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At least 55 records · Page 3Linked to original sources

The role of headwater streams in downstream water quality

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and 40% in fourth- and higher-order rivers that include navigable waters and their tributaries. These results underscore the profound influence that headwater areas have on shaping downstream water quantity and water quality. The results have relevance to water-resource management and regulatory decisions and potentially broaden understanding of the spatial extent of Federal CWA jurisdiction in U.S. waters. ?? 2007 American Water Resources Association.

Journal of the American Water Resources Associatio↗

A calibrated, high-resolution goes satellite solar insolation product for a climatology of Florida evapotranspiration

Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10-year period (1995-2004). These insolation estimates were developed into well-calibrated half-hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2-week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground-based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three-step process: (1) comparison with ground-based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m -2 /day (13%). Calibration reduced errors to 1.7 MJ m -2 /day (10%), and also removed temporal-related, seasonal-related, and satellite sensor-related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2-km resolution maps of estimated daily reference and potential evapotranspiration for water management-related activities. ?? 2009 American Water Resources Association.

Journal of the American Water Resources Associatio↗

Sources of suspended-sediment flux in streams of the chesapeake bay watershed: A regional application of the sparrow model

We describe the sources and transport of fluvial suspended sediment in nontidal streams of the Chesapeake Bay watershed and vicinity. We applied SPAtially Referenced Regressions on Watershed attributes, which spatially correlates estimated mean annual flux of suspended sediment in nontidal streams with sources of suspended sediment and transport factors. According to our model, urban development generates on average the greatest amount of suspended sediment per unit area (3,928 Mg/km2/year), although agriculture is much more widespread and is the greatest overall source of suspended sediment (57 Mg/km2/year). Factors affecting sediment transport from uplands to streams include mean basin slope, reservoirs, physiography, and soil permeability. On average, 59% of upland suspended sediment generated is temporarily stored along large rivers draining the Coastal Plain or in reservoirs throughout the watershed. Applying erosion and sediment controls from agriculture and urban development in areas of the northern Piedmont close to the upper Bay, where the combined effects of watershed characteristics on sediment transport have the greatest influence may be most helpful in mitigating sedimentation in the bay and its tributaries. Stream restoration efforts addressing floodplain and bank stabilization and incision may be more effective in smaller, headwater streams outside of the Coastal Plain. ?? 2010 American Water Resources Association. No claim to original U.S. government works.

Journal of the American Water Resources Associatio↗

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

The U.S. Geological Survey National Water Quality Assessment Program has completed a number of water-quality prediction models for nitrogen and phosphorus for the conterminous United States as well as for regional areas of the nation. In addition to estimating water-quality conditions at unmonitored streams, the calibrated SPAtially Referenced Regressions On Watershed attributes (SPARROW) models can be used to produce estimates of yield, flow-weighted concentration, or load of constituents in water under various land-use condition, change, or resource management scenarios. A web-based decision support infrastructure has been developed to provide access to SPARROW simulation results on stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via a graphical user interface with familiar controls. The SPARROW decision support system (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions and to describe, test, and share modeled scenarios of future conditions. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

Journal of the American Water Resources Associatio↗

Case study comparing multiple irrigated land datasets in Arizona and Colorado, USA

While there are currently a number of irrigated land datasets available for the western United States (U.S.), there is uncertainty regarding in how they relate to each other. To help understand the characteristics of available irrigated datasets, we compared (1) the Cropland Data Layer (CDL), (2) Moderate Resolution Imaging Spectroradiometer Irrigated Agriculture Dataset (IAD), (3) Digitized Irrigated Land (DIL), and (4) Consumptive Use for Irrigation (CUI) data in Arizona and Colorado, U.S. These datasets were derived from multiple sources at various spatial resolutions and temporal scales. We found spatial and temporal trends among all of them. The datasets showed decreases in irrigated land area in Arizona during the 2000–2010 time period. The change ranges and ratios were similar in all Arizona datasets. Irrigated land in Colorado decreased in DIL and CUI but increased in IAD and CDL. The agreement within the same type of dataset during different time periods was from 60% to 80% ( R 2 from 0.35 to 0.72) in Arizona and from 50% to 80% ( R 2 from 0.23 to 0.68) in Colorado. DIL had the highest agreement (80%) in both states. The agreement among different datasets acquired at approximately the same time frame ranged from 51% to 63% ( R 2 from 0.14 to 0.31) in Arizona and from 47% to 69% ( R 2 from 0.32 to 0.40) in Colorado. The results from this study support a greater understanding of the multiresolution and multitemporal nature of these datasets for various applications.

