Figure 1: Example and illustration of the spatial framework that forms the basis of SPARROW. The dark black line represents the drainage boundary for a watershed. At the downstream end of the watershed is a monitoring site that can be used for model calibration. Upstream of the monitoring site, the streams in the watershed are broken up into a number of segments referred to as stream reaches. Drainage boundaries and the contributing areas for stream reaches are defined and illustrated by separate colors. Figure & caption from: https://water.usgs.gov/nawqa/sparrow/FAQs/faq.html#top
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 such as contaminant sources and environmental factors that affect rates of delivery to streams and in-stream processing (Figure 1). The core of the model consists of a nonlinear regression equation describing the non-conservative transport of contaminants from point and non-point (or “diffuse”) sources on land to rivers and through the stream and river network (Figure 2).
USGS scientists developed SPARROW (Smith et al., 1997) to (a) utilize monitoring data and watershed information to better explain the factors that affect water quality, (b) examine the statistical significance of contaminant sources, environmental factors, and transport processes in explaining predicted contaminant loads, and (c) provide a statistical basis for estimating stream loads in unmonitored locations.
The model estimates contaminant concentrations, fluxes (or “mass,” which is the product of concentration and streamflow), and yields in streams (mass of nutrients entering a stream per acre of land), and evaluates the contributions of selected contaminant sources and watershed properties that control transport throughout large river networks. It empirically estimates the origin and fate of contaminants in streams and receiving bodies, and quantifies uncertainties in these estimates based on coefficient error and unexplained variability in the observed data.
The SPARROW model builds on actual stream monitoring by using spatially comprehensive geospatial data in a calibrated SPARROW model to predict water-quality conditions at unmonitored stream locations. The geospatial data sets describe fertilizer and manure applications, atmospheric deposition to the land surface and urban sources. The model predictions are illustrated through detailed maps that provide information about contaminant loadings and source contributions at multiple scales for specific stream reaches, basins, or other geographic areas.
SPARROW methods and selected results for watersheds across the U.S. are presented in Smith et al. (1997). The theory, model documentation, and illustrated user application of SPARROW can be found in Schwarz et al. (2006).
Model description modified from the USGS SPARROW website
Figure 2: Generalized major land-use features included in the SPARROW watershed model. Statistical methods are used to relate water-quality monitoring data to upstream sources and watershed characteristics that affect the fate and transport of constituents to streams, estuaries, and other receiving water bodies. Figure & caption from: https://pubs.usgs.gov/fs/2009/3019/pdf/fs_2009_3019.pdf
References:
Schwarz, G. E., A. B. Hoos, R. B. Alexander, and R. A. Smith (2006) The SPARROW Surface Water-Quality Model: Theory, Application and User Documentation, U.S. Geological Survey Techniques and Methods Book 6, Section B, Chapter 3. Available at: https://pubs.usgs.gov/tm/2006/tm6b3/
Smith, R. A., G. E. Schwarz, and R. B. Alexander (1997) Regional interpretation of water-quality monitoring data, Water Resources Research, v. 33, no. 12, pp. 2781-2798