Record Search Query: [Keyword='Nutrients']
SPAtially Referenced Regressions On Watershed Attributes (SPARROW) Modeling of Surface-Water Quality
Entry ID: 01-usgs_sparrow-01
Abstract: The SPARROW method uses spatially referenced regressions of contaminant
transport on watershed attributes to support regional water-quality assessment
goals, including descriptions of spatial and temporal patterns in water quality
and identification of the factors and processes that influence those
conditions. The method is designed to reduce the problems of data
interpretation caused by sparse ... sampling, network bias, and basin
The regression equation relates measured transport rates in streams to
spatially referenced descriptors of pollution sources and land-surface and
stream-channel characteristics. Spatial referencing of land-based and
water-based variables is accomplished via superposition of a set of contiguous
land-surface polygons on a digitized network of stream reaches that define
surface-water flow paths for the region of interest.
Water-quality measurements are obtained from monitoring stations located in
a subset of the stream reaches. Water-quality predictors in the model are
developed as a function of both reach and land-surface attributes and include
quantities describing contaminant sources (point and non-point) as well as
factors associated with rates of material transport through the watershed (such
as soil permeability and stream velocity).
Predictor formulae describe the transport of contaminant mass from specific
sources to the downstream end of a specific reach. Loss of contaminant mass
occurs during both overland and in-stream transport.
In calibrating the model, measured rates of contaminant transport are
regressed on predicted transport rates at the locations of the monitoring
stations, giving rise to a set of estimated linear and nonlinear coefficients
from the predictor formulae.
Once calibrated, the model is used to estimate contaminant transport and
concentration in all stream reaches. A variety of regional characterizations of
water-quality conditions are then possible based on statistical summarization
of reach-level estimates. The application of bootstrap techniques allows
estimation of the uncertainty of model coefficients and predictions.
Smith, R.A., G.E. Schwarz, and R.B. Alexander, Regional Interpretation of
Water-Quality Monitoring Data, 1997, Water Resources Research, v. 33, no. 12,
Other references are available at the end of the .pdf version of the journal
Creation and Review Dates