Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.5
3.4
Journals
Water
Special Issues
Impacts of Climate Change on Water Resources: Assessment and Modeling
share announcement

Impacts of Climate Change on Water Resources: Assessment and Modeling

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 10796

Special Issue Editors

Dr. Leszek Sobkowiak

E-Mail Website
Guest Editor
Department of Hydrology and Water Management, Adam Mickiewicz University, 61-712 Poznań, Poland
Interests: climate change; time series analysis; river regime; water resource management; water balance; watershed hydrology; watershed management; China
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Dariusz Wrzesiński

E-Mail Website1 Website2
Guest Editor
Department of Hydrology and Water Management, Adam Mickiewicz University, 61-712 Poznań, Poland
Interests: flow regime; flow seasonality; thermal conditions; water chemistry; ice phenomena; climate change; human activity; methods of detecting changes and classifying river regimes
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Water resources are a national source of wealth, and their availability is essential to sustain life and human activities. The amount and availability of water resources in the world varies spatially and temporally, with an increasing number of places facing severe water shortages.

It is predicted that climate change will significantly affect the spatiotemporal distribution of water resources, leading to the transformation of the water cycle in the catchment and changes in the structure of the water balance. An increase in the occurrence of deep low flows in rivers is expected, which may result in a reduction in surface water and ground water resources. In lowland catchments, evapotranspiration will increase at the expense of water resources, causing there to be a reduction. The acceleration of the hydrological cycle may lead to more and more frequent water-related extreme events including droughts and floods, and the expected changes in water resource availability may lead to periodic deficits in the water supplied to the population, as well as shortages in agriculture and forestry, which may entail severe socioeconomic losses.

Being aware of these threats, it is necessary to take actions to mitigate their future effects.

Current forecasts of water consumption trends resulting from socioeconomic development and the climatic changes that overlap with it are subject to considerable uncertainty. Climate models (global circulation of the atmosphere) and demographic and economic development models do not yet allow for precise projections of changes in the hydrological cycle and water resource availability.

This Special Issue invites researchers to present their results of new findings from the assessment and modeling of hydrological processes and water resources under the conditions of climate change, regularities in their spatiotemporal variability in relation to water management, and the related threats.

Dr. Leszek Sobkowiak
Prof. Dr. Dariusz Wrzesiński
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

  • water resources
  • water use
  • surface water
  • ground water
  • variability
  • projections of change
  • water regime
  • seasonality
  • changes in lake water resources
  • modelling changes

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

51 pages, 16488 KiB  
Article
A CMIP6 Multi-Model Analysis of the Impact of Climate Change on Severe Meteorological Droughts through Multiple Drought Indices—Case Study of Iran’s Metropolises
by Rasoul Afsari, Mohammad Nazari-Sharabian, Ali Hosseini and Moses Karakouzian
Water 2024, 16(5), 711; https://0-doi-org.brum.beds.ac.uk/10.3390/w16050711 - 28 Feb 2024
Cited by 1 | Viewed by 675
Abstract
This study extensively explores the impact of climate change on meteorological droughts within metropolises in Iran. Focused on Tehran, Mashhad, Isfahan, Karaj, Shiraz, and Tabriz, this research employed CMIP6 climate models under varying climate change scenarios (SSPs) to forecast severe meteorological droughts spanning [...] Read more.
This study extensively explores the impact of climate change on meteorological droughts within metropolises in Iran. Focused on Tehran, Mashhad, Isfahan, Karaj, Shiraz, and Tabriz, this research employed CMIP6 climate models under varying climate change scenarios (SSPs) to forecast severe meteorological droughts spanning the period from 2025 to 2100. The investigation utilized a diverse set of drought indices (SPI, DI, PN, CZI, MCZI, RAI, and ZSI) to assess the drought severity in each city. This study is crucial as it addresses the pressing concerns of rapidly decreasing water levels in Iran’s dams, serious declines in underground aquifers, and the compounding issues of land subsidence and soil erosion due to excessive groundwater withdrawal in the face of severe droughts. This study culminated in the generation of box plots and heatmaps based on the results. These visual representations elucidated the distribution of the drought values under different indices and scenarios and provided a depiction of the probability of severe drought occurrences until the end of the century for each city. The resulting findings serve as invaluable tools, furnishing policymakers with informed insights to proactively manage and fortify metropolitan resilience against the evolving challenges posed by a changing climate. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources: Assessment and Modeling)
►▼ Show Figures

