The aim of this research was to develop an automated methodology for validating chronological series of natural inflows to reservoirs. Theoretically, gauges located on the same reservoir should indicate the same reading. However, under the influence of meteorological and hydraulic factors, or simply because of failed measuring equipment, there may be large deviations between the various measurements. Since the calculation of historical natural inflows is directly linked to the measurement of reservoir level by the water balance equation, there will be as many series of natural inflows as there are of reservoir levels. A multivariate filtering technique is used to validate the historical natural inflow computed by each water level variation. The multi filter methodology has the advantage of balancing the water volume of natural inflows to the reservoir when applied over a relatively long period of time. As a result, the validated flood peaks are not systematically overestimated or underestimated and the validated natural inflows are nearly identical for all the gauges. The proposed technique has been incorporated into a software program called ValiDeb, which has been successfully tested on-site on the Gatineau River in Quebec.
The purpose of this research project was to develop a method for automatic validation of historical daily natural runoff data. Reservoir level measurements, on which natural runoff calculations are directly based were validated. Depending on the number of limnimeters installed, two different approaches were used to validate and adjust reservoir level times series. The best conditions (those discussed here) are when a reservoir has several water-level stations. Under these conditions, multivariate filtering is used to validate time series of recorded levels at each station. This method, called the multifilter method consists of comparing deviations between the value predicted with an autoregressive model, the measured historical value, and an estimate obtained using a regression model at neighbouring stations. Among the measured value and the estimate derived from the linear regression model, the closest value to the forecast was retained. One advantage in validating historical hydrometric data is the availability of data before and after the date to be validated. In other words, to validate the value of level Nt not only are the values Nt−1Nt−2, … available, but also the values Nt+1, Nt+2 … at the station to be validated as well as at neighbouring stations. To take advantage of this, the multifilter validation process was performed twice: in the usual time direction and backwards. The historical value was considered faulty and discarded only if it was rejected in both the forward and backward validation processes. All techniques developed have been incorporated into the software called ValiDeb and successfully tested at the Gatineau River site in Quebec. Key words: validation, filtering, multivariate, equipment redundance, analysis, levels, runoff, Kalman. [Journal translation]
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