Geology topics

Research about North Carolina

Source-linked reports with geographic coverage including North Carolina.

At least 109 records · Page 6Linked to original sources

USGS2019

Assessing water quality from highway runoff at selected sites in North Carolina with the Stochastic Empirical Loading and Dilution Model (SELDM)

In 2015, the U.S. Geological Survey (USGS) entered into a cooperative agreement with the North Carolina Department of Transportation (NCDOT) to develop a North Carolina-enhanced variation of the national Stochastic Empirical Loading and Dilution Model (SELDM) with available North Carolina-specific streamflow and water-quality data and to demonstrate use of the model by documenting selected simulation scenarios. The USGS developed the national SELDM in cooperation with the Federal Highway Administration (FHWA) to provide the tools and techniques necessary for performing stormwater-quality simulations. SELDM uses a stochastic mass-balance approach to estimate combinations of flows, concentrations, and loads of stormwater constituents from the site of interest (often a highway catchment; nonhighway areas, such as a large impervious area at a shopping center complex, also can be used) and the basin upstream from the stormwater outfall to assess the risk for adverse effects of runoff. SELDM also can be used to simulate the effectiveness of volume reduction, hydrograph extension, and water-quality concentration reductions by stormwater best management practices (BMPs), which are designed to help mitigate the effects of runoff on receiving water bodies. Some of the statistical inputs needed for the North Carolina-enhanced SELDM were either calculated or augmented using local or regional data from North Carolina. Streamflow statistics used by SELDM were determined for 266 streamgages across North Carolina on the basis of data available through the 2015 water year. Recession ratio statistics used for triangular hydrographs were also developed for 30 streamgages across the State. The NCDOT identified previous research reports on highway-runoff and BMP studies in North Carolina for review of potential data addition to the national FHWA Highway-Runoff Database (HRDB). Following USGS review of these data, a total of 25,087 event mean concentration values and 1,140 storm events for 39 highway-runoff sites and 195 analytes were uploaded to the national HRDB from six North Carolina highway-runoff research reports and a recent USGS bridge deck runoff study. Using data for 27 streamgages in North Carolina, a total of 57 water-quality transport curves were developed for seven constituents for use in simulating water-quality conditions in the upstream basin. Performance data for three BMPs (bioretention, grass strip or swale, and wetland channel) from NCDOT research data were incorporated into the North Carolina-enhanced SELDM for volume-reduction statistics, including the effectiveness of treating four water-quality constituents (total suspended solids, total nitrogen, total phosphorus, nitrate plus nitrite) and turbidity. Simulations using the North Carolina-enhanced SELDM are presented for two hypothetical upstream basins in the Piedmont ecoregion and one hypothetical highway site to demonstrate how simulations can be used to provide risk-based information about potential effects of stormwater runoff on downstream water quality and the potential for mitigating those risks by using BMPs. The first group of simulations explores the stochastic variability in dilution factors (the ratio of the highway runoff to the total downstream stormflow) for a hypothetical Piedmont rural creek having drainage areas ranging from 1 to 100 square miles. The second group of simulations examines dilution factors based on variations in precipitation, streamflow, and recession ratios for two hypothetical Piedmont upstream basins (rural and urban) where the drainage area was held constant at 25 square miles. These simulations indicate the sensitivity of results to variations in each of the three variables. The third group of simulations examines the effects of varied concentrations in the upstream basin on water-quality conditions downstream from the highway crossing. Variations in upstream water-quality conditions for three constituents (suspended sediment concentration, total nitrogen, and total phosphorus) are based on water-quality transport curves selected from among the 57 curves developed as part of this study to represent low-, medium-, and high-concentration statistics. Simulations completed for this third group also examine the potential effects of grass swale and bioretention BMP treatment on total nitrogen and total phosphorus concentrations in highway runoff. The BMP performance data from the NCDOT research reports were applied in this group of simulations. The stochastic mass-balance approach used in SELDM analyses and simulations provides a strong tool for engineers and water-resource managers to use in exploring a wide range of possible hydrologic and water-quality inputs and their effects on downstream water quality. The results of this study can not only aid engineers and managers in planning for potential adverse effects of runoff at site-specific locations, they can also help the USGS and other Federal and State agencies with oversight responsibilities in stormwater-quality issues to continue gathering data on potential water-quality effects in receiving streams.

