NUTRIENT CONTRIBUTION OF NONPOINT SOURCE RUNOFF IN THE LAS VEGAS VALLEY1

ABSTRACT: A Geographic Information System (GIS) based non‐point source runoff model is developed for the Las Vegas Valley, Nevada, to estimate the nutrient loads during the years 2000 and 2001. The estimated nonpoint source loads are compared with current wastewater treatment facilities loads to determine the non‐point source contribution of total phosphorus (TP), total nitrogen (TN), and total suspended solids (TSS) on a monthly and annual time scale. An innovative calibration procedure is used to estimate the pollutant concentrations for different land uses based on available water quality data at the outlet. Results indicate that the pollutant concentrations are higher for the Las Vegas Valley than previous published values for semi‐arid and arid regions. The total TP and TN loads from nonpoint sources are approximately 15 percent and 4 percent, respectively, of the total load to the receiving water body, Lake Mead. The TP loads during wet periods approach the permitted loads from the wastewater treatment plants that discharge into Las Vegas Wash. In addition, the GIS model is used to track pollutant loads in the stream channels for one of the subwatersheds. This is useful for planning the location of Best Management Practices to control nonpoint pollutant loads.     

Sources and Delivery of Nutrients to the Northwestern Gulf of Mexico from Streams in the South‐Central United States1

Rebich, Richard A., Natalie A. Houston, Scott V. Mize, Daniel K. Pearson, Patricia B. Ging, and C. Evan Hornig, 2011. Sources and Delivery of Nutrients to the Northwestern Gulf of Mexico From Streams in the South‐Central United States. Journal of the American Water Resources Association (JAWRA) 47(5):1061‐1086. DOI: 10.1111/j.1752‐1688.2011.00583.x Abstract: SPAtially Referenced Regressions On Watershed attributes (SPARROW) models were developed to estimate nutrient inputs [total nitrogen (TN) and total phosphorus (TP)] to the northwestern part of the Gulf of Mexico from streams in the South‐Central United States (U.S.). This area included drainages of the Lower Mississippi, Arkansas‐White‐Red, and Texas‐Gulf hydrologic regions. The models were standardized to reflect nutrient sources and stream conditions during 2002. Model predictions of nutrient loads (mass per time) and yields (mass per area per time) generally were greatest in streams in the eastern part of the region and along reaches near the Texas and Louisiana shoreline. The Mississippi River and Atchafalaya River watersheds, which drain nearly two‐thirds of the conterminous U.S., delivered the largest nutrient loads to the Gulf of Mexico, as expected. However, the three largest delivered TN yields were from the Trinity River/Galveston Bay, Calcasieu River, and Aransas River watersheds, while the three largest delivered TP yields were from the Calcasieu River, Mermentau River, and Trinity River/Galveston Bay watersheds. Model output indicated that the three largest sources of nitrogen from the region were atmospheric deposition (42%), commercial fertilizer (20%), and livestock manure (unconfined, 17%). The three largest sources of phosphorus were commercial fertilizer (28%), urban runoff (23%), and livestock manure (confined and unconfined, 23%).     

Nutrient Loadings to Streams of the Continental United States from Municipal and Industrial Effluent1

Maupin, Molly A. and Tamara Ivahnenko, 2011. Nutrient Loadings to Streams of the Continental United States From Municipal and Industrial Effluent. Journal of the American Water Resources Association (JAWRA) 47(5):950‐964. DOI: 10.1111/j.1752‐1688.2011.00576.x Abstract: Data from the United States Environmental Protection Agency Permit Compliance System national database were used to calculate annual total nitrogen (TN) and total phosphorus (TP) loads to surface waters from municipal and industrial facilities in six major regions of the United States for 1992, 1997, and 2002. Concentration and effluent flow data were examined for approximately 118,250 facilities in 45 states and the District of Columbia. Inconsistent and incomplete discharge locations, effluent flows, and effluent nutrient concentrations limited the use of these data for calculating nutrient loads. More concentrations were reported for major facilities, those discharging more than 1 million gallons per day, than for minor facilities, and more concentrations were reported for TP than for TN. Analytical methods to check and improve the quality of the Permit Compliance System data were used. Annual loads were calculated using “typical pollutant concentrations” to supplement missing concentrations based on the type and size of facilities. Annual nutrient loads for over 26,600 facilities were calculated for at least one of the three years. Sewage systems represented 74% of all TN loads and 58% of all TP loads. This work represents an initial set of data to develop a comprehensive and consistent national database of point‐source nutrient loads. These loads can be used to inform a wide range of water‐quality management, watershed modeling, and research efforts at multiple scales.     