Arizona, Colorado↗

Using boosted regression tree models to predict salinity in Mississippi embayment aquifers, central United States

High salinity limits groundwater use in parts of the Mississippi embayment. Machine learning was used to create spatially continuous and three‐dimensional predictions of salinity across drinking‐water aquifers in the embayment. Boosted regression tree (BRT) models, a type of machine learning, were used to predict specific conductance (SC) and chloride (Cl), and total dissolved solids (TDS) was calculated from a correlation with SC. Explanatory variables for BRT models included well location and construction, surficial variables (e.g., soils and land use), and variables extracted from a groundwater‐flow model, including simulated groundwater ages. BRT model fits ( r 2 ) were 0.74 (SC and Cl) and 0.62 (TDS). BRT models provided spatially continuous salinity predictions across surficial and deeper aquifers where discrete water‐quality samples were missing. Uncertainty was smaller where salinity was lower, and models tended to underpredict in areas of highest salinity. Despite this, BRT models were able to capture areas of documented high salinity that exceed the TDS secondary maximum contaminant level for drinking water of 500 mg/L. Variables that served as surrogates for position along groundwater flowpaths were the most important predictors, indicating that much of the control on dissolved solids is related to rock‐water interaction as residence time increases. BRT models additionally support hypotheses of both surficial and deep sources of salinity.

Alabama, Arkansas, Kentucky, Louisiana, Mississipp↗

Quantifying the response of nitrogen speciation to hydrology in the Chesapeake Bay Watershed using a multilevel modeling approach

Excessive nitrogen (N) inputs to coastal waters can lead to severe eutrophication and different chemical forms of N exhibit varying levels of effectiveness in fueling primary production. Efforts to mitigate N fluxes from coastal watersheds are often guided by models that predict changes in N loads as a function of changes in land use, management practices, and climate. However, relatively little is known on the impacts of such changes on the relative fractions of different N forms. We leveraged a long-term dataset of N loads from over 100 river stations to investigate how the fraction, that is, the ratio of to total N ( /TN), changes as a function of spatio-temporal changes in TN loads in the Chesapeake Bay watershed. We built a hierarchical model that separates the response of to changes in TN load occurring at different scales: Across river stations, where differences in TN loads are largely driven by spatial differences in anthropogenic inputs, and within stations, where inter-annual variability in hydrology is a key driver of changes in TN loads. Results suggest that while increases in TN loads resulting from changes in anthropogenic inputs lead to an increase in the fraction, a decrease in the fraction may occur when increases in TN loads are driven by increased streamflow. These results are especially relevant in watersheds that may experience changes in N loads due to both management decisions and climate-driven changes in hydrology.

Chesapeake Bay watershed↗

Spatially consistent but temporally divergent changes in nitrate and phosphorus loads and yields in Illinois watersheds, 1997–2022

Illinois contributes substantial nutrient loads to the Gulf of America, warranting watershed-scale assessment. This study estimated nitrate-nitrogen (nitrate-N) and total phosphorus (TP) loads and yields for 49 Illinois 8-digit hydrologic unit code (HUC8) watersheds draining to the Mississippi River Basin from 1997–2022, comparing recent (2018–2022) to baseline (1997–2011) conditions. Estimates included point and nonpoint source contributions, dissolved phosphorus, and water yields. During the recent period, nonpoint sources dominated nutrient export (82% nitrate-N, 78% TP), though point sources drove high yields in the Chicago area. Spatially, nonpoint source nutrient hotspots persisted with nitrate-N yields highest in east-central and northern Illinois and TP yields higher in southern and western Illinois. Temporally, statewide nitrate-N loads decreased 9%, while TP loads increased 27%. Nitrate-N yields increased in 22 HUC8s and decreased in 20, while TP yields increased in 32 HUC8s and decreased in 9. For both nutrients, baseline yields were negatively correlated with yield changes, indicating high-yielding watersheds tended toward larger decreases or smaller increases. Water yields increased 19% on average but were weakly correlated with nutrient yield changes ( r = 0.23 and 0.20 for nitrate-N and TP). These results reveal spatially persistent yet temporally divergent nutrient export across Illinois, with contrasting nitrate-N and TP trajectories for nonpoint sources.

