 

Irondequoit Creek at Empire Boulevard, where the Ellison 

Park wetland attenuated the flow. Errors in summer-storm 

volume were large at some sites, but presumably resulted from 

local storms that were not reflected in the precipitation records 

used in model simulation. The low-flow-recession errors at 

the East Branch and main stem Allen Creek sites could not 

be resolved; decreasing the active-ground-water-recession 

coefficient (AGWRC) or increasing the active-ground-wateroutflow modifier (KVARY) by an amount that would have 

corrected this error caused low-flow discrepancies between 

observed and simulated flow-duration plots. The likely causes 

of these errors were the lack of operational records from the 

Jefferson Road stormwater-management facility (subbasin 

EB3) and inaccuracies in the estimates of canal diversions 

and golf-course withdrawals from the Allen Creek subbasin. 

Summer-storm-volume errors in the East Branch and Allen 

Creek subbasins were large also. Adjusting the percentages 

of the pervious and effective impervious areas in the subbasin should have decreased the error by increasing runoff and 

summer-storm peaks, but converting all the pervious “developed” acreages to impervious areas failed to improve the 

results. Simulation of developed areas as entirely impervious 

surfaces was not reasonable; therefore, the original pervious 

and impervious acreages were retained. All HSPEXP error 

statistics for the validation period were greater than those 

for the calibration period, which indicated a limitation of the 

model for predictive purposes—in other words, the calibrated model can be used for comparison of scenarios, but 

should not be used to predict future streamflows.

Model Performance

In addition to the above measures, model performance 

during the calibration and validation simulation periods was 

assessed on the basis of the “weight of evidence” approach 

(Donigian, 2002), which incorporates qualitative and quantitative measures involving graphical comparisons and statistical 

tests. Graphical comparisons included (1) time-series plots 

of monthly observed and simulated values, (2) scatter plots 

of observed and simulated values in relation to a 45-degree 

Precipitation-Runoff Model 33
34 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y. Table 9. Calibration crit eria and errors for simulated streamflow at five streamflow-monitoring sites in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y. [Results generated by HSPEXP, an expert system for calibration of Hydrological Simulation Program-FORTRAN models (Lumb and others, 1994). Values are in percent, except error in low- flow recession, which is unitless. Site locations are shown in figure 1] Calibration criterion Default value Errors for (A) calibration period, October 1, 1991, through September 30, 1998, and (B) validation period, October 1, 1998, through September 30, 2000 Irondequoit Creek at Railroad Mills (04232034) East Branch Allen Creek at Pittsford (0423204920) Allen Creek near Rochester (04232050) Irondequoit Creek at Blossom Road (0423205010) Irondequoit Creek at Empire Boulevard (0423205025)

A B A B A B A B A B

Error in total volume 10.0 2.0 -2.0 -5.6 -14.0 4.0 -10.8 -2.3 -9.5 -1.1 -12.5Error in low-flow recession .03 -.01 -.01 -.03 -.03 -.03 -.02 -.01 -.01 -.03 -.02Error in 50-percent lowest flows 10.0 -3.6 -6.3 1.3 19.1 1.3 -18.1 -2.0 -6.7 -1.6 -9.9Error in 10-percent highest flows 15.0 4.7 -17.7 -5.8 -13.5 1.5 -12.5 -3.3 -21.5 -1.5 -25.9Error in storm volume 20.0 -3.8 -54.0 4.0 33.0 -4.8 -13.5 -7.2 -28.1 14.2 -7.8Seasonal volume error 30.0 1.3 11.6 6.2 46.7 3.2 6.0 13.9 17.9 18.7 22.5Summer storm volume error 50.0 12.4 9.0 -26.9 13.3 -20.6 9.7 5.0 8.7 .1 7.6
linear regression line, and (3) cumulative frequency distributions of observed and simulated values (flow-duration curves). 

Statistical tests included (1) error statistics (mean absolute 

error, mean error, and percent error); and (2) correlation tests 

(linear-correlation coefficient, coefficient of determination, 

and coefficient of model-fit efficiency). 

Mean absolute error (MAE) is the average of the absolute values of the differences between simulated and observed 

values, and equals 

The percent mean absolute error (MAE%) is the average of the absolute values of the differences between simulated and observed values, expressed as a percentage of the 

observed values, and equals

Mean error (ME), or bias, is the average of the differences between simulated and observed values and accounts for 

the positive or negative sign of the difference, and equals 

ME indicates whether the model is biased—that is, overestimating or underestimating a given constituent. 

The percent mean error (ME%) is the average of the differences between simulated and observed values expressed as 

a percentage of the observed value, and equals 

Root mean square error is the square root of the average 

of the squared differences between simulated and observed 

values, and equals 

The correlation coefficient, R, (Duncker and Melching, 

1998) was calculated as

The coefficient of determination, R2, although redundant, 

was included along with the correlation coefficient to enable 

direct comparison with values published for other HSPF 

models. 

The coefficient of model-fit efficiency, E, (Nash and Sutcliffe, 1970; Duncker and Melching, 1998; Zarriello and Reis, 

2000) was defined as 

where the variables are defined as above.

The coefficient of model-fit efficiency is a direct measure of the fraction of the variance of the original data series 

explained by the model (Duncker and Melching, 1998), and 

provides a more rigorous evaluation of fit quality than the correlation coefficient. R indicates only that the series being compared have similar patterns of exceeding and being less than 

their respective mean values, whereas E takes into account the 

magnitude of differences between the observed and simulated 

values.

For HSPF simulations, the agreement between annual and 

monthly simulated and observed flows can be characterized 

as “very good” when the error is less than 10 percent, “good” 

when the error is 10 to 15 percent, and “fair” when the error 

is 15 to 25 percent (table 10; Donigian, 2002). These criteria 

and the percent mean errors for the calibration sites (table 11), 

indicate the Irondequoit Creek model to be “very good” for 

daily and monthly flows at all sites except Allen Creek, for 

which it would be rated “good.” 

The correlation coefficients for simulated-to-observed 

flows ranged from 0.81 to 0.93 for daily flows and 0.88 to 

0.95 for monthly flows at the five calibration sites (table 11). 

These values fell within the range of published values for 

other HSPF models (table 12). The coefficients of model-fit 

efficiency ranged from 0.59 to 0.85 for daily flows and 0.75 to 

0.90 for monthly flows at the Irondequoit Creek sites, which 

generally were in the low range of published values for daily 

flows and in the midrange for monthly flows. 

, (1)

where

S = simulated value,

O = observed value,

N = number of values in the sample,

Σ = sum, and

= absolute value.

∑ S O– ⁄ N

100 × ∑ [ ] S O– ⁄ O ⁄ N . (2)

∑ ( ) S O– ⁄ N . (3)

100 × ∑ [ ( ) S O– ⁄ O ] ⁄ N . (4)

( ) S O– . (5) [∑ 2 ⁄ N]0.5

, (6)

where

= observed flow for given time step,

= average observed flow for given time step,

= simulated flow for given time step, and

= average simulated flow for given time step.

R ∑ (qo qo – ) qs qs × ( ) –

∑ (qo qo )

2 – ∑ qs qs ( ) – 2

×

= -----------------------------------------------------------------------

qo

qo

qs

qs

E , (7) ∑ (qo qo – )

2

∑ qo qs ( ) – 2 –

∑ (qo qo )

2 –

= ------------------------------------------------------------------

Precipitation-Runoff Model 35
Graphical comparison of observed and simulated daily 

and monthly flows (fig. 10) indicated that simulated flows 

were neither consistently low nor high in relation to observed 

flows at the calibration sites. Flow durations of simulated daily 

flows closely matched those of observed flows during the 

calibration period (fig. 11).

The statistical tests and graphical comparisons for the 

simulated and observed flows during the validation period 

gave varied results. Mean errors for Irondequoit Creek at 

Blossom Road and Empire Boulevard were higher during the 

validation period than the calibration period; whereas mean 

absolute errors for the two periods at each site were comparable (table 11). The correlation coefficients for the two periods 

were similar at most sites for both daily and monthly flows. 

The changes in coefficients of model-fit efficiency varied 

among the sites; model performance improved at the Allen 

Creek sites and either remained the same or diminished at the 

Irondequoit Creek sites (table 11). The graphical relations 

between daily and monthly observed and simulated flows during the validation period were similar to those during the calibration period (fig. 10). The flow durations for simulated daily 

flows differed more from observed flows during the validation 

period than during the calibration period; nonetheless, similar 

patterns in the flow-duration plots are evident (fig. 11).

