Geographic and Socioeconomic Risk Factors for Sporadic Cryptosdporidiosis and \u3ci\u3eE. coli\u3c/i\u3e infection in East Tennessee

This research examines risk factors for sporadic cryptosporidiosis and Escherichia coli (E. coli) O157 infection in East Tennessee, using case-control and retrospective ecological approaches. Multiple models and approaches are used to identify risk factors for the two diseases, and to examine the effect of scale on risk for disease in the individual and in the population. Risk factors examined are animal density, land use, geology, surface water impairment, poverty rate and availability of private water supply. The research objectives are, first, to identify risk factors for E. coli O157 and cryptosporidiosis in East Tennessee by relating disease data to environmental data through statistical regression models and second, to examine the effect of scale by comparing risk factors for disease in the individual (case-control approach) and the population (ecological approach). At the individual level Generalized Linear Models (GLMs), Generalized Additive Models (GAMs), and Spatial Logistic Regression Models are compared. At the population level, Spatial Lag, GLMs and GAMs are developed using Gamma, Tweedie and Poisson distributions. Beef cow population density and proximity to karst geology are positively associated with both diseases at the individual scale. Land use variables representing developed land and pasture land are positively associated with both diseases at both scales. Poverty rate is positively associated with both diseases at the regional scale, and availability of private water supply is negatively associated with both diseases at both scales. The results presented here show that the significance of environmental variables as risk factors for cryptosporidiosis and E. coli O157 depend on scale, and that an examination of risk factors for these diseases in the individual and the population can reveal the scale at which variables are important. These results can be used to identify important environmental risk factors for the diseases and to identify the communities where background risk is highest. Limited public health resources can then be targeted to the risk factors and communities most at risk. These results can also be used as the framework upon which to develop a comprehensive epidemiological study that focuses on risk factors important at the individual level

Comparison of Geometric and Volumetric Methods to a 3D Solid Model for Measurement of Gully Erosion and Sediment Yield

Gully erosion is a global problem that degrades land and reduces its utility for agriculture, development, and water quality. Quantification of sediment yield and control of sediment sources is essential for environmental protection. Five methods to evaluate erosion rates and sediment yield on an east Tennessee, USA, hillslope were compared: (1) physical measurement by removal of accumulated sediment using 10 L buckets; (2) repeated measurement of erosion pins in gully (erosional) and delta (depositional) areas; (3) geometric model using a combination trapezoidal prism-cylinder segment; (4) geometric model using a series of trapezoidal pyramids; and (5) 3D solid computer modeling. The 3D solid model created in SolidWorks was selected as the reference model and all other methods overestimated sediment yield to varying degrees. Erosion pin methods overestimated sediment yield by 368% in deltas and 123% in gullies. Volumetric measurement of sediment using buckets overestimated sediment yield by 160% due to void space in the buckets. The trapezoidal prism-cylinder segment model overestimated sediment yield by 66% and the trapezoidal pyramids method overestimated sediment yield by 5.7%. For estimation of sediment trapped behind an elliptical or circular silt fence dam, use of the trapezoidal pyramid method provides a good approximation comparable to 3D solid computer modeling

