SPARROW Modeling in the Mississippi and Atchafalaya River Basins (MARB) Dale Robertson, Richard Alexander, and David Saad U.S. Geological Survey USGS/USEPA.

Slides:



Advertisements
Similar presentations
Institute of Freshwater Ecology and Inland Fisheries Changes of agricultural diffuse nutrient inputs in major European river systems and their contribution.
Advertisements

Overview – Nutrient Fate and Transport Mark B. David University of Illinois at Urbana-Champaign Presented at Building Science Assessments for State-Level.
Land use effect on nutrient loading – nutrient models new assessment tools Inese Huttunen, Markus Huttunen and Bertel Vehviläinen Finnish Environment Institute.
Agricultural and Biological Engineering SWFREC, UF/IFAS Immokalee.
Watersheds and the Hydrologic Cycle
Phosphorus Index Based Management Douglas Beegle Dept. of Crop and Soil Sciences Penn State University
Delaware River Basin SPARROW Model Mary Chepiga Susan Colarullo Jeff Fischer
SPARROW Watershed Modeling of the Entire Great Lakes Basin IAGLR Conference, McMaster University May 29, 2014 (608) By Dale.
U.S. Department of the Interior U.S. Geological Survey Welcome to the USGS Webinar: New Science and Online Management Tools to Help Guide Action on Nutrients.
Developing Modeling Tools in Support of Nutrient Reduction Policies Randy Mentz Adam Freihoefer, Trip Hook, & Theresa Nelson Water Quality Modeling Technical.
Defining Land Management in the Wisconsin River Basin Defining Land Management in the Wisconsin River Basin Adam Freihoefer Wisconsin Department of Natural.
U.S. Department of the Interior U.S. Geological Survey Nutrient Loads to the Gulf of Mexico Mike Woodside U.S. Geological Survey TN.
Scenario Builder and Watershed Model Progress toward the MPA Gary Shenk, Guido Yactayo, Gopal Bhatt Modeling Workgroup 12/2/14 1.
SOURCES AND FLUX OF NUTRIENTS IN THE MISSISSIPPI RIVER BASIN: MONITORING, MODELING, & RESEARCH NEEDS Donald A. Goolsby, U.S. Geological Survey.
The Wisconsin River TMDL: Linking Monitoring and Modeling Ann Hirekatur, Pat Oldenburg, & Adam Freihoefer March 7, 2013 Wisconsin River TMDL Project Team.
Contaminant Source and Watershed Characterization Data Needs Gregory McIsaac, Robert Howarth, and Richard B. Alexander Univ. of Illinois Cornell Univ.
Estimating the Sources and Transport of Nitrogen in the Mississippi River Basin Using Spatially Referenced Modeling Techniques R.B. Alexander, R.A. Smith,
Applications of Scaling to Regional Flood Analysis Brent M. Troutman U.S. Geological Survey.
SPARROW Modeling in the Mississippi River Basin Iowa Science Assessment Davenport, IA Nov. 14, 2012 (608) By Dale M. Robertson*
0 The National Hydrography Dataset Plus a tool for SPARROW Watershed Modeling Richard Moore (presented by Alan Rea)
A FRAMEWORK FOR ASSESSING THE PERFORMANCE OF DWM AT LARGE SCALE MOHAMED A. YOUSSEF and R. WAYNE SKAGGS 1 By.
NuGIS: a Nutrient Use Geographic Information System March 29-31, 2011 Denver, Colorado Paul Fixen Ryan Williams and Quentin Rund.
Water Quality Modeling in GIS Application of Schematic Network Processing Schema Links and Nodes have unique behaviors based on their type A framework.
Soil Water Assessment Tool (SWAT) Model Input
SPARROW Water- Quality Modeling: Application of the National Hydrography Dataset What is SPARROW? Use of NHD SPARROW results By Craig Johnston and Richard.
Impact of Climate Change on Flow in the Upper Mississippi River Basin
Economic and Biophysical Models to Support Conservation Policy: Hypoxia and Water Quality in the Upper Mississippi River Basin CARD Resources and Environmental.
Chesapeake Bay Program Incorporation of Lag Times into the Decision Process Gary Shenk 10/16/12 1.
Transitory storage of N R in watersheds occurs in both surface and subsurface reservoirs. The factors pertaining to storage examined here are: precipitation,
Predicting Sediment and Phosphorus Delivery with a Geographic Information System and a Computer Model M.S. Richardson and A. Roa-Espinosa; Dane County.
Nonpoint Source Pollution u Some basic principles u Example study of total pollution loads in the Corpus Christi Bay System –rainfall-runoff relationship.
Science Assessment to Support an Illinois Nutrient Reduction Strategy Mark David, George Czapar, Greg McIsaac, Corey Mitchell March 11,
Assessing Alternative Policies for the Control of Nutrients in the Upper Mississippi River Basin Catherine L. Kling, Silvia Secchi, Hongli Feng, Philip.
