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USGS2023

Comprehensive water-quality trend analysis for selected sites and constituents in the International Souris River Basin, Saskatchewan and Manitoba, Canada, and North Dakota, United States, 1970–2020

The Souris River Basin is an international basin in southeast Saskatchewan, north-central North Dakota, and southwest Manitoba. Sustained exceedances of water-quality objectives for total phosphorus, sodium, sulfate, total dissolved solids, and total iron have been reported since the late 1990s at the two binational sites on the Souris River (Souris River near Sherwood, North Dakota [U.S. Geological Survey station 05114000] and Souris River near Westhope, N. Dak. [U.S. Geological Survey station 05124000]). To understand conditions at the binational sites, it is important to understand water-quality changes on a basin-wide scale. Because streamflow is highly variable in the basin and changes in streamflow affect water-quality conditions, it is particularly important to use a trend-analysis method that accounts for changes in streamflow. Trends in water-quality concentrations can be affected by human-induced changes on the landscape or natural changes in land-runoff interactions that are driven by climate patterns and reflected by changes in streamflow (commonly referred to as “hydroclimatic variability”). In the primarily agricultural Souris River Basin, human-induced changes that are likely to affect trends are widespread changes in agricultural management such as fertilizer application, tilling practices, and crop types, as well as dam emplacement and artificial drainage. Around 1970, there was a long-term natural (hydroclimatic) change in the basin in which a significant transition from a dry climate state to a wet climate state resulted in higher streamflow in the basin. To assist the International Souris River Board in assessing current water-quality conditions in the Souris River Basin and exceedances of water-quality objectives at the binational sites, the U.S. Geological Survey, in cooperation with the International Joint Commission, completed a comprehensive analysis for selected ions, nutrients, and trace metals for many sites in the basin that included descriptive water-quality statistics, trend analysis using a trend method that considers interannual hydroclimatic variability, and an assessment of exceedances of the water-quality objectives for the binational sites. Water-quality and streamflow or reservoir inflow or outflow data were compiled for 34 sites (30 stream sites and four reservoir sites) and 23 constituents with established water-quality objectives from 1970 to 2020 in the Souris River Basin and were used for descriptive statistics and water-quality trend analysis. Median total dissolved solids, sulfate, and sodium concentrations were low in the headwaters of the Souris River and some of the highest median concentrations were measured in the upper basin. At main-stem Souris River sites, all median sodium concentrations were greater than the binational water-quality objective. Median total phosphorus concentrations in the Souris River Basin were highest in the headwaters of the Souris River and all sites had median concentrations greater than the water-quality objective. Median total iron concentrations were highly variable across the basin, and for most main-stem sites, median concentrations were greater than or equal to the water-quality objective. During the recent period (2009–19), the annual flow-averaged concentrations of total dissolved solids and sulfate increased for nearly all stream sites with most sites having mildly significant or significant increases. One-half of the sites had an annual flow-averaged geometric mean concentration greater than the total dissolved solids water-quality objective, and four sites had sulfate increases greater than 100 milligrams per liter. Trends in annual flow-averaged concentrations of sodium and chloride generally were small and nonsignificant. Most sites had concentrations greater than the sodium water-quality objective, whereas all sites had concentrations much less than the chloride water-quality objective. Annual flow-averaged geometric mean concentration of total phosphorus decreased for nearly all sites across the Souris River Basin, but all sites had concentrations greater than the total phosphorus water-quality objective for the entire period. Small and nonsignificant changes in annual flow-averaged geometric mean concentration of total iron were detected at all sites but the binational site at Sherwood, N. Dak., and by 2019 all sites had concentrations greater than the total iron water-quality objective. For the reservoir sites, during 2000–15, mostly significant increases for total dissolved solids, sulfate, and sodium were detected, whereas changes in total phosphorus and total iron were mixed. During the historical period (1976–2019), large and consistent increases in total dissolved solids and sulfate have occurred since the late 1980s, with the largest increases and the most sites with mildly significant or significant increases generally occurring during the middle period (1988–2005). Large and significant or mildly significant increases in sodium concentrations occurred at eight of 10 sites in the middle period (1988–2005), and by the late period (2005–19) changes were small and nonsignificant. Similar to other basins in the region, such as the Red River of the North and Heart River, large and overall consistent increases since the late 1980s in total dissolved solids and sulfate in the Souris River Basin suggest that long-term natural (hydroclimatic) processes are large contributors to increases in the concentration of salts in streams and reservoirs associated with the onset of wetter conditions. The concurrent increases in sulfate and sodium concentrations at all sites during the middle period (1988–2005) suggest that sodium-sulfate evaporite dissolution may be a factor contributing to increases. Total phosphorus concentrations oscillated between increasing and decreasing during the historical period, with concentrations increasing during the first trend period (1976–88) and decreasing in the fourth trend period (2009–19) to the lowest flow-averaged geometric mean concentration by 2019 for most sites. During the historical period, changes in total iron concentrations were mostly nonsignificant and generally small, and variability in total iron concentrations likely affected the ability to detect statistically significant changes in concentration. The probability of exceeding the water-quality objective for total dissolved solids, sulfate, and sodium increased between 1976 and 2019 for the binational sites, especially for sulfate, which more than doubled for Souris River near Sherwood, N. Dak. and increased more than seven times for Souris River near Westhope, N. Dak. Total phosphorus and total iron concentrations for the binational sites were likely to exceed the water-quality objective for most of the year, but seasonal patterns of total phosphorus and total iron concentrations were different between the sites, suggesting that different factors may affect concentrations at different times of the year. For sodium, total phosphorus, and total iron, exceedance of the water-quality objective most of the time is not unexpected given that the flow-averaged geometric mean concentration for these three constituents for most sites across the basin are greater than the water-quality objective for most of the period. If natural processes are affecting total dissolved solids and sulfate concentrations, concentrations would be expected to vary with time, and as a result, extended periods of concentrations greater or less than the water-quality objective are likely to occur depending upon climatic conditions. A better understanding of the state of water quality across the Souris River Basin is beneficial to understanding and interpreting water-quality conditions at the two Souris River binational sites. The most consistent spatial and temporal change observed for this study was large and consistent increases in sulfate and total dissolved solids among tributary and main-stem sites since the late 1980s. For sulfate and total dissolved solids, wetter climatic conditions combined with naturally occurring and abundant sources of sulfate likely contributed to sustained exceedances of water-quality objectives in recent decades, and extended periods of concentrations greater than or less than the water-quality objective are likely to occur depending on climatic conditions. For sodium, total iron, and total phosphorus, sustained exceedances of the current water-quality objective likely will continue because most sites across the basin had flow-averaged geometric mean concentrations greater than the water-quality objective; and during the 43-year period of analysis, regardless of climatic conditions, exceedances were consistently greater than the water-quality objective. Further investigation into the factors causing increasing sulfate concentrations and a better understanding of reservoir dynamics would enhance the understanding of changes in water-quality conditions in the Souris River Basin. The basin-wide approach of this report provided an improved understanding of water-quality conditions in the Souris River Basin, and results can be used to inform the current water-quality objectives, inform potential changes to water management in the basin, and serve as a starting point for tracking future progress. Gaps in understanding of water-quality conditions can be closed through continued monitoring and further investigation into causes behind changes in water-quality conditions identified in this report.

