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At least 1,567 records · Page 87Linked to original sources

USGS2019

Reduced soil macropores and forest cover reduce warm-season baseflow below ecological thresholds in the upper Delaware River Basin

We examined the impacts of changes in land cover and soil conditions on the flow regime of the upper Delaware River Basin using the Water Availability Tool for Environmental Resources (WATER). We simulated flows for two periods, circa 1600 and 1940, at three sites using the same temperature and precipitation conditions: the East Branch (EB), West Branch (WB), and mainstem Delaware River at Callicoon, NY. The 1600 period represented pristine forest and soils. The 1940 period included reduced forest cover, increased agriculture, and degraded soils with reduced soil macropore fractions. A model-sensitivity test examined the impact of soil macropore and land cover change separately. We assessed changes in flow regimes between the 1600 and 1940 periods using a variety of flow statistics, including established ecological limits of hydrologic alteration (ELOHA) thresholds. Reduced forest soil macropore fraction significantly reduced summer and fall base flows. The 1940 period had significantly lower Q50 flows (50% exceedance) than the 1600 period, as well as summer and fall Q90 and Q75-90 flows below the ELOHA thresholds. The 1- to 7-day minimum flows were also lower for the 1940 period, by 17% on the mainstem. 1940 flows were 6% more likely than the 1600 period to fall below the low-flow threshold for federally endangered dwarf wedgemussel (Alasmidonta heterodon) habitat. In contrast, the 1940 period had higher flows than the 1600 period from late fall to early winter.

New York, Pennsylvania↗

USGS2001

Land use change and effects on water quality and ecosystem health in the Lake Tahoe basin, Nevada and California

Human activity in the Lake Tahoe Basin has increased substantially in the past four decades, causing significant impacts on the quality and clarity of the lake's famous deep, clear water. Protection of Lake Tahoe and the surrounding environment has become an important activity in recent years. A variety of agencies, including the Tahoe Regional Planning Agency, Tahoe Research Group of the University of California at Davis, Desert Research Institute of the University and Community College System of Nevada, U.S. Geological Survey (USGS), and a host of State (both Nevada and California) and local agencies have been monitoring and conducting research in the Basin in order to understand how the lake functions and to what extent humans have affected its landscape and ecosystem processes. In spite of all of these activities, there remains a lack of comprehensive land use change data and analysis for the Basin. A project is underway that unites the land cover mapping expertise of the USGS National Mapping Discipline with the hydrologic expertise of the Water Resources Discipline to assess the impacts of urban growth and land use change in the Lake Tahoe Basin. Three activities are planned over the next 3 years: (1) mapping the current and historic state of the land surface, (2) conducting analysis to document patterns, rates, and trends in urbanization, land use change, and ecosystem health, and (3) assessing the causes and consequences of land use change with regard to water quality and ecosystem health. We hypothesize that changes in the extent of urban growth and the corresponding increases in impervious surfaces and decreases in natural vegetation have resulted in severe impacts on ecosystem health and integrity, riparian zones and water quality over time. We are acting on multiple fronts to test this hypothesis through the quantification of landscape disturbances and impacts.

California, Nevada↗

USGS2022

Whooping crane stay length in relation to stopover site characteristics

Whooping crane ( Grus americana ) migratory stopovers can vary in length from hours to more than a month. Stopover sites provide food resources and safety essential for the completion of migration. Factors such as weather, climate, demographics of migrating groups, and physiological condition of migrants influence migratory movements of cranes (Gruidae) to varying degrees. However, little research has examined the relationship between habitat characteristics and stopover stay length in cranes. Site quality may relate to stay length with longer stays that allow individuals to improve body condition, or with shorter stays because of increased foraging efficiency. We examined this question using habitat data collected at 605 use locations from 449 stopover sites throughout the United States Great Plains visited by 58 whooping cranes from the Aransas–Wood Buffalo Population tracked with platform transmitting terminals. Research staff compiled land cover (e.g., hectares of corn; landscape level) and habitat metric (e.g., maximum water depth; site level) data for day use and evening roost locations via site visits and geospatial mapping. We used Random Forest regression analyses to estimate importance of covariates for predicting stopover stay length. Site-level variables explained 9% of variation in stay length, whereas landscape-level variables explained 43%. Stay length increased with latitude and the proportion of land cover as open-water slough with emergent vegetation as well as alfalfa, whereas stay length decreased as open-water lacustrine wetland land cover increased. At the site-level, stopover duration increased with wetted width at riverine sites but decreased with wetted width at palustrine and lacustrine wetland sites. Stopover duration increased with mean distance to visual obstruction as well as where management had reduced the height of vegetation through natural (e.g., grazing) or mechanical (e.g., harvesting) means and decreased with maximum water depth. Our results suggest that stopover length increases with the availability of preferred land cover types for foraging. High quality stopover sites with abundant forage resources may help whooping cranes maintain fat reserves important to their annual life cycle.

