Integrated Evaluation of Hybrid Water Supply Systems Using a PROMETHEE–GAIA Approach
2. MCDA Methodology
- Multiple attribute utility theory essentially combines multiple objectives into a one-dimensional “multi-attribute” function, which can be a value function that is deterministic or a utility function that includes a measure of risk .
- Interactive techniques consist of alternating computation steps and dialogue in the decision making, where the decision maker brings a direct contribution towards the elaboration of a solution by intervening in the process and not just in the definition of the problem .
- Preference Measures (PM) evaluations,
- Weights, and
- Preference functions.
2.1. PROMETHEE Rankings
2.2. GAIA Plane
2.3. Sensitivity Analysis
3. Application of Methodology
3.1. Case Study
- Scenario 1: Centralized only—It represents the conventional water supply system based exclusively on supplying a treated potable supply using fresh water resources and is used as a reference to compare with the selected hybrid water supply scenarios evaluated in this study.
- Scenario 2: Centralized along with recycled water via third (separate) pipe—This scenario represents the present condition in the area. In this scenario, wastewater is collected at the development level and distributed through a dual reticulation system for toilet flushing and garden irrigation after treatment. The remaining water demand is met from the potable water supply.
- Scenario 3: Centralized supply combined with treated greywater—In this scenario, greywater is collected from bathroom and laundry use and used for garden irrigation and toilet flushing. Other demands are met via potable supply.
- Scenario 4: Centralized supply combined with rainwater harvesting—In this scenario, rain water is provided for the toilet, garden irrigation, and laundry use. Potable water is supplied for bathroom and kitchen use.
- Scenario 5: Centralized supply combined with stormwater harvesting—In this scenario, stormwater is provided for toilet and garden irrigation. Potable water is supplied for bathroom, laundry, and kitchen use.
- Scenario 6: Centralized supply combined with stormwater harvesting and treated grey water—In this scenario, both stormwater and greywater are provided for garden irrigation and toilet use. However, priority is given to greywater over stormwater as greywater occurs at the unit-block scale compared to stormwater, which occurs at precinct scale. Potable water is supplied for bathroom, laundry, and kitchen use.
- Scenario 7: Centralized supply combined with rainwater harvesting and recycled water via 3rd pipe—In this scenario, rainwater is provided for laundry use, garden irrigation, and toilet use, while recycled water is also used for garden irrigation and toilet use, and potable water is supplied for bathroom and kitchen use.
3.2. Evaluation Criteria
- Reduction in potable water demand from centralized WSS,
- Reduction of wastewater generation,
- Reduction of contaminant (Total Suspended Solids (TSS), Total Phosphorous (TP), Total Nitrogen (TN), Biochemical Oxygen Demand (BOD), and Chemical Oxygen Demand (COD)) concentration in wastewater,
- Reduction in stormwater flow,
- Reduction in contaminant (TSS, TP, TN, BOD, and COD) load in stormwater,
- Increased supply reliability of fit-for-purpose water. Supply reliability is defined as the percentage of average demand met from the combination of alternative water supply storages over the modeling period.
3.3. Data Input
- Evaluation matrix: This matrix includes m number of alternatives, n number of PMs, and (m × n) number of PM evaluations. Table 1 shows the evaluation matrix formulated. This table is based on the water and contaminant balance analysis output reported in Sapkota, Arora, Malano, Moglia, Sharma and Pamminger .
- Weights of PMs: Weights required were evaluated by conducting a questionnaire survey among 37 water professionals which included personnel from water utilities, private water consultancies, CSIRO, universities, environmental agencies, and the Australian Water Association. . Table 2 below presents the weight distribution between different subcriteria for various criteria. For internal consistency reliability of the calculated weights of different subcriteria, Cronbach’s alpha  was calculated and found to be within the acceptable range of 0.5–0.9 . Further, a weight sensitivity analysis was conducted in MCDA, as suggested by the study.