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USGS2019

Optimizing historical preservation under climate change—An overview of the optimal preservation model and pilot testing at Cape Lookout National Seashore

Adapting cultural resources to climate-change effects challenges traditional cultural resource decision making because some adaptation strategies can negatively affect the integrity of cultural resources. Yet, the inevitability of climate-change effects—even given the uncertain timing of those effects—necessitates that managers begin prioritizing resources for climate-change adaptation. Prioritization imposes an additional management challenge: managers must make difficult tradeoffs to achieve desired management outcomes related to maximizing the resource values. This report provides an overview of a pilot effort to integrate vulnerability (exposure and sensitivity), significance, and use potential metrics in a decision framework—the Optimal Preservation (OptiPres) Model—to inform climate adaptation planning of a subset of buildings in historic districts (listed on the National Register of Historic Places) at Cape Lookout National Seashore. The OptiPres Model uses a numerical optimization algorithm to assess the timing and application of a portfolio of adaptation actions that could most effectively preserve an assortment of buildings associated with different histories, intended uses, and construction design and materials over a 30-year planning horizon. The outputs from the different budget scenarios, though not prescriptive, provide visualizations of and insights to the sequence and type of optimal actions and the changes to individual building resource values and accumulated resource values. Study findings suggest the OptiPres Model has planning utility related to fiscal efficiency by identifying a budget threshold necessary to maintain the historical significance and use potential of historical buildings while reducing vulnerability (collectively, the accumulated resource value). Specifically, findings identify that a minimum of the industry standard ($222,000 annually for the 17 buildings) is needed to maintain the current accumulated resource value. Additionally, results suggest that additional appropriations provided on regular intervals when annual appropriations are at the industry standard are nearly as efficient as annual appropriations at twice the rate of industry standards and increase the amount of accumulated resource values to nearly the same level. However, periodic increases in funding may increase the risks posed to buildings from the probability of a natural hazard (that is, damage or loss from a hurricane). Suggestions for model refinements include developing standardized cost estimations for adaptation actions based on square footage and building materials, developing metrics to quantify the historical integrity of buildings, integrating social values data, including additional objectives (such as public safety) in the model, refining vulnerability data and transforming the data to include risk assessment, and incorporating stochastic events (that is, hurricane and wind effects) into the model.

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USGS2019

Bayesian analysis of the impact of rainfall data product on simulated slope failure for North Carolina locations

In the past decades, many different approaches have been developed in the literature to quantify the load-carrying capacity and geotechnical stability (or the Factor of Safety, F_s) of variably saturated hillslopes. Much of this work has focused on a deterministic characterization of hillslope stability. Yet, simulated F_s values are subject to considerable uncertainty due to our inability to characterize accurately the soil mantle’s properties (hydraulic, geotechnical and geomorphologic) and spatiotemporal variability of the moisture content of the hillslope interior. This is particularly true at larger spatial scales. Thus, uncertainty-incorporating analyses of physically based models of rain-induced landslides are rare in the literature. Such landslide modeling is typically conducted at the hillslope scale using gauge-based rainfall forcing data with rather poor spatiotemporal coverage. For regional landslide modeling, the specific advantages and/or disadvantages of gauge-only, radar-merged and satellite-based rainfall products are not clearly established. Here, we compare and evaluate the performance of the Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis (TRIGRS) model for three different rainfall products using 112 observed landslides in the period between 2004 and 2011 from the North Carolina Geological Survey database. Our study includes the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis Version 7 (TMPA V7), the North American Land Data Assimilation System Phase 2 (NLDAS-2) analysis, and the reference ‘truth’ Stage IV precipitation. TRIGRS model performance was rather inferior with the use of literature values of the geotechnical parameters and soil hydraulic properties from ROSETTA using soil textural and bulk density data from SSURGO (Soil Survey Geographic database). The performance of TRIGRS improved considerably after Bayesian estimation of the parameters with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm using Stage IV precipitation data. Hereto, we use a likelihood function that combines binary slope failure information from landslide event and ‘null’ periods using multivariate frequency distribution-based metrics such as the False Discovery and False Omission Rates. Our results demonstrate that the Stage IV-inferred TRIGRS parameter distributions generalize well to TMPA and NLDAS-2 precipitation data, particularly at sites with considerably larger TMPA and NLDAS-2 rainfall amounts during landslide events than null periods. TRIGRS model performance is then rather similar for all three rainfall products. At higher elevations, however, the TMPA and NLDAS-2 precipitation volumes are insufficient and their performance with the Stage IV-derived parameter distributions indicate their inability to accurately characterize hillslope stability.

