Jerry D. Wiggert (USM) Wen Long (UMCES) Jiangtao Xu (NOAA/NOS/CSDL) Raleigh R. Hood (UMCES) Erin B. Jones (USM) Lyon W. J. Lanerolle (NOAA) Christopher W. Brown (CICS-ESSIC NOAA) This research funded by NOAA-MERHAB & IOOS-SURA Application of a Coupled Physical-Biogeochemical Model to Simulate and Forecast the Ecological Variability of Chesapeake Bay

Aquatic Sciences, 20 February 2013 Outline - ChesROMS Community Model - Biogeochemical Model Implementation & Waypoints - Assessment of Ecosystem Model Solutions - Concluding Remarks MODIS Image from Kemp et al. 2005

Aquatic Sciences, 20 February 2013 ChesROMS Community Model ✦ ROMS 3.0 ✦ Curvilinear Horizontally ✦ σ-coordinate Vertically ✦ Includes major tributaries ✦ Coarse mesh for model development (100*150*20) ✦ Forcing: Tides, Winds, Heat Fluxes and Rivers ✦ Validated Physical Model w/ 15-Year Hindcast (Xu et al., accepted) ✦ Currently expanding the biogeochemical model ✦ Goal: Improved Simulation of BGC processes & Water Quality Fields ✦ Use Output to inform Ecological Models (HABs, pathogens, etc.) ✦ Open Source Available at: ChesROMS Team: Chris Brown, Tom Gross, Brooke Denton, Raleigh Hood, Mohan Karyampudi, Lyon Lanerolle, Wen Long, Raghu Murtugudde, Dave Potsiadlo, M. Bala Krishna Prasad, Jerry Wiggert, Jiangtao Xu

Aquatic Sciences, 20 February 2013 CBP Sampling Sites CB4.1C (upper bay) CB5.3 (middle bay) CB6.3 (lower bay) Map Courtesy of Chesapeake Bay Program Chesapeake Bay Program ( Data Used For: Initial Conditions River Boundary Conditions Solution Validation Sites (following Xu & Hood, 2006) CB3.3C (Upper Bay) CB5.3 (Mid-bay) C6.3 (Lower Bay) Chlorophyll Dissolved Oxygen DON, PON Freshwater Flux NO 3 /NO 2 /NH 4 TSS

Aquatic Sciences, 20 February 2013 Chesapeake Bay Ecological Prediction System (CBEPS) 1) Ocean Quality Control System (OQCS) Automatic retrieval of historical and real-time data for validation and model forcing 2) Ocean Hydrodynamic Modeling System (OHMS) ChesROMS and Empirical Habitat Models 3) Ocean Model Assessment System (OMAS) Skill assessment of model predictions against data acquired by OQCS 4) Ocean Model Dissemination System (OMDS) Data archive and forecast dissemination Utilizes data interoperability techniques to facilitate efficient provision of model results to end users Brown, et al., J. Mar. Sys., 2013.

Aquatic Sciences, 20 February 2013 BGC Modeling Targets & Implementation Goals 1) Phytoplankton Bloom Dynamics Capture Spatio-temporal Physical-Biogeochemical Interactions Associated with Estuarine Circulation 2) Particulate and Dissolved Constituents N-cycling Linkage of Water Column & Benthos 3) Dissolved Oxygen Evolution Denitrification Onset - Offers Insight into N Balances & Budget Hindcast Year Chosen for Model Implementation is 1999 (“Typical” Conditions; Model Physics Validated) Xu, et al., Est. and Coasts., Improved ChesROMS BGC Realism -> More Robust Ecological Forecast System (CBEPS)

Aquatic Sciences, 20 February 2013 ChesROMS Biogeochemical Flows 1) Benthic NH 4 Efflux & NO 3 Uptake ramp up as overlying DO decreases 2) Reduce POM sinking in bottom layer i) Promote O 2 Demand in Water Column ii) Promote BGC link to Estuarine Circulation 1) Reduce D L Sinking Velocity 2) Particle Aggregation (Stickiness) i) Regulates Bloom Dynamics, POM Loads & Sinking/Export of Organic Matter ii) Tends to Degrade O 2 Evolution (WC DO Increases) Sensitivity Explorations Aspects of Implementation Overcome “Tension” in BGC Mechanisms Bloom Dynamics Hypoxia Realism DIN Concentrations Bloom Dynamics Overall Goals DO is Indicated by the Light Blue Background

Aquatic Sciences, 20 February 2013 Summary of Sensitivity Studies Test 64 -> 85: ⬇ D L Sink Velocity (0.5 x); ⬆ Max Nitrification Rate (4x) Test 64 -> 91: Constant Phytoplankton Growth Rate Test 91 -> 96: ⬇ Non-Dim Zooplankton Growth Rate (0.8x) Test 96 -> 100: ⬆ Coagulation Param (1.5x) Test 91 -> 104: Zooplankton Grazing ≠ f(Temperature) Test 100 -> 105: ⬇ D L Sink Velocity (0.5 x) 1CB2.2 2CB3.1 3CB3.2 4CB3.3C 5CB4.1C 6CB4.1W 7CB4.2W 8CB4.3C 9CB4.3W 10CB4.4 11CB5.1 12CB5.2 13CB5.3 14CB5.4W 15CB5.5 16CB6.1 17CB6.3 18CB6.4 19CB7.1 20CB7.1N 21CB7.1S 22CB7.2 23CB7.2E 24CB7.3 IndexStation ChlorophyllAmmonium NitrateDO

Aquatic Sciences, 20 February 2013 Hypoxic Volume (km 3 ) Comparisons Initial Baseline Solution (Test 64) Test 64 -> 85: ⬇ D L Sink Velocity (0.5 x); ⬆ Max Nitrification Rate (4x) Test 91 -> 96: ⬇ Non-Dim Zooplankton Growth Rate (0.8x) New Baseline Solution (Test 105) 1) Extension of Hypoxic Volume Envelope for Model Overall, the 4 mg/ml threshold is a closer fit to the CBP-based Hypoxic Volume Seasonal variability consisting of onset and dissipation timing are reasonable

Aquatic Sciences, 20 February 2013 Baseline Solution ChlorophyllDissolved Oxygen Upper Bay (4.1C) Upper Bay Mid-Bay (5.3) Mid-Bay Lower Bay (6.3) Lower Bay

Aquatic Sciences, 20 February 2013 Extending the Model Ideally, Phys-BGC Model Will Naturally Capture Interannual Variability or Model Provides Additional Insights into the Chesapeake System

Aquatic Sciences, 20 February 2013 Summary 1) Retain Organic Matter in Water Column Promotes Water Column Oxygen Demand (to a point) BUT! Oxic N-cycling Promotes O 2 Production 2) Model Suggests a “Pulsing” of low DO conditions in bottom waters through the summer Linkage to variability in modeled phytoplankton biomass Refining Hypoxic Fidelity in the Model 3)How to Amplify Denitrification in the Water Column and Anoxia Establishment? Adjust the Nitrification - Denitrification Transition Bottom Dissolved Oxygen Chesapeake Bay System and Availability of CBP Data Provide an Ideal Proving Ground for Development of the Biogeochemical Module

Aquatic Sciences, 20 February 2013 Thank You!