DECISION SUPPORT FOR SUSTAINABLE WATER...

DECISION SUPPORT FOR SUSTAINABLE WATER RESOURCES MANAGEMENT IN SINGAPORE

XI XI

DEPARTMENT OF INDUSTRIAL AND SYSTEMS

ENGINEERING

NATIONAL UNIVERSITY OF SINGAPORE

2012

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DECISION SUPPORT FOR SUSTAINABLE WATER RESOURCES MANAGEMENT IN SINGAPORE

Submitted by

Xi Xi

Department of Industrial and Systems Engineering

In partial fulfillment of the requirements for the Degree of Bachelor of Engineering

National University of Singapore

2012

2

Abstract

In order to alleviate the risks of flooding and diversify Singapore’s sources of water

supply, the country’s former Chief Defense Scientist, Professor Lui Pao Chuen,

proposed an underground water storage system in 2012. This infrastructure could have

significant long-term impacts on the integrated water resources system in Singapore. In

addition, among the many alternatives to augment water supply, decision makers need

to know which ones are the more sustainable plans to pursue.

This research proposes an integrated decision support approach that incorporates

System Dynamics (SD) and a multi-criteria decision support tool called Analytic

Hierarchy Process (AHP). It also demonstrates the usefulness of this innovative

approach in helping to achieve sustainable water resources management in Singapore.

First, a SD model takes in real-world data and simulates the consequences of different

alternative plans under various scenarios. Second, AHP is applied to compare different

alternatives based on their performance as revealed by the SD simulation and the

judgment of decision makers.

Through the SD modeling we found that the proposed underground water storage

system is not going to have a profound impact on Singapore’s adequacy and self-

sufficiency in water, mainly because of its limited capacity and long construction time.

Decision analysis through AHP reveals that if the population increases rapidly or

mildly, then the priorities of development plans are: 1) seawater desalination; 2)

NEWater (brand name for reclaimed water); 3) local water catchments; 4) underground

water storage; 5) status quo. This thesis demonstrates that the integrated SD-AHP

decision support approach is very useful and effective in the long-term planning for

sustainable development.

Keywords System dynamics; Analytic hierarchy process; Decision support; Water

resources management

3i

Acknowledgements

This thesis would not have been possible without the encouragement and assistance of

so many individuals and organizations.

First, and foremost, I would like to express my deepest gratitude to Associate Professor

Poh Kim Leng and Associate Professor Ng Szu Hui, for their guidance and support

throughout my undergraduate studies.

Also, I would like to thank Dr. Chien Wang, Dr. Jason Blake Cohen, and other co-

workers at Singapore-MIT Alliance for Research and Technology and Massachusetts

Institute of Technology. They introduced to me the exciting field of scientific research

and helped to grow as a student researcher.

I am extremely grateful to the wonderful teachers and classmates at University

Scholars Programme. They taught me to strive to be a public intellectual who could

read, write, and speak across disciplines.

Last but not least, I would like to thank my parents for their unconditional love. This

thesis is dedicated to them.

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Table of Contents

Abstract ............................................................................................................................i

Acknowledgements ........................................................................................................ii

Table of Contents ...........................................................................................................iii

List of Acronyms ............................................................................................................v

List of Figures ................................................................................................................vi

List of Tables ................................................................................................................vii

Chapter 1 Introduction ................................................................................................1

1.1 Sustainable water resources management ............................................................1

1.2 Research motivation .............................................................................................1

1.3 Research methodologies and contributions .........................................................2

1.4 Thesis outline .......................................................................................................2

Chapter 2 Literature Review .......................................................................................3

2.1 Water resources management in Singapore .........................................................3

2.2 System Dynamics (SD) and its applications ........................................................5

2.3 Analytic Hierarchy Process (AHP) and its applications ......................................6

Chapter 3 The SD-AHP Decision Support Approach ................................................7

3.1 Overview of the SD-AHP decision support approach .........................................7

3.2 SingaporeWater SD model ...................................................................................7

3.2.1 Justification of the application of SD ........................................................7

3.2.2 Model formulation and development .........................................................8

3.2.3 Model calibration and validation .............................................................11

3.3 AHP for decision support ...................................................................................19

3.3.1 Justification of the application of AHP ....................................................19

3.3.2 AHP explained .........................................................................................19

3.3.3 Basic structure of the decision hierarchy .................................................20

3.4 Two-attribute trade-off analysis .........................................................................21

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Chapter 4 Results and Discussions ............................................................................22

4.1 SD simulation results from SingaporeWater ......................................................22

4.1.1 Simulation results under Scenario 1 ........................................................22



4.2 Alternative selection using AHP ........................................................................26

4.2.1 AHP results under Scenario 1 ..................................................................27



4.3 Two-attribute Trade-off Analysis .......................................................................28

Chapter 5 Conclusion .................................................................................................30

5.1 Contributions of the thesis .................................................................................30

5.2 Limitations and future work ...............................................................................31

List of References ........................................................................................................33

Appendices ..................................................................................................................38

Appendix A Full stock and flow diagram .....................................................................38

Appendix B A survey of water-related projects in Singapore ......................................39

Appendix C Model input data and formulae ................................................................40

Appendix D SD simulation results ...............................................................................50

Appendix E AHP results ...............................................................................................79

Appendix F Trade-off analysis results ..........................................................................87

Appendix G Conference manuscript (accepted) ...........................................................89

Appendix H Essay for INCOSE Essay Competition 2012 (Best Paper Award) ...........99

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List of Acronyms

AHP Analytic Hierarchy Process

CI Consistency Index

CLD Causal Loop Diagram

CR Consistency Ratio

SD System Dynamics

SFD Stock and Flow Diagram

PUB Public Utilities Board

7v

List of Figures

Fig. 1.1 Schematic overview of the integrated SD-AHP decision support approach .................................2

Fig. 2.1 The closed water loop managed by PUB ......................................................................................4

Fig. 3.1 Causal Loop Diagram (CLD) capturing key demand and supply factors .....................................8

Fig. 3.2 Key stocks and flows in SingaporeWater SD model ..................................................................10

Fig. 3.3 Comparison of real population and simulated population ..........................................................12

Fig. 3.4 Demand forecasts in SingaporeWater .........................................................................................13

Fig. 3.5 Four National Taps captured in SingaporeWater ........................................................................14

Fig. 3.6 System responses in the reference mode of SingaporeWater ......................................................16

Fig. 3.7 System responses when total reservoir capacity varies significantly .........................................18

Fig. 3.8 Basic decision hierarchy for sustainable water management ......................................................20

Fig. 4.1 Performance sensitivity under Scenario 1 ...................................................................................27

Fig. 4.2 The efficient frontier under Scenario 1 .......................................................................................29

Fig. A.1 Full stock and flow diagram .......................................................................................................38

Fig. D.1 Growth of population and water demand under Scenario 1 .......................................................50

Fig. D.2 Long-term impacts of investments in underground under Scenario 1 .......................................51

Fig. D.3 Long-term impacts of investments in seawater desalination under Scenario 1 .........................53

Fig. D.4 Long-term impacts of investments in NEWater under Scenario 1 .............................................55

Fig. D.5 Long-term impacts of investments in local water catchments under Scenario 1 .......................57

Fig. D.6 Growth of population and water demand under Scenario 2 .......................................................59

Fig. D.7 System responses under Scenario 2 ...........................................................................................60

Fig. D.8 Long-term impacts of investments in underground under Scenario 2 .......................................61

Fig. D.9 Long-term impacts of investments in seawater desalination under Scenario 2 .........................63

Fig. D.10 Long-term impacts of investments in NEWater under Scenario 2 ...........................................65

Fig. D.11 Long-term impacts of investments in local water catchments under Scenario 2 .....................67

Fig. D.12 Decline of population and water demand under Scenario 3 ....................................................69

Fig. D.13 System responses under Scenario 3 .........................................................................................70

Fig. D.14 Long-term impacts of investments in underground under Scenario 3 .....................................71

Fig. D.15 Long-term impacts of investments in seawater desalination under Scenario 3 .......................73

Fig. D.16 Long-term impacts of investments in NEWater under Scenario 3 ...........................................75

Fig. D.17 Long-term impacts of investments in local water catchments under Scenario 3 .....................77

Fig. E.1 Performance sensitivity under Scenario 2 ..................................................................................86

Fig. E.2 Performance sensitivity under Scenario 3 ..................................................................................86

Fig. F.1 The efficient frontier under Scenario 2 .......................................................................................88

Fig. F.2 The efficient frontier under Scenario 3 .......................................................................................88

vi8viivi vi

List of Tables

Table B.1 Key input data based on related projects in Singapore ............................................................39

Table E.1 Weights of the criteria ..............................................................................................................79

Table E.2 Weights of the alternatives under Scenario 1 ..........................................................................80

Table E.3 Local and global weights under Scenario 1 .............................................................................81





Table F.1 Average self-sufficiency index and cost index under Scenario 1 .............................................87



9vii

Chapter 1 Introduction

1.1 Sustainable water resources management

Water is the world’s most critical natural resource. It is unquestionable that the

survival of the human species depends fundamentally on the availability of quality

water. The severe scarcity of water is a global concern for now and the future. On the

demand side, rapid population growth and economic development will lead to even

higher demand for water worldwide. On the supply side, climate change has caused the

rainfall to be less predictable and natural sources of water less reliable (Piao et al.

2010). The demand-supply imbalance in the water sector calls for more innovative

water management practices, so as to provide sufficient quality water for present and

future generations. This is the ultimate goal of sustainable water resources

management, in alignment with the United Nations’ broader definition of sustainability

(WCED 1987).

1.2 Research motivation

Besides the challenges brought by the climate change on the global scale,

Singapore, a small city state at the heart of Southeast Asia, faces many other

challenges which are unique to its local context. With limited land spaces and water

resources, the Republic has been purchasing water from Malaysia under two water

agreements (PUB 2011a). This dependency on imported water is widely perceived to

be a threat to Singapore’s sovereignty and well-being (Chia 2008).

Furthermore, as extreme storms become more intense and frequent, several

incidents of urban floods have occurred in the country’s premier residential and

business districts (AsiaOne 2011a; Channel NewsAsia 2011). In order to alleviate the

risks of flooding and diversify water supplies, Singapore’s former Chief Defense

Scientist, Professor Lui Pao Chuen, proposed an underground water storage system in

early 2012. This large-scale infrastructure allows extra rainwater to be stored in

underground rock caverns and be pumped up in times of water stress (Chua 2012).

