A Decision Support Framework for Water Management in 

the Upper Delaware River 

By Ken D. Bovee, Terry J. Waddle, John Bartholow, and Lucy Burris 

Open-File Report 2007-1172 

U.S. Department of the Interior 

U.S. Geological Survey 
ii

U.S. Department of the Interior 

DIRK KEMPTHORNE, Secretary 

U.S. Geological Survey 

Mark D. Myers, Director 

U.S. Geological Survey, Reston, Virginia 2007 

For product and ordering information: 

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

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its natural and living resources, natural hazards, and the environment: 

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Telephone: 1-888-ASK-USGS 

Suggested citation: 

Bovee, K.D., Waddle, T.J., Bartholow, J., and Burris, L., 2007, A decision support framework for water 

management in the upper Delaware River: U.S. Geological Survey Open-File Report 2007-1172, 122 p. 

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

endorsement by the U.S. Government. 

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

copyright owners to reproduce any copyrighted material contained within this report. 
iii

Contents 

Contents ..............................................................................................................................................................................iii

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

Montague Target Formula ............................................................................................................................................3

Minimum Reservoir Releases.......................................................................................................................................3

New York City Department of Environmental Protection Operating Decisions ..................................................3

Operating Rule Curves ...................................................................................................................................................3

Reservoir Capacity .........................................................................................................................................................4

Goals and Objectives .........................................................................................................................................................4

Study Segments, Resource Issues, and Site Selection...............................................................................................4

Resource Issues .............................................................................................................................................................5

Site Selection ..................................................................................................................................................................7

Methods ...............................................................................................................................................................................7

Habitat Patch Metrics....................................................................................................................................................8

Bathymetric Data........................................................................................................................................................8

Data Preparation.........................................................................................................................................................9

Conversion of Echosounder Depths to Elevations............................................................................................9

Quality Control for Echosounder Data.................................................................................................................9

Bed Topography....................................................................................................................................................10

Computational Mesh ............................................................................................................................................10

Boundary Conditions ............................................................................................................................................11

Model Calibration..................................................................................................................................................11

Simulation of Unmeasured Discharges ............................................................................................................12

Habitat Classification ...............................................................................................................................................12

Geographic Information System Operations .......................................................................................................13

The Hydraulic Habitat Layer................................................................................................................................13

The Mesohabitat Layer........................................................................................................................................14

Habitat Persistence ..............................................................................................................................................15

Temperature Analysis..................................................................................................................................................17

Model Selection ........................................................................................................................................................18

Data Gathering and Synthesis................................................................................................................................18

Quality Assurance/Quality Control.........................................................................................................................20

Initial Model Simulations.........................................................................................................................................20

Model Calibration......................................................................................................................................................20

Development of Statistical Models .......................................................................................................................21

Model Selection for the DRDSS .............................................................................................................................22

Time Series Generation and Summarization ...........................................................................................................23

Habitat Time Series and Metrics ...........................................................................................................................23

Hydroperiods and Habitat Persistence.................................................................................................................23

Habitat Duration Statistics ......................................................................................................................................25

Habitat Duration Series ...........................................................................................................................................25

Structure and Functions of the DRDSS.....................................................................................................................27

Structure and Organization.....................................................................................................................................27
iv

Functionality...............................................................................................................................................................27

Habitat Time Series Metrics ...............................................................................................................................27

Temperature...........................................................................................................................................................28

Spills ........................................................................................................................................................................29

Storage Volume.....................................................................................................................................................29

Montague Deliveries ............................................................................................................................................29

Out of System Deliveries......................................................................................................................................29

DRDSS Output and Displays ...................................................................................................................................29

The Summary Scoring Page................................................................................................................................30

The Raw Scores Page..........................................................................................................................................33

Flow and Storage Time Series Graphics ..........................................................................................................34

Flow, Temperature, and Storage Duration Curves .........................................................................................34

Habitat Duration Series Graphics ......................................................................................................................36

Results ................................................................................................................................................................................37

Habitat Versus Discharge Functions.........................................................................................................................37

Mesohabitat Versus Discharge .................................................................................................................................42

Habitat Persistence......................................................................................................................................................47

Trout Spawning and Incubation.............................................................................................................................47

Dwarf Wedgemussel................................................................................................................................................54

DRDSS Demonstration Run.............................................................................................................................................58

Discussion..........................................................................................................................................................................60

Interpretation of Results..............................................................................................................................................61

Evaluation of Results....................................................................................................................................................62

Establishing Context.................................................................................................................................................63

Adaptable Management Objectives......................................................................................................................64

Contingency Planning ..............................................................................................................................................64

Model Limitations and Assumptions .........................................................................................................................65

Decision Support and Adaptive Management ........................................................................................................66

Acknowledgements .........................................................................................................................................................67

References Cited ..............................................................................................................................................................68

Appendix 1. Proportional Planform Comparisons for Sites and Segments of the Upper Delaware River.......71

Appendix 2. Final Calibration Results for the River2D Hydraulic Simulation Model at Study Sites in the 

Upper Delaware River. ....................................................................................................................................................76

Appendix 3. Discharge Versus Habitat Area Statistics for Study Sites in the Upper Delaware River. ............83

Appendix 4. Habitat Persistence Tables for Brown Trout (Salmo trutta) Spawning – Incubation and Dwarf 

Wedgemussels (Alasmidonta heterodon)....................................................................................................................93

Appendix 5. User Documentation for the Delaware River Decision Support System .......................................109

Getting Started ............................................................................................................................................................109

Preparing Input Data..................................................................................................................................................109

Importing Data from OASIS to DRDSS................................................................................................................109

Preparing Data for Import from OASIS ...........................................................................................................110

Exporting Data to the DRDSS............................................................................................................................110

Importing Meteorological Data............................................................................................................................113

Setting the Scoring Parameters and Related Information on the “Parameters” Page. ............................115

Making a DSS Run......................................................................................................................................................116
v

Generating Graphics and Displays..........................................................................................................................116

Scoring Summary and Raw Scores Pages ........................................................................................................117

Flow, Storage, and Temperature Duration Curves ...........................................................................................117

Duration Series Curves..........................................................................................................................................118

Flow Plots .................................................................................................................................................................119

The Raw Scores Page............................................................................................................................................119

Information Management .........................................................................................................................................120

Figures 

Figure 1. Tristate map of the Delaware River Basin (Scale = 1:1,500,000)...............................................................1

Figure 2. Upper Delaware River and reservoirs (Scale = 1:500,000). ........................................................................2

Figure 3. Segmentation and study site locations in the upper Delaware Basin.....................................................5

Figure 4. Error distribution of streambed elevations derived from echosounder data compared with those 

obtained by direct survey methods...............................................................................................................................10

Figure 5. Digital representation of a pool tailout. Deepest portion of pool indicated by dark blue polygon and 

crest of riffle by compressed contours of water surface elevations......................................................................14

Figure 6. Illustration of a persistence map for a spawning discharge of 10 m3

/s (350 ft3/s) and an incubation 

discharge of 2.5 m3/s (88 ft3/s).........................................................................................................................................16

Figure 7. Elements used in the construction of a habitat time series: A, flow time series, B, flow versus 

habitat function, and C, the resulting habitat time series. ........................................................................................24

Figure 8. Comparison of habitat duration series for baseline and alternative scenarios...................................26

Figure 9. Layout and information flow in DRDSS Version 2.11.................................................................................28

Figure 10. Layout of the scoring summary page in the DRDSS................................................................................30

Figure 11. Expanded view of the scoring summary page, showing details of the scores and metrics for 

biological resources and spills in the DRDSS.............................................................................................................32

Figure 12. Expanded view of the scoring summary page, showing details of the scores and metrics for the 

full period and global resources in the DRDSS...........................................................................................................32

Figure 13. Expanded view of the “Raw scores” page showing details of the segment-specific scores and 

metrics for habitat and temperature decision variables...........................................................................................33

Figure 14. Time series of daily storage volumes and segment discharges from the “FlowPlots” page of the 

DSS_AGG.xls master spreadsheet................................................................................................................................34

Figure 15. Example flow duration curves for site WB0. The Y-axis was truncated at 3,000 cubic feet per 

second in order to amplify the differences in the lower flow range.......................................................................35

Figure 16. The “DurCurve” page of one of the subsidiary workbooks of the DRDSS, showing locations and 

functions of control buttons used to update a duration chart. ................................................................................36

Figure 17. The “DurSer” page of one of the subsidiary workbooks of the DRDSS, showing locations and 

functions of control buttons used to update a duration series chart. ....................................................................37

Figure 18. Normalized discharge versus unit habitat areas for the shallow-slow current velocity guild at 11 

sites in the upper Delaware River. ................................................................................................................................39

Figure 19. Normalized discharge versus unit habitat areas for the shallow-fast current velocity guild at 11 

sites in the upper Delaware River. ................................................................................................................................39

Figure 20. Normalized discharge versus unit habitat areas for juvenile trout (Salmo trutta) at 11 sites in the 

upper Delaware River......................................................................................................................................................40
vi

Figure 21. Normalized discharge versus unit habitat areas for juvenile American shad (Alosa sapidissima) 

at four sites in the upper Delaware River. ...................................................................................................................40

Figure 22. Normalized discharge versus unit habitat areas for adult trout (Salmo trutta) at 11 sites in the 

upper Delaware River......................................................................................................................................................41

Figure 23. Normalized discharge versus unit habitat areas for spawning American shad (Alosa sapidissima) 

at four sites in the upper Delaware River. ...................................................................................................................41

Figure 24. Normalized discharge versus unit areas of pool mesohabitat types...................................................42

Figure 25. Normalized discharge versus unit areas of fast run mesohabitat types.............................................43

Figure 26. Normalized discharge versus unit areas of run mesohabitat types.....................................................43

Figure 27. Normalized discharge versus unit areas of riffle mesohabitat types. .................................................44

Figure 28. Normalized discharge versus unit areas of inundated vegetation.......................................................44

Figure 29. Normalized discharge versus unit areas of side arm mesohabitat types. ..........................................45

Figure 30. Backwaters and disconnected channels at 25 ft3

/s (0.7 m3/s) in site EB0. ..........................................46

Figure 31. Normalized discharge versus unit areas of backwaters mesohabitat types. ....................................46

Figure 32. Normalized discharge versus unit areas of disconnected mesohabitat types. .................................47

Figure 33. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawning-incubation 

habitat at site WB0...........................................................................................................................................................49

Figure 34. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawning-incubation 

habitat at site WB1...........................................................................................................................................................49

Figure 35. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawning-incubation 

habitat at site EB0.............................................................................................................................................................50

Figure 36. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawning-incubation 

habitat at site EB1.............................................................................................................................................................50

Figure 37. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawning-incubation 

habitat at site EB2.............................................................................................................................................................51

Figure 38. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawning-incubation 

habitat at site DEL1...........................................................................................................................................................51

Figure 39. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawning-incubation 

habitat at site DEL2...........................................................................................................................................................52

Figure 40. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawning-incubation 

habitat at site DEL3...........................................................................................................................................................52

Figure 41. Normalized discharge versus unit area of persistent (Salmo trutta) trout spawning-incubation 

habitat at site NVR0..........................................................................................................................................................53

Figure 42. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawning-incubation 

habitat at site NVR1..........................................................................................................................................................53

Figure 43. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawning-incubation 

habitat at site NVR2..........................................................................................................................................................54

Figure 44. Normalized discharge versus area of persistent dwarf wedgemussel (Alasmidonta heterodon) 

habitat at site DEL1...........................................................................................................................................................55

Figure 45. Normalized discharge versus area of persistent dwarf wedgemussel (Alasmidonta heterodon) 

habitat at site DEL2...........................................................................................................................................................55

Figure 46. Normalized discharge versus area of persistent dwarf wedgemussel (Alasmidonta heterodon) 

habitat at site DEL3...........................................................................................................................................................56

Figure 47. Depth and velocity distributions at DEL1 for the approximate discharge at which dwarf 

wedgemussel (Alasmidonta heterodon) observations (green dots) were made during 2002............................57
vii

Figure 48. Depth and velocity distributions at DEL2 for the approximate discharge at which dwarf 

wedgemussel (Alasmidonta heterodon) observations (green dots) were made during 2002............................57

Figure 49. Depth and velocity distributions at DEL3 for the approximate discharge at which dwarf 

wedgemussel (Alasmidonta heterodon) observations (green dots) were made during 2002............................58

Figure 50. Flow duration curves for sites WB0 and WB1 on the West Branch, for hydroperiod 1 (October–

April) from water years 1990–2000, under the operating rules for Revision 1 and Revision 7. ..........................59

Figure 51. Storage duration curves for the three New York City reservoirs, for hydroperiod 1 (October–April) 

from water years 1990–2000, under the operating rules for Revision 1 and Revision 7. .....................................59

Figure 52. Summary scores page for DRDSS demonstration run comparing Revision 1 and Revision 7 

alternatives. .......................................................................................................................................................................60

Figure 53. Temperature duration curves for the period May 1–September 30, 1990–2000, for Revision1 and 

Revision 7 alternatives at site DEL1. .............................................................................................................................63

Figure 54. Expanded view of the global scores box of the DRDSS, showing changes in system drought 

designations under Revision1 and Revision7 alternatives........................................................................................65

Appendix 1..................................................................................................................................................................71

Figure 1-1.Planform map of segments and sites for the West Branch Delaware River...............................72

Figure 1-2. Comparison of planform distributions between segments and sites for the West Branch 

Delaware River...........................................................................................................................................................72

Figure 1-3.Planform map of segments and sites for the East Branch Delaware River. ...............................73

Figure 1-4. Comparison of planform distributions between segments and sites for the East Branch 

Delaware River...........................................................................................................................................................73

Figure 1-5. Planform map of segments and sites for the main stem Delaware River...................................74

Figure 1-6. Comparison of planform distributions between segments and sites for the main stem 

Delaware River...........................................................................................................................................................74

Figure 1-7.Planform maps of segments and sites for the upper (A) and lower (B) Neversink River. ........75

Figure 1-8. Comparison of planform distributions between segments and sites for the Neversink 

River. ............................................................................................................................................................................75

Appendix 2..................................................................................................................................................................76

Figure 2-1. Comparison of predicted and measured water surface profiles for the final calibration run 

at site WB0.................................................................................................................................................................77

Figure 2-2. Comparison of predicted and measured water surface profiles for the final calibration run 

at site WB1.................................................................................................................................................................77

Figure 2-3. Comparison of predicted and measured water surface profiles for the final calibration run 

at site EB0...................................................................................................................................................................78

Figure 2-4. Comparison of predicted and measured water surface profiles for the final calibration run 

at site EB1...................................................................................................................................................................78

Figure 2-5. Comparison of predicted and measured water surface profiles for the final calibration run 

at site EB2...................................................................................................................................................................79

Figure 2-6. Comparison of predicted and measured water surface profiles for the final calibration run 

at site DEL1.................................................................................................................................................................79

Figure 2-7. Comparison of predicted and measured water surface profiles for the final calibration run 

at site DEL2.................................................................................................................................................................80

Figure 2-8. Comparison of predicted and measured water surface profiles for the final calibration run 

at site DEL3.................................................................................................................................................................80
viii

Figure 2-9. Comparison of predicted and measured water surface profiles for the final calibration run at 

site NVR0. ....................................................................................................................................................................81

Figure 2-10. Comparison of predicted and measured water surface profiles for the final calibration run 

at site NVR1. ...............................................................................................................................................................81

Figure 2-11. Comparison of predicted and measured water surface profiles for the final calibration run 

at site NVR2. ...............................................................................................................................................................82

Appendix 5................................................................................................................................................................109

Figure 5-1. The “From_OASIS” page of “OASIS_formatter.xls.” Outlined box in figure shows where the 

data copied from the OASIS text file are to be pasted. ....................................................................................111

Figure 5-2. The “To_DSS” page of “OASIS formatter.xls.” In the example, the first date of the first water 

year of interest is October 1, 1959, located at cell A11611...............................................................................111

Figure 5-3. The “Flows” page of “DSS_AGG.xls,” with outlined cell indicating where to paste baseline 

data from “OASIS formatter.xls.” .........................................................................................................................112

Figure 5-4. The “Flows” page of “DSS_AGG.xls,” with outlined cell indicating where to paste data for 

an alternative from “OASIS formatter.xls.” ........................................................................................................113

Figure 5-5. Cell F2002 in “met_data.xls,” the starting location for copying a ten-year block of “normal” 

meteorological data corresponding to the dates and flows previously imported to the “Flows” page of 

“DSS_AGG.xls.” .......................................................................................................................................................114

Figure 5-6. Selected block ending at cell I5854 in “met_data.xls,” the ending location for copying a tenyear block of “normal” meteorological data corresponding to the dates and flows previously imported 

to the “Flows” page of “DSS_AGG.xls.”..............................................................................................................114

Figure 5-7. Cell BI11 on the “Flows” page of “DSS_AGG.xls” is outlined. This is where the 

meteorological data originating from the met_data.xls database are pasted. ............................................115

Figure 5-8. Parameters page from “DSS_AGG.xls.” .........................................................................................116

Figure 5-9. Setup to generate a flow duration curve for WB0 on the “WBDurCurve” page of 

“DSS_WB.xls.” Selected Page tab and variables are highlighted.................................................................118

Figure 5-10. Setup to generate a flow duration series curve for WB0 on the “WBDurSer” page of 

“DSS_WB.xls.” Selected Page tab and variables are highlighted.................................................................119

Figure 5-11. Poster template generated for 36 x 74 inch page size in ArcMap, showing locations and 

relative sizes of components.................................................................................................................................122

Tables 

Table 1. Segment boundaries and resource issues associated with upper Delaware Basin. ............................6

Table 2. Suitable depth and velocity ranges for target organisms, as defined by the Delphi panel.................13

Table 3. Hydromorphic units, descriptions, and codification criteria used to classify mesohabitat types.....15

Table 4. Example of a persistence table for brown trout spawning and incubation. ..........................................17

Table 5. Summary of available meteorology data. .....................................................................................................19

Table 6. U. S. Geological Survey discharge gages in the upper Delaware River study sites with four or more 

years of temperature data. .............................................................................................................................................19

Table 7. Conversion constants and normalizing terms by segment........................................................................38

Appendix 3..................................................................................................................................................................83

Table 3-1. Habitat versus discharge relations for segment 0 West Branch Delaware River (WB0). ........84

Table 3-2. Habitat versus discharge relations for segment 1 West Branch Delaware River (WB1). ........84

Table 3-3. Habitat versus discharge relations for segment 0 East Branch Delaware River (EB0).............85
ix

Table 3-4. Habitat versus discharge relations for segment 1 East Branch Delaware River (EB1).............85

Table 3-5. Habitat versus discharge relations for segment 2 East Branch Delaware River (EB2).............86

Table 3-6. Habitat versus discharge relations for segment 2 East Branch Delaware River (EB2) – 

Continued. ...................................................................................................................................................................86

Table 3-7. Habitat versus discharge relations for segment 1 Delaware River main stem (DEL1). .............87

Table 3-8. Habitat versus discharge relations for segment 1 Delaware River main stem (DEL1) – 

Continued. ...................................................................................................................................................................87

Table 3-9. Habitat versus discharge relations for segment 2 Delaware River main stem (DEL2). .............88

Table 3-10. Habitat versus discharge relations for segment 2 Delaware River main stem (DEL2) –

Continued. ...................................................................................................................................................................88

Table 3-11. Habitat versus discharge relations for segment 3 Delaware River main stem (DEL3). ...........89

Table 3-12. Habitat versus discharge relations for segment 3 Delaware River main stem (DEL3) – 

Continued. ...................................................................................................................................................................89

Table 3-13. Habitat versus discharge relations for segment 0 Neversink River (NVR0). .............................90

Table 3-14. Habitat versus discharge relations for segment 1 Neversink River (NVR1). .............................90

Table 3-15. Habitat versus discharge relations for segment 2 Neversink River (NVR2). .............................91

Table 3-16. Habitat versus discharge relations for segment 2 Neversink River (NVR2) – Continued........91

Appendix 4. ................................................................................................................................................................94

Table 4-1. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site WB0. Units of 

habitat are m2/km. ......................................................................................................................................................94

Table 4-2. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site WB1. Units of 

habitat are m2/km. ......................................................................................................................................................95

Table 4-3. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site EB0. Units of 

habitat are m2/km. ......................................................................................................................................................96

Table 4-4. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site EB1. Units of 

habitat are m2

/km. ......................................................................................................................................................97

Table 4-5. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site EB2. Units of 

habitat are m2/km. ......................................................................................................................................................98

Table 4-6. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site DEL1. Units of 

habitat are m2

/km. ......................................................................................................................................................99

Table 4-7. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site DEL2. Units of 

habitat are m2

/km. ....................................................................................................................................................100

Table 4-8. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site DEL3. Units of 

habitat are m2/km. ....................................................................................................................................................101

Table 4-9. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site NVR0. Units of 

habitat are m2

/km. ....................................................................................................................................................102

Table 4-10. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site NVR1. Units of 

habitat are m2

/km. ....................................................................................................................................................103

Table 4-11. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site NVR2. Units of 

habitat are m2/km. ....................................................................................................................................................104

Table 4-12. Persistent habitat for dwarf wedgemussels (Alasmidonta heterodon) at site DEL1. Units of 

habitat are hectares................................................................................................................................................105

Table 4-13. Persistent habitat for dwarf wedgemussels (Alasmidonta heterodon) at site DEL2. Units of 

habitat are hectares................................................................................................................................................106
x

Table 4-14. Persistent habitat for dwarf wedgemussels (Alasmidonta heterodon) at site DEL3. Units of 

habitat are hectares................................................................................................................................................107
1

A Decision Support Framework for Water 

Management in the Upper Delaware River 

By Ken D. Bovee, Terry J. Waddle, John Bartholow, and Lucy Burris 1

Introduction 

The Delaware River Basin occupies an area of 12,765 square miles, in portions of south 

central New York, northeast Pennsylvania, northeast Delaware, and western New Jersey (fig. 1). 

The river begins as two streams in the Catskill Mountains, the East and West Branches. The two 

tributaries flow in a southwesterly direction until they meet at Hancock, N.Y. The length of the 

river from the mouth of Delaware Bay to the confluence at Hancock is 331 miles. Approximately 

200 miles of the river between Hancock, N.Y., and Trenton, N.J., is nontidal. 

Figure 1. Tristate map of the Delaware River Basin (Scale = 1:1,500,000). 

 

1

 U.S. Geological Survey, Fort Collins Science Center, 2150 Centre Avenue, Building C, Fort Collins, Colo., 80526. 
2

New York City’s Delaware system impounds three tributaries at Cannonsville Reservoir on 

the West Branch, Pepacton Reservoir on the East Branch, and the Neversink Reservoir on the 

Neversink River (fig. 2). Approximately 895.5 million m3 (725,985 acre feet) is diverted out of the 

Delaware River Basin from these reservoirs each year through the Delaware Aqueduct. Typically, 

more than one fourth of the diverted water is from Neversink Reservoir while Cannonsville 

Reservoir supplies less than a quarter and Pepacton Reservoir provides the remaining half. 

Figure 2. Upper Delaware River and reservoirs (Scale = 1:500,000). 

The river is currently managed under the terms of a 1954 Supreme Court Decree 

(henceforth the Decree), the result of a series of lawsuits brought by New Jersey and Pennsylvania 

to regulate New York City’s diversions from the Delaware River Basin. The diversion rights and 

release requirements created under the Decree cannot be changed without unanimous consent from 

the Decree parties (Delaware, New Jersey, New York, Pennsylvania, and New York City.) 

Numerous adjustments to the Decree’s diversion and release formula have been made to modify the 

operations of the three New York City reservoirs in the Delaware River Basin. A coldwater fishery 

developed in response to the cold releases from the three New York City reservoirs. During the 

past 25 years, the Decree parties, at the request of the New York State Department of 

Environmental Conservation, have established schedules for minimum releases and have set aside a 

thermal bank for fishery protection. This program has been established, and on several occasions 

has been experimentally modified. 

Several operational and management factors affect the flow regime in the upper Delaware 

River Basin. Among these are the use of the Montague flow target formula, minimum New York 
3

City reservoir releases, New York City Department of Environmental Protection reservoir 

management decisions, the rule curves pertaining to the operation of the reservoirs, and reservoir 

capacity. Information in the following sections was extracted largely from “Preliminary list of flow 

management issues,” prepared by the Greeley-Polhemus Group, West Chester, Pa. and provided 

courtesy of the Delaware River Basin Commission, January, 2004. 

Montague Target Formula 

During normal conditions as defined by the operating rule curves, New York City can 

divert up to 3.03 million m3 (2,456 acre feet) per day, provided that a flow target of 49.6 m3/s 

(1,750 ft3/s) is met at the Montague, N.J., gage. The Delaware River Master, a position within the 

U.S. Geological Survey established by the Decree, directs New York City reservoir releases on a 

daily basis for the purpose of meeting the Montague flow target. New York City must comply with 

this direction but may use any of the three upper Delaware reservoirs to do so. In computing the 

directed release for the New York City reservoirs, the River Master must account for releases from 

the Lake Wallenpaupack and Rio hydropower facilities toward the Montague flow. These 

reservoirs are located downstream of the New York City reservoirs but upstream of Montague. 

Because the power releases and forecast precipitation are highly variable, the directed release 

requirements fluctuate, resulting in a highly variable flow regime in the upper Delaware River and 

tributaries. 

Minimum Reservoir Releases 

In 1977, the New York State Department of Environmental Conservation issued regulations 

that required minimum releases from the three reservoirs for conservation purposes. These 

mandatory releases have been revised a number of times by unanimous consent of the Decree 

parties. During periods of drought watch, drought warning, and drought, as defined by the 

operating rule curves, flow targets and minimum releases are reduced. The minimum releases may 

drop to the basic rates during drought conditions in the event that fishery protection banks are not 

available. In addition, thermal releases can be made when needed to protect coldwater fisheries 

below the reservoirs, provided that water is available in the thermal bank or can be traded from 

another allocation. 

New York City Department of Environmental Protection Operating Decisions 

Releases among the three reservoirs are not evenly divided. The water stored at Neversink 

Reservoir and Pepacton is of higher quality than that at Cannonsville. Consequently, more water is 

diverted from the East Branch and the Neversink than from the West Branch. Cannonsville releases 

to the West Branch equal approximately 61 percent of total storage. In contrast, the release from 

Neversink Reservoir is approximately 19 percent of its total storage, and the Pepacton release is 

approximately 24 percent of total storage. 

Operating Rule Curves 

The rule curves defining drought watch, drought warning, and drought conditions represent 

a seasonal water allocation of New York City reservoir storage among the Decree parties. They do 

not necessarily reflect observed hydrologic conditions elsewhere in the Delaware Basin. Drought or 

drought warning operations have been invoked frequently in recent history. For example, from 

1991 through 1998, a drought warning was declared for a portion of every year except 1996. The 
4

result of the current definition has been the frequent enforcement of the basic conservation release, 

resulting in abnormally low flows for extended periods of time, frequently during fall and winter. 

Reservoir Capacity 

The converse of frequent use of the drought declaration is reservoir spillage, often the result 

of a large runoff event occurring when a reservoir is full or nearly full. Under natural conditions, 

peak flows would normally occur in April and May in response to snowmelt runoff and rainfall. 

Under current operations, reservoir volumes are maintained as full as possible to maximize 

deliverable water supplies. Consequently, there is little buffering capacity to reduce flood events 

during periods of high inflow and uncontrolled spills are common events. Attenuation of peaks is 

greatest in the Neversink River and least in the West Branch due to differences in reservoir 

capacity and inflow. 

Goals and Objectives 

Involvement of the U.S. Geological Survey in the Delaware River was the result of 

Congressional funding directed towards the study of instream habitat needs in the upper portion of 

the river basin. This project was proposed for Federal funding by a coalition of non-profit groups 

(including The Nature Conservancy, Trout Unlimited, and the Delaware River Foundation) and 

supported by the Delaware River Basin Commission (henceforth referred to as the Commission). 

The study plan was developed in collaboration with the Subcommittee on Ecological Flows for the 

Delaware Basin (henceforth, the Subcommittee). The Subcommittee serves the Commission’s Flow 

Management Technical Advisory Committee, composed of State, Federal, non-profit, and 

academic representatives engaged in resource management and assessment in the Delaware Basin. 

The goal of the present study was to provide information relating instream habitat 

characteristics and streamflow, integrated with the Commission’s reservoir operations and 

streamflow routing model, OASIS. The specific objectives of the study were: 

1. The quantification of habitat metrics over a range of discharges and seasons at selected 

locations in the three tributaries and main stem Delaware. 

2. Development and calibration of a network-wide temperature simulation model for the upper 

Delaware River basin. 

3. Development of a prototype Delaware River Decision Support System (DRDSS) to assist the 

Commission and other stakeholders to analyze and interpret water management and reservoir 

operations alternatives. 

Study Segments, Resource Issues, and Site Selection 

To facilitate compatibility of the habitat analysis with the hydrologic simulations derived 

from OASIS, the upper Delaware River and its tributaries were divided into eleven river segments 

(fig. 3, table 1) following the guidelines presented in Bovee and others (1998). Segment 

delineations were based on the following criteria, roughly in order of descending priority: 

1. The flow regime was relatively homogeneous from the top of segment to the bottom (for 

example, boundaries were placed at confluences of major tributaries). 

2. General temperature classification (for example, coldwater, transitional, or warmwater). 

3. Resource issues, target species, and species of concern. 
5

Figure 3. Segmentation and study site locations in the upper Delaware Basin. 

Resource Issues 

The natural resource issues associated with the upper Delaware varied by location within 

the system. Resource issues in the three tributaries were related primarily to production of brown 

trout (Salmo trutta) and rainbow trout (Oncorhynchus mykiss). The upper Delaware main stem, 

from Hancock to the vicinity of Lordville, N.Y., is also very popular for sport fishing, and trout 

production was considered in this reach as well. Issues related to trout production in these segments 

also included provisions for adequate riffle habitat for macroinvertebrates, flow stability during the 

spawning-incubation period, and occasional high temperatures during the summer. 

In the main stem Delaware River, the lower East Branch (EB2), and lower Neversink 

(NVR2), factors affecting the recruitment and rearing of juvenile American shad (Alosa 

sapidissima) were added to the list of issues. Because American shad are anadromous, and because 

the juveniles rear in the Delaware system only from June until August or September, streamflow 

management in support of this species was considered seasonal, rather than year-round. Other 

species of interest included the bridle shiner (Notropus bifrenatus), blue spotted sunfish 

(Enneacanthus gloriosus), eastern mudminnow (Umbra pygmaea), American eel (Anguilla 

rostrata), margined madtom (Noturus insignis), fallfish (Semotilus corporalis), and cutlips minnow 

(Exoglossum maxillingua). 
6

Table 1. Segment boundaries and resource issues associated with upper Delaware Basin. 

River Segment Location Resource issues 

West Branch WB0 

WB1 

 Cannonsville to Oquaga Creek 

Oquaga Creek to Hancock 

Brown trout 

Rainbow trout 

Shallow-fast guild 

Shallow-slow guild 

East Branch EB0 

EB1 

 Downsville to Shinhopple 

Shinhopple to Beaver Kill 

Brown trout 

Rainbow trout 

Shallow-fast guild 

Shallow-slow guild 

 EB2 Beaver Kill to Hancock Brown trout 

Rainbow trout 

American shad 

Shallow-fast guild 

Shallow-slow guild 

Delaware 

main stem 

 

DEL1 

DEL2 

DEL3 

 Hancock to Lordville 

Lordville to Hankins 

Hankins to Callicoon 

Rainbow trout 

American shad 

Shallow-fast guild 

Shallow-slow guild 

Neversink NVR0 

NVR1 

 Neversink Reservoir to Fallsburg 

Fallsburg to Bridgeville 

Brown trout 

Shallow-fast guild 

Shallow-slow guild 

 NVR2 Bridgeville to Port Jervis Brown trout 

American shad 

Shallow-fast guild 

Shallow-slow guild 

Two species guilds were included in the list of issues for all sites and segments, following 

the basic concepts described by Bain and others (1988), Knight and others (1991), and Bowen 

(1996). The shallow-fast (SFCV) guild was intended to represent habitat for riffle-dwelling species 

of fish and aquatic macroinvertebrates. Of the species of concern not listed in table 1, the margined 

madtom can be considered a member of the SFCV guild (Lee and others, 1980). Juvenile fallfish 

and American eels may also use this habitat type extensively, but not exclusively (Scott and 

Crossman, 1973; Bain and others, 1982). The shallow-slow (SSCV) guild was designed to 

represent habitat necessary for young of the year for virtually all species, and for species found 

primarily in slack water areas. The bridle shiner, blue spotted sunfish, eastern mudminnow, and 

cutlips minnow all utilize subsets of this habitat guild, with the first three species highly associated 

with fine substrates and aquatic vegetation (Scott and Crossman, 1973; Lee and others, 1980). 

