A Methodology to Model Water Demand based on the Identification of Homogenous Client Segments. Application to the City of Barcelona

Fontdecaba, Sara; Cintas, Pere Grima; Marco, Lluis; Rodero, Lourdes; Sánchez-Espigares, José A.; Solé, Ignasi; Tort‐Martorell, Xavier; Demessence, Dominique; Pablo, Victor Martínez De; Zubelzu, Jordi

doi:10.1007/s11269-011-9928-5

Cited by 10 publications

(5 citation statements)

References 25 publications

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“…Behavioural tracking (also referred to as individual-centred mapping), a technique of observing and recording people's temporal actions and behaviours in a particular setting using a variety of both heuristic and technology-based techniques, is predominantly used in the fields of environmental psychology, as a means of identifying locational or temporal patterns of people's behaviours (Ng, 2016). While many behaviour capture and modelling methods, such as surveys, observation and diaries, have been used in many studies (Cameron and Wright, 1990;Magiera et al, 2018;Spinks et al, 2011;Wutich, 2009), technology such as IoT and sensing (Yang et al, 2017;Waterwise, 2016), and techniques such as clustering (Fontdecaba et al, 2012;Jorge et al, 2015) referred to as "infrastructure mediated sensing" (Kim et al, 2012) -that can detect when fixtures and appliances are turned on and off in the house.…”

Section: Water Consumption Behavioural Tracking Through Technologymentioning

confidence: 99%

A review of household water demand management and consumption measurement

Abu-Bakar

Williams

Hallett

2021

Journal of Cleaner Production

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Section: Water Consumption Behavioural Tracking Through Technologymentioning

confidence: 99%

A review of household water demand management and consumption measurement

Abu-Bakar

Williams

Hallett

2021

Journal of Cleaner Production

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“…IOP Publishing doi:10.1088/1755-1315/1143/1/012008 4 factors influence water demand including socioeconomic variables such as population density, population growth, water price and area development or called land use covered. [1].…”

Section: Project Areamentioning

confidence: 99%

“…Water demand estimation involves four main sectors namely 1) domestic/residential, 2) livestock, 3) industrial and 4) agriculture. Many factors influence water demand including socioeconomic variables such as population density, water price and area development [1]. The availability and reliability of secondary data need to be collected through engagement with relevant agencies.…”

Section: Introductionmentioning

confidence: 99%

Analyzation of water demand projection for Johor River Basin

Yani

Hussien

Noor

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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This paper presents the projecting or forecasting of water demand for the Johor River Basin (JRB) from the year 2020 up to 2050. The aim for this research is to quantify and analyse the demand for water in the future from each sector which is most crucial around JRB such as domestic/residential, industrial, agriculture, livestock and non-revenue water; it is a key element for water demand quantification for JRB. Recent work for this quantification is more generalizing in terms of water demand as a whole in Johor state. Meanwhile, this research are using composite approaches which involve secondary data from various local authorities and involved four different districts only around JRB. This research also covers the scope of water consumption baseline data and information of JRB with the recent report. It appears that quality of data in terms of availability and reliability is very important and must be dealt with carefully, with good judgement and good engagement with local stakeholders or authorities when it comes to decision making, therefore must be able to get a rapid and simple understanding of water demand for JRB. It is significant to this research which to accommodate with United Nations Development Program and also promote greater awareness of the Sustainable Development Goal (SDG-6) which to ensure availability and sustainable management of water and sanitation for all.

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“…In order to ensure that the sample structure was as robust as possible, the property sample structure was designed by taking into account all major factors that were known to influence household water consumption. In the Barcelona area, clients can be grouped into segments (six segments) with homogeneous consumer habits, which are known to be related to socioeconomic status (Fontdecaba et al [2012]). That was the reason behind considering the variability between households as an important source to consider when designing the sample; accordingly, we wanted to guarantee that households from all 6 segments were included.…”

Section: Data Sourcesmentioning

confidence: 99%

“…Many efforts have been made to understand the factors and behaviors that cause high variations in per capita water consumption among various regions, cities and people. With this in mind, Aigües de Barcelona conducted a study (Fontdecaba et al [2012]) to compare the consumption of clients within homogeneous socioeconomic groups. One significant application of this project was higher accuracy in forecasting future water demand.…”

Section: Introductionmentioning

confidence: 99%

Contributions to industrial statistics

Fontdecaba Rigat

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This thesis is about statistics' contributions to industry. It is an article compendium comprising four articles divided in two blocks: (i) two contributions for a water supply company, and (ii) significance of the effects in Design of Experiments. In the first block, great emphasis is placed on how the research design and statistics can be applied to various real problems that a water company raises and it aims to convince water management companies that statistics can be very useful to improve their services. The article "A methodology to model water demand based on the identification of homogeneous client segments. Application to the city of Barcelona", makes a comprehensive review of all the steps carried out for developing a mathematical model to forecast future water demand. It pays attention on how to know more about the influence of socioeconomic factors on customer's consumption in order to detect segments of customers with homogenous habits to objectively explain the behavior of the demand. The second article -related to water demand management, "An Approach to disaggregating total household water consumption into major end-uses" describes the procedure to assign water consumption to microcomponents (taps, showers, cisterns, washer machines and dishwashers) on the basis of the readings of water consumption of the water meter. The main idea to accomplish this is, to determine which of the devices has caused the consumption, to treat the consumption of each device as a stochastic process. In the second block of the thesis, a better way to judge the significance of effects in unreplicated factorial experiments is described. The article "Proposal of a Single Critical Value for the Lenth Method" analyzes the many analytical procedures that have been proposed for identifying significant effects in not replicated two level factorial designs. Many of them are based on the original "Lenth Method and explain and try to overcome the problems that it presents". The article proposes a new strategy to choose the critical values to better differentiate the inert from the active factors. The last article "Analysing DOE with Statistical Software Packages: Controversies and Proposals" review the most important and commonly used in industry statistical software with DOE capabilities: JMP, Minitab, SigmaXL, StatGraphics and Statistica and evaluates how well they resolve the problem of analyzing the significance of effects in unreplicated factorial designs

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A Methodology to Model Water Demand based on the Identification of Homogenous Client Segments. Application to the City of Barcelona

Cited by 10 publications

References 25 publications

A review of household water demand management and consumption measurement

A review of household water demand management and consumption measurement

Analyzation of water demand projection for Johor River Basin

Contributions to industrial statistics

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