This document summarizes a seminar on integrated modelling of urban water systems. The seminar discusses the history of integrated modelling, definitions, examples of different types of integrated models, considerations for developing integrated models, and challenges around calibration and uncertainty. Integrated modelling aims to account for interactions between different components of urban water systems, like sewers, wastewater treatment plants, and receiving waters. While integrated models can provide benefits, their complexity poses technical and logistical challenges for calibration and uncertainty analysis.
1. Seminar Series, 2012
www.urbanbeatsmodel.com
Integrated Modelling Revisited
The Urban Drainage System and Beyond
Peter M. Bach
Centre for Water Sensitive Cities
Department of Civil Engineering
Monash University, VIC 3800, Australia
18th May, 2012
Co-authors: Wolfgang Rauch, Peter S. Mikkelsen,
David T. McCarthy, Ana Deletic
2. Seminar Series, 2012
www.urbanbeatsmodel.com
01 – Integrated Modelling Revisited : The Urban Drainage System & Beyond
(May 18th, 2012 – Today)
02 – UrbanBEATS : Overview of a Virtual Urban Water System Tool
(June 15th, 2012)
03 – Digital Cities : Development of Spatial Algorithms for Urban Water Models
(TBA)
04 – Optioneering WSUD : Modelling decentralised water management planning
(TBA)
05 – TBA
3. “...Model /ˈ ɒd(ə)l/
m
(2) a thing used as an example to follow or imitate
(3) a simplified description, especially a mathematical one, of a system or
process, to assist calculations and predictions
(4) a person employed to display clothes by wearing them
...”
(Source: Oxford Dictionary)
Seminar Series, 2012 | #01 Integrated Modelling Revisited | Peter M. Bach | www.urbanbeatsmodel.com | 1/32
4. ...from the literature...
“... An engineering model is not the reality, but a limited,
simplified and partial representation of reality, i.e. a tool
built for practical applications....”
– J. L. BETRAND-KRAJEWSKI, 2007 WATER SCIENCE & TECHNOLOGY
“... A „number-crunching‟ or „sledge hammer‟ approach
to theory-building....”
– M. BATTY, 2010 , CAMBRIDGE UNI PRESS
“...A model is any representation of a real system that can
be used to simulate certain features of the more complex
real system...”
– H. JONES, 1992 CAMBRIDGE UNI PRESS
Seminar Series, 2012 | #01 Integrated Modelling Revisited | Peter M. Bach | www.urbanbeatsmodel.com | 2/32
5. Modelling – A “Not-So-Complex” Illustration
Users
!!
MODEL
SETUP & INPUTS OUTPUTS
Problem Definition a “black box” Predictions
Aims & Objectives Analysis
Case Study & Scenarios Interpretation
Parameters& Data
Calibration/Optimization/Training
REFINEMENT, ITERATION, RE-EVALUATION
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7. “...Integration /ɪntɪˈgreʃ(ə)n/
ɪ
the linking and coordination of various parts or aspects
...”
(Source: Oxford Dictionary, with a little difficulty...)
Seminar Series, 2012 | #01 Integrated Modelling Revisited | Peter M. Bach | www.urbanbeatsmodel.com | 5/32
8. Examples of „Integration‟
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9. Today‟s Seminar
Once upon a time...
Integrated Modelling and the Ambiguities therein
Organising integrated models of urban water systems...
Developing Integrated Models, what complexity has been
added?
Current Adoption in Practice, where do we stand?
Future Outlook, is there hope?
Seminar Series, 2012 | #01 Integrated Modelling Revisited | Peter M. Bach | www.urbanbeatsmodel.com | 7/32
10. Our journey begins around the late 1970s
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11. Our journey begins around the late 1970s
Receiving Water Body
Sewer Network
Wastewater Treatment Plant
Source: Gujer et al., 1982
Seminar Series, 2012 | #01 Integrated Modelling Revisited | Peter M. Bach | www.urbanbeatsmodel.com | 9/32
12. adapted from Bach et al. (submitted)
and since then...
I.M. Guidelines
for Urban Drainage
Water Quality Systems
Increased Focus
Awareness
?
