Evaluating the impacts of farmers' behaviors on a hypothetical agricultural water market based on double auction. Issue 5 (18th May 2017) - Du, Erhu; Cai, Ximing; Brozović, Nicholas; Minsker, Barbara
Abstract: Agricultural water markets are considered effective instruments to mitigate the impacts of water scarcity and to increase crop production. However, previous studies have limited understanding of how farmers' behaviors affect the performance of water markets. This study develops an agent‐based model to explicitly incorporate farmers' behaviors, namely irrigation behavior (represented by farmers' sensitivity to soil water deficit λ ) and bidding behavior (represented by farmers' rent seeking μ and learning rate β ), in a hypothetical water market based on a double auction. The model is applied to the Guadalupe River Basin in Texas to simulate a hypothetical agricultural water market under various hydrological conditions. It is found that the joint impacts of the behavioral parameters on the water market are strong and complex. In particular, among the three behavioral parameters, λ affects the water market potential and its impacts on the performance of the water market are significant under most scenarios. The impacts of μ or β on the performance of the water market depend on the other two parameters. The water market could significantly increase crop production only when the following conditions are satisfied: (1) λ is small and (2) μ is small and/or β is large. The first condition requires efficient irrigation scheduling, and the second requires well‐developed water market institutions that provide incentives to bid true valuation of water permits. Key Points: Farmers' behavioral parameters are incorporated in an agent‐based model to evaluate their impacts on an agricultural water market Farmers' irrigation behavior determines the water market's potential Farmers' bidding behavior determines the actual transaction The water market can result in high crop yield when farmers are sensitive to soil dryness, rent seeking is low, and learning rate is high