CBEO Year 3 Planning

Rebecca Murphy

Dec. 9, 2008

CBEO research

Analyze changing relationship of hypoxic volume to N load over 50 years. Hypotheses:• Artifact of interpolation method• Artifact of sampling density

Calculate and analyze Bay stratification:• Its relation to hypoxic volume• When, where and why changes in stratification are occurring

For use by others in CBEO science questions

and network tools

Interpolation methods• Test and compare kriging methods in Bay

2D single depth (x,y) 2D along main stem (z,y) 3D kriging 3D kriging using water distance …3D (or 4D) kriging using travel time (extension project…)

• Use water quality model as covariate in all of these

July 1-15, 2004 DO interpolated

Science Q: Why the shift in relationship between nutrient loading and hypoxia after 1980?

Artifact: interpolation leads to miscalculation of hypoxia volume

1. 2D kriging main channel data: expand laterally to get 3D

Hypoxic Volume (DO<2mg/L) Interpolated from Average July Datasets

0

2

4

6

8

10

12

14

1949 1954 1959 1964 1969 1974 1979 1984 1989 1994 1999 2004

Hyp

oxic

Vol

ume

(km

3 )

0

50

100

150

200

250

300

350

400

450

Spr

ing

N lo

ad (

Mg/

day)

Kriging DO<2 mg/LSpring N load

Hypoxic Volume (DO<2mg/L) Interpolated from Average July Datasets

0

2

4

6

8

10

12

14

16

Hyp

oxic

Vol

ume

(km

3 )

1949 1953 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005

Kriging DO +/- 1 SD .Kriging DO<2 mg/LHagy et al. 2004

1963: There were no samples taken south of the Potomac anywhere in the Bay from July-Aug. This means that there is large uncertainty in the statistical procedure in that region. Considering some methods of accounting for this, since we know the DO won’t be too low in the southern Bay.

Analysis of Hypoxic Volume

Shift in hypoxic volume related to N load does not appear to be an artifact of interpolation method

Early July appears to have the strongest increase in hypoxia/N of each 2 week period in the summer

Early July Cruises: Hypoxic Volume (<2 mg/L) per Spring N Load

y = 1.0589x - 2078.8

R2 = 0.208

0

10

20

30

40

50

60

70

80

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Hyp

oxi

c V

olu

me

/ N

loa

d [

km3

/(G

g/d

ay)

]

P-value on slope = 0.03

Late July Cruises: Hypoxic Volume (<2 mg/L) Per Spring N-Load

y = 0.1323x - 228.52

R2 = 0.0044

0

10

20

30

40

50

60

70

80

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Hyp

oxic

Vol

ume

/ N lo

ad [k

m3/

(Gg/

day)

]Late JulyLinear (Late July)

Science Q: Why the shift in relationship between nutrient loading and hypoxia after 1980?

Artifact: interpolation leads to miscalculation of hypoxia volume

1. 2D kriging main channel data: expand laterally to get 3D

2. 2D kriging at single depths: sum volumes from single depths to get 3D

Early July: Hypoxic Volume (DO <2 mg/L) Per Spring N-loadUsing Different Interpolation Methods

y = 1.0589x - 2078.8

R2 = 0.208

y = 1.0358x - 2029.4

R2 = 0.2127

0

10

20

30

40

50

60

70

80

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Hyp

oxic

Vol

ume

/ N lo

ad (

km 3 /(

Gg/

day)

)

2D profile interpolationsSingle depth slices summedLinear (2D profile interpolations)Linear (Single depth slices summed)

Science Q: Why the shift in relationship between nutrient loading and hypoxia after 1980?

Artifact: interpolation leads to miscalculation of hypoxia volume

1. 2D kriging main channel data: expand laterally to get 3D

2. 2D kriging at single depths: sum volumes from single depths to get 3D

Artifact: interpolation leads to miscalculation of hypoxia volume

3. Sub-sample post-1984 data as if it was pre-1984 data and interpolate

DO samples taken July 9-12, 1970

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2

4

6

8

10

12

14

1949 1953 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005

Hyp

oxi

c V

olu

me

(km

3 )

0

2

4

6

8

10

12

14

Subsampled avg hypoxic vol +/-SD

.

Avg subsampled set hypoxic vol

Full data set, hypoxic vol

July Mainstem Hypoxic Volume (DO <2 mg/L): Kriging Mainstem Data with Sample Density Analysis

Process Hypothesis to Hypoxia Q: Change in StratificationLooking at:

Long term trends in volume of water below pycnocline in July Long term trends in interpolated salinity and temperature data Correlations between pycnocline volumes, DO, temp, salinity, flow

upper and lower pycnocline

Early July Cruises: Hypoxic Volume and Pycnocline Volume

y = 0.1354x - 240.47

R2 = 0.1556

y = 0.176x - 343.04

R2 = 0.0997

y = 0.1761x - 326.71

R2 = 0.2202

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5

10

15

20

25

30

35

40

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Vo

lum

e (k

m3 )

Vol Below Upper Pycnocline

Vol within pycnocline

Hypoxic Vol (<2 mg/L)

Linear (Vol Below Upper Pycnocline)

Linear (Hypoxic Vol (<2 mg/L))

Linear (Vol within pycnocline)

p-value = 0.06

p-value = 0.02

p-value = 0.14

Early July: Hypoxic Volume and Water Temperature

y = 0.0497x - 72.877

R2 = 0.0796

-

5

10

15

20

25

30

35

40

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Vo

lum

e (k

m3 )

20

21

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25

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28

29

30

Su

rfac

e T

emp

(C

)

Volume below upper pycnocline

Interpolated Hypoxic Volume (<2 mg/L)

Interpolated Avg Surface Temp (C)

Linear (Interpolated Avg Surface Temp (C))P-value = 0.19

Identify Locations with Temperature Change Map shows significance level of non-

zero slope in the regression for each station:

Temperature = + Year +

(for surface temperature measurements from each early July, 1984-2006)

Increase in surface temperature appears to be in northern part of Bay

CB1.1

CB3.3C

Summary: Hypoxia and Stratification With improved interpolation, we still observe increased hypoxic

volume per nitrogen load in recent years

Increase in hypoxic volume appears to be strongest in early July

Chesapeake Bay stratification is increasing in early July

This could be a reason for the increased hypoxic volume

Surface water temperature appears to be increasing in early July, and is strongly correlated to hypoxic volume

Temperature could be the reason stratification is increasing

Temperature could be affecting hypoxic volume through stratification OR other means (solubility, increased phytoplankton growth rates, etc)

Year 3 Plan 3D kriging/water distance

Investigate temperature and pycnocline changes and relations to hypoxic volume Recent Climate Change Report for Bay (CBP STAC, Oct 08) Analyze suspended sediment, clarity, and chlorophyll (ideas from student

meeting) Analyze lateral stratification and temperature Pycnocline trends using 3D kriging Model results and regressions

Collaborations with others, including: Kemp, DiToro teams for ideas on pycnocline analysis Jeremy: Interpolations of N, P Jeremy: Analysis of model results Jen: Interpolations of DO at benthic sites

Other CBEO support Testbed organization/documentation/new data GEON data and tool transfer Spatial querying and creating user-friendly model data queries

Year 3 Plan Possible CBEO-related papers:

Hypoxia trend with multiple interpolation methods and digging in more to post-1984 (possibly partner with analysis of N trend)

Interpolation comparisons/method development studies One submitted 3D kriging and water distance possible

Hypoxic volume trend relates to temperature and stratification