Water Resources: Hydroclimatic Forensics Through Reanalysis
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Transcript of Water Resources: Hydroclimatic Forensics Through Reanalysis
Water Resources: Hydroclimatic Forensics Through Reanalysis
Bryson C. BatesLeader, Pathways to Adaptation Theme 24th June 2008
Climate Adaptation
ACRE Workshop 2008
● Colleagues● Steve Charles (CSIRO)
● Richard Chandler (University College London)
● James Hughes (University of Washington)
● Eddy Campbell (CSIRO)
● Funding● Australian Climate Change Science Program
● Indian Ocean Climate Initiative
● South Eastern Australian Climate Initiative
Acknowledgments
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● The problem ● characteristics of multi-year drought
● short hydrologic record lengths < 100 years
● reliability of water supply systems – over-rated &/or over-allocation?
● ACRE applications● deriving the ‘recent’ envelope of natural climate
variability
● documenting atmospheric circulation changes that caused droughts prior to middle of 20th Century?
● putting anthropogenic climate change in context
● stochastic assessments of system reliability
Why ACRE & Water Resources?
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IWSS Dam Inflow Series
Cost of system expansion: 2 billion AUD spent over last decade
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Rules; What Rules?
● Traditional water planning based on assumption of stationarity (constant mean, variance & autocorrelation)
● Observed changes in means, variance & extremes – old rules are breaking down
● Trends or shifts: if, when & why?
● Regimes (periods exhibiting stationarity)?
● Use all of the record; or which part?
ACRE Workshop 2008
● Dam inflow series● trend?
● change points & regimes?
● Stochastic downscaling● changes in atmospheric circulation variables?
● changes in frequencies of synoptic types?
● At-site precipitation● changes in occurrence?
● changes in amounts?
Experimental Design
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IWSS Inflows
Year
Inflo
w (
Gl)
1920 1960 2000
10
10
01
00
0 a
h
Pro
ba
bili
ty v
alu
e
2 6 10
0.0
00
.01
0.0
20
.03 b
h
p-v
alu
e
6 8 10 12
0.1
0.2
0.3
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Site Map
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Nonhomogeneous Hidden Markov Model
● Observed process: sequence of regional precipitation occurrence patterns Rt: t = 1, …, T
● Hidden discrete-valued process: sequence of weather types (or states) St
● State to state transitions driven by atmospheric information (predictors) Xt
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● Season: May to October
● Period of interest: 1958 – 2007
● Fitting: sequential estimation – BIC
● Number of weather states: 6
● Atmospheric predictors:● mean MSLP
● N-S MSLP gradient
● DTd850 = T850 – Td850
● 1st canonical variate
● Testing: split sample & physical scrutiny
NHMM Details
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Interannual & Split Sample Validation
Fitting Validation
Fitting Validation
Dryspell
Wetspell
Validation Fitting
Observed daily rainfall
Sim
ula
ted
da
ily
ra
infa
ll
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Atmospheric Predictors
(1983:2007)
versus
(1958:1982)
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Synoptic Typing & Frequency
199819781958
00.
20.
4
1958 19981978
00.
20.
4
Pro
bab
ility
Pro
bab
ility
Type 3: Wet West & Central Type 5: Dry Everywhere
Southwest Australia
ACRE Workshop 2008
● Overall reduction in precipitation occurrence – changes most notable in west of the region
● Most sites exhibit reductions in mean wet-day precipitation amounts
● Some indication of increase in precipitation intensity in SW corner of the region
At-Site Precipitation
1958 to 2007
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SE Australia
Total River Murray System Inflows (including Darling River)Modelled Annual Inflows - current conditions
0
5 000
10 000
15 000
20 000
25 000
30 000
1892 1902 1912 1922 1932 1942 1952 1962 1972 1982 1992 2002
Ann
ual I
nflo
w (
GL)
Long-term Average Inflow (11 200 GL/yr)
Average Inflows during Drought Periods
5 400 GL/yr4 150 GL/yr
6 300 GL/yr
Drivers of Federation, WWII & current droughts?
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Water planners confronting historically-unprecedented drought non-stationarity in dam inflow series apparent increase in climatic risk due to
anthropogenic climate change
ACRE can assist water planners by providing additional information about envelope of
natural climate variability – system reliability providing explanations for the causes of major
droughts prior to middle of 20th century putting anthropogenic climate change in context –
if & when will the envelope of natural climate variability be breached (approximately)?
Concluding Remarks
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NHMM vs. Null Model
Occurrence Amounts
Period SSM SSE Er SSM SSE Er
1958-77 10306 15567 0.398 919753 2198732 0.295
1978-92 7712 10084 0.433 687208 1640354 0.295
1993-98 3197 4187 0.433 280207 727790 0.278
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SW Australia
0
20
40
60
80
100
120
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecMonth
mm
1925-1975
1976-2003
Indian Ocean Climate Initiative
Informed Adaptation
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"Dry Everywhere" "Wet Everywhere"
Weather Type Probabilities: SE MDB
SEACI