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If constructed and put into operation, this new underground infrastructure will have

significant long-term impacts on the integrated water resources system in Singapore. In

addition, among the many alternatives to augment Singapore’s water supplies, decision

makers need to know which ones are the more sustainable plans to pursue.

1.3 Research methodologies and contributions

This thesis aims to propose an integrated decision support approach that integrates

System Dynamics (SD) and a multi-criteria decision support tool called Analytic

Hierarchy Process (AHP). It also demonstrates the usefulness of this innovative

approach in helping to achieve sustainable water resources management in Singapore.

Fig. 1.1 summarizes this proposed approach. First, a SD model takes in real-world and

simulates the consequences of different alternative plans under three population

scenarios. Second, AHP is applied to compare different alternatives based on their

performance as revealed by the SD simulation and the judgment of decision makers.

1.4 Thesis outline

Chapter 2 offers a critical review of Singapore’s integrated water resources system

and the main methodologies: SD and AHP. Chapter 3 shows how SD and AHP could

be integrated to aid decision making. Chapter 4 presents the SD simulation results and

discusses the priorities of five alternative development plans. Chapter 5 summarizes

main research contributions, discusses shortcomings of this study, and provides

suggestions for future work.

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Fig. 1.1 Schematic overview of the integrated SD-AHP decision support approach

Chapter 2 Literature Review

2.1 Water resources management in Singapore

Situated at the heart of the maritime continent, Singapore receives more than 2400

mm rainfall annually (NEA 2011). Theoretically, this supply of rainwater provides

more than what the country consumes (Chia 2008). However, as local water

catchments are limited and the tropical weather speeds up evaporation of surface

water, Singapore is still a water scarce city state with a fast-growing population.

Because of this scarcity of water, the country has been importing water from

Malaysia under two bilateral agreements after separating from Malay Peninsula in

1965. The first agreement expired in August 2011 and the second will expire in 2061

(PUB 2010). Given that a significant amount of water comes from outside its borders,

and since water supply is a vital element of its national security, Singapore has begun

to focus on sustainable development and attempts to overcome the limits of natural

constraints through technological innovations.

In the past one decade, it has invested heavily in desalination, wastewater

reclamation (branded as NEWater), water catchment management and other similar

projects. All these have resulted in an integrated and systematic approach towards

urban water resources management. Public Utilities Board (PUB), the national water

agency, is now managing the whole water cycle, from sourcing to the collection,

purification/treatment and supply of drinking water and the management of waste and

storm water (PUB 2011b). Fig. 2.1 illustrates the water loop managed by PUB. The

concerted attempts to close this loop demonstrate the country’s sheer determination to

maximize the use of all the water resources it has.

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However, the existing Four National Taps, namely imported water, local water

catchments, desalinated water, and NEWater, have their weaknesses. Even if the

supply of imported water continues after 2061, the price demanded from Malaysia or

Indonesia might cause it to become economically unsustainable (Choong 2001). Water

in local catchments are prone to evaporation, contamination, and pollution (Chia

2008). NEWater and desalination plants both take up scarce land space from industry

and business and are costly and energy-intensive (PUB 2010a).

Another challenge for Singapore’s urban water management is the increasingly

intense flash floods in Bukit Timah residential area and Orchard Road shopping

district (AsiaOne 2011a; Channel NewsAsia 2011). People were exposed to higher

risks of water-borne diseases and the economy was adversely affected (Lur 2011).

Thus, the critical question is could Singapore move beyond the constraints of the

natural water cycle, “[collect] every drop of rain” (PUB 2011b), and alleviate the

problem of urban flooding?

Fig. 2.1 The closed water loop managed by PUB

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Professor Lui, the nation’s former Chief Defense Scientist and current Advisor to

both National Science Foundation (NRF 2007) and Underground Master Plan Task

Force (NUS 2012), proposed a solution to this challenge in early 2012. He suggested

that the country should build an underground water storage system, similar to Jurong

Rock Caverns that will store 1.47 million cubic meters of oil in 2014 (Teo 2011). As

there are already similar rock cavern projects completed in Singapore and around the

world (Nordmark 2002; Parker 2004), building more rock caverns for flood alleviation

and storm-water storage seems to be a technically feasible project for Singapore.

The critical decisions on rock caverns necessitates decision support tools such as

system dynamics to quantitatively and qualitatively analyze the long-term impacts of

the proposed rock caverns on Singapore’s integrated water resources system. In

addition, among many other alternatives to augment Singapore’s water supply, which

ones should the decision makers choose in order to achieve sustainable water resources

management?

The following sections review two computer-based decision support tools to help

enhance the effectiveness of decision-making by reducing information overload and by

augmenting cognitive limitations and rationality bounds of the decision makers (El-

Najdawi and Stylianou 1993).

2.2 System Dynamics (SD) and its applications

System Dynamics (SD) is an approach to understanding the behavior of complex

systems over time. It captures internal feedback loops and time delays that affect the

behavior of the entire system. Developed by Professor Jay Forrester in the 1960s and

popularized by the Club of Rome’s Limits to Growth in the 1970s (SDS 2012), SD has

been successfully applied to study demographics (Forrester 1969), economic growth

(Meadows et al. 1972), business development (Roberts 1981; Karlsson et al. 2000),

water and natural resources management (Winz and Brierley 2009; Simonovic 2002a;

Simonovic 2002b; Simonovic and Rajasekaram 2004), and environmental systems

5

(Liu 2004; Ford 1999). Its capabilities to quantitatively simulate the dynamic

consequences of various policies make it an ideal decision support tool for strategic

policy testing and selection.

The current modeling studies of water resources mainly focus on the irrigation

system of the agricultural industries. For example, SD has been used to study water

resources in Canada (Simonovic 2002a; Simonovic 2002b; Simonovic and

Rajasekaram 2004), Yellow River in China (Xu et al. 2002), water for irrigation in

Spain (Fernandez and Selma 2003), and water balance in Mono Lake, California

(Vorster 1985). To date, there are no published studies utilizing SD as a decision

support tool to analyze Singapore’s integrated water resources in an urban

environment. This project aims to fill in this gap.

2.3 Analytic Hierarchy Process (AHP) and its applications

Because of the inevitable trade-offs among decision criteria, it is usually difficult to

make decisions based on SD simulation results alone. The Analytic Hierarchy Process

(AHP) provides a comprehensive framework to structure a decision problem, represent

and quantify decision criteria, relate these criteria to overall goals, and then evaluate

alternative plans through pair-wise comparisons.

Based on sound mathematics and psychology foundations, AHP has been used

widely in fields such as government, business, industry, healthcare, and education

(Saaty and Vargas 1991; Golden et al. 1989; Liu 2004). It has also been proved to be a

powerful decision support tool in water resources management (Srdjevic and Medeiros

2008; Wang 2009; Greaves 2011). A new research trend is to use AHP in conjunction

with other methods such as linear programming, data envelopment analysis, and

SWOT-analysis (Ishizaka and Labib 2011). Although both SD and AHP are popular

and powerful tools, they have rarely been used together in sustainable development

plans. By proposing to combine the strengths of SD and AHP in sustainable water

resources management, this thesis aims to fill this research gap.

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Chapter 3 The SD-AHP Decision Support Approach

3.1 Overview of the SD-AHP decision support approach

The integrated decision support approach combines SD with AHP to help choose

more sustainable development plans for Singapore’s water sector. The two methods are

used together to complement each other. The first part of this chapter presents the

formulation and validation of the SingaporeWater SD simulation model. The second

part makes use of AHP to find the preferred choice among the alternative plans based

on their simulated performance as revealed by SingaporeWater.

3.2 SingaporeWater System Dynamics (SD) model

In order to capture the essence of Singapore’s water sector, we have developed a

system dynamics model called SingaporeWater. As the second water agreements with

Malaysia will expire in 2061 and the proposed hydrological infrastructures have long

lifespans, the model runs from year 2000 to 2100, so as to reveal the long-term impacts

of proposed plans. It is developed with Vensim Personal Learning Edition, a free

software with a visual graphical user interface that helps conceptualize, build, and test

system dynamics models.

3.2.1 Justification of the application of SD

The SD approach is appropriate for any dynamic system characterized by

interdependence, mutual interaction, information feedback, and circular causality

(MacDonald et al. 2001). It is an excellent tool to study problems that arise in closed-

loop systems. As Singapore’s water resources system is highly centralized and

integrated, SD’s strength in capturing interdependencies and feedbacks between

various sub-systems could be fully exploited. Furthermore, most of the relevant data

needed for model building are readily available on governmental websites, corporate

annual reports, and many other open-access sources. These credible data have

significantly enhanced the validity of the model. Therefore, SD is an ideal tool to

holistically analyze Singapore’s water resources system.

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3.2.2 Model formulation and development

The model is originated from a basic demand and supply framework. On the

demand side, population level and economic growth determines the total demand for

water. On the supply side, the Four National Taps provide water for both domestic and

non-domestic consumptions. These key factors are captured by a Causal Loop

Diagram (CLD) in Fig. 3.1. To a highly modern and developed city state such as

Singapore, the quality of water supply has been carefully monitored, and thus, is not a

great concern in sustainable water management. For this reason, quality index is not

captured in SingaporeWater.

We identified adequacy of water, self-sufficiency in water, and economic

sustainability as the three most important aspects of sustainable water management in

Singapore. They are quantified by three key indices (Eq. 3.1 to 3.3). To have adequate

water means that the total water supply must be equal or higher than the total water

demand. The goal is to have adequacy index larger than one throughout the 21st

century. Self-sufficiency index shows how much water demand is actually met by

Singapore’s own water, excluding imported water from neighboring countries. It

Fig. 3.1 Causal Loop Diagram (CLD) capturing key demand and supply factors

8

should be equal or greater than one in order for Singapore to claim self-sufficiency in

water.

c

Economic sustainability in water sector is captured by the cost index. It gives a

sense of how much investments have gone into the water sector in order to have a

particular level of water supply in Singapore. Generally, the higher the index, the less

cost-effective the investment plans are. Note that the annual investments, from both

private and public sectors, refer to the initial investments in building up the

infrastructures. They do not include the yearly operational and maintenance costs of

the Four National Taps.

From the closed water loop in Fig. 2.1 and CLD in Fig. 3.1, we developed the Stock

and Flow Diagram (SFD) for SingaporeWater. Fig. 3.2 shows the key stocks and flows

in the model. The model also includes the proposed underground water storage system.

