U.S. Department of the Interior

U.S. Geological Survey

SIMULATION OF STREAMFLOW AND WATER QUALITY

IN THE RED CLAY CREEK SUBBASIN OF THE

CHRISTINA RIVER BASIN, PENNSYLVANIA AND DELAWARE,

1994-98

Water-Resources Investigations Report 03-4138

In cooperation with the

DELAWARE RIVER BASIN COMMISSION,

DELAWARE DEPARTMENT OF NATURAL RESOURCES AND ENVIRONMENTAL

CONTROL, and the

PENNSYLVANIA DEPARTMENT OF ENVIRONMENTAL PROTECTION
U.S. Department of the Interior

U.S. Geological Survey

SIMULATION OF STREAMFLOW AND WATER QUALITY

IN THE RED CLAY CREEK SUBBASIN OF THE

CHRISTINA RIVER BASIN, PENNSYLVANIA AND DELAWARE,

1994-98

by Lisa A. Senior and Edward H. Koerkle

Water-Resources Investigations Report 03-4138

In cooperation with the

DELAWARE RIVER BASIN COMMISSION,

DELAWARE DEPARTMENT OF NATURAL RESOURCES AND ENVIRONMENTAL

CONTROL, and the

PENNSYLVANIA DEPARTMENT OF ENVIRONMENTAL PROTECTION

New Cumberland, Pennsylvania

2003
ii

U.S. DEPARTMENT OF THE INTERIOR

GALE A. NORTON, Secretary

U.S. GEOLOGICAL SURVEY

Charles G. Groat, Director

Any use of trade, product, or firm names in this report is for identification purposes only and does not imply

endorsement by the U.S. Geological Survey.

For additional information Copies of this report may be

write to: purchased from:

District Chief U.S. Geological Survey

U.S. Geological Survey Branch of Information Services

215 Limekiln Road Box 25286, Federal Center

New Cumberland, Pennsylvania 17070 Denver, Colorado 80225-0286

Email: dc_pa@usgs.gov Telephone 1-888-ASK-USGS

Internet Address: http://pa.water.usgs.gov
Contents iii

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

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

Purpose and scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Previous studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Description of study area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Physical setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Geology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Soils. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

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

Land use. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Water use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Description of model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Data for model input and calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Model-input data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Meteorologic data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Water-use data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Spatial data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Model-calibration data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Hydrologic data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Water-quality data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Simulation of streamflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Sensitivity analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Model limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Simulation of water quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Water temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Sediment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Dissolved oxygen and biochemical oxygen demand. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Nitrogen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Phosphorus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63

Sensitivity analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

Model limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

Model applications. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

References cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

Appendixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

CONTENTS

Page
iv Contents

Figures 1-3. Maps showing:

1. Location of the Christina River Basin and its four major subbasins and

water-quality monitoring sites, Pennsylvania, Delaware,

and Maryland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2. Mapped soil associations in the Red Clay Creek Basin, Pennsylvania

and Delaware. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

3. Location of National Oceanic and Atmospheric Administration

meteorologic stations and calculated Thiessen polygons in the

vicinity of the Red Clay Creek Basin, Pennsylvania and Delaware . . . . . 11

4-5. Graphs showing:

4. Monthly precipitation measured at the Wilmington Airport National

Oceanic and Atmospheric Administration and Porter Reservoir

meteorologic stations near the Red Clay Creek Basin, 1994-98 . . . . . . . . . 12

5. Monthly estimates of potential evapotranspiration for Wilmington

Airport, Delaware, 1994-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

6-8. Maps showing:

6. Generalized 1995 land-use map for the Red Clay Creek Basin . . . . . . . . . . . . . 16

7. Location of streamflow-measurement stations and water-quality

monitoring sites in the Red Clay Creek Basin. . . . . . . . . . . . . . . . . . . . . . . . 18

8. Graph showing relation between water-quality constituents and streamflow

for stormflow and base-flow samples collected in 1998 at streamflowmeasurement station 01480000, Red Clay Creek at Woodale, Del. . . . . . . . . . . . . . . . 22

9-10. Boxplots showing:

9. Distribution of concentrations of suspended solids, total ammonia

plus organic nitrogen, and dissolved nitrate in samples collected

under stormflow and base-flow conditions at the monitoring site,

01480000 Red Clay Creek at Wooddale, Del., 1998. . . . . . . . . . . . . . . . . . . . 23

10. Distribution of concentrations of dissolved and total ammonia, dissolved

orthophosphate, and total phosphorus in samples collected under

stormflow and base-flow conditions at the monitoring site,

01480000 Red Clay Creek at Wooddale, Del., 1998. . . . . . . . . . . . . . . . . . . . 24

11. Map showing location of segments, model-reach drainage area, and stream

reaches (RCHRES) delineated for HSPF model of the Red Clay Creek Basin . . . . . . 25

12-40. Graphs showing:

12. Simulated and observed daily mean streamflow at three streamflowmeasurement stations in the Red Clay Creek Basin for the period

October 1, 1994, through October 29, 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . 29

13. Simulated and observed streamflow at the nonpoint-source water-quality

monitoring site in the Red Clay Creek Basin for the sampling period

January 1 through October 29, 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

14. Duration curves of simulated and observed hourly mean streamflow for

three sites on the main stem Red Clay Creek for the period

October 1, 1994, through October 29, 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . 31

ILLUSTRATIONS

Page
Contents v

Figures 12-40. Graphs showing:—Continued

15. Cumulative difference between simulated and observed daily mean

streamflow at streamflow-measurement station 01480015, Red Clay

Creek near Stanton, Del., October 1, 1994, through October 29, 1998 . . . . 33

16. Simulated surface runoff, interflow, and base-flow monthly flow

contributions from pervious land segments (PERLNDs) at the most

downstream calibration site in the Red Clay Creek Basin, 01480015

Red Clay Creek near Stanton, Del., 1996-97 . . . . . . . . . . . . . . . . . . . . . . . . . 34

17. Simulated hourly mean and observed instantaneous water temperature at

streamflow-measurement stations (A) 01479820, Red Clay Creek near

Kennett Square, Pa., (B) 01480000, Red Clay Creek at Wooddale, Del.,

and (C) 01480015, Red Clay Creek at Stanton, Del., October 1994 -

October 1998. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

18. Simulated and observed streamflow and suspended-sediment

concentrations and period of composite sample during five storms

in 1998 at streamflow-measurement station 01480000, Red Clay

Creek at Wooddale, Del.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

19. Simulated hourly mean streamflow and suspended-sediment

concentrations, and observed instantaneous streamflow and total

suspended-solids concentrations under base-flow conditions at

monitoring site, 01480000, Red Clay Creek at Wooddale, Del., 1998. . . . . 42

20. Simulated hourly mean and observed instantaneous streamflow at

streamflow-measurement stations (A) 01479820, Red Clay Creek near

Kennett Square, Pa., (B) 01480000, Red Clay Creek at Wooddale, Del.,

and (C) 01480015, Red Clay Creek at Stanton, Del., October 1994 -

October 1998. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

21. Simulated hourly mean suspended-sediment and observed instantaneous

total suspended-solids concentrations and hourly mean loads at

streamflow-measurement stations (A) 01479820, Red Clay Creek near

Kennett Square, Pa., (B) 01480000, Red Clay Creek at Wooddale, Del.,

and (C) 01480015, Red Clay Creek at Stanton, Del., October 1994 -

October 1998. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

22. Simulated daily mean and observed instantaneous dissolved-oxygen

concentrations at streamflow-measurement stations (A) 01479820,

Red Clay Creek near Kennett Square, Pa., (B) 01480000, Red Clay

Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek at Stanton,

Del., October 1994 through October 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

23. Simulated hourly mean and observed instantaneous dissolved-oxygen

concentrations at streamflow-measurement stations (A) 01479820,

Red Clay Creek near Kennett Square, Pa., (B) 01480000, Red Clay

Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek at Stanton,

Del., October 1994 through October 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

24. Simulated and observed concentrations of chlorophyll a in base-flow

samples at streamflow-measurement station 01480000 Red Clay Creek

at Wooddale, Del., 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

ILLUSTRATIONS—Continued

Page
vi Contents

Figure 12-40. Graphs showing:—Continued

25. Simulated hourly mean and observed instantaneous concentrations of

chlorophyll a at streamflow-measurement stations (A) 01480000

Red Clay Creek at Wooddale, Del., and (B) 01480015, Red Clay Creek

at Stanton, Del., October 1994 through October 1998 . . . . . . . . . . . . . . . . . 50

26. Simulated and observed concentrations of 20-day biological oxygen

demand in base-flow samples at streamflow-measurement station

01480000 Red Clay Creek at Wooddale, Del., 1998. . . . . . . . . . . . . . . . . . . . 51

27. Simulated hourly mean and observed instantaneous 20-day biochemical

oxygen demand concentrations and loads at streamflow-measurement

stations (A) 01479820, Red Clay Creek near Kennett Square, Pa.,

(B) 01480000, Red Clay Creek at Wooddale, Del., and (C) 01480015,

Red Clay Creek at Stanton, Del., October 1994 - October 1998 . . . . . . . . . 52

28. Simulated and observed streamflow and dissolved-nitrate concentrations

and period of composite sample during five storms in 1998

at streamflow-measurement station 01480000, Red Clay Creek at

Wooddale, Del.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54

29. Simulated and observed concentrations of (A) nitrate, (B) dissolved

ammonia, and (C) particulate ammonia during base-flow conditions

in 1998 at streamflow-measurement station 01480000 Red Clay Creek

at Wooddale, Del. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

30. Simulated hourly mean and observed instantaneous nitrate

concentrations and loads at streamflow-measurement stations

(A) 01479820, Red Clay Creek near Kennett Square, Pa., (B) 01480000,

Red Clay Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek

at Stanton, Del., October 1994 through October 1998 . . . . . . . . . . . . . . . . . 58

31. Simulated and observed streamflow and dissolved-ammonia

concentrations and period of composite sample during five storms

in 1998 at streamflow-measurement station 01480000, Red Clay

Creek at Wooddale, Del.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

32. Simulated and observed streamflow and particulate ammonia

concentrations and period of composite sample during five storms

in 1998 at streamflow-measurement station 01480000, Red Clay Creek

at Wooddale, Del. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

33. Simulated hourly mean and observed instantaneous total ammonia

concentrations and loads at streamflow-measurement stations

(A) 01479820 Red Clay Creek near Kennett Square, Pa., (B) 01480000,

Red Clay Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek

at Stanton, Del., October 1994 through October 1998 . . . . . . . . . . . . . . . . . 62

34. Simulated and observed streamflow and dissolved-orthophosphate

concentrations and period of composite sample during five storms

in 1998 at streamflow-measurement station 01480000, Red Clay

Creek at Wooddale, Del.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

35. Simulated and observed streamflow and particulate orthophosphate

concentrations and period of composite sample during five storms

in 1998 at streamflow-measurement station 01480000, Red Clay Creek

at Wooddale, Del. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

ILLUSTRATIONS—Continued

Page
Contents vii

Figure 12-40. Graphs showing:—Continued

36. Simulated hourly mean and observed instantaneous dissolved and

particulate orthophosphate concentrations during base-flow

conditions in 1998 at streamflow-measurement station 01480000

Red Clay Creek at Wooddale, Del. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

37. Simulated hourly mean and observed instantaneous dissolved

orthophosphate concentrations and loads at streamflow-measurement

stations (A) 01479820, Red Clay Creek near Kennett Square, Pa.,

(B) 01480000, Red Clay Creek at Wooddale, Del., and (C) 01480015,

Red Clay Creek at Stanton, Del., October 1994 through October 1998 . . . 72

38. Sediment and phosphorus yields in relation to percent agricultural land

use as calculated from observed data for subbasins in the Chesapeake

Bay Watershed and as simulated by the Hydrological Simulation

Program–Fortran (HSPF) model for selected subbasins in the

Brandywine Creek, White Clay Creek, and Red Clay Creek Basins . . . . . 79

39. Yields of nitrate and ammonia in relation to percent agricultural land

use as calculated from observed data for subbasins in the

Chesapeake Bay Watershed and as simulated by the Hydrological

Simulation Program–Fortran (HSPF) model for selected subbasins

in the Brandywine Creek, White Clay Creek, and Red Clay

Creek Basins. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

40. Duration curves of observed daily mean streamflow at 01480000

Red Clay Creek at Wooddale, Del., for the period April 1, 1943,

through September 30, 2001, and for the period of simulation,

October 1, 1994, through October 29, 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . 81

TABLES

Table 1. Nonpoint-source water-quality monitoring sites, Christina River Basin,

Pennsylvania and Delaware . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2. Annual and total precipitation at meteorologic stations near the Red Clay

Creek Basin, Pennsylvania and Delaware, 1994-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3. Days of snowfall and snow-on-ground at the National Oceanic and Atmospheric

Administration meteorologic station Coatesville 2 W, 1994-98 . . . . . . . . . . . . . . . . . . 13

4. Stream withdrawals and discharges of flow and ammonia and phosphorus loads

included in the Hydrological Simulation Program–Fortran (HSPF) model of

the Red Clay Creek Basin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

5. Land-use categories used in the Hydrological Simulation Program–Fortran model

of the Red Clay Creek Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

6. Streamflow-measurement stations in the Red Clay Creek Basin. . . . . . . . . . . . . . . . . . . . . 17

7. Water-quality monitoring sites in the Red Clay Creek Basin during 1994-98 . . . . . . . . . . 19

8. Constituents in nonpoint-source monitoring samples to be determined by

laboratory chemical analysis, Red Clay Creek Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

ILLUSTRATIONS—Continued

Page
viii Contents

Table 9. Reach number, length, drainage area, segment number, and percent of land-use

category in reach-drainage areas for Red Clay Creek model . . . . . . . . . . . . . . . . . . . . 26

10. Calibration criteria and errors for HSPF simulated streamflow at three gaging

sites in the Red Clay Creek Basin, for the period October 1, 1994, through

October 29, 1998. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

11. Statistics for comparison of observed and simulated hourly and daily mean

streamflow at the nonpoint-source water-quality monitoring site during the

January - October 1998 nonpoint-source monitoring period and at three

water-quality monitoring sites during the January 1994 - October 1998

calibration period in the Red Clay Creek Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

12. Observed and simulated streamflow for Red Clay Creek near Stanton, Del.,

1994-98 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

13. Sensitivity analysis of modeled runoff characteristics at Red Clay Creek near

Stanton, Del. (01480015), to variations in selected pervious land (PERLND)

parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

14. Suggested criteria to evaluate water-quality calibration for an Hydrologic

Simulation Program–Fortran (HSPF) model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

15. Cumulative calibration errors in flow volume and constituent loads for selected

storms in 1998 at 01480000 Red Clay Creek at Wooddale, Del., the nonpointsource monitoring site in the Red Clay Creek Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

16. Simulated and observed streamflow and loads of suspended sediment for storms

sampled in 1998 at 01480000 Red Clay Creek at Wooddale, Del.. . . . . . . . . . . . . . . . . 40

17. Observed annual precipitation and simulated annual sediment yields by land

use for three segments of Hydrological Simulation Program–Fortran (HSPF)

model for Red Clay Creek Basin, 1995-97 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

18. Observed annual precipitation and simulated average annual sediment yield by

land use for pervious and impervious land areas in three segments of

Hydrological Simulation Program–Fortran (HSPF) model for Red Clay

Creek Basin, 1995-97 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

19. Simulated and observed streamflow and loads of biochemical oxygen demand

for storms sampled in 1998 at the nonpoint-source monitoring site, 01480000

Red Clay Creek at Wooddale, Del. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

20. Simulated and observed streamflow and loads of dissolved nitrate, dissolved

ammonia, and particulate ammonia for storms sampled in 1998 at the

nonpoint-source monitoring site, 01480000 Red Clay Creek at Wooddale, Del. . . . . 55

21. Observed annual precipitation and simulated annual nitrate yields by land use

for the three segments of the Hydrological Simulation Program–Fortran

(HSPF) model for Red Clay Creek Basin, 1995-97 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

22. Observed annual precipitation and simulated mean annual nitrate yield by

land use for pervious and impervious land areas in the three segments of

the Hydrological Simulation Program–Fortran (HSPF) model for Red Clay

Creek Basin, 1995-97 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

23. Observed annual precipitation and simulated annual total ammonia yields by

land use for the three segments of the Hydrological Simulation Program–

Fortran (HSPF) model for Red Clay Creek Basin, 1995-97 . . . . . . . . . . . . . . . . . . . . . . 66

TABLES—Continued

Page
Contents ix

Table 24. Observed annual precipitation and simulated mean annual total ammonia

yield for pervious and impervious land areas in the three segments of the

Hydrological Simulation Program–Fortran (HSPF) model for Red Clay Creek

Basin, 1995-97. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

25. Simulated and observed streamflow and dissolved and particulate orthophosphate

loads for storms sampled in 1998 at the nonpoint-source monitoring site,

01480000 Red Clay Creek at Wooddale, Del . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

26. Observed annual precipitation and simulated annual total (dissolved plus adsorbed)

orthophosphate yields by land use for the three segments of the Hydrological

Simulation Program–Fortran (HSPF) model for Red Clay Creek Basin, 1995-97 . . . 73

27. Observed annual precipitation and simulated mean annual total orthophosphate

yield by land use for pervious and impervious land areas in the three segments

of the Hydrological Simulation Program–Fortran (HSPF) model for Red Clay

Creek Basin, 1995-97 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

28. Sensitivity of model output for sediment and nutrient yields at streamflowmeasurement station 01480015 Red Clay Creek near Stanton, Del., to changes in

selected parameters affecting sediment contributions from pervious land areas . . . 75

29. Sensitivity of model output for total nutrient yields at streamflow-measurement

station 01480015 Red Clay Creek near Stanton, Del., to changes in selected model

parameters affecting nutrient contributions from pervious land areas . . . . . . . . . . . 76

30. Simulated total loads and loads per acre in 1995 for selected headwater

model-reach drainage areas in the Hydrological Simulation Program–Fortran

(HSPF) model of the Red Clay Creek Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

31. Total simulated nonpoint-source and estimated point-source loads of nitrate,

ammonia, and phosphorus for the 4-year period October 1994 through

September 1998, Red Clay Creek Basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

APPENDIXES

Appendix 1. Results of laboratory analyses of stormflow and base-flow samples . . . . . . . . . . . . . . . . . 87

2. User control input file for Red Clay Creek HSPF model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

TABLES—Continued

Page
x Contents

Multiply By To obtain

Vertical coordinate information is referenced to the National Geodetic Vertical Datum of 1929 (NGVD 1929);

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

Abbreviated water-quality units used in report:

L, liter

mg/L, milligrams per liter

μg/L, micrograms per liter

mL, milliliter

μS/cm, microsiemens per centimeter at 25 degrees Celsius

Length

inch (in) 25.4 millimeter

foot (ft) 0.3048 meter

mile (mi) 1.609 kilometer

Area

acre 4,047 square meter

square mile (mi2

) 2.590 square kilometer

Volume

million gallons (Mgal) 3,785 cubic meter

cubic foot (ft3) 0.02832 cubic meter

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

Flow rate

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

million gallons per day (Mgal/d) 0.04381 cubic meter per second

inch per hour (in/hr) 0.0254 meter per hour

Mass

pound, avoirdupois (lb) 0.4536 kilogram

pound per hour (lb/h) 0.4536 kilogram per hour

pound per day (lb/day) 0.4536 kilogram per day

ton, short (2,000 lb) 0.9072 megagram

Hydraulic gradient

foot per mile (ft/mi) 0.1894 meter per kilometer (m/km)

Application rate

pounds per acre (lb/acre) 1.121 kilograms per hectare

tons per acre (ton/acre) 2.242 megagrams per hectare

tons per acre per year [(ton/acre)/yr] 2.242 megagrams per hectare per year

Temperature

degree Fahrenheit (°F) °C=5/9 (°F-32) degree Celsius

CONVERSION FACTORS, DATUMS AND ABBREVIATED WATER-QUALITY UNITS
Abstract 1

ABSTRACT

The Christina River Basin drains 565 square

miles (mi2) in Pennsylvania and Delaware and includes

the major subbasins of Red Clay Creek, White Clay

Creek, Brandywine Creek, and Christina River. The Red

Clay Creek is the smallest of the subbasins and drains an

area of 54 mi2. Streams in the Christina River Basin are

used for recreation, drinking-water supply, and to

support aquatic life. Water quality in some parts of the

Christina River Basin is impaired and does not support

designated uses of the stream. A multi-agency, waterquality management strategy included a modeling

component to evaluate the effects of point and nonpointsource contributions of nutrients and suspended

sediment on stream water quality. To assist in nonpointsource evaluation, four independent models, one for each

of the four main subbasins of the Christina River Basin,

were developed and calibrated using the model code

Hydrological Simulation Program–Fortran (HSPF).

Water-quality data for model calibration were collected

in each of the four main subbasins and in smaller

subbasins predominantly covered by one land use

following a nonpoint-source monitoring plan. Under

this plan, stormflow and base-flow samples were

collected during 1998 at 1 site in the Red Clay Creek

subbasin and at 10 sites elsewhere in the Christina

River Basin.

The HSPF model for the Red Clay Creek subbasin

simulates streamflow, suspended sediment, and the

nutrients, nitrogen and phosphorus. In addition, the

model simulates water temperature, dissolved oxygen,

biochemical oxygen demand, and plankton as secondary

objectives needed to support the sediment and nutrient

simulations. For the model, the basin was subdivided

into nine reaches draining areas that ranged from 1.7 to

10 mi2. One of the reaches contains a regulated reservoir. Ten different pervious land uses and two impervious land uses were selected for simulation. Land-use

areas were determined from 1995 land-use data. The

predominant land uses in the Red Clay Creek subbasin

are agricultural, forested, residential, and urban.

The hydrologic component of the model was run

at an hourly time step and calibrated using streamflow

data from three U.S. Geological Survey (USGS)

streamflow-measurement stations for the period of

October 1, 1994, through October 29, 1998. Daily

precipitation data from one National Oceanic and

Atmospheric Administration (NOAA) gage and hourly

data from one NOAA gage were used for model input.

The difference between observed and simulated streamflow volume ranged from -0.8 to 2.1 percent for the

4-year period at the three calibration sites. Annual

differences between observed and simulated streamflow

generally were greater than the overall error for the

4-year period. For example, at a site near Stanton, Del.,

near the bottom of the basin (drainage area of 50.2 mi2),

annual differences between observed and simulated

streamflow ranged from -5.8 to 6.0 percent and the

overall error for the 4-year period was -0.8 percent.

Calibration errors for 36 storm periods at the three

calibration sites for total volume, low-flow-recession

rate, 50-percent lowest flows, 10-percent highest flows,

and storm peaks were 20 percent or less. Much of the

error in simulating storm events on an hourly time step

can be attributed to uncertainty in the rainfall data.

The water-quality component of the model was

calibrated using nonpoint-source monitoring data

collected in 1998 at one USGS streamflowmeasurement station and other water-quality

monitoring data collected at three USGS streamflowmeasurement stations. The period of record for waterquality monitoring was variable at the stations, with an

end date of October 1998 but the start date ranging

from October 1994 to January 1998. Because of

availability, monitoring data for suspended-solids

concentrations were used as surrogates for suspendedsediment concentrations, although suspended solids

may underestimate suspended sediment and affect

apparent accuracy of the suspended-sediment

simulation. Comparison of observed to simulated loads

for five storms in 1998 at the one nonpoint-source

monitoring site at Wooddale, Del., indicates that

simulation error commonly is as large as an order of

magnitude for suspended sediment and nutrients. The

simulation error tends to be smaller for dissolved

SIMULATION OF STREAMFLOW AND WATER QUALITY

IN THE RED CLAY CREEK SUBBASIN OF THE

CHRISTINA RIVER BASIN,

PENNSYLVANIA AND DELAWARE, 1994-98

By Lisa A. Senior and Edward H. Koerkle
2 Introduction

nutrients than particulate nutrients. Errors of

40 percent or less for monthly or annual values indicate

a fair to good water-quality calibration according to

recommended criteria, with much larger errors possible

for individual storm events. Assessment of the accuracy

of the water-quality calibration under stormflow

conditions is limited by the sparsity of available waterquality data in the basin.

Users of the Red Clay Creek HSPF model should

be aware of model limitations and consider the following

when predictive scenarios are desired: streamflowduration curves indicate the model simulates streamflow reasonably well when evaluated over a broad range

of conditions and time, although streamflow and the

corresponding water quality for individual storm events

may not be well simulated; streamflow-duration curves

for the simulation period compare well with duration

curves for the 57.5-year period ending in 2001 at

Wooddale, Del., and include all but the extreme highflow and low-flow events; calibration for water quality

was based on sparse data, with the result of increasing

uncertainty in the water-quality simulation.

INTRODUCTION

The Christina River Basin (fig. 1), which

includes Red Clay Creek (54 mi2), White Clay

Creek (drainage area of 108 mi2), Brandywine

Creek (327 mi2), and the Christina River itself

(76 mi2), drains approximately 565 mi2 in southeastern Pennsylvania, northern Delaware, and a

small part of northeastern Maryland. The Christina

River and its tributaries provide drinking water for

more than 40 percent of the residents of Chester

County, Pa., and more than 50 percent of the residents of New Castle County, Del.

Stream waters of the Christina River Basin

are used for public water supply and recreation

and to support aquatic life. Some of these uses are

threatened because water quality has been

impaired by point and nonpoint sources of contamination. Causes of impairment have been identified as sediment, nutrients, and bacteria (Greig

and others, 1998). In addition, some agricultural

areas of the basin are undergoing urbanization,

and the effects of land-use changes on water quality and quantity are unknown. The States of Delaware and Pennsylvania need tools to evaluate

alternative approaches for correcting present

water-quantity and water-quality problems and

for forecasting future conditions.

A 5-year water-quality management strategy

for the Christina River Basin, starting in 1995, was

conceived and directed by the Delaware Department of Natural Resources and Environmental

Control (DNREC), Pennsylvania Department of

Environmental Protection (PADEP), Chester

County Conservation District (CCCD), Water

Resources Agency (WRA) of New Castle County,

Chester County Water Resources Authority

(CCWRA), New Castle County Conservation District, Delaware River Basin Commission (DRBC),

U.S. Environmental Protection Agency (USEPA),

watershed groups and other concerned organizations, groups, and individuals. To assist with the

water-quality management process, the U.S. Geological Survey (USGS) developed a nonpointsource monitoring plan and constructed a hydrologic and water-quality model of the basin to estimate sediment and nutrient contributions from

nonpoint sources. USGS conducted the Christina

River Basin nonpoint-source monitoring and modeling in cooperation with DRBC, DNREC, and

PADEP.

A widely used model, Hydrological Simulation Program—Fortran (HSPF) (Bicknell and others, 1997), was selected as a tool for the waterresources planning and management needs for the

Christina River Basin. Each of the four major subbasins in the Christina River Basin was modeled

separately because HSPF can be applied only to

free-flowing, non-tidal streams, and the lower

reaches of the Christina River and its tributaries,

Brandywine Creek, White Clay Creek and Red

Clay Creek are tide-affected. The watershed

model, HSPF, can be used to simulate the delivery

of nonpoint-source contaminants to main-stem

streams. The model can simulate hydrologic processes, physical transport of nonpoint-source contaminants, and instream chemical reactions. Data

required for this watershed model include concentrations of contaminants of interest over a range of

hydrologic conditions from various land-use areas

that are expected to differ in contribution of nonpoint-source contaminants and hydrologic

response.

The nonpoint-source water-quality sampling

plan, executed in 1997-98, provided streamflow,

nutrient, and suspended solids data that were used

to (1) estimate concentrations and loads of the

selected constituents from various land uses in the

Christina River Basin; and (2) calibrate an HSPF

model of each major subbasin for these selected

constituents. Nonpoint-source water-quality and
Introduction 3

Figure 1. Location of the Christina River Basin and its four major subbasins and water-quality

monitoring sites, Pennsylvania, Delaware, and Maryland.
4 Introduction

streamflow data were collected at four main-stem

sites on the lower free-flowing reaches of the

Christina River and Brandywine, White Clay, and

Red Clay Creeks, and at seven subbasin sites

throughout the Christina River Basin selected principally for land-use characterization (fig. 1;

table 1). All sites were equipped for continuous

streamflow recording and automated water-quality sampling. Six sites were at existing USGS

streamflow-measurement stations (gages), one site

(01480095) was at a discontinued streamflow-measurement station recommissioned for the study,

and four new streamflow/water-quality sites

(01480878, 01480637, 014806318, 01478137) were

constructed for the study (table 1).

The HSPF model for the largest of the subbasins, the Brandywine Creek Basin, was developed

first (Senior and Koerkle, 2003a) and is the basis for

models in the other subbasins, including the Red

Clay Creek Basin. The hydrologic and water-quality characteristics for a specific type of agriculture,

mushroom farming, that is present in the Red Clay

Creek Basin was calibrated during the development of the HSPF model for the White Clay Creek

Basin (Senior and Koerkle, 2003b). Model-input

parameters affecting suspended-sediment and

nutrient contributions from other selected land

uses were calibrated for the Brandywine Creek

model and transferred to the White Clay Creek

model, where applicable. An overview of the

entire monitoring and modeling effort by USGS is

presented in the last of the model reports for the

Christina River Basin (Senior and Koerkle, 2003c).

The HSPF model may be used to evaluate options

for managing contaminants from nonpoint and

point sources and can provide a comprehensive

method of calculating nonpoint-source loads to

meet total maximum daily load (TMDL) requirements. Currently (2003), TMDL assessments are

ongoing in the Christina River Basin.

Purpose and Scope

This report describes the development of an

HSPF model constructed for the Red Clay Creek

subbasin of the Christina River Basin and subsequent hydrologic and water-quality simulations.

The main objective of modeling was to create a tool

to estimate nonpoint-source loads of selected constituents over a range of hydrologic conditions.

The model description includes explanation of the

general aspects, model structure, spatial segmentation, parameterization, and limitations. In addition, data used for model-input and calibration are

Table 1. Nonpoint-source water-quality monitoring sites, Christina River Basin, Pennsylvania and Delaware

(see figure 1 for location of sites)

Type of nonpoint-source

water-quality sampling site

Site

number

on map

Location

U.S. Geological

Survey

streamflowmeasurement

station number

Drainage area

(square miles)

Overall Basin Main-Stem Site

Main stem (White Clay Creek) 1 White Clay Creek near Newark, Del. 01479000 89.1

Main stem (Red Clay Creek) 2 Red Clay Creek near Wooddale, Del. 01480000 47.0

Main stem (Brandywine Creek) 3 Brandywine Creek at Chadds Ford, Pa. 01481000 287

Main stem (Christina River) 4 Christina River at Cooch’s Bridge, Del. 01478000 20.5

Single Land-Use Basins

Urban 5 Little Mill Creek near Newport, Del. 101480095 5.24

Residential - sewered 6 Unnamed tributary to Valley Creek at

Highway 30 at Exton, Pa.

2

01480878 1.47

Residential - unsewered

(on septic systems)

7 Little Broad Run near Marshallton, Pa. 201480637 .6

Agricultural - row crop 8 Doe Run above tributary at Springdell, Pa. 2014806318 11.7

Agricultural - livestock 9 West Branch Brandywine Creek near

Honey Brook, Pa.

01480300 18.7

Agricultural - mushroom 10 Trout Run at Avondale, Pa. 2

01478137 1.31

Forested 11 Marsh Creek near Glenmoore, Pa. 01480675 8.57

1 Streamflow-measurement station restarted for study.

2 New streamflow-measurement station constructed for this study.
Description of Study Area 5

described. The HSPF model for the Red Clay Creek

subbasin was used to simulate streamflow, water

temperature, suspended sediment, and the nutrients, nitrate, ammonia, and orthophosphate, on an

hourly basis. Additionally, the model was used to

simulate water temperature, dissolved oxygen,

biochemical oxygen demand, and plankton as secondary objectives needed to support the sediment

and nutrient simulations on an hourly basis for the

calibration period October 1, 1994, through October 29, 1998. Calibration results, analysis of model

sensitivity to parameter variation, and model limitations are presented and discussed for simulations

of streamflow and water-quality constituents.

Examples of model applications are given, including quantification of nonpoint-source loads from

selected areas of the Red Clay Creek Basin.

Previous Studies

Data on water quality and stream invertebrates collected at two sites in the Red Clay Creek

Basin as part of a long-term monitoring effort in

Chester County, Pa., were evaluated for the period

1969-80 by Moore (1987) and published for the

period of 1981-94 by Reif (1999). Concern about the

presence of contaminants in sediments in the Red

Clay Creek Basin led to a study of metals and

anthropogenic organic compounds in soils and

sediments in the basin (Rice, 1993). Surface-water

quality was related to ground-water quality and

land use in a study of ground-water quality in the

Red Clay Creek Basin using data collected in

1993-94 (Senior, 1996).

Acknowledgments

Water-use data were obtained with the assistance of Gerald Kauffman of the WRA at the University of Delaware, Robert Struble of the

Brandywine Valley Association, and Craig Thomas

of CCWRA. Water-quality data for PADEP monitoring sites in Pennsylvania was provided by

William Goman of PADEP. Information about agricultural uses was obtained from Daniel Greig and

others at CCCD and the New Castle County Conservation District. Overall guidance for the project

was provided by the modeling technical committee of the Christina River Basin Water-Quality

Management group, including David Pollison of

DRBC, Richard Greene and Hassan Mirsajadi of

DNREC, William Goman of PADEP, Jan Bowers of

CCWRA, Gerald Kauffman of WRA, and Larry

Merrill of USEPA. In addition to those mentioned

here, those who helped identify the need for the

project include Nancy Goggin and Jenny McDermott of DNREC and Niki Kasi and Russell Wagner

of PADEP.

DESCRIPTION OF STUDY AREA

The Red Clay Creek drains 54 mi2 in southeastern Pennsylvania and northern Delaware. The

headwaters of Red Clay Creek are in Chester

County, Pa., and the stream flows south into New

Castle County, Del., where it is tributary to the

White Clay Creek, which itself is tributary to the

Christina River (fig. 1). The largest population center in the basin is the borough of Kennett Square,

Pa. The confluence of the East and West Branches

of Red Clay Creek is near the State line between

Pennsylvania and Delaware. Burroughs Run is the

largest named tributary in the Red Clay Creek

Basin.

Physical Setting

The Red Clay Creek Basin encompasses

areas in the Piedmont Physiographic Province in

southeastern Pennsylvania (Berg and others, 1989)

and the Piedmont and Coastal Plain Physiographic

Provinces in northern Delaware. The topography

of the Piedmont Physiographic Province is characterized by gently rolling uplands dissected by narrow valleys, whereas the topography of the

Coastal Plain Physiographic Province is characterized by nearly flat terrain. Elevation of the land

surface in the Red Clay Creek Basin ranges from

near sea level to about 560 ft above sea level. Most

of the basin is in the Piedmont Physiographic

Province, which is underlain predominantly by

metamorphic rocks of igneous and sedimentary

origin. A small part in the southern tip of the basin,

below the Fall Line (fig. 1), is in the Coastal Plain

Physiographic Province, which is underlain by

unconsolidated sediments. The Fall Line forms the

boundary between uplands of the Piedmont and

nearly flat terrain of the Coastal Plain.

Climate

The Red Clay Creek Basin has a modified

humid continental climate. Winters are mild to

moderately cold and summers are warm and

humid. Normal mean annual air temperatures at

National Oceanic and Atmospheric Administration (NOAA) weather station southwest of the

basin at Newark (fig. 1), for 1971-2000 is 54.8°F

(12.7°C) (National Oceanic and Atmospheric

Administration, 2000a). Normal mean annual air
6 Description of Study Area

temperatures (1971-2000) are cooler north of the

basin (51.5°F at Coatesville, Pa.) than south of the

basin (54.4°F at Wilmington, Del.) (National

Oceanic and Atmospheric Administration, 2000a,

2000b). At Newark, the normal mean temperature

(1971-2000) for January, the coldest month, is

32.5°F (0.3°C), and normal mean temperature

(1971-2000) for July, the warmest month, is 76.4°F

(24.7°C). Normal mean annual precipitation

(1971-2000) at Newark is 45.35 in. Precipitation is

distributed fairly evenly throughout the year. In

southeastern Pennsylvania and northern Delaware, snowfall is mainly in the months of December, January, February, and March.

Geology

The Red Clay Creek Basin is underlain by

Paleozoic-age and older metamorphosed sedimentary and igneous rocks. The metasediments

include schist, quartzite, and carbonate rocks. The

Paleozoic-age and older rocks have been folded,

faulted, and metamorphosed various times during

their history, resulting in a structurally complex

assemblage. The primary structural trends are eastnortheast. In the southernmost part of the basin,

below the Fall Line (fig. 1), these rocks are overlain

by Cretaceous-age and quaternary-age sands and

gravels of the Coastal Plain. These Coastal Plain

sediments were deposited on the older bedrock,

forming beds that thicken to the southeast.

Soils

Five soil associations and 15 soil series are

found in the Red Clay Creek Basin (fig. 2) (Kunkle,

1963; Matthews and Lavoie, 1970). In general, the

soils have developed in place and are derived from

the underlying bedrock. Most of the soils are

developed on schist, gneiss, and quartzite, with the

exception of the Hagerstown-Conestoga-Guthrie

association, which is developed on carbonate

rocks, and soils south of the Fall Line, which are

developed on unconsolidated Coastal Plain sediments.

Figure 2. Mapped soil associations in the

Red Clay Creek Basin, Pennsylvania and

Delaware.
Description of Study Area 7

The principal soil association is GlenelgManor-Chester, which overlies almost 90 percent

of the Red Clay Creek Basin. Soils in this association generally are gently to moderately sloping

and well drained. Surface permeabilities of individual soil series range from 0.6 to 2.0 in/hr except

for the Aldino, Hagerstown, Manor, and

Neshaminy series that are limited in extent. Permeabilities in these four series range from 2.0 to

6.3 in/hr.

Hydrology

The metamorphosed sedimentary and igneous rocks that underlie most of the Red Clay Creek

Basin form fractured-rock aquifers. The competent

bedrock is overlain by weathered rock, saprolite,

and soil. The bedrock and overlying materials are

recharged by precipitation. Ground water flows

through the secondary openings (fractures) in fractured-rock aquifers and discharges locally to

streams and springs. The sands and gravels of the

Coastal Plain in the southern tip of the Red Clay

Creek Basin also are recharged by precipitation.

Recharge to these sedimentary beds may discharge

locally to streams and also may recharge the individual beds that dip to the southeast. Ground

water in the Coastal Plain sands and gravels flows

through primary openings (pore spaces).

Approximately 40 percent of the annual

input of precipitation to the Red Clay Creek Basin

is discharged as streamflow (Vogel and Reif, 1993).

The remaining precipitation is lost to evapotranspiration. Streamflow is composed of, on average,

65-percent base flow (ground-water discharge) and

35-percent surface runoff (Vogel and Reif, 1993)

with between year variations of 10 percent not

uncommon. Streams in the Red Clay Creek Basin

mostly are low to moderate gradient. Channel bottoms in higher gradient reaches and forested areas

primarily are exposed bedrock, sand, and gravel.

In low-gradient reaches and pools, channel bottoms are covered in places with finer-grained sediment.

A number of hydraulic structures are located

throughout the Red Clay Creek Basin. The primary

purposes of these structures are impoundment. In

the lower Red Clay Creek Basin, Hoopes Reservoir,

on a tributary to the Red Clay Creek, impounds

6,300 acre-feet. Hoopes Reservoir is regulated

actively to store water pumped from the Brandywine Creek for use as drinking-water supply to the

city of Wilmington, Del. Little water is released

from Hoopes Reservoir to Red Clay Creek,

although, occasionally, water is released to augment flows. The remaining structures consist of

historic low-head dams situated on the mainstem

Red Clay Creek.

Land Use

Land use in the Red Clay Creek Basin in

1993-95 as determined from aerial photographs

was predominantly agricultural, forested, and residential, with lesser amounts of open and urban

land, including industrial and commercial uses

(Greig and others, 1998). From data compiled for

the 1993-95 period, estimated land use in the basin

is about 37 percent agricultural, 28 percent residential, 24 percent forested, 5 percent open, 3 percent

urban, and 2 percent other.

Water Use

Water use in the Red Clay Creek Basin consists of withdrawals and discharges of surface

water and ground water for residential, commercial, and industrial consumptive and non-consumptive uses. Commonly, water from a surfacewater intake or ground-water well is withdrawn,

used as needed, and returned to the source as

waste flow minus consumptive losses. Waste flows

return to surface waters through wastewater-treatment facilities and industrial discharges. In the less

urbanized parts of the basin, ground water is the

primary water supply through wells on individual

properties. Wastewater in these non-sewered areas

typically is discharged and infiltrates to ground

water mainly through septic systems on individual

properties. In and near population centers, public

water suppliers use surface water as the main

water source but may augment with ground water.

A few public water systems rely on ground water

for supply. Wastewater in urban areas generally is

carried by sewers to treatment facilities that typically discharge to streams although alternative

methods have been recently used in the area. Two

municipal systems for disposal of treated waste

water through land treatment (spray irrigation)

have been constructed in the Red Clay Creek Basin

since 1995.

Some of the larger public water systems

maintain complex withdrawal, distribution, and

discharge facilities that allow water redistribution

within or between basins. Although no water is

directly withdrawn from Red Clay Creek for drinking-water supply, water is withdrawn for this pur-
8 Description of Model

pose from White Clay Creek just below the

confluence of Red Clay Creek, treated, and put in a

distribution system that supplies users in Red

Clay, White Clay, and Brandywine Creek Basins. In

addition, the City of Wilmington withdraws from

the Brandywine Creek Basin but commonly stores

some of this water in the Hoopes Reservoir in the

Red Clay Creek Basin. Occasionally, water is

released from Hoopes Reservoir to augment low

flows in the Red Clay Creek. Some of the water

purveyors that supply drinking water in the Red

Clay Creek Basin also have the option to import

water from the West Branch Octoraro Creek in the

Susquehanna River Basin, which borders the

northwestern edge of the Christina River Basin.

In the Christina River Basin, impaired water

quality has been linked to water-use processes

such as wastewater treatment, industrial discharges, and septic systems (Greig and others,

1998). The effects of these processes on streamflow

and water quality in the Red Clay Creek can vary

depending on their location and volumes.

DESCRIPTION OF MODEL

The numerical model HSPF includes a set of

computer codes for algorithms used to simulate

the hydrologic response of land areas to precipitation and flow through stream channels in a basin.

The algorithms used to simulate these processes

are described in detail by Bicknell and others

(1997). The precipitation-driven simulation of

streamflow includes response from pervious and

impervious land areas and routing of water in the

stream channel. Pervious and impervious land

areas are assigned hydrologic-response parameters

on the basis of land use and other characteristics

such as slope. Streamflow routing is controlled by

channel characteristics of model reaches. The HSPF

model can be used to simulate free-flowing

streams and well-mixed reservoirs but cannot be

used to simulate tidal streams.

The HSPF model structure requires dividing

the basin into multiple elements whose number

and size reflect the range of selected hydrologic

characteristics and the scope of available input

data. A first step in structuring the model is segmenting the basin. Segmentation commonly is

delimited by climatological or physical characteristics that would determine specific hydrologic

response to precipitation. When little differences

are apparent in physical characteristics, segmentation may be determined by the number and location of precipitation stations available for input.

The basin also is subdivided into pervious

(PERLND) and impervious (IMPLND) land-use

types. Within each model segment, each PERLND

and IMPLND is assigned hydrologic-response

parameters. These parameters control the partitioning and magnitude of hydrologic outputs in

response to input precipitation. The stream channel is then partitioned into reaches (RCHRES). A

RCHRES generally is delimited by major flow

inputs (tributaries, etc.), calibration locations

(streamflow gages, water-quality sites), and timeof-travel considerations. Each RCHRES receives

flow from land area draining to that reach and

from upstream RCHRES. Runoff, interflow, and

ground water from each PERLND and IMPLND is

directed to a RCHRES. Point-source withdrawals

and discharges can be specified for the RCHRES

where they are located. The overall model structure including assignment of time-series data

(meteorological, streamflow, point-source withdrawals, and discharges), reach connections, landarea to reach relations, channel characteristics, and

land-use category response parameters are

described in the user control input (UCI) file.

The hydrologic response of PERLNDs and

IMPLNDs is handled by their respective modules.

The water budget, or predicted total runoff, for

pervious land is simulated using the section

PWATER of the PERLND module. Total runoff is

the sum of base flow (ground-water discharge to

streams), interflow, and surface runoff. The hydrologic processes modeled by PWATER include infiltration of precipitation, interception by plant

materials, evapotranspiration, surface runoff,

interflow, and ground-water flow. Precipitation

may be evaporated from, move through, and(or)

remain in storage in surface interception, surface

detention, interflow, upper soil zone, lower soil

zone, and active ground water. Predicted total runoff for impervious land is simulated using the section IWATER of the IMPLND module. The

hydrologic processes simulated by IWATER

include retention, routing, and evaporation of

water from impervious areas.

Runoff derived from snowfall, snow accumulation, and snow melt is simulated using the

module SNOW. Meteorological data are used to

determine when precipitation is rain or snow, calculate an energy balance for the snow pack, and

determine the effect of heat fluxes on the snow

pack. The amount of precipitation that occurs as

snow in the Red Clay Creek Basin is highly vari-
Description of Model 9

able. Some years have no snow; others may have

snow and snow cover for most of the winter

months. The assumption was made that simulating snow would result in a more accurate streamflow simulation. However, periods cold enough to

have substantial snowfall also may have poor

observed streamflow record because of channel ice

at streamflow-measurement locations and consequent poor-quality calibration data.

