Campus Units

Industrial and Manufacturing Systems Engineering

Document Type


Publication Version

Accepted Manuscript

Publication Date


Journal or Book Title

Environmental Modelling & Software

First Page


Research Focus Area(s)

​Operations Research




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.


This is a manuscript of an article published as Emirhüseyinoğlu, Görkem, and Sarah M. Ryan. "Land use optimization for nutrient reduction under stochastic precipitation rates." Environmental Modelling & Software (2019): 104527. DOI: 10.1016/j.envsoft.2019.104527. Posted with permission.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

Elsevier Ltd.



File Format


Available for download on Friday, October 22, 2021

Published Version