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mahmoud Mohammad Rezapour Tabari

mahmoud Mohammad Rezapour Tabari

Academic rank: Associate Professor
ORCID: 0000-0002-4837-5026
Education: PhD.
ScopusId: 8703076700
HIndex: 0/00
Faculty: Faculty of Technology and Engineering
Address: University of Mazandaran, Faculty of Engineering, Department of Civil Engineering
Phone: 011-35305133

Research

Title
Development a Novel Integrated Distributed Multi‑objective Simulation‑optimization Model for Coastal Aquifers Management Using NSGA‑II and GMS Models
Type
JournalPaper
Keywords
Coastal aquifer · NSGA-II optimization algorithm · GMS simulation model · Groundwater · Operation wells · Sustainable management
Year
2022
Journal WATER RESOURCES MANAGEMENT
DOI
Researchers mahmoud Mohammad Rezapour Tabari ، Mahbobeh Abyar

Abstract

Groundwater is one of the most valuable water resources in the world in terms of quantity and quality. Therefore, their protection as an important issue should be considered by the operating managers. Among the types of existing groundwater aquifers, the coastal aquifers need more protection because they could be contaminated by salt in the result of seawater intrusion. Their protection is a priority based on an optimal and comprehensive management model. Increasement of demands in these areas, especially in recent years, requires sustainable and optimal management as one of the main objectives for long-term operation in the future. In order to meet this purpose, a simulation-optimization model of BandargazNokandeh coastal groundwater system that located in the north of Iran was proposed by the employment of the Groundwater Modeling System (GMS) numerical model and the NonDominate Sorting Genetic Algorithm-II (NSGA-II) multi-objective evolutionary optimization algorithm. In this study based on the quantitative simulated groundwater model; two managerial issues have been examined; including the control of water-table drawdown and sustainability of extraction from the wells in this aquifer. By combining these two models and implementing them, optimal withdrawal scenarios which examines diferent aspects of the study objectives, have been extracted. Regarding the decision-making methods of Simple Additive Weighting (SAW), Gray Relational Analysis (GRA), and Berda Aggregation method (BAM), the best scenario was determined among the points located on the optimal trade-of curve. The results show that implementations of management strategies to create a sustainable development of the Bandargaz-Nokandeh coastal aquifer, has led to a 48.45 percent decrease in water withdrawal. Also, the comparison of the groundwater table level (GWTL) under the two existing and optimal operating conditions shows a 29.54% reduction (monthly average) in the area of aquifer that contain drawdown