Multi-hazard (earthquake, flood, landslide, debris flow) scenario data from 10 cities for natural hazard risk modelling

https://doi.org/10.5285/dd5c8a28-a82a-4b73-981c-dd1ead32df26

Cite this dataset

This dataset is available under the terms of the Open Government Licence

By accessing or using this dataset, you agree to the terms of the relevant licence agreement(s). You will ensure that this dataset is cited in any publication that describes research in which the data have been used.

This dataset includes hazard data from 10 different cities (Istanbul, Nablus, Chattogram, Cox's Bazaar, Nairobi, Nakuru, Quito, Kokhana, Rapti and Darussalam), to be used in multi-hazard impact modelling. Each dataset represents the hazardscape of the case study area within the cities mentioned above for earthquake, flood, landslide, and debris flow scenarios. The produced hazard maps are simulations that reflect a "what-if" scenario, and not every city contains all hazard type scenarios. The data includes:

Earthquake data: Data representing a potential earthquake hazard sourced from a seismic event, that may effect the study area. The intensity measure is either VS30 or SA for the simulated event.

Flood data: Data representing a potential flood event due to heavy rainfall event or riverine. The intensity measure is flood depth (height).

Landslide / debris flow data: Data representing a potential landslide or debris flow event that is triggered due to heavy rainfall.

Hazard parameter files: This file (in .pdf format) provides information on the background of the each hazard scenario such as the location of the source, attributes included and approach that is used (if available) to create it.

This dataset was created as part of case studies for the Tomorrows Cities: Tomorrowville virtual testbed. It is supported by NERC as part of the GCRF Urban Disaster Risk Hub (NE/S009000/1)

Publication date: 2026-07-10

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How do we collect this information?

Formats

TIFF, Comma-separated values (CSV), geojson

Spatial information

Study area

Spatial representation types

Raster
Tabular (text)

Spatial reference system

WGS 84

Spatial resolution

10 metres

Provenance & quality

First, relevant hazards for the study area were defined based on the regional risk context and stakeholder priorities, ensuring the focus was on those hazards with the most significant impact and available data. Following this, raw data was gathered from a range of sources, including satellite imagery, ground sensors, historical event records, and existing scientific models. This initial data was diverse in format, resolution, and quality. Next, the collected data was pre-processed and standardized, cleaning errors, filling gaps where possible, and harmonizing spatial references and temporal scales to ensure consistency. Where observational data was lacking, global hazard models were developed and calibrated to simulate physical phenomena, producing detailed spatial and temporal hazard maps and time series. These modelled outputs complemented the observational data, forming a robust foundation for integrating multiple hazards into a unified dataset.

Licensing and constraints

This dataset is available under the terms of the Open Government Licence

Cite this dataset as:

Sinclair, H.; Creed, M.; Gentile, R.; Watson, C.S.; Jenkins, L.; Mandahar, V.; Dabbeek, J.; Aljawhari, K.; Cakti, E.; Zisan, B.; Phillips, J.; McCloskey, J. (2026). Multi-hazard (earthquake, flood, landslide, debris flow) scenario data from 10 cities for natural hazard risk modelling. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/dd5c8a28-a82a-4b73-981c-dd1ead32df26

BibTeX RIS

Supplemental information

Cremen, G., Galasso, C., & McCloskey, J. (2022). A Simulation‐Based Framework for Earthquake Risk‐Informed and People‐Centered Decision Making on Future Urban Planning. Earth's Future, 10(1).

https://doi.org/10.1029/2021ef002388

Cremen, G., Galasso, C., McCloskey, J., Barcena, A., Creed, M., Filippi, M. E., Gentile, R., Jenkins, L. T., Kalaycioglu, M., Mentese, E. Y., Muthusamy, M., Tarbali, K., & Trogrlić, R. Š. (2023). A state-of-the-art decision-support environment for risk-sensitive and pro-poor urban planning and design in Tomorrow's cities. International Journal of Disaster Risk Reduction, 85, 103400.

https://doi.org/10.1016/j.ijdrr.2022.103400