From our observations, fine substrates and aquatic vegetation were rare in most places, being most 

commonly found in backwater mesohabitat types. The cutlips minnow is also commonly associated 

with shallow, slow water, but in silt-free, unvegetated areas (Scott and Crossman, 1973). Although 

the habitats for these species were not studied specifically, their general habitat responses were 

assumed to correspond to the SSCV guild. 

Four subpopulations of the Federally endangered dwarf wedgemussel (Alasmidonta 

heterodon) exist in the upper Delaware basin. Dwarf wedgemussel populations were discovered 

between the towns of Equinunk, Pa., and Callicoon, N.Y., depicted in table 1 as sites DEL1, DEL2, 

and DEL3. The lower Neversink River also reportedly supports a large population of dwarf 

wedgemussel, although this study investigated only the main stem Delaware mussel beds. 
7

Site Selection 

The rationale for the selection of study sites was that the habitat characteristics of the site 

should represent those of the segment. Habitat is related to hydraulics, channel structure, and edge 

effects. Hydraulics, channel structure, and edge effects are all related to planform. Therefore, we 

used planform as our initial criterion for site selection. Selections were based on how well the 

proportional distribution of channel types in the candidate site matched those of the total segment. 

Channel types were digitized from 1:40,000 scale digital ortho quarter quadrangles (DOQQ), and 

classified as: 

1. divided channel on a bend (BDC), 

2. single-thread channel on a bend (BSC), 

3. delta/tributary confluence (DELTA), 

4. multiple channel (MC), 

5. straight, single-thread channel (SSC), and 

6. straight, divided channel (SDC). 

A divided channel (of either category) differed from a multiple channel according to the 

number of islands evident in the photographs or verified by site visitations. A divided channel was 

designated where there was a single island, usually in midriver, with approximately equal-sized 

channels on either side of the division. Multiple channel sectors were defined where two or more 

clearly defined islands were adjacent to one another. Unvegetated midchannel bars were not 

considered to be islands, even though multiple channels formed around them at low flows. In some 

cases the distinction between a divided channel and multiple channel was blurred by the presence 

of small secondary channels cutting across a single, dominant island. In these cases, a judgment 

was made regarding the dominant feature of the planform type. Although we strived for 

consistency, the subjectivity of these decisions may have influenced the site-segment comparisons 

somewhat. 

The proportional distribution of each channel type was calculated by dividing the summed 

lengths for each type by the total length of the segment. The segment was then subsampled to find 

a shorter, contiguous reach that closely approximated the proportions of channel types in the 

segment (see appendix 1). This procedure was followed rigorously during the initial selection of 

study sites. After review by the Subcommittee, however, several members recommended the 

addition and modification of sites. Sites WB0, EB0, and NVR0 were added to the West Branch, 

East Branch, and Neversink, respectively, to better describe habitat conditions in the tailwaters 

areas of the three tributaries. The main stem sites (DEL1, DEL2, and DEL3) were concentrated in 

the Hancock-to-Callicoon reach, to correspond to areas of active dwarf wedgemussel research. 

Finally, the reach farthest downstream on the Neversink (NVR2) proved to be inaccessible, and 

was moved to a more accessible location. One consequence of the re-selection process was that the 

lower portion of the main stem of the Delaware from Callicoon to Port Jervis was not included in 

the study. 

Methods 

Three basic types of information were generated for this study. The first category included 

the development of various habitat patch metrics as a function of discharge. The second type was 

the simulation of daily temperatures at specified locations in the system under different input 

conditions of meteorology, reservoir releases, and network hydrology. The third category, used 
8

primarily for calculating summary statistics in the DRDSS, was the generation of time series of 

habitat metrics and temperature. Information related to other decision variables in the DRDSS, 

including reservoir storage, spills, downstream deliveries, and exports, were derived directly from 

the OASIS model. This section briefly describes the methods used to derive each of the three types 

of information and concludes with a description of the organization and functionality of the 

DRDSS. 

Habitat Patch Metrics 

Habitat patch metrics were derived from a combination of stream bathymetry, hydraulic 

model output, and spatially explicit patch morphometry utilizing ArcGIS (ESRI, Version 9.0). 

Development of this database involved seven steps: collection of bathymetric data, preparation of 

input to the hydraulic simulation model, determination of boundary conditions, model calibration, 

simulation of unmeasured discharges, classification of habitat for target organisms and guilds, and 

geographic information system operations to generate patch metrics as functions of discharge. 

Bathymetric Data 

Bathymetric data were collected remotely using boat-mounted echo sounders for deepwater areas and directly via ground surveys of shallow-water and exposed areas. At each study site, 

a semipermanent benchmark was established using the Wide Area Augmentation System (WAAS) 

differentially-corrected Global Positioning System. In effect, our benchmarks were considered as 

“local controls,” but the submeter accuracy of the positions and elevations were well within 

acceptable mapping tolerances for our study. Secondary benchmarks were installed at additional 

locations within the sites by real-time kinematic Global Positioning System in the event that the 

primary benchmark was disturbed and to ensure continuity in radio transmissions from the base 

station. Precision estimates for survey data relative to the primary benchmarks were approximately 

2 cm horizontally and vertically. 

Hydroacoustic mapping was conducted using procedures described in Bowen and others 

(2003b). Bathymetric data were collected with Biosonics DT4000 and DE-X echosounders 

equipped with a single beam, 6o transducer mounted in an inboard acoustic well. The echosounders 

were calibrated by comparing depths recorded on the echogram with depths measured with a 

survey rod at stationary locations in a lake. In this setting, the accuracy of depth measurements was 

approximately 3 cm. 

Five or more longitudinal bed profiles were measured in the main channel and all large side 

channels (20 m or wider), with two profiles tracing each bank, one profile down the centerline of 

the channel, and two other profiles at quarter-channel intervals between the centerline and the bank. 

In channels less than 20 m wide, at least three longitudinal traces were measured. In all channels, 

the longitudinal profile data were augmented by two or more bank-to-bank diagonals for the length 

of the site. All data were georeferenced in the field with a survey-grade Global Positioning System 

mounted adjacent to the acoustic well. 

Direct survey measurements were made with real-time kinematic Global Positioning 

System (Trimble 5800 rover with model 5700 base station) and with an optical total station (Leica 

TC800) with 3-second horizontal and vertical angle precision. Direct survey measurements were 

taken along breaklines defining the toes and tops of banks, cross-sections of floodplain areas and 

islands, and in areas that were too shallow to measure with the echo sounder. All data were 

projected to the Universal Transverse Mercator coordinate system, zone 18 N, using the WGS1984 

datum, and the CONUS99 geoid model. 
9

Data Preparation 

Raw bathymetry data are rarely, if ever, suitable for immediate use in the hydraulic 

simulation model. Echosounder depths must be converted into elevations, and these elevations 

merged with direct survey data. The resulting three-dimensional topography file (known as a bed 

file) must be edited to connect features such as bank edges or thalweg points and to smooth jagged 

contour lines that result from spurious triangulations among measured points. Finally, a 

computation mesh must be constructed as input to the simulation program. 

Conversion of Echosounder Depths to Elevations 

The elevation of the river bed at any point can be calculated as the elevation of the 

transducer face minus the depth. Echosounder data were recorded as binary files of depths and 

geographic locations in latitude and longitude. These data were converted to ASCII format using 

Biosonics Visual Bottom Typer software and projected from latitude-longitude geographic 

reference into the Universal Transverse Mercator coordinate system used with the direct survey 

data. The data were screened for duplicate points and obvious outliers and converted to a 0.5 m by 

0.5 m grid in ArcGIS. Transducer data consisted of x, y coordinates and elevations measured at the 

transducer face using real-time kinematic Global Positioning System recorded at 10-m intervals 

along each of the boat traces. 

Two different approaches were used to calculate the elevations of the transducer face. 

Where data were collected under steady flow conditions, a surface of transducer elevations was 

constructed by interpolation, using the TIN (Triangular Irregular Network) function in ArcGIS. The 

TIN surface was smoothed by removing obvious outliers and converted to a 0.5 m by 0.5 m grid, 

from which the depth grid was subtracted. The resulting grid of bed elevations was then converted 

back to point data that could be used compatibly with the direct ground survey data. 

Where data were collected under unsteady flow conditions, the ping depth was subtracted 

from a transducer elevation interpolated between the two transducer positions bracketing the ping. 

The transducer pair to use was determined by looking up the time stamp of the ping in the time 

stamp list of the transducer points and interpolating a position on the basis of time differential The 

ping depth was subtracted from the interpolated transducer elevation to obtain a bed elevation. 

Quality Control for Echosounder Data 

Prior to constructing the bed files, we conducted an error analysis by comparing the bed 

elevations derived from echosounder data with those obtained by direct survey. We located 

comparable points that were within 1 m of each other and found the difference in surveyed 

elevations from those measured by the echosounder. The error distribution chart (fig. 4) indicated 

that 92 percent of the elevations derived from echo-sounding were within ±15 cm of the surveyed 

elevation, 78 percent were within ±10 cm, and that the errors were nearly normally distributed. 

Differences in elevations were related to the size of the bed materials, in that echosounders measure 

to the tops of the rocks, whereas the range poles used for direct surveys tend to slip into the low 

places between the rocks. The typical bed materials in our sites were commonly in the 20–30 cm 

range, so these differences were considered reasonable and acceptable. Because direct survey 

measurements are inherently more precise than echosounder data, however, precedence was given 

to surveyed data points when disparities in contoured elevations were apparent in the bed file. 
10

0%

5%

10%

15%

20%

25%

-0.35 to 

-0.30

-0.30 to 

- 0.25

-0.25 to 

-0.20

-0.20 to 

-0.15

-0.15 to 

-0.10

-0.10 to 

-0.05

-0.05 to 

0.0

0.0 to 

0.05

0.05 to 

0.10

0.10 to 

0.15

0.15 to 

0.20

0.20 to 

0.25

Error range, in meters

Percent of errors

Figure 4. Error distribution of streambed elevations derived from echosounder data compared 

with those obtained by direct survey methods. 

Bed Topography 

The River2D model (Ghanem and others, 1995, 1996) was used to perform all the hydraulic 

simulations in this study. According to the authors of River2D (University of Alberta, 2006), 

“Accurate representation of the physical features of the river channel bed is probably the most 

crucial factor in successful river flow modeling. In addition to accurate and extensive field data, 

judgment and experience are necessary to connect the scattered data points into a digital surface 

representation.” One of the components of the River2D suite of programs is a bed-topography 

editor, capable of rapid triangulation and contouring of point data. Generally, elevation transitions 

in rivers are relatively smooth (except for the toe-of-bank contour) and highly anisotropic 

(continuous features are aligned longitudinally in correspondence to the banks and thalweg, Turner 

and others, 1989). Triangulation of the raw elevation data invariably results in localized areas of 

sharp transitions, discontinuities of contours in continuous features, and other unrealistic geometry. 

By addition or deletion of points and by connecting points with breaklines, a contour is forced to 

override the River2D default computation. The locations and orientations of the “correct” contours 

were usually fairly obvious, based on DOQQ imagery we used as background, and from descriptive 

coding (for example, for edge-of-bank measurements) in the direct survey data. Where definitive 

information was unavailable, we relied on our collective experience and knowledge of each of the 

sites to modify contours. 

Computational Mesh 

The bed topography file is used in R2D_Mesh to develop a computational discretization as 

input to River2D. The mesh provides a template through which River2D solves for water depths 

and velocities. Generally speaking, larger mesh elements (less discretization) can be used in 
11

uniform or gradually-varying features, such as deep pools, and smaller elements where transitions 

are abrupt, such as along the edges of banks. Shallow water areas can be problematic in River2D 

because localized areas of super-critical flow may be computed, resulting in serious errors such as 

unrealistically high velocity predictions, recirculation (water running uphill), or both. In 

anticipation of such problems, we preemptively increased the mesh density at riffles, runs, delta 

areas, and over bars. As the simulation flows deviated from the calibration flow, new areas of 

shallow water appeared and old ones disappeared, so the mesh was revised accordingly for each 

run. 

There is an inherent trade-off in mesh-building. The rate at which a run can be completed is 

a function of mesh density and mesh quality. Mesh quality refers to the degree to which the 

triangular mesh elements approach equilateral triangles. As mesh density and quality increase, 

problems with abrupt topographic changes and super-critical flow decrease (resulting in better 

accuracy of model predictions), but the time required for the model to converge to a stable solution 

can increase exponentially. Consequently, we used the fewest and highest quality mesh elements 

where appropriate (with at least 10 elements for each channel over 5 m wide), but increased mesh 

density where necessary to achieve high quality simulation runs in a reasonable amount of time. 

Boundary Conditions 

River2D requires the discharge at the inflow boundary and the water surface elevation at the 

outflow boundary as inputs for a simulation run. The boundary conditions for a study site were 

defined by a rating curve or table that related the stage at the outflow with the discharge at the 

inflow. Owing to the compact size of most of our segments, nearly all of the study sites were in 

close proximity to a USGS stream gage. Rating tables for appropriate gages were provided to us by 

the USGS New York Water Science Center located in Troy, N.Y. We translated the gage reading 

associated with a particular discharge with a reference water surface elevation measured at the site 

outflow for calibration purposes. At different simulation discharges, we determined the change in 

stage from the reference discharge and adjusted the outflow elevation by a like amount. 

Model Calibration 

Concurrent with the collection of bathymetric data, a direct-measurement survey of the 

water surface profile was conducted at each site. The discharge associated with the water surface 

profile was either determined from the USGS website for real-time discharge data, or measured in 

the field. 

With the measured inflow discharge and the measured outflow water surface elevation as 

boundary conditions, River2D was run to produce a predicted water surface profile corresponding 

to the measured profile. Adjustments were made to the mesh where increased discretization was 

warranted, and the parameter for roughness height adjusted upward or downward to alter the 

resistance to flow provided by friction. For example, if the predicted water surface profile was 

uniformly lower than the measured profile, roughness height was increased. The increase in 

resistance caused the velocity to decrease and the depth to increase, thereby raising the elevation of 

the predicted water surface profile. This procedure was repeated until a reasonable match between 

the predicted and measured water surface profiles was obtained. 

What constituted a reasonable match depended on the complexity of the profile, the 

elevation differential between the top of the site and the bottom, the behavior of the model during 

the calibration runs, and the potential error associated with individual water surface elevation 

measurements. In general, we attempted to match the measured water surface elevation to ±5 cm or 

less at all measurement points, with the goal of minimizing residuals throughout the profile. While 
12

it is possible to adjust the roughness at specific locations to match the predicted and measured 

water surface elevations exactly, past experiences in hydraulic modeling have demonstrated that 

doing so is inadvisable. Such tight calibration can introduce instabilities in the model that actually 

make subsequent simulations less accurate. 

To avoid mathematical instabilities, we adopted the general guideline that regional 

adjustments to roughness height should not deviate from the site average by more that 50 percent 

without compelling empirical evidence to the contrary. In some cases, no amount of local 

roughness adjustment changed the predicted water surface elevation significantly. In several 

instances, the mismatch between measured and simulated elevations was associated with erroneous 

recording of water surface elevation (for example, miscoding a bed measurement as a water 

surface). Otherwise, the discrepancy was related to the conveyance area through the problem 

section as depicted in the bed file. When large differences (greater than 5 cm) between measured 

and simulated water surface elevations persisted, we first checked the quality of the measurement. 

If the calibration measurement was judged not to be the source of the error, we re-investigated the 

editing (especially breaklines) of the bed topography and modified it where changes were justified 

by the data. Final calibration results for all 11 sites can be found in appendix 2. 

Simulation of Unmeasured Discharges 

A range of simulated discharges was selected to bracket most of the discharges that would 

occur in the baseline or alternative hydrologic time series produced by OASIS. We constructed 

flow duration curves of the average daily discharges for the USGS gages associated with each of 

our study sites, and selected a range representing the 1 percent to 99 percent exceedance 

probabilities. We then applied a logarithmic sampling of this range to select 15 simulation 

discharges between and including these extremes. The effect of the logarithmic sampling process 

was to simulate discharges at closer intervals in the low end of the range, with fewer, more widelyspread discharges at the high end. For each of the simulation discharges, an outflow water surface 

elevation was derived using the procedure described previously under “Boundary Conditions.” 

Habitat Classification 

Ranges of suitable depths and velocities for each of the target species and habitat use guilds 

were defined (table 2) using the Delphi technique as described by Zuboy (1981). A small 

monitoring team devised a questionnaire that was sent out to a larger respondent group of experts. 

Each respondent was asked to provide his or her estimate of the maximum and minimum depths 

and velocities considered to be suitable for each of the target organisms and habitat use guilds. 

After the questionnaire was returned to the monitors, group opinion was summarized by providing 

the median and inter-quartile ranges of the initial responses. These estimates of group opinion were 

then returned to the respondents, who were asked to answer the questionnaire again in light of the 

new information. Anonymity of individual responses was maintained throughout this process to 

minimize the bandwagon effect associated with roundtable discussions. If a respondent’s second 

response was outside the inter-quartile range of the previous round, he or she was asked to provide 

a brief explanation in support of the response. These explanations were provided to the respondent 

group, along with the revised median and inter-quartile ranges of the responses, and the process 

was repeated until the group converged to a consensus of opinion or at least attained a stability in 

the distribution of responses. 
13

Table 2. Suitable depth and velocity ranges for target organisms, as defined by the Delphi panel. 

Target Organism Depth Range (m) Velocity Range (m/s) 

Brown trout adult 0.3–1001 0.0–1.0 

Brown trout juvenile 0.2–0.8 0.0–0.7 

Brown trout spawning 0.2–0.6 0.3–0.81 

Brown trout incubation 0.2–1.0 0.15–1.2 

Rainbow trout adult 0.3–1001

 0.0–1.2 

Rainbow trout juvenile 0.2–1.0 0.0–0.8 

American shad spawning 0.3–3.0 0.2–0.7 

American shad juvenile 0.25–1.6 0.0–0.6 

Shallow-fast guild 0.05–0.3 0.3–1.2 

Shallow-slow guild2

 0.05–0.3 0.0–0.3 

1

 100 m set to represent no effective upper limit. 

2

 Includes fry for both trout and shad species. 

Geographic Information System Operations 

Several types of map layers and intermediate products were generated under the general 

heading of habitat maps. The hydraulic habitat layer consisted of a series of habitat classification 

polygons depicting the spatial distribution of suitable depths and velocities for each target organism 

at each simulated discharge. The hydraulic habitat layer was the source of metrics considered to be 

steady-state functions of discharge (for example, total area of adult brown trout habitat at a specific 

discharge). The mesohabitat layer was a spatial interpretation of larger scale habitat characteristics 

controlled mostly by planform and channel structure (for example, the spatial extent of riffles or 

pools at different discharges). Habitat persistence maps were constructed to quantify the spatial 

stability of habitat for brown trout spawning and incubation and for dwarf wedgemussels under 

conditions of unsteady flow. 

The Hydraulic Habitat Layer 

Output from a River2D simulation run for a particular discharge was exported as a text file 

containing the coordinates, depths, and velocities for each node in the computational mesh. This 

information was used to generate a map layer of the nodes and the attributes of depth and velocity. 

An interpolated surface (a Triangular Irregular Network, or TIN) was constructed for each 

hydraulic variable, using the nodal data as mass points. Each TIN was converted to a 0.5 m x 0.5 m 

grid, reclassified according to the habitat classification criteria (table 2), and the reclassified grids 

combined to create a single grid depicting suitable depth and velocity conditions for each target 

organism and guild. The composite grids were converted to polygon format and the area for each 

polygon was calculated. The attribute tables were exported to a spreadsheet for subsequent 

extraction of habitat metrics and development of the flow versus habitat lookup tables used in time 

series analysis. 
14

The Mesohabitat Layer 

The mesohabitat layer served two purposes in our analysis. First, this layer provided a 

context for the distribution of suitable hydraulic habitat within the channel. For example, several 

authors have suggested that habitat for young of the year fish (our shallow-slow guild) may be 

more valuable if located along shoreline margins than if located in the main channel where 

zooplankton production is lower and predation vulnerability is higher (Kwak, 1988; Freeman and 

others, 2001; Bowen and others, 2003a, b). The second application of the mesohabitat layer was to 

associate suitable spawning habitat with a specific mesohabitat type, defined as the pool tailout. 

Pool tailouts were identified as those portions of the channel having an adverse bed slope (the bed 

slope is opposite the direction of the water surface slope). This mesohabitat type occurs almost 

universally in the region between the deepest portion of a pool and the crest of the riffle 

downstream from the pool (fig. 5). Consensus among the Delphi participants, supported by visual 

observations of brown trout redds in the Neversink River, indicated that the pool tailout provided 

suitable substrates for salmonid spawning and created a favorable hyporheic environment that 

ensured interstitial flow through the redds during incubation. 

Figure 5. Digital representation of a pool tailout. Deepest portion of pool indicated by dark blue 

polygon and crest of riffle by compressed contours of water surface elevations. 

Mesohabitat types were digitized using the water’s edge contour from River2D for each of 

the simulated flows and 1:40,000 scale DOQQ images as templates. For the most part, we codified 

mesohabitat polygons using the definitions provided by Parasiewicz (2001). To ensure consistency 

in coding, we applied specific criteria to each of the mesohabitat types, rather than relying solely on 

the descriptions provided by Parasiewicz (2001). In addition, we added several mesohabitat types 

we considered to be potentially important, most notably the pool tailout, inundated terrestrial 

vegetation, and disconnected areas (table 3). The latter were included because they can either serve 

as refuges or as stranding areas, depending on their size and how long they persist. 
15

Table 3. Hydromorphic units, descriptions, and codification criteria used to classify mesohabitat 

types. 

Hydromorphic Unit Description Criteria 

Riffle 

Shallow stream reach with moderate current velocity, some 

surface turbulence, and high gradient. Convex streambed 

shape. 

Water surface slope ≥ 0.002, 

depth <1 m. 

Rapid Higher gradient reach than a riffle with faster current 

velocity, coarser substrate, and more surface turbulence. 

Water surface slope ≥ 0.002, 

depth >1 m. 

Run Deeper stream reach with moderate current velocity but no 

surface turbulence. Laminar flow. 

0.0005< water surface slope 

< 0.002, depth <1 m 

Fast run Uniform fast-flowing stream channel. 0.0005< water surface slope 

< 0.002, Depth >1 m 

Pool Deep water impounded by a channel blockage or obstruction. 

Slow with concave streambed shape. 

Slope <0.0005 regardless of 

depth. 

Side arm Channel around an island, smaller than half the width of the 

river. 

Channel around an island, 

smaller than half the width 

of the river. Connected to 

river at inflow and outflow. 

Backwater Slack area along channel margins caused by eddies behind 

obstruction. 

Standing water connected to 

the river only at its outflow. 

Pool tailout1

 

Channel areas between 

deepest portions of pools 

and crests of riffles. 

Inundated vegetation1

 

Areas containing perennial 

vegetation, inundated at 

high discharges. 

Disconnected area1

 

Standing water with no 

surface connection to the 

river. 

1

 Added definition. Not described by Parasiewicz (2001). 

A special case of a mesohabitat treatment was our application of a shoreline buffer 

restriction to the calculation of habitat area for the shallow-slow habitat use guild. A 5-m shoreline 

buffer polygon was created around the water’s edge arc at each simulated discharge. The hydraulic 

habitat polygons for the shallow-slow habitat use guild were intersected with the shoreline buffer 

polygon for each flow, resulting in polygons representing suitable hydraulic conditions within five 

meters of the shoreline. The attribute tables for the intersections were exported as lookup tables for 

subsequent use in the habitat time series analyses. 

Habitat Persistence 

Habitat persistence is a measure of the stability of individual habitat patches, applicable 

primarily to organisms with limited mobility (Bovee and others, 2004). Although habitat 

persistence can influence the well-being of many organisms, we confined our analysis to brown 

trout spawning and incubation and to patch stability for dwarf wedgemussels. The conceptual 

model for the spawning-incubation analysis was that trout would spawn in suitable hydraulic 

habitats within pool tailout areas and that hatching success would be related to the continued 

suitability of conditions over the redds throughout the incubation period. Incubation flows that 

were appreciably lower than the spawning flow could result in dewatering of redds, whereas high 

flows could result in their destruction by erosion. Similarly, unsteady flows can be detrimental to 
16

mussels by desiccation or stagnation at low flow and by excessive shear stress at high flow (Layzer 

and Madison, 1995). Whereas the effects of rates and magnitudes of change differ between 

spawning-incubation (measured over months) and mussels (measured over days), the process for 

measuring patch persistence was similar for both phenomena. 

To quantify the persistence of spawning-incubation habitat we performed a multilayer 

intersection of the pool tailout polygons and suitable hydraulic habitat for spawning and incubation, 

respectively (fig. 6). Persistence of spawning patches is a time and flow dependent phenomenon. 

That is, for the same combination of flows, habitat persistence differs depending on whether the 

spawning flow was higher or lower than the incubation flow. Consequently, it was necessary to 

construct overlay maps for all 15 simulated spawning flows and all 15 simulated incubation flows 

(a 15x15 cell matrix). Areas of persistent spawning-incubation habitat were calculated in the 

attribute table for each composite map layer and exported to a persistence table (table 4) for 

subsequent use in the time series analysis. 

Figure 6. Illustration of a persistence map for a spawning discharge of 10 m3

/s (350 ft3/s) and an 

incubation discharge of 2.5 m3

/s (88 ft3/s). 

For dwarf wedgemussels, we used surveyed mussel locations heuristically with hydraulic 

information generated from River2d to estimate suitable conditions for their survival. We obtained 

locations of individual mussels from a survey conducted in the summer of 2002 (personal 

communication, Dr. William Lellis, USGS Northern Appalachian Research Laboratory, Wellsboro, 

Pa., November 17, 2005). Overlays of low flow depths and velocities, high flow shear stresses, and 

mussel locations were developed to estimate the lower suitable limits of depth and velocity and the 

upper suitable limit for shear stress. In consultation with Dr. Lellis and his associates, and by 

recommendations provided by Layzer and Madison (1995), we developed the following interim 

habitat suitability criteria for the dwarf wedgemussel: minimum depth = 10 cm, minimum velocity 

= 2 cm/s, and maximum shear stress = 0.2 pound per square foot. We stress that these criteria are 
17

interim and are subject to change pending a more rigorous analysis by Dr. Lellis and others 

involved with dwarf wedgemussel research. 

Table 4. Example of a persistence table for brown trout spawning and incubation1

. 

 Spawning Discharge (ft3/s) 

 64 88 125 177 247 353 494 706 953 1,341 1,906 2,683 3,777 

64 58 59 59 59 59 59 59 59 59 59 45 23 23 

88 233 482 483 483 483 483 483 483 483 483 405 107 80 

125 493 862 1,153 1,152 1,153 1,152 1,153 1,153 1,153 1,152 933 280 192 

177 1,077 1,606 2,095 2,530 2,530 2,530 2,532 2,531 2,531 2,530 2,242 844 420 

247 1,505 2,661 3,403 3,979 4,603 4,600 4,602 4,602 4,601 4,598 4,300 2,063 695 

353 1,422 2,647 3,952 4,838 5,705 6,645 6,643 6,645 6,642 6,632 6,338 3,851 1,381 

494 1,266 2,421 3,767 5,381 6,888 8,172 9,044 9,043 9,041 9,028 8,742 6,143 3,329 

706 849 1,844 2,978 4,550 6,127 7,791 8,939 9,644 9,640 9,625 9,506 7,002 4,438 

953 411 932 1521 2,614 3,758 5,195 6,413 7,276 7,608 7,593 7,590 6,481 4,515 

1,341 120 263 410 686 1,217 2,114 2,992 3,834 4,260 4,298 4,295 4,275 3,483 

1,906 0 0 1 21 71 212 512 1,020 1,336 1,405 1,429 1,429 1,369 

2,683 0 0 0 0 0 0 1 76 191 236 257 262 260 

Incubation Discharge (ft3/s) 

3,777 0 0 0 0 0 0 0 0 2 3 8 12 13 

1

To read table 4, find the row representing the spawning flow and the column representing the incubation flow. The 

normalized persistent habitat (expressed as m2

 of suitable habitat per kilometer of stream) is listed in the cell of 

intersection. For example, a spawning flow of 350 ft3

/s and an incubation flow of 177 ft3/s yields a persistent habitat 

value of 2,530 m2

 per kilometer, shaded gray. 

We used these criteria to develop polygons of suitable mussel habitat patches for each 

simulated flow using the same techniques for hydraulic habitat mapping described previously. We 

then conducted paired-flow polygon intersections for all combinations of simulated flows. This 

procedure was similar to the one used for spawning-incubation persistence, with the following 

exceptions: 

1. A “mussel bed” mesohabitat polygon was digitized to encompass the general region of mussel 

locations from the 2002 survey, rather than using individual sightings. This polygon functioned 

in a manner similar to the pool tailout for spawning-incubation, but was more restrictive in that 

it applied only to known mussel beds. 

2. Because mussels exhibit some mobility, the order of flows is less an issue for mussels than for 

spawning and incubation. Although the magnitude of change is important to both, the rate of 

change is more important for mussel survival. Consequently, we developed simple paired-flow 

(7x15 rather than 15x15) persistence tables for dwarf wedgemussels. In contrast, the analysis of 

short-term rates of change was considerably more sophisticated for mussels than for spawningincubation (discussed in the section on habitat time series). 

Temperature Analysis 

Previous methods for predicting temperatures in the upper Delaware system have relied on 

a set of nomograms that had a tendency to overestimate the volume of water necessary to support 

thermal requirements at specific downstream locations. The goal of our analysis was to test 
18

alternative approaches to temperature predictions as potential replacements for the currentlyemployed nomograms. The test objectives included the determination of historical data sufficiency, 

calibration of the model, and validation to objective standards. 

The upper Delaware study area was divided into two parts. The first portion included the 

West and East Branches from their respective reservoirs to their confluence at Hancock, and 

approximately 40 km (25 miles) downstream to Callicoon, N.Y. This portion included the 

Beaverkill upstream to the USGS gaging station at Cooks Falls, N.Y. The second portion included 

the Neversink River from the reservoir approximately 27 km (17 miles) to Bridgeville, N.Y. 

Model Selection 

The Stream Network Temperature model (SNTEMP; Theurer and others, 1984) was chosen 

for our initial investigations. This is a well-tested model, though most use has been in the western 

United States. The model has proven especially robust in predicting mean daily water temperatures. 

SNTEMP is normally capable of predicting mean daily water temperatures ±0.5°C (0.9°F), and 

almost always to within 1°C (1.8°F), depending on the quality of the input data (Bartholow, 1989). 

In addition, SNTEMP is far less demanding than many other models in terms of data requirements. 

SNTEMP was an appropriate model to test for this application because of its public domain 

status and support. The model was readily available, as was its source code, allowing modification 

as necessary. In addition, a considerable body of material was available for technology transfer, 

including documentation (Theurer and others, 1984), self-paced learning material (Bartholow, 

2000) and background on data collection techniques (Bartholow, 1989). 

