1. Onondaga County Regional Stream Simulation Study Dan Coyle Major Prof. – Dr. Hassett MPS Degree

2. OUTLINE 1. Introduction 2. Study Questions and Objectives 3. Model Development 4. Results- output charts 5. Discussion

3. Water Resource Management Various water processes- water cycle Quantity- availability Quality- for use Resource- value for use Damages- problems Common to many problems & theory – need for estimates of stream flows

4. 2. Study Questions & Objectives Literature search- 2 broad questions Model type selection? Model development? Second iteration is very limited

5. Categorization of Streamflow Models Lumped vs. spatial distributed Event versus continuous models Theoretical versus empirical My choice- lumped, continuous, & empirical

6. Develop or select model? Purposes- needs, ideas, motivations Learning curves- cost, time Limitations- risks, restrictions Assumptions- applicability Versatility & ease of use-extensibility Time & Money- budget, patience

7. Study Objective and Development Process Create and Evaluate Relatively Simple (and hence Extensible) Streamflow Model(s) Suitable for Central New York Using Readily Available Data Sources Utilize Model Development Process Common to Software Engineering Projects

8. Streamflow as Simulation Problem Stream flows- candidate models Extract model parameters- simple Calibrate parameter values- test Predict flows- validate model for ungauged flows

9. Considerations in Model Development A) Limit Streams to Those in National Water Information System (www.usgs.gov) B) Meteorological Data from Local National Weather Service Stations) (www.noaa.gov) C) Lumped Landuse Descriptors D) User application container E) System life cycle F) Candidate models G) Base flow separation H) Application logic

10. Stream Selection Name USGS # Area mi 2 YearsLand Use Spafford Trib. 0424014980 0.112000-2Rural Trib.#6, Below 04237946 0.322000-3Rural Meadowbrook 04245236 3.062001-3Urban Harborbrook 04240100 10.02001-3Suburban Ley 04240120 29.92002,3Urban Onondaga Cr. Cardiff 04237946 33.9.2001-4Rural

11. 3. Model Development -System Life Cycle Problem definition- purpose Feasibility analysis- possible Project design- specifications Construction- write, build Monitoring- use & test Analysis- evaluate Control- maintain & adjust

12. Review of User Application Containers MS-Excel- time series, solver, UI MS-Access- DB development Arc GIS- newer Arc View- older VB- programming

13. Candidate Models Rainfall Excess - effective precipitation Base flow separation from total flow Rational Model Storages Soil Conservation Service Runoff Moisture indices & other scaling factors Water Balances

14. Rational Model Linear Percentage of rainfall

15. Storages Container outflow

16. SCS Curve Numbers Runoff from single storm event

17. Moisture Indices Approximate /scale precipitation.

18. Water Balance Storage For soil moisture flow or evaporation wells

19. Hamon Equation Estimate Potential Evaporation Transpiration by #hours daylight, temperature, water vapor constant

20. Geographic Averaging To weight or scale multiple weather stations

21. Step Absolute Relative Error Solver Optimization Function and averaged over time steps

22. Nash-Sutcliffe Coefficient Model goodness

23. Water Volume Conversions For stream flows and precipitation

24. Sample Application logic 1) Calculate parameter averages /values 2) Calculate slope or store (& subtract from) contribution for base / flows 3) Calculate other contributions 4) Add up for flow time step 5) Check if new average period (step 1) 6) Step 2

25. Model Equations Sample logic

26. Snow Melt Depth Snow pack contributions in mm

27. 4. Results Table 2. Overview of models Model Name BaseflowRun Off Quick Flow PETYears /Season Monthly slope (sm) sloped line%rain11/01-10/03 Monthly store (rm) reservoir%rain11/01-10/03 daily slope (sd) sloped line%rainSummers 2000-4 daily store (rd) reservoir%rain storeSummers 2000-4

28. Runoff Models Observations Slower base flow from ground contributions Quicker runoffs from precipitation over land & interflows Related processes of infiltration & recharge for base flow Storage, slope, or constant estimations for baseflow

31. Figure 11. Monthly model recharge fraction and area relational curves

32. Figure 8. Monthly model decay rate curves

33. Figure 15. Monthly slope model base slope progressions for May

34. Figure 30. Daily storage model, decay rate relation

35. Figure 31. Daily model reservoir recharge

36. Figure 36. Flow estimates from Tables 6, 8, & 10

37. Figure 26. Sample simulation of daily flow

38. 5. Discussion Ease of use, vesatile & situational PET under/over estimated winter/summer 50% Prediction – daily models Flow & area relation: rate & recharge Approximate PET, recharge factor yearly association Runoff spikes underestimated usually

39. Future Shorter parameter average periods Finish winter season models with snow melt Exponential storage relation? Missed key parameter association?

40. Optimizing function Error calculation - minimize Relative average error – steady flows Monthly step error summaries Absolute differences – peaks? Nash-Sutcliffe Coefficients? Other candidate models?

41. Conceptual models Hydrologic cycle- water budget, possible Lumped & continuous- set choice Simplified or approximate- analytical vs. numerical Historical or stochastic-simulation vs. synthesis Physical or mathematical- analog vs. equations Descriptive or conceptual- observations vs. theory Dynamic vs. static