Illinois↗

A database of natural monthly streamflow estimates from 1950 to 2015 for the conterminous United States

Quantifying and understanding the natural streamflow regime, defined as expected streamflow that would occur in the absence of anthropogenic modification to the hydrologic system, is critically important for the development of management strategies aimed at protecting aquatic ecosystems. Water balance models have been applied frequently to estimate natural flows, but are limited in the number of predictor variables that can be included. Here, a statistical machine learning technique — random forest modeling — was applied to estimate natural flows at a monthly time‐step from 1950 to 2015 for >2.5 million stream reaches in the conterminous United States (U.S.) using 200 potential predictor variables. We describe the development and documentation of this dataset and assess model performance. Model fit statistics (mean Nash–Sutcliffe efficiency = 0.85; observed/expected ratio = 0.94) indicate good correspondence between predicted and observed flows at nearly 2,000 streamgages. As an example application of the dataset, the observed streamflow record at a site prior to and after the construction of an upstream reservoir was compared with estimated natural flows to demonstrate the magnitude of seasonal depletions in streamflow due to the reservoir. This dataset can be applied to quantify natural and anthropogenic processes contributing to streamflow depletion or augmentation, and assess associated ecological effects.

Journal of the American Water Resources Associatio↗

Regional assessment of NLEAP NO 3- N leaching indices

Nonpoint source ground water contamination by nitrate nitrogen (NO 3 -N) leached from agricultural lands can be substantial and increase health risks to humans and animals. Accurate and rapid methods are needed to identify and map localities that have a high potential for contamination of shallow aquifers with NO 3 -N leached from agriculture. Evaluation of Nitrate Leaching and Economic Analysis Package (NLEAP) indices and input variables across an irrigated agricultural area on an alluvial aquifer in Colorado indicated that all leaching indices tested were more strongly correlated with aquifer NO 3 -N concentration than with aquifer N mass. Of the indices and variables tested, the NO 3 -N Leached (NL) index was the NLEAP index most strongly associated with groundwater NO 3 -N concentration (r 2 values from 0.37 to 0.39). NO 3 -N concentration of the leachate was less well correlated with ground water NO 3 -N concentration (r 2 values from 0.21 to 0.22). Stepwise regression analysis indicated that, although inorganic and organic/inorganic fertilizer scenarios had similar r 2 values, the Feedlot Indicator (proximity) variable was significant over and above the NO 3 -N Leached index for the inorganic scenario. The analysis also showed that combination of either Movement Risk Index (MIRI) or NO 3 -N concentration of the leachate with the NO 3 -N Leached index leads to an improved regression, which provides insight into area-wide associations between agricultural activities and ground water NO 3 -N concentration.

Journal of the American Water Resources Associatio↗

Quantifying urban intensity in drainage basins for assessing stream ecological conditions

Three investigations are underway, as part of the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program, to study the relation between varying levels of urban intensity in drainage basins and in-stream water quality, measured by physical, chemical, and biological factors. These studies are being conducted in the vicinities of Boston (Massachusetts), Salt Lake City (Utah), and Birmingham (Alabama), areas where rapid urbanization is occurring. For each study, water quality will be sampled in approximately 30 drainage basins that represent a gradient of urban intensity. This paper focuses on the methods used to characterize and select the basins used in the studies. It presents a methodology for limiting the variability of natural landscape characteristics in the potential study drainage basins and for ranking the magnitude of human influence, or urbanization, based on land cover, infrastructure, and socioeconomic data in potential study basins. Basin characterization efforts associated with the Boston study are described for illustrative purposes.

