Flood Plane Zoning For Kelani River Basin Sri Lanka

Abstract

Sri Lanka is a tropical country situated in the middle of the Indian Ocean. Sri Lanka is vulnerable to different types of hazards such as landslides, floods, drought etc. Among nine administrative districts of Sri Lanka, Colombo is one of the highly populated and highly vulnerable districts due to floods in the Kelani River. In May 2016, more than half a million people were affected by floods and the death toll was 101 with 100 people missing, and hundreds of hectares of crops and houses were destroyed. The main reason of flooding in Kelani river basin is due to illegal low land accumulation for developments. This is due to high land value of this area, comparative to the other areas of the island. High rate of population increase and the industrial development need more lands and people tends to live in lower floodplains to construct new houses and factories. Flood risk mapping and floodplain zoning are emerging as effective tool to reduce the flood damage. In developed countries insurance companies are using flood risk maps extensively. However, for developing country like Sri Lanka the methodologies for flood plain mapping are yet to be developed, learned and mastered. The intent of this study is to develop methodology for flood plain zoning and to demonstrate its use for Kelani river basin. The methodology for flood plain zoning combines with the results of flood frequency analysis, GIS usage and MIKE11 modelling. Six gauging stations along the Kelani River, were considered for flood frequency analysis and Flood quantiles were estimated for each gauging station. Hanwella gauging station was selected for flood plain zoning using MIKE 11 modelling. MIKE 11 NAM model was calibrated and validated with Nash-Sutcliffe efficiency (NSE) 0.766 and 0.607. Time constant for routing over land flow (Ck12), over land flow coefficient (CQOF), root zone threshold value (TG), and maximum moisture content rootzone storage (Lmax) were found as most sensitive NAM model parameters for the basin. Over land flow coefficient (CQOF) was found as most effective NAM model parameter on low flows as well as peak flows. Coupled NAM and HD model was calibrated and validated with NSE 0.917 and 0.871. Calibrated Manning’s ‘n’ parameter found as 0.02 for the stream (Hanwella to sea). Hanwella gauging station calculated 10, 25, 50, 100, 250, and 500-year return period floods were used to generate flood inundation maps using integrated MIKE 11NAM and HD model. Finally, the flood Plain zoning map was developed using model simulation results and Arc GIS software.