Sensitivity of global flood modelling frameworks to input parameter choices

Understanding flood hazard at scale requires consistently generated flood maps. To build flood maps at scale, automated frameworks must be used that can take input data, transform this into hydrodynamic simulations and process it into output flood maps.

This transformation from inputs into simulations can be influenced by the design of the framework and the choices made by modellers as to how the transformations are made. These choices can be influenced by quality and availability of input data, availability of computational resources and desired outputs. There may not be clear objectively better options, so subjective choices have to be made. Understanding the sensitivity of these choices is key in both making them, and rating the uncertainty of the outputs.

Here we present the outputs from some of the sensitivity testing undertaken when developing a global model framework including both their influence on flood hazard and their influence on other deciding factors (such as computational cost) made when building a global flood map. This presentation includes results from tests that were shown to develop key or interesting results, such as:

• How rivers are split into separate simulations
• Minimum size of fluvial river assessed
• Length of pluvial storm assessed