A Novel Standardized Drought and Flood Potential Index Based on Reconstructed Daily GRACE Data

Abstract

Abstract Multiple indicators derived from the Gravity Recovery and Climate Experiment (GRACE) satellite have been used in monitoring floods and droughts. However, these measures are constrained by the relatively short time span (∼20 years) and coarse temporal resolution (1 month) of the GRACE and GRACE Follow-On missions, and the inherent decay mechanism of the land surface system has not been considered. Here we reconstructed the daily GRACE-like terrestrial water storage anomaly (TWSA) in the Yangtze River basin (YRB) during 1961–2015 based on the Institute of Geodesy at Graz University of Technology (ITSG)-Grace2018 solution using the random forest (RF) model. A novel antecedent metric, namely, standardized drought and flood potential index (SDFPI), was developed using reconstructed TWSA, observed precipitation, and modeled evapotranspiration. The potential of SDFPI was evaluated against in situ discharge, VIC simulations, and several widely used indices such as total storage deficit index (TSDI), self-calibrated Palmer drought severity index (sc-PDSI), and multiscale standardized precipitation evapotranspiration index (SPEI). Daily SDFPI was utilized to monitor and characterize short-term severe floods and droughts. The results illustrate a reasonably good accuracy of ITSG-Grace2018 solution when compared with the hydrological model output and regional water balance estimates. The RF model presents satisfactory performances for the TWSA reconstruction, with a correlation coefficient of 0.88 and Nash–Sutcliffe efficiency of 0.76 during the test period 2011–15. Spatiotemporal propagation of the developed SDFPI corresponds well with multiple indices when examined for two typical short-term events, including the 2003 flood and 2013 drought. A total of 22 submonthly exceptional floods and droughts were successfully detected and featured using SDFPI, highlighting its outperformance and capabilities in providing inferences for decision-makers and stakeholders to monitor and mitigate the short-term floods and droughts.