MODELING NUTRIENT LOADING AND EUTROPHICATION RESPONSE TO SUPPORT THE ELKHORN SLOUGH NUTRIENT TOTAL MAXIMUM DAILY LOAD

Transcription

1 MODELING NUTRIENT LOADING AND EUTROPHICATION RESPONSE TO SUPPORT THE ELKHORN SLOUGH NUTRIENT TOTAL MAXIMUM DAILY LOAD Martha Sutula Southern California Coastal Water Research Project Workshop on The Science of Nutrient Transport and Transformation in the Elkhorn Slough Estuary March 19, 2019

2 ELKHORN SLOUGH ON THE 303D LIST FOR EUTROPHICATION (BIOSTIMULATORY SUBSTANCES) Eutrophication: the accelerated delivery, in situ production, and/or accumulation of organic matter within an aquatic ecosystem (Nixon 1995, Cloern 2001) Nitrogen and Phosphorus Loading Hydromodification Light availability Organic Matter Loading Physical Habitat Alteration Temperature Biostimulatory Substances and Conditions: substances such as nutrients (i.e. nitrogen, phosphorus, organic matter) or conditions, such as altered temperature, hydrology, etc. that can cause eutrophication Depth of Aragonite Saturation, Feely et al. (2008) Spatially interpolated eutrophication indices (from Hughes et al. 2011) Low dissolved oxygen/acidification High phytoplankton biomass/ macroalgal blooms/toxic HABs Light limitation to seagrass Poor benthic habitat quality

3 PROJECT GOALS Science Quantify drivers and responses of eutrophication in Elkhorn Slough through numerical modeling Management: To quantify the management actions that can result in the remediation of eutrophication in Elkhorn Slough Nutrient loads (TMDL) Other restoration activities?

4 TECHNICAL APPROACH ELKHORN SLOUGH NUTRIENT TMDL Develop and Calibrate Watershed Loading and Estuarine Water Quality Models Identify Estuarine Eutrophication Targets Basin Plan Objectives Alternative targets Use Models to Assist in Decision-Making on Application of Numeric Targets Use Models to Identify Early Implementation Actions Use Models to Calculate Allowable Nutrient Loads

5 Conceptual Approach to Numerical Modeling Use the models to determine allowable loads and evaluate management actions Hydrodynamic Eutrophication

6 Estimating External Loads Tetra Tech (2018) summarized the nutrient sources and pathways to Elkhorn Slough Direct drainage: STEPL 1 modeling analyses Empirical estimates from OSR Developed coarse estimates of external loads, with major uncertainties Flow from Old Salinas River Groundwater Exchange Contributions from Monterey Bay 1 Spreadsheet Tool for the Estimation of Pollutant Load (Tetra Tech, 2017) Tetra Tech (2018) proposes the use of Soil and Water Assessment Tool (SWAT) to estimate watershed loads

7 TETRA TECH (2018) PROPOSED THE USE OF SOIL AND WATER ASSESSMENT TOOL (SWAT) TO ESTIMATE WATERSHED LOADS Initial model development during previous phase of work Model refinement and calibration during this phase Estimation of contribution to tidally restricted areas a particular focus of SWAT modeling Loads from OSR would still be empirically estimated

8 APPROACH FOR ESTUARY EUTROPHICATION MODEL ENTIRELY DEPENDS ON EUTROPHICATION MANAGEMENT TARGETS Calibration Verification TMDL Scenario Runs Hydrodynamic Model WQ Model Load Management Load Reduction Hydrodynamics in fine grid Transport of Salinity, and TSS Parameterization: Advection, Dispersion, Resuspension Settling Eutrophication: Nutrients/DO/ Macroalgae/pH Water Column Additional Load Eutrophication Sediment (Diagenesis model) Develop and Calibrate Watershed Loading and Estuarine Water Quality Models Identify Estuarine Eutrophication Targets Basin Plan Objectives Alternative targets Use Models to Assist in Decision-Making on Application of Numeric Targets Active Sediment Layer Burial Sediment Layer Use Models to Identify Early Implementation Actions Use Models to Calculate Allowable Nutrient Loads

9 Light Light CONCEPTUAL MODEL OF EUTROPHICATION SYMPTOMS IN MEDITERRANEAN ESTUARIES Nutrient load Nutrient load Shading Macroalgae Phytoplankton Changes in Water Chemistry (DO, ph) Minimally Disturbed Benthic Diatoms Increased Nutrient Loading Changes in Sediment Chemistry (Sulfide, Ammonia) Affected by Eutrophication Seagrass Macroalgae Phytoplankton Dissolved Oxygen ph

