A fuzzy logic-based approach for groundwater vulnerability assessment

Nourani, Vahid; Maleki, Sana; Najafi, Hessam; Baghanam, Aida Hosseini

doi:10.1007/s11356-023-26236-6

Cited by 10 publications

(1 citation statement)

References 48 publications

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“…FOA method in ArcGIS combines multiple layers of geographic data with uncertain boundaries using fuzzy logic. Fuzzy logic assigns membership values between 0 and 1 to features based on their degree of belongingness to speci c classes (Nourani et al, 2023). Operations like intersection, union, or difference are performed on fuzzy sets, considering these membership values (Atagün and Kamacı, 2023).…”

Section: Fuzzy Overlay Analysis (Foa)mentioning

confidence: 99%

Comparative Assessment of Analytical Hierarchy Process (AHP) and Fuzzy Overlay Analysis (FOA) Models in Groundwater Potential Zone Mapping Using Sensitive Analysis: A GIS-RS Integrated Approach

Gandhi,

Songara,

Prakash

et al. 2024

Preprint

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This study addresses the pressing need for assessing groundwater potential in diverse regions worldwide, emphasizing the challenges posed by industrialization and urban expansion. Leveraging remote sensing (RS) data within an ArcGIS framework, a comparison was conducted on the effectiveness of the Analytical Hierarchy Process (AHP) and Fuzzy Overlay Analysis (FOA) models in delineating groundwater potential zones. Ten influencing factors underwent rigorous multicollinearity checks to ensure independent analysis. Both methodologies categorized the output into five classification zones, revealing variations between methods. The sensitivity analysis identified specific influential layers for each method, showcasing heightened sensitivity in assessing groundwater potential zones. Notably, AHP emphasized factors such as NDWI, Lineament density, and Land Use Land Cover (LULC), while FOA prioritized Soil Texture, Lineament Density, and NDWI. Evaluating the reliability of groundwater potential assessments, AHP demonstrated fair agreement (59.18%), while FOA exhibited substantial agreement (77.5%). FOA emerged as superior, offering a more nuanced and precise representation of spatial relationships and uncertainties. The promising performance of FOA in our study suggests its potential applicability in accurate groundwater potential assessment beyond the study area (India) to other countries regions with heterogeneous hydrogeological conditions.

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Section: Fuzzy Overlay Analysis (Foa)mentioning

confidence: 99%