An agent-based-nash modeling framework for sustainable groundwater management: A case study

Saber Farhadi, Mohammad Reza Nikoo, Gholam Reza Rakhshandehroo, Masih Akhbari and Mohammad Reza Alizadeh

Agricultural Water Management, 2016, vol. 177, issue C, 348-358

Abstract: An agent-based-Nash modeling framework has been developed to find a sustainable solution for groundwater management in Daryan Aquifer, Fars Province, Iran. This framework also includes a MODFLOW simulation model, an Artificial Neural Network (ANN), and a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) optimization model. Groundwater state was simulated using MODFLOW and it was calibrated based on the measured data provided by Regional Water Organization (RWO) of Fars Province. In order to reduce the computational time, an ANN was trained and validated based on the input-output data of the MODFLOW model to estimate groundwater level. The validated ANN was linked to a nonhomogeneous elitist NSGA-II multi-objective optimization model to find a Pareto optimal front among the three objectives of reducing irrigation water deficit, increasing equity in water allocation, and reducing groundwater drawdown, as the objectives of the three main groundwater resource stakeholders; farmers, the government executive sector, and the environmental protection institutes. The Nash bargaining model was applied to the optimal solutions in order to find a compromise among the stakeholders. Social influential factors in the study environment, and policy mechanisms to encourage agents to cooperate with the management decisions were implemented in the agent-based model. These factors include training, incentives, penalties, and social norming (neighbors' impacts), as well as considering the executive and judicial systems. After application of the agent-based model, computed optimum solutions were modified according to social conditions. Finally, the Nash bargaining model was used again to find a compromise among modified optimal objectives of the stakeholders. Implementation of this solution led to 58.3% less water extraction and approximately 3m water level uplift.

Keywords: Sustainable groundwater management; Agent-based modeling; Simulation-optimization; Nash bargaining model; NSGA-II multi-objective optimization model (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S037837741630302X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:177:y:2016:i:c:p:348-358

DOI: 10.1016/j.agwat.2016.08.018

Access Statistics for this article

Agricultural Water Management is currently edited by B.E. Clothier, W. Dierickx, J. Oster and D. Wichelns

More articles in Agricultural Water Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().