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Extreme Climate and Precipitation Variability: Advanced Modeling Approaches and Predictions

A Special Issue of Water (ISSN 2073-4441) belonging to the section "Water and Climate Change".

Deadline for manuscript submissions: 30 January 2027 | Viewed by 434

Editors

School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, China
Interests: extreme hydrological events; non-stationary hydrological frequency analysis; drought–flood abrupt alternation; evolution of water cycle; hydrological model

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Guest Editor
School of Hydrology and Water Resources, Nanjing University of In-formation Science and Technology, Nanjing 210044, China
Interests: drought propagation; flash drought; drought–flood abrupt alternation; compound droughts and hot extremes; non-stationary flood and drought assessment

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Guest Editor
College of Environment, Hohai University, Nanjing 210098, China
Interests: satellite precipitation; multi-source data fusion and application; analysis of extreme precipitation events; drought monitoring; machine learning

Special Issue Information

Dear Colleagues,

This Special Issue aims to study the non-stationary changes and impacts of climate and precipitation in a changing en-vironment. We invite original research and review articles on high-resolution regional climate models, hybrid modeling and prediction under the advanced machine learning/deep learning framework, and the exploration of water cycle im-pact mechanisms. By improving our modeling capabilities and prediction accuracy, this Special Issue aims to provide a strong scientific basis for climate adaptation, risk assessment and infrastructure planning.

Key areas of interest include precipitation data fusion correction, hydrometeorological modeling methods and attribu-tion mechanism analysis. The scope of this Special Issue includes, but is not limited to, the following topics:

  • Mechanisms and dynamics of compounding extreme events;
  • Satellite remote sensing in monitoring extreme precipitation;
  • Machine learning and AI in precipitation forecasting;
  • Uncertainty quantification in future climate projections;
  • Climate change attribution and risk assessment.

Dr. Hao Cui
Dr. Menghao Wang
Dr. Linyong Wei
Guest Editors

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Keywords

  • flood
  • mechanisms of extreme precipitation change
  • drought–flood abrupt alternation
  • compound meteorological and hydrological events
  • satellite precipitation monitoring
  • precipitation fusion

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Published Papers (1 paper)

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Research

24 pages, 2542 KB  
Article
Regional Water Resource Carrying Capacity Assessment and Barrier Factor Diagnosis Based on Combined Weighted-TOPSIS Model
by Yang Zhang, Fan Wu, Fulong Chen, Chaofei He, Shuanglin Shao, Aihua Long and Zhengliang Yin
Water 2026, 18(17), 2133; https://doi.org/10.3390/w18172133 - 29 Aug 2026
Viewed by 235
Abstract
Water resource carrying capacity (WRCC) assessment provides an important basis for regional socioeconomic development planning and water resource management. In this study, an 18-indicator WRCC evaluation system was constructed for the Eighth Division of the Xinjiang Production and Construction Corps based on the [...] Read more.
Water resource carrying capacity (WRCC) assessment provides an important basis for regional socioeconomic development planning and water resource management. In this study, an 18-indicator WRCC evaluation system was constructed for the Eighth Division of the Xinjiang Production and Construction Corps based on the Supply–Water-use Efficiency–Demand Pressure–Economy and Society–Regulation (SWDER) framework. Indicator weights were determined using a combined method integrating the Criteria Importance Through Intercriteria Correlation method and the entropy weight method. The Technique for Order Preference by Similarity to an Ideal Solution was then applied to evaluate WRCC across six irrigation districts during 2015–2025 and under different scenarios in 2030. An obstacle factor diagnosis model was further used to identify the main limiting factors and support differentiated management recommendations. The results showed that: (1) the regulation and ecological constraints subsystem was the dominant criterion layer affecting WRCC in the Eighth Division, and industrial value added, ecological water use ratio, and supply–demand ratio were the key high-weight indicators; (2) WRCC in the Eighth Division showed a slow upward trend from 2015 to 2025, with the average evaluation value of the six irrigation districts increasing from 0.2325 to 0.2543, although phased declines occurred in 2020 and 2022. Marked differences were observed among irrigation districts, with the Ningjiahe and Shihezi irrigation districts generally showing higher carrying capacity levels than the other districts; and (3) under both the normal scenario and the rigid water resource constraint scenario in 2030, the average WRCC of the study area increased compared with 2025, but inter-district differentiation remained significant. Except for the Mosuowan Irrigation District, the WRCC evaluation values of the other irrigation districts were lower under the rigid constraint scenario than under the normal scenario. These results provide a scientific basis for rigid water resource constraint management, optimized water resource allocation, and differentiated regulation of irrigation districts in arid regions. Full article
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