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Mechanisms of aquatic species invasions across the South Atlantic Landscape Conservation Cooperative region

Invasive species are a global issue, and the southeastern United States is not immune to the problems they present. Therefore, various analyses using modeling and exploratory statistics were performed on the U.S. Geological Survey Nonindigenous Aquatic Species (NAS) Database with the primary objective of determining the most appropriate use of presence-only data as related to invasive species in the South Atlantic Landscape Conservation Cooperative (SALCC) region. A hierarchical model approach showed that a relatively small amount of high-quality data from planned surveys can be used to leverage the information in presence-only observations, having a broad spatial coverage and high biases of observer detection and in site selection. Because a variety of sampling protocols can be used in planned surveys, this approach to the analysis of presence-only data is widely applicable. An important part of the management of natural landscapes is the preservation of designated protected areas. When the hydrologic connection was considered in this analysis, the number of potential invaders that could spread to each protected area within the SALCC region was greatly increased, with a mean exceeding 30 species and the maximum reaching 57 species. Nearly all protected areas are hydrologically connected to at least 20 nonindigenous aquatic species. To examine possible factors which may contribute to nonindigenous aquatic species richness in the SALCC region, a set of exploratory statistics was employed. The best statistical model that included a combination of three anthropogenic variables (densities of housing, roads, and reservoirs) and two environmental variables (elevation range and longitude) explained approximately 62 percent of the variation in introduced species richness. Highest nonindigenous aquatic species richness occurred in the more upland, mountainous regions, where elevation range favored reservoirs and attracted urban centers. Lastly, patterns seen in a diffusion model may reflect less about the diffusion process of the organism and more about the opportunistic nature of the data collection process. These results of the model are considered exploratory in nature.

Alabama, Florida, Georgia, North Carolina, South C↗

Seasonal and interannual variability in the taxonomic composition and production dynamics of phytoplankton assemblages in Crater Lake, Oregon

Taxonomic composition and production dynamics of phytoplankton assemblages in Crater Lake, Oregon, were examined during time periods between 1984 and 2000. The objectives of the study were (1) to investigate spatial and temporal patterns in species composition, chlorophyll concentration, and primary productivity relative to seasonal patterns of water circulation; (2) to explore relationships between water column chemistry and the taxonomic composition of the phytoplankton; and (3) to determine effects of primary and secondary consumers on the phytoplankton assemblage. An analysis of 690 samples obtained on 50 sampling dates from 14 depths in the water column found a total of 163 phytoplankton taxa, 134 of which were identified to genus and 101 were identified to the species or variety level of classification. Dominant species by density or biovolume included Nitzschia gracilis, Stephanodiscus hantzschii, Ankistrodesmus spiralis, Mougeotia parvula, Dinobryon sertularia, Tribonema affine, Aphanocapsa delicatissima, Synechocystis sp., Gymnodinium inversum , and Peridinium inconspicuum . When the lake was thermally stratified in late summer, some of these species exhibited a stratified vertical distribution in the water column. A cluster analysis of these data also revealed a vertical stratification of the flora from the middle of the summer through the early fall. Multivariate test statistics indicated that there was a significant relationship between the species composition of the phytoplankton and a corresponding set of chemical variables measured for samples from the water column. In this case, concentrations of total phosphorus, ammonia, total Kjeldahl nitrogen, and alkalinity were associated with interannual changes in the flora; whereas pH and concentrations of dissolved oxygen, orthophosphate, nitrate, and silicon were more closely related to spatial variation and thermal stratification. The maximum chlorophyll concentration when the lake was thermally stratified in August and September was usually between depths of 100 m and 120 m. In comparison, the depth of maximum primary production ranged from 60 m to 80 m at this time of year. Regression analysis detected a weak negative relationship between chlorophyll concentration and Secchi disk depth, a measure of lake transparency. However, interannual changes in chlorophyll concentration and the species composition of the phytoplankton could not be explained by the removal of the septic field near Rim Village or by patterns of upwelling from the deep lake. An alternative trophic hypothesis proposes that the productivity of Crater Lake is controlled primarily by long-term patterns of climatic change that regulate the supply of allochthonous nutrients.

Crater Lake↗

Predicting aquatic habitat connectivity across watershed boundaries: Implications for interbasin spread of nonindigenous aquatic species.

