A timely efficient and robust multi-source and multitemporal routine for determination of surface water area in large water reservoirs

Abstract

The Brazilian electrical system has gone through conflicts resulting from recent water crisis. Timely indicators are crucial for properly acting in order to mitigate upcoming problems. In this work we evaluate the potential of Reservoir Water Level (RWL) and Surface Water Area (SWA) indices for estimating physical parameters in the management of water resources. We tested Landsat 8 (L8) and Sentinel-2 (S2) optical image time series, Sentinel-1 (S1) radar, spectral indices and validation with Jason-3 (J3) altimetry. The methodology was developed in the Google Earth Engine (GEE) operational routine, which streamlined the SWA mapping. The best results were between S2 and NDWI and threshold 0, with R² = 0.88 and RMSE of 11.59 km². As main limitations, we highlight the cloud cover for the optical images, which can decrease the temporal sampling, as well as the SAR backscatter response in the presence of bare soil and aquatic vegetation. We could attest that periodic remote sensing data are particularly useful for timely updating spatial variations of RWL and SWA in reservoirs.