Acta Geodaetica et Cartographica Sinica ›› 2026, Vol. 55 ›› Issue (4): 721-738.doi: 10.11947/j.AGCS.2026.20260016

• Geodesy and Navigation • Previous Articles    

Century-scale projection of terrestrial water storage anomaly and drought risk in the Poyang Lake Basin using a CMIP6-driven Transformer-GRU model

Yang LI1,2,3(), Haijun HUANG1, Sulan LIU1, Xiaohui WU1, Qi LIU1, Qipei PANG1, Yunlong WU1,2,3()   

  1. 1.School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
    2.Hubei Key Laboratory of Regional Ecology and Environmental Change, China University of Geosciences, Wuhan 430074, China
    3.Hubei Key Laboratory of Information Technology, China University of Geosciences, Wuhan 430074, China
  • Received:2026-01-14 Revised:2026-03-16 Published:2026-05-11
  • Contact: Yunlong WU E-mail:liyang1105@cug.edu.cn;wuyunlong@cug.edu.cn
  • About author:LI Yang (2002—), male, postgraduate, majors in intelligent processing of geodetic data. E-mail: liyang1105@cug.edu.cn
  • Supported by:
    The National Key Research and Development Program of China(2024YFF1308104);The National Natural Science Foundation of China(42574073; 42274111)

Abstract:

The impact of drought on human society is becoming increasingly severe, making accurate prediction of future terrestrial water storage anomaly (TWSA) data crucial for water resource management and drought monitoring. This study integrates GRACE/GRACE-FO satellite observations, reconstructed long-term TWSA data, and CMIP6 multi-scenario climate model outputs to forecast future TWSA in the Poyang Lake Basin. To precisely capture the complex response relationship between climate drivers and water storage changes, we propose a hybrid Transformer-GRU model driven by climate factors. The model employs a customized cross-attention module that takes the current TWSA state as the guiding query to compute attention weights for precipitation, air temperature, and potential evapotranspiration (PET), together with their lagged terms, and then fuses these variables according to the learned weights to form an integrated climate signal for TWSA prediction, thereby achieving dynamic weighting and effective coupling of multi-source climate drivers. The model, validated through rolling-window cross-validation and independent testing, demonstrated reliable predictive accuracy (correlation coefficientr=0.87, RMSE=5.17 cm during the independent test period). Based on the prediction results, the water storage deficit index (WSDI) for the Poyang Lake Basin was calculated to assess the evolution of drought risk under different emission scenarios. The results indicate that under the high-emission SSP5-8.5 scenario, both the frequency and intensity of droughts are significantly higher than under the SSP2-4.5 scenario, revealing an elevated risk of intensified hydrological drought in the Poyang Lake Basin under a high-emission pathway. This research provides a credible technical solution for effective, century-scale TWSA forecasting with limited observational data, offering a scientific reference for water resource adaptation strategies in the Poyang Lake Basin.

Key words: TWSA, Poyang Lake Basin, scenario-driven prediction, Transformer, drought analysis

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