A multi-criteria decision making approach to balance water supply-demand strategies in water supply systems

Cambrainha, Géssica Maria; Fontana, Marcele Elisa

doi:10.1590/0103-6513.20170062

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Research Article • Prod. 28 • 2018 • https://doi.org/10.1590/0103-6513.20170062 copy

A multi-criteria decision making approach to balance water supply-demand strategies in water supply systems

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Paper aims

this paper proposes a model to aid a group of decision makers to establish a portfolio of feasible actions (alternatives) that are able to balance water supply-demand strategies.

Originality

Long periods of water shortages cause problems in semi-arid region of northeast Brazil, which affects different sectors such as food, public health, among others. This problem situation is intensified by population growth. Therefore, this type of decision making is complex, and it needs to be solving by a structured model.

Research method

The model is based on a problem structuring method (PSM) and a multi-criteria decision making (MCDM) method.

Main findings

Due to society and government influences, the proposed model showed appropriate to conduct a robust and well-structured decision making.

Implications for theory and practice

The main contributions were the study in regions suffering from drought and water scarcity, as well as the combination of PSM and MCDM methods to aid in this problem.

Keywords
Group decision making; Water Supply Systems Plan; Strategic Options Development and Analysis (SODA); PROMETHEE V Method

Authors (year)	Main problem	Method	Criteria
Chung & Lee (2009)Chung, E. S., & Lee, K. S. (2009). Prioritization of water management for sustain- ability using hydrologic simulation model and multicriteria decision making techniques. Journal of Environmental Management, 90(3), 1502-1511. https://doi.org/10.1016/j.jenvman.2008.10.008. https://doi.org/10.1016/j.jenvman.2008.1...	Prioritization of water management	Analytic Hierarchy Process (AHP)	Five criteria: Driver, Pressure, State, Impact, and Response. Sub criteria were defined in two classes: water quantity and water quality.
Garfí & Ferrer-Martí (2011)Garfí, M., & Ferrer-Martí, L. (2011). Decision-making criteria and indicators for water and sanitation projects in developing countries. Water Science and Technology, 64(1), 83-101. PMid:22053462. http://dx.doi.org/10.2166/wst.2011.543. http://dx.doi.org/10.2166/wst.2011.543...	Water and sanitation projects evaluation	Do not use	They were classified in 4 main groups: technical (e.g. local resources use, appropriate management); social (e.g. local community participation, overcoming discrimination of conflict); economic (e.g. low cost, employment of local staff) and environmental criteria (e.g. atmospheric emissions, water pollution).
Garfí et al. (2011)Garfí, M., Ferrer-Martí, L., Bonoli, A., & Tondelli, S. (2011). Multi-criteria analysis for improving strategic environmental assessment of water programmes. A case study in semi-arid region of Brazil. Journal of Environmental Management, 92(3), 665-675. PMid:21035244. http://dx.doi.org/10.1016/j.jenvman.2010.10.007. http://dx.doi.org/10.1016/j.jenvman.2010...	Environmental assessment of water programmes	AHP	They selected two main criteria: (1) General criteria for human development projects (technical, social, environmental and economic criteria - 11 sub criteria) and (2) Technical water supply criteria (12 sub criteria).
Fontana & Morais (2013)Fontana, M. E., & Morais, D. C. (2013). Using Promethee V to select alternatives so as to rehabilitate water supply network with detected leaks. Water Resources Management, 27(11), 4021-4037. http://dx.doi.org/10.1007/s11269-013-0393-1. http://dx.doi.org/10.1007/s11269-013-039...	Network rehabilitation	PROMETHEE V	Amount of water loss, Implementation cost, Maintenance cost, Runtime, and Reliability time.
Kim et al. (2013)Kim, Y., Chung, E.-S., Jun, S.-M., & Kim, S. U. (2013). Prioritizing the best sites for treated wastewater instream use in an urban watershed using fuzzy TOPSIS. Resources, Conservation and Recycling, 73, 23-32. http://dx.doi.org/10.1016/j.resconrec.2012.12.009. http://dx.doi.org/10.1016/j.resconrec.20...	Wastewater	Fuzzy TOPSIS	Five criteria: Driver, Pressure, State, Impact, and Response. Sub criteria were defined in two classes: water quantity and water quality.
Matrosov et al. (2013b)Matrosov, E. S., Woods, A. M., & Harou, J. J. (2013b). Robust decision making and info-gap decision theory for water resource system planning. Journal of Hydrology, 494, 43-58. http://dx.doi.org/10.1016/j.jhydrol.2013.03.006. http://dx.doi.org/10.1016/j.jhydrol.2013...	Water resources planning	Robust Decision Making (RDM) and Info-Gap Decision Theory (IGDT)	Reliability of water supply service, Reservoir storage susceptibility, Environmental performance, Energy consumption, and Total costs.
Scholten et al. (2014)Scholten, L., Scheidegger, A., Reichert, P., Maurer, M., & Lienert, J. (2014). Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis. Water Research, 49(1), 124-143. PMid:24321248. http://dx.doi.org/10.1016/j.watres.2013.11.017. http://dx.doi.org/10.1016/j.watres.2013....	Network rehabilitation	Multi-attribute value model (MAVM)	Reliability, Intergenerational equity, and Cost
Azarnivand & Chitsaz (2015)Azarnivand, A., & Chitsaz, N. (2015). Adaptive policy responses to water shortage mitigation in the arid regions—a systematic approach based on eDPSIR, DEMATEL, and MCDA. Environmental Monitoring and Assessment, 187(2), 1-15. PMID: 25626561. http://dx.doi.org/10.1007/s10661-014-4225-4. http://dx.doi.org/10.1007/s10661-014-422...	Water shortage mitigation	AHP, eDPSIR and DEMATEL	Human population growth, Weak enforcement of law and legislation, Erosion, Declining available freshwater resources, Desertification and sand and dust storms, Salinization, Operational feasibility, and Multi-objectivity.
Fontana & Morais (2015)Fontana, M. E., & Morais, D. C. (2015). Segmentation model for water distribution networks based on the characteristics of consumer units. Production, 25(1), 143-156. http://dx.doi.org/10.1590/S0103-65132013005000071. http://dx.doi.org/10.1590/S0103-65132013...	Network segmentation	SMARTER	Amount of economies (number), Type of economies, Water consumed, and Price tax.
Scholten et al. (2015)Scholten, L., Schuwirth, N., Reichert, P., & Lienert, J. (2015). Tackling uncertainty in multi-criteria decision analysis - An application to water supply infrastructure planning. European Journal of Operational Research, 242(1), 243-260. https://doi.org/10.1016/j.ejor.2014.09.044. https://doi.org/10.1016/j.ejor.2014.09.0...	Water supply infrastructure planning	Multi-attribute utility theory (MAUT)	Five fundamental objectives: Intergenerational equity, Resources and groundwater protection, Water supply, Social acceptance, and Costs.
Fontana & Morais (2016)Fontana, M. E., & Morais, D. C. (2016). Decision model to control water losses in distribution networks. Production, 26(4), 688-697. http://dx.doi.org/10.1590/0103-6513.201815. http://dx.doi.org/10.1590/0103-6513.2018...	Water loss control	SMARTER and Integer linear programming (ILP)	Implementation cost, Efficiency, Runtime, Potential reduction in wastewater, Skilled labour to implement, and Lifetime.
Kumar et al. (2016)Kumar, V., Del Vasto-Terrientes, L., Valls, A., & Schuhmacher, M. (2016). Adaptation strategies for water supply management in a drought prone Mediterranean river basin: application of outranking method. The Science of the Total Environment, 540(1), 344-357. PMid:26277442. http://dx.doi.org/10.1016/j.scitotenv.2015.06.062. http://dx.doi.org/10.1016/j.scitotenv.20...	Water allocation	ELECTRE-III-H	Costs, Water stress, and Environmental impact
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Fontana & Morais (2017)Fontana, M. E., & Morais, D. C. (2017). Water distribution network segmentation based on group multi-criteria decision approach. Production, 27(0), e20162083. http://dx.doi.org/10.1590/0103-6513.208316. http://dx.doi.org/10.1590/0103-6513.2083...	Network segmentation	PROMETHEE GDSS	Implementation cost, Number of segments generated, Water consumed, Difficulty level in implementing and maintaining, Change in network pressure and/or water flow, Type of economies, and Infrastructure impact.
Ilaya-Ayza et al. (2017)Ilaya-Ayza, A. E., Benítez, J., Izquierdo, J., & Pérez-García, R. (2017). Multi-criteria optimization of supply schedules in intermittent water supply systems. Journal of Computational and Applied Mathematics, 309, 695-703. http://dx.doi.org/10.1016/j.cam.2016.05.009. http://dx.doi.org/10.1016/j.cam.2016.05....	Water supply schedule	AHP and ILP	Pressure, Number of users, Number of supply hours, and Ease of operation of the sectors.

