Future tsunami episodes pose a real threat to Indonesia. FITTER will produce stochastic hazard footprints for all these events across Indonesia by developing, and applying, bespoke statistical tools of uncertainty quantification. FITTER will combine these with new vulnerability models of the resilience of the populations to compute losses in livelihoods.

Explaining the science

The methodology is drawn from geophysical sciences, statistics and economics. FITTER will create regional models of major tsunami sources such as earthquakes and landslides over the entire coast of Indonesia. These require specific parameterisations that will be created to generate sets of events. Our team will employ statistical emulators to produce a full​ Probabilistic Tsunami Hazard Assessment (PTHA) for Indonesia.​ To address the scale of the problem, faster emulators will be developed using Gaussian Process regression with multiple outputs, multi-level design of experiments, and bespoke implementation on high performance computing. FITTER will combine our hazard modelling into Oasis with new vulnerability functions of welfare to develop a full Probabilistic Tsunami Risk Assessment (PTRA) for Indonesia.

Project aims

In terms of human losses and economic impacts, Indonesia is one of the countries that has suffered the most from past tsunamis, such as the 2004 Sumatra-Andaman tsunami and the 2018 Sulawesi tsunami.

Our objectives are:

  1. To deliver an unprecedented high-resolution numerical model of physically plausible tsunamis resulting from earthquakes, as well as from landslides triggered by volcanoes and earthquakes.
  2. To carry out new uncertainty quantification of tsunami footprints in terms of both heights and velocities.
  3. To produce high volume event sets for each source, delivering a probabilistic view usable by risk modellers in all sectors.
  4. To provide a national open hazard model reflecting the uncertainties in the source.
  5. To provide a case study in resilient infrastructure by modelling physical and economic impact on selected ports.
  6. To provide estimates of risk to residential and commercial buildings, applying the above hazard research to the best available proxy exposure data sets (e.g. earth observations data (METEOR), Oasis database and Open Street Map).
  7. To produce welfare and livelihood vulnerability functions for various metrics of impacts such as debt and health expenditure.
  8. To provide all data outputs in an accessible and interoperable format, made available on the Oasis open modelling platform.


Our project aims to co-develop, with local stakeholders and experts, an innovative end-to-end catastrophe model of Indonesian tsunamis on the open platform Oasis. This open model will be of use to both the government and the insurance industry, and enable modern disaster risk financing for Indonesia.

Recent updates

1. Dimitra Salmanidou received a poster award from the committee of the International Tsunami Symposium (ITS) 2021 held in Sendai, Japan 1-3 July 2021. The poster presented the results from the paper Salmanidou, D. M., Ehara, A., Himaz, R., Heidarzadeh, M., & Guillas, S. (2021). Impact of future tsunamis from the Java trench on household welfare: Merging geophysics and economics through catastrophe modelling. International Journal of Disaster Risk Reduction, 61, 102291

2. Dimitra Salmanidou was elected in 2020 Chair of the Working Group on dissemination and stakeholder interaction under the framework of the EU network AGITHAR (Accelerating Global science In Tsunami HAzard and Risk analysis). The Working Group aims to communicate tsunami hazard and risk under consideration of uncertainty, linking scientists with key stakeholders from the public and private sector. AGITHAR now consists of 26 countries and is funded by the European Cooperation in Science and Technology (COST) for a duration of four years (2019-2023).

Project leaders

Professor Serge Guillas, UCL, PI
Dr Dimitra Salmanidou, UCL, co-I
Dr Rozana Himaz, UCL, co-I
Dr Mohammad Heidazadeh, Brunel University London, co-I


Kaiyu Li, UCL, PhD student
Ayao Ehara, UCL, PhD student


Contact info

Serge Guillas
[email protected]