Figure 1

16 pages, 1841 KiB  
Article
Climate Change Impacts on Agricultural and Industrial Water Demands in the Beijing–Tianjin–Hebei Region Using Statistical Downscaling Model (SDSM)
by Qian Zhou, Yating Zhong, Meijing Chen and Weili Duan
Water 2023, 15(24), 4225; https://0-doi-org.brum.beds.ac.uk/10.3390/w15244225 - 08 Dec 2023
Cited by 1 | Viewed by 898
Abstract
As a politically and culturally important city cluster, the Beijing–Tianjin–Hebei (BTH) region is the most prominent area in China where the imbalance between the supply and demand of water resources restricts the sustainable and healthy development of the regional social economy. In the [...] Read more.
As a politically and culturally important city cluster, the Beijing–Tianjin–Hebei (BTH) region is the most prominent area in China where the imbalance between the supply and demand of water resources restricts the sustainable and healthy development of the regional social economy. In the context of global warming, research into water demand prediction that takes climate change into consideration would be more in line with the strategic goal of the low-carbon sustainable development of future cities. At the same time, the prediction of agricultural water demands against a background of climate change is urgently needed, while industrial water consumption is weakly correlated with climate change, an investigation of the statistical relationship between the two is needed. Thus, in this paper, future climate data from the BTH region under the scenarios RCP2.6, RCP4.5 and RCP8.5 were generated using a statistical downscaling model, and then coupled with agricultural and industrial water demand prediction models to simulate and analyze the impact of climate change on the agricultural and industrial water demands, respectively. The results show that during the forecast period (2020–2035), the reference crop evapotranspiration (ET0) growth rates in the Beijing, Tianjin and Hebei areas under the RCP2.6 scenario are 1.438 mm·a−1, 1.393 mm·a−1 and 2.059 mm·a−1, respectively. Under the RCP4.5 scenario, they are 2.252 mm·a−1, 2.310 mm·a−1 and 2.827 mm·a−1, respectively. Under the RCP8.5 scenario, they are 3.123 mm·a−1, 2.310 mm·a−1 and 2.141 mm·a−1, respectively. Furthermore, under each climate scenario, the increase in evapotranspiration in the Hebei area is the largest, followed by that in the Tianjin area, and that in the Beijing area is the smallest. For water consumption per CNY 10,000 of industrial added value during the forecast period, under the three different climate scenarios, a downward trend is seen in the Beijing area, with rates of 0.158, 0.153 and 0.110, respectively, but in the Tianjin area, there is an upward trend, with an upward tendency in rates of 0.170, 0.087 and 0.071, and an upward trend in the Hebei area, with an upward tendency in rates of 0.254, 0.071 and 0.036, respectively. This study will help the BTH region to rationally allocate agricultural and industrial water against the background of future climate change, and strengthen the coordination and cooperation between the different regions to promote the healthy and sustainable development of the cities. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources: Assessment and Modeling)
►▼ Show Figures