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USGS2019

Carbon storage potential in a recently created brackish marsh in eastern North Carolina, USA

Carbon (C) sequestration through accumulated plant biomass and storage in soils can potentially make wetland ecosystems net C sinks. Here, we collected GHG flux, plant biomass, and litter decomposition data from three distinct vegetation zones ( Spartina alterniflora , Juncus roemerianus and Spartina patens ) on a 7-year-old created brackish marsh in North Carolina, USA, and integrate these data into an overall C mass balance budget. The marsh fixed an average of 1.85 g C m −2 day −1 through plant photosynthesis. About 41–46% of the fixed C remained in plants, while 18.4% of the C was decomposed and released back to the atmosphere as CO 2 and CH 4 , and 8.6–13.2% of the decomposed C was stored as soil C. In all, this created marsh sequestered 28.7–44.7 Mg CO 2 year −1 across the 14 ha marsh. Because the brackish marsh emitted only small amounts of CH 4 and N 2 O, the CO 2 equivalent emission of the marsh was −0.87 to −0.56 g CO 2-eq m −2 day −1 , indicating the marsh has a net effect in reducing GHGs to the atmosphere and contributes to cooling. However, resultant CO 2 credit (through the increment of soil C) would be worth only $30.76–$47.90 USD per hectare annually, or $431–$671 per year for the project, which, coupled with other enhanced ecosystem services, could provide landowners with some additional economic incentive for future creation projects. Nevertheless, C mass balance determinations and radiative cooling metrics showed promise in demonstrating the potential of a young created brackish marsh to act as a net carbon sink.

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USGS2019

Modeling landowner interactions and development patterns at the urban fringe

Population growth and unrestricted development policies are driving low-density urbanization and fragmentation of peri-urban landscapes across North America. While private individuals own most undeveloped land, little is known about how their decision-making processes shape landscape-scale patterns of urbanization over time. We introduce a hybrid agent-based modeling (ABM) – cellular automata (CA) modeling approach, developed for analyzing dynamic feedbacks between landowners’ decisions to sell their land for development, and resulting patterns of landscape fragmentation. Our modeling approach builds on existing conceptual frameworks in land systems modeling by integrating an ABM into an established grid-based land-change model – FUTURES. The decision-making process within the ABM involves landowner agents whose decision to sell their land to developers is a function of heterogeneous preferences and peer-influences (i.e., spatial neighborhood relationships). Simulating landowners’ decision to sell allows an operational link between the ABM and the CA module. To test our hybrid ABM-CA approach, we used empirical data for a rapidly growing region in North Carolina for parameterization. We conducted a sensitivity analysis focusing on the two most relevant parameters—spatial actor distribution and peer-influence intensity—and evaluated the dynamic behavior of the model simulations. The simulation results indicate different peer-influence intensities lead to variable landscape fragmentation patterns, suggesting patterns of spatial interaction among landowners indirectly affect landscape-scale patterns of urbanization and the fragmentation of undeveloped forest and farmland.

