An increase in the flux of nitrogen from the Mississippi river during the latter half of the twentieth century has caused eutrophication and chronic seasonal hypoxia in the shallow waters of the Louisiana shelf in the northern Gulf of Mexico. This has led to reductions in species diversity, mortality of benthic communities and stress in fishery resources. There is evidence for a predominantly anthropogenic origin of the increased nitrogen flux, but the location of the most significant sources in the Mississippi basin responsible for the delivery of nitrogen to the Gulf of Mexico have not been clearly identified, because the parameters influencing nitrogen-loss rates in rivers are not well known. Here we present an analysis of data from 374 US monitor ing stations, including 123 along the six largest tributaries to the Mississippi, that shows a rapid decline in the average first-order rate of nitrogen loss with channel size--from 0.45 day (-1) in small streams to 0.005 day (-1) in the Mississippi river. Using stream depth as an explanatory variable, our estimates of nitrogen-loss rates agreed with values from earlier studies. We conclude that the proximity of sources to large streams and rivers is an important determinant of nitrogen delivery to the estuary in the Mississippi basin, and possibly also in other large river basins.

Seasonal hypoxia in the northern Gulf of Mexico has been linked to increased nitrogen fluxes from the Mississippi and Atchafalaya River Basins, though recent evidence shows that phosphorus also influences productivity in the Gulf. We developed a spatially explicit and structurally detailed SPARROW water-quality model that reveals important differences in the sources and transport processes that control nitrogen (N) and phosphorus (P) delivery to the Gulf. Our model simulations indicate that agricultural sources in the watersheds contribute more than 70% of the delivered N and P. However, corn and soybean cultivation is the largest contributor of N (52%), followed by atmospheric deposition sources (16%); whereas P originates primarily from animal manure on pasture and rangelands (37%), followed by corn and soybeans (25%), other crops (18%), and urban sources (12%). The fraction of in-stream P and N load delivered to the Gulf increases with stream size, but reservoir trapping of P causes large local-and regional-scale differences in delivery. Our results indicate the diversity of management approaches required to achieve efficient control of nutrient loads to the Gulf. These include recognition of important differences in the agricultural sources of N and P, the role of atmospheric N, attention to P sources downstream from reservoirs, and better control of both N and P in close proximity to large rivers.

The National Institutes of Health chronic prostatitis symptom index provides a valid outcome measure for men with chronic prostatitis. The index is psychometrically robust, easily self-administered and highly discriminative. It was formally developed and psychometrically validated, and may be useful in clinical practice as well as research protocols.

Abstract. We describe a method for using spatially referenced regressions of contaminant transport on watershed attributes (SPARROW) in regional water-quality assessment. The method is designed to reduce the problems of data interpretation caused by sparse sampling, network bias, and basin heterogeneity. The regression equation relates measured transport rates in streams to spatially referenced descriptors of pollution sources and land-surface and stream-channel characteristics. Regression models of total phosphorus (TP) and total nitrogen (TN) transport are constructed for a region defined as the nontidal conterminous United States. Observed TN and TP transport rates are derived from water-quality records for 414 stations in the National Stream Quality Accounting Network. Nutrient sources identified in the equations include point sources, applied fertilizer, livestock waste, nonagricultural land, and atmospheric deposition (TN only). Surface characteristics found to be significant predictors of land-water delivery include soil permeabili•, stream density, and temperature (TN only). Estimated instream decay coefficients for the two contaminants decrease monotonically with increasing stream size. TP transport is found to be significantly reduced by reservoir retention. Spatial referencing of basin attributes in relation to the stream channel network greatly increases their statistical significance and model accuracy. The method is used to estimate the proportion of watersheds in the conterminous United States (i.e., hydrologic cataloging units) with outflow TP concentrations less than the criterion of 0.1 mg/L, and to classify cataloging units according to local TN yield (kg/km2/yr). IntroductionThe objectives of regional water-quality assessments are to describe spatial and temporal patterns in water quality and identify the factors and processes that influence those condi- data from monitoring networks, certain commonly encountered problems make it difficult to interpret point-level waterquality data in areal terms and thus meet the objectives of regional water-quality assessments. Even when their objectives are clearly established and sampling programs are well planned, regional water-quality assessments are often complicated by (1) sparseness of sampling locations due to cost constraints, (2) spatial biases in the sampling network due to the need to target sampling toward specific pollution sources, and (3) drainage basin heterogeneity. These complications impede data interpretation in distinct ways by limiting sample sizes, reducing the regional representativeness of the sampling network, and limiting the ability to relate in-stream conditions to specific pollution sources.In this paper, we describe a method for interpreting monitoring data that reduces the commonly encountered problems of network sparseness, bias, and basin heterogeneity. The method involves construction of a statistical model relating water-quality observations to spatially referenced (and potentially temporally referenced) data on basin a...

SPARROW (SPAtially Referenced Regressions On Watershed attributes) is a watershed modeling technique for relating water-quality measurements made at a network of monitoring stations to attributes of the watersheds containing the stations. The core of the model consists of a nonlinear regression equation describing the non-conservative transport of contaminants from point and diffuse sources on land to rivers and through the stream and river network. The model predicts contaminant flux, concentration, and yield in streams and has been used to evaluate alternative hypotheses about the important contaminant sources and watershed properties that control transport over large spatial scales. This report provides documentation for the SPARROW modeling technique and computer software to guide users in constructing and applying basic SPARROW models. The documentation gives details of the SPARROW software, including the input data and installation requirements, and guidance in the specification, calibration, and application of basic SPARROW models, as well as descriptions of the model output and its interpretation. The documentation is intended for both researchers and water-resource managers with interest in using the results of existing models and developing and applying new SPARROW models. The documentation of the model is presented in two parts. Part 1 provides a theoretical and practical introduction to SPARROW modeling techniques, which includes a discussion of the objectives, conceptual attributes, and model infrastructure of SPARROW. Part 1 also includes background on the commonly used model specifications and the methods for estimating and evaluating parameters, evaluating model fit, and generating water-quality predictions and measures of uncertainty. Part 2 provides a user's guide to SPARROW, which includes a discussion of the software architecture and details of the model input requirements and output files, graphs, and maps. The text documentation and computer software are available on the Web at http://water.usgs.gov/nawqa/sparrow/sparrow-mod.html .