Climate Variability and Freshwater Systems
Lessons for protecting freshwater systems from climate change impacts
Fran SheldonAustralian Rivers Institute
Griffith School of Environment Griffith University
We know Australia’s rivers are variable…..
from Puckridge et al. (1998). Mar. Freshw. Res. 49, 55-72
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Cooper
Diamantina
Burdekin
DarlingVaalFitzroyLimpopo
Danube
MississippiMekong Colorado
Rhine
Summary medians (23 hydrological measures)
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 changeo determining environmental flows and o assessing ecosystem health
Scales of Variability in Dryland Rivers
Reach scale responses to ‘boom and bust’ cycles
Within channel
water level fluctuations
Catchment scale responses to
flood – drought cycles
Temporal Scale (years)
Sp
atia
l Sca
le (
m)
Within channel variability:Lower River Murray
BlanchtownEuston
MorganOverlandCorner
Renmark
Loxton
Mildura
Menindee
MenindeeLakes
1 2 3 45 6 7 8 9 10
ADELAIDE
SouthAustralia
New South Wales
RiverMurray
DarlingRiver
0 100km
Water level variability changes along the channel
Time
Dep
th
Time
Dep
th
TimeD
epth
UP LPMP
UP LPMP
Assemblage differences along the channel reflect different levels of variability
Discrete assemblages between channel sections
Overall diversity very low compared to other large rivers
Differences in assemblages reflect different microhabitats
MDS Plot, Bray-Curtis Dissimilarity, log10(x+1) abundance data
Axis 1
Ax
is 2
Lower Pool
Middle Pool
Upper Pool
Axis 1
Ax
is 2
Lower Pool
Middle Pool
Upper Pool
Reach scale responses to Boom & Bust
Data from CRCFE Dryland River Refugia Project
Photo by Peter Unmack
Photo by Stephen Balcombe
• We know that:– Temporal changes in flow (boom and bust)
have strong influences on dryland river ecosystems
April 2001September 2001October 2002May 2003January 2004 March 2004 June 2004 October 2004 December 2004
Flow variability drives water quality - Cooper Creek
Windorah Water Quality
PCI – 47%Conductivity, Total Hardness, TDS
-2 0 2 4
PCII – 27%Total NTotal P
-2
0
2
4
Dry Samples
Flow Samples
Flood Samples
PCA Plot, Water Quality Data from Windorah reach
200
400
600
800
1000
Dec-99 Jan-01 Feb-02 Mar-03 Apr-04
Dis
ch
arg
e (
ML
/day
*0
00)
Temporal Variability Cooper Creek - Invertebrates
TanbarApril 2001
SpringfieldApril 2001
NoonbahApril 2001
WindorahApril 2001
Sept 2001
Oct 2002
May 2003
Stress = 0.16
Data from CRCFE Dryland River Refugia Project: Marshall, Sheldon, Thoms & Choy 2006
0
200
400
600
800
1000
1200
1400
Jan-00 Jul-00 Jan-01 Jul-01 Jan-02 Jul-02 Jan-03D
isc
ha
rge
(M
L/d
ay)
x 1
03
April2001
September2001
Octoberr2002
May2003
MDS Plot, Bray-Curtis Dissimilarity, log10(x+1) abundance data
Temporal shifts in community composition driven by hydrological connection
Connection Disconnection
Prolonged Disconnection
?
Sequential flooding
0
1000000
2000000
3000000
4000000
5000000
6000000
7000000
1950 1951 1952 1953 1954 1955 1956 1957 1958 1959
Condamine
Macintyre
Mungindi
Darling Bourke
Darling Wilcannia
-40
-30
-20
-10
0
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20
30
1950 1951 1952 1953 1954 1955 1956 1957 1958 1959
SO
I
SOI
Darling River
Larger catchment
scale responses
A large scale sequence of wetlands
Upper Middle LowerWetlands
The BIG ‘booms’
Removing water from the top end…..
The BIG ‘booms’
Upper Middle LowerWetlands
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……
Summary
Photo by Peter Unmack
Photo by Jon Marshall
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