Manitoba, North Dakota, Saskatchewan↗

USGS2009

SSTL UK-DMC SLIM-6 data quality assessment

Satellite data from the Surrey Satellite Technology Limited (SSTL) United Kingdom (UK) Disaster Monitoring Constellation (DMC) were assessed for geometric and radiometric quality. The UK-DMC Surrey Linear Imager 6 (SLIM-6) sensor has a 32-m spatial resolution and a ground swath width of 640 km. The UK-DMC SLIM-6 design consists of a three-band imager with green, red, and near-infrared bands that are set to similar bandpass as Landsat bands 2, 3, and 4. The UK-DMC data consisted of imagery registered to Landsat orthorectified imagery produced from the GeoCover program. Relief displacements within the UK-DMC SLIM-6 imagery were accounted for by using global 1-km digital elevation models available through the Global Land One-km Base Elevation (GLOBE) Project. Positional accuracy and relative band-to-band accuracy were measured. Positional accuracy of the UK-DMC SLIM-6 imagery was assessed by measuring the imagery against digital orthophoto quadrangles (DOQs), which are designed to meet national map accuracy standards at 1 : 24 000 scales; this corresponds to a horizontal root-mean-square accuracy of about 6 m. The UK-DMC SLIM-6 images were typically registered to within 1.0-1.5 pixels to the DOQ mosaic images. Several radiometric artifacts like striping, coherent noise, and flat detector were discovered and studied. Indications are that the SSTL UK-DMC SLIM-6 data have few artifacts and calibration challenges, and these can be adjusted or corrected via calibration and processing algorithms. The cross-calibration of the UK-DMC SLIM-6 and Landsat 7 Enhanced Thematic Mapper Plus was performed using image statistics derived from large common areas observed by the two sensors.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS1995

Sediment oxygen demand in the lower Willamette River, Oregon, 1994

An investigation of sediment oxygen demand (SOD) at the interface of the stream and stream bed was performed in the lower Willamette River (river mile 51 to river mile 3) during August, 1994, as part of a cooperative project with the Oregon Department of Environmental Quality. The primary goals of the investigation were to measure the spatial variability of SOD in the lower Willamette River and to relate SOD to bottom-sediment characteristics. The SOD chambers used in the study were open-bottomed, opaque plastic cylinders that were seated and sealed on the river bottom by scuba divers. When seated, the chambers contained 52 liters of isolated river water, which was slowly recirculated for at least 2 hours over 0.225 square meters of relatively undisturbed bottom sediment. These chambers could not be deployed in areas with gravels and cobbles, which represent about 55 percent of the study area above Willamette Falls and 30 percent of the river below Willamette Falls. Sediment oxygen demand is commonly reported as grams of oxygen consumed per square meter of bottom sediment per day (g/m2 p day). The measured SOD rates, corrected to a temperature of 20 degrees C, ranged from 1.3 to 4.1 g/m2' day in the lower Willamette River. The SOD measured above and below Willamette Falls averaged 2.0 and 2.1 g/m2 ' day, respectively. After adjusting for the amount of bottom material composed of gravels and cobbles, the best estimates for reachwide SOD rates above and below Willamette Falls are 1.4 (+ 0.5) and 1.8 (+ 0.3) g/m2' day, respectively. Sediment samples were collected near each chamber and analyzed for percent water, percent sand, and percent organics. The sand content ranged from 0.1 to 6.2 percent and averaged 1.8 percent. The organic content ranged from 1.4 to 9.6 and averaged 5.6 percent. No statistically significant correlations were found between these sediment characteristics and sediment oxygen demand.

Oregon↗

USGS2015

Elk monitoring in Mount Rainier and Olympic national parks: 2008-2011 synthesis report

In 2008, the USGS collaborated with the NPS, the Muckleshoot and Puyallup Indian Tribes, and WDFW to develop a protocol tor monitor changes in abundance, population composition, and spatial distribution of elk on summer ranges in MORA and OLYM and winter ranges in OLYM. We developed double-observer sightability (DO-S) models that adjusted raw counts of elk as a function of factors influencing detection probabilities from the air, e.g. vegetation, elk group size, light, elk activity, and pilot experience. We plan to develop DO-S models for both MORA and OLYM summer ranges, but due to radiotelemetry collar failures in OLYM, we do not yet have enough data to model detection probabilities in OLYM. We analyzed results of the first 4 years of elk monitoring conducted under the new protocol from 2008-2011. Objectives of this first synthetic analysis are to: • update the DO-S model for MORA aerial survey results • examine abundance, composition, and distribution of elk trends in MORA summer ranges • establish a baseline of counts, population composition, and distribution of elk in OLYM summer ranges • examine trends in counts and distribution of elk in OLYM low-elevation winter ranges during early spring • determine environmental factors influencing abundance and composition of elk in selected MORA summer ranges and unadjusted counts of elk on selected OLYM winter ranges • review progress in developing a DO-S model for OLYM elk surveys • examine aerial survey operations and provide suggestions for future surveys. There was no trend in elk numbers in the N. Rainier TCA from 2008-2011; the trend in the S. Rainier TCA was not statistically significant but increased 3.3%/year. Maximum counts increased in the N. Rainier TCA ~6%/year. Maximum counts in the S. Rainier TCA increased at a rate of 17% annually. Due to failed radiocollars, weather, and other problems, we completed surveys in 2 of 5 OLYM summer range TCAs; no trend data are available. In OLYM winter ranges, we surveyed the Hoh TCA during early spring 2008-10 and of the S. Fork Hoh and Queets in 2008 and 2010. No surveys were done for early-spring counts in 2011 and 2012 due to high snowfall and lack of funding. Legacy early-spring surveys in OLYM since 1985 allowed us to assess trends in counts in the early-spring TCAs from 1985-2010. Counts of elk in the early-spring TCAs declined: 63% in the S. Fork Hoh, 18% in the Hoh, and 22% in the Queets Valley. We continue to develop and improve the DO-S model for application to OLYM summer surveys. In the next synthesis report, we will update findings with additional data following the 2015 field season, based on 8 years of survey results; it will be a more complete analysis of elk population trends.