Understanding habitat connectivity is critical for managing nonindigenous aquatic species (NAS) spread. Dams and watershed boundaries can be impassable to NAS during typical conditions but may become temporarily passable during flooding. The goal of our project was to develop an approach for identifying locations of aquatic connectivity at a fine spatial scale along watershed boundaries using readily available data. To develop this approach, we focused on the potential for range expansion of invasive fish in the United States via possible cross-boundary habitat connections. First, we developed an index using metrics of elevation, watershed size, and geology at regular points along a watershed boundary to stratify points by likelihood of connectivity during high precipitation (>20 mm of precipitation in a 3-day period). We then used a subset of points across a gradient of connectivity likelihoods to gather Landsat-derived observed surface water data and developed a statistical model to predict surface water presence from landscape characteristics. We applied the model throughout the entire watershed boundary to identify locations of hydrologic connectivity during high-water events. The presence of surface water on watershed boundaries was predicted by the interactions between watershed boundary point elevation relative to the minimum adjacent HUC-12 elevations and watershed boundary point elevation relative to neighboring point elevations (marginal R 2 = 0.94). Our approach can be used to identify potential areas of surface water connectivity between watersheds quickly and easily at a fine spatial scale using readily available, remotely sensed data that can inform conservation and management actions across disciplines.

North Dakota, South Dakota↗

A topology of mineralization and its meaning for prospecting

Epigenetic mineral deposits are universal members of an orderly spatial and temporal arrangement of igneous rocks, endomorphic rocks, and hydrothermally altered rocks. The association and sequence of these rocks is invariant whereas the metric relations and configurations of the properties of these rocks are unlimited in variety. This characterization satisfies the doctrines of topology. Metric relations are statistical, and their modes are among the better guides to optimal areas for exploration. Metric configurations are graphically irregular and unpredictable mathematical surfaces like mountain topography. Each mineral edifice must be mapped to locate its mineral deposits. All measurements and observations are only positive or neutral for the occurrence of a mineral deposit. Effective prospecting is based on an increasing density of positive data with proximity to the mineral deposit. This means sampling for maximal numbers of positive data, pragmatically the highest ore-element assays at each site, by selecting rock showing maximal development of lode attributes.

Book chapter↗

A computer program (MODFLOWP) for estimating parameters of a transient, three-dimensional ground-water flow model using nonlinear regression

This report documents a new version of the U.S. Geological Survey modular, three-dimensional, finite-difference, ground-water flow model (MODFLOW) which, with the new Parameter-Estimation Package that also is documented in this report, can be used to estimate parameters by nonlinear regression. The new version of MODFLOW is called MODFLOWP (pronounced MOD-FLOW*P), and functions nearly identically to MODFLOW when the ParameterEstimation Package is not used. Parameters are estimated by minimizing a weighted least-squares objective function by the modified Gauss-Newton method or by a conjugate-direction method. Parameters used to calculate the following MODFLOW model inputs can be estimated: Transmissivity and storage coefficient of confined layers; hydraulic conductivity and specific yield of unconfined layers; vertical leakance; vertical anisotropy (used to calculate vertical leakance); horizontal anisotropy; hydraulic conductance of the River, Streamflow-Routing, General-Head Boundary, and Drain Packages; areal recharge rates; maximum evapotranspiration; pumpage rates; and the hydraulic head at constant-head boundaries. Any spatial variation in parameters can be defined by the user. Data used to estimate parameters can include existing independent estimates of parameter values, observed hydraulic heads or temporal changes in hydraulic heads, and observed gains and losses along head-dependent boundaries (such as streams). Model output includes statistics for analyzing the parameter estimates and the model; these statistics can be used to quantify the reliability of the resulting model, to suggest changes in model construction, and to compare results of models constructed in different ways.

Open-File Report↗

Defining surfaces for skewed, highly variable data

Skewness of environmental data is often caused by more than simply a handful of outliers in an otherwise normal distribution. Statistical procedures for such datasets must be sufficiently robust to deal with distributions that are strongly non-normal, containing both a large proportion of outliers and a skewed main body of data. In the field of water quality, skewness is commonly associated with large variation over short distances. Spatial analysis of such data generally requires either considerable effort at modeling or the use of robust procedures not strongly affected by skewness and local variability. Using a skewed dataset of 675 nitrate measurements in ground water, commonly used methods for defining a surface (least-squares regression and kriging) are compared to a more robust method (loess). Three choices are critical in defining a surface: (i) is the surface to be a central mean or median surface? (ii) is either a well-fitting transformation or a robust and scale-independent measure of center used? (iii) does local spatial autocorrelation assist in or detract from addressing objectives? Published in 2002 by John Wiley & Sons, Ltd.

