GRACE-based hydrological droughts are less frequent but more severe than meteorological droughts in global major basins

• A GRACE-based standardized drought index (STWSI) was constructed using the optimal distributions of terrestrial water storage across 40 large river basins. • STWSI-based hydrological index are strongest correlated at 6–12 month scales with SPI/SPEI-based meteorological indices across global major basins. • STWSI-based drought events show lower frequency, higher intensity, and longer duration than meteorological droughts in global most basins except for tropical basins (e.g., Amazon). Satellite observations from the Gravity Recovery and Climate Experiment and its follow-on mission (GRACE/-FO) enable an integrated monitoring of terrestrial water storage (TWS) dynamics, offering a novel perspective for hydrological drought assessment. Existing studies utilizing TWS data often rely on simplistic indices, limiting their diagnostic capability. To address this gap, we develop a Standardized Terrestrial Water Storage Index (STWSI) by optimizing probability distribution fitting across five parametric models (Beta, Johnson-SB, Gamma, Weibull, and Pearson Ⅲ) for monthly TWS changes in 40 globally distributed major river basins. Results indicate that the Johnson-SB distribution provides the optimal fit for STWSI construction in 34 basins, outperforming traditional Gamma/Pearson Ⅲ distributions used in meteorological drought indices (SPI/SPEI). Multi-scale comparisons (1- to 12-month) reveal significantly stronger correlations between STWSI and SPI/SPEI at longer timescales (R = 0.40–0.80 at 12 months) over global major basins. Crucially, STWSI detects hydrological droughts with lower frequency but longer duration and higher intensity than meteorological droughts across most basins, except for tropical basins (e.g., Amazon). At the moderate drought category and different time scales, the total basin area proportion detected by STWSI (44–54 %) is approximately twice that identified by meteorological indices (17–28 %). This divergence underscores the dominant control of long-term TWS depletion on hydrological drought genesis. Our findings establish STWSI as a transformative tool for monitoring composite hydrological droughts in a warming and changing climate.

Authors

Institutions

Publication Details

Journal
Journal of Hydrology
Published
2025-11-08
DOI
https://doi.org/10.1016/j.jhydrol.2025.134582
Citations
1
Primary Topic
Geophysics and Gravity Measurements
Type
article
Field-Weighted Citation Impact
1.79
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

GRACE-based hydrological droughts are less frequent but more severe than meteorological droughts in global major basins

Xuanze Zhang, Yongqiang Zhang, X. Li, Shijia Wang et al.
1 citations
Journal of Hydrology
Geophysics and Gravity Measurements
1.79
article

GRACE-based hydrological droughts are less frequent but more severe than meteorological droughts in global major basins

Xuanze Zhang, Yongqiang Zhang, X. Li, Shijia Wang, Zixuan Tang, Xian Wang, Jing Tian, Chun-hua REN
article en
1 citations

Abstract

• A GRACE-based standardized drought index (STWSI) was constructed using the optimal distributions of terrestrial water storage across 40 large river basins. • STWSI-based hydrological index are strongest correlated at 6–12 month scales with SPI/SPEI-based meteorological indices across global major basins. • STWSI-based drought events show lower frequency, higher intensity, and longer duration than meteorological droughts in global most basins except for tropical basins (e.g., Amazon). Satellite observations from the Gravity Recovery and Climate Experiment and its follow-on mission (GRACE/-FO) enable an integrated monitoring of terrestrial water storage (TWS) dynamics, offering a novel perspective for hydrological drought assessment. Existing studies utilizing TWS data often rely on simplistic indices, limiting their diagnostic capability. To address this gap, we develop a Standardized Terrestrial Water Storage Index (STWSI) by optimizing probability distribution fitting across five parametric models (Beta, Johnson-SB, Gamma, Weibull, and Pearson Ⅲ) for monthly TWS changes in 40 globally distributed major river basins. Results indicate that the Johnson-SB distribution provides the optimal fit for STWSI construction in 34 basins, outperforming traditional Gamma/Pearson Ⅲ distributions used in meteorological drought indices (SPI/SPEI). Multi-scale comparisons (1- to 12-month) reveal significantly stronger correlations between STWSI and SPI/SPEI at longer timescales (R = 0.40–0.80 at 12 months) over global major basins. Crucially, STWSI detects hydrological droughts with lower frequency but longer duration and higher intensity than meteorological droughts across most basins, except for tropical basins (e.g., Amazon). At the moderate drought category and different time scales, the total basin area proportion detected by STWSI (44–54 %) is approximately twice that identified by meteorological indices (17–28 %). This divergence underscores the dominant control of long-term TWS depletion on hydrological drought genesis. Our findings establish STWSI as a transformative tool for monitoring composite hydrological droughts in a warming and changing climate.

Journal of HydrologyVol. 664
Chinese Academy of Sciences (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 12%
Geophysics and Gravity Measurements
1.79
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.