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Climatic and Anthropogenic Impacts on Groundwater Resources and Adaptation Strategies

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Water Management".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 6665

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Prof. Dr. Yun Pan

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College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
Interests: satellite gravimetry; groundwater hydrology; terrestrial water storage change
Special Issues, Collections and Topics in MDPI journals

Dr. Yuyan Zhou

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Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Interests: climate change; water resources; adaptation
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Dr. Yicheng Gong

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Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Interests: groundwater environment; water resource management; hydrogeology

Dr. Jina Yin

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Guest Editor

Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210078, China
Interests: groundwater modeling; surface water-groundwater interaction; uncertainty quantification

Dr. Ya Huang

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Guest Editor

College of Oceanography, Hohai University, Nanjing 210098, China
Interests: water resources; climate changes; precipitation extremes; hydrological modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Groundwater is a critical resource globally, especially in arid and semiarid regions. However, these regions have been confronted by a changing climate, i.e., fluctuating precipitation patterns and increasing temperatures, altering hydrological processes such as groundwater recharge, storage and discharge. In particular, in climate-sensitive regions, for instance, high-latitude and high-altitude regions, interactions between surface water and groundwater are significantly affected by climate change, increasing water and food insecurity in downstream regions. Another factor impacting groundwater resources is human activity, e.g., population growth, industries consuming high amounts of water and widespread grain planting, all of which have greatly influenced the availability and sustainability of groundwater resources, leading to overexploitation of major aquifers globally, such as those in northwest India, California’s Central Valley and the North China Plain. Consequently, environmental and ecological degradation phenomena, e.g., shrinking water bodies (rivers, lakes and wetlands), land subsidence, salt-water intrusion, groundwater pollution, etc., have emerged as a result. Therefore, it is of great significance to implement adaptive water resources management strategies for groundwater protection. To this end, this Special Issue aims to promote the latest research on the potential impacts and risks of groundwater variations and strategies for water resource protection under changing climate and human activities across various climate and geophysical regions. Original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

Spatiotemporal variations in hydrogeological processes in a changing climate;
Innovations in hydrological observations, big data analysis and computing intelligence;
Impacts of extreme weather and climate events on geothermal heat exchanger;
Interactions between the surface and subsurface water systems;
Mechanism and modeling in hydrogeochemistry, contaminant hydrogeology;
Comprehensive groundwater governance and adaptation strategies.

We look forward to receiving your contributions.

Prof. Dr. Yun Pan
Dr. Yuyan Zhou
Dr. Yicheng Gong
Dr. Jina Yin
Dr. Ya Huang
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.

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Keywords

climate change
surface and groundwater interactions
hydrogeological processes
groundwater resources management
adaptative utilization of groundwater resources and other water sources
groundwater monitoring and observations
hydrological modeling
big data analysis and computing intelligence
hydrogeochemistry

Published Papers (6 papers)

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Research

23 pages, 3902 KiB

Open AccessArticle

Groundwater and Tourism: Analysis of Research Topics and Trends

by Oumaima Lamhour, Imane El Bouazzaoui, Dalia Perkumiené, Larbi Safaa, Marius Aleinikovas and Mindaugas Škėma

Sustainability 2024, 16(9), 3723; https://0-doi-org.brum.beds.ac.uk/10.3390/su16093723 - 29 Apr 2024

