Expected damage technical challenge

Python code to calculate the expected damage for a given risk (e.g. particular asset in a reinsurer's portfolio) located in a given postcode, for which the precise location is unknown. In a given flood event, the water depths observed within this postcode are given in 'depths.csv'.

Flood depth and relationship between depth and damage (vulnerability curve)

Depth observations are taken from a gridded dataset, with pixels of uniform size. 75% of the postcode is inundated, all of which is represented in this collection of observations. The minimum flood depth observed is 0 metres, and the maximum flood depth is 10 metres. The relationship between water depth at the risk's location and damage to that risk is detailed in 'damage_estimate.py'. The set of flood depths and / or vulnerability curve are likely to change between usages of this program.

Setting up the Conda environment

To setup the required python packages to run this code, type the following into the command line:

conda create -n myenv --file package_list.txt

Running the code

python damage_estimate.py depths.csv 200000 10 png --vcurve

arg1 --> csv_depth_file path (string) arg2 --> maximum damage for customised vulnerability curve (integer) arg3 --> maximum flood depth within specified postcode (float) arg4 (optional) --> output file type (string) arg5 (optional) --> use specified vulnerability curve, or calculate (boolean)