Washington↗

USGS2019

Spatial and temporal variability of fish assemblages in acidified streams: Implications for long-term monitoring

Numerous studies have established strong linkages between acid deposition, soil and surface-water acidification, and toxicity to aquatic biota. Little is known however, about the effects of acidification on fish assemblages in headwater streams because they are highly variable, and pre-acidification data are often lacking. The primary purpose of this study was to describe spatial and interannual (temporal) variability of fish assemblages in headwater streams affected by acidification so that future recovery targets and monitoring strategies can be established. Fish communities and water chemistry were sampled at 48 headwater streams in the Western Adirondack Mountains of New York during the summers of 2014 to 2016 to characterize the present-day condition of water quality and local fish assemblages. Additionally, data from six Adirondack streams that were sampled annually from 2014-16 were combined with data from seven streams in the Catskill Mountain region sampled annually for three or more years for an analysis of temporal variability. Inorganic monomeric aluminum concentrations (Ali, the toxic form of Al) were less than 1.0 µmol L-1, between 1 and 2 µmol L-1, and greater than 2 µmol L-1 in 79%, 13%, and 8% of the 48 Adirondack streams. Richness, abundance, and biomass of fish assemblages were negatively related to Ali concentrations. In streams with Ali concentrations less than 1.0 µmol L-1, species richness, density, and biomass averaged 2.0 species, 444.2 fish/0.1 ha, and 1924.4 g/0.1 ha, respectively, and the density and biomass of Brook Trout populations averaged 280.8 fish/0.1 ha and 1384.0 g/0.1 ha. These values may provide a reasonable approximation of fish community condition prior to anthropogenic acidification and can be used as targets for assessing future recovery of acidified streams. A power analysis that considered 21 fish metrics indicated a strong negative relationship between interannual metric variability and statistical power for detecting change over time. Large differences were identified in the sample size necessary to achieve adequate power (0.8) depending on the metric utilized. In general, greater statistical power was obtained from metrics based on entire fish communities and from metrics standardized by reach length or sampling effort. Given the variability observed in our dataset, most metrics could detect a change of 30% with moderate effort, suggesting this may be an appropriate goal for future monitoring. Together, knowledge of biological recovery targets and the statistical power obtained from various fish metrics can be used to develop the most effective strategies for monitoring and assessing biological recovery in New York streams.

New York↗

USGS2022

Hydrogeologic characteristics of Hourglass and New Years Cave Lakes at Jewel Cave National Monument, South Dakota, from water-level and water-chemistry data, 2015–21

Jewel Cave National Monument is in the western Black Hills of South Dakota and contains an extensive cave network, including various subterranean water bodies (cave lakes) that are believed to represent the regionally important Madison aquifer. Recent investigations have sought to improve understanding of hydrogeologic characteristics of cave lakes in Jewel Cave. The U.S. Geological Survey, in cooperation with the National Park Service, collected water-level and water-chemistry data within and near Jewel Cave to better understand groundwater interactions in Jewel Cave and to evaluate recharge characteristics of cave lakes. Continuous water-level data were collected at two cave lakes (Hourglass and New Years Lakes) from 2018 to 2021, and discrete measurements were collected by National Park Service staff from 2015 to 2021. Water samples were collected from one stream, one rain collector, three springs, and two cave lakes. The approach for this study included comparing water-level data collected from two cave lakes to historical climate data and using multivariate statistical analyses to evaluate water samples collected during this study and from previous investigations. This study builds on interpretations from previous investigations that collected similar datasets and performed similar analyses. Hydrographs of Hourglass and News Years Lakes from 2015 to 2021 demonstrated the variability of groundwater levels in Jewel Cave in response to dry and wet climate conditions. Hourglass Lake displayed small (up to 4.8 feet), gradual water-level changes, whereas New Years Lake displayed relatively large (up to at least 27.5 feet) and rapid water-level changes. Hourglass and New Years Lakes are about 0.4 mile apart at the land surface, and the water-level elevation between the lakes varied from 61 to 93.5 feet from 2016 to 2021. The proximity and relatively small elevation difference of Hourglass and New Years Lakes indicated different recharge sources and (or) mechanisms were responsible for hydrograph dissimilarities. Water-level changes at Hourglass Lake were similar to water-level changes at a well completed in the Madison aquifer about 9 miles south of Jewel Cave National Monument, which indicated Hourglass Lake may be recharged similar to the regional Madison aquifer along outcrops north of Jewel Cave. New Years Lake displayed almost no similarities to the well completed in the Madison aquifer—indicating a more direct connection to local recharge rather than solely from outcrops recharging the regional Madison aquifer. Results from multivariate statistical analyses of water-chemistry data were used to evaluate recharge observations from water-level data. The water chemistry of Hourglass Lake indicated its water was chemically more similar to precipitation than other groundwater sites sampled. A conceptual karst recharge model indicated that the dominant recharge source to Hourglass Lake was diffuse allogenic recharge from vertical movement of infiltrated precipitation through vertical or near-vertical fractures that extend through the Minnelusa Formation and unsaturated zone of the Madison Limestone. The water chemistry of New Years Lake was chemically similar to Hell Canyon Creek about 0.2 mile from New Years Lake at the land surface. Streamflow loss zones (concentrated allogenic recharge) along Hell Canyon Creek have not been mapped, but their presence in the Jewel Cave area has been speculated by previous investigations. A fault observed in the cave ceiling above New Years Lake by National Park Service staff could provide a natural conduit for direct recharge from Hell Canyon Creek to New Years Lake if the fault is extensive. Additional water-chemistry and water-level data, as well as streamflow data upstream and downstream of the potential streamflow loss zone along Hell Canyon Creek, are needed to prove the presence of this loss zone and discern further correlations between streamflow and water levels in New Years Lake. Observations from previous investigations and this study indicated recharge to Jewel Cave is complex and occurs on various timescales that are affected temporally by precipitation patterns and spatially by hydrologic connection with the overlying Minnelusa aquifer of the Minnelusa Formation.

