Coastal Flood Disaster in Sri Lanka-May 2017: Exploring Distributional Changes in Rainfall and Their Impacts on Flood Risk

• Published in: Journal of coastal research Vol. 85; no. sp1; pp. 1476 - 1480
• Main Authors: Chandrasekara, S.S.K, Uranchimeg, Sumiya, Kwon, Hyun-Han, Lee, Seung Oh
• Format: Journal Article
• Language: English
• Published: Fort Lauderdale Coastal Education and Research Foundation 01-05-2018; COASTAL EDUCATION & RESEARCH FOUNDATION, INC. [CERF]; Allen Press Inc
• Subjects: Annual rainfall; Bayesian analysis; Climate variability; Coastal ecosystems; Coastal flood; COASTAL MANAGEMENT; Coastal zone; Ecosystems; Environmental risk; Extreme weather; Floods; Frameworks; Landslides & mudslides; Livelihoods; Probability density functions; Probability theory; quantile regression; Quantiles; Rain; Rainfall; Regions; Sri Lanka; Stations; Statistical analysis; Trends; Wind; Sri Lanka; Bay of Bengal
• ISSN: 0749-0208; 1551-5036
• DOI: 10.2112/SI85-296.1

S.S.K, Chandrasekara.; Uranchimeg, S.; Kwon, H-H., and Lee, S-O., 2018. Coastal Flood Disaster in Sri Lanka-May 2017: Exploring Distributional Changes in Rainfall and Their Impacts on Flood Risk. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1476–1480. Coconut Creek (Florida), ISSN 0749-0208. Coastal communities, their livelihoods, and the coastal ecosystems of Sri Lanka are vulnerable to extreme rainfall events. In May 2017, the southern and southwestern coastal regions of Sri Lanka experienced devastating floods, which caused nearly 122 deaths. In light of this, exploring distributional changes in extreme rainfall series recorded across Sri Lanka are crucial to understand flood risk in the context of climate variability and change. This study was focused on investigating possible distributional changes in annual maximum daily rainfall (ADMR) over time for the affected coastal regions in Sri Lanka using a quantile regression approach in a Bayesian framework. A simplified nine–category distributional change scheme based on the empirical probability density functions of two years (i.e., the first year and the last year) was used to determine the distributional changes in ADMR. This study examined the trends of ADMRs for seven stations in coastal regions of Sri Lanka for the period of 1960 – 2015. Three categories in terms of distributional change in ADMR were identified for these regions. One station showed an upward trend in distributional change in ADMR, which could indicate high probability of extreme rainfall. The rest of the stations showed a downward trend in the quantiles, which could indicate low probability of extreme rainfall. Further discussion of the possible reasons for the occurrence of the coastal flood disaster in May 2017 in Sri Lanka is provided below.