It is assumed that excessive rainfall and water surplus will flow into the rock caverns.

Then the stored water could be pumped up whenever the need arises. The complete

SFD is in Appendix A. Comparing the SFD and the system description by PUB leads

us to conclude that the SD model indeed captures the key elements of Singapore’s

integrated water resources system.

(3.1)

(3.2)

(3.3)

9

Most of the input data are obtained from open sources published by various

governmental agencies such as PUB, Ministry of Environment and Water Resources,

Singapore Department of Statistics, and National Environment Agency. The costs of

building underground rock caverns, water reclamation plants, and local water

catchments are estimated from those of similar projects in Singapore. Key figures

about these water-related projects are tabulated in Table B.1 in Appendix B. All the

model input data, formulae and detailed explanations are attached in Appendix C.

Because of limited information and the inherent uncertainties in almost all real-

world systems, assumptions have to be made during model building. The first

assumption is that both the private and public sectors will only start to invest in the

water sector when there is inadequacy of water. This is reasonable because a high

adequacy index does not justify the investments of limited resources into the water

Fig. 3.2 Key stocks and flows in SingaporeWater SD model

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sector. Instead, the resources could be diverted to other sectors such as education,

transportation, and healthcare in which the need for investments might be more urgent.

Secondly, it is assumed that there is a limit to reservoir expansions and underground

rock caverns constructions. As Singapore’s land space is limited, both reservoirs and

underground rock caverns could not expand infinitely. In this model, the limits of

underground storage and surface reservoirs are set at 100 million cubic meters and 500

million cubic meters respectively. These conservative estimates could be updated when

more information are available.

Thirdly, water supply from all Four National Taps are assumed to be of superb

quality. This means that every drop of water meets the quality standard for drinking

water. Although NEWater is mainly for industrial uses, it could also be used as

portable drinking water (PUB 2012). Therefore, the SD model did not distinguish

water supply for industrial consumptions or for domestic consumptions.

Fourthly, it is assumed that there will be no imported water after 2061. In order to

study Singapore’s long-term self-sufficiency in water, it is more reasonable to exclude

imported water in strategic planning.

3.2.3 Model calibration and validation

To increase confidence in SingaporeWater SD model, we performed model

calibration, direct structural tests, and sensitivity analysis. Model calibration is the

process of estimating the model parameters to obtain a match between observed and

simulated behavior (Oliva 2003). Direct structural tests assess the validity of the model

structure, by directly comparing the simulated reference mode with knowledge about

the real system (Barlas 1996). Sensitivity analyses of some uncertain parameters are

“strong” behavior tests that can help uncover potential structural flaws (Barlas 1996).

Although most of the population data are made available by Singapore’s

Department of Statistics, the net immigration level is not publicly accessible. This is an

important variable which significantly affects the future population level and,

11

consequently, the future water demand. Its value is estimated through calibrating it

with the total population level from 2000 to 2011. As shown in Fig. 3.3, the simulated

population level matches the real data satisfactorily when the net immigration level is

estimated at 163,000 persons per year.

Besides calibration, direct structural tests also help to improve the validity of the

model. Fig. 3.4 shows the demand forecasts in SingaporeWater. It captures the

situation when the population level grows at the same rate as that of the 2000s.

On the demand side, as the population grows rapidly, both domestic and non-

domestic demand for water increase significantly throughout the century, as shown in

Fig. 3.4. Fig. 3.5 shows the water supply from the Four National Taps. Imported water

decreases drastically in 2011 and in 2061 because of the expirations of two water

agreements with Malaysia (Fig. 3.5a). Water from local reservoirs are stable with

natural variations due to fluctuations in rainfalls (Fig. 3.5b). Water supplies from

desalination plants and NEWater plants increase as new plants start operation.

However, as the existing plants close down after their useful life, the supply of water

from these two National Taps drops to zero from the 2030s onwards (Fig. 3.5c and

3.5d). As there are no future investments in the reference mode, the cost index, not

featured here, is consistently zero.

Fig. 3.3 Comparison of real population and simulated population

0

2,000,000

4,000,000

6,000,000

2000 2002 2004 2006 2008 2010

Population in Sinagpore

Real population Simulated population

12

(a)Total domestic demand

800 M

600 M

400 M

200 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Total domestic demand : Reference Mode

(b)Total non-domestic demand

800 M

600 M

400 M

200 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

"Total non-domestic demand" : Reference Mode

Fig. 3.4 Demand forecasts in SingaporeWater

13

(a)Water supply from imports

600 M

450 M

300 M

150 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Water supply from imports : Reference Mode

(b)Water supply from catchments

200 M

175 M

150 M

125 M

100 M2000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Water supply from catchments : Reference Mode

Fig. 3.5 Four National Taps captured in SingaporeWater

14

(c)Water supply from desalination

200 M

150 M

100 M

50 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Water supply from desalination : Reference Mode

(d)

Water supply from NEWater200 M

150 M

100 M

50 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Water supply from NEWater : Reference Mode

Fig. 3.5 Four National Taps captured in SingaporeWater (continued)

15

(a)Adequacy of water

4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

Adequacy of water : Reference Mode

(b)

Self-sufficiency in water4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Reference Mode

Fig. 3.6 System responses in the reference mode of SingaporeWater

16

Because of the availability of imported water and the addition of desalinated water

and NEWater, Singapore will continue to enjoy high adequacy of water until early

2030s (Fig. 3.6a). The model demonstrates that Singapore has achieved full self-

sufficiency in water in 2010 and will continue to be self-sufficient till 2030 (Fig. 3.6b).

This is cross-validated with Dr. Lee Poh Onn’s research results, which concluded that

Singapore should no longer be in a “water scarce” condition by 2011 (Lee 2010).

However, due to the termination of imported water and closing down of existing

water plants, the adequacy of water and self-sufficiency in water drop drastically from

the 2030s onwards (Fig. 3.6). The results of these structural tests are consistent with

the situations in the real system and research results of other studies. Thus, it could be

concluded that the SD model is structurally valid.

Stronger than the direct structural tests are the structure-oriented behavior tests,

such as sensitivity analysis. It asks if the real system would exhibit high sensitivity to

one particular parameter with uncertain values (Barlas 1996). One such parameter in

SingaporeWater is the total capacity of the surface reservoirs. We conducted sensitivity

analysis of the reservoir capacity. As the function for sensitivity analysis is not

included in the Vensim PLE version, it was carried out by manually changing each

uncertain parameter one-at-a-time and keeping the others constant.

Fig. 3.7 shows the system responses when the total reservoir capacity is estimated at

100 million cubic meters (red lines) and 300 million cubic meters (blue lines). The

general patterns of the adequacy index and self-sufficiency index are similar in both

cases. They both increase to a peak in 2020 before dropping to below 1 from 2030

onwards. Seasoned researchers know that “a well-structured model will generate the

same general pattern despite the great uncertainty in parameter values” (Ford, 2000).

Therefore, it is demonstrated that the dynamic hypotheses in SingaporeWater are valid.

Furthermore, when the total capacity is set at 300 million cubic meters, the

adequacy index and self-sufficiency index are both unrealistically high (Fig. 3.7). This

17

implies that a lower estimate at around 100 to 200 million cubic meters seems to be

more realistic. Based on this observation, the final reservoir capacity is estimated at

150 million cubic meters.

In a nutshell, the results of the validation process have established a high model

confidence. Driven by credible real-world data, the SD model captures the essence of

Singapore’s water system. It can then be used to test various development plans.

Adequacy of water6

4.5

3

1.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

Adequacy of water : Reservoir capacity 300MAdequacy of water : Reservoir capacity 100M


4.5

3

1.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Reservoir capacity 300M"Self-sufficiency in water" : Reservoir capacity 100M

Fig. 3.7 System responses when total reservoir capacity varies significantly

18

3.3 AHP for decision support

As Singapore strives for high adequacy of water and full self-sufficiency in water, it

is also concerned about economic sustainability in the water sector. For example,

although seawater desalination seems to be promising, at the current level of

technology, it is still energy-intensive and costly (Elimelech and Philip 2011). Thus,

there is an apparent trade-off among these three key aspects of sustainable water

management. It calls for multi-criteria decision-making (MCDM) tools, such as AHP,

to help solve this complex problem with multiple conflicting and subjective criteria.

The following sections briefly explain the rationale of applying AHP, how it works,

and the basic structure of the decision hierarchy used in this study.

3.3.1 Justification of the application of AHP

The strength of the AHP lies in its ability to structure a complex, and multi-attribute

problem hierarchically, and then to investigate each level of the hierarchy separately.

Incorporating both qualitative and quantitative information, AHP educes a relative

ordering of immeasurable subjective preferences by pair-wise comparison. Compared

to other MCDM methods, AHP generates a ranking of all alternatives, instead of the

most favorable alternative. In this way, it provides more information to the decision-

makers rather than simply reporting the “best” alternative (Liu 2004).

Although AHP has been criticized for the possibility of rank reversal, it is still a

useful and powerful tool because of its simplicity and its ability to translate subjective

judgements into quantitative ratios (Stewart 1992). The user-friendly supporting

software, Expert Choice, has certainly contributed to the widespread use of the

method.

3.3.2 AHP explained

The application of AHP method mainly consists of four steps: 1) set up a decision

hierarchy by breaking down the decision problem into goal, criteria, sub-criteria, and

decision alternatives; 2) collect input data for pair-wise comparisons of the decision

19

elements; 3) use the eigenvalue method to estimate the relative weights of the decision

elements, and determine the consistency of the judgements; 4) aggregate the relative

weights of the decision elements to rank the decision alternatives (Liu 2004). For more

details about the method, please refer to Saaty (1982).

3.3.3 Basic structure of the decision hierarchy

This section presents the basic decision hierarchy with the overall goal of achieving

sustainability in water resources management. As shown in Fig. 3.8, the three key

criteria of sustainability in Singapore’s case are defined as adequacy of water, self-

sufficiency in water, and cost. The third level in the hierarchy consists of the five long-

term development plans the public and private sectors could choose to pursue. Plan 1

is not to invest in the water sector so as to keep the status quo. The other four plans are

about investing 1% to 3% of the nation’s Gross Domestic Product (GDP) solely into

one of the Four National Taps.

