Search USGS⌕ Search

SEARCH · Search USGS

Results for “Spatial Statistics”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7Linked to original sources
USGS2009

Monitoring survival rates of Swainson's Thrush Catharus ustulatus at multiple spatial scales

We estimated survival rates of Swainson's Thrush, a common, neotropical, migratory landbird, at multiple spatial scales, using data collected in the western USA from the Monitoring Avian Productivity and Survivorship Programme. We evaluated statistical power to detect spatially heterogeneous survival rates and exponentially declining survival rates among spatial scales with simulated populations parameterized from results of the Swainson's Thrush analyses. Models describing survival rates as constant across large spatial scales did not fit the data. The model we chose as most appropriate to describe survival rates of Swainson's Thrush allowed survival rates to vary among Physiographic Provinces, included a separate parameter for the probability that a newly captured bird is a resident individual in the study population, and constrained capture probability to be constant across all stations. Estimated annual survival rates under this model varied from 0.42 to 0.75 among Provinces. The coefficient of variation of survival estimates ranged from 5.8 to 20% among Physiographic Provinces. Statistical power to detect exponentially declining trends was fairly low for small spatial scales, although large annual declines (3% of previous year's rate) were likely to be detected when monitoring was conducted for long periods of time (e.g. 20 years). Although our simulations and field results are based on only four years of data from a limited number and distribution of stations, it is likely that they illustrate genuine difficulties inherent to broadscale efforts to monitor survival rates of territorial landbirds. In particular, our results suggest that more attention needs to be paid to sampling schemes of monitoring programmes, particularly regarding the trade-off between precision and potential bias of parameter estimates at varying spatial scales.

Bird Study↗
USGS2026

Assessment of long-term trends in streamflow statistics within and near the Mobile Bay and Perdido Bay watersheds, United States, 1950–2022

The U.S. Geological Survey, in cooperation with the Gulf Coast Ecosystem Restoration Council, assessed monotonic trends for a variety of streamflow statistics for 69 long-term U.S. Geological Survey streamgages within either the Mobile Bay or Perdido Bay watersheds that were active through at least at the end of calendar year 2019. Long-term data were defined for this investigation as having at least 50 years of cumulative record within the period since January 1, 1950, with a requirement for a complete record of streamflow during the 2010s (2010–19). The 69 streamgages have at least 54 years and as many as 73 years of daily mean streamflow data; the median period of record is 72 years; and 15 of the streamgages are identified as “major nodes” on the basis of the criteria described. The occurrence of statistically monotonic significant trends for the 69 streamgages at the 0.05 significance level is spatially shown for six statistics. For the major node streamgages, the study depicts (1) time-series graphics of annual mean, annual harmonic mean, decadal 10th, 50th, and 90th-percentile streamflows, and (2) a variation on Quantile-Kendall plots of Kendall’s tau and streamflow nonexceedance probabilities for each of the 365 days of a year. Trend assessment synthesis shows that, except for a few streamgages with relatively greater counts of statistically significant trends than others, the majority (about 93 percent) of individual trend tests indicate no trend in the streamflow and ecological metrics considered.

Alabama, Florida, Georgia, Louisiana, Mississippi,↗
USGS2006

Mining claim activity on federal land in the contiguous United States, 1976 through 2004

Statistical compilations of mining claim activity on Federal Land derived from the Bureau of Land Management's LR2000 database have been published by the U.S Geological Survey. This report updates Causey (2005) by adding statistics for an additional year of mining claim records, incorporating any corrections in older data done by BLM, adding a Public Land Survey spatial database for South Dakota, and improving correlation of the statistics to spatial databases in Washington and Nevada. The statistics compiled from the LR2000 database are counts of number of active mining claims in a section each year from 1976 to 2004 for all states within the contiguous United States. Claims are broken down by lode and placer types and a dataset is provided summarizing all claims including millsite and tunnel-site claims. One table presents data by case type, case status, and number of claims in a section. This report includes a spatial database for each state in which mining claims were recorded. A field is present in both datasets that allows the statistical data to be joined to the spatial databases so that spatial displays and analysis can be done using appropriate software. The data show how mining claim activity has changed in intensity, space, and time. Variations can be examined on a state, as well as a national level. The data are tied to a section of land, approximately 640 acres, which allows it to be used at regional, as well as local scale. It is restricted in that it only encompasses Federal land.

