MIF and AHP methods for delineation of groundwater potential zones using remote sensing and GIS techniques in Tirunelveli, Tenkasi District, India

被引:1
|
作者
Jebaraj, Samuel Prabaharan [1 ]
Rajagopal, Viji [2 ]
机构
[1] Francis Xavier Engn Coll, Dept Civil Engn, Tirunelveli 627003, Tamil Nadu, India
[2] Anna Univ, Dept Civil Engn, BIT Campus, Tiruchirappalli 620024, Tamil Nadu, India
来源
OPEN GEOSCIENCES | 2024年 / 16卷 / 01期
关键词
remote sensing; GIS; groundwater potential zones; data statistical analysis; AHP; MIF; geospatial mapping; TAMIL-NADU;
D O I
10.1515/geo-2022-0619
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
The present study aims to identify whether the delineation of potential groundwater potential zones (GWPZs) is essential for monitoring surface and conserving underground water resources. This study analysed the morphology of earth surface characteristics such as geomorphology, lineament density, lithology, slope, soil types, land use and land cover, drainage density, land surface temperature, normalized difference vegetation index, rainfall, and topographic wetness index parameters to delineate the potential groundwater zones. This article applies the analytical hierarchy process (AHP) and multi-influence factor (MIF) methods to identify potential groundwater zones in the Tirunelveli and Tenkasi districts of Tamil Nadu, India. In the AHP method, individual parameter's geometric mean and normalized weights were determined using the pair-wise matrix analytical method. Remote sensing-geographic information system (RS-GIS) techniques were used to generate thematic map layers from normalized weights to delineate GWPZs. The GWPZs were classified as Very Low, Low, Medium, High, and Very High. The result shows that the GWPZs were identified as 3.57, 0.55, 6.62, 58.09, and 31.21% in the study area for the five classes, respectively. In this study, the thematic maps were also prepared by assigning fixed scores and weights from the MIF approach. In the MIF approach, GWPZs were classified into five classes and identified as 3.16, 0.33, 2.14, 61.21, and 33.16% in the study area, respectively. GWPZ maps were evaluated for both MIF and AHP techniques using the Kappa statistics method with agreement values of 0.77 and 0.72%, respectively. This study's GIS-RS method is more proficient and efficient in delineating the GWPZs.
引用
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页数:16
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