Spatiotemporal analysis of flooding in Tennessee counties: 1996-2021

Tennessee has a long history of floods that have caused property damage and loss of life. In the face of climate change and variability, it is imperative to look at trends to ascertain if there is a significant change in current flood regimes versus past flood events. Trend Analysis and Emerging Hotspot Analysis are useful geospatial tools that can effectively display changes over time and space. This study aims to evaluate the history of flood events in Tennessee to identify spatiotemporal trends and hot spots. A total of 902 flood events from 1996-2021 recorded in the National Oceanic Atmospheric Agency (NOAA) storm events database were analyzed using the number of events per county and the total damages per county at an annual time step. Two 26-year space-time cubes were built in ArcGIS Pro (version 3.0) for flood events and damages using an annual time step, with counties as the spatial unit. GeoGa software (version 1.20.0.22) was used to weight the distance between Tennessee counties to define a statistically significant neighborhood distance at 37km fixed distance. Trend Analysis and Emerging Hotspot Analysis was conducted to assess spatiotemporal trends in flooding events and damages (in dollars). Trend analysis revealed an increasing trend of flood events in eleven counties in middle Tennessee (Davidson, Wilson, Rutherford, Coffee, Marion, Putnam, Overton, Maury, Lawrence and Dickson counties) and Carter county in east Tennessee. Decreasing trends were observed in two counties (Lake and Bradley), all at a 90% or greater confidence level. Increasing trends in flood damages were identified in Cumberland, Putnam, Lawrence, Blount, Sullivan and Green counties, all in east and middle Tennessee. Decreasing trends were identified in Lake, Obion, Dyer, and Tipton, all in west Tennessee. East Tennessee was identified as a sporadic flooding hot spot (Hawkins, Green and Washington counties) with no significant hot spots in middle and west Tennessee. There were no hot spots nor cold spots in flood-related damages across Tennessee. The results indicate that flood events and related damages are decreasing in west Tennessee while parts of middle Tennessee and east Tennessee are experiencing increased flood events. This study is an important step to better understand spatiotemporal trends in flooding and flooding damages and will be useful in hazard mitigation planning in Tennessee at both state and county levels

Seasonal Precipitation Variability and Gully Erosion in Southeastern USA

This study examines the relationship between gully erosion in channels, sidewalls, and interfluves, and precipitation parameters (duration, total accumulation, average intensity, and maximum intensity) annually and seasonally to determine seasonal drivers for precipitation-related erosion. Ordinary Least Square regression models of erosion using precipitation and antecedent precipitation at weekly lags of up to twelve weeks were developed for three erosion variables for each of three geomorphic areas: channels, interfluves, and sidewalls (nine models in total). Erosion was most pronounced in winter months, followed by spring, indicating the influence of high-intensity precipitation from frontal systems and repeated freeze-thaw cycles in winter; erosion in summer was driven by high-intensity precipitation from convectional storms. Annually, duration was the most important driver for erosion, however, during winter and summer months, precipitation intensity was dominant. Seasonal models retained average and maximum precipitation as drivers for erosion in winter months (dominated by frontal systems), and retained maximum precipitation intensity as a driver for erosion in summer months (dominated by convectional storms). In channels, precipitation duration was the dominant driver for erosion due to runoff-related erosion, while in sidewalls and interfluves intensity parameters were equally important as duration, likely related to rain splash erosion. These results show that the character of precipitation, which varies seasonally, is an important driver for gully erosion and that studies of precipitation-driven erosion should consider partitioning data by season to identify these drivers

Freeze-Thaw Induced Gully Erosion: A Long-Term High-Resolution Analysis

Gullies are significant contributors of sediment to streams in the southeastern USA. This study investigated gully erosion in the clay-rich soils of east Tennessee under a humid subtropical climate. The aims of this study were to (1) estimate long-term erosion rates for different gully geomorphic settings, (2) compare patterns of erosion for the different settings, and (3) model the response of gully erosion to freeze-thaw events. Erosion was measured weekly from June 2012 to August 2018 using 105 erosion pins distributed in gully channels, interfluves, and sidewalls. Erosion rates were estimated from average slopes of lines of best fit of pin lengths versus time. Maximum and minimum temperature was calculated daily using an on-site weather station and freeze-thaw events were identified. Gully erosion was modeled using antecedent freeze-thaw activity for the three geomorphic settings. Long-term erosion rates in channels, interfluves, and sidewalls were 2.5 mm/year, 20 mm/year, and 21 mm/year, respectively; however, week-by-week erosion was statistically different between the three settings, indicating different erosive drivers. Models of erosion with lagged freeze-thaw variables explained up to 34.8% of the variability in erosion variables; sidewall erosion was most highly related to freeze-thaw activity. Freeze-thaw in prior weeks was an important variable in all erosion models

