Northern Gulf of Mexico: Linking Sediment and Biological Processes within the Regional Ocean Modeling System (ROMS) Courtney K. Harris Virginia Institute of Marine Sciences In collaboration with: Kevin Xu (Coastal Carolina University), Katja Fennel (Dalhousie University), Rob Hetland and James Kaihatu (Texas A&M University) Could not find logos from CCU and Dalhousie.

Mississippi Birdfoot Delta Atchafalaya Bay New Orleans

Dead zone: seasonal occurrence of hypoxia Figure 4 Distribution of frequency of occurrence of mid-summer bottom-water hypoxia over the 60- to 80-station grid from 1985–2001 (updated from Rabalais et al. 1999, Rabalais& Turner 2001b). Star indicates general location of stations C6A and C6B; transect C identified. From Rabalais, Turner, and Wiseman, 2002.

From EPA Web-site: Mechanism Contributing to Hypoxia

ROMS Physical, Biogeochemical, and Sediment Model Physical model: ROMS v3.0 /3.1 Resolution: 3-5 km horizontal, 20 vertical layers Forcing: 3-hourly winds; climatological surface heat fluxes; waves from SWAN run by Kaihatu. River inputs: daily measurements of FW input by U.S. Army Corps of Engineers; sediment input based on USGS rating curve. Figure from Hetland and DiMarco, 2007 Model reproduces two dominant modes of circulation (summer and non-summer), weather- band variability and surface salinity fields (Hetland & DiMarco, J. Mar. Syst., 2007) Biogeochemistry: “FASHAM”, following Fennel et al Sediment: Community Sediment Transport Modeling System (CSTMS), (Warner et al., 2008)

ROMS Physical, Biogeochemical, and Sediment Model Physical model: ROMS v3.0 /3.1 Resolution: 3-5 km horizontal, 20 vertical layers Forcing: 3-hourly winds; climatological surface heat and freshwater fluxes; waves from SWAN run by Kaihatu. River inputs: daily measurements of FW input by U.S. Army Corps of Engineers; sediment input based on USGS rating curve. Figure from Hetland and DiMarco, 2007 Model reproduces two dominant modes of circulation (summer and non-summer), weather- band variability and surface salinity fields (Hetland & DiMarco, J. Mar. Syst., 2007). Biogeochemistry: “FASHAM”, following Fennel et al Sediment: Community Sediment Transport Modeling System (CSTMS), (Warner et al., 2008).

NO 3 Chlorophyll Large detritus Organic matter N2N2 NH 4 NO 3 Water column Sediment Phytoplankton NH 4 Mineralization Uptake Nitrification Grazing Mortality Zooplankton Susp. particles Aerobic mineralization Denitrification Biological model: nitrogen cycling in water column and simplified sedimentary processes; oxygen coupled (Fennel et al., GBC, 2006) River inputs: USGS nutrients fluxes for Mississippi and Atchafalaya Current limitations: no explicit sediment (instantaneous remineralization), no sediment transport, no P-cycle

Coupled Physical – Biological Model Model ran to represent 1990 – Provided realistic estimates of hypoxic area. Next step: improve treatment of biogeochemical constituents on the sediment bed. Figure: Frequency of occurrence of hypoxia in the realistic coupled physical/biological simulation with NO3 and PON inputs for June (top), July (middle), and August (middle). Model statistics based on 10-year simulation. From Katja Fennel, Dalhousie University. June July August

Coupled Physical – Biological Model Model ran to represent 1990 – Provided realistic estimates of hypoxic area. Next step: improve treatment of biogeochemical constituents on the sediment bed. Figure: Frequency of occurrence of hypoxia in the realistic coupled physical/biological simulation with NO3 and PON inputs for June (top), July (middle), and August (middle). Model statistics based on 10-year simulation. From Katja Fennel, Dalhousie University. June July August Rabalais, Turner, and Wiseman, 2002.

ROMS Physical, Biogeochemical, and Sediment Model Physical model: ROMS v3.0 /3.1 Resolution: 3-5 km horizontal, 20 vertical layers Forcing: 3-hourly winds; climatological surface heat and freshwater fluxes; waves from SWAN run by Kaihatu. River inputs: daily measurements of FW input by U.S. Army Corps of Engineers; sediment input based on USGS rating curve. Figure from Hetland and DiMarco, 2007 Model reproduces two dominant modes of circulation (summer and non-summer), weather- band variability and surface salinity fields (Hetland & DiMarco, J. Mar. Syst., 2007). Biogeochemistry: “FASHAM”, following Fennel et al Sediment: Community Sediment Transport Modeling System (CSTMS), (Warner et al., 2008).

Sediment Model: CSTMS (ROMS v3.0) Figures from Warner et al Noncohesive sediment model. Multiple grain sizes. Bed layers account for armoring. Two sediment sources: - Rivers (Atchafalaya and Mississippi). - Seabed erosion. Sediment routine calculates: Vertical settling. Keeps account of sediment bed layers. Exchange between seabed and water column (erosion and deposition).

Sediment Properties SedimentType τ cr (Pa) Ws (mm/s)Fraction MississippiLarge Flocs % Small Flocs % AtchafalayaLarge Flocs % Small Flocs % Sea bedSand0.1210Spatially Variable Mud m 50m 100m 300m Sandy Muddy US Seabed Data from Jeff Williams (USGS) and Chris Jenkins (INSTAAR) Trinity Shoal Ship Shoal This sediment model presented at Ocean Sciences, March 2008, by Kevin Xu.

