The Physical Modulation of Seasonal Hypoxia in Chesapeake Bay Malcolm Scully Outline: 1)Background and Motivation 2)Role of Physical Forcing 3)Simplified

The Physical Modulation of Seasonal Hypoxia in Chesapeake Bay

Malcolm Scully

Outline:

1) Background and Motivation

2) Role of Physical Forcing

3) Simplified Modeling Approach

4) Sensitivity Studies

5) Physical Mechanisms and Oxygen Budget

6) Historical Observations of Hypoxia

7) Conclusions

Center for Coastal Physical OceanographyOld Dominion University

CCPO Seminar:Monday, March 28, 2011

Center for Coastal Physical Oceanography

From Chesapeake Bay Program newsletter: http://ian.umces.edu/pdfs/do_letter.pdf

Map of Mean Dissolved Oxygen -- Summer 2005

• Low DO has significant impact on a wide array of biological and ecological processes.

• Large regions of Chesapeake Bay are impacted by hypoxia/anoxia.

• Over $ 3.5 billion was spent on nutrient controls in Chesapeake Bay between 1985-1996 (Butt & Brown, 2000)

• Assessing success/failure of reductions in nutrient loading requires understanding of the physical processes that contribute to the inter-annual variability.

From Chesapeake Bay Program newsletter: http://ian.umces.edu/pdfs/do_letter.pdf

Conceptual Model for Hypoxia in Chesapeake Bay

Physical forcing is thought to play an important role in extent and severity of hypoxia: 1) River Discharge; 2) Temperature; 3) Wind forcing

Seasonal and Inter-Annual Variability in Hypoxic Volume (from CBP data 1984-2009)

Maximum observed

Minimum observed

Data compiled from Murphy et al. (submitted)

Regional Ocean Modeling System (ROMS)

ChesROMS Model GridModel forcing

• Realistic tidal and sub-tidal elevation at ocean boundary

• Realistic surface fluxes from NCEP (heating and winds)

• Observed river discharge for all tributaries.

• Temperature and salinity at ocean boundary from World Ocean Atlas.

• Very simple oxygen model

Oxygen Model

• Oxygen is introduced as an additional model tracer.

• Oxygen consumption (respiration) is constant in time, with depth-dependent vertical distribution.

• No oxygen consumption outside of estuarine portion of model

• No oxygen production.

• Open boundaries = saturation

• Surface flux using wind speed dependent piston velocity following Marino and Howarth, 1993.

• No negative oxygen concentration and no super-saturation.

Depth-dependent Respiration Formulation

€

Flux = k DOsat −DOsurf( )

Surface Oxygen Flux using Piston Velocity:

€

k = 3 e0.25W10

From Marino and Howarth, Estuaries, 1993

Model assumes biology is constant so that the role of physical processes can be isolated!

Comparison with Bottom DO at Chesapeake Bay Program Stations

July 19-21, 2004 August 9-11, 2004

Comparison with Chesapeake Bay Program DataBottom Dissolved Oxygen Concentration (mg/L)

Simple model captures seasonal cycle of hypoxia as well as a more complicated bio-geo-chemical model.

In addition to seasonal cycle, model captures some of the inter-annual variability

485 km3days

476 km3days

707 km3days

Model predicts roughly 50% more hypoxia in 2004 than in 2005, solely due to physical variability.

Variability of Physical Forcing

What is relative importance of different physical forcings in controlling seasonal cycle of hypoxia?

Sensitivity to River Discharge

Sensitivity to Temperature

Sensitivity to Wind

Differences between 2004 and 2005 are almost entirely due to wind forcing

Sensitivity to Summer Wind Magnitude

Average Monthly Wind Speed from Model at PNAS

Wind speed during May-August was increased/decreased by 15%

Changes in average summer wind speed of %15 result in roughly 2-fold change in hypoxic volume.