Evaluation of Karst Spring Water Quality Using Water Quality Indices in Northeast Tennessee

Ensuring access to safe drinking water to protect public health in many communities underserved or unserved by centralized water systems in the US requires regular water quality testing and reporting. Following testing, access to easy-to-comprehend water quality information may be challenging. Households served by water utilities have access to water quality information. However, households depending on unregulated water systems like wells and springs are often unaware of their water quality. Therefore, this study utilized multiple water quality parameters to determine the quality of karst spring water using two Water Quality Index (WQI) methods. In-situ measurements of physico-chemical parameters (pH, dissolved oxygen, temperature, turbidity, conductivity, specific conductance, total dissolved solids, oxidation reduction potential were taken at 50 karst springs in east Tennessee during Summer 2021. Water samples were analyzed for microbial (fecal coliform, and E. coli), nutrients (nitrate and nitrite), and radiological (radon) constituents using standard analytical methods. Springs generally met federal and state water quality safe limits for physicochemical parameters, but 100% of water samples contained fecal coliform and 90% contained E. coli revealing widespread fecal contamination; 60% of springs exceeded radon concentrations of 300 pCi/L. WQI method 1 (Brown et al. 1972) rated 12 % of springs as very poor water quality and 88% as unfit for drinking. WQI method 2 (NSFWQI) rated 4% of the sampled springs as good, 92% as moderate and 4 % as bad. Water treatment procedures for microbial pollution purification are advised before the studied springs are used as a drinking water source

Analyzing landslide hotspots and susceptibility in East Tennessee transportation corridors

Landslides in the Southern Appalachian Mountains of East Tennessee often activate and reactivate. Often triggered by high-intensity or prolonged rainfall, landslides are responsible for infrastructure damage, closure of transportation routes, and even fatality. The study area is defined by the New River Watershed which has high elevation and steep slopes cutting through State Route 116. The route has hairpin turns and has experienced damage from past landslide events. The geology here is mostly shale and sandstones with coal bedding throughout. Much of the soil consists of a fine-loamy texture. Most drainage occurs from the New River, fed by runoff from slopes into roadways. This area experiences heavy rainfall with a yearly average of 70 inches. Landcover consists of a mostly forested landscape with shrubs and grassland. In response to previous landslides, the Tennessee Department of Transportation (TDOT) recently repaired six areas within the route intercepted by recent landslides. Aside from the landslides near TDOT’s corridors, approximately 50 additional landslides have been found using Google Earth and LiDAR data. Landslide hotspots were identified using kernel density estimation and the nearest neighbor index. A heuristic landslide susceptibility model was prepared by weighing the ArcGIS layers: slope, soil particle, geology, curvature, elevation, distance from the stream, and land cover, in their contribution to the previous landslides. Results indicate that additional sites in Anderson and Morgan County should be studied further for potential landslide-related damage. The study will improve the proactive decisions of TDOT and justify timely monitoring, maintenance, and strategic protection of the route from slope hazards

Preliminary site assessment for ground monitoring of a complex landslide along I-40 in Roane County, Tennessee

In-ground slope monitoring is an essential part of landslide early warning systems. Precise movement data from borehole monitors can detect emerging hazards near critical infrastructure. Typically, monitoring is done with inclinometers, but lower-cost alternatives have emerged which have yet to be tested in Tennessee. Time domain reflectometry (TDR) records magnitudes and depths of movements along a buried coaxial cable. When paired with a remote data logger, TDR can wirelessly transmit high resolution movement data in real time, making it promising for landslide early warning systems. Tennessee Department of Transportation (TDOT) has proposed a one-year feasibility study to test TDR for use in unstable soil slopes near highways. The study area is a well-known landslide site along Interstate 40 in Roane County, TN. Careful siting of borehole instrumentation is crucial for accurate monitoring. The goal of this study is to optimize TDR installation, with three specific aims: (i) evaluate landslide morphology, (ii) pinpoint locations and depths with greatest movement, and (iii) assess spatiotemporal patterns across the site. Statistical analysis of prior data from 13 inclinometers showed ongoing slope movement over the 21-acre complex landslide. Spatial interpolation suggested an asymmetrical failure surface with both shallow and deep motion. Space-time cube analysis indicated varying movement rates and timing across the site, suggesting separate landslide bodies. Based on these results, three optimal borehole depths and locations were proposed for TDR instruments. This analysis will ensure accuracy in tests of TDR for early warning system feasibility in Tennessee

