A method for automatic validation of long time series of data in urban hydrology

Abstract

Modelling in urban hydrology is largely based on the analysis of long time series of data. The quality of the results strongly depends on the quality of the data used. Doubtful or wrong data must be detected and eventually substituted by reliable ones when it is feasible before any further exploitation. This paper deals with the development of an automatic pre-validation procedure that detects doubtful and not reliable data, in order to facilitate their interpretation. This procedure consists in applying a set of seven tests based on the following criteria : the functioning state of the sensor, the physical range of the quantity, the locally realistic range, the duration since the last maintenance of the sensor, the signal's gradient, material redundancy and analytical redundancy. The results of the tests are coded with the letter A for reliable values, B for doubtful values and C for wrong values. After this automatic prevalidation, the ultimate validation of values marked B and C is carried out manually by the operator, with the assistance of specifically developed visual and graphical tools.