Statistical modeling of daily urban water consumption in Hong Kong: Trend, changing patterns, and forecast

Abstract

[1] This study attempted to address statistical properties and forecast of daily urban water consumption in Hong Kong from 1990 to 2007. A statistical model was formulated to differentiate the effects of five factors on water use, i.e., trend, seasonality, climatic regression, calendar effect, and autoregression. The postulate of the statistical model is that total water use is made up of base, seasonal, and calendrical water use. Daily urban water consumption in Hong Kong from 1990 to 2001 was modeled and the developed statistical model explains 83% of the variance with six factors: trend (8%), seasonality (27%), climatic regression (2%), day-of-the-week effect (17%), holiday effect (17%), and autoregression (12%). The model was further validated using an independent data set from 2002 to 2007, yielding a R 2 of 76%. The results indicated good performance of the developed statistical model in depicting the temporal variations of the urban water use in Hong Kong, offering an improved insight into urban utilization of water resources and acting as the theoretical support for effective urban water resource management in Hong Kong under the changing environment.

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

“…6(a), 84% of the daily estimates are within the error band ±3%, whereas 95% are within ±5%. , which is approximately 2.6 times greater than that of Hong Kong (Wong et al 2010). As previously mentioned, the base (12) indicates that the occurrence of precipitation is more sensitive than the occurrence of maximum temperature.…”

“…They also suggested that the day of the week affects base consumption and that seasonal water use is reduced due to precipitation. Wong et al (2010) analysed the daily water consumption of Hong Kong from 1 December 1990 to 31 January 2007. In the study, the holiday effect was introduced, including that of Chinese traditional holidays, and the contribution of each factor to the water consumption was analysed.…”

Intra-annual Distribution of Streamflow and Individual Impacts of Climate Change and Human Activities in the Dongijang River Basin, China

“…Due to the rapid social-economic development in the Pearl River Delta in the past decades, water demand has dramatically increased (Chen 2001;Wong et al 2010;Tu et al 2012). As a result in the 2000s, there has been a great imbalance between demand and supply of water resources in the dry season, even for a water-rich region.…”

Multiscale variability of streamflow changes in the Pearl River basin, China

“…Taking the Pearl River Delta (PRD) as an example, on less than 0.5% of the country's territory, the PRD region produces about 20% of the national GDP, attracts about 30% of foreign direct investment, and contributes about 40% of export (therefore called ''World Factory''); (2) the East River, one of the tributaries of the Pearl River, bears the heavy responsibility for the water supply for the large cities in the vicinity of the lower Pearl River basin such as Hong Kong, Macau, Shenzhen, Guangzhou. About 80% water supply of Hong Kong is from the East River basin (e.g., Wong et al 2010); (3) our previous researches indicated altered hydrological cycle and the seasonal shifts of precipitation changes were observed (Zhang et al 2009c, which has the potential to alter the spatio-temporal patterns of streamflow variations. In this sense, thorough investigation of statistical properties of seasonal streamflow variations will definitely shed light on theoretical and practical grounds of effective water resource management of the rivers in the humid regions, such as the Pearl River basin, China, in this study.…”