2019
DOI: 10.3390/w11081534
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Flood Risk Analysis of Different Climatic Phenomena during Flood Season Based on Copula-Based Bayesian Network Method: A Case Study of Taihu Basin, China

Abstract: We propose a flood risk management model for the Taihu Basin, China, that considers the spatial and temporal differences of flood risk caused by the different climatic phenomena. In terms of time, the probability distribution of climatic phenomenon occurrence time was used to divide the flood season into plum rain and the typhoon periods. In terms of space, the Taihu Basin was divided into different sub-regions by the Copula functions. Finally, we constructed a flood risk management model using the Copula-base… Show more

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Cited by 13 publications
(6 citation statements)
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“…More than 2 billion people were affected by floods from 1998 to 2017 worldwide (Rehman et al 2019), those who live in floodplains, without efficient flood forecasting systems, are most vulnerable to floods. The Taihu Basin is a typical plain river network area in China, with a developed economy and dense population (Luo et al 2019). It is characterized by a flat terrain, extensive river networks, and numerous polder areas, which are vulnerable to flooding (Zhai et al 2020).…”
Section: Introductionmentioning
confidence: 99%
“…More than 2 billion people were affected by floods from 1998 to 2017 worldwide (Rehman et al 2019), those who live in floodplains, without efficient flood forecasting systems, are most vulnerable to floods. The Taihu Basin is a typical plain river network area in China, with a developed economy and dense population (Luo et al 2019). It is characterized by a flat terrain, extensive river networks, and numerous polder areas, which are vulnerable to flooding (Zhai et al 2020).…”
Section: Introductionmentioning
confidence: 99%
“…The results showed that the developed SWAT-Copula-based method has can be employed in data-scarce regions for effective drought monitoring with the minimum observed inputs. Daneshkhah et al (2016) and Luo et al (2019) constructed a different flood risk management model via the Copulabased Bayesian network to analyze the flood risk. employed the copula theory for estimating joint probability distributions describing the dependence degree between drought conditions and crop yield anomalies of two major rainfed portions of cereal.…”
Section: Introductionmentioning
confidence: 99%
“…One of the first and the most widely applied approaches in dealing with Hybrid BNs is the use of conditional Gaussian models (Friedman et al, 1998;Lauritzen, 1992), which is suitable for continuous variables with Gaussian distributions. In addition to Gaussian models, copula-based non-parametric BNs that can be applied to any continuous variables (Hanea et al, 2015), are gradually being adopted in environmental research (Couasnon et al, 2018;Luo et al, 2019).…”
mentioning
confidence: 99%