{"title":"Spatial downscaling of GRACE terrestrial water storage anomalies for drought and flood potential assessment","authors":"Gaohong Yin , Jongmin Park , Kei Yoshimura","doi":"10.1016/j.jhydrol.2025.133144","DOIUrl":null,"url":null,"abstract":"<div><div>Terrestrial water storage anomaly (TWSA) from the Gravity Recovery and Climate Experiment (GRACE) mission provides invaluable information for quantifying changes in freshwater availability. However, the coarse spatial resolution of GRACE TWSA limits its application to sub-regional studies. The study proposed a systematic framework to spatially downscale GRACE TWSA retrievals using a long short-term memory (LSTM) model over the Texas-Gulf Basin. A synthetic experiment was conducted to demonstrate the robustness of the downscaling framework. The real-world experiment revealed that the downscaled TWSA from LSTM can represent the variation of TWSA at the basin (R<sub>LSTM</sub> = 0.91) and sub-basin scales. The LSTM-based TWSA can better represent the early recovery from extreme droughts for the sub-basins along the coast. Moreover, the LSTM-based TWSA outperformed model-based TWSA in characterizing groundwater variation, especially for sub-basins with deep groundwater levels in the west. The flood analysis showed that the downscaled TWSA from LSTM yielded improved skill in predicting county-level floods, providing a larger true positive rate relative to GRACE TWSA retrievals (TPR<sub>LSTM</sub> = 0.36 and TPR<sub>GRACE</sub> = 0.31). Additionally, the trained LSTM models were used to predict fine-resolution TWSA without requiring GRACE observations. Results demonstrated that the accuracy of LSTM-based TWSA forecasts was slightly inferior to the downscaling case, but they still provided useful information for drought and flood predictions at sub-basin to local scales.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133144"},"PeriodicalIF":5.9000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrology","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022169425004822","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
Terrestrial water storage anomaly (TWSA) from the Gravity Recovery and Climate Experiment (GRACE) mission provides invaluable information for quantifying changes in freshwater availability. However, the coarse spatial resolution of GRACE TWSA limits its application to sub-regional studies. The study proposed a systematic framework to spatially downscale GRACE TWSA retrievals using a long short-term memory (LSTM) model over the Texas-Gulf Basin. A synthetic experiment was conducted to demonstrate the robustness of the downscaling framework. The real-world experiment revealed that the downscaled TWSA from LSTM can represent the variation of TWSA at the basin (RLSTM = 0.91) and sub-basin scales. The LSTM-based TWSA can better represent the early recovery from extreme droughts for the sub-basins along the coast. Moreover, the LSTM-based TWSA outperformed model-based TWSA in characterizing groundwater variation, especially for sub-basins with deep groundwater levels in the west. The flood analysis showed that the downscaled TWSA from LSTM yielded improved skill in predicting county-level floods, providing a larger true positive rate relative to GRACE TWSA retrievals (TPRLSTM = 0.36 and TPRGRACE = 0.31). Additionally, the trained LSTM models were used to predict fine-resolution TWSA without requiring GRACE observations. Results demonstrated that the accuracy of LSTM-based TWSA forecasts was slightly inferior to the downscaling case, but they still provided useful information for drought and flood predictions at sub-basin to local scales.
期刊介绍:
The Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology and hydrogeology. Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, hydraulics, agrohydrology, geomorphology, soil science, instrumentation and remote sensing, civil and environmental engineering are included. Social science perspectives on hydrological problems such as resource and ecological economics, environmental sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope. The science published in the Journal of Hydrology is relevant to catchment scales rather than exclusively to a local scale or site.