Arizona, Arkansas, California, Colorado, Florida, ↗
USGS2017

The Bayesian group lasso for confounded spatial data

Generalized linear mixed models for spatial processes are widely used in applied statistics. In many applications of the spatial generalized linear mixed model (SGLMM), the goal is to obtain inference about regression coefficients while achieving optimal predictive ability. When implementing the SGLMM, multicollinearity among covariates and the spatial random effects can make computation challenging and influence inference. We present a Bayesian group lasso prior with a single tuning parameter that can be chosen to optimize predictive ability of the SGLMM and jointly regularize the regression coefficients and spatial random effect. We implement the group lasso SGLMM using efficient Markov chain Monte Carlo (MCMC) algorithms and demonstrate how multicollinearity among covariates and the spatial random effect can be monitored as a derived quantity. To test our method, we compared several parameterizations of the SGLMM using simulated data and two examples from plant ecology and disease ecology. In all examples, problematic levels multicollinearity occurred and influenced sampling efficiency and inference. We found that the group lasso prior resulted in roughly twice the effective sample size for MCMC samples of regression coefficients and can have higher and less variable predictive accuracy based on out-of-sample data when compared to the standard SGLMM.

Journal of Agricultural, Biological, and Environme↗
USGS2011

Spatial interpolation schemes of daily precipitation for hydrologic modeling

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs.

Colorado, Georgia↗
USGS2020

Bayesian modeling of non-stationary, univariate, spatial data for the Earth sciences

Some Earth science data, such as geochemical measurements of element concentrations, are non-stationary—the mean and the standard deviation vary spatially. It is important to estimate the spatial variations in both statistics because such information is indicative of geological and other Earth processes. To this end, an estimation method is formulated as a Bayesian hierarchical model. The method represents the spatially varying mean and the spatially varying standard deviation with basis functions; this formulation implicitly accounts for a spatially varying covariance function. A unique advantage of this method is that it can map the mean, the standard deviation, quantiles, and exceedance probabilities. The method is demonstrated by mapping titanium concentrations, which are measured in the coastal plain of the southeastern United States. Various checks demonstrate that the model fits the data and that the estimated statistics are geologically plausible.

Techniques and Methods↗
USGS2015

Spatially explicit spectral analysis of point clouds and geospatial data

The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software package PySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python , it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.

Computers & Geosciences↗
USGS2012

Spatial patterns of aftershocks of shallow focus earthquakes in California and implications for deep focus earthquakes

Previous workers have pioneered statistical techniques to study the spatial distribution of aftershocks with respect to the focal mechanism of the main shock. Application of these techniques to deep focus earthquakes failed to show clustering of aftershocks near the nodal planes of the main shocks. To better understand the behavior of these statistics, this study applies them to the aftershocks of six large shallow focus earthquakes in California (August 6, 1979, Coyote Lake; May 2, 1983, Coalinga; April 24, 1984, Morgan Hill; August 4, 1985, Kettleman Hills; July 8, 1986, North Palm Springs; and October 1, 1987, Whittier Narrows). The large number of aftershocks accurately located by dense local networks allows us to treat these aftershock sequences individually instead of combining them, as was done for the deep earthquakes. The results for individual sequences show significant clustering about the closest nodal plane and the strike direction for five of the sequences and about the presumed fault plane for all six sequences. This implies that the previously developed method does work properly. Nonrandom behavior was also found about the slip directions, the P axis, the T axis, and the B axis, but this is probably caused by the lack of independence between these axes and the previously mentioned features of the focal mechanisms. Given that the method does work and that deep aftershocks were not shown to cluster about the main shock nodal planes, the shallow focus data were used to simulate the deep focus study. The goal is to determine if there are artificial factors that make clustering in the deep focus data unobservable. To more closely mimic the work on deep earthquakes, the largest aftershocks from each of the six sequences were combined and studied with respect to their respective main shock focal mechanisms. This reduced the significance of the clustering about the focal mechanism parameters, but not below 95% confidence. Gaussian noise was then added to the aftershock hypocenters in order to determine if the larger hypocentral and focal mechanism errors in the deep focus data could account for the previous negative result. The conclusion is that the following reasons are sufficient to explain the lack of clustering about the main shock nodal planes for the deep focus aftershocks: the need to combine aftershocks from several sequences, the size of the hypocentral location and focal mechanism errors, and the alignment of distant aftershocks with the Wadati-Benioff zone.

Journal of Geophysical Research Solid Earth↗
USGS2019

Phosphorus and nitrogen transport in the binational Great Lakes Basin estimated using SPARROW watershed models

Eutrophication problems in the Great Lakes are caused by excessive nutrient inputs (primarily phosphorus, P, and nitrogen, N) from various sources throughout its basin. In developing protection and restoration plans, it is important to know where and from what sources the nutrients originate. As part of a binational effort, Midcontinent SPARROW (SPAtially Referenced Regression On Watershed attributes) models were developed and used to estimate P and N loading from throughout the entire basin based on nutrient inputs similar to 2002; previous SPARROW models only estimated U.S. contributions. The new models have a higher resolution (~2‐km 2 catchments) enabling improved descriptions of where nutrients originate and the sources at various spatial scales. The models were developed using harmonized geospatial datasets describing the stream network, nutrient sources, and environmental characteristics affecting P and N delivery. The models were calibrated using loads from sites estimated with ratio estimator and regression techniques and additional statistical approaches to reduce spatial correlation in the residuals and have all monitoring sites equally influence model development. SPARROW results, along with interlake transfers and direct atmospheric inputs, were used to quantify the entire P and N input to each lake and describe the importance of each nutrient source. Model results can be used to compare loading and yields from various tributaries and jurisdictions.

