Identifying the Relationships Between Urban Water Consumption and Weather Variables in Seoul, Korea

Abstract

As anthropogenic climate change threatens the reliability of urban water supplies, it is essential to build understanding of the relationships between weather and water consumption. We used daily and monthly data from 2002 to 2007 to conduct a statistical analysis of how seasonal water use in Seoul, South Korea is affected by weather variables. The Pearson, Kendall, and Spearman tests indicated that all weather variables were significantly correlated with per capita water use at most timescales, with mean, minimum, and maximum temperatures and daylight length positively correlated, and precipitation, wind speed, relative humidity, and cloud cover showing an inverse relation with water use. Once the influence of maximum temperature is controlled, water consumption is only significantly associated with wind speed and daylight length, as indicated by the partial correlation coefficient values. Ordinary least square (OLS) regression models explain between 39 and 61% of the variance in seasonal water use, indicating that approximately one-third to two-thirds of the variation is due to weather variables alone. Daily water consumption in July increases up to 4 liters per person with a one degree increase in maximum temperature. Significant improvement of the modeling of seasonal water use was achieved by developing autoregressive integrated moving average (ARIMA) models, which account for autocorrelation in the time series and explain up to 66% of the variance in water use. Our results indicate that weather plays a significant role in determining water consumption in Seoul, and that has important implications for management of urban water resources under potential future climate change.

Keywords:

• temperature
• wind speed
• water consumption
• regression
• ARIMA
• Seoul