Base Summer Winds Positive 90°

Negative 90° 180°

Sensitivity to Summer Wind DirectionModeled summer wind direction

Sensitivity to Summer Wind Direction

Along axis winds result in less total hypoxic volume


Malcolm Scully

Outline:







7) Conclusions




Lateral AdvectionLateral AdvectionLateral Advection

Mechanisms for Oxygen “Ventilation”

Direct Vertical Mixing

Along-Channel Advection

detrainment

€

Qd = uin∂A∫ − uout∂A∫[ ] ×O2

July 2004 average bottom Oxygen

Fixed Volume for Budget calculations

Oxygen Budget Calculations

€

∂O2∂t+ u∂O2∂x+ v∂O2∂y+ w

∂O2∂z=∂

∂zKz∂O2∂z− R

Rate of change

Advection: Turbulent mixing

Respirationhorizontal lateral

Integrate all terms over entire volume

Monthly Averaged Sub-Pycnocline Oxygen Budget

Ekman

wind stress

North Wind

x

Ekman

wind stress

South Wind

Ekman

wind stress

West Wind

xEkman

wind stress

East Wind

Response of Chesapeake Bay to Wind Forcing is Strongly Impacted by Rotation

For most of the deep areas of the Bay, the gradient Richardson almost never drops below 0.25 in pycnocline (year round!).

Richardson Number for CPB Station 4.3

Sensitivity to Summer Wind Direction

Along axis winds result in less total hypoxic volume


Malcolm Scully

Outline:







7) Conclusions




Historical Observations of Hypoxia in Chesapeake Bay

Data from Jim Hagy

1) Multiple regression based on estimated nitrogen loading explains relatively small amount of observed variance.

2) Residuals to fit suggest hypoxic volume is increasing, despite recent reductions in estimated nitrogen loading.

3) One interpretation is that Bay is less able to assimilate nutrient inputs because of ecosystem degradation.

Observed hypoxic volume (< 1 mg/L)Regression Model

€

V = β 0 + β1NL

Residual

Duration of Summer Wind

River Discharge

Nitrogen Loading

N NE E SE S SW W NW

< 2 mg/L 0.00 0.08 0.18 -0.49 -0.37 0.04 0.69 0.32 0.16 0.36

< 1 mg/L -0.02 0.04 0.15 -0.48 -0.34 0.03 0.71 0.36 0.24 0.44

< 0.2 mg/L -0.10 -0.08 0.05 -0.42 -0.17 -0.10 0.55 0.30 0.33 0.62

* values in red denote significance at 95% confidence interval

Correlation of Historic Data (Hagy et al.) with Wind Direction

Wind data from Patuxent Naval Air Station (1950--2007)

Multiple Regression based on Nitrogen Loading and Duration of Westerly Winds

When you account for changes in wind direction, residual slope is no longer significant.

€

V = β 0 + β1NL + β 2W%

Observed hypoxic volume (< 1 mg/L)Regression Model Residual

Have the Winds over Chesapeake Bay Changed in recent Decades?

Conclusions

1) A relatively simple model with no biological variability can reasonably account for the seasonal cycle of hypoxia in Chesapeake Bay.

2) Wind speed and direction are the two most important physical variables controlling hypoxia in the Bay.

3) Model results are largely insensitive to variations in river discharge.4) The model suggests that the dominant balance controlling hypoxia is between

respiration and advective processes not vertical mixing.5) During winter months ventilation is dominated by longitudinal advection.6) During the summer months ventilation is greater by lateral advection.7) Because of the width of Chesapeake Bay, the rotational response to wind forcing is

greater for along-channel winds than for across-channel winds.8) Winds from the north enhance the residual circulation, increasing the longitudinal

flux of oxygen into the hypoxic zone.9) However, winds from then north are not common during the summer months and

subtle shifts between south and west winds may play a significant role in the observed inter-annual variability.

Documents

The Physical Modulation of Seasonal Hypoxia in Chesapeake Bay Malcolm Scully Outline: 1)Background and Motivation 2)Role of Physical Forcing 3)Simplified