Modeling and Optimization for Crop Portfolio Management Under Limited Irrigation Strategies
Abstract
Managing existing water resources has become critically important as overuse, in conjunction with extreme droughts, has placed aquifers in jeopardy. Our goal in this work is to develop a flexible modeling and optimization framework to aid farmers in selecting crop portfolios which offer the best outcomes, under sustainable water usage limitations, over specified time frames. The flexibility is emphasized through incorporation of multi-objective algorithms, allowing farmers to define “best" individually. We then demonstrate the modeling and optimization approach on a three-crop farm over a two year planning horizon and with a case study, the Pajaro Valley of California, known for berry farming. We consider a ten year planning horizon under the presence of increasing water and sale prices to demonstrate how the modeling tool can be used for predictive purposes.
Full Text: PDF
Abstract
Managing existing water resources has become critically important as overuse, in conjunction with extreme droughts, has placed aquifers in jeopardy. Our goal in this work is to develop a flexible modeling and optimization framework to aid farmers in selecting crop portfolios which offer the best outcomes, under sustainable water usage limitations, over specified time frames. The flexibility is emphasized through incorporation of multi-objective algorithms, allowing farmers to define “best" individually. We then demonstrate the modeling and optimization approach on a three-crop farm over a two year planning horizon and with a case study, the Pajaro Valley of California, known for berry farming. We consider a ten year planning horizon under the presence of increasing water and sale prices to demonstrate how the modeling tool can be used for predictive purposes.
Full Text: PDF
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