| description abstract | This paper presents a technique to quantify water savings due to implementation of water restrictions by adopting water restriction indexes as a continuous numerical predictor variable in regression analysis. The adopted modeling technique compares four methods: yearly base difference method, weighted average method, before and after method, and expected use method. These methods are applied to single and multiple dwelling residential sectors in the Blue Mountains region, Australia. In the study, three forms of multiple regression techniques are adopted: raw data, semi-log, and log-log. The model performances are evaluated by a number of statistics such as relative error, Nash-Sutcliffe coefficient, and percentage bias. Moreover, the potential of using the water restriction savings and water conservation savings as continuous predictor variables in the water demand forecasting model is investigated. The performances of different modeling techniques are evaluated using split-sample and leave-one-out cross-validation methods. The yearly base difference method is found to quantify the water savings more accurately in that the savings due to Level 1, Level 2, and Level 3 water restrictions are found to be approximately 9, 18, and 20%, respectively, for the single dwelling residential sector and approximately 4, 8, and 9%, respectively, for the multiple dwelling residential sector. The semi-log model coupled with yearly base difference method is found to perform the best in predicting water demand for both the single and multiple dwelling residential sectors with a relative error of about 3%. | |
