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Results for “Journal of American Water Resources Association”

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At least 37 records · Page 2Linked to original sources
USGS2009

Reducing streamflow forecast uncertainty: Application and qualitative assessment of the upper klamath river Basin, Oregon

The accuracy of streamflow forecasts depends on the uncertainty associated with future weather and the accuracy of the hydrologic model that is used to produce the forecasts. We present a method for streamflow forecasting where hydrologic model parameters are selected based on the climate state. Parameter sets for a hydrologic model are conditioned on an atmospheric pressure index defined using mean November through February (NDJF) 700-hectoPascal geopotential heights over northwestern North America [Pressure Index from Geopotential heights (PIG)]. The hydrologic model is applied in the Sprague River basin (SRB), a snowmelt-dominated basin located in the Upper Klamath basin in Oregon. In the SRB, the majority of streamflow occurs during March through May (MAM). Water years (WYs) 1980-2004 were divided into three groups based on their respective PIG values (high, medium, and low PIG). Low (high) PIG years tend to have higher (lower) than average MAM streamflow. Four parameter sets were calibrated for the SRB, each using a different set of WYs. The initial set used WYs 1995-2004 and the remaining three used WYs defined as high-, medium-, and low-PIG years. Two sets of March, April, and May streamflow volume forecasts were made using Ensemble Streamflow Prediction (ESP). The first set of ESP simulations used the initial parameter set. Because the PIG is defined using NDJF pressure heights, forecasts starting in March can be made using the PIG parameter set that corresponds with the year being forecasted. The second set of ESP simulations used the parameter set associated with the given PIG year. Comparison of the ESP sets indicates that more accuracy and less variability in volume forecasts may be possible when the ESP is conditioned using the PIG. This is especially true during the high-PIG years (low-flow years). ?? 2009 American Water Resources Association.

Journal of the American Water Resources Associatio↗
USGS2011

A regional modeling framework of phosphorus sources and transport in streams of the southeastern United States

We applied the SPARROW model to estimate phosphorus transport from catchments to stream reaches and subsequent delivery to major receiving water bodies in the Southeastern United States (U.S.). We show that six source variables and five land-to-water transport variables are significant ( p < 0.05) in explaining 67% of the variability in long-term log-transformed mean annual phosphorus yields. Three land-to-water variables are a subset of landscape characteristics that have been used as transport factors in phosphorus indices developed by state agencies and are identified through experimental research as influencing land-to-water phosphorus transport at field and plot scales. Two land-to-water variables – soil organic matter and soil pH – are associated with phosphorus sorption, a significant finding given that most state-developed phosphorus indices do not explicitly contain variables for sorption processes. Our findings for Southeastern U.S. streams emphasize the importance of accounting for phosphorus present in the soil profile to predict attainable instream water quality. Regional estimates of phosphorus associated with soil-parent rock were highly significant in explaining instream phosphorus yield variability. Model predictions associate 31% of phosphorus delivered to receiving water bodies to geology and the highest total phosphorus yields in the Southeast were catchments with already high background levels that have been impacted by human activity.

Journal of the American Water Resources Associatio↗
USGS2010

Comparison of two parametric methods to estimate pesticide mass loads in California's Central Valley

Mass loadings were calculated for four pesticides in two watersheds with different land uses in the Central Valley, California, by using two parametric models: (1) the Seasonal Wave model (SeaWave), in which a pulse signal is used to describe the annual cycle of pesticide occurrence in a stream, and (2) the Sine Wave model, in which first-order Fourier series sine and cosine terms are used to simulate seasonal mass loading patterns. The models were applied to data collected during water years 1997 through 2005. The pesticides modeled were carbaryl, diazinon, metolachlor, and molinate. Results from the two models show that the ability to capture seasonal variations in pesticide concentrations was affected by pesticide use patterns and the methods by which pesticides are transported to streams. Estimated seasonal loads compared well with results from previous studies for both models. Loads estimated by the two models did not differ significantly from each other, with the exceptions of carbaryl and molinate during the precipitation season, where loads were affected by application patterns and rainfall. However, in watersheds with variable and intermittent pesticide applications, the SeaWave model is more suitable for use on the basis of its robust capability of describing seasonal variation of pesticide concentrations.

California↗
USGS2010

The effect of channelization on floodplain sediment deposition and subsidence along the Pocomoke River, Maryland

The nontidal Pocomoke River was intensively ditched and channelized by the mid-1900s. In response to channelization; channel incision, head-cut erosion, and spoil bank perforation have occurred in this previously nonalluvial system. Six sites were selected for study of floodplain sediment dynamics in relation to channel condition. Short- and long-term sediment deposition/subsidence rates and composition were determined. Short-term rates (four years) ranged from 0.6 to 3.6 mm/year. Long-term rates (15-100+ years) ranged from -11.9 to 1.7 mm/year. 137Cs rates (43 years) indicate rates of 0.24 to 7.4 mm/year depending on channel condition. Channelization has limited contact between streamflow and the floodplain, resulting in little or no sediment retention in channelized reaches. Along unchannelized reaches, extended contact and depth of river water on the floodplain resulted in high deposition rates. Drainage of floodplains exposed organic sediments to oxygen resulting in subsidence and releasing stored carbon. Channelization increased sediment deposition in downstream reaches relative to the presettlement system. The sediment storage function of this river has been dramatically altered by channelization. Results indicate that perforation of spoil banks along channelized reaches may help to alleviate some of these issues. ?? 2010 American Water Resources Association. No claim to original U.S. government works.

