Geology topics

Research about North Carolina

Source-linked reports with geographic coverage including North Carolina.

At least 37 records · Page 2Linked to original sources

USGS2025

Estuarine exchange flow in the Albemarle-Pamlico estuarine system

Estuarine exchange flow controls the salt balance and regulates biogeochemistry in an estuary. The Albemarle-Pamlico estuarine system (APES) is the largest coastal lagoon in the U.S. and historically susceptible to a series of environmental issues including salt water intrusion and eutrophication, yet its estuarine exchange flow is poorly understood. Here, we investigate the estuarine exchange flow in the APES, its tributary estuaries (Pamlico and Neuse), and sub-basin Albemarle Sound using the total exchange flow analysis framework based on results from a deterministic numerical model. We find the following: (a) Dynamics controlling estuarine exchange flow in the APES vary spatially and depend on timescales considered. At inlets, estuarine exchange flows respond to both tidal prism and residual water levels at weather-to-spring/neap timescales. At a long quasi-steady timescale represented as annual means, estuarine exchange flow is dominated by barotropic flow. Within the tributary estuaries, estuarine exchange flows at timescales of wind periods are controlled by wind-induced straining, whereas the quasi-steady state condition is dominated by gravitational circulation. At Albemarle Sound, exchange flow is dominated by the residual water levels at weather-to-spring/neap timescales, while at quasi-steady state it is controlled by barotropic flow. (b) At the quasi-steady annual timescale, the salt content decreases with river discharge. At the weather-to-spring/neap timescales, salt content is insensitive to variations in estuarine exchange flow, except for within Albemarle Sound. (c) Estuarine exchange flow likely influences the biogeochemistry of the APES by playing a key role in regulating the flushing efficiency and material exchange, a role that has been previously overlooked.

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USGS2025

Automated generation of an urban synthetic elevation checkpoint network across the North Carolina coastline, USA

Lidar and structure from motion-derived digital elevation and surface models have widespread application. Consideration of a topographic model's vertical root mean squared error (RMSEz) and systematic directional bias is important for many of these applications, particularly landscape change detection and measurement. Due to logistic, resource, and time constraints, wide area remotely sensed topographic surveys are not always accompanied by an in situ checkpoint network for validating and characterizing survey error. Here we describe and test a method for automatically generating synthetic elevation checkpoints in bulk across hundreds of kilometers using a publicly available lidar-derived DEM time-series, road vector network, and landcover classification map. Our method produced 6000–10,000 synthetic checkpoints across the developed barrier island coastline of North Carolina. These checkpoints characterized vertical error metrics in a statistically similar way as in situ checkpoints when assessing the vertical accuracy of a contemporary lidar-derived DEM and produced RMSEz metrics an average of 0.018 m from the RMSEz of historical lidar DEMs published with tested accuracy metrics. This new method has the potential to A) lower the cost and time required to validate new remotely sensed topographic surveys by reducing or eliminating the field work associated with in situ checkpoint surveys, B) provide a means of retroactively assessing the absolute vertical accuracy and systematic bias of historical topographic datasets that were not published with tested accuracy metrics, and C) generate reference networks to assess and correct spatially variable patterns of vertical bias in topographic datasets.

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USGS2025

Integrating contaminant source indicators, water quality measures, and ecotoxicity to characterize contaminant mixtures and per- and polyfluoroalkyl substances (PFAS) variability in an urban watershed

Thousands of chemical contaminants threaten watersheds but are time and cost prohibitive to monitor. Identifying their sources, transport, and ecological risk is limited in heterogeneous urban watersheds. We present an integrative watershed approach using source-specific indicator compounds, common water quality measures, and ecotoxicity assays to examine the distribution of contaminant mixtures in an urbanized watershed. Indicator compound concentrations were temporally and spatially distributed for treated/untreated sewage (sucralose, artificial sweetener), road runoff (diphenyl-guanidine [DPG] and 6PPD-quinone [6PPD-Q], automobile tire additives), and lawncare runoff (aminomethanephosphonic acid (AMPA), major degradant of the herbicide glyphosate). Sucralose was predominately sourced from treated wastewater; measurable concentrations in tributaries indicated raw sewage inputs. DPG and 6PPD-Q concentrations correlated to road density during base flow and were elevated during stormflow. AMPA was measurable spring through fall, especially where lawns were dense. When specific sources dominated flow, water quality measures correlated with wastewater (sulfate, potassium, chloride, and sodium) and road runoff (chromium and lead) indicators. The limited behavioral toxicity observed in exposed zebrafish ( Danio rerio ) (18%) was not well explained by source-indicators. PFAS concentrations were highly variable spatially but not well explained by our source-specific indicator compounds. More costly compound-specific monitoring may be necessary when multiple sources exist or when unexpected toxicity trends occur.

