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At least 757 records · Page 42Linked to original sources
USGS2016

Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the public. This paper describes an approach to optimize the selection of training and auxiliary data for deriving the thematic land cover maps based on all available clear observations from Landsats 4–8. Training data were selected from map products of the U.S. Geological Survey’s Land Cover Trends project. The Random Forest classifier was applied for different classification scenarios based on the Continuous Change Detection and Classification (CCDC) algorithm. We found that extracting training data proportionally to the occurrence of land cover classes was superior to an equal distribution of training data per class, and suggest using a total of 20,000 training pixels to classify an area about the size of a Landsat scene. The problem of unbalanced training data was alleviated by extracting a minimum of 600 training pixels and a maximum of 8000 training pixels per class. We additionally explored removing outliers contained within the training data based on their spectral and spatial criteria, but observed no significant improvement in classification results. We also tested the importance of different types of auxiliary data that were available for the conterminous United States, including: (a) five variables used by the National Land Cover Database, (b) three variables from the cloud screening ‘‘Function of mask” (Fmask) statistics, and (c) two variables from the change detection results of CCDC. We found that auxiliary variables such as a Digital Elevation Model and its derivatives (aspect, position index, and slope), potential wetland index, water probability, snow probability, and cloud probability improved the accuracy of land cover classification. Compared to the original strategy of the CCDC algorithm (500 pixels per class), the use of the optimal strategy improved the classification accuracies substantially (15-percentage point increase in overall accuracy and 4-percentage point increase in minimum accuracy).

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2021

Biogeography and ecology of Ostracoda in the U.S. northern Bering, Chukchi, and Beaufort Seas

Ostracoda (bivalved Crustacea) comprise a significant part of the benthic meiofauna in the Pacific-Arctic region, including more than 50 species, many with identifiable ecological tolerances. These species hold potential as useful indicators of past and future ecosystem changes. In this study, we examined benthic ostracodes from nearly 300 surface sediment samples, >34,000 specimens, from three regions—the northern Bering, Chukchi and Beaufort Seas—to establish species’ ecology and distribution. Samples were collected during various sampling programs from 1970 through 2018 on the continental shelves at 20 to ~100m water depth. Ordination analyses using species’ relative frequencies identified six species, Normanicythere leioderma , Sarsicytheridea bradii , Paracyprideis pseudopunctillata , Semicytherura complanata , Schizocythere ikeyai , and Munseyella mananensis , as having diagnostic habitat ranges in bottom water temperatures, salinities, sediment substrates and/or food sources. Species relative abundances and distributions can be used to infer past bottom environmental conditions in sediment archives for paleo-reconstructions and to characterize potential changes in Pacific-Arctic ecosystems in future sampling studies. Statistical analyses further showed ostracode assemblages grouped by the summer water masses influencing the area. Offshore-to-nearshore transects of samples across different water masses showed that complex water mass characteristics, such as bottom temperature, productivity, as well as sediment texture, influenced the relative frequencies of ostracode species over small spatial scales. On the larger biogeographic scale, synoptic ordination analyses showed dominant species— N . leioderma (Bering Sea), P . pseudopunctillata (offshore Chukchi and Beaufort Seas), and S . bradii (all regions)—remained fairly constant over recent decades. However, during 2013–2018, northern Pacific species M . mananensis and S . ikeyai increased in abundance by small but significant proportions in the Chukchi Sea region compared to earlier years. It is yet unclear if these assemblage changes signify a meiofaunal response to changing water mass properties and if this trend will continue in the future. Our new ecological data on ostracode species and biogeography suggest these hypotheses can be tested with future benthic monitoring efforts.

