The Impact of Climate Change on Water Resources

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: 15 May 2024 | Viewed by 7292

Special Issue Editors


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Guest Editor
CARTEL—Centre d’Applications et de Recherches en Télédétection, Département de Géomatique Appliquée, Université de Sherbrooke, Québec, QC J1K 2R1, Canada
Interests: hydrogeology; remote sensing; MODFLOW; GRACE/GRACE-FO data; climate change; SWAT model

E-Mail Website
Guest Editor
CARTEL—Centre d’Applications et de Recherches en Télédétection, Département de Géomatique Appliquée, Université de Sherbrooke, Québec, QC J1K 2R1, Canada
Interests: remote sensing; radar; GRACE/GRACE-FO data; climate change; hydrological modeling

Special Issue Information

Dear Colleagues,

Recent hydrogeological research has confirmed that depletion is the most common problem for groundwater in many parts of the world. Indeed, climate change is leading to water scarcity in many regions due to a decline in heavy and erratic rainfall, flooding, prolonged droughts, changes in the water cycle, and other mechanisms that dependent on it. This situation is exacerbated in the aforementioned regions, characterized by scarce and irregular surface runoff. Groundwater is then the main resource in these regions; it is characterized by very low renewal rates and is extremely sensitive to climate change. 

The depletion of water resources has been the subject of several climatological, hydrological, and hydrogeological studies, which have shown that the status of the resource mainly depends on the internal architecture of aquifers, precipitation, and exploitation, which are mainly controlled by climate change. Therefore, it seems essential to understand the process and phenomena controlling the response of aquifer systems that are exposed to these global changes.

New visualization, processing, and modeling technologies, such as process-oriented methods and remote sensing data-driven methods, are now widely applied in hydrogeological studies. Hydrogeological and hydrological modeling is an increasingly used tool used to check the consistency of available data, for a better understanding and more reliable analysis of the complex responses of the hydrosystems facing climate change. The results that have emerged from the analysis of these works relate to the difficulties of acquiring reliable data and allow us to better account for the complexity of the systems. The objective of this Special Issue is to contribute to analyzing the relevance of new technologies of data acquisition (hydrogeological data and remote sensing data), interpretation, and processing, in order to better elucidate the impact of climate change on water resources.

Dr. Mohamed Hamdi
Dr. Kalifa Goïta
Guest Editors

Manuscript Submission Information

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Keywords

  • climate change
  • safe water
  • strategic water
  • precipitation
  • drought
  • flood
  • meteorological indices
  • remote-sensing-based drought indices
  • water resources management
  • process-oriented method (numerical modeling)
  • satellite data-driven method

Published Papers (7 papers)