Proceedings of the North American Crane Workshop↗

USGS2023

Land development and road salt usage drive long-term changes in major-ion chemistry of streamwater in six exurban and suburban watersheds, southeastern Pennsylvania, 1999-2019

In urbanized areas, the “freshwater salinization syndrome” (FSS), which pertains to long-term increases in concentrations of major ions and metals in fresh surface waters, has been attributed to road salt application. In addition to FSS, the water composition changes as an influx of sodium (Na + ) in recharge may displace calcium (Ca 2+ ), magnesium (Mg 2+ ), potassium (K + ), and trace metals by reverse cation exchange. These changing ion fluxes can result in adverse impacts on groundwater and surface waters used for municipal supplies. Few datasets exist to quantify the FSS on a watershed scale or link its manifestation to potential controlling factors such as changes in urban development, land use/land cover (LULC), or wastewater treatment plant (WWTP) discharges in upstream areas. Here, we use two decades (1999–2019) of monthly streamwater quality data combined with daily streamflow for six exurban and suburban watersheds in southeastern Pennsylvania to examine the relations among Ca 2+ , Mg 2+ , K + , Na + , chloride (Cl − ), sulfate (SO 4 2- ), and alkalinity (HCO 3 − ) concentrations and upstream controlling factors. Flow-normalized annual and baseflow (August ̶ November) concentrations for Ca 2+ , Mg 2+ , Na + , and Cl − increased in all six watersheds over the 20-year study, providing evidence of FSS’s impacts on groundwater that sustains streamflow. Additionally, a redundancy analysis using 2019 flow-normalized values identified the following positive associations between solute concentrations and controlling variables: 1) Cl − , Mg 2+ , and Ca 2+ with impervious surface cover (ISC), 2) Na + and SO 4 2- with ISC and total WWTP discharge volume, and 3) HCO 3 − with agriculture and total WWTP discharge volume. From a human health perspective, 2019 flow-normalized Na + concentrations exceeded the U.S. Environmental Protection Agency’s 20 mg L -1 threshold for individuals restricted to a low sodium diet. Furthermore, indices used to evaluate the corrosivity of source waters to drinking water infrastructure and inform municipal water treatment practices, such as the Chloride to Sulfate Mass Ratio and Larson Ratio, increased between two- and seven-fold over the 20-year time. Collectively, the results elucidate the causal factors of the FSS in suburban and exurban watersheds and its potential impacts on human health and drinking water infrastructure.

Pennsylvania↗

USGS2026

Investigating hydrologic alteration under historical and future scenarios in the Mobile River and Perdido River basins using the cubist algorithm

