I-IV: Physics & Biogeochemistry of Estuarine Turbidity Maxima

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1 I-IV: Physics & Biogeochemistry of Estuarine Turbidity Maxima Estuarine Turbidity Maxima (ETM) are major features in both the North and South Channel of the Columbia River estuary. Detailed understanding and ability to predict the ETM dynamics is necessary to address the variability and change of the biogeochemistry and ecosystem function in the lower Columbia River estuary, under the effects of climate and land/use. Phase 1 focus. The biogeochemistry of the North and South channel ETMs shows important contrasts, the understanding of which matters for CMOP II initiatives in the role of lateral bays on carbon cycle, in estuarine hypoxia/acidification, and in M. rubra blooms. Phase 2 focus. For numerical models to usefully address ETM biogeochemistry, they need to be skilled in representing circulation and trapping mechanisms at fine scales. Core CMOP focus. salinit y: marine estuarine freshwater sandy, vegetated sandflats mudflats 1

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I-IV: Physics & Biogeochemistry of Estuarine Turbidity Maxima. salinity:. marine. freshwater. estuarine. sandflats. sandy, vegetated. mudflats. Estuarine Turbidity Maxima (ETM) are major features in both the North and South Channel of the Columbia River estuary. - PowerPoint PPT Presentation

Transcript of I-IV: Physics & Biogeochemistry of Estuarine Turbidity Maxima

Page 1: I-IV: Physics & Biogeochemistry of Estuarine Turbidity Maxima

1I-IV: Physics & Biogeochemistry of Estuarine Turbidity Maxima

• Estuarine Turbidity Maxima (ETM) are major features in both the North and South Channel of the Columbia River estuary.

• Detailed understanding and ability to predict the ETM dynamics is necessary to address the variability and change of the biogeochemistry and ecosystem function in the lower Columbia River estuary, under the effects of climate and land/use. Phase 1 focus.

• The biogeochemistry of the North and South channel ETMs shows important contrasts, the understanding of which matters for CMOP II initiatives in the role of lateral bays on carbon cycle, in estuarine hypoxia/acidification, and in M. rubra blooms. Phase 2 focus.

• For numerical models to usefully address ETM biogeochemistry, they need to be skilled in representing circulation and trapping mechanisms at fine scales. Core CMOP focus.

salinity: marine estuarine freshwater

sandy, vegetated

sandflats

mudflats

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2ETM resuspension and settling

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3Long-Term Scientific Goals Enabled by the Phase 1 ETM Initiative

To develop highly skilled numerical models that describe key ETM processes, in particular density structure, sediment trapping, and exchanges with the ocean and estuarine lateral bays. This will be accomplished by:

• Measuring and characterizing the dominant physical processes that determine circulation, mixing and trapping in the North Channel, through a combination of long-term observations at endurance stations and of intense fortnightly observations in low and high-flow conditions.

• Characterizing the turbulence structure along the North Channel, and computing eddy coefficients for incorporation in numerical models.

• Rigorously benchmarking numerical models of circulation and sediment transport against the observed physical structure of the North Channel ETM, and exploring strategies for model improvements.

• Conducting a “blind evaluation” of the predictive ability of numerical models to characterize ETMs at the mouth and in the South Channel of the estuary.

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4Phase 1: North Channel Laboratory

Instrumentation to deploy: In addition to endurance stations– Bottom node supporting ADV and CTD– Sigma profiler – Repeated vertical profiling from R/V, including V, T, S, O2, OBS, LISST 100,

altimeter and turbulence profiles, supplemented by appropriate biogeochemistry sensors

– Doppler radar measurements of surface velocity over N. Channel– Mobile profiles of water properties with an autonomous mobile AUV

Field operations (IOP): Two-week operations in May and September 2012Expected Outcomes:

– Improved understanding of flow and mixing in N. Channel– Refined parameterizations of bottom and interfacial stresses– Improved skill of circulation models

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5Long-Term Scientific Goals Enabled by the Phase 2 ETM Initiative

Develop and demonstrate detailed quantitative understanding and predictive ability of how the salinity intrusion and ETM formation influences biogeochemical factors, and demonstrate portability of theses predictive capabilities to the South Channel and entrance ETMs.

• Determine and contrast the dynamics and biogeochemistry of the three Columbia River ETMs, and their role as bioreactors for transformation and removal of river-borne nutrients and biogenic inputs.

• Predict climate change and land-use impacts on Columbia River ETMs, and integrate acquired understanding on regional efforts assessing or managing habitat and water quality for fisheries and aquaculture.

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6What is Needed to Achieve ETM Goals and Operations

• People: Initial team:– Lead PIs: Tom Sanford and Byron Crump– Phase 1 PIs: Jim Lerczak (OSU), Murray Levine (OSU), Antonio Baptista (OHSU), Yvette

Spitz (OSU), Craig McNeil (APL-UW), Gordon Farquharson (APL-UW), Fred Prahl (OSU)

• Prior Studies: CRETM-LMER • Instruments and facilities:

– Endurance stations– R/V Forerunner (scheduling limitations?) and access to UNOLS vessels– PI and CMOP instrumentation and methodologies– CMOP’s Virtual Columbia River modeling

• Funding: – NSF from CMOP II– Contributions from involved PIs from personal grants– Extramural sources, especially for instrumentation

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7ETM resuspension and settling

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8Particle-attached bacterial production correlates with turbidity

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9ETM particles are aggregates, and can be >1mm in size

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10Unique ETM bacteria amid allochthonous communities (1997)

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Ocean River

Estuary

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12Diversity correlates with salinity, varies with season, repeats annually

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Fortunato et al. In Prep

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13Marine Diatoms dominate 18S rRNA sequences in bottom waters.

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0%

20%

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100%

2.3 2.9 5.4 7.3 18.3 2.1

Bottom Surface

Abu

ndan

t dia

tom

seq

uenc

es

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Marine diatom Freshwater diatom

5.9 13.1 10.3 11.8 12.4 0.9

Salinity

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14Conceptual model of OM composition in Estuary

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