Great Lakes↗
USGS2014

Dissolved-solids sources, loads, yields, and concentrations in streams of the conterminous United States

Recent studies have shown that excessive dissolved-solids concentrations in water can have adverse effects on the environment and on agricultural, domestic, municipal, and industrial water users. Such effects motivated the U.S. Geological Survey’s National Water Quality Assessment Program to develop a SPAtially-Referenced Regression on Watershed Attributes (SPARROW) model that has improved the understanding of sources, loads, yields, and concentrations of dissolved solids in streams of the conterminous United States. Using the SPARROW model, long-term mean annual dissolved-solids loads from 2,560 water-quality monitoring stations were statistically related to several spatial datasets that are surrogates for dissolved-solids sources and land-to-water delivery processes. Specifically, sources in the model included variables representing geologic materials, road deicers, urban lands, cultivated lands, and pasture lands. Transport of dissolved solids from these sources was modulated by land-to-water delivery variables that represent precipitation, streamflow, soil, vegetation, terrain, population, irrigation, and artificial drainage characteristics. Where appropriate, the load estimates, source variables, and transport variables were statistically adjusted to represent conditions for the base year 2000. The nonlinear least-squares estimated SPARROW model was used to predict long-term mean annual conditions for dissolved-solids sources, loads, yields, and concentrations in a digital hydrologic network representing nearly 66,000 stream reaches and their corresponding incremental catchments that drain the Nation. Nationwide, the predominant source of dissolved solids yielded from incremental catchments and delivered to local streams is geologic materials in 89 percent of the catchments, road deicers in 5 percent of the catchments, pasture lands in 3 percent of the catchments, urban lands in 2 percent of the catchments, and cultivated lands in 1 percent of the catchments. Whereas incremental catchments with dissolved solids that originated predominantly from geologic sources or from urban lands are found across much of the Nation, incremental catchments with dissolved solids yields that originated predominantly from road deicers are largely found in the Northeast, and incremental catchments with dissolved solids that originated predominantly from cultivated or pasture lands are largely found in the West. The total amount of dissolved solids delivered to the Nation’s streams is 271.9 million metric tons (Mt) annually, of which 194.2 million Mt (71.4%) come from geologic sources, 37.7 million Mt (13.9%) come from road deicers, 18.2 million Mt (6.7%) come from pasture lands, 13.9 million Mt (5.1%) come from urban lands, and 7.9 million Mt (2.9%) come from cultivated lands. Nationwide, the median incremental-catchment yield delivered to local streams is 26 metric tons per year per square kilometer [(Mt/yr)/km 2 ]. Ten percent of the incremental catchments yield less than 4 (Mt/yr)/km 2 , and 10 percent yield more than 90 (Mt/yr)/km 2 . Incremental-catchment yields greater than 50 (Mt/yr)/km 2 mostly occur along the northern part of the West Coast and in a crescent shaped band south of the Great Lakes. For example, the median incremental-catchment yield is 81 (Mt/yr)/km 2 for the Great Lakes, 78 (Mt/yr)/km 2 for the Ohio, and 74 (Mt/yr)/km 2 for the Upper Mississippi water-resources regions. Incremental-catchment yields less than 10 (Mt/yr)/km 2 mostly occur in a wide band across the arid lowland of the interior West that excludes areas along the coast and the extensive, higher mountain ranges. For example, the median incremental-catchment yield is 3 (Mt/yr)/km 2 for the Lower Colorado, 5 (Mt/yr)/km 2 for the Rio Grande, and 8 (Mt/yr)/km 2 for the Great Basin water-resources regions. Predicted incremental loads were cascaded down through the reach network, with loads accumulating from reach to reach. For most stream reaches, the entire incremental load of dissolved solids delivered to the reach was transported to either