Geology topics
Source-linked reports with geographic coverage including Tennessee.
Using 3D Elevation Program data, a modern illustration of each State's landscape showcases its elevation differences in vivid detail. Each State has been consistently adjusted and colorized according to its highest and lowest elevations, accentuating differences even in States with low relief. To further emphasize landforms, shaded relief has been added on top of the elevation colors.
Self-potential (SP) monitoring has emerged as a valuable method for characterizing subsurface hydrogeological features and processes due to its sensitivity to fluid-induced electrokinetic effects. Despite advancements in SP inversion, challenges remain in imaging groundwater dynamics from SP activities due to complex hydrological settings and transient noise. In this study, a deep learning autoencoder (AE)-based framework is proposed for the spatiotemporal localization of subsurface fluid movement from time-lapse SP tomography. Temporal segments of time-lapse numerical inversions were first derived from long-term SP monitoring conducted from a floodplain site in Oak Ridge, Tennessee, known for active hyporheic exchange. Subsequently, AE models based on vision transformer (ViT), convolutional long short-term memory (ConvLSTM), convolutional neural network, and temporal convolutional network were individually trained and compared on the SP tomography segments for reconstruction performance. Finally, the reconstruction error over time serves as an anomaly score to identify moments of active SP variation, whereas spatial distributions of errors within these moments are analyzed to image and localize regions associated with anomalous subsurface fluid movement. The results demonstrate that ConvLSTM- and ViT-AE are most capable for the localization task with contrasting error distributions and consistent delineation of anomalies. Applying the method to both SP arrays parallel and perpendicular to the stream produced consistent anomaly zones near a fault or karst feature, validating the robustness and generalization of the approach. These results demonstrate the potential of the proposed framework as a scalable and interpretable tool for spatiotemporal analysis of subsurface flow dynamics in complex hydrogeological systems.
Cyanobacterial toxins (cyanotoxins) threaten aquatic ecosystems and human health, yet the factors influencing their production and distribution in freshwater remain unclear. In north-central Tennessee, nutrient-rich runoff from agricultural and urban areas, combined with a karst landscape that supports drinking and recreational water use, heightens the need to understand cyanotoxin behavior. To examine cyanotoxin patterns, the U.S. Geological Survey and the Tennessee Department of Environment and Conservation monitored 18 sites, including two wells under the influence of surface water, every two weeks from September 2022 to November 2024. At least one cyanotoxin was detected at all sites, with the highest concentrations in deep reservoirs and lower levels in shallow systems. Most detections occurred during summer and fall, aligning with high temperatures and rapid-onset drought. Statistical analysis indicated that increased specific conductivity and pH raised the likelihood of detecting total microcystin, likely resulting from drought conditions and nutrient-laden runoff. Additionally, dissolved microcystin showed an inverse relationship with Cumberland River water levels, and principal component analysis showed that Secchi depth, chlorophyll a, pH, temperature, and conductivity explained most water quality variability. These results help increase understanding of cyanotoxin distribution and associated water quality conditions during detections to guide future freshwater cyanotoxin monitoring studies.