This study investigates the impacts of human activities and climate variability on hydrologic alterations in the Mobile River and Perdido River Basins of Alabama. The research uses a machine learning approach, specifically cubist models, to quantify and predict changes in flow duration curves (FDCs) under both historical (1980–2009) and future climate scenarios. Future climate projections include the Representative Concentration Pathways (RCP 4.5 and RCP 8.5) and the Shared Socioeconomic Pathways (SSP2 4.5 and SSP5 8.5), evaluated for two future periods: 1980–2069 and 1980–2099. The models incorporate a wide range of covariates, including basin geomorphology, aquifer characteristics, land cover, water storage, environmental factors, solar radiation, census data, and water use data. Under the baseline period (1980–2009), most level 12 hydrologic unit codes (HUC12s) in both basins showed alterations, with substantial differences observed between pre- and post-alteration FDCs. The model performance varied, with a Nash–Sutcliffe Efficiency between 0.91 and 0.95 for testing and between 0.98 and 0.99 for training during the baseline period. Future projections under the RCP 4.5 and RCP 8.5 scenarios generally differed significantly from baseline conditions across all flow regimes ( p < 0.05). In contrast, SSP2 4.5 showed comparatively limited statistical significance, while SSP5 8.5 exhibited significant departures from baseline conditions across all flow regimes, reflecting the greater influence of high-emissions climate forcing on projected hydrologic alterations. Overall, the RCP scenarios projected more widespread statistically significant changes than the corresponding SSP scenarios at the same forcing level, particularly when comparing RCP4.5 with SSP2-4.5, while both RCP8.5 and SSP5-8.5 consistently indicated greater hydrologic alterations than their moderate-emissions counterparts. These findings highlight the importance of considering different flow regimes when assessing the impacts of climate variability on streamflow. This study contributes to the understanding of hydrologic alterations in the Mobile River and Perdido River Basins, providing insights for water resource management and ecological conservation efforts in the region.

Alabama↗

USGS2013

Modeling ecological minimum requirements for distribution of greater sage-grouse leks: implications for population connectivity across their western range, U.S.A.

Greater sage-grouse Centrocercus urophasianus (Bonaparte) currently occupy approximately half of their historical distribution across western North America. Sage-grouse are a candidate for endangered species listing due to habitat and population fragmentation coupled with inadequate regulation to control development in critical areas. Conservation planning would benefit from accurate maps delineating required habitats and movement corridors. However, developing a species distribution model that incorporates the diversity of habitats used by sage-grouse across their widespread distribution has statistical and logistical challenges. We first identified the ecological minimums limiting sage-grouse, mapped similarity to the multivariate set of minimums, and delineated connectivity across a 920,000 km 2 region. We partitioned a Mahalanobis D 2 model of habitat use into k separate additive components each representing independent combinations of species–habitat relationships to identify the ecological minimums required by sage-grouse. We constructed the model from abiotic, land cover, and anthropogenic variables measured at leks (breeding) and surrounding areas within 5 km. We evaluated model partitions using a random subset of leks and historic locations and selected D 2 (k = 10) for mapping a habitat similarity index (HSI). Finally, we delineated connectivity by converting the mapped HSI to a resistance surface. Sage-grouse required sagebrush-dominated landscapes containing minimal levels of human land use. Sage-grouse used relatively arid regions characterized by shallow slopes, even terrain, and low amounts of forest, grassland, and agriculture in the surrounding landscape. Most populations were interconnected although several outlying populations were isolated because of distance or lack of habitat corridors for exchange. Land management agencies currently are revising land-use plans and designating critical habitat to conserve sage-grouse and avoid endangered species listing. Our results identifying attributes important for delineating habitats or modeling connectivity will facilitate conservation and management of landscapes important for supporting current and future sage-grouse populations.

Ecology and Evolution↗

USGS2010

Judging a brook by its cover: The relation between ecological condition of a stream and urban land cover in new England

The US Geological Survey conducted an urban land-use study in the New England Coastal Basins (NECB) area during 2001 to determine how urbanization relates to changes in the ecological condition of streams. Thirty sites were selected that differed in their level of watershed development (low to high). An urban intensity value was calculated for each site from 24 landscape variables. Together, these 30 values reppresented a gradient of urban intensity. Among various biological, chemical, and physical factors surveyed at each site, benthic invertebrate assemblages were sampled from stream riffles and also from multiple habitats along the length of the sampling reach. We use some of the NECB data to derive a four-variable urbanintensity index (NECB-UII), where each variable represents a distinct component of urbanization: increasing human presence, expanding infrastructure, landscape development, and riparian vegetation loss. Using the NECB-UII as a characterization of urbanization, we describe how landscape fragmentation occurs with urbanization and how changes in the invertebrate assemblages, represented by metrics of ecological condition, are related to urbanization. Metrics with a strong linear response included EPT taxa richness, percentage richness of non-insect taxa, and pollution-tolerance values. Additionally, we describe how these relations can help in estimating the expected condition of a stream for its level of urbanization, thereby establishing a baseline for evaluating possible affects from specific point-source stressors.