Regional Scale Stressor‐Response Models in Aquatic Ecosystems1

Abstract: A systematic method for identification and estimation of regional scale stressor‐response models in aquatic ecosystems will be useful in monitoring and assessment of aquatic resources, determination of regional nutrient criteria and for increased understanding of the differences between regions. The model response variable is chlorophyll a, a measure of algal density, while the stressors include nutrient concentrations from the USEPA Nutrient Criteria Database (NCD) for lakes/ponds and reservoirs of the continental United States. The NCD has observations for both stressors and biological responses determined using methods that are not consistently available at the continental scale. To link multiple environmental stressors to biological responses and quantify uncertainty in model predictions, we take a multilevel modeling approach to the estimation of a linear model for prediction of log Chlorophyll a using predictors log TP and log TN. The multilevel modeling approach allows us to adjust the impact of covariates at all levels (observation, higher level groups) for the simultaneous operation of contextual and individual variability in the outcome. Here, we wish to allow separate regression coefficients for inference regarding similarities and differences between each of 14 ecoregions, and between the two water‐body types, lakes/ponds and reservoirs. We are also interested in the nuisance effects of the categorical variables indicating the type of nitrogen measurements (three levels) and the type of chlorophyll a measurements (four levels) used. Model‐based determination of nutrient criteria points to an apparent incompatibility of criteria developed for nutrient stressors and eutrophication responses using current Environmental Protection Agency’s guidance.     

Improving Predictive Models of In‐Stream Phosphorus Concentration Based on Nationally‐Available Spatial Data Coverages

Spatial data are playing an increasingly important role in watershed science and management. Large investments have been made by government agencies to provide nationally‐available spatial databases; however, their relevance and suitability for local watershed applications is largely unscrutinized. We investigated how goodness of fit and predictive accuracy of total phosphorus (TP) concentration models developed from nationally‐available spatial data could be improved by including local watershed‐specific data in the East Fork of the Little Miami River, Ohio, a 1,290 km² watershed. We also determined whether a spatial stream network (SSN) modeling approach improved on multiple linear regression (nonspatial) models. Goodness of fit and predictive accuracy were highest for the SSN model that included local covariates, and lowest for the nonspatial model developed from national data. Septic systems and point source TP loads were significant covariates in the local models. These local data not only improved the models but enabled a more explicit interpretation of the processes affecting TP concentrations than more generic national covariates. The results suggest SSN modeling greatly improves prediction and should be applied when using national covariates. Including local covariates further increases the accuracy of TP predictions throughout the studied watershed; such variables should be included in future national databases, particularly the locations of septic systems.     

Assessing the Hydrologic and Water Quality Benefits of a Network of Stormwater Control Measures in a SE U.S. Piedmont Watershed

The hydrologic and water quality benefits of an existing engineered stormwater control measures (SCMs) network, along with the alternative stormwater control simulations, were assessed in the rapidly urbanizing Beaverdam Creek watershed located in SE U.S. Piedmont region through the use of distributed Model of Urban Stormwater Improvement Conceptualization stormwater model. When compared with predevelopment conditions, the postdevelopment watershed simulation without SCMs indicated a 2 times increase in total runoff volume, 3 times average increase in peak flow for 1.5‐3.2 cm 6‐h storm events, and 30 times, 12 times, and 3 times higher total suspended solids (TSS), total phosphorous (TP), and total nitrogen (TN) loadings, respectively. The existing SCMs network, in comparison with the postdeveloped watershed without SCMs, reduced the average peak flow rates for 1.5‐3.2 cm 6‐h storm events by 70%, lowered the annual runoff volume by 3%, and lowered TSS, TP, TN annual loads by 57, 51, and 10%, respectively. A backyard rain garden simulation resulted in minimal additional reduction in TSS (1.6%), TP (0.4%), and TN (4%). Model simulations indicate that mandatory 85% TSS and 70% TP annual load reductions in comparison with the predevelopment levels would require the diversion of runoff from at least 70% of the contributing drainage areas runoff into additional offline bioretention basins.     

