Assessment of Drought Evolution in the Yangtze River Basin Based on Downscaled Grace Data DOI

Zhiwen You,

Huaiwei Sun, Hao Zhou

et al.

Published: Jan. 1, 2024

Assessing drought characteristics and its evolution patterns in the Yangtze River Basin (YRB) holds significant implications for understanding distribution variability of water resources basin. This study employs a statistical downscaling method based on principle balance to enhance spatial resolution terrestrial storage anomaly (TWSA) estimations derived from Gravity Recovery Climate Experiment (GRACE) into 0.1°. Utilizing downscaled data, we establish high-precision indices including Water Storage Deficit (WSD) Index (WSDI). Furthermore, dispersion rate area (DRDA) average WSDI (WSDIDA) are defined access extent impact severity drought-affected areas. These indicators enable identification analysis spatiotemporal YRB April 2002 September 2021. The main innovation results as follows. (1) Compared with PCR-GLOBWB model, our dataset presents excellent applicability detecting regional within YRB. majority test sampling points demonstrated an increase correlation coefficient reference data by approximately 0.15-0.2 compared premise. (2) During period, experienced 9 basin-wide events, most severe event lasting 18 months total WSD nearly 550 mm. Over 90% basin suffered varying degrees this event. (3) In case no trend observed WSDIDA, DRDA is shrinking at 2.54% per year. Drought conditions sub-basins have been effectively alleviated, evidenced increasing WSDI. (4) Jinsha Han maintain high annual frequency (ADF), their DRDA, Annual Duration (ADD) Severity (ADS) show trends, indicating that entire gradually concentrating these two sub-basins. Our new GRACE proposed promising application prospects assessing local basin, providing robust support prevention scheduling decision-making region.

Language: Английский

How 2022 extreme drought influences the spatiotemporal variations of terrestrial water storage in the Yangtze River Catchment: Insights from GRACE-based drought severity index and in-situ measurements DOI
Guodong Xu, Yunlong Wu, Sulan Liu

et al.

Journal of Hydrology, Journal Year: 2023, Volume and Issue: 626, P. 130245 - 130245

Published: Sept. 27, 2023

Language: Английский

Citations

66

Quantifying the 2022 extreme drought in the Yangtze River Basin using GRACE-FO DOI
Ao Duan, Yulong Zhong, Guodong Xu

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 630, P. 130680 - 130680

Published: Jan. 23, 2024

Language: Английский

Citations

33

High-resolution groundwater storage anomalies in the Middle and Lower Yangtze River Basin of China using machine learning fusion of in-situ wells, satellite gravity and hydrological model DOI
Hu Li, Linsong Wang, Zhenran Peng

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 375, P. 124322 - 124322

Published: Jan. 29, 2025

Language: Английский

Citations

1

Stepwise clustering ensemble downscaling for future drought prediction under climate change: A case study of the Yangtze River Basin DOI

Jiachen Liu,

Guohe Huang, Tangnyu Song

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 633, P. 131005 - 131005

Published: March 11, 2024

Language: Английский

Citations

4

A Probabilistic Approach to Characterizing Drought Using Satellite Gravimetry DOI Creative Commons
Peyman Saemian, Mohammad J. Tourian, Omid Elmi

et al.

Water Resources Research, Journal Year: 2024, Volume and Issue: 60(8)

Published: Aug. 1, 2024

Abstract In the recent past, Gravity Recovery and Climate Experiment (GRACE) satellite mission its successor GRACE Follow‐On (GRACE‐FO), have become invaluable tools for characterizing drought through measurements of Total Water Storage Anomaly (TWSA). However, existing approaches often overlooked uncertainties in TWSA that stem from orbit configuration, background models, intrinsic data errors. Here we introduce a fresh view on this problem which incorporates data: Probabilistic Storage‐based Drought Index (PSDI). Our method leverages Monte Carlo simulations to yield realistic realizations stochastic process time series. These depict range plausible scenarios later are used characterize drought. This approach provides probability each category instead selecting single final at epoch. We compared PSDI with deterministic (Storage‐based Index, SDI) over major global basins. results show leans toward an overestimation storage‐based severity. Furthermore, scrutinize performance across diverse hydrologic events, spanning continents United States Europe, Middle East, Southern Africa, South America, Australia. case, emerges as reliable indicator conditions, providing more comprehensive perspective than conventional indices. contrast common view, our probabilistic characterization TWS drought, making it suited adaptive strategies risk management.

Language: Английский

Citations

4

A machine learning downscaling framework based on a physically constrained sliding window technique for improving resolution of global water storage anomaly DOI
Gangqiang Zhang, Tongren Xu, Wenjie Yin

et al.

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 313, P. 114359 - 114359

Published: Aug. 10, 2024

Language: Английский

Citations

4

The relationship between prenatal drought exposure and the diversity and composition of gut microbiome in pregnant women and neonates DOI Creative Commons

Qingbo Fang,

Tianlai Qiu,

Fenfen Chen

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 2, 2025

Language: Английский

Citations

0

Multiscale Nonlinear Response of Extreme Meteorological–Hydrothermal Events in the Upper Reaches of the Yangtze River DOI Open Access
Long Yu, Wenxian Guo, Huan Yang

et al.

Ecohydrology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 13, 2025

ABSTRACT Under the backdrop of climate warming, outbreak short‐term extreme heat events can easily lead to irreversible changes in aquatic ecosystems. Delving into their intrinsic driving mechanisms and nonlinear characteristics is key preventing natural disasters. This study, focusing on upper Yangtze River as research area, constructs a joint copula function model analyze occurrence probability return period meteorological events. Through bivariate cross–wavelet transform method, study explores multiscale dynamic response relationships phase meteorological–hydrothermal River. Furthermore, multifractal responses for was established. The results indicate that high‐heat tend occur more frequently severely, with duration–kurtosis likely coincide within 2‐year period, well high‐intensity low‐frequency duration–severity occurring simultaneously. Overall, before 2005, high‐hydrothermal exhibited lagging behind changes, which then shifted from lag lead. three scenarios change, exhibit clear relationship. Apart duration, severity kurtosis all show significant relationships.

Language: Английский

Citations

0

Detection of the 2022 extreme drought over the Yangtze River basin using two satellite-gauge precipitation products DOI

Linyong Wei,

S. S. Jiang, Liliang Ren

et al.

Atmospheric Research, Journal Year: 2025, Volume and Issue: unknown, P. 107929 - 107929

Published: Jan. 1, 2025

Language: Английский

Citations

0

Quantifying long-term drought in China’s exorheic basins using a novel daily GRACE reconstructed TWSA index DOI
Shuang Yang, Yulong Zhong, Yunlong Wu

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132919 - 132919

Published: Feb. 1, 2025

Language: Английский

Citations

0