The potential of data exploration methods in identifying the relationship between short-period (daily) water consumption and meteorological factors

Piasecki Adam (), Pilarska Agnieszka and Golba Radosław
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Golba Radosław: Nicolaus Copernicus University in Toruń, Faculty of Earth Sciences and Spatial Management, Toruń, Poland

Bulletin of Geography. Socio-economic Series, 2021, vol. 54, issue 54, 113-122

Abstract: The purpose of the work was to identify the hidden relationship between water consumption and meteorological factors, using principal component analysis. In addition, clusters of similar days were identified based on relationships identified by k-means. The study was based on data from the city of Toruń (Poland). The analysis was based on daily data from 2014–2017 divided into three groups. Group I included data from the entire period, Group II- from warm half-years (April–September), and Group III-from cold half-years (January–March and October–December). For Groups I and II the extent of water consumption was explained by two principal components. PC1 includes variables that increase water consumption, and PC2 includes variables that lessen water demand. In Group III, water consumption was not linked to any component.

Keywords: PCA; k-means method; water consumption; meteorological factors; Toruń; Poland (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:buogeo:v:54:y:2021:i:54:p:113-122:n:5

DOI: 10.2478/bog-2021-0037

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