SPARROW Modeling of Surface Water Quality: Applications to the Lake Michigan Basin
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SPARROW Modeling of Surface Water Quality: Applications to the Lake Michigan Basin By Dale M. Robertson* and David A. Saad, Wisconsin WSC Richard B. Alexander and Gregory E. Schwarz, National Center, Reston, VA [email protected] (608) 821-3867
description
SPARROW Modeling of Surface Water Quality: Applications to the Lake Michigan Basin. By Dale M. Robertson* and David A. Saad, Wisconsin WSC Richard B. Alexander and Gregory E. Schwarz, National Center, Reston, VA. *[email protected] (608) 821-3867. - PowerPoint PPT Presentation
Transcript of SPARROW Modeling of Surface Water Quality: Applications to the Lake Michigan Basin
SPARROW Modeling of Surface Water Quality: Applications to the
Lake Michigan Basin
By Dale M. Robertson* and David A. Saad,
Wisconsin WSC
Richard B. Alexander and Gregory E. Schwarz, National Center, Reston, VA
[email protected] (608) 821-3867
SPARROW Water-Quality Model - Description
SPAtially Referenced Regression on Watershed Attributes http://water.usgs.gov/nawqa/sparrow; Smith et al. 1997
Hybrid statistical and mechanistic process structure; mass-balance constraints; data-driven, nonlinear estimation of parameters
Separates land and in-stream processes
Once calibrated, the model has physically interpretable coefficients; model supports hypothesis testing and uncertainty estimation
Predictions of mean-annual flux reflect long-term, net effects of nutrient supply and loss processes in watersheds
Hybrid statistical and mechanistic process structure; mass-balance constraints; data-driven, nonlinear estimation of parameters
TN Flux (metric tons/yr)< 100100 to 250250 to 1,000> 1,000
States
KEY
SPARROW Predictions of Total Nitrogen Flux
SPARROW Predictions of Nitrogen Flux
USEPA RF1 - 62,000 reaches nationally (~3,200 Upper Miss.) ~ HUC12
TN Flux (metric tons/yr)< 100100 to 250250 to 1,000> 1,000
States
KEY
SPARROW Predictions of Total Nitrogen Flux
SPARROWSPAtially Referenced Regressions On Watershed Attributes
Total Nitrogen Load
Top 4 %
1992 Nitrogen SPARROW Model Output – Alexander and others, 2007
Total Nitrogen – Delivered Incremental Yield
Total Nitrogen – Delivered Incremental Yield
Top 150
2002 Nitrogen SPARROW Output
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
0 25 50 75 100 125 150 175 200
Original Rank
Incr
emen
tal
N Y
ield
(kg
/km2 )
Ranked Incremental Nitrogen Yields From the HUCS, with 90 % CI’s
90 Confidence Intervals for Yields and Ranks
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800
Original Rank
Inc
rem
en
tal N
Yie
ld (
kg
/km
2)
HUCS In or Potentially In The Top 150 For TN
Take Advantage of Data from Other USGS and Other Agency Programs
Sites used in National Models Sites Planned to be used in Regional Models
U.S. Geological Survey SPARROW models
Dale Robertson & Dave Saad, WI
Richard Rebich, MS
Lori Sprague, CO
MRB SPARROWLead ScientistsCoordinator – Steve Preston
Anne Hoos, TN
Richard Moore,NHDan Wise, OR
2002 Models
Mississippi River SPARROW Model
Robertson & Saad, WI
Rebich, MS
Sprague, CO
Mississippi River SPARROW Coordinator: Dale Robertson
Richard Alexander, VA
SPARROW Modeling Result for the Upper Midwest
Incremental Yield Ranking by Incremental Yield
Future Improvements from Regional SPARROW Models
1. Better spatial resolution – More sites and especially more smaller sites, should lead to more accurate predictions at smaller scales.
2. Further reductions in biases.
3. Better definition of source terms – better point-source data, more sites in unique areas, possible better local GIS inputs.
4. Better able to address more regional and local questions.
