Estimating peak daily water demand under different climate change and vacation scenarios

Abstract

Extremes in drinking water demand are commonly quantified with a so called peaking factor, a probabilistic ratio expressing the daily water demand relative to its annual average corresponding with a once in ten year recurrence period. In this study, we present a modeling framework that allows one to quantify of the impact of climate change and variations in vacation absence on the peaking factor for specific geographic regions. The framework consists of a support vector regression model that simulates daily water demand as a function of meteorological parameters and vacation absence, coupled to an extreme value model that translates simulation results to a peaking factor. After initial model development, we simulated the effects of different climate change/vacation scenarios for 2050 on eight water supply areas in the Netherlands and Belgium. We found that on average there is a net increase in water demand of 0.8% in 2050 and a 6.5% increase in peak demand compared to the reference period.