Autonomous fixed station measurements and synoptic …scienceconf2014.deltacouncil.ca.gov/sites/default/files/uploads/... · 10/28/2014 · synoptic spatial characterization provide

Autonomous fixed station measurements and synoptic spatial characterization provide insights into dynamics of organic matter, nutrients and algal pigments in the SF Bay-Delta

Bryan Downing, Brian Bergamaschi, Brian Pellerin, Tamara Kraus, Elizabeth Stumpner, Scott Nagel, Katy O’Donnell, Amy Story, John Franco Saraceno, Travis von Dessonneck and Roger Fujii, and many others.

2014 Bay-Delta Mtg Tuesday, October 28, 2014 @3:35 pm Room

Overarching Monitoring Goals

I. Assess and improve methods to better explain water quality conditions.

II. Characterization and interpretation of spatial and temporal patterns of nutrient and phytoplankton conditions.

III. Support other research activities through availability of consistent and scientifically valid time series.

• When, where and why does phytoplankton production occur in the CSC?

• How are nutrient, DOM, and particle dynamics affected by increased flows and changes in source waters in the CSC?

• Does the CSC act as a subsidy for dissolved and particulate material to the rest of the estuary?

• Is particle composition related to physical dynamics such as flow and turbulence?

Assessing Habitat Conditions

Assessing habitat conditions

• What are the attributes of “good” pelagic aquatic habitat? • More phytoplankton – of the right type.

• Evidence that existing zooplankton stocks are food-limited

• More zooplankton – of the right type.

• An environment conducive to feeding and avoiding predation; not too warm

• Where and when and under what conditions do we observe “good” pelagic aquatic habitats?

• Can we expand the spatial and temporal extent of “good” pelagic aquatic habitat?

Shag

Slo

ugh

Lib

erty

Cu

t

Stair Step

Little Holland Tract

Cache Slough Complex

What, Where and When are NO3 and Chl-a gradients in

Cache Slough Complex found?

Satlantic SUNA in situ optical nitrate analyzer.

Sensors

Accuracy ± 2 μM (±0.028 mg/l-N) or ± 10% of reading, whichever is greater (10 mm pathlength, σ under laboratory conditions)

Precision [at 3σ] 0.3 μM (freshwater or seawater with T-S-Correction) 2.4 μM (seawater [0-40 psu])

Turbidity Range 625 NTU* (10 mm path length) 1250 NTU (5 mm path length)

Detection Range 0.5 to 4000 μM (0.007 to 56 mg/I-N)

YSI model EXO 2: 6-port multiparameter water quality sonde with anti-fouling wiper

• CTD • pH • Turbidity (0 to 4000 FNU) • Dissolved Oxygen • fDOM (0 to 300 ppb QSE) • Chlorophyll-a (0 to 400 ug/L) • Phycocyanin (0 to 100 ug/L)

Continuous monitoring at flow stations

7

monitoring at flow stations

USGS 381443121405701, LIBERTY ISLAND AT HASTINGS TRACT

thli. .... P'-••™..,......,!9d10,_,_,...__. ........ i. .... ~--a""" ~ .. od niwt ,..._ \9 ..... o COAUCl .-~ ....._ rianoit, ... ~ .... '11-1l'l'31Sl)j0t ..... tlolo," ... _

Nutrient concentrations and ratios change rapidly

Sacramento River at Walnut Grove

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

3/27 3/29 3/31 4/2 4/4 4/6 4/8

Ammonium

Nitrate

Phosphate

PO

4-P

(m

g/L

) an

d N

H4

-N (

mg/

L)

NO

3-N

(m

g/L)

0.1

0.2

0.3

0.4

0.5

0.06

0.07

0.08

0.09

0.1

0.11

6/13/2013 6/23/2013 7/3/2013 7/13/2013 7/23/2013 8/2/2013

NO

3 (m

g/L) P

O4

(m

g/L)

PO4 (mg/L)

Nitrate (mg/L)

Stage

Nitrate and Phosphate dynamics in Cache Slough

Nitrate and Chlorophyll dynamics in Cache Slough Nitrate and Chlorophyll dynamics in Cache Slough

0.7 l 0.65

0.6 1 ~0.55 "° E -

0.3

0

• • .__

3/31/13 4/ 1/ 13 4/ 2/ 13 4/ 3/ 13 4/ 4/ 13 4/5/13 4/ 6/ 13 4/7/13

- 30

r 25

20 ~ -"° :I -ra •

15 > ~ a.. e .E

10 6

5

Chlorophyll Source Identification

Chlorophyll peaks track Conductivity in flood tides.