Environmetrics↗

Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models

Gully erosion susceptibility mapping is a fundamental tool for land-use planning aimed at mitigating land degradation. However, the capabilities of some state-of-the-art data-mining models for developing accurate maps of gully erosion susceptibility have not yet been fully investigated. This study assessed and compared the performance of two different types of data-mining models for accurately mapping gully erosion susceptibility at a regional scale in Chavar, Ilam, Iran. The two methods evaluated were: Certainty Factor (CF), a bivariate statistical model; and Maximum Entropy (ME), an advanced machine learning model. Several geographic and environmental factors that can contribute to gully erosion were considered as predictor variables of gully erosion susceptibility. Based on an existing differential GPS survey inventory of gully erosion, a total of 63 eroded gullies were spatially randomly split in a 70:30 ratio for use in model calibration and validation, respectively. Accuracy assessments completed with the receiver operating characteristic curve method showed that the ME-based regional gully susceptibility map has an area under the curve (AUC) value of 88.6% whereas the CF-based map has an AUC of 81.8%. According to jackknife tests that were used to investigate the relative importance of predictor variables, aspect, distance to river, lithology and land use are the most influential factors for the spatial distribution of gully erosion susceptibility in this region of Iran. The gully erosion susceptibility maps produced in this study could be useful tools for land managers and engineers tasked with road development, urbanization and other future development.

Science of the Total Environment↗

Estimation of aquifer scale proportion using equal area grids: assessment of regional scale groundwater quality

The proportion of an aquifer with constituent concentrations above a specified threshold (high concentrations) is taken as a nondimensional measure of regional scale water quality. If computed on the basis of area, it can be referred to as the aquifer scale proportion. A spatially unbiased estimate of aquifer scale proportion and a confidence interval for that estimate are obtained through the use of equal area grids and the binomial distribution. Traditionally, the confidence interval for a binomial proportion is computed using either the standard interval or the exact interval. Research from the statistics literature has shown that the standard interval should not be used and that the exact interval is overly conservative. On the basis of coverage probability and interval width, the Jeffreys interval is preferred. If more than one sample per cell is available, cell declustering is used to estimate the aquifer scale proportion, and Kish's design effect may be useful for estimating an effective number of samples. The binomial distribution is also used to quantify the adequacy of a grid with a given number of cells for identifying a small target, defined as a constituent that is present at high concentrations in a small proportion of the aquifer. Case studies illustrate a consistency between approaches that use one well per grid cell and many wells per cell. The methods presented in this paper provide a quantitative basis for designing a sampling program and for utilizing existing data.

Water Resources Research↗

A multi-scale soil moisture monitoring strategy for California: Design and validation

A multi‐scale soil moisture monitoring strategy for California was designed to inform water resource management. The proposed workflow classifies soil moisture response units (SMRUs) using publicly available datasets that represent soil, vegetation, climate, and hydrology variables, which control soil water storage. The SMRUs were classified, using principal component analysis and unsupervised K‐means clustering within a geographic information system, and validated, using summary statistics derived from measured soil moisture time series. Validation stations, located in the Sierra Nevada, include transect of sites that cross the rain‐to‐snow transition and a cluster of sites located at similar elevations in a snow‐dominated watershed. The SMRUs capture unique responses to varying climate conditions characterized by statistical measures of central tendency, dispersion, and extremes. A topographic position index and landform classification is the final step in the workflow to guide the optimal placement of soil moisture sensors at the local‐scale. The proposed workflow is highly flexible and can be implemented over a range of spatial scales and input datasets can be customized. Our approach captures a range of soil moisture responses to climate across California and can be used to design and optimize soil moisture monitoring strategies to support runoff forecasts for water supply management or to assess landscape conditions for forest and rangeland management.

California↗

Normal streamflows and water levels continue—Summary of hydrologic conditions in Georgia, 2014

The U.S. Geological Survey (USGS) South Atlantic Water Science Center (SAWSC) Georgia office, in cooperation with local, State, and other Federal agencies, maintains a long-term hydrologic monitoring network of more than 350 real-time, continuous-record, streamflow-gaging stations (streamgages). The network includes 14 real-time lake-level monitoring stations, 72 real-time surface-water-quality monitors, and several water-quality sampling programs. Additionally, the SAWSC Georgia office operates more than 204 groundwater monitoring wells, 39 of which are real-time. The wide-ranging coverage of streamflow, reservoir, and groundwater monitoring sites allows for a comprehensive view of hydrologic conditions across the State. One of the many benefits this monitoring network provides is a spatially distributed overview of the hydrologic conditions of creeks, rivers, reservoirs, and aquifers in Georgia. Streamflow and groundwater data are verified throughout the year by USGS hydrographers and made available to water-resource managers, recreationists, and Federal, State, and local agencies. Hydrologic conditions are determined by comparing the statistical analyses of data collected during the current water year to historical data. Changing hydrologic conditions underscore the need for accurate, timely data to allow informed decisions about the management and conservation of Georgia’s water resources for agricultural, recreational, ecological, and water-supply needs and in protecting life and property.

