A Modelling Tool to Inform City Scale Integrated Water Cycle Management Plans

A modelling tool to inform city scale integrated water cycle management plans

Shiroma Maheepala1, Ashis Dey2 and Fareed Mirza1

1CSIRO, 37 Graham Road, Highett, Victoria 3190, Australia; [email protected]; [email protected]

2eWater, Innovation Centre, University Drive, Bruce, ACT 2617, Australia; [email protected]

Abstract Integrated Water Cycle Management (IWCM) is an alternative approach for the traditional management of urban water systems. In recent times, there has been an increased interest for incorporating IWCM principles into urban water systems planning. This is to maximise the productivity, liveability and resilience of urban areas. The first step of adopting IWCM principles is development of an IWCM Plan. However, development of an IWCM plan for a town or a city is a complex task. It requires identifying urban water management options that have the potential to contribute towards achieving IWCM principles, understanding their hydrological, water quality, economic, social and environmental implications, and evaluating them to identify the most effective options that have the potential to maximise IWCM objectives. There are multiple objectives to satisfy. Therefore, there can be many different ways to provide water services, but not all solutions can best meet the objectives. Identifying the most efficient options that can best meet a given set of objectives cannot be done manually. A modelling tool is essential to evaluate the options and identify trade-offs between them. The focus of this paper is to demonstrate the applicability of Source, a modelling tool specifically developed to address Integrated Water Resource Management in river basins, to inform the development of IWCM Plans in cities. Using a hypothetical case study, this paper has demonstrated how the Source model and its optimisation tool, Insight, can be used to identify efficient water sourcing options that can best meet a given set of objectives. The objectives considered in the study are aimed at minimising the total cost of supply and discharges to coastal receiving waters, while maximising the supply reliability.

Introduction Integrated Water Cycle Management (IWCM), known also as Total water cycle management or Integrated Urban Water Management), is an alternative approach for the traditional management of urban water systems. The key aim of the traditional water management is to provide safe and reliable water service while minimising financial cost of the service delivery. In contrast, the aim of IWCM is to maximise the contribution of urban water system to the productivity and liveability of urban areas, while minimising its impact on the natural environment (Maheepala, et al., 2010). This is primarily achieved by using resources more frugally and efficiently, and by generating less wastes and harmful emissions through resource recovery. In recent years, there has been an increased interest to incorporate IWCM principles (Burn et al., 2012) into urban water planning, and develop IWCM plans. Successfully implemented, IWCM plans have the potential to maximise supply security, improve quality of receiving water, increase infrastructure productivity, minimise carbon footprint, optimise the recovery of water, energy and nutrient resources, and maximise the benefits and value of water in the urban environment.

Development of an IWCM plan for any town or city is a complex task. It requires identifying urban water management options that have the potential to contribute towards achieving IWCM principles, understanding their hydrological, water quality, economic, social and environmental implications, and evaluating them to identify the most effective options that have the potential to

1 maximise IWCM objectives. There are multiple objectives to satisfy. Therefore, there can be many different ways to provide water services, but not all solutions can best meet the objectives. Identifying the most efficient options that can best meet a given set of objectives cannot be done manually. A modelling tool is essential to evaluate the options and identify trade-off between them. Understanding trade-offs associated with options is vital to inform the development of an IWCM plan. Given the need for considering total water cycle, the modelling tool should have the capacity to represent the dynamics of whole urban water system (i.e. supply, demand, stormwater, wastewater and receiving water), along with an ability to optimise multiple objectives that is often related to implications of urban water services on physical, economic, social and environmental domains.

The modelling tools capable of representing dynamics of total urban water cycle include Urban Developer (eWater, 2012a), Aquacycle (Mitchell et al., 2001), WaterCress model (Clark et al. 2002), Source (eWater, 2012b) and WEAP (Water Evaluation and Planning, Sieber and Purkey, 2011). Some are applicable at single lot and development (i.e. a number of single lots) scales, such as Urban Developer and Aquacycle, and some are applicable for basin and city scales such as WaterCress, Source and WEAP. Since the focus of this paper is city scale, this paper only looks at city scale tools. Some background analyses have been done in order to select the appropriate tool for this study. The initial observation has shown that tools like WaterCress, WEAP or Source would be more appropriate to achieve the goal of this study.

