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At least 1,045 records · Page 58Linked to original sources
USGS2006

Quantity-activity relationship of denitrifying bacteria and environmental scaling in streams of a forested watershed

The spatial variability of subreach denitrification rates in streams was evaluated with respect to controlling environmental conditions, molecular examination of denitrifying bacteria, and dimensional analysis. Denitrification activities ranged from 0 and 800 ng-N gsed-1 d-1 with large variations observed within short distances (<50 m) along stream reaches. A log-normal probability distribution described the range in denitrification activities and was used to define low (16% of the probability distributibn), medium (68%), and high (16%) denitrification potential groups. Denitrifying bacteria were quantified using a competitive polymerase chain reaction (cPCR) technique that amplified the nirK gene that encodes for nitrite reductase. Results showed a range of nirK quantities from 103 to 107 gene-copy-number gsed.-1 A nonparametric statistical test showed no significant difference in nirK quantifies among stream reaches, but revealed that samples with a high denitrification potential had significantly higher nirK quantities. Denitrification activity was positively correlated with nirK quantities with scatter in the data that can be attributed to varying environmental conditions along stream reaches. Dimensional analysis was used to evaluate denitrification activities according to environmental variables that describe fluid-flow properties, nitrate and organic material quantities, and dissolved oxygen flux. Buckingham's pi theorem was used to generate dimensionless groupings and field data were used to determine scaling parameters. The resulting expressions between dimensionless NO3- flux and dimensionless groupings of environmental variables showed consistent scaling, which indicates that the subreach variability in denitrification rates can be predicted by the controlling physical, chemical, and microbiological conditions. Copyright 2006 by the American Geophysical Union.

Journal of Geophysical Research G: Biogeosciences↗
USGS2008

Design for a region-wide adaptive search for the ivorybilled woodpecker with the objective of estimating occupancy and related parameters

We describe a survey design and field protocol for the Ivory-billed Woodpecker (Campephilus principalis) search effort that will: (1) allow estimation of occupancy, use, and detection probability for habitats at two spatial scales within the bird?s former range, (2) assess relationships between occupancy, use, and habitat characteristics at those scales, (3) eventually allow the development of a population viability model that depends on patch occupancy instead of difficult-to-measure demographic parameters, and (4) be adaptive, allowing newly collected information to update the above models and search locations. The approach features random selection of patches to be searched from a sampling frame stratified and weighted by patch quality, and requires multiple visits per patch. It is adaptive within a season in that increased search activity is allowed in and around locations of strong visual and/or aural evidence, and adaptive among seasons in that habitat associations allow modification of stratum weights. This statistically rigorous approach is an improvement over simply visiting the ?best? habitat in an ad hoc fashion because we can learn from prior effort and modify the search accordingly. Results from the 2006-07 search season indicate weak relationships between occupancy and habitat (although we suggest modifications of habitat measurement protocols), and a very low detection probability, suggesting more visits per patch are required. Sample size requirements will be discussed.

Book chapter↗
USGS2008

Hierarchical modeling of cluster size in wildlife surveys

Clusters or groups of individuals are the fundamental unit of observation in many wildlife sampling problems, including aerial surveys of waterfowl, marine mammals, and ungulates. Explicit accounting of cluster size in models for estimating abundance is necessary because detection of individuals within clusters is not independent and detectability of clusters is likely to increase with cluster size. This induces a cluster size bias in which the average cluster size in the sample is larger than in the population at large. Thus, failure to account for the relationship between delectability and cluster size will tend to yield a positive bias in estimates of abundance or density. I describe a hierarchical modeling framework for accounting for cluster-size bias in animal sampling. The hierarchical model consists of models for the observation process conditional on the cluster size distribution and the cluster size distribution conditional on the total number of clusters. Optionally, a spatial model can be specified that describes variation in the total number of clusters per sample unit. Parameter estimation, model selection, and criticism may be carried out using conventional likelihood-based methods. An extension of the model is described for the situation where measurable covariates at the level of the sample unit are available. Several candidate models within the proposed class are evaluated for aerial survey data on mallard ducks (Anas platyrhynchos).

Journal of Agricultural, Biological, and Environme↗
USGS2018

Metamodeling and mapping of nitrate flux in the unsaturated zone and groundwater, Wisconsin, USA