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Research

21 pages, 5495 KiB  
Article
Assessment of Water Resources under Climate Change in Western Hindukush Region: A Case Study of the Upper Kabul River Basin
by Tooryalay Ayoubi, Christian Reinhardt-Imjela and Achim Schulte
Atmosphere 2024, 15(3), 361; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15030361 - 16 Mar 2024
Viewed by 950
Abstract
This study aims to estimate the surface runoff and examine the impact of climate change on water resources in the Upper Kabul River Basin (UKRB). A hydrological model was developed using the Soil and Water Assessment Tool (SWAT) from 2009 to 2019. The [...] Read more.
This study aims to estimate the surface runoff and examine the impact of climate change on water resources in the Upper Kabul River Basin (UKRB). A hydrological model was developed using the Soil and Water Assessment Tool (SWAT) from 2009 to 2019. The monthly calibration was conducted on streamflow in six stations for the period from 2010 to 2016, and the results were validated from 2017 to 2018 based on available observed data. The hydrological sensitivity parameters were further prioritized using SWAT-CUP. The uncertainty of the model was analyzed by the 95% Prediction Uncertainty (95PPU). Future projections were analyzed for the 2040s (2030–2049) and 2090s (2080–2099) compared to the baseline period (1986–2005) under two representation concentration pathways (RCP4.5, RCP8.5). Four Regional Climate Models (RCMs) were bias-corrected using the linear scaling bias correction method. The modeling results exhibited a very reasonable fit between the estimated and observed runoff in different stations, with NS values ranging from 0.54 to 0.91 in the calibration period. The future mean annual surface runoff exhibited an increase in the 2040s and 2090s compared to the baseline under both RCPs of 4.5 and 8.5 due to an increase in annual precipitation. The annual precipitation is projected to increase by 5% in the 2040s, 1% in the 2090s under RCP4.5, and by 9% in the 2040s and 2% in the 2090s under RCP8.5. The future temperature is also projected to increase and consequently lead to earlier snowmelt, resulting in a shift in the seasonal runoff peak to earlier months in the UKRB. However, the shifts in the timing of runoff could lead to significant impacts on water availability and exacerbate the water stress in this region, decreasing in summer runoff and increasing in the winter and spring runoffs. The future annual evapotranspiration is projected to increase under both scenarios; however, decreases in annual snowfall, snowmelt, sublimation, and groundwater recharge are predicted in the UKRB. Full article
(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)
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15 pages, 3518 KiB  
Article
Hydroclimate Changes Based on Testate Amoebae in the Greater Khingan Mountains’ Peatland (NE China) during the Last Millennium
by Xiao Li, Dongxue Han, Jinxin Cong, Chuanyu Gao and Guoping Wang
Atmosphere 2024, 15(3), 314; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15030314 - 01 Mar 2024
Viewed by 733
Abstract
The driving force of climate change in the monsoon margin is complex, making it a key area for regional and global climate change research. Palaeohydrological studies in the monsoon margin have increased the resolution of research in the long term, transitioning from qualitative [...] Read more.
The driving force of climate change in the monsoon margin is complex, making it a key area for regional and global climate change research. Palaeohydrological studies in the monsoon margin have increased the resolution of research in the long term, transitioning from qualitative to quantitative studies to comprehend climate change processes, patterns, and mechanisms. Testate amoebae (TA) in peat sediments are used as a proxy indicator organism for quantitative reconstruction of palaeohydrology. Thus, their community changes are directly related to precipitation, and widely used to reconstruct the patterns of summer precipitation globally. We investigated TA species and reconstructed palaeohydrological changes in the Greater Khingan Mountains’ Hongtu (HT) peatland, located in the East Asian Summer Monsoon (EASM) margin. The result showed that the most abundant TA species were Assulina muscorum (12.4 ± 5.0%) and Nebela tincta (8.9 ± 4.9%) in the HT peat core. The increase in dry indicator species (e.g., A. muscorum and Alabasta militaris) indicated a drying pattern in the HT peatland since 150 cal yr BP. Principal component analysis (PCA) explained 47.6% of the variation in the selected TA assemblages. During 400 to 250 cal yr BP, PCA axis 1 scores ranged from 0.2 to −1.3 (reflecting a drier climate), associating with the Little Ice Age. The paleohydrology of the northern part of the Greater Khingan Mountains was mainly controlled by the EASM, which was associated with changes in North Atlantic Sea surface temperature and solar radiative forcing. The apparent drying pattern may be the result of the gradual intensification of anthropogenic activities and the increase in EASM intensity. Full article
(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)
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18 pages, 3819 KiB  
Article
Evaluating the Effectiveness of Best Management Practices in Adapting the Impacts of Climate Change-Induced Urban Flooding
by Amrit Bhusal, Balbhadra Thakur, Ajay Kalra, Rohan Benjankar and Aruna Shrestha
Atmosphere 2024, 15(3), 281; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15030281 - 26 Feb 2024
Viewed by 942
Abstract
Floods are amongst the most destructive and costly natural disasters impacting communities around the globe. The severity and reoccurrence of flooding events have been more common in recent years as a result of the changing climate and urbanization. Best Management Practices (BMPs) are [...] Read more.