Statistical and Hybrid Methods Implemented in a Web Application for Predicting Reservoir Inflows during Flood Events

Reservoir management is a critical component of flood management, and information on reservoir inflows is particularly essential for reservoir managers to make real‐time decisions given that flood conditions change rapidly. This study's objective is to build real‐time data‐driven services that enable managers to rapidly estimate reservoir inflows from available data and models. We have tested the services using a case study of the Texas flooding events in the Lower Colorado River Basin in November 2014 and May 2015, which involved a sudden switch from drought to flooding. We have constructed two prediction models: a statistical model for flow prediction and a hybrid statistical and physics‐based model that estimates errors in the flow predictions from a physics‐based model. The study demonstrates that the statistical flow prediction model can be automated and provides acceptably accurate short‐term forecasts. However, for longer term prediction (2 h or more), the hybrid model fits the observations more closely than the purely statistical or physics‐based prediction models alone. Both the flow and hybrid prediction models have been published as Web services through Microsoft's Azure Machine Learning (AzureML) service and are accessible through a browser‐based Web application, enabling ease of use by both technical and nontechnical personnel.     

Phosphorus loading in the Frome catchment, UK: seasonal refinement of the coefficient modeling approach

This paper describes the results of an export coefficient modeling approach to predict total phosphorus (TP) loading in the Frome catchment, Dorset, UK from point and diffuse sources on a seasonal (monthly) basis in 1998 and on an annual basis for 1990-1998. The model predicted an annual TP load of 25 605 kg yr(-1), compared with an observed (measured) value of 23400 kg yr(-1). Monthly loads calculated using the export coefficient model agreed well with monthly observed values except in months of variable discharge, when observed values were low, probably due to infrequent, and therefore unrepresentative, sampling. Comparison between filterable reactive phosphorus (FRP) and TP concentrations observed in the period 1990-1997 showed that trends in FRP could be estimated from trends in TP. A sensitivity analysis (varying individual export coefficients by +/-10%) showed that sewage treatment works (STWs) (3.5%), tilled land (2.7%), meadow-verge-seminatural (1.0%), and mown and grazed turf (0.6%) had the most significant effect (percent difference from base contribution) on model prediction. The model was also used to estimate the effect of phosphorus stripping at STWs in order to comply with a pending change in the European Union wastewater directive. Theoretical reduction of TP from the largest STW in the catchment gave a predicted reduction in TP loading of 2174 kg yr(-1). This illustrates the value of this seasonal export coefficient model as a practical management tool.     

Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States1

Preston, Stephen D., Richard B. Alexander, Gregory E. Schwarz, and Charles G. Crawford, 2011. Factors Affecting Stream Nutrient Loads: A Synthesis of Regional SPARROW Model Results for the Continental United States. Journal of the American Water Resources Association (JAWRA) 47(5):891‐915. DOI: 10.1111/j.1752‐1688.2011.00577.x Abstract: We compared the results of 12 recently calibrated regional SPARROW (SPAtially Referenced Regressions On Watershed attributes) models covering most of the continental United States to evaluate the consistency and regional differences in factors affecting stream nutrient loads. The models – 6 for total nitrogen and 6 for total phosphorus – all provide similar levels of prediction accuracy, but those for major river basins in the eastern half of the country were somewhat more accurate. The models simulate long‐term mean annual stream nutrient loads as a function of a wide range of known sources and climatic (precipitation, temperature), landscape (e.g., soils, geology), and aquatic factors affecting nutrient fate and transport. The results confirm the dominant effects of urban and agricultural sources on stream nutrient loads nationally and regionally, but reveal considerable spatial variability in the specific types of sources that control water quality. These include regional differences in the relative importance of different types of urban (municipal and industrial point vs. diffuse urban runoff) and agriculture (crop cultivation vs. animal waste) sources, as well as the effects of atmospheric deposition, mining, and background (e.g., soil phosphorus) sources on stream nutrients. Overall, we found that the SPARROW model results provide a consistent set of information for identifying the major sources and environmental factors affecting nutrient fate and transport in United States watersheds at regional and subregional scales.     

