R.B. Alexander, R.A. Smith, G.E. Schwarz, and J. Nolan NAWQA, Nutrient Synthesis Group

1. Estimating the Sources and Transport of Nitrogen in the Mississippi River Basin Using Spatially ReferencedModeling Techniques Upper Mississippi River Basin Nutrient Workshop March 25-26, 2002 R.B. Alexander, R.A. Smith, G.E. Schwarz, and J. Nolan NAWQA, Nutrient Synthesis Group http://water.usgs.gov/nawqa/sparrow/

2. Topics Presented • Spatially referenced modeling techniques • Background on SPARROW • Model applications in the Mississippi Basin • N sources and transport • Updates and enhancements to the models • Near-term and future research

3. Integrates watershed data over multiple spatial scales to predict origin & fate of contaminants SPARROW (SPAtially Referenced Regression on Watershed Attributes) Landscape Features Drainage & Impoundments Monitoring Data Land Use & Sources

4. Features of SPARROWSPAtially Referenced Regression on Watershed Attributes • Spatially referenced source inputs & watershed attributes • Mechanistic structure (mass balance; flow paths; non-conservative flux) • Nested monitoring sites • Spatial nonlinear regression • Empirical estimates of flux to streams & watershed outlets from point & diffuse sources • Mean annual or seasonal flux • Constituents: nutrients, atrazine, fecal bacteria, suspended sediment, streamflow

5. SPARROWEstimated Equation Land-to-water transport Stream Load Error Sources Aquatic transport Soil Permeability Slope Runoff Stream Density Temperature (TN) Nutrient Models Fertilizer Animal Wastes Atmosphere (TN) Industrial & Municipal Wastes Nonagricultural Diffuse Sources Streamflow Water Velocity Channel Length Reservoir Hydraulics

6. TN Yield NASQAN I Sites

7. R-square 0.88 to 0.96

8. Evaluations of SPARROW Models Independent Verification of Coefficients & Predictions • Stream measurements of nutrient flux (monitoring data) • Literature rate coefficients • Catchment yields by land use, per capita waste loads, in-stream decay, reservoir settling rates

9. Evaluations of SPARROW Models Independent Verification of Coefficients & Predictions • Stream measurements of nutrient flux (monitoring data) • Literature rate coefficients • Catchment yields by land use, per capita waste loads, in-stream decay, reservoir settling rates • Inter-model comparisons • U.S., Chesapeake Bay, Neuse/Tar R, & New Zealand SPARROWs, SWAT, HSPF, RivR-N, GWLF, regression methods, watershed process models, N budgets (NRC, 2000; Valigura et al. 2001 AGU volume; Seitzinger et al. in press) • Spatial analyses of prediction errors (test of model misspecification) • e.g., SCOPE N project (Alexander et al. in press)

10. SPARROW Applications to the Mississippi River BasinSource Characterization &Nitrogen Delivery to theGulf of Mexico

11. Total Nitrogen Yield Delivered to the Gulf from NASQAN Monitoring Sites • Sources: model accounts for inputs of major diffuse and point sources of N • Transport: model empirically estimates loss as function of 1st-order decay in different sized channels & water travel time Alexander et al. Nature, 2000

12. Sources of Total Nitrogen at the Mississippi River Outlet to the Gulf

13. SPARROW Estimates of Delivered TN Yield Agriculture Point Sources Atmosphere

14. SPARROW 1st-order loss rates estimated separately for different sized streams • Illustrates use of model to test hypotheses about N loss— inverse relation theoretically expected; i.e., less contact btwn. water column and stream bottom in large channels • SPARROW rates compare favorably with each other and literature rates of denitrification- induced losses; depth major limiting factor explaining N loss • Other channel properties account for large variability – need to understand mechanisms • SPARROW provides effective tool for estimating large-scale transport of N Estimates of In-Stream Nitrogen Loss

15. Dendritic Pattern of N Delivery to Gulf of Mexico from Watershed Outlets • Percentage estimated as a • function of stream attributes • only (loss rate, velocity, length) • Higher proportions of N • delivered from areas close • to large rivers (small streams remove N more effectively) • Large differences in delivery • from neighboring watersheds • Management strategies should • consider location of sources • relative to large streams – a commensurate level of control near large streams will remove more N downstream Alexander et al. Nature, 2000

16. SPARROW ModelingUpdates and Enhancements

17. SPARROW Constituents & Methods • New methods • Stream load estimation • Calibration accommodates more spatially and mathematically complex descriptions of transport or storage (e.g., reach-specific decay) • More spatially detailed watershed infrastructure New / updated constituents • Combine 1991 NAWQA with historical NASQAN WQ data • Nutrients (TN, TP; 1992 update) • Suspended Sediment • Fecal coliform • Atrazine (updated methods) • Flow / velocity

