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Improved Environmental Characterization to Support Natural Resource Decision Making: (1) Distributed Soil Characterization, and (2) Treatment of Legacy Nutrients

dc.contributor.authorBuell, Elyce N.en
dc.contributor.committeechairEaston, Zachary M.en
dc.contributor.committeememberStephenson, Stephen Kurten
dc.contributor.committeememberShortridge, Julie Elizabethen
dc.contributor.committeememberLeman, Scotland C.en
dc.contributor.departmentBiological Systems Engineeringen
dc.date.accessioned2022-09-28T08:00:09Zen
dc.date.available2022-09-28T08:00:09Zen
dc.date.issued2022-09-27en
dc.description.abstractEnvironmental concerns are becoming increasingly relevant during a period of hemorrhaging ecosystem goods and services. Restoring these would result in positive outcomes for public health and economic benefit. This thesis seeks to address two environmental concerns: (1) accurate soil mapping and (2) treatment of nitrogen to affect water quality change.The current method of soil mapping, SSURGO (USDA‐NRCS Soil survey), is often erroneous and misleading. Two studies in this dissertation are conducted to evaluate the potential that different resolution digital elevation models (DEMs) have to distribute soil characteristics successfully. These studies are conducted in southwest Virginia and western Vermont. The aforementioned studies evaluated 36 and 59 soil samples, respectively. Spatial characteristics, including slope, catchment area, and topographic wetness, are derived from several DEMs. In chapter 2, these characteristics are spatially compared, and we found that small resolution rasters result in narrow flow paths relative to coarser rasters. In chapter 3, we isolate the analysis to focus on resolution size, instead of a mix of both resolution size and generation method. This is done by recursively coarsening small rasters, deriving spatial attributes from said rasters and evaluating their potential to fit the soil characteristics of interest. Here we found that slopes generated from resolutions smaller than 11m were poor predictors of soil characteristics. Both chapters are finished by proposing and evaluating a soil map. Proposed regressions beat SSURGO in all investigated properties. Furthermore, proposed maps consistently beat out uninformed smallest resolution derived maps.Chesapeake bay water quality managers are struggling to achieve targets for nitrogen loading. This is in part due to the widespread presence of legacy nitrogen. Legacy nitrogen is an emerging issue, and springs exporting high levels of nitrogen are not uncommon in northern Virginia. This thesis explores, in part, a novel concept of treating large loads of nitrogen exported from a spring with a bioreactor. Bioreactors are a young science that most typically pair carbon heavy subterranean receptacles to agricultural drainage. This provides a location for nitrogen fixing bacteria to consume nitrate/nitrite, turning these into inert nitrogen gas. A spring fed bioreactor is studied for 10 months, and bioreactor conditions including influent and effluent nitrogen concentrations, bioreactor flow, and temperature are collected. A model driven by first order reaction equations is found to be most accurate with inputs of temperature and bioreactor age. The resulting marginal effects of these inputs were consistent with previously reported studies.en
dc.description.abstractgeneralCenturies of industrialization have resulted in widespread human progress but have, at times, adversely impacted the environment. Constituents rely heavily on environmental services, such as clean air and water, to subsist. Environmental degradation has resulted in detrimental effects to public health, and remediation is currently economically viable. As such, there are strong incentives for researchers to understand environmental processes at a fundamental level. One such process is soil characteristic distribution. The distribution of soil characteristics, such as soil texture or organic matter, is especially important for agriculturalists, hydrologists and geotechnicians. Soil texture and organic matter distribution can affect crop yield, nitrogen export to surface waters, and structural stability of soils. Thus, accurate characterization of measured soil properties is paramount to multiple fields. The most typically used soil map is USDA‐NRCS Soil survey (commonly referred to as SSURGO). Currently, the SSURGO database is a poor predictor of soil characteristics. There is an opportunity to improve soil characteristic distribution using digital elevation models (DEMs). As DEMs become cheaper to develop, they are typically available in multiple resolutions and generation methods. In this research, several DEMs are used to better soil maps for watersheds in Southwest Virginia and Western Vermont. Both studies showed that DEMs can better distribute soils when compared to the current SSURGO maps. Additionally, we showed that the finest resolution dataset was not always best, and mixed resolution topographic wetness indices to be most advantageous for distributing soils.Another such process is remediation of surface waters from high loads of nitrogen and phosphorus. The Haber-Bosch method of producing nitrogen fertilizer is one of the most important human innovations in recent history. This method is likely responsible for the aversion of widespread famine in the early 1900s. However, residents of multiple river systems, including the Chesapeake Bay and the Mississippi River, are suffering from the adverse effects of widespread hypoxic/anoxic (with little/no oxygen, respectively) zones within water. These have partially been responsible for the decline of commercial ventures such as fisheries and tourism. These zones are caused by eutrophication, a process of unsustainable plant growth in the presence of nitrogen and phosphorus. Water quality managers typically target agricultural runoff and point source polluters when trying to eliminate anthropogenic nitrogen. However, legacy nitrogen (nitrogen stored in groundwater in excess of a year) has become an emerging concern for water quality. It is not uncommon for springs in karst areas to be contaminated with high concentrations of nitrogen. These springs present a point source that can be treated by an emerging technology: bioreactors. Bioreactors are subterranean, woodchip filled basins that provide a location for microbes to exchange water soluble nitrogen for inert nitrogen gas. The consistency in nitrogen loading and constant flow provide stability relative to more traditional bioreactor installations. Most typically, bioreactors are installed downstream of agricultural drainage systems, and influent flow and nitrogen load depend wholly on precipitation/irrigation and nitrogen application. In this thesis, a novel spring fed bioreactor is studied. Removal rates of nitrogen are quantified using a regression driven by reaction kinetics. The analysis showed bioreactor efficiency was intimately related to hydraulic residence time, nitrogen loading, bioreactor bed temperature, and bioreactor age. The spring fed bioreactor is found to be advantageous because of its consistency, and disadvantages because springs are colder and thus less efficient than typical irrigated runoff.en
dc.description.degreeDoctor of Philosophyen
dc.format.mediumETDen
dc.identifier.othervt_gsexam:35494en
dc.identifier.urihttp://hdl.handle.net/10919/112013en
dc.language.isoenen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectSoil Physical Propertiesen
dc.subjectDigital Elevation Model (DEM) Resolutionen
dc.subjectTopographic Indexen
dc.subjectSpecific Catchment Areaen
dc.subjectSlopeen
dc.subjectbioreactorsen
dc.subjectlegacy nitrogenen
dc.subjectbest management practicesen
dc.titleImproved Environmental Characterization to Support Natural Resource Decision Making: (1) Distributed Soil Characterization, and (2) Treatment of Legacy Nutrientsen
dc.typeDissertationen
thesis.degree.disciplineBiological Systems Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.nameDoctor of Philosophyen

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