Use of SWAT to Estimate Spatial Scaling of Phosphorus Export Coefficients and Load Reductions Due to Agricultural BMPS

Phosphorus export coefficients (kg/ha/yr) from selected land covers, also called phosphorus yields, tend to get smaller as contributing areas get larger because some of the phosphorus mobilized on local fields gets trapped during transport to regional watershed outlets. Phosphorus traps include floodplains, wetlands, and lakes, which can then become impaired by eutrophication. The Sunrise River watershed in east central Minnesota, United States, has numerous lakes impaired by excess phosphorus. The Sunrise is tributary to the St. Croix River, whose much larger watershed is terminated by Lake St. Croix, also impaired by excess phosphorus. To support management of these impairments at both local and regional scales, a Soil and Water Assessment Tool (SWAT) model of the Sunrise watershed was constructed to estimate load reductions due to selected best management practices (BMPs) and to determine how phosphorus export coefficients scaled with contributing area. In this study, agricultural BMPs, including vegetated filter strips, grassed waterways, and reduction of soil‐phosphorus concentrations reduced phosphorus loads by 4‐20%, with similar percentage reductions at field and watershed spatial scales. Phosphorus export coefficients from cropland in rotation with corn, soybeans, and alfalfa decreased as a negative power function of contributing area, from an average of 2.12 kg/ha/yr at the upland field scale (~0.6 km²) to 0.63 kg/ha/yr at the major river basin scale (20,000 km²). Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Stream Discharge and Riparian Land Use Influence In-Stream Concentrations and Loads of Phosphorus from Central Plains Watersheds

Total annual nutrient loads are a function of both watershed characteristics and the magnitude of nutrient mobilizing events. We investigated linkages among land cover, discharge and total phosphorus (TP) concentrations, and loads in 25 Kansas streams. Stream monitoring locations were selected from the Kansas Department of Health and Environment stream chemistry long-term monitoring network sites at or near U.S. Geological Survey stream gauges. We linked each sample with concurrent discharge data to improve our ability to estimate TP concentrations and loads across the full range of possible flow conditions. Median TP concentration was strongly linked (R ² = 76%) to the presence of cropland in the riparian zones of the mostly perennial streams. At baseflow, discharge data did not improve prediction of TP, but at high flows discharge was strongly linked to concentration (a threshold response occurred). Our data suggest that on average 88% of the total load occurred during the 10% of the time with the greatest discharge. Modeled reductions in peak discharges, representing increased hydrologic retention, predicted greater decreases in total annual loads than reductions of ambient concentrations because high discharge and elevated phosphorus concentrations had multiplicative effects. No measure of land use provided significant predictive power for concentrations when discharge was elevated or for concentration rise rates under increasing discharge. These results suggest that reductions of baseflow concentrations of TP in streams without wastewater dischargers may be managed by reductions of cropland uses in the riparian corridor. Additional measures may be needed to manage TP annual loads, due to the large percentage of the TP load occurring during a few high-flow events each year.     

DETERMINING NUTRIENT EXPORT COEFFICIENTS AND SOURCE LOADING UNCERTAINTY USING IN‐STREAM MONITORING DATA1

ABSTRACT: Over a three‐year period, flow and nutrients were monitored at 13 sites in the upper North Bosque River watershed in Texas. Drainage areas above sampling sites differed in percent of dairy waste application fields, forage fields, wood/range, and urban land area. A multiple regression approach was used to develop total phosphorus (TP) and total nitrogen (TN) export coefficients for the major land uses in these heterogeneous drainage areas. The largest export coefficients were associated with dairy waste application fields followed by urban, forage fields, and wood/range. An empirical model was then established to assess nutrient contribution by major sources using developed export coefficients and point source loadings from municipal wastewater treatment. This model was verified by comparison of estimated loadings to measured in‐stream data. Monte Carlo simulation techniques were applied to provide an uncertainty analysis for nutrient loads by source, based on the variance associated with each export coefficient. The largest sources of nutrients contributing to the upper North Bosque River were associated with dairy waste application fields and forage fields, while the greatest relative uncertainty in source contribution was associated with loadings from urban and wood/range land uses.     