The routing of water in the stream channel is

simulated by the section HYDR of the module

RCHRES. Routing is based on kinematic-wave or

storage-routing methods, where flow is assumed

to be unidirectional. HYDR calculates rates of outflow and change in storage for a free-flowing reach

or completely mixed reservoir. RCHRES inflows

include runoff from PERLND and IMPLND land

areas draining to that reach, water from upstream

RCHRES, precipitation falling directly on the

RCHRES surface area, and other discharges to the

reach. RCHRES outflows include flow to the

downstream reach, withdrawals from the reach,

and evaporation. A series of reaches are used to

represent the actual network of stream channels.

For each RCHRES, a relation between depth,

surface area, volume, and outflow (discharge) is

assigned and specified in an F-TABLE. When available, data for the F-TABLEs were derived from

stage-discharge ratings for streamflow-measurement stations at RCHRES endpoints. For reaches

that do not end at a streamflow-measurement station, data for the F-TABLE were generated using

the computer program XSECT. XSECT calculates

depth-discharge relations for a hypothetical stream

channel, assuming a trapezoidal shape and using

specified stream length, stream slope, channel

width, channel depth, floodplain slope, Manning’s

n for the stream channel, and Manning’s n for the

floodplain.

The water-quality component of HSPF simulates contributions from pervious and impervious

land areas and accounts for selected chemical reactions in the stream reaches. The model includes

algorithms to describe the transport of constituents

from the land to the stream reach, chemical reactions affecting selected constituents in the reach,

sediment exchange between channel bed and

water column, and the temperature of runoff and

water in a reach. Contributions of constituents

from land areas may vary by land-use category in

the model. Water-quality simulation requires a calibrated hydrodynamic model.

Water temperature, dissolved oxygen, and

carbon dioxide in surface runoff, interflow, and

ground-water outflows from pervious land areas

are simulated in the PWTGAS section of the

PERLND module and from impervious lands in

the IWTGAS section of the IMPLND module.

Water temperature in each reach is simulated by

the HTRCH section of the module RCHRES and

includes heat transported by PERLND and

IMPLND outflows and point-source discharges.

The main heat-transfer processes considered are

transfer by advection, where water temperature is

treated as a thermal concentration, and transfer

across the air-water interface. Heat gain and loss

by radiation also is simulated. Meteorological data,

such as air temperature and wind speed, are used

in the simulation of stream temperature. In-stream

dissolved oxygen concentrations are simulated by

the OXRX section of the RCHRES module that

includes the processes of advections, aeration, and

consumption of oxygen by biological oxygen

demand.

The simulation of sediment includes transport of sediment from land areas and transport

within the stream channel. Sediment release from

pervious areas is simulated in the SEDMNT module. Sediment available for transport is generated

by detachment associated with rainfall. Detached

sediment is transported to the stream as washoff.

Scour also may be simulated for pervious areas.

Sediment release for impervious areas is simulated

in the SOLIDS module. Buildup of solids on impervious areas is transported to the stream in surface

runoff. Sediment transport in the stream channel is

simulated in the SEDTRN module. The channel

simulation includes scour and deposition of bed

material but not bank material.

The transport of nutrients from the land to

the stream is simulated in the PQUAL module for

pervious areas and IQUAL module for impervious

areas. For pervious areas, nutrients associated with

soil are transported with sediment in surface runoff. Nutrients also enter the stream in interflow

and ground-water discharge. For impervious

areas, nutrients accumulate on the surface and are

washed into the stream during storm events. Once

in the stream, the transport and chemical interactions of nutrients are simulated by the modules

NUTRX and PLANK. The NUTRX and PLANK

modules require an active OXRX module for

instream simulation of dissolved oxygen and biological oxygen demand. The NUTRX module

includes physical transport and inorganic chemical
10 Data for Model Input and Calibration

reactions affecting nutrients. The PLANK module

simulates the effect of phytoplankton and periphyton in the stream and includes uptake and release

of nutrients.

DATA FOR MODEL INPUT

AND CALIBRATION

HSPF requires a large amount of data to

characterize effectively the hydrologic and waterquality response of the watershed to precipitation

and other inputs (Donigian and others, 1984). Data

used in creating and defining the model structure

and parameters were derived principally from spatial analysis of basin characteristics and previously

published information. Spatial data analyzed for

model construction includes land use, land-surface

slope, and soil associations. Time-series input for

streamflow and water-quality simulation include

meteorologic, precipitation quality, water-use, and

discharge quantity and quality data. Calibration

data consisted of observed streamflow for the

hydrodynamic simulation and observed water

temperatures and laboratory analyses of grab and

composite stream samples for the water-quality

simulation.

Time-series data for model input and model

output were processed and stored in the binary

format Watershed Data Management (WDM) database. The WDM format is the standard format for

input to and output from HSPF. The computer programs ANNIE (Flynn and others, 1995), IOWDM

(Lumb and others, 1990), METCMP (Alan Lumb,

U.S. Geological Survey, and John Kittle, Aqua

Terra Consultants, written commun., 1995),

WDMUtil (U.S. Environmental Protection Agency,

1999), and GenScn (Kittle and others, 1998) were

used in the processing of WDM time-series data.

Parameter and model-structure data were processed independently of the time-series data and

are defined in the UCI, an ascii text file.

Model-Input Data

The types, resolution, and quantity of the

data needed for input are determined by (1) the

hydrologic and water-quality processes to be

included in the model; (2) the time step selected for

simulation; (3) the length of the simulation period;

and (4) the spatial scale of interest. For example,

simulation of streamflow requires time-series

inputs of precipitation, potential evaporation,

withdrawals from streams, and discharges to

streams. Simulation of stream water quality

requires, in addition to parametric estimates of

chemical inputs from pervious and impervious

land areas, time-series inputs of water-temperature

data and constituent loads in point-source discharges. Because only a limited amount of

recorded water-temperature data were available

for the Red Clay Creek Basin that could be used as

model input, water temperature was simulated.

The simulation of water temperature requires

input of additional meteorological data.

The Red Clay Creek model was run on a

1-hour time step. Time-series data available only at

time intervals greater than hourly required disaggregation. For the simulation period of October 1,

1994, through October 1998, more than 4 years of

reported or estimated hourly values were needed

for the time-series input data sets.

Meteorologic Data

Simulation of mean hourly streamflow in

HSPF required inputs of hourly precipitation and

potential evapotranspiration. Daily precipitation

data used for model input were selected from local

NOAA meteorologic stations based on Thiessen

polygon delineations and analysis of the precipitation records. In addition, hourly precipitation data

for the Red Clay Creek Basin were collected at one

of nine raingages installed in the Christina River

Basin specifically for this modeling effort. However, these data were not used because of their

short period of record (December 1997 to October

1998), which only covered about a quarter of the

model-simulation period, their limitations to any

future extension of the simulation period, and

overall poor quality (related to raingage malfunctions). Daily precipitation data were disaggregated

using METCMP into hourly data based on hourly

precipitation recorded at the NOAA station at the

Wilmington, Del., Airport. Daily potential evapotranspiration data were disaggregated at the time

of simulation.

Thiessen polygons created for all local

NOAA meteorologic stations overlaid the Red

Clay Creek Basin in four areas (fig. 3). The Porter

Reservoir station polygon covered about 60 percent of the central basin; Coatesville 2 W station

polygon covered about 20 percent of the northwest

basin; Newark University Farm station polygon

covered about 10 percent of the northwest basin;

and Wilmington Airport station polygon covered

about 10 percent of the southern basin. Precipitation for these meteorologic stations is listed in

table 2.
Data for Model Input and Calibration 11

The 1994-98 period of simulation spanned

relatively normal, dry, and wet years of precipitation. For example, the long-term (1971-2000)

“normal” annual precipitation as calculated from

monthly precipitation at Wilmington Porter Reservoir is 49.4 in. (Delaware State Climatologist, 2001).

In comparison to the “normal” annual precipitation at Porter Reservoir, the years 1994 and 1995

and the 10-month period of 1998 were within

15 percent of normal (table 2). The greatest departures were in 1996 when annual precipitation was

39 percent above normal and in 1997 when annual

precipitation was 21 percent below normal.

1 Precipitation for January 1 through October 29.

Figure 3. Location of National Oceanic and Atmospheric Administration meteorologic stations and

calculated Thiessen polygons in the vicinity of the Red Clay Creek Basin, Pennsylvania and Delaware.

Table 2. Annual and total precipitation at meteorologic

stations near the Red Clay Creek Basin, Pennsylvania

and Delaware, 1994-98

Raingage

(fig. 3)

Precipitation, in inches

1994 1995 1996 1997 11998 Total

Coatesville

2 W

50.2 47.2 75.1 39.3 39.0 250.8

Porter

Reservoir

57.4 45.1 68.9 38.9 37.0 247.3

Newark

University

Farm

43.9 40.6 60.5 36.9 32.2 214.1

Wilmington

Airport

45.4 40.1 52.4 28.0 34.2 200.1
12 Data for Model Input and Calibration

Comparison of the period-of-simulation precipitation totals shows substantial differences

(table 2) between meteorologic stations. For the

4-year 10-month period, Porter Reservoir reported

23 percent more precipitation than Wilmington

Airport, which is about 10 mi to the south. The

monthly distribution of precipitation (fig. 4) indicates that differences of 30 percent or more

between the Porter Reservoir and Wilmington Airport stations were common. This difference shows

up as a consistent recording bias over the period of

simulation (fig. 4). Comparison of precipitation

data at Porter Reservoir to precipitation data at

other NOAA meteorologic stations near the Red

Clay Creek Basin shows precipitation totals for the

period to be less at Newark University Farm

southwest of the basin (-13 percent) and greater at

Coatesville 2 W to the north of the basin (3 percent)

(table 2). Some of the differences between gages

may be due to spatial variability. The precipitation

record indicates that annual totals decrease from

northeast to southwest across the basin. Although

some discrepancies in total precipitation can be

expected across the basin, a review of numerous

raingage-network studies in the eastern United

States showed that annual differences at adjacent

gages averaged 5 percent or less (Winter, 1981) and

that those differences tend to decrease over longer

periods of record and increase for shorter periods.

Because the Porter Reservoir Thiessen polygon covers 60 percent of the basin, Porter Reservoir

data were selected as the sole precipitation input to

Red Clay Creek Basin model. However, adjustment factors were applied to the Porter Reservoir

precipitation record to account for the northeast to

southwest decrease in observed precipitation, to

complete a satisfactory water balance for the simulation period (Donigian and others, 1984), and

because of the unusually large differences in total

rainfall between meteorologic stations proximate

to Red Clay Creek Basin. The final factors applied

to adjust the precipitation at Porter Reservoir to

input in the Red Clay Creek Basin were from north

to south, 0.9, 0.87, and 0.85 for the three segment

areas of the Red Clay Creek model.

Precipitation data may contain a number of

errors. Measurement errors, whereas known in

general, are not specifically known for the gages

used in the Red Clay Creek model. These errors

may include malfunctioning equipment, incorrect

calibration, and environmental effects (Winter,

1981). Precipitation data from NOAA meteorologic

stations adjacent to the station selected for the

model show departures as great as 15 percent over

the simulation period, whereas individual storm

events have departures as much as 300 percent.

Thus, storms with substantial precipitation in one

J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S

1994 1995 1996 1997 1998

0

20

2

4

6

8

10

12

14

16

18

OBSERVED MONTHLY PRECIPITATION, IN INCHES

PORTER RESERVOIR

WILMINGTON AIRPORT

Figure 4. Monthly precipitation measured at the Wilmington Airport National Oceanic and Atmospheric

Administration and Porter Reservoir meteorologic stations near the Red Clay Creek Basin, Pennsylvania and

Delaware, 1994-98.
Data for Model Input and Calibration 13

part of the basin may appear to result in little or no

streamflow response. Disaggregation of daily precipitation values to hourly values by applying the

hourly distribution of precipitation at the Wilmington, Del., Airport excludes the spatial and temporal variations in rainfall distribution across the Red

Clay Creek Basin. Disaggregation errors can

appear as timing shifts in storm hydrographs.

Potential evapotranspiration at the Wilmington, Del., Airport meteorologic station was used

for model input. The daily estimates of potential

evapotranspiration for Wilmington were calculated by the Northeast Regional Climate Center

using a method described by DeGaetano and others (1994). Monthly totals of potential evapotranspiration are shown in figure 5. Disaggregation of

daily potential evapotranspiration was done automatically by HSPF. Daily potential evapotranspiration totals were divided into 24 equal hourly

values during an HSPF run.

Snow simulation requires precipitation, air

temperature, solar radiation, dewpoint, and windspeed data. Hourly air temperature, solar radiation, dewpoint, and wind speed from Wilmington,

Del., Airport were compiled and used as input to

the model. Observed snowfall and snow-onground at the Coatesville 2 W NOAA meteorologic

station were used for the snowfall and snowmelt

simulation module (SNOW) and for calibration of

the snow-module parameters. The days of snowfall and days that snow covered the ground at the

Coatesville 2 W station for the years 1995-98 are

listed in table 3. No snowfall occurred in the

period October 1, 1994, through December 31,

1994. Snow accumulation and snowmelt had the

most effect on streamflow in the year 1996. Snow

was on the ground for all of January and 2 weeks

of February 1996. In 1996 and 1997, snow cover of

2 in. or greater lasted no longer than 2 weeks.

Simulation of stream water temperature

requires air temperature, dewpoint, wind speed,

cloud cover, and solar radiation. Hourly air temperature, dewpoint, wind speed, and cloud cover

from the Wilmington, Del., Airport were used as

input to the model. In the northern parts of the

basin, air temperatures for input to the model were

derived from data at the Coatesville 2 W NOAA

meteorologic station. Minimum and maximum

daily air temperatures for the Coatesville 2 W

Figure 5. Monthly estimates of potential evapotranspiration for Wilmington Airport, Delaware, 1994-98.

Table 3. Days of snowfall and snow-on-ground at the

National Oceanic and Atmospheric Administration

meteorologic station Coatesville 2 W, 1994-98

Year

Days of snowfall

(maximum in

inches1)

Days of snow

on ground

(maximum in

inches1)

Days of

greater than

2 inches1

of snow on

ground

1994 27 (8.6) 72 (16) 69

1995 10 (9.1) 16 (10) 13

1996 27 (22.8) 52 (29) 39

1997 21 (11.4) 23 (11) 6

2

1998 7 (1.4) 2 (1) 0

1 Inches of snow, not inches of water equivalent.

2 Through October 1998.
14 Data for Model Input and Calibration

station were disaggregated to hourly air temperature with METCMP, using the Wilmington Airport

hourly data. Hourly estimates of solar radiation for

Wilmington, Del., were calculated by the Northeast

Regional Climate Center based on a method

described by DeGaetano and others (1993).

Water-Use Data

Simulation of streamflow and water quality

requires information about stream withdrawals

and discharges. Water withdrawal and discharge

data were obtained from CCWRA, WRA at the

University of Delaware, DNREC, and the Brandywine Valley Association who compiled water-use

information from various sources including

PADEP, DNREC, and individual water users.

Many of these data were reported on a monthly or

annual basis, and in many cases, were available for

only 1, 2, or 3 years of the 1994-98 simulation

period. Where at least 1 year of acceptable monthly

withdrawal data were available, the remaining

years’ missing information was filled by copying

data from the most recent year prior to the missing

period. Where no monthly withdrawal data were

available, missing monthly data were filled with

values equal to 75 percent of permitted withdrawal

maximums. Missing discharge data were filled

using the same method as withdrawals.

The discharges and withdrawals included in

the simulation are presented in table 4. Isolated

single-family residential discharges were not

included in the streamflow simulation. Monthlyto-hourly disaggregation of water-use data were

done by the HSPF model at the time of simulation.

Inputs from point sources include water-quality

constituent loads, discharge temperature, and rate

of discharge. Point-source discharge-quality data,

typically available as monthly or yearly values,

were disaggregated to an hourly time step by

dividing monthly or yearly values by the number

of time steps in those periods during simulation.

Table 4. Stream withdrawals and discharges of flow and ammonia and phosphorus loads included in the Hydrological

Simulation Program–Fortran (HSPF) model of the Red Clay Creek Basin, Pennsylvania and Delaware

[Mgal/d, million gallons per day; lb/d, pounds per day; IND, industrial; IRR, irrigation; STP, sewage-treatment plant;

NCW, non-contact cooling water; SRD, single residence discharge; --, not applicable or no information]

Subbasin Name Type

Flow volume

(Mgal/d)

1994-98 average discharge load

(lb/d)

Capacity

or flow limit

1994-98

average Ammonia Phosphorus

Withdrawals

West Branch J.H. Thompson, Inc. IND 0.0004 0.0004 -- --

East Branch Kennett Square Golf Course IRR -- .032 -- --

Main stem NVF, Yorklyn IND 2.25 2.07 -- --

Main stem Hercules Research Center IND .675 .120 -- --

Main stem Hercules Country Club IRR -- .050 -- --

Main stem Samuel Beard IND .0225 .0226 -- --

Discharges

West Branch New Bolton Center STP -- .022 0.122 0.331

West Branch NVF, Kennett Square NCW .25 .264 .22 .203

West Branch Kennett Square Borough -

sewage treatment plant

STP 1.10 .901 38.1 13.82

East Branch Sunny Dell Foods - PA001 STP .05 .041 .507 .622

East Branch Sunny Dell Foods - PA003 NCW .09 .071 .059 .055

East Branch East Marlborough STP .15 .087 .941 1.326

Main stem Center for Creative Arts STP .0015 .0006 .007 .009

Burroughs Run D’Ambro SRD .0005 .0004 .005 .006

Main stem NVF, Yorklyn NCW 2.17 1.69 1.41 1.295

Main stem Greenville Country Club STP .015 .004 .047 .058

Main stem Hercules Inc. NCW .35 .083 .069 .064

Main stem Haveg/Amtek - 0011 NCW .006 .0004 .0003 .0003

Main stem Haveg/Amtek - 0031 NCW .004 .002 .002 .002

1 Eliminated July 1996.
Data for Model Input and Calibration 15

Spatial Data

Spatial data input to the HSPF model are

used primarily to define the structure and “fixed”

characteristics of the model. The principal structural unit of the HSPF model is the hydrologic

response unit (for example, PERLND and

IMPLND). Hydrologic-response units for the modeled basin were determined from analysis of digital spatial data consisting of land use, elevation,

geology, soil association, and sanitary-sewer service area data. The digital spatial data were compiled from multiple sources by the WRA for New

Castle County for this study (Greig and others,

1998). These data were processed with a geographic information system (GIS) and compiled for

model input. Non-digital data such as information

regarding the location of specific agricultural practices also were used. Fifteen land-use categories

were delineated in the original digital database.

These categories were simplified and reclassified

into 10 pervious and 2 impervious land-use categories that were expected to have distinct nonpoint-source water-quality responses (table 5).

Digital spatial data showing impervious areas

were not available and impervious areas were estimated as a percentage of selected pervious areas,

as discussed later in a section on simulation of

streamflow in this report. The spatial distribution

of the simplified pervious land-use categories is

shown in figure 6. Areas of undesignated land use

were considered to have characteristics of areas

with open land use.

Agricultural land use was divided into three

characteristic subtypes for the model. Agriculturallivestock land use identifies small acreage farms

(less than 100 acres) with high animals-per-acre

densities, limited pasture areas, and rowcrops.

Small acreage dairy operations typify this land-use

type. Agricultural-rowcrop land use identifies

farms with lower animals-per-acre densities (typically beef cattle and horses) and substantial pasture and crop acreage. Agricultural-mushroom

land use is the third type of agricultural land use

delimited. Mushroom growing, which involves the

preparation and use of large amounts of manurebased compost, is more prevalent in the Red Clay

Creek and adjacent White Clay Creek Basin than

elsewhere in the Christina River Basin. Because

digital data were not available to describe the spatial distribution of the three agricultural subtypes,

the distribution of these land-use types were estimated as percentages of the general agricultural

category based on knowledge of the watershed

and information from CCCD.

Forested land is distributed throughout the

basin and tends to be along stream channels, especially in the southern and northern parts of the

basin (fig. 6). The largest amounts of forested land

are in the upper West Branch Red Clay Creek and

in the lower main stem near Hoopes Reservoir.

Table 5. Land-use categories used in the Hydrological Simulation Program–Fortran model of the Red Clay Creek

Basin, Pennsylvania and Delaware

Land-use category for model Description of land use

Pervious land area 1 residential-septic Includes all residential land not within a sewer service area

residential-sewer Includes all residential land within a sewer service area

urban Includes commercial, industrial, institutional, transportation uses

agricultural-livestock Predominantly mixed agricultural activities of dairy cows, row crop,

pasture and other livestock operations

agricultural-rowcrop Predominantly row-crop cultivation (corn, soybean, alfalfa), may

include some hay or pasture

agricultural-mushroom Mushroom growing activities including compost preparation,

mushroom house operations, spent compost processing

open Recreational and other open land not used for agriculture

forested Predominantly forested land

wetlands/water Wetlands and open water

undesignated Land use not defined

Impervious land area2 residential Impervious residential land

urban Impervious commercial, industrial, and other urban land

1 Pervious land area is designated as PERLND in model.

2 Impervious land area is designated as IMPLND in model.
16 Data for Model Input and Calibration

Figure 6. Generalized 1995 land-use map for the Red Clay Creek Basin, Pennsylvania

and Delaware.
Data for Model Input and Calibration 17

Residential land use is distributed throughout the basin and is divided into two types: sewered and non-sewered. Sewered residential areas

tend to have higher housing densities and are

nearer to urban/suburban areas than non-sewered

area. Non-sewered residential areas tend to have

lower densities and are more rural. Urban land use

in the basin generally is concentrated in the southern tip of the basin and in areas underlain by carbonate rocks centered on Kennett Square, Pa.

Other urban land use is in small boroughs and

towns and along major roadways.

Model-Calibration Data

Observed streamflow and water-quality data

are needed to calibrate the hydrologic and waterquality components of the HSPF model, respectively. These data are available at streamflow-measurement stations (gages) and water-quality

monitoring sites established in the basin for this

study and for other purposes. The period of record

and frequency of observations differ among these

gages and monitoring locations. In general, fewer

water-quality data are available than streamflow

data.

Hydrologic Data

Data used for the hydrologic calibration

were collected at three USGS streamflow-measurement stations operating in the Red Clay Creek

Basin during the 1994-98 simulation period

(table 6; fig. 7) (Durlin, 1995; Durlin and Schaffstall, 1997a, 1997b, 1998, 1999; James and others,

1996, 1997, 1998, 1999).

Streamflow data at all the sites were

recorded at time steps smaller than the 1-hour time

step used in model simulations. Because of the

shorter time steps, no disaggregation was needed

for the streamflow data. However, periods of missing data and periods of poor-quality data because

of freezing conditions are numerous in the hourly

streamflow record. Periods of missing data were

estimated by interpolation or regression. During

periods of relatively steady base flow, missing data

were interpolated. During periods of rapidly

changing flow (generally stormflow), missing data

were estimated by linear regression. A regression

equation was generated using data from the nearest upstream or downstream streamflow-measurement station, and which bounded the period of

missing record. Poor-quality data, because of freezing conditions, were more problematic in that data

from nearby stations also usually were affected. As

a result, these data were used as recorded unless

data of better quality were available from a nearby

streamflow-measurement station.

Water-Quality Data

Water-quality data at stream-monitoring

sites were used in model calibration. Water-quality

data for the simulation period 1994-98 were collected by PADEP, DNREC, and USGS as part of

various monitoring efforts in the Red Clay Creek

Basin (fig. 7). The period of record at monitoring

sites varied from 1 to 5 or more years, and the sampling interval varied from hourly or less for storms

to annually (table 7). The chemical analyses of

samples collected as part of these monitoring

efforts varied. Other water-quality data used for

assessing model calibration include annual baseflow nutrients data at two sites sampled by USGS

as part of the stream conditions of Chester County

biological monitoring program.

Two of the monitoring programs were

designed specifically to assist in the current assessment of water quality in the Red Clay Creek:

(1) monthly and bi-monthly monitoring efforts

were conducted by DNREC and PADEP from 1995

to 1998; and (2) a hydrologically based sampling

scheme for nonpoint-source monitoring was done

by USGS, PADEP, and DNREC in 1998. The

monthly and bi-monthly monitoring effort

included analyses for metals, nutrients, suspended

solids, and other constituents in samples collected

at five stream sites in the Red Clay Creek Basin and

was done to support an assessment of water quality during low-flow conditions and target pointsource contributions. The hydrologically based

Table 6. Streamflow-measurement stations in the Red

Clay Creek Basin, Pennsylvania and Delaware

U.S.

Geological

Survey station

identification

number

Station name

Drainage

area

(square

miles)

Period

of record

01479820 Red Clay Creek

near Kennett

Square, Pa.

28.3 1/88 - current

01480000 Red Clay Creek at

Wooddale, Del.

47.0 4/43 - current

01480015 Red Clay Creek

near Stanton,

Del.

1

 52.4 10/88-

current

1 Area determined by analysis of digital spatial data was

50.2 square miles.
18 Data for Model Input and Calibration

Figure 7. Location of streamflow-measurement stations and water-quality monitoring sites

in the Red Clay Creek Basin, Pennsylvania and Delaware.
Data for Model Input and Calibration 19

sampling scheme included analyses for nutrients,

suspended solids, and organic carbon at 1 site in

the Red Clay Creek Basin and 10 sites elsewhere in

the Christina River Basin and was done to support

an assessment of these constituents under baseflow and stormflow conditions throughout the

year and assist in the evaluation of nonpointsource contributions to the stream.

The nonpoint-source water-quality monitoring in 1997-98 in the Christina River Basin was

designed to provide data on the concentrations

and loads of nutrients and suspended solids seasonally under various hydrologic conditions for

the whole of each of the four subbasins and for

seven small areas predominantly covered by one

land use. Samples were collected during four baseflow periods and up to six stormflow events. Continuous data collected at the nonpoint-source

monitoring sites included streamflow and water

temperature. In the Red Clay Creek Basin, samples

collected at the Red Clay Creek at Wooddale, Del.,

site (01480000) provided information about the

water quality of the whole basin (about 85 percent

of the drainage area). Samples collected in the

seven small subbasins predominantly covered by

one land use (table 1) elsewhere in the Christina

River Basin were used to provide information

about the relation between land use and water

quality. The predominant land uses in the smallbasin sites include various types of agricultural,

residential, forested, and urban land use. The

small-basin data were used to develop model

parameters for specific land uses. The parameters

developed for specific land uses may be transferred to simulate water-quality response of those

land uses throughout the modeled area.

The stormflow and base-flow sampling

periods were selected as representative of the

range of seasonal, hydrologic, and land-use conditions in the basin. Timing for the six stormflow

events was as follows: two storms in mid to late

winter (February 4-5, and March 8-9, 1998), one

storm in early spring after pre-planting tillage

(May 2-3, 1998), one storm in late spring/early

Table 7. Water-quality monitoring sites in the Red Clay Creek Basin, Pennsylvania and Delaware, during 1994-98

[--, no data; P, Pennsylvania Department of Environmental Protection; D, Delaware Department of Natural Resources

and Environmental Control; U, U.S. Geological Survey; TSS, total suspended solids]

U.S.

Geological

Survey

station

identification

number

State

site

number

Drainage

area

(square

miles)

Location

(predominant

land use)

Monitoring

agency

Period

of

record

Chemical

analyses

Monthly and bi-monthly monitoring sites

01479820 WQN150 28.3 Red Clay Creek near Kennett Square, Pa. P 1995-98 Nutrients,

TSS

-- 103041 Red Clay Creek at Road 258A in Ashland, Del. D 1995-98 Nutrients,

TSS

-- 103061 Burroughs Run, Rt. 241 at bridge, Del. D 1995-98 Nutrients,

TSS

01480000 103031 47.0 Red Clay Creek, Rt. 48 at Wooddale, Del. D 1995-98 Nutrients,

TSS

01480015 103011 52.4 Red Clay Creek, Rt. 4 at Stanton bridge, Del. D 1995-98 Nutrients,

TSS

Base flow and stormflow nonpoint-source monitoring small and whole basin sites

01480000 -- 45.0 Red Clay Creek at Wooddale, Del.

(mixed-whole basin)

U, P, D 1998 Nutrients,

TSS

Annual biological monitoring sites

01479680 -- West Branch Red Clay Creek at Kennett Square, Pa. U 1971-97 Nutrients

01479800 -- East Branch Red Clay Creek near Five Points, Pa. U 1970-

current

Nutrients
20 Data for Model Input and Calibration

summer after planting of crops (June 12-13, 1998),

one storm in midsummer (July 8-9, 1998), and one

storm in fall after harvest (October 8-9, 1998). Sampling was delayed because of dry conditions in the

fall of 1997. Because of logistical problems, no samples were collected for the February 1998 storm at

Red Clay Creek at Wooddale. In addition, because

of the mild winter of 1998, there was no opportunity to collect samples from frozen-ground runoff

and snow-melt events. Sampled storms resulted

from precipitation events that ranged from about

0.4 to 3.3 in. For Brandywine Creek at Chadds

Ford, Pa., these precipitation events resulted in

peak flows with a 1-year or less recurrence interval. Base flow was sampled in January, April, July,

and September 1998.

Base-flow and stormflow samples collected

from January to October 1998 were analyzed for

concentrations of dissolved and total nitrogen and

phosphorus species and suspended solids (table 8).

Other constituents, such as dissolved organic carbon (DOC) and chlorophyll a, and properties, such

as chemical oxygen demand (COD) and biological

oxygen demand (BOD), also were analyzed to better understand and simulate the chemical processes involving the fate and transport of nutrients.

Chloride was measured to provide data on the

Table 8. Constituents in nonpoint-source monitoring samples to be determined by

laboratory chemical analysis1, Red Clay Creek Basin, Pennsylvania and Delaware

[mg/L, milligrams per liter; EPA, U.S. Environmental Protection Agency; STDMTD,

Standard Methods (American Public Health Association, 1995); μS/cm, microsiemens

per centimeter]

Constituent STORET

code Method

Reporting

limit

(mg/L except

where noted)

Required constituents or properties for all samples

Ammonia nitrogen, dissolved

Ammonia nitrogen, total

00608

00610

EPA 350.1 0.004

.004

Kjehldahl nitrogen, dissolved

Kjehldahl nitrogen, total

00623

00625

EPA 351.2 .05

.05

Nitrite plus nitrate nitrogen, dissolved 00631 EPA 353.2 .05

Orthophosphorus, dissolved 00671 EPA 365.1 .005

Phosphorus, dissolved

Phosphorus, total

00666

00665

EPA 365.1 .005

.005

Chloride 00940 EPA 325.2 1

Specific conductance 90095 EPA 120.1 1. μS/cm

Total suspended solids-concentration 80154 EPA 160.2 1

Biological oxygen demand (BOD20) 00308 EPA 405.1 2.4

Dissolved organic carbon 00681 EPA 415.1 1

Chlorophyll-a2

Pheophytin

70953 92 STDMTD

10200H

.001

.002

Additional constituents-Mainstem site at Red Clay Creek at Wooddale, Del.

Copper, dissolved

Copper, total

01040

01042

EPA 220.2 .005

.005

Lead, dissolved

Lead, total

01049

01052

EPA 239.2 .003

.003

Zinc, dissolved

Zinc, total

01090

01092

EPA 200.7 .010

.010

Chemical oxygen demand 00340 EPA 410.1, 410.2, 410.3 5.0

Total organic carbon 00680 EPA 415.1 1

1 Specifications for analytical method, reporting limit, holding time, sample volume and

preservation provided by the Delaware Department of Natural Resources and Environmental

Control laboratory. 2 First storm sampling event, all grab sampling events.
Data for Model Input and Calibration 21

concentrations of a conservative solute. Stormflow

samples were collected by USGS and the University of Delaware. Base-flow samples were collected

by PADEP and by DNREC. DNREC’s laboratory in

Dover, Del., performed all laboratory chemical

analyses. Results of laboratory analyses for all

stormflow and base-flow samples are listed in

appendix 1.

Two types of samples, discrete and composite, were collected by an automatic sampler during

storm events. Discrete samples, collected at fixedtime intervals during the storm event, represent

instantaneous concentrations. Composite samples

can be used to estimate loads for a storm event.

The automatic sampler was programmed prior to

each storm event to start sampling at a pre-determined change in stage, and collect one series of

fixed-interval discrete samples and another series

of flow-weighted aliquots (250 mL each) for the

composite sample. The fixed-interval series consisted of up to six 2-L samples, collected from 1.5 to

3 hours apart. The flow-weighted series consisted

of up to 48 250-mL samples. The intake for the

automatic sampler was set in mid stream and stage

was determined by a transducer set in the stilling

well and linked to the automatic sampler. Streams

were assumed to be well mixed. The automatic

sampler was programmed to collect a sample at

fixed-time intervals and after each time that a predetermined flow volume, calculated using an

established rating between stage and streamflow,

had passed by the monitoring site. Composite

samples were obtained by mixing the series of

flow-weighted aliquots. Because the automatic

sampler was programmed in advance of storms for

which the intensity and duration were unknown,

the extent of the actual storm periods covered by

samples varied.

The measured concentration of constituents

in discrete storm samples was, in general, related

to streamflow (fig. 8). The concentration of total

suspended solids, total ammonia nitrogen plus

organic-nitrogen, and total phosphorus tended to

increase with increasing streamflow whereas the

concentration of dissolved nitrite plus nitrate nitrogen, dissolved ammonia nitrogen, and dissolved

orthophosphate tended to decrease with increasing

streamflow.

Concentrations of suspended solids and

nutrients in stream samples differed at the Wooddale monitoring location in relation to hydrologic

conditions. The distribution of constituent concentrations at the Wooddale nonpoint-source monitoring site under stormflow and base-flow conditions

are shown in figures 9 and 10. Concentrations of

total suspended solids, total ammonia plus organic

nitrogen, and total phosphorus in stream samples

are greater under stormflow conditions than under

base-flow conditions. Concentrations of dissolved

nitrate in stream samples are greater under baseflow conditions than under stormflow conditions

(fig. 9). Concentrations of dissolved and total

ammonia tend to be slightly greater under stormflow conditions than base-flow conditions. Concentrations of dissolved orthophosphate in stream

samples tend to be slightly greater under base-flow

conditions than under stormflow conditions, but

conversely, concentrations of total phosphorus are

greater under stormflow conditions than base-flow

conditions (fig. 10). Base-flow concentrations are

controlled primarily by ground-water discharge

and stormflow concentrations by runoff and interflow processes.

Elsewhere in the Christina River Basin, differences in water quality may be related to land

use. Data from 1998 (Senior and Koerkle, 2003a,

2003b) indicate that under stormflow conditions,

concentrations of suspended solids, nitrate, ammonia, dissolved orthophosphate, and total phosphorus generally were higher at the sites in

predominantly agricultural subbasins than at sites

in subbasins with predominantly residential or forested land uses with a few exceptions. Concentrations of dissolved nitrate and orthophosphate

under base-flow conditions also commonly were

higher at the two sites in predominantly agricultural subbasins than at sites in subbasins with

other land uses. Concentrations of suspended sediment, nitrate, and total phosphorus under baseflow and stormflow conditions were greater at the

site in the predominantly non-sewered residential

subbasin than at the sites in the predominantly forested and sewered residential subbasins. Although

elevated ammonia and orthophosphate can be

related to the land use, some of these constituents

may be associated with discharge from sewagetreatment plants or other point sources upstream

of monitoring sites.
22 Data for Model Input and Calibration

0

800

200

400

600

TOTAL SUSPENDED SOLIDS,

IN MILLIGRAMS PER LITER

0

0.16

0.02

0.04

0.06

0.08

0.10

0.12

0.14

DISSOLVED AMMONIA,

IN MILLIGRAM PER LITER AS N

0.5

3.0

1.0

1.5

2.0

2.5

TOTAL AMMONIA PLUS ORGANIC NITROGEN,

IN MILLIGRAMS PER LITER AS N

1.0

3.5

1.5

2.0

2.5

3.0

DISSOLVED NITRITE PLUS NITRATE,

IN MILLIGRAMS PER LITER AS N

0 1,000 200 400 600 800

STREAMFLOW, IN CUBIC FEET PER SECOND

0

1.4

0.2

0.4

0.6

0.8

1.0

1.2

1.4

TOTAL PHOSPHORUS,

IN MILLIGRAMS PER LITER AS P

0 1,000 200 400 600 800

STREAMFLOW, IN CUBIC FEET PER SECOND

0.05

0.35

0.10

0.15

0.20

0.25

0.30

DISSOLVED ORTHOPHOSPHATE,

IN MILLIGRAM PER LITER AS P

Figure 8. Relation between water-quality constituents and streamflow for stormflow and base-flow samples

collected in 1998 at streamflow-measurement station 01480000, Red Clay Creek at Wooddale, Del.
Data for Model Input and Calibration 23

STORMFLOW BASE FLOW

FLOW CONDITIONS

1

1,000

2

3

4

5

7

10

20

30

40

50

70

100

200

300

400

500

700

TOTAL SUSPENDED SOLIDS,

IN MILLIGRAMS PER LITER

EXPLANATION

25TH PERCENTILE

MEDIAN

75TH PERCENTILE

INTERQUARTILE RANGE OUTSIDE THE QUARTILE

DATA VALUE LESS THAN OR EQUAL TO 1.5 TIMES THE

INTERQUARTILE RANGE OUTSIDE THE QUARTILE

AND MORE THAN 1.5 TIMES THE

OUTLIER DATA VALUE LESS THAN OR EQUAL TO 3

STORMFLOW BASE FLOW

FLOW CONDITIONS

1.0

3.5

1.5

2.0

2.5

3.0

DISSOLVED NITRITE PLUS NITRATE,

IN MILLIGRAMS PER LITER AS N

STORMFLOW BASE FLOW

FLOW CONDITIONS

0.5

3.0

1.0

1.5

2.0

2.5

TOTAL AMMONIA PLUS ORGANIC NITROGEN,

IN MILLIGRAMS PER LITER AS N

Figure 9. Distribution of concentrations of suspended solids, total ammonia plus organic nitrogen, and

dissolved nitrate in samples collected under stormflow and base-flow conditions at the monitoring site,

01480000 Red Clay Creek at Wooddale, Del., 1998. (See figure 7 for location of and table 7 for description of

monitoring site.)
24 Data for Model Input and Calibration

STORMFLOW BASE FLOW

FLOW CONDITIONS

0

0.20

0.05

0.10

0.15

TOTAL AMMONIA,

IN MILLIGRAM PER LITER AS N

STORMFLOW BASE FLOW

FLOW CONDITIONS

0

0.20

0.05

0.10

0.15

DISSOLVED AMMONIA,

IN MILLIGRAM PER LITER AS N

STORMFLOW BASE FLOW

FLOW CONDITIONS

0

1.4

0.2

0.4

0.6

0.8

1.0

1.2

1.4

TOTAL PHOSPHORUS,

IN MILLIGRAMS PER LITER AS P

EXPLANATION

25TH PERCENTILE

MEDIAN

75TH PERCENTILE

INTERQUARTILE RANGE OUTSIDE THE QUARTILE

DATA VALUE LESS THAN OR EQUAL TO 1.5 TIMES THE

INTERQUARTILE RANGE OUTSIDE THE QUARTILE

AND MORE THAN 1.5 TIMES THE

OUTLIER DATA VALUE LESS THAN OR EQUAL TO 3

INTERQUARTILE RANGE OUTSIDE THE QUARTILE

OUTLIER DATA VALUE MORE THAN 3 TIMES THE

STORMFLOW BASE FLOW

FLOW CONDITIONS

0.05

0.35

0.10

0.15

0.20

0.25

0.30

0.35

DISSOLVED ORTHOPHOSPHATE,

IN MILLIGRAM PER LITER AS P

Figure 10. Distribution of concentrations of dissolved and total ammonia, dissolved orthophosphate, and

total phosphorus in samples collected under stormflow and base-flow conditions at the monitoring site,

01480000 Red Clay Creek at Wooddale, Del.,1998. (See figure 7 for location of and table 7 for description

of monitoring site.)
Simulation of Streamflow 25

SIMULATION OF STREAMFLOW

Streamflow in the Red Clay Creek Basin was

simulated for the period October 1, 1994, through

October 29, 1998, or just over 4 years. Donigian and

others (1984) suggest a 3-year to 5-year simulation

period as optimal for HSPF because a greater variety of climatic conditions will be included.

The Red Clay Creek Basin was divided into

three segments for the model (fig. 11). Segments of

the basin area were defined primarily on the basis

of spatial distribution of land use and soils. Within

each segment, the hydrologic response of land

areas was assumed to differ principally by land use

because soils within each segment were similar. All

model segments (fig. 11) receive precipitation

input from the Porter Reservoir NOAA gage

(fig. 3). The land-based hydrologic response in

each segment was characterized spatially by subdividing the area into as many as 12 land-use categories consisting of 10 pervious and 2 impervious

land-use types (table 9). These simplified land-use

categories represent the predominant land uses in

the Christina River Basin. Initial hydrologicresponse parameters were assigned to the land-use

categories and were modified as needed during

model calibration. Parameters do not vary within a

segment but may vary from segment to segment.

Figure 11. Location of segments, model-reach drainage area, and stream

reaches (RCHRES) delineated for HSPF model of the Red Clay Creek Basin,

Pennsylvania and Delaware.
26 Simulation of Streamflow

The amount of impervious land was calculated from the residential and urban pervious land

uses using factors modified from WRA for New

Castle County values in Greig and others (1998).

Because the HSPF model simulates no infiltration

in impervious areas and some runoff from impervious areas such as roofs and roads does infiltrate,

the amount of effectively impervious area is

expected to be lower than impervious areas estimated by land-use maps. Thus, the amount of

effectively impervious area was reduced from the

amount of impervious area estimated from landuse maps. This type of modification has been

applied in HSPF models in other study areas

(Zarriello, 1999). The proportion of effectively

impervious land was estimated as 10 percent in

residential areas without sewers, 30 percent in residential areas with sewers, 50 percent for urban

areas. and 10 percent for undesignated lands in

sewered areas.

Nine RCHRES were specified for the Red

Clay Creek model (fig. 11). RCHRES lengths

ranged from 0.84 to 7.20 mi in length; the median

length was 5.0 mi. Selection of RCHRES lengths

was guided by the confluences of major tributaries,

the location of calibration points, the location of

dams and impoundments, and major changes in

land use contributing to a stream reach. Reach

lengths were taken from topographic maps. Two

RCHRES are in the West Branch, one RCHRES in

the East Branch, and six in the main stem and tributaries below the confluence of the East and West

Branches. The one reservoir in the basin, Hoopes

Reservoir, was designated a reach but was not simulated in the model because negligible amounts of

water are released from Hoopes Reservoir to Red

Clay Creek except during periods of extreme low

flow. The area draining directly to each reach

ranged from 1.72 to 10.08 mi2, with differing

amounts of the various land-use categories in each

reach drainage area (table 9).

Snowfall, snow accumulation, and snow

melt were simulated throughout the basin because

hydrologic and meteorologic records indicated

substantial snow, ice, and sub-freezing temperatures during the winter of 1995-96. In the coldest

periods, sub-freezing temperatures resulted in

stream channel icing at the calibration sites. During the 1995-96 winter, only estimated daily

streamflows were available during much of

December, January, and February. Hourly streamflow values for these periods are considered poor

and published daily streamflows are reported as

estimated. Final calibration included the simulation of snow.

Table 9. Reach number, length, drainage area, segment number, and percent of land-use category in reach-drainage

areas for Red Clay Creek model, Pennsylvania and Delaware

[mi, miles; mi2, square miles]

Segment

number

Reach

number

Reach

length

(mi)

Reach

drainage

area

(mi2)

Land-use category (percent of drainage area)

Residential -

septic

Residentialsewer

Urban

Agricultural -

livestock

Agricultural -

row crop

Agricultural -

mushroom

Forested

Open

Wetland.water

Undesignated

Impervious -

residential

Impervious -

urban

7 1 5.00 10.08 10.4 1.6 2.1 5.9 46.8 5.9 18.4 2.8 0.4 1.6 1.9 2.2

7 2 4.90 7.39 11.8 .5 .7 0 40.9 17.5 25.2 .3 .2 .7 1.5 .7

7 3 7.20 9.90 14.9 1.9 1.0 0 33.1 14.2 22.5 5.8 .6 2.3 2.5 1.1

4 4 3.40 5.11 35.5 2.3 1.0 1.8 14.2 1.8 28.4 7.9 .8 .6 4.9 1.0

4 5 5.10 5.24 32.2 2.2 .2 0 14.6 0 37.7 6.0 1.2 .9 4.6 .2

4 6 5.00 7.10 23.9 0 .2 0 42.4 0 25.1 5.1 .1 .3 2.7 .2

4 7 1.70 2.10 26.1 0 .5 0 7.2 0 44.4 3.0 14.3 1.1 2.9 .5

6 8 4.30 5.38 1.5 35.3 5.3 0 1.6 0 13.4 13.8 1.4 6.3 15.3 6.0

6 9 .84 1.72 0 45.5 4.8 0 0 0 10.2 3.8 .4 9.9 19.5 5.9

All Total 37.44 54.02 17.1 6.1 1.6 1.3 29.2 6.3 24.0 5.2 1.2 2.0 4.5 1.7
Simulation of Streamflow 27

Assumptions

The simulation of streamflow in Red Clay

Creek was done under the following assumptions:

(1) inputs of hourly precipitation would be estimated reasonably well by disaggregated 24-hour

precipitation data; (2) the average precipitation

over a given land segment would be represented

adequately by weighted data from a single precipitation gage; (3) a simplified set of PERLNDs and

IMPLNDs would not unduly limit a satisfactory

hydrologic calibration of the Red Clay Creek

model.

