Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events

Abstract Floods are among the most common and impactful natural events. The hazard of a flood event depends on its peak (Q), volume (V) and duration (D), which are interconnected to each other. Here, we used a worldwide dataset of daily discharge, two statistics (Kendall’s tau and Spearman’s rho) an...

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Main Authors: L. Rahimi, C. Deidda, C. De Michele
Format: Article
Language:English
Published: Nature Publishing Group 2021-03-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-84664-1
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spelling doaj-9f98347c97504d379220f283d9ab9e642021-03-11T12:15:24ZengNature Publishing GroupScientific Reports2045-23222021-03-0111111010.1038/s41598-021-84664-1Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood eventsL. Rahimi0C. Deidda1C. De Michele2Department of Civil and Environmental Engineering, Politecnico di MilanoDepartment of Civil and Environmental Engineering, Politecnico di MilanoDepartment of Civil and Environmental Engineering, Politecnico di MilanoAbstract Floods are among the most common and impactful natural events. The hazard of a flood event depends on its peak (Q), volume (V) and duration (D), which are interconnected to each other. Here, we used a worldwide dataset of daily discharge, two statistics (Kendall’s tau and Spearman’s rho) and a conceptual hydrological rainfall-runoff model as model-dependent realism, to investigate the factors controlling and the origin of the dependence between each couple of flood characteristics, with the focus to rainfall-driven events. From the statistical analysis of worldwide dataset, we found that the catchment area is ineffective in controlling the dependence between Q and V, while the dependencies between Q and D, and V and D show an increasing behavior with the catchment area. From the modeling activity, on the U.S. subdataset, we obtained that the conceptual hydrological model is able to represent the observed dependencies between each couple of variables for rainfall-driven flood events, and for such events, the pairwise dependence of each couple is not causal, is of spurious kind, coming from the “Principle of Common Cause”.https://doi.org/10.1038/s41598-021-84664-1
collection DOAJ
language English
format Article
sources DOAJ
author L. Rahimi
C. Deidda
C. De Michele
spellingShingle L. Rahimi
C. Deidda
C. De Michele
Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events
Scientific Reports
author_facet L. Rahimi
C. Deidda
C. De Michele
author_sort L. Rahimi
title Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events
title_short Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events
title_full Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events
title_fullStr Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events
title_full_unstemmed Origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events
title_sort origin and variability of statistical dependencies between peak, volume, and duration of rainfall-driven flood events
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-03-01
description Abstract Floods are among the most common and impactful natural events. The hazard of a flood event depends on its peak (Q), volume (V) and duration (D), which are interconnected to each other. Here, we used a worldwide dataset of daily discharge, two statistics (Kendall’s tau and Spearman’s rho) and a conceptual hydrological rainfall-runoff model as model-dependent realism, to investigate the factors controlling and the origin of the dependence between each couple of flood characteristics, with the focus to rainfall-driven events. From the statistical analysis of worldwide dataset, we found that the catchment area is ineffective in controlling the dependence between Q and V, while the dependencies between Q and D, and V and D show an increasing behavior with the catchment area. From the modeling activity, on the U.S. subdataset, we obtained that the conceptual hydrological model is able to represent the observed dependencies between each couple of variables for rainfall-driven flood events, and for such events, the pairwise dependence of each couple is not causal, is of spurious kind, coming from the “Principle of Common Cause”.
url https://doi.org/10.1038/s41598-021-84664-1
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