Maryland↗
USGS2007

Comparison of four artificial substrates and the Ponar grab for benthic invertebrate collection

Four different bottom‐placed artificial substrates were compared with the Ponar grab for collecting benthic invertebrates. Artificial substrate samples of organisms were larger and more diverse than those of the grab. Barbeque Basket samplers caught the most taxa and individuals and Beak Trays caught the least. Chironomids and crustaceans were dominant in artificial substrate samples. Exposure habitat (left or right bank) determined taxa availability, whereas sampler design determined suitability for colonization by the taxa. Diversity for Beak Tray samples was lower than that for other artificial substrates but higher than for Ponar samples. The Barbeque Basket, Bull Basket, and Multiple Plate samples were taxonomically similar. Ponar samples were different, and Beak Trays were of intermediate similarity. As qualitative samplers, Barbeque Baskets were 63 percent efficient, followed by Bull Baskets (55 percent), Multiple Plates (48 percent), Beak Trays (38 percent), and Ponar Grabs (6–10 percent). Bull Baskets required the least and Beak Trays the most replicates to be within a preselected percentage error of the mean at the 95 percent probability level for numbers of taxa and individuals, and for diversity. Under conditions of the study, Bull Baskets ranked highest, followed by Barbeque Baskets and Multiple Plates, in selected performance criteria. Differences between grab and artificial substrate samples are explainable in terms of major riverine habitats and characteristics of the collection methods.

Journal of the American Water Resources Associatio↗
USGS2011

A multi-agency nutrient dataset used to estimate loads, improve monitoring design, and calibrate regional nutrient SPARROW models

Stream-loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long-term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water-quality model, the flow-bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water-quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.

Journal of the American Water Resources Associatio↗
USGS2011

Source and delivery of nutrients to receiving waters in the Northeastern and Mid-Atlantic regions of the United States

This study investigates nutrient sources and transport to receiving waters, in order to provide spatially detailed information to aid water-resources managers concerned with eutrophication and nutrient management strategies. SPAtially Referenced Regressions On Watershed attributes (SPARROW) nutrient models were developed for the Northeastern and Mid-Atlantic (NE US) regions of the United States to represent source conditions for the year 2002. The model developed to examine the source and delivery of nitrogen to the estuaries of nine large rivers along the NE US Seaboard indicated that agricultural sources contribute the largest percentage (37%) of the total nitrogen load delivered to the estuaries. Point sources account for 28% while atmospheric deposition accounts for 20%. A second SPARROW model was used to examine the sources and delivery of phosphorus to lakes and reservoirs throughout the NE US. The greatest attenuation of phosphorus occurred in lakes that were large relative to the size of their watershed. Model results show that, within the NE US, aquatic decay of nutrients is quite limited on an annual basis and that we especially cannot rely on natural attenuation to remove nutrients within the larger rivers nor within lakes with large watersheds relative to the size of the lake.

Journal of the American Water Resources Associatio↗
USGS2011

The Regionalization of National-Scale SPARROW Models for Stream Nutrients

This analysis modifies the parsimonious specification of recently published total nitrogen (TN) and total phosphorus (TP) national‐scale SPAtially Referenced Regressions On Watershed attributes models to allow each model coefficient to vary geographically among three major river basins of the conterminous United States. Regionalization of the national models reduces the standard errors in the prediction of TN and TP loads, expressed as a percentage of the predicted load, by about 6 and 7%. We develop and apply a method for combining national‐scale and regional‐scale information to estimate a hybrid model that imposes cross‐region constraints that limit regional variation in model coefficients, effectively reducing the number of free model parameters as compared to a collection of independent regional models. The hybrid TN and TP regional models have improved model fit relative to the respective national models, reducing the standard error in the prediction of loads, expressed as a percentage of load, by about 5 and 4%. Only 19% of the TN hybrid model coefficients and just 2% of the TP hybrid model coefficients show evidence of substantial regional specificity (more than ±100% deviation from the national model estimate). The hybrid models have much greater precision in the estimated coefficients than do the unconstrained regional models, demonstrating the efficacy of pooling information across regions to improve regional models.

Journal of the American Water Resources Associatio↗
USGS2007

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↗
USGS2018

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↗
USGS2020

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↗
USGS2021

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↗
USGS2026

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↗
USGS2018

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↗
USGS2007

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↗
USGS2007

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↗
USGS2012

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↗