Georgia↗

Social Values for Ecosystem Services, version 3.0 (SolVES 3.0): documentation and user manual

The geographic information system (GIS) tool, S ocial V alues for E cosystem S ervices (SolVES), was developed to incorporate quantified and spatially explicit measures of social values into ecosystem service assessments. SolVES 3.0 continues to extend the functionality of SolVES, which was designed to assess, map, and quantify the social values of ecosystem services. Social values—the perceived, nonmarket values the public ascribes to ecosystem services, particularly cultural services, such as aesthetics and recreation—can be evaluated for various stakeholder groups. These groups are distinguishable by their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with previous versions, SolVES 3.0 derives a quantitative 10-point, social-values metric—the value index—from a combination of spatial and nonspatial responses to public value and preference surveys. The tool also calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. SolVES 3.0 is integrated with Maxent maximum entropy modeling software to generate more complete social-value maps and offer robust statistical models describing the relationship between the value index and explanatory environmental variables. A model’s goodness of fit to a primary study area and its potential performance in transferring social values to similar areas using value-transfer methodology can be evaluated. SolVES 3.0 provides an improved public-domain tool for decision makers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among ecosystem services in a variety of physical and social contexts ranging from forest and rangeland to coastal and marine.

Open-File Report↗

Coastal change analysis program implemented in Louisiana

Landsat Thematic Mapper images from 1990 to 1996 and collateral data sources were used to classify the land cover of the Mermentau River Basin (MRB) within the Chenier Plain of coastal Louisiana. Landcover classes followed the definition of the National Oceanic and Atmospheric Administration's Coastal Change Analysis Program; however, classification methods had to be developed as part of this study for attainment of these national classification standards. Classification method developments were especially important when classes were spectrally inseparable, when classes were part of spatial and spectral continuums, when the spatial resolution of the sensor included more than one landcover type, and when human activities caused abnormal transitions in the landscape. Most classification problems were overcome by using one or a combination of techniques, such as separating the MRB into subregions of commonality, applying masks to specific land mixtures, and highlighting class transitions between years that were highly unlikely. Overall, 1990, 1993, and 1996 classification accuracy percentages (associated kappa statistics) were 80% (0.79), 78% (0.76), and 86% (0.84), respectively. Most classification errors were associated with confusion between managed (cultivated land) and unmanaged grassland classes; scrub shrub, grasslands and forest classes; water, unconsolidated shore and bare land classes; and especially in 1993, between water and floating vegetation classes. Combining cultivated land and grassland classes and water and floating vegetation classes into single classes accuracies for 1990, 1993, and 1996 increased to 82%, 83%, and 90%, respectively. To improve the interpretation of landcover change, three indicators of landcover class stability were formulated. Location stability was defined as the percentage of a landcover class that remained as the same class in the same location at the beginning and the end of the monitoring period. Residence stability was defined as the percent change in each class within the entire MRB during the monitoring period. Turnover was defined as the addition of other landcover classes to the target landcover class during the defined monitoring period. These indicators allowed quick assessment of the dynamic nature of landcover classes, both in reference to a spatial location and to retaining their presence throughout the MRB. Examining the landcover changes between 1990 to 1993 and 1993 to 1996, led us to five principal findings: (1) Landcover turnover is maintaining a near stable logging cycle, although the locations of grassland, scrub shrub, and forest areas involved in the cycle appeared to change. (2) Planting of seedlings is critical to maintaining cycle stability. (3) Logging activities tend to replace woody land mixed forests with woody land evergreen forests. (4) Wetland estuarine marshes are expanding slightly. (5) Wetland palustrine marshes and mature forested wetlands in the MRB are relatively stable.

Louisiana↗

Deep learning for water quality

Understanding and predicting the quality of inland waters are challenging, particularly in the context of intensifying climate extremes expected in the future. These challenges arise partly due to complex processes that regulate water quality, and arduous and expensive data collection that exacerbate the issue of data scarcity. Traditional process-based and statistical models often fall short in predicting water quality. In this Review, we posit that deep learning represents an underutilized yet promising approach that can unravel intricate structures and relationships in high-dimensional data. We demonstrate that deep learning methods can help address data scarcity by filling temporal and spatial gaps and aid in formulating and testing hypotheses via identifying influential drivers of water quality. This Review highlights the strengths and limitations of deep learning methods relative to traditional approaches, and underscores its potential as an emerging and indispensable approach in overcoming challenges and discovering new knowledge in water-quality sciences.

