scholarly journals Historical changes in frequency of extreme floods in Prague

2015 ◽  
Vol 19 (10) ◽  
pp. 4307-4315 ◽  
Author(s):  
L. Elleder

Abstract. This study presents a flood frequency analysis for the Vltava River catchment using a major profile in Prague. The estimates of peak discharges for the pre-instrumental period of 1118–1824 based on documentary sources were carried out using different approaches. 187 flood peak discharges derived for the pre-instrumental period augmented 150 records for the instrumental period of 1825–2013. Flood selection was based on Q10 criteria. Six flood-rich periods in total were identified for 1118–2013. Results of this study correspond with similar studies published earlier for some central European catchments, except for the period around 1750. Presented results indicate that the territory of the present Czech Republic might have experienced extreme floods in the past, comparable – with regard to peak discharge (higher than or equal to Q10) and frequency – to the flood events recorded recently.

2015 ◽  
Vol 12 (2) ◽  
pp. 1633-1652 ◽  
Author(s):  
L. Elleder

Abstract. This study presents a flood frequency analysis for the Vltava River catchment using a major profile in Prague. The estimates of peak discharges for the pre-instrumental period of 1118–1824 based on documentary sources were carried out using different approaches. 187 flood peak discharges derived for the pre-instrumental period augmented 150 records for the instrumental period of 1825–2013. Flood selection was based on Q10 criteria. Six flood-rich periods in total were identified for 1118–2013. Results of this study correspond with similar studies published earlier for some Central European catchments, except for the period around 1750. Presented results indicate that the territory of the present Czech Republic might have experienced in the past, extreme floods comparable, with regard to peak discharge (POTQ10) and frequency, to the flood events recorded recently.


2018 ◽  
Vol 32 (13) ◽  
pp. 4239-4252 ◽  
Author(s):  
Jianzhu Li ◽  
Yuming Lei ◽  
Senming Tan ◽  
Colin D. Bell ◽  
Bernard A. Engel ◽  
...  

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Changjiang Xu ◽  
Jiabo Yin ◽  
Shenglian Guo ◽  
Zhangjun Liu ◽  
Xingjun Hong

Design flood hydrograph (DFH) for a dam is the flood of suitable probability and magnitude adopted to ensure safety of the dam in accordance with appropriate design standards. Estimated quantiles of peak discharge and flood volumes are necessary for deriving the DFH, which are mutually correlated and need to be described by multivariate analysis methods. The joint probability distributions of peak discharge and flood volumes were established using copula functions. Then the general formulae of conditional most likely composition (CMLC) and conditional expectation composition (CEC) methods that consider the inherent relationship between flood peak and volumes were derived for estimating DFH. The Danjiangkou reservoir in Hanjiang basin was selected as a case study. The design values of flood volumes and 90% confidence intervals with different peak discharges were estimated by the proposed methods. The performance of CMLC and CEC methods was also compared with conventional flood frequency analysis, and the results show that CMLC method performs best for both bivariate and trivariate distributions which has the smallest relative error and root mean square error. The proposed CMLC method has strong statistical basis with unique design flood composition scheme and provides an alternative way for deriving DFH.


2021 ◽  
Author(s):  
Anne Bartens ◽  
Uwe Haberlandt

Abstract. In many cases flood frequency analysis needs to be carried out on mean daily flow (MDF) series without any available information on the instantaneous peak flow (IPF). We analyze the error of using MDFs instead of IPFs for flood quantile estimation on a German dataset and assess spatial patterns and factors that influence the deviation of MDF floods from their IPF counterparts. The main dependence could be found for catchment area but also gauge elevation appeared to have some influence. Based on the findings we propose simple linear models to correct both MDF flood peaks of individual flood events and overall MDF flood statistics. Key predictor in the models is the event-based ratio of flood peak and flood volume obtained directly from the daily flow records. This correction approach requires a minimum of data input, is easily applied, valid for the entire study area and successfully estimates IPF peaks and flood statistics. The models perform particularly well in smaller catchments, where other IPF estimation methods fall short. Still, the limit of the approach is reached for catchment sizes below 100 km2, where the hydrograph information from the daily series is no longer capable of approximating instantaneous flood dynamics.


