assessing urban water strategies for total water … urban water strategies for total water cycle...
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Assessing Urban Water Strategies for Total Water Cycle Management
Magnus MogliaSenior Research Scientist, CSIRO Land and Water
Collaborators: Shiroma Maheepala, Daniel Kinsmann
5 December 2012
Urban Water Security Research Alliance
Total Water Cycle Management Plan
• The objective is to identify a strategy that has the potential to move towards a more sustainable state than the current state
•
Assessing against multiple criteria•
Methods to quantify criteria for alternative water strategies (or scenarios)
‐100%‐75%‐50%‐25%0%25%50%75%100%
Scenario 1 Scenario 2 Scenario 3
OzoneDeplet'n
Fossil FuelDeplet'n
MineralsDeplet'n
MarineEcotox
FreshwaterEcotox
TerrestrialEcotox
HumanToxicity
potablesavings
TNreduct'n
GHG
Broad environmental issues – highlights potential future concerns
TWCM: decision problem
• Several cars to choose from•
Indicators help us make an informed decision
•
Litres/100kms•
Safety grading
•
On road performance•
Comfort
•
Price •
Etc
• Uncertainty is an important factor•
Lemons
•
Brand consistency• Value and prioritisation is subjective• Planners make decisions on behalf of other people, with other
peoples money, and have reasons to be risk‐averse
Decision Supporting Framework
Subjective Logic Subjective Logic
Informed actionInformed action
eWater CRC Framework reported in Blackmore et al., 2009.
Handling uncertainty?
A.
All values are absolute; in reality they are uncertain (according to some probability distribution?)
B.
Estimates, including of uncertainty, are difficult to make on the basis of incomplete information.
C.
(Personal or Model based) Judgments are an integral part of assessments
1.
How do we incorporate uncertainty
in estimates into assessments?
2.
How do we incorporate trust
in judgments into assessments?
Subjective Logic: basis
b = beliefd = disbeliefi = ignorance
DisbeliefBeliefBelief
IgnoranceIgnorance
OUTCOME SPACE Example:
Will Australia beat South Africa in the cricket?
Some months ago:Belief = 0.1Disbelief = 0.1Ignorance = 0.8
Now:Belief = 0.1Disbelief = 0.8Ignorance = 0.1
P(X) = 0.5
P(X) = 0.85
Case Study: Subjective Logic applied to TWCM
Assessment approach Variable
Source simulations TNTPTSSFlows
Lifecycle cost Project cost
Caboolture River catchment with CIGA – sub‐catchment 63Caboolture River catchment with CIGA – sub‐catchment 63
A)
Low intensity B)
Medium intensity
C)
High intensity
A)
Low intensity B)
Medium intensity
C)
High intensity
An illustration of how the process / method is applied.
Scenarios
Scenario Management solutions1 Future development meet 80/60/45 % load reduction for TSS/TP/TN
1 Future development meet QDC alternative water supply
1&2 Increased implementation/enforcement of E&SC management practice
1&2 Waterway and riparian revegetation of 3rd and 4th order streams
1&2 Education and/or capacity building and investment in incentive schemes
1&2 Prevention of illegal stormwater inflow connection to sewer
1&2&3 Future greenfield development WSUD measures to achieve no‐worsening
1&2&3 Recycled water supplied to urban users
1&2&3 Stormwater harvesting
Basic model structure
Climate
Scenario
Source EMS data generation
Source EMS data generation
• Model above applied for each land use separately (urban, green space etc)
• Once for each mitigation scenario (1, 2, 3)• 30 year simulation period run outputting daily data• Constituent monthly means and deviations for El Niño, La Niña and
normal Southern Oscillation periods calculated in post processing
Time consuming!Time consuming!
