Transcript lessons for protecting freshwater systems from

Climate Variability and
Freshwater Systems
Lessons for protecting freshwater systems from climate
change impacts
Fran Sheldon
Australian Rivers Institute
Griffith School of Environment
Griffith University
We know Australia’s
rivers are variable…..
0.8
Summary medians
0.7
(23 hydrological measures)
Cooper
Diamantina
0.6
0.5
YAN
GOD
URA
RIO
STH
ARK
WIN
LOI
COL
DNI
SON
IND
KUR
REA
BAH
AMU
MIS
VIS
SAO
NTH
RHI
TIS
ZIJ
SYR
SEV
0
OUB
SAN
FRA
NIL
BAN
DAN
PET
KOL
0.1
Mekong
Mississippi Colorado
Danube
Rhine
OGO
NIG
MEK
NEV
0.2
AUX
ODE
SNA
DAR
VAA
FIT
LIM
BUR
DIA
COO
0.3
KRI
DON
REE
0.4
HUA
ASS
Burdekin
Limpopo
Fitzroy
Vaal
Darling
from Puckridge et al. (1998). Mar. Freshw. Res. 49, 55-72
Predictions are that variability will
increase with climate change…….
 Rainfall & consequently river flow will become more variable
 There will be less frequent, but perhaps larger, floods
 Rivers will be influenced by longer, and more severe, no flow or
drought conditions
 There will be an increase in the number of highly variable rivers
 Understanding flow variability and its influence on rivers will
become important for
o looking at resilience of systems in the face of climate change
o determining environmental flows and
o assessing ecosystem health
Scales of Variability in
Dryland Rivers
Spatial Scale (m)
Catchment scale
responses to
flood – drought
cycles
Reach scale
responses to
‘boom and
bust’ cycles
Within
channel
water level
fluctuations
Temporal Scale (years)
Within channel variability:
Lower River Murray
Darling
River
Menindee
Lakes
Menindee
South
Australia
Morgan
Blanchtown
Overland
Corner
1 2 3
New South Wales
Renmark
56 7
10
8
9
4
Mildura
Euston
River
Murray
Loxton
ADELAIDE
0
100
km
Depth
Depth
Depth
Water level variability
changes along the channel
Time
Time
Time
UP
UP
MP
LP
MP
LP
Discrete
assemblages
between channel
sections
Overall diversity
very low compared
to other large rivers
Differences in
assemblages reflect
different
microhabitats
Axis 2
Assemblage differences along the
channel reflect different levels of
variability
Lower Pool
Middle Pool
Upper Pool
Axis 1
MDS Plot, Bray-Curtis Dissimilarity, log10(x+1) abundance data
Reach scale responses to
Boom & Bust
• We know that:
– Temporal changes in flow (boom and bust)
have strong influences on dryland river
ecosystems
Photo by Stephen Balcombe
Photo by Peter Unmack
Data from CRCFE Dryland River Refugia Project
Flow variability drives water
quality - Cooper Creek
April 2001
September 2001
October 2002
May 2003
January 2004
March 2004
June 2004
October 2004
December 2004
4
Windorah Water Quality
PCII – 27%
Total N
Total P
2
Dry Samples
Flood Samples
0
Flow Samples
Discharge (ML/day *000)
-2
1000
PCI – 47%
Conductivity, Total Hardness, TDS
800
-2
600
400
2
PCA Plot, Water Quality Data from Windorah reach
200
Dec-99
0
Jan-01
Feb-02
Mar-03
Apr-04
4
Temporal Variability
Cooper Creek - Invertebrates
Tanbar
April 2001
Windorah
April 2001
w
w
Springfield
April 2001
w
w
Noonbah
April 2001
1400
1200
May 2003
w
Oct 2002
Discharge (ML/day) x 103
w
1000
800
600
400
April September
2001
2001
Octoberr
2002
May
2003
200
0
Stress = 0.16
w
Jan-00 Jul-00 Jan-01 Jul-01 Jan-02 Jul-02 Jan-03
Sept 2001
MDS Plot, Bray-Curtis Dissimilarity, log10(x+1) abundance data
Data from CRCFE Dryland River Refugia Project: Marshall, Sheldon, Thoms & Choy 2006
Temporal shifts in community
composition driven by
hydrological connection
?
Connection
Disconnection
Prolonged Disconnection
30
Larger
catchment
scale
responses
SOI
20
SOI
10
0
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
-10
-20
7000000
-30
Darling River
-40
Condamine
Macintyre
Mungindi
Darling Bourke
Darling Wilcannia
6000000
5000000
Sequential
flooding
4000000
3000000
2000000
1000000
0
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
A large scale sequence of
wetlands
Upper Middle Lower
Wetlands
The BIG ‘booms’
Removing water from the top
end…..
Upper Middle Lower
Wetlands
The BIG ‘booms’
Protecting variability at all scales
• We recognise variability is important in
driving large river ecology across a range
of scales
• To protect large rivers we need to protect
this variability
• Intrinsic resilience to variability – adapted
to cope with climate change, but
• Climate change + human pressure may be
too much……
Photo by Jon Marshall
Summary
Photo by Peter Unmack