Open-File Report 2007–1441
Abstract The monitoring of wide-area hydrologic events requires the use of geospatial and time series data available in near-real time. These data sets must be manipulated into information products that speak to the location and magnitude of the event. Scientists at the U.S. Geological Survey Earth Resources Observation and Science (USGS EROS) Center have implemented a hydrologic modeling system which consists of an operational data processing system and the Geospatial Stream Flow Model (GeoSFM). The data processing system generates daily forcing evapotranspiration and precipitation data from various remotely sensed and ground-based data sources. To allow for rapid implementation in data scarce environments, widely available terrain, soil, and land cover data sets are used for model setup and initial parameter estimation. GeoSFM performs geospatial preprocessing and postprocessing tasks as well as hydrologic modeling tasks within an ArcView GIS environment. The integration of GIS routines and time series processing routines is achieved seamlessly through the use of dynamically linked libraries (DLLs) embedded within Avenue scripts. GeoSFM is run operationally to identify and map wide-area streamflow anomalies. Daily model results including daily streamflow and soil water maps are disseminated through Internet map servers, flood hazard bulletins and other media. |
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Asante, K.O., Artan, G.A., Pervez, S., Bandaragoda, C., and Verdin, J.P., 2008, Technical Manual for the Geospatial Stream Flow Model (GeoSFM): U.S. Geological Survey Open-File Report 2007–1441, 65 p.
Abstract
Introduction
GeoSFM Architecture
Preprocessing Module
Terrain Analysis Routine
Basin Characterization Routine
Unit Hydrograph Generation Routine
Weather Data Processing Routine
Soil Moisture Accounting Module
Linear Soil Moisture Accounting (LSMA) Routine
Nonlinear Soil Moisture Accounting (NSMA) Routine
River Transport Module
Pure Lag Flow Routine
Diffusion Analog Routine
Muskingum Cunge Routine
Calibration Module
One-At-a-Time (OAT) Sensitivity Analysis
The Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) Algorithm
Postprocessing of Calibration Results
Postprocessing Utilities
Conclusions
References Cited
Appendix 1: GeoSFM Data Specifications