Calibration

The basin hydrology model was calibrated

using HSPEXP (Lumb and others, 1994), a computer program that assists in calibration using an

expert system, and the calibration guidelines in

Donigian and others (1984). The model-calibration

effort was directed at the full range of observed

streamflow with an emphasis on higher streamflows, because transport of many nonpoint source

constituents is greatest at high flows. Prior to calibration, initial estimates of the hydrologic calibration parameters were determined. The initial

values were derived from known watershed characteristics where possible, from parameters determined for calibrated HSPF models for the adjacent

Brandywine and White Clay Creek Basins (Senior

and Koerkle, 2003a, 2003b), from the HSPFParm

database (Donigian and others, 1998), and from

published sources such as Donigian and Davis

(1978) and the U.S. Environmental Protection

Agency Office of Water (2000b). During calibration

with HSPEXP, simulated streamflow is compared

to observed streamflow through statistical and

graphical methods and suggestions are given as to

which parameter(s) needs modification. HSPEXP

also includes default criteria for determination of a

satisfactory hydrologic calibration (table 10). The

criteria are maximum allowable differences

(errors) between observed and simulated streamflow expressed as percent error. These criteria are

not fixed in HSPEXP and can be modified depending on the users’ needs. Donigian and others (1984)

offer the following error criteria for calibration:

annual and monthly values less than 10-percent

difference (Very Good); 10- to 15-percent difference

(Good); 15- to 25-percent difference (Fair). Calibrated hydrologic parameter values are listed in

the Brandywine UCI in appendix 2.

The model was calibrated at gaged locations

along the main stem of Red Clay Creek in downstream order. For example, the part of the basin

above Red Clay Creek at Kennett Square, Pa.,

(01479820) was calibrated before the part of the

basin draining to the next gage downstream, Red

Clay Creek at Wooddale, Del. (01480000). The

period of calibration was October 1, 1994, through

October 29, 1998.

Stormflow hydrograph calibration consisted

of comparing stormflow volume, average simulated peak flows, and recession rates of selected

storms with observed data in HSPEXP and visual

examination of simulated and observed stormflow

hydrographs. Thirty-six storm events were

selected from the simulation period. Storms were

Table 10. Calibration criteria and errors for Hydrological Simulation Program-Fortran (HSPF) simulated

streamflow at three gaging sites in the Red Clay Creek Basin, for the period October 1, 1994, through

October 29, 1998

Calibration

site1

Calibration criteria, in percent2

Total

volume

Low-flow

recession

rate

50-percent

lowest

flows

10-percent

highest

flows

Storm

peaks

Seasonal

volume

error

Summer

storm

volume

error

10.0 0.03 10.0 15.0 20.0 30.0 50.0

Calibration errors from HSPEXP, in percent

01479820 -0.4 0 1.0 0.4 -13.6 7.6 -8.9

01480000 2.1 0 2.7 4.5 -5.4 6.4 -13.9

01480015 -.8 -.01 -3.8 2.3 -6.2 3.4 -9.9

1 Streamflow-measurement station number.

2 Default criteria for satisfactory hydrologic calibration in HSPEXP.
28 Simulation of Streamflow

selected using the following criteria as a guide:

(1) total storm precipitation will be equal to 1 in. or

more and cover a broad area of the drainage basin

in order that all/most segments of the basin exhibit

a hydrologic response to the storm; and (2) all

storms during which water-quality data were collected. The summary statistics: error in total

storm volume, error in the mean of peak stormflows for all selected storms, and error in total

summer storm volume were calculated for the

36 selected stormflow periods collectively. For all

three Red Clay Creek sites, these statistics indicate

simulation errors less than the default HSPEXP

error criteria (table 10). However, these statistics

are not indicative of the errors for individual storm

simulations. Examples of individual stormflow

hydrographs for selected storms in 1998 are presented in the section “Simulation of Water Quality.”

In general, errors in individual storm simulations vary widely. The largest errors in the simulation of stormflow appear to result from incorrectly specified precipitation. Typically, a time discrepancy between the simulated and observed

stormflow hydrographs has no effect on the

HSPEXP error statistics except when the time shift

moves the simulated hydrograph beyond the

established storm-event time boundaries. These

boundaries are set at whole day increments (for

individual storms) or seasonal periods (June, July,

August for the summer). However, a time-shifted

event can cause difficulties with water-quality calibrations; a temporal mismatch between observed

and simulated streamflows produces a corresponding mismatch between observed and simulated water quality. Use of weighting of rainfall

also has the potential to result in incorrectly specified rainfall for individual storm events. Stormflow

simulations with the least error tended to result

from storms that produced the most uniform rainfall distribution across a drainage basin. In the

HSPF model for the adjacent Brandywine Creek

Basin, errors in individual storm simulations

tended to increase with decreasing drainage area

(Senior and Koerkle, 2003a).

Time-series comparison of simulated and

observed daily mean streamflow at the three

streamflow-measurement stations on Red Clay

Creek, 01479820 near Kennett Square, 01480000 at

Wooddale, and 01480015 near Stanton, (fig. 12)

indicate no strong temporal pattern in errors

except during low-flow conditions in 1995. From

July to September 1995, simulated streamflow

exceeds observed streamflow for the near Kennett

Square station and is less than observed streamflow for the other two streamflow-measurement

stations downstream in Delaware. An unquantified diversion (private property owner periodically diverts some streamflow into mill race) at the

streamflow-measurement station at Kennett

Square commonly results in reduced apparent

streamflow at that station. This reduction in measured streamflow is greatest under low-flow conditions.

Time series comparison of simulated and

observed hourly streamflow at the nonpointsource water-quality monitoring site, Red Clay

Creek at Wooddale, are shown in figure 13 for the

sampling period January 1 through October 29,

1998. Simulated low-flow conditions tend to

exceed observed streamflow in the winter and

summer months of 1998. In 1998, most of the larger

storms (greater than 100 ft3/s) are undersimulated,

with the exception of a storm in late January and

another in late May. Observed and simulated

storms in the winter of 1998 tend to be larger in

magnitude than later in the year.
Simulation of Streamflow 29 0.5 5,000

125

102050

100200500

1,0002,000

DAILY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND

1

5,000

25

102050

100200500

1,0002,000

DAILY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND

O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A 

1994 1995 1996 1997 

1

5,000

2

5

102050

100200500

1,0002,000

DAILY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND

Figure 12. Simulated and observed daily mean streamflow at three streamflow-measurement stations in the Red Clay Creek Bas

Delaware, for the period October 1, 1994, through October 29, 1998.

01480015, RED CLAY CREEK NEAR STANTON01479820, RED CLAY CREEK NEAR KENNETT 01480000, RED CLAY CREEK AT WOODDALE, 

OBSERVED

SIMULATED
30 Simulation of Streamflow

Flow-duration curves of simulated and

observed hourly streamflow for the streamflow

sites on the main branch of Red Clay Creek generally indicate good agreement, except for the lowest

observed flows (fig. 14). Overall, the simulated

durations of the highest flows, those that transport

the bulk of nonpoint-source constituents, agree

with observed high flow durations, except for the

highest 0.1 percent of flows at the Kennett Square

site.

The model performance in simulating

hourly and daily streamflow was evaluated at the

one nonpoint-source water-quality monitoring

sites for 1998, the year of stormflow and base-flow

water-quality data collection, and at three sites for

the calibration period of 1994-98. Statistical measures of the hourly and daily streamflow comparison are listed in table 11. Correlation and model-fit

efficiency coefficients for the most-upstream site

(Red Clay Creek near Kennett Square) are lower

than those for the sites downstream (Wooddale

and Stanton). Unlike the flow-duration comparisons, the statistics for one-to-one comparison of

observed and simulated values (table 11) are

affected by errors in the timing of storms. Because

errors in the timing of precipitation and consequent storms commonly occur in shifts on the

order of hours, not days, they result in lower values of correlation and model-fit efficiency coefficients for hourly streamflow compared to those for

daily streamflow (table 11). Errors in timing of precipitation on the order of hours affect simulated

stormflow in small drainage areas to a greater

extent than simulated stormflow in large drainage

areas because the time to peak for storms generally

increases with basin size. The evaluation indicates

that the model-fit efficiency and correlation coefficients at Wooddale are similar and generally

slightly better for the calibration period of 1994-98

than for 1998. Model-fit efficiency coefficients

greater than 0.97 indicate an excellent calibration

(Martin and others, 2000; James and Burgess,

1982).

Simulated and observed streamflow, in

inches, for Red Clay Creek near Stanton, Del., is

listed by year and for the entire 4-year period of

simulation in table 12. A plot of cumulative errors

for Red Clay Creek near Stanton, Del. (fig. 15),

shows that large changes in cumulative error occur

during the winters of 1995-96 and 1996-97 and the

summers of 1995 and 1996. During the winter of

1996-97, snowfall accumulation and snowmelt

were important processes. The winter periods

were oversimulated and the summer periods were

undersimulated.

Water in an HSPF model reach can be subdivided into surface runoff (SURO), interflow

(IFWO), and active ground-water flow (AGWO).

These components represent the volumes of water

discharged to the stream from a pervious land segment (PERLND). Impervious land segments

(IMPLNDs), by definition, have only a surface runoff (SURO) pathway. For the 4-year period of simulation of Red Clay Creek near Stanton, Del., the

cumulative surface runoff is 19.4 in. and about

26 percent of total flow, interflow is 7.8 in. and

about 10 percent of total flow, and active groundwater flow is 47.9 in. and about 64 percent of total

runoff.

J F M A M J J A S O

1998

10

10,000

20

50

100

200

500

1,000

2,000

5,000

HOURLY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND

01480000, RED CLAY CREEK AT WOODDALE, DEL.

OBSERVED STREAMFLOW

SIMULATED STREAMFLOW

Figure 13. Simulated and observed streamflow at the nonpoint-source water-quality monitoring site in the

Red Clay Creek Basin, Pennsylvania and Delaware, for the sampling period January 1 through October 29,

1998.
Simulation of Streamflow 31

0.01 0.1 1 2 5 10 20 30 40 50 60 70 80 90 95 98 99 99.9 99.99

PERCENT OF THE TIME STREAMFLOW EQUALED OR EXCEEDED

0.1

10,000

0.2

0.5

1

2

5

10

20

50

100

200

500

1,000

2,000

5,000

0.01 0.1 1 2 5 10 20 30 40 50 60 70 80 90 95 98 99 99.9 99.99

PERCENT OF THE TIME STREAMFLOW EQUALED OR EXCEEDED

1

10,000

2

5

10

20

50

100

200

500

1,000

2,000

5,000

0.01 0.1 1 2 5 10 20 30 40 50 60 70 80 90 95 98 99 99.9 99.99

PERCENT OF THE TIME STREAMFLOW EQUALED OR EXCEEDED

1

10,000

2

5

10

20

50

100

200

500

1,000

2,000

5,000

HOURLY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND

Figure 14. Duration curves of simulated and observed hourly mean streamflow for three sites

on the main stem Red Clay Creek, Pennsylvania and Delaware, for the period October 1, 1994,

through October 29, 1998.

01479820 RED CLAY CREEK NEAR KENNETT SQUARE, PA.

01480000 RED CLAY CREEK AT WOODDALE, DEL.

01480015 RED CLAY CREEK NEAR STANTON, DEL.

OBSERVED

SIMULATED

SIMULATED

SIMULATED

OBSERVED

OBSERVED

HOURLY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND

HOURLY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND
32 Simulation of Streamflow

Table 11. Statistics for comparison of observed and simulated hourly and daily mean streamflow at the nonpointsource water-quality monitoring site during the January - October 1998 nonpoint-source monitoring period and at

three water-quality monitoring sites during the January 1994 - October 1998 calibration period in the Red Clay Creek

Basin, Pennsylvania and Delaware

Site

Type of

mean

values

Number

of values

Streamflow, in cubic feet per second

Correlation

coefficient

Model-fit

Mean efficiency

observed

Mean

simulated

Mean

error

Mean

absolute

error1

Nonpoint-source monitoring period, January - October 1998

Wooddale Hourly 7,248 48.33 52.98 -4.647 13.29 0.80 0.64

Wooddale Daily 302 48.33 52.98 -4.647 12.38 .85 .71

Calibration period, October 1994 - October 1998

Kennett Square Hourly 35,760 39.37 39.21 .153 11.52 .79 .40

Kennett Square Daily 1,490 39.37 39.21 .153 10.27 .84 .50

Wooddale Hourly 35,760 60.08 61.35 -1.29 15.92 .83 .69

Wooddale Daily 1,490 60.08 61.35 -1.29 13.99 .89 .79

Stanton Hourly 35,760 70.09 69.53 .557 18.17 .84 .68

Stanton Daily 1,490 70.09 69.53 .557 15.66 .89 .79

1 Mean absolute error = sum[|(simulated - observed)|/number of values].

Table 12. Observed and simulated streamflow for Red Clay

Creek near Stanton, Del., 1994-98

Year

Streamflow, in inches

Percent

difference1

Simulated Observed Simulated -

observed

21994 1.95 2.07 -0.12 -5.8

1995 12.4 11.7 .7 6.0

1996 32.2 33.1 -.9 -2.7

1997 16.7 17.6 -.9 -5.1

31998 13.5 12.9 .5 4.7

Total

(1994-98)

76.8 77.4 -.6 -.8

1 100 x (Simulated - Observed) / Observed.

2 October 1 through December 31, 1994.

3 Through October 29, 1998.
Simulation of Streamflow 33

A well-calibrated HSPF model will simulate

satisfactorily the proportioning of surface runoff,

interflow, and ground-water components of the

total volume of water leaving land areas and entering streams. Simulation of flow components is

important because the contaminant transport in

surface runoff, interflow, and ground water is

affected by the amount and rate of water leaving

the land through each process. As a check on the

simulated proportion of base flow, fixed-interval

and local-minimum base-flow-separation techniques (Sloto and Crouse, 1996; Pettyjohn and

Henning, 1979) determined 65.8 and 64.3 percent,

respectively, for base flow as percent of total flow

for Red Clay Creek near Stanton. These percentages agree well with the HSPF simulated base-flow

percentages, although values of active groundwater flow calculated in the HSPF simulation cannot be compared exactly to those calculated by

fixed-interval or local-minimum base-flow-separation techniques because of differences in methodology. These base-flow-separation techniques do

not compute interflow as a separate component.

Rather, interflow (IFWO), as calculated in HSPF, is

divided between base flow and surface runoff in

unknown proportions.

The partitioning of PERLND water among

SURO, IFWO, and AGWO affects the stream

hydrograph and, consequently, the simulation of

nonpoint-source constituent transport (Fontaine

and Jacomino, 1997). The monthly contributions

from SURO, IFWO, and AGWO for a wetter-thanaverage year (1996) and a drier-than-average year

(1997) at Stanton, the most downstream calibration

point that receives contributions from each of the

three model segments, is presented in figure 16.

Simulated surface runoff and interflow are greater

in magnitude and represent a greater percent of

simulated total runoff in the wet year, 1996, than in

the dry year, 1997. In 1996 and 1997, SURO represented 9.8 and 2.9 in., respectively (31 and

18 percent, respectively), of the total runoff at Red

Clay Creek near Stanton. Over the full simulation

period at the three calibration sites, the average

SURO ranged from 24 percent at Red Clay Creek

near Wooddale to 26 percent at Red Clay Creek

near Stanton.

Overall, the calibration of the hydrologic

component of the HSPF model for the Red Clay

Creek Basin generally is balanced over the full

range of observed streamflows, even though more

emphasis was placed on high-flow simulation. The

model was calibrated at mainstem sites draining

areas greater than 28 mi2. As calibrated, the hydrologic component of the model nevertheless has

limitations for the application of simulating water

quality under stormflow conditions. These limitations, related primarily to the regionalization of

O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O

1994 1995 1996 1997 1998

-1.5

1.5

-1.0

-0.5

0

0.5

1.0

CUMULATIVE DIFFERENCE BETWEEN SIMULATED AND

OBSERVED DAILY MEAN STREAMFLOW, IN INCHES

Figure 15. Cumulative difference between simulated and observed daily mean streamflow at streamflowmeasurement station 01480015, Red Clay Creek near Stanton, Del., October 1, 1994, through October 29,

1998.
34 Simulation of Streamflow

distant point source precipitation data, result in a

larger range and magnitude of errors for the simulated hydrologic responses to individual storm

events than for simulated streamflow at daily or

longer time steps. Because of the dependence of

certain water-quality characteristics on streamflow

conditions, limitations in the hydrologic simulations will affect water-quality simulations, particularly during stormflow conditions at sites draining

relatively small areas. Errors in hourly stormflow

simulation are due in part to errors in hourly rainfall estimated by disaggregating daily values. In

the HSPF model for the adjacent Brandywine

Creek Basin, errors commonly were found to be

relatively greater at sites draining smaller areas

(less than 10 mi2) than at sites draining larger areas

(more than 10 mi2) (Senior and Koerkle, 2003a).

Sensitivity Analysis

A sensitivity analysis was performed to

examine the influence of altering selected parameters on streamflow volume simulated by the Red

Clay Creek HSPF model. For the analysis, parameters were altered one at a time. To a large extent,

the relative sensitivities of the model results to

changes in individual parameters are determined

by the algorithm in which they are used. However,

relative sensitivities also are affected by the calibrated values of other parameters because of various degrees of interdependence. IMPLND and

RCHRES parameters were not included in the sensitivity analysis because they proved to have minimal effects on streamflow volumes during the

calibration process. Rather, variations in the timing

of stormflow discharges are affected most by varying IMPLND and RCHRES parameters.

Selected PERLND parameter values were

multiplied by a factor prior to running a simulation while holding all other parameters constant.

Typically, application of the multiplication factors

resulted in doubling or halving the initial parameter value. In some instances, such as the lower zone

evapotranspiration (LZETP) and ground-water

recession (AGWRC) parameters, limitations on the

range of allowable values prevented doubling or

halving the values. In addition, the AGWRC

parameter was only decreased because its calibrated value is close to the maximum allowable

value. Sensitivity analyses were completed for the

site that received flow originating from each of the

three segments in the model structure, Red Clay

Creek near Stanton, Del. The response of simulated

runoff characteristics is listed in table 13.

Total runoff volumes at Stanton show the

greatest sensitivity to lower-zone storage (LZSN),

upper-zone evapotranspiration (UZSN), and

lower-zone evapotranspiration (LZETP). The

LZSN, UZSN, and LZETP parameters directly

affected the amount of water available for simulated evapotranspiration (ET), although UZSN

affects simulated ET to a lesser extent than LZSN

and LZETP. ET is the largest component of the

hydrologic budget. For the adjacent Brandywine

0

6

1

2

3

4

5

TOTAL SIMULATED STREAMFLOW, IN INCHES

SURFACE RUNOFF

INTERFLOW

GROUND-WATER DISCHARGE

Figure 16. Simulated surface runoff, interflow, and base-flow monthly flow contributions from pervious

land segments (PERLNDs) at the most downstream calibration site in the Red Clay Creek Basin,

01480015 Red Clay Creek near Stanton, Del., 1996-97.

J F M A MJJ A S O N D J F M A MJJ A S O N D

1996 1997
Simulation of Streamflow 35 Table 13. Sensitivity analysis of modeled runoff characteristics at Red Clay Creek near Stanton, Del. (01480015), to variations in selecte

parameters [ET, evapotranspiration; Model parameters: AGWRC, active ground-water recession rate; INFILT, infiltration; LZSN, lower-zone storagestorage; UZSN, upper-zone storage; SLSUR, slope of overland flow; NSUR, Manning’s n for overland flow; INTFW, interflow; IRC, interflolower-zone evapotranspiration] Parameter Multiplier Runoff errors (in percent) Total inches (C

Total runoff volume 50-percent low flow 10-percent high flow Seasonal runoff volume Summer storm volume Average storm peak Total runoff Surf

run

Calibrated value1 1 -0.8 -3.8 2.3 3.4 -9.9 -6.2 76.77 19.

AGWRC .75 2.4 -61 37.1 49.5 -20.3 .5 79.24 19.INFILT 2 .5 13.5 -20.3 12.7 0 -46.9 77.78 12.INFILT .5 -1.4 -24.6 31.3 21.6 -22.5 46.9 76.3 29.LZSN 2 -12.7 -18.7 -14.5 8.5 6.3 -28.8 67.52 16.LZSN .5 8.7 -1.4 22.1 29 -38.8 18.6 84.1 22.CEPSC 2 -2.9 -9.9 3.1 9.6 -11.8 -4 75.11 19.CEPSC .5 .6 .3 1.6 .4 -8.9 -8.5 77.85 19.UZSN 2 -4.2 -2.1 -9.7 1.9 -5.9 -26.6 74.09 16.UZSN .5 2.2 -6.1 13.9 .9 -9.9 13 79.08 22.SLSUR 2 -.7 -4.3 3.6 3.4 -10.2 -2.8 76.82 20 SLSUR .5 -.8 -3.2 .9 3.3 -9.7 -9.6 76.71 18.NSUR 2 -.9 -2.6 -.6 3.1 -8.9 -14.1 76.66 17.NSUR .5 -.6 -4.9 4.8 3.7 -10.3 -0.6 76.87 20.INTFW 2 -.5 -4.3 .6 4.9 -12.1 -33.3 76.96 13.INTFW .5 -1 -2.9 5.9 .3 -9 17.5 76.57 25.IRC2 3 2 -.8 .3 -5.4 1.5 -6.1 -9.6 76.73 19.IRC2 .5 -.8 -4.4 5.3 3.4 -9.8 -2.8 76.77 19.LZETP2 3 1.25 -3.5 -7.7 -.6 2.2 -8.7 -9.6 74.68 18.LZETP2 .75 2.4 .7 5.9 4.9 -11.7 -1.7 79.21 20.

1 All parameters. 2 Included monthly entries.3 For IRC and LZETP, when increasing values in UCI file reached or exceeded 1, the value was input as 0.99 or 0.9.
36 Simulation of Streamflow

Creek Basin, ET is estimated to account for about

55 percent of the hydrologic budget (Sloto, 1994).

Interception storage (CEPSC) and the active

ground-water recession constant (AGWRC) also

affect total runoff but more moderately.

The 10-percent highest flows are sensitive

primarily to the infiltration rate (INFILT) and

sensitive secondarily to LZSN and AGWRC. The

50-percent lowest flows are sensitive primarily to

AGWRC and sensitive secondarily to INFILT.

Seasonal runoff volumes are most sensitive

to the active ground-water recession parameter

(AGWRC). Seasonal runoff volume refers to the

differences between summer (June, July, and

August) runoff volumes and winter (December,

January, and February) runoff volumes. Secondary

sensitivity is greatest for LZSN. AGWRC determines how rapidly base flow diminishes over time

after recharge to ground-water storage. Groundwater storage is controlled, in part, by infiltration

and water loss to lower-zone storage and evapotranspiration. Recharge to ground-water storage

typically exhibits seasonality. Base flow simulated

with high ground-water recession rates (AGWRC

close to 1.0) shows or even amplifies the seasonality in ground-water storage, whereas, base flow

simulated with low ground-water recession rates

(AGWRC less than 0.95) suppresses seasonal fluctuations in ground-water storage.

Summer storm volumes show primary sensitivity to LZSN and secondary sensitivity to INFILT.

LZSN generally is not considered as having much

effect over storm volumes. However, because

HSPEXP calculates storm volumes over only

whole 24-hour increments, storm volumes for

short-duration events, which are more prevalent in

the summer, will include more base flow. These

base-flow periods are affected by the LZSN parameter. In addition, HSPEXP analysis is limited to

36 storms. Eleven of the 36 storms selected for

analysis were from the drier than average 1997-98

period that coincided with available water-quality

data. Storms from this period tend to be smaller

(lower rainfall amounts than storms during other

periods) with the result that HSPEXP calculated

storm volumes that contain a large proportion of

base flow.

Peak stormflows are most sensitive to

INFILT. Infiltration rate affects stormflow through

diversion of potential surface runoff into the soil

storages. Surface runoff controls peak stormflows.

Peak stormflow was next most sensitive to interflow (INTFW), LZSN, and UZSN. INTFW diverts

surface runoff into interflow storage. Lower zone

storage (LZSN) and upper zone storage (UZSN)

have a slightly smaller but similar effect on peak

stormflows. In addition to these PERLND parameters, peak stormflow also is affected by IMPLND

parameters, if sufficient IMPLND area is present,

and by RCHRES storages as defined in the

F-Tables. As with storm volumes, the choice of

storms selected for inclusion into HSPEXP has a

substantial effect on the reported peak-stormflow

statistics.

Model Limitations

The final calibration of the hydrology component of the HSPF model for Red Clay Creek satisfies most of the recommended calibration criteria,

but has limitations. These limitations can be classified as either errors in the input and calibration

data or errors in the model structure. Errors in the

input data may result from the measurement,

interpolation, and extrapolation of precipitation

and other climatic data, and discharge and withdrawal rates. Errors in calibration data include

those involved in the measurement of observed

streamflow data. Measurement errors result from

equipment malfunction, incorrect data transcription, and other problems, including ice. Specific

information required to evaluate random or transitory measurement errors generally is unavailable.

Interpolation errors can occur when data are disaggregated to smaller time steps. Extrapolation errors

can occur when spatial variations and timing in

data are lost by applying localized data to large

areas.

Errors resulting from extrapolation, interpolation, and disaggregation of the precipitation data

probably are the greatest limitation to achieving

the best possible model calibration and simulations. Applying point location data from four raingages to the entire 54-mi2 basin and disaggregating

daily precipitation data to hourly data values

introduces substantial errors; stormflow simulations, in particular, have errors in peak flows and

total volumes regularly exceeding 100 percent.

These errors will translate into the water-quality

calibration of the model. In addition, temporal

errors in stormflow simulations can be detrimental

to the water-quality calibration even if stormflow

peaks and volumes are well simulated. The overall

effect of these errors is an increase in the average

error as the time period of simulation is decreased.

Other climatic data such as air temperature, solar
Simulation of Water Quality 37

radiation and wind speed are subject to the same

type of errors but are less important factors than

precipitation in the streamflow simulation.

Measurement errors in observed streamflow

are known and corrected in some instances but

unknown and roughly estimated in other instances

such as ice-affected streamflow data. In many

cases, corrections are limited to daily values and

hourly data are left uncorrected or missing. Periods of missing hourly streamflow record were

filled with estimated data for the model to calculate statistics. However, the errors associated with

this estimated data are unknown. The USGS (Durlin and Schaffstall, 1999) rates periods of estimated

record as poor and states that errors greater than

15 percent can be expected in some instances.

Errors in observed streamflow data can be

expected to affect the statistics used for calibration

evaluation and, if severe, lead to incorrect selection

of parameter values.

Errors in the model structure mainly are due

to limited resolution of PERLND, IMPLND, and

RCHRES spatial characteristics and incorrectly

specified model parameters. In general, spatial

errors result from the loss of local variation in spatial characteristics. Lack of data resolution and the

need to limit the complexity of the model structure

are the primary reasons for this loss. For example,

in the Red Clay Creek model, the number of pervious land-use categories has been limited to 10. In

actuality, more than 10 distinct land-use categories

are present. Further, each of these PERLND categories is assigned individual calibration parameters

that are selected to represent a composite average

for that category. Because of this spatial averaging,

model simulation is limited in the capacity to

resolve responses from land uses with limited areal

extent or that differ greatly from the average.

Many HSPF parameters are not expressed in

terms of known physical characteristics, making

selection of parameter values ambiguous and may

lead to incorrect specification in model simulation.

For example, the parameter AGWRC is not defined

in terms of established ground-water hydrologic

characteristics. Also, in the case of the parameter

INFILT, published soil permeability values cannot

be used directly but only as a guide. A satisfactorily calibrated model can be produced with more

than one combination of parameters and therefore

is not unique.

SIMULATION OF WATER QUALITY

Suspended sediment and nutrients were

simulated for the Red Clay Creek Basin. The simulation included delivery of suspended sediment

and nutrients from pervious and impervious land

areas to stream reaches and transport and chemical

reactions in the stream reaches. The instream simulation of nutrients requires information about

stream temperature and dissolved oxygen, both of

which were simulated in the model. Stream temperature is an important factor in determining

water quality because temperature affects saturation levels of dissolved oxygen and rates of chemical reactions. Dissolved oxygen concentrations

affect the extent of chemical reactions involving

nutrients, such as nitrification. In HSPF, the simulation of water quality is based on and is an extension of the hydrologic simulation.

The simulation of water quality was undertaken with the following assumptions: (1) landbased contributions of sediment and nutrients

could be simulated by a simplified set of land-use

categories; (2) water quality could be represented

by the condition where chemical transformation of

nutrients are simulated explicitly in the stream

channel but not in land processes; (3) the contribution of sediment from bank erosion in the stream

channel can be estimated by sediment from pervious land areas.

Calibration

Each land-use category is assigned parameters that affect interflow and ground-water temperature, sediment release, and nutrient contributions

from land areas. Stream reaches are assigned

parameters that affect the simulation of stream

temperature, sediment transport, bed erosion and

deposition, and chemical reactions in the stream

channel. Individual parameters were adjusted

until the simulated water quality was an acceptable match to observed water quality. The computer program GenScn (Kittle and others, 1998), a

graphical interface to HSPF, was used for the

water-quality calibration.

Suggested guidelines to evaluate sediment

and water-quality calibration, including the nutrients nitrogen and phosphorus, in the HSPF model

are given in percentage differences between

observed and simulated monthly or annual values

(table 14) (Donigian and others, 1984). Comparison

of loads, rather than instantaneous concentrations,

are considered more appropriate when evaluating
38 Simulation of Water Quality

water-quality simulations of nonpoint-source constituents (Donigian and others, 1984). Comparison

of instantaneous concentrations may result in

larger apparent differences between observed and

simulated values than comparison of loads for

some time periods, such as hours or days, because

of the effect of even small lags (errors) in the timing of storm events. In addition, simulation errors

usually are larger for water-quality concentrations

than for streamflow because of the greater complexity in simulating water quality than streamflow.

Water-quality calibration included stormflow and base-flow conditions. Because the hydrologic part of the model is integral to simulation of

water quality, only well-simulated storms ideally

would be used for calibration of suspended sediment and nutrients. In all cases, however, the simulated storm hydrograph does not replicate the

observed storm hydrograph well, especially with

respect to peak flows. Therefore, simulated concentrations of suspended sediment, nitrate, ammonia,

and phosphorus cannot be expected to exactly replicate observed concentrations for all storms. Based

on limited data and model guidelines (Donigian

and others, 1984), calibration was considered satisfactory when the general pattern of simulated

streamflow and suspended-sediment and nutrients

concentrations was simulated and when, for better

simulated storms, simulated loads of suspended

sediment and nutrients were within an order of

magnitude of observed loads. Individual storm

errors considerably larger than the recommended

criteria of 40 percent or less for monthly or annual

values for fair to good water-quality calibration

may occur and have little effect on the overall calibration (Donigian and others, 1984). Calibrated

values for water-quality parameters are given in

the UCI file for Red Clay Creek (appendix 2).

Monthly and annual load data were not

available to assess calibration errors. Simulated

and observed load data for four to five storms in

1998 were used to provide estimates of calibration

accuracy. Loads were calculated from measured

discharge and constituent concentrations in flowweighted composite samples collected during

storms. However, these limited data do not provide a long-term measure of model accuracy and

may include one or more poorly simulated storms

or questionable laboratory analyses, which can

have a large effect on the apparent model accuracy.

The calibration error, calculated as [(simulatedobserved)/observed] for the total flow volume or

constituent load for the five storms sampled, is

listed in table 15. Calibration errors for individual

storms at the nonpoint-source monitoring site are

listed and discussed in more detail in subsequent

sections describing calibration of suspended sediment, nitrogen, and phosphorus. Generally for

these storm events, loads of suspended sediment,

nitrogen, and phosphorus were undersimulated

when streamflow was undersimulated and oversimulated when streamflow was oversimulated.

Dissolved constituents were simulated better than

particulate constituents.

Table 14. Suggested criteria to evaluate water-quality

calibration for an Hydrological Simulation Program–

Fortran (HSPF) model

(from Donigian and others, 1984)

[<, less than]

Constituent

Difference between

observed and simulated

monthly or annual

values, in percent

Quality of calibration

Very

Good Good Fair

Sediment <15 15-25 25-35

Water quality (includes

nitrogen and phosphorus)

<20 20-30 30-40

Table 15. Cumulative calibration errors in flow volume and constituent loads for selected storms in 1998 at 01480000

Red Clay Creek at Wooddale, Del., the nonpoint-source monitoring site in the Red Clay Creek Basin

Site Number

of storms

Cumulative calibration error for selected storm simulations in 1998, in percent1

Streamflow

volume

Suspended

sediment

load

Nitrate

load

Dissolved

ammonia

load

Particulate

ammonia

load

Dissolved

orthophosphate

load

Particulate

phosphorus

load2

Red Clay Creek at

Wooddale, Del.

5 -24 -44 -41 18 -58 -32 -35

1 Percent calibration error = 100 x (simulated-observed)/observed.

2 One fewer storm was available for comparison because total phosphorus was not analyzed in the October 1998 storm.
Simulation of Water Quality 39

Water Temperature

Simulated stream water temperature was

calibrated against observed data collected at three

streamflow-measurement stations on the Red Clay

Creek where intermittent water-temperature data

were available. Comparison of simulated and

observed daily mean water temperature at the

three streamflow-measurement stations (fig. 17)

shows a fairly good correlation between simulated

and observed water temperature over the

observed range of 0 to 25°C except for water temperatures below about 10°C at the Kennett Square

streamflow-measurement station. The line of identity shown in figure 17 indicates where the simulated values exactly equal the observed values.

Simulated water temperatures below about 10°C at

the Kennett Square streamflow-measurement station are greater than observed water temperatures.

The assumption of a constant 12°C discharge temperature at the Kennett Square wastewater-treatment plant may, in part, account for these higher

simulated water temperatures. Errors in the simulated water temperatures, excluding any overall

bias, fall within plus or minus 4°C. Because water

temperature affects the rate of chemical reactions

and biological processes involving nutrients in the

stream, errors in the temperature simulation will

affect calibration of the nutrient simulation.

Sediment

Calibration of suspended sediment in the

stream channel largely is done by adjusting parameters affecting soil detachment, soil washoff, and

soil scour processes for pervious land surfaces, solids build up and washoff processes for impervious

land surfaces, and sediment transport in the channel, including deposition on and scour of the channel bottom controlled by setting shear stress

regimes. Sediment in streams may be derived from

land areas, streambanks, and beds. For the calibration, no net erosion of streambeds was assumed

over the simulation period and, therefore, the principal sources of sediment were assumed to be land

areas and streambanks. Because the process of

bank erosion is not included in the HSPF model

simulation, sediment from streambanks was estimated by simulating scour in pervious land areas.

Simulated concentrations of suspended sediment

were evaluated against total suspended solids data

collected by USGS in 1998 at 01480000 Red Clay

Creek at Wooddale, the nonpoint-source monitor0 30 5 10 15 20 25

OBSERVED INSTANTANEOUS WATER TEMPERATURE,

IN DEGREES CELSIUS

0

30

5

10

15

20

25

SIMULATED HOURLY MEAN

WATER TEMPERATURE, IN DEGREES CELSIUS

0 30 5 10 15 20 25

OBSERVED INSTANTANEOUS WATER TEMPERATURE,

IN DEGREES CELSIUS

0

30

5

10

15

20

25

SIMULATED HOURLY MEAN

WATER TEMPERATURE, IN DEGREES CELSIUS

0 30 5 10 15 20 25

OBSERVED INSTANTANEOUS WATER TEMPERATURE,

IN DEGREES CELSIUS

0

30

5

10

15

20

25

SIMULATED HOURLY MEAN

 WATER TEMPERATURE, IN DEGREES CELSIUS

Figure 17. Simulated hourly mean and observed

instantaneous water temperature at streamflowmeasurement stations (A) 01479820, Red Clay

Creek near Kennett Square, Pa., (B) 01480000,

Red Clay Creek at Wooddale, Del., and

(C) 01480015, Red Clay Creek at Stanton, Del.,

October 1994 - October 1998.

C

B

A LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY
40 Simulation of Water Quality

ing site, as well as data collected by PADEP at sites

in Pennsylvania (1995-98) and by DNREC at sites

in Delaware (1994-98).

The results of suspended-sediment simulation at Red Clay Creek at Wooddale provides a

measure of the overall model accuracy on a basinwide scale. Instantaneous concentrations of suspended solids were measured for five storms and

four base-flow events in 1998. Reported concentrations of suspended solids (nonfilterable material)

were considered estimates for suspended-sediment concentrations. Suspended-solids concentrations are not always accurate estimates of

suspended-sediment concentrations and tend to be

biased low, especially for conditions when sandsized particles represent more than 25 percent of

suspended sediment (Gray and others, 2000).

When suspended solids are used as a surrogate for

suspended-sediment concentrations, the resulting

errors in load computations can be as large as

4-5 orders of magnitude (U.S. Geological Survey,

2000). As noted earlier, only well-simulated storms

(simulation error less than 20 percent for storm

peaks, for example) would, ideally, be used for

calibration of suspended sediment. In many cases,

storms were not well simulated. Observed and

simulated streamflow and suspended sediment for

the five sampled storms at Red Clay Creek at

Wooddale are shown in figure 18. Streamflow is

undersimulated for all five storms. For the three

storms during which discrete samples were collected, the simulated suspended-sediment concentrations range from less than, similar to, and

greater than observed concentrations of suspended

solids.

Composite samples collected during storms

at the Wooddale monitoring site in the Red Clay

Creek Basin in 1998 allow comparison of simulated

and observed loads for the periods monitored.

Peak flows were greatest in the March and June

storms and least in the May and October storms

(table 16). For the sampled storm periods, streamflow volume and suspended-sediment loads tend

to be undersimulated. The difference between

observed and simulated streamflow ranged from

-2 to -59 percent for individual storms and was

-24 percent for the total of all storms. The difference between observed and simulated suspendedsediment loads ranged from -91 to greater than

(>) 1,903 percent for individual storms and was

-44 percent for the total of all storms. The May

storm had the largest percentage difference

between observed and simulated suspended-sediment load yet was the smallest in magnitude of the

sampled storms. The less than 1 mg/L concentration of suspended solids reported in the composite

sample for that storm is uncharacteristically low

even for low-magnitude stormflow conditions and

likely in error.

Comparison of simulated and observed values (table 16) for all sites indicate that when flow is

undersimulated or over simulated, loads of suspended sediment tend to be undersimulated or

oversimulated, respectively, to a greater degree.

For example, in a case of undersimulation, the

cumulative error was -24 percent for simulated

streamflow and -44 percent for simulated suspended-sediment load at Wooddale.

Table 16. Simulated and observed streamflow and loads of suspended sediment for storms sampled in 1998 at

01480000 Red Clay Creek at Wooddale, Del.

[ft3/s, cubic feet per second; >, greater than; mg/L, milligram per liter]

Dates of

storm sampling

Peak

discharge1

(ft3/s)

Streamflow volume (millions of cubic feet) Suspended-sediment load (tons)

Simulated Observed Percentage

difference2 Simulated Observed Percentagedifference2

Red Clay Creek at Wooddale, Del.

March 8-9 688 14.68 19.33 -24 79.37 76.33 4

May 2-3 66 7.45 7.62 -2 4.82 3.24 >1,903

June 12 580 3.05 7.38 -59 6.36 73.92 -91

July 8-9 280 7.77 9.11 -15 6.29 23.60 -73

October 8-9 74 4.20 5.68 -26 3.60 5.20 -31

Total (all storms) 37.15 49.11 -24 100.4 179.3 -44

1 Peak mean hourly discharge during period of composite sampling.

2 100 x (simulated-observed)/observed.

3 Reported value of 1 mg/L for total suspended solids concentration in composite sample appears erroneously low.
Simulation of Water Quality 41

7 8 9 10

March 1998

0

400

100

200

300

SUSPENDED-SEDIMENT CONCENTRATION,

IN MILLIGRAMS PER LITER

0

1,000

200

400

600

800

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

October 1998

0

200

50

100

150

SUSPENDED-SEDIMENT CONCENTRATION,

IN MILLIGRAMS PER LITER

0

250

50

100

150

200

STREAMFLOW, IN CUBIC FEET PER SECOND

EXPLANATION

SIMULATED STREAMFLOW

OBSERVED STREAMFLOW

SIMULATED SUSPENDED SEDIMENT

OBSERVED SUSPENDED SEDIMENT

30 1 2 3 4

April May

1998

0

40

10

20

30

SUSPENDED-SEDIMENT CONCENTRATION,

IN MILLIGRAMS PER LITER

40

70

50

60

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

July 1998

0

200

50

100

150

SUSPENDED-SEDIMENT CONCENTRATION,

IN MILLIGRAMS PER LITER

0

300

100

200

2400 1200 2400 1200 2400 1200 2400

STREAMFLOW, IN CUBIC FEET PER SECOND

11 12 13

June 1998

0

150

50

100

SUSPENDED-SEDIMENT CONCENTRATION,

IN MILLIGRAMS PER LITER

0

600

200

400

STREAMFLOW, IN CUBIC FEET PER SECOND

Figure 18. Simulated and observed streamflow and suspended-sediment concentrations and period of

composite sample during five storms in 1998 at streamflow-measurement station 01480000, Red Clay Creek at

Wooddale, Del.

PERIOD OF COMPOSITE SAMPLE
42 Simulation of Water Quality

The error in the water-quality component of

the load simulation can be estimated by adjusting

for the error in streamflow simulation as follows,

although this approach does not account for a nonlinear relation between flow and concentration:

percentage error in water-quality

component of load =

100 × ([(Ls/Lo) / (Qs/Qo)] -1), (1)

where

Ls is simulated load,

Lo is observed load,

Qs is simulated streamflow, and

Qo is observed streamflow.

Using this approach, the error in the suspendedsediment component of the cumulative load is

-26 percent at Red Clay at Wooddale. The nonlinear relation between streamflow and sediment

accounts for some of the differences in errors for

streamflow and suspended-sediment simulations.

Suspended-sediment simulation is dependent on

accuracy of precipitation data and the flow simulation and has a large degree of error.

Simulated concentrations of suspended sediment under base-flow conditions generally were

within one order of magnitude of observed concentrations at the Wooddale monitoring site

(fig. 19). For these base-flow samples, streamflow

was well simulated, as shown in figure 19. The

average percentage difference between simulated

and observed base flow was -15 percent, indicating

moderate oversimulation (exceedance of observed

values).

Instantaneous loads, calculated from measured streamflows and suspended-solids concentrations in grab samples collected monthly or

bimonthly by PADEP and DNREC at three streamflow-measurement stations, also were used to evaluate model calibration. At the streamflow-measurement stations, 01479820 Red Clay Creek near

Kennett Square, Pa., 01480000 Red Clay Creek at

Wooddale, Del., and 01480015 Red Clay Creek near

Stanton, Del., instantaneous streamflows were

moderately well simulated (fig. 20), with differences between simulated and observed ranging

from -78 to 43 percent. At the three sites, most simulated suspended-sediment instantaneous loads

were within an order of magnitude (or factor of 10)

of observed loads, and in general are only moderately well simulated (fig. 21). Most of the grab samples were collected from July 1995 through October

1998 under moderate (20 to 100 ft3/s at Stanton, for

example) to low-flow (<20 ft3/s at Stanton) conditions, although a few samples were collected under

relatively high-flow (>200 ft3/s at Stanton) (fig. 20)

conditions. The median percent differences

between simulated suspended-sediment loads and

observed suspended-solids loads at the stations

01479820, 01480000, and 01480015 were 33, -16, and

-16 percent, respectively. Although data on

monthly and annual loads of suspended sediment

0 80 20 40 60

OBSERVED INSTANTANEOUS STREAMFLOW,

IN CUBIC FEET PER SECOND

0

80

20

40

60

SIMULATED HOURLY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND

0 40 10 20 30

OBSERVED INSTANTANEOUS TOTAL SUSPENDED SOLIDS

CONCENTRATION, IN MILLIGRAMS PER LITER

0

40

10

20

30

SIMULATED SUSPENDED-SEDIMENT

CONCENTRATION, IN MILLIGRAMS PER LITER

Figure 19. Simulated hourly mean streamflow and

suspended-sediment concentrations, and observed

instantaneous streamflow and total suspended-solids

concentrations under base-flow conditions at

monitoring site, 01480000, Red Clay Creek at

Wooddale, Del.,1998.

LINE OF IDENTITY

LINE OF IDENTITY
Simulation of Water Quality 43

are not available, the median of instantaneous

loads at the three stations provides an estimate of

the adequacy of the sediment calibration as “fair”

to “good” on the basis of guidelines described by

Donigian and others (1984).

In summary, the quality of the suspendedsediment calibration ranges from less than “fair”

(more than 35-percent error) to “very good” (less

than 15-percent error) for individual storms based

on criteria from Donigian and others (1984). Simulated instantaneous suspended-sediment loads at

three long-term fixed time-interval sites generally

were within one order of magnitude of observed

loads. These results indicate the range of variability that might be expected in simulating individual

storms or instantaneous values. Comparison of the

observed and simulated suspended-sediment concentration duration curves indicates that over relatively long time periods (5 years or more), the

model results statistically are similar to observed

data (Senior and Koerkle, 2003a).

Simulated yields of sediment differ by land

use and vary with precipitation from year to year

(table 17). Simulated yields of sediment by land

use were similar in the three segments (tables 17

and 18) and are within the ranges reported for

equivalent land-use types by Dunne and Leopold

(1978, p. 520-522). Most of the simulated sediment

yield was from land areas. Using pervious-land

scour as an estimate of bank erosion, the average

simulated amount of sediment removed by scour

for the years 1994-97 differed among land uses and

ranged from 0 to 17 percent of the total sediment

yield. The highest percentage of sediment yield

produced by scour was in urban and sewered residential land uses (median values of 8 and

4 percent, respectively) and the lowest was in forested and wetland land uses (median values of 1

and 0 percent, respectively). In areas of agricultural

land use, the range of average simulated scour

(bank erosion) was about from 1 to 3 percent of

total sediment yield for 1994-97 and appears to be

slightly lower or similar to estimates obtained elsewhere with similar physical settings. In a study of

sediment sources in two agricultural basins in the

United Kingdom, bank erosion was estimated to

contribute about 10 percent or less of the sediment

yield (Russell and others, 2001).