Plan 4 Invest in NEWater

Plan 5 Invest in local water catchments

Sustainability in Water Management

Cost

Plan 1 Status quo

Plan 3 Invest in desalination

Plan 2 Invest in underground

Adequacy of Water Self-sufficiency in Water

Fig. 3.8 Basic decision hierarchy for sustainable water management

20

As people are the driving force of the economy and the basis of both domestic and

non-domestic demand for water, the priorities of these plans are studied under three

population scenarios: 1) Singapore’s population continues to increase at the same rate

as that of the 2000s; 2) the population grows gradually from five million to six million

people over the 21st century; 3) based on the current birth rate and death rate, the

population shrinks steadily with no intake of immigrants.

3.4 Two-attribute trade-off analysis

The basic decision hierarchy in Fig. 3.8 has included the cost factor into decision

analysis, thus pre-committing the cost constraint into the process of decision making.

However, sometimes, decision makers might want to see how the system could

perform with respect to the cost factor. Another way to analyze the situation is to

isolate the cost factor from other factors and then conduct a two-attribute trade-off

analysis between cost and another critical decision criterion.

To better visualize the trade-off between two decision criteria, we conducted a

simple two-attribute trade-off analysis by plotting the average self-sufficiency index

against the average cost index. This trade-off analysis aims to complement the AHP

analysis and offers an alternative way to visualize the trade-offs which might not be

clearly noticeable in the AHP results. The trade-off analysis results are presented in

Section 4.3.

21

Chapter 4 Results and Discussions

This chapter presents the simulation results from SingaporeWater SD model and the

priorities of the five plans under three population scenarios as listed below.

Scenario 1: Singapore’s population continues to grow rapidly at the same rate as that

of the 2000s.

Scenario 2: The population grows gradually from five million to six million people

over the 21st century.

Scenario 3: The population shrinks steadily with no intake of immigrants and constant

birth rate and death rate.

4.1 SD Simulation results from SingaporeWater

This section presents the simulation results under three population scenarios and

new insights gained from this study. All the figures could be found in Appendix D.

4.1.1 Simulation results under Scenario 1

In Scenario 1 Singapore’s population keeps increasing at the rate of the 2000s. Fig.

D.1 shows that the population grows from about 4 million in 2000 to about 10 million

in 2100. Because of the rapid population growth, the total demand for water also

increases steadily, reaching 1.3 billion cubic meters per year in 2100. In the Y-axis of

Fig. D.1, M and B stand for Million and Billion respectively. If Singapore adopts Plan

1, which is not to invest in the water sector and keep the status quo, then it will suffer

severe inadequacy of water from the early 2030s onwards, as shown in the reference

mode in Fig. 3.6a.

If Singapore invests in underground water storage, due to shortage of water from

the 2030s onwards, water stored underground will be pumped up continuously (Fig. D.

2a). However, it is insufficient to meet the increasing demand for water: adequacy and

self-sufficiency indices (Fig. D.2b and D.2c) are both below 0.5 after 2060. As the

initial costs of building underground rock caverns are significantly higher than other

infrastructure projects, the cost index is consistently at a high level (Fig. D.2d).

22

If the Republic invests in seawater desalination as and when there is inadequacy of

water, then the water supply from desalination (Fig. D.3a) will be oscillating

drastically. Due to the time delay associated with the constructions of new desalination

plants, the adequacy and self-sufficiency indices will follow a cyclic pattern: in each

cycle, it falls below 1 for about five years before shooting up to almost 2 in the

subsequent five years (Fig. D.3b and D.3c).

If Singapore invests in NEWater instead, then the water supply from NEWater (Fig.

D.4a) will also be oscillating from the 2030s to the 2060s. As the shortage of water

grows more severe after 2061, the recyclable used water will also decrease sharply.

Similar to the case of desalination, the adequacy and self-sufficiency indices follow a

cyclic pattern, with five years of water shortage followed by another five years of

water abundance (Fig. D.4b and D.4c).

If the city state invests in local water catchments in early 2030s, in about six years’

time, the limit of reservoir expansions will be reached. This means that even if there

are more investments into it, the water supply from catchments will always stay

constant (Fig. D.5a). As the increase in water supply could not meet the rapid increase

in water demand, both adequacy and self-sufficiency indices are consistently below 1

after 2030 (Fig. D.5b and D.5c). The merit of this plan is that it is least costly among

all the investment plans (Fig. D.5d).

In conclusion, if the population continues to grow rapidly, then investing in

underground or local water catchments is not sufficient to help Singapore achieve

adequacy and self-sufficiency in water. Under the assumption that investments will

only come to the water sector when there is inadequacy of water, investing in

desalination or NEWater would result in about five years of water shortage followed

by another five to six years of water abundance. The cyclic patterns are mainly due to

the construction time of desalination or NEWater plants.

23


In Scenario 2 Singapore’s population increases gradually from about 4 million in

2000 to 6 million in 2100 (Fig. D.6a). This is done in model by setting the net

immigration level at 80000 per year from 2012 onwards. The total demand for water

increases from about 500 million cubic meters in 2000 to about 750 million cubic

meters in 2100 (Fig. D.6b). Because of the milder demand compared to that in

Scenario 1, the adequacy index peaks at about 4 in late 2020s, meaning that the supply

of water is four times more than the demand of water (Fig. D.7a). In this case,

Singapore enjoys high adequacy in water and full self-sufficiency of water from 2010

to 2040 (Fig. D.7a and D.7b). Shortage of water will only set in after 2040, ten years

later than that of Scenario 1.

If Singapore invests in underground water storage from 2040 onwards, then it needs

to continuously pump up water. The water supply from this source reaches about 280

million cubic meters in 2100 (Fig. D.8a). Similar to Scenario 1, underground water

alone is not sufficient to meet Singapore’s increasing water demand. The adequacy and

self-sufficiency indices stagnates at about 0.5 to 0.8 after 2040 (Fig. D.8b and D.8c).

The abrupt jump of the cost index in 2061 is due to the absence of imported water.

This implies that, after 2061, the unit cost of water supply will increase significantly.

If the country invests in seawater desalination, then the annual supply from this

National Tap could reach more than one billion cubic meters in the 2090s (Fig. D.9a).

The long-term impacts will be similar to those in Scenario 1: Singapore will

experience water shortage for about five years before enjoying high water abundance

for another five to six years (Fig. D.9b and D.9c). As we assume that investments will

only come to the water sector when there is inadequacy of water, the cost index has

periodic peaks (Fig. D.9d). The four peaks after 2040 are much higher than others,

implying that the unit cost of water supply is more expensive after the supply from

imported water stops.

24

The system responses are rather different when investments go to NEWater. From

2040 to 2060, the supply from NEWater follows a cyclic pattern, reaching about 500

million cubic meters per year in later 2040s and early 2060s (Fig. D.10a). After 2061,

because of the water shortage, investments keep coming into NEWater, as shown by

the steady cost index in the later part of this century (Fig. D.10d). This results in a

steady increase in water supply in the same period (Fig. D.10a). However, the total

water supply is still not sufficient to meet the total demand: after 2061, adequacy and

self-sufficiency indices are both at around 0.7 to 0.8 (Fig. D.10b and D.10c).

Lastly, if Singapore invests in local water catchments in early 2040s, then in about

eight years’ time, the limit of reservoir expansions will be reached (Fig. D.11a and D.

11d). Note that in Scenario 1 only six years’ of investments could expand the

reservoirs to the fullest. This time difference is due to the GDP level in each scenario.

In Scenario 2 the population growth is slower. This leads to a lower GDP level and,

consequently, a lower amount of investments into the water sector. Again, the supply

from local water catchments is not sufficient to meet Singapore’s water demand: in

later part of the century, both adequacy and self-sufficiency indices stay at about 0.7

(Fig. D.11b and D.11c).

In conclusion, the population growth in Scenario 2 is much more realistic than that

in Scenario 1. The total water demand is milder. The long-term impacts of all four

plans include higher adequacy and self-sufficiency indices compared to those in

Scenario 1.


In Scenario 3 it is assumed that there are no immigrants into Singapore and the

country’s birth and death rates remain constant. In this case, population will decrease

steadily from more than 5 million in 2011 to about 1.6 million in 2100 (Fig. D.12a).

The total demand for water will drop to 200 million cubic meters in 2100 (Fig. D.12b).

Because of this steady drop in water demand, adequacy index will increase to 7.5 in

25

2030 and stays there till 2061 (Fig. D.13a). Similarly, self-sufficiency index will stay

at 6 from 2030 to 2061, before dropping to below 1 in early 2070s (Fig. D.13b). In

other words, from 2010s to late 2060s, Singapore will have extremely high adequacy

of water and full self-sufficiency of water.

If Singapore invests in underground water storage, then 45 million cubic meters of

water stored underground would lift the self-sufficiency index to almost one (Fig. D.

14). If the investments go to seawater desalination, then the system will again exhibit a

cyclic pattern after 2070 (Fig. D.15). If resources go to expanding NEWater’s

capacities, then 200 million cubic meters of used water could be reclaimed (Fig. D.

16a), leading to high adequacy and self-sufficiency indices in the later part of the

century (Fig. D.16b and D.16c). If Singapore chooses to expand its local water

catchments to the fullest, then the adequacy and self-sufficiency indices will both

shoot up to more than 10 by the end of the century, indicating over-supply of water

(Fig. D.17).

Even though Scenario 3 is an extreme case and is unlike to happen, it still gives us

new insights into the water resources system. Water management policies depend

heavily on the population policies. If Singapore chooses to have a declining

population, then there is no need to invest too much resources into the water sector

because there will be over-abundance of water supply till the 2070s.

4.2 Alternative selection using AHP

By using AHP, decision makers could quantify their judgment through pair-wise

comparisons of the criteria and the alternatives. In all three scenarios, the priorities of

the criteria are the same: the relative weights of adequacy, self-sufficiency, and cost are

0.467, 0.467, and 0.067 respectively (Table E.1). For each scenario, the local and

global weights of each plan will be presented. Results of the sensitivity analysis will

also discussed here.

26

4.2.1 AHP results under Scenario 1

In order to strive for sustainable water resources management, Singapore should

pursue development plans in the following order of priorities: 1) seawater desalination;

2) NEWater; 3) local water catchments; 4) underground water storage; 5) status quo

(Table E.3). It is worth to note that the relative weight of investing in underground

water storage (0.088) is almost equal to that of the status quo (0.080). This implies

that, under the assumptions in SingaporeWater, investing in underground is rather

inconsequential in the pursue of adequacy and self-sufficiency in water.

