Effect of storm movement on flood peaks: Analysis framework based on characteristic timescales

Abstract

[1] The aim of this paper is to investigate, in general terms, the effects of storm movement on the resulting flood peaks, and the underlying process controls. For this purpose, we utilize a broad theoretical framework that uses characteristic time and space scales associated with stationary rainstorms as well as moving rainstorms. For a stationary rainstorm the characteristic timescales that govern the peak response include two intrinsic timescales of a catchment and one extrinsic timescale of a rainstorm. On the other hand, for a moving rainstorm, two additional extrinsic scales are required, the storm travel time and storm size. The relationship between the peak response and the timescales appropriate for a stationary rainstorm can be extended in a straightforward manner to describe the peak response for a moving rainstorm. However, the interdependence between rainfall duration and storm travel time makes the behavior of the peak response for a moving rainstorm fundamentally different from that of a stationary rainstorm. We show that the relationship between peak response and characteristic timescales also depends on the relative size of the rainstorm with respect to catchment size. For moving rainstorms, we show that the augmentation of peak response arises from both the effect of overlaying the responses from subcatchments (resonance condition) and the effect of increased responses from subcatchments due to increased duration (interdependence), which results in maximum peak response when the moving rainstorm is slower than the channel flow velocity.

Extreme flood response to short-duration convective rainfall in South-West Germany

“…Zoccatelli et al (2011) showed that an upbasin (downbasin) velocity is associated to a decrease (increase) of flood peak with respect to an equivalent stationary storm. A finding which is often reported is that the effect of storm motion on flood peak is maximized when storm velocity has similar magnitude as the channel flow velocity (Singh, 1998;Seo et al, 2012). Moreover, we introduce a methodology to evaluate the impact of neglecting the storm velocity in flood modeling.…”

“…This originates a downbasin catchment scale storm motion, which reaches a steady velocity around 0.7-0.9 m s −1 in the period between 17:45 and 19:30 CET, characterised by the highest rain rates. According to the literature (Ogden et al, 1995;Seo et al, 2012), the downbasin storm velocity may have added to the severity of the storm, giving rise to a stronger flood peak than that of an equivalent stationary storm characterised by the same temporal rainfall distribution and by the same value of 1 .…”

“…There are a number of aspects related to storm movement which have an impact on the flood response. Among these, the direction and the speed of the storm motion with respect to the catchment morphology is probably the most important one (Seo et al, 2012). To examine in a quantitative way these aspects, we use here the concept of "catchment scale storm velocity" proposed by Zoccatelli et al (2011) and based on the spatial moments of catchment rainfall.…”

An approach for the determination of precipitation input for worst-case flood modelling

“…Uncoupling the precipitation distribution from the parameters of observed events allows for consideration of a great variety of possible patterns. This also applies for the representation of variations in storm motions and storm velocities, which can also strongly influence subsequent PMF estimation (Seo et al 2012, Nikolopoulos et al 2014. Despite this uncoupling, some of the generated distributions are consistent with patterns often observed and correlations in space and time.…”

Classification of mechanisms, climatic context, areal scaling, and synchronization of floods: the hydroclimatology of floods in the Upper Paraná River basin, Brazil

“…The assumptions of homogeneity, stationarity, and randomness in traditional flood frequency studies have been questioned in numerous studies (e.g., Hirschboeck et al, 2000;Jain and Lall, 2001;Milly et al, 2002;Alila and Mtiraoui, 2002;Kwon et al, 2008;Villarini et al, 2009Villarini et al, , 2013Smith et al, 2011;Westra and Sisson, 2011;Vogel et al, 2011;Neiman et al, 2011;Seo et al, 2012;Merz et al, 2014;Lima et al, 2015). To make progress on understanding and mod-response, and large-scale circulation patterns associated with the forecast and diagnosis of rainfall events (Maddox, 1983;Kunkel et al, 1994;Pal and Eltahir, 2002;Schumacher and Johnson, 2005;Amengual et al, 2007;Viglione et al, 2010;Li et al, 2013).…”