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Moradi Nazar Poor, sajjad, Jafari, Hadi. (1404). Predicting Groundwater Capture Zone Characteristics Using Fuzzy Inference System(FIS), Case study: Abarkooh Aquife. , 15(2), 315-322. doi: 10.22059/geope.2025.382188.648788
sajjad Moradi Nazar Poor; Hadi Jafari. "Predicting Groundwater Capture Zone Characteristics Using Fuzzy Inference System(FIS), Case study: Abarkooh Aquife". , 15, 2, 1404, 315-322. doi: 10.22059/geope.2025.382188.648788
Moradi Nazar Poor, sajjad, Jafari, Hadi. (1404). 'Predicting Groundwater Capture Zone Characteristics Using Fuzzy Inference System(FIS), Case study: Abarkooh Aquife', , 15(2), pp. 315-322. doi: 10.22059/geope.2025.382188.648788
Moradi Nazar Poor, sajjad, Jafari, Hadi. Predicting Groundwater Capture Zone Characteristics Using Fuzzy Inference System(FIS), Case study: Abarkooh Aquife. , 1404; 15(2): 315-322. doi: 10.22059/geope.2025.382188.648788

Predicting Groundwater Capture Zone Characteristics Using Fuzzy Inference System(FIS), Case study: Abarkooh Aquife

Geopersia
دوره 15، شماره 2 - شماره پیاپی 22287825، بهمن 2025، صفحه 315-322    اصل مقاله (1.3 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/geope.2025.382188.648788
نویسندگان
sajjad Moradi Nazar Poor* 1؛ Hadi Jafari2
1Faculty of earth Sciences, Shiraz university, Iran
2Faculty of Earth Sciences, Shahrood University of Technology, Shahrood, Iran
چکیده
Groundwater is a vital resource for human water supply, making the study of well capture zones critical, particularly for anthropogenic water sources and water quality management. Capture zones, also known as wellhead protection areas, are influenced by numerous factors, including pumping rate, hydraulic conductivity, groundwater gradient, and other hydrogeological parameters. Various methods exist for calculating capture zones, ranging from analytical approaches to advanced numerical models, and these methods continue to evolve. This research introduces, for the first time, the application of a Fuzzy Inference System (FIS) to predict both the size and elongation of capture zones. Key input parameters include annual well discharge (measured in million cubic meters, MCM), hydraulic conductivity, groundwater gradient, and aquifer thickness. Results from the WhAEM software were used as target values to validate the FIS predictions. The findings reveal strong correlations between the FIS predictions and the WhAEM results, with correlation
coefficients (R) of 0.92 for capture zone size and 0.73 for elongation coefficient. These results underscore the effectiveness of fuzzy logic in accurately predicting critical hydrogeological parameters, offering a robust alternative method for capture zone analysis. These results underscore the effectiveness of fuzzy logic in accurately predicting critical hydrogeological parameters, offering a robust alternative method for capture zone analysis.
کلیدواژه‌ها
Fuzzy inference system؛ Elongation coefficient؛ Capturer zone؛ Abarkooh
مراجع
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