Alabama, Massachusetts, Utah↗

Mapping river bathymetry with a small footprint green LiDAR: Applications and challenges

Airborne bathymetric Light Detection And Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly sought after for high-resolution mapping of fluvial systems. To evaluate the potential utility of bathymetric LiDAR for applications of this kind, we compared detailed surveys collected using wading and sonar techniques with measurements from the United States Geological Survey’s hybrid topographic⁄ bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). These comparisons, based upon data collected from the Trinity and Klamath Rivers, California, and the Colorado River, Colorado, demonstrated that environmental conditions and postprocessing algorithms can influence the accuracy and utility of these surveys and must be given consideration. These factors can lead to mapping errors that can have a direct bearing on derivative analyses such as hydraulic modeling and habitat assessment. We discuss the water and substrate characteristics of the sites, compare the conventional and remotely sensed river-bed topographies, and investigate the laser waveforms reflected from submerged targets to provide an evaluation as to the suitability and accuracy of the EAARL system and associated processing algorithms for riverine mapping applications.

Journal of the American Water Resources Associatio↗

Analysis and modeling of long‐term stream temperatures on the Steamboat Creek Basin, Oregon: Implications for land use and fish habitat

Steamboat Creek basin is an important source of timber and provides crucial spawning and rearing habitat for anadromous steelhead trout ( Oncorhynchus mykiss ). Because stream temperatures are near the upper limit of tolerance for the survival of juvenile steelhead, the possible long‐term effect of clear‐cut logging on stream temperatures was assessed. Twenty‐year (1969–1989) records of summer stream temperature and flow from four tributaries and two reaches of Steamboat Creek and Boulder Creek (a nearby unlogged watershed) were analyzed. Logging records for the Steamboat Creek basin and air temperature records also were used in the analysis. A time‐series model of the components of stream temperature (seasonal cycle of solar radiation, air temperature, streamflow, an autoregressive term of order 1, and a linear trend variable) was fitted to the water‐temperature data. The linear trend variable was significant in all the fitted models except Bend Creek (a tributary fed by cool ground‐water discharge) and Boulder Creek. Because no trends in either climate (i.e., air temperature) or streamflow were found in the data, the trend variable was associated with the pre‐1969 loss and subsequent regrowth of riparian vegetation and shading canopies.

Oregon↗

Evaluation of select velocity measurement techniques for estimating discharge in small streams across the United States

Multiple instruments and methods exist for collecting discrete streamflow measurements in small streams with low flows, defined here as less than 5.7 m 3 /s (200 ft3/s). Included in the available methods are low-cost approaches that are infrequently used, in part, because their uncertainty is not well known. In this work, we evaluated the accuracy and suitability of three low-cost velocity measurement methods (surface float [SF], velocity head rod [VR], and rising body [RB]) and three conventional current meters (acoustic Doppler velocimeter, and mechanical Price type AA and Price Pygmy meters) relative to discharge calculated from stable artificial hydraulic controls. A total of 231 measurements were made by 20 individuals during 88 site visits to 24 sites in eight states. Accuracies were assessed for all methods and precision was evaluated for the low-cost methods. The median percent error was below 5% for conventional methods, and below 20% for the low-cost methods. The SF was the most accurate (median absolute percent error 14%) and precise (mean percent precision of 11%) low-cost method. The RB and VR, respectively, had 15% and 20% median absolute percent error and 29% and 12% mean percent precision. Results suggest that low-cost methods, when used appropriately, can be used to estimate discharge data under low flow conditions when measurements with conventional methods are not feasible and the associated accuracies meet end-user measurement objectives.

continental United States↗

Glyphosate and its degradation product AMPA occur frequently and widely in U.S. soils, surface water, groundwater, and precipitation

Glyphosate use in the United States increased from less than 5,000 to more than 80,000 metric tons/yr between 1987 and 2007. Glyphosate is popular due to its ease of use on soybean, cotton, and corn crops that are genetically modified to tolerate it, utility in no-till farming practices, utility in urban areas, and the perception that it has low toxicity and little mobility in the environment. This compilation is the largest and most comprehensive assessment of the environmental occurrence of glyphosate and aminomethylphosphonic acid (AMPA) in the United States conducted to date, summarizing the results of 3,732 water and sediment and 1,018 quality assurance samples collected between 2001 and 2010 from 38 states. Results indicate that glyphosate and AMPA are usually detected together, mobile, and occur widely in the environment. Glyphosate was detected without AMPA in only 2.3% of samples, whereas AMPA was detected without glyphosate in 17.9% of samples. Glyphosate and AMPA were detected frequently in soils and sediment, ditches and drains, precipitation, rivers, and streams; and less frequently in lakes, ponds, and wetlands; soil water; and groundwater. Concentrations of glyphosate were below the levels of concern for humans or wildlife; however, pesticides are often detected in mixtures. Ecosystem effects of chronic low-level exposures to pesticide mixtures are uncertain. The environmental health risk of low-level detections of glyphosate, AMPA, and associated adjuvants and mixtures remain to be determined.

