Studying Patterns of Rainfall and Topographical Clustering for Kingdom of Bahrain: An Application of Big Data

Abstract

Rainfall is an important aspect for urban planners, especially for professionals related to highway design. This study was aimed at studying the patterns of rainfall in Kingdom of Bahrain using cluster analysis with topographical data. The rainfall data was collected from the website meteorological directorate of ministry of transportation and telecommunication of Bahrain, which consisted of approximately 14000 days, thus referred to as big data. K-means clustering was used to identify the patterns. Moreover, Geographic Information System (GIS) was used for topographical clustering of elevation map of Bahrain. This was done to identify the areas which should receive more attention with regards to drainage due to the topography of Bahrain. The results of this study showed that the time periods which receive comparatively heavier rainfall are around January while those with significantly lower rainfall are during May and October. The topographical analysis showed that the northern parts of the country are supposed to be paid more attention to avoid flooding and, consequently, damage to infrastructure. Moreover, results of the study could be used by the urban and transportation planners in Bahrain for design of efficient drainage resulting in economic benefits to the society.