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USGS2019

Modeling groundwater nitrate exposure in private wells of North Carolina for the Agricultural Health Study

Unregulated private wells in the United States are susceptible to many groundwater contaminants. Ingestion of nitrate, the most common anthropogenic private well contaminant in the United States, can lead to the endogenous formation of N-nitroso-compounds, which are known human carcinogens. In this study, we expand upon previous efforts to model private well groundwater nitrate concentration in North Carolina by developing multiple machine learning models and testing against out-of-sample prediction. Our purpose was to develop exposure estimates in unmonitored areas for use in the Agricultural Health Study (AHS) cohort. Using approximately 22,000 private well nitrate measurements in North Carolina, we trained and tested continuous models including a censored maximum likelihood-based linear model, random forest, gradient boosted machine, support vector machine, neural networks, and kriging. Continuous nitrate models had low predictive performance (R 2 < 0.33), so multiple random forest classification models were also trained and tested. The final classification approach predicted <1 mg/L, 1–5 mg/L, and ≥5 mg/L using a random forest model with 58 variables and maximizing the Cohen's kappa statistic. The final model had an overall accuracy of 0.75 and high specificity for the higher two categories and high sensitivity for the lowest category. The results will be used for the categorical prediction of private well nitrate for AHS cohort participants that reside in North Carolina.

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USGS2019

The potential resiliency of a created tidal marsh to sea-level rise

The purpose of this study was to determine the elevation dynamics of a created tidal marsh on the North Carolina coast. Deep rod surface elevation tables (RSET) and feldspar marker horizons (MH) were installed in plots to measure net surface elevation changes and to quantify contributing processes. Twelve total plots were placed on four elevation gradient transects (three transects within the created marsh and one within a reference marsh) with three plots along each transect. Elevation gradient transects included a low marsh plot dominated by Spartina alterniflora, a middle marsh plot dominated by Juncus roemerianus, and a high marsh plot dominated by Spartina patens. RSET and MH measurements were taken in December 2012, January 2014, April 2017, and March 2018. Elevation change ranged from 0.7 to 4.0 mm yr -1 within the created marsh and -0.6 to 2.1 mm yr -1 within the reference marsh. When compared to the long-term linear trend in local relative sea level rise (RSLR) of 3.10 +/- 0.35 mm yr -1 , the middle marsh plots within the created marsh trended toward survival with an observed elevation increase of 3.1 +/- 0.2 mm yr -1 . Alternatively, the low and high marsh plots within the created marsh trended towards submergence with observed elevation increases of 2.1+/- 0.2 and 1.3 +/- 0.2 mm yr -1 , respectively. These results indicate that a created marsh can display elevation dynamics similar to natural marshes. Surface elevation changes were observed over a short time period and in a relatively young marsh, so it is uncertain if these trends will continue or how the longer-term relationship with RSLR will develop. While this study provided the initial data on the ability of created tidal marshes to respond to observed sea-level rise, long-term observations will be continued to evaluate long-term elevation dynamics.

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USGS2019

Understanding the genetic characteristics of Wild Brook Trout populations in North Carolina thanks to the guidance of Dr. Tim King

We genotyped 7,588 brook trout representing 406 collections from across the State of North Carolina (Figure 1) at 12 microsatellite loci (King et al. 2012). The vast majority of collections appeared to represent single populations, based on general conformance to HardyWeinberg equilibrium and limited evidence for linkage-disequilibrium. Allelic diversity was low to moderate relative to Brook Trout Salvelinus fontinalis populations endemic to higher latitudes. Effective population sizes varied widely among populations, but were often very small and indicate that many populations are at risk of losing diversity through genetic drift. Remarkable levels of genetic differentiation exist among populations, which suggests that little, if any, gene flow occurs among most populations. Analysis of molecular variance (AMOVA) revealed that a substantial portion of the observed genetic variation was attributed to differences among patches (44.8%), and there was some variation (11.2%) even among collections within a single patch. These results, taken in conjunction with high levels of genetic differentiation among populations, suggest that the fundamental unit of management for Brook Trout should be the population. Interestingly, despite extensive stocking across the state, the vast majority of wild populations show limited evidence of introgression by northern origin hatchery strains. These results represent a valuable baseline for management and restoration efforts, and can be used to (a) select suitable donor streams for translocation efforts, (b) identify streams with low effective population sizes that may be vulnerable to extirpation, and (c) target stocking efforts into watersheds where extensive introgression has already occurred. All data associated with this manuscript has been publicly released (Kazyak et al. 2017).