In spite of this model’s advantages, there were also some potential disadvantages. One data 

input item, “percent possible sun” or cloud cover, is no longer regularly collected by National 

Climatic Data Center stations and often requires additional effort to estimate. Also, the model 

assumes steady state hydrologic conditions, which might signal problems when abrupt changes to 

reservoir releases or short term rainfall-driven runoff events occur. Though none of the existing 

reservoirs has a peaking power release, they can and do spill. The SNTEMP model is not a 

reservoir water temperature model, and requires reservoir release temperature estimates as a 

boundary condition. The model operates on a daily time step under steady-state conditions. 

Consequently, the maximum extent of the study area should typically be no more than one day’s 

travel time from the furthest upstream point to the furthest downstream point. This constraint can 

be compromised, but with some degradation in predictive power. 

Data Gathering and Synthesis 

Data gathering generally followed guidelines presented in Bartholow (1989). There are 

three broad categories of data required by SNTEMP: meteorological data, hydrologic data, and 

stream geometry data. Measured water temperature data were also required to perform an objective 

model calibration and validation. 

Representative meteorological data included air temperature, wind speed, relative humidity, 

percent possible sun (cloud cover), and solar radiation. In addition, the elevation of the 

meteorological station must be known. On occasion, it is advantageous to use data from more than 

one meteorological station to enable cross checking for data outliers, filling missing values, or 

creating composite sets that might better represent the whole watershed. Table 5 lists the major 

meteorological stations evaluated for this project. Hydrologic data included the best estimates of 

streamflow throughout the basin. There appeared to be 14 gages with a useful complement of data, 

including long-term water temperature data (table 6). 
19

Table 5. Summary of available meteorology data. 

Location Source Period of Record 

Binghamton NCDC1

May 1, 1994─Sept. 30, 2004 

Monticello NCDC1

May 1, 1994─Sept. 30, 2004 

Stonykill MesoWest May 1, 2003─Sept. 30, 2004 

Sherburne MesoWest May 1, 2003─Sept. 30, 2004 

1

National Climatological Data Center. 

Table 6. U. S. Geological Survey discharge gages in the upper Delaware River study sites with 

four or more years of temperature data. 

Gage 

Number Name Period of Record 

Water 

Temperature 

Data? 

1417000 East Branch Delaware River at Downsville, N.Y. July 1, 1941─Sept. 30, 2003 No 

1417500 East Branch Delaware River at Harvard, N.Y. Oct. 1, 1934─Sept. 30, 2003 Yes 

1420500 Beaverkill at Cooks Falls, N.Y. July 25, 1913─Sept. 30, 2003 Yes 

1420980 East Branch Delaware River above Read Creek 

at Fishs Eddy, N.Y. Nov. 19, 1912─Sept. 30, 2003 Yes 

1421000 East Branch Delaware River at Fishs Eddy, N.Y. Nov. 19, 1912─Sept. 30, 2001 No 

1425000 West Branch Delaware River at Stilesville, N.Y. July 1, 1952─Sept. 30, 2003 Yes 

1426000 Oquaga Creek at Deposit, N.Y. Oct. 1, 1940─Sept. 30, 1973 No 

1426500 West Branch Delaware River at Hale Eddy, N.Y. Nov. 15, 1912─Sept. 30, 2003 Yes 

1427405 Delaware River near Callicoon, N.Y. Aug. 25, 1967─July 8, 1975 No 

1427500 Callicoon Creek at Callicoon, N.Y. Oct. 1, 1940─Sept. 30, 1982 No 

1427510 Delaware River at Callicoon, N.Y. June 27, 1975─Sept. 30, 2003 Yes 

1436000 Neversink River at Neversink, N.Y. Oct. 1, 1941─Sept. 30, 2003 No 

1436500 Neversink River at Woodbourne, N.Y. Oct. 21, 1937─Sept. 30, 1993 No 

1436690 Neversink River at Bridgeville, N.Y. Oct. 1, 1992─Sept. 30, 2003 Yes 

Each of the rivers was partitioned into discrete segments according to aspect (direction of 

flow from the north-south axis). Channel geometry data for each segment included reach length, 

aspect, latitude, elevation, wetted width as a function of discharge, and Manning’s roughness 

coefficient. Stream widths were generally characterized as power functions (for example, w=aQb) 

where the terms a and b were determined by regression of widths and discharges obtained from the 

River2D simulations. 

The topographic elevation (the angle from the middle of the river to the average ridge line) 

was determined using the MapTech Terrain Navigator software and data base for New York. This 

software is composed of scanned 1:24,000 topographic maps that overlay a 10-m Digital Elevation 

Model (DEM). For each segment, a profile line perpendicular to the azimuth of the channel was 

constructed. The visual horizon was then estimated from the DEM and the distance from the river 

and the elevation change to the horizon calculated. The topographic altitude angle was calculated 
20

from these measurements. Riparian vegetative shading was estimated for the same river segments. 

Unlike topography, estimated vegetative characteristics of tree height, crown diameter, and leaf 

density were relatively uniform throughout the various river basins. Differences occurred 

principally in the relative continuity of trees along each bank and their offset from the river’s edge. 

Field measurements, supplemented by the digital 1:24,000 topographic maps, aided the 

development of segment-by-segment riparian shading estimates. 

Measured water temperature data were derived from existing USGS water quality gaging 

stations (see table 6) as well as New York Department of Environmental Conservation 

measurements. Reservoir release temperature data were taken from the most upstream site 

available on each of the three rivers. Groundwater accretion was estimated by prorated mass 

balance between gaging stations and temperatures were approximated by mean annual air 

temperature adjusted for elevation. 

Quality Assurance/Quality Control 

Large compilations of data must be scrutinized for data quality. Water temperature or other 

data may contain spurious values that must be culled from the database. Few strictly objective 

measures exist for examining every data value, but obvious outliers were eliminated from each data 

set. Missing data were generated for meteorological, hydrological data, and estimates of release 

temperatures using station-to-station regressions. 

Potential errors in measured water temperatures were evaluated by comparison of data 

collected at the same location from two independent sources. We compared data collected by 

USGS and the Department of Environmental Conservation for the Harvard site for 1997─1999 

and they agreed very well. Median absolute differences between the two were 0.3°C (0.5°F) for 

mean daily temperatures and 0.2°C (0.4°F) for the maximum daily temperatures (n=316). Some of 

the differences may be explained by the minimum resolution of the data. USGS data were reported 

to the nearest 0.5°C, whereas the Department of Environmental Conservation data were reported to 

the nearest 0.1°C. 

Initial Model Simulations 

SNTEMP models for both the Neversink River, and the Delaware network (East BranchWest Branch-Delaware main stem) were run with data available for the summers of 1997 through 

1999, May 1 through September 30. We determined that the models performed best using 

meteorological data from Monticello, N.Y. 

With current data limitations, but without calibration, the Neversink model performed 

passably. The correlation between predicted and measured values was relatively high (r=0.84), the 

mean error was 0.12°C, and the probable error 1.16°C . Initial model runs for the Delaware 

network showed that model performance was adversely affected by large amounts of missing data 

at some river locations. Although the correlation between measured and simulated temperatures 

was higher (r=0.89), so were the mean error (0.55°C) and the probable error (1.23°C). Maximum 

errors were -7.23°C in the Delaware network and -5.88°C on the Neversink River. These errors 

appear to be directly attributable to missing Monticello meteorological data and do not necessarily 

reflect on the model’s overall predictive ability. 

Model Calibration 

Well-formulated temperature models with high quality input data require little or no 

calibration. Data are always limited to some degree, however. The ability of meteorological data to 
21

truly represent conditions at and along extensive stretches of a river is a universal problem. The 

goal of model calibration is to simultaneously minimize bias and error while maximizing 

correlation. Typical calibration criteria include: (1) near-zero bias, (2) 50 percent of the errors in 

mean daily temperatures less than 0.5°C, (3) absolute maximum errors under 4°C, and (4) overall 

model correlation greater than r=0.9. Criteria for maximum daily temperatures would be similar. 

The general philosophy in model calibration is to vary the least well-known input values within a 

representative range to maximize the model’s goodness-of-fit. 

Mean daily water temperatures were the initial focus of model calibration. Once mean daily 

temperature predictions were as accurate as possible, the focus shifted to maximum daily water 

temperatures. Calibration of maximum temperatures was accomplished via several empirical 

coefficients that account for heat gained over and above the daily average, depending on 

hydrologic and meteorological conditions. 

An extensive analysis was made of the potential sources of model error by correlating many 

of the model inputs or calculated values with the model’s residuals. Because of the preponderance 

of wide, shallow pools on these rivers, air temperature and relative humidity might tend to 

dominate the thermal response rate when discharge was low. However, only air temperature was 

marginally statistically significant in both models. Discharge was also a statistically significant 

contributor to model error on the Neversink River, a result that may have been attributable solely to 

outlying points that represented spills or rainstorms rather than more “normal” reservoir release 

conditions. 

Development of Statistical Models 

The accuracy of the SNTEMP models did not universally meet our initial calibration 

criteria. For this reason, we developed purely statistical models for several important locations 

throughout the two networks as a possible alternative to SNTEMP. Although somewhat less 

flexible in predicting temperatures at unmeasured locations, statistical models might correct for 

systematic biases in the SNTEMP models that we were unable to eliminate otherwise. 

According to Theurer and others (1984), there are several forms of regression models that 

appear to provide a high degree of correlation in predicting stream temperatures, at least for 

“natural” conditions. They range from simple harmonic models: 

Tw = Tavg + ΔT0 · cos[(2π/365) (Di - P)] (1) 

Where Tw = estimated water temperature (mean or maximum), 

Tavg = average water temperature over all observations, 

T0 = half the initial temperature range over all observations, 

Di

 = Julian day number for day i, and 

P = Phase delay in timing of the maximum seasonal temperature. 

to polynomial models: 

Tw = ao + a1Ta

 + a2W + a3R + a4S+ a5H + a6Q+a7Ta

2

 + a8W2 + a9R2 + a10S2 + a11H2 + a12Q2 (2) 

where Tw = estimated water temperature (mean or maximum), 

Ta

 = air temperature (maximum or mean), 

W = wind speed, 

R = relative humidity, 

S = percent possible sun (cloud cover), 
22

H = maximum possible solar radiation for the latitude and time of year, and 

Q = discharge 

to models that incorporate, at least to some degree, the physics of heat flux and heat transport. After 

a considerable amount of trial and error, we settled on a general regression model of the form: 

Tw = k + a1Ta+ a2Ta

2

+ a3H + a4W + a5S + a6Q1 + a7(Q2-Q1) + a9YTw (3) 

where Tw = the estimated water temperature, 

Ta = air temperature, 

H = relative humidity, 

W = wind speed, 

Q1 = the discharge at the temperature node, 

(Q2-Q1) = the upstream to downstream accretion volume, and 

YTw = “yesterday’s temperature estimate.” 

Though initially derived using standard minimization of residuals, final regressions were 

adjusted by weighting each daily squared residual by its dependent water temperature. This step 

was done because our experiments had shown that regressions of this type often tended to 

underestimate high water temperatures. The weighting served to improve the fit of the regressions 

at high temperatures. 

Model Selection for the DRDSS 

As a matter of operational efficiency, we selected the multivariate statistical model 

(equation 3) for use in the DRDSS. Use of SNTEMP as a data source for the DRDSS would have 

required generating the system hydrology in OASIS as input to SNTEMP, and then running the 

temperature model for each scenario to be tested. The advantage of the statistical model was that 

the meteorological data and model parameters could be incorporated directly into the DRDSS, 

along with hydrologic information from OASIS, to produce daily predicted temperatures of the 

same general accuracy as those produced by SNTEMP. Whereas SNTEMP can be used in the 

absence of calibration water temperatures, however, these data are necessary to calibrate the 

statistical model. Sufficient water temperature data for this purpose were not available for the 

Neversink River, so temperature simulations for that river were not included in the prototype 

version of the DRDSS. 

A second disconnect in the scenarios generated for the DRDSS was that the meteorological 

records available for use in equation 3 extended only from 1994–2004 whereas the period of record 

for the hydrologic time series was from 1977–2003. We considered several options for matching 

the periods of record, including the generation of a stochastic meteorological series to use as input 

to equation 3, irrespective of the period of record. We also considered simple repetition of the 

meteorological data series as necessary to fill in all the dates in the hydrologic series. After 

weighing the advantages and disadvantages of the various models, we determined that using actual 

meteorological data from an actual period of record was preferable to the stochastic model. 

Consequently, the DRDSS contains three options for meteorological data. The first is the simple 

repetition model, which is basically a copy and paste of the existing record over previous decades. 

The second option is to use “normal” meteorological conditions for each day, calculated as the 

average air temperature, humidity, cloud cover, and wind speed from the 10-year period of record. 

The third option is a “worst case” meteorological scenario, developed as a combination of daily 
23

maximum air temperature, humidity, and wind speed, and minimum cloud cover. Although none of 

the options is completely realistic, in combination they can provide a range of “expectable” water 

temperatures for different water management scenarios and meteorological conditions. 

Time Series Generation and Summarization 

The structure of the DRDSS requires baseline and alternative management scenarios (or 

two competing alternatives), typically derived by changing the operating rules for one or more of 

the reservoirs in the OASIS model. Management scenarios translate into changes in flow regime, 

reservoir storage, temperature, habitat suitability, and other decision variables. DRDSS scores are 

based on the amount of change each decision variable exhibits between the alternative and the 

baseline over a specified time period. 

Habitat Time Series and Metrics 

The habitat time series is the fundamental building block for quantifying the effect of an 

alternative on the habitat for a target organism (Bovee and others, 1998). Construction of a habitat 

time series (fig. 7) is relatively straight-forward, requiring two essential components: a time series 

of discharges (either baseline or alternative) and a relationship between discharge and habitat area. 

Units of habitat can be expressed as the actual area of habitat within the study site (m2

), normalized 

habitat area expressed as an area per unit length of stream (m2/km), or as total habitat (in hectares) 

for the entire segment, calculated by multiplying the normalized habitat area by the length of the 

segment. The third option was preferred by the Subcommittee and the Commission, so habitat areas 

in the DRDSS were expressed accordingly. 

For every discharge in the flow series, there is a corresponding habitat value from the 

discharge-habitat function. Assembling a time series of habitat is merely a matter of translating the 

discharges for each time step (hours, days, weeks) into their associated habitat values and recording 

the translated values back to the time step. 

Hydroperiods and Habitat Persistence 

The year was divided into three hydroperiods, representing distinct hydrologic and 

biological conditions: October 1–April 15 (spawning/incubation period for brown trout), April 16–

June 30 (emergence of young of the year fish), and July 1–September 30 (summer growing 

season). The October–April hydroperiod was further subdivided to quantify habitat persistence for 

brown trout spawning and incubation. October and November were considered the spawning 

months, and incubation was designated for the period from December 1 through April 15. Habitat 

time series as shown in figure 7 were constructed for pertinent target organisms for each 

hydroperiod, with the exception of habitat persistence for brown trout spawning-incubation and for 

dwarf wedgemussels. 

We selected a spawning discharge to be used as input to the persistence table by calculating 

a trimmed mean discharge based on the central 60 percent of the flows for the months of October 

and November for each year to represent a “typical” discharge that would have occurred during 

spawning. Because habitat persistence is a function of the difference between the spawning flow 

and the incubation flow, we found the maximum and minimum discharges occurring between 

December 1 and April 15 to determine the persistent habitat areas for both combinations of 

spawning and incubation flow-pairs. The smaller of the two areas was then retained as the 

spawning-incubation value for a given year. The habitat time series for spawning-incubation was 

thus constructed as an annual series of these least-area values. 
24

0

1,000

2,000

3,000

4,000

0 50 100 150 200 250 300 350 400

Day in series

Discharge in ft3/s

A

Time step 190

Flow = 2,121 cfs

0

2

4

6

8

0 2,000 4,000 6,000

Discharge, in ft3/s

Habitat area, in ha/km

B

Flow = 2,121 cfs

Area = 6.24 ha

0

2

4

6

8

0 50 100 150 200 250 300 350 400

Day in series

Habitat area, in ha/km

C

Time step 190

Area = 6.24 ha

0

1,000

2,000

3,000

4,000

0 50 100 150 200 250 300 350 400

Day in series

Discharge in ft3/s

A

Time step 190

Flow = 2,121 cfs

0

2

4

6

8

0 2,000 4,000 6,000

Discharge, in ft3/s

Habitat area, in ha/km

B

Flow = 2,121 cfs

Area = 6.24 ha

0

2

4

6

8

0 50 100 150 200 250 300 350 400

Day in series

Habitat area, in ha/km

C

Time step 190

Area = 6.24 ha

Figure 7. Elements used in the construction of a habitat time series: A, flow time series, B, flow 

versus habitat function, and C, the resulting habitat time series. 
25

Habitat persistence for the dwarf wedgemussel differed from spawning-incubation in two 

significant ways. First, dwarf wedgemussels reside in the system year-round, rather than being 

confined to a single hydroperiod. Second, spawning-incubation persistence is primarily affected by 

the maximum differential between the spawning flow and the limiting incubation flow, regardless 

of the time interval between the two events. Dwarf wedgemussels are much more sensitive to rapid 

changes in flow, as they have the capacity to move to suitable habitat if the change is slow enough. 

To mimic this phenomenon, we conducted a search of the daily flows for each hydroperiod to find 

the largest flow differential over any consecutive five-day period. The maximum and minimum 

flows associated with this flow differential were then selected as the two flows to input to the 

persistence table for each hydroperiod, for each year. 

Habitat Duration Statistics 

Comparisons of baseline versus habitat time series plots or data may be qualitatively 

informative, but not very useful for quantification of potentially limiting events. There is a general 

consensus that the most likely habitat limitations for a life stage or species occur during periods 

when habitat is restricted (Bovee and others, 1998). These habitat bottlenecks are defined by 

episodes when the habitat value falls below the median of the habitat time series. More restrictive 

definitions of limiting events can be applied, and in the case of the DRDSS, we used the average of 

the lowest 25 percent of the habitat values in the time series as the criterion for comparison. 

The determination of the cut-off point for any quartile or probability in a habitat time series 

is based on the concept of the habitat duration curve. Such curves were constructed for baseline and 

alternative conditions by the following method: 

1. Habitat time series for each target organism and hydroperiod were sorted from highest to lowest 

and assigned a rank. 

2. The probability that any particular habitat value would be equaled or exceeded was calculated 

as: 

P = r/(n+1) (4) 

Where P = the probability that a value in the series will be equaled or exceeded, 

r is the rank of the sorted data, and 

n is the number of values in the series. 

For comparative purposes in the DRDSS, the average of the lowest 25 percent of the values 

in the series was calculated and retained as the habitat metric for the series representing baseline 

and alternative scenarios, respectively. This metric was chosen for two specific reasons. First, 

biological populations tend to be limited during periods when resources (including space) are most 

restricted (Nehring and Anderson, 1993; Bovee and others, 1994). These values represent a 

compilation of the potentially limiting habitat events associated with either series. Second, the 

metric is a special case of a trimmed mean that removes the possibility that an increased occurrence 

of large values could offset an increased occurrence of small values. In essence, this combination 

could be worse from a biological perspective, but the average for the two series could be the same, 

indicating no impact. 

Habitat Duration Series 

This variation of the habitat duration concept is used to illustrate daily variability in a time 

series. In essence, the habitat duration series is a box-and-whisker plot for every day in the year. 
26

The habitat duration series plot (fig. 8) was constructed by sorting the data hierarchically by month 

and day in ascending order, and magnitude of habitat in descending order. Probabilities of 

exceedance were calculated for each day using equation 4, and the lowest 25 percent of the values 

for baseline and alternative were plotted. Baseline habitat values in figure 8 are depicted as a light 

blue band. The solid lines on figure 8 represent the boundaries for the lowest-quartile habitat values 

for the alternative. 

0

20,000

40,000

60,000

Jan

FebMar

Apr

May

Jun

Jul

Aug

Sept

Oct

Nov

Dec

Habitat area, in m2/km

Base -Low 25% Alt - Min Alt - Low 25% Base - Min

Figure 8. Comparison of habitat duration series for baseline and alternative scenarios. 

The purpose of presenting information in this format is to allow decisionmakers to check 

for potentially adverse habitat conditions that might be masked by aggregation and summarization. 

The scoring metric derived from the habitat duration curve is an average from several month’s data. 

It is possible to increase the metric during part of the hydroperiod and reduce it during another part, 

resulting in no change to the average. An example of this phenomenon can be seen in figure 8 

during the months of July and August. For much of July, the light blue band for the baseline 

appears above the red and black quartile boundaries for the alternative. During August, the pattern 

is reversed. Compared to the baseline, the magnitude of the lowest 25 percent of the habitat events 

was reduced during July but elevated during August under the alternative scenario. Although the 

average of this metric over both months might show little or no difference between the baseline and 

alternative, the duration series plot indicates that this conclusion would not be entirely correct from 

a biological perspective. 
27

Structure and Functions of the DRDSS 

A prototype DRDSS (Version 1.0) was developed for presentation to the Commission and 

Subcommittee in October 2005. Version 1.0 was intended to have operational functionality (input 

data would provide real results) but not operational efficiency. Its primary purpose was to 

demonstrate the organization of the DRDSS and its use as a decisionmaking tool. During the 

developmental stages of the DRDSS, an Excel® spreadsheet was used as the computational 

platform. The advantages of this format were that changes could be made rapidly and transparently. 

The disadvantages were that the spreadsheets were very large (>160 MB), cumbersome to modify, 

and not portable to routinely available computers (required 2 GB of RAM and 3.0 MHz processor 

or better). However, given the volatility of earlier versions of the DRDSS, we believed that the 

advantages outweighed the disadvantages. Owing to the size of the files and slow turn-around on 

runs, however, Version 1.0 provided information only for a limited number of sites (7), and a 

small, fixed number of flows (10 years). 

As a result of the October meeting and subsequent discussions with the Commission and 

Subcommittee, a number of revisions were suggested for a more operational Version 2.0. This 

version involved improvements in operational efficiency, expansion of capability to all study sites, 

and a more extensive set of decision variables and scoring mechanisms. Minor modifications have 

been made to version 2.0 as a result of extensive beta-testing performed by members of the 

Commission and Subcommittee, as well as debugging and quality assurance testing within the 

USGS Fort Collins Science Center. The current version (2.11) operates identically to version 2.0, 

but owing to the modifications, results from comparable runs using the two versions will deviate 

slightly from one another. 

Structure and Organization 

One of the most noticeable changes from Version 1.0 to Version 2.11 is that all the 

calculations in Version 1.0 were done in a single, very large spreadsheet. Version 2.11 is organized 

differently, having a master spreadsheet (DSS_AGG.xls) and four subsidiary spreadsheets 

(henceforth referred to as SUBS) for each of the river segments (DSS_WB, DSS_EB, DSS_DEL, 

and DSS_NVR). Reformatted output from OASIS, selected meteorological data, and user-supplied 

parameters are entered directly to the master spreadsheet, but the calculations for each of the 

decision variables occurs in the SUBS (fig. 9). Results from all the computations in the SUBS are 

then returned to the master spreadsheet, both as a whole system summary, and as segment-specific 

raw scores. Thus, the user can review the overall system response to an alternative, and also 

examine the details about each segment. 

Functionality 

The DRDSS requires as input two continuous (no days or flows missing) streams of daily 

flows for each of the identified study sites. One data set is for a baseline case and the other for an 

alternative. These data are derived from the OASIS model. Scoring comparisons are made for 

changes in habitat characteristics for pertinent target species and guilds, water temperature 

characteristics, spill and reservoir storage, and water deliveries and exports. 

Habitat Time Series Metrics 

Two types of habitat area calculations are used in the DRDSS. The first type is defined as 

“instantaneous habitat,” derived from the hydroperiod habitat time series and habitat duration 

statistics. This is the habitat area for a target species that occurs at a specific discharge, with no 
28

consideration of antecedent or subsequent discharges in the series. The second type is based on a 

time series of persistent habitat, where antecedent or subsequent discharges are directly accounted 

for in the calculation of the habitat metric. Habitat persistence analyses were performed for trout 

spawning-incubation and dwarf wedgemussel habitat only. 

Layout and Information Flow

DSS_AGG

Flows 

from 

OASIS

Met

Data

Parameters

DSS

WB

DSS

EB

DSS

DEL

DSS

NVR

Figure 9. Layout and information flow in DRDSS Version 2.11. Blue arrows indicate the pathways 

for hydrologic data, orange arrows indicate temperature-related information, and gold arrows are 

for habitat metrics returned from each site to the master spreadsheet. The tan arrow represents 

user-supplied options that select different computational algorithms and scoring criteria. DSS_AGG; 

master spreadsheet. DSS_WB, DSS_EB, DSS_DEL, DSS_NVR; subsidiary spreadsheets for the 

West Branch, East Branch, Delaware main stem, and Neversink River, respectively. 

Temperature 

Water temperature was calculated using equation 3 with meteorological data from the 

Monticello weather station and streamflow data from OASIS as inputs. Temperatures were 

calculated only from May 1 to September 30. Three sets of meteorological data, as described in the 

section “Model Selection for the DRDSS” can be found in a separate database, met_data.xls. The 

first set of meteorological input data consists of a replication of the Monticello data to 

corresponding days for the period of record 1954–2003 (for example, May 1, 1954, has the same 

meteorological data as May 1, 1993; May 1, 1955, is the same as May 1, 1994; and so forth). The 

two sets of pseudometrological data (normal and worst-case) for the 50 year period 1953–2003 

contained in the met_data.xls file are repetitive (for example, each May 1 has the same data). 

Temperature is accounted for in two separate places in the DRDSS scoring summary. First, 

the number of days when temperatures exceed the specified thresholds are counted for the baseline 

and alternative conditions, with scores reported as percent change (in day counts), change in the 

number of days, and change in degree-days. Threshold temperatures can be adjusted by the DRDSS 

operator for each river segment on the page labeled “Parameters.” The second reference to 
29

temperature is defined as “Temperature-conditioned habitat.” If temperature in a given segment 

exceeds the temperature threshold on a particular day, the habitat value for that day is set to zero. 

The zero-habitat days are then included in a time series analysis following the same protocols 

explained above for steady-flow habitat. 

Spills 

Spills are calculated as the difference between the discharge measured immediately 

downstream from a dam and the outlet capacity of the dam. If the discharge in the tailwater exceeds 

the outlet capacity, then a spill has occurred by definition. The severity of the spill is calculated as 

the proportion of the total flow in the tailwater that is attributable to the spill. There are three 

default levels of spill intensity. If the spill accounts for 10 percent or less of the tailwater discharge, 

it is considered minor. If it accounts for 50 percent or more of the discharge, it is considered major. 

Spills between 10 and 50 percent of the total discharge are considered moderate. Thresholds for 

each class of spill intensity can be adjusted by the user on the “Parameters” page. Spills are counted 

by hydroperiod for each category, and scores are reported as percent changes and as day-counts. 

Storage Volume 

Reservoir storage volume and triggers representing drought watch, drought warning, and 

drought are obtained directly from the OASIS model. Scores are derived by computing the number 

of days that reservoir storage fell into one of the three drought categories under the baseline and the 

alternative. Scores are reported as a percent change in the number of days within each drought 

category, and also as the difference in days counted in each category. 

Montague Deliveries 

Delivery of Decree flows at Montague is calculated in the OASIS model for both the 

baseline and alternative operations. Scoring of Montague deliveries is based on the number of days 

under each scenario when the specified delivery is not met. Delivery targets are variable, depending 

on system water supply, and the rules determining the targets are coded into OASIS. Three scoring 

criteria are used on the summary page of the DRDSS. A minor violation is scored if the delivery is 

less than 10 percent below the target, and a major violation is recorded if the delivery is more than 

50 percent below the target. Moderate violations are recorded for deliveries between 10 and 50 

percent below target. Scores are recorded as percent change in frequency of violations within each 

category and also as the actual change in frequency. 

Out of System Deliveries 

Similar to the scoring for Montague, deliveries to New York City and to the diversion at the 

Delaware-Raritan (D& R) Canal near Trenton, N.J., are calculated in OASIS, as are the delivery 

targets. In both cases, scoring is reported as both percentage and frequency. The defaults for minor, 

moderate, and major shortages are the same as for the Montague targets, and the classification 

criteria are likewise user-adjustable. 

DRDSS Output and Displays 

Decision support systems can be developed in a bewildering array of styles, functions, and 

purposes. The philosophy guiding our development of the DRDSS was that it should concisely 

display the consequences of a management alternative to a wide array of competing resource 

values, yet should be sufficiently transparent to allow diagnosis of causes and effects. The 
30

following sections describe some of the tabular and graphical outputs that are produced by the 

DRDSS, and how they can be accessed. For full user documentation, the reader is referred to 

appendix 5. 

The Summary Scoring Page 

The summary scoring page is the second page in the DSS_AGG.xls master spreadsheet, but 

is generally the initial focal point when reviewing the outcome of a scenario run. Figure 10 shows 

the layout and some of the features associated with the scoring summary. Delaware DSS Run Date: 11/06/06 Start date End date

Provisional Version 2.11 Baseline: Rev1 10/1/1990 to 9/29/2000

Summary Alternative: Rev 7 10/1/1990 to 9/29/2000

October - April 15

West Branch East Branch Main Hancock-Callicoon Neversink

Resource Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab

Trout Adult, ha 21% 13.50 8% 12.31 2% 7.80 16% 13.42

Trout Spawning/Incu, ha 91% 2.39 3% 0.10 1% 0.06 155% 4.79

SSCV, ha 8% 1.11 -9% -2.54 0% 0.04 18% 3.83

SFCV, ha 52% 2.44 41% 1.04 1% 0.02 27% 3.79

Shad Juvenile, ha

Shad Spawning, ha

Dwarf Wedge Mussel, ha 3% 0.08

Spills, minor, count -6% -1.00 14% 1.00 0% Base, Alt =0

Spills, moderate, count 13% 2.00 15% 2.00 -17% -1.00

Spills, major, count -13% -2.00 -14% -4.00 0% 0.00

April 16 - June

West Branch East Branch Main Hancock-Callicoon Neversink

Resource Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab

Trout Adult, ha 16% 11.47 16% 11.41 4% 6.77 4% 6.84 1% 3.25 1% 2.50 13% 11.57

Trout Spawning/Incu, ha

SSCV, ha 2% 0.24 2% 0.24 -4% -0.84 -3% -0.77 0% 0.02 0% 0.00 24% 4.43

SFCV, ha 11% 0.40 11% 0.40 8% 0.24 8% 0.24 0% 0.02 0% 0.01 16% 2.34

Shad Juvenile, ha

Shad Spawning, ha 16% 5.50 16% 5.50 5% 6.50 4% 6.10 55% 7.86

Dwarf Wedge Mussel, ha 0% -0.02

Spills, minor, count 0% 0.00 14% 1.00 0% 0.00

Spills, moderate, count 0% 0.00 -21% -8.00 -50% -1.00

Spills, major, count 0% 0.00 -5% -2.00 -10% -2.00

July - September

West Branch East Branch Main Hancock-Callicoon Neversink

Resource Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab

Trout Adult, ha -2% -1.45 -2% -1.45 16% 23.40 16% 22.86 -1% -2.52 -2% -7.48 37% 30.01

Trout Spawning/Incu, ha

SSCV, ha 22% 3.06 22% 3.06 -10% -3.29 -10% -3.27 2% 0.80 1% 0.44 43% 10.85

SFCV, ha 85% 5.19 85% 5.19 -4% -0.72 -4% -0.71 11% 1.50 10% 1.38 42% 7.08

Shad Juvenile, ha 9% 7.48 9% 7.48 1% 2.11 -1% -1.59 17% 7.00

Shad Spawning, ha

Dwarf Wedge Mussel, ha -5% -0.34

Spills, minor, count 0% Base, Alt =0 0% Base, Alt =0 -50% -1.00

Spills, moderate, count 0% 0.00 0% 0.00 100% 1.00

Spills, major, count 0% Base, Alt =0 0% 0.00 0% 0.00

Full Period Scores

West Branch East Branch Main Hancock-Callicoon Neversink

Pct Chg Δ Days Pct Chg ΔDegDays Pct Chg Δ Days Pct Chg ΔDegDays Pct Chg Δ Days Pct Chg ΔDegDays Pct Chg Δ Days Pct Chg ΔDegDays

Δ Days > Threshold C 0% 0.00 -2% -0.14 0% 0.00 -1% -0.13 150% 6.00 399% 4.97

Global Scores Run Settings

Montague Flow Pct Chg Δ Days Out of System Deliveries Pct Chg Δ Days

Montague, minor shortage -27% -113.00 NYC, minor shortage 0% 0.00 Maximum Water Temperature West Branch 20 New York Diversion Magnitude Mild 10

Montague, moderate shortage -22% -19.00 NYC, moderate shortage 0% Base, Alt =0 (degrees C) East Branch 20 (% minimum delivery) Major 50

Montague, major shortage 0% Base, Alt =0 NYC, major shortage 0% Base, Alt =0 Main Stem 25

Montague, cfs-days -24% -12464.00 New York City, bg 0% Base, Alt =0 Neversink 20 New York Diversion Magnitude Mild 10

(% minimum delivery) Major 50

System Drought Pct Chg Δ Days Pct Chg Δ Days Spill Magnitude Mild, < 10

Days at Level 1 -22% -92.00 NJ, minor shortage 0% 0.00 (% outflow capacity) Major, > 50 Meterological Series Actual

Days at Level 2 39% 89.00 NJ, moderate shortage 0% Base, Alt =0

Days at Level 3 0% Base, Alt =0 NJ, major shortage 0% Base, Alt =0 Montague Shortage Magnitude Mild, < 10

New Jersey, bg 0% Base, Alt =0 (% minimum flow) Major, > 50

System Storage, bg 0% -2358.70

Figure 10. Layout of the scoring summary page in the DRDSS. 

