Barua, Suchana (2018) Non-residential Urban Water Demand Modelling – a Disaggregation Approach. PhD thesis, Victoria University.

Abstract

Rapid population growth over the 20th century and changing climate has put many urban water supply systems under pressure around the world. Such pressure also exerted on most of the Australian water supply systems, which has led to the introduction of water use restrictions to ensure environmentally sustainable water supply. To operate cost effective and reliable urban water supply systems, analysing urban water use and forecasting future water demand is an essential task. Generally, the urban water use classified as residential and non-residential water use based on different activities. In Melbourne (Australia), water authorities have used end-use models to forecast water demand, in which the residential component is extensively modelled. In these end-use models, the total household water use is broken down to the end-use level (e.g. toilets, showers, washing machines, etc.) for forecasting water demand in the residential sector. However, a simple historical trend-based annual water demand is considered for the non-residential sector, as a whole. No temporal (i.e. quarterly or monthly) and spatial disaggregation were considered in the non-residential water demand forecasts in these end-use models. It was also found that the existing work around the world on water demand modelling mainly focused on residential water use modelling. However, a significant portion of urban water usage is nonresidential. For example, around 25% of the total water use in Melbourne is used by the non-residential sector. Therefore, the modelling of non-residential urban water use has significant importance for effective water supply system in any urban area. Considering this knowledge gap for effective urban water supply, this project aims to forecast short term (i.e. month to year) non-residential water demand which is useful for system operation as well as budgeting and financial management. To achieve this aim, the water use billing data for each non-residential customer located in the Yarra Valley Water service area (in Melbourne, Australia) were used for developing non-residential water demand models in this research. All customers were disaggregated into several groups based on the homogenous water activity such as Schools, Sports Grounds, Councils, Restaurants, Hospitals, Hotels, and Laundries. The high water users (>50 ML/year) were also considered as a separate group in this study named as High Water Users. All customers in the homogenous groups were further divided into smaller groups based on the annual water use (>20 ML, >15-20 ML, >10-15 ML, 5-10 ML, and <5 ML). Data analysis was then carried out for each of these user groups to identify the water use pattern. Data analysis showed that there were some seasonal effects on Schools, Sports Grounds and Councils. Therefore, water use among these groups was modelled using the Multiple Linear Regression (MLR) technique with the available climatic variable and water restrictions data. In the remaining groups no seasonal variations were identified during data analysis. Moreover, most of their water uses are for indoor purposes and therefore, water use modelling was carried out for these remaining groups with the past water use data only due to unavailability of data for other influential factors. All forecasting models developed in this research were validated with the observed data and the model performance was measured with the Nash-Sutcliffe efficiency criteria. Results showed that most of these developed models performed well except for few cases. Some issues and challenges were also identified during models development among the homogenous groups in non-residential sectors. All these issues and challenges are listed in this thesis for future research. The major innovation of this study was the development of the disaggregation approach for sector based non-residential water demand modelling. This approach is successfully demonstrated in this research by disaggregating customers based on their activity and their annual water use. The development of non-residential water demand models at individual customer level is also the knowledge advancement, as limited work was found in this area.

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