Identification and mapping of groundwater recharge zones using multi influencing factor and analytical hierarchy process

被引:15
作者
Meng, Fanxiao [1 ]
Khan, Muhammad Ismail [2 ]
Naqvi, Syed Ali Asad [3 ]
Sarwar, Abid [2 ,5 ]
Islam, Fakhrul [4 ]
Ali, Muhammad [5 ]
Tariq, Aqil [6 ]
Ullah, Sajid [7 ]
Soufan, Walid [8 ]
Faraj, Turki Kh. [9 ]
机构
[1] Fujian Normal Univ, Southern Biomed Res Ctr, Fuzhou 350117, Peoples R China
[2] GIS Lab, Directorate Gen Soil & Water Conservat, Peshawar 25000, Khyber Pakhtunk, Pakistan
[3] Univ Faisalabad, Govt Coll, Dept Geog, Faisalabad 38000, Punjab, Pakistan
[4] Khushal Khan Khattak Univ, Dept Geol, Khyber Pakhtunkhwa 27200, Pakistan
[5] Univ Peshawar, Natl Ctr Excellence Geol, Peshawar 25000, Pakistan
[6] Mississippi State Univ, Coll Forest Resources, Dept Wildlife Fisheries & Aquaculture, 775 Stone Blvd, Mississippi State, MS 39762 USA
[7] Nangarhar Univ, Dept Water Resources & Environm Engn, Jalalabad 2600, Nangarhar, Afghanistan
[8] King Saud Univ, Coll Food & Agr Sci, Plant Prod Dept, Riyadh 11451, Saudi Arabia
[9] King Saud Univ, Coll Food & Agr Sci, Dept Soil Sci, Riyadh 11451, Saudi Arabia
关键词
Remote Sensing and GIS; Multi influencing factor; Sensitivity analysis; Groundwater recharge zones; Analytical hierarchy procedure; GEOGRAPHICAL INFORMATION-SYSTEM; REMOTE-SENSING DATA; POTENTIAL ZONES; DECISION-MAKING; TAMIL-NADU; GIS; DISTRICT; MODEL; INDIA; AHP;
D O I
10.1038/s41598-024-70324-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The management of groundwater systems is essential for nations that rely on groundwater as the principal source of communal water supply (e.g., Mohmand District of Pakistan). The work employed Remote Sensing and GIS datasets to ascertain the groundwater recharge zones (GWRZ) in the Mohmand District of Pakistan. Subsequently, a sensitivity analysis was conducted to examine the impact of geology and hydrologic factors on the variability of the GWRZ. The GWRZ was determined by employing weighted overlay analysis on thematic maps derived from datasets about drainage density, slope, geology, rainfall, lineament density, land use/land cover, and soil types. The use of multi-criteria decision analysis (MCDA) involves the utilization of the multi-influencing factor (MIF) and analytical hierarchy procedure (AHP) to allocate weights to the selected influencing factors. The MIF data found that very high groundwater recharge spanned 1.20%, high zones covered 40.44%, moderate zones covered 50.81%, and low zones covered 7.54%. In comparison, the AHP technique results suggest that 1.81% of the whole area is very high, 33.26 is high, 55.01% is moderate, and 9.92% has low groundwater potential. The geospatial-assisted multi-influencing factor approach helps increase conceptual knowledge of groundwater resources and evaluate possible groundwater zones.
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页数:17
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