2021 ◽  
Author(s):  
Mohamad Haytham Klaho ◽  
Hamid R. Safavi ◽  
Mohamad H. Golmohammadi ◽  
Maamoun Alkntar

Abstract Historically, severe floods have caused great human and financial losses. Therefore, the flood frequency analysis based on the flood multiple variables including flood peak, volume and duration poses more motivation for hydrologists to study. In this paper, the bivariate and trivariate flood frequency analysis and modeling using Archimedean copula functions is focused. For this purpose, the annual flood data over a 55-year historical period recorded at the Dez Dam hydrometric station were used. The results showed that based on goodness of fit criteria, the Frank function built upon the couple of the flood peak-volume and the couple of the flood peak-duration as well as the Clayton function built upon the flood volume-duration were identified to be the best copula families to be adopted. The trivariate analysis was conducted and the Clayton family was chosen as the best copula function. Thereafter, the common and conditional cumulative probability distribution functions were built and analyzed to determine the periodic "and", "or" and "conditional" bivariate and trivariate flood return periods. The results suggest that the bivariate conditional return period obtained for short-term periods is more reliable than the trivariate conditional return period. Additionally, the trivariate conditional return period calculated for long-term periods is more reliable than the bivariate conditional return period.


2013 ◽  
Vol 1 (6) ◽  
pp. 7615-7646 ◽  
Author(s):  
N. Macdonald ◽  
T. R. Kjeldsen ◽  
I. Prosdocimi ◽  
H. Sangster

Abstract. The application of historical flood information as a tool for augmenting instrumental flood data is increasingly recognised as a valuable tool; most previous studies have focused on large catchments with historic settlements, this paper applies the approach to the smaller lowland system of the Sussex Ouse in Southeast England. The reassessment of flood risk on the Sussex Ouse is pertinent in light of severe flooding in October 2000 and heightened concerns of a perceived increase in flooding nationally. Systematic flood level readings from 1960 and accounts detailing past flood events within the catchment are compiled back to c.1750. This extended flood record provides an opportunity to reassess estimates of flood frequency over a timescale not normally possible within flood frequency analysis. This paper re-evaluates flood frequency at Lewes on the Sussex Ouse downstream of the confluence of the Sussex Ouse and River Uck. The paper considers the strengths and weaknesses in estimates resulting from contrasting methods of analysis and their corresponding data: (i) single site analysis of gauged annual maxima; (ii) combined analysis of systematic annual maxima augmented with historical peaks of estimated magnitude; (iii) combined analysis of systematic annual maxima augmented with historical peaks of estimated magnitude exceeding a known threshold, and (iv) sensitivity analysis including only the very largest historical flood events. Use of the historical information was found to yield much tighter confidence intervals of risk estimates, with uncertainty reduced by up to 40% for the 100 yr return frequency event when historical information was added to the gauged data.


Author(s):  
Gabriele Villarini ◽  
Louise Slater

Flood losses in the United States have increased dramatically over the course of the past century, averaging US$7.96 billion in damages per year for the 30-year period ranging from 1985 to 2014. In terms of human fatalities, floods are the second largest weather-related hazard in the United States, causing approximately 80 deaths per year over the same period. Given the wide-reaching impacts of flooding across the United States, the evaluation of flood-generating mechanisms and of the drivers of changing flood hazard are two areas of active research. Flood frequency analysis has traditionally been based on statistical analyses of the observed flood distributions that rarely distinguish among physical flood-generating processes. However, recent scientific advances have shown that flood frequency distributions are often characterized by “mixed populations” arising from multiple flood-generating mechanisms, which can be challenging to disentangle. Flood events can be driven by a variety of physical mechanisms, including rain and snowmelt, frontal systems, monsoons, intense tropical cyclones, and more generic cyclonic storms. Temporal changes in the frequency and magnitude of flooding have also been the subject of a large body of work in recent decades. The science has moved from a focus on the detection of trends and shifts in flood peak distributions towards the attribution of these changes, with particular emphasis on climatic and anthropogenic factors, including urbanization and changes in agricultural practices. A better understanding of these temporal changes in flood peak distributions, as well as of the physical flood-generating mechanisms, will enable us to move forward with the estimation of future flood design values in the context of both climatic and anthropogenic change.


2005 ◽  
Vol 313 (1-2) ◽  
pp. 58-78 ◽  
Author(s):  
Robin Naulet ◽  
Michel Lang ◽  
Taha B.M.J. Ouarda ◽  
Denis Coeur ◽  
Bernard Bobée ◽  
...  

2001 ◽  
Vol 32 (1) ◽  
pp. 49-64 ◽  
Author(s):  
Sheng Yue

This article presents a procedure for use of the Gumbel logistic model to represent the joint distribution of two correlated extreme events. Parameters of the distribution are estimated using the method of moments. On the basis of marginal distributions, the joint distribution, the conditional distributions, and the associated return periods can be deduced. The applicability of the model is demonstrated by using multiple episodic flood events of the Harricana River basin in the province of Quebec, Canada. It is concluded that the model is useful for describing joint probabilistic behavior of multivariate flood events.


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