Stochastic-based approach to quantify the uncertainty of groundwater vulnerability

Ni, Chuen-Fa; Vu, Tien Duc; Li, Wei-Ci; Tran, Minh-Tuan; Bui, Van-Cuong; Truong, Minh-Hoang

doi:10.1007/s00477-022-02372-2

Cited by 3 publications

(1 citation statement)

References 57 publications

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“…Indeed, the AHP method has seen extensive application in recent decades and has proven successful in mapping groundwater potential zones [12][13][14]. The AHP is a conventional index-overlay method that can predict groundwater vulnerability in different climate variations and human activities [15][16][17]. Applying the FE-AHP in mapping the GWPZ would improve the understanding of regional groundwater behavior in practical groundwater resource management.…”

Section: Introductionmentioning

confidence: 99%

Cost-Effective Groundwater Potential Mapping by Integrating Multiple Remote Sensing Data and the Index–Overlay Method

Nainggolan,

Ni,

Darmawan

et al. 2024

Remote Sensing

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The Choushui River groundwater basin (CRGB) in Yunlin County, Taiwan, is a significant groundwater source for the western part of the region. However, increasing groundwater demand and human activities have triggered a potential crisis due to overexploitation. Therefore, groundwater potential zone (GWPZ) maps are crucial for mapping groundwater resources and water resource management. This study employs the normalized index–overlay method and fuzzy extended analytical hierarchy process (FE-AHP) to map GWPZs cost-effectively. The methodology objectively incorporates weightings from various thematic layers by normalizing and correlating parameters with observed groundwater availability (GA). Site-specific observations, including aquifer thickness, depth to the groundwater level, and porosity, inform GA calculations. Seven comprehensive layers derived from remote sensing (RS) data are processed to obtain weightings and ratings for the groundwater potential index (GWPI) in the CRGB. Selected parameters are categorized into hydrological processes, human interventions, geological, and surface profiles. Hydrological processes include precipitation, modified normalized difference water index (MNDWI), and drainage density. Human interventions consist of the enhanced vegetation index (EVI) and normalized difference building index (NDBI). Surface profiles encompass the terrain ruggedness index (TRI) and slope, enhancing the study’s multi-criteria approach. The observed GA validates the GWPZ accuracy, classifying zones into five categories. According to the GWPI of FE-AHP, about 59.56% of the CRGB area can be categorized as “moderate” to “very good” potential groundwater recharge zones. Pearson’s correlation coefficient between GWPI and GA, based on FE-AHP, outperforms the conventional AHP. This RS-based approach efficiently evaluates GA in aquifers with limited wells, highlighting crucial zones in CRGB’s proximal-fan and southeastern mid-fan for informed groundwater management strategies.

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