New hybrid-based approach for improving the accuracy of coastal aquifer vulnerability assessment maps

Khabat Khosravi; Mojgan Bordbar; Sina Paryani; Patricia M Saco; Nerantzis Kazakis

doi:10.1016/j.scitotenv.2021.145416

New hybrid-based approach for improving the accuracy of coastal aquifer vulnerability assessment maps

Sci Total Environ. 2021 May 1:767:145416. doi: 10.1016/j.scitotenv.2021.145416. Epub 2021 Jan 27.

Authors

Khabat Khosravi¹, Mojgan Bordbar², Sina Paryani², Patricia M Saco³, Nerantzis Kazakis⁴

Affiliations

¹ Department of Watershed Management Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.
² Department of GIS/RS, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Iran.
³ Civil, Surveying and Environmental Engineering and Centre for Water Security and Environmental Sustainability, The University of Newcastle, Australia.
⁴ Aristotle University of Thessaloniki, Department of Geology, Lab. of Engineering Geology & Hydrogeology, 54124 Thessaloniki, Greece. Electronic address: kazakis@geo.auth.gr.

PMID: 33636786
DOI: 10.1016/j.scitotenv.2021.145416

Abstract

Due to excessive exploitation, groundwater resources of coastal regions are exposed to seawater intrusion. Therefore, vulnerability assessments are essential for the quantitative and qualitative management of these resources. The GALDIT model is the most widely used approach for coastal aquifer vulnerability assessment, but suffers from subjectivity of the identification of rates and weights. This study aimes at developing a new hybrid framework for improving the accuracy of coastal aquifer vulnerability assessment using various statistical, metaheuristic, and Multi-Attribute Decision Making (MADM) methods to improve the GALDIT model. The Gharesoo-Gorgan Rood coastal aquifer in northern Iran is used as study site. In order to meet this aim, the Differential Evolution (DE) and Biogeography-Based Optimization (BBO) metaheuristic algorithms were employed to optimize the GALDIT weights. In addition, a novel MADM method, named Step-wise Weight Assessment Ratio Analysis (SWARA), and the bivariate statistical method called statistical index (SI) were used to modify the GALDIT ratings. Finally, correlation coefficients between the maps obtained from each method and Total Dissolved Solid (TDS) as an indicator of seawater intrusion were computed to evaluate the models' prediction power. Correlation coefficients of 0.72, 0.75, 0.76 and 0.78 were obtained for the GALDIT_SWARA-BBO, GALDIT_SI-BBO, GALDIT_SWARA-DE and GALDIT_SI-DE models, respectively. The results from the GALDIT_SI-DE model outperformed all other models at improving the accuracy of the vulnerability assessment. Moreover, the statistical-metaheuristic method yielded more accurate results than SWARA-metaheuristic hybrid models. The vulnerability map of the studied region indicates that the northwestern and western areas are very highly vulnerable. According to GALDIT_SI-DE model, 42%, 17%, 18% and 22% of the aquifer areas respectively have a low, medium, high and very high vulnerability to seawater intrusion. The research findings could be applied by regional authorities to manage and protect groundwater resources.

Keywords: BBO; Coastal aquifer; DE; GALDIT; MADM; SI.