the ocean or to one of the large streams flowing along the U.S. international boundary without losses occurring along the way. The exceptions to this include streams in the southwestern part of the country, such as the Colorado River, Rio Grande, and streams of internally drained drainages in the Great Basin, where dissolved-solids loads decreased through streamflow diversion for off-stream use, or by infiltration through the streambed. Long-term mean annual flow-weighted concentrations were derived from the predicted accumulated-load and stream-discharge data. Widespread low concentrations, generally less than 100 milligrams per liter (mg/L), occur in many reaches of the New England, South Atlantic-Gulf, and Pacific Northwest water-resources regions as a result of moderate dissolved-solids yields and high runoff rates. Widespread moderate concentrations, generally between 100 and 500 mg/L, occur in many reaches of the Great Lakes, Ohio, and Upper Mississippi River water-resources regions. Whereas dissolved-solids yields are generally high in these regions, runoff rates are also high, which helps moderate concentrations in these regions. Widespread higher concentrations, generally greater than 500 mg/L, occur across a belt of reaches that extends almost continuously from Canada to Mexico in the Midwest, cutting through the Souris-Red-Rainy, Missouri, Arkansas-White-Red, Texas-Gulf, and Rio Grande water-resources regions. Although dissolved-solids yields are moderate to low in these areas, low runoff rates result in the high concentrations for these areas. In 12.6 percent of the Nation’s stream reaches, predicted concentrations of dissolved solids exceed 500 mg/L, the U.S. Environmental Protection Agency’s secondary, nonenforceable drinking water standard. While this standard provides a metric for evaluating predicted concentrations in the context of drinking-water supplies, it should be noted that it only applies to drinking water actually served to customers by water utilities, and it does not apply to all stream reaches in the Nation nor does it apply during times when water is not being withdrawn for use. Exceedance of 500 mg/L is more pronounced in certain water-resources regions than others. For example, about half of the reaches in the Souris-Red-Rainy region have concentrations predicted to exceed 500 mg/L, and between 25 and 37 percent of the reaches in the Missouri, Arkansas-White-Red, Texas-Gulf, Rio Grande, and Lower Colorado regions are predicted to exceed 500 mg/L. Development of stream-load data for use in the SPARROW model also provided long-term temporal trend information in dissolved-solids concentrations at the monitoring stations for their period of record, which was constrained between 1980 and 2009. For the 2,560 monitoring stations used in this study, long-term trends in flow-adjusted dissolved-solids concentrations increased over time at 23 percent of the stations, decreased at 18 percent of the stations, and did not change over time at 59 percent of the stations. Long-term trends show a strong regional spatial pattern where from the western parts of the Great Plains to the West Coast, concentrations mostly either did not change or decreased over time, and from the eastern parts of the Great Plains to the East Coast, concentrations mostly either did not change or increased over time. Results from the trend analysis and from the SPARROW model indicate that, compared to monitoring stations with no trends or decreasing trends, stations with increasing trends are associated with a smaller percentage of the predicted dissolved-solids load originating from geologic sources, and a larger percentage originating from urban lands and road deicers. Conversely, compared to stations with increasing trends or no trends, stations with decreasing trends have a larger percentage of the predicted dissolved-solids load originating from geologic sources and a smaller percentage originating from urban lands and road deicers. Stations with decreasing trends also have larger percentages of predicted dissolved-solids load originating from cultivated lands and pasture lands, compared to stations with increasing trends or no trends.

