Water storage estimation in ungauged small reservoirs with the TanDEM-X DEM and multi-source satellite observations

Abstract

Monitoring small water bodies (<50 ha) is difficult due to their size, limiting accurate assessments of surface water (SW) resources required for agricultural production and watershed hydrology. In environments where livelihoods depend on surface-water storage (SWS) structures, satellite altimetry-derived water levels are often unavailable. Therefore, seasonal reservoirs require a robust and cost-effective approach for estimating SWS. To approximate SWS throughout a typical environmental setting where irrigation reservoirs are found, we investigate the utility of TanDEM-X digital elevation model (DEM) to extract bathymetry of seasonal reservoir structures. Empirically-derived SWS relationships are combined with estimates of SW area from radar and multi-source optical satellites to illustrate the potential for rapid SWS estimation using satellite-based SW extent as input. Two application examples illustrate the approach: (i) estimating the maximum volume of water in a southern Indian river basin for two monsoon seasons; and (ii) a time-series analysis using a high-volume of satellite observations to show the cycle of water (inflow and outflow) at the reservoir scale. SWS volumes at water levels below 1.5 m were estimated within an absolute volume error range of 6–8%. This study illustrates the applicability and challenges of using satellite remote sensing observations to continuously monitor reservoir SWS. Despite the cloud independent capability for operational monitoring of SW area, Sentinel-1 data should be combined with frequent and high spatial resolution CubeSat observations for hydrometric monitoring of reservoirs to reduce observation errors. Furthermore, we highlight the multi-sensor approach (optical and radar) to achieve high spatio-temporal resolution monitoring of small reservoirs over large spatial scales.