PREDICTING SPATIAL RAINFALL VARIABILITY USING CLIMATIC AND TOPOGRAPHIC VARIABLES IN DATA SCARCE REGION: CASE STUDY IN ANGOLA

Abstract

Rainfall records usually reflects high variability. This variability creates difficulties and complexities in estimating and computing the design values using conventional methods especially in ungauged sites such as the case in developing countries. For this reason, this study has two objectives; firstly, to develop reliable equations using field records which can define the relation between the average annual rainfall and the climatic and topographic variables. Secondly, to check the possibility of estimating the daily rainfall data at various return periods. Consequently, three liear regression equations were developed to predict the average annual rainfall data. Also three linear equations were derived to predict the mean of the maximam daily rainfall values along with three linear equations to predict the 5-year maximum daily rainfall data. The error of these equations was less than 15% which is a considerable improvement in location where no data is available.