Using Spatial Regression to Model Potentially Toxic Metal (PTM) Mobility Based on Physicochemical Soil Properties

Mining processes generate waste rock, tailings, and slag that can increase potentially toxic metal (PTM) concentrations in soils. Un-reclaimed, abandoned mine sites are particularly prone to leaching these contaminants, which may accumulate and pose significant environmental and public health concerns. The characterization and spatial delineation of PTMs in soils is vital for risk assessment and soil reclamation. Bumpus Cove, a once active mining district of eastern Tennessee, is home to at least 47 abandoned, un-reclaimed mines, all permanently closed by the 1950s. This study evaluated soil physicochemical properties, determined the spatial extent of PTMs (Zn, Mn, Cu, Pb, and Cd), and examined the influence of soil properties on PTM distribution in Bumpus Cove, TN. Soil samples (n = 52) were collected from a 0.67 km2 study area containing 6 known abandoned Pb, Zn, and Mn mines at the headwaters of Bumpus Cove Creek. Samples were analyzed for Zn, Mn, Cu, Pb, and Cd by microwave-assisted acid digestion and flame atomic absorption spectrometry (FAAS) (12-1,354 mg/kg Zn, 6-2,574 mg/kg Mn, 1-65 mg/kg Cu, 33-2,271 mg/kg Pb, and 7-40 mg/kg Cd). Of the measured PTMs, only Pb exceeds permissible limits in soils. In addition to the PTM analyses, soil physical (texture, moisture content, and bulk density) and chemical (pH, cation exchange capacity (CEC), and total organic carbon (TOC)) properties were evaluated. Spatially weighted multivariate regression models developed for all PTMs using soil physicochemical properties produced improved results over ordinary least squares (OLS) regression models. Models for Zn (R2 = 0.71) and Pb (R2 = 0.69) retained covariates epH, moisture content, and CEC (Zn), and pH and CEC (Pb). This study will help define PTM concentration and transport and provide a reference for state and local entities responsible for contaminant monitoring in Bumpus Cove, TN

Preparing a Small Town for a Hazardous Materials Incident: An Examination of Evacuation Routing Algorithms and Plume Models

Evacuation and shelter in place are two common protective action measures during hazardous events that involve the release of hazardous materials. These responses are complex and require advanced planning to determine their appropriateness to reduce human exposure to hazardous materials and minimize related health risks. Evacuation and shelter in place responses were assessed for people in the town of Erwin, Tennessee, USA, a small, rural town in the mountains of Northeast Tennessee, using a release of uranium hexafluoride (UF6). The population at risk was identified using historical meteorological data and the Radiological Assessment System for Consequence Analysis tool to create plume models for a hypothetical release of UF6 from a nuclear fuel facility that downblends highly enriched uranium. Two hypothetical evacuation scenarios were modeled. One uses the total road network in Erwin and the other involves a train impeding access to an arterial evacuation route. Two routing algorithms available within the custom network analyst routing tool (ArcCASPER) were used for each scenario: 1) a basic shortest path algorithm and 2) a capacity-aware shortest path evacuation routing algorithm. Post-hoc analyses of each scenario and algorithm indicated that the capacity-aware algorithm predicted the quickest evacuation times for both scenarios. Roads with the longest evacuation times and all critical facilities that would benefit from sheltering in place were identified. The study concluded that the capacity-aware algorithm available within ArcCASPER is the most realistic for the town of Erwin