SPARROW Models Used to Understand Nutrient Sources in the Mississippi/Atchafalaya River Basin.

Nitrogen (N) and phosphorus (P) loading from the Mississippi/Atchafalaya River Basin (MARB) has been linked to hypoxia in the Gulf of Mexico. To describe where and from what sources those loads originate, SPAtially Referenced Regression On Watershed attributes (SPARROW) models were constructed for the MARB using geospatial datasets for 2002, including inputs from wastewater treatment plants (WWTPs), and calibration sites throughout the MARB. Previous studies found that highest N and P yields were from the north-central part of the MARB (Corn Belt). Based on the MARB SPARROW models, highest N yields were still from the Corn Belt but centered over Iowa and Indiana, and highest P yields were widely distributed throughout the center of the MARB. Similar to that found in other studies, agricultural inputs were found to be the largest N and P sources throughout most of the MARB: farm fertilizers were the largest N source, whereas farm fertilizers, manure, and urban inputs were dominant P sources. The MARB models enable individual N and P sources to be defined at scales ranging from SPARROW catchments (∼50 km) to the entire area of the MARB. Inputs of P from WWTPs and urban areas were more important than found in most other studies. Information from this study will help to reduce nutrient loading from the MARB by providing managers with a description of where each of the sources of N and P are most important, thus providing a basis for prioritizing management actions and ultimately reducing the extent of Gulf hypoxia.

Vulnerability of streams to legacy nitrate sources.

The influence of hydrogeologic setting on the susceptibility of streams to legacy nitrate was examined at seven study sites having a wide range of base flow index (BFI) values. BFI is the ratio of base flow to total streamflow volume. The portion of annual stream nitrate loads from base flow was strongly correlated with BFI. Furthermore, dissolved oxygen concentrations in streambed pore water were significantly higher in high BFI watersheds than in low BFI watersheds suggesting that geochemical conditions favor nitrate transport through the bed when BFI is high. Results from a groundwater-surface water interaction study at a high BFI watershed indicate that decades old nitrate-laden water is discharging to this stream. These findings indicate that high nitrate levels in this stream may be sustained for decades to come regardless of current practices. It is hypothesized that a first approximation of stream vulnerability to legacy nutrients may be made by geospatial analysis of watersheds with high nitrogen inputs and a strong connection to groundwater (e.g., high BFI).

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.

Nutrient Inputs to the Laurentian Great Lakes by Source and Watershed Estimated Using SPARROW Watershed Models.

Nutrient input to the Laurentian Great Lakes continues to cause problems with eutrophication. To reduce the extent and severity of these problems, target nutrient loads were established and Total Maximum Daily Loads are being developed for many tributaries. Without detailed loading information it is difficult to determine if the targets are being met and how to prioritize rehabilitation efforts. To help address these issues, SPAtially Referenced Regressions On Watershed attributes (SPARROW) models were developed for estimating loads and sources of phosphorus (P) and nitrogen (N) from the United States (U.S.) portion of the Great Lakes, Upper Mississippi, Ohio, and Red River Basins. Results indicated that recent U.S. loadings to Lakes Michigan and Ontario are similar to those in the 1980s, whereas loadings to Lakes Superior, Huron, and Erie decreased. Highest loads were from tributaries with the largest watersheds, whereas highest yields were from areas with intense agriculture and large point sources of nutrients. Tributaries were ranked based on their relative loads and yields to each lake. Input from agricultural areas was a significant source of nutrients, contributing ∼33-44% of the P and ∼33-58% of the N, except for areas around Superior with little agriculture. Point sources were also significant, contributing ∼14-44% of the P and 13-34% of the N. Watersheds around Lake Erie contributed nutrients at the highest rate (similar to intensively farmed areas in the Midwest) because they have the largest nutrient inputs and highest delivery ratio.

Incorporating Uncertainty Into the Ranking of SPARROW Model Nutrient Yields From Mississippi/Atchafalaya River Basin Watersheds.

Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying "high priority" areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient-reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight-digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.

Agriculture-related trends in groundwater quality of the glacial deposits aquifer, central Wisconsin.

