Application of remote sensing using a GIS based soil water assessment tool(SWAT)to estimate river discharge in the Kabompo river basin-Zambia
MetadataShow full item record
The Kabompo river basin with an area of 72,000 km2, in North-Western Zambia is one of the major tributaries of the upper Zambezi River. Key water resources management problems in the Kabompo include water allocation to agriculture and ecosystems, effects of land-cover change on the flow regime and potential impacts from mine tailing dams. The objectives for the study were to apply Remote Sensing and a GIS based Soil Water Assessment Tool (SWAT) to estimate river discharge for the basin in order to address the water resource management challenges. Because of paucity of observed data in the Kabompo basin, the model primarily depended on remote sensing datasets for calibration and validation. The Kabompo basin was discretized into 177 sub-basins with a total of 1004 hydrological response units. Methodology included the use of a semi-distributed; ArcGIS based Soil Water Assessment Tool (SWAT) software for hydrological modeling. Remote sensing data sets that included weather data, drainage network and slopes, landuse/ land cover and soils were used to create a database for the sub-basins using ArcGIS. The simulated flow from the SWAT model was calibrated with ESA ERS-2 and ENVISAT radar altimetry river stage values converted to discharge. Observed river flow data for six stations over different time periods between 1990 and 2007 were used in validation and uncertainty analysis of the radar altimetry flow data and remotely sensed weather data, respectively. The model’s results showed good correlation with observed data giving a Nash Sutcliffe coefficient of 0.87 and an R² value of 0.93, after calibration. The simulation results obtained from the model can be used in a number of water resources management activities like water rights, water allocation, and flood warning. The model is able to generate estimated river flow and stage values even for un-gauged streams. It’s also able to simulate long-term data of a wider area including inaccessible locations than conventional hydrological techniques. It is concluded that remote sensing is a useful tool for estimation of hydrological data where it is lacking or in unguaged and in accessible areas. Its wide use in a country like Zambia should greatly improve water resources management in a number of areas.