Frequently Asked Questions

Access and Using the Model Outputs

To log in you must belong to an organisation and use an organisation email address that has a Google or Microsoft account for authentication. If it is the first time you or someone from your organisation is logging into this website, your IT Admin team may need to authorise this website at their end. If you are still having trouble, please contact us at [email protected].

No, the platform is free of charge. Access is open but a registration process is required.

Yes. Model outputs are provided in standard geospatial formats compatible with GIS tools such as ArcGIS and QGIS. Formats include shapefiles and GeoTIFFs, allowing for easy integration and visualisation alongside other spatial datasets.

Yes. Each application requires different interpretation of the response uncertainty, spatial uncertainty and model limitations. Please refer to Section 12 of the technical report for details .

Layers that have interpreted output are provided as view-only. They are not directly downloadable as they should only be viewed at regional / national scale. Access requests for these layers should be made via [email protected].

The NLM Portal uses Microsoft Azure AD login as one of the authentication methods. It is a cloud-based identity and access management service managed by Microsoft. This app requires your internal IT administrator's approval to use it as a sign-in method, and to read the user profile (e.g. email and username). If you see a message saying: "Approval required. This app requires your admin's approval to: …" Then you need to contact your organisation's internal IT administrator to approve access.

Once tenant-wide approval has been granted by your administrator, anyone from that same agency will be able to access the NLM Portal. Individual approval for different users within the same agency is not required.

How to provide approval:

  1. Sign in to the Azure portal using an Azure AD user account with one of the following roles:
    • Global Administrator or Privileged Role Administrator, for granting consent for apps requesting any permission, for any API.
    • Cloud Application Administrator or Application Administrator, for granting consent for apps requesting any permission for any API, except Azure AD Graph or Microsoft Graph app roles (application permissions).
    • A custom directory role that includes the permission to grant permissions to applications, for the permissions required by the application.
  2. Select Azure Active Directory, and then select Enterprise applications.
  3. Select the application to which you want to grant tenant-wide admin consent, and then select Permissions.
  4. Carefully review the permissions that the application requires.
  5. If you agree with the permissions the application requires, select Grant admin consent.

Understanding the Model Framework

The National Liquefaction Model (NLM) includes modular components such as a Flatland Model, Geomorphology Model, Groundwater Model, and Liquefaction Vulnerability Model (LVM). It produces outputs for various seismic and groundwater scenarios and supports applications like national loss modelling, land use planning, hazard communication, and policy testing. Outputs include Liquefaction Severity Number (LSN) distributions and land damage probabilities. Other liquefaction mapping is performed regionally or locally depending on the level of detail, using similar data. However, it is combined with local knowledge and engineering judgment. The output is produced as distinct categories reflecting probability of liquefaction, severity of liquefaction and uncertainty in the assessment.

SSPs are spatial units used to group areas expected to exhibit similar liquefaction responses. Each SSP is assigned a lognormal distribution of LSN for different combinations of PGA, Magnitude and groundwater depth. Different SSP tiers reflect different spatial and LSN uncertainty:
  • Tier 1: Minimal or no ground investigation data, boundaries defined by geomorphology mapping – highest uncertainty.
  • Tier 2: Some ground investigations, predictions and boundaries determined from geomorphology mapping and ground investigations.
  • Tier 3: Substantial number of ground investigations showing similar response, boundaries determined primarily from distribution of ground investigations – highest confidence.
This system allows efficient data handling and uncertainty classification while maintaining sufficient resolution.

Kriging, which relies on spatial trends and variograms, would have required separate configurations for each PGA, Magnitude, and groundwater depth combination and the storage of thousands of parameters per point (approximately 7 million points would be needed to cover the flatland area with a 100 m grid). SSPs simplify spatial representation by assuming no spatial trend within each polygon. This allows for straightforward interpretation and supports Bayesian updating using local data, allowing higher confidence estimates in data rich areas, while balancing usability and data storage efficiency.

In data-sparse areas, the model provides estimates based on similar geomorphology that does have ground investigations. These areas are classified as Tier 1 SSPs, which carry higher uncertainty but still provide useful indicative outputs.

Governance and Updates

Each model version is labelled using a year.number format (e.g., 2025.1). When updates occur, version release notes will be provided through the portal that summarise the changes (e.g., updated data, revised methods) and their potential impact on model outputs.

The model can produce outputs that can support the development, validation and review of existing council maps. However, the outputs cannot be applied directly for this purpose without further interpretation and analysis from suitably qualified professionals and careful consideration of the local context within which the maps will be applied. The interpretation of NLM outputs for this purpose requires a clear understanding of the limitations of the NLM covered in the technical report.

Yes. The model is designed to accept new local data, including ground investigations (e.g. Cone Penetration Tests and Boreholes), and groundwater observations. To contribute new datasets either upload them to the New Zealand Geotechnical Database or contact us at [email protected].

The National Liquefaction Model is owned and maintained by the Natural Hazards Commission (NHC) – Toka Tū Ake. It was developed by Tonkin + Taylor and is supported and funded by the NHC, with guidance from key stakeholders.

You can send feedback to [email protected]. We actively review user input when planning future updates and welcome suggestions to improve functionality or expand use cases.

Yes. The platform uses secure authentication via Microsoft or Google accounts and complies with relevant New Zealand privacy and data protection regulations. Only minimal information is stored and used strictly for access control and usage analytics.

Not currently. The NLM portal is a standalone platform focused on liquefaction. However, alignment with other hazard platforms is under consideration for future development. Feedback on integration needs is welcomed.

Didn’t find what you were looking for?
For further information or to report an issue, please contact us.