Cross-scale Advances in CDOM Biogeochemistry: From Molecular to Eco-Regional Perspectives

Patrick Brezonik, Claire Griffin, Raymond Hozalski, Jacques Finlay, Leif Olmanson, Benjamin Allen, Marvin Bauer, and Yiling Chen

University of MinnesotaMinneapolis and St. Paul

Presented at Symposium in honor of George Aiken253rd National meeting, American Chemical Society

San Francisco, California, April 2-6, 2017

Acknowledgments

National Science Foundation, Environmental Engineering Program, Award #1510332,

including citizen science supplement

Legislative & Citizen Commission on Minnesota Resources (LCCMR) grant

Major Project Components

0

5

10

15

0 10 20 30

CD

OM

Year (0 = 1984)

CDOM = fΣai(LCT)i

0

6

0 10 20 30

SUV

ACDOM, a440, m-1

MN landcover types

(LCT)

• UMN & collaborators: 263 sites• MPCA lake monitoring: 123 sites

Study Area

NMW

NLF

NLFNLF

NLF

NCHF

NCHF

NCHF

ECOREGIONS:NLF: Northern Lakes and ForestNCHF: North-Central Hardwood ForestNMW: Northern Minnesota Wetlands

Minnesota

Wisconsin

Michigan

Michigan (UP)

Lake Superior

LakeMichigan

I. Spectral Characteristics of CDOMand Fe-CDOM Complexes

Are CDOM’s spectral properties constant across the regionand concentration range in the region?

Do spectral/Fe variations complicate regional measurementsof CDOM by satellite imagery or estimates of [DOC] from satellite-derived CDOM?

Summary statistics: CDOM, DOC, and SUVA, all 2016 sites

CDOMa440, m-1

DOCmg/L SUVA

N 296 237 232

Mean 4.06 10.70 2.67

Median 1.40 8.26 2.35

Range 0.0-32.5 2.5-47.6 0.5-5.5

R² = 0.65

0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 10 20 30 40

SUV

A

DOC, mg/L

R² = 0.86

0.0

1.0

2.0

3.0

4.0

5.0

6.0

0 10 20 30 40

SUV

A

CDOM (a440), m-1

2016 Data

R² = 0.951

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

0.0 5.0 10.0 15.0 20.0 25.0

SUV

A

CDOM, a440, m-1

R² = 0.89

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

0.0 10.0 20.0 30.0 40.0

SUV

A

DOC, mg/L

2015Data

Plots of SUVA vs. CDOM and DOC fit ln relationships

-0.04

-0.03

-0.02

-0.01

0.00

0 10 20 30 40

S 27

5-2

95

CDOM (a440), m-1

-0.04

-0.03

-0.02

-0.01

0.00

0 10 20 30 40

S 35

0-4

00

CDOM (a440), m-1-0.04

-0.03

-0.02

-0.01

0.00

0 10 20 30 40

S 40

0-4

60

CDOM (a440), m-1

275-295 nm

400-460 nm

350-400 nm

Spectral slopes, Sx-y and slope ratio, Sr, for 2016 data

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0 10 20 30 40

S r

CDOM (a440) m-1

Sr = S275-295/S350-400

Dissolved Fe-CDOM relationship: 2015 data; N = 61

Fe/CDOM

Average: High Low

n = 8 n = 7

Fe/a440 52 23

Diss. Fe 714 371

a440 13.6 16.1

ln a440 2.43 2.61

DOC 20.9 23.0

a440/DOC 0.65 0.70

SUVA254 4.3 4.5

S275-295 -0.0148 -0.0145

S350-400 -0.0172 -0.0178

S400-460 -0.0156 -0.0150

S460-600 -0.0110 -0.0105

Sr 0.85 0.82

y = 37.1x - 34.3R² = 0.77

0

200

400

600

800

1000

1200

1400

0 5 10 15 20 25

Dis

solv

ed

Fe

, μg/

L

CDOM (a440), m-1

CDOM Spectral Properties

0

5

10

15

20

25

30

0 200 400 600 800 1000 1200

CD

OM

(a

44

0),

m-1

[Fe], μg/L

*All samples adjusted to pH 6.5 after each FeIII addition; average slope = 0.0022

Effect of added dissolved FeIII on CDOM absorptivity at 440 nm*

y = 37.1x - 34.3R² = 0.77

0

200

400

600

800

1000

1200

1400

0 5 10 15 20 25

Dis

solv

ed

Fe

, μg/

L

CDOM (a440), m-1

Changing high or low Fe/CDOM ratios to the “best fit” ratio causes only small changes in the CDOM level:

I. Spectral Characteristics of CDOMand Fe-CDOM Complexes

Are CDOM’s spectral properties constant across the regionand concentration range in the region?

Regionally: yes. Across concentration change: yes for CDOM > ~3 m-1;

for low CDOM (0.1-3.0 m-1): jury still out.

Do spectral/Fe variations complicate regional measurementsof CDOM by satellite imagery or estimates of [DOC] from satellite-derived CDOM?

No, or at least not very much.

II. Spatial Patterns in DOC & CDOM

What role does ecoregion status play in CDOM and DOC distribution?

Can we predict CDOM levels from catchment land cover?

How accurately can satellite imagery measure CDOM across the broad range of its occurrence (a440 < 1 to > 30 m-1)?

R² = 0.92

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30 35

DO

C, m

g/L

a440, m-1

R² = 0.94

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30

DO

C, m

g/L

a440, m-1

All sites; N = 234

All but 3 sites with a440 > 3 m-1

were in the NLF. Highest CDOM in NCHF was 5.3 m-1.