PLoS ONE↗
USGS2020

Black oystercatcher (Haematopus bachmani) population size, use of marine reserve complexes, and spatial distribution in Oregon

The Black Oystercatcher is a large shorebird found along the west coast of North America. Because of their small global population size, low reproductive rate, and dependence on rocky intertidal habitats, they are considered a “species of high conservation concern” and may act as an indicator of intertidal ecosystem health. In 2015, the Audubon Society of Portland initiated a 3-year shore-based population survey in Oregon building upon long-term monitoring previously conducted by the U.S. Geological Survey (USGS) and others. The objectives were to 1) Estimate the current minimum population of breeding Black Oystercatchers in Oregon and to compare that to previous estimates to better understand the population trend; 2) Document oystercatcher abundance adjacent to the Oregon’s system of Marine Reserves and Marine Protected Areas; and 3) Describe spatial distribution of breeding oystercatchers along the coast. We targeted all rocky shoreline habitats along Oregon’s coastline to perform abundance surveys each spring. A total of 75 survey routes were sampled using a standardized protocol. Trained volunteer community scientists conducted the majority of the surveys. We used N-mixture statistical models to estimate oystercatcher population size and probability of detection. Population estimates from the best fitting models were consistent, with estimates ranging from 506 oystercatchers in 2016 (95% credible interval, 463-560) to 629 (548-743) in 2015. These estimates indicated a small but stable population. Probability of detection remained consistent across years (ranging from 0.51 to 0.53). The effect of geographic region corresponded with greater bird density in the southern region of Oregon. Oystercatcher abundance adjacent to MR/MPAs accounted for between 12.4-18.3% of the total population estimate which was lower than expected (~25%). We recommend that subsequent conservation efforts directed on Black Oystercatchers in Oregon balance limiting human disturbance, particularly on the north and central coasts, with ensuring protection of core habitats on the south coast where much of the population resides.

Oregon↗
USGS2013

Mercury bioaccumulation in fishes from subalpine lakes of the Wallowa-Whitman National Forest, northeastern Oregon and western Idaho

Mercury (Hg) is a globally distributed pollutant that poses considerable risks to human and wildlife health. Over the past 150 years since the advent of the industrial revolution, approximately 80 percent of global emissions have come from anthropogenic sources, largely fossil fuel combustion. As a result, atmospheric deposition of Hg has increased by up to 4-fold above pre-industrial times. Because of their isolation, remote high-elevation lakes represent unique environments for evaluating the bioaccumulation of atmospherically deposited Hg through freshwater food webs, as well as for evaluating the relative importance of Hg loading versus landscape influences on Hg bioaccumulation. The increase in Hg deposition to these systems over the past century, coupled with their limited exposure to direct anthropogenic disturbance make them useful indicators for estimating how changes in Hg emissions may propagate to changes in Hg bioaccumulation and ecological risk. In this study, we evaluated Hg concentrations in fishes of high-elevation, sub-alpine lakes in the Wallowa-Whitman National Forest in northeastern Oregon and western Idaho. Our goals were to (1) assess the magnitude of Hg contamination in small-catchment lakes to evaluate the risk of atmospheric Hg to human and wildlife health, (2) quantify the spatial variability in fish Hg concentrations, and (3) determine the ecological, limnological, and landscape factors that are best correlated with fish total mercury (THg) concentrations in these systems. Across the 28 study lakes, mean THg concentrations of resident salmonid fishes varied as much as 18-fold among lakes. Importantly, our top statistical model explained 87 percent of the variability in fish THg concentrations among lakes with four key landscape and limnological variables— catchment conifer density (basal area of conifers within a lake’s catchment), lake surface area, aqueous dissolved sulfate, and dissolved organic carbon. The basal area of conifers within a lake’s catchment was by far the most important variable explaining fish THg concentrations, with an increase in THg concentrations of more than 400 percent across the forest density spectrum. Across all study lakes, fish THg concentrations ranged from 0.004 to 0.438 milligrams per kilogram wet weight (mg/kg ww). Only a single individual fish sample exceeded the U.S. Environmental Protection Agency’s (USEPA) human health tissue residue criteria of 0.3 mg/kg ww. However, 54 percent of fish (N=177) exceeded the more stringent tissue residue criteria (0.04 mg/kg ww) adopted by the Oregon Department of Environmental Quality to better protect subsistence fishers. Additionally, 2 and 10 percent of fish exceeded levels associated with reduced common loon reproduction and behavior, respectively. Whereas 25 and 68 percent of fish sampled exceeded concentrations deemed protective of mink and kingfisher, respectively. These results suggest that THg concentrations may be present in these lakes at levels associated with ecological risk. It is important to note however, that accurate inference on potential impairment cannot be made within the context of this study design and further research is needed to better quantify these risks.