10 CHOICE OF ESTUARINE RECEIVING WATER MODELING DEPENDS ON A NUMBER OF FACTORS Options for Targets: Nutrient concentrations (Tetra Tech 2018) Dissolved oxygen (Basin Plan) Carbonate saturation state (ph) Macroalgae Water column chl-a Seagrass HAB toxins Sediment organic matter (Benthic macroinvertebrates) Modeling Approach Will Depend on: Complexity of modeling eutrophication response Availability of data for model forcing and model validation E.g. alkalinity for carbonate saturation state Availability of biological response data Relatively short project window Regulatory approach Formal TMDL (with Basin plan amendment) Alternative TMDL Seagrass

11 OCEAN FORCING TO ELKHORN SLOUGH: WILL LEVERAGE CA OPC AND NOAA INVESTMENTS IN NUMERICAL OCEAN MODELING TO SUPPORT CALIFORNIA S CLIMATE CHANGE ACTIONS PLANS Numerical modeling program goals Disentangle the relative contributions of climate change, natural variability and local pollution impacts on OA, hypoxia (HABs and N20 emissions) CLIMATE CHANGE & NATURAL VARIATION Circulation Temperature ELEMENTAL CYCLES Productivity Trophic Changes HUMAN INPUTS CO2 Wastewater Apply model to support policy decisions Oxygen Light Hypoxia Acidification Harmful algal Blooms Runoff Atmospheric Deposition Directly supports elements of CA OA Action Plan recommendations Manage local pollution sources Create biologically relevant OA water quality criteria Sequester carbon through habitat restoration N20 (GHG) MARINE RESOURCE MANAGEMENT? LOCAL POLLUTION MANAGEMENT?

12 EARTH SYSTEMS MODELING APPROACH Atmospheric forcing WRF model (Weather and Research Forecast Model; Boe et al., 2011) Physical model ROMS (Regional Oceanic Model System; Shchepetkin and McWilliams, 2003, 2005, 2008, 2011) Biogeochemistry and Lower Ecosystem Biogeochemical Elemental Cycling (BEC; Moore et al. 2002) Full model domain is California Current wide at 4 km resolution, with higher resolution grids nested inside (1 km to 300 m) Grid: 60 variable depth levels y z x 2 subdomains at 1 km resolution for CA, OR and WA Within the 1 km CA nest, 2 smaller subdomains at 300 m within Southern California Bight and San Francisco/Monterey Coast 12 aragonite time-series from the model

13 Nitrificatio n PP (Reg) Grazing Coagulation Remineralization Respiration Metabolism Excretion Sloppy feeding Mortalit y Metabolism Air Sea exchange Excretion Metabolis m DOM (C, N, P, Fe) Remineralization Biogeochemical Elemental Cycling (Moore et al. 2002) Oxygen Nutrients Iron Silicate Phosphate Nitrate Nitrite Ammonium PP (New ) Remineralization Remineralization Remineralization Air Sea exchange Photosynth. Predation Phytoplankton Small (C) Diatom (C) Deposition Mortalit y POM (C) Respiration Respiration PP (New & Reg) Depositio n Zooplankton (C) Developed enhanced nitrogen cycling, explicit sinking of particles and carbonate chemistry DIC STATE VARIABLES Ocean physics Nutrients Nitrate, nitrite, ammonia phosphate silicate, Iron Plankton [2 phytoplankton groups an zooplankton biomass] Organic matter Oxygen Carbonate system Key Take Messages for Elkhorn Science Community Collaboration with SFEI (Senn) and UCSC (Edwards) to investigate the effects of anthropogenic nutrient and carbon inputs on OA, hypoxia and N20 on San Francisco Coast and Monterey Bay Model can provide ocean forcing of nutrients, carbon and oxygen to Elkhorn Slough model Elkhorn Slough et al. modeling efforts will provide improved terrestrial forcing to ROMS-BEC assessment of coastal impacts We will be running first set of 300-m resolution simulations (3 yr period) this summer

14 CONCEPTUAL APPROACH ELKHORN SLOUGH NUTRIENT TMDL Develop and Calibrate Watershed Loading and Estuarine Water Quality Models Identify Estuarine Eutrophication Targets Basin Plan Objectives Alternative targets Use Models to Assist in Decision-Making on Application of Numeric Targets Use Models to Identify Early Implementation Actions Use Models to Calculate Allowable Nutrient Loads Water Board wants load and waste load allocations Identification of future restoration actions are a desirable outcome

15 THANK YOU! QUESTIONS? COMMENTS

16 4-KM AND 1-KM VALIDATION PROVIDE ASSURANCE THAT WE VE APPROPRIATELY MODELED OCEAN FORCING Good consistency of coast-wide 4-km and 1-km solutions for atmospheric and oceanic physical & biogeochemical outputs against available coast-wide data sets spatial patterns, seasonal cycles, and range of natural variability Oxygen distribution at sigma=26.5 [~ m] Modeled Observed