GloboLakes: Global Observatory of Lake GloboLakes: Global

GloboLakes: Global Observatory of Lake Global Observatory of Lake
Responses to Environmental Change
p
g
Mike Grant,
Grant PML
(in lieu of Steve Groom)
[email protected]
@
l
k
Introduction and consortium
GloboLakes is a 5 year (2012 -2017) €3 million UK project to investigate the
state off lakes globally using EO
O data & investigate their response to
environmental change drivers
Andrew Tyler, Peter Hunter, Evangelos Spyrakos: University of Stirling, UK
Steve Groom, Victor Vicente-Martinez, Gavin Tilstone, Giorgio Dall’Olmo:
Pl
Plymouth
th M
Marine
i L
Laboratory,
b t
UK
Christopher Merchant, Stuart MacCallum: University of Edinburgh/University of
Reading,
g UK
Mark Cutler, John Rowan, Terry Dawson, Eirini Politi: University of Dundee, UK
Stephen Maberly, Laurence Carvalho, Stephen Thackery, Alex Elliott: Centre for
Ecology & Hydrology, UK
Claire Miller, Marion Scott, Ruth Haggarty: University of Glasgow, UK
Overview
• Rationale and Approach
• In situ sampling
• How
H
will
ill Gl
GloboLakes
b L k b
be off b
benefit
fit ffor
• Future plans
• LIMNADES
Rationale
•
–
–
–
–
•
•
SeaWiFS: 1997‐2010
>300 million lakes globally
Provide essential ecosystem goods & services
Fundamental to global food and water security
Important in global biogeochemical cycling
Yet only <0.0001% sampled regularly
MERIS: 2002‐2012
Aim to observe from EO data ~1000 lakes spanning all
climatic zones
MSI ‐ Sentinel 2: 2015 Timeliness – why
y now?
– Increasing robustness
approaches
of
EO
algorithms
&
ensemble
– Impending launches of Sentinel 2 MSI and 3 OLCI offering
superior capabilities (2015)
– By 2017 will be 20 years of ocean colour observations
OLCI ‐Sentinel 3: 2015
Our approach
•
Set up a satellite-based observatory with archive and near real-time (NRT) data
processing for 1000 lakes globally
•
Process archive/new data to produce time series of:
i) Lake Surface Temperature;
ii) Chl-a;
iii) phycocyanin concentration;
iv) Total Suspended Matter
v) Coloured Dissolved Organic Matter
•
Investigate
est gate spat
spatial
a & te
temporal
po a ttrends
e ds & att
attribute
bute
causes of change for 1000 lakes worldwide
•
Investigate lake sensitivity to environmental change
•
Distribute data freely to external project partners
and end-users via web portal and ftp
•
Opportunistically
pp
y investigate
g
Sentinel 2 MSI
Lake Balaton, Hungary
Ice Cover
Ice Cover
Project structure
2012-15
2013 17
2013-17
2013-15
2014-16
ESA
ARCLakes
(Reading)
WP1: EO algorithms
g
for lakes (Stirling)
ESA DIVERSITY II
(Brockman Consult)
WP2: Operational
NRT processing
(PML)
WP3: Climate and
catchment data
(Dundee)
WP4: Data integration and uncertainty
assessment (Stirling/Glasgow)
WP5: Spatial and
temporal patterns
(Glasgow)
WP6: Attributing
causes (CEH)
2012-17
WP7:
Forecasting
models
(CEH)
WP8: End-user applications for lake management
(Stirling – All)
EO model
development
and processing
Quality assurance
Data analysis and
interpretation
End-user
engagement
Relevance to GEO
• WA‐01 Integrated Water Information (incl. Floods and Droughts)
– Improving water‐resource management through better understanding of the water cycle – GloboLakes contributes to many parts of WATER
GloboLakes contributes to many parts of WATER
– C4 Global Water Quality Products and Services
– Priority Actions
• Develop improved Earth observation derived water‐quality datasets through algorithm development, atmospheric correction and standardization of data processing and products – GloboLakes WP1, 2 and LIMNADES
• Conduct demonstration projects on the value of EO for water management such as p
g
p j
g
expanding the ChloroGIN project as a fast track end‐to‐end exercise to include large lakes and evaluate existing lake algorithms (see SB‐01)
– WP2 extension to ChloroGIN
Hierarchy of Study Lakes
Intercomparison and operationalisation of algorithms using data
from a hierarchical populations of lakes
Level 1. Well understood,
with excellent sampling
~15 lakes
WP1: GloboLakes in situ optics and
biogeochemical data for algorithm
development
Level 2. In-situ
biogeochemical data
available for validation
~50 lakes
WP1/2: Collaborator provided in situ
biogeochemical data and high temporal
resolution buoy data for validation
Level 3. Unknown
characteristics validation
characteristics,
data very limited or absent
~1000 lakes
WP2: Output:
p Level 2/3 data p
provided to
users
Sampling parameters
•
