Advancing global flood hazard simulations by improving comparability, benchmarking,  and integration of global flood models

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1088/1748-9326/aaf3d3.

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Authors

Jannis Hoch , Mark Trigg

Abstract

In recent years, a range of global flood models (GFMs) were developed, each utilizing different
process descriptions as well as validation data sets and methods. To quantify the magnitude of these
differences, studies assessed the performance of GFMs on the continental and catchment level.
Since the default models set-ups resulted in locally marked deviations, there is a clear need for
further and especially more standardized research to not only maintain credibility, but also support
the application of GFM products by end-users. Consequently, we here outline the basic
requirements and challenges of a Global Flood Model Validation Framework for more standardized
model validation and benchmarking in the hope of encouraging the much needed debate, research
developments in this direction, and involvement of science with end-users. By means of the
framework, it is possible to streamline the data sets used for input and validation as well as the
validation approach itself. By subjecting GFMs to more thorough and standardized methods, we
think their quality as well as acceptance will increase as a result, especially amongst end-users of
their outputs. Otherwise GFMs may only serve a purely scientific purpose of continued model
improvement but without practical use. Furthermore, we want to invite GFM developers to make
their models more integratable which would allow for representation of more physical processes
and even more detailed comparison on a model component basis. We think this is pivotal to not only
improve the accuracy of model input data sets, but to focus on the core of each model, the process
descriptions. Only if we know more about why GFMs deviate, are we able to improve them
accordingly and develop a next generation of models, not only providing first-order estimates of
flood extent but supporting the global disaster risk reduction community with more accurate and
actionable information.

DOI

https://doi.org/10.31223/osf.io/jk2e9

Subjects

Earth Sciences, Hydrology, Physical Sciences and Mathematics

Keywords

flood hazard, Benchmarking, Flood Risk, Global Flood Models, Model comparison

Dates

Published: 2018-10-19 11:10

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License

CC BY Attribution 4.0 International

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