Click on “Download PDF” for the PDF version or on the title for the HTML version.

If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.

An optimal stochastic multicrop irrigation scheduling algorithm is presented which allows for the inclusion of detailed crop-soil models and limits on seasonal water use and system capacity. Existing optimal schedulers generally use stochastic dynamic programming (SDP). The main limitation of SDP is the requirement of time independence of all parameters except soil moisture, thereby requiring oversimplistic crop models, limiting the practical use of these schedulers. To overcome this limitation the proposed scheduler uses a simulation model as the objective function with a few decision variables used to control the irrigation management. These decision variables are optimized with Simulated Annealing coupled with a custom population-based heuristic method. A case study compares the schedulers performance with known mathematically optimum solutions produced by SDP. The results indicate the proposed scheduler produces sub-optimal results for two or more crops. Further modifications of the objective function are required to better account for climate variability.