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USGS2025

Numerical simulation of sound-side barrier-island inundation and breaching during Hurricane Dorian (2019)

Hurricane-induced morphological changes and associated community hazards along sandy, barrier-island coastlines have been studied primarily from the perspective of ocean-side attack by storm-driven ocean surge and large waves. Thus, our understanding of long-term barrier island morphological change focuses on beach erosion, overwash, and inlet formation. In contrast, outwash events with inundation from the sound side, such as one that occurred in Cape Lookout National Seashore, North Carolina, USA during Hurricane Dorian (September 2019), are understudied. Studying such events can improve understanding of barrier island response and stability for a broader range of conditions. Here, we model the hydrodynamics and morphological evolution of a barrier island using a coupled wave-current-sediment transport modeling system. Wind-driven surge in Pamlico Sound led to overtopping from the sound side, which eroded outwash channels and transported sediment seaward into the nearshore. Simulations reproduce the channel features observed with aerial imagery and provide information not available from the remote-sensing observations, including channel depths (>2 m) and the fate of the eroded sand. We found that >99% of the eroded sand was deposited in the nearshore, within 1,000 m of the shoreline in depths <10 m, suggesting that the deposited sediment remains available for littoral transport and beach recovery. Simulations with combinations of coarse or fine sediment and vegetated or unvegetated landcover indicate that channel position did not vary with grain size or vegetation, while volume of erosion and channel morphology were more responsive to variations in grain size and less responsive to presence of vegetation.

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USGS2025

Overwinter survival of an estuarine resident fish (Fundulus heteroclitus) in North Carolina salt marsh creeks

The mummichog Fundulus heteroclitus is a trophically important fish inhabiting Atlantic coastal salt marshes, with few in situ estimates of overwinter survival throughout the species range. We estimated overwinter apparent survival rates of F. heteroclitus at the approximate mid-latitudinal species range [coastal North Carolina (USA)] in four tidal creeks that experience variable winter water temperatures. To estimate apparent survival, we fitted a Cormack-Jolly-Seber model to daily mark-resight data autonomously obtained from fish marked with passive integrated transponder tags. Creek, year, mean daily water temperature, change in mean daily temperature, fish length and fish condition were considered for effects on the modelled parameters: apparent survival (Φ) (product of true survival and site fidelity) and detection probability ( p ). Modelling showed that water temperature and fish metrics were not related to Φ. Water temperature was directly related to p , indicating reduced fish activity and thus reduced detection probability or poor antenna detection performance at low temperatures. Creek was related to Φ and p , and the creek most open to its downstream estuary (lacking a culvert) had lower rates than the others. Greater loss (fish mortality plus emigration) in this one creek may more effectively transfer production of F . heteroclitus to larger waterbodies via emigration or predation. Conversely, lower Φ may reflect reduced detection efficiency. The results suggest that F . heteroclitus survival is insensitive to variable winter water temperatures typical of thermal dynamics in shallow estuaries in this region of its range. Median creek-specific overwinter Φ rates (range of median values, 2 × 10 −8 , 0.04) were roughly equal to previously published rates for these creeks during the growing season (April–October). At these latitudes and with increasingly moderate winters, the results indicate that natural mortality could arise equally or more so from predation during the growing season than mechanisms such as starvation, direct mortality, thermal morbidity and stress-related susceptibility to predation resulting from intermittently low water temperatures during the overwinter season.

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USGS2025

Spatially explicit capture-recapture using fecal DNA to estimate elk population abundance and growth in western North Carolina, USA