Floods are amongst the most destructive and costly natural disasters impacting communities around the globe. The severity and reoccurrence of flooding events have been more common in recent years as a result of the changing climate and urbanization. Best Management Practices (BMPs) are commonly used flood management techniques that aim to alleviate flooding and its impacts by capturing surface runoff and promoting infiltration. Recent studies have examined the effectiveness of BMPs in countering the effects of flooding; however, the performance of such strategies still needs to be analyzed for possible future climate change. In this context, this research employs climate model-driven datasets from the North American Regional Climate Change Assessment Program to evaluate the effects of climate change on urban hydrology within a study region by calculating historical and projected 6 h 100-year storm depths. Finally, the climate-induced design storms are simulated in the PCSWMM model, and the three BMP options (i.e., porous pavement, infiltration trench, and green roof) are evaluated to alleviate the impact of flooding events. This study quantifies the impact of changing climate on flood severity based on future climate models. The results indicate that peak discharge and peak volume are projected to increase by a range of 5% to 43% and 8% to 94%, respectively. In addition, the results demonstrated that green roofs, Permeable Pavement, and infiltration trenches help to reduce peak discharge by up to 7%, 14%, and 15% and reduce flood volume by up to 19%, 24%, and 29%, respectively, thereby presenting a promising solution to address the challenges posed by climate change-induced flooding events. Full article
(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)
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18 pages, 7034 KiB  
Article
Impact of Hydroclimatic Changes on Water Security in the Cantareira Water Production System, Brazil
by João Rafael Bergamaschi Tercini and Arisvaldo Vieira Mello Júnior
Atmosphere 2023, 14(12), 1836; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos14121836 - 18 Dec 2023
Viewed by 882
Abstract
The Cantareira Water Production System (CWPS), which supplies water to the most populous region in Brazil, is facing significant challenges due to hydroclimate change, thus threatening its water security. This research integrates data from climate models and field observations with hydrological modeling, aimed [...] Read more.
The Cantareira Water Production System (CWPS), which supplies water to the most populous region in Brazil, is facing significant challenges due to hydroclimate change, thus threatening its water security. This research integrates data from climate models and field observations with hydrological modeling, aimed at quantifying trends in key variables of the hydrological cycle. The GFDL-CM4 climate model, the most suitable for the study area, was employed to generate runoff data under both current conditions and future scenarios (SSP2-4.5 and SSP5-8.5). Our analysis reveals an increasing trend in the frequency of dry hydrological years. The Standard Precipitation Index (SPI) and Drought Magnitude (DM) confirm an increase in both the occurrence and duration of droughts in future scenarios. The runoff in all basins was reduced, causing a substantial decrease in minimum flows of 16.9%, medium flows of 11.8%, and high flows of 9.2% for the SSP5-8.5 scenario. This research introduces an approach to hydroclimate impact assessment, combining rigorous data analysis with advanced modeling techniques. Our findings not only provide a comprehensive understanding of the challenges faced by the CWPS, but also offer critical quantitative insights essential for developing effective public policies and adaptive strategies for sustainable water resource management. Full article
(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)
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19 pages, 7158 KiB  
Article
Quantifying Landscape Pattern–Hydrological Process Linkage in Northwest Iran
by Ali Rasoulzadeh, Raoof Mostafazadeh, Javanshir Azizi Mobaser, Nazila Alaei, Zeinab Hazbavi and Ozgur Kisi
Atmosphere 2023, 14(12), 1814; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos14121814 - 12 Dec 2023
Cited by 2 | Viewed by 826
Abstract
The enormous heterogeneity and complexity of landscape patterns and their linkage with the hydrological responses have rarely been quantified and cataloged, especially in ungauged regions. This research therefore linked the landscape characteristics to hydrological processes using a newly developed runoff landscape index (RLI) [...] Read more.
The enormous heterogeneity and complexity of landscape patterns and their linkage with the hydrological responses have rarely been quantified and cataloged, especially in ungauged regions. This research therefore linked the landscape characteristics to hydrological processes using a newly developed runoff landscape index (RLI) at the watershed scale in Ardabil Province, northwest Iran. First, 11 common landscape metrics were calculated using Fragstats 4.2.1 software. Then, a runoff landscape index (RLI) was developed based on land cover (λC), soil (λK), and topography (λS) factors in 28 watersheds. Correlation and regression analyses were also conducted to determine the relationship between RLI, commonly used landscape metrics, and mean base flow. The spatial variations of all meaningful landscape metrics and RLI were considerable throughout the study watersheds. The mean values of λC, λK, and λS were found to be 2.78 ± 1.08, 0.50 ± 0.10, and 1.22 ± 0.30, respectively. The mean RLI varied from 0.00009 in the Lay Watershed with an area of 19.09 km2 to 0.28 in the Boran Watershed with 10,268.95 km2. The correlation coefficient (r > 0.42; p-value < 0.05) was obtained significantly between RLI and only five landscape metrics, including the largest patch index (LPI), landscape shape index (LSI), landscape division index (DIVISION), splitting index (SPLIT), and Shannon’s diversity index (SHDI). In addition, a regression model with R2 of 0.97 and 0.67, respectively, in calibration and validation steps was established between river base flow as the dependent variable and main waterway length, LPI, LSI, SPLIT, modified Simpson’s diversity index (MSIDI), and λS as independent variables. The result confirms the significant interdependence of RLI and landscape characteristics, which can be used to interpret the landscape’s dynamic and its effects on hydrological processes. Full article
