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Impacts of Climate Change on Water Resources and Water Risks, 2nd Edition

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Resources Management, Policy and Governance".

Deadline for manuscript submissions: 20 May 2025 | Viewed by 12258

Special Issue Editors

Prof. Dr. Haibo Yang

E-Mail Website
Guest Editor
School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou, China
Interests: drought monitor; drought index; drought simulation; remote sensing; satellite precipitation; precipitation downscaling; flood
Special Issues, Collections and Topics in MDPI journals
Dr. Zheng Duan

E-Mail Website1 Website2
Guest Editor
Department of Physical Geography and Ecosystem Science, Lund University, S-22362 Lund, Sweden
Interests: environmental remote sensing; water quality sensing; machine learning; ecohydrological modelling
Special Issues, Collections and Topics in MDPI journals
Dr. Fei Chen

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Guest Editor
General Institute of Water Resources and Hydropower Planning and Design, Beijing, China
Interests: hydrogeology; numerical modelling in geotechnical engineering; ground water simulation; water resource management
Dr. Zhiwei Li

E-Mail Website
Guest Editor
School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou, China
Interests: hydraulics; river dynamics; environmental sediment

Special Issue Information

Dear Colleagues,

Water resources are important for ecosystems and social and economic developments. Climate change has accelerated the heterogeneity of the spatiotemporal distribution of water resources, and has increased the probability of extreme events leading to more water disasters and threats. According to the plausible future scenarios for climate change from the IPCC Report 2022, if global warming transiently exceeds 1.5 °C in the coming decades, then humans and ecosystems will face additional severe risks. Notable, extreme precipitation and heat waves can cause more intensive water risks, such as floods and drought. Considerable efforts have been made to develop advanced remote sensing and other new approaches to monitor relevant variables such as precipitation, runoff, evaporation, soil moisture and groundwater. Various hydrological models are being developed to understand hydrological processes and to quantify their responses to climate change and human activities. Machine learning and deep learning methods are also increasingly being used to facilitate water research. However, how to accurately quantify and predict the impact of climate change on water resources and water risk still needs to be studied further.

This Special Issue aims to gather contributions of the latest scientific research on the impact of climate change on water resources and water risks. This Special Issue will encompass a broad spectrum of topics, including, but not limited to:

  • Climate change impact assessment;
  • Satellite hydrometeorological monitoring;
  • Hydrological modelling;
  • Drought monitoring;
  • Flood simulation and flood risk evaluation;
  • New technologies and approaches for water resources and water risks;

Prof. Dr. Haibo Yang
Dr. Zheng Duan
Dr. Fei Chen
Dr. Zhiwei Li
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 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. 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 resource management
  • drought
  • flood
  • remote sensing

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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (6 papers)