5 500 10 20 50 100 200

OBSERVED INSTANTANEOUS STREAMFLOW,

IN CUBIC FEET PER SECOND

5

500

10

20

50

100

200

SIMULATED HOURLY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND

1 1,000 2 5 10 20 50 100 200

OBSERVED INSTANTANEOUS STREAMFLOW,

IN CUBIC FEET PER SECOND

1

1,000

2

5

10

20

50

100

200

500

SIMULATED HOURLY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND

1 1,000 2 5 10 20 50 100 200

OBSERVED INSTANTANEOUS STREAMFLOW,

IN CUBIC FEET PER SECOND

1

1,000

2

5

10

20

50

100

200

500

SIMULATED HOURLY MEAN STREAMFLOW,

IN CUBIC FEET PER SECOND

Figure 20. Simulated hourly mean and observed

instantaneous streamflow at streamflow-measurement stations (A) 01479820, Red Clay Creek near

Kennett Square, Pa., (B) 01480000, Red Clay Creek

at Wooddale, Del., and (C) 01480015, Red Clay Creek

at Stanton, Del., October 1994 - October 1998.

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

A

B

C
44 Simulation of Water Quality

0.5 100 1 2 5 10 20 50

OBSERVED TOTAL SUSPENDED-SOLIDS

CONCENTRATION, IN MILLIGRAMS PER LITER

0.5

100

1

2

5

10

20

50

SIMULATED SUSPENDED-SEDIMENT

CONCENTRATION, IN MILLIGRAMS PER LITER

1 1,000 2 5 10 20 50 100 200 500

OBSERVED TOTAL SUSPENDED-SOLIDS

LOAD, IN POUNDS PER HOUR

1

1,000

2

5

10

20

50

100

200

500

SIMULATED SUSPENDED-SEDIMENT

LOAD, IN POUNDS PER HOUR

1 5,000 5 10 50 100 500 1,000

OBSERVED TOTAL SUSPENDED-SOLIDS

CONCENTRATION, IN MILLIGRAMS PER LITER

1

5,000

5

10

50

100

500

1,000

SIMULATED SUSPENDED-SEDIMENT

CONCENTRATION, IN MILLIGRAMS PER LITER

1 5,000 5 10 50 100 500 1,000

OBSERVED TOTAL SUSPENDED-SOLIDS

LOAD, IN POUNDS PER HOUR

1

5,000

5

10

50

100

500

1,000

SIMULATED SUSPENDED-SEDIMENT

LOAD, IN POUNDS PER HOUR

1 5,000 5 10 50 100 500 1,000

OBSERVED TOTAL SUSPENDED-SOLIDS

CONCENTRATION, IN MILLIGRAMS PER LITER

1

5,000

5

10

50

100

500

1,000

SIMULATED SUSPENDED-SEDIMENT

CONCENTRATION, IN MILLIGRAMS PER LITER

1 5,000 5 10 50 100 500 1,000

OBSERVED TOTAL SUSPENDED-SOLIDS

LOAD, IN POUNDS PER HOUR

1

5,000

5

10

50

100

500

1,000

SIMULATED SUSPENDED-SEDIMENT

LOAD, IN POUNDS PER HOUR

Figure 21. Simulated hourly mean suspended-sediment and observed instantaneous total suspended-solids

concentrations and hourly mean loads at streamflow-measurement stations (A) 01479820, Red Clay Creek near

Kennett Square, Pa., (B) 01480000, Red Clay Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek at

Stanton, Del., October 1994 - October 1998.

FACTOR OF 10

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

FACTOR OF 10

FACTOR OF 10

FACTOR OF 10

FACTOR OF 10

FACTOR OF 10

A

A

B B

C C
Simulation of Water Quality 45

Table 17. Observed annual precipitation and simulated annual sediment yields

by land use for three segments of Hydrological Simulation Program–Fortran

(HSPF) model for Red Clay Creek Basin, Pennsylvania and Delaware, 1995-97

Segment

Year

1995 1996 1997 1995-97

average

Precipitation (inches) 7,4,6 40.59 61.98 35.01 45.86

Simulated sediment yield (tons per acre per year) by land-use category1

Residential - unsewered 7 .150 .649 .083 .294

Residential -sewered 7 .215 .681 .111 .336

Urban 7 .412 .712 .174 .433

Agricultural - animal/crop 7 1.80 3.32 1.24 2.12

Agricultural - row crop 7 1.76 3.30 1.18 2.08

Agricultural - mushroom 7 2.04 4.08 .945 2.36

Forested 7 .015 .226 .019 .087

Open 7 .183 .650 .116 .316

Wetlands/water 7 .002 .021 .002 .009

Undesignated 7 .175 .650 .115 .313

Impervious - residential 7 .206 .188 .203 .199

Impervious - urban 7 .814 .745 .801 .787

Simulated sediment yield (tons per acre per year) by land-use category1

Residential - unsewered 4 .131 .575 .065 .257

Residential -sewered 4 .176 .622 .081 .293

Urban 4 .363 .655 .143 .387

Agricultural - animal/crop 4 1.46 3.28 .958 1.90

Agricultural - row crop 4 1.41 3.25 .873 1.84

Agricultural - mushroom 4 1.89 3.97 .849 2.24

Forested 4 .011 .157 .012 .060

Open 4 .126 .581 .073 .260

Wetlands/water 4 .002 .020 .002 .008

Undesignated 4 .120 .564 .066 .250

Impervious - residential 4 .205 .187 .202 .198

Impervious - urban 4 .812 .742 .798 .784

Simulated sediment yield (tons per acre per year) by land-use category1

Residential - unsewered 6 .070 .323 .040 .144

Residential -sewered 6 .113 .519 .065 .232

Urban 6 .224 .608 .133 .322

Agricultural - animal/crop 6 .997 3.020 .820 1.61

Agricultural - row crop 6 .953 2.950 .762 1.56

Agricultural - mushroom 6 .981 3.640 .456 1.69

Forested 6 .007 .082 .012 .033

Open 6 .111 .453 .074 .213

Wetlands/water 6 .001 .009 .001 .004

Undesignated 6 .110 .450 .073 .211

Impervious - residential 6 .204 .187 .202 .198

Impervious - urban 6 .808 .742 .798 .783

1 In pervious areas, unless noted.
46 Simulation of Water Quality

Table 18. Observed annual precipitation and simulated average annual sediment yield by

land use for pervious and impervious land areas in three segments of Hydrological

Simulation Program–Fortran (HSPF) model for Red Clay Creek Basin, Pennsylvania

and Delaware, 1995-97

1995-97 Average

Segment 7 Segment 4 Segment 6 Average of

all segments

Precipitation (inches) 145.86 45.86 45.86 45.86

Simulated average annual sediment yield (tons per acre per year) by land-use category2

Residential - unsewered .294 .257 .144 .232

Residential -sewered .336 .293 .232 .287

Urban .433 .387 .322 .381

Agricultural - animals/crops 2.12 1.90 1.61 1.88

Agricultural - row crop 2.08 1.84 1.56 1.83

Agricultural - mushroom 2.36 2.24 1.69 2.10

Forested .087 .060 .033 .060

Open .316 .260 .213 .263

Wetlands/water .009 .008 .004 .007

Undesignated .313 .250 .211 .258

Impervious - residential .199 .198 .198 .198

Impervious - urban .787 .784 .783 .785

1 Precipitation for segment 7 = 0.85 × precipitation at Coatesville 2 W. 2 In pervious areas, unless noted.
Simulation of Water Quality 47

Dissolved Oxygen and

Biochemical Oxygen Demand

Dissolved oxygen and biochemical oxygen

demand (BOD) must be simulated in order to simulate nutrients in the stream. The simulation of dissolved oxygen included the instream effects of air

and water temperature, reaeration, advection, and

algal activity (photosynthesis and respiration).

Oxygen concentrations were simulated in landsurface runoff and were fixed in interflow and

ground water. Dissolved-oxygen concentration

data collected intermittently at three streamflowmeasurement stations in the Red Clay Creek Basin

were used to evaluate the dissolved-oxygen simulation. In order to reproduce the temporal pattern

of diurnal fluctuations in dissolved-oxygen concentrations observed at three continuous monitoring sites on the Brandywine Creek, simulation of

plankton was needed (Senior and Koerkle, 2003a),

and therefore, simulation of phytoplankton and

periphyton was included in the water-quality

modeling for Red Clay Creek. The simulation of

BOD from nonpoint sources included transport of

BOD from land to streams and instream processes

of BOD decay, settling, and advection. Concentrations of BOD in the soil (sediment), interflow, and

ground water were fixed in amounts that differed

by land use. Estimates of BOD in soil, interflow,

and ground water were derived from an HSPF

model of the Pautuxent River Basin in northeastern

Maryland (Stephen D. Preston, U.S. Geological

Survey, written commun., 1995). BOD concentration data from the analysis of grab and composite

stream samples collected at the nonpoint-source

monitoring site were used to evaluate the BOD

simulation.

The general pattern of seasonal changes in

dissolved-oxygen concentrations were simulated

by the model with varying degrees of accuracy, as

shown in figure 22 for three sites on Red Clay

Creek. Simulated dissolved-oxygen concentrations tended to be lower than observed concentrations in the winter months for Red Clay Creek near

Kennett Square, Pa., and higher than observed concentrations throughout the year at the other two

sites downstream (fig. 22). The diurnal fluctuation

in dissolved-oxygen concentrations attributed to

processes of algal photosynthesis and respiration

becomes more pronounced in the summer months

than at other times of the year.

At Red Clay Creek near Kennett Square, the

difference between simulated hourly mean and

observed instantaneous dissolved-oxygen concentrations ranged from -30 to 19 percent [100 × (simulated - observed)/observed] and the average

difference was -3 percent for 35 observations made

from July 1995 through October 1998. At Red Clay

Creek at Wooddale, the difference between simulated hourly mean and observed instantaneous

dissolved-oxygen concentrations ranged from 3 to

77 percent and the average difference was

31 percent for 36 observations made from October

1994 through October 1998. At Red Clay Creek

near Stanton, the difference between simulated

hourly mean and observed instantaneous dissolved-oxygen concentrations ranged from 0 to

135 percent and the average difference was

33 percent for 39 observations made from October

1994 through October 1998. These results indicate

that dissolved-oxygen concentration tends to be

slightly undersimulated at the Kennett Square site

and moderately (by about 20 percent) oversimulated at the Wooddale and Stanton sites downstream (fig. 23).

The simulation of phytoplankton was evaluated using chlorophyll-a concentration data collected under base-flow conditions in 1998 as part

of the nonpoint-source monitoring and under a

range of hydrologic conditions at the two streamflow-measurement stations in Delaware as part of

State monitoring efforts. Evaluation of the limited

data collected and simulated results under baseflow conditions do not indicate a bias in the simulation (fig. 24). However, for the larger amount of

data collected under State monitoring, the model

appears to undersimulate chlorophyll a at higher

concentrations (fig. 25). The highest concentration

of chlorophyll a was measured in the samples at

Wooddale and Stanton collected under the highest

flow conditions of all samples and may include

chlorophyll a from sources (such as periphyton)

disturbed by high-flow conditions.

Samples for BOD analysis were collected

under stormflow and base-flow conditions in 1998

at the nonpoint-source monitoring site, 01480000

Red Clay Creek at Wooddale, Del. Comparison of

simulated and observed BOD loads under stormflow conditions indicates that both simulated

stormflow and BOD are less than observed stormflow and BOD for the five storms sampled and that

the undersimulation for BOD is up to 23 percent
48 Simulation of Water Quality

O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O

1994 1995 1996 1997 1998

2

20

4

6

8

10

12

14

16

18

DISSOLVED-OXYGEN CONCENTRATION,

IN MILLIGRAMS PER LITER

O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O

1994 1995 1996 1997 1998

2

20

4

6

8

10

12

14

16

18

DISSOLVED-OXYGEN CONCENTRATION,

IN MILLIGRAMS PER LITER

O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O

1994 1995 1996 1997 1998

2

20

4

6

8

10

12

14

16

18

DISSOLVED-OXYGEN CONCENTRATION,

IN MILLIGRAMS PER LITER

Figure 22. Simulated daily mean and observed instantaneous dissolved-oxygen concentrations at

streamflow-measurement stations (A) 01479820, Red Clay Creek near Kennett Square, Pa.,

(B) 01480000, Red Clay Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek at Stanton,

Del., October 1994 through October 1998.

A

B

C

SIMULATED DAILY MEAN

OBSERVED INSTANTANEOUS
Simulation of Water Quality 49

0 20 5 10 15

OBSERVED INSTANTANEOUS DISSOLVED-OXYGEN

CONCENTRATION, IN MILLIGRAMS PER LITER

0

20

5

10

15

SIMULATED HOURLY MEAN DISSOLVED-OXYGEN

CONCENTRATION, IN MILLIGRAMS PER LITER

OBSERVED INSTANTANEOUS DISSOLVED-OXYGEN

CONCENTRATION, IN MILLIGRAMS PER LITER

SIMULATED HOURLY MEAN DISSOLVED-OXYGEN

CONCENTRATION, IN MILLIGRAMS PER LITER

0 20 5 10 15

OBSERVED INSTANTANEOUS DISSOLVED-OXYGEN

CONCENTRATION, IN MILLIGRAMS PER LITER

0

20

5

10

15

SIMULATED HOURLY MEAN DISSOLVED-OXYGEN

CONCENTRATION, IN MILLIGRAMS PER LITER

Figure 23. Simulated hourly mean and observed instantaneous dissolved-oxygen concentrations at

streamflow-measurement stations (A) 01479820, Red Clay Creek near Kennett Square, Pa., (B) 01480000,

Red Clay Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek at Stanton, Del., October 1994

through October 1998. (Data from Pennsylvania Department of Environmental Protection and Delaware

Department of Environmental Control.)

C

A

LINE OF IDENTITY

LINE OF IDENTITY

0 20 5 10 15

0

20

5

10

15

B

LINE OF IDENTITY
50 Simulation of Water Quality

0 15 3 6 9 12

OBSERVED INSTANTANEOUS CHLOROPHYLL-a

CONCENTRATION, IN MICROGRAMS PER LITER

0

15

3

6

9

12

SIMULATED HOURLY MEAN CHLOROPHYLL-a

CONCENTRATION, IN MICROGRAMS PER LITER

Figure 24. Simulated and observed

concentrations of chlorophyll a in base-flow

samples at streamflow-measurement station

01480000 Red Clay Creek at Wooddale, Del.,

1998.

LINE OF IDENTITY

0 25 5 10 15 20

OBSERVED INSTANTANEOUS CHLOROPHYLL-a

CONCENTRATION, IN MICROGRAMS PER LITER

0

25

5

10

15

20

SIMULATED HOURLY MEAN CHLOROPHYLL-a

CONCENTRATION, IN MICROGRAMS PER LITER

0 25 5 10 15 20

OBSERVED INSTANTANEOUS CHLOROPHYLL-a

CONCENTRATION, IN MICROGRAMS PER LITER

0

25

5

10

15

20

SIMULATED HOURLY MEAN CHLOROPHYLL-a

CONCENTRATION, IN MICROGRAMS PER LITER

Figure 25. Simulated hourly mean and observed instantaneous concentrations of chlorophyll a at streamflowmeasurement stations (A) 01480000 Red Clay Creek at Wooddale, Del., and (B) 01480015, Red Clay Creek at

Stanton, Del., October 1994 through October 1998. (Data from Pennsylvania Department of Environmental

Protection and Delaware Department of Environmental Control.)

A B

Not plottedobserved value, 45

simulated value 0.59

LINE OF IDENTITY LINE OF IDENTITY
Simulation of Water Quality 51

greater than the undersimulation for streamflow

(table 19). Undersimulation of BOD may result in

undersimulation of BOD decay and consequent

underestimation of oxygen depletion. The amount

of oxygen in the stream reach can affect the extent

of nitrification and denitrification reactions. No

bias in the simulation of BOD under base-flow conditions was apparent for the limited number of

samples (fig. 26). Concentrations of BOD in some

of the samples collected in 1998 under base-flow

conditions were reported as less than the detection

level of 2.4 mg/L and were estimated for analysis

to be 1.2 mg/L, 0.5 times the detection level

(fig. 26).

Data collected by PADEP and DNREC at three

streamflow-measurement stations under a range of

hydrologic conditions also were used to evaluate

the simulation of BOD. As noted earlier, most of

the samples were collected under moderate or

base-flow conditions. The median difference

between simulated and observed BOD concentrations was 20 percent for Red Clay Creek near Kennett Square, -28 percent for Red Clay Creek at

Wooddale, and -32 percent for Red Clay Creek

near Stanton (fig. 27). This pattern of differences

0 10 2 4 6 8

0

10

2

4

6

8

SIMULATED HOURLY MEAN

IN MILLIGRAMS PER LITER

LINE OF IDENTITY

Figure 26. Simulated and observed concentrations of

20-day biological oxygen demand in base-flow samples

at streamflow-measurement station 01480000 Red

Clay Creek at Wooddale, Del., 1998.

OBSERVED INSTANTANEOUS

BIOCHEMICAL OXYGEN DEMAND CONCENTRATION,

IN MILLIGRAMS PER LITER

BIOCHEMICAL OXYGEN DEMAND CONCENTRATION,

Table 19. Simulated and observed streamflow and loads of biochemical oxygen demand for storms

sampled in 1998 at the nonpoint-source monitoring site, 01480000 Red Clay Creek at Wooddale, Del.

[BOD, biochemical oxygen demand; ft3/s, cubic feet per second]

Dates of

storm

sampling

Peak

discharge1

(ft3/s)

Streamflow volume (millions of cubic feet) BOD load (tons)

Simulated Observed Percentage

difference2 Simulated Observed Percentagedifference2

March 8-9 688 14.68 19.33 -24 2.43 3.18 -23

May 2-3 66 7.45 7.62 -2 .79 .86 -8

June 12 580 3.05 7.38 -59 .46 1.90 -76

July 8-9 280 7.77 9.11 -15 1.40 2.12 -34

October 8-9 74 4.20 5.68 -26 .70 1.12 -38

Total (all storms) 37.16 49.11 -25 5.78 9.18 -37

1 Peak mean hourly discharge during period of composite sampling.

2 100 x (simulated-observed)/observed.
52 Simulation of Water Quality

1 100 2 5 10 20 50

OBSERVED INSTANTANEOUS BIOCHEMICAL OXYGEN

DEMAND CONCENTRATION, IN MILLIGRAMS PER LITER

1

100

2

5

10

20

50

SIMULATED HOURLY MEAN BIOCHEMICAL

OXYGEN DEMAND CONCENTRATION,

1 100 2 5 10 20 50

OBSERVED INSTANTANEOUS BIOCHEMICAL OXYGEN

DEMAND CONCENTRATION, IN MILLIGRAMS PER LITER

1

100

2

5

10

20

50

SIMULATED HOURLY MEAN BIOCHEMICAL

OXYGEN DEMAND CONCENTRATION,

1 100 2 5 10 20 50

OBSERVED INSTANTANEOUS BIOCHEMICAL OXYGEN

DEMAND CONCENTRATION, IN MILLIGRAMS PER LITER

1

100

2

5

10

20

50

SIMULATED HOURLY MEAN BIOCHEMICAL

OXYGEN DEMAND CONCENTRATION,

2 200 5 10 20 50 100

OBSERVED INSTANTANEOUS BIOCHEMICAL OXYGEN

DEMAND LOAD, IN POUNDS PER HOUR

2

200

5

10

20

50

100

SIMULATED HOURLY MEAN BIOCHEMICAL

OXYGEN DEMAND LOAD, IN POUNDS PER HOUR

2 200 5 10 20 50 100

OBSERVED INSTANTANEOUS BIOCHEMICAL OXYGEN

DEMAND LOAD, IN POUNDS PER HOUR

2

200

5

10

20

50

100

SIMULATED HOURLY MEAN BIOCHEMICAL

OXYGEN DEMAND LOAD, IN POUNDS PER HOUR

2 200 5 10 20 50 100

OBSERVED INSTANTANEOUS BIOCHEMICAL OXYGEN

DEMAND LOAD, IN POUNDS PER HOUR

2

200

5

10

20

50

100

SIMULATED HOURLY MEAN BIOCHEMICAL

OXYGEN DEMAND LOAD, IN POUNDS PER HOUR

Figure 27. Simulated hourly mean and observed instantaneous 20-day biochemical oxygen demand

concentrations and loads at streamflow-measurement stations (A) 01479820, Red Clay Creek near Kennett

Square, Pa., (B) 01480000, Red Clay Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek at

Stanton, Del., October 1994 through October 1998. (Data from Pennsylvania Department of Environmental

Protection and Delaware Department of Environmental Control.)

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY FACTOR OF 5

FACTOR OF 5

FACTOR OF 5

A A

B B

C C

IN MILLIGRAMS PER LITER IN MILLIGRAMS PER LITER IN MILLIGRAMS PER LITER
Simulation of Water Quality 53

between simulated and observed concentrations is

the converse of the dissolved-oxygen simulation.

Apparent errors in BOD and dissolved-oxygen

simulations may result, in part, from the inverse

relation between BOD and dissolved-oxygen concentration. Errors in load estimates of BOD from

point sources as well as nonpoint sources may contribute to overall errors of BOD in-stream concentrations.

Overall, the simulation of oxygen-related

constituents results in fair to good estimates of dissolved oxygen concentrations that are needed for

the in-stream simulation of nutrients. Errors in the

simulation of BOD and plankton affect the simulation of in-stream dissolved-oxygen concentrations.

Undersimulation of BOD could result in oversimulation of dissolved-oxygen concentration. Undersimulation of plankton could result in the undersimulation of dissolved-oxygen concentration during the day, when photosynthesis occurs, and oversimulation of dissolved oxygen during the night,

when respiration processes are dominant.

Nitrogen

The two inorganic species of nitrogen,

nitrate and ammonia, were simulated. Nitrogen

loads from point and nonpoint sources were

included in the simulation. Loads from pointsource discharges were estimated from reported

average monthly data for input on an hourly time

step to the model. For most point-source discharges, nitrate was estimated from reported

ammonia loads using the ratios specified in U.S.

Environmental Protection Agency Region 3

(2000a), whereas nitrite was assumed to be negligible. The ratio of nitrate to ammonia in point-source

effluent used for model data sets was 0.84 for small

wastewater-treatment plants (WWTPs) (generally

discharging less than 0.5 Mgal/d), 314 for

advanced secondary treatment type 1 WWTPs, 157

for advanced secondary treatment type 2 WWTPs,

and 0.21 for industrial discharges. In the Red Clay

Creek Basin, all WWTPs were considered small

plants (U.S. Environmental Protection Agency

Region 3, 2000a). For nonpoint sources, concentrations of nitrate and ammonia in sediment (soil),

interflow, and ground water were estimated as

fixed concentrations that differed by land use.

Nitrate was assumed to be transported solely in

the dissolved form. Ammonia was assumed to be

transported in both dissolved and adsorbed forms.

Water-quality data from the nonpoint-source

monitoring station, 01480000 Red Clay Creek at

Wooddale, Del., were used in the calibration of

concentrations of dissolved nitrate and dissolved

and particulate ammonia nitrogen in stormflow

and base flow. Simulated and observed concentrations of dissolved nitrate for the five storms sampled at the nonpoint-source monitoring site are

shown in figure 28. Composite samples were collected for all five storms but discrete samples only

were collected for three storms (March, July, and

October 1998). Observed and simulated nitrate

concentrations generally decrease as streamflow

increases during storms, although in two storms

(July and October) simulated decreases in nitrate

concentrations were larger than observed

decreases in nitrate concentrations (fig. 28).

Data from composite stormflow samples collected in 1998 were used in the calculation of loads

of dissolved nitrate and dissolved and particulate

ammonia nitrogen. Calculated loads served as the

observed values in overall evaluation of nitrogen

transport during storms.

Simulated and observed streamflow and

load data for dissolved nitrate for sampled storm

events are presented in table 20. For the sampled

storm periods, streamflow volume and nitrate

loads tend to be undersimulated. The difference

between observed and simulated streamflow

ranged from -2 to -59 percent for individual storms

and was -24 percent for the total of all storms. The

difference between observed and simulated dissolved nitrate loads ranged from -17 to -81 percent

for individual storms and was -41 percent for the

total of all storms. As discussed in the section on

sediment, some error in load simulations is due to

error in streamflow simulation and the difference

between the load error and the streamflow-volume

error may be useful in evaluating the water-quality

component of the overall load error. The cumulative error of -41 percent for simulated nitrate load

adjusted for the cumulative error of -24 percent for

simulated streamflow volume at Wooddale is

-22 percent. At the monitoring site at Wooddale on

Red Clay Creek, the undersimulation of nitrate

may be related to errors in estimating contributions of nitrate from point sources in addition to

those associated with nitrate from nonpoint

sources.
54 Simulation of Water Quality

7 8 9 10

March 1998

0

4

1

2

3

DISSOLVED-NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

0

1,000

200

400

600

800

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

October 1998

0

4

1

2

3

DISSOLVED-NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

0

250

50

100

150

200

STREAMFLOW, IN CUBIC FEET PER SECOND

EXPLANATION

SIMULATED STREAMFLOW

OBSERVED STREAMFLOW

SIMULATED DISSOLVED NITRATE

OBSERVED DISSOLVED NITRATE

30 1 2 3 4

April May

1998

0

4

1

2

3

DISSOLVED-NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

40

70

50

60

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

July 1998

0

4

1

2

3

DISSOLVED-NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

0

300

100

200

STREAMFLOW, IN CUBIC FEET PER SECOND

2400 1200 2400 1200 2400 1200 2400

11 12 13

June 1998

0

4

1

2

3

DISSOLVED-NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

0

600

200

400

STREAMFLOW, IN CUBIC FEET PER SECOND

Figure 28. Simulated and observed streamflow and dissolved-nitrate concentrations and period of composite

sample during five storms in 1998 at streamflow-measurement station 01480000, Red Clay Creek at Wooddale, Del.

PERIOD OF COMPOSITE SAMPLE
Simulation of Water Quality 55 Table 20. Simulated and observed streamflow and loads of dissolved nitrate, dissolved ammonia, and particulate ammonia for storms sa

nonpoint-source monitoring site, 01480000 Red Clay Creek at Wooddale, Del. [ft3/s, cubic feet per second; --, not calculated; mg/L, milligrams per liter] Dates of storm sampling Peak flow1 (ft3/s) Streamflow volume (millions of cubic feet) Dissolved nitrate load (pounds as nitrogen) Dissolved ammonia load (pounds as nitrogen) Pa

Simulated Observed Percent difference2 Simulated Observed Percent difference2 Simulated Observed Percent difference2 Simula

March 8-9 688 14.68 19.33 -24 1,907 2,711 -30 102 109 -7 14.1 

May 2-3 66 7.45 7.62 -2 1,351 1,627 -17 40.7 13.5 202 .7June 12 580 3.05 7.38 -59 241 1,283 -81 9.4 18.7 -50 .5July 8-9 280 7.77 9.11 -15 867 1,359 -36 35.5 36.3 -2 .6October 8-9 74 4.20 5.68 -26 410 1,156 -65 26.3 41.8 1,368 .5

Total (all storms) 37.16 49.11 -24 4,776 8,136 -41 214 179 19 16.6 

1 Peak mean hourly discharge during period of composite sampling. 2 100 x (simulated-observed)/observed. 3 Reported total ammonia concentration of less than dissolved ammonia concentration in composite storm sample is questionably low. 4 Reported dissolved ammonia concentration of less than 0.005 mg/L in composite storm sample is questionably low. 5 Reported total ammonia concentration of 0.048 mg/L in composite storm sample is questionably high relative to dissolved ammonia concentratio
56 Simulation of Water Quality

Simulated concentrations of dissolved

nitrate in base flow were within 0.2 mg/L or

13 percent of observed concentrations at the nonpoint-source monitoring site at Wooddale, Del.

(fig. 29). Streamflow was well simulated for all

base-flow samples, as shown in figure 19. The

monitoring site at Wooddale is downstream of

point-source discharges that can affect concentrations of nitrate and other constituents. Observed

hourly concentrations of nitrate for point-source

discharges were not available but were interpolated from reported average monthly concentrations of ammonia assuming a constant ratio of

nitrate to ammonia. The ratio of nitrate to ammonia in effluent probably fluctuates through time.

Data on nitrate concentrations at sites

upstream of major point-source discharges were

collected through county and State monitoring

programs (table 7). These data indicate the nitrate

concentrations tend to be undersimulated at the

West Branch Red Clay Creek at Kennett Square site

(average difference was -30 percent), adequately

simulated at the East Branch near Five Points site

(average difference was 0 percent), and oversimulated at the Burroughs Run site (average difference

was 63 percent). Sites on the West and East

Branches of Red Clay Creek were sampled under

base-flow condition and the Burroughs Run site

0 6 1 2 3 4 5

OBSERVED INSTANTANEOUS NITRITE PLUS NITRATE

CONCENTRATION, IN MILLIGRAMS PER LITER AS N

0

6

1

2

3

4

5

SIMULATED HOURLY MEAN NITRATE

CONCENTRATION, IN MILLIGRAMS PER LITER AS N

0.001 0.5 0.002 0.005 0.01 0.02 0.05 0.1 0.2

OBSERVED INSTANTANEOUS DISSOLVED AMMONIA

CONCENTRATION, IN MILLIGRAM PER LITER AS N

0.001

0.5

0.002

0.005

0.01

0.02

0.05

0.1

0.2

SIMULATED HOURLY MEAN DISSOLVED AMMONIA

CONCENTRATION, IN MILLIGRAM PER LITER AS N

0.0001 0.02 0.0002 0.0005 0.001 0.002 0.005 0.01

OBSERVED INSTANTANEOUS PARTICULATE AMMONIA

CONCENTRATION, IN MILLIGRAM PER LITER AS N

0.0001

0.02

0.0002

0.0005

0.001

0.002

0.005

0.01

SIMULATED HOURLY MEAN PARTICULATE AMMONIA

CONCENTRATION, IN MILLIGRAM PER LITER AS N

Figure 29. Simulated and observed concentrations of (A) nitrate, (B) dissolved ammonia, and (C) particulate

ammonia during base-flow conditions in 1998 at streamflow-measurement station 01480000 Red Clay Creek at

Wooddale, Del.

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

A

C B
Simulation of Water Quality 57

was sampled under a range of hydrologic conditions. These results suggest that the ground-water

contribution of nitrate is larger than simulated for

the West Branch drainage area and less than simulated for the Burroughs Run drainage area.

Data collected by PADEP and DNREC at

three streamflow-measurement stations under a

range of hydrologic conditions also were used to

evaluate the simulation of nitrate. All three of the

sites are downstream of point-source discharges.

As noted earlier, most of the samples were collected under moderate or base-flow conditions

(fig. 20). Observed nitrate concentrations tend to

decrease downstream from Kennett Square to

Wooddale to Stanton, possibly because of dilution

or instream nitrate uptake. The average difference

between simulated and observed nitrate concentrations was -20 percent for Red Clay Creek near

Kennett Square, 5 percent for Red Clay Creek at

Wooddale, and 2 percent for Red Clay Creek near

Stanton. Nitrate concentrations tend to be undersimulated at Red Clay Creek near Kennett Square

and oversimulated at the downstream stations,

Red Clay Creek at Wooddale and Red Clay Creek

near Stanton (fig. 30). Errors in load estimates of

nitrate from point sources and nonpoint sources as

well as instream processes may contribute to overall errors of instream nitrate concentrations. At all

sites, simulated nitrate loads generally were within

a factor of 5 or less of observed loads (fig. 30).

Simulated concentrations of dissolved and

particulate ammonia were compared to observed

concentrations of dissolved and particulate ammonia in stormflow, and base-flow conditions where

observed particulate ammonia concentrations

were calculated by subtracting dissolved-ammonia

concentrations from total ammonia concentrations.

Review of 1998 monitoring data indicates that, on

average, dissolved ammonia represents about

71 percent of total ammonia concentrations for

samples collected at Red Clay Creek at Wooddale.

Simulated and observed concentrations of

dissolved and particulate ammonia for the five

storms sampled at the nonpoint-source monitoring

site, Red Clay Creek at Wooddale, are shown in

figures 31 and 32. Composite samples were collected for all five storms but discrete samples only

were collected for three storms (March, July, and

October 1998). Observed concentrations of dissolved ammonia generally tend to increase as

streamflow increases during storms but simulated

concentrations of ammonia appear to fluctuate

more in response to changes in time than streamflow (fig. 31). The temporal pattern of fluctuations

in simulated dissolved-ammonia concentrations

probably is related to the simulated processes of

ammonia uptake and release by periphyton and

phytoplankton. The available nonpoint-source

monitoring data are insufficient to calibrate the

effects of algal growth and respiration on instream

dissolved-ammonia concentrations, and the algal

(periphyton and phytoplankton) simulation is a

source of error for the dissolved-ammonia simulation. Observed and simulated concentrations of

particulate ammonia also tend to increase as

streamflow increases during storms (fig. 32).

Although the general range of observed dissolved

and particulate ammonia concentrations during

storms is simulated in the model, errors or differences between observed and simulated concentrations are apparent. Errors or differences between

observed and simulated particulate ammonia concentrations are due in part to errors in flow, suspended-sediment simulation, and timing of

rainfall for storms.

Data from composite stormflow samples collected in 1998 were used in the calculation of loads

of dissolved nitrate, and dissolved and particulate

ammonia nitrogen. Calculated loads served as the

observed values in overall evaluation of nitrogen

transport during storms. Simulated and observed

streamflow and loads of dissolved and particulate

ammonia nitrogen for storm events in 1998 are presented in table 20. Observed loads of dissolved

ammonia commonly are greater than observed

loads of particulate ammonia except for one storm

in October 1998, for which the particulate ammonia was greater than the dissolved ammonia load.

The analytical results for the ammonia concentrations in the October composite storm sample are

questionable, however, partly because of the

unusual ratio of observed total dissolved ammonia. For all five storms, streamflow was undersimulated. For three storms sampled, dissolved

ammonia was undersimulated. The difference

between observed and simulated streamflow

ranged from -2 to -59 percent for individual storms

and was -24 percent for the total of all storms. The

difference between observed and dissolved ammonia loads ranged from -50 to 1,368 percent for individual storms and was 19 percent for the total of all

storms. The maximum values in percent differences are associated with storm samples with

questionable analytical results. Adjusting for the

cumulative error of -24 percent for simulated
58 Simulation of Water Quality

0 8 1 2 3 4 5 6 7

OBSERVED NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

0

8

1

2

3

4

5

6

7

SIMULATED NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

1 1,000 2 5 10 20 50 100 200 500

OBSERVED NITRATE LOAD,

IN POUNDS AS N PER HOUR

1

1,000

2

5

10

20

50

100

200

500

SIMULATED NITRATE LOAD,

IN POUNDS AS N PER HOUR

0 8 1 2 3 4 5 6 7

OBSERVED NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

0

8

1

2

3

4

5

6

7

SIMULATED NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

1 1,000 2 5 10 20 50 100 200 500

OBSERVED NITRATE LOAD,

IN POUNDS AS N PER HOUR

1

1,000

2

5

10

20

50

100

200

500

SIMULATED NITRATE LOAD,

IN POUNDS AS N PER HOUR

0 8 1 2 3 4 5 6 7

OBSERVED NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

0

8

1

2

3

4

5

6

7

SIMULATED NITRATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS N

1 1,000 2 5 10 20 50 100 200 500

OBSERVED NITRATE LOAD,

IN POUNDS AS N PER HOUR

1

1,000

2

5

10

20

50

100

200

500

SIMULATED NITRATE LOAD,

IN POUNDS AS N PER HOUR

Figure 30. Simulated hourly mean and observed instantaneous nitrate concentrations and loads at

streamflow-measurement stations (A) 01479820, Red Clay Creek near Kennett Square, Pa.,

(B) 01480000, Red Clay Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek at Stanton, Del.,

October 1994 through October 1998. (Data from Pennsylvania Department of Environmental Protection

and Delaware Department of Environmental Control.)

LINE OF IDENTITY

LINE OF IDENTITY LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY LINE OF IDENTITY

FACTOR OF 5

FACTOR OF 5

FACTOR OF 5

A A

B B

C C
Simulation of Water Quality 59

7 8 9 10

March 1998

0

0.20

0.05

0.10

0.15

DISSOLVED-AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0

1,000

200

400

600

800

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

October 1998

0

0.24

0.05

0.10

0.15

0.20

DISSOLVED-AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0

250

50

100

150

200

STREAMFLOW, IN CUBIC FEET PER SECOND

EXPLANATION

SIMULATED STREAMFLOW

OBSERVED STREAMFLOW

SIMULATED DISSOLVED AMMONIA

OBSERVED DISSOLVED AMMONIA

30 1 2 3 4

April May

1998

0

0.20

0.05

0.10

0.15

DISSOLVED-AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

40

70

50

60

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

July 1998

0

0.20

0.05

0.10

0.15

DISSOLVED-AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0

300

100

200

2400 1200 2400 1200 2400 1200 2400

STREAMFLOW, IN CUBIC FEET PER SECOND

11 12 13

June 1998

0

0.20

0.05

0.10

0.15

DISSOLVED-AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0

600

200

400

STREAMFLOW, IN CUBIC FEET PER SECOND

Figure 31. Simulated and observed streamflow and dissolved-ammonia concentrations and period of composite

sample during five storms in 1998 at streamflow-measurement station 01480000, Red Clay Creek at Wooddale, Del.

PERIOD OF COMPOSITE SAMPLE
60 Simulation of Water Quality

7 8 9 10

March 1998

0

0.03

0.01

0.02

PARTICULATE AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0

1,000

200

400

600

800

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

October 1998

0

0.03

0.01

0.02

PARTICULATE AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0

250

50

100

150

200

STREAMFLOW, IN CUBIC FEET PER SECOND

EXPLANATION

SIMULATED STREAMFLOW

OBSERVED STREAMFLOW

SIMULATED PARTICULATE AMMONIA

OBSERVED PARTICULATE AMMONIA

30 1 2 3 4

April May

1998

0

0.03

0.01

0.02

PARTICULATE AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

40

70

50

60

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

July 1998

0

0.03

0.01

0.02

PARTICULATE AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0

300

100

200

2400 1200 2400 1200 2400 1200 2400

STREAMFLOW, IN CUBIC FEET PER SECOND

11 12 13

June 1998

0

0.03

0.01

0.02

PARTICULATE AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0

600

200

400

STREAMFLOW, IN CUBIC FEET PER SECOND

Figure 32. Simulated and observed streamflow and particulate ammonia concentrations and period of composite

sample during five storms in 1998 at streamflow-measurement station 01480000, Red Clay Creek at Wooddale, Del.

PERIOD OF COMPOSITE SAMPLE
Simulation of Water Quality 61

streamflow, as discussed in the section on sediment, the 19-percent cumulative error for simulated dissolved-ammonia loads at Wooddale

indicates a cumulative error of 58 percent associated with the simulation of dissolved ammonia for

the five storms. At the monitoring site at Wooddale

on Red Clay Creek, the oversimulation and undersimulation of dissolved-ammonia concentrations

may be related to analytical errors and errors in

estimating contributions of ammonia from point

sources in addition to those associated with nitrate

from nonpoint sources.

For four storms sampled, particulate ammonia was undersimulated (table 20). The difference

between observed and particulate ammonia loads

ranged from -97 to -90 percent for individual

storms and was -58 percent for the total of all

storms. Adjusting for the cumulative error of

-24 percent for simulated streamflow, the cumulative error of -58 percent for simulated particulate

ammonia loads at Wooddale indicates a cumulative error of -45 percent associated with the simulation of particulate ammonia for the five storms.

The undersimulation of particulate ammonia may

be related to errors in partitioning from dissolved

to sorbed phases and to errors in sediment transport. Using monthly or yearly annual load criteria

(Donigian and others, 1984), the dissolved and particulate ammonia calibration ranges from “very

good” to worse than “fair” for individual storms.

Simulated concentrations of dissolved

ammonia under base-flow conditions generally

were greater than observed concentrations by 0.028

to 0.163 mg/L as nitrogen (N) at the Wooddale

monitoring site (fig. 29). As noted previously,

streamflow was well simulated for all base-flow

samples (fig. 19). The oversimulation of dissolved

ammonia at the Wooddale site may be related to

the lack of temporal resolution in estimated ammonia concentrations in discharges from WWTPs

upstream and to inaccurate simulation of instream

processes that include ammonia uptake and

release by algae. Mean hourly ammonia loads for

point-source discharges were estimated from

reported average monthly ammonia values; however, hourly values probably vary within each

month. Simulated concentrations of particulate

ammonia were less than 0.005 mg/L as N at all six

sites and are less than the observed concentrations

of particulate ammonia, which ranged from 0.002

to 0.01 mg/L as N.

Data collected by PADEP and DNREC at

three streamflow-measurement stations under a

range of hydrologic conditions also were used to

evaluate the simulation of total ammonia. All three

of the sites are downstream from point-source discharges. As noted earlier, most of the samples were

collected under moderate or base-flow conditions

(fig. 20). Ammonia concentrations are not well simulated. The average difference between simulated

and observed total ammonia concentrations was

653 percent for Red Clay Creek near Kennett

Square, 295 percent for Red Clay Creek at Wooddale, and 319 percent for Red Clay Creek near

Stanton. Total-ammonia concentrations tend to be

oversimulated at all three sites at lower concentrations (fig. 33). Errors in load estimates of nitrate

from point sources and nonpoint sources as well as

instream processes may contribute to overall errors

of instream ammonia concentrations. At all sites,

simulated ammonia loads generally were within a

factor of 10 or less of observed loads (fig. 33).

Overall, the nitrate and dissolved and particulate ammonia simulation under base-flow and

stormflow conditions generally appears to represent the observed patterns of ammonia concentrations in response to flow conditions and defined

land uses. Nitrate concentrations and loads were

simulated better than the ammonia concentrations

and loads in the HSPF model. Based on the criteria

of Donigian and others (1984), the overall simulation of nitrate was “good,” and the overall

simulation of dissolved and particulated ammonia

was “fair” to “worse than fair.” Dissolved ammonia storm loads and base-flow concentrations tend

to be oversimulated at the whole-basin site (Red

Clay Creek at Wooddale) that is downstream from

various point-source discharges and this oversimulation partly may be related to inaccurate characterization of ammonia uptake upstream of the

sampling site and (or) inadequate characterization

of ammonia in discharges. Commonly, for the Red

Clay Creek model, errors expressed in percent are

greater for particulate ammonia simulation than

for dissolved ammonia simulation and are greater

for the ammonia simulation than the nitrate simulation. Of the nitrogen species simulated, nitrate

represents the greatest amount and particulate

ammonia represents the least amount of the inorganic nitrogen load. In storms, nitrate loads are an

order of magnitude greater than dissolved-ammonia loads and two orders of magnitude greater

than particulate ammonia loads (table 20).
62 Simulation of Water Quality

0.005 1 0.01 0.02 0.05 0.1 0.2 0.5

OBSERVED TOTAL AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0.005

1

0.01

0.02

0.05

0.1

0.2

0.5

SIMULATED TOTAL AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0.05 10 0.1 0.2 0.5 1 2 5

OBSERVED TOTAL AMMONIA LOAD,

IN POUNDS AS N PER HOUR

0.05

10

0.1

0.2

0.5

1

2

5

SIMULATED TOTAL AMMONIA LOAD,

IN POUNDS AS N PER HOUR

0.005 1 0.01 0.02 0.05 0.1 0.2 0.5

OBSERVED TOTAL AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0.005

1

0.01

0.02

0.05

0.1

0.2

0.5

SIMULATED TOTAL AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0.05 200 0.1 0.2 0.5 1 2 5 10 20 50 100

OBSERVED TOTAL AMMONIA LOAD,

IN POUNDS AS N PER HOUR

0.05

200

0.1

0.2

0.5

1

2

5

10

20

50

100

SIMULATED TOTAL AMMONIA LOAD,

IN POUNDS AS N PER HOUR

0.005 1 0.01 0.02 0.05 0.1 0.2 0.5

OBSERVED TOTAL AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0.005

1

0.01

0.02

0.05

0.1

0.2

0.5

SIMULATED TOTAL AMMONIA CONCENTRATION,

IN MILLIGRAM PER LITER AS N

0.05 200 0.1 0.2 0.5 1 2 5 10 20 50 100

OBSERVED TOTAL AMMONIA LOAD,

IN POUNDS AS N PER HOUR

0.05

200

0.1

0.2

0.5

1

2

5

10

20

50

100

SIMULATED TOTAL AMMONIA LOAD,

IN POUNDS AS N PER HOUR

Figure 33. Simulated hourly mean and observed instantaneous total ammonia concentrations and loads

at streamflow-measurement stations (A) 01479820, Red Clay Creek near Kennett Square, Pa.,

(B) 01480000, Red Clay Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek at Stanton, Del.,

October 1994 through October 1998. (Data from Pennsylvania Department of Environmental Protection

and Delaware Department of Environmental Control.)

FACTOR OF 10

FACTOR OF 10

FACTOR OF 10

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

A A

B B

C C
Simulation of Water Quality 63

Simulated annual yields of nitrogen varied

by land use. Annual yields of nitrate and ammonia

are presented per land-use category per segment in

tables 21 and 23 and mean yields of nitrate and

ammonia for the simulation period are presented

per land-use category per segment in tables 22

and 24. For most land uses, simulated nitrate

yields generally are at least one order of magnitude greater than simulated total ammonia yields.

