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Climate Change, Hydrological Uncertainty and Sustainable Water Management

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Water Management".

Deadline for manuscript submissions: 10 March 2026 | Viewed by 536

Special Issue Editor


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Guest Editor
Department of Civil and Architectural Engineering, Sultan Qaboos University, Muscat 123, Oman
Interests: hydrology; climate change; remote sensing and GIS applications in water and environmental studies

Special Issue Information

Dear Colleagues,

Climate change profoundly impacts the hydrological cycle, leading to more frequent and intense extreme weather events, while also increasing uncertainty in water resources management, making it essential to develop innovative strategies that enhance resilience, minimize risks, and secure water resources for the future. Addressing hydrological uncertainty—stemming from climate fluctuations, data gaps, and model limitations—is crucial in terms of formulating adaptive water management policies and infrastructure solutions.

This Special Issue seeks to deepen scientific knowledge of climate-driven hydrological variability and its effects on sustainable water management. It aims to highlight interdisciplinary approaches that integrate hydrological modeling, climate adaptation strategies, water governance, and policy development. By tackling these critical issues, the Special Issue contributes to global sustainability goals, particularly SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 15 (Life on Land).

The Special Issue welcomes original research and review articles on a broad range of topics, including:

  • Hydrological Uncertainty and Climate Change: Examining climate change’s influence on water resources, enhancing predictive models, and incorporating AI-based forecasting techniques.
  • Sustainable Water Management and Adaptation Strategies: Investigating nature-based solutions, urban water conservation methods, and integrated water resources management to support long-term sustainability.
  • Hydrological Modeling: Utilizing new and emerging technologies and decision-support tools to strengthen climate-resilient water governance.
  • Water Policy, Governance, and Societal Impacts: Assessing policy frameworks, transboundary water management, and community-driven solutions for fair water distribution.

By bringing together contributions from researchers, policymakers, and practitioners, this Special Issue seeks to promote innovative approaches that enhance climate resilience in water management. We invite submissions that offer fresh perspectives on hydrological processes, uncertainty analysis, and adaptive governance strategies to effectively address the water-related challenges of climate change.

We look forward to receiving your contributions.

Dr. Ghazi Ali Al-Rawas
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climate change
  • hydrological uncertainty
  • water resources management
  • extreme events
  • resilience
  • hydrological modeling
  • water governance
  • sustainable water management
  • integrated water resources management

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Published Papers (1 paper)

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Research

19 pages, 2237 KiB  
Article
Flood Season Division Model Based on Goose Optimization Algorithm–Minimum Deviation Combination Weighting
by Yukai Wang, Jun Li and Jing Fu
Sustainability 2025, 17(15), 6968; https://doi.org/10.3390/su17156968 - 31 Jul 2025
Viewed by 280
Abstract
The division of the flood season is of great significance for the precise operation of water conservancy projects, flood control and disaster reduction, and the rational allocation of water resources, alleviating the contradiction of the uneven spatial and temporal distribution of water resources. [...] Read more.
The division of the flood season is of great significance for the precise operation of water conservancy projects, flood control and disaster reduction, and the rational allocation of water resources, alleviating the contradiction of the uneven spatial and temporal distribution of water resources. The single weighting method can only determine the weight of the flood season division indicators from a certain perspective and cannot comprehensively reflect the time-series attributes of the indicators. This study proposes a Flood Season Division Model based on the Goose Optimization Algorithm and Minimum Deviation Combined Weighting (FSDGOAMDCW). The model uses the Goose Optimization Algorithm (GOA) to solve the Minimum Deviation Combination model, integrating weights from two subjective methods (Expert Scoring and G1) and three objective methods (Entropy Weight, CV, and CRITIC). Combined with the Set Pair Analysis Method (SPAM), it realizes comprehensive flood season division. Based on daily precipitation data of the Nandujiang River (1961–2022), the study determines its flood season from 1 May to 30 October. Comparisons show that: ① GOA converges faster than the Genetic Algorithm, stabilizing at T = 5 and achieving full convergence at T = 24; and ② The model’s division results have the smallest Intra-Class Differences, avoiding indistinguishability between flood and non-flood seasons under special conditions. This research aims to support flood season division studies in tropical islands. Full article
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