Source simulations results
InputsFlow TN TP TSS
MeanStandard
deviation Mean
Standard
deviation Mean
Standard
deviation Mean
Standard
deviation
Scenario 1 La Nina 15.89 1.07 9.21 1.14 7.13 1.24 13.09 1.38Scenario 1 El Nino 12.96 1.10 6.29 1.15 4.21 1.25 10.16 1.38Scenario 1 Normal 15.64 1.11 8.97 1.17 6.89 1.28 12.84 1.41Scenario 2 La Nina 13.41 1.07 6.73 1.14 4.65 1.24 10.34 1.34Scenario 2 El Nino 12.96 1.10 6.29 1.15 4.21 1.25 9.90 1.36Scenario 2 Normal 12.96 1.10 6.29 1.15 4.21 1.25 9.90 1.36Scenario 3 La Nina 13.41 1.07 6.68 1.13 4.56 1.23 10.18 1.33Scenario 3 El Nino 12.96 1.10 6.24 1.14 4.12 1.24 9.74 1.36Scenario 3 Normal 13.15 1.11 6.44 1.16 4.32 1.27 9.95 1.38
Convert to
appropriate
distribution &
discretise
Inputs Flow50% worse Same 25% better 50% better 75% better 90% better
Scenario 1 La Nina 44.0% 25.0% 12.0% 13.0% 4.0% 2.0%Scenario 1 El Nino 0.2% 1.2% 2.0% 8.4% 13.8% 74.3%Scenario 1 Normal 35.7% 24.6% 13.2% 16.0% 6.7% 3.8%Scenario 2 La Nina 1.0% 2.8% 4.1% 13.9% 18.7% 59.8%Scenario 2 El Nino 0.2% 1.2% 2.0% 8.4% 13.8% 74.3%Scenario 2 Normal 0.2% 1.2% 2.0% 8.4% 13.8% 74.3%Scenario 3 La Nina 0.7% 2.8% 4.1% 13.9% 18.7% 59.8%Scenario 3 El Nino 0.2% 1.2% 2.0% 8.4% 13.8% 74.3%Scenario 3 Normal 0.5% 1.9% 2.9% 10.8% 15.9% 68.0%
NPV-min NPV-max
Scenario 1$
50,080 $ 10,516,727
Scenario 2$
65,105 $ 11,268,924
Scenario 3$
2,238,561 $ 15,254,263 Mean Std
Scenario 1$
5,283,404 $ 2,670,063
Scenario 2$
5,667,014 $ 2,858,117
Scenario 3$
8,746,412 $ 3,320,332
Cost estimation
Scenario management solutionsNPV total cost (2011 $) min NPV cost max NPV cost
1 Future development meet 80/60/45 % load reduction for TSS/TP/TN $ 7,700,448 $ 5,008 $ 7,712,267
1 Future development meet QDC alternative water supply $ 1,419,358 $ 45,072 $ 2,804,461
2 Increased implementation/enforcement of E&SC management practice $ 636 $ 1 $ 1,002
2 Waterway and riparian revegetation of 3rd and 4th order streams $ 180,287 $ 15,024 $ 751,195
2 Education and/or capacity building and investment in incentive schemes not costed not costed not costed
2 Prevention of illegal stormwater inflow connection to sewer not costed not costed not costed
3 Future greenfield development WSUD measures to achieve no-worsening $ 7,700,448 $ 10,016 $ 7,712,267
3 Recycled water supplied to urban users $ 1,852,947 $ 976,553 $ 4,086,500 3 Stormwater harvesting $ 3,450,488 $ 1,251,991 $ 3,455,496
Shiroma MShiroma M
Added values and climate
Outcome variable Cost per tonne ($/t)TN $273,000/tTP $220,000 /tTSS $213 /tFlow $0.2
Pollutant costs for “no worsening”
LTA of ENSO conditions
Murray HallMurray Hall
SOI Time SeriesSOI Time Series
Strategy satisfaction
Cost range
Added value*
No added value Some added value Significant value
0 to $1,000,000 $1,000,000 to $3,000,000$3,000,000 to
$15,000,000
<$1,000,000 1 0.3 0.1
$2,500,000 3.5 1.2 0.2
$5,000,000 3.5 1.2 0.2
$7,500,000 12.5 4.2 0.7
$10,000,000 17.5 5.8 1.0
>$10,000,000 30 10.0 1.7
Extremely unlikely (1%)Quite unlikely (10%Neither unlikely or likely (50%)Quite likely (75%)Highly likely (90%)Extremely likely (99%)
Years before value >= cost
Note: Should be done by
stakeholders
Note: Should be done by
stakeholders
Reliability of information –
illustration only
• Inherently subjective• We use “cues” to help assess
reliability – i.e. what categorises rigorous analysis? Existence of sensitivity analysis, high level of scrutiny of data sources, critical peer review, etc.
Input data Assigned reliabilitySource EMS Neither reliable or
unreliable (50%)Lifecycle
CostingSomewhat reliable
(75%)
Lack of justification for parameter values, consistent
use of linear functions, errors in running models, black‐box
Lack of justification for parameter values, consistent
use of linear functions, errors in running models, black‐box
Something we have some experience with. Assumptions
clear. Parameters not plucked completely out of thin air.
Something we have some experience with. Assumptions
clear. Parameters not plucked completely out of thin air.
Software: Intelfuze
• Intelfuze: software was in Beta‐testing (Subjective Logic is a novel and patented analysis approach within a software) – for Bayesian Networks
http://www.veriluma.com/products/metafuze/
Results
Scenario Prob(strategy satisfaction)
“Trust” of assessments
1 56% 33%*2 75% 49%3 61% 22%
During El Nino conditions, Scenario 1 is the preferred option! => you can explore sensitivity to climate and other factors
Model is sensitive to formulation, i.e. cost-benefit acceptance matrix and discretisation process.
*This is indicated in the software with a warning: derived observation has the potential for being derived from inadequate information.
Concluding words• Assessment result aligns with MCA recommendations, but
Subjective Logic method provides additional information on uncertainty and reliability
•
Underlying reliability of assessments – needs consideration of the reliability and justification of input parameters
•
Can explore sensitivity to underlying factors such as climate• Model is sensitive to •
Cost‐benefit acceptance matrix => requires stakeholder input
•
The discretisation
process => this is a concern and requires careful thinking• Model can relatively easily expanded to explore sensitivity to
other factors• Source EMS model is not set up to easily undertake sensitivity
assessments for catchment modelling•
First, clarify reliability and justification of input parameters
Urban Water Security Research Alliance
THANK YOU!
www.urbanwateralliance.org.au