The Duck River is a remarkable national resource, boasting outstanding biodiversity (Ahlstedt et al. 2017). It contains 151 fish species, over 60 mussel species, and 22 snail species, many of which are federally listed (Etnier and Starnes 1993; Johnson et al. 2013; Ahlstedt et al. 2017; Womble and Rosenberger 2025a). The Duck River watershed is at a pivotal time in its management and ecological history due to significant growth in human population and economic activity. The consequent increase in surface water demand presents challenges for sustainable water resource management. The Tennessee Department of Environment and Conservation (TDEC) has permitted or proposed to permit eight water utilities to withdraw over 77 million gallons per day (mgd) from the Duck River, representing > 40% increase from previously permitted amounts (USFWS 2025). On November 20, 2024, Tennessee Governor Bill Lee signed Executive Order No 108 to ensure long-term stability of the Duck River watershed through balancing economic growth, water resource management, and environmental conservation. Some primary components of this plan are the creation of a Comprehensive Regional Drought Management Plan, the development of a Habitat Conservation Plan, and the establishment of the Duck River Watershed Planning Partnership (DRWPP). Although the planning partnership is not focused on a sole aspect of the Duck River, but the watershed as a whole, the mussel assemblages of the Duck River have been a particular focus due to their importance in providing ecosystem services, sensitivity to water quality, conservation status, and sensitivity to periodic drought conditions in this system. With multiple state and federal agencies involved in managing the Duck River’s unique water resources, a focused review on how future water management could affect the freshwater mussel communities in the Duck River will contribute to this process. Our objectives of this review are to: 1. Review the effects of changing flow regimes on mussels, with emphasis on the effect of droughts/low flows, highlighting key processes/factors affecting mussels. 2. Highlight critical data gaps that could allow future, evidence-based water management decisions in this system. 3. Propose research topics to address critical data gaps and enable evidence-based water management decisions that consider the needs of freshwater mussels. Freshwater mussels are a critical component of riverine ecosystems, providing ecosystem services including water filtration, nutrient cycling, and habitat provision (Vaughn et al. 2004; Haag 2012) that benefit human communities. Environmental flows, also referred to as ecological or e-flows, refer to the quantity, timing, and quality of water flows necessary to maintain the ecological health of rivers, wetlands, and other aquatic ecosystems (Acreman and Dunbar 2004; Acreman 2016). For freshwater mussels, environmental flows include maintaining a flow regime and associated water quality regimes that are favorable for both juveniles and adults while also seasonally supporting host fish and the survival of settling glochidia (i.e., larval mussels) in suitable environments (Gates et al. 2015). Freshwater mussels are adapted to the natural flow regime of their native streams, including seasonal variability in flows. As sedentary filter feeders, mussels require adequate water flow to provide oxygen and food (Allen and Vaughn 2009); however, they also require periods of low flow to increase access to fish hosts and to ensure juveniles are not displaced (Gates et al 2015). Mussels are sensitive to water quality conditions, including pollutants, sedimentation, and artificial alterations of temperature and pH (Strayer and Malcom 2012). Mussel community characteristics, including presence, abundance, and species richness, generally increase with stream size (e.g., stream order); however, responses to changes in flow conditions are often species-specific, and the magnitude and timing of extreme flow conditions have more predictive power for mussel community response than general changes in flow (Lopez and Vaughn 2021). Complex hydraulic variables, such as relative shear stress and Reynolds number, can be strong predictors of mussel community responses because they combine simple hydraulic variables (e.g., velocity, depth) with stream channel characteristics, such as substrate composition and dynamics. Droughts directly and indirectly affect mussels by influencing their physiology, behavior, reproduction, and ecosystem roles. Mass mussel die-offs during droughts and low water conditions are widely documented (Vaughn et al. 2015; Sousa et al. 2018; Dubose et al. 2019). Droughts can also lead to a shift in mussel community composition, with drought-tolerant species becoming more dominant while more sensitive species experience declines (Galbraith et al, 2010; Lopez et al. 2022; Vaughn and Atkinson 2025). Droughts affect mussels through direct mortality from stranding as well as physiological stress from altered water temperature and quality, reduced habitat and food availability and quality, increased predation and competition, disruption of reproductive cycles, and increased susceptibility to disease and pathogens. Although the effects of droughts, water withdrawals, and low flow conditions on mussels are an increasing area of study, there is a general paucity of data-driven consensus regarding optimal mitigation approaches and strategies (Cushway et al. 2024). Long-term management decisions regarding water withdrawals, particularly during extended or multi-year drought conditions, may consider factors beyond direct mortality such as the sublethal effects of drought and low flow conditions on freshwater mussels for a comprehensive understanding of the effects of prolonged low flows on freshwater mussels and aquatic communities.