Phosphorus

The model was used to simulate inorganic

phosphorus, where dissolved and adsorbed orthophosphate are considered to be the principal dissolved and particulate inorganic phosphorus

species. Phosphorus loads from point and nonpoint sources are included in the simulation. Loads

from point-source discharges were estimated from

reported monthly average values for input on an

hourly time step to the model. For nonpoint

sources, dissolved and particulate phosphorus

were estimated at fixed concentrations in sediment

(soil), interflow, and ground water that differed by

land use. Phosphorus was assumed to be

transported in both dissolved and adsorbed forms

from the land surface and in the stream channel.

Review of 1994-98 DNREC monitoring data on the

mainstem of Red Clay Creek collected typically

under moderate-flow conditions indicates that, on

average, dissolved orthophosphate represents

about 70 percent of total phosphorus concentrations. For 1998 data collected at the Wooddale nonpoint-source monitoring station under a range of

flow conditions, dissolved orthophosphate represented, on average, about 41 percent of total phosphorus concentrations.

Water-quality data from the nonpoint-source

monitoring station, Red Clay Creek at Wooddale,

were used to assess the calibration of dissolved

and particulate (adsorbed) orthophosphate.

Observed concentrations of particulate orthophosphate were estimated by subtracting dissolvedphosphorus concentrations from total-phosphorus

concentrations and assuming the difference was

particulate orthophosphate.

Simulated and observed dissolved and particulate orthophosphate concentrations are shown

in figures 34 and 35 for the five storms sampled at

the nonpoint-source monitoring site, Red Clay

Creek at Wooddale. Composite samples were collected for all five storms but discrete samples only

were collected for three storms (March, July, and

October 1998). Samples from the October 1998

storm were not analyzed for total phosphorus and,

therefore, particulate phosphorus concentrations

could not be estimated. Observed dissolved and

particulate orthophosphate concentrations generally tend to increase as streamflow increases during storms (figs. 34 and 35). The general pattern of

observed dissolved and particulate orthophosphate concentrations during storms are simulated

by the model only for some storms.
64 Simulation of Water Quality

Table 21. Observed annual precipitation and simulated annual nitrate yields by land use

for the three segments of the Hydrological Simulation Program–Fortran (HSPF) model for

Red Clay Creek Basin, 1995-97

Segment

Year

1995 1996 1997 1995-97

average

Precipitation (inches)1 7,4,6 40.59 61.98 35.01 45.86

Simulated annual nitrate yield (pounds as nitrogen per acre per year), by land-use category2

Residential - unsewered 7 7.03 18.6 11.8 12.5

Residential -sewered 7 3.78 9.89 6.12 6.60

Urban 7 3.93 9.58 6.05 6.52

Agricultural - animal/crop 7 15.0 35.5 22.0 24.2

Agricultural - row crop 7 13.1 31.0 18.9 21.0

Agricultural - mushroom 7 17.8 42.7 24.8 28.4

Forested 7 .728 2.11 1.39 1.41

Open 7 2.61 6.92 4.31 4.61

Wetlands/water 7 .741 2.25 1.47 1.49

Undesignated 7 2.53 6.93 4.32 4.59

Impervious - residential 7 2.03 2.06 2.03 2.04

Impervious - urban 7 2.03 2.06 2.03 2.04

Simulated annual nitrate yield (pounds as nitrogen per acre per year), by land-use category2

Residential - unsewered 4 7.06 19 10.7 12.3

Residential -sewered 4 3.81 10.3 5.65 6.59

Urban 4 3.93 9.95 5.55 6.48

Agricultural - animal/crop 4 14.4 36.5 19.8 23.6

Agricultural - row crop 4 8.89 22.8 12.0 14.6

Agricultural - mushroom 4 17.6 43.7 22.7 28.0

Forested 4 .732 2.09 1.25 1.36

Open 4 2.56 7.09 3.92 4.52

Wetlands/water 4 .738 2.32 1.43 1.50

Undesignated 4 2.57 7.16 3.95 4.56

Impervious - residential 4 2.02 2.05 2.03 2.03

Impervious - urban 4 2.02 2.05 2.03 2.03

Simulated annual nitrate yield (pounds as nitrogen per acre per year), by land-use category2

Residential - unsewered 6 9.09 22.1 8.52 13.2

Residential -sewered 6 4.77 11.8 4.42 7.00

Urban 6 4.86 11.7 4.43 7.00

Agricultural - animal/crop 6 17.3 42.1 15.9 25.1

Agricultural - row crop 6 14.7 36.2 13.5 21.5

Agricultural - mushroom 6 21.2 52.7 19.3 31.1

Forested 6 .896 2.36 .909 1.39

Open 6 3.23 7.94 2.98 4.72

Wetlands/water 6 .951 2.85 1.04 1.61

Undesignated 6 3.23 7.95 2.98 4.72

Impervious - residential 6 2.02 2.05 2.03 2.03

Impervious - urban 6 2.02 2.05 2.03 2.03

1 Precipitation input to segment 7 = 0.85 x precipitation recorded at Coatesville.

2 In pervious areas, unless noted.
Simulation of Water Quality 65

Table 22. Observed annual precipitation and simulated mean annual nitrate yield by land use

for pervious and impervious land areas in the three segments of the Hydrological Simulation

Program–Fortran (HSPF) model for Red Clay Creek Basin, 1995-97

 1995-97 Average

Segment 7 Segment 4 Segment 6 Mean of all

segments

Precipitation (inches) 145.86 45.86 45.86 45.86

Simulated mean annual nitrate yield (tons as nitrogen per acre per year), by land-use category2

Residential - unsewered 12.48 12.25 13.24 12.66

Residential -sewered 6.60 6.59 7.00 6.73

Urban 6.52 6.48 7.00 6.66

Agricultural - animals/crops 24.2 23.6 25.1 24.3

Agricultural - row crop 21.0 14.6 21.5 19.0

Agricultural - mushroom 28.4 28.0 31.1 29.2

Forested 1.41 1.36 1.39 1.39

Open 4.61 4.52 4.72 4.62

Wetlands/water 1.49 1.50 1.61 1.53

Undesignated 4.59 4.56 4.72 4.62

Impervious - residential 2.04 2.03 2.03 2.03

Impervious - urban 2.04 2.03 2.03 2.03

1 Precipitation for segment 7 = 0.85 x precipitation at Coatesville 2 W.

2 In pervious areas, unless where noted.
66 Simulation of Water Quality

Table 23. Observed annual precipitation and simulated annual total ammonia yields

by land use for the three segments of the Hydrological Simulation Program–Fortran

(HSPF) model for Red Clay Creek Basin, 1995-97

Segment

Year

1995 1996 1997 1995-97

average

Precipitation (inches)1 7,4,6 40.59 61.98 35.01 45.86

Simulated annual total ammonia yield (pounds as nitrogen per acre per year), by land-use category2

Residential - unsewered 7 .088 .286 .109 .161

Residential -sewered 7 .050 .138 .060 .083

Urban 7 .068 .133 .065 .088

Agricultural - animal/crop 7 .764 1.430 .583 .926

Agricultural - row crop 7 .576 1.10 .443 .706

Agricultural - mushroom 7 3.15 6.31 1.61 3.69

Forested 7 .020 .055 .038 .037

Open 7 .073 .205 .106 .128

Wetlands/water 7 .012 .040 .024 .025

Undesignated 7 .070 .206 .106 .127

Impervious - residential 7 .370 .371 .372 .371

Impervious - urban 7 .431 .426 .432 .430

Simulated annual total ammonia yield (pounds as nitrogen per acre per year), by land-use category2

Residential - unsewered 4 .083 .274 .097 .151

Residential -sewered 4 .047 .138 .054 .080

Urban 4 .063 .133 .058 .085

Agricultural - animal/crop 4 .489 1.110 .368 .656

Agricultural - row crop 4 .264 .624 .215 .368

Agricultural - mushroom 4 2.90 6.07 1.40 3.46

Forested 4 .020 .055 .034 .036

Open 4 .067 .204 .094 .122

Wetlands/water 4 .012 .040 .023 .025

Undesignated 4 .067 .204 .094 .122

Impervious - residential 4 .370 .370 .372 .371

Impervious - urban 4 .431 .426 .432 .430

Simulated annual total ammonia yield (pounds as nitrogen per acre per year), by land-use category2

Residential - unsewered 6 .086 .242 .075 .134

Residential -sewered 6 .049 .143 .042 .078

Urban 6 .059 .147 .048 .085

Agricultural - animal/crop 6 .367 1.060 .309 .579

Agricultural - row crop 6 .214 .609 .181 .335

Agricultural - mushroom 6 1.05 3.72 .553 1.77

Forested 6 .024 .064 .024 .037

Open 6 .081 .214 .073 .123

Wetlands/water 6 .015 .048 .017 .027

Undesignated 6 .081 .213 .073 .122

Impervious - residential 6 .370 .370 .372 .371

Impervious - urban 6 .430 .426 .431 .429

1 Precipitation for segment 7 = 0.85 x precipitation at Coatesville 2 W.

2 In pervious areas, unless where noted.
Simulation of Water Quality 67

Table 24. Observed annual precipitation and simulated mean annual total ammonia yield for

pervious and impervious land areas in the three segments of the Hydrological Simulation

Program–Fortran (HSPF) model for Red Clay Creek Basin, 1995-97

1995-97 Average

Segment 7 Segment 4 Segment 6 Mean of all

segments

Precipitation (inches) 1 45.86 45.86 45.86 45.86

Simulated mean annual total ammonia yield (tons as nitrogen per acre per year), by land-use category2

Residential - unsewered .161 .151 .134 .149

Residential -sewered .083 .080 .078 .080

Urban .088 .085 .085 .086

Agricultural - animals/crops .926 .656 .579 .720

Agricultural - row crop .706 .368 .335 .470

Agricultural - mushroom 3.69 3.46 1.77 2.97

Forested .037 .036 .037 .037

Open .128 .122 .123 .124

Wetlands/water .025 .025 .027 .026

Undesignated .127 .122 .122 .124

Impervious - residential .371 .371 .371 .371

Impervious - urban .430 .430 .429 .430

1 Precipitation for segment 7 = 0.85 x precipitation at Coatesville 2 W.

2 In pervious areas, unless where noted.
68 Simulation of Water Quality

7 8 9 10

March 1998

0

0.25

0.05

0.10

0.15

0.20

DISSOLVED-ORTHOPHOSPHATE CONCENTRATION,

IN MILLIGRAM PER LITER AS P

0

1,000

200

400

600

800

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

October 1998

0

0.25

0.05

0.10

0.15

0.20

DISSOLVED-ORTHOPHOSPHATE CONCENTRATION,

IN MILLIGRAM PER LITER AS P

0

250

50

100

150

200

STREAMFLOW, IN CUBIC FEET PER SECOND

EXPLANATION

SIMULATED STREAMFLOW

OBSERVED STREAMFLOW

SIMULATED DISSOLVED ORTHOPHOSPHATE

OBSERVED DISSOLVED ORTHOPHOSPHATE

30 1 2 3 4

April May

1998

0

0.20

0.05

0.10

0.15

DISSOLVED-ORTHOPHOSPHATE CONCENTRATION,

IN MILLIGRAM PER LITER AS P

40

70

50

60

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

July 1998

0

0.20

0.05

0.10

0.15

DISSOLVED-ORTHOPHOSPHATE CONCENTRATION,

IN MILLIGRAM PER LITER AS P

0

300

100

200

2400 1200 2400 1200 2400 1200 2400

STREAMFLOW, IN CUBIC FEET PER SECOND

11 12 13

June 1998

0

0.20

0.05

0.10

0.15

DISSOLVED-ORTHOPHOSPHATE CONCENTRATION,

IN MILLIGRAM PER LITER AS P

0

600

200

400

STREAMFLOW, IN CUBIC FEET PER SECOND

Figure 34. Simulated and observed streamflow and dissolved-orthophosphate concentrations and period of

composite sample during five storms in 1998 at streamflow-measurement station 01480000, Red Clay Creek at

Wooddale, Del.

PERIOD OF COMPOSITE SAMPLE
Simulation of Water Quality 69

7 8 9 10

March 1998

0

1.5

0.5

1.0

PARTICULATE ORTHOPHOSPHATE CONCENTRATION,

IN MILLIGRAMS PER LITER AS P

0

1,000

200

400

600

800

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

October 1998

0

0.06

0.02

0.04

PARTICULATE ORTHOPHOSPHATE CONCENTRATION,

IN MILLIGRAM PER LITER AS P

0

250

50

100

150

200

STREAMFLOW, IN CUBIC FEET PER SECOND

EXPLANATION

SIMULATED STREAMFLOW

OBSERVED STREAMFLOW

SIMULATED PARTICULATE ORTHOPHOSPHATE

OBSERVED PARTICULATE ORTHOPHOSPHATE

30 1 2 3 4

April May

1998

0

0.06

0.02

0.04

PARTICULATE ORTHOPHOSPHATE CONCENTRATION,

IN MILLIGRAM PER LITER AS P

40

70

50

60

STREAMFLOW, IN CUBIC FEET PER SECOND

7 8 9 10

July 1998

0

0.9

0.3

0.6

PARTICULATE ORTHOPHOSPHATE CONCENTRATION,

IN MILLIGRAM PER LITER AS P

0

300

100

200

2400 1200 2400 1200 2400 1200 2400

STREAMFLOW, IN CUBIC FEET PER SECOND

11 12 13

June 1998

0

0.6

0.2

0.4

PARTICULATE ORTHOPHOSPHATE CONCENTRATION,

IN MILLIGRAM PER LITER AS P

0

600

200

400

STREAMFLOW, IN CUBIC FEET PER SECOND

Figure 35. Simulated and observed streamflow and particulate orthophosphate concentrations and period of

composite sample during five storms in 1998 at streamflow-measurement station 01480000, Red Clay Creek at

Wooddale, Del.

PERIOD OF COMPOSITE SAMPLE
70 Simulation of Water Quality

Data from composite stormflow samples collected in 1998 were used in the calculation of dissolved orthophosphate and particulate orthophosphate loads. Calculated loads served as the

observed values in the evaluation of overall phosphorus transport during storms. Simulated and

observed streamflow, and dissolved and particulate orthophosphate loads for storm events in 1998

are presented in table 25. Observed loads of particulate orthophosphate commonly are greater than

observed loads of dissolved orthophosphate. For

one small storm in May 1998, dissolved orthophosphate loads were greater than particulate orthophosphate loads. Dissolved and particulate

orthophosphate loads tend to be undersimulated

when flow is undersimulated, with the exception

of the March 1998 storm.

The difference between observed and simulated dissolved orthophosphate loads ranged from

-77 to 98 percent for individual storms and was

-32 percent for the total of all storms (table 25). The

difference between observed and simulated

particulate orthophosphate loads ranged from -95

to 36 percent for individual storms and was

-35 percent for the total of all storms. At the monitoring site at Wooddale on Red Clay Creek, some

errors may be associated with estimated contributions of phosphorus from point sources in addition

to those associated with simulated orthophosphate

from nonpoint sources. The greater undersimulation of particulate orthophosphate compared to

dissolved orthophosphate may be related to errors

in partitioning from dissolved to sorbed phases

and to errors in sediment transport. As discussed

in the sections on sediment and nitrogen, some

error in load simulations is due to the error in

streamflow simulation. Adjusting for the cumulative error of -24 percent for simulated streamflow,

the cumulative errors of -32 and -35 percent for

simulated dissolved and particulate orthophosphate loads at Wooddale (table 25) indicate cumulative errors of -10 and -14 percent associated with

the simulation of dissolved and particulate orthophosphate concentrations for the five storms.

Using monthly or yearly annual load criteria

(Donigian and others, 1984), the dissolved and particulate orthophosphate calibration is “worse than

fair” for individual storm loads but “good” for the

cumulative storms loads.

Simulated concentrations of dissolved orthophosphate under base-flow conditions were less

than observed concentrations at the Red Clay

Creek at Wooddale monitoring site in 1998 (fig. 36).

The mean difference between observed and simulated dissolved orthophosphate for base-flow conditions was 0.109 mg/L as P, and the average

percent difference was about -60 percent. As noted

previously, streamflow was well simulated for all

base-flow samples (fig. 19). Simulated concentrations of particulate orthophosphate under baseflow conditions were both lower and higher than

observed concentrations. The mean difference

between observed and simulated particulate orthophosphate for three samples collected under baseflow conditions was 0.04 mg/L as P, and the average percent difference was -11 percent.

Data collected by PADEP and DNREC at

three streamflow-measurement stations under a

range of hydrologic conditions also were used to

evaluate the simulation of dissolved orthophosphate. All three of the sites are downstream of

Table 25. Simulated and observed streamflow and dissolved and particulate orthophosphate loads for storms sampled

in 1998 at the nonpoint-source monitoring site, 01480000 Red Clay Creek at Wooddale, Del.

[ft3/s, cubic feet per second; na, not applicable; nd, not done]

Dates of

storm

sampling

Peak

flow1

(ft3/s)

Streamflow volume

(millions of cubic feet)

Dissolved orthophosphate load

(pounds as phosphorus)

Particulate orthophosphate load

(pounds as phosphorus)

Simulated Observed Percent

difference2 Simulated Observed Percentdifference2 Simulated Observed Percentdifference2

March 8-9 688 14.68 19.33 -24 164 83 98 486 357 36

May 2-3 66 7.45 7.62 -2 27 72 -62 9 27 -67

June 12 580 3.05 7.38 -59 13 57 -77 13 270 -95

July 8-9 280 7.77 9.11 -15 24 90 -73 10 143 -93

October 8-9 74 4.20 5.68 -26 15 56 -73 na nd na

Total (all storms) 37.15 49.12 -24 243 358 -32 518 797 -35

1 Peak mean hourly discharge during period of composite sampling.

2 100 x (observed-simulated)/observed.
Simulation of Water Quality 71

point-source discharges. As noted earlier, most of

the samples were collected under moderate or

base-flow conditions (fig. 20). Dissolved-orthophosphate concentrations frequently were slightly

undersimulated (fig. 37). The average difference

between simulated and observed dissolved-orthophosphate concentrations was -29 percent for Red

Clay Creek near Kennett Square, -24 percent for

Red Clay Creek at Wooddale, and -12 percent for

Red Clay Creek near Stanton. At all sites, simulated orthophosphate loads generally were within

a factor of 5 or less of observed loads (fig. 37).

Errors in load estimates of dissolved orthophosphate from point sources and nonpoint sources as

well as instream processes may contribute to overall errors of instream orthophosphate concentrations.

Overall, the dissolved and particulate orthophosphate simulation under base-flow and stormflow conditions generally appears to represent the

observed patterns of phosphorus concentrations in

response to flow conditions and defined land uses.

At the nonpoint-source monitoring site, 01480000

Red Clay Creek at Wooddale, errors expressed in

percent are greater for particulate orthophosphate

simulation than for dissolved orthophosphate

simulation under stormflow conditions. In most

storms, observed particulate orthophosphate loads

commonly are from 1.5 to 5 times greater than

observed dissolved-orthophosphate loads

(table 25).

Simulated annual yields of phosphorus

varied by land use. Simulated yields of total orthophosphate (dissolved plus adsorbed or particulate

orthophosphate) are presented per land-use category per segment per year in table 26 and mean

yields of total orthophosphate for the simulation

period are presented per land-use category per

segment in table 27.

0.01 1 0.02 0.05 0.1 0.2 0.5

OBSERVED INSTANTANEOUS

CONCENTRATION, IN MILLIGRAM PER LITER AS P

0.01

1

0.02

0.05

0.1

0.2

0.5

SIMULATED HOURLY MEAN

IN MILLIGRAM PER LITER AS P

Figure 36. Simulated hourly mean and observed

instantaneous dissolved and particulate orthophosphate

concentrations during base-flow conditions in 1998 at

streamflow-measurement station 01480000 Red Clay

Creek at Wooddale, Del.

LINE OF IDENTITY

 DISSOLVED ORTHOPHOSPHATE CONCENTRATION,

DISSOLVED ORTHOPHOSPHATE

0.005 0.5 0.01 0.02 0.05 0.1 0.2

OBSERVED INSTANTANEOUS

CONCENTRATION, IN MILLIGRAM PER LITER AS P

0.005

0.5

0.01

0.02

0.05

0.1

0.2

SIMULATED HOURLY MEAN

IN MILLIGRAM PER LITER AS P

LINE OF IDENTITY

PARTICULATE ORTHOPHOSPHATE CONCENTRATION,

PARTICULATE ORTHOPHOSPHATE
72 Simulation of Water Quality

0.01 2 0.02 0.05 0.1 0.2 0.5 1

OBSERVED DISSOLVED ORTHOPHOSPHATE

CONCENTRATION, IN MILLIGRAMS PER LITER AS P

0.01

2

0.02

0.05

0.1

0.2

0.5

1

SIMULATED DISSOLVED ORTHOPHOSPHATE

CONCENTRATION, IN MILLIGRAMS PER LITER AS P

0.1 10 0.2 0.5 1 2 5

OBSERVED DISSOLVED ORTHOPHOSPHATE

LOAD, IN POUNDS AS P PER HOUR

0.1

10

0.2

0.5

1

2

5

SIMULATED DISSOLVED ORTHOPHOSPHATE

LOAD, IN POUNDS AS P PER HOUR

0.01 2 0.02 0.05 0.1 0.2 0.5 1

OBSERVED DISSOLVED ORTHOPHOSPHATE

CONCENTRATION, IN MILLIGRAMS PER LITER AS P

0.01

2

0.02

0.05

0.1

0.2

0.5

1

SIMULATED DISSOLVED ORTHOPHOSPHATE

CONCENTRATION, IN MILLIGRAMS PER LITER AS P

0.1 100 0.2 0.5 1 2 5 10 20 50 0.1

100

0.2

0.5

1

2

5

10

20

50

SIMULATED DISSOLVED ORTHOPHOSPHATE

LOAD, IN POUNDS AS P PER HOUR

0.01 2 0.02 0.05 0.1 0.2 0.5 1

OBSERVED DISSOLVED ORTHOPHOSPHATE

CONCENTRATION, IN MILLIGRAMS PER LITER AS P

0.01

2

0.02

0.05

0.1

0.2

0.5

1

SIMULATED DISSOLVED ORTHOPHOSPHATE

CONCENTRATION, IN MILLIGRAMS PER LITER AS P

0.1 100 0.2 0.5 1 2 5 10 20 50

OBSERVED DISSOLVED ORTHOPHOSPHATE

LOAD, IN POUNDS AS P PER HOUR

0.1

100

0.2

0.5

1

2

5

10

20

50

SIMULATED DISSOLVED ORTHOPHOSPHATE

LOAD, IN POUNDS AS P PER HOUR

Figure 37. Simulated hourly mean and observed instantaneous dissolved orthophosphate concentrations

and loads at streamflow-measurement stations (A) 01479820, Red Clay Creek near Kennett Square, Pa.,

(B) 01480000, Red Clay Creek at Wooddale, Del., and (C) 01480015, Red Clay Creek at Stanton, Del.,

October 1994 through October 1998. (Data from Pennsylvania Department of Environmental Protection and

Delaware Department of Environmental Control.)

LINE OF IDENTITY

FACTOR OF 5

FACTOR OF 5

FACTOR OF 5

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

LINE OF IDENTITY

A A

B B

C C

OBSERVED DISSOLVED ORTHOPHOSPHATE

LOAD, IN POUNDS AS P PER HOUR
73

Table 26. Observed annual precipitation and simulated annual total (dissolved plus adsorbed)

orthophosphate yields by land use for the three segments of the Hydrological Simulation Program–

Fortran (HSPF) model for Red Clay Creek Basin, 1995-97

Year

Segment 1995 1996 1997 1995-97

average

Precipitation (inches)1 7,4,6 40.59 61.98 35.01 45.86

Simulated annual total orthophosphate yield (pounds as phosphorus per acre per year), by land-use category2

Residential - unsewered 7 .136 .501 .131 .256

Residential - sewered 7 .172 .504 .147 .274

Urban 7 .281 .479 .177 .312

Agricultural - animal/crop 7 7.17 13.1 5.04 8.44

Agricultural - row crop 7 7.02 13.0 4.79 8.27

Agricultural - mushroom 7 28.3 55.8 13.3 32.5

Forested 7 .010 .031 .019 .020

Open 7 .166 .565 .127 .286

Wetlands/water 7 .006 .020 .012 .013

Undesignated 7 .158 .566 .126 .283

Impervious - residential 7 .407 .397 .401 .402

Impervious - urban 7 .932 .868 .918 .906

Simulated annual total orthophosphate yield (pounds as phosphorus per acre per year), by land-use category2

Residential - unsewered 4 .125 .463 .114 .234

Residential - sewered 4 .151 .482 .123 .252

Urban 4 .254 .465 .153 .291

Agricultural - animal/crop 4 5.86 13.0 3.90 7.59

Agricultural - row crop 4 5.63 12.9 3.57 7.37

Agricultural - mushroom 4 26.3 54.5 11.9 3.90

Forested 4 .100 .030 .017 .049

Open 4 .120 .514 .090 .241

Wetlands/water 4 .006 .021 .012 .013

Undesignated 4 .116 .502 .085 .234

Impervious - residential 4 .405 .395 .400 .400

Impervious - urban 4 .929 .865 .915 .903

Simulated annual total orthophosphate yield (pounds as phosphorus per acre per year), by land-use category2

Residential - unsewered 6 .105 .343 .084 .177

Residential - sewered 6 .130 .455 .098 .228

Urban 6 .191 .487 .134 .271

Agricultural - animal/crop 6 4.03 12.1 3.32 6.48

Agricultural - row crop 6 3.86 11.9 3.09 6.28

Agricultural - mushroom 6 13.7 5.50 6.45 23.6

Forested 6 .012 .033 .012 .019

Open 6 .114 .422 .083 .206

Wetlands/water 6 .008 .024 .008 .013

Undesignated 6 .113 .420 .082 .205

Impervious - residential 6 .403 .395 .399 .399

Impervious - urban 6 .925 .865 .913 .901

1 Precipitation input to segment 7 = 0.85 × precipitation recorded at Coatesville. 2 In pervious areas, unless noted.
74

Table 27. Observed annual precipitation and simulated mean annual total orthophosphate yield

by land use for pervious and impervious land areas in the three segments of the Hydrological Simulation

Program–Fortran (HSPF) model for Red Clay Creek Basin, 1995-97

1995-97 Average

Segment 7 Segment 4 Segment 6 Mean of all

segments

Precipitation (inches) 145.86 45.86 45.86 45.86

Simulated mean annual total orthophosphate yield (tons per acre per year), by land-use category2

Residential - unsewered .256 .234 .177 .222

Residential - sewered .274 .252 .228 .251

Urban .312 .291 .271 .291

Agricultural - animals/crops 8.44 7.59 6.48 7.50

Agricultural - row crop 8.27 7.37 6.28 7.31

Agricultural - mushroom 32.5 3.90 23.6 29.0

Forested .020 .049 .019 .029

Open .286 .241 .206 .245

Wetlands/water .013 .013 .013 .013

Undesignated .283 .234 .205 .241

Impervious - residential .402 .400 .399 .400

Impervious - urban .906 .903 .901 .903

1 Precipitation input to segment 7 = 0.85 × precipitation recorded at Coatesville. 2 In pervious areas, unless noted.
Simulation of Water Quality 75

Sensitivity Analysis

Calibration of water temperature is specified

by 13 parameters; 5 for pervious land surfaces,

2 for impervious land surfaces, and 6 for stream

reaches. For water-temperature simulation, the

model is more sensitive to parameters in the reach

modules than to parameters in pervious and

impervious modules. Water temperature in a reach

is simulated as a function of the variables:

upstream flow and land-surface inflow temperatures; air temperature; and radiation, conduction,

and convection gains or losses. Of these variables,

radiation, conduction, and convection gains and

losses have calibration parameters. Simulated

water temperatures are most sensitive to the

parameters CFSAEX, the solar radiation correction

factor, and KCOND, the conduction-convection

coefficient. Daily high temperatures are affected by

CFSAEX and nighttime low temperatures by

KCOND. In combination, CFSAEX and KCOND

also affect daily mean water temperature.

The simulated sediment yield from pervious

and impervious land areas is dependent on parameters affecting soil detachment, soil scour, and soil

or sediment washoff and is sensitive to parameters

affecting soil detachment (KRER, JRER), soil

washoff (KSER, JSER), and soil-scour processes

(KGER, JGER) for pervious land surfaces, and solids build up (ACCSDP, REMDSP) and washoff

processes for impervious land surfaces (KEIM,

JEIM). Sediment washoff or transport capacity is

dependent on surface runoff (SURO) and, therefore, the hydrologic component of the simulation.

In addition, calibration of suspended sediment in

the stream channel is sensitive to parameters controlling shear stress regimes (TAUD, TAUS) that

determine deposition on and scour of the channel

bottom. The sensitivity of sediment yields to

changes in parameters affecting pervious landsurface processes was investigated by varying

para-meters by selected multiplication factors.

Results reported at Red Clay Creek near Stanton,

Del., include the total effects in the three segments

above the station (table 28). Because nutrients can

Table 28. Sensitivity of model output for sediment and nutrient yields at streamflow-measurement station 01480015

Red Clay Creek near Stanton, Del., to changes in selected parameters affecting sediment contributions from pervious

land areas

[Model parameters: KRER, coefficient in soil detachment equation; JRER, exponent in soil detachment equation;

KSER, coefficient in detached-sediment washoff equation; JSER, exponent in detached-sediment washoff equation;

KGER, coefficient in soil-matrix scour equation; JGER, exponent in soil-matrix scour equation]

Parameter Multiplier

Sediment yield Nitrate yield Ammonia yield Phosphorus yield

Tons per

acre

Percent

difference1

Pounds

per acre

Percent

difference

Pounds

per acre

Percent

difference

Pounds

per acre

Percent

difference

Preliminary

calibration value2

1 3.34 0 47.01 0 1.89 0 18.04 0

Detachment processes

KRER .5 1.93 -42.4 44.61 -5.1 1.19 -36.7 10.10 -44.0

KRER 2 4.71 41.0 49.39 5.1 2.67 41.4 26.73 48.2

JRER .5 5.15 54.1 50.15 6.7 2.94 55.7 29.64 64.3

JRER 1.5 2.02 -39.5 44.78 -4.8 1.23 -34.7 10.56 -41.4

Washoff processes

KSER .5 2.40 -28.1 45.46 -3.3 1.51 -20.1 13.56 -24.8

KSER 2 3.70 10.6 47.57 1.2 2.01 6.5 19.40 7.6

JSER .75 3.78 13.1 47.67 1.4 2.04 8.2 19.81 9.8

JSER 1.5 2.02 -39.7 44.82 -4.7 1.30 -31.1 11.30 -37.3

Soil-scour processes

KGER .5 3.30 -1.2 47.01 0 1.89 0 18.04 0

KGER 2 3.42 2.2 47.01 0 1.89 0 18.04 0

JGER .5 3.55 6.2 47.01 0 1.89 0 18.04 0

JGER 1.5 3.42 2.2 47.01 0 1.89 0 18.04 0

1 Percent difference from calibrated value = 100 x (changed result - calibrated result)/calibrated result.

2 All parameters.
76 Simulation of Water Quality

be attached to sediment, factors affecting sediment

yields also affect nutrient yields. The sensitivity of

nutrient yields to changes in parameters that control sediment yields from land surfaces is shown in

table 28. Ammonia and phosphorus yields are

more sensitive than nitrate yields to changes in

sediment parameters.

The simulated yields of nitrate, ammonia,

and phosphate from pervious and impervious land

areas are dependent on parameters affecting concentrations of each constituent on sediment

(POTFW) and in interflow (IFLW-CONC) and

ground water (GRND-CONC). The sensitivity of

simulated total nutrient yields to changes in these

parameters was investigated by varying the

parameters by selected multiplication factors

(table 29). The parameters affecting ground-water

concentrations affect nitrate yields more than

yields of ammonia and phosphorus because of differences in the primary mechanisms that deliver

these nutrients to the streams. Consequently,

changes to parameters affecting concentrations of

nutrients in soil (POTFW) and interflow (IFLWCONC) affect yields of ammonia and phosphorus

more than nitrate.

Model Limitations

The simulation of water-quality constituent

concentrations and loads is dependent on the output of the hydrologic portion of the model. Thus,

the accuracy of the water-quality simulations will

be limited by the hydrologic model. In addition,

the water-quality calibration was based on few

(six or less storms) observed water-quality data;

therefore, compared to a calibration with many

water-quality data, greater uncertainty is associated with the simulation of water quality and

assessment of the model performance is more difficult.

Model parameters used for water-quality

simulation were obtained from calibration of models in adjacent basins of various sizes and may not

be representative of land uses in the Red Clay

Creek Basin. Concentrations of suspended sediment, nitrate, ammonia, and phosphorus for individual storms or short time periods may not be

well simulated by the model because of hydrologic

limitations related to accuracy of rainfall data. The

timing and intensity of rainfall affect detachment

processes for soil and soil-related constituents, as

well as transport of the solids from land to streams.

Simulated sediment concentrations were calibrated using measured suspended-solids concentrations in samples collected at one point in the

stream. However, these point samples may not

accurately represent average suspended-sediment

concentrations for the entire cross section in stream

reaches that are not well mixed. Simulation of

water quality may be less accurate for small-basin

Table 29. Sensitivity of model output for total nutrient yields at streamflow-measurement station 01480015 Red Clay

Creek near Stanton, Del., to changes in selected model parameters affecting nutrient contributions from pervious

land areas

[Model parameters: POTFW, potency factor of sediment in washoff; IFLW-CONC, concentration in interflow;

GRND-CONC, concentration in ground water]

Parameter Multiplier

Nitrate as N Ammonia as N Phosphate as P

Pounds

per acre

Percent

difference1

Pounds

per acre

 Percent

difference

Pounds

per acre

Percent

difference

Preliminary calibration value2 1 47.01 0 1.89 0 18.04 0

POTFW 0.5 44.26 -5.9 1.11 -40.9 9.21 -49.0

POTFW 2 52.48 11.6 3.43 81.7 35.70 97.9

IFLW-CONC 0.5 43.52 -7.4 1.85 -1.7 18.00 -.2

IFLW-CONC 2 53.63 14.1 1.95 3.4 18.11 .4

GRND-CONC 0.5 29.54 -37.2 1.74 -7.5 17.89 -.8

GRND-CONC 2 81.96 74.3 2.17 14.9 18.34 1.7

1 Percent difference from calibrated value = 100 x (changed result - calibrated result)/calibrated result.

2 All parameters.
Model Applications 77

areas than for large-basin areas because of model

spatial resolution. The hydrologic component of

the model was calibrated at sites on the main

branches and main stem of the Red Clay Creek

rather than at small-basin sites.

The simulation of the nutrients, nitrogen and

phosphorus, included the biological processes of

algal plankton and benthic algal nutrient uptake

and release but not the effect of zooplankton. Thus,

the magnitude of diurnal fluctuations in concentrations of dissolved oxygen due to processes of instream photosynthesis and respiration may not be

fully characterized by the simulation. The simulation of instream nutrient concentrations is affected

further by the quality and quantity of information

about nutrients in discharge from point sources.

For example, although the model is run on an

hourly time step, data on point-source discharges

generally are available as monthly mean values for

ammonia and contributions of phosphorus. Nitrate

discharges are extrapolated from reported monthly

ammonia concentrations in discharges. The model,

as configured, is better used to estimate loads of

nonpoint-source nutrients from land areas than to

predict concentrations after considerable instream

transport and residence time at downstream sites.

The simulation of particulate orthophosphorus was calibrated to an estimated value, calculated as observed total-phosphorus concentration

minus observed dissolved-phosphorus concentration. This difference, however, may include forms

of phosphorus other than orthophosphorus.

Because the model, as configured, only simulates

orthophosphorus, particulate phosphorus that

includes other forms of phosphorus may be undersimulated.

MODEL APPLICATIONS

The HSPF model for the Red Clay Creek

Basin was developed to assist in the assessment of

suspended sediment and nutrient loads from nonpoint sources to streams. The model-simulated

load estimates may be used as part of an ongoing

TMDL assessment for the Christina River Basin to

indicate the possible location and magnitude of

load reductions that might be needed to maintain

or improve water quality where impaired. These

load estimates are based on the land-use conditions during the period of calibration and do not

reflect the effects of best- management practices

put in place after 1998 (Daniel Greig, Chester

County Conservation District, oral commun.,

2002).

The model can be used to estimate loads

from individual basins for the purposes of evaluating relative and absolute contributions of suspended sediment, nitrogen, and phosphorus. This

information may be helpful in assessing areas that

appear to generate elevated nonpoint-source loads

of these constituents. For example, simulated total

loads and loads per acre in 1995 for selected headwater areas are listed in table 30. Precipitation in

1995 was similar to the long-term average, and

yields in that year might be assumed to be similar

to average. Results of model simulation indicate

that for this time period, nitrate loads per acre are

lower in the Burroughs Run subbasin than in the

upper East and West Branches of Red Clay Creek.

Land use in the Burroughs Run subbasin is relatively more residential and less agricultural than in

the other two subbasins (table 9).

The HSPF model for the Red Clay Creek

Basin can be used to compare simulated loads in

the Red Clay Creek and adjacent basins, where

monitoring data are limited, to loads calculated

Table 30. Simulated total loads and loads per acre in 1995 for selected headwater model-reach drainage areas in the

Hydrological Simulation Program–Fortran (HSPF) model of the Red Clay Creek Basin, Pennsylvania and Delaware

(See figure 11 for location of model reaches.)

[lb, pounds; lb/acre, pounds per acre; tons/acre, tons per acre]

Model

reach

number

Model-reach

stream name

Drainage

area

(acres)

Relative loads (mass per acre) Total loads (mass)

Nitrate

(lb/acre)

Ammonia

(lb/acre)

Phosphate

(lb/acre)

Sediment

(tons/acre)

Nitrate

(lb)

Ammonia

(lb)

Phosphate

(lb)

Sediment

(tons)

1 Upper W. Br. Red Clay Creek 6,451 9.14 0.55 5.55 1.07 58,940 3,538 35,800 6,920

3 Upper E. Br. Red Clay Creek 6,336 8.14 .71 6.58 .90 53,270 4,471 41,710 5,697

6 Burroughs Run1 4,554 5.78 .17 2.51 .64 26,280 755 11,390 2,902

1 Loads for Burroughs Run include contributions from a small point-source discharge.
78 Model Applications

from extensive observed data in nearby basins to

the west that drain to the Chesapeake Bay. Evaluation of monitoring data from these nearby basins

indicates a positive correlation between the percentage of land in agricultural use and calculated

yields of nitrate, ammonia, phosphorus, and suspended sediment (Langland and others, 1995).

Similar relations are indicated by results of the

HSPF model for the Brandywine Creek, White

Clay Creek, and Red Clay Creek (Senior and

Koerkle, 2003a, 2003b). Comparison of simulated

and calculated yields indicates that the simulation

provides reasonable results (figs. 38 and 39).

The HSPF model for the Red Clay Creek

Basin also can be used to compare simulated loads

from nonpoint sources based in land areas to

reported loads from point-source discharges to

streams in the basin. For example, total nitrate,

ammonia, and orthophosphorus loads as estimated by the HSPF model for the drainage area

above Red Clay Creek near Stanton, Del., are listed

with estimated and reported loads from pointsource discharges to the Brandywine in table 31.

Simulated loads for ammonia from nonpoint

sources are about equal to the estimated loads for

ammonia from point sources. Simulated nitrate

loads are about 25 times greater than estimated

nitrate loads from point sources, and simulated

phosphorus loads from nonpoint sources are about

20 times greater than estimated phosphorus loads

from point sources.

The simulated loads shown in table 31 are

for the whole basin for the 4-year period (October

1994-October 1998) and include a range of hydrologic conditions. Model-simulated loads from the

whole basin and selected subbasins in the Red

Clay Creek Basin could be estimated under baseflow or stormflow conditions for an actual time

period, such as 1996-97. Additionally, the HSPF

model for the Red Clay Creek Basin may be used

as a predictive tool to estimate loads under statistically identified flow conditions, such as based on

some period of record. For example, the model

could be used to estimate an average daily phosphorus load at high-flow conditions for daily mean

flows that occur between about 5 and 10 percent of

the time based on the simulation period. At

streamflow-measurement station 01480015 Red

Clay Creek near Stanton, model simulation indicates that average daily phosphorus loads from

both nonpoint and point sources is 9.2 lbs at highflow conditions for daily mean flows of 100 -

200 ft3/s that occur between about 5 and 10 percent of the time based on the simulation period of

1994-98. Further, the model simulation indicates

that about 80 percent of the total phosphorus load

for the period 1994-98 at Red Clay Creek near Stanton is carried by daily mean flows of greater than

200 ft3/s and that occur 5 percent or less of the

time.

Successful application of the Red Clay Creek

HSPF model to future scenarios or periods of

record other than the calibration period will be

best supported if the model was calibrated to a

broad range of representative hydrologic conditions. The Red Clay Creek model was calibrated to

a range of streamflows conveying all but the most

extreme high-flow and low-flow events. Comparison of the daily mean streamflow-duration curve

for the simulation period at station 01480000 Red

Clay Creek at Wooddale, Del., to the daily mean

streamflow-duration curve for the 57.5-year period

from April 15, 1943, to September 30, 2001 (fig. 40),

shows generally good agreement. Below about

12 ft3/s, the duration curves are substantially different. Thus, the performance of the model simulations at these low flows is unknown; however, the

transport of suspended nonpoint-source constituents can be expected to be negligible during these

infrequent flows. The highest streamflows generally produce the largest loads of suspended constituents, but they also are infrequent events. Daily

mean streamflows greater than 1,600 ft3/s only

have been exceeded seven times in the 57.5-year

period of record examined and once in the simulation period.

Table 31. Total simulated nonpoint-source and

estimated point-source loads of nitrate, ammonia,

and phosphorus for the 4-year period October 1994

through September 1998, Red Clay Creek Basin

Total load, 1994-981, in tons

1 Period from October 1, 1994, through September

30, 1998.

Nitrate2

2 Estimated from reported ammonia loads.

Ammonia Phosphorus

Nonpoint source3

3 Calculated for drainage area above the station Red

Clay Creek near Stanton, Del.

695 29 4

 266

4 Nonpoint source estimates are total

orthophosphate.

Point source5

5 Includes all discharges above Stanton, Del.

26 31 13
Model Applications 79

0 10 20 30 40 50 60 70 80 90 100

AGRICULTURAL LAND USE, IN PERCENT

0.02

20

0.05

0.1

0.2

0.5

1

2

5

10

PHOSPHORUS YIELD, IN POUNDS PER ACRE

0 10 20 30 40 50 60 70 80 90 100

AGRICULTURAL LAND USE, IN PERCENT

0

6,000

1,000

2,000

3,000

4,000

5,000

SEDIMENT YIELD, IN POUNDS PER ACRE

EXPLANATION

CHESAPEAKE BAY - PIEDMONT SITES: MINIMUM, MAXIMUM,

AND MEAN FOR 1972-92 (LANGLAND AND OTHERS, 1995)

CHESAPEAKE BAY - NON-PIEDMONT SITES: MINIMUM, MAXIMUM,

AND MEAN FOR 1972-92 (LANGLAND AND OTHERS, 1995)

BRANDYWINE CREEK SIMULATION FOR 1995

WHITE CLAY CREEK SIMULATION FOR 1995

RED CLAY CREEK SIMULATION FOR 1995

Figure 38. Sediment and phosphorus yields in relation to percent agricultural land use as

calculated from observed data for subbasins in the Chesapeake Bay Watershed and as

simulated by the Hydrological Simulation Program–Fortran (HSPF) model for selected

subbasins in the Brandywine Creek, White Clay Creek, and Red Clay Creek Basins,

Pennsylvania and Delaware.
80 Model Applications

0 10 20 30 40 50 60 70 80 90 100

AGRICULTURAL LAND USE, IN PERCENT

0

40

10

20

30

NITRATE YIELD, IN POUNDS PER ACRE AS NITROGEN

0 10 20 30 40 50 60 70 80 90 100

AGRICULTURAL LAND USE, IN PERCENT

0.01

100

0.02

0.05

0.1

0.2

0.5

1

2

5

10

20

50

AMMONIA YIELD, IN POUNDS PER ACRE AS NITROGEN

EXPLANATION

CHESAPEAKE BAY - PIEDMONT SITES: MINIMUM, MAXIMUM,

AND MEAN FOR 1972-92 (LANGLAND AND OTHERS, 1995)

CHESAPEAKE BAY - NON-PIEDMONT SITES: MINIMUM, MAXIMUM,

AND MEAN FOR 1972-92 (LANGLAND AND OTHERS, 1995)

BRANDYWINE CREEK SIMULATION FOR 1995

WHITE CLAY CREEK SIMULATION FOR 1995

RED CLAY CREEK SIMULATION FOR 1995

Figure 39. Yields of nitrate and ammonia in relation to percent agricultural land use as

calculated from observed data for subbasins in the Chesapeake Bay Watershed and as

simulated by the Hydrological Simulation Program–Fortran (HSPF) model for selected

subbasins in the Brandywine Creek, White Clay Creek, and Red Clay Creek Basins,

Pennsylvania and Delaware.
Summary 81

SUMMARY

The Christina River Basin drains 565 mi2 in

Pennsylvania and Delaware and is used for recreation, drinking-water supply, and support of

aquatic life. The Christina River Basin includes the

major subbasins of Brandywine Creek, Red Clay

Creek, White Clay Creek, and the Christina River.

The Red Clay Creek is the smallest of the four main

subbasins and drains an area of 54 mi2. Monitoring

data indicate that water quality in some parts of

the Christina River Basin is impaired and does not

support the States’ designated uses of the stream.