Nitrate contamination of groundwater in agricultural areas poses a major challenge to the sustainability of water resources. Aquifer vulnerability models are useful tools that can help resource managers identify areas of concern, but quantifying nitrogen (N) inputs in such models is challenging, especially at large spatial scales. We sought to improve regional nitrate (NO 3 − ) input functions by characterizing unsaturated zone NO 3 − transport to groundwater through use of surrogate, machine-learning metamodels of a process-based N flux model. The metamodels used boosted regression trees (BRTs) to relate mappable landscape variables to parameters and outputs of a previous “vertical flux method” (VFM) applied at sampled wells in the Fox, Wolf, and Peshtigo (FWP) river basins in northeastern Wisconsin. In this context, the metamodels upscaled the VFM results throughout the region, and the VFM parameters and outputs are the metamodel response variables. The study area encompassed the domain of a detailed numerical model that provided additional predictor variables, including groundwater recharge, to the metamodels. We used a statistical learning framework to test a range of model complexities to identify suitable hyperparameters of the six BRT metamodels corresponding to each response variable of interest: NO 3 − source concentration factor (which determines the local NO 3 − input concentration); unsaturated zone travel time; NO 3 − concentration at the water table in 1980, 2000, and 2020 (three separate metamodels); and NO 3 − “extinction depth”, the eventual steady state depth of the NO 3 − front. The final metamodels were trained to 129 wells within the active numerical flow model area, and considered 58 mappable predictor variables compiled in a geographic information system (GIS). These metamodels had training and cross-validation testing R 2 values of 0.52 – 0.86 and 0.22 – 0.38, respectively, and predictions were compiled as maps of the above response variables. Testing performance was reasonable, considering that we limited the metamodel predictor variables to mappable factors as opposed to using all available VFM input variables. Relationships between metamodel predictor variables and mapped outputs were generally consistent with expectations, e.g. with greater source concentrations and NO 3 − at the groundwater table in areas of intensive crop use and well drained soils. Shorter unsaturated zone travel times in poorly drained areas likely indicated preferential flow through clay soils, and a tendency for fine grained deposits to collocate with areas of shallower water table. Numerical estimates of groundwater recharge were important in the metamodels and may have been a proxy for N input and redox conditions in the northern FWP, which had shallow predicted NO 3 − extinction depth. The metamodel results provide proof-of-concept for regional characterization of unsaturated zone NO 3 − transport processes in a statistical framework based on readily mappable GIS input variables.

Wisconsin↗
USGS2022

Industrial particulate pollution and historical land use contribute metals of concern to dust deposited in neighborhoods along the Wasatch Front, UT, USA

The Salt Lake Valley, UT, USA, is proximal to the desiccating Great Salt Lake (GSL). Prior work has found that this lakebed/playa contributes metals-laden dust to snow in the Wasatch and Uinta Mountains. Dust and industrial particulate pollution are also delivered to communities along the Wasatch Front, but their sources, compositions, and fluxes are poorly characterized. In this study, we analyzed the dust deposited in 18 passive samplers positioned near the GSL, in cities in and near the Salt Lake Valley for total dust flux, the <63 µm dust fraction, 87 Sr/ 86 Sr, and trace element geochemistry. We compared spatial patterns in metal flux and abundance with community-level socioeconomic metrics. We observed the highest dust fluxes at sites near the GSL playa. Within the urban corridor, 87 Sr/ 86 Sr and trace element relative abundances suggest that most of the dust to which people are regularly exposed may be fugitive dust from local soil materials. The trace metal content of dust deposited along the Wasatch Front exceeded Environmental Protection Agency screening levels and exhibited enrichment relative to both the upper continental crust and the dust collected adjacent to GSL. Sources of metals to dust deposited along the Wasatch Front may include industrial activities like mining, oil refining, as well as past historical pesticide and herbicide applications. Arsenic and vanadium indicated a statistically significant positive correlation with income, whereas lead, thallium, and nickel exhibited higher concentrations in the least wealthy and least white neighborhoods.

Wasatch Front↗
USGS2012

Concentrations, loads, and yields of select constituents from major tributaries of the Mississippi and Missouri Rivers in Iowa, water years 2004-2008

Excess nutrients, suspended-sediment loads, and the presence of pesticides in Iowa rivers can have deleterious effects on water quality in State streams, downstream major rivers, and the Gulf of Mexico. Fertilizer and pesticides are used to support crop growth on Iowa's highly productive agricultural landscape and for household and commercial lawns and gardens. Water quality was characterized near the mouths of 10 major Iowa tributaries to the Mississippi and Missouri Rivers from March 2004 through September 2008. Stream loads were calculated for select ions, nutrients, and sediment using approximately monthly samples, and samples from storm and snowmelt events. Water-quality samples collected using standard streamflow-integrated protocols were analyzed for major ions, nutrients, carbon, pesticides, and suspended sediment. Statistical data summaries of sample data used parametric and nonparametric techniques to address potential bias related to censored data and multiple levels of censoring of data below analytical detection limits. Constituent stream loads were computed using standard pre-defined models in S-LOADEST that include streamflow and time terms plus additional terms for streamflow variability and streamflow anomalies. Streamflow variability terms describe the difference in streamflow from recent average conditions, whereas streamflow anomaly terms account for deviations from average conditions from long- to short-term sequentially. Streamflow variability or anomaly terms were included in 44 of 80 site/constituent individual models, demonstrating the usefulness of these terms in increasing accuracy of the load estimates. Constituent concentrations in Iowa streams exhibit streamflow, seasonal, and spatial patterns related to the landform and climate gradients across the studied basins. The streamflow-concentration relation indicated dilution for ions such as chloride and sulfate. Other constituent concentrations, such as dissolved organic carbon and suspended sediment, increased with streamflow. Nitrogen concentrations (total nitrogen and nitrate plus nitrite) increased with low and moderate streamflows, but decreased with high streamflows. Seasonal patterns observed in constituent concentrations were affected by streamflow, algae blooms, and pesticide application. The various landform regions produced different water-quality responses across the study basins; for example, total phosphorus, suspended sediment, and turbidity were greatest from the steep, loess-dominated southwestern Iowa basins. Nutrient concentrations, though not regulated for drinking water at the study sites, were high compared to drinking-water limits and criteria for protection of aquatic life proposed for other Midwestern states (Iowa criteria for aquatic life have not been proposed). Nitrate plus nitrite concentrations exceeded the drinking-water limit [10 milligrams per liter (mg/L)] in 11 percent of all samples at the 10 sites, and exceeded Minnesota's proposed aquatic life criteria (4.9 mg/L) in 68 percent of samples. The Wisconsin standard for total phosphorus (0.1 mg/L) was exceeded in 92 percent of samples. Ammonia standards, current during sample collection and at publication of this report, for protection of aquatic life were met for all samples, but draft criteria proposed in 2009 to protect more sensitive species like mussels, were exceeded at three sites. Loads and yields also differed among sites and years. The Big Sioux, Little Sioux, and Des Moines Rivers produced the greatest sulfate yields. Mississippi River tributaries had greater chloride yields than Missouri River tributaries. The Big Sioux River also had the lowest silica yields and total nitrogen and nitrate yields, whereas nitrogen yields were greater in the northeastern rivers. The Boyer and Nishnabotna River total phosphorus yields were the greatest in the study. The Boyer River orthophosphate yields were greatest except in 2008, when the Maquoketa River produced the greatest yield. Rivers in southwestern Iowa's Western Loess Hills and Steeply Rolling Loess Prairie ecoregions had the greatest suspended-sediment yields, whereas the smallest yields were in the Big Sioux and Wapsipinicon Rivers. In the 10 Iowa rivers studied, combined annual total nitrogen stream transport ranged from 3.68 to 9.95 tons per square mile per year, and total phosphorus transport ranged from 0.138 to 0.570 tons per square mile per year. Six-month loads relative to fertilizer use ranged from 8 to 56 percent for nitrogen, and 1.0 to 11.1 percent for phosphorus. The smallest loads relative to fertilizer use for both nitrogen and phosphorus occurred in July-December of dry years, and the largest nitrogen and phosphorus loads relative to use were in wet years from January-June.