Scientific Investigations Report↗
USGS2025

Groundwater hydrology, groundwater and surface-water interactions, water quality, and groundwater-flow simulations for the Wet Mountain Valley alluvial aquifer, Custer and Fremont Counties, Colorado, 2017–19

In 2017, the U.S. Geological Survey, in cooperation with the Upper Arkansas Water Conservancy District, began a study to provide a comprehensive analysis of the Wet Mountain Valley alluvial aquifer, Custer and Fremont Counties, Colorado. The study included collection of data pertaining to groundwater hydrology, groundwater and surface-water interactions, and water quality in the alluvial aquifer. In addition to providing foundational information on the hydrology of the alluvial aquifer, a numerical groundwater-flow model was developed to estimate the potential effects of additional storage of groundwater in the alluvial aquifer. Groundwater-level elevation data from 30 wells were used to estimate groundwater-flow directions in the alluvial aquifer, which were generally from the southwest to northeast, away from the Sangre de Cristo Mountains and towards perennial streams in the center of the valley. Although some seasonal variation was apparent in groundwater-level elevation records, no statistically significant seasonal trends were indicated. Statistically significant long-term trends were indicated in groundwater-level elevation records for 8 of the 30 wells, and of these wells with statistically significant trends, all but 1 indicated a negative trend of groundwater-level elevations. Spatial evaluation of wells with statistically significant negative groundwater-level elevation trends showed many are in areas of denser well drilling for domestic or other uses, indicating increasing groundwater use could potentially be causing groundwater-level elevation declines. There were instances of wells with no statistically significant groundwater-level elevation trends also located in areas of greater density of well completions. Additional investigations may be necessary to more fully characterize the processes responsible for negative groundwater-level elevation trends. Streamflow gain or loss calculations were completed for low flow in 2017–19 and for high flow in 2018 in nine reaches of streams within the study area. Stream reaches of the upper Texas Creek, upper Grape Creek, upper-middle Grape Creek, and Taylor Creek displayed consistent streamflow loss in each period from 2017 to 2019. These stream reaches represent long-term sources of recharge to the alluvial aquifer. Streamflow gain or loss varies through time in other stream reaches (lower Texas Creek, lower-middle Grape Creek, lower Grape Creek below Westcliffe, and lower Grape Creek above DeWeese Reservoir). The temporally variable behavior indicates these stream reaches may be sources of groundwater recharge or areas of groundwater discharge, likely depending on temporal dynamics between the elevation of the water table and the stream. Water-quality samples were collected from 10 groundwater wells and 10 stream sites during September through November 2019. All groundwater and stream samples were analyzed for major and trace elements and stable isotopes of water. A subset of groundwater samples was also analyzed for the environmental tracers sulfur hexafluoride, tritium, and noble gases. Comparison of water-quality results to U.S. Environmental Protection Agency drinking water-quality standards indicated no constituents exceeded primary standards for human health. Spatial evaluation of water quality indicated the concentrations of various constituents are likely controlled by groundwater and surface-water interactions and by spatial variability in bedrock geology underlying the alluvial aquifer. Specifically, streams shown to gain from groundwater had water chemistry constituent compositions similar to groundwater, whereas streams exiting the Sangre de Cristo Mountains tended to have compositions consistent with snowmelt. Groundwater geochemistry appeared to be partially controlled by oxidation-reduction processes and by proximity to igneous rocks in the Wet Mountains. Environmental tracers used to estimate groundwater age indicated all sampled groundwater contained tracers representing modern recharge (approximately less than 65 years old) but mixing of premodern recharge (approximately more than 65 years old) also occurs. Spatial evaluation of environmental tracers indicated large faults may be conduits for upwelling of older groundwater. No trends were observed in groundwater age with well depth, indicating all sampled wells are located within the zone of active groundwater flow. The presence of modern groundwater in wells with statistically significant negative groundwater-level elevation trends indicates groundwater storage depletions may be partially offset by capture of modern recharge. Repeated sampling of groundwater age would be necessary, however, to determine if any trends in groundwater age exist, which may indicate changing groundwater recharge, storage, or discharge. Additional investigations could also consider quantifying groundwater age in deeper wells to more fully define the depth of active groundwater flow. A numerical groundwater-flow model was developed to estimate components of the water budget, simulate groundwater and surface-water interactions, and evaluate the potential effects of aquifer storage and recovery. Simulated groundwater-level elevations from the calibrated groundwater-flow model are similar to the observed pattern of groundwater-level elevations with higher elevations in the western part of the study area along the Sangre de Cristo Mountains. Simulated water-budget components indicate most of the recharge to the alluvial aquifer is derived from streamflow losses, which is consistent with observations of losing streams along the mountain front. The largest groundwater discharge component of the alluvial aquifer was to streams in the center of the valley, where observations of stream gain or loss indicated the predominance of gaining conditions. Comparison of groundwater and surface-water interactions between the calibrated groundwater-flow model for 2000-19 (the base-case model) and a simulation including additional recharge, representing potential aquifer storage and recovery operations, indicated the additional recharge distributed throughout the area had minimal effects on streamflow in the nearby Grape Creek. An analysis of subregional groundwater budgets showed approximately 54 percent of the additional recharge flowed back to nearby Grape Creek, and the other 46 percent was distributed laterally into adjacent cells in the alluvial aquifer. The comparison of simulations and subregional water budget show the additional recharge did not substantially alter groundwater-level elevations or basin wide groundwater storage. Although the analysis of additional recharge provided in the numerical groundwater-flow model considers only one of many possible recharge scenarios, the model provides a useful tool that could be modified for various scenarios to understand potential effects of managed aquifer recharge.

Colorado↗
USGS1980

Determining the availability of sediment-bound trace metals to aquatic deposit-feeding animals

Physicochemical form affects, by as much as 1000 fold, the uptake rate by deposit-feeding clams of metals bound to sediments. The strength of metal binding to the different sedimentary binding substrates controls this effect. Statistical studies that were spatially intensive (comparing 35 stations in 17 estuaries) and temporally intensive (2 stations through 2 years time) indicate that sediments control the availability of Ag, Cd, Co, Pb, Zn, Fe, and Mn, and possibly Cu to clams and polychaete worms in nature. Metal concentrations removed from sediments by chemical extractants generally follow availability better than do total metal concentrations, but the specific extractant differs among different metals. Concentrations of binding substrates (Fe, Mn, organic carbon, humic substances) also statistically explain a proportion of the variance of metal concentrations in the animals, suggesting that metal partitioning among substrates in sediments is an important control on metal availability. The specific substrates which contribute to availability also differ among metals. Statistical assessment of metal form in sediments suggested that different substrates compete for the partitioning of metals, that each metal is partitioned among a variety of forms in an oxidized sediment, and that partitioning will vary with the physicochemical characteristics of the sediments. (USGS)

Open-File Report↗
USGS2024

Spatial variability of water temperature within the White River basin, Mount Rainier National Park Washington

