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Groundwater Potential Assessment in Gannan Region, China, Using the Soil and Water Assessment Tool Model and GIS-Based Analytical Hierarchical Process

Authors :
Zeyi Zhang
Shuangxi Zhang
Mengkui Li
Yu Zhang
Meng Chen
Qing Zhang
Zhouqing Dai
Jing Liu
Source :
Remote Sensing, Vol 15, Iss 15, p 3873 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

The Gannan region is situated in Ganzhou City, Jiangxi Province, China, and has a complicated geological background. Seasonal droughts significantly jeopardize the water security of the local population. Groundwater is essential to alleviate the region’s water needs. In this research, the groundwater potential (GWP) of the Gannan region was assessed using the Soil and Water Assessment Tool (SWAT) and the Analytical Hierarchical Process (AHP). The groundwater recharge and rainfall estimated by the SWAT model exhibited notable inconsistencies regarding their spatial distribution. Eight groundwater potential assessment factors (lithology, fault density, land use, slope, convergence index, drainage density, rainfall, and groundwater recharge) were constructed by integrating remote sensing, geological, and SWAT output data. Two GWP maps were constructed by an overlay analysis based on the obtained weights using the AHP, with the rainfall and groundwater recharge assigned the same weight to calculate the GWP with the other six factors separately. Each map was split into five classes: excellent, good, moderate, poor, and very poor. Data from 23 wells and 42 springs were collected to validate the two maps by correlation analysis between the GWP and flow rates of wells and springs. The correlation analysis result indicates that the GWP calculated by the recharge (R2 = 0.8 and 0.74, respectively) is more accurate than the GWP calculated by the rainfall (R2 = 0.21 and 0.48, respectively) and can provide a theoretical basis for groundwater management and exploration in the area.

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
15
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.5def163a83a042c791a23b7d7097c4db
Document Type :
article
Full Text :
https://doi.org/10.3390/rs15153873