Figure 1

23 pages, 9255 KiB  
Article
Future Bioclimatic Change of Agricultural and Natural Areas in Central Europe: An Ultra-High Resolution Analysis of the De Martonne Index
by Ioannis Charalampopoulos, Fotoula Droulia, Ioannis P. Kokkoris and Panayotis Dimopoulos
Water 2023, 15(14), 2563; https://0-doi-org.brum.beds.ac.uk/10.3390/w15142563 - 13 Jul 2023
Cited by 3 | Viewed by 1079
Abstract
Bioclimate alteration unquestionably poses a current but also a potential future threat to natural and agricultural ecosystems and their services. In this scope, the present and future bioclimatic footprint of the Central European territory is investigated and presented. For the first time, an [...] Read more.
Bioclimate alteration unquestionably poses a current but also a potential future threat to natural and agricultural ecosystems and their services. In this scope, the present and future bioclimatic footprint of the Central European territory is investigated and presented. For the first time, an ultrahigh spatial resolution (<250 m) of the de Martonne index is analyzed over the entire area, as well as for individual countries (Austria, Switzerland, Czech Republic, Hungary and Slovakia). The research is performed for the reference period (1981–2010) and for three time series (2011–2040; 2041–2070; 2071–2100) under two emissions scenarios (SSP370 and SSP585) for the determination of the potential short-term and distant future bioclimatic change trends. Projection results reveal higher xerothermic trends over the lowland agricultural areas mostly in 2071–2100 and under the extreme SSP585, with the classes’ spatial distributions going from 0.0% to 2.3% for the semi-dry class and from 0.0% to 30.1% for the presiding Mediterranean class. Additionally, more than half of the territory’s agricultural surface area (53.4%) is foreseen to be depending on supplementary irrigation by 2100. Overall, more intense dry thermal conditions are expected to impact the agricultural areas of the Czech Republic, Slovakia and Hungary with the latter emerging as particularly vulnerable. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources: Assessment and Modeling)
►▼ Show Figures

Figure 1

23 pages, 16126 KiB  
Article
The Thermal State of the North Atlantic Ocean and Hydrological Droughts in the Warta River Catchment in Poland during 1951–2020
by Andrzej A. Marsz, Leszek Sobkowiak, Anna Styszyńska, Dariusz Wrzesiński and Adam Perz
Water 2023, 15(14), 2547; https://0-doi-org.brum.beds.ac.uk/10.3390/w15142547 - 12 Jul 2023
Viewed by 845
Abstract
This study presents the direct relationships between changes in the annual surface temperature of the North Atlantic (SST) and the number of days per year experiencing low flows in the Warta River catchment (WRC) in Central Europe, Poland, in the multi-annual period of [...] Read more.
This study presents the direct relationships between changes in the annual surface temperature of the North Atlantic (SST) and the number of days per year experiencing low flows in the Warta River catchment (WRC) in Central Europe, Poland, in the multi-annual period of 1951–2020. The number of days experiencing low flows (TLF) was used to describe the conditions of hydrological drought in the WRC. Moderately strong (r~0.5) but statistically highly significant (p < 0.001) relationships were found between TLF and the SST in the subtropical (30–40° N, 60–40° W) and subpolar North Atlantic (70° N, 10° W–10° E). With the increase in the annual SST in these parts of the North Atlantic, the number of days in a year experiencing low flows in the WRC also increased. It was determined that besides synchronous (i.e., in the same year) relationships between TLF and SST, asynchronous relations also occurred: the SST changes were one year ahead of the TLF changes. With the increase in the SST in the subtropical and subpolar North Atlantic, the sunshine duration and air temperature in the WRC increased, while the relative humidity decreased. The relationships between precipitation in the WRC and SST were negative (from −0.04 to −0.14), but statistically insignificant (p > 0.2). This indicates that the impact of SST changes on TLF in the WRC is mainly caused by the shaping of the amount of surface evaporation, which strongly increases in years of high SST, and the climatic water balance becomes negative, resulting in an increase in extremely low flows. The analysis of the causes of these relationships shows that the SST changes in the North Atlantic control, through changes in the height of the geopotential (h500), changes in the atmospheric circulation over Europe. In the periods of SST h500 growth over Central Europe, the atmospheric pressure (SLP) increases. That area is more frequently than average under the influence of the Azores High; this leads to an increase in the frequency of anticyclonic weather. A significant increase in the number of TLFs and prolonged periods of hydrological drought in the WRC after 2000 are associated with a strong increase in the SST in the area of the tropical and subtropical North Atlantic. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources: Assessment and Modeling)
►▼ Show Figures