Water temperature is a primary control on the occurrence and distribution of cold-water species. Rivers draining Mount Rainier in western Washington, including the White River along its northern flank, support several cold-water fish populations, but the spatial distribution of water temperatures, particularly during late-summer base flow between August and September, and the climatic, hydrologic, and physical processes regulating this temperature distribution are not well understood. Spatial stream network (SSN) models, which are generalized linear models that incorporate streamwise spatial autocovariance structures, were fit to mean and seven-day average daily maximum water temperature for August and September for the White River basin located with Mount Rainier National Park. The SSN models were calibrated using water temperature measurements collected between 2010 and 2020. Significant covariates within the best-fit models included the proportion of ice cover and forest cover within the basin, mean August air temperature, the proportion of consolidated geologic units, and snow water equivalent. Statistical models that included spatial autocovariance structures had better predictive performance than those that did not. In addition, models of mean August and September water temperature had better predictive performance than those of seven-day average daily maximum temperature in August and September. Predictions of the spatial distribution of water temperature were similar between August and September with a general warming in the downstream part of main-stem White River compared to cooler water temperatures in the high-elevation headwater streams. Estimated water temperatures for the upper White River model are three to four degrees Celsius warmer for tributaries but one to two degrees cooler for the main stem compared to the regional-scale model. Differences between the upper White River SSN model and the regional-scale SSN model are attributed the upper White River SSN including water temperature observations specific to the upper White River, whereas water temperature observations from lower elevation streams and downstream of the Mount Rainer National Park boundary were used in the regional-scale model.

EarthArXiv↗
USGS1997

Stream habitat characteristics of fixed sites in the western Lake Michigan drainages, Wisconsin and Michigan, 1993-95

Habitat characteristics of 11 fixed sites in the Western Lake Michigan Drainages were examined by the U.S. Geological Survey from 1993 through 1995 as part of the ecological assessment of the National Water-Quality Assessment Program. Evaluation of habitat consisted of more than 75 measurements at three spatial levels: drainage basin, stream segment between major tributaries (length from 1 to 14 kilometers), and stream reach (approximately 150 meters). The 11 fixed sites consisted of 8 "indicator" sites with drainage basins that differ in bedrock type, surficial deposits, and land use; and 3 "integrator" sites with drainage basins that contain a mixture of bedrock type, surficial deposits, and land use. Spatial and temporal variations in habitat characteristics are described and compared. Comparisons are limited to indicator sites except for comparisons amongbasin characteristics, which include all fixed sites. Two habitat classification schemes used in Wisconsin and Michigan were used to rank the quality of habitat in indicator streams. Reach-level data were collected at two additional reaches at three of the indicator sites to assess the representativeness of the reach for overall stream conditions. Although the number of sites is small, statistical analyses indicate that spatial distribution of several characteristics can be related to land use, geology, topography, and width of the riparian zone. Land use and geology, in combination, appeared to be important factors in controlling flood magnitudes. Annual mean flow was correlated with basin shape and drainage density and low flow was correlated with permeability of soils in the basin. At the reach level, a wide variety of characteristics were observed at the eight indicator sites, with many of the characteristics significantly different between sites. Spatial differences in some reach characteristics can be attributed to the percentage of agriculture in the drainage basin, type of surficial deposits, and width of the riparian zone. Temporal variability in width, depth, and velocity can be attributed to variable flow conditions; whereas temporal variability in streambank measurements are attributed to problematic identification of the boundary between the flood plain and streambanks. Data from multiple-reach sites indicate that the primary reach adequately represented the variability found within the stream segment for depth, streambank stability index, and canopy angle. However, velocity, dominant substrate type, embeddedness, streambank height, streambank angle, and streambank vegetative stability differed among the multiple reaches at one or more of the three sites. Correlation analyses of habitat characteristics with median concentrations of four nutrients, pH, and specific conductance indicates that dissolved nitrate plus nitrite concentrations are related to percentage of agriculture in the basin and fine-grained sediment deposition in the reach. Geology and land use appear to be major influences on pH, but their influence on specific conductance, although expected, was not confirmed in this study. Habitat evaluation scores at the eight indicator sites ranged from poor to good. Scores were correlated to the percentage of agricultural or urban land in the drainage basins, width of the riparian zone, and streambank stability index. Results from this study illustrate the need for collection of habitat data at multiple scales along with water-chemistry data for determining major influences on distribution of aquatic communities. These results also indicate the importance of collecting land use, geological, and geomorphic information at the drainage-basin level to adequately describe how natural and human factors influence local aquatic habitat conditions.

