Industrial and Manufacturing Systems Engineering
Journal or Book Title
Environmental Modelling & Software
Research Focus Area(s)
A nutrient reduction strategy for Iowa identifies land use and conservation alternatives to reduce nutrient loss from agriculture and the resulting Gulf of Mexico hypoxia. From the viewpoint of a policy maker concerned with regional costs and benefits, we develop a land use optimization model to maximize profit while satisfying nutrient reduction constraints. Because uncertain precipitation levels affect both yields and nutrient loss, we formulate two variants of a multistage stochastic mixed-integer program with probabilistic scenarios for annual precipitation generated from a Markov chain model. Numerical sensitivity analyses on the recourse variant reveal complicated interactions among the nutrient reduction and labor availability constraints as well as crop prices. The chance-constrained variant provides needed flexibility in meeting nutrient reduction goals by neglecting low-probability precipitation outcomes. Case study results indicate that, although significant financial incentives might be required for landowners to implement optimal strategies, substantial reductions in nutrient loss can be achieved.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Emirhuseyinoglu, Gorkem and Ryan, Sarah M., "Land use optimization for nutrient reduction under stochastic precipitation rates" (2019). Industrial and Manufacturing Systems Engineering Publications. 216.
Available for download on Friday, October 22, 2021