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USGS2018

Behavior and survival of stocked trout in southern Appalachian Mountain streams

Stocking of trout to support recreational fisheries is a common practice among state and federal agencies to meet angling and harvest demands. Success of stocking efforts relies upon fish behavior and survival to maximize the availability of fish to anglers. We quantitatively described the movement behavior and survival of stocked Brook Trout Salvelinus fontinalis , Brown Trout Salmo trutta , and Rainbow Trout Oncorhynchus mykiss in three southern Appalachian Mountain streams in western North Carolina, USA, that were managed under delayed harvest regulations. Hatchery trout were tagged with a combination of PIT tags and radio transmitters (radio tags); stocked into “Delayed Harvest Trout Waters” of the North Toe, East Prong Roaring, and Little rivers; and monitored during the catch-and-release season from October to June. Assessed according to river and species, 19–65% of trout emigrated from the delayed harvest study reaches, while 1–29% died within the reaches. The majority of radio-tagged fish (71%; 59–85% by river) remained within 2 km of the stocking location, whereas 6% migrated over 10 km from the stocking location. Few trout stocked during fall (October and November) were available to anglers the following June due to a combination of migration and mortality. Emigration from delayed harvest study reaches was associated with stocking and high-flow events. Multi-state modeling detailed these observations with weekly estimates of migration and survival rates. River-specific differences in emigration and mortality suggested that emigration was a greater source of trout loss than mortality in all rivers; no pattern related to river size was apparent in emigration, but mortality was greater in small streams. Brook Trout mortality rates were highest among the three species, and large fish of most species showed higher emigration and mortality than catchable-sized trout. Fisheries managers can apply our results to alter stocking regimes so as to enhance the efficiency of stocking and the acclimation of stocked trout to instream environments.

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USGS2018

Kinematic, deformational, and thermochronologic conditions along the Gossan Lead and Fries shear zones: Constraining the western-eastern Blue Ridge boundary in northwestern North Carolina

The fault boundary between the western and eastern Blue Ridge (WBR-EBR) in the southern Appalachians separates Mesoproterozoic basement rocks and their cover from Neoproterozoic to Paleozoic accreted rocks. Several northeast striking faults delineate the boundary, including the Gossan Lead shear zone in northwestern North Carolina. Varying tectonic interpretations of WBR-EBR boundary include a premetamorphic fault, an Acadian dextral strike-slip fault, or an Alleghanian fault. We use field-based, microstructural, and theromochronometric analyses to determine the conditions, kinematics, and timing of deformation, in order to distinguish among competing hypotheses for the Gossan Lead shear zone. This comprehensive approach has allowed us to attribute a number of new and previously observed tectonic fabrics to specific orogenic events; key relationships necessary to the study of multiply deformed tectonic margins. Detailed mapping and microstructural analysis of the Gossan Lead shear zone document a several kilometer-wide mylonitic zone with kinematic indicators that record dominantly top-to-the-NW thrust motion, with local strike-slip and normal sense indicators. Dynamically recrystallized quartz and feldspar constrain a range of deformation conditions from amphibolite to greenschist facies. Two unaltered lineation-forming amphiboles from mylonitic amphibolites record 40 Ar/ 39 Ar cooling ages of 347–345 Ma, and a mylonitized metagraywacke records a muscovite 40 Ar/ 39 Ar cooling age of 336 Ma. These data are consistent with dominantly NW directed thrusting along the Gossan Lead shear zone at amphibolite to greenschist facies conditions, and rapid cooling in the Middle Mississippian. We suggest these data support overprinting and/or reactivation of an earlier structure along this complexly deformed boundary by 336 Ma.