Michigan, Wisconsin↗
USGS2001

Critical habitat for ovigerous Dungeness crabs

The Dungeness crab, Cancer magister , supports an important fishery in the northeastern Pacific Ocean, yet there is limited knowledge of ovigerous female brooding locations and brooding behavior. Our earlier research suggests that ovigerous crabs aggregate at the same brooding locations for many years. Within these locations, ovigerous females occur in high densities, with the majority of the aggregation buried within the sediment. These locations often have similar water depths and sediment types and appear to be critical for this life history stage. Our study was designed to examine the bathymetric distribution of Dungeness crabs in bays with and without sea otters at eight locations within the Glacier Bay area by conducting transects with a video-equipped manned submersible. Two of the bays investigated contained large aggregations of ovigerous females. At both sites the substrate was composed primarily of sand. However, only a small percentage of the 33 km of transects were classified as sand. These data suggest that sand substrate may be a limiting resource. Since crab brooding aggregations represent a large portion of the crab population within a small area, and because they are a critical component of Dungeness life history, areas with these characteristics need to be investigated, mapped, and protected from development or exploitation. The areas requiring protection from the impact of anthropogenic wastes, fishing, and logging activities could be quite small, thus limiting conflict with alternative users.

Conference Paper↗
USGS2017

Landscape genetic approaches to guide native plant restoration in the Mojave Desert

Restoring dryland ecosystems is a global challenge due to synergistic drivers of disturbance coupled with unpredictable environmental conditions. Dryland plant species have evolved complex life-history strategies to cope with fluctuating resources and climatic extremes. Although rarely quantified, local adaptation is likely widespread among these species and potentially influences restoration outcomes. The common practice of reintroducing propagules to restore dryland ecosystems, often across large spatial scales, compels evaluation of adaptive divergence within these species. Such evaluations are critical to understanding the consequences of large-scale manipulation of gene flow and to predicting success of restoration efforts. However, genetic information for species of interest can be difficult and expensive to obtain through traditional common garden experiments. Recent advances in landscape genetics offer marker-based approaches for identifying environmental drivers of adaptive genetic variability in non-model species, but tools are still needed to link these approaches with practical aspects of ecological restoration. Here, we combine spatially-explicit landscape genetics models with flexible visualization tools to demonstrate how cost-effective evaluations of adaptive genetic divergence can facilitate implementation of different seed sourcing strategies in ecological restoration. We apply these methods to Amplified Fragment Length Polymorphism (AFLP) markers genotyped in two Mojave Desert shrub species of high restoration importance: the long-lived, wind-pollinated gymnosperm Ephedra nevadensis , and the short-lived, insect-pollinated angiosperm Sphaeralcea ambigua . Mean annual temperature was identified as an important driver of adaptive genetic divergence for both species. Ephedra showed stronger adaptive divergence with respect to precipitation variability, while temperature variability and precipitation averages explained a larger fraction of adaptive divergence in Sphaeralcea . We describe multivariate statistical approaches for interpolating spatial patterns of adaptive divergence while accounting for potential bias due to neutral genetic structure. Through a spatial bootstrapping procedure, we also visualize patterns in the magnitude of model uncertainty. Finally, we introduce an interactive, distance-based mapping approach that explicitly links marker-based models of adaptive divergence with local or admixture seed sourcing strategies, promoting effective native plant restoration.

Mojave Desert↗
USGS2008

Spatial dynamics of overbank sedimentation in floodplain systems

Floodplains provide valuable social and ecological functions, and understanding the rates and patterns of overbank sedimentation is critical for river basin management and rehabilitation. Channelization of alluvial systems throughout the world has altered hydrological and sedimentation processes within floodplain ecosystems. In the loess belt region of the Lower Mississippi Alluvial Valley of the United States, channelization, the geology of the region, and past land-use practices have resulted in the formation of dozens of valley plugs in stream channels and the formation of shoals at the confluence of stream systems. Valley plugs completely block stream channels with sediment and debris and can result in greater deposition rates on floodplain surfaces. Presently, however, information is lacking on the rates and variability of overbank sedimentation associated with valley plugs and shoals. We quantified deposition rates and textures in floodplains along channelized streams that contained valley plugs and shoals, in addition to floodplains occurring along an unchannelized stream, to improve our understanding of overbank sedimentation associated with channelized streams. Feldspar clay marker horizons and marker poles were used to measure floodplain deposition from 2002 to 2005 and data were analyzed with geospatial statistics to determine the spatial dynamics of sedimentation within the floodplains. Mean sediment deposition rates ranged from 0.09 to 0.67??cm/y at unchannelized sites, 0.16 to 2.27??cm/y at shoal sites, and 3.44 to 6.20??cm/y at valley plug sites. Valley plug sites had greater rates of deposition, and the deposited sediments contained more coarse sand material than either shoal or unchannelized sites. A total of 59 of 183 valley plug study plots had mean deposition rates > 5??cm/y. The geospatial analyses showed that the spatial dynamics of sedimentation can be influenced by the formation of valley plugs and shoals on channelized streams; however, responses can vary. Restoration efforts in the region need to have basinwide collaboration with landowners and address catchment-scale processes, including the geomorphic instability of the region, to be successful. ?? 2008 Elsevier B.V. All rights reserved.

