1. Geospatial Stream Flow Model (GeoSFM) USGS FEWS NET EROS Data Center Sioux Falls, SD 57198 U.S. Department of the Interior U.S. Geological Survey

2. Objectives  To develop a model is a wide-area flood risk monitoring using existing datasets  To use the model to routinely monitor flood risk across Africa and provide early warning to decision makers

3. GIS IN FLOOD MONITORING  The Mid-West Floods of 1993  Creation of Global Elevation Datasets for hydrologic modeling in 1997  Initiation of GIS-based distributed flood modeling at the USGS in the late 1990’s;  Now being applied in Southern Africa, East African and the Mekong River Basin in Vietnam

4. Model Overview  Leverage the vast geospatial data archived at EDC Initial parameters derived from existing datasets Input data generated daily from available datasets  Catchment scale modeling framework Semi-distributed hydrologic model Inputs aggregated to the catchment level  GIS based Modeling Takes advantage of existing spatial analysis algorithms Includes integration with external routing codes

5. FEWS Flood Risk Monitoring System Flow Diagram Flood Inundation Mapping GIS PostprocessingGIS Preprocessing Satellite Rainfall Estimates GDAS PET Fields FAO Soil Data Land Use/ Land Cover Elevation Data Rainfall Forecasts Stream Flow Model Water Balance Lumped Routing Dist. Routing Stage Forecasting http:/www.fews.net

6. Geospatial Stream Flow Model, An ArcView 3.2 Extension

7. Using Menus,Message Boxes and Tools Hydrograph plotting tool Tool for Dam Insertion

8. Model Components  Terrain Analysis Module  Parameter Estimation Module  Data Preprocessing Module  Water Balance Module  Flow routing Module  Post-processing Module

9. Terrain Analysis Module

10. The goal of Terrain Analysis  to divide the study area into smaller subbasin, rivers  to establish the connectivity between these elements  to compute topography dependent parameters

11. Using ArcView’s Terrain Analysis Functions with USGS 1 km DEM Flow Direction Flow Accumulation Flow Length Hill Length Slope Downstream Subbasin Subbasins

12. Key Lessons from Terrain Analysis  Procedures for Terrain Analysis have been refined over the last decade, and they work very well  USGS 1km DEM (Hydro1k) is sufficient for delineation in most basins; it is currently being refined for trouble areas

13. Parameter Estimation Module

14. The goal of Parameter Estimation  to estimate surface runoff parameters in subbasins  to estimate flow velocity and attenuation parameters  to summarize parameters for each subbasin

15. Estimating Surface Runoff Characteristics  Initially computed on a cell by cell basis  Now moving towards generalizing land cover and soil class over subbasin first (Maidment (Ed.), 1993, Handbook of Hydrology) (Chow et al, 1988, Applied Hydrology)

16. Overland Velocity with Manning’s Equation  Initially computed on a cell by cell basis  Now moving towards generalizing land cover and slopes class over subbasin first V = (1/n) * R 2/3 * S 1/2

17. Weighted flow length and aggregation algorithm to create Unit Hydrographs Overland Velocity, Flow Time Flow Path, Flow Length Aggregate cells at basin outlet During each routing interval

18. Key Lessons in Parameterization  While GIS routines work well, existing parameter tables in hydrology textbooks are only of limited utility  There is no on-going effort to document parameters from previous studies though these are often extremely useful  Uniform parameter estimates are often at least as good spatially distributed parameters; simpler is better  Field observations and local estimates are invaluable

19. Data Preprocessing Module

20. The goal of Data Processing  to convert available station & satellite rainfall estimates into a common format  to set up ascii files for water balance and flow routing models to ingest

21. Interpolation routines to grid point rainfall data Daily GridsGage Data Grids adhere to a naming convention which allows for subsequent automation

22. Zonal algorithms to compute subbasin mean values and export to an ASCII files Rain / Evap Grid Output to ASCII File Subbasins

23. Key Lessons in Data Preprocessing  Using a single rainfall value for each subbasin is consistent with the resolution/precision of the satellite rainfall estimates  Saving data values in ASCII files (instead of directly assessing the grids) speeds up subsequent flow routing computations considerably

24. Water Balance Module

25. The goal of Water Balance  to separate input rainfall into evapotranspiration, surface, interflow, baseflow and ground water components  to maintain an accounting of water in storage (soil moisture content) at the end of each simulation time step