Viewed by 511

Abstract

Recent years have seen an increase in the popularity of exploring the correlation between groundwater and tourism as a research topic. Although previous studies have touched on certain aspects of this relationship, none has yet plunged to the heart of the matter. This Bibliometric study examines the literature on the relationship between tourism and groundwater in the overall context of economic development. The bibliometric tools VOS Viewer version 1.6.19 and R Bibliometrix were employed to analyze 104 publications selected via the Preferred Reporting Items for Systematic Reviews and Meta-Analyses diagram. The results suggest a growing interest in the subject and the need for broader and collaborative research, to fully understand these dynamics. Major contributions come from Spanish, American, Chinese, and Mexican authors, focusing on sustainability, anthropogenic impact, physical characteristics, and groundwater quality. In conclusion, this study provides an overview of the current research landscape, identifies trends and gaps, and encourages international collaboration for a better understanding of groundwater issues in the tourism context. Although our work provides very important knowledge, it should be recognized that the analysis is made only based on the Scopus-indexed literature. This restriction highlights the necessity for future research to do a more comprehensive and integrated bibliometric analysis. The array of research sources will thus definitely enhance the joint academic knowledge on that subject and lead to more inclusive and, therefore, higher-quality academic discourse. Full article

(This article belongs to the Special Issue Climatic and Anthropogenic Impacts on Groundwater Resources and Adaptation Strategies)

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23 pages, 4174 KiB

Open AccessArticle

Multi-Scale Analysis of Surface Building Density and Land Subsidence Using a Combination of Wavelet Transform and Spatial Autocorrelation in the Plains of Beijing

by Shuai Jiao, Xiaojuan Li, Jie Yu, Mingyuan Lyu, Ke Zhang, Yuehui Li and Pengyuan Shi

Sustainability 2024, 16(7), 2801; https://0-doi-org.brum.beds.ac.uk/10.3390/su16072801 - 27 Mar 2024

Viewed by 507

Abstract

Land subsidence is a major issue in the Beijing Plain in China, caused by the construction of new buildings and infrastructure combined with groundwater extraction. This study employs a multi-level two-dimensional wavelet decomposition to decompose land subsidence into high- and low-frequency components, and Moran’s I index to analyze the spatial distribution of land subsidence and its main influencing factors. By comparing the spatial distributions of the high- and low-frequency components, we estimate the correlation between land subsidence and influencing factors at different scales. Utilizing a combination of wavelet decomposition and Moran’s I analysis, our study establishes a clear spatial correlation between continuously varying factors such as groundwater and clay layer thickness, and the low-frequency components of land subsidence, allowing for a focused analysis of the relationship between surface building density and the high-frequency components of land subsidence. Quantitatively, the study identifies a significant correlation at specific granularities, particularly at 480 m and 960 m, underscoring the nuanced interaction between urban development and land subsidence patterns. These insights into the spatial distribution of land subsidence and its contributing factors can inform the development of effective strategies to address this issue. Full article

(This article belongs to the Special Issue Climatic and Anthropogenic Impacts on Groundwater Resources and Adaptation Strategies)

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16 pages, 2165 KiB

Open AccessArticle

Evaluation of Restoration Effect of Submerged Plant Community in Urban Rivers Replenished by Reclaimed Water

by Fei Xu, Xu Wang, Yonggang Wang, Changhong Sun, Jing Dong and Yacui Li

Sustainability 2023, 15(18), 13861; https://0-doi-org.brum.beds.ac.uk/10.3390/su151813861 - 18 Sep 2023

Viewed by 612

Abstract

Submerged plant community construction is extensively used in the field of urban river ecological restoration, but it is sometimes difficult to establish a large area of survival or a stable community after restoration. Therefore, there is some uncertainty in determining the restoration effect. To verify the restoration effect of urban rivers replenished by reclaimed water through the application of a submerged plant community, this paper takes the typical urban rivers with reclaimed water in Beijing, the Liangshui River and the Dalong River, as the research objects and takes the Yongding River, a river replenished by natural water, as the comparison to establish a water eco-environment quality index and carry out the restoration effect evaluation of a submerged plant community based on field monitoring. In a comparison of the water eco-environment quality index of rivers and the coverage of submerged plants, the evaluation results indicate that the Yongding River and Liangshui River have the same number of submerged plant species, yet their plant coverage is different. The ecological environment quality condition of the Yongding River is superior to that of the Liangshui River and the Dalong River. The ecological environment quality of the reclaimed water river segment with an average coverage of submerged plants greater than or equal to 50% is relatively better, with relatively more sensitive species. This suggests that for rivers replenished by reclaimed water, the construction of submerged plant communities will improve the water ecological conditions on the premise of ensuring a certain degree of submerged plant species and coverage. By calculating the correlation coefficients relating to the coverage of submerged plants by 32 environmental factors including the indicators of water quality, hydrology and sediment, the paper initially screens out water depth, ammonia nitrogen, nitrite nitrogen, BOD, permanganate index, and total nitrogen and organic carbon in the sediment as the major environmental factors affecting the coverage status of submerged plants. It can provide a reference for the control of environmental factors in the construction and maintenance of submerged plants to guarantee a restoration effect in the future. Full article

