Integrated approach for optimizing groundwater monitoring systems using evolutionary algorithms

被引：0

作者：

Mahmod, Wael Elham ^{[1
,2
]}

Mohamed, Hassan, I ^{[1
]}

Suleiman, Ahmed H. ^{[3
]}

机构：

[1] Assiut Univ, Fac Engn, Civil Engn Dept, Assiut 71515, Egypt

[2] Taif Univ, Fac Engn, Civil Engn Dept, At Taif, Saudi Arabia

[3] Arab Consulting Engineers ACE, Assiut Barrage Dev Consultants ABDC, Cairo, Egypt

来源：

HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES | 2021年 / 66卷 / 13期

关键词：

groundwater monitoring system (GMS); evolutionary algorithms; genetic algorithms (GA); modified genetic algorithms (MGA); Assiut New Barrage (ANB); LIMITED HYDROGEOLOGICAL DATA; NEURAL-NETWORK; GENETIC ALGORITHM; NUBIAN SANDSTONE; CONJUNCTIVE USE; SURFACE-WATER; KHARGA OASIS; GREY MODEL; OPTIMIZATION; FLOW;

D O I：

10.1080/02626667.2021.1968404

中图分类号：

TV21 [水资源调查与水利规划];

学科分类号：

081501 ;

摘要：

This study aimed to develop a new approach to build a functioning groundwater monitoring system by detecting a reduced set of observation wells (OWs) that optimally matches the hydraulic heads measured by other OWs within the field, namely as leader wells (LWs). The optimization models used in this work are the well-known genetic algorithm (GA) and modified genetic algorithm (MGA) and a new progressive combination (PC) model. Optimization was applied to achieve three sequential selection processes: best input combinations (BICk), LWs and core leader wells (CLWs). This approach was applied to the Assiut New Barrage (ANB), a megaproject located in Assiut city, Egypt. The results show that nine LWs among 33 OWs are adequate for regular monitoring, with a reduction ratio of 72.72%. Moreover, assigning CLWs among LWs increases the accuracy of fitting to existing OWs, and helps in understanding the spatial relationships among OWs.

引用

页码：1963 / 1978

页数：16

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