Iowa;Minnesota;South Dakota↗
USGS2009

An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery

In recent years, application of remote sensing to marine mammal surveys has been a promising area of investigation for wildlife managers and researchers. In April 2006, the United States and Russia conducted an aerial survey of Pacific walrus (Odobenus rosmarus divergens) using thermal infrared sensors to detect groups of animals resting on pack ice in the Bering Sea. The goal of this survey was to estimate the size of the Pacific walrus population. An initial analysis of the U.S. data using previously-established methods resulted in lower detectability of walrus groups in the imagery and higher variability in calibration models than was expected based on pilot studies. This paper describes an improved procedure for detection and enumeration of walrus groups in airborne thermal imagery. Thermal images were first subdivided into smaller 200 x 200 pixel "tiles." We calculated three statistics to represent characteristics of walrus signatures from the temperature histogram for each the. Tiles that exhibited one or more of these characteristics were examined further to determine if walrus signatures were present. We used cluster analysis on tiles that contained walrus signatures to determine which pixels belonged to each group. We then calculated a thermal index value for each walrus group in the imagery and used generalized linear models to estimate detection functions (the probability of a group having a positive index value) and calibration functions (the size of a group as a function of its index value) based on counts from matched digital aerial photographs. The new method described here improved our ability to detect walrus groups at both 2 m and 4 m spatial resolution. In addition, the resulting calibration models have lower variance than the original method. We anticipate that the use of this new procedure will greatly improve the quality of the population estimate derived from these data. This procedure may also have broader applicability to thermal infrared surveys of other wildlife species. Published by Elsevier B.V.

International Journal of Applied Earth Observation↗
USGS2021

Status and understanding of groundwater quality in the northern Sierra Nevada foothills domestic-supply aquifer study units, 2015–17—California GAMA Priority Basin Project