Journal of the American Water Resources Associatio↗

Nutrient mass balance and trends, Mobile River Basin, Alabama, Georgia, and Mississippi

A nutrient mass balance - accounting for nutrient inputs from atmospheric deposition, fertilizer, crop nitrogen fixation, and point source effluents; and nutrient outputs, including crop harvest and storage - was calculated for 18 subbasins in the Mobile River Basin, and trends (1970 to 1997) were evaluated as part of the U.S. Geological Survey National Water Quality Assessment (NAWQA) Program. Agricultural nonpoint nitrogen and phosphorus sources and urban nonpoint nitrogen sources are the most important factors associated with nutrients in this system. More than 30 percent of nitrogen yield in two basins and phosphorus yield in eight basins can be attributed to urban point source nutrient inputs. The total nitrogen yield (1.3 tons per square mile per year) for the Tombigbee River, which drains a greater percentage of agricultural (row crop) land use, was larger than the total nitrogen yield (0.99 tons per square mile per year) for the Alabama River. Decreasing trends of total nitrogen concentrations in the Tombigbee and Alabama Rivers indicate that a reduction occurred from 1975 to 1997 in the nitrogen contributions to Mobile Bay from the Mobile River. Nitrogen concentrations also decreased (1980 to 1995) in the Black Warrior River, one of the major tributaries to the Tombigbee River. Total phosphorus concentrations increased from 1970 to 1996 at three urban influenced sites on the Etowah River in Georgia. Multiple regression analysis indicates a distinct association between water quality in the streams of the Mobile River drainage basin and agricultural activities in the basin.

Alabama, Georgia, Mississippi↗

The road to NHDPlus — Advancements in digital stream networks and associated catchments

A progression of advancements in Geographic Information Systems techniques for hydrologic network and associated catchment delineation has led to the production of the National Hydrography Dataset Plus (NHDPlus). NHDPlus is a digital stream network for hydrologic modeling with catchments and a suite of related geospatial data. Digital stream networks with associated catchments provide a geospatial framework for linking and integrating water-related data. Advancements in the development of NHDPlus are expected to continue to improve the capabilities of this national geospatial hydrologic framework. NHDPlus is built upon the medium-resolution NHD and, like NHD, was developed by the U.S. Environmental Protection Agency and U.S. Geological Survey to support the estimation of streamflow and stream velocity used in fate-and-transport modeling. Catchments included with NHDPlus were created by integrating vector information from the NHD and from the Watershed Boundary Dataset with the gridded land surface elevation as represented by the National Elevation Dataset. NHDPlus is an actively used and continually improved dataset. Users recognize the importance of a reliable stream network and associated catchments. The NHDPlus spatial features and associated data tables will continue to be improved to support regional water quality and streamflow models and other user-defined applications.

Journal of the American Water Resources Associatio↗

Regression models of herbicide concentrations in outflow from reservoirs in the midwestern USA, 1992-1993

Reservoirs are used to store water for public water supply, flood control, irrigation, recreation, hydropower, and wildlife habitat, but also often store undesirable substances such as herbicides. The outflow from 76 reservoirs in the midwestern USA, was sampled four times in 1992 and four times in 1993. At least one herbicide was detected in 82.6 percent of all samples, and atrazine was detected in 82.1 percent of all samples. Herbicide properties; topography, land use, herbicide use, and soil type in the contributing drainage area; residence time of water in reservoirs; and timing of inflow, release, and rainfall all can affect the concentration of herbicides in reservoirs. A GIS was used to quantify characteristics of land use, agricultural chemical use, climatic conditions, topographic character, and soil type by reservoir drainage basins. Multiple linear and logistic regression equations were used to model mean herbicide concentrations in reservoir outflow as a function of these characteristics. Results demonstrate a strong association between mean herbicide concentrations in reservoir outflow and herbicide use rates within associated drainage basins. Results also demonstrate the importance of including soils and basin hydrologic characteristics in models used to estimate mean herbicide concentrations.

Journal of the American Water Resources Associatio↗