Real-time Control
Fieldwork New Types of
First concepts Integration Inter-disciplinary
Model
Integration
Advancements New Modelling
Technologies Legislation Changes
Softwares Emerge
1970s 1980s 1990s 2000s Time
First Emerging 1993 2000 2002 ~ 2006 2012
mentions interest in 1st INTERURBA EU Water 2nd IUWM Present
of integration understanding Conference Framework INTERURBA paradigm Day
component Directive Conference emerges
interactions
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13. So what is “Integrated Modelling”?
“...modelling of interactions between two or more urban
water system components...”
– Rauch et al., 2002, Olsson and Jeppsson, 2006
“...ability to focus on understanding the behaviour of parts of
the system with respect to the broader picture...”
– Beck, 1976
“... recognises both the positive and negative feedbacks
between components and exploits these for significantly more
efficient solutions...”
– Marsalek et al., 1993, Mitchell et al., 2007
Seminar Series, 2012 | #01 Integrated Modelling Revisited | Peter M. Bach | www.urbanbeatsmodel.com | 11/32
14. • Positive Feedback
• Negative Feedback
• Short & Long-term Effects
• More than the Sum of Parts
Subsystem
Subsystem
Subsystem
Subsystem
Subsystem
Subsystem
Subsystem
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15. Users
!!
“...the prerequisite to an SETUP & INPUTS
MODEL
OUTPUTS
a “black box”
integrated approach is the Problem Definition
Aims & Objectives
Case Study & Scenarios
Predictions
Analysis
Interpretation
identification of the ‘‘axes and Parameters& Data
Calibration/Optimization/Training
planes’’ in which integration
REFINEMENT, ITERATION, RE-EVALUATION
needs to take place...”
– Rauch et al., 2005
Sub-Systems
Disciplines
Processes
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16. Yet...
The body of literature is massive, repetitive and
ambiguous based on two kinds of templates
We are faced with “linguistic uncertainty”
Integrated is “...ill-chosen and ambiguous term as it implies a
sense of completeness...” – Rauch et al., 2005
We lack a means to classify models based on:
different scopes of the urban water system
considerations for model development
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17. Organising Integrated Modelling in UWS
Integrated urban water system models IUWSMs
Integrated urban water infrastructure models IUWIMs
Integrated urban drainage models Integrated water supply models
Integrated component-based models
IUDMs IWSMs
Catchment Drainage,
ICBMs
Runoff and Pollution Water demand patterns
Water WWTP Natural
Sewer Transport Supply Treatment Reservoir Storage-behaviour
Combined Sewer Overflow System System Decentralised water sources
Receiving Water Body Natural Water distribution network
Sewer
Quality Water Body Water treatment plant
Processes
Flood Protection
Decentralised & Total Urban Water Cycle Water Resources
Water recycling
Centralised systems (Supply & Drainage) Allocation
Soil & Air Social
Local/Regional Economic Ecological
Quality Behaviour Energy Models
Climate Model Models Models
Models Models
Environmental Decision Support Systems EDSS
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18. Some Examples
ICBMs:
• Benchmark Simulation Model No. 2 (Grau et al., 2007)
(whole of wastewater treatment plant model)
IUDMs & IWSMs:
• SIMBA (IFAK, 2007)
(sewer system and wastewater treatment plant)
• SAMBA, RUMBA, FOXTROT (Harremoes & Rauch, 1996)
(sewer system, wastewater treatment plant, receiving
waters)
• EPANET (Rossman, 2000)
(simulation of water distribution networks
& storages)
Seminar Series, 2012 | #01 Integrated Modelling Revisited | Peter M. Bach | www.urbanbeatsmodel.com | 16/32
19. Some Examples
IUWIMs:
• MUSIC (eWater)
• UrbanDeveloper (eWater)
• Aquacycle (Mitchell et al., 2001)
• MIKE URBAN (DHI)
IUWSMs: current only sparse
• Work by Fagan et al., 2010
• VIBe (Sitzenfrei et al., 2010)
• OpenMI (OpenMI Association, 2010)
• DAnCE4Water & UrbanBEATS
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20. Developing Integrated Models
Define Aims & Objectives and Source: Bach et al. (submitted)
Make initial selection of Model
Aims & Objectives Features (from Table 3)
Identify/Quantify/Acknowledge/Track reducible and irreducible UNCERTAINTY
Select relevant state variables
List relevant Interactions
& delineate system boundary
between system components
(level of integration e.g. IUDM)
Find/Make the
models
Select existing relevant models
for each component Determine Transfer Functions
(develop if non-existent) (conversion processes, feedbacks)
String’em together
Select method of integration &
Iterative
