Impact of Rainfall Patterns on Flood Dynamics in the Gin River Basin, Sri Lanka: A Data Warehouse Approach

Abstract

This research study investigates the impact of rainfall patterns on flood dynamics in the Gin River basin, located in the Southwestern area of Sri Lanka, with a multidimensional data warehouse application to integrate and analyze hydro-climatological data across various temporal scales. Granular exploration of rainfall patterns and water levels is enabled through Online Analytical Processing (OLAP) architecture and Key Performance Indicators (KPI). The findings of the study show that the Southwest (SW) monsoon is the primary driver in flood occurrences in the basin, with the highest mean rainfall (80.94 mm/day) and statistically significant at p < 0.05 and p < 0.01 compared to other seasons. Transitional seasons, particularly the 2nd Inter Monsoon (IM2), also contributed to floods. Generalized Extreme Value (GEV) analysis revealed increasing extreme rainfall risks, especially in SW and IM2. Moreover, the land use changes such as deforestation and rapid urbanization in the basin have caused a growth of flood risks by increasing the surface runoff. This approach offers a scalable data warehouse applicable to any other flood-prone area, assisting effective flood risk management.