The header lines at the top of the page contain information regarding the dates of the run, 

the names of the baseline and the alternative used in the OASIS run, and the period of record used 

in the time series analyses. The top portion of the scoring summary reports the habitat time series 

outcomes of the scenario for each of the target organisms of concern. This section of the report is 

divided in rows by hydroperiod, arrayed in blocks from hydroperiod 1 to hydroperiod 3, and in 

columns by major river system. From left to right, information is provided for the West Branch, 

East Branch, Delaware mainstem, and Neversink River. Biological decision variables and resources 

of concern are listed in the first column and repeated for each hydroperiod. 

The cells in the summary page are conditionally formatted such that the cell background 

turns green if the scenario results in an improvement for a decision variable and red if it results in a 

decrement. In this portion of the summary, a change in a decision variable of less than 10 percent 

(±) was considered to be undetectable, so the cells do not change color unless the habitat metric 

changes by an amount greater than 10 percent. Some of the cells have grey backgrounds, which 
31

indicate that the decision variable is not applicable for that cell. For example, American shad do not 

inhabit the West Branch, and temperature conditioning of habitat was not performed for 

hydroperiod 1, so these cells all have grey backgrounds. 

Also included in the upper portion of the scoring sheet are three rows of scores for spills, 

divided among hydroperiods and river components. The conditional formatting of these cells is 

different from that used to score changes in habitat. First, spills are tracked by magnitude and 

defined as minor, moderate, or major. The percentages refer to the proportion of spills in each 

category occurring under the two alternatives being compared. By definition, spills were 

considered to be undesirable, so any scenario that increases their frequency by 10 percent or more 

results in a red background. Conversely, if the scenario results in a 10 percent or greater decrease in 

the frequency of spills, the scoring cell turns green. The cell retains a white background if the 

change in frequency is less than 10 percent in either direction. 

Figure 11 shows an expanded view of the biological resources and spills scores for the West 

and East Branches for hydroperiods 1 and 2. The various target species and guilds are shown listed 

under “Resource” in the leftmost column. Four columns appear for each resource under the header 

for the river system. Columns labeled “PctChg” contain the percentage change in the metric, 

whether change in habitat area or spill frequency. Columns labeled “ ΔHab” refer to the change in 

habitat area in hectares for the entire river reach. This metric is based on the prorated sum of the 

calculated habitat areas for all the segments in the reach. Columns labeled “ΔTCondHab” refer to 

changes in temperature-conditioned habitat area. 

 The lower portion of the summary page (fig. 12) contains “full period” and “global” 

variables. These include items such as the number of days when temperature thresholds were 

exceeded; violations of the delivery targets for Montague, New York City, and the D & R 

diversion; and changes in the frequency of drought warning and drought events caused by changes 

in system reservoir storage. Violations of temperature thresholds are considered full period rather 

than global because they are recorded separately by river component, but for the entire summer 

(hydroperiods 2 and 3) instead of each hydroperiod. Otherwise, the conditional formatting for this 

variable is the same as for spills. If the frequency of violations increases by more than 10 percent 

the cell turns red and if it decreases by more than 10 percent it turns green. 
32

Delaware DSS Run Date: 11/06/06

Provisional Version 2.11 Baseline: Rev1

Summary Alternative: Rev 7

October - April 15

West Branch East Branch

Resource Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab

Trout Adult, ha 21% 13.50 8% 12.31

Trout Spawning/Incu, ha 91% 2.39 3% 0.10

SSCV, ha 8% 1.11 -9% -2.54

SFCV, ha 52% 2.44 41% 1.04

Shad Juvenile, ha

Shad Spawning, ha

Dwarf Wedge Mussel, ha

Spills, minor, count -6% -1.00 14% 1.00

Spills, moderate, count 13% 2.00 15% 2.00

Spills, major, count -13% -2.00 -14% -4.00

April 16 - June

West Branch East Branch

Resource Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab

Trout Adult, ha 16% 11.47 16% 11.41 4% 6.77 4% 6.84

Trout Spawning/Incu, ha

SSCV, ha 2% 0.24 2% 0.24 -4% -0.84 -3% -0.77

SFCV, ha 11% 0.40 11% 0.40 8% 0.24 8% 0.24

Shad Juvenile, ha

Shad Spawning, ha 16% 5.50 16% 5.50

Dwarf Wedge Mussel, ha

Spills, minor, count 0% 0.00 14% 1.00

Spills, moderate, count 0% 0.00 -21% -8.00

Spills, major, count 0% 0.00 -5% -2.00

Figure 11. Expanded view of the scoring summary page, showing details of the scores and 

metrics for biological resources and spills in the DRDSS. 

Full Period Scores

West Branch East Branch

Pct Chg Δ Days Pct Chg ΔDegDays Pct Chg Δ Days Pct Chg

Δ Days > Threshold C 0% 0.00 -2% -0.14 0% 0.00 -1%

Global Scores

Montague Flow Pct Chg Δ Days Out of System Deliveries Pct Chg Δ Days

Montague, minor shortage -27% -113.00 NYC, minor shortage 0% 0.00

Montague, moderate shortage -22% -19.00 NYC, moderate shortage 0% Base, Alt =0

Montague, major shortage 0% Base, Alt =0 NYC, major shortage 0% Base, Alt =0

Montague, cfs-days -24% -12464.00 New York City, bg 0% Base, Alt =0

System Drought Pct Chg Δ Days Pct Chg Δ Days

Days at Level 1 -22% -92.00 NJ, minor shortage 0% 0.00

Days at Level 2 39% 89.00 NJ, moderate shortage 0% Base, Alt =0

Days at Level 3 0% Base, Alt =0 NJ, major shortage 0% Base, Alt =0

New Jersey, bg 0% Base, Alt =0

System Storage, bg 0% -2358.70

Figure 12. Expanded view of the scoring summary page, showing details of the scores and 

metrics for the full period and global resources in the DRDSS. 

Delivery targets and deliveries for Montague, New York City, and the D&R canal are 

reported daily from OASIS and are input directly into the DRDSS (on the “Flows” page). The 

DRDSS records the number of days under baseline and alternative when the delivery was less than 

the target. These shortages are then classified according to severity (minor, moderate, or major) 

using criteria similar to those applied to spills. The defaults are <10 percent, 10 to 50 percent not 

inclusive, and >50 percent for each classification, respectively, but can be changed by the user to 

impose more- or less-restrictive definitions of severity. 
33

The system drought component tracks daily reservoir storage and records the number of 

times that total volume drops below the rule curves for drought watch (Level 1), drought warning 

(Level 2) or drought (Level 3). Like data for deliveries, this information is generated by OASIS and 

is imported directly into the DRDSS. Scoring for this component is nearly identical to that used for 

delivery targets, except that the criteria for the defaults (<10 percent, 10–50 percent not inclusive, 

>50 percent) cannot be changed. 

The column headers in figure 12 are fairly self-explanatory and follow labeling 

nomenclature similar to that described for the river-specific metrics. A primary difference is the 

column labeled “ΔDegDays,” which refers to the difference in degree-days between the two 

alternatives. Degree days are calculated as the sum of temperatures greater than the threshold for all 

the days in the time series. Dividing “ΔDegDays” by the term “ΔDays” provides the average 

magnitude of the temperature change (unless ΔDays = 0). 

The Raw Scores Page 

The raw scores page (fig. 13) is the third page in the DSS_AGG.xls master workbook. The 

layout and format of this page is similar to the summary page, but information is provided at the 

segment level, rather than at the whole-river scale. Aside from being segment-specific, the raw 

scores page displays total segment habitat areas for the baseline and scenario, with and without 

temperature conditioning. 

Delaware DSS RunDate: 11/06/06

Provisional Version 2.11 Baseline: Rev1 10/01/90

Resource Scores Alternative: Rev 7 10/01/90

By Study Site October - April 15

Hydro Period

October - April 15 WB0 WB0 WB1 WB1

No Termperature adjustment Termperature adjustment No Termperature adjustment Termperature adjustment

Resource Base Scenario % Change Base Scenario % Change Base Scenario % Change Base Scenario % Change

Trout Adult, sq m 2967 5357 81% 2967 5357 81% 27001 32373 20% 27001 32373 20%

Trout Spawning/Incu, sq m 0 27 26655% 1117 2134 91%

SSCV, sq m 5358 6000 12% 5358 6000 12% 5083 5450 7% 5083 5450 7%

SFCV, sq m 384 2458 539% 384 2458 539% 1950 2646 36% 1950 2646 36%

Shad Juvenile, sq m

Shad Spawning, sq m

Dwarf Wedge Mussel, sq m

Δ Days > Threshold

April 16 - June April 16 - June

Resource WB0 WB0 WB1 WB1

Trout Adult, sq m 5848 6850 17% 5413 6277 16% 28979 33712 16% 28979 33712 16%

Trout Spawning/Incu, sq m

SSCV, sq m 4259 4516 6% 4004 4254 6% 4527 4589 1% 4527 4589 1%

SFCV, sq m 2304 2759 20% 2138 2587 21% 1196 1293 8% 1196 1293 8%

Shad Juvenile, sq m

Shad Spawning, sq m

Dwarf Wedge Mussel, sq m

Δ Days > Threshold 12 12 0% 0 0 0%

July - September July - September

Resource WB0 WB0 WB1 WB1

Trout Adult, sq m 15563 13183 -15% 15563 13183 -15% 36282 36057 -1% 36282 36057 -1%

Trout Spawning/Incu, sq m

SSCV, sq m 4565 5457 20% 4565 5457 20% 5304 6465 22% 5304 6465 22%

SFCV, sq m 3800 4521 19% 3800 4521 19% 1974 4070 106% 1974 4070 106%

Shad Juvenile, sq m

Shad Spawning, sq m

Dwarf Wedge Mussel, sq m

Δ Days > Threshold 0 0 0% 0 0 0%

Figure 13. Expanded view of the “Raw scores” page showing details of the segment-specific 

scores and metrics for habitat and temperature decision variables. 
34

Flow and Storage Time Series Graphics 

Time series plots of segment discharges and reservoir storage (fig. 14) can be found on the 

“FlowPlots” page of the DSS_AGG.xls master spreadsheet. These plots show the hydrologic 

outcomes of an OASIS run chronologically, comparing the baseline (dark blue) with the alternative 

(pink). The plots can be scrolled horizontally to examine selected portions of the record. These 

charts are useful in determining what really happened in OASIS as opposed to what the alternative 

was intended to do. When such disparities occur, they provide insights into the mechanics of 

implementing an alternative and may help link the means with the desired ends. Flow and storage 

time series are also valuable during interpretation and diagnosis of habitat time series results. 

Cannonsville Storage Cannonsville Storage

WB0 Stilesville WB0 Stilesville

0.00

20.00

40.00

60.00

80.00

100.00

120.00

10/1/199011/1/199012/1/1990

1/1/19912/1/19913/1/19914/1/19915/1/19916/1/19917/1/19918/1/19919/1/1991

10/1/199111/1/199112/1/1991

1/1/19922/1/19923/1/19924/1/19925/1/19926/1/19927/1/19928/1/19929/1/1992

bg

1.00

10.00

100.00

1000.00

10000.00

10/1/199011/1/199012/1/1990

1/1/19912/1/19913/1/19914/1/19915/1/19916/1/19917/1/19918/1/19919/1/1991

10/1/199111/1/199112/1/1991

1/1/19922/1/19923/1/19924/1/19925/1/19926/1/19927/1/19928/1/1992

9/1/1992

cfs

Figure 14. Time series of daily storage volumes and segment discharges from the “FlowPlots” 

page of the DSS_AGG.xls master spreadsheet. 

Flow, Temperature, and Storage Duration Curves 

Duration curves are commonly used to consolidate large masses of time series data, such as 

illustrated in figure 14, into a concise graphical form. Rather than depicting time series events 

chronologically, they are displayed as a cumulative probability function (fig. 15). Construction of a 

duration curve follows the same procedure described for “habitat duration statistics” except that 

daily flows, temperatures, or storage volumes are plotted instead of habitat areas. These curves are 

not restricted to the lowest quartile, but show the entire probability distribution. However, the Yaxis scaling can be changed to magnify portions of the curve that might be of greater interest, such 

as the low flow portion of a hydrograph. 
35

The duration curves and the mechanisms for drawing them are located on the segmentspecific SUBS workbooks. The variables and sites for which the duration plot are generated are 

selected on the page entitled “<site_name>DurCurve” as illustrated in figure 16. Drop-down menus 

of variables and sites are made available by clicking on the green activator buttons, and individual 

variables and sites selected by highlighting them. When the purple button is activated, the chart 

(fig. 15, for example) on the “DurCurveChart” page is automatically updated. An important 

distinction between this application and the chronological time series plots is that individual 

duration curve plots are not saved but change each time they are updated. Therefore, it is necessary 

to print each graph or save it to a separate file as it is generated if the information is to be saved for 

later reference. 

WB0 Flows

0

500

1,000

1,500

2,000

2,500

3,000

20% 40% 60% 80%

Flow in ft3/s

Baseline

Alternative

04/03/0 Delaware DSS: Rev 1 and Rev 7

Provisional Version 2.1

Figure 15. Example flow duration curves for site WB0. The Y-axis was truncated at 3,000 cubic 

feet per second in order to amplify the differences in the lower flow range. 
36

Figure 16. The “DurCurve” page of one of the subsidiary workbooks of the DRDSS, showing 

locations and functions of control buttons used to update a duration chart. 

Habitat Duration Series Graphics 

Habitat duration series charts are also site-specific and generated for only one habitat or 

flow variable at a time. Like the duration curves, these charts and their drivers are located in each 

of the SUBS workbooks under the pages entitled “DurSerChart” and “<site name>DurSer,” 

respectively. The target resource (either habitat for one of the target organisms or the flow) and the 

segment can be selected from dropdown menus in the “DurSer” pages (fig. 17). The period of 

record is predefined by the period extracted from OASIS, but the number of leap days in the record 

must be specified on this page. Leap days are eliminated, but the program must be able to find them 

in the record. Selection of the variable and site follows the same general procedure described for 

the duration charts, but the user can specify whether the habitat duration series are temperatureconditioned (button 4). Button 5 (Update Duration) activates a macro that re-sorts the data. Once 

the duration series has been updated, button 6 (Update Chart) activates a macro that re-draws the 

graph on the “DurSerChart” page (see fig. 8, for example). Like the duration curves, these graphs 

are not saved automatically. Users are advised to copy and export graphs before each update. 
37

Page tab for duration series controls

Select Target

Here

Select Site

Here Temperature

Conditioning

On/off switch

Re-sorter

Macro Chart

Update

Macro

Page tab for duration series controls

Select Target

Here

Select Site

Here Temperature

Conditioning

On/off switch

Re-sorter

Macro Chart

Update

Macro

Page tab for duration series controls

Select Target

Here

Select Site

Here Temperature

Conditioning

On/off switch

Re-sorter

Macro Chart

Update

Macro

Figure 17. The “DurSer” page of one of the subsidiary workbooks of the DRDSS, showing 

locations and functions of control buttons used to update a duration series chart. 

Results 

Habitat Versus Discharge Functions 

There are several ways to express the habitat versus discharge functions extracted from the 

map data. The discharges used to derive the habitat time series represent the average daily flows 

that would have occurred in a specific segment under baseline and alternative operating scenarios. 

This expression is necessary for generation of the habitat time series, but some form of normalized 

discharge may be more useful for comparing the habitat versus flow functions among the various 

sites. Similarly, habitat can be expressed as a total area for the segment or normalized for 

comparison. Discharge was expressed as segment-specific mean daily discharge and as “unit 

discharge,” calculated as cubic meters per second per square mile of drainage. Habitat areas are 

expressed as both normalized area (ha/km) and as total area for the segment (ha). Conversion 

constants for each of the study segments are summarized in table 7, and habitat versus flow 

statistics are presented in appendix 3. 
38

Table 7. Conversion constants and normalizing terms by segment. 

Segment 

Length 

(km) 

Drainage area 

(mi2) 

WB0 3.9 456 

WB1 23.2 595 

EB0 12.2 372 

EB1 15.1 458 

EB2 25.6 784 

DEL1 14.9 1,590 

DEL2 17.1 1,668 

DEL3 11.7 1,820 

NVR0 12.9 113 

NVR1 26 171 

NVR2 23.7 307 

Shallow-slow habitat types were maximized at the lowest range of flows, with peak areas 

occurring around 0.1 to 0.3 cubic feet per second per square mile (fig. 18). Shallow-fast habitat 

types were also maximized at relatively low flows (fig. 19), but not as low as shallow-slow habitat 

types. At discharges less than 0.3 cubic feet per second per square mile, water velocities tend to be 

too low to be suitable for this guild, but at discharges greater than 0.6 cubic feet per second per 

square mile, depths become too large to be considered “shallow.” 

Habitat areas for juvenile trout (fig. 20) and juvenile American shad (fig. 21) behaved 

similarly with respect to discharge, both showing an increase in area at discharges up to about 0.6 

cubic feet per second per square mile and then declining at discharges greater than 0.9 cubic feet 

per second per square mile. Habitat areas for adult trout (fig. 22) and American shad spawning (fig. 

23) also show similar patterns, but are shifted slightly to the right on the discharge axis, reflecting a 

preference for deeper and faster water than juveniles as indicated in Table 2. Habitat areas for these 

two target organisms were maximized in the range of about 1–3 cubic feet per second per square 

mile. In all cases, depths are too shallow for discharges below the peaks of the curves and 

velocities are too high at discharges above the peaks. 
39

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

0 1 2 3 4 5 6 7 8 9 10

Normalized discharge, in ft3/s/mi2

Unit habitat area,

in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 18. Normalized discharge versus unit habitat areas for the shallow-slow current velocity 

guild at 11 sites in the upper Delaware River. 

0.00

0.50

1.00

1.50

2.00

2.50

0 1 2 3 4 5 6 7 8 9 10

Normalized discharge, in ft3/s/mi2

Unit habitat area,

in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 19. Normalized discharge versus unit habitat areas for the shallow-fast current velocity 

guild at 11 sites in the upper Delaware River. 
40

0.00

2.00

4.00

6.00

8.00

10.00

0 1 2 3 4 5 6 7 8 9 10

Normalized discharge, in ft3/s/mi2

Unit habitat area,

in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 20. Normalized discharge versus unit habitat areas for juvenile trout (Salmo trutta) at 11 

sites in the upper Delaware River. 

0.00

2.00

4.00

6.00

8.00

10.00

12.00

0 1 2 3 4 5 6 7 8 9 10

Normalized discharge, in ft3/s/mi2

Unit habitat area,

in ha/km

EB2 DEL1 DEL2 DEL3

Figure 21. Normalized discharge versus unit habitat areas for juvenile American shad (Alosa 

sapidissima) at four sites in the upper Delaware River. 
41

0.00

4.00

8.00

12.00

16.00

0 1 2 3 4 5 6 7 8 9 10

Normalized discharge, in ft3/s/mi2

Unit habitat area,

in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 22. Normalized discharge versus unit habitat areas for adult trout (Salmo trutta) at 11 sites 

in the upper Delaware River. 

0.00

2.00

4.00

6.00

8.00

10.00

12.00

0 1 2 3 4 5 6 7 8 9 10

Normalized discharge, in ft3/s/mi2

Unit habitat area,

in ha/km 

EB2 DEL1 DEL2 DEL3

Figure 23. Normalized discharge versus unit habitat areas for spawning American shad (Alosa 

sapidissima) at four sites in the upper Delaware River. 
42

Mesohabitat Versus Discharge 

Patterns of mesohabitat distributions similar to those of the discharge versus habitat area 

functions were evident among the sites. Figures 24–29 and figures 31–32 illustrate the normalized 

areas of mesohabitat types, roughly in descending order of abundance. Pools were the most 

prominent mesohabitat types at low flows, but were replaced by fast runs at the higher flows (figs. 

24 and 25). The shift from pool to fast run was indicative of the lesser influence of riffles as 

hydraulic controls (features in the stream that create backwater effects in an upstream direction) at 

higher discharges, resulting in an overall increase in hydraulic gradients. At low flows, runs were 

second in abundance to pools at most sites (fig. 26) and were also replaced by fast runs at the 

higher discharges. It is noteworthy that the two West Branch sites and the site farthest upstream on 

the Neversink (NVR0) did not develop very much fast run mesohabitat (except at WB1 at the 

highest flow), retaining about the same amount of pool and run mesohabitats across the entire range 

of discharges. We believe that this phenomenon may be related to the formation of very large 

deltas at tributaries in these sites. These deltas provided strong and stable hydraulic control over a 

wide range of flows, so the backwater effects needed to create pools were retained, rather than 

being “drowned out” at higher discharges. 

Riffles (fig. 27) were comparatively less extensive than the other major mesohabitat types 

and generally mimicked the pattern of the shallow-fast habitat guild with respect to streamflow. 

The exceptions occurred at WB0 and in the Neversink (both for riffles and SFCV) where the 

amount of riffle habitat either remained constant or increased with increased discharge. 

As might be expected, the area of inundated vegetation (fig. 28) was zero or near zero at all 

sites at low discharges and increased steadily as discharges increased. With the exception of DEL1, 

the area of inundated vegetation was minimal at discharges less than about 3 cubic feet per second 

per square mile. 

0.00

2.00

4.00

6.00

8.00

10.00

12.00

0123456

Normalized discharge, in ft3/s/mi2

Unit pool area,

in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 24. Normalized discharge versus unit areas of pool mesohabitat types. 
43

0.00

2.00

4.00

6.00

8.00

10.00

12.00

0123456

Normalized discharge in ft3/s/mi2

Unit area of fast runs,

in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 25. Normalized discharge versus unit areas of fast run mesohabitat types. 

0.00

1.00

2.00

3.00

4.00

5.00

6.00

0123456

Normalized discharge, in ft3/s/mi2

Unit area of runs, 

in ha/km

WB0 WB1 EB0 EB1 EB2 DEL1

DEL2 DEL3 NVR0 NVR1 NVR2

Figure 26. Normalized discharge versus unit areas of run mesohabitat types. 
44

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

2.00

0123456

Normalized discharge, in ft3/s/mi2

Unit riffle area,

in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 27. Normalized discharge versus unit areas of riffle mesohabitat types. 

0.00

2.00

4.00

6.00

0123456

Normalized discharge, in ft3/s/mi2

Unit area of inundated vegetation,

in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 28. Normalized discharge versus unit areas of inundated vegetation. 

The most dynamic mesohabitat types were side arms (fig. 29), backwaters (fig. 30), and 

disconnected areas (fig. 32). The variability in the areas of these three mesohabitat types occurred, 
45

at least in part, because they would change from one type to another depending on the discharge. 

An area might be disconnected at a very low flow, become connected as a backwater at an 

intermediate flow, and connected from top and bottom (thereby becoming a side arm) at higher 

flows. Generally speaking, side arms tended to be most consistent in stream reaches containing 

large, highly dissected, and relatively high-elevation islands (for example, DEL3,WB1, EB0, EB1, 

and the Neversink sites), and most variable where the side channels were around midchannel, lowelevation bars (for example, DEL1, WB0, EB2). A complicating factor was that not all sections of 

divided channel were classified as side arms. According to our definitions, bisected channels were 

not classified as side arms, even though they may have exhibited some of the same properties. 

0.00

0.75

1.50

2.25

3.00

0123456

Normalized discharge, in ft3/s/mi2

Unit area of side channels,

in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 29. Normalized discharge versus unit areas of side arm mesohabitat types. 

As discharge decreases, inflow to a side arm may cease and the extant channel will be come 

a backwater or a disconnected channel (fig. 30). Although neither mesohabitat type accounted for a 

large proportion of the surface area of any of the sites, some were impressive nonetheless. At the 

lowest classified discharges, very large backwaters formed at EB0, WB1, WB0, DEL1, and NVR0 

(fig. 31). In each instance, the channel was divided by a very long island, with inflow to one of the 

divisions cut off at low flows. A similar process occurred at intermediate flows at DEL1 and DEL3, 

both in perched side arms that were disconnected from the main channel at low flows and 

connected at the inflow and outflow at high discharges. 

Disconnected mesohabitats (fig. 32) occurred wherever there was a depression of sufficient 

depth that water could be stored by groundwater connection, but with no surface connection. 

Disconnected areas did not account for a significant proportion of mesohabitat area, although 

relatively large disconnects occurred at WB0 and at DEL2. In both of these locations, the outflows 

of long side arm channels were elevated sufficiently to isolate the channels at low discharges. At 

DEL2, the isolated channel persisted at lower flows, but the surface area was smaller owing to 

lower ground water levels. 
46

Direction of flowDirection of flow

Figure 30. Backwaters and disconnected channels at 25 ft3/s (0.7 m3/s) in site EB0. Note the 

hydraulic connections or lack thereof at the outflow and the inflow in the north channel. At slightly 

higher discharges, the inflow is connected and the entire area is classified as a side arm. 

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0123456

Normalized discharge, in ft3/s/mi2

Unit area of backwaters,

in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 31. Normalized discharge versus unit areas of backwaters mesohabitat types. 
47

0.00

0.05

0.10

0.15

0.20

0.25

01234567

Normalized discharge, in ft3

/s/mi2

Unit area of disconnected channels,

 in ha/km

WB0 WB1 EB0 EB1

EB2 DEL1 DEL2 DEL3

NVR0 NVR1 NVR2

Figure 32. Normalized discharge versus unit areas of disconnected mesohabitat types. 

Habitat Persistence 

Habitat persistence was determined as the intersection of habitat patches for spawning and 

incubation and for dwarf wedgemussels for every combination of simulated discharges at each site. 

The exported and compiled persistence tables for both target organisms can be found in appendix 4. 

Trout Spawning and Incubation 

At most of the sites, maximum areas of persistent habitat appeared to be more influenced by 

the overlap of suitable incubation conditions than by the suitable spawning areas (figs. 33–43). This 

phenomenon was manifested by the maximum areas of the three-dimensional surfaces being 

elongated along the axes for spawning flows and narrowed along the incubation flow axis. The 

exception to this rule was at EB0 (fig. 36), which exhibited the opposite tendency. Here the 

maximum areas were associated with a fairly narrow range of spawning flows, but a relatively wide 

band of incubation flows. 

At all sites, the axes of the maximum persistent area bands were essentially orthogonal, 

indicating a relatively independent relation between spawning and incubation flows in the optimal 

range. If the spawning and incubation flows were within their optimal ranges, it did not matter 

whether the incubation flows were higher or lower than the spawning flows. In contrast, all sites 

illustrated dependence among the smaller areas of persistent habitat, where the influences of the 

flow differential between spawning flows and the incubation flows were more evident. At higher 

spawning flows, more persistent habitat occurred if the incubation flows were also high. Likewise, 

persistent habitat associated with low spawning flows was more abundant if the incubation flows 

were also low. 
48

We found distinct groupings of optimal flow ranges for spawning and incubation among the 

sites. In the West Branch, maximum persistent habitat occurred with spawning flows between 

approximately 0.8 and 3.8 ft3/s/mi2 and incubation flows between 0.8 and 1.6 ft3/s/mi2 (figs. 33 and 

34). Regardless of discharge, however, WB1 contained a much larger area of spawning and 

incubation habitat than WB0, attributable primarily to the more extensive pool tail-outs that 

occurred at WB1. Overall, spawning and incubation habitat persistence at WB0 appeared to be 

somewhat more sensitive to incubation flows than at WB1, as indicated by the width of the 

polygons along the x (incubation) axis. 

In the upper East Branch, maximum values of persistent spawning and incubation habitat 

occurred at much lower discharges than in the West Branch. At EB0, spawning flows between 0.4 

and 1.0 ft3

/s/mi2 and incubation flows in the range of 0.2 to 4 ft3/s/mi2 produced the maximum area 

of persistent habitat (fig. 35). At EB1, persistent habitat was maximized with spawning flows 

between 0.8 and 2.7 ft3

/s/mi2 and incubation flows between 0.5 and 0.8 ft3/s/mi2 (fig.36). Maximum 

habitat persistence at EB2 (fig. 37) was similar to the West Branch sites with respect to spawning 

flows (maximized between 0.8 and 2.7 ft3/s/mi2), but more like the other East Branch sites with 

respect to incubation flows (maximized between 0.8 and 0.9 ft3

/s/mi2). 

The habitat versus discharge response surfaces for the main-stem Delaware sites were 

similar to those of the West Branch and lower East Branch. DEL1 (fig. 38) exhibited the widest 

range of optimal spawning flows of any of the sites (0.3 to 6.2 ft3/s/mi2), but was constrained by a 

relatively narrow range of optimal incubation flows (0.5 to 0.9 ft3/s/mi2). Unlike most of the other 

sites, persistent habitat areas were not skewed at the upper and lower ranges of spawning and 

incubation discharges. Maximum areas of persistent habitat at DEL2 and DEL 3 (figs. 39 and 40) 

occurred over flow ranges more typical of the West Branch and exhibited the high-low flow skew 

observed at other sites. At DEL2, the largest areas of persistent habitat occurred with spawning 

flows in the range of 0.7 to 2.5 ft3/s/mi2 and incubation flows of 0.7 to 1.0 ft3/s/mi2. 

Smaller areas of persistent habitat were highly skewed at DEL2, indicating that spawning 

and incubation at this site were relatively sensitive to flow differential. DEL3 provided the largest 

maximum area of persistent spawning and incubation habitat of all the sites (fig. 40). Maximum 

persistent habitat for this site occurred with a range of spawning flows from 0.8 to 3.5 ft3/s/mi2 and 

incubation flows from 0.7 to 1.0 ft3

/s/mi2. 

The maximum areas of persistent spawning and incubation habitat in the Neversink River 

occurred at higher ranges of normalized discharges than in any of the other rivers studied. 

