SPATIAL-TEMPORAL ANALYSIS OF RAINFALL DISTRIBUTION, CASE STUDY: KINGDOM OF SAUDI ARABIA (KSA)

Abstract

This research aims to study daily rainfall variability and distribution over Kingdom of Saudi Arabia (KSA). KSA is counted as dry country with combination of arid and semi-arid areas. The rainfall showed high variability with no defined pattern spatially, with highest amount over southwestern and northwestern regions, and temporally, as seasonality affects both amount and pattern. The first step of classifying the rainfall data; the rainfall stations were spatially clustered using K-means method, which has showed sensitivity to initialization, repetition and number of clusters. Afterwards, Two-Step clustering method was adapted to test if the clusters needed to be sub-clustered depending on the nature of the rainfall data. Then, to have a complete continuous datasets, gaps were filled by weighting both correlation and distance between stations within same cluster. Eventually, a recommendation lists for the empirical frequency distribution, isohyetal maps and IDF curves are provided for the clusters separately.