Stable isotopes reveal the water conversion and transition dynamics in a heavily-polluted plateau marginal basin: implications for aquatic ecosystem protection DOI
Chengcheng Xia, Jie Wei, Guodong Liu

et al.

Process Safety and Environmental Protection, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 1, 2024

Language: Английский

Wetter trend in source region of Yangtze River by runoff simulating based on Grid-RCCC-WBM DOI
Zhongrui Ning, Nan Wu, Jianyun Zhang

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 631, P. 130702 - 130702

Published: Jan. 23, 2024

Language: Английский

Citations

5
Study on the evolution of shallow groundwater levels and its spatiotemporal response to precipitation in the Beijing Plain of China based on variation points DOI Creative Commons

Xueting Zhong,

Huili Gong, Beibei Chen

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112466 - 112466

Published: Aug. 12, 2024

Language: Английский

Citations

4
Enhanced Spatial Dry–Wet Contrast in the Future of the Qinghai–Tibet Plateau DOI
Fan Yang, Aizhong Ye, Yunfei Wang

et al.

Hydrological Processes, Journal Year: 2025, Volume and Issue: 39(2)

Published: Feb. 1, 2025

ABSTRACT The geographical uniqueness of the Qinghai–Tibet Plateau (QTP) determines its significance as ‘Asia's Water Tower’. It is expected that climate change in this area will cause extreme weather occurrences, stress water resources and increase vulnerability ecosystems future. However, precise quantitative impact on QTP remains uncertain. In study, using coupled model intercomparison project (CMIP) phase 6 multi‐model data a distributed time‐variant gain hydrological (DTVGM), we examined spatiotemporal attributes hydrology across under various socioeconomic progress trajectories greenhouse gas emission scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 SSP5‐8.5). Over next 80 years, an overall warming trend was observed QTP, accompanied by decrease annual total resources. drier arid regions, wetter are humid regions future QTP. Runoff 74.92% region, evaporation 84.93% from 2020 to 2099. SSP5‐8.5, precipitation rate −6.22 mm/10a, runoff −8.84 mm/10a. After year abrupt (2052–2064), became significantly faster. approximately 58.00% surface runoff. Unlike trend, displayed fluctuating upward pattern, with average 2.78 Spatially, variations dry–wet conditions more evident, showing substantial noteworthy northeastern plateau. southeastern region Yarlung Tsangpo River Basin, rates were notably higher than those other regions. Moreover, there significant surge areas adjacent glaciers. conclusion, study offers valuable insights into decision‐making concerning developmental region.

Language: Английский

Citations

0
Improve streamflow simulations by combining machine learning pre-processing and post-processing DOI
Yuhang Zhang, Aizhong Ye, Jinyang Li

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132904 - 132904

Published: Feb. 1, 2025

Language: Английский

Citations

0
Integrating multi-model frameworks to unravel the spatiotemporal dynamics of flash floods in the Tianshan Mountain, China DOI Creative Commons
Biao Zhang, Haiyan Fang, Guotao Zhang

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 172, P. 113259 - 113259

Published: Feb. 26, 2025

Language: Английский

Citations

0
Runoff spatiotemporal variability driven by climate change and human activity for the Nianchu River Basin in Southwestern Tibet DOI Creative Commons
Zhe Yuan, K. Liu, Dan Zeng

et al.

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 58, P. 102301 - 102301

Published: March 6, 2025

Language: Английский

Citations

0
A novel remote Sensing-Based calibration and validation method for distributed hydrological modelling in ungauged basins DOI

Daolan Zheng,

Wenbin Zhu, Yan Han

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 133119 - 133119

Published: March 1, 2025

Language: Английский

Citations

0
Assessing climate change and human impacts on runoff and hydrological droughts in the Yellow River Basin using a machine learning-enhanced hydrological modeling approach DOI
Lei Wang,

Li Yi,

Asim Biswas

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 380, P. 125091 - 125091

Published: March 28, 2025

Language: Английский

Citations

0
Analysis of Runoff Variability and Periodicity in the Qinghai Lake Basin DOI Creative Commons
Panpan Yao,

Hongyan Gao,

Xinxiao Yu

et al.

Hydrology, Journal Year: 2025, Volume and Issue: 12(4), P. 83 - 83

Published: April 10, 2025

This study, based on hydrological station data and wavelet analysis, explores the periodic variation characteristics trends of two main tributaries (Buha River Shaliu River) in Qinghai Lake Basin from 1960 to 2016. Wavelet transform is used analyze runoff data, revealing long-term fluctuations their correlation with precipitation changes. The study finds that, 2003 2016, daily peak flow minimum rivers increase compared period 2003, though magnitude differ. At monthly scale, patterns show that June October for concentrated basin, July August being months. Additionally, interannual changes both a gradually increasing trend amid fluctuations, varying fluctuation intensities observed different years. analysis results indicate periodicity 23 years, closely linked precipitation. reveals Basin, providing valuable insights watershed water resource management hydrometeorological forecasting.

Language: Английский

Citations

0
Quantitative attribution analysis of water and sediment changes in the Lower Yellow River (1950–2022) under the influence of climate change and human activities DOI

Yihao Wen,

Haijue Xu, Jinliang Zhang

et al.

Environmental Earth Sciences, Journal Year: 2025, Volume and Issue: 84(9)

Published: April 25, 2025

Language: Английский

Citations

0