干旱区生态环境知识资源中心(Arid): A Simulation-Optimization Modeling Approach for Conjunctive Water Use Management in a Semi-Arid Region of Iran

Arid

DOI	10.3390/su14052691
	A Simulation-Optimization Modeling Approach for Conjunctive Water Use Management in a Semi-Arid Region of Iran
	Kayhomayoon, Zahra; Milan, Sami Ghordoyee; Arya Azar, Naser; Bettinger, Pete; Babaian, Faezeh; Jaafari, Abolfazl
通讯作者	Milan, SG
来源期刊	SUSTAINABILITY
EISSN	2071-1050
出版年	2022
卷号	14 期号:5
英文摘要	Agricultural months are the critical period for the allocation of surface water and groundwater resources due to the increased demands on water supplies and decreased recharge rate. This situation urges the necessity of using conjunctive water management to fulfill the entire water demand. Here, we proposed an approach for aquifer stabilization and meeting the maximum water demand based on the available surface and groundwater resources and their limitations. In this approach, we first used the MODFLOW model to simulate the groundwater level to control the optimal withdrawal and the resulting drop. We next used a whale optimization algorithm (WOA) to develop an optimized model for the planning of conjunctive use to minimize the monthly water shortage. In the final step, we incorporated the results of the optimized conjunctive model and the available field data into the least squares-support vector machine (LS-SVM) model to predict the amounts of water shortage for each month, particularly for the agricultural months. The results showed that during the period from 2005 to 2020, the most water shortage belonged to 2018, in which only about 52% of water demand was met with the contribution of groundwater (67%) and surface water (33%). However, the groundwater level could have increased by about 0.7 m during the study period by implementing the optimized model. The results of the third part revealed that LS-SVM could predict the water shortage with better performance with a root-mean-square error (RMSE), mean absolute percentage error (MAPE), and Nash-Sutcliffe Index of 5.70 m, 3.43%, and 0.89 m, respectively. The findings of this study will enable managers to predict the water shortage in future periods to make more informed decisions for water resource allocation.
英文关键词	water management conjunctive use water supply optimization WOA LS-SVM machine learning
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000769308000001
WOS关键词	SURFACE-WATER ; GROUNDWATER ; SYSTEM ; WELL
WOS类目	Green & Sustainable Science & Technology ; Environmental Sciences ; Environmental Studies
WOS研究方向	Science & Technology - Other Topics ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/394548
推荐引用方式 GB/T 7714	Kayhomayoon, Zahra,Milan, Sami Ghordoyee,Arya Azar, Naser,et al. A Simulation-Optimization Modeling Approach for Conjunctive Water Use Management in a Semi-Arid Region of Iran[J],2022,14(5).
APA	Kayhomayoon, Zahra,Milan, Sami Ghordoyee,Arya Azar, Naser,Bettinger, Pete,Babaian, Faezeh,&Jaafari, Abolfazl.(2022).A Simulation-Optimization Modeling Approach for Conjunctive Water Use Management in a Semi-Arid Region of Iran.SUSTAINABILITY,14(5).
MLA	Kayhomayoon, Zahra,et al."A Simulation-Optimization Modeling Approach for Conjunctive Water Use Management in a Semi-Arid Region of Iran".SUSTAINABILITY 14.5(2022).