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

dzrobert@usgs.gov (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.