Northeastern Naturalist↗

USGS1994

A comparison of change detection methods using multispectral scanner data

Change detection methods were investigated as a cooperative activity between the U.S. Geological Survey and the National Bureau of Surveying and Mapping, People's Republic of China. Subtraction of band 2, band 3, normalized difference vegetation index, and tasseled cap bands 1 and 2 data from two multispectral scanner images were tested using two sites in the United States and one in the People's Republic of China. A new statistical method also was tested. Band 2 subtraction gives the best results for detecting change from vegetative cover to urban development. The statistical method identifies areas that have changed and uses a fast classification algorithm to classify the original data of the changed areas by land cover type present for each image date.

Open-File Report↗

USGS2021

Comparison of simple averaging and latent class modeling to estimate the area of land cover in the presence of reference data variability

Estimates of the area or percent area of the land cover classes within a study region are often based on the reference land cover class labels assigned by analysts interpreting satellite imagery and other ancillary spatial data. Different analysts interpreting the same spatial unit will not always agree on the land cover class label that should be assigned. Two approaches for accommodating interpreter variability when estimating the area are simple averaging (SA) and latent class modeling (LCM). This study compares agreement between area estimates obtained from SA and LCM using reference data obtained by seven trained, professional interpreters who independently interpreted an annual time series of land cover reference class labels for 300 sampled Landsat pixels. We also compare the variability of the LCM and SA area estimates over different numbers of interpreters and different subsets of interpreters within each interpreter group size, and examine area estimates of three land cover classes (forest, developed, and wetland) and three change types (forest gain, forest loss, and developed gain). Differences between the area estimates obtained from SA and LCM are most pronounced for the estimates of wetland and the three change types. The percent area estimates of these rare classes were usually greater for LCM compared to SA, with the differences between LCM and SA increasing as the number of interpreters providing the reference data increased. The LCM area estimates generally had larger standard deviations and greater ranges over different subsets of interpreters, indicating greater sensitivity to the selection of the individual interpreters who carried out the reference class labeling.

Washington↗

USGS2023

Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California

In arid and Mediterranean regions, landscape-scale wetland conservation requires understanding how wildlife responds to dynamic freshwater availability and conservation actions to enhance wetland habitat. Taking advantage of Landsat satellite data and structured and community science bird survey data, we built species distribution models to describe how three duck species, the Northern Pintail ( Anas acuta ), Green-winged Teal ( Anas crecca ), and Northern Shoveler ( Anas clypeata ), respond to freshwater supply and food resources on different flooded land cover types in the Central Valley of California. Specifically, our models compared duck habitat suitability between the wettest and driest conditions in each month from September through April. Using abundance-weighted boosted regression trees, we created three sets of species occurrence models based on different covariates: (1) near real-time (hereafter “real-time”) covariates in which duck observations were matched to the water availability within the 16-day window of a Landsat observation, (2) a combination of real-time covariates and waterfowl food resource covariates describing annual corn and rice biomass and managed wetland moist soil seed yield estimates derived from Landsat data, and (3) long-term average covariates—the most common approach to species distribution modeling—in which long-term average surface water availability was used. We modeled the monthly occurrence of three duck species as a function of surface water availability, land cover type, road density, temperature, and bird data source. We found that dry conditions result in reduced habitat suitability, with the biggest reductions in November through January and in agricultural fields; in contrast, suitability of flooded wetland habitat was relatively robust to surface water availability. When models of habitat suitability based on long-term average climate conditions were compared to models based on real-time conditions, the highest long-term suitability values occurred in areas where suitability was high regardless of whether it was a wet or a dry year. While all models performed well, the inclusion of crop and wetland plant yield covariates resulted in slightly higher model performance. Overall, species distribution models created using data on the environmental conditions present at the time of bird observations can aid conservation efforts under extreme conditions over large spatial scales.