A water-quality management strategy developed

by a group of local, county, State, and Federal

agencies to address water-quality problems

included a modeling component to evaluate the

effects of point and nonpoint-source contributions

of nutrients and suspended sediment on stream

water quality. The model selected for the nonpointsource evaluation was HSPF. The HSPF model for

the Christina River Basin was constructed and calibrated by the USGS, in cooperation with the

DRBC, DNREC, and PADEP, and consists of four

independent models, one for each of the four main

subbasins.

The USGS also developed and executed a

monitoring plan to collect water-quality data in

each of the four main subbasins and in small areas

predominantly covered by one land-use category

for model calibration. Under this monitoring plan,

stormflow and base-flow samples were collected

during 1998 at 1 site in the Red Clay Creek subbasin and 10 sites elsewhere in the Christina River

Basin. Seven of the 11 total monitored stream sites

in the Christina River Basin drained areas, ranging

in size from 0.6 to 18.7 mi2, that were covered predominantly by one land use: animal/row crop;

agricultural; row-crop agricultural; forested; sewered residential; unsewered residential; or urban.

The nonpoint-source monitoring site at the streamflow-measurement station, 01480000 Red Clay

Creek at Wooddale, was about 4 mi upstream of

the outlet of the Red Clay subbasin and drained

47 mi2 of mixed land uses. Water samples were

analyzed for dissolved and total nutrients and suspended solids. Because suspended-sediment

analyses were not available, suspended-solids data

were used as a surrogate for suspended-sediment

data. Suspended solids and total phosphorus concentrations were higher in stormflow than in base0.01 0.1 1 2 5 10 20 30 40 50 60 70 80 90 95 98 99 99.9 99.99

PERCENT OF THE TIME STREAMFLOW EQUALED OR EXCEEDED

1

10,000

2

5

10

20

50

100

200

500

1,000

2,000

5,000

DAILY MEAN STREAMFLOW, IN CUBIC FEET PER SECOND

Figure 40. Duration curves of observed daily mean streamflow at 01480000 Red Clay Creek at

Wooddale, Del., for the period April 1, 1943, through September 30, 2001, and for the period of

simulation, October 1, 1994, through October 29, 1998.

PERIOD OF OCTOBER 1994 - OCTOBER 1998

PERIOD OF APRIL 1943 - SEPTEMBER 2001
82 Summary

flow samples, whereas dissolved nitrate concentrations tended to be higher in base-flow than stormflow samples.

The HSPF model for the Red Clay Creek

Basin was used to simulate streamflow, suspended

sediment, and the nutrients of nitrogen and phosphorus. For the model, the basin was subdivided

into nine reaches draining areas that ranged from

1.7 to 10.1 mi2. One of the reaches contains a regulated reservoir. Ten different pervious land uses

and two impervious land uses were selected for

simulation. Land-use areas were determined from

1995 land-use data. The predominant land uses in

the Red Clay Creek Basin are agricultural, forested,

residential, and urban.

The hydrologic component of the HSPF

model was run at an hourly time step and

calibrated using streamflow data at three USGS

streamflow-measurement stations for the period

October 1, 1994, through October 29, 1998. Daily

precipitation data from one NOAA gage near the

Red Clay Creek Basin to the east and hourly precipitation-intensity data from one NOAA gage

near the tip of the basin to the south were used for

model input. The difference between observed and

simulated streamflow volume ranged from -0.8 to

2.1 percent for the 4-year period at the three sites

used for model calibration. Annual differences

between observed and simulated streamflow generally were greater than the overall error. For

example, near the outlet of the basin at streamflowmeasurement station 01480015, Red Clay Creek

near Stanton, Del. (drainage area of 50.2 mi2),

annual differences between observed and simulated streamflow ranged from -5.8 to 6.0 percent

and the overall error for the 4-year period was

-0.8 percent (-0.6 in.). At the three streamflow-measurement stations, calibration errors for total flow

volume, low-flow-recession rate, 50-percent lowest

flows, 10-percent highest flows, storm peaks and

other seasonal measures generally were within recommended criteria for a satisfactory calibration.

Much of the error in simulating storm events on an

hourly time step can be attributed to uncertainty in

the rainfall data.

Model parameters affecting water quality

were taken, with minor adjustments, from calibrated HSPF models for the adjacent White Clay

and Brandywine Creek Basins, where data were

available to calibrate inputs from specific land

uses. The calibration of the water-quality component of the Red Clay Creek model was assessed

using monitoring data collected at three USGS

streamflow-measurement stations with variable

periods of record ending October 1998. All three

stations were downstream of point-source discharges. The date for the start of water-quality

monitoring ranged from October 1994 to January

1998. Suspended-solids data collected during monitoring were used as estimates for suspended sediment. Fewer data were available for water-quality

calibration than for streamflow calibration. On the

basis of limited water-quality data, simulated

loads of suspended sediment, nitrate, dissolved

and particulate ammonia, and dissolved orthophosphate and particulate phosphorus are within

an order of magnitude or less of observed loads for

storms sampled in 1998 at the nonpoint-source

monitoring site, 01480000 Red Clay Creek at

Wooddale, Del., and for grab samples collected by

State agencies at the three streamflow-measurement stations. Errors in ammonia simulation

apparently are greater than errors in nitrate and

orthophosphate simulation. Some error could be

related to variability in point-source discharges

upstream of monitoring sites. The error in waterquality loads typically is larger than and includes

the error in stormflow simulation. Cumulative

errors for five storms in 1998 at the Wooddale

monitoring site, adjusted for the error in streamflow simulation, were -26 percent for suspendedsediment loads, -22 percent for nitrate loads,

58 percent for dissolved ammonia loads, -45 percent for particulate ammonia loads, -10 percent for

dissolved-orthophosphate loads, and -14 percent

for particulate orthophosphate loads. Error in simulation of dissolved constituents commonly was

less than the error in simulation of particulate constituents. In storms, particulate phosphorus loads

generally are greater than dissolved orthophosphate loads, and nitrate loads are about one order

of magnitude greater than dissolved ammonia

loads and two orders of magnitude greater than

particulate ammonia loads.

Simulated yields (loads per acre) for

suspended sediment, nitrate, ammonia, and orthophosphate were greatest from agricultural land

uses compared to other land uses. Simulated yields

of suspended sediment, nitrate, and ammonia for

subbasins in the Red Clay Creek Basin were similar

to yields simulated for adjacent basins and to

yields calculated from monitoring data for subbasins in the nearby Chesapeake Bay Watershed.

Yields (expressed in pounds per acre) of these constituents tend to increase as the percent of agricul-
REFERENCES CITED 83

tural land increases. Simulated loads of nitrate and

orthophosphate from nonpoint sources were

greater than estimated loads of nitrate and phosphorus from point sources. However, simulated

loads of ammonia from nonpoint sources were less

than estimated loads of ammonia from point

sources.

Users of the Red Clay Creek HSPF model

should be aware of model limitations and consider

the following when predictive scenarios are

desired: duration curves indicate that the model

simulates streamflow reasonably well when evaluated over a broad range of conditions and time,

although streamflow and the corresponding water

quality for individual storm events may not be

well simulated; streamflow-duration curves for the

simulation period compare well with duration

curves for the 57.5-year period ending in 2001 at

Red Clay Creek at Wooddale, Del., and include all

but the extreme high-flow and low-flow events;

calibration for water quality was based on sparse

data, with the result of increasing uncertainty in

the water-quality simulation.

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Kunkle, W.M., 1963, Soil survey of Chester and

Delaware Counties, Pennsylvania: U.S.

Department of Agriculture Soil Conservation Service Soil Survey Series 1959, no. 19,

124 p.
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Water-Resources Investigations Report 95-

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1994, Users manual for an expert system

(HSPEXP) for calibration of the Hydrological

Simulation Program–Fortran: U.S. Geological Survey Water-Resources Investigations

Report 94-4168, 102 p.

Martin, G.R., Zarriello, P.J., and Shipp, A.A., 2000,

Hydrologic and water-quality characterization and modeling of the Chenowith Run

Basin, Jefferson County, Kentucky:

U.S. Geological Survey Water-Resources

Investigations Report 00-4239, 197 p.

Matthews, E.D., and Lavoie, O.L., 1970, Soil survey

of New Castle County, Delaware:

U.S. Department of Agricultural Soil

Conservation Service in cooperation with

Delaware Agricultural Experiment Station,

97 p.

Moore, C.R., 1987, Determination of benthicinvertebrate indices and water-quality

trends of selected streams in Chester County,

Pennsylvania, 1969-80: U.S. Geological

Survey Water-Resources Investigations

Report 85-4177, 62 p.

National Oceanic and Atmospheric Administration, 2000a, Monthly station normals of

temperature, precipitation, and heating and

cooling degree days, 1971-2000: Climatography of the United States no. 07, Delaware.

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the United States no. 36, Pennsylvania.

Pettyjohn, W.A., and Henning, Rodger, 1979,

Preliminary estimation of ground-water

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data for selected streams in Chester County,

Pennsylvania, 1981-94: U.S. Geological

Survey Open-File Report 99-216, 607 p.

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Watershed, Pennsylvania and Delaware:

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in the UK: Journal of Hydrology, v. 252,

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relation to hydrogeology, land use, and

surface-water quality in the Red Clay Creek

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111 p.

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for part of the Ninemile Creek watershed

near Camillus, Onandaga County, New

York: U.S. Geological Survey WaterResources Investigation Report 98-4201,

60 p.
Appendix 1 87

APPENDIX 1

RESULTS OF LABORATORY ANALYSES OF STORMFLOW

AND BASE-FLOW SAMPLES
88 Appendix 1

Table 1. Results of laboratory analyses of discrete and composite samples collected during storms in 1998 at one

nonpoint-source monitoring site in the Red Clay Creek basin, Pennsylvania and Delaware

 ELEV. DIS- DIS- SPE- RESIDUE NITRO-

 AGENCY AGENCY OF LAND CHARGE, CHARGE, CIFIC CHLO- TOTAL GEN,

 ANA- COL- SURFACE IN INST. DRAIN- CON- RIDE, AT 105 AMMONIA

 LYZING LECTING DATUM CUBIC CUBIC AGE DUCT- DIS- DEG. C, DIS-

 ENDING ENDING SAMPLE SAMPLE (FT. FEET FEET AREA ANCE SOLVED SUS- SOLVED

 DATE TIME DATE TIME (CODE (CODE ABOVE PER PER (SQ. LAB (MG/L PENDED (MG/L

 NUMBER) NUMBER) NGVD) SECOND SECOND MI.) (US/CM) AS CL) (MG/L) AS N)

 (00028) (00027) (72000) (00060) (00061) (81024) (90095) (00940) (00530) (00608)

01480000 RED CLAY CREEK AT WOODDALE, DE (LAT 39 45 46N LONG 075 38 11W)

 MAR 1998

 08... 1630 19980309 1115 10003 1028 81.46 293 -- 47.00 238 21.0 125 .089

 09... 0215 -- -- 10003 1028 81.46 -- 337 47.00 264 21.7 85 .043

 09... 1015 -- -- 10003 1028 81.46 -- 565 47.00 175 14.2 689 .119

 09... 1215 -- -- 10003 1028 81.46 -- 839 47.00 196 15.2 249 .108

 MAY

 01... 2251 19980503 1010 10003 1028 81.46 63 -- 47.00 305 27.4 1 .028

 JUN

 12... 1233 19980612 1515 10003 1028 81.46 578 -- 47.00 251 22.6 317 .040

 JUL

 08... 0940 -- -- 10003 1028 81.46 -- 49 47.00 261 20.2 59 .020

 08... 0940 19980709 0804 10003 1028 81.46 114 -- 47.00 268 22.0 82 .063

 08... 1240 -- -- 10003 1028 81.46 -- 90 47.00 286 22.9 90 .007

 08... 1410 -- -- 10003 1028 81.46 -- 280 47.00 298 25.3 275 .033

 08... 1540 -- -- 10003 1028 81.46 -- 246 47.00 282 22.7 185 .054

 OCT

 08... 1218 19981009 1009 10003 1028 81.46 71 -- 47.00 328 35.0 29 <.005

 09... 1218 -- -- 10003 1028 81.46 -- 22 47.00 363 33.0 20 .022

 09... 1424 -- -- 10003 1028 81.46 -- 23 47.00 285 29.0 8 .059

 09... 1554 -- -- 10003 1028 81.46 -- 32 47.00 282 29.0 12 .034

 09... 1724 -- -- 10003 1028 81.46 -- 35 47.00 302 32.0 13 .032

 NITRO- NITRO- NITRO- PHOS- OXYGEN

 GEN,AM- GEN,AM- NITRO- GEN, PHOS- PHORUS CARBON, OXYGEN DEMAND,

 MONIA + MONIA + GEN, NO2+NO3 PHORUS ORTHO, PHOS- ORGANIC CARBON, DEMAND, CHEM-

 ORGANIC ORGANIC AMMONIA DIS- DIS- DIS- PHORUS DIS- ORGANIC BIOCHEM ICAL

 DIS. TOTAL TOTAL SOLVED SOLVED SOLVED TOTAL SOLVED TOTAL CARBON. (HIGH

 DATE (MG/L (MG/L (MG/L (MG/L (MG/L (MG/L (MG/L (MG/L (MG/L 20 LEVEL)

 AS N) AS N) AS N) AS N) AS P) AS P) AS P) AS C) AS C) (MG/L) (MG/L)

 (00623) (00625) (00610) (00631) (00666) (00671) (00665) (00681) (00680) (80087) (00340)

01480000 RED CLAY CREEK AT WOODDALE, DE (LAT 39 45 46N LONG 075 38 11W)

 MAR 1998

 08... .85 2.2 .09 2.22 .097 .068 .389 7.0 7.0 5.2 23

 09... .74 1.8 .04 3.14 .185 .060 .299 7.0 5.0 6.2 7

 09... 1.1 2.2 .16 1.35 .098 .073 1.34 8.0 8.0 10 61

 09... 1.2 2.8 .13 1.68 .224 .186 .602 10 7.0 6.1 49

 MAY

 01... .82 .77 .05 3.38 .161 .149 .217 4.0 7.0 3.6 <1

 JUN

 12... .65 2.0 .05 2.75 .116 .122 .694 10 10 8.1 <1

 JUL

 08... .33 1.1 .03 2.27 .071 .105 .260 6.0 5.0 6.1 37

 08... .52 1.5 .07 2.36 .128 .157 .376 8.0 6.0 7.4 26

 08... .17 1.2 .03 2.69 .087 .117 .344 5.0 3.0 3.4 32

 08... .87 2.9 .04 2.75 .132 .147 .793 5.0 4.0 4.9 41

 08... .75 2.2 .05 2.73 .134 .154 .581 5.0 4.0 4.9 38

 OCT

 08... -- -- .05 3.22 -- .360 -- 6.0 8.0 6.3 <1

 09... -- -- .04 2.96 -- .221 -- 7.0 6.0 4.5 <1

 09... -- -- .05 2.69 -- .208 -- 5.0 5.0 3.0 <1

 09... -- -- .06 2.78 -- .192 -- 6.0 6.0 <3.0 <1

 09... -- -- .06 2.55 -- .205 -- 6.0 6.0 <3.0 10

Remark codes used in this report:

 < -- Less than
Appendix 1 89

Table 2. Results of laboratory analyses of grab samples collected during base-flow conditions in 1998 at one

nonpoint-source monitoring site in the Red Clay Creek basin, Pennsylvania and Delaware

 ELEV. DIS- PH ANC RESIDUE

 AGENCY AGENCY OF LAND CHARGE, WATER SPE- WATER CHLO- TOTAL

 ANA- COL- SURFACE INST. DRAIN- WHOLE CIFIC UNFLTRD RIDE, AT 105

 LYZING LECTING DATUM CUBIC AGE OXYGEN, FIELD CON- TEMPER- FET DIS- DEG. C,

 SAMPLE SAMPLE (FT. FEET AREA DIS- (STAND- DUCT- ATURE FIELD SOLVED SUS-

 DATE TIME (CODE (CODE ABOVE PER (SQ. SOLVED ARD ANCE WATER MG/L AS (MG/L PENDED

 NUMBER) NUMBER) NGVD) SECOND MI.) (MG/L) UNITS) (US/CM) (DEG C) CACO3 AS CL) (MG/L)

 (00028) (00027) (72000) (00061) (81024) (00300) (00400) (00095) (00010) (00410) (00940) (00530)

01480000 RED CLAY CREEK AT WOODDALE, DE (LAT 39 45 46N LONG 075 38 11W)

 JAN 1998

 12... 0956 10003 1028 81.46 26 47.00 13.2 7.2 349 .5 71 37.0 4

 APR

 27... 1115 10003 1028 81.46 53 47.00 12.2 7.3 300 1.3 54 26.8 10

 JUL

 23... 1226 10003 1028 81.46 24 47.00 9.5 7.9 328 24.4 73 34.0 5

 SEP

 15... 1011 10003 1028 81.46 13 47.00 7.9 7.5 380 22.7 87 43.0 3

 NITRO- NITRO- NITRO- NITRO- PHOS- OXYGEN PHEO-

 GEN, GEN,AM- GEN,AM- NITRO- GEN, PHOS- PHORUS CARBON, OXYGEN DEMAND, PHYTIN

 AMMONIA MONIA + MONIA + GEN, NO2+NO3 PHORUS ORTHO, PHOS- ORGANIC CARBON, DEMAND, CHEM- PHYTO-

 DIS- ORGANIC ORGANIC AMMONIA DIS- DIS- DIS- PHORUS DIS- ORGANIC BIOCHEM ICAL PLANK-

 SOLVED DIS. TOTAL TOTAL SOLVED SOLVED SOLVED TOTAL SOLVED TOTAL CARBON. (HIGH TON,

 DATE (MG/L (MG/L (MG/L (MG/L (MG/L (MG/L (MG/L (MG/L (MG/L (MG/L 20 LEVEL) ACID M.

 AS N) AS N) AS N) AS N) AS N) AS P) AS P) AS P) AS C) AS C) (MG/L) (MG/L) (UG/L)

 (00608) (00623) (00625) (00610) (00631) (00666) (00671) (00665) (00681) (00680) (80087) (00340) (32218)

01480000 RED CLAY CREEK AT WOODDALE, DE (LAT 39 45 46N LONG 075 38 11W)

 JAN 1998

 12... -- -- .72 .06 3.31 -- .195 .255 9.0 6.0 4.1 -- 7.00

 APR

 27... .028 .71 1.2 .03 3.16 .135 .124 .154 4.0 4.0 <2.4 22 6.00

 JUL

 23... .020 .86 1.2 .03 2.64 .213 .230 .237 4.0 4.0 <2.4 2 2.00

 SEP

 15... <.005 .36 .65 <.01 3.18 .020 .281 .288 4.0 5.0 <2.4 6 4.00

 CHLORO-

 HPYLL A

 PHYTO-

 PLANK-

 TON

 DATE ACID M.

 (UG/L)

 (32211)

01480000 RED CLAY CREEK AT WOODDALE, DE (LAT 39 45 46N LONG 075 38 11W)

 JAN 1998

 12... 3.00

 APR

 27... 11.0

 JUL

 23... 5.00

 SEP

 15... <1.00

Remark codes used in this report:

 < -- Less than
Appendix 2 91

APPENDIX 2

USER CONTROL INPUT FILE

FOR RED CLAY CREEK HSPF MODEL
92 Appendix 2

RUN

GLOBAL

RED CLAY CREEK HYDROLOGY - BASE SCENARIO - ALL SEGMENTS

 START 1994 10 1 0 0 END 1998 10 29 24 0

 RUN INTERP OUTPUT LEVEL 3 2

 RESUME 0 RUN 1 UNIT SYSTEM 1

END GLOBAL

FILES

<type> <fun>***<------------fname--------------------------------------------->

WDM 26 redclay.wdm

MESSU 25 redclay.ech

 90 REDCLAY.out

END FILES

OPN SEQUENCE

 INGRP INDELT 1:00

 PERLND 702

 PERLND 703

 PERLND 704

 PERLND 705

 PERLND 706

 PERLND 707

 PERLND 708

 PERLND 709

 PERLND 710

 PERLND 711

 IMPLND 701

 IMPLND 702

 RCHRES 1

 RCHRES 3

 RCHRES 2

 GENER 1

 GENER 2

COPY 10

 COPY 200

 PERLND 402

 PERLND 403

 PERLND 404

 PERLND 405

 PERLND 406

 PERLND 407

 PERLND 408

 PERLND 409

 PERLND 410

 PERLND 411

 IMPLND 401

 IMPLND 402

 RCHRES 4

 GENER 3

 GENER 4

COPY 11

 RCHRES 6

 GENER 7

 GENER 8

COPY 13

 RCHRES *** 7

 RCHRES 5

 GENER 5

 GENER 6

COPY 12

 COPY 300

 PERLND 602

 PERLND 603

 PERLND 604

 PERLND 605

 PERLND 606

 PERLND 607

 PERLND 608

 PERLND 609

 PERLND 610

 PERLND 611

 IMPLND 601

 IMPLND 602

 RCHRES 8

 GENER 9

 GENER 10

COPY 14

 COPY 400

 END INGRP

END OPN SEQUENCE

PERLND

 ACTIVITY

 # # ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC ***

 402 711 1 1 1 1 1 1 1 0 0 0 0 0

 END ACTIVITY

 PRINT-INFO

 # # ATMP SNOW PWAT SED PST PWG PQAL MSTL PEST NITR PHOS TRAC *********
Appendix 2 93

 402 711 6 5 5 5 6 6 5 0 0 0 0 0 0 12

 END PRINT-INFO

 GEN-INFO

 # # NAME NBLKS UCI IN OUT ENGL METR ***

 702 RESIDENTIAL-SEPTIC 1 1 1 1 90 0

 703 RESIDENTIAL-SEWER 1 1 1 1 90 0

 704 COMMERCIAL/INDUSTRY 1 1 1 1 90 0

 705 AGRICULTURAL-COWS 1 1 1 1 90 0

 706 AGRICULTURAL-CROPS 1 1 1 1 90 0

 707 AGRICULTURAL-MUSHROOM 1 1 1 1 90 0

 708 FOREST 1 1 1 1 90 0

 709 OPEN LAND 1 1 1 1 90 0

 710 WETLANDS, WATER 1 1 1 1 90 0

 711 undesignated use 1 1 1 1 90 0

 402 RESIDENTIAL-SEPTIC 1 1 1 1 90 0

 403 RESIDENTIAL-SEWER 1 1 1 1 90 0

 404 COMMERCIAL/INDUSTRY 1 1 1 1 90 0

 405 AGRICULTURAL-COWS 1 1 1 1 90 0

 406 AGRICULTURAL-CROPS 1 1 1 1 90 0

 407 AGRICULTURAL-MUSHROOM 1 1 1 1 90 0

 408 FOREST 1 1 1 1 90 0

 409 OPEN LAND 1 1 1 1 90 0

 410 WETLANDS, WATER 1 1 1 1 90 0

 411 undesignated use 1 1 1 1 90 0

 602 RESIDENTIAL-SEPTIC 1 1 1 1 90 0

 603 RESIDENTIAL-SEWER 1 1 1 1 90 0

 604 COMMERCIAL/INDUSTRY 1 1 1 1 90 0

 605 AGRICULTURAL-COWS 1 1 1 1 90 0

 606 AGRICULTURAL-CROPS 1 1 1 1 90 0

 607 AGRICULTURAL-MUSHROOM 1 1 1 1 90 0

 608 FOREST 1 1 1 1 90 0

 609 OPEN LAND 1 1 1 1 90 0

 610 WETLANDS, WATER 1 1 1 1 90 0

 611 undesignated use 1 1 1 1 90 0

 END GEN-INFO

  AIR TEMPERATURE ** **

 ATEMP-DAT

 ELDAT AIRTMP ***

 # # (ft) (deg F) ***

 702 711 -290.0 48.3

 402 411 -390.0 48.3

 602 611 50.0 53.6

 END ATEMP-DAT

  SNOW ** **

 ICE-FLAG

*** <PLS > ICEFG

*** # #

 402 711 1

 END ICE-FLAG

 SNOW-PARM1

*** <PLS > LAT MELEV SHADE SNOWCF COVIND

*** # # (deg) (ft) (in)

 702 711 39.9 350. 0.20 1.0 0.60

 402 411 39.8 250. 0.40 1.0 0.60

 602 611 39.7 125. 0.40 1.0 0.60

 END SNOW-PARM1

 SNOW-PARM2

*** <PLS > RDSCN TSNOW SNOEVP CCFACT MWATER MGMELT

*** # # (degF) (in/day)

 702 711 0.15 30.0 0.08 0.60 0.03 0.010

 402 411 0.15 30.0 0.08 0.60 0.03 0.020

 602 611 0.15 30.0 0.08 0.60 0.03 0.030

 END SNOW-PARM2

  HYDROLOGY ** **

 PWAT-PARM1

*** <PLS > Flags

*** x - x CSNO RTOP UZFG VCS VUZ VNN VIFW VIRC VLE IFFC

 702 1 0 0 1 0 0 0 1 1 1

 703 1 0 0 1 0 0 0 1 1 1

 704 1 0 0 1 0 0 0 1 1 1

 705 1 0 0 1 0 0 0 1 1 1

 706 1 0 0 1 0 0 0 1 1 1

 707 1 0 0 1 0 0 0 1 1 1

 708 1 0 0 1 0 0 0 1 1 1

 709 1 0 0 1 0 0 0 1 1 1

 710 1 0 0 0 0 0 0 1 0 1

 711 1 0 0 1 0 0 0 1 1 1

 402 1 0 0 1 0 0 0 0 1 1

 403 1 0 0 1 0 0 0 0 1 1

 404 1 0 0 1 0 0 0 0 1 1

 405 1 0 0 1 0 0 0 0 1 1

 406 1 0 0 1 0 0 0 0 1 1

 407 1 0 0 1 0 0 0 0 1 1

 408 1 0 0 1 0 0 0 0 1 1
94 Appendix 2

 409 1 0 0 1 0 0 0 0 1 1

 410 1 0 0 0 0 0 0 0 0 1

 411 1 0 0 1 0 0 0 0 1 1

 602 1 0 0 1 0 0 0 0 1 1

 603 1 0 0 1 0 0 0 0 1 1

 604 1 0 0 1 0 0 0 0 1 1

 605 1 0 0 1 0 0 0 0 1 1

 606 1 0 0 1 0 0 0 0 1 1

 607 1 0 0 1 0 0 0 0 1 1

 608 1 0 0 1 0 0 0 0 1 1

 609 1 0 0 1 0 0 0 0 1 1

 610 1 0 0 0 0 0 0 0 0 1

 611 1 0 0 1 0 0 0 0 1 1

 END PWAT-PARM1

 PWAT-PARM2

*** <PLS> FOREST LZSN INFILT LSUR SLSUR KVARY AGWRC

*** x - x (in) (in/hr) (ft) (1/in) (1/day)

 702 0.0 8.500 0.100 275.0 0.1962 0.000 0.990

 703 0.0 8.500 0.100 275.0 0.1908 0.000 0.990

 704 0.0 8.500 0.100 275.0 0.1944 0.000 0.990

 705 0.0 8.500 0.110 275.0 0.1727 0.000 0.990

 706 0.0 8.500 0.110 275.0 0.1727 0.000 0.990

 707 0.0 8.500 0.070 275.0 0.1727 0.000 0.990

 708 0.0 8.500 0.150 275.0 0.1980 0.000 0.990

 709 0.0 8.500 0.120 275.0 0.1962 0.000 0.990

 710 0.0 8.500 0.100 275.0 0.1835 0.000 0.990

 711 0.0 8.500 0.120 275.0 0.1763 0.000 0.990

 402 0.0 8.500 0.100 600.0 0.2717 0.000 0.985

 403 0.0 8.500 0.100 600.0 0.1370 0.000 0.985

 404 0.0 8.500 0.100 600.0 0.1530 0.000 0.985

 405 0.0 8.500 0.110 600.0 0.2642 0.000 0.985

 406 0.0 8.500 0.110 600.0 0.2642 0.000 0.985

 407 0.0 8.500 0.070 600.0 0.2642 0.000 0.985

 408 0.0 8.500 0.150 600.0 0.3620 0.000 0.985

 409 0.0 8.500 0.120 600.0 0.2272 0.000 0.985

 410 0.0 8.500 0.100 600.0 0.1799 0.000 0.985

 411 0.0 8.500 0.120 600.0 0.1281 0.000 0.985

 602 0.0 7.500 0.130 250.0 0.1962 2.000 0.985

 603 0.0 7.500 0.130 250.0 0.1908 2.000 0.985

 604 0.0 7.500 0.130 250.0 0.1944 2.000 0.985

 605 0.0 7.500 0.140 250.0 0.1727 2.000 0.985

 606 0.0 7.500 0.140 250.0 0.1727 2.000 0.985

 607 0.0 7.500 0.100 250.0 0.1727 2.000 0.985

 608 0.0 7.500 0.170 250.0 0.1980 2.000 0.985

 609 0.0 7.500 0.140 250.0 0.1962 2.000 0.985

 610 0.0 7.500 0.100 250.0 0.1835 2.000 0.985

 611 0.0 7.500 0.140 250.0 0.1763 2.000 0.985

 END PWAT-PARM2

 PWAT-PARM3

*** <PLS> PETMAX PETMIN INFEXP INFILD DEEPFR BASETP AGWETP

*** x - x (deg F) (deg F)

 702 709 40.0 36.0 2.0 2.0 0.010 0.055 0.000

 710 40.0 36.0 2.0 2.0 0.010 0.055 0.400

 711 40.0 36.0 2.0 2.0 0.010 0.055 0.000

 402 409 40.0 36.0 2.0 2.0 0.010 0.050 0.000

 410 40.0 36.0 2.0 2.0 0.010 0.050 0.400

 411 40.0 36.0 2.0 2.0 0.010 0.050 0.000

 602 609 40.0 36.0 2.0 2.0 0.000 0.000 0.000

 610 40.0 36.0 2.0 2.0 0.000 0.000 0.400

 611 40.0 36.0 2.0 2.0 0.000 0.000 0.000

 END PWAT-PARM3

 PWAT-PARM4

*** <PLS > CEPSC UZSN NSUR INTFW IRC LZETP

*** x - x (in) (in) (1/day)

 702 0.050 0.700 0.35 0.70 0.400 0.600

 703 0.050 0.700 0.30 0.70 0.400 0.600

 704 0.050 0.600 0.25 0.70 0.400 0.600

 705 0.050 0.400 0.20 0.70 0.400 0.700

 706 0.050 0.400 0.30 0.70 0.400 0.700

 707 0.050 0.700 0.30 0.70 0.400 0.700

 708 0.100 1.000 0.35 0.70 0.400 0.800

 709 0.050 0.600 0.30 0.70 0.400 0.600

 710 0.050 1.000 0.05 0.70 0.400 0.900

 711 0.050 0.600 0.30 0.70 0.400 0.600

 402 0.050 0.600 0.35 0.70 0.500 0.600

 403 0.050 0.600 0.35 0.70 0.500 0.600

 404 0.050 0.500 0.25 0.70 0.500 0.600

 405 0.050 0.400 0.20 0.70 0.500 0.700

 406 0.050 0.400 0.30 0.70 0.500 0.700

 407 0.050 0.600 0.30 0.70 0.500 0.700

 408 0.100 0.900 0.35 0.70 0.500 0.800

 409 0.050 0.600 0.30 0.70 0.500 0.600

 410 0.050 1.000 0.05 0.70 0.500 0.900

 411 0.050 0.600 0.30 0.70 0.500 0.600

 602 0.050 0.700 0.35 0.75 0.300 0.600

 603 0.050 0.700 0.30 0.75 0.300 0.600

 604 0.050 0.600 0.25 0.75 0.300 0.600

 605 0.050 0.400 0.20 0.75 0.300 0.700

 606 0.050 0.400 0.30 0.75 0.300 0.700
Appendix 2 95

 607 0.050 0.700 0.30 0.75 0.300 0.700

 608 0.100 1.000 0.35 0.75 0.300 0.800

 609 0.050 0.600 0.30 0.75 0.300 0.600

 610 0.050 1.000 0.05 0.75 0.300 0.900

 611 0.050 0.600 0.30 0.75 0.300 0.600

 END PWAT-PARM4

 MON-INTERCEP

*** <PLS > Interception storage capacity at start of each month (in)

*** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 702 704 .040 .040 .060 .080 .100 .100 .100 .100 .080 .060 .040 .040

 705 707 .030 .030 .030 .030 .060 .090 .110 .110 .110 .080 .070 .030

 708 .040 .040 .070 .110 .140 .160 .160 .150 .120 .090 .050 .040

 709 711 .040 .040 .060 .080 .100 .100 .100 .100 .080 .060 .040 .040

 402 404 .040 .040 .060 .080 .100 .100 .100 .100 .080 .060 .040 .040

 405 407 .030 .030 .030 .030 .060 .090 .110 .110 .110 .080 .070 .030

 408 .040 .040 .070 .110 .140 .160 .160 .150 .120 .090 .050 .050

 409 411 .040 .040 .060 .080 .100 .100 .100 .100 .080 .060 .040 .040

 602 604 .040 .040 .060 .080 .100 .100 .100 .100 .080 .060 .040 .040

 605 607 .030 .030 .030 .030 .060 .090 .110 .110 .110 .080 .070 .030

 608 .040 .040 .070 .110 .140 .160 .160 .150 .120 .090 .050 .040

 609 611 .040 .040 .060 .080 .100 .100 .100 .100 .080 .060 .060 .060

 END MON-INTERCEP

 MON-UZSN

*** <PLS > Upper zone storage at start of each month (inches)

*** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 705 706 .350 .350 .400 .430 .450 .450 .400 .400 .400 .400 .350 .350

 405 406 .350 .350 .400 .430 .450 .450 .400 .400 .400 .400 .350 .350

 605 606 .350 .350 .400 .430 .450 .450 .400 .400 .400 .400 .350 .350

 END MON-UZSN

 MON-IRC

***

*** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 402 711 0.3 0.3 0.3 0.3 0.4 0.5 0.7 0.7 0.5 0.5 0.4 0.3

 END MON-IRC

 MON-LZETPARM

*** <PLS > Lower zone evapotransp parm at start of each month

 702 707 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.0 0.3 0.7 0.7

 708 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.0 0.4 0.8 0.8

 709 711 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.0 0.3 0.7 0.7

 402 407 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.0 0.2 0.7 0.7

 408 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.0 0.3 0.8 0.8

 409 411 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.0 0.2 0.7 0.7

 602 607 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.0 0.2 0.7 0.7

 608 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.0 0.3 0.8 0.8

 609 611 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.0 0.2 0.7 0.7

*** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 END MON-LZETPARM

 PWAT-STATE1

*** <PLS> PWATER state variables (in)

*** x - x CEPS SURS UZS IFWS LZS AGWS GWVS

 702 0.0 0.00 .70 0.0 7.5 1.8 0.0

 703 0.0 0.00 .70 0.0 7.5 1.8 0.0

 704 0.0 0.00 .60 0.0 7.5 1.8 0.0

 705 0.0 0.00 .40 0.0 7.5 1.8 0.0

 706 0.0 0.00 .40 0.0 7.5 1.8 0.0

 707 0.0 0.00 .70 0.0 7.5 1.8 0.0

 708 0.0 0.00 1.00 0.0 7.5 1.8 0.0

 709 0.0 0.00 .60 0.0 7.5 1.8 0.0

 710 0.0 0 .90 0.0 7.5 1.8 0.0

 711 0.0 0.00 .60 0.0 7.0 1.8 0.0

 402 0.0 0.00 .80 0.0 7.0 1.8 0.0

 403 0.0 0.00 .80 0.0 7.0 1.8 0.0

 404 0.0 0.00 .70 0.0 7.0 1.8 0.0

 405 0.0 0.00 .40 0.0 7.0 1.8 0.0

 406 0.0 0.00 .40 0.0 7.0 1.8 0.0

 407 0.0 0.00 .70 0.0 7.0 1.8 0.0

 408 0.0 0.00 1.20 0.0 7.0 1.8 0.0

 409 0.0 0.00 .70 0.0 7.0 1.8 0.0

 410 0.0 0 .90 0.0 7.0 1.8 0.0

 411 0.0 0.00 .70 0.0 7.0 1.8 0.0

 602 0.0 0.00 .50 0.0 7.0 1.5 0.0

 603 0.0 0.00 .50 0.0 7.0 1.5 0.0

 604 0.0 0.00 .50 0.0 7.0 1.5 0.0

 605 0.0 0.00 .40 0.0 7.0 1.5 0.0

 606 0.0 0.00 .40 0.0 7.0 1.5 0.0

 607 0.0 0.00 .50 0.0 7.0 1.5 0.0

 608 0.0 0.00 .70 0.0 7.0 1.5 0.0

 609 0.0 0.00 .50 0.0 7.0 1.5 0.0

 610 0.0 0 .90 0.0 7.0 1.5 0.0

 611 0.0 0.00 .50 0.0 7.0 1.5 0.0

 END PWAT-STATE1

 SED-PARM1

*** <PLS > Sediment parameters 1

*** x - x CRV VSIV SDOP

 402 711 1 0 1
96 Appendix 2

 END SED-PARM1

 SED-PARM2

*** <PLS > SMPF KRER JRER AFFIX COVER NVSI

*** x - x (/day) lb/ac-day

 702 703 1.000 0.500 2.000 0.010 0.000 1.000

 704 1.000 0.500 2.000 0.010 0.000 1.000

 705 706 1.000 0.500 2.000 0.010 0.000 1.000

 707 1.000 0.500 2.000 0.010 0.000 1.000

 708 1.000 0.450 2.000 0.002 0.000 2.000

 709 1.000 0.500 2.000 0.010 0.000 2.000

 710 1.000 0.400 2.000 0.002 0.000 2.000

 711 1.000 0.500 2.000 0.010 0.000 2.000

 402 403 1.000 0.500 2.000 0.010 0.000 1.000

 404 1.000 0.500 2.000 0.010 0.000 1.000

 405 406 1.000 0.520 2.000 0.010 0.000 1.000

 407 1.000 0.520 2.000 0.010 0.000 1.000

 408 1.000 0.450 2.000 0.002 0.000 2.000

 409 1.000 0.500 2.000 0.010 0.000 2.000

 410 1.000 0.400 2.000 0.002 0.000 2.000

 411 1.000 0.500 2.000 0.010 0.000 2.000

 602 603 1.000 0.500 2.000 0.010 0.000 1.000

 604 1.000 0.500 2.000 0.010 0.000 1.000

 605 606 1.000 0.520 2.000 0.010 0.000 1.000

 607 1.000 0.520 2.000 0.010 0.000 1.000

 608 1.000 0.450 2.000 0.002 0.000 2.000

 609 1.000 0.500 2.000 0.010 0.000 2.000

 610 1.000 0.400 2.000 0.002 0.000 2.000

 611 1.000 0.450 2.000 0.010 0.000 2.000

 END SED-PARM2

 SED-PARM3

*** <PLS > Sediment parameter 3

*** x - x KSER JSER KGER JGER

 702 0.250 1.800 0.010 2.000

 703 0.350 1.800 0.020 2.000

 704 0.550 1.800 0.045 2.000

 705 706 2.150 1.800 0.035 2.000

 707 2.350 1.800 0.035 2.000

 708 0.145 1.800 0.000 2.000

 709 0.350 1.800 0.004 2.000

 710 0.008 1.800 0.000 2.000

 711 0.350 1.800 0.004 2.000

 402 0.250 1.800 0.010 2.000

 403 0.350 1.800 0.020 2.000

 404 0.550 1.800 0.045 2.000

 405 406 2.150 1.800 0.035 2.000

 407 2.350 1.800 0.035 2.000

 408 0.145 1.800 0.000 2.000

 409 0.350 1.800 0.004 2.000

 410 0.010 1.800 0.000 2.000

 411 0.350 1.800 0.004 2.000

 602 0.350 1.800 0.015 2.000

 603 0.550 1.800 0.025 2.000

 604 0.800 1.800 0.065 2.000

 605 606 2.600 1.800 0.055 2.000

 607 2.800 1.800 0.055 2.000

 608 0.250 1.800 0.000 2.000

 609 0.500 1.800 0.005 2.000

 610 0.008 1.800 0.000 2.000

 611 0.500 1.800 0.005 2.000

 END SED-PARM3

 MON-COVER

*** <PLS > Monthly values for erosion related cover

*** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 702 704 0.90 0.90 0.90 0.91 0.93 0.93 0.93 0.93 0.93 0.91 0.90 0.90

 705 706 0.50 0.45 0.20 0.10 0.15 0.45 0.65 0.65 0.65 0.60 0.60 0.55

 707 0.50 0.45 0.10 0.10 0.10 0.50 0.50 0.50 0.50 0.50 0.50 0.50

*** 705 707 0.50 0.45 0.00 0.00 0.10 0.50 0.75 0.93 0.93 0.85 0.70 0.55

 708 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97

 709 0.90 0.90 0.90 0.90 0.92 0.93 0.93 0.93 0.93 0.91 0.90 0.90

 710 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97

 711 0.90 0.90 0.90 0.90 0.92 0.93 0.93 0.93 0.93 0.91 0.90 0.90

 402 404 0.90 0.90 0.90 0.91 0.93 0.93 0.93 0.93 0.93 0.91 0.90 0.90

 405 406 0.50 0.45 0.20 0.10 0.15 0.45 0.65 0.65 0.65 0.60 0.60 0.55

 407 0.50 0.45 0.10 0.10 0.10 0.50 0.50 0.50 0.50 0.50 0.50 0.50

*** 405 407 0.50 0.45 0.00 0.00 0.10 0.50 0.75 0.93 0.93 0.85 0.70 0.55

 408 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97

 409 0.90 0.90 0.90 0.90 0.92 0.93 0.93 0.93 0.93 0.91 0.90 0.90

 410 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97

 411 0.90 0.90 0.90 0.90 0.92 0.93 0.93 0.93 0.93 0.91 0.90 0.90

 602 604 0.90 0.90 0.90 0.91 0.93 0.93 0.93 0.93 0.93 0.91 0.90 0.90

 605 606 0.50 0.45 0.20 0.10 0.15 0.45 0.65 0.65 0.65 0.60 0.60 0.55

 607 0.50 0.45 0.10 0.10 0.10 0.50 0.50 0.50 0.50 0.50 0.50 0.50

*** 605 607 0.50 0.45 0.00 0.00 0.10 0.50 0.75 0.93 0.93 0.85 0.70 0.55

 608 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97

 609 0.90 0.90 0.90 0.90 0.92 0.93 0.93 0.93 0.93 0.91 0.90 0.90

 610 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97 0.97

 611 0.90 0.90 0.90 0.90 0.92 0.93 0.93 0.93 0.93 0.91 0.90 0.90

 END MON-COVER
Appendix 2 97

 SED-STOR

*** <PLS > Detached sediment storage (tons/acre)

*** x - x DETS

 402 711 0.4000

 END SED-STOR

 PSTEMP-PARM1

*** <PLS > Flags for section PSTEMP

*** x - x SLTV ULTV LGTV TSOP

 402 711 1 1 0 1

 END PSTEMP-PARM1

 PSTEMP-PARM2

PERLND *** ASLT BSLT ULTP1 ULTP2 LGTP1 LGTP2

 402 711 32.0 0.50 32.0 0.90 54.0 0.0

 END PSTEMP-PARM2

 MON-ASLT

PERLND *** JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 402 711 32.9 35.3 37.9 42.7 46.9 52.6 55.0 54.3 51.4 46.3 40.5 36.6

 END MON-ASLT

 MON-BSLT

PERLND *** JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 402 711 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.23

 END MON-BSLT

 MON-ULTP1

PERLND *** JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 402 711 40.0 41.0 43.0 46.0 48.6 52.8 56.8 57.8 53.5 48.8 45.0 42.0

 END MON-ULTP1

 MON-ULTP2

PERLND *** JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 402 711 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10

 END MON-ULTP2

 PSTEMP-TEMPS

PERLND *** AIRTC SLTMP ULTMP LGTMP

 402 711 50.0 60.0 57.0 53.0

 END PSTEMP-TEMPS

 PWT-PARM2

PERLND *** ELEV IDOXP ICO2P ADOXP ACO2P

 402 711 400. 8.80 0 8.80 0

 END PWT-PARM2

 MON-IFWDOX

PERLND *** JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 402 711 11.0 10.0 10.0 10.0 9.00 7.00 6.00 6.00 7.00 9.00 10.0 11.0

 END MON-IFWDOX

 MON-GRNDDOX

PERLND *** JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 402 711 11.0 10.0 10.0 10.0 9.00 7.00 6.00 6.00 7.00 9.00 10.0 11.0

 END MON-GRNDDOX

 PWT-TEMPS

PERLND *** SOTMP IOTMP AOTMP

 402 711 60. 57. 53.

