IWRA Proceedings

AbstractDeficit irrigation has been thought as a strategy to increase overall system benefits watercrop production scheme. However, as a common practice in deficit irrigation, the inherent uncertainty in crop water demand has been largely ignored. In the present study, two types of uncertainty namely demand side uncertainty and allocation side uncertainty are considered. A constraint state formulation for stochastic optimization of weekly irrigation strategy is used to incorporate the effects of the above uncertainties in deficit irrigation scheduling. This formulation is based on the first and second order moment analysis of the stochastic soil moisture state variable, considering soil moisture at both saturation and deficit cases as the maximum and minimum bounds, respectively. As a result, mean and variance of actual evapotranspiration are used for reliability analysis of the relative net benefit based on the Advanced First Order Second Method (AFOSM) for deficit irrigation case. This method is widly used in engineering applications. The optimization and simulation results are indicative of the importance of crop water demand uncertainty consideration when determining optimal deficit irrigation strategy. Also the probability of intra- seasonal crop water stress index is determined based on the moment analysis and using the double bounded density function methodology. The results indicate that achieving a high long-term expected relative net benefit by decreasing the crop water allocation and increasing the irrigated land may fail as a strategy when crop demand uncertainty is ignored in the optimization process.