Forecasting watershed loading and lagoon response along the Delmarva Peninsula due to changing land use and climate

Transcription

1 Forecasting watershed loading and lagoon response along the Delmarva Peninsula due to changing land use and climate A VA-MD-DE regional Sea Grant project Mark Brush (VIMS), Lora Harris (UMCES), & Joanna York (UDEL)

2 NRC (2000) called for: A reasonably accurate model accessible to managers to predict nutrient loads Simple frameworks for characterizing estuarine response Project Objectives Develop novel, management-focused models: Watershed loading model (NLM) Lagoon ecosystem model (LEM) Virtual eelgrass meadow (VEM) To Quantify changes in TN loads under changing land use, population, agricultural activities, and BMPs. Model lagoon response to these loads coincident with climate change focus on water quality and seagrass habitat. Provide the models for direct use by regional stakeholders.

3 Watershed land use: Project Objectives Images: IAN (UMCES), Virginian-Pilot, K. Reece (VIMS), VIMS, dcerp.rti.org Lagoon water quality & habitat: Predicted TN load Predicted lagoon response

4 Regional Focus End Product Online, user-friendly modeling tools for direct use by stakeholders

5 Regional Stakeholder Workshops Workshop 1: March 27, Ocean City, MD Workshop 2: September 24, Wachapreague, VA Workshop 3: TBD Participants: Wii Tables, Workshop 2: DE: DNREC, USGS, UDel Extension MD: DNR, MCBP, NPS, TNC, Worcester Co. VA: ANPDC, Accomack Co., Northampton Co., Chincoteague, TNC Sea Grant: facilitators & leadership Janet Krenn/VASG

6 Valiela et al. (2000) Nitrogen Loading Model (NLM)

7 Cole (2005) Giordano (2009) Brush et al. (2010) Giordano et al. (2011)

8 Atmospheric deposition NADPP, CastNet NLM Inputs Crop distributions USDA, state, & county agricultural statistics Photos: ian.umces.edu, Chesapeake Bay Program, Virginian-Pilot Residential development (septic tanks, lawns) TIGER & county sources Land use NLDC, RESAC 2-yr corn-soy-wheat rotation Poultry operations local grow-out schedule & density (from aerial photos) Point sources EPA Output

9 Delmarva Modeling Workshop 2 September 24, 2014 VIMS, Wachapreague, VA Image: Google Earth NLM Spreadsheet Version

10 NLM Initial Model Calibration Modeled Annual TN Load (kg N y -1 ) 250, , , ,000 50, :1 38% Boundary 0 50, , , , ,000 Measured Annual TN Load (kg N y -1 ) Field measurements to constrain the NLM (J. York & K. Kroeger): Predicted Annual N Load (kg N y -1 ) 2,500 2,000 1,500 1, Measured Annual N Load (kg N y -1 ) 1:1 38% Boundary

11 Bulls Eye Farm, DE Row crops (corn, wheat, soy)

12 Delmarva Modeling Workshop 2 September 24, 2014 VIMS, Wachapreague, VA Image: Google Earth Stoichiometric Estimation of P loads Phase V load ratios: TN:TP mol mol -1 DIN:DIP mol mol -1 Delaware Maryland VA - Accomack Bulls Eye Farm, DE Row crops (corn, wheat, soy) VA - Northampton mean: st. dev.:

13 Delmarva Modeling Workshop 2 September 24, 2014 VIMS, Wachapreague, VA Image: Google Earth Incorporating BMP Removal Efficiencies BMP Minimum %N Removal Maximum %N Removal Average (if reported) Advanced Septic LID techniques (green roofs, bioretention cells, permeable pavement) Permeable Reactive Barriers Treatment wetlands Riparian Zones Artificial lakes and reservoirs Stream Restoration

14 Delmarva Modeling Workshop 2 September 24, 2014 VIMS, Wachapreague, VA Image: Google Earth Coupling the NLM to the LEM Predicted N & P load Lagoon response NLM? LEM Modulation of loads by tidal creeks: B. Dean, M.S. student, VIMS

15 Lagoon Ecosystem Model (LEM) Images: ian.umces.edu, wikipedia.org, Microsoft Clipart Flushing Nutrient cycling X Denitrification

16 Lagoon Ecosystem Model (LEM) Clam Aquaculture M. Kuschner, M.S. Student, VIMS

17 LEM Calibration: Hog Island Bay, VA

18 Example Nutrient Loading Scenarios

19 Delmarva Modeling Workshop 2 September 24, 2014 VIMS, Wachapreague, VA Image: Google Earth LEM Calibration: Monitoring Data

20 Virtual Eelgrass Meadow (VEM) INITIAL CONDITIONS Ramet Age Ramet Morphology Time of Year Life History Stage Ramet: Flower or Not Meadow Boundaries Depth Ramet Density Labyrinthula density (S r ) INDIVIDUAL RAMET MODEL Specific Growth Rate Biomass Light Availability Internode Length Leaf Length Lesion Size Leaf Detritus Whole Ramet Responses to Forcing Functions and Mass Balance of Biomass FORCING FUNCTIONS Incident Light Water Temperature Current Velocity Nutrients Epiphyte Biomass Water Column Light Attenuation Salinity Sediment Sulfide RULES Growth Allocation Branching Flowering Leaf Shedding Spore Trapping VIRTUAL MEADOW VISUALIZATION MODEL FEEDBACKS Canopy Shading Density Dependent Transmission Dilution of Spores with distance from edge of meadow.

21 Virtual Eelgrass Meadow (VEM)

22 Jess Foley, M.S. student, UMCES-CBL Virtual Eelgrass Meadow (VEM)

23 Virtual Eelgrass Meadow (VEM) + Light & Temp

24 Delmarva Modeling Workshop 2 September 24, 2014 VIMS, Wachapreague, VA Image: Google Earth Coupled NLM-LEM: New Online Interface

25 Delmarva Modeling Workshop 2 September 24, 2014 VIMS, Wachapreague, VA Image: Google Earth Coupled NLM-LEM: New Online Interface

26 Delmarva Modeling Workshop 2 September 24, 2014 VIMS, Wachapreague, VA Image: Google Earth Coupled NLM-LEM: New Online Interface

27 Delmarva Modeling Workshop 2 September 24, 2014 VIMS, Wachapreague, VA Image: Google Earth Coupled NLM-LEM: New Online Interface

28 Delmarva Modeling Workshop 2 September 24, 2014 VIMS, Wachapreague, VA Image: Google Earth Coupled NLM-LEM: New Online Interface

29 Project Status Workshops 1 & 2 completed Workshop 3 via small group meetings/webinar, Mar-May 2015 NLM: Complete re-parameterization and distribution, Feb 2015 LEM & VEM: Complete calibration and delivery by May 2015 Online Model