Scenario Builder and Watershed Model Progress toward the MPA Gary Shenk, Guido Yactayo, Gopal Bhatt Modeling Workgroup 12/2/14 1.

Slides:



Advertisements
Similar presentations
1 Hayward Zone 4 Line A Watershed Modeling Item #2a-2.
Advertisements

Trends in Suspended Sediment Input to the San Francisco Bay from Local Tributaries Presented by Setenay Bozkurt Philip Williams &
SPARROW Modeling in the Mississippi and Atchafalaya River Basins (MARB) Dale Robertson, Richard Alexander, and David Saad U.S. Geological Survey USGS/USEPA.
EPA response to hydrodynamic workshop and subsequent letters Gary Shenk 3/27/2012.
Delaware River Basin SPARROW Model Mary Chepiga Susan Colarullo Jeff Fischer
5. Final Remarks Information and the GIS package developed will be used to evaluate the effectiveness of implemented watershed management practices in.
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.
The Chesapeake Bay Program Partnership’s Watershed Model Gary Shenk Presentation to COG 10/4/2012.
Minnesota Watershed Nitrogen Reduction Planning Tool William Lazarus Department of Applied Economics University of Minnesota David Mulla Department of.
Current Planning for 2017 Mid-Point Assessment Gary Shenk COG 10/4/2012 presentation credit to Katherine Antos and the WQGIT ad hoc planning team.
Conservation Effects Assessment Project (CEAP) Measuring the Environmental Benefits of Conservation Managing the Agricultural Landscape for Environmental.
Estimating the Sources and Transport of Nitrogen in the Mississippi River Basin Using Spatially Referenced Modeling Techniques R.B. Alexander, R.A. Smith,
Land Use Change and Its Effect on Water Quality: A Watershed Level BASINS-SWAT Model in West Georgia Gandhi Raj Bhattarai Diane Hite Upton Hatch Prepared.
Chesapeake Bay TMDL Primer: Chesapeake Bay Watershed and Bay Water Quality Models The Economics of Water Quality Improvements in Chesapeake Bay Workshop.
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)
Chesapeake Bay Program Modeling Chesapeake Bay Program Watershed Model 101.
Hydrological Modeling FISH 513 April 10, Overview: What is wrong with simple statistical regressions of hydrologic response on impervious area?
NYCDEP Evaluation of Watershed Management Programs FAD requirement: Last one ; Next FAD Assessment : Use models to evaluate effects.
ABSTRACT We are developing ReNuMA, an event-based, regional watershed-scale nutrient loading model with biogeochemical dynamics that is readily accessible.
Soil Water Assessment Tool (SWAT) Model Input
Determining the effectiveness of best management practices to reduce nutrient loading from cattle grazed pastures in Utah Nicki Devanny Utah State University,
A Water Quality Loading Model for Tillamook Bay Patrice A. Melancon Thanks to: Dr. David Maidment Dr. Michael Barrett Dr. Francisco Olivera Dr. Maidment’s.
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
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,
Nonpoint Source Pollution u Some basic principles u Example study of total pollution loads in the Corpus Christi Bay System –rainfall-runoff relationship.
The Chesapeake Bay Program’s Scenario Builder Gary Shenk CCMP workshop 5/11/2010.
Karl Berger Dept. of Environmental Programs Metropolitan Washington Council of Governments Chesapeake Bay Program Modeling Developments April 28, 2015.
The Importance of Watershed Modeling for Conservation Policy Or What is an Economist Doing at a SWAT Workshop?
Watershed Management Assessment Through Modeling: SALT and CEAP Dr. Claire Baffaut Water Quality Short Course Boone County Extension Office April 12, 2007.
Modeling experience of non- point pollution: CREAMS (R. Tumas) EPIC (A. Povilaitis and R.Tumas SWRRBWQ (A. Dumbrauskas and R. Tumas) AGNPS (Sileika and.