Estuarine source

Chlorophyll peaks track conductivity in ebb

tides. River chlorophyll from Liberty/ Cache

Complex

CSC North to South Jan-Oct 2014

0

200

400

600

800

1000

0

2

4

6

1/11 3/2 4/21 6/10 7/30 9/18 11/7

SpC

on

d (

uS/

cm)

NO

3-N

(m

g/L

)

FCH

L-a

(RFU

)

TOE DRAIN

LIBERTY CUT

LIBERTY MOUTH

0

100

200

300

400

500

0

2

4

6

1/11 3/2 4/21 6/10 7/30 9/18 11/7

SpC

on

d (

uS/

cm)

NO

3-N

(m

g/L

FC

HL-

a (R

FU)

0

200

400

600

800

1000

0

2

4

6

1/11 3/2 4/21 6/10 7/30 9/18 11/7

SpC

on

d (

uS/

cm)

NO

3-N

(m

g/L

)

FCH

L-a

(ug

/L)

Panel A and B: 1. Thermosalinograph (Sea-Bird), 2. CDOM fluorometer (WET Labs), 3. Chl-a fluorometer (WET Labs), 4. Transmissometer (WET Labs), 5. ISUS nitrate sensor (Satlantic), 6. Custom fluorometer (WET Labs) Panel C: CR1000 (Campbell Scientific) integrated into the data collection platform

Spatial mapping using underway measurements

What long residence time does to nutrients

Nutrient concentrations and ratios change vary in space Cache Slough Complex

10/30/13

Residence time model for Liberty Island

• ESA PWA residence time model • Sac R, Toe Drain and western sloughs are sources • Northward flow direction

Source – Matt Brennan, ESA

Spatial Mapping & Fixed Stations NO3 (mg/L) 5/14

LIB

DWS

LCT

CCH

ISUS

0.10 - 0.50

0.51 - 0.75

0.76 - 0.85

0.86 - 1.00

1.01 - 2.00

LCT

LIB

CCH

DWS

Spatial Mapping & Fixed Stations Chl-a (µg/L)

WS_Chl

0.11 - 3.00

3.01 - 5.00

5.01 - 8.00

8.01 - 17.00

17.01 - 38.00

5/14

*Local meteoric water line slope = 7.1, intercept = -1.3

**Real-time isotope data slope = 5.4, intercept = -19.3

*Carol Kendall USGS, Menlo Park ** Kate Dennis and Jeffery Carter, Picarro inc,

Isotope Hydrology

Wat

er

d2

H

Water d18O

10/1/14 data

dH_60

-79.56 - -75.00

-74.99 - -71.00

-70.99 - -67.00

-66.99 - -63.00

-62.99 - -60.00

dO_60

-10.77 - -9.75

-9.74 - -8.75

-8.74 - -7.75

-7.74 - -7.00

Data collection: 8:30 – 15:00 High Tide @ 11:15 Low Tide @15:45

ISUS

0.34 - 0.40

0.41 - 0.50

0.51 - 0.60

0.61 - 0.70

0.71 - 0.80

NO3 mg/L d2H d18O

Applications for remote sensing

Conclusions

• Nutrient concentrations change quickly: need continuous high freq. sampling < 1 hour.

• Continuous sampling useful to understand biological processes associated with nutrient cycling.

• Spatial mapping can help us understand links between nutrients and primary production.

• The combined approach provides additional insight in the shallow water habitat of CSC.

Acknowledgements

We thank Erwin Van Nieuwenhuyse / BOR for funding this project. Jon Burau for continued support, hours of advice and fair warnings. Special thanks to Scott Nagel, Paul Kreun, Katy O’Donnell, Angela Hansen and Travis von Dessonneck for technical and lab support.