Results of sensitivity analysis are illustrated in Fig. 4.1. With respect to adequacy in

water, desalination ranks higher than NEWater. However, with respect to self-

sufficiency, NEWater have a small edge over desalination. In terms of costs, keep

status quo ranks the highest and investing in underground ranks the lowest. With

respect to the overall goal, investments in seawater desalination and NEWater are

ranked much higher than the other three plans.

Fig. 4.1 Performance sensitivity under Scenario 1

27


The priorities of the five plans under Scenario 2 is similar to those in Scenario 1:

investing in seawater desalination and NEWater are of higher priorities compared to

other three plans (Table E.5 and Fig. E.1).

In Scenario 1, desalination and NEWater are ranked much higher than local water

catchments and underground water storage. However, in Scenario 2, the gap between

them gets narrower (Fig. E.1). This means that in the case of milder population growth,

investing in water catchments and underground becomes slightly more favorable. In

other words, if the demand for water is milder, then it is less attractive to invest in

more costly projects such as desalination and NEWater.


The situations in Scenario 3 are completely different. The AHP results suggest that

Singapore should pursue development plans in the following order of priorities: 1)

local water catchments; 2) NEWater; 3) desalination; 4) status quo; 5) underground

water storage (Table E.7 and Fig. E.2). In particular, the global weight of local water

catchments is higher than that of the other four plans combined. This means that

investing in local water catchments is of ultimate importance. When the demand for

water declines, the most sustainable development plan is to expand the local water

catchments. Other plans become much less attractive in the case of the population

decline. Interestingly, Plan 1 is of higher weight than Plan 2. This means that it is more

sustainable to keep the status quo rather than investing in the costly underground water

storage.

4.3 Two-attribute Trade-off Analysis

The average self-sufficiency index and cost index under Scenario 1 to 3 are

tabulated in Table F.1, F.2, and F.3 respectively. These averages are obtained from SD

simulation results for 2061 and onwards. This time period is chosen because 2061 is a

critical year in which the imported water will be terminated.

28

In a plot of the efficient frontier, the preferred direction is one with increasing self-

sufficiency in water and decreasing costs, as indicated by the red arrow in Fig. 4.2.

Decision makers could start with the least cost alternative, and then decide if investing

more resources to reach the next best alternative is worthwhile.

In Scenario 1, the efficient solutions, on the efficient frontier, are “Plan 3 Invest in

desalination”, “Plan 4 Invest in NEWater”, and “Plan 5 Invest in local water

catchments”. “Plan 2 Invest in underground” is clearly dominated by the three efficient

solutions (Fig. 4.2). This is consistent with the AHP results, which demonstrates that

the proposed underground water storage system is of a much lower priority compared

to other plans. In Scenario 2, the efficient solutions are still Plan 3, Plan 4, and Plan 5

(Fig. F.1). Similar to the situation in Scenario 1, these three plans also dominate Plan 2

by a large margin. In Scenario 3, a case of declining population, the most efficient plan

is “Plan 5 Invest in local water catchments” (Fig. F.2). All other plans become less

efficient because the demand of water is declining in this case.

Fig. 4.2 The efficient frontier under Scenario 1

29

Chapter 5 Conclusion

5.1 Contributions of the thesis

Driven by credible real-world data, SingaporeWater SD model adequately captures

the essence of the integrated water resources system in Singapore. AHP takes in the

judgment of the decision makers and helps to quantify the priorities of various

development plans. This integrated SD-AHP decision support approach has provided

new insights for sustainable water resources management. The unique strength of the

integrated approach is probably its capability to fully exploit the critical strengths of

both SD and AHP. Its successful application to Singapore’s water system, as

demonstrated in this thesis, could be a starting point for wider applications in other

similar integrated systems such as education system, transportation system, healthcare

system etc.

More specifically, the application of this integrated SD-AHP approach provides the

following key research findings:

1. The proposed underground water storage could store extra rainfall, alleviate the risk

of flooding in urban areas, and diversify sources of water supply. However, because

of its limited capacity and long construction time, it cannot be the country’s main

source of water supply. Furthermore, if it is built in 10 million cubic meters only, as

suggested by Prof. Lui, then it is not going to have a profound impact on

Singapore’s adequacy and self-sufficiency in water.

2. If investments only go into the water sector when there is inadequacy of water, then

there will be periodic and drastic oscillations in water supply, mainly due to the

constructions of new water plants. For instance, the long-term impacts of investing

in seawater desalination is that Singapore will experience five years of water

shortage followed by another five to six years of water abundance. This highlights

the need to plan well in advance. SingaporeWater SD model is able to simulate

when and how much capacity expansions are most suitable for Singapore.

30

3. The situations in the water sector depend heavily on the population policies. This is

shown in the AHP results under three population scenarios. If the population

increases rapidly or mildly (Scenarios 1 and 2), then the priorities of plans are: 1)

seawater desalination; 2) NEWater; 3) local water catchments; 4) underground water

storage; 5) status quo. In fact, the global weight of underground water storage is

most equal to that of the status quo. This implies that it is almost as inconsequential

as status quo. If Singapore chooses to have a declining population (Scenario 3), then

there is no need to invest too much resources into the water sector because there will

be over-abundance of water till the 2070s. Therefore, policies for sustainable water

resources management should be tailored to the country’s long-term population

policies, so as to optimize resource allocations.

5.2 Limitations and future work

Models are always provisional and there is no perfect model (Ford 1999). The

current version of SingaporeWater has been useful in answering our research

questions. There are limitations in this study, which could be worked on in the future.

1. It was assumed that the public and private sectors will only start to invest in the

water sector when there is inadequacy of water. This leads to the cyclic patterns in

the results. How funding from public and private sectors go into the water sector

could be better captured in the system.

2. When there is severe inadequacy of water, Singapore’s economy and population

level will definitely be affected. However, this delicate feedback loop has not been

captured in SingaporeWater.

3. The water sector consumes a huge amount of energy in its daily operations. Running

the underground water storage system with pumping stations to pump stored water

up to the ground level is probably going to be more energy intensive. Coordination

and integration of policies related to the management of both water and energy

sectors are needed. Impacts on energy consumption could be analyzed in the future.

31

4. Linear programming could be used to find the optimal investment plans for the

water sector, so that the self-sufficiency and adequacy of water could be achieved at

minimal costs.

5. This thesis focused on the long-term impacts of capacity expansions such as

building more underground rock caverns and water treatment plants. Key policy

variables such as social-economic factors, government investments have been

included in the model. This allows many other policy analysis to be done with

SingaporeWater. For example, it could simulate the situation in which Singapore

experience a prolonged period of droughts. In other words, the SD model could be

updated and improved to address a wide range of policy questions for Singapore and

beyond.

32

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http://www.pub.gov.sg/water/Pages/ImportedWater.aspx.




http://www.pub.gov.sg/annualreport2011/.




http://www.pub.gov.sg/Marina/Pages/3-in-1-benefits.aspx#wc.




PUB (2012) NEWater. http://www.pub.gov.sg/water/newater/Pages/default.aspx. Accessed 20 August 2012

Roberts EB (1981) Managerial Applications of System Dynamics. Productivity Press, Cambridge, Massachusetts

SDS (System Dynamics Society) (2012) The Field of System Dynamics. http://www.systemdynamics.org/what-is-s/. Accessed 20 August 2012

Teo E (2011) JTC seeks operator for Jurong Rock Caverns. The Straits Times, 14 December, 2011

Saaty TL (1982) Decision Making for Leaders: The Analytical Hierarchy Process for Decisions in a Complex World. RWS Publications

Saaty TL, Vargas LG (1991) Prediction, Projection and Forecasting. Kluwer Academic Publishers, Norwell, Massachusetts

Saaty TL (2003) Decision-making with the AHP: Why is the principal eigenvector necessary. European Journal of Operational Research 145:85-91

Simonovic SP (2002a) World water dynamics: global modeling of water resources. Journal of Environmental Management 66:249-267

Simonovic SP (2002b) Assessment of Water Resources Through System Dynamics Simulation: From Global Issues to Regional Solutions. In: the 36th Hawaii International Conference on System Sciences, Hawaii. IEEE, 2002

Simonovic SP, Rajasekaram V (2004) Integrated Analyses of Canada's Water Resources: A System Dynamics Approach. Canadian Water Resources Journal 29 (4):223-250

Srdjevic B, Medeiros YDP (2008) Fuzzy AHP Assessment of Water Management Plans. Water Resources Management (22):877-894

Stewart TJ (1992) A critical survey on the status of multiple criteria decision-making theory and practice. International Journal of Management Science 20:569-586

Vorster P (1985) A Water Balance Forecast Model for Mono Lake, California. Dissertation, California State University, Hayward, California

Wang X (2009) A Proposal and Application of the Integrated Benefit Assessment Model for Urban Water Resources Exploitation and Utilization. Water Resources Management (23):1171-1182

36

http://www.pub.gov.sg/water/newater/Pages/default.aspx.

http://www.pub.gov.sg/water/newater/Pages/default.aspx.

http://www.systemdynamics.org/what-is-s/.




WCED (World Commission on Environment and Development) (1987) Our common future. Oxford University Press, Oxford

Winz I, Brierley G (2009) The Use of System Dynamics Simulation in Integrated Water Resources Management. In: the 27th International Conference of the System Dynamics Society, Albuquerque, New Mexico, 2009.

Xu ZX, Takeuchi K, Ishidaira H, Zhang XW (2002) Sustainability Analysis for Yellow River Water Resources Using the System Dynamics Approach. Water Resources Management 16:239-261

37

Appendices

Appendix A Full stock and flow diagram

38

Fig. A.1 Full stock and flow diagram

Appendix B A survey of water-related projects in Singapore

Table B.1 Key input data based on related projects in Singapore

ProjectsConstruction time Construction

cost (S$)

Capacity (m3 /year)

Capacity increase per

dollar investedProjects

Concession period

Construction cost (S$)

Capacity (m3 /year)

Capacity increase per

dollar invested

Sea desalination

SingSpring Desalination Plant at Tuas (Hyflux 2002)

1.75 years(2004 to 2005)

250 million 49.8 million 0.20

Sea desalination

SingSpring Desalination Plant at Tuas (Hyflux 2002) 20 years

(2005 to 2025)


Sea desalination

Tuaspring Desalination Plant at

Tuas (Peng 2012)

2~3 years(2011-2013)

1.05 billion 116.25 million 0.11

Sea desalination

Tuaspring Desalination Plant at

Tuas (Peng 2012) 25 years (2013 to 2038)

1.05 billion 116.25 million 0.11

NEWater

Bedok NEWater Plant(Hyflux 2001)

1~2 years(2001 to 2002)

16.1 million 14.6 million 0.91

NEWater

Bedok NEWater Plant(Hyflux 2001) N.A.


