Reducing Agricultural Water Pollution in Texas: An Application of Linear Optimization

EditorMesser, Kent D.
Date Accessioned2015-10-12T17:00:34Z
Date Available2015-10-12T17:00:34Z
Publication Date2013-11
AbstractLinear optimizations models have been used for many practical purposes throughout the years – maximization and minimization models have proved to be key tools when striving to reach a goal. This case study employs such a model with the goal of maximizing an approximate reduction of pollutant loads from individual parcels per year with the implementation of BMPs throughout Fort Bend, Texas. The motivations for this study are the ever growing levels of Nitrogen, Phosphorus and sediment pollutant levels throughout the San Bernard Watershed, in which Fort Bend belongs. To do this, several BMPs related to livestock pollutant loads are examined and selected to be included in the model. This model will choose BMP and parcel combinations in order to provide maximum potential pollutant reductions for each parcel. As a result we obtained 32 BMP implementation recommendations across 31 parcels for a maximum reduction in pollutant loads of roughly 4.3 million pounds per year. A parameter analysis on the maximum budget concluded that the budget could increase until approximately $6 million where it begins to level off at 65 million pounds of pollutant reduction per year. There are several opportunities to expand this research, including developing a watershed wide model.en_US
URLhttp://udspace.udel.edu/handle/19716/17121
Languageen_USen_US
PublisherDepartment of Applied Economics and Statistics, University of Delaware, Newark, DE.en_US
Part of SeriesRR2013-02
TitleReducing Agricultural Water Pollution in Texas: An Application of Linear Optimizationen_US
TypeResearch Reporten_US
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