干旱区生态环境知识资源中心(Arid): Progressive improvement of DRASTICA and SI models for groundwater vulnerability assessment based on evolutionary algorithms

Arid

DOI	10.1007/s11356-022-19620-1
	Progressive improvement of DRASTICA and SI models for groundwater vulnerability assessment based on evolutionary algorithms
	Zare, Masoumeh; Nikoo, Mohammad Reza; Nematollahi, Banafsheh; Gandomi, Amir H.; Al-Wardy, Malik; Al-Rawas, Ghazi Ali
通讯作者	Nikoo, MR
来源期刊	ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
ISSN	0944-1344
EISSN	1614-7499
出版年	2022
卷号	29 期号:37 页码:55845-55865
英文摘要	Groundwater management is essential in water and environmental engineering from both quantity and quality aspects due to the growing urban population. Groundwater vulnerability evaluation models play a prominent role in groundwater resource management, such as the DRASTIC model that has been used successfully in numerous areas. Several studies have focused on improving this model by changing the initial parameters or the rates and weights. The presented study investigated results produced by the DRASTIC model by simultaneously exerting both modifications. For this purpose, two land use-based DRASTIC-derived models, DRASTICA and susceptibility index (SI), were implemented in the Shiraz plain, Iran, a semi-arid region and the primary resource of groundwater currently struggling with groundwater pollution. To develop the novel proposed framework for the progressive improvement of the mentioned rating-based techniques, three main calculation steps for rates and weights are presented: (1) original rates and weights; (2) modified rates by Wilcoxon tests and original weights; and (3) adjusted rates and optimized weights using the genetic algorithm (GA) and particle swarm optimization (PSO) algorithms. To validate the results of this framework applied to the case study, the concentrations of three contamination pollutants, NO3, SO4, and toxic metals, were considered. The results indicated that the DRASTICA model yielded more accurate contamination concentrations for vulnerability evaluations than the SI model. Moreover, both models initially displayed well-matched results for the SO4 concentrations, specifically 0.7 for DRASTICA and 0.58 for SI, respectively. Comparatively, the DRASTICA model showed a higher correlation with NO3 concentrations (0.8) than the SI model (0.6) through improved steps. Furthermore, although both original models demonstrated less correlation with toxic metal concentrations (0.05) compared to SO4 and NO3 concentrations, the DRASTICA and SI models with modified rates and optimized weights exhibited enhanced correlation with toxic metals of about 0.7 and 0.2, respectively.
英文关键词	Groundwater vulnerability index DRASTICA SI Genetic algorithm Particle swarm optimization Wilcoxon test
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000772315900020
WOS关键词	COASTAL AQUIFER ; CONTAMINATION ; OPTIMIZATION ; POLLUTION
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/392520
推荐引用方式 GB/T 7714	Zare, Masoumeh,Nikoo, Mohammad Reza,Nematollahi, Banafsheh,et al. Progressive improvement of DRASTICA and SI models for groundwater vulnerability assessment based on evolutionary algorithms[J],2022,29(37):55845-55865.
APA	Zare, Masoumeh,Nikoo, Mohammad Reza,Nematollahi, Banafsheh,Gandomi, Amir H.,Al-Wardy, Malik,&Al-Rawas, Ghazi Ali.(2022).Progressive improvement of DRASTICA and SI models for groundwater vulnerability assessment based on evolutionary algorithms.ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,29(37),55845-55865.
MLA	Zare, Masoumeh,et al."Progressive improvement of DRASTICA and SI models for groundwater vulnerability assessment based on evolutionary algorithms".ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 29.37(2022):55845-55865.