This study examines the impact of weekly and seasonal weather forecasts on the optimal irrigation scheduling problem. We compare stochastic and deterministic simulation-optimization frameworks for irrigation scheduling using perfect weekly (deterministic) and imperfect seasonal (stochastic) forecasts. The analysis is performed on a case study of irrigated chickpeas in Kibbutz HaZore’a in northern Israel. The results demonstrate that, for the case study area and crop, the optimization with seasonal stochastic forecasts outperforms the deterministic optimization that uses perfect weekly forecast.

This paper presents a modeling framework for real-time decision support for irrigation scheduling using probabilistic seasonal weather forecasts which are incorporated into a simulation-optimization framework. The simulation of the field processes is performed by the Soil Water Atmosphere Plant (SWAP) model, whereas the optimization is performed by three different stochastic programming methods: implicit approach, explicit single-stage approach and explicit two-stage approach. To evaluate the benefit of the probabilistic forecasts, the irrigation schedules from the different stochastic methods are compared with the best benchmark of perfect forecasts as well as with the real field and the Agriculture Extension Service of Israel schedules. The analysis is performed on a real case study of irrigated chickpeas field in Kibbutz Hazorea, Northern Israel. The results show that incorporating stochastic weather forecasts could lead to substantial improvements compared with current irrigation practices.

The ensemble Kalman filter (EnKF) is a widely used data assimilation method in soil hydrology. However, underestimation of the modeling errors and of the sampling errors may cause systematic reduction of state variances and rejection of the observations. Inflation methods are used to alleviate this phenomenon. Here, we suggest a novel inflation method based on confidence intervals constructed using the collected ensemble of the measurements. The proposed method is illustrated via two synthetic examples of a three‐layer soil with (i) precipitation and evaporation boundary condition and (ii) irrigation boundary condition. We present a comparison of two existing inflation methods and discuss the advantages and limitations of the proposed method. Basically, the suggested method behavior is superior to the behavior of the existing methods.