26. Conceptual Model of Water Balance

27. Two Water Balance Options  Single layered soil with Hortonian with partial contributing areas Same subsurface reservoir but multiple residence times for interflow and baseflow  Two layered soil with SCS Curve Number Method Separate reservoirs and residence times for interflow and baseflow

28. Soil layer Ground Water Saturated Hydraulic Conductivity Hortonian with Partial Contributing Areas Rainfall Partitioning Fluxes in single layered model

29. Ground Water Soil layer Interflow Linear Reservoir + Baseflow Linear Reservoir Unit Hydrograph Rainfall Surface Runoff Transferring Fluxes in single layered model

30. Upper layer Lower layer Ground Water Green – Ampt Based Parameterization SCS Curve Number Method Rainfall Partitioning Fluxes in two layered model

31. Upper layer Ground Water Interflow Baseflow Lower layer Conceptual Linear Reservoir Unit Hydrograph Rainfall Surface Runoff Conceptual Linear Reservoir Transferring Fluxes in two layered model

32. Key Lessons in Water Balance  SCS Curve number classes don’t match up very well with land cover / vegetation classes  Hortonian with partial areas performs at least as well and is easier to parameterize than SCS method for runoff generation  Recession portion of the hydrograph has been the most difficult to model correctly

33. Flow routing Module

34. The goal of Flow Routing  to aggregate the runoff contributions of each subbasin at the subbasin outlet  to move the runoff from one subbasin to the next, through the river network to the basin outlet

35. Routing Overview Outlet Sub-basin 3 Main channel Sub-basin 2 Sub-basin 4 + + + Sub-basin 1 Main channel

36. Within subbasin routing Apply unit hydrograph to excess runoff to obtain runoff at subbasin outlet Water Balance Runoff Unit Hydrograph

37. Three Flow Routing Options  Pure Translation Routing  Diffusion Analog Routing  Muskingum Cunge Routing

38. Pure Translation Routing Flow Time Input Flow Time Output Only parameter required is lag time or celerity Simple but surprising effective in large basins

39. Diffusion Analog Routing Linear routing method Requires two parameters Velocity for translation Diffusion coefficient for attenuation Flow Time Input Flow Time Output

40. Muskingum-Cunge Routing Flow Depth Distance along river reach River reach Conceptual reach sections with time varying storage Non-Linear, Variable Parameter routing method Accounts for both translation and dispersion

41. Key Lessons in Flow Routing  The less parameters you have to estimate, the easier it is to obtain a representative model  The ease of developing a representative model (not precision of the model) determines whether or not end users adopt the model  I highly recommend the diffusion analog model for large scale applications; it achieves a reasonable balance between simplicity and process representation

42. Post-processing Module

43. The goal of Postprocessing  to compute flow statistics (max, min, mean, 25, 75, 33, 66 and 50 percentile flow)  to rank and display current flows relative to percentile flows (high, low, medium)  to perform preliminary inundation mapping (based on uniform flow depths within each reach)  to display hydrographs where needed

44. Characterizing Flood Risk Generate Daily Historical Rainfall (1961-90) by reanalysis Produce a synthetic streamflow record Compute Bankfull storage Determine locations where bankfull storage Is exceeded

45. Colour coded maps to indicate level of risk

46. Hydrographs with their historical context

47. Nzoia Basin, Kenya

48. Nzoia Basin, Modeled vs Observed Streamflow

49. Limpopo River Basin

50. Olifants, Kruger National Park - Mamba

51. Key Lessons in Postprocessing  The importance of hydrographs to decision makers is highly overrated  The most important questions decision makers want answered are how many people were/will be affected, and where are they?  Risk maps and flood maps are far better methods of commuting to decision makers than hydrographs  Estimates of affected/at risk populations and their locations are the most useful outputs of the hydrologic analysis

52. Conclusions  The Geospatial Stream Flow Model (GeoSFM) is a semi- distributed hydrologic model for wide-area hydrologic analysis  It uses globally available terrain, soil and land cover data, and satellite derived estimates of daily rainfall and PET  The model outputs include stream flow and flood hazard maps  Preliminary results of model validation in the Nzoia and Limpopo river basins were satisfactory  The model continues to evolve in response to field applications