South Dakota↗

USGS2018

Spatial capture–recapture with partial identity: An application to camera traps

Camera trapping surveys frequently capture individuals whose identity is only known from a single flank. The most widely used methods for incorporating these partial identity individuals into density analyses discard some of the partial identity capture histories, reducing precision, and, while not previously recognized, introducing bias. Here, we present the spatial partial identity model (SPIM), which uses the spatial location where partial identity samples are captured to probabilistically resolve their complete identities, allowing all partial identity samples to be used in the analysis. We show that the SPIM outperforms other analytical alternatives. We then apply the SPIM to an ocelot data set collected on a trapping array with double-camera stations and a bobcat data set collected on a trapping array with single-camera stations. The SPIM improves inference in both cases and, in the ocelot example, individual sex is determined from photographs used to further resolve partial identities—one of which is resolved to near certainty. The SPIM opens the door for the investigation of trapping designs that deviate from the standard two camera design, the combination of other data types between which identities cannot be deterministically linked, and can be extended to the problem of partial genotypes.

Annals of Applied Statistics↗

USGS2017

Analysis of the variability in ground-motion synthesis and inversion

In almost all past inversions of large-earthquake ground motions for rupture behavior, the goal of the inversion is to find the “best fitting” rupture model that predicts ground motions which optimize some function of the difference between predicted and observed ground motions. This type of inversion was pioneered in the linear-inverse sense by Olson and Apsel (1982), who minimized the square of the difference between observed and simulated motions (“least squares”) while simultaneously minimizing the rupture-model norm (by setting the null-space component of the rupture model to zero), and has been extended in many ways, one of which is the use of nonlinear inversion schemes such as simulated annealing algorithms that optimize some other misfit function. For example, the simulated annealing algorithm of Piatanesi and others (2007) finds the rupture model that minimizes a “cost” function which combines a least-squares and a waveform-correlation measure of misfit. All such inversions that look for a unique “best” model have at least three problems. (1) They have removed the null-space component of the rupture model—that is, an infinite family of rupture models that all fit the data equally well have been narrowed down to a single model. Some property of interest in the rupture model might have been discarded in this winnowing process. (2) Smoothing constraints are commonly used to yield a unique “best” model, in which case spatially rough rupture models will have been discarded, even if they provide a good fit to the data. (3) No estimate of confidence in the resulting rupture models can be given because the effects of unknown errors in the Green’s functions (“theory errors”) have not been assessed. In inversion for rupture behavior, these theory errors are generally larger than the data errors caused by ground noise and instrumental limitations, and so overfitting of the data is probably ubiquitous for such inversions. Recently, attention has turned to the inclusion of theory errors in the inversion process. Yagi and Fukahata (2011) made an important contribution by presenting a method to estimate the uncertainties in predicted large-earthquake ground motions due to uncertainties in the Green’s functions. Here we derive their result and compare it with the results of other recent studies that look at theory errors in a Bayesian inversion context particularly those by Bodin and others (2012), Duputel and others (2012), Dettmer and others (2014), and Minson and others (2014). Notably, in all these studies, the estimates of theory error were obtained from theoretical considerations alone; none of the investigators actually measured Green’s function errors. Large earthquakes typically have aftershocks, which, if their rupture surfaces are physically small enough, can be considered point evaluations of the real Green’s functions of the Earth. Here we simulate smallaftershock ground motions with (erroneous) theoretical Green’s functions. Taking differences between aftershock ground motions and simulated motions to be the “theory error,” we derive a statistical model of the sources of discrepancies between the theoretical and real Green’s functions. We use this model with an extended frequency-domain version of the time-domain theory of Yagi and Fukahata (2011) to determine the expected variance 2 τ caused by Green’s function error in ground motions from a larger (nonpoint) earthquake that we seek to model. We also differ from the above-mentioned Bayesian inversions in our handling of the nonuniqueness problem of seismic inversion. We follow the philosophy of Segall and Du (1993), who, instead of looking for a best-fitting model, looked for slip models that answered specific questions about the earthquakes they studied. In their Bayesian inversions, they inductively derived a posterior probability-density function (PDF) for every model parameter. We instead seek to find two extremal rupture models whose ground motions fit the data within the error bounds given by 2 τ , as quantified by using a chi-squared test described below. So, we can ask questions such as, “What are the rupture models with the highest and lowest average rupture speed consistent with the theory errors?” Having found those models, we can then say with confidence that the true rupture speed is somewhere between those values. Although the Bayesian approach gives a complete solution to the inverse problem, it is computationally demanding: Minson and others (2014) needed 1010 forward kinematic simulations to derive their posterior probability distribution. In our approach, only about107 simulations are needed. Moreover, in practical application, only a small set of rupture models may be needed to answer the relevant questions—for example, determining the maximum likelihood solution (achievable through standard inversion techniques) and the two rupture models bounding some property of interest. The specific property that we wish to investigate is the correlation between various rupturemodel parameters, such as peak slip velocity and rupture velocity, in models of real earthquakes. In some simulations of ground motions for hypothetical large earthquakes, such as those by Aagaard and others (2010) and the Southern California Earthquake Center Broadband Simulation Platform (Graves and Pitarka, 2015), rupture speed is assumed to correlate locally with peak slip, although there is evidence that rupture speed should correlate better with peak slip speed, owing to its dependence on local stress drop. We may be able to determine ways to modify Piatanesi and others’s (2007) inversion’s “cost” function to find rupture models with either high or low degrees of correlation between pairs of rupture parameters. We propose a cost function designed to find these two extremal models.