Maximum persistent habitat at site NVR0 occurred with a range of spawning flows from 1.2 to 3.6 

ft3/s/mi2 and incubation flows from 1.5 to 1.7 ft3/s/mi2 (fig. 41). Peak areas of persistent habitat at 

NVR1 occurred with spawning flows between 0.7 and 5 ft3

/s/mi2 and incubation flows ranging 

from 1.4 to 1.8 ft3/s/mi2 (fig. 42). Both sites showed relatively little skew in persistent habitat areas 

at the high and low extremes of discharge, indicating somewhat lower sensitivity to flow 

differential than other sites. Persistent habitat at site NVR2 was maximized with spawning flows 

between about 1 and 3 ft3/s/mi2 and incubation flows of 1 to 1.5 ft3/s/mi2 (fig. 43). The differences 

in the response surfaces for the Neversink compared with those of the other sites may be an artifact 

of stream order and size. All the Neversink sites had considerably smaller drainage areas (our 

discharge normalizing term) than the other sites, and the overall slopes were greater by 50 to 300 

percent (except at NVR1, which was comparable to EB0). Consequently, the Neversink may have 

resembled more of a headwater stream than the others we studied. 
49

0.02

0.03

0.05

0.07

0.12

0.18

0.27

0.42

0.65

1.02

1.58

2.45

3.81

5.92

9.19

0.020.030.050.070.120.180.270.420.651.021.582.453.815.929.19

Incubation flow, in ft3/s/mi2

0-500 500-1,000

1,000-1,500 1,500-2,000

2,000-2,500 2,500-3,000

3,000-3,500 3,500-4,000

4,000-4,500 4,500-5,000

Persistent habitat area, in m2

/km

Spawing flow, in ft3/s/mi2

Figure 33. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawningincubation habitat at site WB0. 

0.08

0.11

0.15

0.21

0.30

0.42

0.59

0.83

1.19

1.60

2.25

3.20

4.51

6.35

8.96

0.080.110.150.210.300.420.590.831.191.602.253.204.516.358.96

0-500 500-1,000

1,000-1,500 1,500-2,000

2,000-2,500 2,500-3,000

3,000-3,500 3,500-4,000

4,000-4,500 4,500-5,000

5,000-5,500 5,500-6,000

6,000-6,500 6,500-7,000

7,000-7,500 7,500-8,000

8,000-8,500 8,500-9,000

9,000-9,500 9,500-10,000

Persistent habitat area, in m2

/km

Spawing flow, in ft3/s/mi2

Incubation flow, in ft3/s/mi2

Figure 34. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawningincubation habitat at site WB1. 
50

Spawing flow, in ft3/s/mi2

Incubation flow, in ft3/s/mi2

0.02

0.05

0.10

0.24

0.54

1.25

2.89

6.68

0.020.030.050.070.100.150.240.350.540.821.251.902.894.40

0-500 500-1,000

1,000-1,500 1,500-2,000

2,000-2,500 2,500-3,000

3,000-3,500 3,500-4,000

Persistent habitat area, in m2

/km

Figure 35. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawningincubation habitat at site EB0. Spawing flow, in ft3/s/mi2

Incubation flow, in ft3/s/mi2

0.08

0.15

0.31

0.60

1.17

2.23

4.38

8.45

0.080.120.150.220.310.430.600.841.171.612.233.144.386.078.45

c

0-500 500-1,000

1,000-1,500 1,500-2,000

2,000-2,500

Persistent habitat area, in m2

/km

Figure 36. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawningincubation habitat at site EB1. 
51

Spawing flow, in ft3/s/mi2

Incubation flow, in ft3/s/mi2

0.13

0.25

0.57

1.28

1.96

4.08

8.54

0.130.190.250.380.570.891.281.781.962.684.085.878.5412.62

0-500 500-1,000

1,000-1,500 1,500-2,000

2,000-2,500 2,500-3,000

3,000-3,500 3,500-4,000

4,000-4,500 4,500-5,000

5,000-5,500 5,500-6,000

Persistent habitat area, in m2

/km

Figure 37. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawningincubation habitat at site EB2. Spawing flow, in ft3/s/mi2

Incubation flow, in ft3/s/mi2

0.22

0.36

0.60

1.00

1.69

2.84

4.75

7.99

0.220.270.360.470.600.781.001.311.692.202.843.694.756.177.99

0-500 500-1,000

1,000-1,500 1,500-2,000

2,000-2,500 2,500-3,000

3,000-3,500 3,500-4,000

4,000-4,500 4,500-5,000

5,000-5,500 5,500-6,000

6,000-6,500

Persistent habitat area, in m2

/km

Figure 38. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawningincubation habitat at site DEL1. 
52

Spawing flow, in ft3/s/mi2

Incubation flow, in ft3/s/mi2

0.28

0.46

0.74

1.21

1.98

3.22

5.25

8.55

0.280.360.460.580.740.951.211.541.982.523.224.115.256.708.55

0-500 500-1,000

1,000-1,500 1,500-2,000

2,000-2,500 2,500-3,000

3,000-3,500

Persistent habitat area, in m2

/km

Figure 39. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawningincubation habitat at site DEL2. 

0.28

0.46

0.76

1.26

2.09

3.46

5.73

9.50

0.280.360.460.580.760.981.261.622.092.693.464.455.737.389.50

Incubation flow, in ft3/s/mi2

0-500 500-1,000

1,000-1,500 1,500-2,000

2,000-2,500 2,500-3,000

3,000-3,500 3,500-4,000

4,000-4,500 4,500-5,000

5,000-5,500 5,500-6,000

6,000-6,500 6,500-7,000

7,000-7,500 7,500-8,000

8,000-8,500 8,500-9,000

9,000-9,500 9,500-10,000

10,000-10,500 10,500-11,000

11,000-11,500 11,500-12,000

12,000-12,500 12,500-13,000

13,000-13,500

Persistent habitat area, in m2

/km

Spawing flow, in ft3/s/mi2

Figure 40. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawningincubation habitat at site DEL3. 
53

0.12

0.16

0.22

0.28

0.37

0.50

0.66

0.87

1.19

1.56

2.06

2.72

3.59

4.78

6.31

0.120.160.220.280.370.500.660.871.191.562.062.723.594.786.31

Spawing flow, in ft3/s/mi2

Incubation flow, in ft3/s/mi2

0-500 500-1000

1000-1500 1500-2000

2000-2500 2500-3000

3000-3500

Persistent habitat area, in m2/km

Figure 41. Normalized discharge versus unit area of persistent (Salmo trutta) trout spawningincubation habitat at site NVR0. Spawing flow, in ft3/s/mi2

Incubation flow, in ft3/s/mi2

0.17

0.23

0.32

0.44

0.62

0.85

1.19

1.65

2.30

3.19

4.43

6.16

8.55

11.88

16.51

0.170.230.320.440.620.851.191.652.303.194.436.168.5511.8816.51

0-500 500-1000

1000-1500 1500-2000

2000-2500 2500-3000

Persistent habitat area, in m2/km

Figure 42. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawningincubation habitat at site NVR1. 
54

Spawing flow, in ft3/s/mi2

Incubation flow, in ft3/s/mi2

0.23

0.30

0.38

0.49

0.64

0.82

1.07

1.38

1.78

2.30

2.97

3.83

4.95

6.39

9.37

0.230.300.380.490.640.821.071.381.782.302.973.834.956.399.37

0-500 500-1000

1000-1500 1500-2000

2000-2500 2500-3000

3000-3500 3500-4000

4000-4500 4500-5000

5000-5500 5500-6000

6000-6500

Persistent habitat area, in m2/km

Figure 43. Normalized discharge versus unit area of persistent trout (Salmo trutta) spawningincubation habitat at site NVR2. 

Dwarf Wedgemussel 

The analysis of persistence in dwarf wedgemussel habitat differed from that of trout 

spawning and incubation in one significant aspect. Two different sets of habitat suitability criteria 

were used to define the polygons intersected in the spawning-incubation maps, whereas the same 

criteria were evaluated at combinations of paired discharges for dwarf wedgemussels. In the 

spawning-incubation case, the habitat polygons were independent spatially, but order-dependent. 

For dwarf wedgemussels, the opposite was true. Consequently, the three-dimensional habitat 

response surfaces (figs. 44, 45, and 46) for the dwarf wedgemussel were highly skewed along a 

diagonal between pairs of discharges. This bias occurred because the largest area of persistent 

habitat for any pair of discharges occurs when they are the same. As the two discharge pairs deviate 

from one another, the area of persistent habitat always decreases. In this sense, habitat persistence 

for the dwarf wedgemussel (as we described it) was more sensitive to flow differential than it was 

for spawning and incubation. The second obvious characteristic of the habitat response surfaces for 

dwarf wedgemussels is that they were highly symmetrical (kaleidoscopic), compared to the more 

amorphous surfaces for spawning and incubation. This phenomenon was an artifact of comparing 

pairs of discharge for the same target organism in an order-independent fashion. That is, a flow 

combination of 100 ft3

/s and 1,000 ft3/s produced the same amount of persistent mussel habitat as a 

combination of 1,000 ft3

/s and 100 ft3/s. This was decidedly not the case for spawning and 

incubation. 
55

0.22

0.27

0.36

0.47

0.60

1.00

1.31

1.69

2.20

2.84

3.69

4.22

4.75

6.17

7.990.22

0.270.360.470.601.001.311.692.202.843.694.224.756.177.99

Discharge #1, in ft3/s/mi2

Discharge #2, in ft3/s/mi2 

0.00-0.25 0.25-0.50

0.50-0.75 0.75-1.00

1.00-1.25 1.25-1.50

1.50-1.75 1.75-2.00

2.00-2.25 2.25-2.50

2.50-2.75 2.75-3.00

3.00-3.25 3.25-3.50

3.50-3.75 3.75-4.00

Persistent habitat area, in hectares

Figure 44. Normalized discharge versus area of persistent dwarf wedgemussel (Alasmidonta 

heterodon) habitat at site DEL1. 

Discharge #1, in ft3/s/mi2

Discharge #2, in ft3/s/mi2 

0.28

0.36

0.46

0.58

0.95

1.21

1.54

1.98

2.52

3.22

4.11

4.68

5.25

6.70

8.55

0.280.360.460.580.951.211.541.982.523.224.114.685.256.708.55

0.00-0.25 0.25-0.50

0.50-0.75 0.75-1.00

1.00-1.25 1.25-1.50

1.50-1.75 1.75-2.00

2.00-2.25 2.25-2.50

2.50-2.75 2.75-3.00

3.00-3.25 3.25-3.50

3.50-3.75 3.75-4.00

4.00-4.25 4.25-4.50

4.50-4.75 4.75-5.00

5.00-5.25 5.25-5.50

5.50-5.75 5.75-6.00

6.00-6.25 6.25-6.50

Persistent habitat area, in hectares

Figure 45. Normalized discharge versus area of persistent dwarf wedgemussel (Alasmidonta 

heterodon) habitat at site DEL2. 
56

Discharge #1, in ft3/s/mi2

Discharge #2, in ft3/s/mi2 

0.28

0.36

0.46

0.58

0.76

0.98

1.26

1.62

2.09

2.69

3.46

4.45

5.73

7.38

9.50

0.280.360.460.580.760.981.261.622.092.693.464.455.737.389.50

0.00-0.25 0.25-0.50

0.50-0.75 0.75-1.00

1.00-1.25 1.25-1.50

1.50-1.75 1.75-2.00

2.00-2.25 2.25-2.50

2.50-2.75 2.75-3.00

3.00-3.25 3.25-3.50

3.50-3.75 3.75-4.00

4.00-4.25 4.25-4.50

4.50-4.75

Persistent habitat area, in hectares

Figure 46. Normalized discharge versus area of persistent dwarf wedgemussel (Alasmidonta 

heterodon) habitat at site DEL3. 

The habitat response surfaces were also highly influenced by the characteristics of the 

mussel beds observed by Dr. Lellis and his colleagues during the 2002 survey. We did not 

normalize habitat areas for dwarf wedgemussels, so each response surface and persistence table 

reflects a site-specific total area. Because the mussel beds at DEL2 were much larger than those at 

the other two main-stem sites, the maximum area of the response surface for that site (fig. 45) was 

also considerably larger. The response to discharge for DEL1 and DEL 2 were quite similar, with 

the maximum area occurring at discharges in the range of about 0.9 to 2.5 ft3

/s/mi2 (figs. 44 and 

45). In contrast to the upper two main-stem sites, persistent habitat at DEL3 was optimized at 

discharges between 0.5 and 1 ft3

/s/mi2 (fig. 46). 

A review of the characteristics of the mussel beds at DEL1 and DEL2 revealed a high 

degree of hydraulic and spatial similarity. Mussels were primarily found near the south shoreline in 

low velocity (but not stagnant) shallow pools, typically less than 1 m deep (figs. 47 and 48). The 

observed locations of the mussels at DEL3 may have affected the lower range of optimal flows for 

its habitat response surface. Whereas mussels at the upper sites were observed in shallow, slow 

pools, a number of mussels at the DEL3 site were found along the margins of a fairly steep riffle 

(fig. 49). The distribution of mussels at DEL3 influenced our delineation of the mussel bed in the 

original mapping exercise. The optimal flow range for this site may be lower because a large 

portion of the mussel bed was included in the riffle. Consequently, shear stresses likely became 

limiting at higher flows, thereby reducing the utility of the area as habitat for mussels. It is 

probably not too surprising that after a flood event in 2005, mussels were found in about the same 

locations at the two upper sites, but were not found at DEL3 (William Lellis, USGS, oral commun., 

April 2006). 
57

Figure 47. Depth and velocity distributions at DEL1 for the approximate discharge at which dwarf 

wedgemussel (Alasmidonta heterodon) observations (green dots) were made during 2002. 

Figure 48. Depth and velocity distributions at DEL2 for the approximate discharge at which dwarf 

wedgemussel (Alasmidonta heterodon) observations (green dots) were made during 2002. 
58

Figure 49. Depth and velocity distributions at DEL3 for the approximate discharge at which dwarf 

wedgemussel (Alasmidonta heterodon) observations (green dots) were made during 2002. 

DRDSS Demonstration Run 

To illustrate the operation and interpretation of Version 2.11 of the DRDSS, we performed 

an analysis of two alternative operating plans developed through the Commission and sanctioned 

by the Decree parties, known as Revision 1 and Revision 7. For this demonstration, we used the 

OASIS output for Revision 1 to serve as the baseline condition. 

The intent of Revision 7 was to increase the lowest discharges that had occurred under 

Revision 1 to provide more habitat area during the (presumed) most limiting flow events in each 

hydroperiod. This objective was achieved in OASIS by withholding releases from the reservoirs 

during periods of relatively higher inflows, and releasing additional water when needed to meet 

downstream flow targets. Figure 50 shows flow duration curves for the two West Branch sites 

during hydroperiod 1 to illustrate the general changes in streamflow that resulted from the 

imposition of the Revision 7 rules for the water years 1990–2000. The basic pattern of change was 

to reduce flows in the intermediate range and increase the magnitudes of the lowest flows, as 

indicated by the differences between the solid and dashed lines on figure 50. Similar changes 

occurred in the other rivers and hydroperiods, with some subtle differences. Figure 51 shows the 

changes in storage volume at the three reservoirs that resulted from Revision 7. Essentially, storage 

was kept the same or somewhat higher under Revision 7, which may have provided the buffer 

needed for higher releases during low flow periods. 

For this demonstration run, we used the “normal” meteorological data set and left all the 

adjustable scoring thresholds at their default values, except for the temperature threshold for the 

main stem Delaware, which was set to 25oC. Summary results for the run are shown in figure 52. 
59

0

500

1,000

1,500

2,000

0% 20% 40% 60% 80% 100%

Percent equaled or exceeded

Discharge, in ft3/s

WB0_REV1 WB0_REV7

WB1_REV1 WB1_REV7

Figure 50. Flow duration curves for sites WB0 and WB1 on the West Branch, for hydroperiod 1 

(October–April) from water years 1990–2000, under the operating rules for Revision 1 and Revision 7. 

0

20

40

60

80

100

120

140

160

0% 20% 40% 60% 80% 100%

Percent equaled or exceeded

Storage volume, in billions of gallons

Cannonsville_Rev1 Cannonsville_Rev7

Pepacton_Rev1 Pepacton_Rev7

Neversink_Rev1 Neversink_Rev7

Figure 51. Storage duration curves for the three New York City reservoirs, for hydroperiod 1 

(October–April) from water years 1990–2000, under the operating rules for Revision 1 and Revision 7. 
60

Delaware DSS Run Date: 11/06/06 Start date End 

Provisional Version 2.11 Baseline: Rev1 10/1/1990 to 9/29/2

Summary Alternative: Rev 7 10/1/1990 to 9/29/2

October - April 15

West Branch East Branch Main Hancock-Callicoon Neversink

Resource Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg

Trout Adult, ha 21% 13.50 8% 12.31 2% 7.80

Trout Spawning/Incu, ha 91% 2.39 3% 0.10 1% 0.06

SSCV, ha 8% 1.11 -9% -2.54 0% 0.04

SFCV, ha 52% 2.44 41% 1.04 1% 0.02

Shad Juvenile, ha

Shad Spawning, ha

Dwarf Wedge Mussel, ha 3% 0.08

Spills, minor, count -6% -1.00 14% 1.00

Spills, moderate, count 13% 2.00 15% 2.00

Spills, major, count -13% -2.00 -14% -4.00

April 16 - June

West Branch East Branch Main Hancock-Callicoon Neversink

Resource Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg

Trout Adult, ha 16% 11.47 16% 11.41 4% 6.77 4% 6.84 1% 3.25 1% 2.50

Trout Spawning/Incu, ha

SSCV, ha 2% 0.24 2% 0.24 -4% -0.84 -3% -0.77 0% 0.02 0% 0.00

SFCV, ha 11% 0.40 11% 0.40 8% 0.24 8% 0.24 0% 0.02 0% 0.01

Shad Juvenile, ha

Shad Spawning, ha 16% 5.50 16% 5.50 5% 6.50 4% 6.10

Dwarf Wedge Mussel, ha 0% -0.02

Spills, minor, count 0% 0.00 14% 1.00

Spills, moderate, count 0% 0.00 -21% -8.00

Spills, major, count 0% 0.00 -5% -2.00

July - September

West Branch East Branch Main Hancock-Callicoon Neversink

Resource Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg Δ Hab Pct Chg ΔTCondHab Pct Chg

Trout Adult, ha -2% -1.45 -2% -1.45 16% 23.40 16% 22.86 -1% -2.52 -2% -7.48

Trout Spawning/Incu, ha

SSCV, ha 22% 3.06 22% 3.06 -10% -3.29 -10% -3.27 2% 0.80 1% 0.44

SFCV, ha 85% 5.19 85% 5.19 -4% -0.72 -4% -0.71 11% 1.50 10% 1.38

Shad Juvenile, ha 9% 7.48 9% 7.48 1% 2.11 -1% -1.59

Shad Spawning, ha

Dwarf Wedge Mussel, ha -5% -0.34

Spills, minor, count 0% Base, Alt =0 0% Base, Alt =0

Spills, moderate, count 0% 0.00 0% 0.00

Spills, major, count 0% Base, Alt =0 0% 0.00

Full Period Scores

West Branch East Branch Main Hancock-Callicoon Neversink

Pct Chg Δ Days Pct Chg ΔDegDays Pct Chg Δ Days Pct Chg ΔDegDays Pct Chg Δ Days Pct Chg ΔDegDays Pct Chg

Δ Days > Threshold C 0% 0.00 -2% -0.14 0% 0.00 -1% -0.13 150% 6.00 399% 4.97

Global Scores Run Settings

Montague Flow Pct Chg Δ Days Out of System Deliveries Pct Chg Δ Days

Montague, minor shortage -27% -113.00 NYC, minor shortage 0% 0.00 Maximum Water Temperature West Branch 20 New York Diversion Magnitude

Montague, moderate shortage -22% -19.00 NYC, moderate shortage 0% Base, Alt =0 (degrees C) East Branch 20 (% minimum delivery)

Montague, major shortage 0% Base, Alt =0 NYC, major shortage 0% Base, Alt =0 Main Stem 25

Montague, cfs-days -24% -12464.00 New York City, bg 0% Base, Alt =0 Neversink 20 New York Diversion Magnitude

(% minimum delivery)

System Drought Pct Chg Δ Days Pct Chg Δ Days Spill Magnitude Mild, < 10

Days at Level 1 -22% -92.00 NJ, minor shortage 0% 0.00 (% outflow capacity) Major, > 50 Meterological Series

Days at Level 2 39% 89.00 NJ, moderate shortage 0% Base, Alt =0

Days at Level 3 0% Base, Alt =0 NJ, major shortage 0% Base, Alt =0 Montague Shortage Magnitude Mild, < 10

New Jersey, bg 0% Base, Alt =0 (% minimum flow) Major, > 50

System Storage, bg 0% -2358.70

Figure 52. Summary scores page for DRDSS demonstration run comparing Revision 1 and Revision 

7 alternatives. 

Based on the information summarized in figure 52, one could conclude that for most of the 

decision variables considered, Revision 7 resulted in improved or unchanged conditions compared 

to Revision 1, at least for the decade of the 1990’s. The incidence of minor-to-moderate spill events 

from Cannonsville Reservoir increased during hydroperiod 1, from Pepacton Reservoir during 

hydroperiods 1 and 2, and from Neversink Reservoir during hydroperiod 3. Water deliveries to 

Montague, New York City, and the D&R diversion appeared to have improved or remained the 

same under Revision 7 operations. The only biologically-oriented warning flag occurred in the 

main stem Delaware, where the temperature threshold of 25oC was exceeded on six more days 

under Revision 7 than under Revision 1. 

Discussion 

One of the most important characteristics of the DRDSS is its feedback mechanism. The 

primary driver of the DRDSS is the OASIS model, the output of which serves as input to a network 

of linked habitat and temperature models. This characteristic results in a cascading effect among 

the decision variables. For example, a simple change to the rule curves for one reservoir in an 

OASIS run can propagate throughout the hydrologic network, influencing the operations of other 
61

reservoirs, the magnitude and timing of stream discharges, the habitat dynamics of the receiving 

streams, and summer water temperatures. Feedback can be highly informative because it can reveal 

unanticipated consequences from a proposed action. Feedback can also be frustrating for the same 

reason, sometimes tempting decisionmakers to assume that something was wrong with the models, 

rather than examining their own paradigms and assumptions. From a pragmatic viewpoint, 

decisionmaking based on model output should consist of at least two separate processes: 

interpretation and evaluation. Interpretation refers to understanding the cause and effect relations 

between an input scenario and the results displayed in the decision support system. Evaluation 

refers to judging the relative degrees of success or failure to meet the multiple objectives of a 

scenario. Interpretation is necessary to determine why a certain outcome was produced. Evaluation 

is necessary to determine whether one alternative is substantially “better” than another. Both 

processes should include an understanding and acknowledgement of limitations of the models 

(including OASIS), as well as any preconceived notions of what the model results should have 

been. 

Interpretation of Results 

In the DRDSS, instream habitat is defined by the interactions among discharge, gradient, 

channel structure, and the physical requirements of the aquatic organisms. With a few exceptions, a 

typical response function between discharge and habitat area appears as a skewed bell-shaped 

curve, or in the case of persistent habitat, as a dome-shaped surface. The common characteristic of 

these functions is that habitat area tends to increase as discharge increases in the low-to-moderate 

flow range, but then decreases as discharge continues to increase. Where channel structure and 

gradient are similar, the peak of the habitat-discharge curve would be expected to occur at or near 

the same relative (normalized) discharge, although the magnitude of habitat area will vary as a 

function of channel width and concomitant surface area, as illustrated in figures 18–23. 

In contrast, shallow-slow habitat types in streams dominated by single-thread channels (see 

appendix 1) generally exhibit a monotonic decline as discharge increases. Shallow-fast habitat 

types respond to flow in a similar fashion, but to a lesser degree (for example, figs. 18 and 19). 

This response is caused by increased depth and velocity as discharge increases, resulting in less 

area of shallow water (affecting habitat for both guilds) and slow water (affecting habitat for the 

shallow-slow guild). However, another characteristic of these habitat types is a leveling-off or 

increase in habitat area at very high flows, where new areas of shallow water are created as islands 

and floodplain areas are inundated. A comparison of figures 18 and 19 with figures 20–23 

illustrates the fundamental conflict between shallow water habitats and the deeper habitats utilized 

by adult or juvenile fish. Flows that result in increased habitat for one group tend to reduce habitat 

for the other group. 

Another common “within-resource” conflict occurs between shallow-slow habitat area and 

stream water temperature. Increasing flows to achieve lower temperatures will often result in a 

reduction in shallow-slow habitat areas. Conversely, attempts to mitigate habitat reductions 

associated with high flows may have the unintended consequence of elevated water temperatures, 

especially at downstream locations during late spring and summer. 

A scenario designed to increase the magnitude of low flows is usually presumed to result in 

an overall increase in habitat area. When the results displayed in the DRDSS show no change or a 

negative change, one or two causal factors are often to blame. One common mechanism is reservoir 

depletion resulting from excessive releases to augment instream flows for habitat improvement. In 

this case, habitat area may be substantially increased during part of a hydroperiod, but decreased 

later in the season as reservoir storage is exhausted. The most immediate confirmation that this 
62

phenomenon has happened is a review of the flow and storage time series plots on the “FlowPlots” 

page of the DSS_AGG.xls master workbook. Symptoms of the mechanism are also expressed on 

the summary scoring page by an increase in the frequency of drought watches and warnings 

associated with the scenario. Review of the habitat duration series in the subsidiary notebooks can 

also be used to determine the day-to-day response of habitat to a scenario. It is worthwhile to 

review these graphics routinely, because they may show a counterbalancing increase and decrease 

in habitat area throughout the hydroperiod despite little or no change to the average for the period. 

Then, the decisionmakers must evaluate the outcome to determine whether the change was 

positive, negative, or neutral. 

The second common mechanism for a counterintuitive result (reduced habitat area 

associated with increased base flows) is that the scenario may have resulted in an increased 

frequency of high flow events. An increase in the frequency of spills displayed on the summary 

scoring page is symptomatic of this feedback mechanism. To help identify potential feedback 

surprises, is advisable to generate flow duration and storage duration curves (for example, figs. 50 

and 51) as routine input to the decision process. This simple step will provide early indications 

whether the scenario performed hydrologically as it was intended, or whether the scenario created 

unforeseen consequences. 

Evaluation of Results 

Public decisions are rarely made unilaterally. Those that are tend to be either 

inconsequential or short-lived. Nor are decisions made with complete and perfect information. 

Decisionmaking can be complicated by agency policies, values, assumptions, and paradigms that 

transcend the relatively simple processes of data interpretation and quantification. Not all the 

members of the Decree parties, the Commission, and the Subcommittee likely share a universal set 

of values, goals, and objectives related to the upper Delaware. One of the reasons for inclusion of 

global variables such as water deliveries to New York City, Montague, and the D&R Canal was to 

display the consequences of a management action to both water users and habitat resources. 

Developing shared ownership in the values and objectives of all parties is a worthwhile goal, and 

the DRDSS may facilitate progress toward that goal. 

A frequent complaint of groups involved in multiple-use resource management is that there 

is insufficient (or irrelevant) information on which to base a decision. Through our interactions 

with the major stakeholders on the upper Delaware, we have attempted to provide accurate, 

realistic, and relevant information by way of the DRDSS. In contrast to the complaint of 

insufficient information, the DRDSS may produce too much information, in too many places, for 

easy comprehension. The structure of the system was designed to provide a broad overview for the 

“big picture” decisionmaker, with increasingly detailed information available for diagnostics and 

interpretation. The advantage of the summary scores page is that it provides a compact synopsis of 

the results of a scenario run. The disadvantage is that the synopsis can mask undesirable results (or 

causes) that can only be detected by examination of the duration series plots and duration curves. 

Therefore, the summary scoring page alone can be misleading. 

Evaluation of alternatives also involves trade-offs, both between and among resources. It 

would be nearly impossible to derive an alternative that caused every cell on the summary page to 

turn green. Many of the values embodied by the scoring variables of the DRDSS work at cross 

purposes, which is a true reflection of the environment in which many water management decisions 

are made. In this sense, the DRDSS provides a modicum of realism with regard to the decision 

environment. Several techniques can be used to ameliorate some of these inevitable conflicts: 

establishing context, using adaptable management objectives, and developing contingencies. 
63

Establishing Context 

Loosely translated, establishing context means that a red cell on the summary scoring page 

is not necessarily a bad thing, and in fact, may be a positive outcome depending on one’s 

perspective. For example, the summary scoring sheet for the Revision 1 and Revision 7 comparison 

(fig. 52) indicated an increase in temperature threshold violations in the main stem Delaware sites 

under Revision 7. In order to evaluate the biological ramifications of this temperature increase, the 

context of the change both in terms of magnitude and time scale should be examined. The average 

magnitude of the temperature change can be determined by dividing the degree-day sum in column 

M of the scoring summary by the days in column K (in this case, 4.97 oC-days /6 days = 0.83oC). 

Although the average threshold violation will not distinguish between six days at 0.83oC above the 

threshold or one day at 4.0oC and five at 0.2oC above the threshold, it provides an indication of the 

relative severity of the problem. Examination of the temperature duration curve for the period (fig. 

53) shows that the incidence of temperature threshold violations increased from about 0.1 percent 

of the time under Revision 1 to 0.5 percent of the time under Revision 7. Although the change 

represents a fivefold increase in the frequency of threshold violations, the data indicated that 

violations in either case occurred less than 0.5 percent of the time. That fact, combined with 

knowledge of the probable magnitude of the temperature change for this example, may suggest that 

the temperature flag on the scoring summary is not serious and could be ignored. Figure 53 also 

reveals that temperature generally increased across all time periods under Revision 7, but 

consistently remained below the threshold. This result suggests that temperature conditions may 

not have deteriorated significantly for salmonids and may have improved for the native species of 

concern. 

0.0

5.0

10.0

15.0

20.0

25.0

30.0

0% 20% 40% 60% 80%

Percent equaled or exceeded

Temperature, in degrees Celsius

DEL1 rev1 DEL1 rev7

Temperature threshold

Figure 53. Temperature duration curves for the period May 1–September 30, 1990–2000, for 

Revision1 and Revision 7 alternatives at site DEL1. 
64

Adaptable Management Objectives 

Habitat management decisions must evaluate the differential responses of multiple habitat 

types to changes in flow. The issue is whether stream fish populations actually respond to habitat 

changes described by the model over spatial and temporal scales that are relevant to the 

decisionmakers. For example, a system managed consistently (and successfully) to increase habitat 

types related to reproduction and recruitment may eventually experience an increase of juvenile 

and adult fish density to the point that habitat for these life stages becomes a limiting factor. 

Furthermore, one might expect a shift in the size distribution of the population, with an abundance 

of relatively small members and a paucity of large fish. Conversely, managing to consistently favor 

adult habitat could result in population decline over time owing to insufficient recruitment. 

Adaptive management objectives are designed to manage habitat for different life stages or species 

periodically and opportunistically. Because shallow-slow habitat tends to be limited at high flows 

(fig. 18), it might be advantageous to manage flows to favor adult and juvenile habitat during wet 

years, and flows favoring spawning-incubation and young of the year habitat during dry years. 

Contingency Planning 

The physical feasibility of a management alternative in the DRDSS is a function of water 

supply, storage volume, and cumulative demand. When the demand exceeds the supply for a 

sufficient time period, the alternative is considered infeasible, at least for that time interval. In this 

context, it is highly unlikely that a single-alternative operating policy will be feasible everywhere at 

all times. A contingency plan acknowledges this fact and anticipates operational changes needed to 

ameliorate the mismatch between supply and demand. In practice, contingency plans are already 

imbedded within the OASIS model. For example, the delivery targets for New York City, 

Montague, and the D&R canal are scaled back when system inflow and reservoir storage fall to 

specified trigger levels. Likewise, reservoir releases for habitat maintenance may be reduced during 

drought periods, although in some cases reserves may be released to reduce impacts of low flows 

on temperature or habitat. 

Because contingencies are intrinsic to OASIS, it is incumbent upon users of the DRDSS to 

recognize that developing an operating scenario will likely involve modification or redefinition of 

the rules of engagement for those contingencies. Several aspects of contingency planning should be 

observed when such modifications are made. First, how often and under what circumstances will 

normal operations fail due to insufficient water supply? Second, what trigger levels are imbedded 

in the operational rule curves to modify releases or exports? Third, how are allocations changed 

among downstream releases, deliveries, and exports during shortages? 