In an effort to restore extirpated elk to their historical range, 52 elk were reintroduced to Great Smoky Mountains National Park (GRSM) in North Carolina, USA, during 2001 and 2002. Since their reintroduction, elk numbers have increased, and elk have extended their range beyond GRSM boundaries. We used spatially explicit capture-recapture (SCR) methods based on fecal DNA to identify individual elk and estimate population abundance ( N ), apparent survival ( φ ), per capita recruitment ( f ), and population growth rate ( λ ) in western North Carolina. We walked a series of transects during 3 winter field seasons (2020–2022) and collected elk pellets encountered along those transects. We created spatially explicit capture histories and incorporated those data into both closed and open population SCR models. The top performing closed SCR models for males and females estimated density by year and as a function of the scaled distance to the nearest field, with densities decreasing as the distance increased. Combined male and female N were 179 elk (95% CI = 149–215) in 2020, 220 elk (95% CI = 188–256) in 2021, and 240 elk (95% CI = 207–279) in 2022. The top open population model estimated both φ and λ as functions of sex and year. The estimate of φ for males was 0.682 (95% CI = 0.317–0.908) during 2020–2021 and 0.339 (95% CI = 0.152–0.596) during 2021–2022 and for females was 0.953 (95% CI = 0.830–1.000) during 2020–2021 and 0.829 (95% CI = 0.601–1.000) during 2021–2022. The annual population growth rate ( λ ) for males was 1.127 (95% CI = 0.806–1.575) during 2020–2021 and 0.811 (95% CI = 0.566–1.163) during 2021–2022 and for females was 1.559 (95% CI = 1.162–2.091) during 2020–2021 and 1.122 (95% CI = 0.876–1.437) during 2021–2022. Our elk abundance estimates in areas >300 m from fields were negligible, and we suggest that sampling only the areas in and adjacent to fields in the future will result in reliable but more cost-efficient population estimates. Confidence intervals for vital rate parameters were wide for our 3-year dataset, but continued annual pellet sampling will increase sample sizes for vital rate estimation and thus improve precision. If elk herd expansion on public lands is desired, we suggest habitat modification to establish open grasslands adjacent to forests.

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USGS2025

Emotions and political identity predict public acceptance of urban deer management

Addressing public preferences can enhance wildlife management effectiveness and reduce backlash. We conducted novel research on public acceptance of wildlife management by accounting for the role of underexplored drivers including emotion and political identity across an urban-to-rural gradient. Using data from a 2022 survey about white-tailed deer ( Odocoileus virginianus ) in Durham County, North Carolina, we analyzed drivers of acceptance for three management strategies: passive management, lethal management by hunting, and lethal management by professionals. Support for deer management varied across the urban-to-rural gradient, as rural residents favored hunting but were less supportive of passive management compared to urban and suburban residents. Emotions and general attitudes toward deer were the strongest predictors of management acceptance. Support for passive management was higher among residents with more positive emotions toward deer, whereas support for lethal strategies was higher among those with more negative emotions. Additionally, political identity emerged as a complex yet influential factor in shaping support for lethal management. Conservative respondents exhibited a higher acceptance of hunting, whereas liberal respondents exhibited a higher acceptance of professional sharpshooting. Collectively, our results demonstrate the ways in which emotions, politics, and other socio-demographic factors interact to influence public support for deer management across the urban–rural gradient. When direct experience with wildlife is lacking (e.g., in urban areas), emotions may act as heuristic guides that shape preferences. Managers aiming to increase deer management acceptability could integrate insights about emotional, political, and demographic drivers of public management support in communication efforts, potentially rendering urban deer management more effective.

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USGS2024

Genome sequences of toxigenic cyanobacteria from a bloom in Lake Mattamuskeet, North Carolina (United States)

Lake Mattamuskeet, the largest lake in North Carolina, USA, has undergone decades-long eutrophication causing reduced water quality and promoting cyanobacterial blooms that may produce toxins. It is therefore necessary to evaluate the cyanobacterial diversity of the lake and their toxigenic potential. We present draft genomes of Microcystis , Pelatocladus , Raphidiopsis , and Umezakia strains isolated from Lake Mattamuskeet. The whole-genome shotgun projects for Umezakia ovalisporum BLCC-F208, Microcystis sp. BLCC-F209, Microcystis sp. BLCC-F210, Pelatocladus sp. BLCC-F211, U. ovalisporum BLCC-F215, and Raphidiopsis BLCC-F218 have been deposited in GenBank under accession numbers JBHFLK000000000, JBHFLL000000000, CP169647, JBHFLM000000000, JBHFLN000000000, and JBHFLO000000000, respectively. Based on the genomic analysis, several biosynthetic gene clusters (BCGs) with varying degrees of similarity to known toxic and bioactive compound gene clusters were identified across the different cyanobacterial strains.

