Satellite gravimetry helps monitor the operation of large reservoirs

All over the world, water levels are constantly changing. From lakes, to rivers, to oceans, the patterns of the water levels change due to different factors. With hydrological extremes increasing in intensity and duration around the world, it is important to understand what changes these levels in order to better predict and mitigate the negative impacts of changing water level.

The goal of this study is to use estimates of terrestrial water storage (TWS) variability from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to predict reservoir operation in Brazil. To do this, reservoir water elevations are derived from multi-satellite radar altimetry (RA) data and used as a proxy of their operation. 30 reservoirs in Southern Brazil are considered. For each reservoir, the Pettitt test was used to identify the point break within the TWS data, and the Mann-Kendall test was used to identify trends before and after these breaks. A machine learning approach was used to reconstruct RA-based water elevations using GRACE data. The approach considered numerous geomorphologic and meteorologic characteristics of reservoirs, including reservoir area, volume, location, extent, depth, drainage area, and elevation, in addition to precipitation and temperature. Break points of time series and trends were also computed for each reservoir to explain why some reservoirs present better fit than others. The findings of this study will give insight into what variables affect the relationship between TWS and RA height in the Parana Basin in Southern Brazil.