The frequency of failure under normal operating conditions is somewhat a matter of 

context. If an operating scenario only fails once every 20 years, it may not be worth worrying about 

in a strategic planning mode. If it fails over 75 percent of the time (for example), perhaps another 

alternative should be considered. Although failure might be too strong a term, an increase in the 

frequency of days under the various levels of system drought displayed on the scoring summary 

page (fig. 52) should serve as a warning that normal operations cannot be sustained without causing 

eventual problems. Review of the storage duration curves (fig. 51, for example) will reveal which 

reservoirs are most affected and the respective probabilities of contingency-triggering events. 

The circumstances leading to imposition of one of the drought rule contingencies result 

from cumulative demands exceeding inflow for a sufficient period of time to draw the reservoirs 

down to their respective trigger levels. Whether this is a concern during development and 

evaluation of an alternative is once again a matter of context. An alternative that increases the 

frequency of drought watch designations, but decreases the frequency of drought warnings (the 
65

opposite of the Revision1-Revision7 comparison in fig. 54) might be perfectly acceptable. One that 

increases the frequency of level 3 drought designations might be unacceptable regardless of 

changes to the lower categories. 

Global Scores

Montague Flow Pct Chg Δ Days Out of System Deliveries Pct Chg Δ Days

Montague, minor shortage -27% -113.00 NYC, minor shortage 0% 0.00

Montague, moderate shortage -22% -19.00 NYC, moderate shortage 0% Base, Alt =0

Montague, major shortage 0% Base, Alt =0 NYC, major shortage 0% Base, Alt =0

Montague, cfs-days -24% -12464.00 New York City, bg 0% Base, Alt =0

System Drought Pct Chg Δ Days Pct Chg Δ Days

Days at Level 1 -22% -92.00 NJ, minor shortage 0% 0.00

Days at Level 2 39% 89.00 NJ, moderate shortage 0% Base, Alt =0

Days at Level 3 0% Base, Alt =0 NJ, major shortage 0% Base, Alt =0

New Jersey, bg 0% Base, Alt =0

System Storage, bg 0% -2358.70

Figure 54. Expanded view of the global scores box of the DRDSS, showing changes in system 

drought designations under Revision1 and Revision7 alternatives. 

The trigger levels for each of the drought contingency rules, along with a recent history of 

system storage volume, can be viewed on the web page for the Delaware River Basin Commission 

(http://www.state.nj.us/drbc/nyc.htm). The reader is advised, however, that this display and all 

information derived as OASIS output refer to system-wide storage rather than for individual 

reservoirs. 

For a normal operating scenario in the DRDSS, one of the primary changes customarily 

made will be seasonal or monthly release targets to maintain or improve habitat and temperature 

conditions. These targets will likely need to be modified as part of a contingency plan. In most 

cases, the releases would be reduced in order to conserve storage. However, if such reductions 

result in unacceptable decreases in habitat it may be necessary to revise the rule curves themselves. 

One potential modification would be to initiate the release reduction earlier, so that the impact to 

habitat is less in magnitude but longer in duration. To some extent, it may also be possible to 

spread the impact of drought to different locations in the system by reducing releases from one 

reservoir in order to allow near-normal releases from another. Under true drought conditions, 

however, this option would necessarily be considered a short-term solution because normal releases 

would eventually draw the reservoir down to its drought trigger anyway. 

Model Limitations and Assumptions 

Since the inception of this study, we have attempted to respond to suggestions provided by 

the Commission and the Subcommittee to make the DRDSS relevant, realistic, and accurate. We 

have also strived to produce accurate and realistic input data in the form of hydraulic simulations, 

habitat maps, and temperature predictions. Regardless of their complexity or sophistication, all 

models are simplifications of the real world. In application, they may be further simplified or 

limited by assumptions made by their users. 

In this application, we have assumed that the channels of all measured rivers are currently 

in a state of dynamic equilibrium as described by Leopold and others (1964). We have taken a 

snapshot of the stream bathymetry as it existed in 2004 and 2005. When we suspected that a site 

might have been altered by a large flood event, the site was resurveyed. Nonetheless, if the 

channels are not in dynamic equilibrium, the results of our models will become less representative 

of the rivers with the passage of time. 
66

We have also assumed that our selection process produced study sites that were 

representative of the stream segments, that the boundary conditions we obtained from gaging 

station rating curves closely approximated those at the sites, and that our survey data were accurate 

depictions of site bathymetry. To some extent, the validity of these assumptions was supported by 

the similarity of the normalized flow versus habitat functions. Each stream was sampled, measured, 

and modeled independently. If the bathymetric and hydraulic characteristics for a site were 

markedly different from those of other sites in comparable settings, its response functions would 

have been noticeably different from the others. The similarity of the functions suggests that errors 

associated with sampling and data collection were consistent across all the sites, final model 

outputs were insensitive to these errors, or both. It is important to remember that the comparative 

statistics generated in the DRDSS are relative, not absolute. The advantage of relative scoring is 

that any inaccuracies of the models will be equally distributed in both the baseline and alternative 

simulations. In that sense, the effects of modeling inaccuracies are neutral. 

Decision Support and Adaptive Management 

A fundamental paradigm underlying the entire habitat analysis portion of the DRDSS is that 

fish populations respond somehow to changes in habitat. The general hypothesis is that more 

habitat has the potential to support more fish (or mussels or aquatic insects). Relations between 

habitat dynamics and population responses are more complex, however, because populations can 

be affected by variables not included in the habitat models, at spatial and temporal scales that are 

different from those incorporated in this study. As previously mentioned, conditions favoring an 

increase in habitat for adults of a species commonly correspond to a reduction in habitat for young 

of the year. As a result, an increase in adult habitat may have the unintended consequence of 

reducing recruitment, thereby causing a reduction in adult population over time. Indeed, the few 

empirical studies that have examined linkages between habitat and biology have failed to identify a 

unifying connection between the two. Some studies have shown strong relations between fish 

population size and habitat dynamics (Jowett, 1993; Nehring and Anderson, 1993; Bovee and 

others, 1994; Bowen, 1996; Freeman and others, 2001; Capra and others, 2003; Fjellheim and 

others, 2003; Souchon and Capra, 2004). Some have found no relation at all (Irvine and others, 

1987; Scott and Shirvell, 1987; Zorn and Seelbach, 1995), and at least one indicated a negative 

relation (Garciá de Jalón and others, 1996). Dunham and others (2002) noted that the relations 

between habitat and fish populations in individual streams could be variable depending on 

biological factors, such as presence of non-native species, or spatial factors such as habitat 

connectivity. 

Given the uncertainties of how populations or communities are influenced by habitat 

dynamics, the DRDSS should not be viewed as a precise indicator of population response to flow 

regime. The DRDSS, in its present form, can be used as a tool for strategic planning by the 

Commission, the Subcommittee, and the Decree parties. The DRDSS was not designed to perform 

as a tactical tool for daily operations and should not be used as such. Its strength is as a “hypothesis 

screener.” The DRDSS can be used to distinguish among alternatives that may be effective or 

ineffective, feasible or infeasible, high-risk or low-risk. In many decision environments, such 

information is sufficient for policy makers to decide on a course of action and implement it. 

Derivation of a “good enough” solution may be “good enough,” even though it may not be the most 

effective or lowest risk alternative. 

To improve and refine the information base, the DRDSS could be used as a precursor to a 

process of adaptive management by identifying promising operational alternatives that could be 

implemented and monitored to determine outcomes. In a setting such as the upper Delaware, 
67

limited reservoir capacity and uncertain and water supplies hinder full experimental control, but 

partial control is possible. Experimental control could be established by implementing the baseline 

operations of the reservoirs as depicted in the DRDSS for several years. During that time, reservoir 

releases, stream discharge, habitat dynamics, and population or community-level characteristics 

(for example, year class strength, growth rates, condition, adult populations, and size structure) 

would be monitored. The experimental treatment would consist of monitoring the same variables 

for a similar length of time, but operating the reservoirs according the alternative depicted in the 

DRDSS, such as those used to generate Revision 7. Advantages to this strategy include: 

1. Follow-up monitoring of flows and population dynamics could provide validation of the 

physical models used in the DRDSS and help define habitat and biological linkages. 

2. The feasibility of implementing the operational rules of the alternative could be physically 

tested through day-to-day operations. Furthermore, actual operations can be compared with 

simulated (OASIS) operations to monitor compliance and deviations thereof. 

3. Ecological resets, such as catastrophic floods, could be adapted into the experimental design. A 

deficiency of “natural” experiments is that they cannot always be completely or rigorously 

controlled. Deviations from an experimental release plan can create serious problems with a 

purely empirical adaptive management study because the treatment may be overridden by an 

uncontrolled event. The habitat impacts of such deviations predicted with the DRDSS models 

could be compared with biological responses as part of a revised experiment. 

4. The addition of information to the body of knowledge regarding habitat dynamics and 

biological responses is invaluable. Not only would such knowledge benefit stakeholders and 

decisionmakers in the Delaware River system, it would undoubtedly be of value to others 

facing similar situations elsewhere. 

Acknowledgements 

Funding for this study was provided by a special Congressional appropriation in 2004 and 

by the U.S. Geological Survey Fisheries and Aquatic Resources Program in 2005 and 2006. We 

appreciate the support of The Nature Conservancy, Trout Unlimited, the Delaware River 

Foundation, the Delaware River Basin Commission, the Subcommittee for Ecological Flows, and 

the Decree parties in securing resources with which to complete this study. We also thank 

Congressman Maurice Hinchey and staff for their efforts in funding the study. Colin Apse of The 

Nature Conservancy has been a constant source of support and guidance and has been instrumental 

in bringing the necessary information and tools development to fruition in the DRDSS. 

We received a great deal of help from a vast array of agency personnel, nongovernmental 

organizations, landowners, and private citizens. We are grateful to the USGS New York Water 

Resources Science Center in Troy, N.Y., for providing us with the rating tables we used to establish 

the boundary conditions at many our study sites. Logistical and field survey support was provided 

by the National Park Service, New York Department of Environmental Conservation, the Delaware 

River Foundation, the USGS Connecticut Water Resources Science Center, and the Susquehanna 

River Basin Commission. In particular, we acknowledge the assistance of Don Hamilton, Alan 

Ellsworth, Jamie Meyers, Rich Evans, Jeff Shriner, Jim Serio, Wayne Elliot, Elizabeth Ahern, 

Remo Mondazzi, and Krista Nelson. Leanne Hanson, Kathryn Holland, and Julie Roth from the 

USGS Fort Collins Science Center were mainstays during the field surveys, data preparation, and 

hydraulic simulations involved with this study. Our temperature analysis benefited from the 

contributions of many individuals, including Robert Angyal, Alan Ellsworth, Colin Apse, Jerry 

Butch, Wayne Elliot, Glenn Horton, Robert Klosowski, Bill Lellis, Rick Naro, Charles Olson, 
68

Margaret Phillips, Don Pierson, and Hernan Quinodoz. Thank you all for your dedication and hard 

work. 

Many of our study sites would have been inaccessible without the cooperation and support 

of the landowners who allowed us to use their boat ramps and accommodated survey crews and 

benchmarks on their property. Special thanks to the West Branch Anglers Resort on the West 

Branch; Beaver Del Lodge, Buckhorn Lodge, Del Valley Campground, and Catskill Mountain 

Campground on the East Branch; American Family Campgrounds and John Edwards on the 

Neversink and the Red Barn and Soaring Eagle Campgrounds and Ed and Dawn Joyce on the main 

stem Delaware. 

Members of the Delphi panel responsible for developing the habitat suitability criteria used 

for this study included Doug Sheppard, Leroy Young, Rich Horwitz, Wayne Elliot, Brandon Kulik, 

and Robert Bachman. Dr. William Lellis and Jeff Cole provided valuable information regarding the 

habitat characteristics of the dwarf wedgemussel. Many individuals provided comments and 

suggestions on the original study plans and on earlier drafts of this report, as well as beta-testing 

the DRDSS. We thank Colin Apse, Wayne Elliot, Leroy Young, Richard Horwitz, Jeff Hoffman, 

Mike Principe, Ed Santoro, Dave Arnold, Alan Ellsworth, Don Hamilton, Robert Bachman, Doug 

Sheppard, Jim Serio, Charles Cutietta-Olson, Richard Evans, Dave Arnold, and Hernán Quinodoz 

for their reviews and thoughtful insights. Dr. Quinodoz is also recognized for his role in running 

the OASIS model scenarios used as examples in this report. 

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71

Appendix 1. Proportional Planform Comparisons for Sites and Segments 

of the Upper Delaware River. 
72

Figure 1-1. Planform map of segments and sites for the West Branch Delaware River. 

0%

25%

50%

75%

100%

Planform Type

Percent of length

WB0_segment 0.00 0.07 0.10 0.02 0.02 0.79

WB0_site 0.00 0.05 0.08 0.03 0.00 0.84

WB1_segment 0.01 0.11 0.04 0.12 0.22 0.50

WB1_site 0.00 0.00 0.00 0.15 0.35 0.50

Percent divided 

channel, on 

bend

Percent single 

channel, on 

bend

Percent delta Percent multiple 

channel

Percent straight 

divided channel

Percent straight 

single channel

Figure 1-2. Comparison of planform distributions between segments and sites for the West 

Branch Delaware River. 
73

Figure 1-3. Planform map of segments and sites for the East Branch Delaware River. 

0%

25%

50%

75%

100%

Planform Type

Percent of length

EB0_segment 0.13 0.16 0.03 0.07 0.14 0.47

EB0_site 0.13 0.14 0.05 0.07 0.18 0.44

EB1_segment 0.05 0.15 0.07 0.05 0.14 0.52

EB1_site 0.07 0.27 0.10 0.10 0.07 0.38

EB2_segment 0.08 0.14 0.05 0.02 0.20 0.52

EB2_site 0.05 0.13 0.04 0.00 0.22 0.56

Percent divided 

channel, on bend

Percent single 

channel, on bend Percent delta Percent multiple 

channel

Percent straight 

divided channel

Percent straight 

single channel

Figure 1-4. Comparison of planform distributions between segments and sites for the East Branch 

Delaware River. 
74

Figure 1-5. Planform map of segments and sites for the main stem Delaware River. 

0%

25%

50%

75%

100%

Planform Type

Percent of length

DEL1_segment 0.02 0.24 0.05 0.17 0.04 0.47

DEL1_site 0.00 0.25 0.08 0.23 0.14 0.30

DEL2_segment 0.05 0.35 0.09 0.02 0.07 0.42

DEL2_site 0.10 0.09 0.15 0.10 0.16 0.39

DEL3_segment 0.09 0.31 0.03 0.07 0.06 0.44

DEL3_site 0.07 0.22 0.08 0.22 0.15 0.27

Percent divided 

channel, on bend

Percent single 

channel, on bend Percent delta Percent multiple 

channel

Percent straight 

divided channel

Percent straight 

single channel

Figure 1-6. Comparison of planform distributions between segments and sites for the main stem 

Delaware River. 
75

A B

Figure 1-7. Planform maps of segments and sites for the upper (A) and lower (B) Neversink River. 

0%

25%

50%

75%

100%

Planform Type

Percent of length

NVR0_segment 0.02 0.18 0.02 0.04 0.10 0.64

NVR0_site 0.00 0.14 0.00 0.10 0.08 0.68

NVR1_segment 0.04 0.21 0.01 0.02 0.10 0.61

NVR1_site 0.07 0.16 0.02 0.00 0.10 0.65

NVR2_segment 0.03 0.18 0.02 0.03 0.14 0.61

NVR2_site 0.00 0.03 0.04 0.11 0.33 0.50

Percent divided 

channel, on bend

Percent single 

channel, on bend Percent delta Percent multiple 

channel

Percent straight 

divided channel

Percent straight 

single channel

Figure 1-8. Comparison of planform distributions between segments and sites for the Neversink 

River. 
76

Appendix 2. Final Calibration Results for the River2D Hydraulic Simulation 

Model at Study Sites in the Upper Delaware River. 
77

299.0

299.5

300.0

300.5

301.0

301.5

302.0

302.5

303.0

303.5

0 500 1,000 1,500 2,000 2,500 3,000

Distance from top of site (m)

Water surface elevation (m)

Measured Predicted

Figure 2-1. Comparison of predicted and measured water surface profiles for the final calibration 

run at site WB0. 

281.5

282.0

282.5

283.0

283.5

284.0

284.5

285.0

0 500 1,000 1,500 2,000 2,500 3,000

Distance from top of site (m)

Water surface elevation (m)

Measured Predicted

Figure 2-2. Comparison of predicted and measured water surface profiles for the final calibration 

run at site WB1. 
78

325.5

326.0

326.5

327.0

327.5

328.0

328.5

329.0

0 500 1,000 1,500 2,000 2,500 3,000

Distance from top of site (m)

Water surface elevation (m)

Measured Predicted

Figure 2-3. Comparison of predicted and measured water surface profiles for the final calibration 

run at site EB0. 

302.5

303.0

303.5

304.0

304.5

305.0

305.5

306.0

0 500 1,000 1,500 2,000

Distance from top of site (m)

Water surface elevation (m)

Measured Predicted

Figure 2-4. Comparison of predicted and measured water surface profiles for the final calibration 

run at site EB1. 
79

292.0

292.5

293.0

293.5

294.0

294.5

295.0

295.5

296.0

296.5

297.0

297.5

298.0

0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000

Distance from top of site (m)

Water surface elevation (m)

Measured Predicted

Figure 2-5. Comparison of predicted and measured water surface profiles for the final calibration 

run at site EB2. 

257.0

257.5

258.0

258.5

259.0

259.5

260.0

260.5

0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 4,500

Distance from top of site (m)

Water Surface Elevation (m)

Measured Predicted

Figure 2-6. Comparison of predicted and measured water surface profiles for the final calibration 

run at site DEL1. 
80

237.0

238.0

239.0

240.0

241.0

242.0

243.0

244.0

0 500 1,000 1,500 2,000 2,500 3,000 3,500

Distance from top of site (m)

Water surface elevation (m)

Measured Predicted

Figure 2-7. Comparison of predicted and measured water surface profiles for the final calibration 

run at site DEL2. 

224.0

224.5

225.0

225.5

226.0

226.5

227.0

227.5

0 500 1,000 1,500 2,000 2,500 3,000 3,500

Distance from top of site (m)

Water surface elevation (m)

Measured Predicted

Figure 2-8. Comparison of predicted and measured water surface profiles for the final calibration 

run at site DEL3. 
81

350.0

350.5

351.0

351.5

352.0

0 200 400 600 800

Distance from top of site (m)

Water surface elevation (m)

Measured Predicted

Figure 2-9. Comparison of predicted and measured water surface profiles for the final calibration 

run at site NVR0. 

322.0

322.5

323.0

323.5

324.0

324.5

325.0

0 250 500 750 1,000 1,250 1,500 1,750 2,000

Distance from top of site (m)

Water surface elevation (m)

Measured Predicted

Figure 2-10. Comparison of predicted and measured water surface profiles for the final 

calibration run at site NVR1. 
82

136.0

136.5

137.0

137.5

138.0

138.5

139.0

139.5

140.0

140.5

141.0

0 250 500 750 1,000 1,250

Distance from top of site (m)

Water surface elevation (m)

Measured Predicted

Figure 2-11. Comparison of predicted and measured water surface profiles for the final 

calibration run at site NVR2. 
83

Appendix 3. Discharge Versus Habitat Area Statistics for Study Sites in 

the Upper Delaware River. 
84

Table 3-1. Habitat versus discharge relations for segment 0 West Branch Delaware River (WB0). 

Discharge Brown trout adult Brown trout juveniles Shallow-fast guild Shallow-slow guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2/km Ha m2/km Ha m2/km Ha m2/km 

9 0.02 1.09 2,786 2.23 5,720 0.09 218 3.48 8,913 

14 0.03 1.26 3,242 2.75 7,047 0.27 686 3.65 9,364 

21 0.05 1.49 3,826 3.27 8,395 0.59 1,505 3.74 9,587 

32 0.07 2.10 5,375 4.17 10,686 1.10 2,830 4.05 9,983 

53 0.11 3.04 7,790 5.38 13,785 2.44 6,264 4.48 10,379 

81 0.17 4.08 10,460 7.20 18,451 3.96 10,159 4.70 11,486 

124 0.27 5.11 13,091 10.78 27,647 6.14 15,734 4.76 12,059 

191 0.41 7.70 19,751 15.16 38,871 7.88 20,202 3.96 12,196 

297 0.64 11.72 30,041 19.13 49,048 8.92 22,870 3.10 10,160 

462 0.99 18.83 48,283 19.91 51,040 4.90 12,557 2.40 7,946 

717 1.54 23.11 59,255 16.40 42,046 1.90 4,877 1.68 6,158 

1,112 2.39 23.06 59,119 10.81 27,710 1.56 4,011 1.37 4,304 

1,730 3.72 18.57 47,611 5.56 14,263 1.15 2,937 1.29 3,523 

2,683 5.77 12.07 30,938 3.67 9,418 0.65 1,675 1.09 3,302 

4,165 8.96 6.90 17,688 2.60 6,666 0.26 659 0.00 2,792 

1

Constrained by 5-m shoreline buffer. 

Table 3-2. Habitat versus discharge relations for segment 1 West Branch Delaware River (WB1). 

Discharge Brown trout adult Brown trout juvenile Shallow-fast guild Shallow-slow guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2/km Ha m2/km Ha m2/km Ha m2/km 

46 0.08 40.39 1,7410 61.24 2,6399 0.01 6 26.07 11,235 

64 0.11 45.72 1,9706 69.05 2,9765 9.10 3,923 29.11 12,547 

88 0.15 52.29 2,2537 79.88 3,4429 14.65 6,316 30.01 12,934 

125 0.21 61.75 2,6618 90.57 3,9041 20.66 8,904 29.79 12,842 

177 0.30 73.47 3,1670 103.67 4,4685 27.31 11,772 29.22 12,594 

247 0.42 89.91 3,8756 116.92 5,0398 30.97 13,349 28.38 12,233 

353 0.59 110.98 4,7835 128.78 5,5511 28.88 12,447 26.10 11,251 

494 0.83 132.19 5,6978 133.01 5,7331 22.80 9,827 23.14 9,973 

706 1.19 153.12 6,6000 123.96 5,3433 15.10 6,507 18.11 7,805 

953 1.60 170.43 7,3459 96.25 4,1488 6.14 2,648 13.52 5,827 

1,341 2.25 174.09 7,5040 66.27 2,8563 1.98 853 10.44 4,499 

1,906 3.20 153.29 6,6075 42.51 1,8322 1.30 558 9.90 4,265 

2,683 4.51 123.01 5,3024 30.01 1,2933 1.95 841 9.53 4,107 

3,777 6.35 88.13 3,7986 26.44 1,1395 2.76 1,189 9.90 4,266 

5,330 8.96 71.82 3,0959 26.02 1,1216 3.12 1,346 6.43 2,773 

1

Constrained by 5-m shoreline buffer. 
85

Table 3-3. Habitat versus discharge relations for segment 0 East Branch Delaware River (EB0). 

Discharge Brown trout adult 

Brown trout 

juvenile Shallow-fast guild Shallow-slow guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km Ha m2/km Ha m2/km 

7 0.02 11.10 9,096 9.85 8,071 0.08 63 11.56 9,477 

11 0.03 11.83 9,700 11.05 9,053 0.25 208 11.60 9,511 

18 0.05 13.12 10,755 13.05 10,699 0.71 585 11.64 9,542 

25 0.07 14.28 11,703 14.48 11,866 1.12 917 11.82 9,687 

39 0.10 16.70 13,691 17.79 14,586 1.95 1,597 11.85 9,716 

56 0.15 18.95 15,531 21.73 17,808 2.81 2,305 11.86 9,720 

88 0.24 22.13 18,142 25.90 21,229 3.85 3,154 10.74 8,805 

131 0.35 28.66 23,493 28.90 23,685 4.33 3,553 10.58 8,675 

201 0.54 36.48 29,898 32.42 26,570 2.32 1,905 8.38 6,867 

304 0.82 42.53 34,862 32.89 26,961 1.06 867 6.90 5,657 

462 1.24 46.70 38,278 29.82 24,443 0.68 558 5.67 4,645 

702 1.89 49.55 40,617 20.82 17,067 0.73 599 5.48 4,493 

1,070 2.88 50.66 41,526 14.06 11,523 1.39 1,141 5.84 4,790 

1,627 4.37 49.06 40,216 15.14 12,414 1.61 1,323 6.43 5,274 

2,471 6.64 50.97 41,778 19.11 15,665 1.73 1,421 5.52 4,524 

1

Constrained by 5-m shoreline buffer. 

Table 3-4. Habitat versus discharge relations for segment 1 East Branch Delaware River (EB1). 

Discharge Brown trout adult 

Brown trout 

juvenile Shallow-fast guild Shallow-fast guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km Ha m2/km Ha m2/km 

38 0.08 37.17 24,615 30.53 20,221 2.31 1,527 11.70 7,748 

53 0.12 40.00 26,490 33.33 22,074 3.54 2,347 11.67 7,727 

74 0.16 43.15 28,575 35.95 23,807 4.76 3,152 11.39 7,543 

103 0.22 46.76 30,967 38.10 25,231 5.39 3,569 10.96 7,257 

143 0.31 51.89 34,362 39.62 26,237 4.74 3,137 10.60 7,017 

199 0.43 56.43 37,372 40.50 26,819 3.63 2,402 10.18 6,741 

277 0.60 61.14 40,492 39.41 26,098 2.06 1,361 9.40 6,223 

385 0.84 63.68 42,175 37.77 25,016 1.36 898 8.56 5,667 

537 1.17 66.44 44,003 34.46 22,821 0.77 513 8.22 5,443 

746 1.63 65.89 43,638 29.10 19,274 0.78 514 8.03 5,317 

1,039 2.27 67.22 44,517 24.36 16,133 1.28 847 7.90 5,230 

1,446 3.16 67.03 44,391 21.32 14,117 2.32 1,537 7.40 4,901 

2,012 4.39 63.75 42,220 20.17 13,355 2.81 1,864 7.06 4,678 

2,802 6.12 58.49 38,736 23.87 15,811 3.29 2,179 6.96 4,611 

3,901 8.52 58.17 38,524 33.36 22,090 8.88 5,883 7.03 4,658 

1

Constrained by 5-m shoreline buffer. 
86

Table 3-5. Habitat versus discharge relations for segment 2 East Branch Delaware River (EB2). 

Discharge Brown trout adult 

Brown trout 

juvenile Shallow-fast guild Shallow-slow guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km Ha m2/km Ha m2/km 

100 0.13 77.55 30,292 77.74 30,366 13.73 5,364 21.81 8,519 

150 0.19 85.28 33,313 82.97 32,411 17.04 6,657 21.63 8,447 

200 0.25 91.92 35,908 85.31 33,325 18.15 7,089 21.04 8,218 

300 0.38 104.82 40,947 85.69 33,473 17.36 6,782 18.90 7,382 

450 0.57 118.20 46,170 83.68 32,687 15.69 6,130 16.87 6,589 

700 0.89 131.09 51,206 76.43 29,855 11.82 4,616 14.09 5,502 

1,000 1.28 139.34 54,430 65.34 25,524 7.02 2,744 11.35 4,435 

1,399 1.78 140.32 54,812 51.67 20,185 3.41 1,331 10.35 4,045 

1,539 1.96 143.28 55,967 49.72 19,424 2.27 887 10.35 4,042 

2,099 2.68 127.04 49,623 35.34 13,804 1.07 418 8.78 3,428 

3,199 4.08 100.25 39,159 23.74 9,274 0.86 336 8.06 3,149 

4,598 5.87 65.68 25,656 20.27 7,919 0.76 298 8.63 3,369 

6,697 8.54 49.51 19,338 21.72 8,484 0.49 193 9.70 3,787 

9,896 12.62 48.71 19,028 28.87 11,279 0.25 98 10.47 4,090 

21,191 27.03 73.87 28,855 42.89 16,753 0.12 48 12.15 4,748 

1

Constrained by 5-m shoreline buffer. 

Table 3-6. Habitat versus discharge relations for segment 2 East Branch Delaware River (EB2) – 

Continued. 

Discharge 

American shad 

juvenile 

American shad 

spawning 

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km 

100 0.13 84.58 33,038 9.31 3,636 

150 0.19 91.86 35,884 19.69 7,690 

200 0.25 97.95 38,263 30.36 11,858 

300 0.38 105.93 41,377 60.60 23,673 

450 0.57 110.72 43,250 83.21 32,503 

700 0.89 110.25 43,067 96.55 37,716 

1,000 1.28 98.42 38,445 97.06 37,914 

1,399 1.78 75.53 29,506 84.93 33,176 

1,539 1.96 77.25 30,175 85.74 33,490 

2,099 2.68 50.26 19,632 56.64 22,123 

3,199 4.08 36.37 14,206 32.79 12,808 

4,598 5.87 29.65 11,582 22.32 8,719 

6,697 8.54 27.54 10,759 21.06 8,226 

9,896 12.62 31.17 12,176 22.99 8,982 

21,191 27.03 51.77 20,224 38.07 14,870 
87

Table 3-7. Habitat versus discharge relations for segment 1 Delaware River main stem (DEL1). 

Discharge Brown trout adult 

Brown trout 

juvenile Shallow-fast guild Shallow-slow guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km Ha m2/km Ha m2/km 

344 0.22 107.70 72,285 88.74 59,555 5.70 3,828 18.09 12,142 

426 0.27 118.24 79,355 97.15 65,201 7.38 4,955 16.74 11,234 

568 0.36 130.34 87,475 104.20 69,931 9.64 6,472 14.91 10,004 

746 0.47 146.05 98,019 107.20 71,944 7.73 5,187 14.21 9,540 

959 0.60 160.33 107,607 107.41 72,085 4.25 2,855 13.62 9,141 

1,243 0.78 171.07 114,810 102.51 68,800 2.07 1,388 13.04 8,752 

1,598 1.00 179.58 120,526 93.54 62,780 0.75 506 11.12 7,464 

2,095 1.32 185.92 124,779 79.78 53,544 1.10 737 9.65 6,476 

2,698 1.70 190.73 128,004 60.87 40,851 1.50 1,007 8.12 5,449 

3,515 2.21 194.99 130,866 45.84 30,768 1.52 1,021 7.70 5,167 

4,544 2.86 197.91 132,824 38.27 25,686 1.69 1,136 7.46 5,007 

5,893 3.71 189.00 126,843 40.36 27,084 1.23 828 7.60 5,103 

7,597 4.78 177.78 119,318 48.36 32,457 0.80 536 7.35 4,933 

9,869 6.21 176.79 118,653 56.94 38,216 2.52 1,690 5.94 3,989 

12,780 8.04 176.06 118,163 64.34 43,182 0.27 181 3.50 2,349 

1

Constrained by 5-m shoreline buffer. 

Table 3-8. Habitat versus discharge relations for segment 1 Delaware River main stem (DEL1) – 

Continued. 

Discharge 

American shad 

juvenile 

American shad 

spawning 

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km 

344 0.22 109.52 73,505 31.53 21,163 

426 0.27 119.34 80,092 43.29 29,056 

568 0.36 130.70 87,718 64.02 42,969 

746 0.47 140.62 94,373 89.16 59,837 

959 0.60 144.41 96,918 109.30 73,355 

1,243 0.78 143.68 96,427 123.69 83,010 

1,598 1.00 135.79 91,137 132.97 89,244 

2,095 1.32 124.12 83,304 137.40 92,215 

2,698 1.70 110.12 73,909 133.57 89,641 

3,515 2.21 90.82 60,953 113.43 76,125 

4,544 2.86 78.96 52,992 91.08 61,126 

5,893 3.71 70.55 47,348 76.91 51,618 

7,597 4.78 67.45 45,268 68.70 46,106 

9,869 6.21 73.77 49,508 72.20 48,460 

12,780 8.04 82.60 55,435 84.22 56,521 
88

Table 3-9. Habitat versus discharge relations for segment 2 Delaware River main stem (DEL2). 