Oregon;Idaho↗
USGS2020

Modeling occupancy of rare stream fish species in the upper Cumberland and Kentucky River Basins

Biological conservation often requires an understanding of how environmental conditions affect species occurrence and detection probabilities. We used a hierarchical framework to evaluate these effects for several Appalachian stream fish species of conservation concern: Chrosomus cumberlandensis (BSD; blackside dace), Etheostoma sagitta (CAD; Cumberland arrow darter), and Etheostoma spilotum (KAD; Kentucky arrow darter). Etheostoma susanae (Cumberland darter) also is present in the study area but was too rare to model in this analysis. In this study, conducted by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, fish and habitat data were collected from 205 randomly selected stream sites in the upper Cumberland and Kentucky River Basins (120 and 85 sites, respectively) of Kentucky and Tennessee. Sites were sampled with 10 spatial replicates (2 meter x 5 meter electrofishing zones) to enable estimation of detection probabilities and environmental effects. The best models (that is, lowest Akaike information criterion scores) showed the effects of agriculture (negative) on occurrence of BSD and stream conductivity (negative) on occurrence of CAD and KAD. These effects were statistically more important than measures of basin area, elevation, and substrate size. Conductivity and agriculture showed nonlinear effects on species occurrence, and effects of conductivity were more precise above 400 microsiemens per centimeter than below this threshold. Models incorporated detection-level effects of electrofishing time (positive), flow velocity (negative), sand substrate (positive), and gravel/cobble substrate (negative). Models accounting for detection of BSD estimated occupancy rates similar to the observed proportion of occupied sites (0.10), but the best-supported models for CAD and KAD increased expected occupancy by about 4 percent for each species (from 0.17 to 0.21 for CAD and from 0.07 to 0.11 for KAD). Results of this study provide new inferences for modeling stream fish occurrence and detection processes and highlight the importance of continued monitoring and assessment of rare fish species in Appalachian headwater streams.

Kentucky, Tennessee, Virginia↗
USGS2016

Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes

Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40–75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site-specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution.

Remote Sensing of Environment↗
USGS2026

Using sediment chemical fractions and multivariate statistics on water to identify sources, mobility, and bioavailability of aluminum in the Florida River near Durango, Colorado

The Florida River in southwestern Colorado, USA, flows through the Southern Ute Reservation and is a cultural and water resource to Tribal and non-Tribal communities. High concentrations of total Al, up to 16 400 µg l –1 , have been detected in the Florida River. Elevated Al concentrations in water may affect aquatic organisms’ ability to regulate ions and inhibit respiratory functions. Water chemistry collected during three sampling events in 2022 from the Florida River and two of its tributaries are used here to better understand the spatial distribution, seasonality, and sources of Al concentrations in the Florida River. Streambed sediment and rock chemistry is also used to infer geologic sources of Al in the watershed. A five-stage sequential extraction was performed on streambed sediment and rock samples to help determine Al transport processes. We assessed relations between major and trace elements in water using a principal component analysis, finding that high Al concentrations in the Florida River (>3500 µg l –1 total Al) are caused by the erosion of Al-laden sediments. We used a stepwise multiple linear regression to investigate the relationship between land use and Al concentrations. Land use did not reliably predict Al concentration, though increased streamflow connected to reservoir releases – particularly in the Salt Creek tributary – were found to contribute Al to the Florida River during the irrigation season. In this study, we demonstrate that successful metal source appropriation may be achieved through limited field sampling when performed with sufficient water chemistry analysis, sequential chemical extraction of stream sediments, and statistical and land-use analysis.

