نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه علوم و مهندسی آب، دانشکده کشاورزی، مشهد، دانشگاه فردوسی مشهد، ایران
2 علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه فردوسی مشهد، مشهد، ایران
3 دانشیار گروه مهندسی آب، دانشکده مهندسی کشاورزی، دانشگاه فردوسی مشهد، مشهد، ایران
4 گروه ریاضیات کاربردی، دانشکده ریاضی، مشهد، دانشگاه فردوسی مشهد، ایران
چکیده
کلیدواژه‌ها
عنوان مقاله [English]
نویسندگان [English]
Groundwater management requires accurate quantitative and qualitative monitoring of groundwater with proper spatial and temporal distribution. Minimizing the number of monitoring wells with maximum spatial distribution for making it economical to monitor groundwater systems is required by managers. Therefore, the structure of groundwater monitoring networks and the number of required wells becomes an engineering optimization problem. The purpose of this study is to find candidates for optimal monitoring network with the least number of wells that provide sufficient coverage to identify groundwater quality in an area. Hence, the excess wells in the network are identified. The meta-heuristic Tabu search algorithm has been used in this research. The objective function in this study consists of two conflicting goals. The first goal is the maximization of the match between the interpolated groundwater quality index distributions obtained using data from all wells and the wells from newly-generated network. The Nash-Sutcliffe model was utilized as a criterion to evaluate this compliance. In this study, groundwater quality is expressed using a water quality index, including nine quality parameters. The second goal is to minimize the number of monitoring wells selected to save on monitoring costs. The two mentioned goals are summed up in a function using a weight coefficient that determines the importance of the goals compared to each other. The mentioned model was used for a number of different active wells. Also, using the Tabu search algorithm, the best combination of different active wells that achieves the maximum objective function was identified. Optimal networks suggest managers and decision makers to choose the optimal network to monitor water quality according to the accepted budget and error. Consequently, this optimizing model could reduce the number of monitoring wells by 34 - 75%.
کلیدواژه‌ها [English]
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