A multivariate integrated drought characterization framework using GNSS-GRACE terrestrial water storage and precipitation
5 affiliations
- 1School of AirSpace Technology, Jiangxi University of Science and Technology, Ganzhou, China
- 2Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang, 330022, China; Corresponding author.
- 3Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen, 518055, China
- 4Institute of Meteorology and Climatology, Leibniz University Hannover, Germany
- 5Institute Dom Luiz (IDL), University of Beira Interior, Covilhã, 6201-001, Portugal
Abstract
Study region: The Yangtze River Basin, the largest river basin in China, is vital for regional water resources, ecosystem sustainability, and socioeconomic development. Increasing drought frequency and severity in recent years, particularly during the extreme 2022 event, have intensified the demand for robust hydrological drought monitoring frameworks. Study focus: GNSS, GRACE, and GRACE Follow-On observations provide valuable information on terrestrial water storage (TWS) changes for drought assessment. However, drought indicators based on GNSS-only or GRACE-only estimates are limited by sparse observations, leakage effects, and spatial resolution constraints. This study develops a Joint Precipitation and Joint-EWH Multivariate Standardized Drought Index (JP-MSDI), which integrates precipitation and TWS changes derived from a joint GNSS-GRACE inversion framework using a Copula-based probabilistic model. The framework was applied to the Yangtze River Basin during 2011–2024. New hydrological insights for the region: Joint GNSS-GRACE inversion reveals spatially heterogeneous TWS variations, with larger amplitudes in the Jinsha River Basin and eastern middle-lower Yangtze plains, but smaller variations in the central basin and around Tai Hu Lake. Compared with GNSS-only estimates, the joint inversion shows higher correlations and lower RMSE values when evaluated against GLDAS. JP-MSDI identified eight drought events during 2011–2024 and reflected the progression from precipitation deficits to TWS anomalies during the 2022 extreme drought.Compared with runoff observations, the Standardized Runoff Index from multiple hydrological stations, and historical drought records indicate that JP-MSDI captures the main temporal patterns of basin-scale drought.
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BibTeX
@article{he2026multivariate,
title = {{A multivariate integrated drought characterization framework using GNSS-GRACE terrestrial water storage and precipitation}},
author = {Xiaoxing He and Jing Yang and Shunqiang Hu and Hai Zhu and Gaël Kermarrec and Rui Fernandes and Jean‑Philippe Montillet and Mingjia Li},
journal = {Journal of Hydrology: Regional Studies},
year = {2026},
month = oct,
doi = {10.1016/j.ejrh.2026.104113},
url = {https://doi.org/10.1016/j.ejrh.2026.104113},
note = {CC BY},
}
RIS
TY - JOUR
TI - A multivariate integrated drought characterization framework using GNSS-GRACE terrestrial water storage and precipitation
AU - Xiaoxing He
AU - Jing Yang
AU - Shunqiang Hu
AU - Hai Zhu
AU - Gaël Kermarrec
AU - Rui Fernandes
AU - Jean‑Philippe Montillet
AU - Mingjia Li
PY - 2026
DA - 2026/10/30
JO - Journal of Hydrology: Regional Studies
DO - 10.1016/j.ejrh.2026.104113
UR - https://doi.org/10.1016/j.ejrh.2026.104113
AB - Study region: The Yangtze River Basin, the largest river basin in China, is vital for regional water resources, ecosystem sustainability, and socioeconomic development. Increasing drought frequency and severity in recent years, particularly during the extreme 2022 event, have intensified the demand for robust hydrological drought monitoring frameworks. Study focus: GNSS, GRACE, and GRACE Follow-On observations provide valuable information on terrestrial water storage (TWS) changes for drought assessment. However, drought indicators based on GNSS-only or GRACE-only estimates are limited by sparse observations, leakage effects, and spatial resolution constraints. This study develops a Joint Precipitation and Joint-EWH Multivariate Standardized Drought Index (JP-MSDI), which integrates precipitation and TWS changes derived from a joint GNSS-GRACE inversion framework using a Copula-based probabilistic model. The framework was applied to the Yangtze River Basin during 2011–2024. New hydrological insights for the region: Joint GNSS-GRACE inversion reveals spatially heterogeneous TWS variations, with larger amplitudes in the Jinsha River Basin and eastern middle-lower Yangtze plains, but smaller variations in the central basin and around Tai Hu Lake. Compared with GNSS-only estimates, the joint inversion shows higher correlations and lower RMSE values when evaluated against GLDAS. JP-MSDI identified eight drought events during 2011–2024 and reflected the progression from precipitation deficits to TWS anomalies during the 2022 extreme drought.Compared with runoff observations, the Standardized Runoff Index from multiple hydrological stations, and historical drought records indicate that JP-MSDI captures the main temporal patterns of basin-scale drought.
SN - 2214-5818
ER -