Optimal Extraction from Coastal Groundwater Resources using Parallel Processing Based Simulation - Optimization Decision Model (Case Study of Ajabshir Coastal Aquifer, Iran)

Document Type : Original Article

Authors

1 M.Sc., Water Resources Engineering Dept., Tarbiat Modares University, Tehran, Iran.

2 Assistant Professor, Water Resources Engineering Dept., Tarbiat Modares University, Tehran, Iran,

Abstract

Groundwater is one of the main sources of freshwater in coastal areas. In case of occurrence seawater intrusion into coastal aquifers, remediation of aquifer requires long-term and expensive efforts. Therefore, it is essential to prevent of excessive seawater intrusion. For this purpose, a simulation - optimization model can be used as a decision model for determining the optimal management strategies. In this study, a simulation - optimization decision model of Ajabshir plain aquifer has been used via the SUTRA numerical model and the evolutionary optimization algorithm of ant colony optimization. In order to reduce the runtime of simulation - optimization decision model, parallel processing in the population computations of optimization algorithm was used as this caused to reduce the runtime. Two management problems have been examined in this study with objective functions and constraints under opposite behavior one is minimizing the net recharge rate (meaning the maximizing extraction from the aquifer and the other is controlling the seawater intrusion (preventing the deterioration of the salinity situation at the control points). Results from simulation - optimization decision model exhibited that by changing the extraction of aquifer zones, the net recharge of the aquifer in the second half of year decreases -1.87 million cubic meters compared to the current situation (Increase extraction) in the first management problem while in the second management problem, the average salinity concentration at the control points decreases 30%.

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References

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History

  • Receive Date: 15 December 2018
  • Revise Date: 02 March 2019
  • Accept Date: 06 March 2019

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