California↗

USGS2015

Spatially explicit modeling of blackbird abundance in the Prairie Pothole Region

Knowledge of factors influencing animal abundance is important to wildlife biologists developing management plans. This is especially true for economically important species such as blackbirds (Icteridae), which cause more than $100 million in crop damages annually in the United States. Using data from the North American Breeding Bird Survey, the National Land Cover Dataset, and the National Climatic Data Center, we modeled effects of regional environmental variables on relative abundance of 3 blackbird species (red-winged blackbird, Agelaius phoeniceus ; yellow-headed blackbird, Xanthocephalus xanthocephalus ; common grackle, Quiscalus quiscula ) in the Prairie Pothole Region of the central United States. We evaluated landscape covariates at 3 logarithmically related spatial scales (1,000 ha, 10,000 ha, and 100,000 ha) and modeled weather variables at the 100,000-ha scale. We constructed models a priori using information from published habitat associations. We fit models with WinBUGS using Markov chain Monte Carlo techniques. Both landscape and weather variables contributed strongly to predicting blackbird relative abundance (95% credibility interval did not overlap 0). Variables with the strongest associations with blackbird relative abundance were the percentage of wetland area and precipitation amount from the year before bird surveys were conducted. The influence of spatial scale appeared small—models with the same variables expressed at different scales were often in the best model subset. This large-scale study elucidated regional effects of weather and landscape variables, suggesting that management strategies aimed at reducing damages caused by these species should consider the broader landscape, including weather effects, because such factors may outweigh the influence of localized conditions or site-specific management actions. The regional species distributional models we developed for blackbirds provide a tool for understanding these broader landscape effects and guiding wildlife management practices to areas that are optimally beneficial. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

Iowa, Minnesotta, Montana, Nebraska, North Dakota↗

USGS2019

Wetlands and development influence fish diversity in a species-rich small river

We identified in-stream and off-stream characteristics that influenced various species diversity metrics in reaches of the Duck River Basin, Tennessee, USA. This relatively small basin is home to one of the most diverse freshwater fish faunas in North America. In all, over 325,000 native fish representing 136 native fish species were electrofished in 207 collections across 86 stations. Diversity of native species and of seven taxa and functional guilds, including imperiled species, increased with size of the catchment above a station, an effect that was mediated by altitude. After removing the effects of catchment and altitude, diversity was influenced by in-stream factors and mostly by off-stream land composition such as wetlands within 0.1 km from the channel and urban/suburban development within 2.5 km. Pastures next to streams unexpectedly increased diversity. Our analyses suggest that there are detectable hotspots associated with off-stream landscape characteristics where conservation efforts may be focused. Our results may encourage conservation planners to apply geospatial analyses to identify diversity hotspots based on land cover distributions and develop recommendations for management of specific stream reaches. Alternatively, geospatial analysis may be used by planners to estimate the impacts of alternative land-use scenarios, thus preemptively conserving species richness.

Tennessee↗

USGS1981

The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example

The U. S. Geological Survey's Earth Resources Observations Systems Data Center, in cooperation with the U.S. Army Corps of Engineers, Portland District, developed and tested techniques that used remotely sensed and other spatial data in predictive models to evaluate irrigation agriculture in the Umatilla River Basin of north-central Oregon. Landsat data and 1:24,000-scale aerial photographs were initially used to map he expansion of irrigate from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a composite map of land suitability for irrigation development based on land cover (from Landsat), land-ownership, soil irrigability, slope gradient, and potential energy costs. The methods and data used in the study demonstrated the flexibility of remotely sensed and other spatial data as input for predictive models. When combined, they provided useful answers to complex questions facing resource managers.

Oregon↗

USGS2020

Changes in climate and land cover affect seasonal streamflow forecasts in the Rio Grande headwaters

Seasonal streamflow forecast bias, changes in climate, snowpack, and land cover, and the effects of these changes on relations between basin‐wide snowpack, SNOw TELemetry (SNOTEL) station snowpack, and seasonal streamflow were evaluated in the headwaters of the Rio Grande, Colorado. Results indicate that shifts in the seasonality of precipitation and changing climatology are consistent with periods of overprediction and underprediction in streamflow forecasts. Multiple linear regression of SNOTEL data, postcedent precipitation, and land‐cover changes explained 2%–18% more variability in streamflow prediction than using SNOTEL station data alone. Simulated basin‐wide snowpack from a physically based model had significant negative trends in snow water equivalent (−4.33 mm/yr) and snow‐covered area (−0.05%/yr) during the melt period April–June. Simulated streamflow from a precipitation‐runoff model increased an average 5% when the effects of bark beetle‐induced tree mortality were compared to a baseline simulation with static vegetation. The effects of a 2013 wildfire increased simulated seasonal streamflow an average 35% for 1–4 years postfire. The combined effects of climate and land‐cover changes on snowpack‐streamflow relations highlight the difficulty in seasonal streamflow forecasting, which has important implications for water‐resource management.