 END PWT-TEMPS

 PWT-GASES

PERLND *** SODOX SOCO2 IODOX IOCO2 AODOX AOCO2

 402 711 8.8 0 8.8 0 8.8 0

 END PWT-GASES

*** Water Quality Constituents N and P ***

 NQUALS

 # # NQAL ***

 402 711 5

 END NQUALS

 QUAL-PROPS

 # #<--QUALID--> QTID QSD VPFW VPFS QSO VQO QIFW VIQC QAGW VAQC ***

 402 711 NO3 LBS 1 2 0 0 0 1 4 1 4

 END QUAL-PROPS

 QUAL-INPUT

 # # SQO POTFW POTFS ACQOP SQOLIM WSQOP IOQC AOQC ***

 402 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 403 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 404 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 405 0.100 1. 1. 0.0411 0.7500 0.500 1. 1. ***

 406 0.100 1. 1. 0.0411 0.7500 0.500 1. 1. ***

 407 0.100 1. 1. 0.0411 0.7500 0.500 1. 1. ***

 408 0.100 1. 1. 0.0137 0.2500 0.500 1. 1. ***

 409 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 410 0.100 1. 1. 0.0137 0.2500 0.500 1. 1. ***

 411 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 702 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 703 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***
98 Appendix 2

 704 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 705 0.100 1. 1. 0.0411 0.7500 0.500 1. 1. ***

 706 0.100 1. 1. 0.0411 0.7500 0.500 1. 1. ***

 707 0.100 1. 1. 0.0411 0.7500 0.500 1. 1. ***

 708 0.100 1. 1. 0.0137 0.2500 0.500 1. 1. ***

 709 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 710 0.100 1. 1. 0.0137 0.2500 0.500 1. 1. ***

 711 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 602 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 603 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 604 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 605 0.100 1. 1. 0.0411 0.7500 0.500 1. 1. ***

 606 0.100 1. 1. 0.0411 0.7500 0.500 1. 1. ***

 607 0.100 1. 1. 0.0411 0.7500 0.500 1. 1. ***

 608 0.100 1. 1. 0.0137 0.2500 0.500 1. 1. ***

 609 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 610 0.100 1. 1. 0.0137 0.2500 0.500 1. 1. ***

 611 0.100 1. 1. 0.0274 0.5000 0.500 1. 1. ***

 END QUAL-INPUT

 MON-POTFW

 Potency factors for NO3 (lb NO3-N/ton sediment) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5

 702 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5

 602 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5

 403 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4

 703 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4

 603 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4

 404 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 704 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 604 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 405 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 705 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 605 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

*** reduce no3 load for lower intensity ag in 400 series crop (hay)

 406 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4 1.4

*** original estimate for 406 soil no3

 406 *** 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 706 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 606 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 407 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 707 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 607 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 408 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 708 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 608 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 409 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 709 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 609 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 410 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 710 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 610 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 411 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 711 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 611 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 END MON-POTFW

 MON-IFLW-CONC

 Interflow concentration of NO3-N (mg/l) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5

 702 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5

 602 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5

 403 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 703 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 603 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 404 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 704 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 604 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 405 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0

 705 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0

 605 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0

*** reduce no3 load for lower intensity ag in 400 series crop (hay)

 406 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5

***original estimate for 406 inreflow no3

 406 *** 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0

 706 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0

 606 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0

 407 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0

 707 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0

 607 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0

 408 .400 .400 .400 .350 .350 .300 .300 .250 .300 .300 .350 .400

 708 .400 .400 .400 .350 .350 .300 .300 .250 .300 .300 .350 .400

 608 .400 .400 .400 .350 .350 .300 .300 .250 .300 .300 .350 .400

 409 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 709 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 609 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 410 .700 .680 .600 .570 .530 .470 .430 .360 .430 .500 .570 .640

 710 .700 .680 .600 .570 .530 .470 .430 .360 .430 .500 .570 .640

 610 .700 .680 .600 .570 .530 .470 .430 .360 .430 .500 .570 .640

 411 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2
Appendix 2 99

 711 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 611 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 END MON-IFLW-CONC

 MON-GRND-CONC

 Active groundwater concentration of NO3-N (mg/l) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5

 702 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5

 602 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5

 403 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 703 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 603 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 404 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 704 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 604 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

 405 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0

 705 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0

 605 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0 6.0

*** reduce no3 load for lower intensity ag in 400 series crop (hay)

 406 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5

***original estimate for 406 gw no3

 406 *** 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0

 706 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0

 606 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0

 407 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0

 707 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0

 607 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0 8.0

 408 .400 .400 .400 .350 .350 .300 .300 .250 .300 .300 .350 .400

 708 .400 .400 .400 .350 .350 .300 .300 .250 .300 .300 .350 .400

 608 .400 .400 .400 .350 .350 .300 .300 .250 .300 .300 .350 .400

 409 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 709 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 609 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 410 .700 .680 .600 .570 .530 .470 .430 .360 .430 .500 .570 .640

 710 .700 .680 .600 .570 .530 .470 .430 .360 .430 .500 .570 .640

 610 .700 .680 .600 .570 .530 .470 .430 .360 .430 .500 .570 .640

 411 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 711 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 611 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2

 END MON-GRND-CONC

 QUAL-PROPS

 # #<--QUALID--> QTID QSD VPFW VPFS QSO VQO QIFW VIQC QAGW VAQC ***

 402 711 NH4 LBS 1 2 0 0 0 1 4 1 4

 END QUAL-PROPS

 MON-POTFW

 Potency factors for NH4 (lb NH4-N/ton sediment) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 .24 .24 .24 .24 .24 .24 .24 .24 .24 .24 .24 .24

 702 .24 .24 .24 .24 .24 .24 .24 .24 .24 .24 .24 .24

 602 .24 .24 .24 .24 .24 .24 .24 .24 .24 .24 .24 .24

 403 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 703 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 603 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 404 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 704 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 604 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 405 .30 .30 .30 .30 .30 .30 .30 .30 .30 .30 .30 .30

 705 .40 .40 .40 .40 .40 .40 .40 .40 .40 .40 .40 .40

 605 .30 .30 .30 .30 .30 .30 .30 .30 .30 .30 .30 .30

 406 .15 .15 .15 .15 .15 .15 .15 .15 .15 .15 .15 .15

 706 .30 .30 .30 .30 .30 .30 .30 .30 .30 .30 .30 .30

 606 .15 .15 .15 .15 .15 .15 .15 .15 .15 .15 .15 .15

 407 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5

 707 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.5

 607 .95 .95 .95 .95 .95 .95 .95 .95 .95 .95 .95 .95

 408 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002

 708 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002

 608 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002

 409 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 709 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 609 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 410 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002

 710 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002

 610 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002 .002

 411 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 711 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 611 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10 .10

 END MON-POTFW

 MON-IFLW-CONC

 Interflow concentration of NH4-N (mg/l) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 702 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 602 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 403 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 703 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 603 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 404 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015
100 Appendix 2

 704 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 604 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 405 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 705 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 605 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 406 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 706 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 606 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 407 .080 .080 .080 .080 .080 .080 .080 .080 .080 .080 .080 .080

 707 .150 .150 .150 .150 .150 .150 .150 .150 .150 .150 .150 .150

 607 .080 .080 .080 .080 .080 .080 .080 .080 .080 .080 .080 .080

 408 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 708 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 608 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 409 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 709 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 609 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 410 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 710 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 610 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 411 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 711 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 611 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 END MON-IFLW-CONC

 MON-GRND-CONC

 Active groundwater concentration of NH4-N (mg/l) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 702 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 602 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 403 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 703 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 603 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 404 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 704 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 604 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015 .015

 405 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 705 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 605 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 406 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 706 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 606 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028 .028

 407 .050 .050 .050 .050 .050 .050 .050 .050 .050 .050 .050 .050

 707 .060 .060 .060 .060 .060 .060 .060 .060 .060 .060 .060 .060

 607 .050 .050 .050 .050 .050 .050 .050 .050 .050 .050 .050 .050

 408 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 708 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 608 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 409 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 709 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 609 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 410 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 710 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 610 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 411 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 711 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 611 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027 .027

 END MON-GRND-CONC

 QUAL-PROPS

 # #<--QUALID--> QTID QSD VPFW VPFS QSO VQO QIFW VIQC QAGW VAQC ***

 402 711 PO4 LBS 1 2 0 0 0 1 4 1 4

 END QUAL-PROPS

 MON-POTFW

 Potency factors for PO4 (lb PO4-P/ton sediment) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6

 702 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6

 602 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6

 403 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6

 703 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6

 603 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6

 404 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6

 704 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6

 604 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6

 405 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

 705 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

 605 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

 406 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

 706 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

 606 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

 407 14. 14. 14. 14. 14. 14. 14. 14. 14. 14. 14. 14.

 707 14. 14. 14. 14. 14. 14. 14. 14. 14. 14. 14. 14.

 607 14. 14. 14. 14. 14. 14. 14. 14. 14. 14. 14. 14.

 408 .010 .010 .010 .010 .010 .025 .035 .035 .025 .010 .010 .010

 708 .010 .010 .010 .010 .010 .025 .035 .035 .025 .010 .010 .010

 608 .010 .010 .010 .010 .010 .025 .035 .035 .025 .010 .010 .010

 409 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8

 709 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8

 609 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8
Appendix 2 101

 410 .020 .020 .020 .020 .020 .025 .035 .035 .035 .020 .020 .020

 710 .020 .020 .020 .020 .020 .025 .035 .035 .025 .020 .020 .020

 610 .020 .020 .020 .020 .020 .025 .035 .035 .025 .020 .020 .020

 411 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8

 711 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8

 611 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8

 END MON-POTFW

 MON-IFLW-CONC

 Interflow concentration of PO4-P (mg/l) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 702 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 602 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 403 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 703 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 603 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 404 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 704 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 604 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 405 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 705 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 605 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 406 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 706 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 606 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 407 .120 .120 .120 .120 .120 .120 .120 .120 .120 .120 .120 .120

 707 .120 .120 .120 .120 .120 .120 .120 .120 .120 .120 .120 .120

 607 .120 .120 .120 .120 .120 .120 .120 .120 .120 .120 .120 .120

 408 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 708 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 608 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 409 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 709 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 609 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 410 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 710 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 610 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 411 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 711 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 611 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 END MON-IFLW-CONC

 MON-GRND-CONC

 Active groundwater concentration of PO4-P (mg/l) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 702 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 602 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 403 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 703 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 603 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 404 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 704 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 604 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025 .025

 405 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 705 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 605 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 406 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 706 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 606 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040 .040

 407 .060 .060 .060 .060 .060 .060 .060 .060 .060 .060 .060 .060

 707 .070 .070 .070 .070 .070 .070 .070 .070 .070 .070 .070 .070

 607 .060 .060 .060 .060 .060 .060 .060 .060 .060 .060 .060 .060

 408 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 708 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 608 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 409 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 709 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 609 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 410 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 710 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 610 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005 .005

 411 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 711 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 611 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010 .010

 END MON-GRND-CONC

 QUAL-PROPS

 # #<--QUALID--> QTID QSD VPFW VPFS QSO VQO QIFW VIQC QAGW VAQC ***

 402 711 BOD LBS 1 2 0 0 0 1 4 1 4

 END QUAL-PROPS

 MON-POTFW

 Potency factors for BOD (lb BOD/ton sediment) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 25. 25. 25. 25. 25. 25. 25. 25. 25. 25. 25. 25.

 702 25. 25. 25. 25. 25. 25. 25. 25. 25. 25. 25. 25.

 402 25. 25. 25. 25. 25. 25. 25. 25. 25. 25. 25. 25.

 403 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 703 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 603 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.
102 Appendix 2

 404 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 704 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 604 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 405 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35.

 705 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35.

 605 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35.

 406 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35.

 706 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35.

 606 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35.

 407 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35.

 707 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35.

 607 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35. 35.

 408 8.5 8.5 8.5 8.5 8.5 5.5 5.5 5.5 5.5 8.5 8.5 8.5

 708 8.5 8.5 8.5 8.5 8.5 5.5 5.5 5.5 5.5 8.5 8.5 8.5

 608 8.5 8.5 8.5 8.5 8.5 5.5 5.5 5.5 5.5 8.5 8.5 8.5

 409 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 709 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 609 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 410 8.5 8.5 8.5 8.5 8.5 5.5 5.5 5.5 5.5 8.5 8.5 8.5

 710 8.5 8.5 8.5 8.5 8.5 5.5 5.5 5.5 5.5 8.5 8.5 8.5

 610 8.5 8.5 8.5 8.5 8.5 5.5 5.5 5.5 5.5 8.5 8.5 8.5

 411 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 711 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 611 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20. 20.

 END MON-POTFW

 MON-IFLW-CONC

 Interflow concentration of BOD (mg/l) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65

 702 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65

 602 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65

 403 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 703 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 603 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 404 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 704 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 604 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 405 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 705 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 605 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 406 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 706 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 606 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 407 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 707 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 607 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 408 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5

 708 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5

 608 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5

 409 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 709 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 609 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 410 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1

 710 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1

 610 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1

 411 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 711 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 611 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 END MON-IFLW-CONC

 MON-GRND-CONC

 Active groundwater concentration of BOD (mg/l) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65

 702 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65

 602 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65 .65

 403 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 703 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 603 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 404 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 704 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 604 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 405 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 705 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 605 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 406 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 706 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 606 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 407 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 707 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 607 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2. 2.

 408 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5

 708 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5

 608 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5 .5

 409 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 709 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 609 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 410 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1

 710 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1

 610 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1

 411 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6
Appendix 2 103

 711 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 611 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 END MON-GRND-CONC

 QUAL-PROPS

 # #<--QUALID--> QTID QSD VPFW VPFS QSO VQO QIFW VIQC QAGW VAQC ***

 402 711 ORGN LBS 1 1 0 0 0 1 4 1 4

 END QUAL-PROPS

 MON-POTFW

 Potency factors for ORGN (lb ORGN/ton sediment) ***

 402 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 702 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 602 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 403 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3

 703 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3

 603 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 404 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 704 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 604 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.

 405 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

 705 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

 605 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0

 406 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0

 306 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0

 606 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0

 407 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0

 707 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0

 607 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0

 408 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 708 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 608 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 409 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 709 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 609 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 410 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 710 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 610 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 411 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 711 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 611 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0

 END MON-POTFW

 MON-IFLW-CONC

 Interflow concentration of ORGN (mg/l) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25

 702 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25

 602 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25

 403 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2

 703 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2

 603 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2

 404 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2

 704 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2

 604 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2

 405 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 705 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 605 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 406 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 706 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 606 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 407 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 707 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 607 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6 .6

 408 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2

 708 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2

 608 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2 .2

 409 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25

 709 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25

 609 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25

 410 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1

 710 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1

 610 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1 .1

 411 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25

 711 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25

 611 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25 .25

 END MON-IFLW-CONC

 MON-GRND-CONC

 Active groundwater concentration of ORGN (mg/l) ***

 # # JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC ***

 402 811 .15 .15 .15 .15 .15 .15 .15 .15 .15 .15 .15 .15

 END MON-GRND-CONC

END PERLND

IMPLND

 ACTIVITY

 # # ATMP SNOW IWAT SLD IWG IQAL ***

 401 702 1 1 1 1 1 1

 END ACTIVITY
104 Appendix 2

 PRINT-INFO

 # # ATMP SNOW IWAT SLD IWG IQAL PIVL PYR ***

 401 702 6 6 5 5 5 5 0 12

 END PRINT-INFO

 GEN-INFO

 # # NAME UCI IN OUT ENGL METR ***

 701 ROADS,BUILDING-resid 1 1 1 90 0

 702 ROADS,BUILDING-urban 1 1 1 90 0

 401 ROADS,BUILDING-resid 1 1 1 90 0

 402 ROADS,BUILDING-urban 1 1 1 90 0

 601 ROADS,BUILDING-resid 1 1 1 90 0

 602 ROADS,BUILDING-urban 1 1 1 90 0

 END GEN-INFO

  AIR TEMPERATURE ** **

 ATEMP-DAT

 ELDAT AIRTMP ***

 # # (ft) (deg F) ***

 701 702 -290.0 48.3

 401 402 -390.0 48.3

 601 602 50.0 53.6

 END ATEMP-DAT

  SNOW ** **

 ICE-FLAG

*** <ILS > ICEFG

*** # #

 401 702 1

 END ICE-FLAG

 SNOW-PARM1

*** <ILS > LAT MELEV SHADE SNOWCF COVIND

*** # # (deg) (ft) (in)

 701 702 39.9 350. 0.20 1.0 0.60

 401 402 39.8 250. 0.20 1.0 0.60

 601 602 39.7 125. 0.20 1.0 0.60

 END SNOW-PARM1

 SNOW-PARM2

*** <ILS > RDSCN TSNOW SNOEVP CCFACT MWATER MGMELT

*** # # (degF) (in/day)

 701 702 0.15 30.0 0.08 0.60 0.03 0.05

 401 402 0.15 30.0 0.08 0.60 0.03 0.05

 601 602 0.15 30.0 0.08 0.60 0.03 0.05

 END SNOW-PARM2

  HYDROLOGY ** **

 IWAT-PARM1

*** <ILS > Flags

*** x - x CSNO RTOP VRS VNN RTLI

 401 702 1 0 1 0 0

 END IWAT-PARM1

 IWAT-PARM2

*** <ILS > LSUR SLSUR NSUR RETSC

*** x - x (ft) (in)

 701 150.0 0.036 0.07 0.0

 702 150.0 0.031 0.05 0.0

 401 150.0 0.036 0.07 0.0

 402 150.0 0.031 0.05 0.0

 601 150.0 0.036 0.07 0.0

 602 150.0 0.031 0.05 0.0

 END IWAT-PARM2

 IWAT-PARM3

*** <ILS > PETMAX PETMIN

*** x - x (deg F) (deg F)

 401 702 40.0 35.0

 END IWAT-PARM3

 MON-RETN

*** <ILS > Retention storage capacity at start of each month (in)

*** x - x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 401 702 .03 .03 .04 .04 .05 .065 .065 .065 .05 .04 .04 .03

 END MON-RETN

 IWAT-STATE1

*** <ILS > IWATER state variables (inches)

*** x - x RETS SURS

 401 702 0.0 0.0

 END IWAT-STATE1

 SLD-PARM1

*** <ILS > Flags

*** x - x VASD VRSD SDOP

 401 702 0 0 1

 END SLD-PARM1
Appendix 2 105

 SLD-PARM2

IMPLND *** KEIM JEIM ACCSDP REMSDP

 701 1.0 1.2 0.0010 0.08

 702 1.0 1.2 0.0040 0.08

 401 1.0 1.2 0.0010 0.08

 402 1.0 1.2 0.0040 0.08

 601 1.0 1.2 0.0010 0.08

 602 1.0 1.2 0.0040 0.08

 END SLD-PARM2

 SLD-STOR

IMPLND *** SLDS

 401 702 0.05

 END SLD-STOR

 IWT-PARM1

*** <ILS > Flags for section IWTGAS

*** x - x WTFV CSNO

 401 702 1 1

 END IWT-PARM1

 IWT-PARM2

IMPLND *** ELEV AWTF BWTF

 701 702 350. 34.0 0.3

 401 402 250. 34.0 0.3

 601 602 125. 34.0 0.3

 END IWT-PARM2

 MON-AWTF

IMPLND *** JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 401 702 32.9 36.0 39.1 45.1 50.3 57.4 60.4 59.6 55.9 49.5 42.4 37.4

 END MON-AWTF

 MON-BWTF

IMPLND *** JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 401 702 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38

 END MON-BWTF

 IWT-INIT

*** <ILS > SOTMP SODOX SOCO2

*** x - x (deg F) (mg/l) (mg C/l)

 401 702 55.

 END IWT-INIT

*** WATER QUALITY CONSTITUENTS ***

 NQUALS

 # # NQAL ***

 401 402 4

 701 702 4

 601 602 4

 END NQUALS

 QUAL-PROPS

 # #<--QUALID--> QTID QSD VPFW QSO VQO ***

 401 402 NO3 LBS 0 0 1 0

 701 702 NO3 LBS 0 0 1 0

 601 602 NO3 LBS 0 0 1 0

 END QUAL-PROPS

 QUAL-INPUT

 # # SQO POTFW ACQOP SQOLIM WSQOP ***

 401 402 0.050 0.0060 0.4000 0.500

 701 702 0.050 0.0060 0.4000 0.500

 601 602 0.050 0.0060 0.4000 0.500

 END QUAL-INPUT

 QUAL-PROPS

 # #<--QUALID--> QTID QSD VPFW QSO VQO ***

 401 402 NH4 LBS 1 0 1 0

 701 702 NH4 LBS 1 0 1 0

 601 602 NH4 LBS 1 0 1 0

 END QUAL-PROPS

 QUAL-INPUT

 # # SQO POTFW ACQOP SQOLIM WSQOP ***

 401 402 0.020 0.1 0.0010 0.1200 0.500

 701 702 0.020 0.1 0.0010 0.1200 0.500

 601 602 0.020 0.1 0.0010 0.1200 0.500

 END QUAL-INPUT

 QUAL-PROPS

 # #<--QUALID--> QTID QSD VPFW QSO VQO ***

 401 402 PO4 LBS 1 0 1 0

 701 702 PO4 LBS 1 0 1 0

 601 602 PO4 LBS 1 0 1 0

 END QUAL-PROPS

 QUAL-INPUT

 # # SQO POTFW ACQOP SQOLIM WSQOP ***

 401 0.010 1.2 0.0006 0.0090 0.500

 402 0.010 1.0 0.0004 0.0090 0.500
106 Appendix 2

 701 0.010 1.2 0.0006 0.0090 0.500

 702 0.010 1.0 0.0004 0.0090 0.500

 601 0.010 1.2 0.0006 0.0090 0.500

 602 0.010 1.0 0.0004 0.0090 0.500

 END QUAL-INPUT

 QUAL-PROPS

 # #<--QUALID--> QTID QSD VPFW QSO VQO ***

 401 402 BOD LBS 0 0 1 0

 701 702 BOD LBS 0 0 1 0

 601 602 BOD LBS 0 0 1 0

 END QUAL-PROPS

 QUAL-INPUT

 # # SQO POTFW ACQOP SQOLIM WSQOP ***

 401 402 1.900 0.3600 9.0000 0.500

 701 702 1.900 0.3600 9.0000 0.500

 601 602 1.900 0.3600 9.0000 0.500

END QUAL-INPUT

END IMPLND

RCHRES

 ACTIVITY

 RCHRES Active Sections (1=Active; 0=Inactive) ***

 # - # HYFG ADFG CNFG HTFG SDFG GQFG OXFG NUFG PKFG PHFG ***

 1 9 1 1 0 1 1 0 1 1 1 0

 END ACTIVITY

 PRINT-INFO

 RCHRES Print-flags ***

 # - # HYDR ADCA CONS HEAT SED GQL OXRX NUTR PLNK PHCB PIVL PYR ***

 1 9 5 6 6 5 5 5 5 12

 END PRINT-INFO

 GEN-INFO

 RCHRES<-------Name------->Nexit Unit Systems Printer ***

 # - # User t-series Engl Metr LKFG ***

 in out ***

 1 UPR WEST BR 1 1 1 1 90 0 0

 2 LWR WBR-KENNETT GAGE 2 1 1 1 90 0 0

 3 EAST BR-CONFL WBR 2 1 1 1 90 0 0

 4 MS-ASHLAND 2 1 1 1 90 0 0

 5 ASHLAND-WOODDALE 1 1 1 1 90 0 0

 6 BURROUGHS RUN 1 1 1 1 90 0 0

 7 HOOPES RESERVOIR 1 1 1 1 90 0 0

 8 WOODDALE-STANTON 4 1 1 1 90 0 0

 9 STANTON-WHITE CLAY 1 1 1 1 90 0 0

 END GEN-INFO

  HYDRAULICS

 HYDR-PARM1

 RCHRES VC A1 A2 A3 ODFVFG for each ** * ODGTFG for each FUNCT for each

 # - # FG FG FG FG possible exit *** possible exit possible exit

 1 0 1 1 1 4 0 0 0 0 0 0 0 0 0 1 1 1 1 1

 2 4 0 1 1 1 4 0 0 0 0 0 2 0 0 0 1 1 1 1 1

 5 7 0 1 1 1 4 0 0 0 0 0 0 0 0 0 1 1 1 1 1

 8 0 1 1 1 4 0 0 0 0 0 2 3 4 0 1 1 1 1 1

 9 0 1 1 1 4 0 0 0 0 0 0 0 0 0 1 1 1 1 1

 END HYDR-PARM1

 HYDR-PARM2

 RCHRES FTABNO LEN DELTH STCOR KS DB50 ***

 # - # (miles) (ft) (ft) (in) ***

 1 1 5.00 160.0 0.0 0.5 0.01

 2 2 4.90 70.0 0.0 0.5 0.01

 3 3 7.20 170.0 0.0 0.5 0.01

 4 4 3.40 50.0 0.0 0.5 0.01

 5 5 5.10 60.0 0.0 0.5 0.01

 6 6 5.00 220.0 0.0 0.5 0.01

 7 7 1.70 0.0 0.0 0.5 0.01

 8 8 4.30 79.5 0.0 0.5 0.01

 9 9 0.84 0.5 0.0 0.5 0.01

 END HYDR-PARM2

 HYDR-INIT

 RCHRES VOL *** Initial value of COLIND Initial value of OUTDGT

 # - # ac-ft *** for each exit for each exit (ft3)

 1 2.10 4.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

 2 6.80 4.0 0.0 0.0 0.0 0.0 0.0 .001 0.0 0.0 0.0

 3 3.10 4.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

 4 5.70 4.0 0.0 0.0 0.0 0.0 0.0 3.1 0.0 0.0 0.0

 5 11.80 4.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

 6 1.30 4.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

 7 *** 5000.00 4.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

 8 8.00 4.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

 9 7.00 4.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

 END HYDR-INIT

 HT-BED-FLAGS

RCHRES *** BDFG TGFG TSTP
Appendix 2 107

 1 9 1 3

 END HT-BED-FLAGS

 HEAT-PARM

RCHRES *** ELEV ELDAT CFSAEX KATRAD KCOND KEVAP

 1 7 200. -440. 0.50 9.4 10.0 2.2

 8 9 40. -35. 0.50 9.4 10.0 2.2

 END HEAT-PARM

 HT-BED-PARM

RCHRES *** MUDDEP TGRND KMUD KGRND

 1 9 0.01 61. 80 0.0

 END HT-BED-PARM

 MON-HT-TGRND

RCHRES *** JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

 1 9 39.0 40.0 44.0 51.0 58.0 64.0 69.0 70.0 66.0 60.0 51.0 44.0

 END MON-HT-TGRND

 HEAT-INIT

RCHRES *** TW AIRTMP

 1 9 59. 50.

 END HEAT-INIT

 SANDFG

RCHRES *** SNDFG

 1 9 3

 END SANDFG

 SED-GENPARM

RCHRES *** BEDWID BEDWRN POR

 1 9 25. 6. 0.7

 END SED-GENPARM

 SAND-PM

RCHRES *** D W RHO KSAND EXPSND

 1 9 .005 0.1 2.5 0.10 3.92

 END SAND-PM

 SILT-CLAY-PM

RCHRES *** D W RHO TAUCD TAUCS M

 1 0.00040 0.0003 2.2 0.13 0.50 0.90

 2 3 0.00040 0.0003 2.2 0.12 0.45 0.90

 4 0.00040 0.0003 2.2 0.15 0.58 0.90

 5 0.00040 0.0003 2.2 0.15 0.55 0.90

 6 7 0.00040 0.0003 2.2 0.16 0.60 0.90

 8 9 0.00040 0.0003 2.2 0.18 0.73 0.90

 END SILT-CLAY-PM

 SILT-CLAY-PM

RCHRES *** D W RHO TAUCD TAUCS M

 1 0.00010 0.00001 2.0 0.11 0.45 0.90

 2 3 0.00010 0.00001 2.0 0.10 0.40 0.90

 4 0.00010 0.00001 2.0 0.13 0.53 0.90

 5 0.00010 0.00001 2.0 0.13 0.50 0.90

 6 7 0.00010 0.00001 2.0 0.14 0.55 0.90

 8 9 0.00010 0.00001 2.0 0.16 0.68 0.90

 END SILT-CLAY-PM

 SSED-INIT

RCHRES *** SSED1 SSED2 SSED3

 1 9 1. 25. 25.

 END SSED-INIT

 BED-INIT

RCHRES *** BEDDEP SANDFR SILTFR CLAYFR

 1 9 3. .70 .20 .10

 END BED-INIT

 BENTH-FLAG

*** RCHRES BENF

 1 9 1

 END BENTH-FLAG

 SCOUR-PARMS

RCHRES *** SCRVEL SCRMUL

 1 9 3. 2

 END SCOUR-PARMS

 OX-FLAGS

*** RCHRES REAM

 1 9 3

 END OX-FLAGS

 OX-GENPARM

RCHRES *** KBOD20 TCBOD KODSET SUPSAT

*** 1 9 .004 1.047 .021 1.25

 1 9 .010 1.050 .020 1.25

*** 1 3 .025 1.050 .200 1.25

*** 4 5 .015 1.050 .200 1.25

*** 6 7 .025 1.050 .200 1.25

*** 8 9 .015 1.050 .200 1.25
108 Appendix 2

 END OX-GENPARM

 OX-BENPARM

RCHRES *** BENOD TCBEN EXPOD BRBOD1 BRBOD2 EXPREL

 1 9 10. 1.1 1.2 10. 15. 2.5

END OX-BENPARM

 OX-REAPARM

RCHRES *** TCGINV REAK EXPRED EXPREV

 1 9 1.024 .726 -1.673 .970

 END OX-REAPARM

 OX-INIT

RCHRES *** DOX BOD SATDO

 1 9 11.3 2.92 12.0

 END OX-INIT

  NUTRIENTS ** **

 NUT-FLAGS

 RCHRES TAM NO2 PO4 AMV DEN ADNH ADPO PHFG ***

 # - # ***

 1 9 1 0 1 0 1 1 1 2

 END NUT-FLAGS

 NUT-NITDENIT

 RCHRES KTAM20 KNO220 TCNIT KNO320 TCDEN DENOXT ***

 # - # /hr /hr /hr mg/l ***

*** 1 9 .05 .050 1.045 .005 1.04 1.

 1 9 .07 .050 1.045 .005 1.04 1.

 END NUT-NITDENIT

 NUT-BEDCONC

 RCHRES Bed concentrations of NH4 & PO4 (mg/kg) ***

 # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay ***

 1 9 1. 30. 50. 90. 700. 900.

 END NUT-BEDCONC

 NUT-ADSPARM

 RCHRES Partition coefficients for NH4 AND PO4 (ml/g) ***

 # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay ***

 1 9 10. 700. 900. 600. 15000. 18000.

 END NUT-ADSPARM

 NUT-DINIT

 RCHRES NO3 TAM NO2 PO4 PH ***

 # - # mg/l mg/l mg/l mg/l ***

 1 9 2.0 .055 .033 7.

 END NUT-DINIT

 NUT-ADSINIT

 RCHRES Initial suspended NH4 and PO4 concentrations (mg/kg) ***

 # - # NH4-sand NH4-silt NH4-clay PO4-sand PO4-silt PO4-clay ***

 1 9 0.1 0.3 0.5 0.1 0.5 0.8

 END NUT-ADSINIT

  PLANKTON ** **

 PLNK-FLAGS

 RCHRES PHYF ZOOF BALF SDLT AMRF DECF NSFG ZFOO ***

 # - # ***

 1 9 1 0 1 0 0 1 1 2

 END PLNK-FLAGS

 PLNK-PARM1

 RCHRES RATCLP NONREF LITSED ALNPR EXTB MALGR ***

 # - # /ft /hr ***

*** 1 9 .60 .5 0. 0.8 .20 .200

 1 .60 .5 0. 0.6 .20 .200

 2 .60 .5 0. 0.5 .20 .200

 3 .60 .5 0. 0.6 .20 .200

 4 5 .60 .5 0. 0.5 .20 .200

 6 7 .60 .5 0. 0.7 .20 .200

 8 9 .60 .5 0. 0.5 .20 .200

 END PLNK-PARM1

 PLNK-PARM2

 RCHRES *** CMMLT CMMN CMMNP CMMP TALGRH TALGRL TALGRM

 # - # ***ly/min mg/l mg/l mg/l deg F deg F deg F

 1 9 .03 .045 .029 .015 95. 32. 55.

 END PLNK-PARM2

 PLNK-PARM3

 RCHRES ALR20 ALDH ALDL OXALD NALDH PALDH ***

 # - # /hr /hr /hr /hr mg/l mg/l ***

 1 9 .045 .010 .001 .03 .015 .001

 END PLNK-PARM3

 PHYTO-PARM

 RCHRES SEED MXSTAY OREF CLALDH PHYSET REFSET ***

 # - # mg/l mg/l ug/l ***

 1 9 .4 .8 20. 50. .012 .010

 END PHYTO-PARM
Appendix 2 109

 PLNK-INIT

 RCHRES PHYTO ZOO BENAL ORN ORP ORC ***

 # - # mg/l org/l mg/m2 mg/l mg/l mg/l ***

 1 9 .700 .03 1.0E-8 1. .2 8.

END PLNK-INIT

END RCHRES

FTABLES

 FTABLE 1

 ROWS COLS *** West Br., to Chandler’s Mill Rd.

 15 4

 DEPTH AREA VOLUME DISCH FLO-THRU ***

 (FT) (ACRES) (AC-FT) (CFS) (MIN) ***

 0.00 0.0 0.0 0.0 0.

 0.33 10.5 3.4 6.0 408.

 0.67 11.3 7.0 19.3 264.

 1.00 12.1 10.9 38.3 207.

 1.33 12.9 15.1 62.8 174.

 1.67 13.7 19.5 92.4 153.

 2.00 14.5 24.2 127.2 138.

 2.67 16.2 34.5 212.1 118.

 3.33 17.8 45.8 318.2 104.

 4.00 19.4 58.2 446.0 95.

 5.33 51.7 105.6 836.0 92.

 6.67 84.0 196.1 1368. 104.

 8.00 116.4 329.7 2067. 116.

 9.33 148.7 506.4 2957. 124.

 10.67 181.0 726.2 4057. 130.

 END FTABLE 1

 FTABLE 2

 ROWS COLS *** West Br., to confluence w/ East Br.

 15 4

 DEPTH AREA VOLUME DISCH FLO-THRU ***

 (FT) (ACRES) (AC-FT) (CFS) (MIN) ***

 0.00 0.0 0.0 0.0 0.

 0.42 14.7 5.9 7.6 565.

 0.83 15.8 12.3 24.4 366.

 1.25 16.9 19.1 48.6 286.

 1.67 18.0 26.4 79.5 241.

 2.08 19.1 34.1 117.1 212.

 2.50 20.2 42.3 161.1 191.

 3.33 22.4 60.1 268.5 162.

 4.17 24.5 79.6 402.3 144.

 5.00 26.7 101.0 563.4 130.

 6.67 66.3 178.5 1051. 123.

 8.33 105.9 322.0 1714. 136.

 10.00 145.5 531.6 2582. 149.

 11.67 185.1 807.1 3684. 159.

 13.33 224.7 1148.6 5043. 165.

 END FTABLE 2

 FTABLE 3

 ROWS COLS *** East Br., to Kennett gage

 15 4

 DEPTH AREA VOLUME DISCH FLO-THRU ***

 (FT) (ACRES) (AC-FT) (CFS) (MIN) ***

 0.00 0.0 0.0 0.0 0.

 0.38 11.4 4.2 4.9 628.

 0.77 12.4 8.8 15.5 409.

 1.15 13.3 13.7 30.8 322.

 1.53 14.3 19.0 50.4 273.

 1.92 15.2 24.6 74.0 241.

 2.30 16.1 30.6 101.8 218.

 3.07 18.0 43.7 169.6 187.

 3.83 19.9 58.3 254.3 166.

 4.60 21.8 74.3 356.6 151.

 6.13 66.4 141.9 675.9 152.

 7.67 111.0 278.0 1123. 180.

 9.20 155.6 482.4 1728. 203.

 10.73 200.2 755.3 2513. 218.

 12.27 244.8 1096.5 3502. 227.

 END FTABLE 3

 FTABLE 4

 ROWS COLS *** MStem, Kennett Gage to Barley Mill Rd.(Ashland)

 15 4

 DEPTH AREA VOLUME DISCH FLO-THRU ***

 (FT) (ACRES) (AC-FT) (CFS) (MIN) ***

 0.00 0.0 0.0 0.0 0.

 0.58 20.2 11.6 29.4 287.

 1.17 20.5 23.5 93.1 183.

 1.75 20.9 35.6 182.3 142.

 2.33 21.3 47.9 293.5 119.

 2.92 21.7 60.5 424.6 103.

 3.50 22.0 73.2 573.9 93.

 4.67 22.8 99.4 923.4 78.

 5.83 23.6 126.4 1335. 69.

 7.00 24.3 154.3 1806. 62.

 9.33 62.8 256.0 3082. 60.

 11.67 101.2 447.3 4768. 68.
110 Appendix 2

 14.00 139.7 728.4 6946. 76.

 16.33 178.2 1099.3 9687. 82.

 18.67 216.6 1559.9 13053. 87.

 END FTABLE 4

 FTABLE 5

 ROWS COLS *** MStem,Barley Mill Rd to Wooddale Gage

 15 4

 DEPTH AREA VOLUME DISCH FLO-THRU ***

 (FT) (ACRES) (AC-FT) (CFS) (MIN) ***

 0.00 0.0 0.0 0.0 0.

 0.60 31.5 18.7 33.2 409.

 1.20 32.1 37.8 105.1 261.

 1.80 32.8 57.3 206.0 202.

 2.40 33.4 77.1 331.9 169.

 3.00 34.0 97.4 480.3 147.

 3.60 34.6 117.9 649.7 132.

 4.80 35.9 160.2 1046. 111.

 6.00 37.1 204.0 1515. 98.

 7.20 38.3 249.3 2051. 88.

 9.60 87.8 400.6 3492. 83.

 12.00 137.2 670.6 5347. 91.

 14.40 186.7 1059.3 7675. 100.

 16.80 236.1 1566.7 10526. 108.

 19.20 285.6 2192.8 13948. 114.

 END FTABLE 5

 FTABLE 6

 ROWS COLS *** Burroughs Run

 15 4

 DEPTH AREA VOLUME DISCH FLO-THRU ***

 (FT) (ACRES) (AC-FT) (CFS) (MIN) ***

 0.00 0.0 0.0 0.0 0.

 0.49 9.7 4.6 12.0 280.

 0.98 10.3 9.5 37.9 183.

 1.48 10.9 14.8 74.5 144.

 1.97 11.5 20.3 120.8 122.

 2.46 12.1 26.1 175.9 108.

 2.95 12.7 32.2 239.8 97.

 3.93 13.9 45.3 393.1 84.

 4.92 15.2 59.6 580.4 75.

 5.90 16.4 75.1 802.3 68.

 7.87 40.2 130.7 1475. 64.

 9.83 64.0 233.2 2383. 71.

 11.80 87.9 382.6 3571. 78.

 13.77 111.7 578.9 5076. 83.

 15.73 135.6 822.0 6929. 86.

 END FTABLE 6

 FTABLE 7

 ROWS COLS *** Hoopes Reservoir

 12 4

 DEPTH AREA VOLUME DISCH FLO-THRU ***

 (FT) (ACRES) (AC-FT) (CFS) (MIN) ***

 0.00 0.0 0.0 0.0 0.

 12.5 3.0 31.0 0.0 0.

 22.5 5.0 107.0 0.0 0.

 32.5 10.0 276.0 0.0 0.

 42.5 19.0 583.0 0.0 0.

 52.5 33.0 982.0 0.0 0.

 62.5 52.0 1534.0 0.0 0.

 72.5 90.0 2240.0 0.0 0.

 82.5 105.0 3284.0 0.0 0.

 92.5 150.0 4604.0 0.0 0.

 102.5 200.0 6267.0 0.0 0.

 104.5 210.0 6598.0 58.4 0.

 END FTABLE 7

 FTABLE 8

 ROWS COLS *** MStem, Wooddale Gage to Stanton Gage

 15 4

 DEPTH AREA VOLUME DISCH FLO-THRU ***

 (FT) (ACRES) (AC-FT) (CFS) (MIN) ***

 0.00 0.0 0.0 0.0 0.

 0.72 37.7 27.6 81.6 246.

 1.45 36.8 54.7 249.5 159.

 2.17 36.0 81.1 472.2 125.

 2.90 35.1 106.8 734.7 106.

 3.62 34.2 131.9 1027. 93.

 4.35 33.4 156.4 1341. 85.

 5.80 31.6 203.6 2012. 73.

 7.25 29.9 248.1 2712. 66.

 8.70 28.1 290.2 3418. 62.

 11.60 128.9 517.9 5292. 71.

 14.50 229.7 1037.9 7996. 94.

 17.40 330.4 1850.1 11848. 113.

 20.30 431.2 2954.5 17115. 125.

 23.20 532.0 4351.1 24033. 131.

 END FTABLE 8

 FTABLE 9

 ROWS COLS *** MStem, Stanton to confl w/White Clay
Appendix 2 111

 15 4

 DEPTH AREA VOLUME DISCH FLO-THRU ***

 (FT) (ACRES) (AC-FT) (CFS) (MIN) ***

 0.00 0.0 0.0 0.0 0.

 0.83 6.6 5.5 16.5 244.

 1.67 6.4 11.0 50.4 158.

 2.50 6.3 16.3 95.5 124.

 3.33 6.2 21.5 148.6 105.

 4.17 6.0 26.6 207.9 93.

 5.00 5.9 31.6 271.7 84.

 6.67 5.6 41.2 408.6 73.

 8.33 5.4 50.3 552.5 66.

 10.00 5.1 59.1 698.3 61.

 13.33 39.0 132.6 1113. 86.

 16.67 73.0 319.3 1802. 129.

 20.00 106.9 619.1 2894. 155.

 23.33 140.8 1032.0 4494. 167.

 26.67 174.8 1558.0 6697. 169.

