Using satellite-based rainfall estimates for streamflow modelling: Bagmati Basin

In this study, we have described a hydrologic modelling system that uses satellitebased rainfall estimates and weather forecast data for the Bagmati River Basin of Nepal. The hydrologic model described is the US Geological Survey (USGS) Geospatial Stream Flow Model (GeoSFM). The GeoSFM is a spatially semidistributed, physically based hydrologic model. We have used the GeoSFM to estimate the streamflow of the Bagmati Basin at Pandhera Dovan hydrometric station. To determine the hydrologic connectivity, we have used the USGS Hydro1k DEM dataset. The model was forced by daily estimates of rainfall and evapotranspiration derived fromweather model data. The rainfall estimates used for the modelling are those produced by the National Oceanic and Atmospheric Administration Climate Prediction Centre and observed at ground rain gauge stations. The model parameters were estimated from globally available soil and land cover datasets ‐ the Digital Soil Map of the World by FAO and the USGS Global Land Cover dataset. The model predicted the daily streamflow at Pandhera Dovan gauging station. The comparison of the simulated and observed flows at Pandhera Dovan showed that the GeoSFM model performed well in simulating the flows of the Bagmati Basin.

[1]  Phillip A. Arkin,et al.  Analyses of Global Monthly Precipitation Using Gauge Observations, Satellite Estimates, and Numerical Model Predictions , 1996 .

[2]  B. Minasny,et al.  Digital Soil Map of the World , 2009, Science.

[3]  J. Verdin,et al.  Users Manual for the Geospatial Stream Flow Model (GeoSFM) , 2008 .

[4]  M. Shrestha,et al.  Preparing for Flood Disaster: Mapping and Assessing Hazard in the Ratu Watershed, Nepal , 2007 .

[5]  Lotta Andersson,et al.  Estimating rainfall and water balance over the Okavango River Basin for hydrological applications , 2006 .

[6]  J. Salas,et al.  A COMPARATIVE ANALYSIS OF TECHNIQUES FOR SPATIAL INTERPOLATION OF PRECIPITATION , 1985 .

[7]  Ofir Arkin.  Tracing Hackers: Part 1 , 2002 .

[8]  James P. Verdin,et al.  Grid‐cell‐based crop water accounting for the famine early warning system , 2002 .

[9]  Stéphane Kluser,et al.  Reducing Disaster Risk: a challenge for development , 2004 .

[10]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[11]  H. Savenije,et al.  Regional calibration of the Pitman model for the Okavango River , 2006 .

[12]  James P. Verdin,et al.  Adequacy of satellite derived rainfall data for stream flow modeling , 2007 .

[13]  James P. Verdin,et al.  Developing a Flood Monitoring System From Remotely Sensed Data for the Limpopo Basin , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Potential Erosion Map For Bagmati Basin Using GRASS GIS , 2002 .