The WEAP model operates on the basic principle of a water balance. It can simulate a broad range of natural and engineered components of these systems, including rainfall runoff, base flow, and groundwater recharge, demand analyses, water conservation, water rights and allocation priorities, reservoir operations, hydropower generation, pollution tracking and water quality, vulnerability assessments, and ecosystem requirements. The WaterCress model has features similar to the WEAP model. It has been used widely in South Australia whereas the WEAP model has been used in many countries. The Source model is an Australian model, and is designed to simulate all aspects of water resource systems to support integrated planning, operations and governance from urban, catchment to river basin scales including human and ecological influences. Source accommodates diverse climatic, geographic, water policy and governance settings for both Australian and international climatic conditions. Source provides a consistent hydrological and water quality modelling and reporting framework to support transparent urban, catchment and river management decisions. Fundamental to this design is the flexibility which makes it readily customisable and easy to update as new science becomes available. New capabilities can be incorporated via plugins developed to suit particular needs while maintaining the overarching consistent decision and policy framework.

The strengths of the Source model over WEAP and WaterCress models are its flexibility and plug-in functionalities. While all three models can be dynamically linked with standalone optimisation tools (for example, Paton et al. (2014) linked WaterCress model with a multi-objective algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) (Deb, 2001), and Vonk et al. (2014) linked WEAP model with NSGA-II), the Source model has an added benefit with regard to optimisation, due to the existence of its customised optimisation tool, Insight (eWater, 2012). The Insight tool, also uses NSGA-II to provide multi-objective optimisation capability, and is fully compatible with the Source model, which makes it easier to use for optimisation purposes, in conjunction with a simulation model developed using the Source model, without spending time on linking aspects of the models. This is an important aspect to consider, particular for practitioners who may not have time and resources for linking models. The Source model has also been recognised as the national hydrologic modelling platform in Australia by the Australian Government. Considering all these benefits it has been decided that Source would be the tool of choice for this study.

However, most of Source applications to date are for river basin modelling to inform development of integrated water resource plans in river basins. Therefore, its abilities to inform IWCM plans in urban areas are not well known. The objective of this paper is to demonstrate the use of Source model and its companion optimisation tool Insight, to inform the identification of most efficient ways of providing water supply services, for a given city, in terms of a defined set of objectives. The objectives are aimed at providing a productive, environmentally sustainable and resilient city. It should be noted that identifying the most efficient ways of providing water supply services is a key attribute of an IWCM plan. Hence this study demonstrates the nature of analysis undertaken to inform a key attribute of an IWCM plan.

Case study A hypothetical case study has been designed to represent a coastal city with a current population of 2.5 million in a Mediterranean climate with hot summers and mild winters. Water supply for the city is considered to be currently sourced from two surface water reservoirs. Each reservoir has a capacity of 200 GL. The average annual demand of the city is assumed to be 344 GL (i.e. 377 L/person/day). At present, surface water is just adequate to meet water demand of the city. Wastewater and stormwater generated from the city is considered to be collected via two independent pipe networks and discharged to coastal waters, which is considered to be of high environmental and recreational value by the community living in the city. Wastewater is treated prior to discharging to coastal waters. However, stormwater is not treated.

The water demand of the city is expected to grow by about 60% (i.e. 550 GL) by the end of next 30 years. Given the capacity of two surface water reservoirs is limited to 400 GL, clearly, additional supply sources are required to meet the growth in demand. Seawater desalination is considered as a possible supply option. However, the institutions responsible for delivering water services to the city are not only interested in meeting the future water demand, but also, interested in identifying affordable solutions that could improve coastal water quality, by reducing the amount of stormwater and wastewater discharging to receiving waters. This is to provide a productive, sustainable and resilient water system. Hence there is a keen interest for investigating the possibility of diversifying water supply for fit-for-purpose use of water, by considering possible use of stormwater, treated wastewater (i.e. recycled water) and desalinated water, in addition to the current supply (i.e. surface water), and developing an evidence-based IWCM plan, built on the outcomes of such an investigation.

