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Managing Water Under a New Hydrological Normal: Innovations for Resilience in the Face of Climate Change

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water and Climate Change".

Deadline for manuscript submissions: 30 May 2026 | Viewed by 943

Special Issue Editors

Institute of Ocean Energy and Intelligent Construction, Tianjin University of Technology, Tianjin 300384, China
Interests: adaptive reservoir operation; hydrology and water environment modeling; hydro-informatics; digital twin of watershed; artificial intelligence (AI)
Department of Hydraulic and Hydropower Engineering, College of Hydraulic and Civil Engineering, Northeast Agricultural University, Harbin, China
Interests: runoff forecasting; hydrological modeling; optimization and scheduling of water resources; reservoir scheduling; smart water conservancy

Special Issue Information

Dear Colleagues,

Climate change is fundamentally altering the global hydrological cycle, impacting not only surface water but also critical groundwater–surface water interactions. These shifts, which exacerbate the frequency and intensity of extreme hydrological events, challenge the core assumptions of traditional water management. Building resilience—the capacity of water systems and societies to adapt to and thrive amidst these changes—is therefore paramount. This Special Issue seeks to compile cutting-edge research that bridges the gap between understanding climate-altered hydrological processes and developing innovative management strategies for water resilience. We welcome contributions that address the following topics, among others:

  • Advanced Hydrological Modeling and Forecasting: Predicting extreme events (floods, droughts) and water availability under non-stationary climates.
  • Altered Groundwater–Surface Water Interactions: Investigating the impacts of climate change on exchange processes, recharge rates, and baseflow dynamics.
  • Adaptive Water Resources Management: Multi-objective optimization, resilient reservoir operation, and allocation strategies to balance water supply, ecology, hydropower, and flood control.
  • Hydro-Monitoring and Data Integration: Leveraging novel sensing technologies, remote sensing, and IoT for improved system monitoring and decision support.
  • Nature-Based Solutions: Implementing green infrastructure and ecological engineering for climate adaptation and enhanced water security.

This Special Issue aims to advance the scientific foundation for creating robust, adaptable, and sustainable water management systems worldwide.

Dr. Jia Wang
Dr. Yi Ji
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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. Water 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 2600 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
  • water resilience
  • hydrological modeling
  • adaptive water management
  • groundwater-surface water interactions
  • adaptive reservoir operation
  • multi-objective optimization
  • hydro-monitoring

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Published Papers (1 paper)

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Research

21 pages, 4568 KB  
Article
How Does Multi-Source Social Media Data Serve in Urban Flood Information Collection, Recognition, and Analysis?
by Jia Wang, Nan Zhang, Yang Liu, Mengmeng Liu, Xiao Wang and Zijun Li
Water 2026, 18(3), 405; https://doi.org/10.3390/w18030405 - 4 Feb 2026
Viewed by 646
Abstract
Urban flood information enables managers to rapidly synthesize comprehensive flood event profiles, serving as critical evidence for flood control decision making. Compared with traditional methods, public data offer unprecedented spatiotemporal granularity due to its high volume, multidimensionality, and real-time nature. In this paper, [...] Read more.
Urban flood information enables managers to rapidly synthesize comprehensive flood event profiles, serving as critical evidence for flood control decision making. Compared with traditional methods, public data offer unprecedented spatiotemporal granularity due to its high volume, multidimensionality, and real-time nature. In this paper, we investigated public data’s usefulness and generalizability of spatial feature differences using multi-source social media data as an entry point. We selected rainstorm events that occurred in three cities located in the North China Plain, the Southeast Coastal Region, and the Western Region of China, with vastly different developmental statuses in 2023. Then, multi-platform data from the events were collected and analyzed through crawling and topic mining. The results indicate that: (1) social media data from different sources are complementary to each other and can collectively extract plenty of neglected waterlogging points to supplement official data, with a supplementary rate reaching 171% on average; and (2) social media data has significant value in spatial characterization, which means that its availability remains constant despite geographical differences and can self-adapt to local geography, inhabitant profiles and social development levels. To address the issues of limited available data and essential information lacking during the analysis process, we propose recommendations for data processing and city managers to enhance the scientific value of social media data utilized in practice. Full article
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