2023 – Reviewing Catchment Nonlinearity for Extreme Flood Estimates

Tim Rhodes, Kosta Tsourdalakis, Amir Behroozi

Extreme flood estimates constitute a key input to dam risk assessments, and they are subject to a high degree of uncertainty due to both a limited understanding of the meteorologic drivers and catchment runoff generation processes. Current estimation methods routinely apply an assumption of nonlinearity which results in increased peak flows. In essence, doubling rainfall results in more than double the runoff peak flow. There is little strong evidence to support the nonlinear assumption in the extreme flood range. An analysis of flow records has been undertaken to investigate catchment nonlinearity and a method has been derived that allows linear catchment responses to be identified. Applying this method to extreme floods provides a basis for reducing flood magnitudes relative to the current industry standard approach.

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