CALIBRATION OF STORM LOADS IN THE SOUTH PRONG WATERSHED,FLORIDA, USING BASINS/HSPF1

ABSTRACT: The South Prong watershed is a major tributary system of the Sebastian River and adjacent Indian River Lagoon. Continued urbanization of the Sebastian River drainage basin and other watersheds of the Indian River Lagoon is expected to increase runoff and nonpoint source pollutant loads. The St. Johns River Water Management District developed watershed simulation models to estimate potential impacts on the ecological systems of receiving waters and to assist planners in devising strategies to prevent further degradation of water resources. In the South Prong system, a storm water sampling program was carried out to calibrate the water quality components of the watershed model for total suspended solids (TSS), total phosphorous (TP), and total nitrogen (TN). During the period of May to November 1999, water quality and flow data were collected at three locations within the watershed. Two of the sampling stations were located at the downstream end of major watercourses. The third station was located at the watershed outlet. Five storm events were sampled and measured at each station. Sampling was conducted at appropriate intervals to represent the rising limb, peak, and recession limb of each storm event. The simulations were handled by HSPF (Hydrologic Simulation Program‐Fortran). Results include calibration of the hydrology and calibration of the individual storm loads. The hydrologic calibration was continuous over the period 1994 through 1999. Simulated storm runoff, storm loads, and event mean concentrations were compared with their corresponding observed values. The hydrologic calibration showed good results. The outcome of the individual storm calibrations was mixed. Overall, however, the simulated storm loads agreed reasonably well with measured loads for a majority of the storms.     

PREDICTION OF CHLOROPHYLL A CONCENTRATIONS IN FLORIDA LAKES: THE IMPORTANCE OF PHOSPHORUS AND NITROGEN1

ABSTRACT: Models for the prediction of chlorophyll a concentrations were developed and tested using data on 223 Florida lakes. A statistical analysis showed that the best model was log (Chl a) =?2.49 + 0.269 log (TP) + 1.06 log (TN) or log (Chl a) =?2.49 + 1.06 log (TN/TP) + 1.33 log (TP) where Chl a is the chlorophyll a concentration (mg m^-3), TP is the total phosphorus concentration (mg m^-3) and TN is the total nitrogen concentration (mg m^-3). The model yields unbiased estimates of chlorophyll a concentrations over a wide range of lake types and has a 95 percent confidence interval of 29–319 percent of the calculated chlorophyll a concentrations. Other models, especially the published Dillon-Rigler and Jones-Bachmann phosphorus-chlorophyll models, are less precise when applied to Florida lakes. The data support the hypothesis that nitrogen is an important limiting nutrient in hypereutrophic lakes.     

Estimation of Nonpoint Source Nitrate Concentrations in Indiana Rivers Based on Agricultural Drainage in the Watershed

Subsurface tile‐drained agricultural fields are known to be important contributors to nitrate in surface water in the Midwest, but the effect of these fields on nitrate at the watershed scale is difficult to quantify. Data for 25 watersheds monitored by the Indiana Department of Environmental Management and located near a U.S. Geological Survey stream gage were used to investigate the relationship between flow‐weighted mean concentration (FWMC) of nitrate‐N and the subsurface tile‐drained area (DA) of the watershed. The tile DA was estimated from soil drainage class, land use, and slope. Nitrate loads from point sources were estimated based on reported flows of major permitted facilities with mean nitrate‐N concentrations from published sources. Linear regression models exhibited a statistically significant relationship between annual/monthly nonpoint source (NPS) nitrate‐N and DA percentage. The annual model explained 71% of the variation in FWMC of nitrate‐N. The annual and monthly models were tested in 10 additional watersheds, most with absolute errors within 1 mg/l in the predicted FWMC. These models can be used to estimate NPS nitrate for unmonitored watersheds in similar areas, especially for drained agricultural areas where model performance was strongest, and to predict the nitrate reduction when various tile drainage management techniques are employed.     

Effects of watershed configuration and composition on downstream lake water quality

We evaluated the relationships between landscape characteristics and lake water quality in receiving waters by regressing four water quality responses on landscape variables that were measured for whole watersheds and three different buffer distances (30, 60, and 120 m). Classical percolation theory was used to conceptualize nutrient pathways and to explain nonlinear responses. The response variables were total nitrogen (TN), total phosphorus (TP), chlorophyll-a (Chl-a), and Secchi transparency (SD). Landscape data were obtained from satellite image-derived maps of 130 watersheds in Iowa using geographic information systems software. We developed regression models with a stepwise protocol selecting the optimal number of significant explanatory variables. Configuration variables such as contagion, the cohesion of cropland and urban land, and the aggregation index of forest were very important and more important than variables assessing landscape composition (e.g., percentage farmland). Whole watershed models predicted between 15 and 67% of the variability in TN, TP, Chl-a, and SD. Proximity-explicit data offered only slightly improved statistical power over land cover data derived from the entire watershed for variables TN, Chl-a. and SD, but not for TP.     