(This article belongs to the Special Issue Climatic and Anthropogenic Impacts on Groundwater Resources and Adaptation Strategies)

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18 pages, 7983 KiB

Open AccessArticle

Assessing the Impact of Climate Change on Water Usage in Typical Industrial Enterprises

by Jun Liu, Yuyan Zhou, Lihua Chen and Lichuan Wang

Sustainability 2023, 15(13), 10141; https://0-doi-org.brum.beds.ac.uk/10.3390/su151310141 - 26 Jun 2023

Viewed by 792

Abstract

Climate change and water scarcity are significant global issues both currently and in the future. Investigating the changes in industrial water usage under this backdrop holds crucial guidance for enabling adaptive changes within industries. It offers methods and case support for assessing the impact of climate on the water usage processes of industrial enterprises as well. This study employed a physical model to examine the impact of climate factors on the primary water consumption processes of a selected case of a coal-fired power plant. Additionally, by utilizing the ScenarioMIP experimental outcomes from CMIP6 models, the future water consumption processes were predicted under four different SSPs-RCPs scenarios. A relevant LSTM neural network was constructed based on the primary water consumption calculation to establish connections between the power generation process, meteorological process, water consumption process, and water intake process. Findings from the study reveal that the annual average primary water consumption showed a decreasing trend in different SSPs-RCPs scenarios. Specifically, there were reductions of 1600, 5300, 9000, and 11,400 t/year in each respective scenario from SSP1–2.6 to SSP5–8.5. Conversely, the water intake exhibited a gradual increase, with increments of 2000, 5600, 9200, and 10,000 t/year, respectively. Moreover, the impact of climate change on evaporation showed an annual decrease of less than 0.056%, while the increase in water intake was below 0.044%. Under the SSPs-RCPs scenarios, both water intake and consumption exhibited a gradually increasing trend with fluctuations ranging from 1–2.6 to 5–8.5. However, the annual trends remained relatively stable. It is crucial to acknowledge that climate change has amplified the uncertainty surrounding water intake and consumption. Industrial enterprises should proactively ensure the stability of their production processes in response to climate change. Full article

(This article belongs to the Special Issue Climatic and Anthropogenic Impacts on Groundwater Resources and Adaptation Strategies)

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21 pages, 14233 KiB

Open AccessArticle

Evaluating Spatiotemporal Variations of Groundwater–Surface Water Interaction Using an Integrated Hydrological Model in Huashan Basin, China

by Lu Zhang, Yunfeng Dai, Jin Lin, Jiangbo Han, Xiaomin Sun, Xue Li, Peng Liu and Aimin Liao

Sustainability 2022, 14(21), 14325; https://0-doi-org.brum.beds.ac.uk/10.3390/su142114325 - 02 Nov 2022

