Reducing uncertainty of design floods of two-component mixture distributions by utilizing flood timescale to classify flood types in seasonally snow covered region

Abstract

The conventional flood frequency analysis typically assumes the annual maximum flood series (AMFS) result from a homogeneous flood population. However, actually AMFS are frequently generated by distinct flood generation mechanisms (FGMs), which are controlled by the interaction between different meteorological triggers (e.g., thunderstorms, typhoon, snowmelt) and properties of underlying surface (e.g., antecedent soil moisture and land-cover types). To consider the possibility of two FGMs in flood frequency analysis, researchers often use the two-component mixture distributions (TCMD) without explicitly linking each component distribution to a particular FGM. To improve the mixture distribution modeling in seasonally snow covered regions, an index called flood timescale (FT), defined as the ratio of the flood volume to peak value and chosen to reflect the relevent FGM, is employed to classify each flood into one of two types, i.e., the snowmelt-induced long-duration floods and the rainfall-induced short-duration floods, thus identifying the weighting coefficient of each component distribution beforehand. In applying the FT-based TCMD to model the AMFS of 34 watersheds in Norway, ten types of mixture distributions are considered. The design floods and associated confidence intervals are calculated using parametric bootstrap method. The results indicate that the FT-based TCMD model reduces the uncertainty in the estimation of design floods for high return periods by up to 40% with respect to the traditional TCMD. The improved predictive ability of the FT-based TCMD model is attributed to its explicit recognition of distinct 3 generation mechanisms of floods, thereby being able to identify the weighting coefficient and FGM of each component distribution without optimization.

On the flood peak distributions over China

“…An improved understanding of flood hazard requires essential knowledge of flood-generation mechanisms. This is also a critical aspect to consider for improved flood frequency analysis (Hirschboeck, 1988;Singh et al, 2005;Leonard et al, 2014;Brooks and Day, 2015;Yan et al, 2017Yan et al, , 2019. Smith et al (2018) show that the most extreme flood peaks are frequently determined by extreme events resulting from anomalous flood agents for particular regions of the United States (which is the notion of "strange floods").…”

On the Flood Peak Distributions over China

“…In addition to annual maximum flood peak magnitude, we examine the timing of annual maximum flood peak (as represented by day of the year) in this study. Analysis on the timing of annual flood peaks (e.g., seasonality) can shed light on floodgenerating mechanisms, and is an important aspect of flood frequency analysis (Hirschboeck, 1988;Singh et al, 2005;Leonard et al, 2014;Brooks and Day, 2015;Yan et al, 2017Yan et al, , 2019. Annual flood peaks resulted from different flood-generation mechanisms violate the assumption of homogeneous flood population that most conventional methods for flood frequency analysis rely on.…”

Atributos morfométricos e hidrológicos da Bacia Hidrográfica do Alto Sapucaí, Minas Gerais

“…A sazonalidade no regime climático típico de regiões tropicais é ilustrada pela Figura 4C, com duas estações bem definidas: o verão quente e úmido, que concentra a pluviosidade e o inferno frio e seco, com estiagem. Esta sazonalidade é, em geral, negligenciada pelos gestores públicos e promove a intranquilidade na população das áreas densamente povoadas, devido favorecer eventos de enchentes e inundações (YAN et al 2019), como observado nas regiões metropolitanas de São Paulo e Belo Horizonte, no verão de 2020. As variações do clima aliadas à ausência de planejamento urbano são responsáveis pelas tragédias recorrentes que poderiam ser evitadas com planejamento urbano, investimentos em infraestrutura e capacitação técnica da Defesa Civil para fornecer respostas imediatas para situações emergenciais (CELARINO & LADEIRA, 2014).…”