The Effect of Variations in Micro-components of Domestic Water Consumption Data on the Classification of Excessive Water Usage

Salleh, Nor Salyana Mohd; Rasmani, Khairul A.; Jamil, Nur Izzah

doi:10.1016/j.sbspro.2015.06.422

Cited by 5 publications

(4 citation statements)

References 7 publications

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“…While the majority of respondents engaged in laundry and dish washing, there were slightly lower participation rates (99.54% and 98.16%, respectively) compared to other activities. This could be attributed to variations in personal circumstances, such as the availability of washing facilities or the use of alternative methods [10,19]. This result highlighted the consistent participation in essential water-related activities such as drinking water, hygiene practices (teeth brushing, bathing, ablution, and hand washing), as well as household tasks (laundry, dish washing, cooking, and food washing).…”

Section: Hem Variables From Water Demand Surveymentioning

confidence: 86%

“…This result highlighted the consistent participation in essential water-related activities such as drinking water, hygiene practices (teeth brushing, bathing, ablution, and hand washing), as well as household tasks (laundry, dish washing, cooking, and food washing). The lower participation rates in activity like swimming may be influenced by many factors such as personal behavior, availability of resources, or specific demographic factors [10,19,20].…”

Section: Hem Variables From Water Demand Surveymentioning

confidence: 99%

“…The water usage pattern is often complex because it depends on the water source reliability, accessibility/ location and communities economic condition [10]. In the implementation, collecting community's water usage data was very challenging as the water demands were varied between individuals.…”

Section: Introductionmentioning

confidence: 99%

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Water usage pattern of peri-urban community in the river basin: analyzing crucial variables for human exposure model

Utami,

Yoga,

Geerling

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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The human exposure model (HEM) is an important tool to predict the amount of contaminants carried by water to the community. Proper input variables play a crucial role in running the HEM, which is often scarce, particularly in low- and middle-income countries like Indonesia. To overcome that problem, we conducted a water demand survey of 10 water-related activities in a peri-urban community of the Upper Citarum River Basin. The survey resulted in three main variables of the exposure model from those activities, i.e. frequency, volume, and duration. This study aims to analyze if the contaminant uptakes from the HEM output were significantly different between groups (i.e.: male and female groups, 18 – 65 y.o. and ≥ 65 y.o. groups) and which exposure routes and water-related activities contribute the most to the contaminant’s total uptake by using statistical and proportional analysis. The output of carbofuran deterministic modelling showed the average total uptake was 1.06.E+00 ng/kg/day. The statistical analysis revealed a significant difference between oral and dermal uptake, but there was no significant difference in total uptake between gender and age groups. After conducting the proportional analysis, it was found that oral uptake contributed almost 99% to the total uptake of carbofuran. The analysis also showed that drinking and cooking were two activities contributing the most to the total uptake. This study’s results are necessary for health risk assessment and HEM development, especially in the field of river basin management.

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Section: Hem Variables From Water Demand Surveymentioning

confidence: 86%

Section: Hem Variables From Water Demand Surveymentioning

confidence: 99%

See 1 more Smart Citation

Water usage pattern of peri-urban community in the river basin: analyzing crucial variables for human exposure model

Utami,

Yoga,

Geerling

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…At the household scale, WDDs represent domestic water demands and are primarily used to build descriptive and predictive models of water demand, estimate demand peak timing and magnitude to inform water network operations, and inform conservation campaigns and demand management interventions [43,44]. Finally, at end use scale, WDDs are used to improve our understanding of residential water consumption behaviors, develop disaggregation models to estimate the share of household water consumption of individual fixtures, develop customized water demand management strategies and billing reports, and overall increase customer engagement and help water utilities and customers promote efficient water usage [45,46]. In keeping with the different spatial and temporal scales considered in this study, this review includes both water consumption data retrieved with digital water meters and data measured with low resolution meters or retrieved from water bills [47][48][49].…”

mentioning

confidence: 99%

Urban Water Consumption at Multiple Spatial and Temporal Scales. A Review of Existing Datasets

Mauro

Cominola

Castelletti

et al. 2020

Water

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Over the last three decades, the increasing development of smart water meter trials and the rise of demand management has fostered the collection of water demand data at increasingly higher spatial and temporal resolutions. Counting these new datasets and more traditional aggregate water demand data, the literature is rich with heterogeneous urban water demand datasets. They are characterized by heterogeneous spatial scales—from urban districts, to households or individual water fixtures—and temporal sampling frequencies—from seasonal/monthly up to sub-daily (minutes or seconds). Motivated by the need of tracking the existing datasets in this rapidly evolving field of investigation, this manuscript is the first comprehensive review effort of the state-of-the-art urban water demand datasets. This paper contributes a review of 92 water demand datasets and 120 related peer-review publications compiled in the last 45 years. The reviewed datasets are classified and analyzed according to the following criteria: spatial scale, temporal scale, and dataset accessibility. This research effort builds an updated catalog of the existing water demand datasets to facilitate future research efforts end encourage the publication of open-access datasets in water demand modelling and management research.

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Open Datasets and IoT Sensors for Residential Water Demand Monitoring at the End-Use Level: A Pilot Study Site in Naples (Italy)

et al. 2022

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The Effect of Variations in Micro-components of Domestic Water Consumption Data on the Classification of Excessive Water Usage

Cited by 5 publications

References 7 publications

Water usage pattern of peri-urban community in the river basin: analyzing crucial variables for human exposure model

Water usage pattern of peri-urban community in the river basin: analyzing crucial variables for human exposure model

Urban Water Consumption at Multiple Spatial and Temporal Scales. A Review of Existing Datasets

Open Datasets and IoT Sensors for Residential Water Demand Monitoring at the End-Use Level: A Pilot Study Site in Naples (Italy)

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