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Geospatial Stream Flow Model (GeoSFM)

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. Objectives. To develop a model is a wide-area flood risk monitoring using existing datasets

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Geospatial Stream Flow Model (GeoSFM)

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  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. ModelOverview • 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. Stream Flow Model GIS Preprocessing GIS Postprocessing Satellite Rainfall Estimates Water Balance Rainfall Forecasts GDAS PET Fields Lumped Routing FAO Soil Data Flood Inundation Mapping Dist. Routing Land Use/ Land Cover Elevation Data Stage Forecasting FEWS Flood Risk Monitoring System Flow Diagram 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. Flow Direction Flow Accumulation Flow Length Hill Length Slope Subbasins Downstream Subbasin Using ArcView’s Terrain Analysis Functions with USGS 1 km DEM

  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) * R2/3 * S1/2

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

  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 Grids adhere to a naming convention which allows for subsequent automation Gage Data Daily Grids

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

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

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

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

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

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

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

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

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

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

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

  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

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