干旱区生态环境知识资源中心(Arid): A New Approach for Regional Groundwater Level Simulation: Clustering, Simulation, and Optimization

Arid

DOI	10.1007/s11053-021-09913-6
	A New Approach for Regional Groundwater Level Simulation: Clustering, Simulation, and Optimization
	Kayhomayoon, Zahra; Milan, Sami Ghordoyee; Azar, Naser Arya; Moghaddam, Hamid Kardan
通讯作者	Kayhomayoon, Z (corresponding author), Payame Noor Univ, Dept Geol, Tehran, Iran.
来源期刊	NATURAL RESOURCES RESEARCH
ISSN	1520-7439
EISSN	1573-8981
出版年	2021
英文摘要	In this study, a new 3-stage approach that consists of clustering, simulation, and optimization stages is proposed for the simulation of groundwater level (GWL) in an arid region of eastern Iran. In the first stage, K-means clustering was used to divide the study aquifer into five different clusters based on precipitation, water recharge, water discharge, transmissivity, earth level, and water table. In the second stage, to simulate GWL in each cluster, several input variables, such as water level at the previous month, aquifer discharge, aquifer recharge, evaporation, temperature, and precipitation, were used in the form of various input patterns that were fed to an artificial neural network (ANN). Finally, in the third stage, two advanced optimization methods, i.e., particle swarm optimization (PSO) and whale optimization algorithm (WOA), were utilized to optimize the ANN results. Various patterns were identified as suitable clusters based on the studied models. A pattern including water level at the previous month, aquifer discharge, aquifer recharge, and precipitation was identified as the best model for four clusters, except for cluster 3. The validation with root mean squared error (RMSE), mean absolute percentage error (MAPE), and Nash Sutcliffe index (NSE) revealed RMSE = 0.01, NSE = 0.97, and MAPE = 0.13 for the first cluster, RMSE = 0.011, NSE = 0.99, and MAPE = 0.22 for the second cluster, RMSE = 0.003, NSE = 0.99, and MAPE = 0.30 for the fourth cluster, and RMSE = 0.001, NSE = 0.98, and MAPE = 0.05 for the fifth cluster. For the third cluster, a pattern including water level at the previous month, aquifer discharge, and aquifer recharge was identified as the best model resulting in RMSE = 0.006, NSE = 0.99, and MAPE = 0.05. Finally, according to the results, the ANN-PSO model was applied to three clusters, while the ANN-WOA model was applied to the remaining clusters. In general, this study showed that optimization algorithms can improve the simulation accuracy of ANN, and the efficient use of each method depends on the clustering type. The application of the approach proposed here can be extended to other aquifers that have a relatively large area and limited data availability.
英文关键词	Groundwater level WOA PSO Aquifer hydrograph Spatial clustering
类型	Article ; Early Access
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000673062800001
WOS关键词	ARTIFICIAL NEURAL-NETWORK ; PARTICLE SWARM OPTIMIZATION ; FUZZY INFERENCE SYSTEM ; WHALE OPTIMIZATION ; K-MEANS ; SPATIAL PREDICTION ; ANN-PSO ; ALGORITHM ; MODELS
WOS类目	Geosciences, Multidisciplinary
WOS研究方向	Geology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/364218
作者单位	[Kayhomayoon, Zahra] Payame Noor Univ, Dept Geol, Tehran, Iran; [Milan, Sami Ghordoyee] Univ Tehran, Dept Irrigat & Drainage Engn, Aburaihan Campus, Tehran, Iran; [Azar, Naser Arya] Univ Tabriz, Fac Agr, Dept Water Engn, Tabriz, Iran; [Moghaddam, Hamid Kardan] Water Res Inst, Dept Water Resources Res, Tehran, Iran
推荐引用方式 GB/T 7714	Kayhomayoon, Zahra,Milan, Sami Ghordoyee,Azar, Naser Arya,et al. A New Approach for Regional Groundwater Level Simulation: Clustering, Simulation, and Optimization[J],2021.
APA	Kayhomayoon, Zahra,Milan, Sami Ghordoyee,Azar, Naser Arya,&Moghaddam, Hamid Kardan.(2021).A New Approach for Regional Groundwater Level Simulation: Clustering, Simulation, and Optimization.NATURAL RESOURCES RESEARCH.
MLA	Kayhomayoon, Zahra,et al."A New Approach for Regional Groundwater Level Simulation: Clustering, Simulation, and Optimization".NATURAL RESOURCES RESEARCH (2021).