Idenitfying the Influential Factors of the Temporal Variation of Water Consumption : A Case Study using Multiple Linear Regression Analysis

Sammanfattning: This thesis is a part of the water development project conducted by Svenskt Vatten, which is the Swedish Water and Wastewater Association (SWWA) as well as Tyréns, a consultancy company with offices based in Stockholm, Sweden. Prior to this thesis work, a quality assessment was conducted for some of the locations provided by municipalities in Sweden. This thesis builds upon the revised water consumption data, and also continues to work with validating and modifying the water measurement data in order to proceed with the next step of the water development project, which is to identify any trends in the temporal variation of water consumption. The main objective of this thesis work is to investigate the influence of climatic, time-related and categorical factors on water consumption data collected for different regions in Sweden, and includes a number of different sectors such as residential, industrial and agricultural water user sectors. For the analysis of data, spectral analysis and sinusoidal modelling will be applied in order to find the periodicity of the data, and then simulate the fitted sinusoidal equation to the observed water consumption data for the hourly interval period. Multiple linear regression analysis is then used to assess what independent variables such as climate, time-related and categorical variables can explain the variation in water consumption over hourly and daily periods of time.  Spectral analysis identifies high peaks in the spectral density of the data at 12 and 24 hour cycles, for the hourly water consumption data. For the total daily consumption of water, there is a peak at 7 days, which clarifies that there is a weekly pattern occurring throughout the year. The results from the simple linear regression analysis, where the linear relationship between temperature and water consumption was determined, reveals that the water consumption tends to increase within an increasing temperature, where in Lönashult, Alvesta municipality the water demand increased by 5.5% with every 2 ºC rise in temperature, at a threshold of 12 ºC. For Kalix municipality the three areas selected have around 1-2 % increase in water demand with every 2 ºC rise in temperature for the period of May to December. In Gothenburg, areas that were mixed villa areas or areas with summer homes there was a rise of around 2-12 % in water demand, however areas that are situated in the inner city Gothenburg, or that have majority student housing, the water consumption tends to decrease by 2-7% in water demand with every 2 ºC rise in temperature, with a threshold of 12 ºC. In multiple regression analysis, the hourly water consumption results in adjusted R2 values were in the range from 0.58 to 0.87 (58-87%) for the best model approach and therefore has a significant relationship between water consumption and the explanatory variables chosen for this study. For the daily water consumption, the adjusted R2 values were in the range of 0.22-0.83 (22-83%).  The adjusted R2 values are lower for certain areas and can be explained by a number of factors, such as the different variables used for the daily water consumption analysis, as variables that explain more the periodicity of the data such as the sinusoidal fitted variable and hourly or night/day changes in consumption are not included. As well as this, not all independent variables such as the climate variables were available or complete for particular time periods, and also errors in the data can lead to a significantly lower R2 value.