A new approach for assessing the assembled vulnerability of coastal aquifers based on optimization models-Reference-Cited by-同舟云学术

A new approach for assessing the assembled vulnerability of coastal aquifers based on optimization models

Published:2023-10 Issue: Volume:625 Page:130084
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Gharekhani Maryam,Reza Nikoo Mohammad,Allah Nadiri Ata,Al-Rawas Ghazi,Sana Ahmad^ORCID,Gandomi Amir H.,Nematollahi Banafsheh^ORCID,Senapathi Venkatramanan^ORCID

Funder

Iran's National Elites Foundation

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference63 articles.

1. Aller, L., Bennet, T., Leher, J., Petty, R., Hackett, G., 1987. DRASTIC: A Standardized system for evaluating groundwater pollution potential using hydro-geological settings, Kerr Environmental Research Laboratory. U.S Environmental Protection Agency Report, (EPA/600/2-87/035).

2. Vulnerability assessment of urban groundwater resources to nitrate: the case study of Mashhad, Iran;Asadi;Environmental Earth Sciences,2017

3. Fuzzy vulnerability mapping of urban groundwater systems to nitrate contamination;Asadi;Environ. Model. Softw.,2017

4. A GIS-based DRASTICmodel for assessing aquifer vulnerability in Kakamigahara Heights, Gifu Prefecture, central Japan;Babiker;Sci. Total Environ.,2005

5. Spatial assessment of groundwater vulnerability using DRASTIC model with GIS in Uppar odai sub-watershed, Nandiyar, Cauvery Basin Tamil Nadu;Bhuvaneswaran;Groundwater for Sustainable Development,2019

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Coastal Zone Information Model: A comprehensive architecture for coastal digital twin by integrating data, models, and knowledge;Fundamental Research;2024-06

2. Risk Estimation of Surface Water Pollution in Vam Co Tay River Based on Remote Sensing Data and Multi-criteria Decision Analysis Methods;2024-03-25

3. Comparative study for coastal aquifer vulnerability assessment using deep learning and metaheuristic algorithms;Environmental Science and Pollution Research;2024-03-04

4. Assessing vulnerability of coastal aquifer to seawater intrusion using Convolutional Neural Network;Marine Pollution Bulletin;2023-12