Ingrid Luffman

Ensuring access to safe drinking water to protect public health in communities underserved or unserved by centralized water systems requires regular water quality testing and reporting. However, households depending on unregulated water systems like wells and springs, which are less routinely tested, may be unaware of their water quality. Access to easy‐to‐comprehend water quality information may be challenging. Therefore, this study utilized multiple water quality parameters to determine karst spring water quality using two water quality index (WQI) methods. This approach aggregates and summarizes water quality data into a single value or index characterizing the general health status of water at a given location in an easy‐to‐understand way. In situ measurements of physicochemical parameters (pH, dissolved oxygen, temperature, turbidity, conductivity, specific conductance, total dissolved solids, and oxidation–reduction potential) were taken at 50 karst springs in east Tennessee during summer 2021. Water samples were analyzed for microbial (fecal coliform and Escherichia coli), nutrients (nitrate and nitrite), and radiological (radon) constituents using standard analytical methods. WQI method 1 (Brown et al. Water Quality Index) rated 12% of springs as “very poor” water quality and 88% as “unfit for drinking.” WQI method 2 (National Sanitation Foundation Water Quality Index) rated 4% of the sampled springs as “good,” 92% as “moderate,” and 4% as “bad.” Given the prevalence of fecal contamination in the sampled springs, even springs rated good should be properly treated before consumption. Overall, these findings demonstrate the importance of selecting appropriate WQI for the end water use, and for water quality information that is easily understandable by water users.

An important first step in the geotechnical asset management of Great Smoky Mountains National Park (GRSM) is the creation of an unstable slope inventory along major transportation corridors. Slope-stability problems are frequent in GRSM, often initiated in highly weathered and fractured metasedimentary rocks. In this study, an unstable slope inventory was created using the Unstable Slope Management Program for Federal Land Management Agencies protocols. Hazards and risks were evaluated for 285 unstable slopes along 243.67 km of roadway. Kernel density estimation was used to identify unstable slope hotspots and establish 14 sites for site-specific investigations to evaluate potential impacts of discrete unstable slopes along major roadways. Two-dimensional probabilistic rockfall simulations and acid-base accounting tests were used to predict rockfall pathways and evaluate the acid-producing potential of rocks. Simulations indicated that rock material would likely enter the roadway at all 14 sites. Acid-base accounting test results indicated that slaty rocks of the Anakeesta Formation and graphitic schist of the Wehutty Formation are primary acid-producing rocks in rockfall-prone areas. This research illustrates an approach for prioritizing areas for site-specific investigations towards the goal of improving safety in GRSM, including developing mitigation strategies for rockfall by widening ditches, installing barriers, and encapsulating acidic rockfall material.

Aeolian erosion is a significant but overlooked factor in gully erosion in humi...

Karst springs are an essential source of private water supply for about 10% of households in Tennessee. However, the water quality of these springs is unmonitored and unregulated even though many springs are highly productive yet vulnerable to contamination. This study assesses spatial patterns in the water quality of roadside springs in northeast Tennessee. Karst spring water samples collected from 50 springs were assessed using EPA Standard methods for pathogens, nutrients, radon, and physicochemical parameters. From statistical and spatial analyses, all but five samples contained E. coli, while all samples contained fecal coliform. High E. coli was spatially clustered (Local Moran’s I = 0.177, pseudo p-value = 0.012) in regions of high agricultural land use, resulting in a fecal contamination hot spot on the border of Washington and Sullivan Counties, Tennessee. Radon concentrations exceeded the 300 pCi/L proposed MCL in 29 (58%) of springs, with one spring in Unicoi County exceeding 1000 pCi/L. A radon hot spot was identified in northern Washington County (Local Moran’s I = 0.160, pseudo p-value = 0.014). Cokriging of E. coli with land use and radon with distance to mapped fault did not improve interpolation models for either parameter. Other parameters, including nitrate, pH, and total dissolved solids, were within recommended ranges for drinking water. This snapshot of spring water quality status identifies areas of poor spring water quality of which spring water users in the region should be aware, and establishes the need for longitudinal sampling of spring water quality in contamination hot spots.

