Monitoring reservoir storage in South Asia from multisatellite remote sensing

Reservoir storage information is essential for accurate flood monitoring and prediction. South Asia, however, is dominated by international river basins where communications among neighboring countries about reservoir storage and management are extremely limited. A suite of satellite observations were combined to achieve high‐quality estimation of reservoir storage and storage variations in South Asia from 2000 to 2012. The approach used water surface area estimations from the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices product and the area‐elevation relationship to estimate reservoir storage. The surface elevation measurements were from the Geoscience Laser Altimeter System (GLAS) on board the Ice, Cloud, and land Elevation Satellite (ICESat). In order to improve the accuracy of water surface area estimations for relatively small reservoirs, a novel classification algorithm was developed. In this study, storage information was retrieved for a total of 21 reservoirs, which represents 28% of the integrated reservoir capacity in South Asia. The satellite‐based reservoir elevation and storage were validated by gauge observations over five reservoirs. The storage estimates were highly correlated with observations (i.e., coefficients of determination larger than 0.9), with normalized root mean square error (NRMSE) ranging from 9.51% to 25.20%. Uncertainty analysis was also conducted for the remotely sensed storage estimations. For the parameterization uncertainty associated with surface area retrieval, the storage mean relative error was 3.90%. With regard to the uncertainty introduced by ICESat/GLAS elevation measurements, the storage mean relative error was 0.67%. Key Points A novel algorithm for estimating reservoir storage from satellite remote sensing Storage time series for 21 reservoirs in South Asia from 2000 to 2012 Data products were validated by gauge observations