Stephen D. Preston

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

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.

Digital data used to relate nutrient inputs to water quality in the Chesapeake Bay watershed

Digital data sets compiled by the U.S. Geological Survey were used as input for a collection of Spatially Referenced Regressions On Watershed (SPARROW) attributes for the Chesapeake Bay region including parts of Delaware, Maryland, New York, Pennsylvania, Virginia, West Virginia, and the District of Columbia. These regressions use a nonlinear statistical approach to relate nutrient sources and land-surface characteristics to nutrient loads of streams throughout the Chesapeake Bay watershed. A digital segmented-watershed network serves as the primary framework for spatially referencing nutrient-source and land-surface characteristic data within a geographic information system. Flow direction and flow accumulation generated from a 30-meter cell-size Digital Elevation Model and attributes from 1:500,000-scale stream data were used to generate stream and watershed networks. Spatial data sets representing nutrient inputs of total nitrogen and total phosphorus from the early 1990’s were created and compiled from numerous sources. Data include atmospheric deposition, septic systems, point-source locations, land use, land cover, and agricultural sources such as commercial fertilizer and manure. Some land-surface characteristic data sets representing factors that affect the transport of nutrients also were compiled. Data sets include land use, land cover, averageannual precipitation and temperature, slope, hydrogeomorphic regions, and soil permeability. Nutrient-input and land-surface characteristic data sets merged with the segmentedwatershed network provide the spatial detail by watershed segment required by SPARROW. Stream-nutrient load estimates for 132 sampling sites representing the early 1990’s (103 for total nitrogen and 121 for total phosphorus) serve as the dependent variables for the regressions. These estimates were used to calibrate models of total nitrogen and total phosphorus depicting 1992 land-surface conditions. Examples of model predictions consist of stream-nutrient load and source percentages contributed locally to each stream reach, as well as percentages of the load that reach Chesapeake Bay.

Sparrow Modeling to Understand Water-Quality Conditions in Major Regions of the United States: A Featured Collection Introduction

Preston, Stephen D., Richard B. Alexander, and David M. Wolock, 2011. SPARROW Modeling to Understand Water-Quality Conditions in Major Regions of the United States: A Featured Collection Introduction. Journal of the American Water Resources Association (JAWRA) 47(5):887-890. DOI: 10.1111/j.1752-1688.2011.00585.x

The Regionalization of National-Scale SPARROW Models for Stream Nutrients

Abstract 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.

A hydrologic network supporting spatially referenced regression modeling in the Chesapeake Bay watershed

The U.S. Geological Survey has developed a methodology for statistically relating nutrient sources and land-surface characteristics to nutrient loads of streams. The methodology is referred to as SPAtially Referenced Regressions On Watershed attributes (SPARROW), and relates measured stream nutrient loads to nutrient sources using nonlinear statistical regression models. A spatially detailed digital hydrologic network of stream reaches, stream-reach characteristics such as mean streamflow, water velocity, reach length, and travel time, and their associated watersheds supports the regression models. This network serves as the primary framework for spatially referencing potential nutrient source information such as atmospheric deposition, septic systems, point-sources, land use, land cover, and agricultural sources and land-surface characteristics such as land use, land cover, average-annual precipitation and temperature, slope, and soil permeability. In the Chesapeake Bay watershed that covers parts of Delaware, Maryland, Pennsylvania, New York, Virginia, West Virginia, and Washington D.C., SPARROW was used to generate models estimating loads of total nitrogen and total phosphorus representing 1987 and 1992 land-surface conditions. The 1987 models used a hydrologic network derived from an enhanced version of the U.S. Environmental Protection Agencys digital River Reach File, and course resolution Digital Elevation Models (DEMs). A new hydrologic network was created to support the 1992 models by generating stream reaches representing surface-water pathways defined by flow direction and flow accumulation algorithms from higher resolution DEMs. On a reach-by-reach basis, stream reach characteristics essential to the modeling were transferred to the newly generated pathways or reaches from the enhanced River Reach File used to support the 1987 models. To complete the new network, watersheds for each reach were generated using the direction of surface-water flow derived from the DEMs. This network improves upon existing digital stream data by increasing the level of spatial detail and providing consistency between the reach locations and topography. The hydrologic network also aids in illustrating the spatial patterns of predicted nutrient loads and sources contributed locally to each stream, and the percentages of nutrient load that reach Chesapeake Bay.

Spatially Explicit Modeling to Evaluate Regional Stream Water Quality

Spatially referenced regressions on watershed attributes (SPARROW) models have been developed and applied over the past two decades to address the need for large-scale, spatially explicit information on stream water quality conditions. The strength of SPARROW models is that they describe the primary environmental processes that affect the supply and transport of contaminant mass in watersheds, based on the use of stream monitoring and geospatial data to statistically estimate model parameters. SPARROW models were first applied at the scale of the conterminous US, but their use has grown through applications in many smaller regions of the US and in other countries. Recent developments include a web-based decision support system that provides open access to model results without the assistance of technical experts or special software. As it is highlighted in this chapter, SPARROW modeling provides a flexible framework for studying many aspects of water quality to support both research and resource management objectives.