Volunteered Geographic Information, data contributed by community scientists, is an increasingly popular tool to collect scientific data, involve the community in scientific research, and provide information and education about a prominent issue. Johnson City, Tennnessee, USA has a long history of downtown flooding, and recent redevelopment of two land parcels has created new city parks that mitigate flooding through floodwater storage, additional channel capacity, and reduced impervious surfaces. At Founders Park, a project to collect stage data using text messages from community scientists has collected 1479 stage measurements from 597 participants from May 2017 through July 2021. Text messages were parsed to extract the stage and merged with local precipitation data to assess the stream’s response to precipitation. Of 1479 observations, 96.7% were correctly parsed. Only 3% of observations were false positives (parser extracted incorrect stage value) or false negatives (parser unable to extract correct value but usable data were reported). Less than 2% of observations were received between 11 p.m. and 7 a.m., creating an overnight data gap, and fewer than 7% of observations were made during or immediately following precipitation. Regression models for stage using antecedent precipitation explained 21.6% of the variability in stream stage. Increased participation and development of an automated system to record stage data at regular intervals will provide data to validate community observations and develop more robust rainfall–runoff models.

Inorganic contaminants, including potentially toxic metals (PTMs), originating from un-reclaimed abandoned mine areas may accumulate in soils and present significant distress to environmental and public health. The ability to generate realistic spatial distribution models of such contamination is important for risk assessment and remedial planning of sites where this has occurred. This study evaluated the prediction accuracy of optimized ordinary kriging compared to spatial regression-informed cokriging for PTMs (Zn, Mn, Cu, Pb, and Cd) in soils near abandoned mines in Bumpus Cove, Tennessee, USA. Cokriging variables and neighborhood sizes were systematically selected from prior statistical analyses based on the association with PTM transport and soil physico-chemical properties (soil texture, moisture content, bulk density, pH, cation exchange capacity (CEC), and total organic carbon (TOC)). A log transform was applied to fit the frequency histograms to a normal distribution. Superior models were chosen based on six diagnostics (ME, RMS, MES, RMSS, ASE, and ASE-RMS), which produced mixed results. Cokriging models were preferred for Mn, Zn, Cu, and Cd, whereas ordinary kriging yielded better model results for Pb. This study determined that the preliminary process of developing spatial regression models, thus enabling the selection of contributing soil properties, can improve the interpolation accuracy of PTMs in abandoned mine sites.

The first reported case of COVID-19 in Tennessee (TN) occurred on March 5, 2020, growing to 580,809 cases state-wide by the end of 2020. A GIS dashboard was developed using data from the TN Department of Health to communicate state-wide COVID-19 spread, and a relationship between pandemic development and rurality was observed during the first wave (through September 2020), noted in other US and global research. Because > 90% of TN counties are designated rural or mixed-rural, we examined metrics to describe development as it relates to rurality. Metrics included days to the first case/hospitalization/fatality, days between state and county peak, and days to an incidence rate of ten per 100,000. Metrics were compared within different classes of rurality, using seven rurality classification schemes. Significant differences were noted in four of the five metrics between classes of rurality. Rural counties in TN experienced significant lags to the first case, hospitalization, and fatality, and the peak cases in rural counties were delayed relative to urban counties when outlier counties with early state prison outbreaks were excluded. In rural TN counties, regardless of rurality definition, cases, hospitalizations, and fatalities were slower to appear. However, once community spread was established, rurality no longer had a protective effect.

Sinking Creek (HUC 06010103046), in the Watauga watershed of northeast Tennessee, is impaired due to Escherichia coli. To assess how E. coli and other water quality parameters fluctuated during storm events, water samples were collected with automated samplers during eight storms at two locations: Sinking Creek and a feeder spring. Turbidity and electrical conductivity data loggers were deployed in the creek, and dissolved oxygen (DO) was measured in situ. The presence of optical brighteners, used in detergents and an indicator of residential wastewater, was assessed using cotton fabric deployed at both sites and analyzed by an external laboratory. The Colilert Quanti‐Tray method was used to process water samples for E. coli. Relationships between water quality parameters and lagged precipitation were assessed using cross‐correlation. At the creek, E. coli and turbidity increased within 2 h of precipitation, exceeding the single sample water quality standard of 941 cfu 100 ml⁻¹ during the storm. At the spring, E. coli became elevated more quickly than at the stream, within 30 min of precipitation, and decreased below the standard during the event. Electrical conductivity decreased within 1.5 h of the storm at the creek, and DO levels were higher at the creek than at the spring. Optical brightener analysis indicated possible presence of residential wastewater during one of two sampled storms. Targeted sampling and dye tracing are recommended to validate this hypothesis. These results may be used to inform field methods in similar storm sampling studies and will be useful in watershed restoration efforts in Sinking Creek.