UCL Institute for Risk and Disaster Reduction


Future Indonesian Tsunamis: Towards End-to-End Quantification of Risk (FITTER)

FITTER is a 3 year project (2019-2022) that looked at how geophysics and economics can be merged to model tsunami risk holistically for Indonesia using a catastrophe modelling framework.

Project staff from FITTER

3 January 2024

A key innovation in the project was to incorporate non-conventional aspects such as health and livelihoods into the vulnerability module of catastrophe modelling, beyond infrastructure or buildings as is conventional.

The challenge

Indonesia has been severely and repeatedly hit by tsunamis, and will be again in the future. We co-develop, with local stakeholders and experts, an innovative end-to-end catastrophe model of Indonesian tsunamis on the open platform Oasis. We create regional models of all major sources of tsunamis generated by earthquakes over the entire coast of Indonesia, as well as potential tsunamigenic landslide sources triggered by earthquakes and volcanoes since these can have severe local impacts. We produce stochastic hazard footprints for all these events by developing, and applying, bespoke statistical tools of Uncertainty Quantification.

Novel vulnerability functions for the resilience of livelihoods and health of populations are produced. This open model will be of use to both Government and the insurance industry, and enable modern disaster risk financing for Indonesia. The project also looked at post-tsunami business recovery and health costs to households using longitudinal data.


The key innovations and contributions of the project are as follows:

  • New probabilistic tsunami model for South Java, Sumatra, East Kalimantan, simulating high-resolution inundation for estimating impacts
    • Unprecedented level of inundation detail for such a large geographic domain
    • Available to run now in Oasis LMF: ready to be applied to insurance portfolios, building stock data, population datasets
  • Social vulnerability model developed and demonstrated in catastrophe model (Oasis LMF)
    • First case of household level data being applied to estimate loss of household assets in a cat model
    • First case of household level data being applied to estimate loss of household health expenditure in a cat model
    • Support novel design of Disaster Risk Financing, social safety nets, Disaster Risk Management activities in an industry cat modelling framework
  • Events held with Insurance Development Forum (IDF), Oasis, National Disaster Management Agency, Ministry of Finance, National Research and Innovation Agency (BRIN), UNDP and others
    • Developed understanding of probabilistic risk modelling, generated concrete use of Oasis in research (BRIN) and demonstrated where this model can complement ongoing risk management activities

Funding details

This project was funded by the Lloyd's Tercentenary Research Foundation, the Lighthill Risk Network and the Lloyd's Register Foundation-Data Centric Engineering Programme of the Alan Turing Institute

Project duration: July 2019 – November 2022

Principal Investigator: Prof. Serge Guillas, UCL Statistical Sciences

Co-Investigator and Social Science Lead: Dr Rozana Himaz UCL IRDR

Co-Investigators: Dr Dimitra Salmanidou; Dr. Mohammad Heiderzardeh

IRDR Research Assistants: Dr. Daim Syukriyah; Khonsa Zulfa

Collaborating/stakeholder organisations: Insurance Development Forum, Oasis, UNDP, National Research and Innovation Agency (BRIN)