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USGS2024

Scalable, data-assimilated models predict large-scale shoreline response to waves and sea-level rise

Coastal change is a complex combination of multi-scale processes (e.g., wave-driven cross-shore and longshore transport; dune, bluff, and cliff erosion; overwash; fluvial and inlet sediment supply; and sea-level-driven recession). Historical sea-level-driven coastal recession on open ocean coasts is often outpaced by wave-driven change. However, future sea-level-driven coastal recession is expected to increase significantly in tandem with accelerating rates of global sea-level rise. Few models of coastal sediment transport can resolve the multitude of coastal-change processes at a given beach, and fewer still are computationally efficient enough to achieve large-scale, long-term simulations, while accounting for historical behavior and uncertainties in future climate. Here, we show that a scalable, data-assimilated shoreline-change model can achieve realistic simulations of long-term coastal change and uncertainty across large coastal regions. As part of the modeling case study of the U.S. South Atlantic Coast (Miami, Florida to Delaware Bay) presented here, we apply historical, satellite-derived observations of shoreline position combined with daily hindcasted and projected wave and sea-level conditions to estimate long-term coastal change by 2100. We find that 63 to 94% of the shorelines on the U.S. South Atlantic Coast are projected to retreat past the present-day extent of sandy beach under 1.0 to 2.0 m of sea-level rise, respectively, without large-scale interventions.

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USGS2024

Detecting trajectories of regime shifts and loss of resilience in coastal wetlands using remote sensing

Many freshwater forested wetlands along the southeastern United States coastline are rapidly transitioning from forest to marsh or open water, due to climate change-related disturbances. Recent studies have found early warning signals (EWS) of regime shifts in other ecosystems, but it is unclear if these can be detected for coastal wetlands. In this study, we examined the ability to detect EWS of regime shifts in coastal wetlands within the Albemarle Pamlico peninsula (APP), North Carolina, U.S.A. We used the Landsat record (1985–2021) to examine trends of normalized difference vegetation index (NDVI) time series for selected areas known to have undergone regime shifts. We found that while 77% of the APP was either stable or revegetating, 22% of the landscape underwent a decrease in NDVI that would indicate a transition from forest to marsh or open water. Of the areas that transitioned, about half (11%) experienced an abrupt decrease in NDVI and 10% experienced a gradual decline. Increasing standard deviation and skewness of time series could serve as EWS of abrupt transitions, but can also provide false negative and positives. Our results suggest that ecosystem transitions from a forest to a marsh or open water can occur both rapidly and slowly, and remote sensing of NDVI time series can help identify EWS for some areas, but not all. Our results allow for prioritization of conservation/restoration of coastlines which will become important in the face of climate change and sea level rise.

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USGS2024

The projected exposure and response of a natural barrier island system to climate-driven coastal hazards

Accelerating sea level rise (SLR) and changing storm patterns will increasingly expose barrier islands to coastal hazards, including flooding, erosion, and rising groundwater tables. We assess the exposure of Cape Lookout National Seashore, a barrier island system in North Carolina (USA), to projected SLR and storm hazards over the twenty-first century. We estimate that with 0.5 m of SLR, 47% of current subaerial barrier island area would be flooded daily, and the 1-year return period storm would flood 74%. For 20-year return period storms, over 85% is projected to be flooded for any SLR. The modelled groundwater table is already shallow (< 2 m deep), and while projected to shoal to the land surface with SLR, marine flooding is projected to overtake areas with emergent groundwater. Projected shoreline retreat reaches an average of 178 m with 1 m of SLR and no interventions, which is over 60% of the current island width at narrower locations. Compounding these hazards is subsidence, with one-third of the study area currently lowering at > 2 mm/yr. Our results demonstrate the difficulty of managing natural barrier systems such as those managed by federal park systems tasked with maintaining natural ecosystems and protecting cultural resources.

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USGS2024

Applying mark-resight, count, and telemetry data to estimate effective sampling area and fish density with stationary underwater cameras

Accurate estimates of abundance and density for geographically open populations must account for the effective sampling area (ESA) of sampling gears. We describe a Marked N-Mixture model to estimate ESA and density (number of individuals/unit area) from repeated counts of unmarked and marked individuals, integrating mark-resight, camera counts, and telemetry data of red snapper ( Lutjanus campechanus ) at a 1.6 km 2 reef off North Carolina, USA. Cameras recorded observations of unmarked and marked individuals, whereas telemetry data indicated the number of tagged fish present on the reef. We estimated density (95 individuals/km 2 , 95%CI: 58–149), ESA (which was lower when current direction was towards the camera), detection probability (0.06, 95%CI: 0.03–0.09), and covariate relationships. Simulation studies under different scenarios of data quality and space use identified positive bias in density estimates from N-mixture models due to fish movement. In contrast, the Marked N-Mixture model returned unbiased estimates of density, ESA, and detection parameters, and appears to be a more robust method for modeling density given the data available for this analysis. This approach can be applied to other populations where count and telemetry data overlap in space and time.

