Water Demand Modelling Using Independent Component Regression Technique

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• 作者：Md Mahmudul Haque ; Amaury de Souza ; Ataur Rahman
• 关键词：Indepdent component regression ; Principal component regression ; Multiple linear regression ; Water demand ; Brazil
• 刊名：Water Resources Management
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：31
• 期：1
• 页码：299-312
• 全文大小：
• 刊物类别：Earth and Environmental Science
• 刊物主题：Hydrogeology; Hydrology/Water Resources; Geotechnical Engineering & Applied Earth Sciences; Atmospheric Sciences; Civil Engineering; Environment, general;
• 出版者：Springer Netherlands
• ISSN：1573-1650
• 卷排序：31

文摘

Water demand modelling is an active field of research. The modelling and forecasting tools are useful to get the estimation of forecasted water demand for different forecast horizons (e.g. 1 h to 10 years) in order to achieve more efficient and sustainable water resources management systems. However, modelling and forecasting of accurate water demand are challenging and difficult tasks. Several issues make the demand forecasting challenging such as the nature and quality of available data, numerous water demand variables, diversity in forecast horizons and geographical differences in modelling catchments. These issues have motivated a number of studies to be conducted to produce better water demand modelling and forecasting tools in order to improve forecast reliability. A variety of techniques have been adopted in water demand forecasting, however, application of independent component regression (ICR) technique has not been investigated yet. Hence, this study explores, for the first time, the use of the ICR technique in medium term urban water demand forecasting. This uses data from the city of Aquidauana, Brazil. It also compares the performance of the developed ICR model with two other commonly modeling methods, principal component regression and multiple linear regression models. It has been found that ICR model perform better than the other two models in modelling water demand with a higher performance indices (i.e. R2, RMSE, NSE and MARE) for the independent validation period. The results indicate that the ICR technique has the potential to develop water demand models successfully. The methodology adopted in this paper can be applied to other countries to develop water demand forecasting model.