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The monitoring of hydrological extremes requires water level measurement. Owing to the decreasing number of continuous operating hydrological stations globally, remote sensing indices have been advocated for water level reconstruction recently. Nevertheless, the feasibility of gravimetrically derived terrestrial water storage (TWS) and its corresponding index for water level reconstruction have not been investigated. This paper aims to construct a correlative relationship between observed water level and basin-averaged Gravity Recovery and Climate Experiment (GRACE) TWS and its Drought Severity Index (GRACE-DSI), for the Yangtze river basin on a monthly temporal scale. The results are subsequently compared against traditional remote sensing, Palmer’s Drought Severity Index (PDSI), and El Nino Southern Oscillation (ENSO) indices. Comparison of the water level reconstructed from GRACE TWS and its index, and that of remote sensing against observed water level reveals a Pearson Correlation Coefficient (PCC) above 0.90 and below 0.84, with a Root-Mean-Squares Error (RMSE) of 0.88–1.46 m, and 1.41–1.88 m and a Nash-Sutcliffe model efficiency coefficient (NSE) above 0.81 and below 0.70, respectively. The ENSO-reconstructed water levels are comparable to those based on remote sensing, whereas the PDSI-reconstructed water level shows a similar performance to that of GRACE TWS. The water level predicted at the location of another station also exhibits a similar performance. It is anticipated that the basin-averaged, remotely-sensed hydrological variables and their standardized forms (e.g., GRACE TWS and GRACE-DSI) are viable alternatives for reconstructing water levels for large river basins affected by the hydrological extremes under ENSO influence.

Water Level Reconstruction Based on Satellite Gravimetry in the Yangtze River Basin