Open-File Report↗

USGS2007

Summary of selected U.S. Geological survey data on domestic well water quality for the Centers for Disease Control's National Environmental Public Health Tracking Program

About 10 to 30 percent of the population in most States uses domestic (private) water supply. In many States, the total number of people served by domestic supplies can be in the millions. The water quality of domestic supplies is inconsistently regulated and generally not well characterized. The U.S. Geological Survey (USGS) has two water-quality data sets in the National Water Information System (NWIS) database that can be used to help define the water quality of domestic-water supplies: (1) data from the National Water-Quality Assessment (NAWQA) Program, and (2) USGS State data. Data from domestic wells from the NAWQA Program were collected to meet one of the Program's objectives, which was to define the water quality of major aquifers in the United States. These domestic wells were located primarily in rural areas. Water-quality conditions in these major aquifers as defined by the NAWQA data can be compared because of the consistency of the NAWQA sampling design, sampling protocols, and water-quality analyses. The NWIS database is a repository of USGS water data collected for a variety of projects; consequently, project objectives and analytical methods vary. This variability can bias statistical summaries of contaminant occurrence and concentrations; nevertheless, these data can be used to define the geographic distribution of contaminants. Maps created using NAWQA and USGS State data in NWIS can show geographic areas where contaminant concentrations may be of potential human-health concern by showing concentrations relative to human-health water-quality benchmarks. On the basis of national summaries of detection frequencies and concentrations relative to U.S. Environmental Protection Agency (USEPA) human-health benchmarks for trace elements, pesticides, and volatile organic compounds, 28 water-quality constituents were identified as contaminants of potential human-health concern. From this list, 11 contaminants were selected for summarization of water-quality data in 16 States (grantee States) that were funded by the Environmental Public Health Tracking (EPHT) Program of the Centers for Disease Control and Prevention (CDC). Only data from domestic-water supplies were used in this summary because samples from these wells are most relevant to human exposure for the targeted population. Using NAWQA data, the concentrations of the 11 contaminants were compared to USEPA human-health benchmarks. Using NAWQA and USGS State data in NWIS, the geographic distribution of the contaminants were mapped for the 16 grantee States. Radon, arsenic, manganese, nitrate, strontium, and uranium had the largest percentages of samples with concentrations greater than their human-health benchmarks. In contrast, organic compounds (pesticides and volatile organic compounds) had the lowest percentages of samples with concentrations greater than human-health benchmarks. Results of data retrievals and spatial analysis were compiled for each of the 16 States and are presented in State summaries for each State. Example summary tables, graphs, and maps based on USGS data for New Jersey are presented to illustrate how USGS water-quality and associated ancillary geospatial data can be used by the CDC to address goals and objectives of the EPHT Program.

Scientific Investigations Report↗

USGS2024

Evaluation of metrics and thresholds for use in national-scale river harmful algal bloom assessments

The spatiotemporal distribution of harmful algal blooms (HABs) in rivers remains poorly understood, and there is an urgent need to develop a consistent set of metrics to better document HAB occurrences and forecast future events. Using data from seven sites in the Illinois River Basin, we computed metrics focused on HAB conditions related to excess algal growth and hypoxia. Daily mean chlorophyll and dissolved oxygen (DO) concentrations, gross primary productivity (GPP), and net ecosystem productivity (NEP) rates, focused on water quality status, identifying the timing of the transition from a clear-water to an algal dominated state. Early warning indicators (EWIs), the first-order autoregressive process (Ar1) and standard deviation (SD) of chlorophyll concentrations, focused on future events, forecasting blooms. Metrics were compared to either literature-derived or statistical-based thresholds and were normalized by total number of daily samples for an exceedance rate. Exceedances of a daily mean chlorophyll concentration averaged 50 % across all sites using a 10 µg L −1 threshold but increasing the threshold to 50 μg L −1 reduced the average exceedance rate to 5 %. The average exceedance rate for GPP (∼8 g O 2 m 2 d −1 threshold) was 15 %, similar to the daily amplitude DO concentration (∼3 mg L −1 threshold), but the average for NEP (0 g O 2 m 2 d −1 threshold) was higher, at 28 %. The number of days with at least 1 continuous DO concentration below the threshold of 5, 3, or 2 mg L −1 , had basin wide exceedance rates of 9 %, 3 %, and 2 %, respectively. Thresholds for EWIs, Ar1 and SD, were exceeded at 5 of the 7 sites with high chlorophyll concentrations and GPP rates. The correlation between proxies for algal biomass (chlorophyll concentration) and productivity (GPP) was strongest for sites in the middle region of the basin, with R 2 values between 0.54 and 0.74. Although, cyanotoxin concentrations are the most commonly used metrics by states to define an inland water HAB, there is a paucity of publicly available data. The wider availability of chlorophyll and oxygen data combined with the results from this study suggest that biomass and productivity state and event-based metrics may be a promising way to assess and predict the vulnerability of rivers to some of the deleterious effects of HABs at broad spatial scales.

Illinois, Indiana, Wisconsin↗

USGS2023

A review of N-mixture models

N-mixture models were born in 2004 of the necessity to model animal population size from point counts with imperfect detection of individuals, where capture-recapture methods are infeasible. Initially developed for applications where population size was assumed constant, N-mixture models were extended in 2011 to include population dynamics, allowing application to populations whose size fluctuates during the study. A further extension in 2014 accommodates populations with multiple “states” such as age class or sex. More recent extensions model spatial movement of animals among habitat patches or the spatial spread of infectious disease in a human population. The core idea underlying this class of models is a hierarchical structure, where the observation model is defined conditional on the model for true abundance. This hierarchy allows researchers to incorporate information about observation and abundance processes, while permitting distinct inferences about elements affecting detection and those affecting abundance. Another benefit of the hierarchical approach is the ability to accommodate many existing sampling protocols such as removal sampling and distance sampling. One drawback to N-mixture models is that since they estimate both abundance and detection from replicated but unmarked counts, model parameters may not be clearly identifiable. A second drawback is that when observed counts are large, calculating the N-mixture likelihood is computationally infeasible. This difficulty motivated an approximate likelihood based on the normal approximation to the binomial. The normal approximation provides a diagnostic of parameter estimability based on the closed-form expression of the Fisher information matrix for a multivariate normal likelihood.