 END FTABLE 9

END FTABLES

COPY

 TIMESERIES

 # - # NPT NMN ***

 10 400 18

 END TIMESERIES

END COPY

EXT SOURCES

<-Volume-> <Member> SsysSgap<--Mult-->Tran <-Target vols> <-Grp> <-Member-> ***

<Name> # <Name> # tem strg<-factor->strg <Name> # # <Name> # # ***

*** Meteorological data

WDM1 76 PREC 0 ENGL 0.90 PERLND 702 711 EXTNL PREC 1 1

WDM1 76 PREC 0 ENGL 0.87 PERLND 402 411 EXTNL PREC 1 1

WDM1 76 PREC 0 ENGL 0.85 PERLND 602 611 EXTNL PREC 1 1

WDM1 160 NO3X 0 METR 1.0 PERLND 402 611 EXTNL NIADCN 1 1

WDM1 161 NH3X 0 METR 1.0 PERLND 402 611 EXTNL NIADCN 2 1

WDM1 76 PREC 0 ENGL 17509. COPY 200 INPUT MEAN 4 1

WDM1 76 PREC 0 ENGL 28678. COPY 300 INPUT MEAN 4 1

WDM1 76 PREC 0 ENGL 31121. COPY 400 INPUT MEAN 4 1

WDM1 52 ATMP 0 ENGL 1.0 PERLND 702 711 EXTNL GATMP 1 1

WDM1 52 ATMP 0 ENGL 1.0 PERLND 402 411 EXTNL GATMP 1 1

WDM1 50 ATMP 0 ENGL 1.0 PERLND 602 611 EXTNL GATMP 1 1

WDM1 20 PETX 0 ENGL 1.1 PERLND 402 711 EXTNL PETINP 1 1

WDM1 45 DWPT 0 ENGL 1.0 PERLND 402 711 EXTNL DTMPG 1 1

WDM1 30 WIND 0 ENGL 1.0 PERLND 402 711 EXTNL WINMOV 1 1

WDM1 10 SOLR 0 ENGL 1.0 PERLND 402 711 EXTNL SOLRAD 1 1

WDM1 76 PREC 0 ENGL 0.90 IMPLND 701 702 EXTNL PREC 1 1

WDM1 76 PREC 0 ENGL 0.87 IMPLND 401 402 EXTNL PREC 1 1

WDM1 76 PREC 0 ENGL 0.85 IMPLND 601 602 EXTNL PREC 1 1

WDM1 52 ATMP 0 ENGL 1.0 IMPLND 701 702 EXTNL GATMP 1 1

WDM1 52 ATMP 0 ENGL 1.0 IMPLND 401 402 EXTNL GATMP 1 1

WDM1 50 ATMP 0 ENGL 1.0 IMPLND 601 602 EXTNL GATMP 1 1

WDM1 20 PETX 0 ENGL 1.1 IMPLND 401 702 EXTNL PETINP 1 1

WDM1 45 DWPT 0 ENGL 1.0 IMPLND 401 702 EXTNL DTMPG 1 1

WDM1 30 WIND 0 ENGL 1.0 IMPLND 401 702 EXTNL WINMOV 1 1

WDM1 10 SOLR 0 ENGL 1.0 IMPLND 401 702 EXTNL SOLRAD 1 1

WDM1 76 PREC 0 ENGL 0.90 RCHRES 1 3 EXTNL PREC 1 1

WDM1 76 PREC 0 ENGL 0.87 RCHRES 4 7 EXTNL PREC 1 1

WDM1 76 PREC 0 ENGL 0.85 RCHRES 8 9 EXTNL PREC 1 1

WDM1 160 NO3X 0 METR 1.0 RCHRES 1 9 EXTNL NUADCN 1 1

WDM1 161 NH3X 0 METR 1.0 RCHRES 1 9 EXTNL NUADCN 2 1

WDM1 52 ATMP 0 ENGL 1.0 RCHRES 1 3 EXTNL GATMP 1 1

WDM1 52 ATMP 0 ENGL 1.0 RCHRES 4 7 EXTNL GATMP 1 1

WDM1 50 ATMP 0 ENGL 1.0 RCHRES 8 9 EXTNL GATMP 1 1

WDM1 45 DWPT 0 ENGL 1.0 RCHRES 1 9 EXTNL DEWTMP 1 1

WDM1 40 COVR 0 ENGL 1.0 RCHRES 1 9 EXTNL CLOUD 1 1

WDM1 30 WIND 0 ENGL 1.0 RCHRES 1 9 EXTNL WIND 1 1

WDM1 20 PETX 0 ENGL 1.1 RCHRES 1 9 EXTNL POTEV 1 1

WDM1 10 SOLR 0 ENGL 1.0 RCHRES 1 9 EXTNL SOLRAD 1 1

*** Point source Discharges to Red Clay

***New Bolton Center

WDM1 300 PTSQ 0 ENGL 1.0 RCHRES 1 EXTNL IVOL 1 1

WDM1 301 TSSX 0 ENGL 1.0 RCHRES 1 INFLOW ISED 3 1

WDM1 302 BODX 0 ENGL 1.0 RCHRES 1 INFLOW OXIF 2 1

WDM1 303 NH3X 0 ENGL 1.0 RCHRES 1 INFLOW NUIF1 2 1

WDM1 304 NO3X 0 ENGL 1.0 RCHRES 1 INFLOW NUIF1 1 1

WDM1 305 NO2X 0 ENGL 1.0 RCHRES 1 INFLOW NUIF1 3 1

WDM1 306 PO4X 0 ENGL 1.0 RCHRES 1 INFLOW NUIF1 4 1

WDM1 308 HEAT 0 ENGL 1.0 RCHRES 1 INFLOW IHEAT 1 1

*** Sunny Dell Foods PA-001

WDM1 310 PTSQ 0 ENGL 1.0 RCHRES 3 EXTNL IVOL 1 1

WDM1 311 TSSX 0 ENGL 1.0 RCHRES 3 INFLOW ISED 3 1

WDM1 312 BODX 0 ENGL 1.0 RCHRES 3 INFLOW OXIF 2 1

WDM1 313 NH3X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 2 1

WDM1 314 NO3X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 1 1

WDM1 315 NO2X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 3 1

WDM1 316 PO4X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 4 1

WDM1 318 HEAT 0 ENGL 1.0 RCHRES 3 INFLOW IHEAT 1 1

*** Sunny Dell Foods PA-003

WDM1 320 PTSQ 0 ENGL 1.0 RCHRES 3 EXTNL IVOL 1 1

WDM1 321 TSSX 0 ENGL 1.0 RCHRES 3 INFLOW ISED 3 1
112 Appendix 2

WDM1 322 BODX 0 ENGL 1.0 RCHRES 3 INFLOW OXIF 2 1

WDM1 323 NH3X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 2 1

WDM1 324 NO3X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 1 1

WDM1 325 NO2X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 3 1

WDM1 326 PO4X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 4 1

WDM1 328 HEAT 0 ENGL 1.0 RCHRES 3 INFLOW IHEAT 1 1

*** East Marlborough Twp STP

WDM1 330 PTSQ 0 ENGL 1.0 RCHRES 3 EXTNL IVOL 1 1

WDM1 331 TSSX 0 ENGL 1.0 RCHRES 3 INFLOW ISED 3 1

WDM1 332 BODX 0 ENGL 1.0 RCHRES 3 INFLOW OXIF 2 1

WDM1 333 NH3X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 2 1

WDM1 334 NO3X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 1 1

WDM1 335 NO2X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 3 1

WDM1 336 PO4X 0 ENGL 1.0 RCHRES 3 INFLOW NUIF1 4 1

WDM1 338 HEAT 0 ENGL 1.0 RCHRES 3 INFLOW IHEAT 1 1

*** NVF Kennett Square

WDM1 340 PTSQ 0 ENGL 1.0 RCHRES 1 EXTNL IVOL 1 1

WDM1 341 TSSX 0 ENGL 1.0 RCHRES 1 INFLOW ISED 3 1

WDM1 342 BODX 0 ENGL 1.0 RCHRES 1 INFLOW OXIF 2 1

WDM1 343 NH3X 0 ENGL 1.0 RCHRES 1 INFLOW NUIF1 2 1

WDM1 344 NO3X 0 ENGL 1.0 RCHRES 1 INFLOW NUIF1 1 1

WDM1 345 NO2X 0 ENGL 1.0 RCHRES 1 INFLOW NUIF1 3 1

WDM1 346 PO4X 0 ENGL 1.0 RCHRES 1 INFLOW NUIF1 4 1

WDM1 348 HEAT 0 ENGL 1.0 RCHRES 1 INFLOW IHEAT 1 1

*** Kennett Square Borough STP

WDM1 350 PTSQ 0 ENGL 1.0 RCHRES 2 EXTNL IVOL 1 1

WDM1 351 TSSX 0 ENGL 1.0 RCHRES 2 INFLOW ISED 3 1

WDM1 352 BODX 0 ENGL 1.0 RCHRES 2 INFLOW OXIF 2 1

WDM1 353 NH3X 0 ENGL 1.0 RCHRES 2 INFLOW NUIF1 2 1

WDM1 354 NO3X 0 ENGL 1.0 RCHRES 2 INFLOW NUIF1 1 1

WDM1 355 NO2X 0 ENGL 1.0 RCHRES 2 INFLOW NUIF1 3 1

WDM1 356 PO4X 0 ENGL 1.0 RCHRES 2 INFLOW NUIF1 4 1

WDM1 358 HEAT 0 ENGL 1.0 RCHRES 2 INFLOW IHEAT 1 1

*** D’Ambro

WDM1 360 PTSQ 0 ENGL 1.0 RCHRES 6 EXTNL IVOL 1 1

WDM1 361 TSSX 0 ENGL 1.0 RCHRES 6 INFLOW ISED 3 1

WDM1 362 BODX 0 ENGL 1.0 RCHRES 6 INFLOW OXIF 2 1

WDM1 363 NH3X 0 ENGL 1.0 RCHRES 6 INFLOW NUIF1 2 1

WDM1 364 NO3X 0 ENGL 1.0 RCHRES 6 INFLOW NUIF1 1 1

WDM1 365 NO2X 0 ENGL 1.0 RCHRES 6 INFLOW NUIF1 3 1

WDM1 366 PO4X 0 ENGL 1.0 RCHRES 6 INFLOW NUIF1 4 1

WDM1 368 HEAT 0 ENGL 1.0 RCHRES 6 INFLOW IHEAT 1 1

*** NVF Yorklyn

WDM1 370 PTSQ 0 ENGL 1.0 RCHRES 4 EXTNL IVOL 1 1

WDM1 371 TSSX 0 ENGL 1.0 RCHRES 4 INFLOW ISED 3 1

WDM1 372 BODX 0 ENGL 1.0 RCHRES 4 INFLOW OXIF 2 1

WDM1 373 NH3X 0 ENGL 1.0 RCHRES 4 INFLOW NUIF1 2 1

WDM1 374 NO3X 0 ENGL 1.0 RCHRES 4 INFLOW NUIF1 1 1

WDM1 375 NO2X 0 ENGL 1.0 RCHRES 4 INFLOW NUIF1 3 1

WDM1 376 PO4X 0 ENGL 1.0 RCHRES 4 INFLOW NUIF1 4 1

WDM1 378 HEAT 0 ENGL 1.0 RCHRES 4 INFLOW IHEAT 1 1

*** Greenville County Club

WDM1 380 PTSQ 0 ENGL 1.0 RCHRES 5 EXTNL IVOL 1 1

WDM1 381 TSSX 0 ENGL 1.0 RCHRES 5 INFLOW ISED 3 1

WDM1 382 BODX 0 ENGL 1.0 RCHRES 5 INFLOW OXIF 2 1

WDM1 383 NH3X 0 ENGL 1.0 RCHRES 5 INFLOW NUIF1 2 1

WDM1 384 NO3X 0 ENGL 1.0 RCHRES 5 INFLOW NUIF1 1 1

WDM1 385 NO2X 0 ENGL 1.0 RCHRES 5 INFLOW NUIF1 3 1

WDM1 386 PO4X 0 ENGL 1.0 RCHRES 5 INFLOW NUIF1 4 1

WDM1 388 HEAT 0 ENGL 1.0 RCHRES 5 INFLOW IHEAT 1 1

*** Hercules Inc.

WDM1 390 PTSQ 0 ENGL 1.0 RCHRES 8 EXTNL IVOL 1 1

WDM1 391 TSSX 0 ENGL 1.0 RCHRES 8 INFLOW ISED 3 1

WDM1 392 BODX 0 ENGL 1.0 RCHRES 8 INFLOW OXIF 2 1

WDM1 393 NH3X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 2 1

WDM1 394 NO3X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 1 1

WDM1 395 NO2X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 3 1

WDM1 396 PO4X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 4 1

WDM1 398 HEAT 0 ENGL 1.0 RCHRES 8 INFLOW IHEAT 1 1

*** Haveg/Ametek -003

WDM1 400 PTSQ 0 ENGL 1.0 RCHRES 8 EXTNL IVOL 1 1

WDM1 401 TSSX 0 ENGL 1.0 RCHRES 8 INFLOW ISED 3 1

WDM1 402 BODX 0 ENGL 1.0 RCHRES 8 INFLOW OXIF 2 1

WDM1 403 NH3X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 2 1

WDM1 404 NO3X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 1 1

WDM1 405 NO2X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 3 1

WDM1 406 PO4X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 4 1

WDM1 408 HEAT 0 ENGL 1.0 RCHRES 8 INFLOW IHEAT 1 1

*** Haveg/Ammetek -001

WDM1 410 PTSQ 0 ENGL 1.0 RCHRES 8 EXTNL IVOL 1 1

WDM1 411 TSSX 0 ENGL 1.0 RCHRES 8 INFLOW ISED 3 1

WDM1 412 BODX 0 ENGL 1.0 RCHRES 8 INFLOW OXIF 2 1

WDM1 413 NH3X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 2 1

WDM1 414 NO3X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 1 1

WDM1 415 NO2X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 3 1

WDM1 416 PO4X 0 ENGL 1.0 RCHRES 8 INFLOW NUIF1 4 1

WDM1 418 HEAT 0 ENGL 1.0 RCHRES 8 INFLOW IHEAT 1 1

*** Center for Creative Arts

WDM1 420 PTSQ 0 ENGL 1.0 RCHRES 4 EXTNL IVOL 1 1

WDM1 421 TSSX 0 ENGL 1.0 RCHRES 4 INFLOW ISED 3 1

WDM1 422 BODX 0 ENGL 1.0 RCHRES 4 INFLOW OXIF 2 1

WDM1 423 NH3X 0 ENGL 1.0 RCHRES 4 INFLOW NUIF1 2 1
Appendix 2 113

WDM1 424 NO3X 0 ENGL 1.0 RCHRES 4 INFLOW NUIF1 1 1

WDM1 425 NO2X 0 ENGL 1.0 RCHRES 4 INFLOW NUIF1 3 1

WDM1 426 PO4X 0 ENGL 1.0 RCHRES 4 INFLOW NUIF1 4 1

WDM1 428 HEAT 0 ENGL 1.0 RCHRES 4 INFLOW IHEAT 1 1

*** Withdrawals from Red Clay

*** NVF, Yorklyn

WDM1 200 WITH 0 ENGL 1.0SAME RCHRES 4 EXTNL OUTDGT 2 1

*** Hercules Research Center, Wooddale

WDM1 210 WITH 0 ENGL 1.0SAME RCHRES 8 EXTNL OUTDGT 2 1

*** Hercules Country Club, Wooddale

WDM1 220 WITH 0 ENGL 1.0SAME RCHRES 8 EXTNL OUTDGT 3 1

*** Samuel Beard, Wilmington

WDM1 230 WITH 0 ENGL 1.0SAME RCHRES 8 EXTNL OUTDGT 4 1

*** J.H. Thompson, New Garden

WDM1 240 WITH 0 ENGL 1.0SAME RCHRES 2 EXTNL OUTDGT 2 1

*** Kennett Sq. Golf, Kennett Square

WDM1 250 WITH 0 ENGL 1.0SAME RCHRES 3 EXTNL OUTDGT 2 1

END EXT SOURCES

EXT TARGETS

<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Volume-> <Member> Tsys Aggr Amd ***

<Name> x <Name> x x<-factor->strg <Name> x <Name>qf tem strg strg***

***mult factor for rovol is 12/area

*** mult factor for others 1/area

RCHRES 2 OFLOW OVOL 1 .000685362 WDM 1120 FLOW ENGL REPL

RCHRES 2 HYDR O 1 WDM 1129 FLOW ENGL REPL

COPY 200 OUTPUT MEAN 1 .000057113 WDM 1121 SURO ENGL REPL

COPY 200 OUTPUT MEAN 2 .000057113 WDM 1122 IFWO ENGL REPL

COPY 200 OUTPUT MEAN 3 .000057113 WDM 1123 AGWO ENGL REPL

COPY 200 OUTPUT MEAN 4 .000057113 WDM 1124 PREC ENGL REPL

COPY 200 OUTPUT MEAN 5 .000057113 WDM 1125 PETX ENGL REPL

COPY 200 OUTPUT MEAN 6 .000057113 WDM 1126 TAET ENGL REPL

COPY 200 OUTPUT MEAN 7 .000057113 WDM 1127 UZSX ENGL REPL

COPY 200 OUTPUT MEAN 8 .000057113 WDM 1128 LZSX ENGL REPL

RCHRES 5 ROFLOW ROVOL .000418439 WDM 1110 FLOW ENGL REPL

RCHRES 5 HYDR RO WDM 1119 FLOW ENGL REPL

COPY 300 OUTPUT MEAN 1 .000034870 WDM 1111 SURO ENGL REPL

COPY 300 OUTPUT MEAN 2 .000034870 WDM 1112 IFWO ENGL REPL

COPY 300 OUTPUT MEAN 3 .000034870 WDM 1113 AGWO ENGL REPL

COPY 300 OUTPUT MEAN 4 .000034870 WDM 1114 PREC ENGL REPL

COPY 300 OUTPUT MEAN 5 .000034870 WDM 1115 PETX ENGL REPL

COPY 300 OUTPUT MEAN 6 .000034870 WDM 1116 TAET ENGL REPL

COPY 300 OUTPUT MEAN 7 .000034870 WDM 1117 UZSX ENGL REPL

COPY 300 OUTPUT MEAN 8 .000034870 WDM 1118 LZSX ENGL REPL

*** total loads from pervious and impervious areas above Wooodale

COPY 300 OUTPUT MEAN 10 1.00000000 WDM 2100 SOSED ENGL REPL

COPY 300 OUTPUT MEAN 11 1.00000000 WDM 2125 PONO3 ENGL REPL

COPY 300 OUTPUT MEAN 12 1.00000000 WDM 2126 PONH4 ENGL REPL

COPY 300 OUTPUT MEAN 13 1.00000000 WDM 2127 POPHOS ENGL REPL

COPY 300 OUTPUT MEAN 14 1.00000000 WDM 2130 SOSLD ENGL REPL

COPY 300 OUTPUT MEAN 15 1.00000000 WDM 2135 IONO3 ENGL REPL

COPY 300 OUTPUT MEAN 16 1.00000000 WDM 2136 IONH4 ENGL REPL

COPY 300 OUTPUT MEAN 17 1.00000000 WDM 2137 IOPHOS ENGL REPL

*** output for Reach 8 Stanton

RCHRES 8 OFLOW OVOL 1 .000373587 WDM 1100 FLOW ENGL REPL

RCHRES 8 HYDR O 1 WDM 1109 FLOW ENGL REPL

COPY 400 OUTPUT MEAN 1 .000031132 WDM 1101 SURO ENGL REPL

COPY 400 OUTPUT MEAN 2 .000031132 WDM 1102 IFWO ENGL REPL

COPY 400 OUTPUT MEAN 3 .000031132 WDM 1103 AGWO ENGL REPL

COPY 400 OUTPUT MEAN 4 .000031132 WDM 1104 PREC ENGL REPL

COPY 400 OUTPUT MEAN 5 .000031132 WDM 1105 PETX ENGL REPL

COPY 400 OUTPUT MEAN 6 .000031132 WDM 1106 TAET ENGL REPL

COPY 400 OUTPUT MEAN 7 .000031132 WDM 1107 UZSX ENGL REPL

COPY 400 OUTPUT MEAN 8 .000031132 WDM 1108 LZSX ENGL REPL

*** total loads from pervious and impervious areas above Stanton

COPY 400 OUTPUT MEAN 10 1.00000000 WDM 2200 SOSED ENGL REPL

COPY 400 OUTPUT MEAN 11 1.00000000 WDM 2225 PONO3 ENGL REPL

COPY 400 OUTPUT MEAN 12 1.00000000 WDM 2226 PONH4 ENGL REPL

COPY 400 OUTPUT MEAN 13 1.00000000 WDM 2227 POPHOS ENGL REPL

COPY 400 OUTPUT MEAN 14 1.00000000 WDM 2230 SOSLD ENGL REPL

COPY 400 OUTPUT MEAN 15 1.00000000 WDM 2235 IONO3 ENGL REPL

COPY 400 OUTPUT MEAN 16 1.00000000 WDM 2236 IONH4 ENGL REPL

COPY 400 OUTPUT MEAN 17 1.00000000 WDM 2237 IOPHOS ENGL REPL

***water temperature output

RCHRES 2 HTRCH TW WDM 1520 WTEM METR REPL

RCHRES 5 HTRCH TW WDM 1510 WTEM METR REPL

RCHRES 8 HTRCH TW WDM 1500 WTEM METR REPL

*** suspended sediment concentration output

RCHRES 1 SEDTRN SSED 4 WDM 1600 SEDC METR REPL

RCHRES 2 SEDTRN SSED 4 WDM 1620 SEDC METR REPL

RCHRES 3 SEDTRN SSED 4 WDM 1640 SEDC METR REPL

RCHRES 4 SEDTRN SSED 4 WDM 1660 SEDC METR REPL

RCHRES 5 SEDTRN SSED 4 WDM 1680 SEDC METR REPL

RCHRES 6 SEDTRN SSED 4 WDM 1700 SEDC METR REPL

RCHRES 8 SEDTRN SSED 4 WDM 1740 SEDC METR REPL

*** Water Quality

*** oxygen, bod, nutrients

RCHRES 1 OXRX DOX WDM 1601 DOXX METR REPL

RCHRES 1 OXRX BOD WDM 1602 BODX METR REPL

*** Dissolved NO3

RCHRES 1 NUTRX DNUST 1 WDM 1603 NO3X METR REPL
114 Appendix 2

*** Dissolved NH3

RCHRES 1 NUTRX DNUST 2 WDM 1604 NH4X METR REPL

*** Dissolved PO4

RCHRES 1 NUTRX DNUST 4 WDM 1605 PO4X METR REPL

*** particulate ammonia and phosphate

COPY 11 OUTPUT MEAN 1 *** WDM 1666 NH4P METR REPL

COPY 11 OUTPUT MEAN 2 *** WDM 1667 PO4P METR REPL

*** organic nitrogen and chlorophyll-A

RCHRES 1 PLANK PHYCLA 1 WDM 1608 PHCA METR REPL

RCHRES 1 PLANK PKST3 4 WDM 1609 TORN METR REPL

RCHRES 2 OXRX DOX WDM 1621 DOXX METR REPL

RCHRES 2 OXRX BOD WDM 1622 BODX METR REPL

RCHRES 2 NUTRX DNUST 1 WDM 1623 NO3X METR REPL

RCHRES 2 NUTRX DNUST 2 WDM 1624 NH4X METR REPL

RCHRES 2 NUTRX DNUST 4 WDM 1625 PO4X METR REPL

COPY 10 OUTPUT MEAN 1 WDM 1626 NH4P METR REPL

COPY 10 OUTPUT MEAN 2 WDM 1627 PO4P METR REPL

RCHRES 2 PLANK PHYCLA 1 WDM 1628 PHCA METR REPL

RCHRES 2 PLANK PKST3 4 WDM 1629 TORN METR REPL

RCHRES 3 OXRX DOX WDM 1641 DOXX METR REPL

RCHRES 3 OXRX BOD WDM 1642 BODX METR REPL

RCHRES 3 NUTRX DNUST 1 WDM 1643 NO3X METR REPL

RCHRES 3 NUTRX DNUST 2 WDM 1644 NH4X METR REPL

RCHRES 3 NUTRX DNUST 4 WDM 1645 PO4X METR REPL

COPY 11 OUTPUT MEAN 1 WDM 1666 NH4P METR REPL

COPY 11 OUTPUT MEAN 2 WDM 1667 PO4P METR REPL

RCHRES 3 PLANK PHYCLA 1 WDM 1648 PHCA METR REPL

RCHRES 3 PLANK PKST3 4 WDM 1649 TORN METR REPL

RCHRES 4 OXRX DOX WDM 1661 DOXX METR REPL

RCHRES 4 OXRX BOD WDM 1662 BODX METR REPL

RCHRES 4 NUTRX DNUST 1 WDM 1663 NO3X METR REPL

RCHRES 4 NUTRX DNUST 2 WDM 1664 NH4X METR REPL

RCHRES 4 NUTRX DNUST 4 WDM 1665 PO4X METR REPL

COPY 11 OUTPUT MEAN 1 WDM 1666 NH4P METR REPL

COPY 11 OUTPUT MEAN 2 WDM 1667 PO4P METR REPL

RCHRES 4 PLANK PHYCLA 1 WDM 1668 PHCA METR REPL

RCHRES 4 PLANK PKST3 4 WDM 1669 TORN METR REPL

RCHRES 5 OXRX DOX WDM 1681 DOXX METR REPL

RCHRES 5 OXRX BOD WDM 1682 BODX METR REPL

RCHRES 5 NUTRX DNUST 1 WDM 1683 NO3X METR REPL

RCHRES 5 NUTRX DNUST 2 WDM 1684 NH4X METR REPL

RCHRES 5 NUTRX DNUST 4 WDM 1685 PO4X METR REPL

COPY 12 OUTPUT MEAN 1 WDM 1686 NH4P METR REPL

COPY 12 OUTPUT MEAN 2 WDM 1687 PO4P METR REPL

RCHRES 5 PLANK PHYCLA 1 WDM 1688 PHCA METR REPL

RCHRES 5 PLANK PKST3 4 WDM 1689 TORN METR REPL

RCHRES 6 OXRX DOX WDM 1701 DOXX METR REPL

RCHRES 6 OXRX BOD WDM 1702 BODX METR REPL

RCHRES 6 NUTRX DNUST 1 WDM 1703 NO3X METR REPL

RCHRES 6 NUTRX DNUST 2 WDM 1704 NH4X METR REPL

RCHRES 6 NUTRX DNUST 4 WDM 1705 PO4X METR REPL

COPY 14 OUTPUT MEAN 1 WDM 1706 NH4P METR REPL

COPY 14 OUTPUT MEAN 2 WDM 1707 PO4P METR REPL

RCHRES 6 PLANK PHYCLA 1 WDM 1708 PHCA METR REPL

RCHRES 6 PLANK PKST3 4 WDM 1709 TORN METR REPL

RCHRES 8 OXRX DOX WDM 1741 DOXX METR REPL

RCHRES 8 OXRX BOD WDM 1742 BODX METR REPL

RCHRES 8 NUTRX DNUST 1 WDM 1743 NO3X METR REPL

RCHRES 8 NUTRX DNUST 2 WDM 1744 NH4X METR REPL

RCHRES 8 NUTRX DNUST 4 WDM 1745 PO4X METR REPL

COPY 14 OUTPUT MEAN 1 WDM 1746 NH4P METR REPL

COPY 14 OUTPUT MEAN 2 WDM 1747 PO4P METR REPL

RCHRES 8 PLANK PHYCLA 1 WDM 1748 PHCA METR REPL

RCHRES 8 PLANK PKST3 4 WDM 1749 TORN METR REPL

*** sediment calibration data sets

RCHRES 1 HYDR TAU WDM 9001 TAU ENGL REPL

RCHRES 2 HYDR TAU WDM 9002 TAU ENGL REPL

RCHRES 3 HYDR TAU WDM 9003 TAU ENGL REPL

RCHRES 4 HYDR TAU WDM 9004 TAU ENGL REPL

RCHRES 5 HYDR TAU WDM 9005 TAU ENGL REPL

RCHRES 6 HYDR TAU WDM 9006 TAU ENGL REPL

RCHRES 7 HYDR TAU WDM 9007 TAU ENGL REPL

RCHRES 8 HYDR TAU WDM 9008 TAU ENGL REPL

RCHRES 9 HYDR TAU WDM 9009 TAU ENGL REPL

PERLND 702 SEDMNT DETS WDM 9023 DETS ENGL REPL

PERLND 703 SEDMNT DETS WDM 9026 DETS ENGL REPL

PERLND 704 SEDMNT DETS WDM 9027 DETS ENGL REPL

PERLND 705 SEDMNT DETS WDM 9028 DETS ENGL REPL

PERLND 706 SEDMNT DETS WDM 9029 DETS ENGL REPL

PERLND 707 SEDMNT DETS WDM 9030 DETS ENGL REPL

PERLND 708 SEDMNT DETS WDM 9031 DETS ENGL REPL

PERLND 709 SEDMNT DETS WDM 9032 DETS ENGL REPL

PERLND 710 SEDMNT DETS WDM 9033 DETS ENGL REPL

PERLND 711 SEDMNT DETS WDM 9034 DETS ENGL REPL

PERLND 402 SEDMNT DETS WDM 9035 DETS ENGL REPL

PERLND 403 SEDMNT DETS WDM 9036 DETS ENGL REPL

PERLND 404 SEDMNT DETS WDM 9037 DETS ENGL REPL

PERLND 405 SEDMNT DETS WDM 9038 DETS ENGL REPL

PERLND 406 SEDMNT DETS WDM 9039 DETS ENGL REPL

PERLND 407 SEDMNT DETS WDM 9040 DETS ENGL REPL
Appendix 2 115

PERLND 408 SEDMNT DETS WDM 9041 DETS ENGL REPL

PERLND 409 SEDMNT DETS WDM 9042 DETS ENGL REPL

PERLND 410 SEDMNT DETS WDM 9043 DETS ENGL REPL

PERLND 411 SEDMNT DETS WDM 9044 DETS ENGL REPL

PERLND 602 SEDMNT DETS WDM 9045 DETS ENGL REPL

PERLND 603 SEDMNT DETS WDM 9046 DETS ENGL REPL

PERLND 604 SEDMNT DETS WDM 9047 DETS ENGL REPL

PERLND 605 SEDMNT DETS WDM 9048 DETS ENGL REPL

PERLND 606 SEDMNT DETS WDM 9049 DETS ENGL REPL

PERLND 607 SEDMNT DETS WDM 9050 DETS ENGL REPL

PERLND 608 SEDMNT DETS WDM 9051 DETS ENGL REPL

PERLND 609 SEDMNT DETS WDM 9052 DETS ENGL REPL

PERLND 610 SEDMNT DETS WDM 9053 DETS ENGL REPL

PERLND 611 SEDMNT DETS WDM 9054 DETS ENGL REPL

END EXT TARGETS

SCHEMATIC

<-Source-> <--Area--> <-Target-> <ML> ***

<Name> # <-factor-> <Name> # # ***

*** Note: All PLS-RCH and ILS-RCH multiplication factors are acres.

*** Conversion factors, where applicable, are in Mass-Link.

***

*** Segment & (Upper Red Clay)

*** Tributary to Reach 1 (Upper West Br.)

PERLND 702 669.7700 RCHRES 1 1

PERLND 703 103.100 RCHRES 1 1

PERLND 704 138.210 RCHRES 1 1

PERLND 705 377.356 RCHRES 1 1

*** original mushroom area estimate

PERLND 706 3018.848 RCHRES 1 1

PERLND 707 377.356 RCHRES 1 1

***

PERLND 708 1187.260 RCHRES 1 1

PERLND 709 180.470 RCHRES 1 1

PERLND 710 28.470 RCHRES 1 1

PERLND 711 107.490 RCHRES 1 1

IMPLND 701 118.260 RCHRES 1 2

IMPLND 702 141.840 RCHRES 1 2

*** Tributary to Reach 2 (Lower W.Br. to Kennett gage)

PERLND 702 556.810 RCHRES 2 1

PERLND 703 23.820 RCHRES 2 1

PERLND 704 31.450 RCHRES 2 1

PERLND 705 0.000 RCHRES 2 1

***original mushroom estimate

PERLND 706 1934.016 RCHRES 2 1

PERLND 707 828.864 RCHRES 2 1

***

PERLND 708 1192.800 RCHRES 2 1

PERLND 709 12.640 RCHRES 2 1

PERLND 710 10.450 RCHRES 2 1

PERLND 711 30.920 RCHRES 2 1

IMPLND 701 72.080 RCHRES 2 2

IMPLND 702 33.150 RCHRES 2 2

*** Tributary to Reach 3 (East Br. to conf W.Br)

PERLND 702 943.250 RCHRES 3 1

PERLND 703 122.940 RCHRES 3 1

PERLND 704 64.000 RCHRES 3 1

PERLND 705 0.000 RCHRES 3 1

***original mushroom estimate

PERLND 706 2098.173 RCHRES 3 1

PERLND 707 899.217 RCHRES 3 1

***

PERLND 708 1425.110 RCHRES 3 1

PERLND 709 368.250 RCHRES 3 1

PERLND 710 38.470 RCHRES 3 1

PERLND 711 148.400 RCHRES 3 1

IMPLND 701 157.490 RCHRES 3 2

IMPLND 702 68.690 RCHRES 3 2

 Reach Connections ***

RCHRES 1 RCHRES 2 3

RCHRES 3 RCHRES 2 4

RCHRES 2 RCHRES 4 4

*** Segment 4 (East Br. and mainstem Red Clay)

*** Tributary to Reach 4 (Kennett gage to Ashland)

PERLND 402 1161.330 RCHRES 4 1

PERLND 403 75.870 RCHRES 4 1

PERLND 404 32.700 RCHRES 4 1

PERLND 405 57.504 RCHRES 4 1

PERLND 406 460.032 RCHRES 4 1

PERLND 407 57.504 RCHRES 4 1

PERLND 408 930.100 RCHRES 4 1

PERLND 409 257.520 RCHRES 4 1

PERLND 410 26.440 RCHRES 4 1

PERLND 411 18.770 RCHRES 4 1

IMPLND 401 161.550 RCHRES 4 2

IMPLND 402 32.910 RCHRES 4 2
116 Appendix 2

*** Tributary to Reach 5 (Ashland to Wooddale gage)

PERLND 402 1079.360 RCHRES 5 1

PERLND 403 74.560 RCHRES 5 1

PERLND 404 9.330 RCHRES 5 1

PERLND 405 0.000 RCHRES 5 1

PERLND 406 492.060 RCHRES 5 1

PERLND 407 0.000 RCHRES 5 1

PERLND 408 1266.250 RCHRES 5 1

PERLND 409 199.560 RCHRES 5 1

PERLND 410 40.640 RCHRES 5 1

PERLND 411 29.100 RCHRES 5 1

IMPLND 401 151.890 RCHRES 5 2

IMPLND 402 10.320 RCHRES 5 2

*** Tributary to Reach 6 (Burroughs Run)

PERLND 402 1085.790 RCHRES 6 1

PERLND 403 0.000 RCHRES 6 1

PERLND 404 8.550 RCHRES 6 1

PERLND 405 0.000 RCHRES 6 1

*** original ag land

PERLND 406 1928.530 RCHRES 6 1

***

PERLND 407 0.000 RCHRES 6 1

PERLND 408 1140.260 RCHRES 6 1

***original open

PERLND 409 232.900 RCHRES 6 1

***

PERLND 410 6.010 RCHRES 6 1

PERLND 411 12.480 RCHRES 6 1

IMPLND 401 120.640 RCHRES 6 2

IMPLND 402 8.550 RCHRES 6 2

*** Tributary to Reach 7 (Hoopes Reservoir)

PERLND 402 *** 350.380 RCHRES 7 1

PERLND 403 *** 0.440 RCHRES 7 1

PERLND 404 *** 6.420 RCHRES 7 1

PERLND 405 *** 0 RCHRES 7 1

PERLND 406 *** 97.200 RCHRES 7 1

PERLND 407 *** 0 RCHRES 7 1

PERLND 408 *** 596.300 RCHRES 7 1

PERLND 409 *** 39.980 RCHRES 7 1

PERLND 410 *** 192.370 RCHRES 7 1

PERLND 411 *** 14.930 RCHRES 7 1

IMPLND 401 *** 39.120 RCHRES 7 2

IMPLND 402 *** 6.450 RCHRES 7 2

 Reach Connections ***

RCHRES 4 RCHRES 5 4

RCHRES 6 RCHRES 5 3

RCHRES 7 *** RCHRES 5 3

RCHRES 5 RCHRES 8 3

***

*** Segment 6 (Wooddale gage to confl.)

*** Tributary to Reach 8 (Wooddale to Stanton gage)

PERLND 602 52.700 RCHRES 8 1

PERLND 603 1215.470 RCHRES 8 1

PERLND 604 182.160 RCHRES 8 1

PERLND 605 0.000 RCHRES 8 1

PERLND 606 54.610 RCHRES 8 1

PERLND 607 0.000 RCHRES 8 1

PERLND 608 464.550 RCHRES 8 1

PERLND 609 475.640 RCHRES 8 1

PERLND 610 47.930 RCHRES 8 1

PERLND 611 216.950 RCHRES 8 1

IMPLND 601 526.770 RCHRES 8 2

IMPLND 602 206.210 RCHRES 8 2

*** Tributary to Reach 9 (Stanton gage to confl.)

PERLND 602 0.040 RCHRES 9 1

PERLND 603 501.850 RCHRES 9 1

PERLND 604 52.640 RCHRES 9 1

PERLND 605 0 RCHRES 9 1

PERLND 606 0 RCHRES 9 1

PERLND 607 0 RCHRES 9 1

PERLND 608 112.890 RCHRES 9 1

PERLND 609 41.680 RCHRES 9 1

PERLND 610 4.860 RCHRES 9 1

PERLND 611 109.470 RCHRES 9 1

IMPLND 601 215.080 RCHRES 9 2

IMPLND 602 64.800 RCHRES 9 2

 Reach Connections ***

RCHRES 8 RCHRES 9 4

*** HSPEXP ***

 Kennett Sq. gage - Output from Reach 2 ***

PERLND 702 2169.830 COPY 200 91

PERLND 703 249.890 COPY 200 91

PERLND 704 233.660 COPY 200 91

PERLND 705 377.356 COPY 200 91

PERLND 706 7051.037 COPY 200 91

PERLND 707 2105.437 COPY 200 91

PERLND 708 3805.170 COPY 200 91
Appendix 2 117

PERLND 709 561.360 COPY 200 91

PERLND 710 77.390 COPY 200 91

PERLND 711 286.810 COPY 200 91

IMPLND 701 347.830 COPY 200 92

IMPLND 702 243.680 COPY 200 92

 Red Clay at Wooddale gage - Output from reach 5 ***

PERLND 702 2169.830 COPY 300 91

PERLND 703 249.890 COPY 300 91

PERLND 704 233.660 COPY 300 91

PERLND 705 377.356 COPY 300 91

PERLND 706 7051.037 COPY 300 91

PERLND 707 2105.437 COPY 300 91

PERLND 708 3805.170 COPY 300 91

PERLND 709 561.360 COPY 300 91

PERLND 710 77.390 COPY 300 91

PERLND 711 286.810 COPY 300 91

IMPLND 701 347.830 COPY 300 92

IMPLND 702 243.680 COPY 300 92

PERLND 402 3326.480 COPY 300 91

PERLND 403 150.430 COPY 300 91

PERLND 404 50.580 COPY 300 91

PERLND 405 57.504 COPY 300 91

PERLND 406 2880.682 COPY 300 91

PERLND 407 57.504 COPY 300 91

PERLND 408 3336.610 COPY 300 91

PERLND 409 689.980 COPY 300 91

PERLND 410 73.090 COPY 300 91

PERLND 411 60.350 COPY 300 91

IMPLND 401 434.080 COPY 300 92

IMPLND 402 51.780 COPY 300 92

 Red Clay at Stanton gage output from reach 8 ***

PERLND 702 2169.830 COPY 400 91

PERLND 703 249.890 COPY 400 91

PERLND 704 233.660 COPY 400 91

PERLND 705 377.356 COPY 400 91

PERLND 706 7051.037 COPY 400 91

PERLND 707 2105.437 COPY 400 91

PERLND 708 3805.170 COPY 400 91

PERLND 709 561.360 COPY 400 91

PERLND 710 77.390 COPY 400 91

PERLND 711 286.810 COPY 400 91

IMPLND 701 347.830 COPY 400 92

IMPLND 702 243.680 COPY 400 92

PERLND 402 3326.480 COPY 400 91

PERLND 403 150.430 COPY 400 91

PERLND 404 50.580 COPY 400 91

PERLND 405 57.504 COPY 400 91

PERLND 406 2880.682 COPY 400 91

PERLND 407 57.504 COPY 400 91

PERLND 408 3336.610 COPY 400 91

PERLND 409 689.980 COPY 400 91

PERLND 410 73.090 COPY 400 91

PERLND 411 60.350 COPY 400 91

IMPLND 401 434.080 COPY 400 92

IMPLND 402 51.780 COPY 400 92

PERLND 602 52.70 COPY 400 91

PERLND 603 1215.47 COPY 400 91

PERLND 604 182.16 COPY 400 91

PERLND 605 0 COPY 400 91

PERLND 606 54.610 COPY 400 91

PERLND 607 0 COPY 400 91

PERLND 608 464.55 COPY 400 91

PERLND 609 475.64 COPY 400 91

PERLND 610 47.93 COPY 400 91

PERLND 611 216.95 COPY 400 91

IMPLND 601 526.77 COPY 400 92

IMPLND 602 206.21 COPY 400 92

END SCHEMATIC

MASS-LINK

 MASS-LINK 1

<Srce> <-Grp> <-Member-><--Mult--> <Targ> <-Grp> <-Member-> ***

<Name> <Name> <Name> # #<-factor-> <Name> <Name> <Name> # # ***

PERLND PWATER PERO 0.0833333 RCHRES INFLOW IVOL

PERLND SEDMNT SOSED 0.10 RCHRES INFLOW ISED 1

PERLND SEDMNT SOSED 0.40 RCHRES INFLOW ISED 2

PERLND SEDMNT SOSED 0.50 RCHRES INFLOW ISED 3

PERLND PWTGAS POHT RCHRES INFLOW IHEAT

PERLND PWTGAS PODOXM RCHRES INFLOW OXIF 1

PERLND PQUAL POQUAL 1 RCHRES INFLOW NUIF1 1

PERLND PQUAL POQUAL 2 RCHRES INFLOW NUIF1 2

PERLND PQUAL POQUAL 3 RCHRES INFLOW NUIF1 4

PERLND PQUAL POQUAL 4 RCHRES INFLOW OXIF 2

PERLND PQUAL POQUAL 5 RCHRES INFLOW PKIF 3

 END MASS-LINK 1

 MASS-LINK 2

<Srce> <-Grp> <-Member-><--Mult--> <Targ> <-Grp> <-Member-> ***

<Name> <Name> <Name> # #<-factor-> <Name> <Name> <Name> # # ***

IMPLND IWATER SURO 0.0833333 RCHRES INFLOW IVOL

IMPLND SOLIDS SOSLD 0.10 RCHRES INFLOW ISED 1

IMPLND SOLIDS SOSLD 0.40 RCHRES INFLOW ISED 2
118 Appendix 2

IMPLND SOLIDS SOSLD 0.50 RCHRES INFLOW ISED 3

IMPLND IWTGAS SOHT RCHRES INFLOW IHEAT

IMPLND IWTGAS SODOXM RCHRES INFLOW OXIF 1

IMPLND IQUAL SOQUAL 1 RCHRES INFLOW NUIF1 1

IMPLND IQUAL SOQUAL 2 RCHRES INFLOW NUIF1 2

IMPLND IQUAL SOQUAL 3 RCHRES INFLOW NUIF1 4

IMPLND IQUAL SOQUAL 4 RCHRES INFLOW OXIF 2

 END MASS-LINK 2

 MASS-LINK 3

<Srce> <-Grp> <-Member-><--Mult--> <Targ> <-Grp> <-Member-> ***

<Name> <Name> <Name> # #<-factor-> <Name> <Name> <Name> # # ***

RCHRES ROFLOW RCHRES INFLOW

 END MASS-LINK 3

 MASS-LINK 4

<Srce> <-Grp> <-Member-><--Mult--> <Targ> <-Grp> <-Member-> ***

<Name> <Name> <Name> # #<-factor-> <Name> <Name> <Name> # # ***

RCHRES OFLOW 1 RCHRES INFLOW

 END MASS-LINK 4

 MASS-LINK 91

<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Target vols> <-Grp> <-Member-> ***

<Name> <Name> x x<-factor->strg <Name> <Name> x x ***

PERLND PWATER SURO COPY INPUT MEAN 1

PERLND PWATER IFWO COPY INPUT MEAN 2

PERLND PWATER AGWO COPY INPUT MEAN 3

PERLND PWATER PET COPY INPUT MEAN 5

PERLND PWATER TAET COPY INPUT MEAN 6

PERLND PWATER UZS COPY INPUT MEAN 7

PERLND PWATER LZS COPY INPUT MEAN 8

PERLND PWATER AGWS COPY INPUT MEAN 9

PERLND SEDMNT SOSED COPY INPUT MEAN 10

PERLND PQUAL POQUAL 1 COPY INPUT MEAN 11

PERLND PQUAL POQUAL 2 COPY INPUT MEAN 12

PERLND PQUAL POQUAL 3 COPY INPUT MEAN 13

 END MASS-LINK 91

 MASS-LINK 92

<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Target vols> <-Grp> <-Member-> ***

<Name> <Name> x x<-factor->strg <Name> <Name> x x ***

IMPLND IWATER SURO COPY INPUT MEAN 1

IMPLND IWATER PET COPY INPUT MEAN 5

IMPLND IWATER IMPEV COPY INPUT MEAN 6

IMPLND SOLIDS SOSLD COPY INPUT MEAN 14

IMPLND IQUAL SOQUAL 1 COPY INPUT MEAN 15

IMPLND IQUAL SOQUAL 2 COPY INPUT MEAN 16

IMPLND IQUAL SOQUAL 3 COPY INPUT MEAN 17

 END MASS-LINK 92

 MASS-LINK 93

<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Target vols> <-Grp> <-Member-> ***

<Name> <Name> x x<-factor->strg <Name> <Name> x x ***

COPY OUTPUT MEAN 1 COPY INPUT MEAN 1

COPY OUTPUT MEAN 2 COPY INPUT MEAN 2

COPY OUTPUT MEAN 3 COPY INPUT MEAN 3

COPY OUTPUT MEAN 4 COPY INPUT MEAN 4

COPY OUTPUT MEAN 5 COPY INPUT MEAN 5

COPY OUTPUT MEAN 6 COPY INPUT MEAN 6

COPY OUTPUT MEAN 7 COPY INPUT MEAN 7

COPY OUTPUT MEAN 8 COPY INPUT MEAN 8

COPY OUTPUT MEAN 9 COPY INPUT MEAN 9

COPY OUTPUT MEAN 10 COPY INPUT MEAN 10

COPY OUTPUT MEAN 11 COPY INPUT MEAN 11

COPY OUTPUT MEAN 12 COPY INPUT MEAN 12

COPY OUTPUT MEAN 13 COPY INPUT MEAN 13

COPY OUTPUT MEAN 14 COPY INPUT MEAN 14

COPY OUTPUT MEAN 15 COPY INPUT MEAN 15

COPY OUTPUT MEAN 16 COPY INPUT MEAN 16

COPY OUTPUT MEAN 17 COPY INPUT MEAN 17

 END MASS-LINK 93

END MASS-LINK

NETWORK

<-Volume-> <-Grp> <-Member-><--Mult-->Tran <-Target vols> <-Grp> <-Member-> ***

<Name> # <Name> # #<-factor->strg <Name> # # <Name> # # ***

*** Results for calibration

 PARTICULATE N (ADSORBED NH3 + ORG N) ***

RCHRES 2 NUTRX RSNH4 4 GENER 1 INPUT ONE

RCHRES 2 HYDR VOL GENER 1 INPUT TWO

GENER 1 OUTPUT TIMSER 0.368 COPY 10 INPUT MEAN 1

RCHRES 4 NUTRX RSNH4 4 GENER 3 INPUT ONE

RCHRES 4 HYDR VOL GENER 3 INPUT TWO

GENER 3 OUTPUT TIMSER 0.368 COPY 11 INPUT MEAN 1

RCHRES 5 NUTRX RSNH4 4 GENER 5 INPUT ONE

RCHRES 5 HYDR VOL GENER 5 INPUT TWO

GENER 5 OUTPUT TIMSER 0.368 COPY 12 INPUT MEAN 1

RCHRES 6 NUTRX RSNH4 4 GENER 7 INPUT ONE

RCHRES 6 HYDR VOL GENER 7 INPUT TWO

GENER 7 OUTPUT TIMSER 0.368 COPY 13 INPUT MEAN 1

RCHRES 8 NUTRX RSNH4 4 GENER 9 INPUT ONE
Appendix 2 119

RCHRES 8 HYDR VOL GENER 9 INPUT TWO

GENER 9 OUTPUT TIMSER 0.368 COPY 14 INPUT MEAN 1

 PARTICULATE P (ADSORBED PO4 + ORG P) ***

RCHRES 2 NUTRX RSPO4 4 GENER 2 INPUT ONE

RCHRES 2 HYDR VOL GENER 2 INPUT TWO

GENER 2 OUTPUT TIMSER 0.368 COPY 10 INPUT MEAN 2

RCHRES 4 NUTRX RSPO4 4 GENER 4 INPUT ONE

RCHRES 4 HYDR VOL GENER 4 INPUT TWO

GENER 4 OUTPUT TIMSER 0.368 COPY 11 INPUT MEAN 2

RCHRES 5 NUTRX RSPO4 4 GENER 6 INPUT ONE

RCHRES 5 HYDR VOL GENER 6 INPUT TWO

GENER 6 OUTPUT TIMSER 0.368 COPY 12 INPUT MEAN 2

RCHRES 6 NUTRX RSPO4 4 GENER 8 INPUT ONE

RCHRES 6 HYDR VOL GENER 8 INPUT TWO

GENER 8 OUTPUT TIMSER 0.368 COPY 13 INPUT MEAN 2

RCHRES 8 NUTRX RSPO4 4 GENER 10 INPUT ONE

RCHRES 8 HYDR VOL GENER 10 INPUT TWO

GENER 10 OUTPUT TIMSER 0.368 COPY 14 INPUT MEAN 2

END NETWORK

GENER

 OPCODE

 #thru# code ***

 1 14 19

 END OPCODE

END GENER

END RUN