Model Sensitivity to Parameter Values

Many published reports on HSPF models have included 

analyses of model sensitivity to parameter values, and 

researchers are in general agreement as to the specific 

parameters whose values have the greatest effect on model 

results. Laroche and others (1996) list the following 10 

parameters that strongly affect the hydrologic component 

of an HSPF model:

 INFILT Index of soil-infiltration capacity;

 IRC Interflow-recession coefficient, an index for the 

 rate of shallow subsurface flow;

 INTFW Interflow-inflow parameter, controls the amount 

 of infiltrated water that becomes shallow 

 subsurface flow;

 LZSN Lower-zone nominal storage, an index to the 

 soil-moisture holding capacity of the unsaturated 

 zone;

 UZSN Upper-zone nominal storage, an index to the 

 amount of storage capacity in depressions and 

 the surface-soil layer;

 LZETP Lower-zone evapotranspiration parameter, 

 represents the density of deep-rooted vegetation 

 that conveys water from the unsaturated zone 

 upward to the atmosphere; 

 AGWRC Ground-water recession coefficient, controls the 

 rate at which ground water drains from the land; 

 KVARY Ground-water outflow modifier, represents the 

 variable influence that ground-water inflow has 

 on ground-water outflow;

 INFEXP Infiltration equation exponent, controls the rate 

 of infiltration decrease as a function of increas-

 ing soil moisture; and 

 INFILD Ratio of maximum to mean infiltration rate.

The hydrologic results of the Irondequoit Creek model were 

strongly affected by the values assigned to all of these parameters. KVARY strongly affected the shape of the groundwater-recession curve, but AGWRC alone was sufficient to 

simulate this part of the hydrograph. Therefore, default values 

were used for KVARY, as well as for INFEXP and INFILD, 

for which no reason to alter their values was found. Four other 

parameters were found to affect the calibration of snowmelt 

periods: 

 SHADE Fraction of the land surface shaded from solar 

 radiation by trees or slope,

 COVIND Amount of snowfall required to completely cover 

 the land surface,

 SNOEVP Snow-evaporation-adjustment factor, and

 CCFACT Condensation and convection melt-adjustment 

 factor.

Two other snowmelt parameters—MWATER, the liquid-water 

storage capacity in the snowpack, and MGMELT, the rate of 

melt caused by ground heat—can strongly affect snowmelt 

processes but did not affect the Irondequoit Creek model; 

therefore, default values were used for these parameters.

Model Uncertainty

Sources of model uncertainty included (1) insufficient 

number of precipitation-monitoring sites to adequately represent the precipitation patterns over the basin, (2) inaccurate 

estimates of diversions, (3) misclassification of land-use and 

land-cover data, (4) changes in land use during the simulation period, and (5) differences in scale of the subbasins used 

for calibration and the consequent effect on parameter values. 

Table 10. Selected criteria for evaluating Hydrological Simulation Program—FORTRAN (HSPF) model performance.

[Data from Donigian (2002)]

Percent difference between observed and 

simulated monthly or annual values

Very good Good Fair

Streamflow < 10 10–15 15–25

Sediment loads < 20 20–30 30–45

Water temperature < 7 8–12 13–18

Nutrient loads < 15 15–25 25–35

Correlation coefficient (R)

Daily streamflow 0.89–0.95 0.84–0.89 0.77–0.84

Monthly streamflow 0.92–0.97 0.87–0.92 0.81–0.87

Coefficient of determination (R2)

Daily streamflow 0.80–0.90 0.70–0.80 0.60–0.70

Monthly streamflow 0.85–0.95 0.75–0.85 0.65–0.75

36 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
Some of these sources of uncertainty have been identified by 

other researchers (Troutman, 1982, 1983; Chaubey and others, 

1999; Carrubba, 2000; Wood and others, 1988, 1990; Doherty 

and Johnston, 2003) and can be minimized through attention 

to their respective causes, but are largely considered unavoidable in many models. Each of these five sources of uncertainty 

are described below.

1. Inadequate representation of precipitation patterns: A precipitation-runoff model is driven primarily by the 

precipitation records, which are not only subject to measurement error, but, due to a sparse network, can fail to adequately 

represent nonuniform precipitation patterns across the basin, 

especially during local summer thunderstorms. This inadequacy, in turn, can produce a large uncertainty in the model 

results (Troutman, 1982, 1983; Chaubey and others, 1999; 

Straub and Bednar, 2000). The two precipitation-monitoring 

sites (Rochester Airport and Victor) that were available for 

model calibration were insufficient to capture the precipitation patterns across the basin, and actually lie outside of the 

Irondequoit Creek basin. Comparison of the records from the 

two sites indicates large differences in precipitation quantities 

and timing. For example, recorded precipitation at the Rochester Airport exceeded that at Victor by 6.8 in. during 1998 and 

by 8.7 in. during 1995. Whether these differences were real or 

reflect measurement error, using one rather than the other to 

simulate precipitation across the entire basin would have 

Table 11. Model-performance statistics for simulated streamflow at five monitoring sites in the Irondequoit Creek basin, 

Monroe and Ontario Counties, N.Y.

[Locations of monitoring sites are shown in figure 1]

Statistic

Model performance statistics for (A) calibration period, October 1, 1991, through September 30, 1998, and 

(B) validation period, October 1, 1998, through September 30, 2000

Irondequoit Creek 

at Railroad Mills 

(04232034)

East Branch Allen 

Creek at Pittsford 

(0423204920)

Allen Creek 

near Rochester 

(04232050)

Irondequoit Creek 

at Blossom Road 

(0423205010)

Irondequoit Creek 

at Empire Boulevard 

(0423205025)

A B A B A B A B A B

Daily mean streamflow

Mean error and bias -0.69 -2.20

 

 0.47 -0.12

 

 3.32 -0.56 -7.50 -14.9 -1.33 -16.0

(percent) (-1.7) (-7.3) (4.9) (-1.5) (10.5) (-2.2) (-5.6) (-13.8) (-.93) (-13.7)

Mean absolute error 10.3 8.38

 

 3.89 4.10

 

 10.7 10.6 30.2 29.1 32.1 32.1

(percent) (26) (28) (41) (52) (34) (40) (22) (27) (22) (28)

Root mean square error 20.7 18.2 10.3 8.79 29.1 26.9 62.9 63.3 69.2 66.1

Correlation coefficient .90 .88 .81 .80 .85 .85 .93 .92 .91 .90

Coefficient of determination .81 .77 .65 .65 .72 .72 .86 .85 .83 .82

Coefficient of model-fit 

efficiency

 .80 .74 .59 .59 .69 .72 .85 .80 .82 .79

Monthly mean streamflow

Mean error and bias -.72 -2.23

 

 .48 -.12

 

 3.36 -.56 -7.54 -15.0 -1.39 -16.1

(percent) (-1.8) (-7.3) (5.1) (-1.6) (11) (-2.1) (-5.6) (-14) (-1.0) (-14)

Mean absolute error 6.03 4.54

 

 2.1 1.90

 

 6.30 5.76 19.3 20.1 19.2 22.3

(percent) (15) (15) (22) (24) (20) (22) (14) (19) (13) (19)

Root mean square error 8.32 6.38 3.10 2.58 9.17 7.18 27.5 31.9 29.7 34.6

Correlation coefficient .95 .95 .88 .95 .91 .92 .95 .95 .94 .95

Coefficient of determination .91 .91 .77 .91 .83 .84 .91 .90 .89 .89

Coefficient of model-fit 

efficiency

 .89 .89 .75 .85 .78 .84 .90 .81 .89 .81

Precipitation-Runoff Model 37
Table 12. Published model-performance results for streamflow simulated by Hydrological Simulation Program—

FORTRAN models.