Reservoir cascades in large river systems impose directional pathways that can structure biological invasions, yet how these pathways interact with propagule supply and lock-mediated passage opportunity to influence arrival timing remains poorly understood. We used interval- and right-censored time-to-event models to evaluate spread dynamics of silver carp ( Hypophthalmichthys molitrix ) across the Tennessee River and Cumberland River reservoir cascades and test whether the timing of first detection was explained by position within the cascade, annual water locked, or accumulated propagule exposure from downstream source populations. The timing of first detection was related to distance from the invasion source, but cumulative exposure metrics offered no supplementary model support, suggesting that arrival timing was mostly associated with position within the cascade. Models incorporating annual water locked offered modest supplementary support, suggesting that lock-mediated passage opportunity may partially influence the progression of the invasion front. Spread progressed directionally but was not complete in the Tennessee River cascade, indicating that pathway structure alone does not guarantee arrival. Patterns were consistent across both rivers, suggesting that spread through reservoir cascades can follow repeatable patterns in which arrivals are constrained by downstream source populations and lock-mediated connectivity. From a management perspective, our results suggest distinct leverage points across spatial and temporal scales, including early detection and containment at downstream reservoirs, suppression of source populations to slow spread, and interventions at invasion fronts or key connectivity points to limit further expansion. Recognizing reservoir cascades as directional dispersal pathways provides a simple and transferable basis for anticipating and managing invasions in large river networks.
Eastern wild turkey ( Meleagris gallopavo silvestris ) population growth is driven by variation in reproduction, and poult survival is a crucial vital rate. Traditional poult survival monitoring uses flush counts of radio-tagged females, but brood flocking (when broods and females merge into larger flocks) and mark retention are potential problems with this method and can produce biased estimates. Alternatively, radio-tagging poults to estimate survival offers a potentially less-biased method if tagging and tracking poults can be conducted without adverse effects on the poults. We compared poult survival estimates derived from flush counts and from radio-tagged poults over a 56-day monitoring period during 2018–2022 in south-central Tennessee, USA. We radio-tagged 183 poults and monitored 85 broods via 2-week flush counts and observed 572 individual poults during flush counts over the 56-day monitoring period. We used known-fate survival models for the telemetry data, Lukacs survival models for the flush count data, and a modified known-fate model to estimate whether radio-tagging poults affected their survival. Two-week survival estimates from the flush count of broods, and radio-tagged poults were similar (flush count: day 0–28: 0.25, 95% CI: 0.20–0.31, day 29–56: 0.56, 95% CI: 0.36–0.76; radio-tagged: day 0–28: 0.30, 95% CI: 0.23–0.37, day 29–56: 0.68, 95% CI: 0.49–0.87). Using known-fate survival models, radio-tagged poults had similar survival rates to non-tagged poults within the brood (day 0–28: Ŝ Radio-tagged = 0.15, 95% CI: 0.10–0.20 v. Ŝ Non-tagged = 0.20, 95% CI: 0.16–0.23), which suggests the radio-tags did not directly affect survival. However, survival of individuals that were trapped was lower than survival of broods that were not trapped during the first 14 days. Trapping methods may need to be adjusted to limit incidental capture effects when choosing to use radio-tagged poults. Conducting flush counts every 14 days until day 56 of the brood-rearing period likely is the most cost-effective method for estimating poult survival. However, monitoring individual radio-tagged poults may yield additional information, such as cause-specific mortality, that may better inform management.
Malacologists generally acknowledge that the Alasminota holstonia (Tennessee Heelsplitter) populations in the Caney Fork, Elk, and Duck river drainages in the Barrens Plateau region of middle Tennessee likely represent a closely related, but distinct, species, collectively referred to as Alasminota sp. (Barrens Heelsplitter). Recent surveys indicate that the species persists in at least 5 streams: Collins River, Pocahontas Branch, Witty Creek, and Pepper Hollow Branch in the Caney Fork River drainage and Little Duck River in the Duck River drainage, with evidence of recruitment in 2 of these streams. These findings suggest a restricted distribution and highlight the need for taxonomic assessment through genetic analysis. If elevated to species status, the Barrens Heelsplitter would represent a narrow endemic that may require conservation attention, underscoring the ecological significance of Tennessee's Barrens Plateau Region.
