نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی دکتری منابع آب، گروه علوم و مهندسی آب، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.
2 استادیار گروه علوم و مهندسی آب، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران.
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
The main purpose of this study is to develop a multi-criteria decision model based on stakeholders in the study area of Varamin plain with the approach of aquifer subsidence control. One of the important tools for developing a decision model for land subsidence control is to use numerical models and evaluate different scenarios in these models. Due to the relationship and sensitivity of groundwater abstraction with subsidence, use of MODFLOW model to quantitatively simulate the aquifer and then use of SUB software package to simulate the amount of subsidence can determine this relationship well. Quantitative analysis and simulation of the subsidence model showed that the condition of the aquifer is critical and the rate of aquifer drop in a period of 5 years is more than 6 meters and subsequently the subsidence in the central parts of the aquifer will reach 37 cm. Accordingly, the effectiveness of these strategies was studied by considering 8 scenario strategies that are a combination of reducing the withdrawal of groundwater resources and artificial feeding of the aquifer. The results of weighting the criteria showed that the environmental criterion, which is related to the land subsidence adjustment index, has the highest weight with value of 0.27 and was introduced as the most important criterion in decision making. After evaluating the results and priorities of the solutions by COPRAS method, it was found that the A8 scenario is introduced as the first priority of aquifer treatment. The results also showed that by applying this scenario, the amount of subsidence will be reduced and the maximum amount of subsidence will be 23.5 cm in the central part of the aquifer. Finally, the quantitative status of the aquifer also improved by 76% compared to the forecast period (2024).
کلیدواژهها [English]