Modeling adaptive decision-making of farmer: An integrated economic and management model, with an application to smallholders in India

This thesis develops and discusses farmers’ decision-making modeling approaches for representing the adaptation of farming to global changes and water policies: their effects on agricultural economics and practices and water resources comprise critical information for decision makers. After a summary, six articles are presented. The first article reviews bio-economic and bio-decision models, in which strategic and tactical decisions are included in dynamic adaptive and expectation-based processes, in 40 literature articles. The second article describes the case-study and presents a typology of Indian farmers from a survey including 684 farms in Berambadi, an agricultural watershed in South India. The third article presents a step-by-step approach that combines decision-making analysis with a modeling approach inspired by cognitive sciences and software -development methods. This methodology bridges the gap between field observations and the design of the decision model. It is a useful tool to guide modelers in building decision model in farming system. The fourth article describes the conceptual model NAMASTE, which was conceived to represents farmers adaptation processes under uncertainty. Since NAMASTE was designed in an extreme case of highly vulnerable agriculture, its generic framework and formalisms can be used to conceptually represent many other farm production systems. The fifth article investigates the role of water management policies on groundwater resource depletion under climate change conditions. We built a stochastic dynamic programming farm model. The model reproduced decision on irrigation investment and cropping system made each year with the concern of future impacts on water availability for irrigation. The sixth article describes the NAMASTE dynamic simulation Model developed to model farming systems for evaluation and test of water management policies