Figure 1

15 pages, 6196 KiB  
Article
Flood-Triggering Rainfall and Potential Losses—The Copula-Based Approach on the Example of the Upper Nysa Kłodzka River
by Adam Perz, Dariusz Wrzesiński, Waldemar W. Budner and Leszek Sobkowiak
Water 2023, 15(10), 1958; https://0-doi-org.brum.beds.ac.uk/10.3390/w15101958 - 22 May 2023
Viewed by 4897
Abstract
Floods are natural phenomena, inextricably related to river regimes, which can threaten human health and life, the environment, cultural heritage, economic activity and infrastructure. The aim of the research is to assess the connection between rainfall and river flood risk. The proposed methodology [...] Read more.
Floods are natural phenomena, inextricably related to river regimes, which can threaten human health and life, the environment, cultural heritage, economic activity and infrastructure. The aim of the research is to assess the connection between rainfall and river flood risk. The proposed methodology is presented on the example of the upper Nysa Kłodzka River (NKR) catchment and Kłodzko town located on NKR, which are two of the most flood-prone areas in the Odra River basin. The methodology is based on the well-established methods of potential flood losses (PFL) estimation and the copula-based model, allowing an assessment of connections between rainfall and flood losses in a probabilistic way. The results are presented using the ‘synchronicity’ measure. Seventeen significant summer (rainfall-driven) flood waves were selected, for which PFL were estimated and cumulative rainfall was calculated for 24, 48, 72, 96 and 120 h preceding the flood peak. It was found that the synchronicity of PFL and the 24 h rainfall was the lowest among the analyzed variants, while for the 48 to 120 h rainfall the highest synchronicity was identified at precipitation gauge Podzamek. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources: Assessment and Modeling)
►▼ Show Figures

Figure 1

17 pages, 4191 KiB  
Article
Evaluation of Artificial Precipitation Enhancement Using UNET-GRU Algorithm for Rainfall Estimation
by Renfeng Liu, Huabing Zhou, Dejun Li, Liping Zeng and Peihua Xu
Water 2023, 15(8), 1585; https://0-doi-org.brum.beds.ac.uk/10.3390/w15081585 - 19 Apr 2023
Cited by 2 | Viewed by 1784
Abstract
The evaluation of the effects of artificial precipitation enhancement remains one of the most important and challenging issues in the fields of meteorology. Rainfall is the most important evaluation metric for artificial precipitation enhancement, which is mainly achieved through physics-based models that simulate [...] Read more.
The evaluation of the effects of artificial precipitation enhancement remains one of the most important and challenging issues in the fields of meteorology. Rainfall is the most important evaluation metric for artificial precipitation enhancement, which is mainly achieved through physics-based models that simulate physical phenomena and data-driven statistical models. The series of effect evaluation methods requires the selection of a comparison area for effect comparison, and idealized assumptions and simplifications have been made for the actual cloud precipitation process, leading to unreliable quantitative evaluation results of artificial precipitation effects. This paper proposes a deep learning-based method (UNET-GRU) to quantitatively evaluate the effect of artificial rainfall. By comparing the residual values obtained from inverting the natural evolution grid rainfall of the same area under the same artificial rainfall conditions with the actual rainfall amount after artificial rainfall operations, the effect of artificial rainfall can be quantitatively evaluated, effectively solving the problem of quantitative evaluation of artificial precipitation effects. Wuhan and Shiyan in China are selected to represent typical plains and mountainous areas, respectively, and the method is evaluated using 6-min resolution radar weather data from 2017 to 2020. During the experiment, we utilized the UNET-GRU algorithm and developed separate algorithms for comparison against common persistent baselines (i.e., the next-time data of the training data). The prediction of mean squared error (MSE) for these three algorithms was significantly lower than that of the baseline data. Moreover, the indicators for these algorithms were excellent, further demonstrating their efficacy. In addition, the residual results of the estimated 7-h grid rainfall were compared with the actual recorded rainfall to evaluate the effectiveness of artificial precipitation. The results showed that the estimated rainfall was consistent with the recorded precipitation for that year, indicating that deep learning methods can be successfully used to evaluate the impact of artificial precipitation. The results demonstrate that this method improves the accuracy of effect evaluation and enhances the generalization ability of the evaluation scheme. Full article
(This article belongs to the Special Issue Impacts of Climate Change on Water Resources: Assessment and Modeling)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop