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The Impact of Climate Change on Water Resources

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

Deadline for manuscript submissions: closed (15 May 2024) | Viewed by 14184

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Dr. Mohamed Hamdi

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

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CARTEL—Centre d’Applications et de Recherches en Télédétection, Département de Géomatique Appliquée, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
Interests: remote sensing; radar; GRACE/GRACE-FO data; climate change; hydrological modeling
Special Issues, Collections and Topics in MDPI journals

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

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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

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Published Papers (10 papers)

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Research

14 pages, 3809 KiB

Open AccessArticle

Variations in the Thermal Low-Pressure Location Index over the Qinghai–Tibet Plateau and Its Relationship with Summer Precipitation in China

by Qingxia Xie, Mingfei Zhou, Yulei Zhu, Hongzhong Tang, Dongpo He, Jing Yang and Qingbing Pang

Atmosphere 2024, 15(8), 931; https://doi.org/10.3390/atmos15080931 - 4 Aug 2024

Viewed by 766

Abstract

The thermal and dynamic effects of the special topography of the Qinghai–Tibet Plateau have a significant impact on rainfall in China. Utilizing NCEP/NCAR monthly reanalysis data alongside precipitation observations from 1936 monitoring stations across China spanning from 1966 to 2022, this study establishes a location index for the thermal low-pressure center situated over the Qinghai–Tibet Plateau. Temporal variations in the location index and summer (July) precipitation patterns in China were studied. Over the past six decades, thermal low-pressure centers have been predominantly positioned near 90° E and 32.5° N within a geopotential height of 4360 gpm, with their distribution extending from east to west rather than from south to north. The longitudinal and latitudinal position indices showed the same linear trend, with a negative trend before the 21st century, and then began to turn positive. Mutation analysis highlights pronounced weakening mutations occurring in 1981 and 1973, with the longitudinal index transitioning from an interannual cycle of approximately 6–8 years, while the latitudinal index displays quasi-cyclic oscillations of 5 and 8 and 12–14 years. Strong negative correlations are evident between the location indices and precipitation along the southeastern edge of the Qinghai–Tibet Plateau and in southern China, contrasting with the positive correlations observed in the central-eastern plateau, northwest, north, and the Huang-Huai region of China. The center of the thermal low is located to the east and north, corresponding to the deeper surface thermal low in most areas east of China, and the stronger transport of warm and wet air from the southwest wind, leading to greater convergence of southwest wind and northwest wind in China’s northern region. The south of the Yangtze River is controlled by the strengthening West Pacific subtropical high and South Asia high, resulting in a significant decrease in precipitation, and the warm and humid air from the southwest on the west side of the West Pacific subtropical high is also transported to the north, increasing the precipitation in most parts of the north. Full article

(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)

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24 pages, 7939 KiB

Open AccessArticle

Quantifying the Impacts of Density-Dependent Flow on Surface Water–Groundwater Interaction in a Riparian Setup

by Shahab Doulabian, Amirhossein Shadmehri Toosi and Sina Alaghmand

Atmosphere 2024, 15(7), 795; https://doi.org/10.3390/atmos15070795 - 30 Jun 2024

Viewed by 875

Abstract

Surface Water–Groundwater (SW–GW) interaction is a crucial aspect of the hydrological cycle and requires accurate modeling for reliable predictions. In many basic hydrological models and calculations, it is common to assume that the water density is constant. However, density-dependent flow, which accounts for changes in water density, plays a significant role in various hydrological processes. This study aims to quantify the effects of density-dependent flow on SW–GW interaction and evaluate the sensitivity of dominant hydrological drivers to density-dependent flow. Our simulations using the HydroGeoSphere model revealed that neglecting density-dependent flow in SW–GW interaction can lead to inaccurate estimations of water and solute balances. In particular, including density-dependent flow in the model yielded more realistic salinity distributions under gaining river scenarios and captured the gradual expansion of freshwater lenses under losing river scenarios. The results also indicated that under non-density-dependent flow, more saline groundwater is exposed to evapotranspiration, resulting in higher solute mass storage and a more saline unsaturated zone. Further, surface recharge and pumping rates played crucial roles in salinity distribution. This study highlights the critical importance of incorporating density-dependent flow in simulations, providing valuable insights for improving the accuracy of predictions and effectively managing water and solute balances in floodplain aquifers. Full article

(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)

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28 pages, 2875 KiB

Open AccessArticle

Ocean Surface Warming and Long-Term Variability in Rainfall in Equatorial Pacific Atolls

by Ian White, Tony Falkland and Farran Redfern

Atmosphere 2024, 15(6), 666; https://doi.org/10.3390/atmos15060666 - 31 May 2024

Viewed by 574

Abstract

Freshwater availability in Pacific equatorial atolls is highly variable because of the influence of El Niño–Southern Oscillation (ENSO) on rainfall. IPCC projections for the central and western tropical Pacific suggest annual rainfall (P_a) will increase as sea surface temperature (SST) rises. Future changes in ENSO frequency and intensity and in hydrological droughts, however, are uncertain. Here, trends in monthly, seasonal, annual, annual maximum, and minimum rainfall in two equatorial atolls in the eastern and central tropical Pacific are compared with trends in the SST of the surrounding Nino regions from 1951 to 2023. Significant increasing trends in the warm season, annual, and annual maximum SST in the Nino1 + 2, Nino3, and Nino4 regions were of order +1.0 °C/100 y. There were no significant trends in the cool season or annual minimum SST. Despite ocean warming, there were no significant trends in atoll P_a, in intra-annual or interannual variability over 7 decades for either SST or P_a, or in the relative strengths of warm/cool and wet/dry seasons. Extreme, large P_a only occurred after 1987, indicative of ocean warming. Extreme, small P_a happened throughout the period, suggesting no change in drought frequency. Correlations between 12-month P and SST were very strong, with historic rates of increases in P_a of around 1200 mm/y/°C, consistent with projections. The results indicate that the recharge of atoll groundwater will increase as oceans warm, but droughts will remain a major challenge. Full article

(This article belongs to the Special Issue The Impact of Climate Change on Water Resources)

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21 pages, 5495 KiB

Open AccessEditor’s ChoiceArticle

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://doi.org/10.3390/atmos15030361 - 16 Mar 2024

Cited by 1 | Viewed by 1662

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 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

Open AccessArticle

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://doi.org/10.3390/atmos15030314 - 1 Mar 2024

Cited by 1 | Viewed by 1222

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 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

Open AccessArticle

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://doi.org/10.3390/atmos15030281 - 26 Feb 2024

Viewed by 2182

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 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

Open AccessArticle

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://doi.org/10.3390/atmos14121836 - 18 Dec 2023

Cited by 3 | Viewed by 1334

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 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

Open AccessArticle

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://doi.org/10.3390/atmos14121814 - 12 Dec 2023

Cited by 3 | Viewed by 1280

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) 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

Open AccessArticle

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://doi.org/10.3390/atmos14111624 - 29 Oct 2023

Viewed by 1289

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 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

Open AccessArticle

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://doi.org/10.3390/atmos14101514 - 29 Sep 2023

Cited by 2 | Viewed by 1489

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 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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