Influence of the number of residents and climatic factors on residential water consumption

Abstract

Water scarcity is becoming increasingly noticeable in large urban centers. Therefore, the aim of this research is to analyze the factors that influence residential water consumption in a residential building located in the city of Goiânia, Brazil, during a pre-pandemic period of 6 months. To this end, graphical analysis, trend curves, and multiple regressions were used using the R language. The sample consisted of 43 housing units with a population of one to five people in each. Once the construction aspects of the building were fixed and the water price and the type of consumption measured, it was found that the number of residents, the monthly precipitation, and the maximum daily temperature directly influence residential water consumption.

Prediction of Daily Water Consumption in Residential Areas Based on Meteorologic Conditions—Applying Gradient Boosting Regression Tree Algorithm

“…Moreover, they have discerningly established water consumption quotas for diverse residential typologies. In a separate scholarly endeavor, Reis et al [34] have dissected the determinants impacting residential water usage within a residential complex located in Goiânia, Brazil, thereby gaining comprehensive insights into residents' water consumption patterns.…”

“…Chen [32] has ingeniously employed an adaptive Markov chain Monte Carlo simulation approach to derive posterior density estimates pertaining to daily water consumption, thereby yielding probabilistic forecasts. Concurrently, Reis [34] has adroitly leveraged the R programming language to undertake graphical analysis, trend curve fitting, and multivariate regression analysis, thereby shedding light upon the multifaceted factors that influence residential water consumption.…”