Sites with CDOM (a440) > 3 m-1

R² = 0.35

0

2

4

6

8

10

12

14

16

0.0 0.5 1.0 1.5 2.0 2.5 3.0

DO

C, m

g/L

a440, m-1R² = 0.41

0

2

4

6

8

10

12

14

16

0.0 1.0 2.0 3.0

DO

C, m

g/L

a440, m-1

R² = 0.38

0

2

4

6

8

10

12

14

16

0.0 1.0 2.0 3.0

DO

C, m

g/L

a440, m-1

NCHF: N = 82

NLF: N = 84

2016 sites with a440 < 3 m-1

All sites: N = 166

a440 = % Woody Wetlands + % Evergreen Forest −% Open Water

R2 = 0.52, n = 152

From NLCD and MN DNR Watersheds Data

Land Use Land Cover and CDOM in the Ely Area for Headwater Basins

State- and region-wide relationships may be different, as there is little developed (< 6.5%) or cultivated (< 0.3%) land cover in Ely-area catchments.

Best fit relationship:

A “Kutser-like”model, a440 = a0(O3/O4)a1, yielded a good fit (R2 = 0.81) for data fromCDOM-dominated, northern MN lakes (■), but inclusion of 5 sites from the opticallycomplex St. Louis River (∆), which had highcolor, chlorophyll and TSS, yielded much poorer fit (R2 = 0.24).

ln(a440) = -48.2ln(O3/O4) + 6.34R² = 0.81

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0.00 0.03 0.06 0.09 0.12 0.15

ln(a

44

0)

ln(O3/O4)

According to Olmanson et al. (2016)(RSE special issue on Landsat 8):

O3 = reflectance in Landsat 8 green bandO4 = reflectance in Landsat 8 red band

ln(a440) = b0 + b1(O3/O5) + b2(O4) (R2 = 0.82; n = 28)

ln(a440) = b0 + b1(O2/O5) + b2(O1) (R2 = 0.79; n = 28)

Two-term models similar to those of Brezonik et al. (2005) yieldedgood fit for all the data:

Band key: O1 (violet deep blue); O2 (blue); O3 (green); O4 (red); O5 (near IR)

0 100 200 300 40050Kilometers

“Preliminary”Minnesota CDOM

Map (2015)

Two-variable universal modelfor multiple Landsat images:

a440 = -5.48*OLI3/OLI4 -0.633*LN(OLI4/OLI5) + 8.13

See next slide

Ely

Boundary Waters Canoe Area Wilderness

Shagawa L.

Burntside L.

White Iron L.L. Vermilion

Birch L.

Pike R. Bay

CDOM distribution in lakes near Ely, MN based on 2015 Landsat 8 image

II. Spatial Patterns in DOC-CDOM Relationships

Role of ecoregion status in CDOM and DOC distribution

High CDOM (a440 > ~ 3 m-1) mostly in NLF, rarely in NCHF.

Can we predict CDOM levels from catchment land cover?

We think so (coupled with basic hydrologic information).

How accurately can satellite imagery measure CDOM acrossthe range of its occurrence (a440 < 1 to > 30 m-1)?

Accuracy good up to at least a440 ≈ 13 m-1.

III. Historical Trends in CDOM Levels

Is CDOM increasing in north-central U.S. surface water on a decadal basis, as has been shown across Scandinavia?

If so, what are the causes?

y = 0.21x + 3.24R² = 0.40

0

2

4

6

8

10

12

14

0 5 10 15 20 25

a4

40

Year (0 = 1990)

Crystal Bog, WI; data from UW LTERProgram (From Brezonik et al. 2015)

Ground-based data in the Upper Midwest are very sparse. Can historical Landsat imagery provide answers?

Dates for clear Landsat imagery for analysis of historical CDOM trends in NE Minnesota

All images in Path 27, Rows 26-30, covering the CDOM-rich area north and south of Ely.

1984 1986 1987 1988 1989 1990 (2) (2) (2)

1991 1992 1994 1995 1997 1998 1999 2000(3) (2) (3)

2001 2002 2003 2005 2006 2007 2008 2009 2010(2) (2) (2)

2011 2012 2013 2015 2016

9/25/87 10/9/98

9/26/2005 11/9/2015

Preliminary CDOM maps based on Landsat imagery for area near Ely, MN over four decades

0

5

10

15

20

25

9/16/84 9/25/87 10/20/91 10/30/94 10/9/98 10/28/99 9/12/00 8/25/02 9/26/05 10/8/08 11/9/15

CD

OM

, a4

40

East Vermillion

West Vermilion

Pike Bay

Buck

Big Moose

Echo

Pine

Armstrong

Shagawa

Burntside

Farm

Preliminary CDOM time trends for 11 Ely-area lakes for 11 dates from 1984 to 2015

III. Historical Trends in CDOM Levels

Is CDOM increasing in north-central U.S. surface water on a decadal basis, as has been shown in Scandinavia?

Preliminary data suggest not; we’ll know much more by the end of 2017.

If so, what are the causes?

TBD.

Prospects for the Future

Frequent (~ weekly) large-scale monitoring of CDOM and otherkey water quality parameters now is possible (or will be oncecurrent Landsat and Sentinel satellites are fully operational).

CDOM monitoring (via satellite or citizen science) will become apart of routine local-state-national water quality monitoring programs. (We have relatively little information now).

Coordinated studies combining field measurements, laboratorystudies, and satellite imagery will greatly enhance understandingof spatial and temporal variations of CDOM in aquatic ecosystemsand its impacts on water treatment processes (e.g., disinfection)and on important photochemical processes.