As part of developing an IWCM Plan, the following questions have been raised:

• How can the supply from water sources be optimised by considering fit-for-purpose use, infrastructure cost, supply reliability and discharge implications on coastal waters, for the water demand expected to occur during the next 30 years?

• What source will provide the maximum benefit in terms of infrastructure cost, reliability of supply and discharge implications on coastal waters, if the cost of supply from a source can be reduced by a defined amount, by investing in technological and operational advancements?

It should be noted that water utilities in most major cities and towns in Australia and the globe, interested in adopting IWCM principles to water management, are faced the challenge of addressing similar questions mentioned above. The methodology developed to address the above-mentioned questions is described below.

Methodology The methodology used is systems analysis, which is a widely used approach to inform water resources planning (Loucks et al., 1981; Loucks and van Beek, 2005). The particular systems analysis techniques used are simulation and multi-objective optimisation. These two techniques have been used both as standalone approaches and as a combined approach in the past, for water supply systems with multiple reservoirs to inform both long-term and operational planning (Labadie, 2004; Rani and Moreira, 2010; Mortarzavi et al., 2012; Paton et al, 2014). For this study, we have used a combined simulation and multi-objective optimisation approach.

The combined simulation and multi-objective optimisation involves formulating a multi-objective optimisation problem (i.e. formulating of objectives, constraints and decision variables), and evaluating the objectives for different combinations of decision variables using the information generated through a simulation model of the system being analysed. Dynamics of the system being simulated can be changed by assigning various values to the decision variables through optimisation. The advantage of using the combined simulation-optimisation approach is that it allows incorporating operation preferences of system components, any carry-over effects of water available in the system and the effect of climate change/variability on various system components such as water demand, stormwater runoff and surface water availability, in the optimisation. Consequently, solutions identified through a combined simulation-optimisation approach can be considered as a robust set of solutions (Savic, 2005; Mortarzavi et al., 2012; Paton et al, 2014).

North S North demand zone North Water Treatment Plant North Reservoir t

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f v r r o e m s Wastewater e R S o h t Treatment Plant u u t o Treated Wastewater discharge h S

R to e s w e o r l v f n o I South demand zone i r South Water Treatment Plant South Reservoir

Stormwater Treated wastewater Harvested South Aquifer Potable water Recycled water stormwater

South Surface water reservoir Stormwater harvesting Stormwater scheme

Harvesting S t Lumped aquifer storage o r South Stormwater Scheme 2 m Water treatment plant w S t Harvesting Scheme 1 a o t r e m rge r Potable demand Wastewater treatment plant discha i w water n Storm f a l t o e w r i n f l Non-potable demand Demand zone o w

Figure 1. Schematic diagram of the hypothetical case study

A schematic diagram of the water system being considered to apply the combined simulation- optimisation approach is shown in Figure 1. It comprises two surface water reservoirs: North Reservoir and South Reservoir (i.e. current supply sources), a desalination plant, four stormwater harvesting schemes and a wastewater treatment plant with an ability to produce recycled water. As shown in Figure 1, the city is considered to be comprised with two demand zones: North demand

4 zone and South demand zone. North and South demand zones contain 53% and 47% of the total demand, respectively. It is assumed that the city has two aquifer systems that have the potential for storing water. They are assumed to be located in North and South demand zones (refer to as North Aquifer and South Aquifer respectively, see Figure 1). Of the four potential stormwater harvesting schemes, two are assumed to be located in the North demand zone, whereas the other two potential schemes are assumed to be located in the South demand zone. Given the existence of aquifers, aquifer storage and recovery (ASR) is considered to be the most appropriate harvesting method for stormwater.

Table 1. Unit relative cost of supplying water from different sources

Source unit relative cost ($/ML) Desalination 1 Surface water from North reservoir 0.5 Surface water from South reservoir 0.5 Wastewater treatment for discharge 0.4 Additional wastewater treatment to produce recycled water 1 Stormwater from North Scheme 1 1 Stormwater from North Scheme 2 1 Stormwater from South Scheme 1 1 Stormwater from South Scheme 2 1

Optimisation component Considering the questions to be addressed, the multi-objective optimisation problem has been formulated with the following objectives:

• Minimise the total relative cost of supply

• Maximise the time reliability of system supply

• Minimise total discharge to coastal waters

Subject to the following preference order for utilisation of sources:

• For potable demands, utilise surface water prior to utilising desalinated water; and

• For non-potable demands, the order of preference is recycled water, stormwater, surface water, and desalinated water.

