Statistical interpretation of the daily variation of urban water consumption in Beijing, China

Abstract

The efficient planning and design of water networks, as well as the management and strategies of existing water supply systems, require accurate short-term water demand forecasts. In this study, a statistical model for the estimation of daily urban water consumption was developed. The model was applied to analyse and forecast the daily water consumption in the main district of Beijing, China, from 2006 to 2010. The model exhibited good performance with a coefficient of determination, R 2 , greater than 0.9 in both the calibration and validation periods. The results indicate that: (a) the 7-day moving average temperature is an efficient variable that can be used to depict water-use variation in a year; (b) a daily maximum temperature of 31.1°C and the occurrence of precipitation are two thresholds of water-use behaviour; and (c) the current day's water consumption has a strong correlation with the consumption of one, two and seven days ago.Key words daily urban water consumption; time series analysis; statistical regression; threshold model; Beijing, China Interprétation statistique de la variation quotidienne de la consommation d'eau en milieu urbain à Beijing (Chine) Résumé La planification efficace et la conception des réseaux d'eau, ainsi que la gestion et les stratégies des systémes d'approvisionnement en eau existants, nécessitent des prévisions de la demande en eau précises à court terme. Dans cette étude, un modéle statistique pour l'estimation de la consommation d'eau quotidienne urbaine a été élaboré. Le modéle a été appliqué pour analyser et prévoir la consommation d'eau quotidienne dans le quartier principal de Beijing en Chine, de 2006 à 2010. Le modéle présente de bonnes performances avec un coefficient de détermination R 2 supérieur à 0,9 à la fois pour les périodes d'étalonnage et de validation. Les résultats indiquent que (a) la moyenne mobile à 7 jours de la température est une variable efficace qui peut ètre utilisée pour représenter la variation de l'utilisation de l'eau sur une année; (b) une température maximale quotidienne de 31,1°C et la survenue de précipitations sont deux seuils de comportement de l'utilisation de l'eau, et (c) la consommation d'eau du jour courant a une forte corrélation avec la consommation d'eau, un, deux et sept jours plus tôt.

Assessment of the Water Footprint in Low-Income Urban Neighborhoods from Developing Countries: Case Study Fátima (Gamarra, Colombia)

“…Gregory and Di Leo [65] indicate that water management devices and conservation practices influence intrahousehold water use. The WF gray found in this research differs from findings in India and Nigeria, where water consumption is limited due to availability and supply [66], but lower compared with values from Hong Kong and Beijing, where there is a direct relationship between the Gross Domestic Product (GDP) and the increase on the base water use rate [67].…”

Comparing Meteorological Data Sets in the Evaluation of Climate Change Impact on Hydrological Indicators: A Case Study on a Mexican Basin

“…In the following step, hydrological model GR4J was calibrated (over the 1987-1993 period) and validated (over the 1995-2000 period) with the four meteorological data sets. Table 3 shows the performance of the hydrological simulations with several statistics: 1) the Nash Sutcliffe Efficiency Coefficient (NS) [33] which ranges from −∞ to 1, where 1 indicates a perfect match between simulated and observed discharge; 2) the Mean Absolute Percentage Error (MAPE) [34,35]; and 3) the Threshold statistics (TS), which is the number of data points with an absolute relative error less than x% [36]. A smaller MAPE and larger TS indicate a good performance.…”