The seasonal irrigation water demand under uncertainty, which lies at the core of this paper, is still very roughly known. We know, however, that irrigated agriculture accounts for a large proportion of water use, especially in many water-scarce areas. In this paper, we estimate the irrigation water demand, for various climatic conditions characterizing the distribution of the necessarily stochastic, demand functions under uncertainty. We use a dynamic programming model to represent the farmer's decision program under uncertainty. A crop-growth simulation model (EPIC-PHASE), provides the response function to the decisions taken and climatic events and is linked to a CRRA utility function representing the farmer's objective function. This model is used to generate the data allowing the estimation of irrigation water demand by a nonparametric procedure. An application to irrigation water demand is proposed in the South-West of France. We show that the estimated demand functions present four main areas: For very small quantities, where the farmer considers water as an essential input to crop growth, the demand is inelastic. The second area corresponds to mean quantities where the plant has reached a satisfactory level of growth; water is no more an essential input and is not yet a risk reducing input. The farmer is more responsive to change in water price. But, we find a third, non-intuitive, area for larger quantities where the water is a risk reducing input and the demand becomes inelastic again. The last area is classic, the water demand is obviously elastic for important total water quantities. This result is of great importance to analyze a regulation policy.

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 Record created 2017-04-01, last modified 2017-04-26

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