According to the National Emergency Management Agency, flooding is the greatest hazard in New Zealand, in terms of frequency, losses and civil defence emergencies. With major flood events occurring on average every 8 months (New Zealand – FloodList), it is necessary to produce high precision flood models and in order to do better planning, risk assessment and response to flood events.
The Flood Resilience Digital Twin can provide a better understanding of the degree of impact flood events can have on physical assets like buildings, roads, railways, transmission lines, etc. The digital twin not only represents the current status of the visualised assets but also how they will perform/react to future situations. The digital twin, when used to run flood models combined with other sources of information can allow us to make predictions.
Data for analysis and modelling are collected from open data portals provided by multiple organisations or data providers such as LINZ, StatsNZ, opentopography, NIWA, MFE, and more.
See our draft paper for Journal of Open Source Software for more details.
The following list defines the basic steps required to set up and run the digital twin.
Create API keys for each of these services. You may need to create an account and log in
Clone this repository to your local machine.
Create a file called api_keys.env
, copy the contents of api_keys.env.template
and fill in the blank values with API credentials from the above links.
Create a file called .env
in the project root, copy the contents of .env.template
and fill in all blank fields unless a comment says you can leave it blank.
Blank fields to fill in include things like the POSTGRES_PASSWORD
variable and CESIUM_ACCESS_TOKEN
. You may configure other variables as needed.
From project root, run the command docker compose up -d
to run the database, backend web servers, and helper services.
You may inspect the logs of the backend using docker compose logs -f backend celery_worker
docker compose logs -f celery_worker
.Visit our wiki for some instructions on how to set up your development machine to work with on the FReDT project.