WIREs Computational Statistics↗

USGS2006

Hierarchical models of animal abundance and occurrence

Much of animal ecology is devoted to studies of abundance and occurrence of species, based on surveys of spatially referenced sample units. These surveys frequently yield sparse counts that are contaminated by imperfect detection, making direct inference about abundance or occurrence based on observational data infeasible. This article describes a flexible hierarchical modeling framework for estimation and inference about animal abundance and occurrence from survey data that are subject to imperfect detection. Within this framework, we specify models of abundance and detectability of animals at the level of the local populations defined by the sample units. Information at the level of the local population is aggregated by specifying models that describe variation in abundance and detection among sites. We describe likelihood-based and Bayesian methods for estimation and inference under the resulting hierarchical model. We provide two examples of the application of hierarchical models to animal survey data, the first based on removal counts of stream fish and the second based on avian quadrat counts. For both examples, we provide a Bayesian analysis of the models using the software WinBUGS.

Journal of Agricultural, Biological, and Environme↗

USGS2014

Geospatial association between adverse birth outcomes and arsenic in groundwater in New Hampshire, USA

There is increasing evidence of the role of arsenic in the etiology of adverse human reproductive outcomes. Because drinking water can be a major source of arsenic to pregnant women, the effect of arsenic exposure through drinking water on human birth may be revealed by a geospatial association between arsenic concentration in groundwater and birth problems, particularly in a region where private wells substantially account for water supply, like New Hampshire, USA. We calculated town-level rates of preterm birth and term low birth weight (term LBW) for New Hampshire, by using data for 1997–2009 stratified by maternal age. We smoothed the rates by using a locally weighted averaging method to increase the statistical stability. The town-level groundwater arsenic probability values are from three GIS data layers generated by the US Geological Survey: probability of local groundwater arsenic concentration >1 µg/L, probability >5 µg/L, and probability >10 µg/L. We calculated Pearson’s correlation coefficients ( r ) between the reproductive outcomes (preterm birth and term LBW) and the arsenic probability values, at both state and county levels. For preterm birth, younger mothers (maternal age <20) have a statewide r = 0.70 between the rates smoothed with a threshold = 2,000 births and the town mean arsenic level based on the data of probability >10 µg/L; for older mothers, r = 0.19 when the smoothing threshold = 3,500; a majority of county level r values are positive based on the arsenic data of probability >10 µg/L. For term LBW, younger mothers (maternal age <25) have a statewide r = 0.44 between the rates smoothed with a threshold = 3,500 and town minimum arsenic concentration based on the data of probability >1 µg/L; for older mothers, r = 0.14 when the rates are smoothed with a threshold = 1,000 births and also adjusted by town median household income in 1999, and the arsenic values are the town minimum based on probability >10 µg/L. At the county level for younger mothers, positive r values prevail, but for older mothers, it is a mix. For both birth problems, the several most populous counties—with 60–80% of the state’s population and clustering at the southwest corner of the state—are largely consistent in having a positive r across different smoothing thresholds. We found evident spatial associations between the two adverse human reproductive outcomes and groundwater arsenic in New Hampshire, USA. However, the degree of associations and their sensitivity to different representations of arsenic level are variable. Generally, preterm birth has a stronger spatial association with groundwater arsenic than term LBW, suggesting an inconsistency in the impact of arsenic on the two reproductive outcomes. For both outcomes, younger maternal age has stronger spatial associations with groundwater arsenic.

New Hampshire↗

USGS2005

Candidate-penetrative-fracture mapping of the Grand Canyon area, Arizona, from spatial correlation of deep geophysical features and surficial lineaments

Some aquifers of the southwestern Colorado Plateaus Province are deeply buried and overlain by several impermeable shale layers, and so recharge to the aquifer probably is mainly by seepage down penetrative-fracture systems. The purpose of this 2-year study, sponsored by the U.S. National Park Service, was to map candidate deep penetrative fractures over a 120,000-km2 area, using gravity and aeromagnetic-anomaly data together with surficial-fracture data. The study area was on the Colorado Plateau south of the Grand Canyon and west of Black Mesa; mapping was carried out at a scale of 1:250,000. The resulting database constitutes a spatially registered estimate of deep-fracture locations. Candidate penetrative fractures were located by spatial correlation of horizontal- gradient and analytic-signal maximums of gravity and magnetic anomalies with major surficial lineaments obtained from geologic, topographic, side-looking-airborne-radar, and satellite imagery. The maps define a subset of candidate penetrative fractures because of limitations in the data coverage and the analytical technique. In particular, the data and analytical technique used cannot predict whether the fractures are open or closed. Correlations were carried out by using image-processing software, such that every pixel on the resulting images was coded to uniquely identify which datasets are correlated. The technique correctly identified known and many new deep fracture systems. The resulting penetrative-fracture-distribution maps constitute an objectively obtained, repeatable dataset and a benchmark from which additional studies can begin. The maps also define in detail the tectonic fabrics of the southwestern Colorado Plateaus Province. Overlaying the correlated lineaments on the normalized-density-of-vegetation-index image reveals that many of these lineaments correlate with the boundaries of vegetation zones in drainages and canyons and so may be controlling near-surface water availability in some places. Many derivative products can be produced from the database, such as fracture-density-estimate maps, and maps with the number of correlations color-coded to estimate the possible quality of correlation. The database contained in this report is designed to be used in a geographic information system and image-processing systems, and most data layers are in georeferenced tagged image format (Geotiff) or ARC grids. The report includes 163 map plates and various metadata, supporting, and statistical diagram files.