Colorado↗
USGS2020

Landscape and climatic influences on actual evapotranspiration and available water using the Operational Simplified Surface Energy Balance (SSEBop) Model in eastern Bernalillo County, New Mexico, 2015

The U.S. Geological Survey, in cooperation with the Bernalillo County Public Works Division, conducted a 1-year study in 2015 to assess the spatial and temporal distribution of evapotranspiration (ET) and available water within the East Mountain area in Bernalillo County, New Mexico. ET and available water vary spatiotemporally because of complex interactions among environmental factors, including vegetation characteristics, soil characteristics, topography, and climate. Precipitation data from the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) ( P ) were used in conjunction with actual ET ( ETa ) data from the Operational Simplified Surface Energy Balance (SSEBop) model to estimate available water ( P – ETa ) at 100-meter (m) resolution in the study area. Maps, descriptive statistics, boxplots, regression analyses (continuous data), and multiple comparison tests (categorical data) were used to characterize P , ETa , and available water and their relations to topographic, soil, and vegetation datasets in the East Mountain area. Five categories of the natural land-cover type (evergreen forest, shrub, herbaceous, deciduous forest, and mixed forest) and four categories of developed land-cover type specific to residential intensity (developed open, developed low, developed medium, and developed high) were analyzed individually and in interaction with multiple elevation, tree canopy, and soil texture classes. Annual mean P in 2015 in the East Mountain area was 608 millimeters (mm), and annual mean ETa was 543 mm (89 percent of annual P in 2015), indicating that in 2015, a spatial mean of about 65 mm of water was available for runoff, soil moisture replenishment, or groundwater recharge. Monthly ETa was greatest in July and smallest in January. The intervening months did not show smooth temporal or consistent spatial changes from month to month. Months with lower ETa (January to March, October to December) also tended to have greater available water, indicating that soil moisture (water supply) and potential ET (water demand) may have been out of phase. Regression analyses showed that monthly ETa data had the highest correlation with annual ETa among the atmospheric, topographic, soil, or vegetation datasets, particularly during the early and late growing season (March, April, May, and September). In contrast, monthly P was highly variable and not as highly correlated with annual ETa . Among landscape variables, correlations with annual ETa were highest for tree canopy cover (coefficient of determination [R 2 ] = 0.46). Correlations between ETa and other landscape variables were lower (R 2 = 0.06–0.19): available soil water in the top 100 centimeters, soil bulk density of layer 1, slope, sand content of soil layer 1, soil depth, available soil water in the top 25 centimeters, leaf area index, aspect eastness, and elevation. Evergreen forest areas had the highest annual median ETa , followed by mixed forest, open residential areas, and deciduous forest. Available water typically was higher in landcover types with lower ETa : herbaceous cover, followed by deciduous forest, high-intensity developed areas, and shrub. Deciduous forest had the second highest median available water, despite having the fourth highest ETa , because deciduous forest had greater P than most other areas. Annual median ETa typically was greatest in the second highest elevation band (2,401–2,800 m above the North American Vertical Datum of 1988 [NAVD 88]), and lower in the highest elevation band (2,801–3,254 m above NAVD 88), despite having greater P , likely because of decreased tree canopy cover or a shift from evergreen to deciduous trees at the highest elevations. Annual median ETa increased with tree canopy cover, regardless of landcover type. ETa correlation was higher with tree canopy than with leaf area index or normalized difference vegetation index. This result indicates that it is important to include the thermal band (from satellite multispectral data) in vegetation indices used to describe ETa , perhaps to account for the influence of energy limitation or water limitation on ET. Of all natural landcover types, finer soils had the most available water, whereas coarser soils had the least available water. Relations of soil type with P – ETa were different than with ETa , indicating ET and available water have a complex response to differences in soil type. Further modeling would be useful in determining soils’ infiltration, storage, conductivity, and plant-water availability relations to individual storms for each position in the landscape, as well as the corresponding effects of these processes on ET and available water. The best multivariate linear model for annual ETa had an R 2 value of 0.62. Monthly ETa models had R 2 values between 0.16 and 0.65. Models usually, but not always, performed best during the growing season. These results indicate that even the best multivariate linear models cannot explain a notable amount of the variability in ET. The monthly ETa models with the highest correlations (August and September) followed a July having almost twice the mean precipitation for July (1981–2010), which indicates that a soil-moisture variable is needed to more accurately model monthly ETa . Further study is needed to better characterize this system, the variables that affect ET and available water, and the partitioning of available water into runoff, soil moisture storage, and groundwater recharge.