construct integrated model
Refine if necessary
Determine calibration method Define “verification criteria” of
Calibrate & Run & data requirements the integrated model
Analyse Model Outputs
Calibrate & Run the Model (according to performance and
verification criteria)
Interpret Output
Cross-check Results with
Aims & Objectives
Seminar Series, 2012 | #01 Integrated Modelling Revisited | Peter M. Bach | www.urbanbeatsmodel.com | 18/32
21. Key Considerations
Model Structure Empirical vs. Conceptual vs. Mechanistic
Primary vs. Surrogates
Deterministic vs. Stochastic
Simulation Config. Sequential vs. Parallel
Online vs. Offline
Spatial Detailing Branched vs. Looped
Distributed vs. Lumped
Temporal Detailing Continuous vs. Discontinuous Simulation
Uniform vs. Variable Time Step
Process Nature Water Quantity (Hydrologic & Hydraulic)
Water Quality (Physical, Biological, Chemical)
Computation Single Core vs. Multi-Core Processing
Single run vs. Optimisation vs. Benchmarking
Software Supermodel vs. Interface vs. Hybrid
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22. Key Considerations – Sequential vs. Parallel
Sequential: “One-node-at-a-time”
for entire time period
Parallel: All at once
“One-time-step-at-a-time”
1 4
Catchment 1 Treatment 1
2 5 6
Catchment 2 Treatment 2 Storage 1
3 t1 7
t2
Catchment 3 River
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23. Key Considerations – Single vs. Multi-core Processing
Source: Burger et al., 2010 WST
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24. Key Considerations – Supermodel, Interface & Hybrid
Sewer Sewer
Sewer
+ +
Wastewater Wastewater
Treatment Wastewater Treatment
Plant Treatment Plant Plant
+
Receiving
Receiving Water Receiving
Water Body
Body Water Body
Supermodel Interface Hybrid
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25. The Pragmatism vs. Parsimony Debate
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26. Calibrating and Validating these Beasts
Three methods identified:
#1 :: calibrate the whole integrated model at once
#2 :: start upstream, then gradually move
downstream, quantity before quality
#3 :: calibrate individual models first, then integrate
them
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27. Calibrating and Validating these Beasts
Integrated models as “unwieldy” and “highly complex” – a
technical and logistical challenge!
Error propagation, equifinality and sometimes unavoidable
auto-correlation more pronounced with increasing
complexity
Calibration/Validation feasibility decreasing with larger
integrated models – still useful?
Overcome data limitations with semi-hypothetical case
studies and exploration
Overcome overparametrisation by using simpler surrogate
models
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28. Uncertainty
Types:
• Statistical (outcomes known and quantifiable)
• Scenario (outcomes known but not quantifiable)
• Qualitative (not all outcomes known nor quantifiable)
• Recognised Ignorance
Statistical received great attention (many methods to
quantify)
Scenario partly explored
Should integrated modelling field rely on classical
uncertainty estimation methods?
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29. Driving the Adoption of Integrated Models
(1) Global Change & the IUWM Paradigm
(2) Changing Legislation
(3) Diversity of Integrated Model Use
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30. Driving the Adoption of Integrated Models
Diversity e.g. Semi-Hypothetical/Virtual Case Studies
(Sitzenfrei et al. 2010, Urich et al. 2010)
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31. Barriers that we still face Data Requirements
User-friendliness
Legislation
Uncertainty
Communication
Model Complexity
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32. So what does the future hold?
The literature‟s Key goals
More „now-casting‟
More transparent process in using
integrated models
More interdisciplinary work
The direction of future research(?) - “Virtual Playgrounds”
encompassing the technical and non-technical
Fragmentation in practice needs to be overcome
Legislation needs to evolve more than it has
Participatory approach
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33. Concluding Remarks
Limited Success Story for Integrated Models of Urban
Water Systems
Good grasp of the field in theory, need to move towards
unravelling more complexity
Slow uptake in practice, but there is progress
This collation of knowledge is also the starting point for
new innovations in modelling
Contact me for more information and the in-depth review
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