The Obed River is the last undammed river in Tennessee. The Obed Wild and Scenic River is managed by the National Park Service and covers a protected area of the Obed River headwaters (including four contributing tributaries). The Obed Wild and Scenic River supports a unique ecosystem with eight federally listed species. The National Park Service is responsible for preserving the baseline free-flowing condition of the river and associated outstandingly remarkable values (ORVs). Previous studies have been mostly project-based with differing methods, thus complicating efforts to quantify long-term changes in environmental conditions. This report presents a science plan summarizing (1) ORV conditions, (2) recent results of a decision-support hydrologic model for OBRI, and (3) possible future research priorities. The decision-support model was created to model streamflow conditions and changes in the ORVs since park establishment in 1976 and during three additional time periods. Established baseline conditions could help with management of ORVs not dependent on streamflow.
Using environmental DNA (eDNA) surveillance methods, we report the first evidence of the persistence of the Chucky Madtom ( Noturus crypticus ) in Little Chucky Creek, Tennessee, which has been absent from conventional surveys since 2004, and in Dunn Creek, Tennessee, where it was last collected in 1940. This highlights the utility of eDNA for detecting cryptic, rare fish species that may persist at extremely low population densities when conventional surveys fail, as well as its effectiveness as a contemporary tool to guide targeted conventional sampling efforts; however, it is not intended to replace the ‘in hand’ detection of the species.
To improve estimates of the frequency of annual peak flows for ungaged locations on non-urban, unregulated streams in Tennessee, generalized least-squares multiple linear-regression techniques were used to relate annual peak flows from streamgages operated by the U.S. Geological Survey to physical, climatic, and land-use characteristics of their drainage basins. Geospatial data acquired since the previous study in 2003, annual peak-streamflow data through the 2013 water year, and Bulletin 17C methods for frequency analysis of annual peak-streamflow data were used in the study. Generalized least-squares regression equations were developed for four hydrologic areas with distinct hydrologic, geologic, and topographic characteristics. Drainage area was used as an explanatory variable in equations developed for each hydrologic area. In addition to drainage area, a 2-year recurrence-interval climate factor was used for hydrologic area 1, a 10–85 channel slope was used for hydrologic area 2, and percent imperviousness was used for hydrologic area 4. The regression equations can be used to estimate annual exceedance probability streamflows for ungaged locations on non-urban, unregulated streams in Tennessee. The term “unregulated” indicates that streamflow is not appreciably influenced by regulation from reservoirs or other impoundments. Average standard errors of prediction for the regression equations ranged from 44.4 to 51.4 percent for hydrologic area 1; 30.4 to 42.9 percent for hydrologic area 2; 35.7 to 42.6 percent for hydrologic area 3; and 32.5 to 47.4 percent for hydrologic area 4.
We have developed a comprehensive database for freshwater mussels for the Duck River drainage in Tennessee, including its largest tributary, the Buffalo River. This database is intended to serve as an expandable template that could be applied statewide. The Duck River is one of the most biologically diverse rivers in the world, with historically over 70 mussel species, and it has been selected as a priority watershed by multiple management and conservation entities. The database for this system compiles over 7,000 mussel records, spanning 200 years, from multiple Federal, State, academic, and private entities, representing 77 native species. The database is spatially explicit and includes temporal and methodological data for each record, and notes of negative survey data were made when possible. The database can facilitate the creation of distribution maps for each species and temporal maps of species richness to show watershed-wide trends. This project addresses the present lack of a centralized mussel database in Tennessee for a critical system. It will be available to facilitate species status assessments, inform conservation planning, and serve as a model for similar databases for other Tennessee watersheds.
