1. A Decision Support System for
Integrated Semi-centralised Urban
Wastewater Treatment Systems
MIROSLAWA ALUNOWSKA FIGUEROA
DPhil candidate, Engineering Science, University of Oxford
LISBON CONGRESS CENTRE, 23 SEPTEMBER 2014
CONTENTS:
• Introduction
• Method
• Results & conclusions

2. 2
INTRODUCTION
ADecisionSupportSystemforintegratedSemi-centralisedUrbanWastewaterTreatmentSystems
Grimm N. B., S. H. Faeth, N. E. Golubiewski, C. L. Redman, J. Wu, X. Bai, J. M. Briggs. (2008). Global Change and the Ecology of Cities. Science, 319 (5864), pp. 756-760
By 2050: 2/3 of 9 billion people will be living in cities.

3. 3
INTRODUCTION
Objective To develop a novel modelling framework
for the design of integrated semi-centralised urban
wastewater treatment systems.
ADecisionSupportSystemforintegratedSemi-centralisedUrbanWastewaterTreatmentSystems
The Problem • Stress on resources and services infrastructure.
• Population growth.
• High number of stakeholders.
• Complex engineering problem.
Decentralised CentralisedSemi-centralised

4. 4
METHODS
• Probabilistic specification-based Design Model1:
application of decision-makers’ preferences.
• Sensitivity and Scenario Analysis (intuitive logics method).
• Integration of alternative technical and scientific methods.
• Flexibility to allow application to any city:
o Uses region-specific geographical and socio-
technological factors.
o Object-oriented design.
ADecisionSupportSystemforintegratedSemi-centralisedUrbanWastewaterTreatmentSystems
[1] Wallace D. R., M. J. Jakiela, W. C. Flowers. (1996). Design search under probabilistic specifications using genetic algorithms. Computer-Aided
Design, 28(5), pp. 405-421.

5. 5
DECISION SUPPORT SYSTEM
ADecisionSupportSystemforintegratedSemi-centralisedUrbanWastewaterTreatmentSystems
• Decision model
• Semi-centralised wastewater treatment system designer
• Sewerage system designer
• Path Calculator
• Wastewater Allocator
• Wastewater Treatment Technologies
• Pipeline Technology
Analytical Kernel
Generates recommended design.
Uses set of decision-makers’ preferences.
Decision Making
Uses spatial socio-economic factors.
Geographical Information Systems (GIS)
Uses regional technological preferences.
Graphical User Interface
Enables user interaction.
Engineering Design Libraries

6. 6
CASE STUDY

7. 7
RESULTS & CONCLUSIONS
ADecisionSupportSystemforintegratedSemi-centralisedUrbanWastewaterTreatmentSystems

8. 8
RESULTS & CONCLUSIONS
ADecisionSupportSystemforintegratedSemi-centralisedUrbanWastewaterTreatmentSystems
Parameter
Impact on
Number of
WWTPs opened
Sewerage
System Layout
Cost
Height ■■ ■■ ■■■
Number of WWTP site
options
■■ ■■ ■■■
Wastewater quantity ■ ■■ ■■■
Distribution
population density
■ ■
WWT Tech cost ■ ■
Running through different scenarios:
The assessment of an urban wastewater treatment system is
extremely contextual.

9. 9
RESULTS & CONCLUSIONS
Strengths and capabilities
• Capable of being used by
non-technical decision-
makers for analysis of
alternatives.
• Capable of being applied to
any city.
• Built on object oriented
principles. Flexible design:
alternative technologies
tested without recoding.
Limitations
• The user may not appreciate
the full complexity within the
“black-box.”
• Alternative optimisation
algorithm could have been
used.
• Given its complexity, it needs
support if it future updates
are required.
ADecisionSupportSystemforintegratedSemi-centralisedUrbanWastewaterTreatmentSystems

10. 10
Thanks 
miroslawa.alunowska-figueroa@balliol.ox.ac.uk
This research project was possible thanks to the financial support of:
ADecisionSupportSystemforintegratedSemi-centralisedUrbanWastewaterTreatmentSystems