淡江大學機構典藏:Item 987654321/117054
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    Title: Modeling and investigating the mechanisms of groundwater level variation in the Jhuoshui River Basin of Central Taiwan
    Authors: Tao Bai;Wen-Ping Tsai;Yen-Ming Chiang;Fi-John Chang;Wan-Yu Chang;Li-Chiu Chang;Kuang-Chih Chang
    Keywords: groundwater level;recharge groundwater;Gamma test (GT);accumulated rainfall;artificial neural networks (ANNs)
    Date: 2019-07-27
    Issue Date: 2019-09-19 12:10:51 (UTC+8)
    Publisher: MDPI
    Abstract: Due to nonuniform rainfall distribution in Taiwan, groundwater is an important water source in certain areas that lack water storage facilities during periods of drought. Therefore, groundwater recharge is an important issue for sustainable water resources management. The mountainous areas and the alluvial fan areas of the Jhuoshui River basin in Central Taiwan are considered abundant groundwater recharge regions. This study aims to investigate the interactive mechanisms between surface water and groundwater through statistical techniques and estimate groundwater level variations by a combination of artificial intelligence techniques and the Gamma test (GT). The Jhuoshui River basin in Central Taiwan is selected as the study area. The results demonstrate that: (1) More days of accumulated rainfall data are required to affect variable groundwater levels in low-permeability wells or deep wells; (2) effective rainfall thresholds can be properly identified by lower bound screening of accumulated rainfall; (3) daily groundwater level variation can be estimated effectively by artificial neural networks (ANNs); and (4) it is difficult to build efficient models for low-permeability wells, and the accuracy and stability of models is worse in the proximal-fan areas than in the mountainous areas.
    Relation: Water 11(8)
    DOI: 10.3390/w11081554
    Appears in Collections:[Graduate Institute & Department of Water Resources and Environmental Engineering] Journal Article

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