Groundwater quality in the northern Sierra Nevada foothills region of California was investigated as part of California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring Assessment Priority Basin Project (GAMA-PBP). The region was divided into two study units: the Yuba-Bear watersheds (YBW) study unit and the American-Cosumnes-Mokelumne watersheds (ACMW) study unit. The GAMA-PBP made a spatially unbiased assessment of aquifer systems used for domestic drinking-water supply in the study region, which are predominantly composed of fractured, hard-rock aquifers of varying lithology. These assessments characterized the quality of raw groundwater to evaluate ambient conditions in the domestic-supply aquifer and not the quality of treated drinking water. The study included three components: (1) a status assessment , which characterized the quality of groundwater resources used for domestic drinking-water supply in the YBW and ACMW study units; (2) an understanding assessment , which evaluated natural and anthropogenic explanatory factors that could potentially affect groundwater quality in the study region; and (3) a comparative assessment between the groundwater resources used for domestic and public drinking-water supply in the study region. The status assessment was based on data collected by the GAMA-PBP from 74 sites in the YBW study unit during 2015–16 and 67 sites in the ACMW study unit from 2016 to 2017. To contextualize water-quality results, concentrations of water-quality constituents in ambient groundwater were compared to regulatory and non-regulatory benchmarks typically used by the State of California and Federal agencies as health-based or aesthetic standards for public drinking water. The status assessment used a grid-based method to estimate proportions of groundwater resources with concentrations approaching or exceeding benchmark thresholds. This method provides spatially unbiased results and allows inter-comparability with similar groundwater-quality assessments. Inorganic constituents with health-based benchmarks were present at high relative concentration (RC), meaning they exceeded the benchmark threshold, in 5.4 and 10 percent of domestic-supply aquifer systems in the YBW and ACMW study units, respectively. Inorganic constituents with aesthetic-based benchmarks were detected at high-RCs in 20 and 28 percent of the YBW and ACMW study units, respectively. The inorganic constituents present at high RC were arsenic, barium, boron, molybdenum, strontium, nitrate, adjusted gross-alpha particle activity, chloride, total dissolved solids, specific conductance, iron, manganese, and hardness. Groundwater samples were tested for presence or absence of three microbial indicators (total coliform, Escherichia coli , and Enterococci ). At least one microbial indicator was present in 26 and 28 percent of the YBW and ACMW study units, respectively. At least one organic constituent was detected in 30 and 42 percent of the YBW and ACMW study units, respectively. Organic constituents were not present at high RC, but tetrachloroethene (PCE), trichloroethene (TCE), and toluene were detected in the YBW study unit at moderate RC (between the benchmark concentration and one-tenth of the benchmark concentration). Methyl tert -butyl ether (MTBE) and chloroform were present at low RC (less than one-tenth of the benchmark concentration) in the YBW and ACMW study units with detection frequencies greater than 10 percent. Perchlorate, a constituent of special interest, was detected in 31 and 41 percent of the YBW and ACMW study units, respectively, at either low or moderate RCs. Relations among select water-quality constituents and potential explanatory factors were evaluated using statistical and graphical approaches. Nitrate, microbial indicators, and perchlorate were all correlated to elevation-dependent variables relating to climate, land use, and recharge condition. Isotopic and dissolved noble-gas tracers indicated these water-quality constituents are associated with recharge conditions associated with irrigation during the summer dry-season, which is common in areas of rural-residential or agricultural land uses. Higher concentrations of iron and manganese were primarily associated with anoxic groundwater in aquifers of metasedimentary lithology. Increased hardness was primarily associated with anoxic groundwater in aquifers of mafic-ultramafic or metavolcanics lithologies at lower elevations in the study region in the Melones fault zone. Chloroform and MTBE were associated with shallow groundwater (wells depths less than 130 m) under oxic and anoxic redox conditions, respectively. The comparative assessment evaluated differences between the aquifer systems used for domestic- and public-supply in study region based on (1) well-construction characteristics, and (2) water quality. Analysis of over 60,000 well-completion reports in the study region showed that although domestic-supply wells span the deepest depth zones in regional aquifers, median depths for public-supply wells were significantly greater than those of domestic-supply wells in both study units. Water-quality data from more than 300 public-supply wells in the study region were assessed using a spatially weighted method for calculation aquifer-scale proportions and compared with the domestic-supply assessment results. Detections of inorganic constituents at high RC and detection frequencies for organic constituents were generally similar between the domestic- and public-supply aquifer systems in both study units, with a few notable exceptions in the ACMW study unit: nitrate was greater for the public- compared to domestic-supply aquifer system and both manganese, hardness, and MTBE were greater in the domestic- compared to public-supply aquifer system. These differences are likely related to contrasting land uses, aquifer lithologies, landscape positions, and depths characterizing domestic- and public-supply wells in the ACMW study unit. Overall, fewer samples from domestic-supply wells in the northern Sierra Nevada foothills exceeded health-based benchmarks compared to aesthetic-based benchmarks for groundwater quality. Exceedences of health-based benchmarks were primarily caused by nitrate and coliform bacteria, which were associated with recharge from diverted surface water used primarily for irrigation. Exceedences of aesthetic-based benchmarks were primarily caused by iron, managanese, and hardness, which were associated with geologic factors. Regional irrigation practices and aquifer lithology can affect groundwater quality in fractured-rock aquifers in the northern Sierra Nevada foothills used for domestic drinking-water supply.

California↗
USGS2022

Spatially integrating microbiology and geochemistry to reveal complex environmental health issues: Anthrax in the contiguous United States

Maxent models were run using the B. anthracis presence data and/or the animal outbreak presence data. Models run using the animal outbreak data alone utilized two scales: the Outbreak State scale which included only states reporting animal anthrax outbreaks from 2001 to 2013 and the National scale which included all states in the contiguous United States. Three iterations of the environmental data were used and included the Sample Location dataset which utilized the environmental variable data with assigned latitude and longitude locations from the USGS NASGLP project; the Normalized dataset which scaled the environmental variables so that the values fell between 0 and 1; and the Interpolated dataset which provided an interpolation of the environmental variables averaged for each county and assigned to a point for that county at the centroid (rather than using the NASGLP latitude and longitude location). Two metrics were used to measure model performance including the widely used area under the curve (AUC) and an alternative method, the True Skill Statistic (TSS). The AUC gives the probability that a randomly chosen presence location has been correctly ranked higher than the absence/background site. AUC values at 0.5 or lower mean the ranking is no better than random, while the AUC values nearer to 1 mean the model is a better predictor. The TSS provides a comparison of how well the background predictions made by the model match the model results at the test dataset (presence) locations. TSS values near +1 means the model approaches perfect agreement, while values near −1 indicate the model is no better than random. Maxent models to determine the influence of environmental factors on the B. anthracis distribution using the PCR data yielded a low TSS, which suggested the model might be underfitting the data. This was not surprising due to the difficulty in recovering B. anthracis in soil samples as well as the samples themselves being discrete in nature and only capturing a snapshot in time. Therefore, the distribution of B. anthracis and its niche in the contiguous United States could not be determined in this study. However, efforts to investigate environmental factors that would have a higher potential of supporting an anthrax outbreak in wildlife and livestock yielded better results. Results showed that most of the Maxent models in this study performed best when using the Outbreak State scale. When the models were scaled up to the National scale, model performance declined, except for the Normalized variable dataset. At the Outbreak State scale, a large proportion of the area was predicted to be of higher probability for wildlife/livestock anthrax outbreaks, and the statistical measures assumed the model was underfitting the data. The model with the highest AUC and TSS scores for this study was the Outbreak State scale using Sample Location dataset (AUC = 0.918 and TSS = 0.82). Some of the variables found to be closely related to the occurrence of B. anthracis in this study included pH, drainage potential, and concentration of elements including Na, Ca, Sr, and Mg, which have also been found to be related to animal outbreaks or to the occurrence of B. anthracis in previous studies. The models in the current study indicated possible regions that have not had recent wildlife/livestock anthrax outbreaks but contained environmental conditions that could potentially support an outbreak if one were to occur (Michigan and Maine). This work provides an extension to the use of ecological niche modeling to outbreak potential in livestock/wildlife in the United States because it utilizes additional soil geochemistry data and has shown that further validation techniques, such as the TSS, should be considered in addition to AUC. Results from this study could be used by animal and public health officials to identify areas with a higher potential for anthrax outbreak in wildlife and livestock due to naturally occurring soil and environmental conditions.