Watershed Management Assessment Through Modeling: SALT and CEAP Dr. Claire Baffaut Water Quality Short Course Boone County Extension Office April 12, 2007.
Forecasting changes in water quality and aquatic biodiversity in response to future bioenergy landscapes in the Arkansas-White-Red River basin Peter E.
Iowa Nutrient Load Estimations for Point and Non-point Sources Iowa DNR November 14, 2012.
SPARROW Surface Water Quality Workshop October 29-31, 2002 Reston, Virginia Section 5. Comparison of GIS Approaches, Data Sources and Management.
Modeling experience of non- point pollution: CREAMS (R. Tumas) EPIC (A. Povilaitis and R.Tumas SWRRBWQ (A. Dumbrauskas and R. Tumas) AGNPS (Sileika and.
1 Evaluating and Estimating the Effect of Land use Changed on Water Quality at Selorejo Reservoir, Indonesia Mohammad Sholichin Faridah Othman Shatira.
Gulf of Mexico Hypoxia and Mississippi River Basin Nutrient Losses Herb Buxton, USGSRob Magnien, NOAA Co-Chairs, Monitoring, Modeling, and Research Workgroup,
How Breakthroughs in Information Systems Can Impact Local Decisions Bruce Babcock Center for Agricultural and Rural Development Iowa State University.
Twinning water quality modelling in Latvia Helene Ejhed
U.S. Department of the Interior U.S. Geological Survey Using Monitoring Data from Multiple Networks/Agencies to Calibrate Nutrient SPARROW* Models, Southeastern.
Delaware River Basin SPARROW Model Mary Chepiga, , Susan Colarullo, , Jeff Fischer, ,
Chesapeake Bay Program Decision Support System Management Actions Watershed Model Bay Model Criteria Assessment Procedures Effects Allocations Airshed.
Invest Nutrient Retention model Yonas Ghile.
Vision for the National Geospatial Framework for Surface Water Robert M. Hirsch Associate Director for Water U.S. Department of the Interior U.S. Geological.
Patapsco and Back River HSPF Watershed Model Part II – Water Quality Maryland Department of the Environment.
Gulf of Mexico Hypoxia and Nutrient Management in the Mississippi River Basin Herb Buxton, U.S. Geological Survey.
Clifton Bell, P.E., P.G. Chesapeake Bay Modeling Perspectives for the Regulated Community.
KWWOA Annual Conference April 2014 Development of a Kentucky Nutrient Strategy Paulette Akers Kentucky Division of Water Frankfort, KY.
Relating Surface Water Nutrients in the Pacific Northwest to Watershed Attributes Using the USGS SPARROW Model Daniel Wise, Hydrologist US Geological Survey.
Building an OpenNSPECT Database for Your Watershed Shan Burkhalter and Dave Eslinger National Oceanic and Atmospheric Administration (NOAA) Office for.
Opportunities for Collaboration on Water- Quality Issues in the Mississippi River Basin Herb Buxton, Office of Water Quality.
Integrating the NAWQA approach to assessments in rivers and streams By Donna Myers, Bill Wilber, Anne Hoos, and Charlie Crawford U.S. Geological Survey,
Surface Water Surface runoff - Precipitation or snowmelt which moves across the land surface ultimately channelizing into streams or rivers or discharging.
SPARROW: A Model Designed for Use With Monitoring Networks Richard A. Smith, Gregory E. Schwarz, and Richard B. Alexander US Geological Survey, Reston,
U.S. Department of the Interior U.S. Geological Survey Reston, Virginia (703) NHD Flow and Velocity Project Greg Schwarz, Reston,
Controls on Catchment-Scale Patterns of Phosphorous in Soil, Streambed Sediment, and Stream Water Marcel van der Perk, et al… Journal of Environmental.
Science Assessment to Support an Illinois Nutrient Reduction Strategy Mark David, George Czapar, Greg McIsaac, Corey Mitchell August 8,
Effect of Potential Future Climate Change on Cost-Effective Nonpoint Source Pollution Reduction Strategies in the UMRB Manoj Jha, Philip Gassman, Gene.
Nitrogen Budgets for the Mississippi River Basin using the linked EPIC-CMAQ-NEWS Models Michelle McCrackin, Ellen Cooter, Robin Dennis, Jana Compton, John.
Predicting the hydrologic implications of land use change in forested catchments Dennis P. Lettenmaier Department of Civil and Environmental Engineering.
Bayesian SPARROW Model Song Qian Ibrahim Alameddine The University of Toledo American University of Beirut.
Phosphorous Transport in Surface Overland Flow
Water Quality Analysis for Selected Streams in Utah and Idaho
Nonpoint Source Pollution
Image courtesy of NASA/GSFC
Iowa Agriculture Water Alliance
Jacob Piske, Eric Peterson, Bill Perry
Presentation transcript:

SPARROW Modeling in the Mississippi and Atchafalaya River Basins (MARB) Dale Robertson, Richard Alexander, and David Saad U.S. Geological Survey USGS/USEPA WEBEX Meeting June 29, 2007

Outline Overview of SPARROW Recent advances in SPARROW and applications to the Mississippi/Atchafalaya R. Basin Summary of nitrogen and phosphorus results for large regional basins Preliminary watershed rankings – nutrient delivery to the Gulf Future SPARROW modeling

SPARROW Water-Quality Model SPAtially Referenced Regression on Watershed Attributes Smith et al Hybrid statistical and mechanistic process structure; mass-balance constraints; data-driven, nonlinear estimation of parameters Spatially explicit; separates land and water processes 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

Sources Land-to-water transport SPARROW modeling approach: - Regress water-quality conditions (monitored load) on upstream sources and factors controlling transport - Incorporates instream decay of nutrients Monitored load Instream transport

Nonlinear Regression Model SPARROW SPAtially Referenced Regressions On Watershed Attributes For each watershed

Estimation of mean-annual nutrient load at stream monitoring sites – Model Inputs Log Load (kg/day) 1992 Base Year Actual Load Predicted Load Load Confidence Interval Mean-annual TN load for 1992 base year (detrended; flow-adjusted )

SPARROWs Reach-Scale Mass Balance Reach network relates watershed data to monitored loads Load leaving a reach = Load generated within upstream reaches and transported to the reach via the stream network + Load originating within the reachs incremental watershed and delivered to the reach segment

Earlier SPARROW Results Total Nitrogen Delivery to the Gulf of Mexico 1987 Base Year Agriculture Municipal Wastewater Atmosphere Alexander et al. 2000, Nature

Model structure: specification, flux- routing algorithms, stream monitoring loads, documentation Data infrastructure: climate, 1-km DEM, 30-m NLCD land use, cropping and drainage systems Result: Added complexity Model accuracy improved by 20% Recent Advances in SPARROW Climate Watersheds Topography Land Use Artificial Drainage

SPARROW Sources and Transport Features NUTRIENT SOURCES (1992) Urban and population sources Atmospheric N deposition Farm fertilizer use allocated to major crops: –County fertilizer sales and expenditures; crop acreage –NLCD agricultural land use –State application rates (corn, soybeans, cotton, wheat, other crops) –Corn/soybean rotations N 2 fixation – cultivated lands Animal manure: –Non-recoverable on pasture/rangelands –Recoverable on crops Natural and residual sources (lands in forest, barren, shrub) AQUATIC ATTENUATION Streams –First-order decay ~ f(water travel time, flow and depth) Reservoirs –First-order decay ~ f(areal hydraulic loadratio of outflow to surface area) LAND-TO-WATER DELIVERY Climate (precipitation, temperature) Soils (permeability) Topography/subsurface (slope, specific catchment area) Artificial drainage (tiles, ditches)

SPARROW Delivery of Agricultural Nutrients to Streams CROP NUTRIENTS COMMERCIAL FERTILIZER BIOLOGICAL N 2 FIXATION ANIMAL MANURE (Non-recoverable) UNCONFINED ANIMALS RECOVERABLE MANURE CONFINED ANIMALS Model Source & Delivery Coefficients Model Source & Delivery Coefficients STREAMS & RESERVOIRS N P Harvesting

The Improved SPARROW Nutrient Models Observed vs. Predicted Yield

Stream and Reservoir Transport for 1992

SPARROW Rates of Aquatic Nutrient Loss Nutrient removal rate declines in larger rivers and more rapidly flushed reservoirs Nitrogen literature rates from Howarth et al. 1996; Seitzinger et al. 2002; Bohlke et al. 2004; Mulholland et al. 2004) STREAMSRESERVOIRS

Percentage of Stream Nutrients Delivered to the Gulf of Mexico Total Nitrogen Total Phosphorus Remove 1 kg at Gulf outlet Remove 1.1 kg = 1/0.9 Remove 4 kg = 1/0.25

Aquatic Removal of Nutrients in MARB Regional Watersheds Regional Watersheds

Nutrient Source Contributions to Stream Flux: Types and Regional Geography

Sources Contributions to Stream Nutrient Flux Mississippi River at St. Francisville, LA

Regional Contributions to the Stream Nutrient Flux to the Gulf of Mexico Regional Watersheds

Changes in Stream Nutrient Flux, 1992 to 2002 Simulate changes in flow-adjusted stream nutrient flux Account for changes in population and agriculture (animal manure; crop fertilizer application, acreage, and production) Account for changes in harvested nutrients with changes in marginal rate of crop production Assume steady-state conditions with constant model coefficients over time