Animal movement influences local transmission and geographic spread of pathogens. Waterfowl are known reservoirs of pathogens, including H5 goose/Guangdong lineage (H5 GsGd) highly pathogenic avian influenza (HPAI). This HPAI virus lineage causes high rates of morbidity and mortality in domestic poultry and many wild bird species. Mallards ( Anas platyrhynchos ) are a generalist waterfowl species whose habitat largely overlaps with many other waterfowl and are considered effective spillover vectors of HPAI. To investigate the potential contribution of waterfowl to HPAI spillover, we used mallards as a proxy and measured the spatiotemporal overlap of 183 GPS-tagged mallards during 2021–2022 with respect to confirmed wild bird spillover events in United States (U.S.) poultry farms. Additionally, we estimated the probability of HPAI spillover events as a function of mallard overlap and poultry farm type. We found infrequent overlap instances between mallards and poultry farms; however, several of these overlap instances lasted > 5 days and up to 19 days. Population-level overlap with poultry farms was greatest during pre-breeding migration, followed by the breeding season. The probability of HPAI spillover was predicted to be greatest for commercial turkey farms, followed by backyard poultry farms. Importantly, farms overlapped by mallards were more than twice as likely to experience a spillover (i.e., increased risk probability), even in the absence of known mallard infection status at the time of overlap. These findings suggest that mallards (and/or other waterfowl) may be important contributors to HPAI spillover into poultry farms and that additional biosecurity measures may be needed. Because few instances of overlap occurred between mallards and farms with reported spillover events, tagged mallards are likely a proxy for other untagged waterfowl. Further studies of wild waterfowl interactions with poultry farms could improve understanding of how landscape characteristics influence spatial overlap, potentially informing which premises may require enhanced biosecurity measures.
This paper introduces the use of acoustic Doppler current profiler (ADCP) measurements as input for the Acoustic Mapping Velocimetry (AMV) method, a technique for characterizing the dynamics of riverine bedforms. The performance of this new approach, ADCP-AMV, is compared with input from a multibeam echosounder through a field study conducted on the Mississippi River (USA). A virtual ADCP tool has been created to support the ADCP-AMV measurements with optimal data density predictions. To the authors’ knowledge, this is the first time ADCP measurements have been used in conjunction with the AMV dune-tracking method. Subsequently, the paper discusses the coupling of ADCP-AMV measurements with ancillary data extracted from the ADCP. These ancillary data are processed using previously developed protocols to characterize hydrodynamics and the suspended sediment distribution in the water column. This paper emphasizes the capability of ADCPs to characterize open-channel river hydromorphodynamic parameters with high spatiotemporal resolution. Recommendations to accurately and efficiently acquire these multi-variable measurements and derived datasets are discussed.
We provide 2 independent radioisotopic age estimates for cored basal sediments of the Gray Fossil Site using cosmogenic nuclides. The first estimate uses meteoric 10 Be/ 9 Be from the bottom of the GFS-1 core, as well as from modern local grasses, to constrain the deposition of basal GFS sinkhole complex sediments to 6.60 ± 0.85 Ma. We corroborated this age estimate using in-situ 10 Be and 26 Al in quartz sands from the GFS-1 core. This estimate provided a looser constraint than the 10 Be met / 9 Be approach, yielding a minimum burial age for the basal sediments of 4.43 ± 0.34 Ma. These independent geochronometers provide evidence that the deepest GFS sediments are at least early Pliocene in age, and likely date to the late Miocene.
Introduction In 2021, the Tennessee Department of Environment and Conservation (TDEC) and the U.S. Geological Survey worked in cooperation to develop a geographic information system (GIS)-based methodology that systematically assesses the vulnerability of public-supply drinking water to potential contaminants consistent with the standards set forth in the Tennessee Source Water Assessment Program ( SWAP ) . As of June 2022, public-supply water was provided by 643 active public water systems across Tennessee that withdrew water for public use from 1,378 individual water sources. With the newly developed methodology , referred to as “TN- SWAPyT , ” TDEC can consistently delineate source water assessment zones and evaluate source susceptibility on the basis of information such as the proximity of contaminant sources, land-use activities, geologic information, and additional environmental spatial data. A major benefit of the TN- SWAPyT methodology is to provide TDEC with consistent reports that can be used as a starting point for assessing public supplies. Communities and public water systems can then build upon these reports by using local knowledge and site-specific information.