Book chapter↗
USGS2022

Evaluation of post-stocking dispersal and mortality of juvenile lake trout Salvelinus namaycush in Lake Ontario using acoustic telemetry

Wild reproduction by stocked lake trout Salvelinus namaycush in Lake Ontario has yet to produce a self-sustaining population, requiring a reliance on stocking. Once released, age-1 juvenile lake trout are not typically surveyed until age-2, creating a gap in knowledge of fine-scale post-release behaviors. A method to track fine-scale movements and estimate mortality of juvenile lake trout could complement standard survey methods and benefit management decisions regarding stocking locations. We used acoustic telemetry to estimate post-stocking mortality and observe fine-scale spatial and temporal movements of 38 hatchery-reared, age-1 lake trout from an offshore stocking site in the eastern basin of Lake Ontario from 2017 to 2018. Cumulative post-stocking mortality was estimated at 5.3%, 10.5%, and 26.3% after one week, one month and one year, respectively. The majority of lake trout (68.4%) emigrated from the stocking location within two months and entered deep water (∼50 m) once warm-water incursions at the stocking site exceeded lake trout thermal preferences (15 °C). Lake trout made large movements (i.e., median 1.9 km, maximum 12.4 km straight-line distance) within the first hour post-release and had an average swimming speed of 1.64 km‧hr −1 over the first day. There was no statistically significant relationship between total distance traveled and time of day, although distance traveled tended to be greater during crepuscular and dark periods compared to daylight. Our results provide a conservative estimate of post-release mortality and reveal behaviors of hatchery-reared juvenile lake trout that may be helpful when selecting stocking locations beneficial to restoration program goals.

Lake Ontario↗
USGS2010

Effects of low-impact-development (LID) practices on streamflow, runoff quantity, and runoff quality in the Ipswich River Basin, Massachusetts: A summary of field and modeling studies

Low-impact-development (LID) approaches are intended to create, retain, or restore natural hydrologic and water-quality conditions that may be affected by human alterations. Wide-scale implementation of LID techniques may offer the possibility of improving conditions in river basins, such as the Ipswich River Basin in Massachusetts, that have run dry during the summer because of groundwater withdrawals and drought. From 2005 to 2008, the U.S. Geological Survey, in a cooperative funding agreement with the Massachusetts Department of Conservation and Recreation, monitored small-scale installations of LID enhancements designed to diminish the effects of storm runoff on the quantity and quality of surface water and groundwater. Funding for the studies also was contributed by the U.S. Environmental Protection Agency’s Targeted Watersheds Grant Program through a financial assistance agreement with Massachusetts Department of Conservation and Recreation. The monitoring studies examined the effects of replacing an impervious parking-lot surface with a porous surface on groundwater quality, installing rain gardens and porous pavement in a neighborhood of 3 acres on the quantity and quality of stormwater runoff, and installing a 3,000-ft2 (square-foot) green roof on the quantity and quality of rainfall-generated roof runoff. In addition to these small-scale installations, the U.S. Geological Survey’s Ipswich River Basin model was used to simulate the basin-wide effects on streamflow of several changes: broad-scale implementation of LID techniques, reduced water-supply withdrawals, and water-conservation measures. Water-supply and conservation scenarios for application in model simulations were developed with the assistance of two technical advisory committees that included representatives of State agencies responsible for water resources, the U.S. Environmental Protection Agency, the U.S. Geological Survey, water suppliers, and non-governmental organizations. From June 2005 to June 2007, groundwater quality was monitored at the Silver Lake town beach parking lot in Wilmington, Massachusetts, prior to and following the replacement of the conventional, impervious-asphalt surface with a porous surface consisting primarily of porous asphalt and porous pavers designed to enhance rainfall infiltration into the groundwater and to minimize runoff to Silver Lake. Concentrations of phosphorus, nitrogen, cadmium, chromium, copper, lead, nickel, zinc, and total petroleum hydrocarbons in groundwater were monitored. Enhancing infiltration of precipitation did not result in discernible increases in concentrations of these potential groundwater contaminants. Concentrations of dissolved oxygen increased slightly in groundwater profiles following the removal of the impervious asphalt parking-lot surface. In Wilmington, Massachusetts, in a 3-acre neighborhood, stormwater runoff volume and quality were monitored to determine the ability of selected LID enhancements (rain gardens and porous paving stones) to reduce flows and loads of the selected constituents to Silver Lake. Water-quality samples were analyzed for nutrients, metals, total petroleum hydrocarbons, and total-coliform and E. coli bacteria. A decrease in runoff quantity was observed for storms of 0.25 inch or less of precipitation. Water-quality-monitoring results were inconclusive; there were no statistically significant differences in concentrations or loads when the pre- and post-installation-period samples were compared. In a third field study, the characteristics of runoff from a vegetated "green" roof and a conventional, rubber-membrane roof were compared. The two primary factors affecting the green roof’s water-storage capacity were the amount of precipitation and antecedent dry period. Although concentrations of many of the chemicals in roof runoff were higher from the green roof than from the conventional roof, the ability of the green roof to retain water generally resulted in decreased differences between the total amounts (loads) of the chemicals that ran off the roofs. Land-use and water-management changes associated with LID implementation were investigated at multiple spatial scales, using the U.S. Geological Survey’s Ipswich River Basin model, to evaluate the effects of updated water-supply withdrawals for the towns of Reading and Wilmington (representing new baseline conditions for all simulations), potential land-use changes at buildout (potential future development), widespread implementation of retrofitting LID techniques, basin-scale water withdrawal reductions based on water-conservation pilot programs conducted by the Massachusetts Department of Conservation and Recreation, and land-use change and LID applications at a local scale. The new baseline simulation indicated that reduced water-supply withdrawals for the towns of Reading and Wilmington led to substantially higher medium and low flows in most of the reaches upstream from the South Middleton streamgage in the upper Ipswich River basin. Overall, simulations pointed to the importance of spatial scale in determining the effects of land-use change and LID practices on streamflow. Potential land-use changes at buildout had modest effects on streamflow in most subbasins (percent differences of less than 20 percent) because relatively little land in the basin was available for development. Results of the simulations conducted to evaluate widespread effective-impervious-area reductions upstream from the South Middleton streamgage indicated that the percentages of urban land use and associated effective impervious area were too small for even a 50-percent reduction of effective impervious area to appreciably affect streamflow in most subbasins. In contrast, the results of the hypothetical local-scale simulations indicated that for smaller streams, with high percentages of urban land use and associated effective impervious area, land-use change, development patterns, and LID practices may have substantial effects on streamflow. Modeling studies concurred with the results of fieldwork in the assessment that LID enhancements would likely have the greatest effect on decreasing stormwater runoff when broadly applied to highly impervious urban areas.

