Lake Topography and Active Storage From Satellite Observations of Flood Frequency

Topography is critical information for water resources management in lakes, and remote sensing provides a unique opportunity to estimate topography in ungauged regions. We introduce here a new method that estimates nearshore topography of water bodies based on a flood frequency map and time series of water levels by assuming the equivalence between flood frequency and water level exceedance probability at a given area. Test cases are performed for two lakes and 12 hydropower reservoirs using the proposed Flood2Topo app. This new application generates the bottom level pixel by pixel and level-area-active storage relationship directly from the topography map, without the need to fit functions. Flood extent estimates from the Landsat based Global Surface Water (GSW) data set, the current state-of-the-art, were used to run Flood2Topo, together with water levels from satellite altimetry and in situ gauges. Results show bottom level root mean square deviation (RMSD) values of 18.5 and 146 cm for Lake Poopo (Bolivia) and Lake Curuai (Amazon basin), respectively. For reservoir active storage, RMSD normalized values ranged from 2% to 11% for 11 reservoirs (average NRMSD of 6.4%). The method can be applied to any seasonally flooded area using any data set. Considering the surface water occurrence map from the GSW data set, the method is applicable to 35.8% (86%) of the global seasonally flooded areas delimited by flood frequencies between 0 and 95% (99%) over 35 years. The flood frequency-based method is a promising tool for obtaining data for hydrodynamic simulations and monitoring of ungauged water bodies.