Multivariate modeling of flood characteristics using Vine copulas

Tosunoğlu, Fatih; Gürbüz, Faruk; İspirli, Muhammet Nuri

doi:10.1007/s12665-020-09199-6

Cited by 36 publications

(33 citation statements)

References 52 publications

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“…To analyze the AMF hydrograph coincidence risk probability, an AMF event must be defined by specific characteristics that allow the occurrence of an AMF event to be objectively recognized (Tosunoglu et al 2020). The following criteria were used to define and characterize an AMF event.…”

Section: Definitions Of Amf Event Characteristicsmentioning

confidence: 99%

“…The traditional copula functions used in the construction of a multidimensional joint distribution are mainly multidimensional elliptic copula and Archimedean copula, but their structures are relatively fixed, and they require the same correlation structure among variables. Therefore, they cannot accurately describe the dependencies of higher-dimensional variables (Aas et al 2009;Schepsmeier and Czado 2016;Yu et al 2019;Jane et al 2020;Tosunoglu et al 2020;Wu et al 2020;).…”

Section: Copula Functionsmentioning

confidence: 99%

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Flood hydrograph coincidence analysis of the upper Yangtze River and Dongting Lake, China

Chao

Wang

et al. 2021

Nat Hazards

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In hydrological research, flood events can be analyzed by flood hydrograph coincidence. Existing flood hydrograph coincidence research mostly focuses on the analysis of the coincidence risk probability of the annual maximum flood event using the 15-day maximum annual flood volume; the actual duration of the flood hydrograph is neglected. The duration of the flood hydrograph is a key variable in (1) determining whether flood hydrograph coincidence occurs, and (2) accurately calculating the flood hydrograph coincidence risk probability. This paper creatively proposes a novel method to analyze the flood hydrograph coincidence risk probability by establishing a five-dimensional joint distribution of flood volumes, durations and interval time for two hydrologic stations. More specifically, using the annual maximum flood of the upper Yangtze River and input from Dongting Lake as an example, the Pearson Type III and the mixed von Mises distributions were used to establish the marginal distribution of flood volumes, flood duration and interval time. Subsequently, the five-dimensional joint distribution based on vine copula was established to analyze the flood hydrograph coincidence risk probability. The results were verified by comparison with a historical flood sequence. The flood hydrograph coincidence volume-risk probability curve was also obtained, providing theoretical support for flood control safety and risk management in the middle and lower Yangtze River. This study also demonstrates the significant beneficial role of regulation by the Three Gorges Water Conservancy Project in mitigating flood risk of the Yangtze River.

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Section: Definitions Of Amf Event Characteristicsmentioning

confidence: 99%

Section: Copula Functionsmentioning

confidence: 99%

Flood hydrograph coincidence analysis of the upper Yangtze River and Dongting Lake, China

Chao

Wang

et al. 2021

Nat Hazards

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“…Copula function is used for joint analysis of several drought characteristic variables with correlation. Copula function has been widely used in the study of drought disaster [24], flood disaster [25], rainstorm disaster [26] and other meteorological disasters. Its theoretical basis was first proposed by Sklar [27], which can well describe the correlation between two variables.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Drought Characteristics in Northern Shaanxi Based on Copula Function

Wang

Rong

et al. 2021

Water

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Precipitation is low and drought occurs frequently in Northern Shaanxi. To study the characteristics and occurrence and development of drought events in Northern Shaanxi is beneficial to the prevention and control of drought disasters. Based on the monthly rainfall data of 10 meteorological stations in Northern Shaanxi from 1960 to 2019, the characteristic variables of drought events at each meteorological station in Northern Shaanxi were extracted by using run theory and copula function. The joint probability distribution and recurrence period were obtained by combining the duration and intensity of drought, and the relationship between drought characteristics and crop drought affected area was studied. The results show that (1) from 1960 to 2019, drought events mainly occurred in Northern Shaanxi with long duration and low severity, short duration and high severity, or short duration and low severity, among which the frequency of drought events that occurred in Yuyang and Baota districts was higher. The frequency of light drought and extreme drought was more in the south and less in the north, while the frequency of moderate drought and severe drought was more in the north and less in the south. (2) The optimal edge distribution of drought intensity and drought duration in Northern Shaanxi is generalized Pareto distribution, and the optimal fitting function is Frank copula function. The greater the duration and intensity of drought, the greater the cumulative probability and return period. (3) The actual recurrence interval and the theoretical recurrence interval of drought events in Northern Shaanxi were close, and the error was only 0.1–0.3a. The results of the joint return period can accurately reflect the actual situation, and this study can provide effective guidance for the prevention and management of agricultural dryland in Northern Shaanxi.

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“…Under the influence of global climate warming and human activities, the water cycle of the ecosystem speeds up and its stability decreases, leading to a sharp increase in the occurrence frequency of abnormal precipitation disasters, such as rainstorm disaster, drought disaster, flood disaster and snow disaster [1][2][3][4]. Dryness/wetness are the most common natural disasters in the world, which occur frequently, cause great losses and affect a wide range of areas [5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

“…Copula function is often used in the study of drought disasters, which can combine drought characteristic variables, so as to more accurately analyze the complex and changeable drought events, and determine the multivariable joint probability distribution and joint return period of drought [1,4,40,41]. In the research of dry-wet events abrupt alternation, few people use Copula function to analyze dry-wet events abrupt alternation.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Characteristics of Dry–Wet Events Abrupt Alternation in Northern Shaanxi, China

Zhang

Rong

et al. 2021

Water

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In this study, Yulin city and Yan’an city in northern Shaanxi Province were taken as the study area. Based on the diurnal dry–wet events abrupt alternation index DWAAI, the joint probability distribution of two characteristic variables of “urgency” and “alternation” of dry–wet events abrupt alternation was established by using copula function, and the characteristics of dry–wet events abrupt alternation were analyzed. DWAAI was calculated from daily precipitation data and the applicability of the index was verified. On this basis, the two characteristic variables of “urgency” and “alternation” were separated, and the appropriate marginal distribution function was selected to fit them, and the correlation between the two variables was evaluated. Finally, the appropriate copula function was selected to fit the bivariate of each station, and the joint cumulative probability and recurrence period of the two variables were calculated. The results show that the DWAAI index is suitable for the identification of dry–wet events abrupt alternation in the study area. Light and moderate dry–wet events abrupt alternation occurs more frequently, while severe events rarely occur in the study area. The frequency of severe dry–wet events abrupt alternation in Jingbian station and its northern area is greater than that in the southern area, and the risk of dry–wet events abrupt alternation of disasters in the northern area is higher. The greater the degree of “urgency” and “alternation”, the greater the joint cumulative probability and the greater the return period. The return period of severe dry–wet events abrupt alternation was more than five years, while the return period of light and moderate dry–wet events abrupt alternation was less than five years.

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Multivariate modeling of flood characteristics using Vine copulas

Cited by 36 publications

References 52 publications

Flood hydrograph coincidence analysis of the upper Yangtze River and Dongting Lake, China

Flood hydrograph coincidence analysis of the upper Yangtze River and Dongting Lake, China

Analysis of Drought Characteristics in Northern Shaanxi Based on Copula Function

Analysis of Characteristics of Dry–Wet Events Abrupt Alternation in Northern Shaanxi, China

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