The objective related to the cost aims at minimising the total relative cost of supply. The relative cost of each source (in $/year) is determined by multiplying unit relative cost in $/ML (see Table 1) by the average annual supply over the planning period (in ML/year), which is determined by simulating the behaviour of the system shown in Figure 1. It should be noted that the unit relative costs in Table 1 are hypothetical values. The unit costs encompass the capital, operation and replacement costs of infrastructure required for capture, storage, treatment and distribution of water from a particular source. The assumed relative costs indicate that desalinated water, stormwater and recycled water are twice the cost of surface water.

The objective related to the time reliability of the system aims at minimising the frequency of not supplying water at a particular time-step, to both potable and non-potable uses. It is computed by dividing the number of time-steps during which the system demand is not fully met by the total number of time steps in the simulation.

The objective related to discharge aims at minimising the total discharge to coastal water. This is to protect the health of coastal ecosystems. The total discharge is the sum of stormwater and wastewater discharge and spills from surface water reservoirs (see Figure 1). The total discharge is computed as part of simulation. The optimisation problem is formulated with six decision variables (see Table 2).

The optimisation problem described above is implemented in the Insight model. As mentioned above, it uses the NSGA-II approach (Deb, 2001), to identify efficient solutions. A population size of 100 with 100 generations have been used to search for the efficient solutions that best fit the three objectives mentioned above.

Table 2. Decision variables

Decision variable Nature of the variable Range Capacity of the desalination plant continuous 0 – 100 GL/month Amount of treated wastewater that can be continuous 0 – 20 GL/month recycled Percent of stormwater captured and injected into continuous 0 – 1 North Scheme 1 Percent of stormwater captured and injected into continuous 0 – 1 North Scheme 2 Percent of stormwater captured and injected into continuous 0 – 1 South Scheme 1 Percent of stormwater captured and injected into continuous 0 – 1 South Scheme 2

Simulation component As described above, the objectives of the optimisation require the following information computed through simulating the system shown in Figure 1:

• The average annual volume of water supplied from each source;

• The average annual injection volumes for each harvesting scheme;

• The total stormwater and wastewater discharge to coastal water;

• The total volume of spill from surface water reservoirs; and

• The number of time periods during which the total system demand is not met.

The simulation component is implemented in the Source model. Representation of the water system shown in Figure 1 in the Source model, is shown in Figure 2. The simulation model represents the sources, demands and discharges as nodes and the infrastructure that connects them as links. The time-step of the simulation is considered as a month. The duration of the simulation is 50 years from

July 1963 to June 2013. The climate conditions occurred during the simulation period is assumed to be representative of the climatic conditions expected in 30 years. The total water demand of each zone is disaggregated into potable and non-potable demands (see Figure 1) to allow for fit-for- purpose supply. The potable demand comprises both residential and non-residential potable demands and the non-potable demand comprises both residential and non-residential non-potable demands. Of the total system demand, 41% is potable and 59% is non-potable (Table 3). The monthly variability assumed for the total demand is shown in Figure 3. Stormwater Wastewater and recycled water

Desalinated water

Surface water

Potable and non-potable demands

Figure 2. Representation of the water system shown in Figure 1 in the Source model

The surface water reservoirs have been modelled as finite capacity storages, using ‘storage node’ functionality available in the Source model (see Figure 2). A storage node receives inflow from an inflow node and makes releases to meet human consumption and environmental flow requirement. For the study reported in this paper, the environmental flow requirement is assumed to be met by spills from each reservoir. The average annual inflow to North and South reservoirs are 197 GL and 431 GL, respectively, whereas the average monthly flows to North and South reservoirs are 16.5 GL and 35.9 GL respectively.

