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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

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
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


Gis in flood monitoring
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


Model overview
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


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


Geospatial Stream Flow Model,

An ArcView 3.2 Extension


Using Menus,Message Boxes and Tools

Hydrograph

plotting tool

Tool for Dam

Insertion


Model components
Model Components

  • Terrain Analysis Module

  • Parameter Estimation Module

  • Data Preprocessing Module

  • Water Balance Module

  • Flow routing Module

  • Post-processing Module



The goal of terrain analysis
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


Flow

Direction

Flow

Accumulation

Flow

Length

Hill

Length

Slope

Subbasins

Downstream

Subbasin

Using ArcView’s Terrain Analysis

Functions with USGS 1 km DEM


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



The goal of parameter estimation
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


Estimating surface runoff characteristics
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)


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


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


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



The goal of data processing
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


Interpolation routines to grid

point rainfall data

Grids adhere to a naming

convention which allows

for subsequent automation

Gage Data

Daily Grids


Zonal algorithms to compute subbasin mean values and export to an ASCII files

Rain / Evap Grid

Output to

ASCII File

Subbasins


Key Lessons in Data Preprocessing to an ASCII files

  • 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


Water Balance Module to an ASCII files


The goal of water balance
The goal of Water Balance to an ASCII files

  • 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



Two water balance options
Two Water Balance Options to an ASCII files

  • 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


Partitioning fluxes in single layered model
Partitioning Fluxes in single layered model to an ASCII files

Rainfall

Hortonian with Partial Contributing Areas

Soil layer

Saturated Hydraulic Conductivity

Ground Water


Transferring Fluxes in single layered model to an ASCII files

Rainfall

Surface Runoff

Unit Hydrograph

Soil layer

Interflow Linear Reservoir

+

Baseflow Linear Reservoir

Ground Water


Partitioning fluxes in two layered model
Partitioning Fluxes in two layered model to an ASCII files

Rainfall

SCS Curve Number Method

Upper layer

Lower layer

Green – Ampt Based Parameterization

Ground Water


Transferring fluxes in two layered model
Transferring Fluxes in two layered model to an ASCII files

Rainfall

Surface Runoff

Unit Hydrograph

Upper layer

Interflow

Conceptual Linear Reservoir

Lower layer

Baseflow

Conceptual Linear Reservoir

Ground Water


Key Lessons in Water Balance to an ASCII files

  • 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


Flow routing module
Flow routing Module to an ASCII files


The goal of flow routing
The goal of Flow Routing to an ASCII files

  • 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


Sub-basin 1 to an ASCII files

Sub-basin 2

+

Main channel

+

Sub-basin 3

Sub-basin 4

Main channel

+

Outlet

Routing Overview


Within subbasin routing
Within subbasin routing to an ASCII files

Apply unit hydrograph to excess runoff to obtain runoff at subbasin outlet

Runoff

Water Balance

Unit Hydrograph


Three flow routing options
Three Flow Routing Options to an ASCII files

  • Pure Translation Routing

  • Diffusion Analog Routing

  • Muskingum Cunge Routing


Pure translation routing
Pure Translation Routing to an ASCII files

  • Only parameter required is lag time or celerity

  • Simple but surprising effective in large basins

Input

Output

Flow

Flow

Time

Time


Diffusion analog routing
Diffusion Analog Routing to an ASCII files

  • Linear routing method

  • Requires two parameters

    • Velocity for translation

    • Diffusion coefficient for attenuation

Input

Output

Flow

Flow

Time

Time


Muskingum cunge routing
Muskingum-Cunge Routing to an ASCII files

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


Key Lessons in Flow Routing to an ASCII files

  • 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


Post processing module
Post-processing Module to an ASCII files


The goal of Postprocessing to an ASCII files

  • 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


Characterizing flood risk
Characterizing Flood Risk to an ASCII files

Produce a synthetic streamflow record

Generate Daily

Historical Rainfall

(1961-90) by reanalysis

Determine locations

where bankfull storage

Is exceeded

Compute Bankfull storage




Nzoia basin kenya
Nzoia Basin, Kenya to an ASCII files



Limpopo River Basin to an ASCII files



Key Lessons in Postprocessing to an ASCII files

  • 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


Conclusions
Conclusions to an ASCII files

  • 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


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