Climate change adaptation through robust land use planning: two-stage stochastic optimization for risk-informed decision making

Uncertainty and variability of climate changes are key challenges for adaptation planning. In the face of uncertainty, the decision-making can be addressed in two interdependent stages: make only partial ex-ante anticipative actions to keep options open until new information is revealed; and adapt the first-stage decisions with respect to newly acquired information. This decision-making approach corresponds to the two-stage stochastic optimization (STO) incorporating both anticipative exante and adaptive ex-post decisions within a single model. The paper develops a two-stage STO model for climate change adaptation through robust land use and irrigation planning in the condition of uncertain water supply. The model identifies the differences between the decision-making in the cases of perfect information, full uncertainty, and uncertainty with perspectives of learning about uncertainty. The two-stage anticipative and adaptive risk-informed decision-making with safety constraints induces risk aversion characterized by quantile-based Value-atRisk and Conditional Value-at-Risk risk measures. The ratio between the ex-ante and ex-post costs and the shape of uncertainty 61 determines the balance between the anticipative and adaptive decisions. Selected numerical results illustrate that the alteration of the ex-ante agricultural production costs can affect crop production, land management technologies, and natural resource utilization