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Bennett, W G and Karunarathna, H (2019) Coastal flood alleviation through management interventions under changing climate conditions. International Journal of Disaster Resilience in the Built Environment, 11(02), 187–203.

Haigh, R, Sakalasuriya, M M, Amaratunga, D, Basnayake, S, Hettige, S, Premalal, S and Jayasinghe Arachchi, A (2020) The upstream-downstream interface of Sri Lanka’s tsunami early warning system. International Journal of Disaster Resilience in the Built Environment, 11(02), 219–40.

Hamza, M and Månsson, P (2019) The human dimension of early warning – a viewpoint. International Journal of Disaster Resilience in the Built Environment, 11(02), 263–74.

Hanggara, D and Wijeyewickrema, A C (2019) Vulnerability assessment of reinforced concrete buildings in Indonesia subjected to tsunami inundation forces. International Journal of Disaster Resilience in the Built Environment, 11(02), 204–18.

Rahayu, H P, Comfort, L K, Haigh, R, Amaratunga, D and Khoirunnisa, D (2020) A study of people-centered early warning system in the face of near-field tsunami risk for Indonesian coastal cities. International Journal of Disaster Resilience in the Built Environment, 11(02), 241–62.

Randil, C, Siriwardana, C and Hewawasam, K (2019) Framework to analyze Sri Lanka disaster management mechanism. International Journal of Disaster Resilience in the Built Environment, 11(02), 289–307.

Rathnayake, D K, Kularatne, D, Abeysinghe, S, Shehara, I, Fonseka, T, Edirisinghe Mudiyanselage, S D J, Kamalrathne, W G C T, Siriwardana, C, Alagiyawanna Mohotti Appuhamilage, C S B and Dissanayake, R (2020) Barriers and enablers of coastal disaster resilience – lessons learned from tsunami in Sri Lanka. International Journal of Disaster Resilience in the Built Environment, 11(02), 275–88.

Wickramaratne, S, Wirasinghe, S C and Ruwanpura, J (2019) An update of proposed Sri Lanka warning system for east and west coast tsunamis. International Journal of Disaster Resilience in the Built Environment, 11(02), 169–86.

• Type: Journal Article
• Keywords: Sri Lanka; Buoys; Indian Ocean; Tide gauges; Tsunami detection; Tsunami warning;
• ISBN/ISSN: 1759-5908
• URL: https://doi.org/10.1108/IJDRBE-08-2019-0052
• Abstract:
  Based on the existing provisions/operations of tsunami warning in the Indian Ocean, authors observed that detection as well as arrival time estimations of regional tsunami service providers (RTSPs) could be improved. In particular, the detection mechanisms have been eccentrically focussed on Sunda and Makran tsunamis, although tsunamis from Carlsberg ridge and Chagos archipelago could generate devastating tsunamis for which inadequate provisions exist for detection and arrival time/wave height estimation. RTSPs resort to assess estimated arrival time/wave heights from a scenario-based, pre-simulated database. These estimations in terms of Sri Lanka have been found inconsistent. In addition, current warning mechanism poorly manages non-seismic tsunamis. Thus, the purpose of this study is to investigate these drawbacks and attempt to carve out a series of suggestions to improve them. The work initiated with data retrieved from global earthquake and tsunami databases, followed by an estimation of probabilities of tsunamis in the Indian Ocean with particular emphasis on Carlsberg and Chagos tsunamis. Second, probabilities of tsunami detection in each sub-region have been estimated with the use of available tide gauge and tsunami buoy data. Third, the difficulties in tsunami detection in the Indian Ocean are critically assessed with case studies, followed by recommendations to improve the detection and warning. Probabilistic estimates show that given the occurrence of a significant earthquake, both Makran and Carlsberg/Chagos regions possess higher probabilities to harbour a tsunami than the Sunda subduction zone. Meanwhile, reliability figures of tsunami buoys have been declined from 79-92 to 68-91 per cent over the past eight years. In addition, a Chagos tsunami is left to be detected by only one tide gauge prior to it reaching Sri Lankan coasts. The study uses an averaged tsunami speed of 882 km/h based on 2004 Asian tsunami. However, using exact bathymetric data, Tsunamis could be simulated to derive speeds and arrival times more accurately. Yet, such refinements do not change the main derivations and conclusions of this study. Tsunami detection and warning in the Indian Ocean region have shown room for improvement, based on the inadequate detection levels for Carlesberg and Chagos tsunamis, and inconsistent warnings of regional tsunami service providers. The authors attempted to remedy these drawbacks by proposing a series of suggestions, including a deployment of a new tsunami buoy south of Maldives, revival of offline buoys, real-time tsunami simulations and a strategy to deal with landslide tsunamis, etc. Indian Ocean is prone to mega tsunamis as witnessed in 2004. However, more than 50 per cent of people in the Indian Ocean rim countries dwell near the coast. This is verified with deaths of 227,898 people in 14 countries during the 2004 tsunami event. Thus, it is of paramount importance that sufficient detection levels are maintained throughout the Indian Ocean without being overly biased towards Sunda tsunamis. With respect to Sri Lanka, Makran, Carlesberg or Chagos tsunamis could directly hit the most populated west coast and bring about far worse repercussions than a Sunda tsunami. This is the first instance where the threats from Carlesberg and Chagos tsunamis to Sri Lanka are discussed, probabilities of tsunamis are quantified and their detection levels assessed. In addition, reliability levels of tsunami buoys and tide gauges in the Indian Ocean are recomputed after eight years to discover that there is a drop in reliability of the buoy data. The work also proposes a unique approach to handle inconsistencies in the bulletins of regional tsunami service providers, and to uphold and improve dwindling interest on tsunami buoys.

Wijetunge, J J (2019) A multi-scenario assessment of the seismogenic tsunami hazard for Bangladesh. International Journal of Disaster Resilience in the Built Environment, 11(02), 156–68.