[>, greater than. Dashes indicate no data]

Reference Number of basins or 

calibration points

Analysis 

interval

Correlation 

coefficient 

(R)

Coefficient of 

determination 

(R2)

Coefficient of 

model-fit 

efficiency 

(E)

Duncker and others (1995) 5 basins: individual (best-fit) 

calibration parameter set

monthly 0.93–0.97 -- 0.87–0.93

5 basins: regional-calibration 

parameter set

monthly .93–0.95 -- .86–0.91

2 basins: verification using 

regional parameter set

monthly .93–0.94 -- .87–0.88

Duncker and Melching (1998) 3 basins: individual (best-fit) 

calibration parameter set

monthly .93–0.96 -- .86–0.92

3 basins: regional-calibration 

parameter set

monthly .92–0.94 -- .83–0.86

3 basins: verification using 

regional parameter set

monthly .78–0.93 -- .34–0.82

3 basins: recalibration using 

regional parameter set

monthly .87–0.92 -- .76–0.83

James and Burgess (1982) -- daily > .98 -- > .98

Crawford and Linsley (1966) 7 basins daily .94–0.98 -- --

Chiew and others (1991) 1 basin monthly .8 -- --

Price (1994) 4 basins monthly .88–0.95 -- --

Jones and Winterstein (2000) 2 basins monthly .93 -- .83–0.85

Zarriello and Reis (2000) 2 calibration points annual -- 0.85–0.99 .72–0.98

monthly -- .95–0.98 .90–0.95

daily -- .89–0.94 .79–0.88

Martin and others (2001) 2 calibration points monthly .98 -- .95–0.96

daily .98 -- .95–0.96

hourly .89–0.93 -- .79–0.86

Wicklein and Schiffer (2002) 2 calibration basins monthly .86–0.88 -- .72–0.75

3 validation basins monthly .88–0.91 -- .68–0.78

Senior and Koerkle (2003) 9 calibration points daily .66–0.95 -- .42–0.85

hourly .24–0.91 -- .05–0.79

Donigian (2002) 2 calibration points monthly .93 .87 .87

daily .86 .74 .73

38 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
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Figure 10. Daily and monthly observed and simulated flows at five calibration sites in the Irondequoit Creek basin, Monroe and Ontario 

Counties, N.Y. (Site locations are shown in figure 1.)

Precipitation-Runoff Model 39
introduced large errors that would have necessitated unwarranted adjustments to parameter values to improve the fit 

between observed and simulated flows. Two additional, though 

partial, records of precipitation within the southern half of 

the basin (Honeoye Falls-Lima and Mendon Ponds) indicated 

large differences in precipitation quantities, especially during 

the summers. These additional records were not used, however, because they were either incomplete or would have limited the period of simulation to an unacceptably short period. 

Additionally, continuation of these precipitation stations is 

not certain. The discrepancies among the precipitation records 

indicate that any single record cannot reliably represent the 

precipitation patterns throughout the basin. 

2. Estimated inflows and diversions: The estimated 

inflows to the basin from the EBC siphons and from gate 

leakages, unknown outflow from the Jefferson Road stormwater-management facility (detention basin) on East Branch 

Allen Creek (subbasin EB3; fig. 8), and unrecorded withdrawals for golf-course irrigation in the Allen Creek subbasin were 

a second source of model uncertainty. Siphon and leakage 

diversions were estimated from infrequent discharge measurements. Outflow from the detention basin was regulated by a 

valve in the outflow structure, but valve-opening changes were 

not recorded and could be estimated only through comparison 

of observed and simulated flows at the East Branch Allen 

Creek monitoring station. The irrigation withdrawals also were 

not recorded and were estimated through a comparison of 

observed and simulated flows at the Allen Creek monitoring 

station. Although the magnitude of these inflows and diversions is relatively small in relation to the total annual flow in a 

given stream, they represent a large percentage of the summertime base flows in Thomas and Allen Creeks, and probably 

contributed to the difficulty in calibrating low-flow recessions 

and base flows in these subbasins.

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Figure 10. Daily and monthly observed and simulated flows at five calibration sites in the Irondequoit Creek basin, Monroe and 

Ontario Counties, N.Y. (Site locations are shown in figure 1.)—Continued.

40 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
3. Misclassification of land-use and land-cover data:

Land-use and land-cover data collected by satellite imagery 

are subject to error. A general field check of the data was 

conducted, but a thorough assessment of the accuracy of the 

data across the entire basin was impractical. Revisions were 

made as described previously. Errors in land-use or land-cover 

classification affect the acreage values assigned to HRUs, and, 

thus, the values of parameters assigned to simulate the hydrologic processes within these HRUs.

4. Changes in land use: The 1991–2000 simulation 

period was selected for model development because rainfallrunoff patterns appeared to be stable, especially in the urbanized subbasins (fig. 6); but this apparent stability probably 

reflected a counterbalancing of hydrologic processes. For 

example, increased runoff from newly developed impervious 

areas could be mitigated by on-site detention basins, but the 

requirement for inclusion of detention basins could vary from 

town to town. The selected values of parameters that would 

simulate runoff processes for a given HRU would not optimally simulate flows in either situation, but rather would be 

average values that simulated average conditions. Therefore, 

the predictive capability of the model would be limited by the 

changing conditions in the basin; that is, the parameter values 

that were used to minimize the simulated-to-observed streamflow error during the 1990s calibration period were probably 

not the optimum values to simulate flows during the previous 

or following decades.

5. Effect of subbasin scale: The development of the 

HRUs required assumptions and parameter values that represented average conditions over a range of slopes and permeability that were applicable at a basinwide scale. As subbasin 

size decreases, the ranges of slope and permeability narrow, 

and basin characteristics (actual slope, overland flow length, 

upper- and lower-zone nominal storages, infiltration-capacity, 

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Figure 11. Flow-duration plots of observed and simulated flows at five calibration sites in the Irondequoit Creek basin, Monroe and 

Ontario Counties, N.Y. (Site locations are shown in figure 1.)

Precipitation-Runoff Model 41
and interflow indices) become increasingly uniform, thus, the 

optimal parameter values depart from the basinwide averages. 

The ideal modeling situation—where parameter values remain 

constant regardless of subbasin size—probably does not 

occur because certain key parameters are likely to vary from 

one subbasin to another, even within the same geographic 

area (Donigian and others, 1983; Laroche and others, 1996; 

Carrubba, 2000). Consequently, parameter values selected to 

minimize errors at a basinwide scale cannot be expected to 

yield satisfactory results at a local or development scale, where 

the subbasin characteristics can differ substantially from the 

basinwide averages.

In summation of model uncertainty, therefore, unavoidable errors in the input data must inevitably affect the values 

selected for the related key parameters in the model, and 

adjustment of parameter values during model calibration to 

minimize the differences between observed and simulated 

values will also unavoidably be minimizing the errors in the 

input data.

Water-Quality Components of Model

The water-quality components of the Irondequoit Creek 

basin model included simulation of water temperature, 

sediment loads, and nutrient loads, which were calibrated 

to records collected at the five streamflow and water-quality 

monitoring sites from September 1, 1991, through September 

30, 1998, and were validated through comparison with the 

records collected from October 1, 1998, through September 

30, 2000. Guidance in the calibration of these constituents was 

provided by Donigian and others (1984). Calibration entailed 

comparison of graphs of daily water temperatures and monthly 

sediment and nutrient loads and adjustment of pertinent 

parameter values to minimize the percent error between annual 

observed and simulated loads. Model performance was evaluated through comparison of (1) percent differences between 

observed and simulated values with target values presented by 

Donigian (2002; table 10), and (2) simulated annual loading 

rates of the selected constituents with observed values. The 

simulations of all water-quality constituents in the Irondequoit 

Creek model were rated “good” to “very good.”

The parameter values for the water-quality components of 

the model were adjusted to provide the best fit of each constituent at all five water-quality monitoring sites. Precise calibration at a given monitoring site was not possible because two 

major assumptions could not be totally met; these assumptions 

were that (1) the primary basin characteristics that controlled 

the removal and transport of constituents in the basin had 

been identified, and (2) the parameter values used to represent 

these characteristics for a given HRU were not affected by the 

HRU’s location (in relation to its assigned precipitation record) 

in the basin. In other words, the best combination of parameter 

values at one calibration point might not have been the best 

at another; therefore, the values that collectively gave the best 

results and minimized the differences between observed and 

simulated values on a basinwide basis were selected.

Calibration of chemical loads was primarily dependent 

on the simulated flows. Any errors in flow would be incorporated into the simulations of sediment and nutrient loads. 

Calibration of the chemical loads was complicated by the 

differences in the major flow components at each monitoring 

site; for example, flow in Irondequoit and Thomas Creeks was 

dominated by ground-water inflow, followed by interflow, 

and then surface runoff; whereas, flow in Allen Creek and its 

East Branch was dominated by surface runoff. These distinctions added to the difficulties in calibrating the nutrient loads 

because the dominant removal and transport mechanisms 

changed from subbasin to subbasin along with the dominant 

flow component. The simulations of nutrient loads were also 

subject to (1) errors in simulated water temperature and dissolved oxygen concentrations, which strongly affect withinchannel microbial activity and the transformations of nutrients, 

and (2) errors in the simulated processes of accumulation and 

removal of sediment from land surfaces and on the movement 

of that sediment from one reach to another, which controls the 

volume and transport of constituents associated with sediment.