Colorado↗

USGS1995

The strategy for improving water-quality monitoring in the United States; final report of the Intergovernmental Task Force on Monitoring Water Quality; technical appendices

The Intergovernmental Task Force on Monitoring Water Quality (ITFM) prepared this report in collaboration with representatives of all levels of government and the private sector. The report recommends a strategy for nationwide water-quality monitoring and technical monitoring improvements to support sound water-quality decisionmaking. The strategy is intended to achieve a better return on public and private investments in monitoring, environmental protection, and natural resources management. It is also designed to expand the base of information useful to a variety of users at multiple geographic scales. Institutional and technical changes are needed to improve water-quality monitoring and to meet the full range of monitoring requirements. Monitoring must be incorporated as a critical element of program planning, implementation, and evaluation. The strategy includes recommendations in many key elements, such as the development of goal-oriented monitoring and indicators, institutional collaboration, and methods comparability. Initial actions have been taken to implement the strategy. Several Federal agencies have jointly purchased and shared remotely sensed land-cover information needed for water assessment. Major agency data systems are using common data-element names and reference tables that will ensure easy sharing of data. A number of States have held meetings with collectors of water information to initiate statewide monitoring strategies. New monitoring guidance has been developed for Federal water-quality grants to States. Many State offices have changed monitoring programs to place emphasis on priority watersheds and to improve assessment of water quality. As the competition increases for adequate supplies of clean water, concerns about public health and the environment escalate, and more demands are placed on the water information infrastructure. To meet these demands, the collaborative approach has already produced benefits, which will continue to grow as the recommendations are implemented

Open-File Report↗

USGS2013

Land-cover effects on the fate and transport of surface-applied antibiotics and 17-beta-estradiol on a sandy outwash plain, Anoka County, Minnesota, 2008–09

A plot-scale field experiment on a sandy outwash plain in Anoka County in east-central Minnesota was used to investigate the fate and transport of two antibiotics, sulfamethazine (SMZ) and sulfamethoxazole (SMX), and a hormone, 17-beta-estradiol (17BE), in four land-cover types: bare soil, corn, hay, and prairie. The SMZ, SMX, and 17BE were applied to the surface of five plots of each land-cover type in May 2008 and again in April 2009. The cumulative application rate was 16.8 milligrams per square meter (mg/m 2 ) for each antibiotic and 0.6 mg/m2 for 17BE. Concentrations of each chemical in plant-tissue, soil, soil-water, and groundwater samples were determined by using enzyme-linked immunosorbent assay (ELISA) kits. Soil-water and groundwater sampling events were scheduled to capture the transport of SMZ, SMX, and 17BE during two growing seasons. Soil and plant-tissue sampling events were scheduled to identify the fate of the parent chemicals of SMZ, SMX, and 17BE in these matrices after two chemical applications. Areal concentrations (mg/m 2 ) of SMZ and SMX in soil tended to decrease in prairie plots in the 8 weeks after the second chemical application, from April 2009 to June 2009, but not in other land-cover types. During these same 8 weeks, prairie plots produced more aboveground biomass and had extracted more water from the upper 125 centimeters of the soil profile compared to all other land-cover types. Areal concentrations of SMZ and SMX in prairie plant tissue did not explain the temporal changes in areal concentrations of these chemicals in soil. The areal concentrations of SMZ and SMX in the aboveground plant tissues in June 2009 and August 2009 were much lower, generally two to three orders of magnitude, than the areal concentrations of these chemicals in soil. Pooling all treatment plot data, the median areal concentration of SMZ and SMX in plant tissues was 0.01 and 0.10 percent of the applied chemical mass compared to 22 and 12 percent in soil, respectively. Furthermore, areal concentrations of SMZ and SMX in plant-tissue samples were variable, and did not differ significantly between control and treatment plots within each land-cover type. SMZ was detected in 23 percent of soil-water samples and in 16 percent of groundwater samples collected between October 2008 and October 2009 in treatment plots, indicating that surface-applied SMZ leached below the rooting zone and reached groundwater. SMX was detected in only 1 percent of soil-water and groundwater samples during this same time period. In contrast to the antibiotics, 17BE was not reliably detected in soil samples. Additionally, ELISA-determined 17BE concentrations in plant-tissue, soil-water, and groundwater samples indicated the presence of chemicals that were not applied as part of this experiment [17BE from an external source or other chemical(s) that interfered with the 17BE ELISA kits].