Geomorphology↗
USGS2006

Ground-water quality data in the north San Francisco Bay hydrologic provinces, California, 2004: Results from the California Ground-water Ambient Monitoring and Assessment (GAMA) program

Ground-water quality in the ~1,000 square-mile (mi2) North San Francisco Bay study unit was investigated from August to November, 2004, as part of the California Groundwater Ambient Monitoring and Assessment (GAMA) program. Samples were collected from 89 public-supply wells, 7 hydrothermal wells, and 1 hydrothermal spring in Napa, Sonoma and Marin Counties. Eighty-four of the public-supply wells sampled were selected to provide a spatially distributed, randomized monitoring network for statistical calculations and constituent detection frequency. The study was designed to provide a spatially-unbiased assessment of raw ground-water quality within the study unit, as well as a statistically-consistent basis for comparing the water quality of different study units. Ground-water samples were analyzed for major and minor ions, trace elements, nutrients, volatile organic compounds, pesticides and pesticide degradates, waste-water indicators, dissolved methane, nitrogen, carbon dioxide and noble gases (in collaboration with Lawrence Livermore National Laboratory). Naturally occurring isotopes (tritium, carbon-14, oxygen-18, deuterium and helium-4) also were measured in the samples to help identify the source and age of the ground water. Results show that no anthropogenic constituents were detected at concentrations higher than those levels set for regulatory purposes, and relatively few naturally-occurring constituents were detected at concentrations greater than regulatory levels. In this study, 21 of the 88 volatile organic compounds (VOCs) and gasoline additives and (or) oxygenates investigated were detected in ground-water samples, however, detected concentrations were one-half to one-forty-thousandth the maximum contaminant levels (MCL). Thirty-two percent of the randomized wells sampled had at least a single detection of a VOC or gasoline additive and (or) oxygenate. The most frequently detected compounds were chloroform, found in 12 of the 84 randomized wells; carbon disulfide, found in 8 of the 84 randomized wells; and toluene, found in 4 of the 84 randomized wells. Trihalomethanes were the most frequently detected class of VOCs. Nine of the 122 pesticides and (or) pesticide degradates investigated were detected in ground-water samples, however, concentrations were one-seventieth to one-eight-hundredth the MCLs. Seventeen percent of the randomized wells sampled had at least a single detection of pesticide and pesticide degradate. Herbicides were the most frequently detected class of pesticides. The most frequently detected compound was simazine, found in 8 of the 84 of the randomized wells. Chlordiamino-s-triazine and deisopropyl atrazine were both found in 2 of the 84 randomized wells sampled. Thirteen out of 63 compounds that may be indicative of the prescence of waste-water were detected in ground-water samples. Twenty-six percent of the randomized wells sampled for waste-water indicators had at least one detection. Isophorone was the most frequently detected in 6 of the 84 randomized wells. Bisphenol-A, caffeine, and indole each were detected in 3 of the 84 randomized wells. Major and minor ions and dissolved solids (DS) samples were collected at 33 public-supply wells; 3 samples had DS concentrations above the secondary maximum contaminant level (SMCL) of 500 mg/L. Ground-water samples from 32 public-supply wells were analyzed for trace elements. Arsenic concentrations above the MCL of 10 μg/L were measured at 4 public-supply wells, boron concentrations above the detection level for the purpose of reporting (DLR) of 100 μg/L were measured at 19 wells. Iron concentrations above the SMCL of 300 μg/L were measured at 7 wells, a lead concentration above the California notification level (NL) of 15 μg/L at one well, and manganese concentrations above the SMCL of 50 μg/L were measured at 17 wells. Vanadium concentrations above the DLR of 3 μg/L were measured at 9 public-supply wells; and chromium(VI) concentrations above the DLR of 1 μg/L were measured at 48 public-supply wells. Major and minor ions and dissolved solids (DS) samples were collected at 33 public-supply wells; 3 samples had DS concentrations above the secondary maximum contaminant level (SMCL) of 500 mg/L. Ground-water samples from 32 public-supply wells were analyzed for trace elements. Arsenic concentrations above the MCL of 10 μg/L were measured at 4 public-supply wells, boron concentrations above the detection level for the purpose of reporting (DLR) of 100 μg/L were measured at 19 wells. Iron concentrations above the SMCL of 300 μg/L were measured at 7 wells, a lead concentration above the California notification level (NL) of 15 μg/L at one well, and manganese concentrations above the SMCL of 50 μg/L were measured at 17 wells. Vanadium concentrations above the DLR of 3 μg/L were measured at 9 public-supply wells; and chromium(VI) concentrations above the DLR of 1 μg/L were measured at 48 public-supply wells. Microbial constituents were analyzed in 22 ground-water samples. Total coliform was detected in three wells. Counts ranged from 2 colonies per 100 mL to 20 colonies per 100 mL. MCLs for microbial constituents are based on reoccurring detection, and will be monitored during future sampling.

California↗