Cited by 5 | Viewed by 1369

Abstract

Quantifying the spatiotemporal variations of basin-scale surface water (SW)–groundwater (GW) interactions is vital for the conjunctive management of water resources in the basin. In this study, an integrated hydrological model (SWAT-MODFLOW) is used to simulate the SW–GW system in the Huashan Basin. The numerical model was calibrated and validated using the streamflow observations of the watershed outlet and the groundwater levels of the long-term monitoring wells from 2016 to 2020 in the study area. The model results show that the SWAT–MODFLOW can achieve a better fit for the streamflow discharge, compared with the results in the single SWAT model, with R² (coefficient of correlation) and NSE (Nash-Sutcliffe efficiency coefficient) of 0.85 and 0.83, respectively. The water table fitting results indicate that R² and RMSE can reach 0.95 and 0.88, respectively. The water budgets analysis demonstrates that the average rate (0.5281 m³/s) of GW abstraction to SW is larger than the rate (0.1289 m³/s) of SW recharge to GW. Moreover, the exchange rate of SW and GW gradually reaches a peak value from June to August, and the lowest value is shown in April, for each hydrological year. Based on the IPPC6 CanESM5 dataset supplied by the Canadian Climate Centre, the regional precipitation scenario subject to climate change was predicted by the ASD (Auto Statistical Downscaling Model) a statistical downscaling method, under the climate scenarios of SSP2_4.5 and SSP5_8.5. The SW–GW interaction pattern was modeled under the future scenarios in the study area. The current (2016–2020) average annual rate of the SW–GW interaction is considered as the base value. Subject to the SSP2_4.5 scenario, the average exchange rate of the SW recharge to GW is 0.1583 m³/s, which is an increase of 22.8%. The average exchange rate of the GW discharge to SW is 0.5189 m³/s which is a reduction of 0.017%. Subject to the SSP5_8.5 scenario, the average exchange rate of SW recharge to GW is 0.1469 m³/s, which is an increase of 14.7%. The average exchange rate of the GW discharge to SW is 0.5953 m³/s, which is an increases of 12.7%. The results can assist in water resource management in the basin, by identifying potential locations of nutrient transport from the aquifer to the river, as well as changes in spatial variability under future climatic conditions. Full article

(This article belongs to the Special Issue Climatic and Anthropogenic Impacts on Groundwater Resources and Adaptation Strategies)

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16 pages, 3299 KiB

Open AccessArticle

Daily Groundwater Level Prediction and Uncertainty Using LSTM Coupled with PMI and Bootstrap Incorporating Teleconnection Patterns Information

by Haibo Chu, Jianmin Bian, Qi Lang, Xiaoqing Sun and Zhuoqi Wang

Sustainability 2022, 14(18), 11598; https://0-doi-org.brum.beds.ac.uk/10.3390/su141811598 - 15 Sep 2022

Cited by 8 | Viewed by 1888

Abstract

Daily groundwater level is an indicator of groundwater resources. Accurate and reliable groundwater level (GWL) prediction is crucial for groundwater resources management and land subsidence risk assessment. In this study, a representative deep learning model, long short-term memory (LSTM), is adopted to predict groundwater level with the selected predictors by partial mutual information (PMI), and bootstrap is employed to generate different samples combination for training many LSTM models, and the predicted values by many LSTM models are used for the uncertainty assessment of groundwater level prediction. Two wells of different climate zones in the USA were used as a case study. Different significant predictors of GWL for two wells were identified by PMI from candidate predictors incorporating teleconnection patterns information. The results show that GWL is significantly affected by antecedent GWL, AO, Niño 3.4, Niño 1 + 2, and precipitation in humid areas, and by antecedent GWL, AO, Niño 3.4, Niño 3, Niño 1 + 2, and PNA in arid areas. Predictor selection can assist in improving the prediction performance of the LSTM model. The relationship between GWL and significant predictors were modeled by the LSTM model, and it achieved higher accuracy in humid areas, while the performance in arid areas was poorer due to limited precipitation information. The performance of LSTM was improved by increasing correlation coefficient (R²) values by 10% and 25% for 2 wells compared to generalized regression neural network (GRNN). Three uncertainty evaluation metrics indicate that LSTM reduced the uncertainty compared to GRNN model. LSTM coupling with PMI and bootstrap can be a promising approach for accurate and reliable groundwater level prediction for different climate zones. Full article

(This article belongs to the Special Issue Climatic and Anthropogenic Impacts on Groundwater Resources and Adaptation Strategies)

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