- Preference functions of PMs: Preference functions were determined by conducting a questionnaire survey among experts, representing water professionals from Victorian water utilities to determine the preference function . Usual preference function as shown in Figure 2 was used for this study. For this type of function, the decision maker has a strict preference for the alternative having the greatest value . This means that even if there is a very small difference in criterion value, an alternative with a higher value is selected.
4.1. PROMETHEE Rankings
4.2. GAIA Analysis
4.3. Sensitivity Analysis
- MCDA analysis shows that Scenario 5 (centralized system along with stormwater harvesting) is the most preferred scenario, with Scenario 7 (centralized system along with treated wastewater and rainwater tanks) is the second preference.
- The same analysis shows that Scenario 2 (centralized with treated waste water) is presented as the worst scenario in the study.
- GAIA analysis shows that Scenario 5 (centralized water supply system along with stormwater harvesting) is the best and Scenario 2 (centralized water supply system along with treated wastewater) is the worst
- Thus, MCDA and GAIA analyses provide similar results in terms of scenario ranking
- Potable water supply peak flow, stormwater peak flow, and wastewater contaminant concentration are found to be the most robust criteria in ranking the hybrid water supply scenarios
- Stormwater contaminant load is found to be the unstable criterion in ranking the scenarios.
Conflicts of Interest
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|Criteria||Sub Criteria||Sce 1||Sce 2||Sce 3||Sce 4||Sce 5||Sce 6||Sce 7|
|Potable water supply||Volume(ML/year)||1036||860||859||787||856||856||761|
|Sewage contaminants||TN (mg/L)||59.1||78.1||74.3||59.6||59.1||74.3||62.7|
|Potable water supply||Volume||0.47|
|Wastewater contaminants||Scenario 5|
|Potable water peak||Scenario 6|
|Wastewater volume||Scenario 6|
|Wastewater peak||Scenario 6|
|Supply reliability||Scenario 1|
|Potable water volume||Scenario 7|
|Stormwater peak||Scenario 7|
|Stormwater volume||Scenario 4|
|Preference Measures||Current Weight (%)||Minimum Weight (%)||Maximum Weight (%)||Range Difference (%)|
|Potable Water Supply Volume||9.09||0||9.42||9.42|
|Potable Water Supply Peak Flow||7.95||7.44||100||92.56|
|Wastewater Flow Volume||8.82||0||9.23||9.23|
|Wastewater Flow Peak||8.02||0||8.43||8.43|
|Stormwater Flow Volume||8.18||0||8.36||8.36|
|Stormwater Flow Peak||7.41||6.89||100||93.11|
|Wastewater TN Concentration||3.31||2.87||100||97.13|
|Wastewater TP Concentration||3.18||2.75||100||97.25|
|Wastewater TSS Concentration||2.99||2.55||100||97.45|
|Wastewater BOD Concentration||3.24||2.8||100||97.2|
|Wastewater COD Concentration||3.17||2.74||100||97.26|
|Stormwater TN Load||3.46||0||4.53||4.53|
|Stormwater TP Load||3.47||0||3.83||3.83|
|Stormwater TSS Load||3.35||0||4.42||4.42|
|Stormwater BOD Load||3.22||0||4.3||4.3|
|Stormwater COD Load||3.18||0||3.72||3.72|
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Sapkota, M.; Arora, M.; Malano, H.; Sharma, A.; Moglia, M. Integrated Evaluation of Hybrid Water Supply Systems Using a PROMETHEE–GAIA Approach. Water 2018, 10, 610. https://doi.org/10.3390/w10050610
Sapkota M, Arora M, Malano H, Sharma A, Moglia M. Integrated Evaluation of Hybrid Water Supply Systems Using a PROMETHEE–GAIA Approach. Water. 2018; 10(5):610. https://doi.org/10.3390/w10050610Chicago/Turabian Style
Sapkota, Mukta, Meenakshi Arora, Hector Malano, Ashok Sharma, and Magnus Moglia. 2018. "Integrated Evaluation of Hybrid Water Supply Systems Using a PROMETHEE–GAIA Approach" Water 10, no. 5: 610. https://doi.org/10.3390/w10050610