Table 3. Percent of total demand in each demand zone and in potable and non-potable components

Demand zone Total demand = 550,297 ML/year Percent of Percent of potable demand in Percent of non-potable demand total demand each demand zone in each demand zone in each demand zone North Zone 0.22 0.31 0.53 South Zone 0.19 0.28 0.47 Percent of 0.41 0.59 potable/non-potable demand

Figure 3. Monthly variability of the total demand

The desalination plant has been modelled as an infinite capacity storage with no rainfall on or evaporation from the surface (see Figure 2). The capacity of the plant is represented by a maximum-

8 order-constraint node connected to the release link downstream of the storage node and its value is determined through the optimisation.

The modelling method developed to represent wastewater treatment plant (WWTP) has assumed that: (a) inflow to a WWTP at a particular simulation time-step (say, T) is treated fully during that time-step; (b) the treated wastewater produced in time-step T is available to use as recycled water, if there is a demand for recycled water in time-step T; and (c) the portion of treated wastewater not recycled in time-step T, above a set volume, is discharged to the environment, at the end of time- step T. This modelling method is represented in the Source model by using an inflow node to represent wastewater inflow, which is considered to be converted into treated wastewater instantaneously, a splitter node to split treated wastewater stream to recycled water and discharges to the environment, and a gauge node to represent the treated wastewater discharging to the environment (see Figure 2). The link representing recycled water stream is connected to a maximum-order-constraint node, which represents recycling capacity of the plant. The recycling capacity is controlled through optimisation. The maximum capacity is assumed to be 20 GL/month. A storage node is introduced between the inflow node and the splitter node to allow specifying the preference order of sources, which has been defined as part of formulating the optimisation component. The maximum-order-constraint node is connected to a second splitter node, which splits recycled water to non-potable demands in North and South demand zones (see Figure 2). The average annual inflow to the WWTP is 502 GL, and the average monthly inflow to the WWTP is 42 GL. Therefore, it should be noted that the maximum recycling capacity represents approximately 48% of the wastewater inflow.

Stormwater is represented as an inflow node (see Figure 2). There are four such inflow nodes to represent the four catchments considered in the study (i.e. two stormwater catchments in each demand zone). Capture of stormwater from each catchment has been modelled by using an extraction node and a demand node connected to the extraction node. The extraction and demand nodes represent the portion of the inflow captured and injected into the aquifer. The portion of inflow captured is controlled by the optimisation. The portion of inflow not captured, flows to the catchment located downstream of the scheme and ends up as discharge to coastal waters, unless the flow is captured by another scheme. In this study, North Stormwater Scheme 2 is located downstream of North Stormwater Scheme 1 (see Figure 1). Similarly, South Stormwater Scheme 2 is located downstream of South Stormwater Scheme 1 (see Figure 1). However, there is no interaction between the catchments in North and South demand zones. Extracted water, flows into an aquifer, which is represented by using a storage node. Supply from this storage represents supply of stormwater to demand zones. Spill from this storage is considered as captured runoff that cannot be injected due to insufficient pump capacity and hence that runoff is considered to be part of uncaptured stormwater, which ends up as a discharge to coastal waters. The supply capacity of each aquifer has been set to 20 GL/month, using a maximum-order-constraint node, located downstream of each aquifer. Storage capacity of each aquifer is assumed to be 20 GL. The average annual inflows to the potential stormwater harvesting schemes in North demand zone are 16 GL and 29 GL, respectively, whereas for the potential stormwater harvesting schemes in South demand zone are 59 GL and 8 GL, respectively. That is, the average annual total stormwater runoff from the case study area is 112 GL, of which 40% generated from the catchments in North demand zone and 60% generated from the catchments in South demand zone.

Results and discussion The combined simulation and optimisation approach implemented in the Source model and its optimisation tool, Insight, has been executed with the relative costs given in Table 1, to examine efficient supply options. To addresses the question: ‘how can the supply from water sources can be optimised by considering fit-for-purpose use, infrastructure cost, reliability of supply and discharge

9 implications on coastal waters, for the demand expected in 30 years?’, the following three scenarios have been considered:

• Scenario_1: comprises with surface water as the only supply source

• Scenario_2, comprises with surface and desalinated water as supply sources

• Scenario_3, comprises with surface, desalinated, stormwater and recycled water as supply sources

All three scenarios used the relative costs shown in Table 1. That is, desalinated water, stormwater and recycled water have the same unit cost and surface water is half the unit cost of these alternative sources.

