Christian Troost

Dealing with Uncertainty in Agent-Based Simulation: Farm-Level Modeling of Adaptation to Climate Change in Southwest Germany

Climate change will most likely confront agricultural producers with natural, economic, and political conditions that have not previously been observed and are largely uncertain. As a consequence, extrapolation from past data reaches its limits, and a process-based analysis of farmer adaptation is required. Simulation of changes in crop yields using crop growth models is a first step in that direction. However, changes in crop yields are only one pathway through which climate change affects agricultural production. A meaningful process-based analysis of farmer adaptation requires a whole-farm analysis at the farm level. We use a highly disaggregated mathematical programming model to analyze farm-level climate change adaptation for a mountainous area in southwest Germany. Regional-level results are obtained by simulating each full-time farm holding in the study area. We address parameter uncertainty and model underdetermination using a cautious calibration approach and a comprehensive uncertainty analysis. We deal with the resulting computational burden using efficient experimental designs and high-performance computing. We show that in our study area, shifted crop management time slots can have potentially significant effects on agricultural supply, incomes, and various policy objectives promoted under German and European environmental policy schemes. The simulated effects are robust against model uncertainty and underline the importance of a comprehensive assessment of climate change impacts beyond merely looking at crop yield changes. Our simulations demonstrate how farm-level models can contribute to a process-based analysis of climate change adaptation if they are embedded into a systematic framework for treating inherent model uncertainty.

Quantifying the economic importance of irrigation water reuse in a Chilean watershed using an integrated agent‐based model

Irrigation with surface water enables Chilean agricultural producers to generate one of the countrys most important economic exports. The Chilean water code established tradable water rights as a mechanism to allocate water amongst farmers and other water-use sectors. It remains contested whether this mechanism is effective and many authors have raised equity concerns regarding its impact on water users. For example, speculative hoarding of water rights in expectations of their increasing value has been described. This paper demonstrates how farmers can hoard water rights as a risk management strategy for variable water supply, for example, due to the cycles of El Nino or as consequence of climate change. While farmers with insufficient water rights can rely on unclaimed water during conditions of normal water availability, drought years overproportionally impact on their supply of irrigation water and thereby farm profitability. This study uses a simulation model that consists of a hydrological balance model component and a multiagent farm decision and production component. Both model components are parameterized with empirical data, while uncertain parameters are calibrated. The study demonstrates a thorough quantification of parameter uncertainty, using global sensitivity analysis and multiple behavioral parameter scenarios.