Massachusetts↗
USGS2022

BFS—A non-linear, state-space model for baseflow separation and prediction

Streamflow in rivers can be separated into a relatively steady component, or baseflow, that represents reliably available surface water and more dynamic components of runoff that typically represent a large fraction of total streamflow. A spatially aggregated numerical time-series model was developed to separate the baseflow component of a streamflow time-series using a state-space framework in which baseflow is a non-linear function of upstream storage, an unmeasured state variable. The state-space framework allows forecasting of baseflow for periods with no rainfall or snowmelt and estimation of residence times in contrast to other hydrograph separation models. The use of a non-linear relation between baseflow and storage maintains model performance over a wide range of time scales but will only provide reliable predictions for periods when the rate of streamflow recession as a fraction of streamflow decreases over time. The baseflow separation model, BFS, is implemented as set of functions in the statistical computing language R. BFS is run using the main function, bf_sep, which reads model input (a time series of streamflow), calculates the baseflow component of streamflow, writes model output to a file, and returns an error to the user to facilitate automated calibration. The function, bf_sep, has six arguments, which a user must enter: a numerical vector with the time series of measured streamflow volume for each time step; a character string, timestep , that has a value of either “daily” or “hourly” indicating the time step; a character string, error_basis, indicating which simulated streamflow components are used for error calculations; a six-element numeric vector, flow , with parameters characterizing streamflow; a six-element vector, basin_char , with parameters characterizing the geometry of stream basin and reservoirs; and a six-element vector, gw_hyd , with hydraulic parameters. The function bf_sep calls a series of other functions to calculate surface and base reservoir storage and fluxes. Calibration of a non-linear model for baseflow recession must confront three issues. First, baseflow is a component of streamflow, so it is always less than or equal to streamflow but there is no independent standard for the baseflow component of streamflow. Second, optimization routines can converge on a set of model parameters that result in relatively steady but minimal baseflow that does not exceed streamflow, Q , but has a limited dynamic range. Third, the power function used to generate non-linear first-order baseflow recession ( dQ/dt )/Q ≠ constant) may only be sensitive to parameters over a limited range of values, which may not be found by optimization routines. To address these issues, BFS calculates error as the mean of weighted differences between measured streamflow and either simulated baseflow or the sum of simulated baseflow and surface flow as a fraction of measured streamflow. The difference for each time step is weighted by an exponential function of the length of recession for each time step ranging from 0 for periods when streamflow increases and approaching 1 for long recessional periods. The weight is set to 1 for any time step when simulated streamflow exceeds measured streamflow. Error calculation incorporates limited precision of streamflow measurements. A four-step calibration process was developed to find a set of viable parameters that maximize the baseflow component within the constraints of the conceptual model (a first-order recession rate that decreases during dry periods). BFS was calibrated at 13,208 U.S. Geological Survey streamgages with available daily streamflow records for at least 300 days from water years 1981 to 2020. The total simulated baseflow component as a fraction of streamflow (BFF) was generally less than the baseflow index (BFI) for 8,368 streamgages where BFF and BFI were available. The median difference was BFF–BFI = 0.11. Large differences were most common in the Interior West where streamflow in many rivers is regulated and is generated predominantly by snowmelt. The baseflow separation model generally allocates less streamflow to baseflow than graphical hydrograph separation in snowmelt rivers. BFS can be used to forecast streamflow during dry periods by using a time series of real-time streamflow with values of Not Available (NA), appended to the time-series to represent missing (future) streamflow values. The forecast skill of BFS was evaluated in terms of difference between simulated baseflow and measured streamflow as a fraction of measured streamflow on the days of the annual maximum recession period at 5,916 of the sites with at least 10 years of record. The median annual error was less than 50 percent at one-half of the sites and generally improved for drier years with longer recession periods.