The relative cost, discharge and supply reliability of scenario_1 are 238,554 $/year, 767.5 GL/year and 42% respectively (Table 4). Time-based supply reliability of 42% clearly indicates that surface water alone cannot meet the demand fully. The corresponding volumetric reliability is 87%, which indicates that the surface water is adequate to meet only 87% of the total demand over the 50-year simulation period.

Table 4. Solutions with 100% supply reliability for ‘SurW_DW’ and ‘All_sources’ scenarios

Scenario Solution ID Relative cost Total Supply Percent Percent $/year discharge reliability change in change in GL/year % cost discharge compared compared to the cost to the of discharge of Scenario_2 Scenario_2 Scenario_1 Scenario_1_1 238,554 767.5 42 Scenario_2 Scenario_2_1 420,809 789.3 100 0.0% 0.1% Scenario_2 Scenario_2_2 420,832 788.5 100 0.0% 0.0% Scenario_3 Scenario_3_1 430,362 692.5 100 2.3% -12.2% Scenario_3 Scenario_3_2 497,006 687.2 100 18.1% -12.9% Scenario_3 Scenario_3_3 465,885 690.0 100 10.7% -12.5% Scenario_3 Scenario_3_4 490,528 688.1 100 16.6% -12.7%

The efficient solutions (or Pareto solutions) corresponding to scenario_2 are shown in Figure 4 and

Figure 5. The Pareto solutions indicate that as the cost increases, supply reliability and discharge increases, too. This is because higher cost solutions have higher use of desalinated water, which provides higher supply reliability, but allows surface water reservoirs to spill more often, resulting in larger volumes of discharge to coastal waters. Of the 100 optimal solutions (because the population size is 100) shown in Figure 4 and

Figure 5, there are only two solutions with 100% supply reliability.

Figure 4. Optimal solutions for Scenario_1: tradeoffs between discharge and infrastructure cost

Figure 5. Optimal solutions for Scenario_1: tradeoffs between infrastructure cost and system reliability

Figure 6. Optimal solutions for Scenario_2: tradeoffs between discharge and infrastructure cost

Similarly, the Pareto solutions corresponding to scenario_2 are shown in

Figure 6 and Figure 7. Unlike for scenario_1, the Pareto solutions of Scenari_2 indicate a reduction in discharge and an increase in supply reliability with an increase in cost. This is because of higher utilisation of wastewater and stormwater in conjunction with surface water and desalinated water. For scenario_2, there are four solutions with 100% supply reliability.

The solutions with 100% supply reliability for scenario_2 and scenari_3 are listed in Table 4. If the acceptable supply reliability is 100%, all the solutions in Table 4 (except solution scenario_1_1) can be treated as acceptable solutions. They are all optimal solutions that satisfy 100% reliability criterion. Additional information must be defined to enable narrowing the search for a ‘preferred solution’. To demonstrate this process, discharge minimisation is considered as preferable over cost minimisation. This criterion allows selecting scenario_2_2 as the preferred solution for scenario_2, and scenario_3_2 as the preferred solution for scenario_3. These solutions are listed in Table 4 and Table 5.

Figure 7. Optimal solutions for Scenario_2: tradeoffs between infrastructure cost and system reliability

Table 5. Preferred solutions for scenario_2 and scenario_3

Solution ID Wastewater Desalinated Surface Storm Recycling Desalination Storm (%) water water water capacity capacity water (%) (%) (%) GL/yr GL/yr capture GL/yr Scenario_2_2 0 18 82 0 0 600 0 Scenario_3_2 33 0 60 7 240 0 42 19 from North; 23 from South

Using the preferred solutions listed in Table 5, the answer to the question on ‘how can the supply from water sources can be optimised by considering fit-for-purpose use, infrastructure cost, reliability of supply and discharge implications on coastal waters, for the demand expected in 30 years?’ can be answered as follows:

• If desalinated water is the only preferred source, and desalinated water is twice the cost of surface water, 100% supply reliability and maximum utilisation of surface water can be achieved by having a desalinated plant of capacity 600 GL/year (or 50 GL/month) (Table 5). However, this solution will not reduce stormwater and wastewater discharging to coastal waters; and

• If stormwater, recycled water and desalinated water are considered as alternatives to the surface water, and they all have the twice the cost surface water, 100% supply reliability and the highest reduction in discharge can be achieved with scenario_3_2 solution. This solution requires recycled water production capacity of 240 GL/year (or 20 GL/month) and harvesting of 42 GL/year of stormwater (19 GL/year (i.e. 43% of runoff) from the catchments located in North demand zone and 23 GL/year (i.e. 34% of runoff) from the catchments located in South demand zone). This solution will not require desalinated water.

Figure 8. Comparison of cost and discharge values of scenarios 3, 4, 5 and 6 with scenario 2

To answer the question on ‘what source will provide the maximum benefit in terms of infrastructure cost, reliability of supply and discharge implications on coastal waters, if the cost of supply from a source can be reduced by a defined amount (say, by 50%), by investing in technological and operational advancements?’, the following scenarios have been considered:

• Scenario_4, same as scenario_3, but reduce the cost of stormwater by 50%

• Scenario_5, same as scenario_3, but reduce the cost of recycled water by 50%

• Scenario_6, same as scenario_3, but reduce the cost of desalinated water by 50%

The Pareto solutions of each scenario have been found by executing Source and Insight models. The solution that has 100% supply reliability, the highest reduction in discharge volume and the highest reduction in cost, in each scenario has been compared with the cost and discharge of scenario_2 (see Figure 8). The results shown in Figure 8 indicate that if stormwater, recycled water and desalinated water are all considered as alternatives to the current supply, i.e. surface water, the maximum reduction in discharge expected is 12.9% of the discharge of scenario_2 (i.e. the scenario in which desalinated water is considered as the preferred alternative to meet the demand expected in next 30 years). Scenarios 3, 4, 5 and 6, each have at least one solution capable of achieving this maximum reduction in discharge. However, the costs of these solutions are different. The lowest cost solution is exhibited by scenario_5, which has implied that if there is an option to invest in one of the alternative sources to improve its operation and capital cost, the recycled water should be chosen. Utilisation of sources and infrastructure requirement are as same as those of solution scenario_3_2 (see Table 5), but the cost of this solution is 3.8% less than the cost of solution scenario_3_2.

Conclusions This hypothetical case study has demonstrated how the Source model and its optimisation tool, Insight, can be used to identify optimal water sourcing options that can best meet a given set of objectives. The objectives considered in the study are aimed at minimising the total cost of supply and discharges to coastal receiving waters, while maximising the supply reliability. Such objectives are commonly used when adopting Integrated Water Cycle Management principles for long-term planning of water systems in cities. The study has demonstrated how to identify optimal solutions

14 that satisfy a given set of objectives and how to examine trade-offs associated with each optimal solution, to identify a preferred solution. Using a concept of relative cost of supply, the case study has demonstrated that if all the alternative sources have the same supply cost and the supply cost is twice the cost of surface water and, if there is a need to reduce discharge to receiving waters, utilisation of stormwater and recycled water is preferable over desalinated water. While this is an expected outcome, the study has identified the amount of stormwater to be harvested and the amount of recycled water to be produced to maximise the utilisation of surface water, while minimising discharges to receiving waters and maximising supply reliability. Further, by examining trade-offs, the study has concluded that utilisation of recycled water will provide the best benefit in terms of cost, reliability of supply and discharge implications on coastal waters, if the relative cost of recycled water can be reduced by 50%, i.e. by making the cost of recycle water similar to cost of surface water. However, it should be noted that results presented in this paper are based on a hypothetical case study. Nevertheless, this study demonstrates how the Source model and its optimisation tool, Insight can be used to inform policy questions related to an IWCM plan in an urban area. In addition, the case study demonstrates how to utilise relative costs of infrastructure to provide insights to questions related to planning of urban water systems.

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