Regionalization and spatial estimation of ethiopian mean annual rainfall

Abstract

AbstractThis study aims at developing methods that will lead to the generation of a reliable mean annual precipitation data base for Ethiopia. Multiple regression models have been formulated that explain the mean annual rainfall as a function of elevation and geographical location. The estimations, based on yearly values from a data set of 63 Ethiopian rainfall stations with records between 1969 and 1985, were developed for the whole country as well as for the already existing Food and Agricultural Organization (FAO) rainfall pattern regions and a new zonation derived by principal component and common factor analyses (PCA/CFA). In the PCA/CFA study, monthly rainfall values between 1968 and 1985 for 43 stations were used. The optimal zonation was derived by testing 36 different combinations resulting in different rainfall pattern regions. The alternatives tested were: correlation and covariance dispersion matrices, PCA and CFA eigentechni‐ques, unrotated and rotated (Varimax and Direct Oblimin) components/factors and number of possible significant components/factors (3, 7, and 11). Principal component analysis of covariance matrix, Varimax rotation and seven extracted components gave by far the best relationship between mean annual rainfall, elevation, and geographical location. Models explaining at least 72 per cent of the variation in rainfall were constructed for regions covering about 98 per cent of the country, which is better than models based on the FAO rainfall pattern regions (69 per cent explained variation for 81 per cent of the country) and a model for the whole country (66·5 per cent explained variation).