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USGS2024

Triangle Area Water Supply Monitoring Project, North Carolina

Introduction Rivers and surface-water reservoirs supply drinking water to most residents throughout the Triangle area in North Carolina. These drinking-water supplies may be at risk because of rapid and continued land use change throughout the region. In partnership with the U.S. Geological Survey, several Triangle-area municipalities established a long-term water-quality and streamflow monitoring program to quantify changes in water quality and water availability over time and to evaluate the relative risk of potential contaminants in these drinking-water sources.

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USGS2024

Assessment of nutrient load estimation approaches for small urban streams in Durham, North Carolina

This cooperative study between the City of Durham Public Works Department, Stormwater Division and U.S. Geological Survey evaluated whether alternate monitoring strategies that incorporated samples collected across an increased range of streamflows would improve nutrient load estimates for Ellerbe and Sandy Creeks, two small, highly urbanized streams in the City of Durham, North Carolina. Water-quality and streamflow data collected between January 2009 and December 2020 were used to develop instream nutrient-load models using the U.S. Geological Survey R-LOADEST program. This study compared model results from two sampling scenarios: routine monthly (fixed frequency) sampling combined with targeted high-streamflow sampling (scenario A), and fixed frequency sampling only (scenario B). Calibration diagnostic results were used to select the final, or most optimal, models. Most final models included seasonality terms to compensate for intra-annual variability in the data. Storm-runoff samples provided better definition at higher streamflows and improved the overall concentration versus flow relations for all constituents, except nitrate + nitrite. Uncertainties in the nutrient load estimates were lower and less variable for the scenario A tests compared to the scenario B tests. Five time steps representing 12-, 9-, 7-, 6-, and 5-year subsets of the overall dataset were used to examine the effect of prediction period length on the computed loads and uncertainties. In focusing on the scenario A results, nutrient loads tended to be higher for the shorter time steps. These shorter time steps also produced higher errors, or uncertainty, in the load estimates compared to longer time steps. Evaluations of annual nutrient loads during 2016–20 indicated that the most consistent load estimates and tightest confidence intervals were obtained for longer 12- and 9-year time steps. Estimated loads were more variable and uncertain when based on the shorter 6- and 5-year time steps. The degree of uncertainty (standard error of prediction) in the nutrient load estimation results was influenced by sampling approach, calibration time step, and hydrologic characteristics during the model period of interest.

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USGS2024

Artificial structure selection by economically important reef fishes at North Carolina artificial reefs

Artificial reefs can play an important role in marine fisheries management by supplementing or enhancing natural habitats. Despite their increased use in recent years, the choice of structures used at artificial reefs remains largely haphazard due to the lack of information on reef structure performance. Few studies have examined the use of different artificial reef structures by individual fish. From 2021-2022, we acoustically tagged 72 black sea bass ( Centropristis striata ), 34 gag ( Mycteroperca mircrolepis ), 27 greater amberjack ( Seriola dumerili ), nine almaco jack ( S. rivoliana ), and eight red snapper ( Lutjanus campechanus ) on four artificial reef complexes near Cape Lookout, North Carolina, U.S. Available artificial reef structures consisted of materials of various sizes and heights made of concrete and metal. We tracked tagged fish using a fine-scale positioning system for ~100 days. Black sea bass exhibited high site fidelity to the artificial structure where we caught them, rarely moving away from that structure. The limited movement resulted in low transition probabilities; we conclude that black sea bass do not select for particular artificial structures. Gag and red snapper moved greater distances away from artificial structures and routinely moved between them. Greater amberjack and almaco jack moved the most within the complexes displaying circling behavior around individual structures and were the only species that regularly moved off the artificial reef complexes. Greater amberjack movements away from artificial sites were most commonly directed to surrounding shipwrecks. Whereas gag, red snapper, almaco jack, and greater amberjack used all available structures, they consistently selected for high relief structures, such as vessels, more than other structures. These results will be useful to managers charged with decisions on what types of structures to place at artificial reef complexes to supplement or enhance habitat for economically important fishes.