Water Temperature

Graphical comparison of daily mean water temperatures 

indicated close agreement between observed and simulated 

values (fig. 12). Errors in the simulated temperatures showed 

a seasonal pattern; simulated temperatures generally were 

higher than observed temperatures from April through June, 

and lower than observed temperatures during December and 

January. The monthly percent differences between simulated 

and observed temperatures ranged from -16.3 to 10.6 percent 

among all five calibration sites, and the percent mean error 

was less than or equal to 5.0 percent, and the percent mean 

absolute error was less than or equal to 6.5 percent at the five 

calibration sites (table 13). The consistent negative percent 

mean errors at all sites indicated an underestimation bias in 

water-temperature simulations. Nonetheless, the water-temperature simulations were rated “very good” on the basis of 

the model-performance criteria as defined by Donigian (2002; 

table 10).

Sediment Loads

Sediment accumulation and washoff from land surfaces, 

and sediment transport within stream channels, was simulated 

to provide an option for improving the calibration for nutrients 

that had strong correlations with sediment load. No sedimentload data were available for the Irondequoit Creek basin; but 

total suspended solids (TSS) loads were measured throughout 

the study period, 1991–2000. TSS and suspended-sediment 

(SS) differ in how their concentrations are measured and in 

how they are generated in a basin. Both constituents are often 

similarly described as the solid-phase material suspended in 

a water-sediment mixture; however, the analytical procedures 

for measuring TSS from an aliquot of a sample and SS from 

the whole sample may produce considerably different results 

(Gray and others, 2000). This difference is especially evident 

42 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
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Figure 12. Daily observed and simulated water temperatures at five calibration sites in the Irondequoit Creek 

basin, Monroe and Ontario Counties, N.Y. (Site locations are shown in figure 1.)

Precipitation-Runoff Model 43
Table 13. Model-performance statistics for monthly simulated water temperature, sediment loads, and chemical loads 

at five water-quality monitoring sites in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.

[Locations of monitoring sites are shown in figure 1. Periods of records for observed water temperature and chemical loads are listed in table 3] 

Statistic

Irondequoit Creek 

at Railroad Mills 

(04232034)

East Branch Allen 

Creek at Pittsford 

(0423204920)

Allen Creek 

near Rochester 

(04232050)

Irondequoit Creek 

at Blossom Road 

(0423205010)

Irondequoit 

Creek at Empire 

Boulevard 

(0423205025)

Mean water temperature

Percent mean error (bias) -3.6 -4.0 -3.0 -5.0 -3.3

Percent mean absolute error 4.8 6.5 6.1 6.1 5.2

Correlation coefficient .98 .97 .91 .98 .95

Model-fit efficiency .94 .92 .91 .92 .95

Observed total suspended solids and simulated sediment loads

Percent mean error (bias) -3.7 -0.8 12 12 5.3

Percent mean absolute error 55 65 56 57 46

Correlation coefficient .60 .53 .66 .65 .64

Model-fit efficiency .22 .25 .39 .39 .41

Orthophosphate loads

Percent mean error (bias) 5.0 -10 18 12 13

Percent mean absolute error 38 66 55 37 39

Correlation coefficient .82 .38 .50 .66 .60

Model-fit efficiency .61 .13 .22 .39 .27

Total phosphorus loads

Percent mean error (bias) 2.7 -2.9 18 -10 -2.1

Percent mean absolute error 33 67 49 54 41

Correlation coefficient .87 .52 .65 .76 .72

Model-fit efficiency .75 .27 .39 .44 .52

Ammonia loads

Percent mean error (bias) 20 -14 17 6.2 5.4

Percent mean absolute error 62 78 59 48 24

Correlation coefficient .51 .27 .43 .70 .85

Model-fit efficiency .10 -.08 .07 .47 .71

Ammonia-plus-organic nitrogen loads

Percent mean error (bias) 11 -0.7 19 1.3 4.3

Percent mean absolute error 31 40 33 29 27

Correlation coefficient .83 .76 .80 .88 .86

Model-fit efficiency .57 .58 .53 .77 .70

Nitrate-plus-nitrite nitrogen loads

Percent mean error (bias) 7.6 -10 8.6 -2.8 3.8

Percent mean absolute error 21 51 28 18 21

Correlation coefficient .90 .81 .90 .94 .92

Model-fit efficiency .71 .56 .80 .87 .84

44 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
when a substantial percentage of the sediment in the sample 

consists of sand-sized material. Also, even though SS and TSS 

loads are generated mainly during periods of storm runoff or 

snowmelt, only TSS loads are measurable under all flow conditions. Therefore, observed TSS was used as a surrogate for 

SS for calibration of sediment loads to the pattern, if not the 

magnitude, of TSS loads (fig. 13).

The percent mean error between the monthly observed 

TSS and simulated sediment loads ranged from -3.7 to 12 percent; no bias in the simulations was indicated (table 13). The 

percent mean absolute errors were between 46 and 65 percent 

at the five calibration sites. The coefficients of correlation 

and model-fit efficiency were low, presumably because of the 

differences between TSS- and SS-load generation as described 

above. Simulated loading rates of sediment were comparable 

to observed TSS rates at all sites (table 14) and generally were 

in the low range of values found in the literature for single 

land-use sites (table 4). Simulated sediment loading rates 

varied little—from 0.28 ton/acre for mixed-rural land use to 

0.25 ton/acre for combined rural and suburban use, and 0.27 

for mixed-urban use. The highest simulated loading rate, 

0.37 ton/acre, was at Irondequoit Creek at Blossom Road. 

This rate was more than twice the rate at Irondequoit Creek 

at Empire Boulevard as a result of the documented decrease 

in particulate loads through sedimentation in the Ellison Park 

wetland (Coon and others, 2000; Coon, 2004).

Nutrient Loads

Atmospheric contributions of nutrients, along with fertilizer-application data and manure-spreading rates, are often 

used in HSPF models where agricultural land covers a large 

percentage of the basin and detailed simulation of nutrienttransformation and uptake processes are required; this requirement does not apply to the Irondequoit Creek basin. Atmospheric contributions of phosphorus and nitrogen, although 

available for the Irondequoit Creek model for this period, were 

not used because their inclusion greatly overestimated the 

quantity of a particular constituent that would be available for 

wash off from a land surface and, thus, hindered calibration of 

the nutrient loads. Therefore, nutrient accumulation rates were 

estimated for the Irondequoit Creek model. 

The simulations of nutrient loads were calibrated to the 

observed monthly loads of orthophosphate (PO4), total phosphorus (TP), ammonia (NH3

), ammonia-plus-organic nitrogen 

(TKN), and nitrate-plus-nitrite nitrogen (NOx) at the five 

water-quality monitoring sites for October 1, 1991, through 

September 30, 1998; and were validated through comparison 

with monthly loads for October 1, 1998, through September 

30, 2000. Nutrient loads were calibrated to minimize the differences between observed and simulated monthly and annual 

loads. Percent differences between observed and simulated 

monthly and annual nutrient loads are rated “very good” when 

the difference is less than 15 percent, “good” when the difference is between 15 to 25 percent, and “fair” when the difference is 25 to 35 percent (table 10; Donigian, 2002). Results of 

the calibrations of phosphorus and nitrogen loads are summarized below.

Phosphorus Constituents

Monthly observed and simulated PO4 loads are presented 

in figure 14. Percent mean absolute errors ranged from 37 to 

66 percent, but the percent mean errors were less than 15 at all 

five monitoring sites except Allen Creek, where it was 18 percent (table 13). Average annual simulated loading rates of PO4

were essentially the same as the observed loading rates at all 

five sites; the greatest difference—0.02 lb/acre—was at East 

Branch Allen Creek (table 14). Overall, the PO4 loads simulated by the Irondequoit Creek model are rated “good.”

Monthly observed and simulated TP loads are presented 

in figure 15. The fit between simulated and observed TP loads 

was similar to that of PO4 loads. Percent mean absolute errors 

for TP ranged from 33 to 67 percent, and the percent mean 

errors were equal to or less than 10 percent at all monitoring 

sites except Allen Creek, where it was 18 percent (table 13). 

No bias in TP simulations was noted. Average annual simulated loading rates of TP were close to observed values at all 

monitoring sites, except Allen Creek, where the simulated 

loading rate of 0.64 lb/acre was substantially higher than the 

observed loading rate of 0.53 lb/acre. (table 14). The simulated loading rates at other sites were within 0.05 lb/acre of 

the respective observed loading rates. The decrease in the TP 

loading rate from Blossom Road to Empire Boulevard resulted 

from TP removal in the intervening Ellison Park wetland 

(Coon and others, 2000; Coon, 2004).