18. RF1 reach RF1 reach watershed boundary

19. Sources of Total Nitrogen in U.S. Streams (1992 model: R2=0.90; 370 sites) • NLCD land-use data allows more detailed estimation of nonagricultural diffuse sources (urban, forests) • Other sources insensitive to addition of land-use terms • Model fitted land-use yields and per-capita waste loads compare favorably with literature rates

20. Total Nitrogen Loss in 75 Reservoirs of the Waikato River Basin, New Zealand • Empirically estimated loss with SPARROW as function of 1st- order settling velocity and areal water load (based on Vollenweider-type models) • TN loss inversely related to reservoir flushing rate—i.e., smaller losses occur in more rapidly flushed reservoirs Alexander et al., Water Resour. Res., in press

21. SPARROW Estimates of Nitrogen Loss in Reservoirs • SPARROW settling rates compare favorably with literature • Magnitude of SPARROW rates suggest denitrification (rather than algal uptake and particulate burial) may be a dominant long- term loss process in reservoirs • Impoundments are prominent features of U.S. landscape (> 70,000)—their location and size may be important to understanding N fate in watersheds

22. SPARROW ApplicationsWater-Quality Management

23. NATURAL BACKGROUND CONCENTRATIONS OF NUTRIENTS (BY NUTRIENT ECOREGION) • STUDY DESIGN • Used study of reference sites by Clark et al, 2000 • Hybrid SPARROW model • Compare with models of S. American & African R. • Make predictions for all reaches in 14 “ecoregions” • Summarize as frequency distributions (see figure) • CONCLUSIONS • TN concentrations exceed background by larger factor than do TP concentrations • Large variation in background in several regions due to runoff & stream size • Background exceeds EPA-proposed criteria in many regions

24. Network Design Using SPARROW Objective: Select the “optimal” set of monitoring locations that improves the precision of model estimates of the “delivered TN yield” to the Gulf of Mexico Method: (a) stratify the distribution of delivered yield for sites (273 NASQAN & NAWQA) and reaches; (b) determine the sample size from each strata that satisfies the objective; (c) randomly select 100 locations from the four strata Additional design scenarios possible: (a) alternate populations of streams having different attributes; (b) effect of station sample size; (c) different objective functions (e.g., concentration)

25. SPARROW Near-Term / Future Research • Temporally variable models: • Stream loads modeled explicitly as function of time (mean-annual loads estimated for selected time periods such as 1987, 1992, and 1997) • Account for multi-year terrestrial storage of nutrients • Include ’91, ’94, and ’97 NAWQA data and 1996-2000 NASQAN data • Simultaneous multi-contaminant models (e.g., N forms; pesticides) • NAWQA Cycle II activities (HST, ACT and NEET topical teams)

26. SPARROW Near-Term / Future Research • Linking deterministic models to SPARROW • Tests of process hypotheses • More detailed management simulations • examples: TOPMODEL, SWAT, GW models (regional SPARROWs) • Evaluation / validation of model source characterizations and in-stream decay rates • N, O isotopes • experimental measurements of denitrification / mass balance studies

27. SPARROW Near-Term / Future Research • Biological modeling • Microbiological (pathogens, indicators) • Chlorophyll and algae • Fish tissue • Benthic invertebrates • “Emerging” contaminants (e.g., antibiotics)

28. Cyber Seminar Presentation on Regional Sparrow Models—April 18, 2002(Chesapeake Bay, New Eng., Neuse/Tar R.) Studies provide an infrastructure for integrating local monitoring data, research, and management activities

29. SPARROW Workshop(Fall, 2002) Three day workshop in Reston, VA: • Introduction to SPARROW modeling for initiating regional or national studies • Presentation of results from national and regional studies • Description of new capabilities • Discussion of potential regions, constituents and applications for future modeling SPARROW Web Site: http://water.usgs.gov/nawqa/sparrow/

31. SPARROW WEBWatershed Data and Model Predictionsfor 62,000 Stream Reaches • Mean-annual streamflow, water velocity, drainage area • MRLC land use (1992) • Population, waste disposal type (1990 Census) • Mean-annual nutrient conditions (yield, concentration, sources, prediction uncertainties) • Natural background nutrient conditions • Public release: Sept. 2002 Internal URL: http://hqsun2.er.usgs.gov/~mierardi/hucmaster