Nature Water↗

Documentation of the U.S. Geological Survey sea floor stress and sediment mobility database

The U.S. Geological Survey Sea Floor Stress and Sediment Mobility Database contains estimates of bottom stress and sediment mobility for the U.S. continental shelf. This U.S. Geological Survey database provides information that is needed to characterize sea floor ecosystems and evaluate areas for human use. The estimates contained in the database are designed to spatially and seasonally resolve the general characteristics of bottom stress over the U.S. continental shelf and to estimate sea floor mobility by comparing critical stress thresholds based on observed sediment texture data to the modeled stress. This report describes the methods used to make the bottom stress and mobility estimates, statistics used to characterize stress and mobility, data validation procedures, and the metadata for each dataset and provides information on how to access the database online.

Open-File Report↗

Hydrogeomorphic segments and hydraulic microhabitats of the Niobrara River, Nebraska— With special emphasis on the Niobrara National Scenic River

The Niobrara River is an ecologically and economically important resource in Nebraska. The Nebraska Department of Natural Resources’ recent designation of the hydraulically connected surface- and groundwater resources of the Niobrara River Basin as “fully appropriated” has emphasized the importance of understanding linkages between the physical and ecological dynamics of the Niobrara River so it can be sustainably managed. In cooperation with the Nebraska Game and Parks Commission, the U.S. Geological Survey investigated the hydrogeomorphic and hydraulic attributes of the Niobrara River in northern Nebraska. This report presents the results of an analysis of hydrogeomorphic segments and hydraulic microhabitats of the Niobrara River and its valley for the approximately 330-mile reach from Dunlap Diversion Dam to its confluence with the Missouri River. Two spatial scales were used to examine and quantify the hydrogeomorphic segments and hydraulic microhabitats of the Niobrara River: a basin scale and a reach scale. At the basin scale, digital spatial data and hydrologic data were analyzed to (1) test for differences between 36 previously determined longitudinal hydrogeomorphic segments; (2) quantitatively describe the hydrogeomorphic characteristics of the river and its valley; and (3) evaluate differences in hydraulic microhabitat over a range of flow regimes among three fluvial geomorphic provinces. The statistical analysis of hydrogeomorphic segments resulted in reclassification rates of 3 to 28 percent of the segments for the four descriptive geomorphic elements. The reassignment of classes by discriminant analysis resulted in a reduction from 36 to 25 total hydrogeomorphic segments because several adjoining segments shared the same ultimate class assignments. Virtually all of the segment mergers were in the Canyons and Restricted Bottoms (CRB) fluvial geomorphic province. The most frequent classes among hydrogeomorphic segments, and the dominant classes per unit length of river, are: a width-restricted valley confinement condition, sinuous-planview pattern, irregular channel width, and an alternate bar configuration. The Niobrara River in the study area flows through a diversity of fluvial geomorphic settings in its traverse across northern Nebraska. In the Meandering Bottoms (MB) fluvial geomorphic province, river discharge magnitudes are low, and the valley exerts little control on the channel-planview pattern. Within the CRB province, the river flows over a diversity of geologic formations, and the valley and river narrow and expand in approximate synchronicity. In the Braided Bottoms (BB) fluvial geomorphic province, the river primarily flows over Cretaceous Pierre Shale, the valley and channel are persistently wide, and the channel slope is generally uniform. The existence of vegetated islands and consequent multithread channel environments, indicated by a higher braided index, mostly coincided with reaches having gentler slopes and less unit stream power. Longitudinal hydrology curves indicate that the flow of the Niobrara River likely is dominated by groundwater as far downstream as Norden. Unit stream power values in the study area vary between 0 and almost 2 pounds per foot per second. Within the MB province, unit stream power steadily increases as the Niobrara gains discharge from groundwater inflow, and the channel slope steepens. The combination of steep slopes, a constrained channel width, and persistent flow within the CRB province results in unit stream power values that are between three and five times greater than those in less confined segments with comparable or greater discharges. With the exception of hydrogeomorphic segment 3, which is affected by Spencer Dam, unit stream power values in the BB province