Data Series↗

USGS2010

Status and distribution of mangrove forests of the world using earth observation satellite data

Aim Our scientific understanding of the extent and distribution of mangrove forests of the world is inadequate. The available global mangrove databases, compiled using disparate geospatial data sources and national statistics, need to be improved. Here, we mapped the status and distributions of global mangroves using recently available Global Land Survey (GLS) data and the Landsat archive. Methods We interpreted approximately 1000 Landsat scenes using hybrid supervised and unsupervised digital image classification techniques. Each image was normalized for variation in solar angle and earth–sun distance by converting the digital number values to the top-of-the-atmosphere reflectance. Ground truth data and existing maps and databases were used to select training samples and also for iterative labelling. Results were validated using existing GIS data and the published literature to map ‘true mangroves’. Results The total area of mangroves in the year 2000 was 137,760 km2 in 118 countries and territories in the tropical and subtropical regions of the world. Approximately 75% of world's mangroves are found in just 15 countries, and only 6.9% are protected under the existing protected areas network (IUCN I-IV). Our study confirms earlier findings that the biogeographic distribution of mangroves is generally confined to the tropical and subtropical regions and the largest percentage of mangroves is found between 5° N and 5° S latitude. Main conclusions We report that the remaining area of mangrove forest in the world is less than previously thought. Our estimate is 12.3% smaller than the most recent estimate by the Food and Agriculture Organization (FAO) of the United Nations. We present the most comprehensive, globally consistent and highest resolution (30 m) global mangrove database ever created. We developed and used better mapping techniques and data sources and mapped mangroves with better spatial and thematic details than previous studies.

Global Ecology and Biogeography↗

USGS2000

Design of a shallow ground-water network to monitor agricultural chemicals, Lake Wales Ridge, central Florida

Extensive agricultural land use and dynamic hydraulic connections between the land surface and ground-water resources render many of Florida's aquifers vulnerable to chemical contamination. In these areas, there is a need to monitor shallow ground water for agricultural chemicals to evaluate potential migration of the chemicals to the subsurface and to deeper aquifers, and to assess the effects of agricultural practices on ground-water quality. Historically, efforts to monitor water-table aquifers have been minimal compared with monitoring deeper aquifers used for municipal drinking-water supply. The Florida Department of Agriculture and Consumer Services has proposed the establishment of long-term, water-quality networks to monitor shallow ground water in agricultural areas of Florida. These networks will bridge the current information gap between local-scale short-duration field studies, which are required for pesticide licensing, and statewide monitoring of deeper ground-water resources. Laboratory (experimental) and short-term field evaluations of the transport of agricultural chemicals to the subsurface contain some degree of uncertainty due to widespread variations in environmental conditions. The proposed regional-scale shallow ground-water networks will serve as "early warning" networks to avoid contamination of ground-water resources. The objectives of these shallow ground-water networks are to provide information for early detection of pesticides and nitrate in the subsurface, and for evaluating temporal trends in concentrations in relation to changes in land use and agricultural practices. Information on trends is important to the U.S. Environmental Protection Agency, State agencies, and agricultural managers, and is an integral part of Florida's Pesticide Management Plan, which evaluates the effectiveness of implementing "best management practices" to minimize environmental impacts. Lake Wales Ridge in Polk and Highlands Counties has been identified by the Florida Department of Agriculture and Consumer Services as a pilot study area for implementing a regional shallow ground-water network. Information gained from designing the Lake Wales Ridge Network will be used to develop plans as similar networks are considered for other areas of Florida. Lake Wales Ridge is heavily utilized for citrus production, but the well-drained, clean sands underlying the region, coupled with a hydraulic connection with deeper karst formations, render the area extremely vulnerable to the transport and migration of agricultural chemicals within the subsurface. The network design for Lake Wales Ridge was developed on the basis of the objectives of monitoring, factors affecting aquifer vulnerability, probability (statistical) sampling theory, and specifications regarding well construction, sampling, and laboratory analysis. The network will provide estimates of regional pesticide and nitrate concentrations in targeted ground water, monitor for trends over time, and will provide baseline, regional-scale information. The areas targeted for sampling were citrus groves located on soils classified as vulnerable to leaching of agricultural chemicals, and ground water in close proximity to the water table. The duration of monitoring is planned to be long term. Chemicals targeted for monitoring include selected nutrients, trace elements, and pesticides used for citrus management. Standardization of field sampling and laboratory methods, and construction of a computerized data-base repository will be important for long-term utility of the data. The proposed network design consists of existing and newly drilled wells. Existing wells were evaluated as candidates for the network based on location and well-construction specifications for water-quality monitoring. Using probability selection techniques, new well locations were selected in areas that lacked adequate existing wells. Implementation of the network will occur in phases. Quarterly sampling of 13 Phase I wells commenced in April 1999. An additional 11 Phase II wells were added to the network in April 2000. Proposed locations have been identified for 8 Phase III wells. Future topics for study include a regional water-quality analysis, a network design evaluation, and consideration of local-scale studies needed to support regional monitoring efforts. An analysis of historical water-quality data for Lake Wales Ridge, including Phase I wells, is needed for the purpose of examining trends, providing a preliminary description of spatial and short-term variability in water quality, and evaluating the proposed network design for cost effectively meeting program objectives. Local-scale, process-oriented studies are needed to provide important information for evaluating regional water-quality data. Coordination between individuals conducting such local-scale studies and those interpreting regional sampling results will be considered as a component of the network design, and will require coordination between multiple agencies.

