Planning & Management
394874 - Utilizing probabilistic weather forecasting for optimal irrigation scheduling
Thursday, June 7
10:30 AM - 12:00 PM
Location: Greenway GH
Optimal use of water resources is one of the most important aims to face the future climate change and food security concerns. In this study we developed a Decision Support System (DSS) to optimize the water use in the agriculture sector by deriving optimal irrigation schedule on the field scale. The developed DSS utilizes stochastic optimization approaches (which are based on probabilistic seasonal weather forecasts) and decision space aggregation methodology for facilitation the solution of the obtained optimization problems. Three stochastic approaches were investigated: implicit approach, single-stage approach and two-stage approach. In addition to the stochastic approaches, a deterministic approach using either perfect seasonal forecasts or perfect weekly forecast is presented for comparison purposes. To evaluate the benefit of the developed DSS it was compared to benchmark solutions for a chickpea field in Kibbutz HaZorea, Israel. The results show that using stochastic optimization approaches may outperform classical irrigation scheduling methodologies.
To reduce this number of decision variables, weekly aggregation was performed after the first next week, so that every seven days have the same daily irrigation amount.