Optimizing the exploitation of the Shahryar plain aquifer by simulating the groundwater flow using the combined modeling method

Subject Areas :

Nima  Salehi Shafa ¹ (Graduated Ph.D. Candidate of Irrigation and Drainage, Department of Water Science and Engineering, Faculty of Agriculture and Food Industry, Science and Research Branch, Islamic Azad University, Tehran, Iran.)
Hossein  Babazadeh ² (Professor, Department of Water Science and Engineering, Faculty of Agriculture and Food Industry, Science and Research Branch, Islamic Azad University, Tehran, Iran.)
Fayaz  Aghayari ³ (Assistant Professor, Department of Agronomy, Faculty of Agriculture, Karaj Branch, Islamic Azad University, Karaj, Iran.)
Ali  Saremi ⁴ (Assistant Professor, Department of Water Science and Engineering, Faculty of Agriculture and Food Industry, Science and Research Branch, Islamic Azad University, Tehran, Iran.)
MohammadReza  Ghafouri ⁵ (Graduated M.Sc. Student in Hydrogeology, Department of Water and Environmental Engineering, Iran Structural Consulting Engineers, Tehran, Iran.)
Masoud  Safavi ⁶ (Ph.D. student of Irrigation and Drainage, Department of Water Science and Engineering, Faculty of Agriculture and Natural Resources, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran.)
Ali  Panahdar ⁷ (Graduated M.Sc. Student of hydraulic structures, Department of Hydraulic Structures, Faculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran.)

Received: 2022-11-11 Accepted : 2022-12-25 Published : 2023-02-20

Keywords: Groundwater potential, Optimal planning, Artificial Neural Network (ANN), GMS model,

Abstract :

In this study, a multi-objective simulation model was presented and six scenarios were defined based on the groundwater budget for optimal exploitation of Shahryar plain aquifer. For this purpose, first, using the GIS based models and using fuzzy and weight methods, the regions with high water and low water in the study area were identified in order to prioritize resources and uses. Then the desired scenarios were simulated and evaluated by the (GMS) model. Finally, in order to increase the accuracy of the research results, the (TDS) concentration and the groundwater budget were simulated using the artificial neural network model (ANN). According to the results of fuzzy and weighted methods, the areas of Rabat Karim, then Islamshahr and finally Shahryar were identified as low water areas. Based on the obtained results, the unsteady state budget and verification were calculated as -344.68 and -109.98 (MCM), respectively. The third scenario with a budget of 203.33 (MCM) was chosen as the best scenario and the budget resulting from that, ratio to the budget resulting from the model (GMS) and the neural network for the year 95, has increased by 284.87 percent and 284.83 percent respectively. Also, the concentration of total dissolved solids in the groundwater obtained from the desired models in the entire study period was estimated by 655 and 651 mg/liter on average. The criteria of correlation coefficient and determination coefficient obtained from neural network models for groundwater budget and total data were estimated to be equal to one and for the total dissolved solids concentration of groundwater were estimated to be 0.997 and 0.994, respectively. In the present research, the multi-objective simulation pattern as a comprehensive and practical method by providing new simulation methods has the ability to support several effective scenarios and leads to increase the stability of the groundwater system.