A stochastic model for identifying the long term dynamics of indoor household water uses
Date
2008
Authors
Cui, L.
Thyer, M.
Coombes, P.
Kuczera, G.
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Conference paper
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Proceedings of Water Down Under 2008: incorporating 31st Hydrology and Water Resources Symposium and 4th International Conference on Water Resources and Environment Research, 2008: pp.1-12
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Lijie Cui, Mark Thyer, Peter Coombes and George Kuczera
Conference Name
Water Down Under 2008 (2008 : Adelaide, South Australia)
Abstract
The emerging integrated water cycle management paradigm (IWCM) places a greater emphasis on demand-side management at the household/cluster scale than traditional design approaches for water cycle infrastructure. It is therefore important to understand the dynamics of household water uses at spatial and temporal scales smaller than those traditionally adopted for such design work. However, there exist very few models on residential indoor water demand analysis. This is the motivation for developing models that capture the dynamics of indoor household water use at smaller spatial and temporal scales. This study utilised data from Hunter Water Corporation (HWC) that consisted of 161 houses with measurements of monthly indoor water use over a period of 10 years. Temporal analysis of the HWC dataset indicates that the household occupancy is the most significant factor that influences household indoor water use; the household indoor water use possibly increases with income, whereas age does not indicate a strong influence. Statistical analysis of the HWC data showed that temporal shifts/cycles are a major source of variability in the household indoor water use. This study is attempted to develop an indoor water use model to identity the long-term dynamics of household occupancy. The household occupancy was categorized into several discrete states. The changes in state, modelled using a Markov process, are hypothesized to represent long-term or permanent changes in household occupancy – due to people moving in and/or out of the household. The proposed model is calibrated to the HWC dataset. The preliminary model diagnostics indicate that a reasonable fit was obtained for up to 98% of the households. Suitable drivers of the long-term dynamics and the short-term dynamics evident in the HWC dataset will be examined. The study will also investigate approaches to characterise the household heterogeneity and develop separate parameterisations of the short-term and long-term occupancy dynamics.
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Copyright 2008