Robust Stackelberg Equilibrium Water Allocation Patterns in Shallow Groundwater Areas

It is challenging for decision‐makers (DMs) to deal with uncertainties in multi‐level agricultural water resource systems, where DMs independently make decisions but have different levels of power. In this paper, we model the multi‐level agricultural water resources system under deep uncertainties a...

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Vydáno v:Water resources research Ročník 60; číslo 8
Hlavní autoři: Zhang, Xiaoxing, Castelletti, Andrea, Wang, Xuechao, Guo, Ping
Médium: Journal Article
Jazyk:angličtina
Vydáno: Washington John Wiley & Sons, Inc 01.08.2024
Wiley
Témata:
Agricultural resources
Critical point
decision making
Economic benefits
Equilibrium
financial economics
Food production
Game theory
Groundwater
multi‐level programming
Optimization
Risk assessment
robust
Robustness (mathematics)
shallow groundwater area
Stackelberg game
Uncertainty
Water allocation
Water policy
Water resources
ISSN:0043-1397, 1944-7973
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Shrnutí:It is challenging for decision‐makers (DMs) to deal with uncertainties in multi‐level agricultural water resource systems, where DMs independently make decisions but have different levels of power. In this paper, we model the multi‐level agricultural water resources system under deep uncertainties as a Stackelberg game, use multi‐level programming to solve equilibrium water allocation problems, and introduce robustness metrics into multi‐level programming to balance solution feasibility and model optimality within uncertain environments. The approach is applied to a shallow groundwater area with three decision levels, pursuing, from the top level to the bottom one, high food production, fair water allocation, and increased economic benefit. The model generated a series of optimal equilibrium solutions with different robustness degrees. DMs can choose “rational” solutions according to their acceptable costs, oriented robustness degree, expected objective values, and advance risk assessment of uncertainties. Among these solutions, we capture a critical point with high objective values and strong robustness, where DMs can accomplish both objective optimality and solution robustness with a low cost. The proposed approach in this study provides a posterior decision support to consider solution robustness while designing policies in multi‐level agricultural water resource systems under deep uncertainties. Key Points An introduction of robust measure into multi‐level programming balances solution robustness and model optimality There is a critical point that decision makers can achieve high objective values and strong robustness with low costs
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ISSN:0043-1397
1944-7973
DOI:10.1029/2023WR035373