Predicting Lake Levels by Exponential Smoothingby Sivajogi D. Koppula, (A.M.ASCE), Section Head; Design and Construction Div., Alberta Environment, 16403-102 Street Edmonton, Alberta, T5X 2G9, Canada,
Serial Information: Journal of the Hydraulics Division, 1981, Vol. 107, Issue 7, Pg. 867-878
Document Type: Journal Paper
A statistical univariate forecasting technique called Exponentially Weighted Moving Average (EWMA) is used to obtain the estimates of future water levels of a large lake. The characteristics of the time series data consisting of average monthly lake levels is examined, and the parameters of the EWMA model are determined. The ex-post forecasts generated by this model are compared with the actual observations of lake water levels and with results obtained earlier with other stochastic methods. EWMA yields forecasts which are statistically indistinguishable from the actual observations.
Subject Headings: Lakes | Forecasting | Data processing | Water level | Parameters (statistics) | Time series analysis | Hydrologic data
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