Indoor Household Water Consumption Data Generation Model by Use of Probability Distributions

Abstract

Abstract An indoor household water consumption data generation model is proposed by use of probability distributions of six different end-uses (shower, bath，toilet, tap, washing mashing, dishwasher) on a temporal scale of one hour. Based on the probability distributions of six residential indoor end-use events in terms of household size, daily event frequency, event occurrence time and water consumption volume recently developed, the precise daily water consumption in hour resolution can be analytically deduced without original dataset collected from water resource management department. Then, the quantitative relationships between household water usage and the influence factors affecting the residential water consumption: air temperature and water-saving consciousness are derived to modify the above data in order to make the results more consistent with the actual situation. Considering that the daily air temperature is closely related to the shower, bath, washing machine frequency, setting the 25℃ as the temperature threshold. At the meantime, residents’ awareness of water-saving has a significant effect on water resource conservation that the water flows from tap can be recycled utilized for flushing the toilet. Simulation results show that the data generated from the model have a strong consistency with real data demonstrating the effectiveness and merit of the proposed method.