NEWater

Kranji NEWater Plant

Phase 1 (PUB 2005)

1~2 years(2001 to 2002)

N.A. 12.4 million N.A.

NEWater


Phase 1 (PUB 2005) N.A.


NEWater


Phase 2 (PUB 2005)

0.5 years (2005 to 2006)


NEWater


Phase 2 (PUB 2005) N.A.


NEWaterSeletar NEWater

Plant (Hyflux 2003)

0.5~1 years( 2003 to 2004)


NEWaterSeletar NEWater

Plant (Hyflux 2003) Decommissioned in May 2009


NEWater

Ulu Pandan NEWater Plant (Keppel 2010)

2 years(2005 to 2006)

90~100 million 54 million 0.54~0.6

NEWater

Ulu Pandan NEWater Plant (Keppel 2010) 20 years

(2007 to 2027)

90~100 million 54 million 0.54~0.6

NEWater

Changi NEWater Plant (Channel

NewsAsia 2008)

2 years(2008 to 2010)


NEWater

Changi NEWater Plant (Channel

NewsAsia 2008) 25 years (2010 to 2035)


Local water catchments

Marina Reservoir (PUB 2011c)

2 years(2009 to 2011)

226 million 60 million 0.265


Marina Reservoir (PUB 2011c)

N.A.



Punggol- Serangoon Reservoir (AsiaOne

2011b)

5 years(2006 to 2011)



Punggol- Serangoon Reservoir (AsiaOne

2011b) N.A.


Underground rock caverns

Jurong Rock CavernsPhase 1 (Teo 2011)

5~6 years(2007 to 2013)

890 million 1.47 million 0.00165Underground rock caverns

Jurong Rock CavernsPhase 1 (Teo 2011)

N.A.


39

Appendix C Model input data and formulae

(01) Adequacy of water=SingaporeWater/Total water demand Units: Dmnl [0,10]

The goal is to have sufficient water supply to meet the water demand in any particular year. This means that supply/demand should be larger or equal to 1.

(02) Average rainfall increase rate=RANDOM UNIFORM( -0.01, 0.025 , 10 ) Units: Dmnl The annual rainfall data is obtained from Singapore government (http://data.gov.sg/).

(03) Birth=Population/100*Birth rate Units: persons per year (04) Birth rate=RANDOM UNIFORM( 0.0085, 0.0128, 8) Units: Dmnl This estimate is obtained from Singapore Department of Statistics (http://www.singstat.gov.sg/stats/keyind.html).

(05) Capacity increase per dollar invested in catchment expansions= RANDOM UNIFORM (0.1, 0.3, 6) Units: cubic meters per dollar [0,?] Based on Marina Reservoir and Punggol-Serangoon Reservoir.

(06) Capacity increase per dollar invested in desalination= RANDOM UNIFORM(0.1,0.2,5) Units: cubic meters per dollar [0,?] This is derived from Hyflux's 200million dollar project to build a desalination plant which could provide 5.11*10^7 cubic meters of water (http://www.pub.gov.sg/mpublications/Pages/PressReleases.aspx?Ite).

(07) Capacity increase per dollar invested in NEWater= RANDOM UNIFORM(0.5, 0.6,3) Units: cubic meters per dollar [0,5] This is based on the costs of the existing five NEWater plants in Singapore.

(08) Capacity increase per dollar invested in underground storage=0.00165 Units: cubic meters per dollar [0,?] This estimate is based on the Jurong Underground Rock Caverns Project.

(09) Construction time for a desalination plant= RANDOM UNIFORM( 1.5, 2.5, 1) Units: years [0,10]

40

http://data.gov.sg

http://data.gov.sg

http://www.singstat.gov.sg/stats/keyind.html


http://www.pub.gov.sg/mpublications/Pages/PressReleases.aspx?Ite

http://www.pub.gov.sg/mpublications/Pages/PressReleases.aspx?Ite

The two existing desalination plants in Singapore took about 1.5 to 2.5 years to complete construction.

(10) Construction time for NEWater plants=RANDOM UNIFORM(1,2,3) Units: years [0,10] Based on existing five NEWater plants in Singapore.

(11) Construction time for underground storage=RANDOM UNIFORM(4,6,1) Units: years [0,10] Based on Jurong Underground Rock Caverns Project in Singapore.

(12) Cost Index=Funding inflow/SingaporeWater Units: dollars per year/cubic meters per year [0,?] This indicator measures how much funding has been invested in order to generate one cubic meter of water in Singapore.

(13) Current desalination capacity= STEP(4.98e+07,2006)+STEP(-4.98e+07,2026)+STEP(1.1625e +08,2013)+STEP(-1.1625e+08,2038) Units: cubic meters per year [0,?] Data is obtained from PUB website (http://www.pub.gov.sg/water/Pages/DesalinatedWater.aspx). The second desalination plant will operate from 2013 to 2038.

(14) Current NEWater capacity=STEP(1.46e+07,2002)+STEP(-1.46e +07,2022)+STEP(1.655e+07,2006)+STEP(-1.655e +07,2026)+STEP(1.46+07,2005)+STEP(-1.46e+07,2009)+STEP(5.4e +07,2007)+STEP(-5.4e+07,2027)+STEP(8.32e+07,2010)+STEP(-8.32e +07,2035) Units: cubic meters per year [0,?] Data is obtained from PUB website (http://www.pub.gov.sg/water/newater/Pages/default.aspx). Assume that each plant has a life span of 20 years, if the commission period of the project is not available.

(15) Current reservoir capacity=1.5e+08 Units: cubic meters [1e+08,5e+08]

This is cited from P. O. Lee, "The Four Taps: Water Self-sufficiency in Singapore," in Management of Success: Singapore Revisited, T. Chong, Ed., ed Singapore: ISEAS Publishing, 2010, pp. 417-442.

(16) Current underground capacity=STEP(1e+07*5*0,2020) Units: cubic meters [0,1e+08]

Up to now, Singapore does not have underground rock caverns to store water.

41

http://www.pub.gov.sg/water/Pages/DesalinatedWater.aspx

http://www.pub.gov.sg/water/Pages/DesalinatedWater.aspx

http://www.pub.gov.sg/water/newater/Pages/default.aspx).Assume

http://www.pub.gov.sg/water/newater/Pages/default.aspx).Assume

(17) Death=Population/Life expectancy Units: persons per year

(18) Desalinated water= INTEG (Inflow from seawater-Water supply from desalination, 0) Units: cubic meters [0,?]

(19) Domestic consumption per capita per year=RANDOM UNIFORM( 140, 170,1 )*0.001*365 Units: cubic meters per person per year

Estimated based on data from K. C. Goh, "Water Supply in Singapore," Greener Management International, 2003.

(20) Excessive rainfall not stored in water catchments=IF THEN ELSE( Precipitation>Inflow, Precipitation-Inflow, 0) Units: cubic meters per year [0,?]

This assumes that all the extra rainfall not captured in the local water catchments will go to the underground rock caverns, if they are built in Singapore. And if the rock caverns are full, no extra rainfall could be collected.

(21) FINAL TIME = 2100 Units: Year The final time for the simulation.

(22) Funding allocation=Future funding in water sector Units: dollars per year (23) Funding inflow=IF THEN ELSE(Adequacy of water>=1,0, DELAY3(Singapore's GDP*Percentage of GDP to invest in the water sector,Time to respond to inadequacy of water)) Units: dollars per year [0,?] Assume that both the public and private sectors, such as PUB and private water companies, will only start to fund projects in the water sector when there is inadequacy of water in Singapore.

(24) Future funding in water sector= INTEG (STEP(Funding inflow-Processing funding for desalination-Processing funding for NEWater-Processing funding for local catchments-Processing funding for underground storage,2013),0) Units: dollars [0,?] (25) GDP per capita = INTEG (GDP per capita growth rate*GDP per capita, Initial GDP per capita in 2000) Units: dollars per year per person [0,?] This value is estimated based on the year-by-year growth rate in the past one decade. GDP per capita is at current price.

42

(26) GDP per capita growth rate=RANDOM UNIFORM( -0.04, 0.05,6) Units: Dmnl Based on data from Singapore Department of Statistics (http://www.singstat.gov.sg/stats/themes/economy/hist/gdp.html). This is the real growth rate, taking into account the impacts of inflations on purchasing power.

(27) "Gov. investment in local catchments"=DELAY3(Processing funding for local catchments,Time for local catchment expansion) Units: dollars per year (28) "Gov. investments in desalination"=Processing funding for desalination Units: dollars per year (29) "Gov. investments in NEWater"=Processing funding for NEWater Units: dollars per year (30) "Gov. investments in underground storage"=Processing funding for underground storage Units: dollars per year (31) Imported water= INTEG (Inflow from imports-Water supply from imports, 5.6575e+08) Units: cubic meters per year [0,?] (32) Inflow= INTEG (MIN((1-Percentage of rainfall lost)*Precipitation, Maximum capacity of local catchments-Water in local catchments), Maximum capacity of local catchments) Units: cubic meters per year [0,?] Rainfall could only be collected when there is spare capacity in the reservoirs.

(33) Inflow from imports=Maximum import capacity Units: cubic meters per year [0,?] Assume that Singapore is importing water from Johor at the maximum capacity, as stipulated by the water agreements between Singapore and Malaysia.

(34) Inflow from seawater=Maximum capacity of desalination plants Units: cubic meters per year [0,?] Assume all desalination plants are operating at full capacity during their lifespan.

(35) Inflow of excessive rainfall=IF THEN ELSE (Excessive rainfall not stored in water catchments>0,MIN(Excessive rainfall not stored in water

43

http://www.singstat.gov.sg/stats/themes/economy/hist/gdp.html


catchments,(Maximum capacity of underground storage-Water stored underground)),0) Units: cubic meters per year [0,?] (36) Initial GDP per capita in 2000=40974 Units: dollars per year [0,?] GDP per capita in year 2000, data is obtained from Singapore Department of Statistics (http://www.singstat.gov.sg/stats/themes/economy/hist/gdp.html).

