Transformation of Generation Processes From Small Runoff Events to Large Floods

L Tarasova,R Merz,S Basso

doi:10.1029/2020gl090547

Abstract

AbstractMixture of runoff generation processes poses a challenge for predicting upper flood quantiles. We examined transformations of generation processes from all identifiable runoff events to frequent and upper tail floods for a large set of mesoscale catchments and observed a substantial change of the dominant processes. Two trajectories of transformation were detected. In regions where floods occur almost exclusively in winter the dominance of processes related to snowmelt consistently increases from small events to frequent and upper tail floods. In catchments characterized by frequent winter‐spring floods and occasional summer‐autumn flood events triggered by rare meteorological phenomena (e.g., Vb cyclones), processes that dominate upper tails are not adequately represented in the sample of frequent floods. Predictions of extremes and projections of flood changes might remain highly uncertain in the latter cases.

Highlights

Predicting magnitude and frequency of large floods and their possible changes is critical for hazard assessment, making the topic of their origins of significant practical importance (Smith et al, 2018)
We examined transformations of generation processes from all identifiable runoff events to frequent and upper tail floods for a large set of mesoscale catchments and observed a substantial change of the dominant processes
In this study we primarily focused on four event samples: ordinary runoff events isolated by the above mentioned event separation method, two alternative samples of frequent floods defined as series of maximum annual floods (MAFs) and peak-over-threshold events (POT4, the threshold was selected iteratively to sample on average 4 events per year), and upper tail floods

Summary

Introduction

Predicting magnitude and frequency of large (extreme) floods and their possible changes is critical for hazard assessment, making the topic of their origins of significant practical importance (Smith et al, 2018). Detailed studies of extreme and catastrophic floods (e.g., Blöschl et al, 2013; Hirschboeck, 1987a; Nakamura et al, 2013; Rogger et al, 2012; Smith et al, 2018) and specific atmospheric mechanisms generating the largest flood peaks (e.g., Barth et al, 2017; Doswell et al, 1996; De Luca et al, 2017; Lima et al, 2017; Ralph et al, 2006; Villarini et al, 2011) provided evidences on the heterogeneity of processes in flood samples These works fueled debates on the origins and the choice of appropriate methods for estimating upper tail (i.e., the largest) floods. Recently developed approaches that utilize the whole range of observed streamflows to derive flood frequency curves (Basso et al, 2016; Claps & Laio, 2003; Miniussi et al, 2020) delivered more accurate predictions of upper tails, supporting the hypothesis that the largest floods (statistically) might originate from ordinary runoff events

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