Aim to measure as many parameters as feasible  optical closure
Field parameters
Bio‐optical parameters
Laboratory parameters
Secchi disk depth
Remote sensing reflectance (Satlantic
HyperSAS; Trios RAMSES)
Chl‐a (spectrophotometric ISO method)
Water depth
Subsurface irradiance reflectance (Satlantic HyperOCRs)
Size‐fractionated Chl‐a
Water temperature
Spectral absorption coefficients
(Wetlabs AC‐S;
(Wetlabs AC
S; PSICAM)
PSICAM)
HPLC pigments (CSIRO method)
Wind speed
Spectral attenuations coefficients
(Wetlabs AC‐S)
Phycocyanin (adapted from Horváth et al., 2013)
Digital photos (water & sky conditions)
Spectral backscattering coefficients (Wetlabs BB3)
CDOM (a200‐800 & SCDOM)
Aerosol optical depth (using a Microtops)
Temperature, depth, salinity profiles (Sea‐Bird Electronics)
CDOM synchronous fluorescence scans (Universidade de Vigo)
TSM PIM POM (REVAMP protocol)
TSM, PIM, POM (REVAMP
t l)
Particulate absorption (NASA Ocean Optics method)
DOC (Shimadzu TOC‐VSCN)
POC (Perkin Elmer CHN analyzer)
Phytoplankton samples (preserved in Lugol’s)
Flow cytometry (preserved)
Sampling in 2013
UK
Lakes
• UK lakes:
• Loch Leven (4 times),
Loch Lomond (7), Windermere (2),
Bassenthwaite (1) & Derwent Water (1)
• Range of sizes: 5-71km2; oligotrophic
to eutrophic; range of depths
• Hungary
• Lake Balaton (4) & Kis Balaton (1) Hungary
Lomond
Leven
UK lakes
Hungarian
lakes
Windermere
Bassenthwaite
Derwent
Balaton
Kis Balaton
Total
Stations
35
17
Samples
93
51
Casts
161
121
7
5
5
11
2
82
21
15
15
33
2
230
37
21
22
150
8
520
│
May
│
│
│
June
│
│
July
│
August
September
│
│
│
│
││
│
│
│
│
│
│
│
│
││
│
│
│
• 82 stations sampled; 230 water samples; 520 optics casts
• Additional above water continuous radiance measurements
│
│
Results from 2013
• Analysis is at an early stage
• Biogeochemical Summary:
• TSM 0.4 -10 mg L-1;
• chl-a 6 - 100 mg m-3;
• PC: 0 – 51 mg m-3;
• DOC 1.4
1 4 – 7 mg L-1
• Unfortunately there were no appropriate satellite observations
(i.e. MERIS expired in 2012)
Algorithm validation in Balaton
Atmospheric correction validation
Four AC models
• MERIS MEGS (Standard
ESA)
• NASA SeaDAS
• CoastColour (Brockman
Consult lead ESA project)
• SCAPE-M (Guanter et al.,
2010)
Dataset
r
RM SE
Bias
Slope
I ntercept
MERIS MES
0.8295
0.1795
0.0869
0.9300
0.1636
MERIS MEF
0 8897
0.8897
0 2371
0.2371
0 0994
0.0994
1 4016
1.4016
-0.328
0 328
CoastColour
0.5142
0.5372
0.5114
0.1906
1.5179
SCAPE-M
0.8320
0.1886
-0.123
0.6913
0.2122
Proposed sampling for 2014
Extended in Europe through EC FP7 INFORM
Mid May
Early June
Mid June
July
Mid August
Mid September
Loch Lomond, UK
Lake Geneva, Switzerland
Loch Ness
Ness, UK
Lake Balaton, Hungary (EC FP7 INFORM/EUFAR)
Cumbrian Lakes, UK
Mantua Lakes
Lakes, Italy (INFORM/EUFAR)
Opportunistic
Opportunistic
Oppo
u s c
Loch Leven
Loch
oc Lomond
o o d
Summer
NERC Airborne Remote
Sensing
g flights
g
(Leven,
(
Lomond, Lough Neagh/
Windermere)
Specim Fenix 400 – 2500nm
Specim Owl superspectral
Thermal IR
Proposed sampling for 2015
Sentinel 3 validation…
Opportunistic sampling targeting S2
overpasses (and S3 if available) with 24 h
mobilization in weather windows)
•
•
Loch Leven
Loch Lomond
Mid July
Mid August
INCIS-3IVE)
Lough Neagh (NI)
Lake Vanern (Sweden;
Installation of radiometers on UKLEON buoy
y
(Loch Leven or Loch Lomond; TBC)
Real time Chla, turbidity and CDOM from (at
Real-time
least) 11 UKLEON buoys (8 on lakes > 0.5
km2)
WP2 5 Dissemination: OGC Portal
WP2.5 Dissemination: OGC Portal
WP2 5 Dissemination: OGC Portal
WP2.5 Dissemination: OGC Portal
WP2 5 Dissemination: OGC Portal
WP2.5 Dissemination: OGC Portal
WP2 5 Dissemination: OGC Portal
WP2.5 Dissemination: OGC Portal
MERIS
17 Mar 2012 Lake Balaton, Hungary, kd490
LIMNADES
Lake bIo-optical MeasuremeNts And matchup Data for rEmote Sensing (LIMNADES)
C
Community-owned
it
dd
database
t b
off AOP
AOPs, IOPs,
IOP constituent
tit
t concentrations
t ti
and
d ancillary
ill
data
d t
• >110 lakes
• 20 countries
• 5 continents
• GloboLakes is aiming to
• Develop improved approaches to retrieve bio-optical parameters over
lakes globally
• Undertake archive and near-real time processing to produce a global
time series in >1000 lakes worldwide
• Contribute to GEO WATER tasks
• Other work (PML)
• EC FP7 INFORM
INFORM: lake
l k primary
i
production
d ti and
d phytop.
h t
size
i classes
l
• EC FP7 EartH2Observe: focus on high CDOM + cyanobacterial lakes in
Estonia
Thank you!
www.globolakes.ac.uk