Minnesota↗

USGS2013

A regional classification of the effectiveness of depressional wetlands at mitigating nitrogen transport to surface waters in the Northern Atlantic Coastal Plain

Nitrogen from nonpoint sources contributes to eutrophication, hypoxia, and related ecological degradation in Atlantic Coastal Plain streams and adjacent coastal estuaries such as Chesapeake Bay and Pamlico Sound. Although denitrification in depressional (non-riparian) wetlands common to the Coastal Plain can be a significant landscape sink for nitrogen, the effectiveness of individual wetlands at removing nitrogen varies substantially due to varying hydrogeologic, geochemical, and other landscape conditions, which are often poorly or inconsistently mapped over large areas. A geographic model describing the spatial variability in the likely effectiveness of depressional wetlands in watershed uplands at mitigating nitrogen transport from nonpoint sources to surface waters was constructed for the Northern Atlantic Coastal Plain (NACP), from North Carolina through New Jersey. Geographic and statistical techniques were used to develop the model. Available medium-resolution (1:100,000-scale) stream hydrography was used to define 33,799 individual watershed catchments in the study area. Sixteen landscape metrics relevant to the occurrence of depressional wetlands and their effectiveness as nitrogen sinks were defined for each catchment, based primarily on available topographic and soils data. Cluster analysis was used to aggregate the 33,799 catchments into eight wetland landscape regions (WLRs) based on the value of three principal components computed for the 16 original landscape metrics. Significant differences in topography, soil, and land cover among the eight WLRs demonstrate the effectiveness of the clustering technique. Results were used to interpret the relative likelihood of depressional wetlands in each WLR and their likely effectiveness at mitigating nitrogen transport from upland source areas to surface waters. The potential effectiveness of depressional wetlands at mitigating nitrogen transport varies substantially over different parts of the NACP. Depressional wetlands are common in three WLRs covering 32 percent of the area, and have a relatively high potential to mitigate nitrogen transport from nonpoint sources. Conversely, 37 percent of the study area includes rolling hills with relatively high slope and relief, and little likelihood of depressional wetlands. The remainder of the Coastal Plain includes relatively flat watersheds with moderate to low relative likelihood of nitrogen mitigation. The delineation of WLRs in this model should be useful for targeting wetland conservation or restoration efforts, and for estimating the effects of depressional wetlands on the regional nitrogen budget, but should be considered in light of limitations and assumptions inherent in the model.

Scientific Investigations Report↗

USGS2010

Quantifying human disturbance in watersheds: Variable selection and performance of a GIS-based disturbance index for predicting the biological condition of perennial streams

Characterizing the relative severity of human disturbance in watersheds is often part of stream assessments and is frequently done with the aid of Geographic Information System (GIS)-derived data. However, the choice of variables and how they are used to quantify disturbance are often subjective. In this study, we developed a number of disturbance indices by testing sets of variables, scoring methods, and weightings of 33 potential disturbance factors derived from readily available GIS data. The indices were calibrated using 770 watersheds located in the western United States for which the severity of disturbance had previously been classified from detailed local data by the United States Environmental Protection Agency (USEPA) Environmental Monitoring and Assessment Program (EMAP). The indices were calibrated by determining which variable or variable combinations and aggregation method best differentiated between least- and most-disturbed sites. Indices composed of several variables performed better than any individual variable, and best results came from a threshold method of scoring using six uncorrelated variables: housing unit density, road density, pesticide application, dam storage, land cover along a mainstem buffer, and distance to nearest canal/pipeline. The final index was validated with 192 withheld watersheds and correctly classified about two-thirds (68%) of least- and most-disturbed sites. These results provide information about the potential for using a disturbance index as a screening tool for a priori ranking of watersheds at a regional/national scale, and which landscape variables and methods of combination may be most helpful in doing so.

Ecological Indicators↗