Discharge Brown trout adult 

Brown trout 

juvenile Shallow-fast guild Shallow-slow guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km Ha m2/km Ha m2/km 

466 0.28 95.35 55,758 58.95 34,476 100.23 6,898 12.46 6,441 

597 0.36 99.94 58,445 57.13 33,410 108.08 6,765 12.23 9,405 

762 0.46 104.11 60,884 54.55 31,900 117.15 6,185 11.95 11,885 

974 0.58 107.93 63,118 50.78 29,697 125.80 5,745 11.42 13,104 

1,243 0.74 110.74 64,761 48.12 28,143 134.33 5,509 10.75 13,836 

1,585 0.95 114.57 67,000 44.99 26,308 144.52 4,165 10.38 14,460 

2,023 1.21 117.90 68,950 40.17 23,490 155.00 2,133 9.57 14,660 

2,577 1.54 116.63 68,207 34.56 20,208 161.68 1,589 9.79 13,404 

3,297 1.98 114.98 67,241 29.26 17,110 168.35 1,466 8.86 10,232 

4,208 2.52 107.75 63,009 25.82 15,101 175.28 1,288 8.67 7,459 

5,373 3.22 90.36 52,839 22.66 13,252 181.96 1,062 8.85 5,640 

6,855 4.11 72.83 42,589 21.13 12,359 189.35 1,091 8.90 4,645 

8,751 5.25 62.12 36,328 20.63 12,067 199.07 1,485 8.96 4,016 

11,172 6.70 62.93 36,799 21.13 12,356 210.90 2,181 8.70 4,497 

14,261 8.55 57.39 33,559 17.67 10,332 222.47 2,381 7.40 4,116 

1

Constrained by 5-m shoreline buffer. 

Table 3-10. Habitat versus discharge relations for segment 2 Delaware River main stem (DEL2) –

Continued. 

Discharge 

American shad 

juvenile 

American shad 

spawning 

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km 

466 0.28 77.03 47,917 11.80 19,969 

597 0.36 75.98 49,255 11.57 29,156 

762 0.46 74.28 49,822 10.58 36,845 

974 0.58 71.82 49,080 9.82 40,624 

1,243 0.74 68.20 47,903 9.42 42,892 

1,585 0.95 64.58 47,155 7.12 44,826 

2,023 1.21 56.52 43,229 3.65 45,446 

2,577 1.54 49.79 35,338 2.72 41,552 

3,297 1.98 43.02 29,567 2.51 31,721 

4,208 2.52 36.30 25,347 2.20 23,122 

5,373 3.22 31.36 22,408 1.82 17,484 

6,855 4.11 28.14 20,771 1.87 14,401 

8,751 5.25 28.33 20,429 2.54 12,449 

11,172 6.70 28.67 21,547 3.73 13,939 

14,261 8.55 23.75 17,409 4.07 12,760 
89

Table 3-11. Habitat versus discharge relations for segment 3 Delaware River main stem (DEL3). 

Discharge Brown trout adult 

Brown trout 

juvenile Shallow-fast guild Shallow-slow guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km Ha m2/km Ha m2/km 

505 0.28 90.42 89,632 83.19 78,648 0.25 9,616 17.87 13,671 

650 0.36 102.83 101,955 82.78 82,072 9.00 8,919 13.85 11,834 

833 0.46 113.78 112,806 86.01 85,280 9.24 9,164 13.57 11,595 

1,059 0.58 123.76 122,705 88.18 87,425 8.71 8,640 13.21 11,289 

1,377 0.76 133.47 132,326 87.64 86,890 7.56 7,499 12.24 10,460 

1,779 0.98 143.03 141,805 81.59 80,888 5.76 5,707 10.57 9,035 

2,291 1.26 148.64 147,369 70.45 69,846 2.84 2,812 8.76 7,484 

2,951 1.62 149.26 147,980 56.07 55,590 1.27 1,255 7.71 6,592 

3,798 2.09 145.95 144,705 38.16 37,837 1.16 1,154 6.85 5,858 

4,889 2.69 136.23 135,066 24.66 24,445 1.17 1,162 6.37 5,441 

6,294 3.46 113.46 112,489 17.66 17,511 0.97 961 6.05 5,171 

8,105 4.45 91.62 90,842 15.90 15,767 1.08 1,067 6.13 5,242 

10,435 5.73 67.99 67,408 16.26 16,118 1.52 1,504 6.54 5,586 

13,435 7.38 54.46 53,994 16.64 16,493 1.68 1,664 6.57 5,612 

17,297 9.50 44.30 43,922 16.87 16,725 2.22 2,201 6.58 5,624 

1

Constrained by 5-m shoreline buffer. 

Table 3-12. Habitat versus discharge relations for segment 3 Delaware River main stem (DEL3) – 

Continued. 

Discharge 

American shad 

juvenile 

American shad 

spawning 

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km 

505 0.28 114.55 91,086 97.72 42593 

650 0.36 78.13 98,197 99.04 54535 

833 0.46 74.04 103,348 104.24 69793 

1,059 0.58 68.30 106,551 107.47 86566 

1,377 0.76 59.22 107,856 108.79 98783 

1,779 0.98 43.01 100,496 101.36 107196 

2,291 1.26 32.63 88,923 89.69 105451 

2,951 1.62 27.03 76,806 77.47 94660 

3,798 2.09 23.01 62,344 62.88 78693 

4,889 2.69 18.81 46,805 47.21 58188 

6,294 3.46 16.80 35,255 35.56 37469 

8,105 4.45 17.69 33,698 33.99 30722 

10,435 5.73 19.93 31,471 31.74 27913 

13,435 7.38 17.22 25,411 25.63 23804 

17,297 9.50 13.71 20,891 21.07 19517 
90

Table 3-13. Habitat versus discharge relations for segment 0 Neversink River (NVR0). 

Discharge Brown trout adult 

Brown trout 

juvenile Shallow-fast guild Shallow-slow guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km Ha m2/km Ha m2/km 

14 0.12 13.01 10,084 15.11 11,709 13.01 711 9.43 7,311 

18 0.16 13.42 10,400 15.58 12,080 13.42 1,060 9.72 7,534 

25 0.22 14.17 10,985 16.75 12,987 14.17 1,708 9.68 7,505 

32 0.28 14.87 11,531 18.43 14,284 14.88 2,298 9.62 7,458 

42 0.37 15.83 12,270 19.68 15,259 15.84 2,995 9.25 7,168 

56 0.50 17.17 13,312 20.70 16,048 17.20 3,896 8.79 6,811 

74 0.66 19.34 14,996 22.33 17,312 19.41 4,434 7.98 6,189 

99 0.87 22.22 17,225 23.18 17,965 22.34 3,784 6.96 5,393 

134 1.19 24.62 19,085 23.73 18,396 24.80 3,482 6.09 4,720 

177 1.56 27.26 21,130 22.99 17,824 27.63 2,783 4.93 3,820 

233 2.06 29.64 22,974 21.89 16,969 30.74 1,811 4.33 3,356 

307 2.72 30.69 23,791 19.89 15,415 33.32 1,235 4.06 3,145 

406 3.59 30.11 23,339 17.18 13,320 35.43 969 3.98 3,082 

540 4.78 29.71 23,030 13.99 10,846 37.13 1,219 3.95 3,063 

713 6.31 29.17 22,614 11.53 8,937 38.88 2,004 4.33 3,356 

1

Constrained by 5-m shoreline buffer 

Table 3-14. Habitat versus discharge relations for segment 1 Neversink River (NVR1). 

Discharge Brown trout adult 

Brown trout 

juvenile Shallow-fast guild Shallow-slow guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km Ha m2/km Ha m2/km 

28 0.17 24.39 9,380 37.46 14,408 3.35 1,288 17.00 6,538 

39 0.23 27.96 10,752 41.44 15,938 4.97 1,911 16.75 6,443 

54 0.32 34.36 13,214 46.27 17,798 6.28 2,416 16.39 6,303 

76 0.44 40.48 15,571 51.27 19,720 8.35 3,211 15.44 5,938 

105 0.62 47.54 18,286 55.78 21,455 8.38 3,224 14.04 5,401 

146 0.85 55.93 21,510 59.11 22,733 7.89 3,035 10.91 4,198 

203 1.19 64.85 24,943 58.63 22,551 4.58 1,761 8.53 3,282 

282 1.65 71.24 27,399 54.83 21,087 1.89 728 6.47 2,489 

393 2.30 73.69 28,343 47.31 18,196 0.81 310 5.72 2,202 

545 3.19 73.82 28,391 34.03 13,090 0.67 258 5.52 2,125 

758 4.43 74.96 28,830 20.85 8,019 0.79 302 6.40 2,463 

1,053 6.16 68.65 26,402 14.66 5,639 1.32 506 6.40 2,463 

1,463 8.55 65.71 25,275 15.02 5,777 1.03 398 6.64 2,556 

2,032 11.88 104.13 40,048 32.93 12,665 0.92 352 6.59 2,536 

2,824 16.51 47.30 18,194 17.87 6,872 0.38 146 6.56 2,525 

1

Constrained by 5-m shoreline buffer 
91

Table 3-15. Habitat versus discharge relations for segment 2 Neversink River (NVR2). 

Discharge Brown trout adult 

Brown trout 

juvenile Shallow-fast guild Shallow-slow guild1

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km Ha m2/km Ha m2/km 

70 0.23 36.96 15,597 40.63 17,145 8.62 3,637 18.28 7,715 

90 0.29 40.42 17,056 43.62 18,405 10.14 4,276 19.02 8,023 

117 0.38 44.88 18,938 46.01 19,414 11.19 4,720 17.25 7,277 

151 0.49 49.27 20,788 47.59 20,079 12.55 5,293 16.77 7,076 

195 0.63 53.59 22,610 46.70 19,704 14.07 5,937 16.17 6,823 

252 0.82 59.83 25,246 46.26 19,520 12.36 5,214 15.66 6,609 

325 1.06 63.51 26,797 43.83 18,494 11.28 4,761 14.53 6,130 

420 1.37 64.81 27,345 40.90 17,255 10.47 4,418 13.62 5,746 

543 1.77 63.42 26,758 37.05 15,632 9.92 4,184 12.59 5,311 

701 2.28 61.46 25,932 29.70 12,533 10.67 4,503 10.80 4,557 

905 2.95 59.83 25,246 25.91 10,932 10.06 4,243 9.56 4,032 

1,169 3.81 54.71 23,084 22.72 9,585 6.90 2,909 8.50 3,585 

1,511 4.92 46.97 19,817 19.54 8,245 4.09 1,724 7.90 3,335 

1,951 6.36 38.52 16,253 17.22 7,264 2.37 1,000 7.44 3,141 

2,859 9.31 29.61 12,492 15.25 6,434 3.04 1,282 6.54 2,760 

1

Constrained by 5-m shoreline buffer.

Table 3-16. Habitat versus discharge relations for segment 2 Neversink River (NVR2) – Continued. 

Discharge 

American shad 

juvenile 

American shad 

spawning 

Q 

(ft3

/s) 

Q 

(ft3/s/mi2) Ha m2

/km Ha m2/km 

70 0.23 47.33 16,503 10.92 3,809 

90 0.29 51.06 17,806 14.99 5,228 

117 0.38 54.92 19,152 21.20 7,394 

151 0.49 57.37 20,006 28.22 9,839 

195 0.63 56.31 19,638 33.73 11,761 

252 0.82 56.90 19,842 40.90 14,263 

325 1.06 55.24 19,262 44.48 15,509 

420 1.37 52.47 18,295 48.10 16,773 

543 1.77 44.21 15,416 47.18 16,453 

701 2.28 39.70 13,844 40.89 14,258 

905 2.95 34.32 11,969 37.20 12,971 

1,169 3.81 29.06 10,134 31.38 10,942 

1,511 4.92 24.89 8,681 22.66 7,902 

1,951 6.36 22.85 7,969 17.61 6,142 

2,859 9.31 21.30 7,427 13.57 4,733 
92
93

Appendix 4. Habitat Persistence Tables for Brown Trout (Salmo trutta) 

Spawning – Incubation and Dwarf Wedgemussels (Alasmidonta 

heterodon).
94

Table 4-1. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site WB0. Units of habitat ar

Incubation flow 

(ft3/s/mi2) 0.02 0.03 0.05 0.07 0.12 0.18 0.27 0.42 0.65 1.02 1.58 2.45 

(ft3/s) 9 14 21 32 53 82 124 192 298 465 721 1,118 

0.02 9 0 0 0 0 0 0 0 0 0 0 0 0 0.03 14 0 0 0 0 0 0 0 0 0 0 0 0 0.05 21 0 0 0 0 0 0 0 0 0 0 0 0 0.07 32 0 0 0 0 0 1 1 1 1 1 1 1 0.12 53 2 26 39 51 126 126 124 126 126 126 126 123 0.18 82 2 30 40 74 173 327 324 328 328 328 328 320 0.27 124 2 29 40 81 210 488 748 748 749 748 748 738 0.42 192 2 21 29 82 277 599 1,113 2,205 2,206 2,206 2,206 2,194 0.65 298 1 12 22 72 295 724 1,605 3,160 4,105 4,103 4,094 4,092 1.02 465 0 2 11 51 232 581 1,529 3,221 4,375 4,748 4,702 4,742 1.58 721 0 0 3 31 151 425 1,280 2,756 3,848 4,225 4,634 4,629 2.45 1,118 0 0 0 3 8 12 50 485 1,144 1,527 1,883 2,273 3.81 1,740 0 0 0 0 0 0 0 0 47 119 211 406 5.92 2,698 0 0 0 0 0 0 0 0 2 5 15 39 

Spawning 

flow 

9.19 4,189 0 0 0 0 0 0 0 0 0 0 0 0 
95

Table 4-2. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site WB1. Units of habitat ar

Incubation flow 

(ft3/s/mi2) 0.08 0.11 0.15 0.21 0.30 0.42 0.59 0.83 1.19 1.60 2.25 3.20 

(ft3/s) 46 64 88 125 177 247 353 494 706 953 1,341 1,906 

0.08 46 0 0 0 0 0 0 0 0 0 0 0 0 0.11 64 0 58 59 59 59 59 59 59 59 59 59 45 0.15 88 0 233 482 483 483 483 483 483 483 483 483 405 0.21 125 0 493 862 1,153 1,152 1,153 1,152 1,153 1,153 1,153 1,152 933 0.30 177 0 1,077 1,606 2,095 2,530 2,530 2,530 2,532 2,531 2,531 2,530 2,242 0.42 247 0 1,505 2,661 3,403 3,979 4,603 4,600 4,602 4,602 4,601 4,598 4,300 0.59 353 0 1,422 2,647 3,952 4,838 5,705 6,645 6,643 6,645 6,642 6,632 6,338 0.83 494 0 1,266 2,421 3,767 5,381 6,888 8,172 9,044 9,043 9,041 9,028 8,742 1.19 706 0 849 1,844 2,978 4,550 6,127 7,791 8,939 9,644 9,640 9,625 9,506 1.60 953 0 411 932 1,521 2,614 3,758 5,195 6,413 7,276 7,608 7,593 7,590 2.25 1,341 0 120 263 410 686 1,217 2,114 2,992 3,834 4,260 4,298 4,295 3.20 1,906 0 0 0 1 21 71 212 512 1,020 1,336 1,405 1,429 4.51 2,683 0 0 0 0 0 0 0 1 76 191 236 257 6.35 3,777 0 0 0 0 0 0 0 0 0 2 3 8 

Spawning 

flow 

8.96 5,330 0 0 0 0 0 0 0 0 0 0 0 0 
96

Table 4-3. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site EB0. Units of habitat are 

Incubation flow 

(ft3/s/mi2) 0.02 0.03 0.05 0.07 0.10 0.15 0.24 0.35 0.54 0.82 1.25 1.90 

(ft3/s) 7 11 18 25 39 57 89 131 202 305 465 706 

0.02 7 0 0 0 0 0 0 0 0 0 0 0 0 0.03 11 0 0 0 0 0 0 0 0 0 0 0 0 0.05 18 0 0 0 0 0 0 0 0 0 0 0 0 0.07 25 0 3 6 6 6 6 6 6 6 6 6 6 0.10 39 0 13 27 30 32 32 32 32 32 32 32 31 0.15 57 0 28 108 150 186 190 190 190 190 190 190 179 0.24 89 0 35 211 481 797 840 849 849 849 849 849 838 0.35 131 0 35 210 524 1,412 2,134 2,891 2,940 2,940 2,940 2,940 2,928 0.54 202 0 25 155 368 1,217 2,339 3,621 3,873 3,949 3,949 3,949 3,949 0.82 305 0 0 63 183 871 1,933 3,213 3,668 3,963 3,991 3,991 3,991 1.25 465 0 0 0 18 523 1,393 2,406 2,776 3,096 3,210 3,215 3,215 1.90 706 0 0 0 0 0 0 0 86 223 312 327 338 2.89 1,076 0 0 0 0 0 0 0 0 0 0 1 6 4.40 1,637 0 0 0 0 0 0 0 0 0 0 0 0 

Spawning 

flow 

6.68 2,485 0 0 0 0 0 0 0 0 0 0 0 0 
97

Table 4-4. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site EB1. Units of habitat are 

Incubation flow 

(ft3/s/mi2) 0.08 0.12 0.15 0.22 0.31 0.43 0.60 0.84 1.17 1.61 2.23 3.14 

(ft3/s) 35 53 70 102 141 197 275 384 535 739 1,021 1,440 

0.08 35 91 91 91 91 91 91 91 91 82 50 40 26 0.12 53 176 289 289 289 289 289 289 289 265 206 186 160 0.15 70 333 474 599 600 600 600 600 600 571 478 447 408 0.22 102 525 709 893 1,003 1,003 1,003 1,003 1,003 975 866 825 763 0.31 141 629 906 1,148 1,324 1,439 1,440 1,439 1,440 1,413 1,295 1,211 1,121 0.43 197 670 1,009 1,303 1,560 1,725 1,862 1,859 1,862 1,857 1,741 1,619 1,501 0.60 275 598 938 1,328 1,635 1,868 2,087 2,194 2,194 2,193 2,120 2,010 1,869 0.84 384 269 496 831 1,149 1,455 1,751 1,966 2,014 2,015 1,991 1,936 1,804 1.17 535 59 139 257 478 815 1,158 1,435 1,570 1,642 1,626 1,631 1,569 1.61 739 0 0 2 28 73 151 359 488 637 813 802 802 2.23 1,021 0 0 0 0 0 15 103 186 341 539 701 701 3.14 1,440 0 0 0 0 0 0 0 2 33 184 374 815 4.38 2,006 0 0 0 0 0 0 0 0 0 45 117 537 6.07 2,781 0 0 0 0 0 0 0 0 0 0 0 144 

Spawning 

flow 

8.45 3,872 0 0 0 0 0 0 0 0 0 0 0 0 
98

Table 4-5. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site EB2. Units of habitat are 

Incubation flow 

(ft3/s/mi2) 0.13 0.19 0.25 0.38 0.57 0.89 1.28 1.78 1.96 2.68 4.08 5.87 

(ft3/s) 100 150 200 300 450 700 1,000 1,399 1,539 2,099 3,199 4,598 

0.13 100 543 543 543 543 543 543 543 543 543 475 166 121 0.19 150 1,185 1,437 1,438 1,438 1,438 1,438 1,438 1,438 1,438 1,292 362 249 0.25 200 1,919 2,244 2,408 2,409 2,409 2,409 2,409 2,409 2,409 2,234 753 342 0.38 300 2,499 3,089 3,319 3,546 3,547 3,547 3,547 3,547 3,547 3,363 1,689 514 0.57 450 1,868 2,872 3,538 4,200 4,666 4,667 4,667 4,667 4,667 4,487 2,899 1,238 0.89 700 1,068 1,882 2,599 3,935 4,977 5,675 5,676 5,676 5,676 5,546 4,069 2,533 1.28 1,000 124 422 790 1,813 3,130 4,192 4,375 4,375 4,375 4,375 3,664 2,533 1.78 1,399 0 20 54 422 1,312 2,518 2,810 2,859 2,859 2,859 2,678 1,982 1.96 1,539 0 5 18 242 990 2,146 2,431 2,473 2,473 2,474 2,294 1,698 2.68 2,099 0 0 0 0 10 328 489 571 573 606 604 572 4.08 3,199 0 0 0 0 0 0 0 1 1 16 22 22 5.87 4,598 0 0 0 0 0 0 0 0 0 0 0 0 8.54 6,697 0 0 0 0 0 0 0 0 0 0 0 0 

12.62 9,896 0 0 0 0 0 0 0 0 0 0 0 0 

Spawning 

flow 

27.03 21,191 0 0 0 0 0 0 0 0 0 0 0 0 
99

Table 4-6. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site DEL1. Units of habitat ar

Incubation flow 

(ft3/s/mi2) 0.22 0.27 0.36 0.47 0.60 0.78 1.00 1.31 1.69 2.20 2.84 3.69 

(ft3/s) 342 424 565 741 953 1,236 1,589 2,083 2,683 3,495 4,518 5,860 

0.22 342 431 1,831 1,833 1,833 1,833 1,832 1,832 1,831 1,832 1,832 1,833 1,820 0.27 424 2,603 2,643 2,644 2,644 2,644 2,643 2,642 2,641 2,642 2,642 2,643 2,630 0.36 565 3,710 3,803 3,841 3,841 3,842 3,841 3,840 3,838 3,839 3,838 3,840 3,828 0.47 741 4,886 5,092 5,188 5,227 5,227 5,226 5,225 5,223 5,223 5,222 5,224 5,214 0.60 953 4,859 5,357 5,565 5,643 5,662 5,660 5,660 5,658 5,657 5,655 5,658 5,651 0.78 1,236 4,199 5,062 5,722 5,949 6,018 6,028 6,026 6,024 6,025 6,022 6,025 6,018 1.00 1,589 2,912 3,699 4,484 4,952 5,086 5,151 5,169 5,165 5,167 5,163 5,166 5,164 1.31 2,083 1,318 1,768 2,279 2,600 2,786 2,908 3,006 3,040 3,040 3,039 3,039 3,038 1.69 2,683 314 435 605 772 880 992 1,125 1,250 1,270 1,270 1,270 1,270 2.20 3,495 0 9 64 132 192 244 335 509 589 613 613 612 2.84 4,518 0 0 0 0 0 5 20 120 193 241 253 253 3.69 5,860 0 0 0 0 0 0 5 47 84 117 126 126 4.75 7,554 0 0 0 0 0 0 0 2 12 20 22 22 6.17 9,813 0 0 0 0 0 0 0 0 0 0 0 0 

Spawning 

flow 

7.99 12,708 0 0 0 0 0 0 0 0 0 0 0 0 
100

Table 4-7. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site DEL2. Units of habitat ar

Incubation flow 

(ft3/s/mi2) 0.28 0.36 0.46 0.58 0.74 0.95 1.21 1.54 1.98 2.52 3.22 4.11 

(ft3/s) 466 597 762 974 1,243 1,585 2,023 2,577 3,297 4,208 5,373 6,855 

0.28 466 2,219 2,220 2,220 2,220 2,219 2,214 2,201 2,147 1,801 1,195 457 361 0.36 597 2,216 2,380 2,381 2,381 2,380 2,380 2,375 2,330 1,985 1,355 629 500 0.46 762 2,009 2,478 2,716 2,716 2,716 2,716 2,715 2,687 2,380 1,785 1,097 852 0.58 974 1,625 2,294 2,661 2,836 2,836 2,836 2,835 2,835 2,617 2,101 1,467 1,126 0.74 1,243 1,114 1,771 2,297 2,727 3,117 3,118 3,117 3,118 3,100 2,682 2,065 1,566 0.95 1,585 531 1,091 1,549 2,032 2,480 3,215 3,214 3,215 3,214 3,123 2,587 1,951 1.21 2,023 95 287 655 1,044 1,487 2,246 2,428 2,428 2,427 2,428 2,175 1,635 1.54 2,577 0 6 72 319 694 1,421 1,609 1,798 1,798 1,797 1,779 1,327 1.98 3,297 0 0 0 10 143 561 743 986 1,219 1,219 1,219 922 2.52 4,208 0 0 0 0 0 8 86 307 668 833 833 821 3.22 5,373 0 0 0 0 0 0 0 57 330 790 844 844 4.11 6,855 0 0 0 0 0 0 0 0 33 275 592 867 5.25 8,751 0 0 0 0 0 0 0 0 0 10 137 480 6.70 11,172 0 0 0 0 0 0 0 0 0 0 4 32 

Spawning 

flow 

8.55 14,261 0 0 0 0 0 0 0 0 0 0 0 0 
101

Table 4-8. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site DEL3. Units of habitat ar

Incubation flow 

(ft3/s/mi2) 0.28 0.36 0.46 0.58 0.76 0.98 1.26 1.62 2.09 2.69 3.46 

(ft3/s) 505 650 833 1,059 1,377 1,779 2,291 2,951 3,798 4,889 6,294 

0.28 505 8,678 8,678 8,678 8,678 8,678 8,678 8,678 8,678 8,678 8,670 8,224 0.36 650 10,362 10,546 10,546 10,546 10,546 10,546 10,546 10,546 10,546 10,538 10,153 0.46 833 10,604 11,079 11,270 11,270 11,270 11,270 11,270 11,270 11,270 11,262 11,023 0.58 1,059 9,535 10,381 10,889 11,338 11,669 11,729 11,729 11,729 11,729 11,724 11,532 0.76 1,377 7,111 8,806 9,819 11,433 12,231 12,376 12,376 12,376 12,376 12,373 12,247 0.98 1,779 4,006 5,665 9,796 11,554 12,943 13,195 13,195 13,195 13,195 13,195 13,153 1.26 2,291 591 1,400 3,163 6,015 8,729 9,230 9,357 9,342 9,348 9,355 9,357 1.62 2,951 73 309 710 2,141 5,455 6,377 6,598 6,746 6,747 6,747 6,747 2.09 3,798 0 0 38 244 1,095 1,821 2,237 2,485 2,586 2,586 2,584 2.69 4,889 0 0 0 1 69 400 686 1,051 1,283 1,364 1,358 3.46 6,294 0 0 0 0 0 0 32 215 418 564 668 4.45 8,105 0 0 0 0 0 0 0 0 19 102 211 5.73 10,435 0 0 0 0 0 0 0 0 0 2 32 7.38 13,435 0 0 0 0 0 0 0 0 0 0 0 

Spawning 

flow 

9.50 17,297 0 0 0 0 0 0 0 0 0 0 0 
102

Table 4-9. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site NVR0. Units of habitat a

Incubation flow 

(ft3/s/mi2) 0.12 0.16 0.22 0.28 0.37 0.50 0.66 0.87 1.19 1.56 2.06 2.72 

(ft3/s) 14 18 25 32 42 56 74 99 134 177 233 307 

0.12 14 1 1 1 1 1 1 1 1 1 1 1 0 0.16 18 5 10 11 11 11 11 11 11 11 11 10 3 0.22 25 39 55 81 81 81 81 81 81 81 80 75 64 0.28 32 82 104 142 170 171 171 172 172 172 170 162 150 0.37 42 88 128 177 230 273 273 273 273 273 271 263 245 0.50 56 89 133 209 542 628 721 720 721 720 719 710 688 0.66 74 89 138 323 873 1,121 1,243 1,559 1,549 1,552 1,534 1,553 1,529 0.87 99 79 125 373 1,134 1,530 1,670 1,964 2,109 2,109 2,084 2,107 2,094 1.19 134 55 92 362 1,145 1,628 1,934 2,338 2,550 2,604 2,554 2,585 2,602 1.56 177 28 63 346 1,134 1,650 2,015 2,578 2,818 2,972 3,069 3,070 3,070 2.06 233 6 27 212 936 1,382 1,663 2,076 2,308 2,558 2,708 2,884 2,884 2.72 307 0 18 185 815 1,194 1,430 1,769 1,978 2,259 2,496 2,707 2,788 3.59 406 0 0 1 9 148 286 492 618 847 1,087 1,329 1,463 4.78 540 0 0 0 0 1 1 27 104 241 411 619 774 

Spawning 

flow 

6.31 713 0 0 0 0 0 0 0 1 10 55 176 263 
103

Table 4-10. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site NVR1. Units of habitat 

Incubation flow 

(ft3/s/mi2) 0.17 0.23 0.32 0.44 0.62 0.85 1.19 1.65 2.30 3.19 4.43 6.16 

(ft3/s) 28 39 54 76 105 146 203 282 393 545 758 1,053 

0.17 28 0 0 0 0 0 0 0 0 0 0 0 0 0.23 39 31 95 95 95 95 95 95 95 95 95 95 95 0.32 54 51 131 161 162 162 162 162 162 162 162 162 158 0.44 76 191 340 400 425 425 425 425 425 425 425 425 237 0.62 105 321 734 817 860 896 896 896 896 896 896 896 521 0.85 146 339 855 1,067 1,166 1,260 1,322 1,322 1,321 1,322 1,322 1,322 943 1.19 203 304 824 1,221 1,932 2,211 2,322 2,343 2,344 2,344 2,344 2,344 1,995 1.65 282 209 713 1,094 1,919 2,424 2,623 2,663 2,670 2,670 2,670 2,670 2,373 2.30 393 62 328 558 979 1,451 1,706 1,790 1,827 1,841 1,841 1,841 1,738 3.19 545 0 0 2 53 365 591 676 751 789 791 791 792 4.43 758 0 0 0 0 0 15 61 104 143 162 165 165 6.16 1,053 0 0 0 0 0 0 0 0 3 5 8 8 8.55 1,463 0 0 0 0 0 0 0 0 0 0 0 0 

11.88 2,032 0 0 0 0 0 0 0 0 0 0 0 0 

Spawning 

flow

16.51 2,824 0 0 0 0 0 0 0 0 0 0 0 0 
104

Table 4-11. Persistent spawning-incubation habitat for brown trout (Salmo trutta) at site NVR2. Units of habitat 

Incubation flow 

(ft3/s/mi2) 0.23 0.30 0.38 0.49 0.64 0.82 1.07 1.38 1.78 2.30 2.97 3.83 

(ft3/s) 70 90 117 151 195 252 325 420 543 701 905 1,169 

0.23 70 995 993 996 996 988 984 970 941 747 483 331 224 0.30 90 1,280 1,370 1,371 1,371 1,371 1,371 1,361 1,333 1,140 757 545 396 0.38 117 1,571 1,708 1,839 1,841 1,841 1,841 1,836 1,809 1,621 1,207 870 669 0.49 151 1,993 2,284 2,507 2,718 2,721 2,721 2,720 2,702 2,518 2,111 1,663 1,393 0.64 195 2,932 3,624 4,094 4,477 4,785 4,788 4,788 4,785 4,624 4,226 3,726 3,358 0.82 252 2,717 3,823 4,472 4,982 5,366 5,718 5,720 5,720 5,682 5,347 4,867 4,393 1.07 325 2,262 3,314 4,125 4,864 5,407 5,878 6,174 6,177 6,177 6,078 5,694 5,159 1.38 420 1,891 2,821 3,531 4,300 4,974 5542 5,920 6,169 6,171 6,171 5,971 5,494 1.78 543 1,617 2,397 2,963 3,574 4,174 4,718 5,182 5,514 5,777 5,778 5,776 5,488 2.30 701 858 1,389 1,769 2,125 2,563 3,007 3,409 3,725 3,968 4,185 4,187 4,138 2.97 905 1 23 67 117 186 310 495 701 890 1,103 1,248 1,250 3.83 1,169 0 1 5 15 33 76 133 223 329 486 633 685 4.95 1,511 0 0 0 2 6 21 39 64 109 203 312 398 6.39 1,951 0 0 0 0 1 1 5 15 28 62 118 180 

Spawning 

flow 

9.37 2,859 0 0 0 0 0 0 0 0 0 4 22 44 
105

Table 4-12. Persistent habitat for dwarf wedgemussels (Alasmidonta heterodon) at site DEL1. Units of habitat a