(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)
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26 pages, 6285 KiB  
Article
Semiarid Lakes of Southwestern Siberia as Sentinels of On-Going Climate Change: Hydrochemistry, the Carbon Cycle, and Modern Carbonate Mineral Formation
by Andrey Novoselov, Alexandr Konstantinov, Elizaveta Konstantinova, Yulia Simakova, Artem Lim, Alina Kurasova, Sergey Loiko and Oleg S. Pokrovsky
Atmosphere 2023, 14(11), 1624; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos14111624 - 29 Oct 2023
Viewed by 888
Abstract
Towards a better understanding of factors controlling carbon (C) exchange between inland waters and atmosphere, we addressed the inorganic carbon cycle in semiarid lakes of Central Eurasia, subjected to the strong impact of on-going climate change. As such, we assessed the hydrochemical variability [...] Read more.
Towards a better understanding of factors controlling carbon (C) exchange between inland waters and atmosphere, we addressed the inorganic carbon cycle in semiarid lakes of Central Eurasia, subjected to the strong impact of on-going climate change. As such, we assessed the hydrochemical variability and quantified its control on the formation of authigenic carbonate minerals, occurring within the upper layer of sediments in 43 semiarid lakes located in the southwest of Western Siberia (Central Eurasia). Based on measurements of pH, total dissolved solids (TDS), cationic and anionic composition, dissolved organic and inorganic C, as well as textural and mineralogical characterization of bottom sediments using X-ray diffraction and scanning electron microscopy, we demonstrate that lake water pH and TDS are primarily controlled by both the lithological and climatic context of the lake watershed. We have not revealed any direct relationships between lake morphology and water chemistry. The most common authigenic carbonates scavenging atmospheric CO2 in the form of insoluble minerals in lake sediments were calcite, aragonite, Mg-calcite, dolomite and hydromagnesite. The calcite was the most common component, aragonite mainly appears in lakes with sediments enriched in gastropod shells or artemia cysts, while hydromagnesite was most common in lakes with high Mg/Ca molar ratios, as well as at high DIC concentrations. The relationships between mineral formation and water chemistry established in this study can be generalized to a wide suite of arid and semiarid lakes in order to characterize the current status of the inorganic C cycle and predict its possible modification under on-going climate warming such as a rise water temperature and a change in hydrological connectivity, primary productivity and nutrient regime. Full article
(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)
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18 pages, 4155 KiB  
Article
Evaluating Drought Effects on Soil: Innovative Soil Salinity Monitoring via SAR Data, Sentinel-2 Imagery, and Machine Learning Algorithms in Kerkennah Archipelago
by Sarra Hihi, Rim Katlane, Boubaker Kilani, Mohamed Waddah Zekri, Rafik Bensalah, Christian Siewert and Monem Kallel
Atmosphere 2023, 14(10), 1514; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos14101514 - 29 Sep 2023
Viewed by 973
Abstract
The Kerkennah archipelago in Tunisia is one of the most vulnerable areas where the influence of climate change is undeniable. Soil salinization has emerged as a major consequence of climate variation on this island. In this study, remote sensing techniques were implemented to [...] Read more.
The Kerkennah archipelago in Tunisia is one of the most vulnerable areas where the influence of climate change is undeniable. Soil salinization has emerged as a major consequence of climate variation on this island. In this study, remote sensing techniques were implemented to develop a model for predicting soil salinity from satellite images. Machine learning algorithms, Sentinel-1 and Sentinel-2 data, and ground truth measurements were used to estimate soil salinity. Several algorithms were considered to achieve accurate findings. These algorithms are categorized as polynomial regression, random forest regression, exponential regression, and linear regression. The results demonstrate that exponential regression is the pre-eminent algorithm for estimating soil salinity with high predictive accuracy of R2 = 0.75 and RMSE = 0.47 ds/m. However, spatiotemporal soil salinity maps reveal distinct and clear distribution patterns, highlighting salty areas (i.e., sebkhas) and agricultural parcels. Thus, through the model, we explore areas of moderately high salinity within agricultural lands that could be affected by irrigation practices. The present work demonstrates a reliable model for soil salinity monitoring in the Kerkennah archipelago and inspires more successful technologies such as remote sensing and machine learning to improve the estimation of soil salinity in climate-affected vulnerable areas. Full article
(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)
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