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USGS2018

Persistence-based area prioritization for conservation: Applying occupancy and habitat threats and risks analyses

Effective habitat conservation is predicated on maintaining high levels or increasing local persistence probability of the species it purports to protect. Thus, methodological approaches that improve the inferential value of local persistence are of utmost value to guide conservation planning as they inform area selection processes. Herein we used the painted bunting Passerina ciris, a species of conservation interest in North Carolina, as an illustrative case that combined single-season, single-species occupancy analyses and a threats and risk decision support tool to rank five areas of conservation interest in terms of local persistence probability. We used survey data from two seasons (2008–2009) grouped into 21 natal dispersal sampling units and land-cover data from 12 habitat classes to establish the relationship between local occupancy probability and habitat. Occupancy increased most strongly with increasing amount of maritime forest. Projections to year 2050, relative to year 2000, indicated that a potential loss of maritime forest of 200–1,300 ha, depending on the area of interest. Projected loss was lowest at Bald Head Island–Wilmington (2%) and highest at Camp Lejune (27%). Bald Head Island–Wilmington ranked highest in projected local persistence probability (0.91; 95% confidence interval [CI] = 0.53–0.99), whereas Top Sail–Hammocks Beach Park ranked lowest (0.28; 95% CI = 0.03–0.82). Estimates of local persistence offer decision-makers another criterion to prioritize areas for conservation and help guide efforts aimed at maintaining or enhancing local persistence. These include in situ habitat management, expanding or connecting existing areas of interest. In the future, we recommend the use of multiseason occupancy models, coupled with measures of uncertainty of land-cover projections, to strengthen inferences about local persistence, particularly useful in nonstationary landscapes driven by human activities.

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USGS2018

Hydrologic conditions and simulation of groundwater and surface water in the Great Dismal Swamp of Virginia and North Carolina

The U.S. Geological Survey (USGS), in cooperation with the U.S Fish and Wildlife Service, has investigated the hydrology of the Great Dismal Swamp (Swamp) National Wildlife Refuge (Refuge) in Virginia and North Carolina and developed a three-dimensional numerical model to simulate groundwater and surface-water hydrology. The model was developed with MODFLOW-NWT, a USGS numerical groundwater flow modeling program, in combination with the Surface-Water Routing Process, a software package that simulates dynamic surface-water flows, water control structure management, and groundwater/surface-water interactions. The steady-state model was calibrated to average spring conditions by using automated parameter estimation software (PEST) to reduce simulation errors and assess model parameter sensitivity. The model was then used to simulate wet and dry climatic conditions and a variety of hypothetical scenarios in which water levels in the Swamp were raised and lowered by simulated management of water control structures. Results of the model simulations indicate that, under average spring conditions, precipitation is the primary water input (92%); surface-water (5%) and groundwater (3%) inflows make up the remainder. The primary outflow (or loss) is evapotranspiration (55%), with surface outflows (about 41%) and groundwater outflow (about 4%) making up the remainder. Simulated adjustment of water control structure weir levels demonstrates that groundwater levels are affected by water levels in adjacent ditches and that surface-water and groundwater levels can be controlled through management of water control structures, allowing the Refuge to better manage fire risks and preserve forested-wetland ecosystems in the Refuge. The 13 water control structures proposed in the simulated scenario representing possible future conditions effectively raised simulated water levels in the northeastern corner of the study area, a goal of the Refuge management. Results of this study demonstrate use of MODFLOW with the Surface-Water Routing Process for simulating water management options in peat wetlands and will help Refuge managers to better understand existing hydrologic conditions, assess the hydrologic effects of planned changes to water control structures, and apply the new simulation tool to guide water management on the Refuge.