Measuring and understanding trends in groundwater quality is necessary for determining whether changes in land-management practices have an effect on groundwater quality. This paper describes an approach that was used to measure and understand trends using data from two groundwater studies conducted in central Wisconsin as part of the USGS NAWQA program. One of the key components of this approach, determining the age of sampled groundwater, gave a temporal component to the snapshots of water quality that were obtained through synoptic-sampling efforts. This approach can be used at other locations where groundwater quality data are collected, groundwater age can be determined, and associated temporal data are available. Results of these studies indicate measured concentrations of nitrate and atrazine plus deethylatrazine were correlated to historical patterns of fertilizer and atrazine use. Concentrations of nitrate in groundwater have increased over time; concentrations of atrazine plus deethylatrazine increased and then decreased. Concentrations of nitrate also were correlated to screen depth below the water level and concentrations of dissolved O(2); concentrations of atrazine plus deethylatrazine were correlated to dissolved O(2) and annual precipitation. To measure trends in concentrations of atrazine plus deethylatrazine, the data, collected over a near-decadal period, were adjusted to account for changes in laboratory-reporting levels and analytical recoveries. Only after accounting for these changes was it apparent that the median concentrations of atrazine plus deethylatrazine decreased over the near-decadal interval between sampling efforts.

Linking ground-water age and chemistry data along flow paths: implications for trends and transformations of nitrate and pesticides.

Tracer-based ground-water ages, along with the concentrations of pesticides, nitrogen species, and other redox-active constituents, were used to evaluate the trends and transformations of agricultural chemicals along flow paths in diverse hydrogeologic settings. A range of conditions affecting the transformation of nitrate and pesticides (e.g., thickness of unsaturated zone, redox conditions) was examined at study sites in Georgia, North Carolina, Wisconsin, and California. Deethylatrazine (DEA), a transformation product of atrazine, was typically present at concentrations higher than those of atrazine at study sites with thick unsaturated zones but not at sites with thin unsaturated zones. Furthermore, the fraction of atrazine plus DEA that was present as DEA did not increase as a function of ground-water age. These findings suggest that atrazine degradation occurs primarily in the unsaturated zone with little or no degradation in the saturated zone. Similar observations were also made for metolachlor and alachlor. The fraction of the initial nitrate concentration found as excess N2 (N2 derived from denitrification) increased with ground-water age only at the North Carolina site, where oxic conditions were generally limited to the top 5 m of saturated thickness. Historical trends in fluxes to ground water were evaluated by relating the times of recharge of ground-water samples, estimated using chlorofluorocarbon concentrations, with concentrations of the parent compound at the time of recharge, estimated by summing the molar concentrations of the parent compound and its transformation products in the age-dated sample. Using this approach, nitrate concentrations were estimated to have increased markedly from 1960 to the present at all study sites. Trends in concentrations of atrazine, metolachlor, alachlor, and their degradates were related to the timing of introduction and use of these compounds. Degradates, and to a lesser extent parent compounds, were detected in ground water dating back to the time these compounds were introduced.

A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis.

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States.

Environmental water-quality zones for streams: a regional classification scheme.

Various approaches have been used to classify large geographical areas into smaller regions of similar water quality or extrapolate water-quality data from a few streams to other unmonitored streams. A combination of some of the strengths of existing techniques is used to develop a new approach for these purposes. In this new approach, referred to here as SPARTA (SPAtial Regression-Tree Analysis), environmental characteristics for each monitored stream are first quantified using a Geographic Information System (GIS) and then regression-tree analysis is used to determine which characteristics are most statistically important in describing the distribution of a specific water-quality constituent. GIS coverages of only the most statistically significant environmental characteristics are then used to subdivide the area of interest into relatively homogeneous environmental water-quality zones. Results from the regression-tree analysis not only define the most important environmental characteristics, but also describe how to subdivide the coverage of the specific characteristic (for example, areas with <26% or >or=26% soil clay content). The resulting regionalization scheme is customized for each water-quality constituent based on the environmental characteristics most statistically related to that constituent. SPARTA was used to delineate areas of similar phosphorus, nitrogen, and sediment concentrations (by including land-use characteristics) and areas of similar potential water quality (by excluding land-use characteristics). The SPARTA approach reduced the variability in water-quality concentrations (phosphorus, total nitrogen, Kjeldahl nitrogen, and suspended sediment) within similarly classified zones from that obtained using the US Environmental Protection Agency's nutrient ecoregions.