Estimation de lames d'eau spatiales à l'aide de données de pluviomètres et de radar météorologique — Application au pas de temps journalier dans la région de Montréal

Abstract

Several areal rainfall estimation methods using rain gage and weather radar data are reviewed including: (1) Thiessen's and Kriging methods relying on rain gage measurements only; (2) the classical cumulative procedure after transformation of reflectivity measurements using a standard Z- R relationship for conventional radar measurements alone; and (3) the uniform calibration method (using a constant multiplicative factor or a nonlinear regression) and the simplified cokriging method (previously proposed by the authors) for rain gage-radar combinations. An objective procedure based on the definition of reference rainfall depths at ground level and a set of validation criteria is proposed to compare these methods. The methods have been applied to a sample of eleven daily rainfall events observed in the Montreal area by the McGill weather radar and the Environment Canada rain gage network. The results show that the methods taking into account the spatial variability of rainfall (kriging, simplified cokriging) work much better than more classical approaches. Furthermore, the optimal combination of radar and rain gage information through simplified cokriging leads to better results than each measurement system alone for six out of eleven cases (especially for those presenting high areal variability).