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USGS2018

Trends in water quality of selected streams and reservoirs used for water supply in the Triangle area of North Carolina, 1989–2013

As the population of the Triangle area in central North Carolina increases, the demand for good quality drinking water from streams and lakes within the upper Neuse and upper Cape Fear River Basins also increases. The Triangle area includes Raleigh, Cary, Research Triangle Park, Durham, Chapel Hill, and the surrounding communities. The U.S. Geological Survey examined temporal trends in water quality for 13 stream and 8 reservoir sites in the two basins on the basis of data collected during 1989–2013. Trends were analyzed using a fitted time-series model that accommodated for shifting trends and variations in streamflow at multiple time scales. Seventeen water-quality properties and constituents were evaluated, including specific conductance and major ions, nutrients, and organic carbon. Suspended solids and suspended sediment were examined at stream sites; chlorophyll a and Secchi transparency were examined at lake sites. The investigation identified considerable changes in population, land cover, streamflow, and selected water-quality characteristics in the study area over the 25-year period. Specific conductance and concentrations of calcium, magnesium, potassium, sodium, and chloride tended to increase throughout the study area. Area-wide increases were also observed for organic nitrogen. Trends for other water-quality constituents varied on a more site-specific basis because of local watershed influences such as changes to wastewater-treatment processes and substantial shifts from rural to urban land use. Water quality is influenced by multiple, often confounding factors, and thus may change in a non-uniform manner over time. Long-term monitoring is critical for tracking these trends and ensuring resiliency of water supplies for the future. Results from this study may promote the understanding of water-quality response to a growing population and land-cover changes and can assist water-resource managers in the Triangle area in tracking progress toward water-quality goals.

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USGS2018

Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager

In this study, we demonstrated that the Landsat-8 Operational Land Imager (OLI) sensor is a powerful tool that can provide periodic and system-wide information on the condition of drinking water reservoirs. The OLI is a multispectral radiometer (30 m spatial resolution) that allows ecosystem observations at spatial and temporal scales that allow the environmental community and water managers another means to monitor changes in water quality not feasible with field-based monitoring. Using the provisional Land Surface Reflectance product and field-collected chlorophyll- a (chl- a ) concentrations from drinking water monitoring programs in North Carolina and Rhode Island, we compared five established approaches for estimating chl- a concentrations using spectral data. We found that using the three band reflectance approach with a combination of OLI spectral bands 1, 3, and 5 produced the most promising results for accurately estimating chl- a concentrations in lakes ( R 2 value of 0.66; root mean square error value of 8.9 µg l −1 ). Using this model, we forecast the spatial and temporal variability of chl- a for Jordan Lake, a recreational and drinking water source in piedmont North Carolina and several small ponds that supply drinking water in southeastern Rhode Island.

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USGS2018

Quantifying the visual-sensory landscape qualities that contribute to cultural ecosystem services using social media and LiDAR

Landscapes are increasingly recognized for providing valuable cultural ecosystem services with numer- ous non-material benefits by serving as places of rest, relaxation, and inspiration that ultimately improve overall mental health and physical well-being. Maintaining and enhancing these valuable benefits through targeted management and conservation measures requires understanding the spatial and tem- poral determinants of perceived landscape values. Content contributed through mobile technologies and the web are emerging globally, providing a promising data source for localizing and assessing these land- scape benefits. These georeferenced data offer rich in situ qualitative information through photos and comments that capture valued and special locations across large geographic areas. We present a novel method for mapping and modeling landscape values and perceptions that leverages viewshed analysis of georeferenced social media data. Using a high resolution LiDAR (Light Detection and Ranging) derived digital surface model, we are able to evaluate landscape characteristics associated with the visual- sensory qualities of outdoor recreationalists. Our results show the importance of historical monuments and attractions in addition to specific environmental features which are appreciated by the public. Evaluation of photo-image content highlights the opportunity of including temporally and spatially vari- able visual-sensory qualities in cultural ecosystem services (CES) evaluation like the sights, sounds and smells of wildlife and weather phenomena.

