Skip to main content

Integrated approach for optimizing groundwater monitoring systems using evolutionary algorithms

مؤلف البحث
Wael Elham Mahmod ,Hassan I. Mohamed, Ahmed H. Suleiman
تاريخ البحث
سنة البحث
2021
مجلة البحث
Hydrological Sciences Journal
الناشر
Taylor & Francis
عدد البحث
VOL. 66, NO. 13
تصنيف البحث
https://doi.org/10.1080/02626667.2021.1968404
صفحات البحث
1963–1978
موقع البحث
https://www.tandfonline.com/doi/abs/10.1080/02626667.2021.1968404?src=&journalCode=thsj20
ملخص البحث

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), modfied 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) selection. 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 to understand the spatial relationships between OWs.