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Research

16 pages, 5810 KiB  
Article
Deep Learning Downscaling of Precipitation Projection over Central Asia
by Yichang Jiang, Jianing Guo, Lei Fan, Hui Sun and Xiaoning Xie
Water 2025, 17(7), 1089; https://doi.org/10.3390/w17071089 - 5 Apr 2025
Viewed by 226
Abstract
Central Asia, as a chronically water-stressed region marked by extreme aridity, faces significant environmental challenges from intensifying desertification and deteriorating ecological stability. The region’s vulnerability to shifting precipitation regimes and extreme hydrometeorological events has been magnified under anthropogenic climate forcing. Although global climate [...] Read more.
Central Asia, as a chronically water-stressed region marked by extreme aridity, faces significant environmental challenges from intensifying desertification and deteriorating ecological stability. The region’s vulnerability to shifting precipitation regimes and extreme hydrometeorological events has been magnified under anthropogenic climate forcing. Although global climate models (GCMs) remain essential tools for climate projections, their utility in Central Asia’s complex terrain is constrained by inherent limitations: coarse spatial resolution (~100–250 km) and imperfect parameterization of orographic precipitation mechanisms. This investigation advances precipitation modeling through deep learning-enhanced statistical downscaling, employing convolutional neural networks (CNNs) to generate high-resolution precipitation data at approximately 10 km resolution. Our results show that the deep learning models successfully simulate the high center of precipitation and extreme precipitation near the Tianshan Mountains, exhibiting high spatial applicability. Under intermediate (SSP-245) and high-emission (SSP-585) future scenarios, the increase in extreme precipitation over the next century is significantly more pronounced compared to mean precipitation. By the end of the 21st century, the interannual variability of mean precipitation and extreme precipitation will become even larger under SSP-585, indicating an increased risk of extreme droughts/floods in Central Asia under high greenhouse gas emissions. Our findings provide technical support for climate change impact assessments in the region and highlight the potential of CNN-based downscaling for future climate change studies. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources and Water Risks, 2nd Edition)
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19 pages, 12795 KiB  
Article
Building Reservoirs as Protection against Flash Floods and Flood Basins Management—The Case Study of the Stubo–Rovni Regional Water-Management System
by Ljubiša Bezbradica, Boško Josimović, Boris Radić, Siniša Polovina and Tijana Crnčević
Water 2024, 16(16), 2242; https://doi.org/10.3390/w16162242 - 8 Aug 2024
Viewed by 1181
Abstract
Global warming and climate change cause large temperature oscillations and uneven annual rainfall patterns. The rainy cycles characterized by frequent high-intensity rainfall in the area of the Stubo–Rovni water reservoir, which in 2014 peaked at 129 mm of water in 24 h (the [...] Read more.
Global warming and climate change cause large temperature oscillations and uneven annual rainfall patterns. The rainy cycles characterized by frequent high-intensity rainfall in the area of the Stubo–Rovni water reservoir, which in 2014 peaked at 129 mm of water in 24 h (the City of Valjevo, the Republic of Serbia), caused major floods in the wider area. Such extremes negatively affect erosion processes, sediment production, and the occurrence of flash floods. The erosion coefficient before the construction of the water reservoir was Zm = 0.40, while the specific sediment production was about 916.49 m3∙km−2∙year−1. A hydrological study at the profile near the confluence of the Jadar and Obnica rivers, i.e., the beginning of the Kolubara river, the right tributary of the Sava (in the Danube river basin), indicates that the natural riverbed can accommodate flows with a 20% to 50% probability of occurrence (about 94 m3/s), while centennial flows of about 218 m3/s exceed the capacities of the natural riverbed of the Jadar river, causing flooding of the terrain and increasing risks to the safety of the population and property. The paper presents the impacts of the man-made Stubo–Rovni water reservoir on the catchment area and land use as the primary condition for preventing erosion processes (specific sediment production has decreased by about 20%, the forest cover increased by about 25%, and barren land decreased by 90%). Moreover, planned and controlled management of the Stubo–Rovni reservoir has significantly influenced the downstream flow, reducing the risks of flash floods. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources and Water Risks, 2nd Edition)
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17 pages, 5245 KiB  
Article
Multiscale Spatiotemporal Dynamics of Drought within the Yellow River Basin (YRB): An Examination of Regional Variability and Trends
by Lei Jin, Shaodan Chen and Mengfan Liu
Water 2024, 16(5), 791; https://doi.org/10.3390/w16050791 - 6 Mar 2024
Cited by 4 | Viewed by 1832
Abstract
Drought, as a recurring extreme climatic event, inflicts diverse impacts on ecological systems, agricultural productivity, water resources, and socio-economic progress globally. Discerning the drought patterns within the evolving environmental landscape of the Yellow River Basin (YRB) is imperative for enhancing regional drought management [...] Read more.
Drought, as a recurring extreme climatic event, inflicts diverse impacts on ecological systems, agricultural productivity, water resources, and socio-economic progress globally. Discerning the drought patterns within the evolving environmental landscape of the Yellow River Basin (YRB) is imperative for enhancing regional drought management and fostering ecological conservation alongside high-quality development. This study utilizes meteorological drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the self-calibrating Palmer Drought Severity Index (scPDSI), for a detailed spatiotemporal analysis of drought conditions. It examines the effectiveness of these indices in the basin’s drought monitoring, offering a comprehensive insight into the area’s drought spatiotemporal dynamics. The findings demonstrate the following: (1) SPEI values exhibit distinct fluctuation patterns at varying temporal scales, with more pronounced fluctuations at shorter scales. Drought years identified via the 12-month SPEI time scale include 1965, 1966, 1969, 1972, 1986, 1997, 1999, 2001, and 2006. (2) A modified Mann–Kendall (MMK) trend test analysis of the scPDSI time series reveals a worrying trend of intensifying drought conditions within the basin. (3) Correlation analysis between SPEI and scPDSI across different time scales yields correlation coefficients of 0.35, 0.54, 0.69, 0.76, and 0.62, highlighting the most substantial correlation at an annual scale. Spatial correlation analysis conducted between SPEI and scPDSI across various scales reveals that, within diverse temporal ranges, the correlation peaks at a 12-month time scale, with subsequent prominence observed at 6 and 24 months. This observed pattern accentuates the applicability of scPDSI in the monitoring of medium- to long-term drought phenomena. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources and Water Risks, 2nd Edition)
