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Corresponding Author

Heejun Chang

Abstract

The sensitivity of municipal water consumption to climate and weather variability is investigated for Portland’s water provider service area between 1960 and 2013. The relationship between detrended seasonal urban water use (the difference between total water use and base use) and weather and climate variables (precipitation, maximum temperature) is examined at daily, monthly, and seasonal scales using stepwise multiple regression and autoregressive integrated moving average (ARIMA) models. At a seasonal and a monthly timescales, interannual variation in maximum temperature is the most important predictor of seasonal water consumption per capita, explaining up to 48% of the variation in seasonal monthly water consumption in June and July. At a daily scale, one-day lagged seasonal water demand and maximum temperature are the variables that are significant in all the daily models. Together with day of the week and precipitation, these variables explained up to 87 % of the variation in seasonal daily water consumption in summer. ARIMA models that take into account temporal autocorrelation explain between 70 and 81% of daily seasonal water consumption in summer months. This study provides useful climate information to urban water resource managers for seasonal water consumption forecasting at multiple temporal scales. Our results demonstrate the sensitivity of seasonal urban water consumption to climate variables as the scale of analysis changes. Urban water managers can use such information to establish proactive seasonal water resource management plans under increasing pressure from potential climate change, as understanding of the climatic sensitivity of seasonal water consumption is necessary for responding to changes.

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