Premium
A MONTHLY TIME SERIES MODEL OF MUNICIPAL WATER DEMAND 1
Author(s) -
Hansen Roger D.,
Narayanan Rangesan
Publication year - 1981
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1981.tb01263.x
Subject(s) - multivariate statistics , environmental science , econometrics , statistic , regression analysis , precipitation , statistics , water resources , daylight , linear regression , time series , mathematics , hydrology (agriculture) , meteorology , geography , engineering , ecology , physics , geotechnical engineering , optics , biology
A multivariate time series model is formulated to study monthly variations in municipal water demand. The left hand side variable in the multivariate regression model is municipal water demand (gallons per connection per day) and the right hand side contains (explanatory) variables which include price (constant dollars), average temperature, total precipitation, and percentage of daylight hours. The application of the regression model to Salt Lake City Water Department data produced a high multiple correlation coefficient and F‐statistic. The regression coefficients for the right hand side variables all have the appropriate sign. In an ex post forecast, the model accurately predicts monthly variations in municipal water demand. The proposed monthly multivariate model is not only found useful for forecasting water demand, but also useful for predicting and studying the impact of nonstructural management decisions such as the effect of price changes, peak load pricing methods, and other water conservation programs.