Total phosphorus was difficult to simulate at all stations 

under all flow conditions. Unlike some nutrients, which occur 

in a single form and are transported through a single process, 

phosphorus occurs in dissolved and particulate forms and in 

association with sediment and atmospheric deposition. Phosphorus is also affected by biological processes that vary with 

water temperature and the concentrations of dissolved oxygen, other nutrients (nitrogen), and microbial energy sources 

(carbon). The transport of phosphorus in a stream can be 

complicated by the deposition and scour of sediment to which 

phosphorus can adsorb. The simulated loads of TP failed to 

match observed loads at most monitoring sites during many 

peak-load months (fig. 15). Efforts to decrease these discrepancies at a given site increased the errors in simulated loads 

under other flow conditions or at other sites. 

Nitrogen Constituents

Of the three nitrogen species simulated by the model—

NH3, TKN, and NOx—NH3 made up only a small percentage 

of the total. Therefore, the fit of the latter two components was 

emphasized during the calibration process whenever a tradeoff was necessary between the simulation accuracy of NH3

 and 

that of TKN or NOx. 

Monthly observed and simulated NH3 loads are presented 

in figure 16. Percent mean absolute errors ranged from 24 to 

78 percent, and percent mean errors were equal to or less than 

Precipitation-Runoff Model 45
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Figure 13. Monthly observed total suspended solids (TSS) and simulated sediment loads at five calibration sites in the Irondequoit 

Creek basin, Monroe and Ontario Counties, N.Y. (Site locations are shown in figure 1.)

46 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
20 percent at all monitoring sites (table 13). Average annual 

simulated NH3 loading rates were comparable to the observed 

loading rates (table 14); the maximum difference was 

0.03 lb/acre at the East Branch Allen Creek site. 

Because NH3 loads were small compared to total nitrogen 

loads, small changes in simulated loads could produce large 

percent differences. Simulated loads at Irondequoit Creek at 

Railroad Mills were particularly susceptible to this effect 

(fig. 16), especially during 1994 and 1995, when annual 

observed loads were less than 0.10 ton, and loads for some 

months were zero (Sherwood, 2001). In contrast, the simulated 

loads during these years were comparable to those simulated 

during other years within the calibration period. The extremely 

small observed loads resulted in magnified percent differences. 

The large increase in the NH3 loading rate from Blossom Road 

to Empire Boulevard reflected the generation and export of 

NH3 through wetland processes in the Ellison Park wetland 

(Coon and others, 2000; Coon, 2004).

Monthly observed and simulated TKN loads are presented in figure 17. Percent mean absolute errors ranged from 

27 to 40 percent, and percent mean errors were less than 

20 percent at all monitoring sites (table 13). Comparison of 

average annual observed loading rates with simulated values 

indicated varied results; values were comparable at three 

sites—East Branch Allen Creek, Irondequoit Creek at Blossom Road, and Irondequoit Creek at Empire Boulevard—

whereas the simulated loading rates at Irondequoit Creek at 

Railroad Mills and Allen Creek were 0.22 and 0.57 lb/acre 

higher, respectively, than observed loading rates (table 14).

Monthly observed and simulated NOx loads are presented 

in figure 18. Percent mean absolute errors ranged from 18 to 

51 percent, and percent mean errors were less than or equal 

to 10 percent at all monitoring sites (table 13). Comparison of 

average annual observed loading rates with simulated values 

indicated varied results; differences ranged from 0.08 lb/acre 

at Irondequoit Creek at Blossom Road to 0.71 lb/acre at East 

Branch Allen Creek (table 14).

Total nitrogen loads were computed as the sum of the 

TKN and NOx loads. Calibration and model-performance 

statistics, as well as simulated loading rates (table 14), reflect 

the combined effects of the simulations of these two constituents, and percent differences lie between those previously 

mentioned for these two constituents.

Table 14. Observed and simulated annual loading rates for selected constituents at five water-quality monitoring 

sites in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y., 1991–98.

[Values are in pounds per acre unless otherwise noted. Obs., observed; Sim., simulated; PO4, orthophosphate; TP, total phosphorus; 

NH3, ammonia; TKN, ammonia-plus-organic nitrogen; NOx, nitrate-plus-nitrite nitrogen; TN, total nitrogen; TSS, total suspended solids; --, 

no value available or computed. Locations of monitoring sites are shown in figure 1]

Constituent

Irondequoit Creek 

at Railroad Mills 

(04232034)

East Branch Allen 

Creek at Pittsford 

(0423204920)

Allen Creek 

near Rochester 

(04232050)

Irondequoit Creek 

at Blossom Road 

(0423205010)

Irondequoit Creek 

at Empire Boulevard 

(0423205025)

Obs. Sim. Obs. Sim. Obs. Sim. Obs. Sim. Obs. Sim.

PO4 0.03 0.03 0.12 0.10 0.08 0.09 0.04 0.05 0.06 0.06

TP .39 .40 .65 .62 .53 .64 .69 .64 .38 .40

NH3 .04 .05 .14 .11 .07 .09 .06 .06 .12 .13

TKN 2.06 2.28 3.39 3.31 2.82 3.39 2.67 2.68 2.42 2.55

NOx 3.36 3.65 6.52 5.81 3.82 4.19 3.46 3.38 3.26 3.42

TN 5.42 5.93 9.92 9.12 6.64 7.58 6.14 6.06 5.68 5.98

TSS, tons/acre .28 -- .26 -- .25 -- .35 -- .15 --

Sediment, tons/acre -- .28 -- .25 -- .27 -- .37 -- .16

Precipitation-Runoff Model 47
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Figure 14. Monthly observed and simulated orthophosphate loads at five calibration sites in the Irondequoit Creek basin, Monroe and 

Ontario Counties, N.Y. (Site locations are shown in figure 1.)

48 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
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Figure 15. Monthly observed and simulated total phosphorus loads at five calibration sites in the Irondequoit Creek basin, Monroe 

and Ontario Counties, N.Y. (Site locations are shown in figure 1.)

Precipitation-Runoff Model 49
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Figure 16. Monthly observed and simulated ammonia loads at five calibration sites in the Irondequoit Creek basin, Monroe and 

Ontario Counties, N.Y. (Site locations are shown in figure 1.)

50 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
Figure 17. Monthly observed and simulated ammonia-plus-organic nitrogen loads at five calibration sites in the Irondequoit Creek 

basin, Monroe and Ontario Counties, N.Y. (Site locations are shown in figure 1.)

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Precipitation-Runoff Model 51
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Figure 18. Monthly observed and simulated nitrate-plus-nitrite loads at five calibration sites in the Irondequoit Creek basin, Monroe 

and Ontario Counties, N.Y. (Site locations are shown in figure 1.)

52 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
Model Applications

Three analyses were performed as examples to illustrate 

the utility of the Irondequoit Creek model. The first simulated 

the effects of land-use changes on flooding and stream-water 

quality, and the second simulated the effects of a stormflow 

detention basin on flooding and water quality. The steps 

involved in the creation and analysis of land-use scenarios and 

detention basins in the Irondequoit Creek basin are provided 

in Coon (2003). The third analysis entailed computation of 

flood frequencies from model-generated annual peak flows for 

1971–2000 (the period for which precipitation records were 

available), and comparison with those computed from annual 

peak flows recorded at two streamflow-monitoring sites. The 

model was then revised to simulate nine hypothetical instream 

detention basins of various sizes and drainage areas, and the 

resultant peak flows were then used to compute a third set 

of flood frequencies, from which the probable effects of the 

detention basins on flood magnitudes were assessed. 

These comparative analyses were done through the 

computer program GenScn (Generation and Analysis of 

Model Simulation Scenarios for Watersheds) (Kittle and others, 1998). The WDM file was organized such that (1) flows 

generated from one or two land-use-change scenarios and one 

or two detention-basin scenarios could be uniquely stored for 

each RCHRES, as explained by Coon (2003); and (2) chemical loads of sediment, TP, TKN, NOx, and TN, from as many 

as three scenarios could be simulated and stored in uniquely 

identified files. A user-defined location (such as RCHRES 100 

in subbasin T5) could have data stored from three water-quality scenarios—WQSCEN1, WQSCEN2, and WQSCEN3—as 

identified in the UCI and WDM files.

