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利用多影响因素和层次分析法识别与绘制地下水补给区

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

作者信息

Meng Fanxiao, Khan Muhammad Ismail, Naqvi Syed Ali Asad, Sarwar Abid, Islam Fakhrul, Ali Muhammad, Tariq Aqil, Ullah Sajid, Soufan Walid, Faraj Turki Kh

机构信息

Southern Biomedical Research Center, Fujian Normal University, Fuzhou, 350117, China.

GIS Lab, Directorate General Soil & Water Conservation, Peshawar, 25000, Khyber Pakhtunkhwa, Pakistan.

出版信息

Sci Rep. 2024 Aug 20;14(1):19240. doi: 10.1038/s41598-024-70324-7.

Abstract

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.

摘要

对于依赖地下水作为公共供水主要来源的国家(如巴基斯坦的莫赫曼德地区)而言,地下水系统管理至关重要。该研究利用遥感和地理信息系统数据集来确定巴基斯坦莫赫曼德地区的地下水补给区(GWRZ)。随后,进行了敏感性分析,以研究地质和水文因素对GWRZ变异性的影响。GWRZ是通过对从排水密度、坡度、地质、降雨、线性构造密度、土地利用/土地覆盖和土壤类型等数据集得出的专题地图进行加权叠加分析来确定的。多标准决策分析(MCDA)的应用涉及利用多影响因素(MIF)和层次分析法(AHP)为选定的影响因素分配权重。MIF数据显示,极高地下水补给区占1.20%,高补给区占40.44%,中等补给区占50.81%,低补给区占7.54%。相比之下,AHP技术结果表明,整个区域中1.81%为极高,33.26%为高,55.01%为中等,9.92%的地下水潜力较低。地理空间辅助多影响因素方法有助于增加对地下水资源的概念性认识,并评估可能的地下水区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e2f/11335863/18feb9aec2ec/41598_2024_70324_Fig1_HTML.jpg

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