The Little Sequatchie River and Pryor Cove Branch, in southern Tennessee, drain the eastern escarpment of the Cumberland Plateau to the Sequatchie River near the southern end of the Sequatchie Valley. The Little Sequatchie River is the largest tributary to the Sequatchie River by drainage area, covering over 120 square miles. The hydrology of the two drainage areas has been largely altered by karst processes, which has caused the majority of the streams to sink at the contact between the Mississippian Pennington Formation and the underlying Mississippian Bangor Limestone. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service and Tennessee Department of Environment and Conservation, initiated a study in 2021 to map the karst groundwater pathways in both watersheds in order to delineate recharge areas for several springs. One of these springs, Sequatchie Cave, represents a significant habitat for two Species of Greatest Conservation Need, the Glyphopsyche sequatchie (Sequatchie caddisfly) and the federally endangered Marstonia ogmorhaphe (royal marstonia). Springs and springflow-dominated streams in the Little Sequatchie River valley and Pryor Cove also provide water for agricultural practices and serve as a drinking water source for nearby communities. During the study, a total of 25 dye injections were conducted over eight rounds from January 2022 through March 2023. Dye traces from these injections helped to delineate recharge areas for six major springs, ranging from 7.3 to 65.2 square miles in area. The majority of the dye traces remained subsurface (from sinkpoint to recovery site) for long distances, with karst groundwater travelling nearly 8 miles before resurfacing. The dye traces also had rapid traveltimes, often travelling hundreds to thousands of feet per hour. The goal of this project was to provide scientific data related to karst groundwater pathways and spring recharge areas to aid State and Federal agencies in making informed decisions to protect and preserve this unique and vulnerable karst system.
A self-potential (SP) data-inversion algorithm was developed and tested on an analytical model of electrical-potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP-monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock-lined riverbed. The algorithm combined stochastic source-localization by particle-swarm-optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least-squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical-model data to evaluate the algorithm performance. Results indicated that true parameters of single-source models were inverted and approximated with small residual error, whereas inversion of analytical-model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non-uniqueness of the inverse-model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point-scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP-monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.
Ten state wildlife management agencies in the United States, including six within the Southeast, have delayed their spring wild turkey ( Meleagris gallopavo ) hunting seasons since 2017 by five or more days to address concerns related to the potential effects of hunting on wild turkey seasonal productivity. One hypothesis posits that if the spring hunting season is too early, there may be insufficient time for males to breed hens before being harvested, thus leading to reduced seasonal productivity. We conducted an experiment to determine whether delaying the wild turkey hunting season by 2 weeks in south-middle Tennessee would affect various reproductive rates. In 2021 and 2022, the Tennessee Fish and Wildlife Commission experimentally delayed the spring hunting season to open 14 days later than the traditional date (the Saturday closest to 1 April) in Giles, Lawrence, and Wayne counties. We monitored reproductive rates from 2017 to 2022 in these three counties as well as two adjacent counties, Bedford and Maury, that were not delayed. We used a Before-After-Control-Impact design to analyze the proportion of hens nesting, clutch size, hatchability, nest success, poult survival and hen survival with linear mixed-effect models and AIC model selection to detect relationships between the 14-day delay and reproductive parameters. We detected no relationship ( p > .05) between the 14-day delay and any individual reproductive parameter. In addition, recruitment (hen poults per hen that survived until the next breeding season) was very low (<0.5) and did not increase because of the 14-day delay. The traditional Tennessee start date had been in place since 1986 while the turkey harvest increased markedly until about 2006 and more recently stabilized. Our data indicate that moving the start of the hunting season from a period just prior to peak nest initiation to 2 weeks later, to coincide with a period just prior to peak nest incubation initiation, resulted in no change to productivity or populations in wild turkey flocks in south-middle Tennessee.