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Response of a Coastal Groundwater System to Natural and Anthropogenic Factors

Case Study on East Coast of Laizhou Bay, China

Bibliographic Data

ID15512292
AuthorsYa Sun (0000-0002-7318-4408, Dalian University of Technology), Shiguo Xu (0000-0002-2656-8628, Dalian University of Technology, corresponding author), Qin Wang (0000-0003-4488-3039, Dalian University of Technology), Suduan Hu (Dalian University of Technology), Guoshuai Qin (Dalian University of Technology), Huijuan Yu (0000-0003-3222-7608, Dalian University of Technology)
Year2020
Volume17
Issue14
Pages5204-5204
Publication date2020-07-18
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph17145204
PMID32708499
OpenAlexW3043729442
LanguageEN
References cited35

With a shifting climate pattern and enhancement of human activities, coastal areas are exposed to threats of groundwater environmental issues. This work takes the eastern coast of Laizhou Bay as a research area to study the response of a coastal groundwater system to natural and human impacts with a combination of statistical, hydrogeochemical, and fuzzy classification methods. First, the groundwater level dynamics from 1980 to 2017 were analyzed. The average annual groundwater level dropped 13.16 m with a descent rate of 0.379 m/a. The main external environmental factors that affected the groundwater level were extracted, including natural factors (rainfall and temperature), as well as human activities (irrigated area, water-saving irrigated area, sown area of high-water-consumption crops, etc.). Back-propagation artificial neural network was used to model the response of groundwater level to the above driving factors, and sensitivity analysis was conducted to measure the extent of impact of these factors on groundwater level. The results verified that human factors including irrigated area and water-saving irrigated area were the most important influencing factors on groundwater level dynamics, followed by annual precipitation. Further, groundwater samples were collected over the study area to analyze the groundwater hydrogeochemical signatures. With the hydrochemical diagrams and ion ratios, the formation of groundwater, the sources of groundwater components, and the main hydrogeochemical processes controlling the groundwater evolution were discussed to understand the natural background of groundwater environment. The fuzzy C-means clustering method was adopted to classify the groundwater samples into four clusters based on their hydrochemical characteristics to reveal the spatial variation of groundwater quality in the research area. Each cluster was spatially continuous, and there were great differences in groundwater hydrochemical and pollution characteristics between different clusters. The natural and human factors resulted in this difference were discussed based on the natural background of the groundwater environment, and the types and intensity of human activity

Geography · Groundwater · Hydrology (agriculture · Precipitation · Surface water · Environmental Science · Groundwater and Isotope Geochemistry · Hydrological Forecasting Using AI · Water Quality and Pollution Assessment · Environmental Engineering · Geology

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