Scientific Investigations Report↗
USGS2021

Characterizing methane emission hotspots from thawing permafrost

Methane (CH 4 ) emissions from climate-sensitive ecosystems within the northern permafrost region represent a potentially large but highly uncertain source, with current estimates spanning a factor of seven (11–75 Tg CH 4 yr −1 ). Accelerating permafrost thaw threatens significant increases in pan-Arctic CH 4 emissions, amplifying the permafrost carbon feedback. We used airborne imaging spectroscopy with meter-scale spatial resolution and broad coverage to identify a previously undiscovered CH 4 emission hotspot adjacent to a thermokarst lake in interior Alaska. Hotspot emissions were confined to <1% of the 10 ha lake study area. Ground-based chamber measurements confirmed average daily fluxes from the hotspot of 1,170 mg CH 4 m −2 d −1 , with extreme daily maxima up to 24,200 mg CH 4 m −2 d −1 . Ground-based geophysical measurements revealed thawed permafrost directly beneath the CH 4 hotspot, extending to a depth of ∼15 m, indicating that the intense CH 4 emissions likely originated from recently thawed permafrost. Hotspot emissions accounted for ∼40% of total diffusive CH 4 emissions from the lake study site. Combining study site findings with hotspot statistics from our 70,000 km 2 airborne survey across Alaska and northwestern Canada, we estimate that pan-Arctic terrestrial thermokarst hotspots currently emit 1.1 (0.1–5.2) Tg CH 4 yr −1 , or roughly 4% of the annual pan-Arctic wetland budget from just 0.01% of the northern permafrost land area. Our results suggest that significant proportions of pan-Arctic CH 4 emissions originate from disproportionately small areas of previously undetermined thermokarst emissions hotspots, and that pan-Arctic CH 4 emissions may increase non-linearly as thermokarst processes increase under a warming climate.

Alaska↗
USGS2005

Significance of stress transfer in time-dependent earthquake probability calculations

A sudden change in stress is seen to modify earthquake rates, but should it also revise earthquake probability? Data used to derive input parameters permits an array of forecasts; so how large a static stress change is require to cause a statistically significant earthquake probability change? To answer that question, effects of parameter and philosophical choices are examined through all phases of sample calculations, Drawing at random from distributions of recurrence-aperiodicity pairs identifies many that recreate long paleoseismic and historic earthquake catalogs. Probability density funtions built from the recurrence-aperiodicity pairs give the range of possible earthquake forecasts under a point process renewal model. Consequences of choices made in stress transfer calculations, such as different slip models, fault rake, dip, and friction are, tracked. For interactions among large faults, calculated peak stress changes may be localized, with most of the receiving fault area changed less than the mean. Thus, to avoid overstating probability change on segments, stress change values should be drawn from a distribution reflecting the spatial pattern rather than using the segment mean. Disparity resulting from interaction probability methodology is also examined. For a fault with a well-understood earthquake history, a minimum stress change to stressing rate ratio of 10:1 to 20:1 is required to significantly skew probabilities with >80-85% confidence. That ratio must be closer to 50:1 to exceed 90-95% confidence levels. Thus revision to earthquake probability is achievable when a perturbing event is very close to the fault in question or the tectonic stressing rate is low.

Journal of Geophysical Research B: Solid Earth↗
USGS2000

MODFLOW-2000, the U.S. Geological Survey modular ground-water model; user guide to the observation, sensitivity, and parameter-estimation processes and three post-processing programs