New Mexico↗
USGS2008

Mapping regional distribution of a single tree species: Whitebark pine in the Greater Yellowstone Ecosystem

Moderate resolution satellite imagery traditionally has been thought to be inadequate for mapping vegetation at the species level. This has made comprehensive mapping of regional distributions of sensitive species, such as whitebark pine, either impractical or extremely time consuming. We sought to determine whether using a combination of moderate resolution satellite imagery (Landsat Enhanced Thematic Mapper Plus), extensive stand data collected by land management agencies for other purposes, and modern statistical classification techniques (boosted classification trees) could result in successful mapping of whitebark pine. Overall classification accuracies exceeded 90%, with similar individual class accuracies. Accuracies on a localized basis varied based on elevation. Accuracies also varied among administrative units, although we were not able to determine whether these differences related to inherent spatial variations or differences in the quality of available reference data.

Sensors↗
USGS2018

A global empirical model for near real-time assessment of seismically induced landslides

Earthquake-triggered landslides are a significant hazard in seismically active regions, but our ability to assess the hazard they pose in near real-time is limited. In this study, we present a new globally applicable model for seismically induced landslides based on the most comprehensive global dataset available; we use 23 landslide inventories that span a range of earthquake magnitudes and climatic and tectonic settings. We use logistic regression to relate the presence and distribution of earthquake-triggered landslides with spatially distributed estimates of ground shaking, topographic slope, lithology, land-cover type, and a topographic index designed to estimate variability in soil wetness to provide an empirical model of landslide distribution. We tested over 100 combinations of independent predictor variables to find the best-fitting model, using a diverse set of statistical tests. Blind validation tests show the model accurately estimates the distribution of available landslide inventories. The results indicate that the model is reliable and stable, with high “balanced accuracy” (correctly vs. incorrectly classified pixels) for the majority of test events. A cross validation analysis shows high balanced accuracy for a majority of events as well. By combining near-real time estimates of ground shaking with globally available landslide susceptibility data, this model provides a tool to estimate the distribution of co-seismic landslide hazard within minutes of the occurrence of any earthquake worldwide for which a USGS ShakeMap is available.

Journal of Geophysical Research: Earth Surface↗
USGS2020

Simultaneous Middle Pleistocene eruption of three widespread tholeiitic basalts in northern California (USA): Insights into crustal magma transport in an actively extending back arc

Mapping and chronology are central to understanding spatiotemporal volcanic trends in diverse tectonic settings. The Cascades back arc in northern California (USA) hosts abundant lava flows and normal faults, but tholeiitic basalts older than 200 ka are difficult to discriminate by classic mapping methods. Paleomagnetism and chemistry offer independent means of correlating basalts, including the Tennant, Dry Lake, and Hammond Crossing basalt fields. Paleomagnetic analysis of these chemically similar basalts yield notable overlap, with statistical analysis yielding 7 chances in 1,000,000 that their similar mean remanent directions are random. These basalts also have overlapping 40 Ar/ 39 Ar ages of 272.5 ± 30.6 ka (Tennant), 305.8 ± 23.9 ka (Dry Lake), and 300.4 ± 15.2 and 322.6 ± 17.4 ka (Hammond Crossing). Chemical and paleomagnetic analyses indicate that these spatially distributed basalts represent simultaneous (<100 yr uncertainty) eruptions, and thus we use 305.5 ± 9.8 ka (weighted mean) as the eruption age. Their vents align on a N25°W trend over a distance of 39 km. Tennant erupted the largest volume (3.55 ± 0.75 km 3 ) at the highest elevation; both factors decay to the south-southeast at Dry Lake (0.75 ± 0.15 km 3 ) and Hammond Crossing (0.15 ± 0.05 km 3 ). We propose vertical magma ascent beneath the Tennant vent area, where the most evolved, high-SiO 2 magma erupted, with lateral dike propagation in the brittle crust. Propagation was near orthogonal to east-west extension (0.3–0.6 mm/yr) along north-northwest–trending normal faults.

California↗
USGS1977

Analysis and machine mapping of the distribution of band recoveries

A method of calculating distance and bearing from banding site to recovery location based on the solution of a spherical triangle is presented. X and Y distances on an ordinate grid were applied to computer plotting of recoveries on a map. The advantages and disadvantages of tables of recoveries by State or degree block, axial lines, and distance of recovery from banding site for presentation and comparison of the spatial distribution of band recoveries are discussed. A special web-shaped partition formed by concentric circles about the point of banding and great circles at 30-degree intervals through the point of banding has certain advantages over other methods. Comparison of distributions by means of a X? contingency test is illustrated. The statistic V = X?/N can be used as a measure of difference between two distributions of band recoveries and its possible use is illustrated as a measure of the degree of migrational homing.

