Water Demand Forecasting using Kalman Filtering

M. Jacobi, D. Karimanzira, and C. Ament (Germany)


Time Series, Prediction, Water Management, Resource Management


In this work a method of demand forecasting of water us age which is based on Kalman filtering is presented. The Kalman filter is a method that provides an efficient compu tational solution in least squares sense. It has thus received much attention for estimation purposes. To demonstrate the efficiency of the proposed technique, it is used to pre dict the water usage demand of Beijing. The data employed in the forecasting process are the previously forecasted de mand and several exogenous influences. This method em ploys a simple mathematical process with less computa tional consumption.

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