Zhang, S; Gao, HL (2020). Using the Digital Elevation Model (DEM) to Improve the Spatial Coverage of the MODIS Based Reservoir Monitoring Network in South Asia. REMOTE SENSING, 12(5), 745.

Satellite remote sensing of near real-time reservoir storage variations has important implications for flood monitoring and water resources management. However, satellite altimetry data, which are essential for estimating storage variations, are only available for a limited number of reservoirs. This lack of high-density spatial coverage directly hinders the potential use of remotely sensed reservoir information for improving the skills of hydrological modeling over highly regulated river basins. To solve this problem, a reservoir storage dataset with high-density spatial coverage was developed by combining the water surface area estimated from Moderate Resolution Imaging Spectroradiometer (MODIS) imageries with the Digital Elevation Model (DEM) data collected by the Shuttle Radar Topography Mission (SRTM). By including more reservoirs, this reservoir dataset represents 46.6% of the overall storage capacity in South Asia. The results were validated over five reservoirs where gauge observations are accessible. The storage estimates agree well with observations, with coefficients of determination ranging from 0.47 to 0.91 and normalized root mean square errors (NRMSE) ranging from 15.46% to 37.69%. Given the general availability of MODIS and SRTM data, this algorithm can be potentially applied for monitoring global reservoirs at a high density.