Special Scientific Report - Wildlife↗
USGS2002

Artificial intelligence based decision support for trumpeter swan management

The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988-2000. Applying the Matched Pairs Multivariate Permutation Test as a statistical tool was a new approach for comparing flyway distributions of waterfowl over time that seemed to work well. Based on this approach, the empirical evidence that I gathered led me to conclude that the base queuing model does accurately simulate swan distributions in the flyway. The system was insensitive to almost all model parameters tested. That remains perplexing, but might result from the base queuing model, itself, being particularly effective at representing the actual ecological diversity in the world of Rocky Mountain trumpeter swans, both spatial and temporally.

Idaho, Montana, Utah, Wyoming↗
USGS2000

Fire frequency in the Interior Columbia River Basin: Building regional models from fire history data

Fire frequency affects vegetation composition and successional pathways; thus it is essential to understand fire regimes in order to manage natural resources at broad spatial scales. Fire history data are lacking for many regions for which fire management decisions are being made, so models are needed to estimate past fire frequency where local data are not yet available. We developed multiple regression models and tree-based (classification and regression tree, or CART) models to predict fire return intervals across the interior Columbia River basin at 1-km resolution, using georeferenced fire history, potential vegetation, cover type, and precipitation databases. The models combined semiqualitative methods and rigorous statistics. The fire history data are of uneven quality; some estimates are based on only one tree, and many are not cross-dated. Therefore, we weighted the models based on data quality and performed a sensitivity analysis of the effects on the models of estimation errors that are due to lack of cross-dating. The regression models predict fire return intervals from 1 to 375 yr for forested areas, whereas the tree-based models predict a range of 8 to 150 yr. Both types of models predict latitudinal and elevational gradients of increasing fire return intervals. Examination of regional-scale output suggests that, although the tree-based models explain more of the variation in the original data, the regression models are less likely to produce extrapolation errors. Thus, the models serve complementary purposes in elucidating the relationships among fire frequency, the predictor variables, and spatial scale. The models can provide local managers with quantitative information and provide data to initialize coarse-scale fire-effects models, although predictions for individual sites should be treated with caution because of the varying quality and uneven spatial coverage of the fire history database. The models also demonstrate the integration of qualitative and quantitative methods when requisite data for fully quantitative models are unavailable. They can be tested by comparing new, independent fire history reconstructions against their predictions and can be continually updated, as better fire history data become available.

California, Idaho, Montana, Nevada, Oregon, Utah, ↗
USGS2026

HyFlood: A surrogate-model-based framework for compound coastal flooding

Compound coastal flooding is a major threat to low-lying coastal regions and is expected to intensify under future climate change projections. However, modeling the joint interaction of waves, storm surge, tides, and rainfall remains computationally demanding, limiting the development of fast and reliable forecast tools. Here we present HyFlood, a hybrid statistical-numerical downscaling framework capable of computing and mapping high-resolution compound flood hazards while substantially reducing the computational cost compared with fully process-based hydrodynamic modeling. HyFlood combines statistical sampling and selection algorithms with a cascade of reduced-complexity surrogate models that emulate nearshore wave transformation, surf-zone hydrodynamics, and coastal, fluvial, and pluvial flooding. The surrogate models employ machine-learning and regression algorithms applied to a low-dimensional representation of the flooding outputs, obtained through statistical dimensionality reduction. The framework is demonstrated in southern O'ahu, Hawai'i, a region exposed to elevated sea levels driven by tides, waves, and storm surge along with frequent precipitation-driven flash flooding. Validation of the surrogates against the physics-based model outputs demonstrates that HyFlood accurately reproduces daily maxima of spatially distributed flooding depths. This hybrid approach offers a scalable and efficient tool to better quantify how changes in flooding drivers translate into hazard and impact assessments, and to support compound-flood risk assessments and climate-change adaptation planning.