Reservoir	Total capacity (m³)	in Jun 2015		in March 2017
Reservoir	Total capacity (m³)	Volume (m³)	Water catchment (m³/d)	Volume (m³)	Water catchment (m³/d)
Prata	42,147,000.00	26,028,278.54	60,480.00	6,919,513.91	4,5792.00
Jucazinho	327,045,336.00	23,232,108.30	93,312.00	0	0
Total	369,192,336.00	49,260,386.84	153,792.00	6,919,513.91	4,5792.00

Alternative	C₁ (millions - R$)	C₂ (months)	C₃ (nominal)	C₄ (percentage)	C₅ (nominal)	C₆ (m³/ second)
A₁₁	1,350.00	24	Very high	NO	Very complex	8.0
A₁₂	750.00	36	High	NO	Very complex	4.0
A₁₃	8.00	36	Very low	NO	Little complex	0.0
A₁₄	2.00	60	Low	NO	Moderately	0.0
A₂₁	1.50	2	Moderate	Low	Little complex	0.0
A₂₂	0.30	1	High	Moderate	Complex	0.0
A₂₃	1.20	60	Very high	Low	Moderately	0.0
A₂₄	5.00	60	Low	Very low	Complex	0.0
A₂₅	100.00	120	High	NO	Moderately	0.3
A₂₆	1.00	24	Moderate	NO	Moderately	0.0
Parameters	C₁	C₂	C₃	C₄	C₅	C₆
Objective	Minimize	Minimize	Maximize	Maximize	Minimize	Maximize
Weight	0.20	0.05	0.25	0.20	0.1	0.2
Preference function	Level criterion	U-Shape criterion	Usual criterion	Usual criterion	Usual criterion	Usual criterion
Threshold	q = 0.5	q = 2.0	--	--	--	--
	p = 1.0	--	--	--	--	--

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