Quantifying differences between reservoir inflows and dam site floods using frequency and risk analysis methods

Zhong, Yanfei; Liu, Zhangjun; Wang, Yun; Yin, Jiabo

doi:10.1007/s00477-017-1401-4

Cited by 24 publications

(9 citation statements)

References 73 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(1) Derive the corresponding design flood hydrographs of each sub-basin using the peak and volume amplitude (PVA) method (Zhong et al, 2017;Yin et al, 2018) based on the FRC results and design flood hydrographs in construction period. The advantage of PVA method is that it ensures that both the flood peak and volume are equal to the assigned values without modifying flood duration (Yin et al, 2018).…”

Section: Design Flood In Operation Period Modulementioning

confidence: 99%

A general framework of design flood estimation for cascade reservoirs in operation period

Xiong

Guo

Liu

et al. 2019

Journal of Hydrology

Self Cite

View full text Add to dashboard Cite

The hydrological regimes of downstream reservoirs have been significantly altered due to the operation and regulation of upstream cascade reservoirs. The original design flood quantiles, namely "design flood in construction period", do not consider anthropogenic impacts in reservoir operation period, and have led to enormous conflicts between flood control and conservation. In this study, the "design flood and flood limited water level in operation period" are defined for practical application. We establish a general framework to measure the spatiotemporal pattern of streamflow and to estimate design floods of cascade reservoirs in operation period.The multivariate t-copula and a genetic algorithm strategy are proposed to solve the curse of dimensionality encountered in the derivation of most likely regional composition. The Jinsha River and Yalong River cascade reservoir system in China, which consists of 13 large reservoirs with the total storage capacity of 74.06 billion m 3 and hydropower capacity of 71.47GW, is selected as a case study. Results indicate that: (1) The curse of dimensionality can be well addressed by applying multivariate t-copula to build high dimensional joint distribution and using the genetic algorithm to achieve the most likely regional composition. (2) Compared with the design floods in

show abstract

Section: Design Flood In Operation Period Modulementioning

confidence: 99%

A general framework of design flood estimation for cascade reservoirs in operation period

Xiong

Guo

Liu

et al. 2019

Journal of Hydrology

Self Cite

View full text Add to dashboard Cite

show abstract

“…In addition to that, the EFC method observed a considerable difference with the TFH as evident from Figures 6 and 7. TFH is an observed hydrograph whose shape may pose a threat to the downstream section [31,56] and the EFC considers the equivalent frequency of the occurrence probability of hydrological quantiles, therefore, the DFH obtained by the EFC method is considerably larger. In this context, the EFC method advanced a relatively greater difference with TFH than MLC method on both rivers as indicated in Figures 6 and 7.…”

Section: Derivation Of Dfhmentioning

confidence: 99%

Deriving Design Flood Hydrographs Based on Copula Function: A Case Study in Pakistan

Rizwan

Guo

Yin

et al. 2019

Water

Self Cite

View full text Add to dashboard Cite

Flood events are characterized by flood peaks and volumes that can be mutually constructed using a copula function. The Indus basin system of Pakistan is periodically threatened by floods during monsoon seasons and thus causes huge losses to infrastructure as well as the community and economy. The design flood hydrograph (DFH) of suitable magnitude and degree is imperative for sheltering dams against the flood risk. The hydrological pair of flood peak and volume is required to be defined using a multivariate analysis method. In this paper, the joint probability function of the hydrological pair is employed to derive the DFH in the Indus basin system of Pakistan. Firstly, we compared the fitting performance of different probability distributions (PDs) as a marginal distribution. Next, we compared the Archimedean family of copulas to construct the bivariate joint distribution of flood peak and volume. Later, the equal frequency combination (EFC) method and most likely combination (MLC) method using "OR" joint return period (JRP or ), was involved to derive the design flood quantiles. Finally, we derived the DFH using the two combination methods based on Gumbel-Hougaard copula for different return periods. We presented the combination methods for updating the shape of the DFH in Pakistan. Our study will contribute towards the improvement of design standards of dams and environmental recovery in Pakistan.

show abstract

“…In recent years, copula functions have become a research hotspot in the field of hydrology, and been widely used in multivariate hydrological analysis. For example, they have been used for flood frequency analysis (Salvadori and Michele 2004;Zhang and Singh 2006;Reddy and Ganguli 2012;Li et al 2013;Sraj et al 2015;Zhong et al 2018;Karahacane et al 2020), rainfall frequency analysis (De Michele and Salvadori 2003;Govindaraju 2007, 2008;Ashkar and Aucoin 2011;Zhang and Singh 2012), rain and flood analysis (Xiao et al 2009;Keef et al 2009;Candela et al 2014), and multivariate simulation (Aghakouchak et al 2010a, b;Chen et al 2015Chen et al , 2016Poduje and Haberlandt 2017).…”

Section: Introductionmentioning

confidence: 99%

Comparative Study of Flood Coincidence Risk in The Mainstream and Its Tributaries

Xiong

Wang

2021

Preprint

Self Cite

View full text Add to dashboard Cite

The coincidence of floods in the mainstream and its tributaries may lead to a large flooding in the downstream confluence area, and the flood coincidence risk analysis is very important for flood prevention and disaster reduction. In this study, the multiple regression model was used to establish the functional relationship among flood magnitudes in the mainstream and its tributaries. The mixed von Mises distribution and Pearson Type III distribution were selected to fit the probability distribution of the annual maximum flood occurrence dates and magnitudes, respectively. The joint distributions of the annual maximum flood occurrence dates and magnitudes were established using copula function. Fuhe River in the Poyang Lake region was selected as a study case. The joint probability, co-occurrence probability and conditional probability of flood magnitudes were calculated and compared with the simulated results of the observed data. The results show that the selected marginal and joint distributions perform well in simulating the observed flood data. The coincidence probabilities of flood occurrence dates in the upper mainstream and its tributaries mainly occur from May to early July. Among the three coincidence probability calculation methods, the conditional probability is the most consistent with the flood coincidence risk in the mainstream and its tributaries, which is more reliable and rational in practice. The results reflect the actual flood coincidence situation in the Fuhe River basin and can provide technique support for flood control decision-making.

show abstract

Quantifying differences between reservoir inflows and dam site floods using frequency and risk analysis methods

Cited by 24 publications

References 73 publications

A general framework of design flood estimation for cascade reservoirs in operation period

A general framework of design flood estimation for cascade reservoirs in operation period

Deriving Design Flood Hydrographs Based on Copula Function: A Case Study in Pakistan

Comparative Study of Flood Coincidence Risk in The Mainstream and Its Tributaries

Contact Info

Product

Resources

About