Land-Use Changes

The Irondequoit Creek basin is undergoing rapid changes 

in land use. Rural areas that were dominated by forests, farms, 

and pasture land are being converted to suburban residential developments and large technology parks and shopping 

malls. Development of the basin is spreading southward and 

eastward in the townships of Pittsford, Victor, Perinton, and 

Penfield (fig. 4). The Town of Mendon and the western part of 

the Town of Victor still retain their rural characteristics, except 

along major thoroughfares, which are subject to commercial 

“strip” development with office buildings, retail stores, restaurants, and other service-related businesses. Water-resources 

managers in the counties and towns are concerned with the 

effect that continued development might have on flooding 

and water quality in the basin. Therefore, a land-use-change 

scenario was simulated to illustrate the process by which the 

model could be used to assess these effects. In that scenario, 

10 percent of the area in subbasin T5 in the southern part of 

the basin (fig. 8) was changed from open and(or) rural grass 

or forested designations to pervious and impervious developed 

areas by revising the acreages listed in the SCHEMATIC module of the UCI file as instructed by Coon (2003). The effects 

of these changes on streamflow and stream-water quality were 

automatically simulated by HSPF. The only other required 

revision to the UCI file (in the EXT TARGETS module) was 

to identify unique dataset numbers in the WDM file in which 

output would be stored. (For example, see WDM dataset numbers in tables 15 and 16). Unique DSNs enabled comparison 

of the original flows and chemical loads with those generated 

by the land-use-change scenario.

Effects on Streamflow

The effects of converting 10 percent of subbasin T5 

from open and(or) rural grass or forested land to pervious 

and impervious developed areas were evaluated through a 

comparison of (1) the peak flows that occurred during eight 

rainstorms (table 15) and (2) the flow durations and storm 

hydrographs produced by the two scenarios (fig. 19). The 

hypothetical land-use change caused peak flows to increase 

by 43.3 percent, on average, which meant that infiltration had 

decreased and in turn caused base flows to decrease, as indicated by the change in flow duration and shown by the storm 

hydrographs of July 4–10, 1998.

Effects on Stream-Water Quality

Annual loads of sediment and total phosphorus increased 

by 11.0 and 3.6 percent, respectively, as a result of the landuse changes in subbasin T5. Loads of TKN and NOx were not 

appreciably affected by the increase in developed area of the 

basin (table 16).

Stormflow-Detention Basin

Mitigation of the adverse effects of urbanization on 

flooding has become a major objective of planning and 

development of populated watersheds. The optimal design 

objective for any flood-control measure would be to maintain postdevelopment discharges at or below predevelopment 

rates for specified storm frequencies. Methods to reduce the 

effects of increased runoff, such as infiltration trenches and 

pits, porous pavement, rooftop storage, and cisterns, can be 

expensive or constrained by site-specific limitations (Natural 

Resources Conservation Service, 1986). Detention basins are 

an effective alternative that has been widely used to control 

peak flows because they (1) are relatively inexpensive as 

compared to other flood-control measures, (2) can be designed 

to fit a wide variety of sites and outflow requirements, (3) can 

be incorporated into a proposed development plan, and (4) can 

be constructed in areas that are limited in their developmental 

potential by their susceptibility to flooding. A detention basin 

can use storage available in these areas for minor (5- to 20-

year recurrence interval) floods without appreciably increasing 

the areal extent of flooding that occurs during major (50- to 

100-year recurrence interval) floods. 

Model Applications 53
Table 15. Changes in peak flows resulting from land-use-change and stormflow-detention 

scenarios in a subbasin of Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.

[Flow values are in cubic feet per second. DSN, dataset number in Watershed Data Management file]

Date of storm

Base 

scenario

(DSN 1001)

Land-use change 

scenario1

(DSN 1004)

Detention basin 

scenario2

(DSN 1002)

Peak flow Peak flow Percent 

difference Peak flow Percent difference

March 27, 1992 31.2 36.4 16.7 35.1 -3.6

August 28, 1992 19.7 44.2 124 34.6 -21.7

April 13, 1994 18.5 24.1 30.3 22.5 -6.6

April 13, 1996 30.2 39.3 30.1 33.5 -14.8

October 19, 1996 42.3 51.7 22.2 47.5 -8.1

December 2, 1996 82.4 97.8 18.7 68.0 -30.5

July 8, 1998 94.3 114 20.9 75.4 -33.9

May 13, 2000 37.8 69.3 83.3 51.5 -25.7

Average percent difference 43.3 -18.1

1

Ten percent of the land area in subbasin T5 was converted from open and(or) rural grass or forested land to 

pervious and impervious developed areas.

2

Stormflow detention in RCHRES T5 was simulated by modifying the outflow rates in the Ftable to 

50 percent of the original rates.

Table 16. Changes in chemical loads resulting from land-use-change and stormflow-detention scenarios in a subbasin of the 

Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.

[Values are in tons. Loads are the sum of annual loads over a 9-year simulation period, 1992-2000. DSN, dataset number in Watershed Data Management file]

Constituent

Base scenario

(WQSCEN1)

Land-use-change scenario1

(WQSCEN2)

Detention-basin scenario2

(WQSCEN3)

DSN Load DSN Load Percent

difference DSN Load Percentdifference

Sediment 9100 5,974 9110 6,631 11.0 9120 4,281 -35.4

Total phosphorus 9101 3.806 9111 3.943 3.6 9121 2.025 -48.6

Ammonia-plus-organic nitrogen 9102 21.84 9112 22.14 1.4 9122 15.17 -31.5

Nitrate-plus-nitrite nitrogen 9103 26.10 9113 25.98 -0.5 9123 12.99 -50.0

Total nitrogen 9104 47.95 9114 48.13 0.4 9124 28.17 -41.5

1

Ten percent of the land area in subbasin T5 was converted from open-grass or forested land to pervious and impervious developed areas.

2

Stormflow detention in RCHRES T5 was simulated by modifying the outflow rates in the Ftable to 50 percent of the original rates.

54 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
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Figure 19. Effects of hypothetical land-use changes and stormflow detention on streamflow in 

subbasin T5 of Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.: (A.) Flow duration. 

(B.) Hydrograph for storm of July 4–10, 1998. (Site location is shown in figure 8.)

Model Applications 55
Detention basins can be incorporated into a site-development plan to mitigate the effects of individual projects on 

flooding and sediment and nutrient loads, or, alternatively, 

large stormwater-management facilities can be installed adjacent to or within a stream channel to mitigate the cumulative 

effects of extensive urbanization. Often, detention basins are 

desired for multiple purposes—water-quality improvement as 

well as flood mitigation. A single detention basin might not 

fulfill both purposes, however, because flood control is optimized by providing the maximum storage capacity, whereas 

water-quality improvement is optimized by maximizing the 

detention time of stormwater. The longer the detention period, 

the less storage is available for a subsequent storm. 

The effects of a detention basin on flooding and water 

quality were illustrated through a modification of the previous 

land-use-change scenario by simulation of an instream detention basin in subbasin T5; detention was simulated as a 50-percent decrease in the outflow rate, following the steps described 

by Coon (2003). The water-quality effects of this detention 

basin were simulated as a best-management practice through 

the BMPRAC module as discussed previously in the section 

“Simulation Complexities.” In addition to the steps described 

by Coon (2003), the following two steps were required to 

activate the BMPRAC option in the model: 

 (1) In the OPN SEQUENCE block, a line for the applicable BMPRAC was added as shown for the hypothetical 

detention basins included in the model. 

 (2) In the SCHEMATIC block, the RCHRES-toRCHRES link was replaced by a pair of commands that route 

output from the RCHRES to the BMPRAC (with mass-link 

20) and from the BMPRAC to the downstream RCHRES 

(with mass-link 21) as shown for the hypothetical detention 

basins included in the model. This substitution automatically 

identified the proper mass links and the removal fractions 

associated with each constituent that was affected by the 

detention basin. As with the land-use-change scenario, unique 

dataset numbers were identified in the EXT TARGETS 

module so that previously stored values in the WDM file that 

might be required for comparison with the current scenario 

would not be overwritten. 

Effects on Streamflow

The inclusion of a detention basin in subbasin T5 

decreased peak flows by an average of 18.1 percent below 

those simulated for the land-use-change scenario (table 15). 

The magnitude of the decrease in peak flow increased with 

an increase in the original (base scenario) peak flow. In other 

words, the detention basin caused a decrease in low and 

medium peak flows below those generated by the land-use 

change, but these peaks were not smaller than the original 

peaks. The effectiveness of the detention basin increased with 

increasing runoff, and peak flows were decreased, not only to 

below those of the land-use-change scenario, but also below 

the original flows.