WATER QUALITY ANALYSIS OF THE HALIFAX RIVER,FLORIDA1

ABSTRACT: An application of the receiving water block of the EPA Storm Water management Model (SWMM) is presented to quantify water quality impacts and evaluated control alternatives for a 208 areawide waste water management plan in Volusia Country, Florida. The water quality impact analyses were conducted for dry-and wet-weather conditions to simulate dissolved oxygen (DO), chlorides, total nitrogen (TN), and total phosphorus (TP) in the Halifax Rivers, Florida, a 40-kilometer-long tidal estuary located on the Atlantic coast of Florida near Daytona Beach. Dry-weather analysis was performed using conventional 7-day, 10-year low flow conditions to determine a set of unit transfer coefficients which estimate the pollutant concentration transferred to any point in the estuary from a constant unit discharge of pollutants at the existing waste water treatment plant outfall locations. Wet-weather analysis was performed by continuous simulation of a typical three-month summer wet season in Florida. Three-month cumulative duration curves of DO, TN and TP concentrations were constructed to estimate the relative value of controlling urban runoff of waste water treatment plant effluent on the Halifax River. The three-month continuous simulation indicated that the greatest change in DO, TN, and TP duration curves is possible by abatement of waste water treatment plant pollution.     

NUTRIENT LOADS TO WISCONSIN LAKES: PART I. NITROGEN AND PHOSPHORUS EXPORT COEFFICIENTS1

ABSTRACT: Export coefficients (kg/km²/yr) for dissolved ortho-phosphate (OP), total phosphorus (TP), total inorganic nitrogen (TIN), and total nitrogen (TN) were derived for watersheds in Wisconsin using data bases available for 17 basins from the U.S. Environmental Protection Agency — National Eutrophication Survey, U.S. Geological Survey, and the Wisconsin Department of Natural Resources. Three general land use categories, representative of most regions in Wisconsin, were established: forest, mixed, and agricultural. Data for the 17 basins indicated greater exports of OP. TP, TIN, and TN as the percentage of forest decreased and agriculture increased. These region-specific coefficients are compared to the values reported in the literature representing much broader areas of the U.S.     

Geostatistical analysis and risk assessment on soil total nitrogen and total soil phosphorus in the Dongting Lake plain area, China

Nonpoint-source pollution and water body eutrophication have become increasing concerns for scientists and policymakers. Nitrogen and phosphorus affect environmental pollution, especially lake eutrophication. To assess the environmental risk of soil total nitrogen (TN) and total phosphorus (TP) pollution, a typical ecological unit of Dongting Lake plain was selected as the experimental site. To verify the stationary of the data, a moving windows technique was adopted. Our results showed that Box-Cox transformation achieved normality in the data set and dampened the effect of outliers. The best theoretical model for semivariogram of TN and TP was a spherical model. The ordinary kriging estimates of TN and TP concentrations were mapped. The integrative comparisons of semivariogram parameters with different trends to the kriging prediction errors of TN and TP indicated that the two-order trend is preferable. Kriging SDs provided valuable information that will increase the accuracy of TN and TP mapping. The probability kriging method is useful to assess the risk of N and P pollution by providing the conditional probability of N and P concentrations exceeding the threshold concentrations of 3.2 and 1.05 g/kg, respectively. The probability distribution of TN and TP at different levels will be helpful to conduct risk assessment, optimize fertilization, and control the pollution of N and P.     

A Multi‐Agency Nutrient Dataset Used to Estimate Loads,Improve Monitoring Design,and Calibrate Regional Nutrient SPARROW Models1

Saad, David A., Gregory E. Schwarz, Dale M. Robertson, and Nathaniel L. Booth, 2011. A Multi‐Agency Nutrient Dataset Used to Estimate Loads, Improve Monitoring Design, and Calibrate Regional Nutrient SPARROW Models. Journal of the American Water Resources Association (JAWRA) 47(5):933‐949. DOI: 10.1111/j.1752‐1688. 2011.00575.x Abstract: 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.