Characterization of Basin-Scale Dynamic Storage–Discharge Relationship Using Daily GRACE Based Storage Anomaly Data

Despite the fact that streamflow occurs mainly due to depletion of storage, our knowledge on how a drainage basin stores and releases water is very limited due to measurement limitations. A window of opportunity, however, is provided to us by GRACE (Gravity Recovery and Climate Experiment) satellite mission that provides storage anomaly (San) data. Many studies have explored a range of potential applications of San data such as flood forecasting. Here we argue that the capability of GRACE satellite mission has not been fully explored as most of the studies in the past have performed analysis using monthly San data for large river basins. In this study, we use daily San data for several mid-sized catchments to perform storage–discharge analysis. Our results support the earlier notion that storage–discharge relationship is highly dynamic. Furthermore, we demonstrate that San data can be exploited for prediction of k of the Brutsaet–Nieber equation −dQ/dt = kQα (Q is discharge at time t). For comparison we also use storage information provided by Catchment Land Surface Model (CLSM) as well as past discharge information to predict k. Our results suggest that GRACE based storage information can be used to predict k reasonably well in gauged as well as ungauged basins. © 2020 by the authors. Licensee MDPI, Basel, Switzerland