Effects on Stream-Water Quality

Simulation of the detention basin in subbasin T5 for 

water-quality improvement resulted in substantial decreases 

in constituent loads (table 16) that paralleled the percent 

removals that were input to the model through the BMPRAC 

module. TP and NOx loads decreased by about 50 percent; 

TKN by 32 percent; and sediment by 35 percent. The basin 

decreased loads of all constituents below those simulated for 

the base scenario.

Flood-Frequency Analysis

Flooding in the Irondequoit Creek basin has been, and 

continues to be, a serious problem, especially in heavily developed areas, such as Panorama Plaza, a commercial development that lies on the flood plain and occupies almost the entire 

valley bottom near the confluence of Allen and Irondequoit 

Creeks (fig. 1). Various measures to control the frequency and 

magnitude of flooding in that area have been proposed; one is 

the construction of instream detention basins to decrease peak 

flows. The Irondequoit Creek model was used to assess the 

probable changes in flood frequencies that would result from 

one existing and nine hypothetical detention basins of various 

sizes and drainage areas at selected locations throughout the 

Irondequoit Creek basin (fig. 8). 

The UCI file was revised to permit simulation of a longer 

period (1970–2000) than was used for calibration of the 

model. The first revision was application of the Rochester Airport precipitation record to the part of the basin that ordinarily 

would use the Victor record as precipitation input from 1970 

to 1985 because the Victor precipitation record did not begin 

until January 1, 1986. This revision meant that only one precipitation record was used for the entire basin during this 16-

year early period. This revision could have a substantial effect 

on the simulated flows because precipitation is a major driving 

force for the model. The second revision entailed omission of 

the estimated diversions from the NYS Erie (Barge) Canal into 

the basin. These estimates were based on intermittent measurements of discharges from the canal, which did not begin 

until the spring of 1986 at the siphon sites on Allen and East 

Branch Allen Creeks, and the spring of 1988 at the waste-gate 

sites at Cartersville and Fairport. The effect of this omission 

on model results was considered negligible, however, because 

this analysis was concerned only with annual peak flows. 

Two additional factors that affected model results were (1) 

extension of the simulation period beyond the calibration and 

validation periods (1990–2000), and (2) an occasional poor 

temporal match between observed and simulated peaks. The 

extension of the simulation period back to 1970 ignored the 

assumption of a stable precipitation-to-runoff relation during 

the 30-year extended simulation period. Differences in the 

timing of simulated peak flows in comparison to the dates of 

observed peaks was not unexpected, and the annual maximum 

56 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
simulated flows were used in the following calculations of 

flood frequencies regardless of their date of occurrence.

Flood frequencies were computed with the program 

PEAKFQ (Thomas and others, 1998), which fits the logarithms of the peak flows to a Pearson Type-III frequency 

distribution (Interagency Advisory Committee on Water Data, 

1982). Flood frequencies for simulated annual peak flows 

were computed and compared with those for observed annual 

peak flows (fig. 20A; table 17). Differences between flood frequencies ranged from 10 to 760 ft3

/s for 5-yr and 500-yr recurrence-interval (RI) flows, respectively, on Allen Creek, and 

from 0 to 370 ft3/s for 2-yr and 500-yr RI flows on Irondequoit 

Creek above Blossom Road. After simulation of 50-percent 

reductions in flow at the Jefferson Road stormwater-management facility and at the nine hypothetical detention basins, 

flood frequencies for the simulated annual peak flows were 

recomputed and indicated that these reductions would result 

in 14- to 17-percent decreases in peak flows on Allen Creek, 

and 17- to 18-percent decreases on Irondequoit Creek at Blossom Road (fig. 20B; table 17), if the basins were installed 

as proposed and designed to mimic the storage capacity and 

outflow rates as simulated by the Irondequoit Creek model. 

This analysis indicated, however, that even with the 50-percent 

decrease in flows at the 10 detention basins, overbank flooding 

(albeit with shallower depths than now occur) would probably 

occur at a similar frequency as is currently (2003) experienced, especially in the flood-plain area of Panorama Plaza. 

Thus, substantial decreases in overbank-flooding frequency 

would require larger detention basins that would control runoff 

from a greater percentage of the basin than those simulated 

by the model. The nine hypothetical detention-basin locations 

assessed in this analysis were points on a map selected by the 

IWC for simulation purposes. The feasibility of constructing 

any one of these basins was not evaluated and would require a 

site-specific survey to identify the hydraulic, economic, social, 

and environmental limitations of a given site, and the capability of such a basin to achieve the detention benefits that were 

simulated in this analysis.

Summary

The 150 mi2 Irondequoit Creek basin in Monroe and 

Ontario Counties, N.Y. is underlain by sedimentary rock that 

dips gently to the south-southwest. Bedrock is overlain by 

glacial deposits throughout most of the basin. Sand-and-gravel 

outwash partly fills the buried preglacial Irondogenesee River 

valley and forms the present-day Irondogenesee aquifer. Soils 

in the basin are derived from glacial deposits, and their characteristics—permeability, erodibility, and runoff potential—are 

directly related to the parent materials in which they formed.

Virtually all of the Irondequoit Creek basin has been 

affected by human activity. Presently (2003), more than 

50 percent of the basin is in some form of developed condition. The southern third of the basin is predominantly rural 

and agricultural and consists mostly of pasture, row crops, and 

forests. Suburban development increases northward across 

the basin and occupies large parts of the Towns of Henrietta, 

Pittsford, Perinton, and Penfield. High-density residential, 

commercial and industrial land uses dominate the northwestern corner of the basin, which includes parts of the Town of 

Brighton and the City of Rochester. 

Irondequoit Creek flows northward down the approximate center of the basin with the Allen Creek subbasin to the 

west and the Thomas Creek subbasin to the east. The creek is 

32.6 mi long and descends 525 ft at its head in Ontario County 

to its mouth at Irondequoit Bay. Almost 7 percent of the basin 

consists of wetlands, lakes, and ponds. The New York State 

Erie (Barge) Canal cuts across the basin, dividing it into 

northern and southern sections and complicating basin hydrology. Ground-water flow generally is toward nearby streams, 

although regional flow is northward toward Lake Ontario. 

Urbanization has aggravated flooding and, along with agricultural activities, has contributed to the degradation of streamwater quality in the basin.

A precipitation-runoff model of the basin that uses the 

HSPF (Hydrological Simulation Program—FORTRAN) 

model code was developed by the U.S. Geological Survey 

(USGS), in cooperation with the Irondequoit Creek Watershed 

Collaborative, to assist water-resource managers in addressing 

the problems of urbanization and to guide decisions regarding 

future development in the basin. The model enables simulation 

of the effects of land-use changes and stormflow-detention 

basins on flooding and nonpoint-source pollution on the basin. 

The hydrology, stream-water temperature, and sediment and 

nutrient loads of the basin were simulated and calibrated with 

data collected from five USGS streamflow and water-quality-monitoring sites. The basin was divided into hydrologic 

response units (HRUs)—areas where hydrologic and waterquality processes were assumed to be uniform—on the basis 

of land use and land cover, soil permeability, and slope.

The Irondequoit Creek basin presented many modeling 

complexities, including areas where ground water moves out 

of the surface-water-defined basin, hydrologic connections 

with and diversions from the Erie (Barge) Canal, and surface 

water lost to fractured bedrock or diverted out of the basin. 

Wetlands were simulated separately on the basis of their location in the basin and their dominant functions. One existing 

stormflow-detention basin and nine hypothetical ones were 

simulated to permit assessment of their individual and collective effects on flooding and water quality. 

Model performance was evaluated through a combination 

of graphical comparisons and statistical tests and indicated 

“very good” agreement (mean error less than 10 percent) 

between observed and simulated daily and monthly streamflows, between observed and simulated monthly water temperatures, and between observed total suspended solids loads 

and simulated sediment loads. Agreement between monthly 

observed and simulated nutrient loads was “very good” (mean 

error less than 15 percent) or “good” (mean error between 15 

and 25 percent).

Summary 57
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Figure 20. Flood frequencies for observed and simulated annual peak flows at two sites in the Irondequoit Creek basin, 

Monroe and Ontario Counties, N.Y.: (A.) Flood frequencies for observed and simulated peak discharges. (B.) Changes in flood 

frequencies resulting from detention basins. (Site locations are shown in figure 1.)