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18 pages, 4925 KiB  
Article
Study on the Optimization of Multi-Objective Water Resources Allocation in the Henan Yellow River Water Supply Zone
by Yanbin Li, Ke Sun, Ruyi Men, Fei Wang, Daoxi Li, Yuhang Han and Yanping Qu
Water 2023, 15(22), 4009; https://doi.org/10.3390/w15224009 - 18 Nov 2023
Cited by 7 | Viewed by 1956
Abstract
With the continuous growth in the global population, rapid socioeconomic development, and the impacts of factors like climate change, we are facing increasingly severe challenges regarding water scarcity. The scientific and rational allocation of water resources has become a key factor in ensuring [...] Read more.
With the continuous growth in the global population, rapid socioeconomic development, and the impacts of factors like climate change, we are facing increasingly severe challenges regarding water scarcity. The scientific and rational allocation of water resources has become a key factor in ensuring sustainable development. The Henan Yellow River water supply zone occupies a crucial position in the socioeconomic development of Henan Province. Currently, there is a shortage of water resources with relatively low utilization rates. To alleviate the contradiction between water supply and demand, a study on the optimization of water resources (with p = 90%) for the years 2025 and 2030 was conducted. In this study, we constructed a multi-objective optimization model with the objectives of maximizing economic benefits, minimizing total water shortage, and maximizing water use efficiency. The second-generation non-dominated sorting genetic algorithm (NSGA-II) was utilized to solve this model. The results indicate that by 2025, the optimized allocation of water resources will correspond to 17.663 billion m3, reducing the average water shortage rate in the research area to 9.69%. By 2030, the optimized allocation of water resources will further increase to 18.363 billion m3, bringing down the average water shortage rate to 8.34%. Concurrently, the supply structure of the research area will significantly improve after optimization. This is manifested through an increase in the proportion of surface water supply and a substantial rise in the proportion of supply from other water sources, while the proportion of groundwater supply noticeably decreases. These research findings can serve as a reference for the rational utilization and distribution of water resources in the future and can also offer insights for optimizing water resource allocation in other regions. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources and Water Risks, 2nd Edition)
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20 pages, 10767 KiB  
Article
Dynamic Characteristics of Meteorological Drought and Its Impact on Vegetation in an Arid and Semi-Arid Region
by Weijie Zhang, Zipeng Wang, Hexin Lai, Ruyi Men, Fei Wang, Kai Feng, Qingqing Qi, Zezhong Zhang, Qiang Quan and Shengzhi Huang
Water 2023, 15(22), 3882; https://doi.org/10.3390/w15223882 - 7 Nov 2023
Cited by 7 | Viewed by 2417
Abstract
Under the background of global climate warming, meteorological drought disasters have become increasingly frequent. Different vegetation types exhibit varying responses to drought, thus, exploring the heterogeneity of the impact of meteorological drought on vegetation is particularly important. In this study, we focused on [...] Read more.
Under the background of global climate warming, meteorological drought disasters have become increasingly frequent. Different vegetation types exhibit varying responses to drought, thus, exploring the heterogeneity of the impact of meteorological drought on vegetation is particularly important. In this study, we focused on Inner Mongolia (IM) as the research area and employed Standardized Precipitation Evapotranspiration Index (SPEI) and Vegetation Health Index (VHI) as meteorological drought and vegetation indices, respectively. The Breaks for Additive Seasons and Trend algorithm (BFAST) was utilized to reveal the dynamic characteristics of both meteorological drought and vegetation changes. Additionally, the Pixel-Based Trend Identification Method (PTIM) was employed to identify the trends of meteorological drought and vegetation during spring, summer, autumn, and the growing season. Subsequently, we analyzed the correlation between meteorological drought and vegetation growth. Finally, the response of vegetation growth to various climate factors was explored using the standardized multivariate linear regression method. The results indicated that: (1) During the study period, both SPEI and VHI exhibited a type of interrupted decrease. The meteorological drought was aggravated and the vegetation growth was decreased. (2) Deserts and grasslands exhibited higher sensitivity to meteorological drought compared to forests. The strongest correlation between SPEI-3 and VHI was observed in desert and grassland regions. In forest areas, the strongest correlation was found between SPEI-6 and VHI. (3) The r between severity of meteorological drought and status of vegetation growth was 0.898 (p < 0.01). Vegetation exhibits a more pronounced response to short-term meteorological drought events. (4) Evapotranspiration is the primary climatic driving factor in the IM. The findings of this study provide valuable insights for the rational utilization of water resources, the formulation of effective irrigation and replenishment policies, and the mitigation of the adverse impacts of meteorological drought disasters on vegetation growth in the IM. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources and Water Risks, 2nd Edition)
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18 pages, 7043 KiB  
Article
Flood Hazard Evaluation Using a Flood Potential Index
by Nicolae-Cristian Popescu and Alina Bărbulescu
Water 2023, 15(20), 3533; https://doi.org/10.3390/w15203533 - 10 Oct 2023
Cited by 5 | Viewed by 3564
Abstract
Areas subject to flooding must be carefully analyzed to make correct measures for preventing disasters that impact the population’s lives and economy. In this article, we propose a flood potential index (FPI) to estimate flood susceptibility, using an optimal selection of weights for [...] Read more.
Areas subject to flooding must be carefully analyzed to make correct measures for preventing disasters that impact the population’s lives and economy. In this article, we propose a flood potential index (FPI) to estimate flood susceptibility, using an optimal selection of weights for the criteria contributing to flooding risk evaluation. Comparisons with the situation when equal weights are assigned to each factor are exemplified in a case study from the Vărbilău catchment (Romania). The study reveals the necessity of an objective factor weighting choice for determining the flooded zones. The results are validated with the available data from the Romanian Waters Institute. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources and Water Risks, 2nd Edition)
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