Florida↗

USGS2020

A within-season approach for detecting early crop stage of corn and soybean using high temporal and spatial resolution imagery

Crop emergence is a critical stage for crop development and crop growth modeling. Mapping crop emergence using remote sensing data is challenging. Previous remote sensing phenology algorithms showed that crop stages could be detected around the V3-V4 (3 to 4 established leaves) vegetative stage. Traditional approaches have a strong assumption regarding the temporal evolution of plant growth and normally require a complete growth period of observations to define seasonal changes. Most approaches were not designed for the within-season mapping in the early growing season. In the current paper, we developed a new within-season emergence (WISE) approach to mapping crop green-up date using satellite observations during early growth stages. The approach was first optimized using high spatiotemporal resolution (10 m, 2 day revisit) imagery from the Vegetation and Environment monitoring New MicroSatellite (VENµS) research mission, and assessed using ground observations of early crop growth stages (emergence VE and one leaf V1 stages for corn, and emergence VE and unifoliolate VC stages for soybeans) collected over the Beltsville Agricultural Research Center (BARC) experimental fields in Beltsville, MD during the 2019 growing season. Results show that early crop growth stages can be reliably detected at sub-field scale about two weeks after crop emergence. The remote sensing green-up dates were about 4-5 days after crop emergence on average. Coefficients of determination (R2) between green-up dates and the mid-point dates of the early growth stages were above 0.90. The mean absolute differences, standard deviations, and root mean square errors comparing to the early growth stage mid-point dates were within six days. The maximum differences were within ±10 days across all fields. The WISE approach was assessed using operational Sentinel-2 data (10 m, 5 day revisit) in BARC. The detected green-up dates from Sentinel-2 were found close to VENµS results. Some fields were not detected due to the lack of observations during emergence dates. For independent evaluation, the WISE approach was applied over an agricultural watershed on the Maryland Eastern Shore using both VENµS and the harmonized Landsat and Sentinel-2 (HLS) data (30 m, 3-4 day revisit). The green-up dates were compared with crop progress reports of crop emergence dates from the National Agricultural Statistics Service (NASS) at the state-level. The WISE -detected green-up dates at the regional scale are within VE stage ranges but slightly earlier than NASS crop progress reports at the state-level. The WISE approach uses remote sensing observations during the early crop growth stages and has potential for operational application within the season using Sentinel-2 and HLS data.

Maryland↗

USGS2023

Ecological effects of pinyon-juniper removal in the Western United States—A synthesis of scientific research, January 2014–March 2021

Executive Summary Increasing density of pinyon ( Pinus spp. ) and juniper ( Juniperus spp. ) woodlands (hereinafter “pinyon-juniper”), as well as expansion of these woodlands into adjacent shrublands and grasslands, has altered ecosystem function and wildlife habitat across large areas of the interior western United States. Although there are many natural and human-caused drivers of woodland infilling and expansion, restoration of sagebrush ( Artemisia spp. ) habitat through removal of pinyon-juniper is considered an urgent management objective in many locations, particularly in support of sagebrush-dependent wildlife species of conservation concern. In December 2020, the Bureau of Land Management (BLM) established the Pinyon-Juniper Management Categorical Exclusion (PJCX) to expedite the regulatory process for pinyon-juniper removal projects on public lands, largely intended to benefit mule deer ( Odocoileus hemionus ) and greater sage-grouse ( Centrocercus urophasianus ) habitats. During final preparation of this report, the BLM discontinued use of the PJCX (as of November, 2022), but the pinyon-juniper tree removal techniques assessed in this report are commonly used and understanding their effects remains relevant to land use planning. To address areas of uncertainty relative to potential ecological effects of the PJCX, we conducted a review of the peer-reviewed science literature to better understand the likely responses of vegetation, environmental (for example, soils), and wildlife variables to specific tree removal techniques permitted by the PJCX. In brief, the PJCX permitted removal of trees by either manual cutting, mechanical cutting, or mastication; allowed certain methods to redistribute or remove resulting tree biomass after treatment; and prohibited broadcast burning, roadbuilding, removal of old-growth, and seeding of non-native species. Specifically, we conducted our review to address the following questions: How will PJCX removal techniques affect plant communities, soils, and abiotic resources? How do these pinyon-juniper removal techniques affect wildlife communities, including both woodland- and sagebrush-dependent species? What are the potential ecological implications of different pinyon-juniper removal treatment types and implementation strategies (for example, treatment sizes) over time? What are the most important gaps in our scientific understanding of how treatments might affect targeted ecosystems over space and time (for example, potential effects of climate change)? To answer these questions, we considered studies related to pinyon-juniper ecosystems, focusing on research that occurred over a large portion of the interior western United States that is the primary focus of the PJCX. We also focused on papers published from 2014 onward, to avoid excessive overlap with other recent reviews on pinyon-juniper management effects. Using strict criteria, including only considering research that tested responses for statistical significance, we identified 48 papers that primarily examined treatment effects on vegetation and other environmental variables (1,709 responses), and 11 papers that addressed effects on wildlife (132 responses). Responses to the PJCX-permitted treatments were summarized as either positive (that is, a significant increase), negative (that is, a significant decrease), or non-significant (that is, no significant difference). Responses were assigned to categories (for example, Native Annual Grass/Forb Abundance) and hierarchical treatment levels. We found that there were large proportions of non-significant responses among all categories combined, with roughly half or more of all responses non-significant (48 percent for wildlife, 60 percent for vegetation-environmental), comparable to other recent systematic reviews of pinyon-juniper treatment effects. However, we also found that when there were significant responses, some important trends potentially emerged. Important undesirable outcomes included far more positive than negative responses of exotic grass and forb abundance among nearly all treatment types. Cutting treatments were also more likely to decrease biocrust cover and microbial activity. Potentially beneficial outcomes included mostly positive responses among sagebrush obligate species, including more positive than negative responses for mule deer and sage-grouse. Some treatment types (for example, mastication) also resulted in more positive than negative responses for native grasses and forbs (although, non-significant responses were the majority). We also highlighted many limitations of this review, including how responses often come from few studies, and how some response-treatment category combinations lack adequate response data. Moreover, the existing research is often insufficient to address many key questions about treatment effects, largely owing to short time-scales and limited spatial extents of observations, which do not match the size of treatments being implemented by land managers, nor capture long-term, post-treatment ecological dynamics. We also identify a lack of research that addresses key interactions that could undermine restoration objectives, including potential effects of climate change and grazing on post-treatment environments. Thus, we emphasize the importance of integrating these factors into future pinyon-juniper treatment research, and we stress the need for use of monitoring programs and research studies that partake in data collection and analysis over long durations and broad spatial scales.

Open-File Report↗