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USGS2024

Triangle Area Water Supply Monitoring Project, North Carolina—Overview of hydrologic and water-quality monitoring activities and data quality assurance

Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of local governments have participated in a cooperative effort, known as the Triangle Area Water Supply Monitoring Project, to track water-quality and quantity conditions in several of the area’s water-supply reservoirs and streams. This report summarizes the hydrologic and water-quality monitoring activities through this cooperative effort, including an overview of previous and current data collection and quality-assurance and quality-control activities.

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USGS2024

Phytoplankton, taste-and-odor compounds, and cyanotoxin occurrence in four water-supply reservoirs in the Triangle area of North Carolina, April–October 2014

Prior to 2014, local utilities and State agencies monitored for cyanotoxins and taste-and-odor (T&O) compounds and reported occasional detections in three water-supply reservoirs in Wake County, North Carolina. Comparable data for cyanotoxins and T&O compounds were lacking for other water-supply reservoirs in the Triangle area of North Carolina. This report assesses whether cyanotoxins and T&O compounds occurred in four previously unmonitored North Carolina Triangle area water-supply reservoirs at levels that exceed existing North Carolina and U.S. Environmental Protection Agency recreational and drinking water health advisory, guidance, and criterion levels based on data collected during the peak phytoplankton growth period in 2014. Samples were collected from five sites across the study reservoirs (Cane Creek Reservoir, West Fork Eno River Reservoir, B. Everett Jordan Lake, and University Lake) between April and October 2014 and analyzed for physical characteristics, chemical constituents, phytoplankton communities, cyanotoxins, and T&O compounds. Lake stratification during the sampling period in 2014 could indicate that the deep zones of the water column, during stratified anoxic conditions, may serve as possible sources of nutrients and metals for algal growth and other biogeochemical processes. Differences in phytoplankton communities were attributed to variability in environmental conditions across the sites and sampling events. Differences generally were greater among sites than among sampling events for phytoplankton communities and environmental conditions. Phytoplankton community assemblages, within reservoirs, often were dominated by cyanobacteria that contained genera capable of producing T&O compounds and cyanotoxins during summer and fall months. The occurrence and associated biovolumes of potential producers of cyanotoxins and T&O compounds varied across the sites and sampling events. Of 20 samples collected during the study, the T&O compound geosmin and the cyanotoxin microcystin were present in 19 and 18 samples, respectively. While not harmful, the aesthetically displeasing geosmin concentrations periodically exceeded the human detection threshold of 15 nanograms per liter at most sites. The T&O compound 2-methylisoborneol (MIB) was detected in 11 of 20 samples, with concentrations below the human detection threshold of 15 nanograms per liter in all but one sample. The cyanotoxin anatoxin-a was detected in two of the samples. No other cyanotoxins were detected during the study. In general, results did not indicate the biovolume of any given phytoplankton genera in the study was correlated with increased concentrations of MIB, geosmin, or microcystin. Results from this study indicated that microcystin concentrations in the water-supply reservoirs in the Triangle area were below EPA-recommended recreational level of 8 micrograms per liter, but periodically exceeded the EPA finished-water 10-day health advisory level of 0.3 microgram per liter for bottle-fed infants and preschool-age children. This suggests longer term data collection may be necessary to better understand the magnitude and frequency of cyanotoxin concentrations in these four water-supply reservoirs, particularly those with an elevated risk of exceeding the EPA 10-day health advisory levels in the finished drinking water or those with a higher frequency of T&O compound occurrence.

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USGS2024

Developing a decision tree model to forecast runup and assess uncertainty in empirical formulations

The coastal zone is a dynamic region that can change rapidly and significantly with respect to the morphology of the beach and incoming wave conditions. Runup forecasts may be improved by adapting a dynamic approach that allows for different runup models to be implemented in response to changes in beach state. Accurately forecasting wave runup is critical to characterize exposure to coastal hazards and provide an early warning against potential erosion and inundation. Here, we developed a decision tree model to produce a weighted ensemble of existing runup models to predict 1.25 years of runup at Duck, North Carolina, USA. We then applied the calibrated decision tree model to reproduce observed runup during the DUNEX experiment in Pea Island, North Carolina, USA. We found that the decision tree approach yielded a prediction that was comparable or greater in accuracy (i.e. higher r2, lower RMSE) than the individual runup models. We also interrogated the decision tree predictions to determine how the individual models perform relative to each other and why certain models perform better than others under the same observed wave and beach conditions. We found that the decision tree approach drew on the processes represented in the individual models in the ensemble to produce a forecast that is accurate and explainable without relying on prior knowledge of the study site(s) or requiring manual adjustments beyond the initial model training.

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