نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی کارشناسی ارشد بخش مهندسی عمران و محیط زیست، دانشگاه شیراز
2 استادیار بخش مهندسی عمران و محیط‌زیست، دانشکده مهندسی، دانشگاه شیراز،
3 استاد تمام بخش مهندسی عمران و محیط‌زیست، دانشکده مهندسی، دانشگاه شیراز
چکیده
کلیدواژه‌ها
عنوان مقاله [English]
Optimal management and operation of groundwater resources need to attract a great attention according to their special characteristics. Groundwater resources exploitation operation involves important issues such as conflicting and complex objectives, a large number of decision variables and different uncertainties. Conflict between goals of stakeholders is more obvious, especially when there are different stakeholders with conflicting objectives. The methodology presented in this paper is to determine an optimal allocation of groundwater resources with emphasis on resolving conflicts between involved stakeholders for developing appropriate policies based on the Social Choice Rule (SCR). In this study, an optimal groundwater resources allocation is determined by developing a simulation-optimization model. For this purpose, a meta-model based on Multi-Layer Perceptron (MLP) neural network is trained and validated using results of repeated executions of the groundwater simulation model (MODFLOW) to predict groundwater drawdowns. NSGA-II optimization model is utilized to determine the trade-off (Pareto fronts) between conflicting objectives. The best non-dominated solution on Pareto fronts is selected using the SCR as a compromise solution. A performance of the proposed methodology was analyzed by applying it to the case study of the Kavar-Maharlu aquifer in the Fars Province, Iran. Results indicated an acceptable performance of the proposed methodology for determining optimal groundwater allocation policy. By applying the suggested policy of proposed simulation-optimization model to the Kavar-Maharlu aquifer. An average annual withdrawal from the aquifer was reduced by 56% and reached 25.52 million cubic meters per year.
کلیدواژه‌ها [English]
)