This report documents the Observation, Sensitivity, and Parameter-Estimation Processes of the ground-water modeling computer program MODFLOW-2000. The Observation Process generates model-calculated values for comparison with measured, or observed, quantities. A variety of statistics is calculated to quantify this comparison, including a weighted least-squares objective function. In addition, a number of files are produced that can be used to compare the values graphically. The Sensitivity Process calculates the sensitivity of hydraulic heads throughout the model with respect to specified parameters using the accurate sensitivity-equation method. These are called grid sensitivities. If the Observation Process is active, it uses the grid sensitivities to calculate sensitivities for the simulated values associated with the observations. These are called observation sensitivities. Observation sensitivities are used to calculate a number of statistics that can be used (1) to diagnose inadequate data, (2) to identify parameters that probably cannot be estimated by regression using the available observations, and (3) to evaluate the utility of proposed new data. The Parameter-Estimation Process uses a modified Gauss-Newton method to adjust values of user-selected input parameters in an iterative procedure to minimize the value of the weighted least-squares objective function. Statistics produced by the Parameter-Estimation Process can be used to evaluate estimated parameter values; statistics produced by the Observation Process and post-processing program RESAN-2000 can be used to evaluate how accurately the model represents the actual processes; statistics produced by post-processing program YCINT-2000 can be used to quantify the uncertainty of model simulated values. Parameters are defined in the Ground-Water Flow Process input files and can be used to calculate most model inputs, such as: for explicitly defined model layers, horizontal hydraulic conductivity, horizontal anisotropy, vertical hydraulic conductivity or vertical anisotropy, specific storage, and specific yield; and, for implicitly represented layers, vertical hydraulic conductivity. In addition, parameters can be defined to calculate the hydraulic conductance of the River, General-Head Boundary, and Drain Packages; areal recharge rates of the Recharge Package; maximum evapotranspiration of the Evapotranspiration Package; pumpage or the rate of flow at defined-flux boundaries of the Well Package; and the hydraulic head at constant-head boundaries. The spatial variation of model inputs produced using defined parameters is very flexible, including interpolated distributions that require the summation of contributions from different parameters. Observations can include measured hydraulic heads or temporal changes in hydraulic heads, measured gains and losses along head-dependent boundaries (such as streams), flows through constant-head boundaries, and advective transport through the system, which generally would be inferred from measured concentrations. MODFLOW-2000 is intended for use on any computer operating system. The program consists of algorithms programmed in Fortran 90, which efficiently performs numerical calculations and is fully compatible with the newer Fortran 95. The code is easily modified to be compatible with FORTRAN 77. Coordination for multiple processors is accommodated using Message Passing Interface (MPI) commands. The program is designed in a modular fashion that is intended to support inclusion of new capabilities.

Open-File Report↗
USGS2000

A decision support system for prioritizing forested wetland restoration in the Yazoo Backwater Area, Mississippi

A working prototype decision support system (DSS) was developed for the Yazoo Backwater Area, Mississippi, to help planners and managers prioritize, plan, conduct, and optimize forested wetland restoration activities. The DSS comprises geographic information system (GIS) spatial data themes, application programs that provide a cumulative analysis of the relative ability of sites to function as wetlands, and output data that are specific to a given restoration analysis scenario. The DSS input includes GIS data themes such as geomorphology, soils, land use, elevation, farmed wetlands, flood frequency, topographic depressions, streams, public lands, roads, and permanent water bodies, which can be used as spatial templates to define areal hydrologic settings. These GIS data themes can then be ranked and combined to estimate the relative suitability of a potential wetland restoration site, thereby, determining relative wetland equivalence on the landscape. The GIS applications used in this DSS perform the following three functions: assess the ecology (the Eco-Assessor); reclassify land-use in areas selected for restoration (the Tree-Translator); and generate output data to compare restoration scenarios (the Parameter-Generator). Areas selected for reforestation are translated (in the GIS) into ?forested? land use, and the tree species that are ?planted? on the landscape (in the DSS) either compose an ecologically optimal or an economically optimal community of tree species. Output from the DSS can be compared and analyzed by using economic, statistical, graphical, and tabular methods. Output data for seven selected scenarios were generated for the Yazoo Backwater Area and are presented as examples to illustrate the flexibility of the DSS to identify areas that meet restoration objectives.

Water-Resources Investigations Report↗
USGS2013

Potential climate change impacts on temperate forest ecosystem processes

Large changes in atmospheric CO2, temperature and precipitation are predicted by 2100, yet the long-term consequences for carbon, water, and nitrogen cycling in forests are poorly understood. We applied the PnET-CN ecosystem model to compare the long-term effects of changing climate and atmospheric CO2 on productivity, evapotranspiration, runoff, and net nitrogen mineralization in current Great Lakes forest types. We used two statistically downscaled climate projections, PCM B1 (warmer and wetter) and GFDL A1FI (hotter and drier), to represent two potential future climate and atmospheric CO2 scenarios. To separate the effects of climate and CO2, we ran PnET-CN including and excluding the CO2 routine. Our results suggest that, with rising CO2 and without changes in forest type, average regional productivity could increase from 67% to 142%, changes in evapotranspiration could range from –3% to +6%, runoff could increase from 2% to 22%, and net N mineralization could increase 10% to 12%. Ecosystem responses varied geographically and by forest type. Increased productivity was almost entirely driven by CO2 fertilization effects, rather than by temperature or precipitation (model runs holding CO2 constant showed stable or declining productivity). The relative importance of edaphic and climatic spatial drivers of productivity varied over time, suggesting that productivity in Great Lakes forests may switch from being temperature to water limited by the end of the century.

Michigan;Minnesota;Wisconsin↗
USGS1995

Land-cover sampling designs, data-collection procedures, and land-cover data for the Central Nebraska Basins, 1993-94

Within the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program, land-cover data are used in characterizing drainage areas upstream from surface-water sampling sites and areas selected for spatially distributed ground-water sampling. During the period of time when the initial 20 NAWQA study study-unit investigations were evaluating existing land-cover data, a Prototype 190 Conterminous U.S. land Cover Characteristics Data Set was produced by the Survey's EROS Data Center in Sioux Falls, South Dakota. As part of the Central Nebraska Basins (CNB) study-unit investigation, a method was developed to estimate the areal extent of the principal land-cover types within selected seasonally distinct land-cover (SDLC) regions defined in the 1990 prototype data set. This report describes the sampling designs and methods used to collect land-cover data in the CNB study unit. Data collected at 309 sampling sites during the summers of 1993 and 1994 are presented and statistically summarized. Eleven land-cover categories were quantified, including major field crops and broad noncropland cover types.

Open-File Report↗