Theses and Dissertations at Montana State University (MSU)
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Item Making the shift from grey to green infrastructure for stormwater management: a case study of austin, texas(Montana State University, 2021) Oliver, Rebecca L.Austin, Texas is the eleventh most populous city in the United States as of July 2019, and the population is swiftly growing (U.S. Census Bureau, 2020). Increasing urbanization inadvertently leads to pollutant deposition and build-up that is consequently washed-off with stormwater runoff into the receiving waters (Goonetilleke & Lampard, 2019). The culmination of this changing land use is a higher likelihood of flooding, severe stream-bank erosion, and degraded water quality throughout the city's watersheds. Therefore, I evaluated whether shifting away from a traditional stormwater management approach towards a green infrastructure strategy would be beneficial to Austin. I focused on the Slaughter Creek Watershed within the city. To model pollutant concentrations in runoff, I evaluated historical daily precipitation data for a 51-year period from a station in central Austin was evaluated to calculate the average precipitation value of the two-year storm. Twenty years of water quality data for untreated stormwater were acquired from a monitoring location in central Austin and paired with the precipitation values. Regression analysis was used to determine a relationship between measured precipitation and the concentration of each of four pollutants: total suspended solids, total nitrogen, total phosphorus, and E. coli, in stormwater runoff. The pollutant removal efficacy of two traditional stormwater management features, underground detention vaults and sand filters, and two green infrastructure features, bioretention and permeable pavers, was evaluated against the calculated pollutant concentrations. The EPA-funded Community-enabled Lifecycle Analysis of Stormwater Infrastructure Costs tool was used to determine implementation costs and cobenefits of three stormwater management scenarios in the Slaughter Creek Watershed. The results of the model indicate that a hybrid approach, combining both green and traditional infrastructure features, is the most inexpensive and captures the most runoff by volume. However, the green infrastructure approach has significantly more co-benefits and has greater positive water quality impacts. The traditional infrastructure scenario was the most expensive, had the fewest co-benefits and water quality impacts, and captured the least runoff volume. The information in this study indicates that the Slaughter Creek Watershed will benefit from a revised hybrid approach featuring primarily green infrastructure practices yet incorporating traditional features where more practicable.Item Optimizing site-specific nitrogen fertilizer management based on maximized profit and minimized pollution(Montana State University - Bozeman, College of Agriculture, 2022) Hegedus, Paul Briggs; Chairperson, Graduate Committee: Bruce D. Maxwell and Stephanie A. Ewing (co-chair); This is a manuscript style paper that includes co-authored chapters.Application of nitrogen fertilizers beyond crop needs contributes to nitrate pollution and soil acidification. Excess nitrogen applications are most prevalent when synthetic fertilizers are applied at uniform rates across fields. Precision agroecology harnesses the tools and technology of variable rate precision agriculture, a common but underutilized management strategy, to make ecologically conscious decisions about field management that promote economic and environmental sustainability. On-farm precision experimentation provides the basis for making data driven ecological management decisions through the field-specific assessment of crop responses. This dissertation work used on-farm experimentation with variable nitrogen fertilizer rates, combined with intensive data collection and data science, to address the main objective of this dissertation: development and evaluation of optimized nitrogen fertilizer management on a subfield scale, based on maximization of farmer net-returns and nitrogen use efficiency. The response of winter wheat yield and grain protein concentration to rates of nitrogen fertilizer application varied among fields, and across time, which influenced the model form used to characterize the relationships of grain yield and quality to fertilizer within a field. Machine learning approaches, such as random forest regression, tended to provide the lowest degree of error when forecasting future crop responses. Machine learning also demonstrated its utility for use in agronomic applications, as a support vector regression model provided the most accurate predictions of nitrogen use efficiency on a subfield scale. Crop response and nitrogen use efficiency models were integrated into a decision-making framework for optimized site-specific based nitrogen fertilizer management based on between maximized profits and minimized potential of nitrogen loss. Simulations of optimized site-specific nitrogen fertilizer management compared to farmer's status quo management showed a 100% probability across all fields tested that that mean net-return from the site-specific approaches were more profitable than applications of farmer selected nitrogen fertilizer rates. However, even while considering minimization of the potential for nitrogen loss when identifying optimum nitrogen fertilizer rates, there was field specific variation in the probability that site-specific, compared to farmer selected, nitrogen fertilizer management reduced the total amount of nitrogen applied across a field.Item Decomposition rates of residual crude oil in soil : a comparison of soil amendments(Montana State University - Bozeman, College of Agriculture, 1989) Cormier, Michael FrancisItem Comparative evaluation of solute transport using suction lysimeters, ion-exchange resin capsules and soil cores(Montana State University - Bozeman, College of Agriculture, 1994) Mulcahy, James MichaelItem Verification of resin capsule method for monitoring bromide transport in soils(Montana State University - Bozeman, College of Agriculture, 1992) Li, ChengmingItem Biodegradation of 2,4-dichlorophenoxyacetic acid (2,4-D) and pentachlorophenol (PCP) in soils(Montana State University - Bozeman, College of Agriculture, 1997) Doughten, Ronald Allen