[Post-doc] Bachar Tarraf : Consideration of meteorological uncertainties for irrigation management models in agriculture

Apr 28 2022


Consideration of meteorological uncertainties for irrigation management models in agriculture

Abstract: Agriculture is one of the activities most impacted by weather hazards, modulating in particular the crop cycle, irrigation management, crop protection, etc. This sector has a strong demand for decision support tools (DST) aimed at adjusting crop operations according to weather constraints. In recent years, weather forecasts have evolved, now offering information on uncertainty. These probabilistic forecasts, also known as ensemble forecasts, make it possible to propose realistic scenarios to represent the uncertainties of forecasts up to 15 days. In addition, farmers are equipping themselves with connected stations to provide weather observation to the DST. Nevertheless, the deployment of these new low-cost stations raises the question of their quality and therefore of the associated uncertainties as well. At the same time, all these elements contribute to the construction of precision agriculture. The objective of this post-doc is to evaluate the impact of the uncertainties of weather forecasts on water balance forecasts and, ultimately, on the recommendations made by the DST for irrigation management. For this purpose, the overall forecasts will be used. In addition, the sensitivity of these DST to the three main categories of uncertainty sources will be jointly evaluated: the overall forecasts, the meteorological observations from connected stations and the agronomic parameters or input variables. We will consider 2 decision support tools for irrigation management in vineyards and maize. It will show the interest of ensemble forecasting approaches compared to classical forecasts or frequency approaches.
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Source: Digital Agriculture Convergence Lab