Simulated Changes in Flow-Adjusted Nutrient Flux, 1992 to 2002 Changes in flux typically less than 5% Geography of 2002 source shares are generally unchanged from 1992 *statistically sig. (p<0.06)

MARB Watershed Rankings Nutrient Delivery to the Gulf of Mexico for 1992 Preliminary watershed rankings based on nutrient delivery to the Gulf Try to answer questions that have been popping up during past discussions. Future SPARROW modeling - Additional Refinements to the SPARROW models

Definitions: Load – Total amount of a constituent transported – (kgs) Incremental Yield – Amount of a constituent transported per unit area between two points – kg/km 2 Delivered Incremental Yield – Amount of a constituent transported per unit area between two points that is delivered or transported to some specific point – kg/km 2 Yield – Total amount of a constituent transported per unit area – kg/km 2

Total Nitrogen Load – Compare with Monitoring Data - Can be used to estimate instream concentrations Top 4 % 1992 Nitrogen SPARROW Model Output

Total Nitrogen – Incremental Yield - Can be used to demonstrate the highest export areas 1992 Nitrogen SPARROW Model Output

Total Nitrogen – Incremental Yield Top 10 % 1992 Nitrogen SPARROW Model Output

Total Nitrogen – Delivered Incremental Yield to the Gulf 1992 Nitrogen SPARROW Model Output

Total Nitrogen – Delivered Incremental Yield to the Gulf Top 10 % 1992 Nitrogen SPARROW Model Output

Total Nitrogen – Delivered Incremental Yield HUC 8 Scale 1992 Nitrogen SPARROW Model Output

Total Nitrogen – Delivered Incremental Yield Top 100 Top 100 represent 42% of the Total Load

Total Nitrogen – Delivered Incremental Yield Top Nitrogen SPARROW Model Output

Ranked Top 100 HUC 8s Total Nitrogen – Ranked based on total delivered incremental yield Ranked Top 10 HUC 8s 1992 Nitrogen SPARROW Model Output

1,500 km 2 SPARROW Calibration Basins 160 km km 2 5 th Percentile 3,200 km 2 SPARROW Median Basin Size 86 km 2 10% <12 km 2 Best to predict for Basins > 200 km 2

Accumulated Nitrogen Loading 1992 Nitrogen SPARROW Model Output

To Obtain a 30% Reduction in the Total Nitrogen Load With a 100% Removal in TN Load, it would require the top 68 HUCs With a 50% Removal in TN Load, it would require the top 171 HUCs

Total Phosphorus Loading Top 4 % 1992 Phosphorus SPARROW Model Output

Total Phosphorus – Delivered Incremental Yield Top 10 % 1992 Phosphorus SPARROW Model Output

Total Phosphorus – Delivered Incremental Yield HUC 8 Scale 1992 Phosphorus SPARROW Model Output

Total Phosphorus – Delivered Incremental Yield HUC 8 Scale Top 100 Top 100 > 42% of the Total Load

Total Phosphorus – Delivered Incremental Yield HUC 8 Scale Top Phosphorus SPARROW Model Output

Ranked Top 100 HUC 8s Total Phosphorus – Ranked based on total delivered incremental yield Ranked Top 10 HUC 8s 1992 Phosphorus SPARROW Model Output

Accumulated Phosphorus Loading 1992 Phosphorus SPARROW Model Output

To Obtain a 30% Reduction in the Total Phosphorus Load With a 100% Removal in TP Load, it would require the top 70 HUCs With a 50% Removal in TP Load, it would require the top 162 HUCs

U.S. Geological Survey SPARROW models National Model – Richard Alexander, G. Schwarz, and R. Smith 1992 and 2002 Models Dale Robertson, WI Richard Rebich, MS Lori Sprague, CO Major River Basin Lead MRB Scientists Anne Hoos, TN Richard Moore

Mississippi River SPARROW Model Dale Robertson, WI Richard Rebich, MS Lori Sprague, CO Mississippi River SPARROW Coordinator: Dale Robertson Richard Alexander, VA

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.

Approximately sites used in National SPARROW Models (Number of sites used in models varies by constituent)

~1000 Potential Load Sites for MRB3 SPARROW Model WQ Data: -NWIS -STORET -States (IN,IL, WI) Flow Data: -NWIS Potential load site EXPLANATION Additional Sites to be Added for Model Calibration

~1000 Potential Load Sites for MRB3 SPARROW Model Potential Sites in the Missouri River Basin ~350 sites ~ sites in the Lower Mississippi River Basin

Standardized Residuals Map for Total Phosphorus Further Reduction in Spatial Biases Standardized Residuals

Refinement of Source Contributions to Stream Nutrient Flux Mississippi River at St. Francisville, LA

Better able to address more regional and local questions

SPARROW Modeling in the Mississippi and Great Lakes Basins Captain Jack Sparrow