EGU23-5418, updated on 10 Jan 2024
EGU General Assembly 2023
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

High resolution exposure model for a flood displacement risk assessment

Daria Ottonelli1, Sylvain Ponserre2, Lauro Rossi1, Roberto Rudari1, and Eva Trasforini1
Daria Ottonelli et al.
  • 1CIMA Research Foundation, Risk assessment and loss data, Savona, Italy (
  • 2Internal Displacement Monitoring Centre (IDMC), Geneva, Switzerland

Disaster risk determines the potential loss of life, injury, or destroyed or damaged assets which could occur to a system, society or a community in a specific period of time, determined probabilistically as a function of hazard, exposure, vulnerability and capacity. This paper focuses on the exposure elements, that expresses people, infrastructure, housing, production capacities and other tangible human assets located in hazard-prone areas (UNDRR, 2017).  In performing risk analyses, an accurate exposure model should be constructed and specified according to the purpose and spatial scale of the assessment.

The scope of the present work is the flood displacement risk assessment for two small island developing states in the Pacific Ocean, Fiji and Vanuatu, where a new methodology is proposed, that considers different but intrinsically linked components in assessing the contribution of disasters to displacement. In this assessment, three main elements are supposed to trigger (or at least contribute to cause) flood displacements: the loss of housing, the loss of livelihoods or the loss of access to basic services. This implies that, besides the classical vulnerability characterization of a asset based on occupancy (residential, commercial, industrial, etc.) and structural elements (number of stories, basement, etc.), the exposure model must also consider a spatial representation of the population relying on the specific function of that asset: residential population in case of residential building; population working in that building in case of commercial, industrial, or service buildings; population working in crop or grazing areas in case of agricultural field; number of students in case of school.

In this context, a procedure for avoiding potential double counting was also implemented. It means that, to evaluate the ratio of population that could suffer impacts due to floods on both livelihoods and housing, each worker must be associated to his/her home with his/her workplace.

Regarding the spatial scale, the small size of the countries allows for the definition of a high-resolution exposure model, that entails a characterization at building Level.

The construction of the exposure model is articulated in three main steps: 1) analysis and integration of different sources of employment and residential data (from global to local information); 2) physical characterization of assets at building scale, using building footprints from the Open Street Map layer and attributes from existing exposure models, such as Pacific Catastrophe Risk Assessment and Financing Initiative (PCRAFI) project that lasted from 2012 to 2017 and Global Earthquake Model (GEM) within the project Global Exposure Map (v2018.1); 3) the procedure to avoid double counting, which associates each worker to his/her home with his/her workplace, following the criterion of minimum geometric distance between workplace and residence.

The exposure model is then used in a probabilistic risk assessment, where different flood scenarios and related damage scenarios are computed at building scale. Physical damage above a certain threshold is considered to cause the unavailability of asset function (residence, workplace), thus triggering the displacement of people relying on that function.

How to cite: Ottonelli, D., Ponserre, S., Rossi, L., Rudari, R., and Trasforini, E.: High resolution exposure model for a flood displacement risk assessment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5418,, 2023.

Supplementary materials

Supplementary material file