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Geospatial Stream Flow Model(GeoSFM)
USGS FEWS NETEROS Data Center
Sioux Falls, SD 57198
U.S. Department of the InteriorU.S. Geological Survey
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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
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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
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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
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FEWS Flood Risk Monitoring System Flow Diagram
Flood Inundation Mapping
GIS PostprocessingGIS Preprocessing
SatelliteRainfall 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
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Geospatial Stream Flow Model, An ArcView 3.2 Extension
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Using Menus,Message Boxes and Tools
Hydrographplotting tool
Tool for Dam Insertion
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Model Components Terrain Analysis Module Parameter Estimation Module Data Preprocessing Module Water Balance Module Flow routing Module Post-processing Module
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Terrain Analysis Module
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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
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Using ArcView’s Terrain Analysis Functions with USGS 1 km DEM
Flow Direction
Flow Accumulation
FlowLength
Hill Length
Slope
Downstream Subbasin
Subbasins
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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
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Parameter Estimation Module
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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
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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)
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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
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Weighted flow length and aggregationalgorithm to create Unit Hydrographs
Overland Velocity, Flow Time
Flow Path, Flow Length
Aggregate cells at basin outlet During each routing interval
n
i i
i
vl
t 1
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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
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Data Preprocessing Module
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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
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Interpolation routines to grid point rainfall data
Daily GridsGage Data
Grids adhere to a namingconvention which allowsfor subsequent automation
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Zonal algorithms to compute subbasin mean values and export to an ASCII files
Rain / Evap Grid Output toASCII File
Subbasins
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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
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Water Balance Module
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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
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Conceptual Model of Water Balance
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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
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Soil layer
Ground Water
Saturated Hydraulic Conductivity
Hortonian with Partial Contributing Areas
Rainfall
Partitioning Fluxes in single layered model
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Ground Water
Soil layer Interflow Linear Reservoir
+Baseflow Linear Reservoir
Unit Hydrograph
Rainfall
Surface Runoff
Transferring Fluxes in single layered model
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Upper layer
Lower layer
Ground Water
Green – Ampt Based Parameterization
SCS Curve Number Method
Rainfall
Partitioning Fluxes in two layered model
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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
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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
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Flow routing Module
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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
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Routing Overview
Outlet
Sub-basin 3
Main channel
Sub-basin 2
Sub-basin 4
+
+
+
Sub-basin 1
Main channel
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Within subbasin routingApply unit hydrograph to excess runoff to obtain runoff at subbasin outlet
Water Balance
Runoff
Unit Hydrograph
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Three Flow Routing Options
Pure Translation Routing Diffusion Analog Routing Muskingum Cunge Routing
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Pure Translation RoutingFl
o w
Time
InputFl
ow
Time
Output
• Only parameter required is lag time or celerity• Simple but surprising effective in large basins
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Diffusion Analog RoutingLinear routing method
Requires two parameters• Velocity for translation• Diffusion coefficient for attenuation
Flo w
Time
InputFl
ow
Time
Output
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Muskingum-Cunge RoutingFl
ow D
e pth
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
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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
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Post-processing Module
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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
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Characterizing Flood RiskGenerate Daily
Historical Rainfall (1961-90) by reanalysis
Produce a synthetic
streamflow record
Compute Bankfull storage
Determine locations where bankfull storage
Is exceeded
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Colour coded maps to indicate level of risk
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Hydrographs with their historical context
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Nzoia Basin, Kenya
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Nzoia Basin, Modeled vs Observed Streamflow
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Limpopo River Basin
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Olifants, Kruger National Park - Mamba
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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
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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