are generally uniform. Channel sinuosity values in the study area varied generally between 1 and 2.5, but with locally higher values measured in the MB province and at the entrenched bedrock meanders of hydrogeomorphic segment 18 in the CRB province. The differences in channel morphology and hydraulic geometries between fluvial geomorphic provinces are evident in the types, relative abundance, and response of hydraulic microhabitats to changing discharges. The four gaging stations chosen for hydraulic microhabitat analysis are distributed among three different fluvial geomorphic provinces. In the MB province, the smaller channel and lower discharges resulted in the dominance of shallow and intermediate-depth hydraulic environments with the vast majority of hydraulic microhabitat restricted to shallow categories even during upper-decile discharges. In the CRB province, intermediate depth hydraulic conditions, particularly intermediate-swift, dominate over all ranges of discharge. Hydraulic microhabitat conditions were most diverse in the BB province, with most hydraulic microhabitat categories present over the entire range of discharges analyzed. The calculated differences in hydraulic microhabitat distributions, abundance, and adjustments between streamflow-gaging stations were the result of differences in physical structure of the channel and subsequent channel hydraulic geometry. At the reach scale, field measurements made in water years 2008 and 2009 in four study reaches within the Scenic Reach were used to (1) characterize the elevation and geomorphic processes associated with fluvial landforms, (2) build hydraulic geometry relations, (3) examine flow hydraulics over a range of discharges, and (4) examine the types and responses of hydraulic microhabitats to a range of flow magnitudes. Four landform groups were identified and named in order of increasing elevation: low flood plains, intermediate flood plains, low terraces, and high terraces. The terraces were poorly characterized because the surveys did not extend across the full width of the alluvial valley bottom. The two lowest fluvial landforms are likely active in the modern hydroclimatic regime. Sediment samples obtained in the study reaches indicate that the primary bed material in the active channel ranged in size from coarse silt to coarse sand. Grain-size distributions from samples also indicate that the bed of the Niobrara River among the study reaches coarsens and has increasing grainsize variability in the downstream direction. Values of at-a-station hydraulic geometry exponents indicate that the Niobrara River in the study reaches adjusts its geometry to changing discharges primarily through increases in flow depth and velocity. Relations at one cross section indicated that, at least locally, changes in width were also an important channel adjustment mechanism. Hydraulic behavior over the range of flows measured was not consistent among all study reaches, but two general modes of hydraulic behavior were observed in the reaches with substantial coverage of the bed by fine sediment. At the Sunny Brook and Muleshoe study reaches, average boundary-shear stress remained approximately constant, and hydraulic resistance decreased, for discharges below 900 cubic feet per second (ft 3 /s). Above 900 ft 3 /s, average boundary shear stress and hydraulic resistance both increased. The Rock Barn study reach did not exhibit the same two-mode hydraulic behavior observed at the Sunny Brook and Muleshoe reaches. The coincident increase in boundary shear stress above 900 ft 3 /s observed at the Sunny Brook and Muleshoe study reaches represents a potential hydraulic threshold above which bedload transport rates were likely to increase markedly. No consistent bed-adjustment pattern (scour or fill) was identified in the study reaches over the range of flows or over the measurement season. Analysis of hydraulic microhabitats over the range of discharges measured at the study reaches indicates that some percentage of most habitat niche categories was available for at least one discharge condition, but the majority of hydraulic habitat available was within the intermediate-swift and deepswift habitat niche categories. Deep-swift conditions dominated nearly all study reaches under all measured discharge conditions. Slight differences in habitat distributions were observed between the study reaches with substantial coverage of the bed by fine sediment—Sunny Brook, Muleshoe, and Rock Barn—and the bedrock-dominated reach, Crooked Creek. Although the four study reaches occupy three different hydrogeomorphic segments, the types, relative abundance, and response of hydraulic microhabitat niche distributions to changing discharge conditions generally were similar among all reaches.

Nebraska↗

Sediment distribution and hydrologic conditions of the Potomac aquifer in Virginia and parts of Maryland and North Carolina