Chowan River TMDL Development Tidewater Area 08/26/04.
1 Evaluating and Estimating the Effect of Land use Changed on Water Quality at Selorejo Reservoir, Indonesia Mohammad Sholichin Faridah Othman Shatira.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Hydrologic and Water Quality Modeling of the Chesapeake Bay Watershed Huan.
Twinning water quality modelling in Latvia Helene Ejhed
Assessment of Runoff, Sediment Yield and Nutrient Load on Watershed Using Watershed Modeling Mohammad Sholichin Mohammad Sholichin 1) Faridah Othman 2)
Water Quality Modeling of Bonnet Carré Freshwater Flows in the Pontchartrain Estuary Rachel Roblin Alex McCorquodale Ioannis Georgiou.
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.
Patapsco and Back River HSPF Watershed Model Part II – Water Quality Maryland Department of the Environment.
Clifton Bell, P.E., P.G. Chesapeake Bay Modeling Perspectives for the Regulated Community.
Chesapeake Bay Program’s Baywide and Basinwide Monitoring Networks: Options for Adapting Monitoring Networks and Realigning Resources to Address Partner.
Description of WMS Watershed Modeling System. What Model Does Integrates GIS and hydrologic models Uses digital terrain data to define watershed and sub.
Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.
Relating Surface Water Nutrients in the Pacific Northwest to Watershed Attributes Using the USGS SPARROW Model Daniel Wise, Hydrologist US Geological Survey.
1 Phase 5.3 Calibration Gary Shenk 3/31/ Calibration Method Calibration method largely unchanged for several years –P5.1 – 8/ first automated.
Chesapeake Bay Program Phase 6 Watershed Model Development Update, Key Issues & Recommendations Water Resources Technical Committee Oct. 29, 2015 Presented.
Robert M. Hirsch, Research Hydrologist, USGS September 6, 2012 Nitrogen, Phosphorus, and Suspended Sediment fluxes from the Susquehanna River to the Bay.
Surface Water Surface runoff - Precipitation or snowmelt which moves across the land surface ultimately channelizing into streams or rivers or discharging.
Modeling Stream Flow of Clear Creek Watershed-Emory River Basin Modeling Stream Flow of Clear Creek Watershed-Emory River Basin Presented by Divya Sharon.
SPARROW: A Model Designed for Use With Monitoring Networks Richard A. Smith, Gregory E. Schwarz, and Richard B. Alexander US Geological Survey, Reston,
SUstainable Management of water and human interactions on Andean Amazon River basins - SUMAAR An Andean Amazon Initiative sumbitted to IAI Remigio Galárraga-Sánchez.
Precision Management beyond Fertilizer Application Hailin Zhang.
Integrated Approach for Assessing and Communicating Progress toward the Chesapeake Bay Water-Quality Standards Scott Phillips USGS, STAR May 14, 2012 PSC.
Nitrogen Budgets for the Mississippi River Basin using the linked EPIC-CMAQ-NEWS Models Michelle McCrackin, Ellen Cooter, Robin Dennis, Jana Compton, John.
Introduction. The Hanford Site.
Nitrogen loading from forested catchments Marie Korppoo VEMALA catchment meeting, 25/09/2012 Marie Korppoo, Markus Huttunen 12/02/2015 Open DATA: Nutrient.
It’s The Final Countdown To The Mid-point Assessment:
Precipitation-Runoff Modeling System (PRMS)
Model Calibration Mode
Nonpoint Source Pollution
Image courtesy of NASA/GSFC
Predicting the hydrologic and water quality implications of climate and land use change in forested catchments Dennis P. Lettenmaier Department of Civil.
Overview of Climate Impact Assessment Framework and Implementation
Chesapeake Bay Program Climate Change Modeling 2.0
Gopal Bhatt1 and Lewis Linker2 1 Penn State, 2 US EPA
Watershed Restoration, Chesapeake Bay
Presentation transcript:

Scenario Builder and Watershed Model Progress toward the MPA Gary Shenk, Guido Yactayo, Gopal Bhatt Modeling Workgroup 12/2/14 1

2 REVIEW The Models CREATE The Models USE The Models

Phase 6 3 NutrientsSediment Directly Simulated in HSPF for river averaging at least 100 cfs Calibrated to WQ data Can we estimate EOF loads directly based on available information? Should we update the sediment EOF estimates? Can we estimate watershed delivery based on landscape parameters? Can we estimate small stream effects?

4

1-Slide Status Report Land Use Types and Acreage Land Use Loading Rates Climate Change Scenario Builder Development and Code Versioning Watershed Model Development and Code Versioning Calibration Methodology Sensitivities to inputs Fine-scale Processes Atmospheric Data Groundwater Lag Better Representation of Reservoirs 5

6 Precipitation Fertilizer Manure Atmospheric deposition (…) Phase 6 Hydrology submodel River Sediment submodel Nutrient Submodels Temporal Nutrient model } BMPs, Land to Stream, Stream to River HSPF

7 Precipitation Fertilizer Manure Atmospheric deposition (…) Phase 6 Hydrology submodel River Sediment submodel Nutrient Submodels Temporal Nutrient model } BMPs, Land to Stream, Stream to River Nutrient Submodels Guido Yactayo

Recommendations for Phase 6- PQUAL Nitrogen Sensitivity Guido Yactayo – UMCES

Objectives To estimate multiple watershed models sensitivity to nutrient inputs in the Chesapeake Bay To develop, review and implement model sensitivities in the phase 6 version of the Chesapeake Bay Watershed model To decide on Phase 6-PQUAL nitrogen sensitivities * The input-output relationship or the effect of changes in nutrient inputs on nutrient export is referred to in this analysis as sensitivity.

Sensitivities to total nitrogen inputs Following STAC recommendations of using multiple models, APEX, SPARROW, and P532-AGCHEM models were included in this analysis. The models sensitivities represent the relationship between nutrient predicted yields and input loads for cropland. APEX – CEAP SPARROW Phase APEX – CEAP SPARROW Phase Sensitivity to fertilizer TN inputs Sensitivity to manure TN inputs 1.APEX – CEAP: Ratio between output and input (No-practice, 2006, and 2011 scenarios including all input sources in cropland areas) 2.SPARROW: source specific coefficient (Various studies in the Chesapeake bay and Northeastern and Mid-Atlantic regions) * 3.Phase 5.3.2: Ratio between input and output, slope of multivariate regression, and slope between output and input (14 scenarios, hwm, hom, lwm, alf, and hyw) * Preston and Brakebill (1999), Ator et al. (2011), Moore et al. (2011), and Preston et al. (2011).

Sensitivity implementation on phase 6 Total nitrogen sensitivities from other existing models support the Phase 532- AGCHEM findings. Phase 532-AGCHEM sensitivities are available not only for TN but also by nitrogen species. Phase 532-AGCHEM DIN and organic nitrogen sensitivities have been implemented in phase 6. Phase Phase 6

Decide on Phase 6 nitrogen sensitivities Phase 532-AGCHEM sensitivities are more extensive and robust than other models sensitivities. The new recommendation is to adopt the Phase AGCHEM nitrogen sensitivities. Please review both the Phase AGCHEM and multiple model sensitivity analyses in order to make a decision. ftp://ftp.chesapeakebay.net/Modeling/phase5/Phase532/Sensiti vity/

13 Precipitation Fertilizer Manure Atmospheric deposition (…) Phase 6 Hydrology submodel River Sediment submodel Nutrient Submodels } BMPs, Land to Stream, Stream to River Temporal Nutrient model Gopal Bhatt

14 Phase 6 Nutrient Submodels Temporal Nutrient Model UNEC HSPF

15 UNEC - Nitrogen Nutrient Submodels HSPFTime => Concentration=> Surface Subsurface Sum= Each Loading Event

16 UNEC - Phosphorus Nutrient Submodels HSPFTime => Concentration=> Surface Subsurface Sum= Each Loading Event

Unit Nutrient Export Curve (UNEC) An examination of transit time distribution 17

Lead Edge = 5 months Peak Conc. = 10 months Trail Edge = 1200 months Recession = 0.05 Lag in nutrient export for a dirac-delta (pulse) input Unit nutrient export curve stochastically describes transport of nutrients as a probability density function. In other words, transit times are variable for inputs applied at same time

Lead Edge = 0 months Peak Conc. = 0 months Trail Edge = 1200 months Recession = Here, a unit nutrient export curve is described using one parameter. This parameter would be obtained from mean transit times estimated from models (e.g. MODFLOW, APLE) and observations. 19

Dirac-delta / Pulse input 20

Dirac deltas / Pulse inputs UNECs are superimposed to obtain the output as the convolutions of inputs. 21

Continuous inputs 22

Sinusoidal inputs 23