58 Effects of Land-Use Changes and Stormflow-Detention Basins on Flooding and Pollution, Irondequoit Creek Basin, N.Y.
The model and associated files were designed to permit 

creation of scenarios that represent planned or hypothetical 

development in the basin, and assessment of flooding and 

chemical loads that are likely to result. These scenarios were 

created simply by changing the acreages associated with 

HRUs found in a subbasin. Instream stormflow-detention 

basins could subsequently be modeled in a separate scenario 

to assess the potential mitigative possibilities of this management practice. Several revisions to the model were required to 

simulate instream detention basins, including modification of 

a reach’s storage capacity or outflow rates, and activation of a 

HSPF module (BMPRAC) that is designed to simulate chemical load reductions resulting from a best-management practice. 

A filing system for scenario output was established within a 

data-management file to facilitate use of the model by waterresource managers. 

Three examples of model applications are presented: 

(1) assessment of land-use changes; (2) inclusion of a 

stormflow-detention basin at the downstream end of a 

subbasin; and (3) assessment of the combined effects of 10 

stormflow-detention basins on peak flows. Flows and loads 

of sediment and nutrients that resulted from the land-usechange scenario, in which 10 percent of a rural subbasin 

was converted from forest and grassland to pervious 

and impervious developed areas, were compared with 

predevelopment values through a post-processing program 

that was directly linked to the data-management file. Peak 

flows and loads of sediment and total phosphorus increased. 

Inclusion of a stormflow-detention basin mitigated these 

effects by lowering peak flows, some to less than the original 

observed peaks, and substantially decreased the simulated 

loads of sediment, phosphorus, and nitrogen. The combined 

effects of one existing stormflow-detention basin and nine 

hypothetical basins on flooding were assessed through a 

flood-frequency analysis of the simulated annual peak flows 

on Allen Creek and Irondequoit Creek at Blossom Road. The 

model was revised to span a 30-year (1970–2000) period and 

to simulate 50-percent flow reductions from the detention 

basins. Flood flows decreased by 14 to 17 percent on Allen 

Creek and by 17 to 18 percent on Irondequoit Creek at 

Blossom Road.

Acknowledgments

Thanks are extended to those from the Monroe County 

Environmental Health Laboratory, who operated the streamflow and water-quality monitoring stations and analyzed the 

water samples collected from these sites, and to the many individuals from each of the towns and counties in the Irondequoit 

Creek Watershed Collaborative, who provided additional data. 

Table 17. Changes in flood frequency of annual peak flows resulting from one existing and nine hypothetical stormflow-detention 

basins at two sites in the Irondequoit Creek basin, Monroe and Ontario Counties, N.Y.

[Flows are in cubic feet per second. Site locations are shown in figure 1]

Peak-flow 

recurrence 

interval

(years)

Allen Creek (04232050) Irondequoit Creek above Blossom Road (0423205010), 

1971 to 2000

Observed 

peaks, 

1960-2000

Simulated 

peaks, 

1960-20001

Simulated 

peaks, 

1971-20002

Simulated peaks 

with detention 

basins, 1971-2000

Percent 

decrease 

in peak 

flow

Observed 

peaks3

Simulated 

peaks

Simulated peaks 

with detention 

basins

Percent 

decrease 

in peak 

flow

2 814 785 821 709 14 1,340 1,340 1,100 18

5 1,190 1,200 1,260 1,070 15 2,090 2,060 1,690 18

10 1,470 1,530 1,600 1,360 15 2,680 2,630 2,160 18

25 1,860 2,020 2,090 1,760 16 3,550 3,450 2,840 18

50 2,180 2,430 2,510 2,100 16 4,290 4,150 3,420 18

100 2,520 2,890 2,970 2,480 16 5,120 4,920 4,070 17

200 2,890 3,400 3,480 2,890 17 6,040 5,780 4,780 17

500 3,420 4,180 4,250 3,510 17 7,430 7,060 5,850 17

1

Simulated peak flows were available from 1971 to 2000 only. Observed peaks were added from 1960 to 1970 to extend the period of record to a length 

comparable to the observed peak-flow record. 

2

Simulated peak flows were available from 1971 to 2000 only. The flood frequencies were recomputed for this time period to permit comparison with the 

flood frequencies computed from the peak flows for simulated detention basins. 

3

Observed peak flows were available for 1982 to 2000 only. Simulated peaks were added from 1971 to 1981 to extend the period of record to a length comparable to the simulated peak-flow record. 

Acknowledgments 59
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References 65

Sources of the Geographic Information System coverages, data—meteorological, soils, channel cross-section elevations, streamflow, and water-quality—and computer programs 

that were used in development of the Irondequoit Creek model 

are listed below.

Geographic Information System Coverages

Digital (Surface) Elevation Models (DEMs): 10- by 10-meter 

grid size; 0.1 meter elevation resolution; by 7.5 minute 

USGS quadrangles. Elevation accuracy is plus or minus 

half the contour interval. Obtained from Cornell University 

Geospatial Information Repository (CUGIR) at http://cugir.

mannlib.cornell.edu.

Hydrology and drainage-area delineation: base maps obtained 

from U.S. Geological Survey, Troy, N.Y.

Wetlands: (1) U.S. Fish and Wildlife Service National Wetlands Inventory obtained from www.nwi.fws.gov/maps. 

(2) New York State Department of Environmental Conservation Regulatory Freshwater Wetlands for Monroe and 

Ontario counties obtained from CUGIR at http://cugir.

mannlib.cornell.edu/Isite/CUGIR_DATA. (3) Areas delineated on town maps.

Land cover–land use: National Land Cover Data; 30- by 

30-meter Landsat thematic mapper data acquired by the 

Multi-resolution Land Characterization Consortium; 

nominal-1992 acquisitions. Obtained from New York State 

GIS Clearinghouse at www.nysgis.state.ny.us, or CUGIR at 

http://cugir.mannlib.cornell.edu. Revisions based on Monroe and Ontario Counties tax-parcel maps, obtained from 

respective county offices.

Surficial and bedrock geology: obtained from New York State 

Museum Publications Department at www.nysm.nysed.gov.

Bedrock elevation: contours digitized from Young (1980) for 

Monroe County and from Leggette and others (1935) for 

Ontario County.

Statewide digital orthophotography: obtained from New York 

State GIS Clearinghouse at www.nysl.nysed.gov/gis/gateway/inde.html.

Slope data: derived in GIS program, ArcInfo (Environmental 

Systems Research Institute, 1994), from DEM data.

Ground-water divide: digitized from plate 4, Yager and others 

(1985).

Miscellaneous Data

Climatic data: obtained from (1) Environmental Protection 

Agency at www.epa.gov/OST/ftp/basins/wdm_data/NY_

wdm.exe, (2) National Climatic Data Center, National Oceanic and Atmospheric Administration at www.ncdc.noaa.

gov, and (3) Northeast Regional Climate Center, Cornell 

University at http://met-www.cit.cornell.edu.

Soil permeability: areas were digitized from Plate 3, Yager and 

others (1985); these original data were extracted from Monroe, Ontario, and Wayne Counties’ soil surveys (Heffner 

and Goodman, 1973; Pearson and Cline, 1958; Higgins and 

Neeley, 1978, respectively). Permeability for areas identified as “urban with no permeability classification” in these 

references were obtained from a generalized map of waterinfiltration potential (Waller and others, 1982); the source of 

which data was Sweet and others (1938).

Channel cross-section data: obtained from town and village 

Federal Emergency Management Agency (FEMA) Flood 

Insurance Studies (hydraulic data for water-surface profile 

analyses), or extracted from DEMs using ArcInfo (Environmental Systems Research Institute, 1994) GIS programs 

and adjusted by field measurements of channel widths and 

depths.

Streamflow data: obtained from USGS database, ADAPS.

Water- and atmospheric-deposition quality data: obtained from 

USGS database, QWDATA.

Computer Programs

HSPF, ANNIE, IOWDM, HSPEXP, and CGAP: all obtained 

from USGS web site http://water.usgs.gov/software.

WDMUtil and HSPFParm: obtained from http://www.epa.

gov/OST/BASINS/

GenScn: obtained from ftp://hspf.com/GenScn.

Appendix—Sources of Data

Appendix 67
Prepared by the New York and New Hampshire-Vermont Water Science Centers Publications Units

For more information concerning the research in this report, contact:

Rafael W. Rodriguez, Director

U.S. Geological Survey

New York Water Science Center

425 Jordan Rd.

Troy, NY 12180-8349

or visit our Web site at:

http://ny.water.usgs.gov