Discharge # 2 

(ft3/s/mi2) 0.22 0.27 0.36 0.47 0.60 0.78 1.00 1.31 1.69 2.20 2.84 3.69 

(ft3/s) 342 424 565 741 953 1,236 1,589 2,083 2,683 3,495 4,518 5,860 

0.22 342 2.83 2.82 2.82 2.82 2.82 2.79 2.79 2.82 2.72 2.50 2.03 1.73 0.27 424 2.82 3.04 3.04 3.03 3.03 3.00 3.00 3.03 2.92 2.70 2.22 1.91 0.36 565 2.82 3.04 3.18 3.18 3.17 3.14 3.14 3.17 3.07 2.84 2.35 2.02 0.47 741 2.82 3.03 3.18 3.30 3.29 3.27 3.27 3.29 3.18 2.95 2.44 2.11 0.60 953 2.82 3.03 3.17 3.29 3.39 3.36 3.36 3.38 3.27 3.04 2.52 2.19 0.78 1,236 2.79 3.00 3.14 3.27 3.36 3.56 3.55 3.56 3.46 3.22 2.70 2.35 1.00 1,589 2.79 3.00 3.14 3.27 3.36 3.55 3.67 3.67 3.56 3.32 2.79 2.44 1.31 2,083 2.82 3.03 3.17 3.29 3.38 3.56 3.67 3.82 3.69 3.44 2.91 2.55 1.69 2,683 2.72 2.92 3.07 3.18 3.27 3.46 3.56 3.69 3.82 3.57 3.02 2.66 2.20 3,495 2.50 2.70 2.84 2.95 3.04 3.22 3.32 3.44 3.57 3.70 3.12 2.76 2.84 4,518 2.03 2.22 2.35 2.44 2.52 2.70 2.79 2.91 3.02 3.12 3.29 2.88 3.69 5,860 1.73 1.91 2.02 2.11 2.19 2.35 2.44 2.55 2.66 2.76 2.88 2.95 4.75 7,554 1.44 1.59 1.69 1.77 1.85 2.00 2.09 2.19 2.30 2.39 2.47 2.53 6.17 9,813 0.99 1.11 1.19 1.26 1.32 1.46 1.54 1.63 1.74 1.82 1.86 1.89 

Discharge # 1 

7.99 12,708 0.79 0.88 0.94 0.99 1.04 1.16 1.22 1.31 1.40 1.47 1.53 1.55 
106

Table 4-13. Persistent habitat for dwarf wedgemussels (Alasmidonta heterodon) at site DEL2. Units of habitat a

Discharge # 2 

(ft3/s/mi2) 0.28 0.36 0.46 0.58 0.74 0.95 1.21 1.54 1.98 2.52 3.22 4.11 

(ft3/s) 466 597 762 974 1,243 1,585 2,023 2,577 3,297 4,208 5,373 6,855 

0.28 466 5.56 5.56 5.56 5.56 5.56 5.55 5.54 5.33 4.85 4.11 3.23 2.73 0.36 597 5.56 5.71 5.71 5.71 5.71 5.70 5.69 5.47 4.98 4.22 3.32 2.81 0.46 762 5.56 5.71 5.86 5.86 5.86 5.85 5.84 5.62 5.12 4.34 3.42 2.90 0.58 974 5.56 5.71 5.86 6.06 6.06 6.05 6.03 5.81 5.30 4.50 3.55 3.02 0.74 1,243 5.56 5.71 5.86 6.06 6.25 6.25 6.23 5.99 5.47 4.66 3.67 3.13 0.95 1,585 5.55 5.70 5.85 6.05 6.25 6.36 6.34 6.11 5.57 4.75 3.75 3.20 1.21 2,023 5.54 5.69 5.84 6.03 6.23 6.34 6.47 6.23 5.68 4.85 3.83 3.26 1.54 2,577 5.33 5.47 5.62 5.81 5.99 6.11 6.23 6.35 5.78 4.93 3.90 3.33 1.98 3,297 4.85 4.98 5.12 5.30 5.47 5.57 5.68 5.78 5.94 5.06 4.02 3.43 2.52 4,208 4.11 4.22 4.34 4.50 4.66 4.75 4.85 4.93 5.06 5.19 4.10 3.50 3.22 5,373 3.23 3.32 3.42 3.55 3.67 3.75 3.83 3.90 4.02 4.10 4.23 3.60 4.11 6,855 2.73 2.81 2.90 3.02 3.13 3.20 3.26 3.33 3.43 3.50 3.60 3.67 5.25 8,751 2.23 2.30 2.38 2.48 2.58 2.64 2.70 2.75 2.84 2.91 2.98 3.05 6.70 11,172 1.51 1.56 1.62 1.69 1.77 1.80 1.84 1.89 1.93 1.95 1.88 1.79 

Discharge # 1

8.55 14,261 0.91 0.94 0.98 1.04 1.09 1.12 1.15 1.19 1.23 1.25 1.23 1.18 
107

Table 4-14. Persistent habitat for dwarf wedgemussels (Alasmidonta heterodon) at site DEL3. Units of habitat a

Discharge # 2 

(ft3/s/mi2) 0.28 0.36 0.46 0.58 0.76 0.98 1.26 1.62 2.09 2.69 3.46 4.45 

(ft3/s) 505 650 833 1,059 1,377 1,779 2,291 2,951 3,798 4,889 6,294 8,105 

0.28 505 3.53 3.48 3.39 3.27 3.15 2.97 2.74 2.44 2.06 1.76 1.36 0.90 0.36 650 3.48 3.91 3.80 3.68 3.55 3.14 2.96 2.71 2.36 2.03 1.57 1.04 0.46 833 3.39 3.80 4.29 4.16 4.02 3.49 3.13 2.95 2.68 2.29 1.78 1.16 0.58 1,059 3.27 3.68 4.16 4.59 4.44 3.90 3.40 3.11 2.93 2.48 1.92 1.26 0.76 1,377 3.15 3.55 4.02 4.44 4.72 4.25 3.74 3.29 3.09 2.61 2.01 1.32 0.98 1,779 2.97 3.14 3.49 3.90 4.25 4.52 4.02 3.53 3.15 2.38 1.84 1.19 1.26 2,291 2.74 2.96 3.13 3.40 3.74 4.02 4.14 3.72 3.27 2.26 1.77 1.16 1.62 2,951 2.44 2.71 2.95 3.11 3.29 3.53 3.72 3.95 3.33 2.78 2.11 1.33 2.09 3,798 2.06 2.36 2.68 2.93 3.09 3.15 3.27 3.33 3.49 2.85 2.11 1.31 2.69 4,889 1.76 2.03 2.29 2.48 2.61 2.38 2.26 2.78 2.85 3.02 2.07 1.25 3.46 6,294 1.36 1.57 1.78 1.92 2.01 1.84 1.77 2.11 2.11 2.07 2.39 1.15 4.45 8,105 0.90 1.04 1.16 1.26 1.32 1.19 1.16 1.33 1.31 1.25 1.15 1.59 5.73 10,435 0.31 0.39 0.46 0.50 0.52 0.45 0.46 0.52 0.50 0.49 0.46 0.33 7.38 13,435 0.21 0.26 0.31 0.33 0.35 0.31 0.32 0.35 0.33 0.32 0.32 0.24 

Discharge # 1 

9.50 17,297 0.24 0.28 0.32 0.35 0.37 0.34 0.34 0.37 0.36 0.35 0.32 0.24 
108
109

Appendix 5. User Documentation for the Delaware River Decision Support 

System 

Getting Started 

The very first step in using the Delaware River Decision Support System (DRDSS) is to 

make sure that the computational infrastructure is up to the task. The system appears to run 

adequately on computers having a 3 GHz processor and at least 1 GB of RAM. In addition, we 

have found that the DRDSS requires Excel 2003 in order to load all the required spreadsheets. 

Excel 2002 will open some of them, but not all. Each run of the DRDSS requires a separate 

directory containing all the spreadsheets and any supporting files. Consequently, the volume of 

hard drive space consumed by DRDSS directories can accumulate rapidly. A convenient and 

economical solution to this problem is to store DRDSS directories on an external hard drive. 

External hard drives provide good system backup as well as ease of transport from one computer to 

another (especially useful for public hearings or meetings where multiple runs are to be displayed). 

Although the most of the graphics displays in the DRDSS are formatted to be distinguishable in 

black and white, a color printer capable of handling tabloid-sized paper (11 x 17 in) or larger will 

provide greater definition of graphs and charts. In some cases, access to a large-format plotter 

capable of generating poster-sized printouts may be desirable. 

The DRDSS consists of five linked spreadsheets titled DSS_AGG.XLS, DSS_WB.XLS, 

DSS_EB.XLS, DSS_DEL.XLS, and DSS_NVR.XLS. In addition, there are two utility 

spreadsheets,”met_data.xls” and “OASIS reformatterV2_1.xls” that are integral components to the 

DRDSS. “Met_data.xls” contains the meteorological data (historical, normal, and worst-case) 

needed to perform temperature simulations. The OASIS reformatter converts hydrologic 

information from OASIS into the format required as input to the DRDSS. 

None of these spreadsheets is adequately protected to prevent inadvertent damage caused by 

keystroke errors or information pasted into the wrong places. Even minor modifications to the code 

can render the entire system useless, so users are advised to work on copies of the DRDSS master 

files instead of working on the original version. Before doing anything else, the user should create a 

directory named according to the alternatives to be tested (for example, REV1_REV7 as a directory 

name). The DSS_AGG worksheet, all four of the SUBS (DSS_WB.XLS, DSS_EB.XLS, 

DSS_DEL.XLS, and DSS_NVR.XLS), and the two utility files should be copied into this directory. 

The DRDSS cannot be run from the native medium (in this case, a CD) and must be copied to a 

hard drive. It is helpful to include a small “README” file to this directory that describes the 

OASIS modifications performed for the comparisons embodied in the particular DRDSS run. 

These two steps will provide backup in the event that the DRDSS files are compromised and will 

assist the user in recalling the changes made to test an alternative. Describing the characteristics of 

the run is especially important if multiple runs are made because some of the changes may be 

subtle. It can be extremely frustrating to arrive at a promising solution and not remember how it 

was derived. 

Preparing Input Data 

Importing Data from OASIS to DRDSS 

There are several critical details to keep in mind before starting. First, order is critical, both 

temporally and spatially. If data are not entered in the order expected by the DSS, the results will 
110

be incorrect; in such a case, the only way to gain correct results would be to start over. Incorrect or 

erroneous applications of the DRDSS may be virtually indistinguishable from correct applications. 

Finding mistakes can be traumatic, especially if they are found during a public hearing or 

negotiations setting. Fixing them can be time-consuming and frustrating. 

An example of this type of mix-up occurred during the beta-testing of version 2.0, where a 

user entered OASIS output for the baseline period 1990 – 2000, but used the record from 1960 – 

1970 for the alternative. The mistake was detected by the decisionmakers, who realized that the 

outcome displayed on the summary scoring page was counterintuitive. In this case, the intuition of 

the decisionmakers was correct and the model results were wrong. 

The DRDSS operates on a 10-year period of water years, which begin on October 1 

(October 1, 1995, is the first day of water year 1996). Any 10-year period between 1953 and 2000 

can be used, so long as it starts on October 1, ends on September 30, and has 10 years of data 

between the two. Note that OASIS output extends back to 1928. The usable period in the DRDSS 

extends only to 1953 because of limitations of the meteorological database. 

Output derived from OASIS consists of at least two individual text files containing daily 

flow data, reservoir storage and release data, system-wide drought trigger data, Montague flows, 

and export data for New York City and the Delaware and Raritan canal diversion in New Jersey. 

One file contains data for the baseline and the other contains data for the alternative. The spatial 

order of the data from left to right is the same in the OASIS text files as it is in the DRDSS with 

one major exception: OASIS does not produce flow statistics for the Beaverkill, but there is a 

column in the DRDSS “FLOWS” sheet for the Beaverkill. The historical discharges of the 

Beaverkill have been incorporated in the “OASIS reformatter.xls” spreadsheet, provided to convert 

OASIS output to the correct spatial order required to the DRDSS. 

Preparing Data for Import from OASIS 

1. Open the “OASIS formatter.xls” spreadsheet and click on the page labeled “From_OASIS” 

(Fig. 5-1). 

2. Open the first (baseline) OASIS text file in a new Excel workbook as a space delimited file. 

3. Go to the first data value (the first Stilesville flow) in the newly opened OASIS workbook. 

Select and copy all the data values. Do not copy dates or column headers. 

4. Open the “From_OASIS” page in the OASIS_formatter spreadsheet and paste the OASIS data 

to cell B15 (Fig 5-1). 

5. As soon as the OASIS data are pasted into the “From_OASIS” sheet, the “To_DSS” sheet is 

automatically updated. 

Exporting Data to the DRDSS 

6. Click on the tab “To_DSS” in the OASIS formatter spreadsheet (fig. 5-2). 

7. Move the cursor to the first day of the first water year to be processed in the DRDSS (for 

example, October 1, 1959, for water year 1960). 

8. Select and copy the entire block of data (including the date) from this point to the last data 

column for the last day of the tenth water year from the start date (in this example, September 

30, 1969; fig. 5-2). 
111

Figure 5-1. The “From_OASIS” page of “OASIS_formatter.xls.” Outlined box in figure shows 

where the data copied from the OASIS text file are to be pasted. 

Figure 5-2. The “To_DSS” page of “OASIS formatter.xls.” In the example, the first date of the first 

water year of interest is October 1, 1959, located at cell A11611. 
112

9. In the DSS_AGG.xls workbook, click on the tab labeled “Flows” (fig. 5-3). This worksheet 

contains the flows, storage volumes, releases, and spills computed by OASIS. Flows are 

arrayed by date (row) and by study area (column) in two blocks (left and right). The first block 

pertains to the baseline, and starts at cell A11 (fig 5-3). The second block is for the alternative, 

and it starts in cell AB11. Do not forget to update the second block with the same period of 

record as the first one. 

10. Having copied the 10-year data baseline block from “OASIS formatter.xls,” SELECT cell A11 

on the “Flows” page of DSS_AGG.xls and PASTE SPECIAL/VALUES. The data must be 

pasted as values because the dates in the data block from “OASIS formatter.xls” are actually 

formulas. 

Figure 5-3. The “Flows” page of “DSS_AGG.xls,” with outlined cell indicating where to paste 

baseline data from “OASIS formatter.xls.” 

11. Open the second OASIS text file, containing information for the alternative and repeat steps 1 – 

10, but pasting the data from “OASIS_reformatter.xls” in cell AE11 on the “Flows” page of 

“DSS_AGG.xls” (fig. 5-4). Note that the dates for the baseline and the alternative are copied 

and pasted into their respective locations independently from each “OASIS_reformatter.xls” 

scenario. The DRDSS compares the ranges of dates to confirm that the same period of record 

was used for both cases. The DRDSS will run successfully if mismatched data sets are used, but 

the user is alerted to the disparity on the scoring pages. 
113

Figure 5-4. The “Flows” page of “DSS_AGG.xls,” with outlined cell indicating where to paste data 

for an alternative from “OASIS formatter.xls.” 

Importing Meteorological Data 

To reiterate, there are three choices with regard to the meteorological data used in the 

DRDSS temperature calculations: (1) repetitive cycles of the 1993 – 2003 empirical data set from 

Monticello, (2) normal (average) meteorological values arranged by date, or (3) extreme daily 

values arranged by date. These data are contained in the file “met_data.xls.” Records in this 

spreadsheet match the period of record applicable to the DSS, extending from October 1, 1953, to 

September 30, 2003, with daily values filled in accordingly. As with the flow data, it is extremely 

important to match the dates from which the meteorological data are to be extracted with the dates 

used for the flow data. However, with the meteorological date, the copy/paste sequence is a little 

trickier because data are only recorded for the period May 1 – September 30. The rest of the dates 

have no data, but MUST BE COPIED ANYWAY in order to synchronize properly with the flow 

data. Furthermore, the dates for the meteorological data are not copied to the “Flows” page, so 

cross checking is not performed within the DRDSS to ensure synchronization. 

1. If not previously done, make a copy of “met_data.xls” and work off the copy. 

2. Continuing with our previous example, our period of record is from October 1, 1959, through 

September 30, 1969. Supposing that we are using “normal” meteorological conditions, the 

block from cell F2002 to I5854 would be copied (figs. 5-5 and 5-6). 
114

Beginning 

address for

data block to be 

copied. Note that 

there is nothing 

in the cell, but it 

must be copied 

anyway.

Beginning 

address for

data block to be 

copied. Note that 

there is nothing 

in the cell, but it 

must be copied 

anyway.

Figure 5-5. Cell F2002 in “met_data.xls,” the starting location for copying a ten-year block of 

“normal” meteorological data corresponding to the dates and flows previously imported to the 

“Flows” page of “DSS_AGG.xls.” 

Ending address of 

copied data block.

Figure 5-6. Selected block ending at cell I5854 in “met_data.xls,” the ending location for copying 

a ten-year block of “normal” meteorological data corresponding to the dates and flows previously 

imported to the “Flows” page of “DSS_AGG.xls.” 
115

3. Once the desired block of meteorological data has been copied, return to the “Flows” page of 

DSS_AGG.xls, and paste the data to cell BI11 (fig. 5-7). 

Do not be alarmed 

that nothing shows up 

in this cell. It 

corresponds to 

October 1 and there 

should be no data until 

May 1. Check the last 

row of the page, 

however, to ensure 

that the last line of the 

meteorological data 

matches the last line 

of the other data.

Do not be alarmed 

that nothing shows up 

in this cell. It 

corresponds to 

October 1 and there 

should be no data until 

May 1. Check the last 

row of the page, 

however, to ensure 

that the last line of the 

meteorological data 

matches the last line 

of the other data.

Figure 5-7. Cell BI11 on the “Flows” page of “DSS_AGG.xls” is outlined. This is where the 

meteorological data originating from the met_data.xls database are pasted. 

Setting the Scoring Parameters and Related Information on the “Parameters” Page. 

1. Open the DSS_AGG workbook and click on the tab labeled Parameters (fig. 5-8). 

2. Update parameters and scoring thresholds as desired. If no data are supplied, the values in the 

Default column (column C) will be used instead. Any value in column D (as well as E, F, or G 

in the case of temperature thresholds) will override the Default. User values must be in correct 

units or formatted as shown in the Units column (column B). Do not overwrite the values in 

column C as this will replace the defaults. If the default value is acceptable, no entry needs to 

be made in column D. Otherwise, modify the appropriate values as desired in column D. The 

exceptions are for entries 4, 5, and 6 (cells D17, D19, D20, and D22), which should be updated 

to keep track of the specifics of a scenario. The meteorological series entry (D39) is a 

documentation field only and DOES NOT import the meteorological data automatically. The 

DRDSS uses the meteorological data from the last run unless new data have been copied and 

pasted from “met_data.xls.” Run settings, labels for baseline and alternative scenarios, and the 

period of record are updated automatically on the “Summary” and “Raw Scores” pages of the 

DSS_AGG.xls spreadsheet as an aid to run documentation. 
116

Figure 5-8. Parameters page from “DSS_AGG.xls.” 

Making a DSS Run 

1. Double check all imported data to make sure everything lines up correctly with respect to dates 

and locations. 

2. Review the “Parameters” page to ensure that all the thresholds are correctly set and that the run 

identification data are entered correctly. 

3. Press the pink button labeled “Update Source Calculations” (fig. 5-8). The Update Source 

Calculations button sequentially opens each of the subsidiary workbooks (DSS_WB.xls, 

DSS_EB.xls, DSS_DEL.xls, and DSS_NVR.xls); copies the flow, meteorology, and parameter 

data into them; and recalculates all the values for the stream segment. Links to the stream files 

are updated in the DSS_AGG.xls file. Typical run times vary from 20 to 40 minutes, depending 

on processor speed. Do not push this button until all pertinent changes have been made and 

checked. 

Generating Graphics and Displays 

The DRDSS can generate a wide variety of graphics, all of which can be useful at different 

stages of interpreting and evaluating the outcomes of a run. Some displays should be generated for 

every run, whereas others need only to be generated on a case-by-case basis. Some of the graphics 

generated by the DRDSS are not automatically saved and can be overwritten. Therefore, it is 

advisable to save any desired graphics as hard copy, in electronic format (JPEG, TIF, or BMP, for 

example), or both. In this section, we have arranged the types of graphics and the means of 

generating them as a hierarchy, starting with graphics that should always be generated. 
117

Scoring Summary and Raw Scores Pages 

These scoring pages are actually tables that appear as Excel spreadsheet pages. Neither is a 

self-contained graphical unit, but must be manipulated to look like one for export, either to a printer 

or to an electronic graphics file. These pages can be printed directly from Excel to a single sheet, 

using the page setup and print preview options. Clarity and legibility can be improved by printing 

on tabloid-sized paper (11 x17 in), or larger. To create an electronic graphics file: 

1. Outline the block of cells to be included in the graphics file (cells A1 to Q64 for the summary 

page or cells B1 to BP103 for the raw scores page). Copy the block. 

2. Open Microsoft Word or (preferably) Powerpoint, select a new page (Word) or slide 

(Powerpoint) and click Edit/Paste Special/Picture. When the table appears satisfactorily on 

the page or slide, save the file under a name that reflects the alternatives being compared (for 

example, Rev1_Rev7_norm_60, for Revision 1 versus Revision 7 using normal year 

meteorological data for the decade 1960–1970). The advantage of storing these graphics in 

Powerpoint is that individual slides can be saved as JPEGs or other electronic graphics files. 

They cannot be saved directly in this format from Word. 

Flow, Storage, and Temperature Duration Curves 

These graphics are grouped together because they are all generated the same way. Flow and 

storage curves should be generated for every location and scenario. Temperature curves are 

optional and the decision to generate them depends on site- or situation-specific circumstances. 

1. Generate a duration curve for one of the sites. We will use flows at WB0 for this example. 

Generation of duration curves for other variables and sites will follow a parallel approach. 

a. Open one of the SUBS spreadsheets (in this example, DSS_WB.xls) and move to the 

WBDurCurve tab (fig. 5-9). 

b. Select “Flows” from the menu adjacent to the button labeled “Get Variable Plot” and “WB0 

from the menu next to the button labeled “Get Study Site” (fig. 5-9). 

c. Press the purple button labeled “Update Data.” The associated macros will proceed to sort 

the data and update the graph at the “DurCurveChart” page. 

d. As soon as the chart has updated, Excel automatically tabs to the DurCurveChart page, 

accompanied by an information window stating that the update is complete. Click OK on 

the information box. 

2. If desired, rescale the Y-axis to accentuate the low-flow portion of the curve. Set the cursor 

over the Y-axis, right click, and select “Format axis.” From the menu, select “Scale” and 

manually set the limit for the maximum value. Reset the increments between the maximum and 

minimum values if necessary by manually changing the number in the box labeled “Major 

Unit.” Click OK. Note that once the scale has been changed, the same scale will be used for all 

subsequent charts, sometimes with unintelligible results. To avoid such problems, the scale can 

be reset to automatically adjust after the graph has been printed or saved. 
118

Figure 5-9. Setup to generate a flow duration curve for WB0 on the “WBDurCurve” page of 

“DSS_WB.xls.” Selected Page tab and variables are highlighted. 

3. IMMEDIATELY print and/or save the chart. 

a. Left click anywhere on the chart area. Black highlight dots should appear to outline the 

chart. To print, select File/Print. (The default print settings are for letter-sized paper and 

landscape orientation. Check to ensure that the printer paper matches the size specified in 

the print settings). 

b. To save the chart electronically, select the chart area as above, and click Edit/Copy. Then 

open the electronic graphics file (the Word or Powerpoint file) created for the scenario, 

create a new page or slide, and Paste Special/Picture to paste the chart. Save the File and 

return to the WBDurCurve page in the DSS_WB.xls spreadsheet 

4. Select the next site or variable, and repeat steps 1–3 as necessary until all appropriate duration 

curves have been generated, printed, and saved. When finished, close the DSS_WB.xls 

workbook without saving. 

5. Open the next SUB workbook, such as DSS_EB.xls and repeat steps 1–4. Repeat for all the 

SUBS workbooks until the full complement of duration curves has been generated and saved. 

Duration Series Curves 

Duration series curves are generated by procedures almost identical to those used to 

produce the duration curves described in the previous section. The basic differences are that the 

variables and sites are selected on the <sitename>DurSer page of the SUB workbook (fig. 5-10), 

and the chart will be updated on the DurSerChart page of that site’s workbook. These charts may 

be considered optional, but should at least be reviewed and those showing “interesting” patterns of 

habitat availability should be saved or printed. The methods of printing or saving electronic 
119

versions of these charts are identical to those described for duration curves in the previous section. 

Unlike the duration curves, however, it will probably never be necessary to rescale the Y-axis to 

accentuate a particular portion of the chart. 

Note the 

requirement to 

specify the number 

of leap days in the 

decade used for 

the period of 

record. Selection 

of the wrong 

number of leap 

days can produce 

“interesting”

results.

Note the 

requirement to 

specify the number 

of leap days in the 

decade used for 

the period of 

record. Selection 

of the wrong 

number of leap 

days can produce 

“interesting”

results.

Figure 5-10. Setup to generate a flow duration series curve for WB0 on the “WBDurSer” page of 

“DSS_WB.xls.” Selected Page tab and variables are highlighted. 

Flow Plots 

The time series plots of flows in each segment and storage volumes in the three reservoirs 

are found on the “Flow Plots” page of the DSS_AGG workbook. The original intent of 

incorporating these plots into the DRDSS was to provide a quick on-screen review of the sequence 

of flows and storage volumes. The charts are set up to lock the window for the Y-axis, allowing the 

user to scroll back and forth through the sequence. Unfortunately, the sequence is so long that 

plotting the whole thing compresses the scale so much that the plot is virtually unreadable. 

There are several options available, however, in the event that a legible plot is needed. If the 

user has access to a large format color plotter, such as those used to produce poster presentations, 

the entire time series can be copied and pasted to a custom-sized (for example, 36 x 48 in) 

Powerpoint slide and printed in its entirety. Otherwise portions of the series can be copied to a 

more commonly-used size (either letter or tabloid) in a Powerpoint presentation file. The easiest 

way to copy a portion of the series is to scroll to the desired part of the sequence and use the “Print 

Screen” function on the computer. The contents of the clipboard can then be pasted to a Powerpoint 

slide and trimmed up to make presentable. 

The Raw Scores Page 

On occasion, it may be desirable to generate the Raw Scores page of the DSS_AGG 

workbook, especially if there are substantial spatial differences in the habitat responses to a change 
120

in operations. For example, the same operating rules might result in an increase of habitat metrics 

at WB0 and a decrease at WB1. Such a result could be masked on the Summary Scores page, 

which might indicate little or no change for the West Branch as a whole. 

The Raw Scores page is organized in exactly the same format as the Summary Scores page. 

The difference between the two scoring pages is that the Raw Scores page contains information for 

each study segment instead of a compilation of scores for each stream. Because the Raw Scores 

page is so much larger than the Summary Scores page, we encounter the same problem discussed 

previously for the Flow Plots. The entire Raw Scores page can be copied to a letter-sized slide or 

document, but no one will be able to read it. Tabloid size is marginally better, but still hard to read. 

The best overall option is the use of a custom sized Powerpoint slide that can be printed on 

a large format color plotter, or viewed as a projected image on a screen. To be as legible as a 

tabloid-sized version of the Summary Scores page, the page size for Raw Scores should be about 

three times as large (approximately 36 x 48 in). The same general procedures described for 

generating the Summary Scores page apply to copying and pasting the Raw Scores page, except 

that the block to be copied is much larger. 

Information Management 

The purpose of the DRDSS is to compare operations and results for numerous runs, so data 

management and organization of tabular and graphical output is of paramount importance. Each 

run has the potential of generating 89 different graphs and figures: 

1. One (1) Summary Scores page, 

2. Eleven (11) flow duration plots, 

3. Three (3) storage duration plots, 

4. Eight (8) temperature duration plots (none for the Neversink), 

5. Forty-eight (48) duration series curves (85 if curves including both temperature conditioned and 

unconditioned habitat are generated), 

6. Eleven or more (11+) flow series plots, depending on whether a series of partial plots must be 

generated, 

7. Three or more (3+) storage series plots, with the same caveat as above, and 

8. Four (4) Raw Scores pages. 

Recall that a DRDSS run represents the outcome for a single OASIS alternative for one 

decade. If the analyst were only to produce the minimum number of routinely-generated graphics 

(items 1–3 above) for all five decades in the period of record, there would be at least 45 graphs for 

each alternative. The need for organization should be obvious to even the most casual of observers. 

We have already discussed some of the basics regarding information management, such as 

setting up individual computer directories for each run. A parallel approach can be followed to 

organize the results from each run: 

1. Create a single directory for each run, named according to the alternative tested and the time 

period represented by the run (for example, Rev1_Rev7_1960s). The directory can consist of a 

file folder if all the results are to consist of hard copy. If the directory is to be created 

electronically, a backup folder should be created on an independent medium such as a CDROM or external hard drive. 

2. Write a README file containing the specifics of the objectives of the alternative and the 

operating rules defining the baseline and the alternative in the OASIS run, and put it in the 
121

folder. Over the years, we have witnessed a widespread failure to do this. Universally, everyone 

who has not documented the alternatives has regretted it later. 

3. Generate and save the necessary graphics. It may be convenient to save electronic graphics as a 

series of slides in an appropriately named Powerpoint presentation file. For hardcopy, it may be 

worthwhile to segregate graphics of a particular type, such as all the flow duration curves, into 

a subfolder. 

4. To the extent possible, conduct a cause-and-effect analysis of the run and write a brief synopsis 

of the mechanics leading to particular outcomes. For example, “Spawning-incubation habitat 

was decreased under the alternative. The probable cause was that streamflow was increased 

during October and November and remained the same as the baseline from December through 

April. The net result was that the differential between spawning flows and incubation flows 

increased, thereby causing a reduction in persistent spawning-incubation habitat.” Although this 

step might be considered optional, documenting the cause-effect mechanisms for both positive 

and negative outcomes will be extremely useful for developing the next scenario or a 

contingency plan. 

One idea for organizing these materials with consistent format and content is to collect all 

the aforementioned products into a poster. A primary advantage of the poster format is that the 

results of multiple runs can be displayed side-by-side for comparison during public hearings or 

Commission-related meetings. The best information in the world is useless if no one can 

understand it. It is almost as useless if decisionmakers cannot find or readily identify the 

information they need to address a particular problem. 

The poster option is available only for users having access to a large format color plotter, 

but it may be of sufficient utility to justify acquiring access to one by purchase, lease, or contract. 

Figure 5-11 illustrates a basic poster template that accommodates the summary scores page, 

multiple graphics ( in this case, all the flow and storage duration curves), and text boxes describing 

the conditions and outcomes of a DRDSS run. A similar design can be used for displaying raw 

scores and additional graphics. The poster shown in figure 5-11 was generated in ArcMap and 

originally dimensioned to 36 x 74 inches. This seems to be a suitable size because the items on the 

poster are legible at distances of two to three meters, but the posters are small enough to display 

several of them side-by-side in a meeting room. 

The poster format is a promising technique for consolidating, organizing, and displaying 

large amounts of information. The advantages of posters are that they can be fairly self-explanatory 

(not much text required or wanted) and visually stimulating, facilitating “big-picture” comparisons 

among alternatives. A disadvantage of posters is that it may difficult to anticipate what information 

the decisionmakers will find the most useful. This can lead the poster designer to try to include 

everything, at the risk of creating an illegible billboard overloaded with information. It may take 

several attempts before the most effective combination of design and content is accomplished, but 

the goal should always be to convey the most information to the most people in the most 

understandable way possible. 
122

Synopsis of 

objectives and 

operational 

differences for 

alternatives

Summary scores

page from 

DSS_AGG

Flow, storage, 

and

temperature 

duration curves

Diagnosis of 

results and 

cause-effect 

relations

Synopsis of 

objectives and 

operational 

differences for 

alternatives

Summary scores

page from 

DSS_AGG

Flow, storage, 

and

temperature 

duration curves

Diagnosis of 

results and 

cause-effect 

relations

Figure 5-11. Poster template generated for 36 x 74 inch page size in ArcMap, showing locations 

and relative sizes of components.