GALDIT Modification for Seasonal Seawater Intrusion Mapping Using Multi Criteria Decision Making Methods

Abstract

Recently, coastal aquifers have been found to be increasingly exposed to seawater intrusion (SWI) due to climate change and anthropogenic activities. Various method exists for coastal aquifer vulnerability mapping and the one most commonly used is GALDIT because of its simplicity. The present study modified the original GALDIT ratings and weights using Shannon’s entropy theory to study the seasonal vulnerability of coastal aquifer in the coastal region of Benin, West Africa. Thus, the monthly GALDIT index for the study region was computed using 5 years of (2015–2019) average data of GALDIT dynamic input parameters. The original and modified GALDIT approaches were validated using total dissolved solid (TDS) concentration. Pearson’s correlation and Spearman coefficient correlations were calculated, and generally the modification of the GALDIT parameters’ relative weight using entropy has improved the method as this gave a better correlation with TDS concentration (0.739). From the calculated monthly GALDIT index, the most vulnerable period was identified using TOPSIS method. Based on TOPSIS results, the coastal aquifer of Benin is more vulnerable to seawater intrusion in February due to the decrease of groundwater level in that period and less vulnerable in July. The performed sensitivity analysis showed that height of groundwater level above the mean sea level, distance from shore, and thickness of the saturated aquifer have the most influence in vulnerability to SWI assessment in the study area.

Preliminary study of sea water intrusion using geographic information system in Temon, Kulon Progo, Yogyakarta, Indonesia

“…The obtained data were analyzed in situ, using parameters of electrical conductivity (EC), total dissolved solids (TDS), and salinity. These parameters are commonly used in Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktik dalam Bidang Pendidikan dan Ilmu Geografi 28(2), 2023, 193-208 seawater intrusion identification research (Gusman et al, 2020;Salem, Mountasir, & Shames, 2018;Simuningkalit & Lumbantoruan, 2016;Yang, Jeong, Agossou, Sohn, & Lee, 2022). The insitu analysis was carried out directly in the field.…”

Assessment of Pleistocene Aquifer Vulnerability to Saline Intrusion in the Coastal Region of Ba Ria-Vung Tau Province Using GIS and Entropy-GALDIT

“…In this study, the weights W i are calculated by the Entropy method to replace the basic weights in the GALDIT index of Chachadi [6], named Entropy-GALDIT. These steps are used to determine the entropy weights [16,17]:…”

“…It is utilized all over the world [15]. The GALDIT index with variable weights with respect to Entropy increases the index's ability to produce results that are more pertinent to actual conditions, reducing the uncertainty of the methodological framework for managing saline coastal aquifers [16,17]. In Iran, Mojgan Bordbar et al [16] improved the GALDIT index with Entropy weights integrated with GIS to map the vulnerability of the Gharesoo-Gorgan Rood coastal aquifer affected by seawater intrusion due to the overexploitation of groundwater.…”

“…The results demonstrated that areas affected by seawater intrusion into coastal aquifers can be more precisely identified using adjusted weights of GALDIT, given the actual conditions. Similarly, Jeong-Seok Yang et al [17] applied Entropy-GALDIT to examine the vulnerability of aquifers in coastal Benin, west Africa. According to the results, the height of the groundwater level above sea level, the distance from the shore to wells, and the thickness of the aquifer significantly influence the results of vulnerable zoning for saline intrusion.…”

Hydrogeologic Framework Model‐Based Numerical Simulation of Groundwater Flow and Salt Transport and Analytic Hierarchy Process‐Based Multi‐Criteria Evaluation of Optimal Pumping Location and Rate for Mitigation of Seawater Intrusion in a Complex Coastal Aquifer System

“…However, multi‐objective optimization modeling approaches also requires more numerical burdens and consumes more computational costs (i.e., times and storages) in addition to preceding or prerequisite numerical simulations of groundwater flow and salt transport (e.g., Fan et al., 2020; Lal & Datta, 2019; Nishikawa, 2018; Tabari & Abyar, 2022; Yang, Song, et al., 2021). As relatively simple and numerically more efficient alternatives, various multi‐criteria decision‐making or multi‐criteria ranking approaches have been successfully applied to mapping, assessing, and mitigating seawater intrusion in actual coastal aquifer systems (e.g., Azizi et al., 2019; Kazakis et al., 2018; Nasiri et al., 2021; Yang, Jeong, et al., 2022; Zghibi et al., 2020).…”