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Optimization Operation of Water Resources Using Game Theory and Marine Predator Algorithm

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Abstract

Today, one of the most important issues in the field of common water resources management is the allocation of water resources to different stakeholders with different interests. Game theory and conflict resolution methods, taking into account the interests and strategies of the players, provide efficient methods for allocating reservoirs water resources to stakeholders. In this research, for the first time, a wide range of different methods of game theory are used in order to allocate the water resources of Idoghmosh Dam reservoir (East Azarbaijan—Iran) to the agricultural and environmental stakeholders in the downstream. For this purpose, the NASH and four methods of bankruptcy theory, including PRO, AP, CEA, and CEL are used in this research. Also, in this research, the dam component is considered as a player. In the presented model for the optimal allocation of water to consumers, for the first time, the combination of game theory and the MPA as main innovation of this study is used, and the results obtained from it are compared with the GA. The proposed model is used in the base period (1987–2000) and the 14-year climate change period (2026–2039). In the following, for the first time, a wide range of different efficiency indexes of reliability, resiliency, vulnerability, flexibility, availability, supply to demand, volume reliability and SSD are used to analyze the reservoir operation policies. The results show that for each agricultural and environmental player in different base and future periods, the performance of different game theory methods on different indexes has been different. For example, the results for the agricultural player in the future period show that MPA with PRO method and then AP provided the best results for the indexes of vulnerability, resiliency, reliability, SSD, and supply to demand, that the similar values provided using GA and other bankruptcy methods have assigned lower values than MPA.

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Abbreviations

NASH:

Nash Conflict Resolution Model

PRO:

Proportional

AP:

Adjusted Proportional

CEA:

Constrained Equal Award

CEL:

Constrained Equal Loss

MPA:

Marine Predators Algorithm

GA:

Genetic Algorithm

SSD :

Sum of Squared Deficits

CWAM:

Collaborative Water Allocation Model

NSGA-II :

Non-Dominated Sorting Genetic Algorithm

RSBT:

Rubinstein Sequential Bargaining Theory

ESE:

Evolutionary Stable Equilibrium

HGT-MPM:

Hybrid Game Theory and Mathematical Programming Model

GMCR:

Graph Model Conflict Resolution

WEAP:

Water Evaluation and Planning

AHP:

Analytical Hierarchy Process

FADs:

Fish Aggregating Devices

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Authors and Affiliations

  1. Department of Civil Engineering, University of Qom, Qom, Iran

    Shirin Moradi Far & Parisa-Sadat Ashofteh

Authors
  1. Shirin Moradi Far
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  2. Parisa-Sadat Ashofteh
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Contributions

Shirin Moradi Far developed the theory and performed the computations. Parisa-Sadat Ashofteh verified the analytical methods and encouraged Shirin Moradi Far to investigate a specific aspect. Parisa-Sadat Ashofteh supervised the findings of this work. All authors discussed the results and contributed to the final manuscript. Shirin Moradi Far wrote the manuscript with support from Parisa-Sadat Ashofteh. Parisa-Sadat Ashofteh conceived the original idea.

Corresponding author

Correspondence to Parisa-Sadat Ashofteh.

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Supplementary Section in the Appendix

Supplementary Section in the Appendix

Fig. 12
figure 12

Changes in the volume of a release and b water deficit of reservoir, along with changes in the volume of demand for the agricultural player in the base period based on the rules extracted from the bankruptcy method (PRO, AP, CEA, CEL) and Nash theory (NASH) using GA

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Fig. 13
figure 13

Changes in the volume of a release and b water deficit of reservoir, along with changes in the volume of demand for the agricultural player in the future period based on the rules extracted from the bankruptcy method (PRO, AP, CEA, CEL) and Nash theory (NASH) using GA

Full size image
Fig. 14
figure 14

Changes in the volume of a release and b water deficit of reservoir, along with changes in the volume of demand for the environmental player in the base period based on the rules extracted from the bankruptcy method (PRO, AP, CEA, CEL) and Nash theory (NASH) using MPA

Full size image
Fig. 15
figure 15

Changes in the volume of a release and b water deficit of reservoir, along with changes in the volume of demand for the environmental player in the future period based on the rules extracted from the bankruptcy method (PRO, AP, CEA, CEL) and Nash theory (NASH) using MPA

Full size image
Fig. 16
figure 16

Changes in the volume of a release and b water deficit of reservoir, along with changes in the volume of demand for the environmental player in the base period based on the rules extracted from the bankruptcy method (PRO, AP, CEA, CEL) and Nash theory (NASH) using GA

Full size image
Fig. 17
figure 17

Changes in the volume of a release and b water deficit of reservoir, along with changes in the volume of demand for the environmental player in the future period based on the rules extracted from the bankruptcy method (PRO, AP, CEA, CEL) and Nash theory (NASH) using GA

Full size image
Fig. 18
figure 18

Changes in the volume of a storage and b spill, along with changes in the demand volume in the base period based on the rules extracted from bankruptcy method (PRO, AP, CEA, CEL) and Nash theory (NASH) using GA

Full size image
Fig. 19
figure 19

Changes in the volume of a storage and b spill, along with changes in the demand volume in the future period based on the rules extracted from bankruptcy method (PRO, AP, CEA, CEL) and Nash theory (NASH) using GA

Full size image

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Far, S.M., Ashofteh, PS. Optimization Operation of Water Resources Using Game Theory and Marine Predator Algorithm. Water Resour Manage 38, 665–699 (2024). https://doi.org/10.1007/s11269-023-03692-w

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