(37) Initial population in 2000=4.0279e+06 Units: persons [0,?] Population in year 2000. Data is obtained from Singapore Department of Statistics.

(38) Initial rainfall in 2000=1.7e+09 Units: cubic meters per year [1e+09,3e+09] This is estimated based on the study of Seattle's annual rainfall volume (http://hypertextbook.com/facts/2006/GinaCastellano.shtml). As Singapore is in the tropical region with an average rainfall of 2400 mm and it is about 3 times larger than Seattle, the rainfall volume in Singapore is estimated to be 1.7e+09.

(39) INITIAL TIME = 2000 Units: Year The initial time for the simulation.

(40) Life expectancy=RANDOM UNIFORM(78,81,2) Units: Dmnl [70,100] From Singapore Department of Statistics (http://www.singstat.gov.sg/stats/keyind.html).

(41) Maximum capacity of desalination plants= Current desalination capacity+DELAY3(Capacity increase per dollar invested in desalination*"Gov. investments in desalination",Construction time for a desalination plant) Units: cubic meters per year [0,?] Assume that the increase in desalination capacity is gradual, instead of increasing sharply after a opening of a new desalination plant.

(42) Maximum capacity of local catchments= INTEG (MIN(Capacity increase per dollar invested in catchment expansions*"Gov. investment in local catchments", 1e+09-Maximum capacity of local catchments), Current reservoir capacity) Units: cubic meters per year [0,5e+08]

44



http://hypertextbook.com/facts/2006/GinaCastellano.shtml

http://hypertextbook.com/facts/2006/GinaCastellano.shtml



There is a limit to reservoir expansions, due to the limited land space Singapore has. It is assumed to be 1 billion cubic meters in this study. (43) Maximum capacity of NEWater plants= Current NEWater capacity+DELAY3(Capacity increase per dollar invested in NEWater*"Gov. investments in NEWater",Construction time for NEWater plants) Units: cubic meters per year [0,?] Assume that the increase in NEWater capacity is gradual, instead of increasing sharply after a opening of a new NEWater plant.

(44) Maximum capacity of underground storage= INTEG( MIN(DELAY3("Gov. investments in underground storage"*Capacity increase per dollar invested in underground storage, Construction time for underground storage),1e+08-Current underground capacity), Current underground capacity) Units: cubic meters per year [0,?] There is a limit to how many underground rock caverns could Singapore possibly build. We assume 100 million cubic meters in this study. (45) Maximum import capacity=STEP(-1.15e+06*365, 2061)+ 1.15e +06*365+400000*365+STEP(-400000*365,2011) Units: cubic meters per year [0,?] Data from the official agreements between Singapore and Malaysia. Cited from E. S. Chia, "A Large-Scale Systems Engineering Perspective of Water Management in Singapore," INCOSE, 2008.

(46) Naturalization of NEWater=NEWater*0.02 Units: cubic meters per year [0,?] A small amount of NEWater is naturalised in the reservoirs. Cited from Singapore Ministry of Environment and Water Resources, "Towards Environmental Sustainability," 2005.

(47) Net immigration=163000 Units: persons per year [0,500000] This is estimated based on the population pattern from 2000 to 2012. Net immigration is the number of immigrants minus the number of emigrants.

(48) NEWater= INTEG (Used water to be treated- Naturalization of NEWater -Water supply from NEWater, Current NEWater capacity) Units: cubic meters per year [0,?] (49) "Non-domestic consumption per capita per year"=RANDOM UNIFORM(150,210,1)*0.001*365 Units: cubic meters per person per year

45

(50) Other outflows=SingaporeWater*0.05 Units: cubic meters per year Unaccounted-water-flow is about 0.05 in Singapore. Cited from Ministry of Environment and Water Resources, "Towards Environmental Sustainability," ed. Singapore, 2005.

(51) Other outflows from local catchments=Water in local catchments*0.05 Units: cubic meters per year (52) Outflow to the sea=Used water-Used water to be treated Units: cubic meters per year (53) Percentage of GDP to invest in the water sector=RANDOM UNIFORM(0.005, 0.01, 5) Units: Dmnl Assume that investments worth 0.5% to 1% of GDP is invested into the water sector, be it government funding or private funding.

(54) Percentage of rainfall lost=RANDOM UNIFORM( 0.2, 0.4, 1 ) Units: Dmnl [0,1] Rainfall loss is mostly caused by interception by vegetation, infiltration into the soil, retention on the surface etc.

(55) Percentage of reservoir water treated=RANDOM UNIFORM( 0.8, 0.9,1) Units: Dmnl [0,1]

(56) Percentage of used water treated=0.8 Units: Dmnl [0,1] (57) Population= INTEG (Birth-Death+Net immigration, Initial population in 2000) Units: persons per year [0,?] This is an important variable with great impact in water demand and economic growth in the future.

(58) Precipitation= INTEG (Precipitation*Average rainfall increase rate, Initial rainfall in 2000) Units: cubic meters per year (59) Processing funding for desalination= Funding allocation*0 Units: dollars per year Plan 1 is that no funding will go into the water sector.

(60) Processing funding for local catchments= Funding allocation*0 Units: dollars per year

46

Plan 1 is that no funding will go into the water sector.

(61) Processing funding for NEWater= Funding allocation*0 Units: dollars per year Plan 1 is that no funding will go into the water sector. (62) Processing funding for underground storage= Funding allocation*0 Units: dollars per year Plan 1 is that no funding will go into the water sector. (63) SAVEPER = 1 Units: Year [0,?] The frequency with which output is stored.

(64) "Self-sufficiency in water"=(SingaporeWater-Imported water)/Total water demand Units: Dmnl Total self-sufficiency of water is achieved when this index is >=1.

(65) Singapore's GDP=GDP per capita*Population Units: dollars per year

(66) SingaporeWater= INTEG (-Other outflows-Total water consumption+Water pumped up+Water supply from desalination+Water supply from imports+Water supply from NEWater+Water supply from catchments-Water surplus-Water exports to Malaysia,Water supply from imports+Water supply from catchments-Water exports to Malaysia)

Units: cubic meters per year [0,?] (67) Surface evaporation=Water in local catchments*RANDOM UNIFORM( 0.1 , 0.2 , 8) Units: cubic meters per year [0,?] Assume that about 10% to 20% of the water in local catchments are lost due to surface evaporation.

(68) Time for local catchment expansion=RANDOM UNIFORM(2, 5, 5) Units: years [0,?] Based on the construction time of Marina reservoir and Punggol-Serangoon reservoir.

(69) TIME STEP = 0.125 Units: Year [0,?] The time step for the simulation.

47

(70) Time to respond to inadequacy of water=1 Units: Year Assume that both the public and the private sector in Singapore is very efficient in responding to inadequacy of water.

(71) Total domestic demand=Population*Domestic consumption per capita per year Units: cubic meters per year (72) "Total non-domestic demand"="Non-domestic consumption per capita per year"*Population Units: cubic meters per year (73) Total water consumption=IF THEN ELSE( (SingaporeWater>Total water demand), Total water demand, SingaporeWater) Units: cubic meters per year [0,?] If there are enough water to meet the demand, then all the water demand is satisfied. Otherwise, Singapore could only consume whatever amount of water that is available in Singapore.

(74) Total water demand=Total domestic demand+"Total non-domestic demand" Units: cubic meters per year (75) Used water= INTEG (Total water consumption-Outflow to the sea-Used water to be treated, 5.08e+08) Units: cubic meters per year

(76) Used water to be treated=MIN(Used water*Percentage of used water treated, Maximum capacity of NEWater plants) Units: cubic meters per year [0,?] This is constrained by the actual capacity of the NEWater plants

(77) Water exports to Malaysia=Water supply from imports*0.12 Units: cubic meters per dollar [0,?] Up to 12% of the imported water has to be sent back to Johor as part of the agreement. Cited from K. C. Goh, "Water Supply in Singapore," Greener Management International, vol. 42, pp. 77-86, Summer 2003 2003.

(78) Water in local catchments= INTEG (Inflow+Naturalization of NEWater-Other outflows from local catchments-Surface evaporation-Water supply from catchments, Current reservoir capacity)

Units: cubic meters per year [0,?]

48

(79) Water pumped up= IF THEN ELSE(SingaporeWater>Total water demand, 0, MIN(Total water demand-SingaporeWater,Water stored underground)) Units: cubic meters per year [0,?] Assume that when there is a shortage of water, water stored underground will be pumped up.

(80) Water stored underground= INTEG (Inflow of excessive rainfall+Water surplus-Water pumped up, 0) Units: cubic meters per year [0,?]

(81) Water supply from catchments= Percentage of reservoir water treated*Water in local catchments Units: cubic meters per year [0,?] (82) Water supply from desalination=Desalinated water Units: cubic meters per year (83) Water supply from imports=Imported water Units: cubic meters per year (84) Water supply from NEWater=NEWater*0.98 Units: cubic meters per year

(85) Water surplus=IF THEN ELSE ((SingaporeWater-Total water demand)>=0,MIN(Maximum capacity of underground storage -Water stored underground,(SingaporeWater-Total water demand)),0) Units: cubic meters per year

49

Appendix D SD simulation results

(a)Population

20 M

15 M

10 M

5 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

pers

ons

per y

ear

Population : Scenario 1

(b)

Total water demand2 B

1.5 B

1 B

500 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Total water demand : Scenario 1

Fig. D.1 Growth of population and water demand under Scenario 1

50

(a)Water pumped up

600 M

450 M

300 M

150 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Water pumped up : Plan 2 Invest in underground

(b)

Adequacy of water4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

Adequacy of water : Plan 2 Invest in underground

Fig. D.2 Long-term impacts of investments in underground under Scenario 1

51

(c)Self-sufficiency in water

2

1.5

1

0.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Plan 2 Invest in underground (d)

Cost Index40

30

20

10

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear

Cost Index : Plan 2 Invest in underground

Fig. D.2 Long-term impacts of investments in underground under Scenario 1 (continued)

52

(a)Water supply from desalination

2 B

1.5 B

1 B

500 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Water supply from desalination : Plan 3 Invest in desalination

(b)Adequacy of water

4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

Adequacy of water : Plan 3 Invest in desalination

Fig. D.3 Long-term impacts of investments in seawater desalination under Scenario 1

53


4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Plan 3 Invest in desalination