Sediments of the heavily used Potomac aquifer broadly contrast across major structural features of the Atlantic Coastal Plain Physiographic Province in eastern Virginia and adjacent parts of Maryland and North Carolina. Thicknesses and relative dominance of the highly interbedded fluvial sediments vary regionally. Vertical intervals in boreholes of coarse-grained sediment commonly targeted for completion of water-supply wells are thickest and most widespread across the central and southern parts of the Virginia Coastal Plain. Designated as the Norfolk arch depositional subarea, the entire sediment thickness here functions hydraulically as a single interconnected aquifer. By contrast, coarse-grained sediment intervals are thinner and less widespread across the northern part of the Virginia Coastal Plain and into southern Maryland, designated as the Salisbury embayment depositional subarea. Fine-grained intervals that are generally avoided for completion of water-supply wells are increasingly thick and widespread northward. Fine-grained intervals collectively as thick as several hundred feet comprise two continuous confining units that hydraulically separate three vertically spaced subaquifers. The subaquifers are continuous northward but merge southward into the single undivided Potomac aquifer. Lastly, far southeastern Virginia and northeastern North Carolina are designated as the Albemarle embayment depositional subarea, where both coarse- and fine-grained intervals are of only moderate thickness. The entire sediment thickness functions hydraulically as a single interconnected aquifer. A substantial hydrologic separation from overlying aquifers is imposed by the upper Cenomanian confining unit. Potomac aquifer sediments were deposited by a fluvial depositional complex spanning the Virginia Coastal Plain approximately 100 to 145 million years ago. Westward, persistently uplifted granite and gneiss source rocks sustained a supply of coarse-grained sand and gravel. Immature, high-gradient braided streams deposited longitudinal bars and channel fills across the Norfolk arch subarea. By contrast, across the Salisbury and Albemarle embayment subareas, mature, medium- to low-gradient meandering streams deposited medium- to coarse-grained channel fills and point bars segregated from fine-grained overbank deposits. The Virginia depositional complex merged northward across the Salisbury embayment subarea with another complex in Maryland. Here, additional sediments were received from schist source rocks that underwent three cycles of initial uplift and rapid erosion followed by crustal stability and erosional leveling. Because of the predominance of coarse-grained sediments, transmissivity, hydraulic conductivity, and regional velocities of lateral flow through the Potomac aquifer are greatest across the Norfolk arch depositional subarea, but decrease progressively northward with increasingly fine-grained sediments. Confining units hydraulically separate the Potomac aquifer from overlying aquifers, as indicated by large vertical hydraulic gradients. By contrast, most of the Potomac aquifer internally functions hydraulically as a single interconnected aquifer, as indicated by uniformly small vertical gradients. Most fine-grained sediments within the aquifer do not hydraulically separate overlying and underlying coarse-grained sediments. Across the Salisbury embayment depositional subarea, however, hydraulic separation among the vertically spaced subaquifers is imposed by the intervening confining units. The Potomac aquifer is the largest and most heavily used source of groundwater in the Virginia Coastal Plain. Water-level declines as great as 200 feet create the potential for saltwater intrusion. Conventional stratigraphic correlation has been generally ineffective at accurately characterizing complexly distributed fluvial sediments that compose the Potomac aquifer. Consequently, the aquifer’s internal hydraulic connectivity and overall hydrologic function have not been well understood. Water-supply planning and development efforts have been hampered, and interpretations of regulatory criteria for allowable water-level declines have been ambiguous. An investigation undertaken during 2010–11 by the U.S. Geological Survey, in cooperation with the Virginia Department of Environmental Quality, provides a comprehensive regional description of the spatial distribution of Potomac aquifer sediments and their relation to hydrologic conditions. Altitudes and thicknesses of 2,725 vertical sediment intervals represent the spatial distribution of Potomac aquifer sediments in the Virginia Coastal Plain and adjacent parts of Maryland and North Carolina. Sediment intervals are designated as either dominantly coarse or fine grained and were determined by interpretation of geophysical logs and ancillary information from 456 boreholes. Sediment-interval and borehole summary statistical data indicate regional trends in sediment lithology and stratigraphic continuity, upon which three structurally based and hydrologically distinct sediment depositional subareas are designated. Broad patterns of sediment deposition over time are inferred from published sediment pollen-age data. Discrepancies in previously drawn hydrostratigraphic relations between southeastern Virginia and northeastern North Carolina are partly resolved based on borehole geophysical logs and a recently documented geologic map and corehole. A conceptual model theorizes the depositional history of the sediments and geologically accounts for their distribution. Documented pumping tests of the Potomac aquifer at 197 locations produced 336 values of transmissivity and 127 values of storativity. Based on effective aquifer thicknesses, 296 values of sediment hydraulic conductivity and 113 values of sediment specific storage are calculated. Vertical hydraulic gradients are calculated from 9,479 pairs of water levels measured between November 17, 1953, and October 4, 2011, in 129 closely spaced pairs of wells. Borehole sediment-interval and related data provide a means to achieve high yielding production wells in the Potomac aquifer by site-specific targeting of drilling operations toward water-bearing coarse-grained sand and gravel. Advance knowledge of the potential of different parts of the aquifer also aids in planning optimal groundwater-development areas. Depositional subareas further provide a possible context for resource management. Current (2013) regulatory limits on water-level declines are relative to top surfaces of subdivided upper, middle, and lower Potomac aquifers across the entire Virginia Coastal Plain, but have the potential to exceed the same limit relative to a single undivided Potomac aquifer. By contrast, designation of the sediments as a single aquifer in the Norfolk arch and Albemarle embayment subareas—and as a series of vertically spaced subaquifers and intervening confining units in the Salisbury embayment subarea—best reflects understanding of the Potomac aquifer and can avoid the potential for excessive water-level declines. Simulation modeling to evaluate effects of groundwater withdrawals could be designed similarly, including vertical discretization and (or) zonation of the Potomac aquifer based on depositional subareas and a geostatistical distribution of aquifer properties derived from borehole sediment-interval data. Further resource-management information needs extend beyond the developed part of the Potomac aquifer, particularly across the Northern Neck and Middle Peninsula where only the shallowest part of the aquifer is known, and include structural aspects such as faults, basement bedrock, and the Chesapeake Bay impact crater.