Hawaii↗
USGS2010

Stochastic analysis of solute arrival time in heterogeneous porous media

Longitudinal advective solute movement in heterogeneous porous media is investigated by considering the solute arrival time at a plane perpendicular to the mean fluid velocity. The moments of the solute arrival time are defined in terms of the stochastic properties of a statistically anisotropic hydraulic conductivity field. The flux‐averaged concentration is specified by introducing the moments of the arrival time into a probability density function for the arrival time. The quadratic dependence of the arrival time variance on position in the vicinity of an injection point is indicative of a nondiffusive process. For the assumed spatial correlation of the hydraulic conductivity, the variance of the arrival time asymptotically approaches a linear dependence on the position from the injection point similar to a diffusion process. The impact of assuming solute movement to be a diffusive process from the onset of the solute injection causes erroneous estimates of flux‐averaged concentrations at distances from the injection point that are of the order of the correlation length of the hydraulic conductivity. The arrival time analysis and the particle position analysis given in Dagan (1982, 1984) are complementary interpretations of advective solute movement that yield different definitions of the solute concentration; the position analysis intrinsically defines the resident or volume‐averaged concentration, while the flux‐averaged concentration is defined from the arrival time analysis. The temporal variation of the resident and flux‐averaged concentration are similar at a given position for small values of the variance of the hydraulic conductivity, or at distances from the solute injection point that are large relative to correlation length of the hydraulic conductivity.

Water Resources Research↗
USGS2009

Streamflow Simulations and Percolation Estimates Using the Soil and Water Assessment Tool for Selected Basins in North-Central Nebraska, 1940-2005

The U.S. Geological Survey, in cooperation with the Upper Elkhorn, Lower Elkhorn, Upper Loup, Lower Loup, Middle Niobrara, Lower Niobrara, Lewis and Clark, and Lower Platte North Natural Resources Districts, used the Soil and Water Assessment Tool to simulate streamflow and estimate percolation in north-central Nebraska to aid development of long-term strategies for management of hydrologically connected ground and surface water. Although groundwater models adequately simulate subsurface hydrologic processes, they often are not designed to simulate the hydrologically complex processes occurring at or near the land surface. The use of watershed models such as the Soil and Water Assessment Tool, which are designed specifically to simulate surface and near-subsurface processes, can provide helpful insight into the effects of surface-water hydrology on the groundwater system. The Soil and Water Assessment Tool was calibrated for five stream basins in the Elkhorn-Loup Groundwater Model study area in north-central Nebraska to obtain spatially variable estimates of percolation. Six watershed models were calibrated to recorded streamflow in each subbasin by modifying the adjustment parameters. The calibrated parameter sets were then used to simulate a validation period; the validation period was half of the total streamflow period of record with a minimum requirement of 10 years. If the statistical and water-balance results for the validation period were similar to those for the calibration period, a model was considered satisfactory. Statistical measures of each watershed model's performance were variable. These objective measures included the Nash-Sutcliffe measure of efficiency, the ratio of the root-mean-square error to the standard deviation of the measured data, and an estimate of bias. The model met performance criteria for the bias statistic, but failed to meet statistical adequacy criteria for the other two performance measures when evaluated at a monthly time step. A primary cause of the poor model validation results was the inability of the model to reproduce the sustained base flow and streamflow response to precipitation that was observed in the Sand Hills region. The watershed models also were evaluated based on how well they conformed to the annual mass balance (precipitation equals the sum of evapotranspiration, streamflow/runoff, and deep percolation). The model was able to adequately simulate annual values of evapotranspiration, runoff, and precipitation in comparison to reported values, which indicates the model may provide reasonable estimates of annual percolation. Mean annual percolation estimated by the model as basin averages varied within the study area from a maximum of 12.9 inches in the Loup River Basin to a minimum of 1.5 inches in the Shell Creek Basin. Percolation also varied within the studied basins; basin headwaters tended to have greater percolation rates than downstream areas. This variance in percolation rates was mainly was because of the predominance of sandy, highly permeable soils in the upstream areas of the modeled basins.