(d) Cost Index

60

45

30

15

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear

Cost Index : Plan 3 Invest in desalination

Fig. D.3 Long-term impacts of investments in seawater desalination under Scenario 1 (continued)

54

(a)Water supply from NEWater

1 B

750 M

500 M

250 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Water supply from NEWater : Plan 4 Invest in NEWater (b)

Adequacy of water4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

Adequacy of water : Plan 4 Invest in NEWater

Fig. D.4 Long-term impacts of investments in NEWater under Scenario 1

55


2

1.5

1

0.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Plan 4 Invest in NEWater

(d)

Cost Index40

30

20

10

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear

Cost Index : Plan 4 Invest in NEWater

Fig. D.4 Long-term impacts of investments in NEWater under Scenario 1 (continued)

56

(a)Water supply from catchments

600 M

450 M

300 M

150 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Water supply from catchments : Plan 5 Invest in local water catchments

(b)

Adequacy of water4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

Adequacy of water : Plan 5 Invest in local water catchments

Fig. D.5 Long-term impacts of investments in local water catchments under Scenario 1

57


2

1.5

1

0.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Plan 5 Invest in local water catchments

(d)

Cost Index20

15

10

5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear

Cost Index : Plan 5 Invest in local water catchments

Fig. D.5 Long-term impacts of investments in local water catchments under Scenario 1 (continued)

58

(a)Population

6 M

5.5 M

5 M

4.5 M

4 M2000 2015 2030 2045 2060 2075 2090

Time (Year)

pers

ons

per y

ear


(b)

Total water demand800 M

700 M

600 M

500 M

400 M2000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r


Fig. D.6 Growth of population and water demand under Scenario 2

59


6

4.5

3

1.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

Adequacy of water : Plan 1 Status Quo

(b)


3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Plan 1 Status Quo

Fig. D.7 System responses under Scenario 2

60

(a)Water pumped up

400 M

300 M

200 M

100 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r


(b)

Adequacy of water6

4.5

3

1.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl



61


4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Plan 2 Invest in underground

(d)

Cost Index40

30

20

10

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear



62


2 B

1.5 B

1 B

500 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r


(b)

Adequacy of water6

4.5

3

1.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl



63


4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl


(d)

Cost Index40

30

20

10

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear



64


600 M

450 M

300 M

150 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Water supply from NEWater : Plan 4 Invest in NEWater

(b)

Adequacy of water6

4.5

3

1.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

Adequacy of water : Plan 4 Invest in NEWater


65


4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Plan 4 Invest in NEWater

(d)

Cost Index40

30

20

10

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear



66


600 M

450 M

300 M

150 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r


(b)

Adequacy of water6

4.5

3

1.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl



67


4

3

2

1

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl


(d)

Cost Index20

15

10

5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear



68

(a)Population

6 M

4.5 M

3 M

1.5 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

pers

ons

per y

ear


(b)

Total water demand800 M

600 M

400 M

200 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r


Fig. D.12 Decline of population and water demand under Scenario 3

69


10

7.5

5

2.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

Adequacy of water : Plan 1 Status Quo

(b)


6

4

2

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Plan 1 Status Quo

Fig. D.13 System responses under Scenario 3

70

(a)Water pumped up

60 M

45 M

30 M

15 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r


(b)

Adequacy of water10

7.5

5

2.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl



71


8

6

4

2

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl

"Self-sufficiency in water" : Plan 2 Invest in underground

(d)

Cost Index40

30

20

10

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear



72


400 M

300 M

200 M

100 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r


(b)

Adequacy of water10

7.5

5

2.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl



73


8

6

4

2

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl


(d)

Cost Index40

30

20

10

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear



74


400 M

300 M

200 M

100 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r

Water supply from NEWater : Plan 4 Invest in NEWater

(b)

Adequacy of water10

7.5

5

2.5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl



75


8

6

4

2

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl


(d)Cost Index

20

15

10

5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear



76


600 M

450 M

300 M

150 M

02000 2015 2030 2045 2060 2075 2090

Time (Year)

cubi

c m

eter

s pe

r yea

r


(b)

Adequacy of water20

15

10

5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl



77


20

15

10

5

02000 2015 2030 2045 2060 2075 2090

Time (Year)

Dm

nl


(d)

Cost Index40

30

20

10

02000 2015 2030 2045 2060 2075 2090

Time (Year)

dolla

rs p

er y

ear/c

ubic

met

ers

per y

ear



78

Appendix E AHP results

Table E.1 Weights of the criteria

Goal Adequacy Self-sufficiency Cost Weight vector

Adequacy 1 1 7 0.467

Self-sufficiency 1 1 7 0.467

Cost 1/7 1/7 1 0.067

λmax = 3 CI = 0 CR = 0

79

Table E.2 Weights of the alternatives under Scenario 1

Adequacy Plan 1 Plan 2 Plan 3 Plan 4 Plan 5 Weightvector

Plan 1 1 1/3 1/5 1/7 1/3 0.047

Plan 2 3 1 1/5 1/5 1/3 0.077

Plan 3 5 5 1 2 5 0.438

Plan 4 7 5 1/2 1 3 0.307

Plan 5 3 3 1/5 1/3 1 0.130

λmax= 5.28 CI = 0.07 CR = 0.063

Self-sufficiency

Plan 1 Plan 2 Plan 3 Plan 4 Plan 5 Weightvector

Plan 1 1 1/3 1/5 1/4 1/4 0.055

Plan 2 3 1 1/3 1/4 1/2 0.105

Plan 3 5 3 1 1 3 0.336

Plan 4 4 4 1 1 3 0.346

Plan 5 4 2 1/3 1/3 1 0.157

λmax= 5.16 CI = 0.04 CR = 0.036

Cost Plan 1 Plan 2 Plan 3 Plan 4 Plan 5 Weight vector

Plan 1 1 7 5 5 3 0.488

Plan 2 1/7 1 1/3 1/4 1/6 0.040

Plan 3 1/5 3 1 1/3 1/5 0.073

Plan 4 1/5 4 3 1 1/3 0.131

Plan 5 1/3 6 5 3 1 0.269

λmax= 5.28 CI = 0.07 CR = 0.063

80

Table E.3 Local and global weights under Scenario 1

Plan Adequacy (0.467)

Self-sufficiency

(0.467)

Cost(0.067)

Global weights

1 Status quo 0.047 0.055 0.488 0.080

2 Invest in underground 0.077 0.105 0.040 0.088

3 Invest in desalination 0.438 0.336 0.073 0.366

4 Invest in NEWater 0.307 0.346 0.131 0.314

5 Invest in local water catchments

0.130 0.157 0.269 0.152

81


Adequacy Plan 1 Plan 2 Plan 3 Plan 4 Plan 5 Weight vector

Plan 1 1 1/3 1/6 1/7 1/3 0.046

Plan 2 3 1 1/3 1/3 1/2 0.105

Plan 3 6 3 1 2 6 0.452

Plan 4 7 3 1/2 1 2 0.266

Plan 5 3 2 1/6 1/2 1 0.131

λmax= 5.20 CI = 0.05 CR = 0.045

Self-sufficiency

Plan 1 Plan 2 Plan 3 Plan 4 Plan 5 Weightvector

Plan 1 1 1/2 1/4 1/5 1/4 0.057

Plan 2 2 1 1/3 1/4 1/4 0.084

Plan 3 4 3 1 2 1 0.314

Plan 4 5 4 1/2 1 2 0.300

Plan 5 4 4 1 1/2 1 0.244

λmax= 5.20 CI = 0.05 CR = 0.045


Plan 1 1 8 5 4 4 0.510

Plan 2 1/8 1 1/3 1/4 1/6 0.038

Plan 3 1/5 3 1 1/2 1/5 0.076

Plan 4 1/4 4 2 1 1/3 0.120

Plan 5 1/4 6 5 3 1 0.256

λmax= 5.24 CI = 0.06 CR = 0.054

82



Self-sufficiency

(0.467)

Cost(0.067)

Global weights

1 Status quo 0.046 0.057 0.510 0.082





0.131 0.244 0.256 0.192

83


Adequacy Plan 1 Plan 2 Plan 3 Plan 4 Plan 5 Weight vector

Plan 1 1 1 1/3 1/2 1/6 0.067

Plan 2 1 1 1/3 1/3 1/6 0.063

Plan 3 3 3 1 2 1/5 0.182

Plan 4 2 3 1/2 1 1/5 0.127

Plan 5 6 6 5 5 1 0.560

λmax= 5.16 CI = 0.04 CR = 0.036

Self-sufficiency

Plan 1 Plan 2 Plan 3 Plan 4 Plan 5 Weight vector

Plan 1 1 1 1/3 1/2 1/6 0.068

Plan 2 1 1 1/3 1/2 1/6 0.068

Plan 3 3 3 1 2 1/5 0.184

Plan 4 2 2 1/2 1 1/5 0.116

Plan 5 6 6 5 5 1 0.563

λmax= 5.12 CI = 0.03 CR = 0.027


Plan 1 1 8 4 3 3 0.460

Plan 2 1/8 1 1/3 1/5 1/4 0.043

Plan 3 1/4 3 1 1/2 1/2 0.104

Plan 4 1/3 5 2 1 1/3 0.156

Plan 5 1/3 4 2 3 1 0.237

λmax= 5.20 CI = 0.05 CR = 0.045

84



Self-sufficiency

(0.467)

Cost(0.067)

Global weights

1 Status quo 0.067 0.068 0.460 0.094





0.560 0.563 0.237 0.540

85

Fig. E.1 Performance sensitivity under Scenario 2

Fig. E.2 Performance sensitivity under Scenario 3

86

Appendix F Trade-off analysis results

Table F.1 Average self-sufficiency index and cost index under Scenario 1

Plan 1 Status quo

Plan 2 Invest in

underground

Plan 3Invest in

desalination


Plan 5Invest in local

water catchments

Self-sufficiency Index

0 0.40 1.0 0.45 0.40

Cost Index 0 30 25 23 10


Plan 1 Status quo

Plan 2 Invest in

underground

Plan 3Invest in

desalination



water catchments


0 0.40 1.0 0.8 0.65

Cost Index 0 28 20 15 10


Plan 1 Status quo

Plan 2 Invest in

underground

Plan 3Invest in

desalination



water catchments


0 0.9 1.2 1.2 5

Cost Index 0 18 10 8 10

87

Fig. F.1 The efficient frontier under Scenario 2

Fig. F.2 The efficient frontier under Scenario 3

88

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