Maryland, North Carolina, Virginia↗

Improving predictive power of physically based rainfall-induced shallow landslide models: a probablistic approach

Distributed models to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides are deterministic. These models extend spatially the static stability models adopted in geotechnical engineering and adopt an infinite-slope geometry to balance the resisting and the driving forces acting on the sliding mass. An infiltration model is used to determine how rainfall changes pore-water conditions, modulating the local stability/instability conditions. A problem with the existing models is the difficulty in obtaining accurate values for the several variables that describe the material properties of the slopes. The problem is particularly severe when the models are applied over large areas, for which sufficient information on the geotechnical and hydrological conditions of the slopes is not generally available. To help solve the problem, we propose a probabilistic Monte Carlo approach to the distributed modeling of shallow rainfall-induced landslides. For the purpose, we have modified the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) code. The new code (TRIGRS-P) adopts a stochastic approach to compute, on a cell-by-cell basis, transient pore-pressure changes and related changes in the factor of safety due to rainfall infiltration. Infiltration is modeled using analytical solutions of partial differential equations describing one-dimensional vertical flow in isotropic, homogeneous materials. Both saturated and unsaturated soil conditions can be considered. TRIGRS-P copes with the natural variability inherent to the mechanical and hydrological properties of the slope materials by allowing values of the TRIGRS model input parameters to be sampled randomly from a given probability distribution. The range of variation and the mean value of the parameters can be determined by the usual methods used for preparing the TRIGRS input parameters. The outputs of several model runs obtained varying the input parameters are analyzed statistically, and compared to the original (deterministic) model output. The comparison suggests an improvement of the predictive power of the model of about 10% and 16% in two small test areas, i.e. the Frontignano (Italy) and the Mukilteo (USA) areas, respectively. We discuss the computational requirements of TRIGRS-P to determine the potential use of the numerical model to forecast the spatial and temporal occurrence of rainfall-induced shallow landslides in very large areas, extending for several hundreds or thousands of square kilometers. Parallel execution of the code using a simple process distribution and the Message Passing Interface (MPI) on multi-processor machines was successful, opening the possibly of testing the use of TRIGRS-P for the operational forecasting of rainfall-induced shallow landslides over large regions.

Geoscientific Model Development and Discussions↗

Evaluation of a regional monitoring program's statistical power to detect temporal trends in forest health indicators

Forests are socioeconomically and ecologically important ecosystems that are exposed to a variety of natural and anthropogenic stressors. As such, monitoring forest condition and detecting temporal changes therein remain critical to sound public and private forestland management. The National Parks Service’s Vital Signs monitoring program collects information on many forest health indicators, including species richness, cover by exotics, browse pressure, and forest regeneration. We applied a mixed-model approach to partition variability in data for 30 forest health indicators collected from several national parks in the eastern United States. We then used the estimated variance components in a simulation model to evaluate trend detection capabilities for each indicator. We investigated the extent to which the following factors affected ability to detect trends: (a) sample design: using simple panel versus connected panel design, (b) effect size: increasing trend magnitude, (c) sample size: varying the number of plots sampled each year, and (d) stratified sampling: post-stratifying plots into vegetation domains. Statistical power varied among indicators; however, indicators that measured the proportion of a total yielded higher power when compared to indicators that measured absolute or average values. In addition, the total variability for an indicator appeared to influence power to detect temporal trends more than how total variance was partitioned among spatial and temporal sources. Based on these analyses and the monitoring objectives of the Vital Signs program, the current sampling design is likely overly intensive for detecting a 5 % trend·year −1 for all indicators and is appropriate for detecting a 1 % trend·year −1 in most indicators.

New Jersey, Pennsylvania, Virginia, West Virginia↗