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Detecting the extreme hydrological events over China in 2022 using sparse GNSS and GRACE/GRACE-FO
Remote Sensing of Environment ( IF 11.1 ) Pub Date : 2024-10-31 , DOI: 10.1016/j.rse.2024.114488 Ze Wang, Weiping Jiang, Jian Wang, Dongzhen Wang, Wenlan Fan, Meilin He
Remote Sensing of Environment ( IF 11.1 ) Pub Date : 2024-10-31 , DOI: 10.1016/j.rse.2024.114488 Ze Wang, Weiping Jiang, Jian Wang, Dongzhen Wang, Wenlan Fan, Meilin He
In the context of global climate change, extreme hydrological events frequently occurred worldwide, impacting global and regional hydrological cycles. Global Navigation Satellite System (GNSS) and Gravity Recovery and Climate Experiment (GRACE) can provide innovative solutions for terrestrial water storage (TWS) estimation from different perspectives, thereby identifying and detecting extreme drought and flood events. We propose a method to directly combine GNSS and GRACE observations for recovering TWS, which can effectively mitigate the clustering effect that arises when estimating TWS in large regions with sparse GNSS networks. Multiple synthetic water models were conducted to test the joint inversion method. The results indicate that the joint GNSS and GRACE estimation of TWS offers excellent spatial continuity compared to GNSS-only and traditional methods. The correlation coefficients between the recovered TWS and synthetic models are in the range of 0.78 to 0.82, confirming the reliability of the method. Based on 249 GNSS stations and GRACE Mascon solutions, we estimated the changes of TWS across mainland China from 2011 to 2022, successfully detecting the floods and droughts of the past twelve years. Successive monthly snapshots of TWS anomalies reproduced the dynamic evolution of the compound extreme hydrological events in China in 2022. The results indicate that the Southeast and Pearl River Basins experienced a water surplus of up to 462 mm in June. Subsequently, the Yangtze River Basin underwent an unprecedented drought starting in July, with the most severe water deficit reaching 383 mm in October. The propagation and evolution of this compound extreme hydrological events were corroborated by in-situ hydrological variables across different basins. Additionally, we provided insights into the atmospheric dynamics behind this event by analyzing atmospheric circulation patterns. This method provides a demonstration for the recovery of available TWS in large-area with sparse GNSS networks to detect compound extreme hydrological events and enhance the understanding of the coupling between extreme hydrological events and abnormal atmospheric circulation.
更新日期：2024-10-31
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