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USGS2018

Tropical storm-induced landslide potential using combined field monitoring and numerical modeling

When heavy rainfall, such as that associated with tropical storms, falls on steep hillsides, shallow landslides are often one of the damaging consequences. To assess landslide potential from heavy rainfall, a strategy of combined numerical simulation and field monitoring of variably saturated hillslope conditions is developed. To test the combined method, hillslope hydrologic data from paired field monitoring sites in western North Carolina are examined. The hydrologic data collected from the field monitoring site where no shallow landslide has occurred is used to identify and calibrate the hydromechanical parameters used in a numerical ground water flow model. The identified parameters are then used to simulate landslide potential at the two hillslopes during heavy rainfall associated with hurricanes Frances and Ivan (HFI) that impacted western North Carolina in 2004. Results identify the timing of instability at the shallow landslide site and show that the stable site remains stable during rainfall associated with the HFI tropical storms. Thus, the results demonstrate the effectiveness of combined numerical modeling and field monitoring to evaluate landslide potential under variably saturated conditions.

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USGS2018

Hydrologic characteristics of freshwater mussel habitat: novel insights from modeled flows

The ability to model freshwater stream habitat and species distributions is limited by the spatially sparse flow data available from long-term gauging stations. Flow data beyond the immediate vicinity of gauging stations would enhance our ability to explore and characterize hydrologic habitat suitability. The southeastern USA supports high aquatic biodiversity, but threats, such as landuse alteration, climate change, conflicting water-resource demands, and pollution, have led to the imperilment and legal protection of many species. The ability to distinguish suitable from unsuitable habitat conditions, including hydrologic suitability, is a key criterion for successful conservation and restoration of aquatic species. We used the example of the critically endangered Tar River Spinymussel ( Parvaspina steinstansana ) and associated species to demonstrate the value of modeled flow data (WaterFALL™) to generate novel insights into population structure and testable hypotheses regarding hydrologic suitability. With ordination models, we: 1) identified all catchments with potentially suitable hydrology, 2) identified 2 distinct hydrologic environments occupied by the Tar River Spinymussel, and 3) estimated greater hydrological habitat niche breadth of assumed surrogate species associates at the catchment scale. Our findings provide the first demonstrated application of complete, continuous, regional modeled hydrologic data to freshwater mussel distribution and management. This research highlights the utility of modeling and data-mining methods to facilitate further exploration and application of such modeled environmental conditions to inform aquatic species management. We conclude that such an approach can support landscape-scale management decisions that require spatial information at fine resolution (e.g., enhanced National Hydrology Dataset catchments) and broad extent (e.g., multiple river basins).

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USGS2018

Demographic rates of two southeastern populations of Painted Bunting, 2007–2015

Painted Buntings ( Passerina ciris ) have been declining in the southeastern United States since the 1970s. A recent demographic assessment highlighted the importance of estimating demographic parameters, which have received little attention to date. The dearth of information is troublesome because attempts to reverse declining trends require a better understanding of the relationship between habitat quality and age- and sex-specific survival and recruitment rates. We used capture–mark–recapture data collected from 2007 to 2015 on Bald Head Island (BHI) and at Hammocks Beach State Park (HBSP) in North Carolina, USA, to estimate local age- and sex-specific annual survival rates and local population size and recruitment rates using programs MARK and LOLASURVIV. Juveniles had lower local survival rates than adults (HBSP: 0.28 ± 0.14 vs. 0.67 ± 0.06; BHI: 0.28 ± 0.04 vs. 0.57 ± 0.02). Local annual survival rates for males on BHI (0.50 ± 0.03) were lower than those for females (0.57 ± 0.02). Age-specific differences were consistent with known differential age-dependent survival skills, and sex-specific differences were consistent with the potential influence of sexual dichromism. Conservative estimates of population size on BHI averaged 101 juveniles and 263 adults annually. Annual in situ reproductive recruitment averaged 28 individuals plus an additional 120 new immigrants, indicating successful reproduction and connectivity with neighboring coastal populations. Local adult survival estimates from our 2 North Carolinian study populations were similar to high-end estimates from across the eastern and western range of the species (∼0.60). Finite observed population growth rate estimates between the BHI population (λ = 1.10) and a South Carolinian population (λ = 0.87) underscore the potential role of differential habitat quality and the importance of information from multiple sites, including nonbreeding grounds, for proper inferences about the status of the species. Reported vital rates provide a stronger foundation on which to base habitat quality as assessed with demographic parameters and to guide Painted Bunting conservation regionally.

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