Scientific Investigations Report↗
USGS2013

Nutrient and sediment concentrations, yields, and loads in impaired streams and rivers in the Taunton River Basin, Massachusetts, 1997-2008

Rapid development, population growth, and the changes in land and water use accompanying development are placing increasing stress on water resources in the Taunton River Basin. An assessment by the Massachusetts Department of Environmental Protection determined that a number of tributary streams to the Taunton River are impaired for a variety of beneficial uses because of nutrient enrichment. Most of the impaired reaches are in the Matfield River drainage area in the vicinity of the City of Brockton. In addition to impairments of stream reaches in the basin, discharge of nutrient-rich water from the Taunton River contributes to eutrophication of Mount Hope and Narragansett Bays. To assess water quality and loading in the impaired tributary stream reaches in the basin, the U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection compiled existing water-quality data from previous studies for the period 1997-2006, developed and calibrated a Hydrological Simulation Program-FORTRAN (HSPF) precipitation-runoff model to simulate streamflow in areas of the basin that contain the impaired reaches for the same time period, and collected additional streamflow and water-quality data from sites on the Matfield and Taunton Rivers in 2008. A majority of the waterquality samples used in the study were collected between 1999 and 2006. Overall, the concentration, yield, and load data presented in this report represent water-quality conditions in the basin for the period 1997-2008. Water-quality data from 52 unique sites were used in the study. Most of the samples from previous studies were collected between June and September under dry weather conditions. Simulated or measured daily mean streamflow and water-quality data were used to estimate constituent yields and loads in the impaired tributary stream reaches and the main stem of the Taunton River and to develop yield-duration plots for reaches with sufficient water-quality data. Total phosphorus concentrations in the impaired-reach areas ranged from 0.0046 to 0.91 milligrams per liter (mg/L) in individual samples (number of samples (n)=331), with a median of 0.090 mg/L; total nitrogen concentrations ranged from 0.34 to 14 mg/L in individual samples (n=139), with a median of 1.35 mg/L; and total suspended solids concentrations ranged from 2/d) for total phosphorus and 100 lb/mi 2 /d for total nitrogen in these reaches. In most of the impaired reaches not affected by the Brockton Advanced Water Reclamation Facility outfall, yields were lower than in reaches downstream from the outfall, and the difference between measured and threshold yields was fairly uniform over a wide range of flows, suggesting that multiple processes contribute to nonpoint loading in these reaches. The Northeast and Mid-Atlantic SPAtially-Referenced Regression On Watershed (SPARROW) models for total phosphorus and total nitrogen also were used to estimate annual nutrient loads in the impaired tributary stream reaches and main stem of the Taunton River and predict the distribution of these loads among point and diffuse sources in reach drainage areas. SPARROW is a regional, statistical model that relates nutrient loads in streams to upstream sources and land-use characteristics and can be used to make predictions for streams that do not have nutrient-load data. The model predicts mean annual loads based on longterm streamflow and water-quality data and nutrient source conditions for the year 2002. Predicted mean annual nutrient loads from the SPARROW models were consistent with the measured yield and load data from sampling sites in the basin. For conditions in 2002, the Brockton Advanced Water Reclamation Facility outfall accounted for over 75 percent of the total nitrogen load and over 93 percent of the total phosphorus load in the Salisbury Plain and Matfield Rivers downstream from the outfall. Municipal point sources also accounted for most of the load in the main stem of the Taunton River. Multiple municipal wastewater discharges in the basin accounted for about 76 and 46 percent of the delivered loads of total phosphorus and total nitrogen, respectively, to Mount Hope Bay. For similarly sized watersheds, total delivered loads were lower in watersheds without point sources compared to those with point sources, and sources associated with developed land accounted for most of the delivered phosphorus and nitrogen loads to the impaired reaches. The concentration, yield, and load data evaluated in this study may not be representative of current (2012) point-source loading in the basin; in particular, most of the water-quality data used in the study (1999-2006) were collected prior to completion of upgrades to the Brockton Advanced Water Reclamation Facility that reduced total phosphorus and nitrogen concentrations in treated effluent. Effluent concentration data indicate that, for a given flow rate, effluent loads of total phosphorus and total nitrogen declined by about 80 and 30 percent, respectively, between the late 1990s and 2008 in response to plant upgrades. Consequently, current (2012) water-quality conditions in the impaired reaches downstream from the facility likely have improved compared to conditions described in the report.

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