Wind, Wave, Water and Sediment Discharge in 1993 (USGS discharge data from C. Demas and B. Meade) ‘Storm of Century’ LATEX tetrapod observation Wind Speed (m/s) and SWAN Wave Height at Tetrapod (m)

Model estimates for 1993 storm. This sediment model presented at Ocean Sciences, March 2008, by Kevin Xu.

Estimates for 1993  On average, currents flow westward along coast.  Wave resuspension significantly impacts sediment resuspension.  Fluvial material from the Atchafalaya and Mississippi mix on the Louisiana shelf.

Storm of the Century (March 12 – 16, 1993) Salinity Mean Current Near-bed Suspended Sediment Wave Height (1) (2) (3) Current-wave dominated Low-medium water discharge Strong winds Three Phases

Salinity, Mean Current, Wind Wave Height Storm of the Century Onshore Transport Along-Shore Transport (3) (2) Near-bed Current Suspended Sediment

Storm of the Century Deposition Erosion Erosion/Deposition relative to river sediment on the sea bed on Mar/12/1993  On shore sediment transport during cold fronts (Kineke et al., 2006, CSR)  Facilitate on-shore accumulation  May set the stage for summertime hypoxia. (log 10 kg/m 2 ) Peak of Storm Post Storm

LATEX (May-June, 1993) River-dominated High water discharge Weak winds LATEX tetrapod (see Wright, et al. 1997) Stratified water column Horizontal sediment advection B B’ B 30 psu isohaline

Comparison of Model to LATEX Data 1. Near bottom flows This Model (Wright et al, 1997, MG) 2. Wave Orbital Speed 3. Sediment Concentration

Sediment Model: Conclusions Waves increased sediment concentration and dispersal, and facilitated on- shore accumulation offshore of Atchafalaya Bay. During the ‘Storm of the Century’, currents and waves dominated transport. Water column was well mixed and sediment was eroded from middle shelf and deposited on the inner shelf. Net shoreward flux of sediment. During ‘Calm LATEX’ conditions, river plumes dominated transport in stratified water. Currents and waves occasionally resuspended sediment. Model showed reasonable agreement to tetrapod data. Both Mississippi and Atchafalaya sediment contributed to turbidity south of the Atchafalaya Bay.

Sediment-Biology Coupling Ongoing work (Fennel et al., 2006, GBC) At least 13 tracers Temperature Salinity Large floc sed. Small floc sed. Sand Nitrate Ammonium Chlorophyll Phytoplankton Zooplankton Large Detritus Small Detritus Oxygen (Warner et al., 2008)

Organic MatterFlocs Sea Water Sea Bed Settling Resuspension Partition & Aggregation Diagenesis Sediment-Biology Coupling Bio model has Large Detritus Small Detritus Sediment model has Large Flocs Small Flocs Sediment bed needs Organic Matter

Flocs Sea Water Sea Bed Settling Resuspension Partition & Aggregation Diagenesis Sediment-Biology Coupling Bio model has Oxygen, Ammonium, Nitrate Sediment bed needs Oxygen, Ammonium, Nitrate, “ODU”

Coupling of Biogeochemistry and Sediment: Particulate Organic Matter Fennel et al. (2006) specifies particulate organic matter using ▫Large detritus; small detritus (stored in t[i,j,k,itracer]). ▫These interact with other constituents. ▫When they settle to the bed, they are (now) instantly remineralized. Sediment model uses ▫Large flocs; small flocs. ▫These can be resuspended (t[i,j,k,ised]); settle to the bed (bed_frac[i,j,kbed,ised], bed_mass[i,j,kbed,ised]), and re-erode. ▫These classes do not interact. To couple these, we defined “bed_tracer[i,j,kbed,isb]” (mmol/km 2 of bed) ▫This stores the deposited particulate organic matter, which can be resuspended. ▫The index isb identifies the constituent (large detritus, small detritus). ▫Particulate “bed_tracer” constituents also must be linked to a sediment class. ▫Each “bed_tracer” will be linked to 1 or more water column tracer(s).

SEDBIO TOY One dimensional model that has particulate organic matter. Large detritus linked to large floc. Small detritus linked to small floc. When detritus settles: it adds to bed_tracer(i,j,kbed=1,itracer=“organic matter”). When organic matter erodes: it adds to t(i,j,k=1,itracer=detritus). At present, neglect any interactions between detrital classes on the bed.

SEDBIO Toy Test: Conservation One-dimensional sediment & water column. Suspended detritus settles and adds to bed mass. Winds increase; detritus resuspended. Winds decrease and material redeposits. Organic matter is conserved.

Early Diagenesis Model Next: Following model developed by Soetart et al. (1996). 1.Add other bed_tracers (oxygen, nitrate, ammonium, and “ODU”). These will interact with water column tracers through diffusion, burial, and erosion. 2.Add reaction terms to bed_tracers. Model parameters needed for the bed_tracers (like reactivity). Bed diffusivity will need to be added. 3.The goal here is to improve the water column calculations.

Challenges and Issues Run-time: computational limits are always present, this will need to track at least 15 tracers. Need to work within cohesive bed model. Will likely stress some parts of the sediment model that have not been tested or developed (Porosity? Biodiffusion?) Inherent mis-match in spatial scales / temporal scales between sediment dynamics and diagenesis(?). Will we have data to set model parameters, and for validation?

Summary The MCH (Mechanisms Controlling Hypoxia) modeling group has produced coupled physical – sediment; and physical – biological models; both of which seem to be working well. At present, particulate organic matter in the sediment routine has been linked to water column detritus. Efforts to link other water column tracers to the seabed will face some challenges but the goal is to improve on the current simplistic assumptions used in the biology model.

THE END