Digital Elevation Models (DEMs) are computer-generated representations of the earth's surface. These surfaces can be used to predicted Line-of-Sight (LOS) radio propagation. DEM resolution can affect the results of this prediction. This study examines the effect of DEM resolution on accuracy by comparing varied resolution terrain data for a portion of Blacksburg, Virginia using the prediction of ESRI's ArcView® viewshed algorithm. Results show that resolutions between one-meter and thirty-meters have little effect on the aggregate accuracy of the viewshed. / Master of Science

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The purpose of this study was to determine if light detection and ranging (LiDAR) imagery could provide a significantly more accurate data set for modeling near line-of-sight (LOS) propagation at higher frequencies, specifically 27.810 GHz. than a USGS digital elevation model (DEM). In addition, the study tested for significant differences in LiDAR elevation data created at various resolutions ranging from 1 to 100 meters. Finally, this study examined the effects of various classification thresholds for transforming continuous signal strength measurements into LOS or non-LOS (NLOS) classifications used in determining prediction accuracy. The capability to transmit information via higher frequency wireless equipment requires a near LOS path between the transmitter and the antenna receiving the signal. USGS DEMs, commonly used in GIS programs to predict communication viewsheds (commsheds), represent the bare earth topography and do not reflect surface features such as vegetation and buildings. In actuality these surface features can significantly influence near LOS paths and therefore a data set that contains these features can greatly improve the ability to predict commshed areas. LiDAR is a form of active imagery that records both the bare-earth as well as these surface features, at a high resolution, making it well suited for wireless modeling applications. Results indicate that signal strength threshold classification has a direct influence on the accuracy of predicted commsheds across all resolutions. Secondly, LiDAR resolutions lower than 40m as well as bare-earth DEMs were unsuccessful in predicting an accurate commshed while LiDAR resolutions coarser than 15m provided significant predictions of equal accuracy. These results indicate that high resolution LiDAR is needed to accurately model commsheds but signal strength threshold classification determines which of these higher resolutions are significant. / Master of Science

Environmental 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. / Doctor of Philosophy / Centuries 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.

This thesis provides a novel investigation into rainfall-runoff processes occurring within a unique two-tiered depth-driven overland flow physical modelling environment, as well as within a numerical model context where parameterisation and DEM/building resolution influences have been investigated using an innovative de-coupled methodology. Two approaches to simulating urban rainfall-runoff responses were used. Firstly, a novel, 9 m2 physical modelling environment consisting of a: (i) a low-cost rainfall simulator component able to simulate consistent, uniformly distributed rainfall events of varying duration and intensity, and; (ii) a modular plot surface layer was used. Secondly, a numerical hydroinundation model (FloodMap2D-HydroInundation) was used to simulate a short-duration, high intensity surface water flood event (28th June 2012, Loughborough University campus). The physical model showed sensitivities to a number of meteorological and terrestrial factors. Results demonstrated intuitive model sensitivity to increasing the intensity and duration of rainfall, resulting in higher peak discharges and larger outflow volumes at the model outflow unit, as well as increases in the water depth within the physical model plot surface. Increases in percentage permeability were also shown to alter outflow flood hydrograph shape, volume, magnitude and timing due to storages within the physical model plot. Thus, a reduction in the overall volume of water received at the outflow hydrograph and a decrease in the peak of the flood event was observed with an increase in permeability coverage. Increases in the density of buildings resulted in a more rapid receding limb of the hydrograph and a steeper rising limb, suggesting a more rapid hydrological response. This indicates that buildings can have a channelling influence on surface water flows as well as a blockage effect. The layout and distribution of permeable elements was also shown to affect the rainfall-runoff response recorded at the model outflow, with downstream concentrated permeability resulting in statistically different hydrograph outflow data, but the layout of buildings was not seen to result in significant changes to the outflow flood hydrographs; outflow hydrographs appeared to only be influenced by the actual quantity and density of buildings, rather than their spatial distribution and placement within the catchment. Parameterisation of hydraulic (roughness) and hydrological (drainage rate, infiltration and evapotranspiration) model variables, and the influence of mesh resolution of elevation and building elements on surface water inundation outputs, both at the global and local level, were studied. Further, the viability of crowdsourced approaches to provide external model validation data in conjunction with dGPS water depth data was assessed. Parameterisation demonstrated that drainage rate changes within the expected range of parameter values resulted in considerable losses from the numerical model domain at global and local scales. Further, the model was also shown to be moderately sensitive to hydraulic conductivity and roughness parameterisation at both scales of analysis. Conversely, the parameterisation of evapotranspiration demonstrated that the model was largely insensitive to any changes of evapotranspiration rates at the global and local scales. Detailed analyses at the hotspot level were critical to calibrate and validate the numerical model, as well as allowing small-scale variations to be understood using at-a-point hydrograph assessments. A localised analysis was shown to be especially important to identify the effects of resolution changes in the DEM and buildings which were shown to be spatially dependent on the density, presence, size and geometry of buildings within the study site. The resolution of the topographic elements of a DEM were also shown to be crucial in altering the flood characteristics at the global and localised hotspot levels. A novel de-coupled investigation of the elevation and building components of the DEM in a strategic matrix of scenarios was used to understand the independent influence of building and topographic mesh resolution effects on surface water flood outputs. Notably, the inclusion of buildings on a DEM surface was shown to have a considerable influence on the distribution of flood waters through time (regardless of resolution), with the exclusion of buildings from the DEM grid being shown to produce less accurate results than altering the overall resolution of the horizontal DEM grid cells. This suggests that future surface water flood studies should focus on the inclusion and representation of buildings and structural features present on the DEM surface as these have a crucial role in modifying rainfall-runoff responses. Focus on building representation was shown to be more vital than concentrating on advances in the horizontal resolution of the grid cells which make up a DEM, as a DEM resolution of 2 m was shown to be sufficiently detailed to conduct the urban surface water flood modelling undertaken, supporting previous inundation research.

Regional landslide risk, as it is most commonly defined, is a product of the following: hazard, vulnerability and exposed population. The first objective of this research project is to estimate the regional landslide hazard level by calculating its probability of slope failure based on maximum slope angles, as estimated using data provided by digital elevation models (DEM). Furthermore, it addresses the impact of DEM resolution on perceived slope angles, using local averaging theory, by comparing the results predicted from DEM datasets of differing resolutions. Although the likelihood that a landslide will occur can be predicted with a hazard assessment model, the extent of the damage inflicted upon a region is a function of vulnerability. This introduces the second objective of this research project: vulnerability assessment. The third and final objective concerns the impact of urbanization and population growth on landslide risk levels.