scholarly journals Regional frequency analysis of extreme storm surges along the French coast

2011 ◽  
Vol 11 (6) ◽  
pp. 1627-1639 ◽  
Author(s):  
L. Bardet ◽  
C.-M. Duluc ◽  
V. Rebour ◽  
J. L'Her
Keyword(s):  
Exponential Distribution ◽  
Frequency Analysis ◽  
Extreme Events ◽  
Regional Distribution ◽  
Storm Surges ◽  
Regional Frequency Analysis ◽  
Regional Approach ◽  
Extreme Storm ◽  
Mixed Exponential Distribution ◽  
Regional Frequency

Abstract. A good knowledge of extreme storm surges is necessary to ensure protection against flood. In this paper we introduce a methodology to determine time series of skew surges in France as well as a statistical approach for estimating extreme storm surges. With the aim to cope with the outlier issue in surge series, a regional frequency analysis has been carried out for the surges along the Atlantic coast and the Channel coast. This methodology is not the current approach used to estimate extreme surges in France. First results showed that the extreme events identified as outliers in at-site analyses do not appear to be outliers any more in the regional empirical distribution. Indeed the regional distribution presents a curve to the top with these extreme events that a mixed exponential distribution seems to recreate. Thus, the regional approach appears to be more reliable for some sites than at-site analyses. A fast comparison at a given site showed surge estimates with the regional approach and a mixed exponential distribution are higher than surge estimates with an at-site fitting. In the case of Brest, the 1000-yr return surge is 167 cm in height with the regional approach instead of 126 cm with an at-site analysis.

scholarly journals ASSESSMENT OF THE REGIONAL FREQUENCY ANALYSIS TO THE ESTIMATION OF EXTREME STORM SURGES

2012 ◽  
Vol 1 (33) ◽  
pp. 27 ◽  
Author(s):  
Jérôme Weiss ◽  
Pietro Bernardara ◽  
Michel Benoit
Keyword(s):  
Frequency Analysis ◽  
Storm Surges ◽  
Regional Frequency Analysis ◽  
Dependence Structure ◽  
The North ◽  
Extreme Storm ◽  
Physically Based ◽  
Pairwise Dependence ◽  
Homogeneous Regions ◽  
Regional Frequency

Regional frequency analysis (RFA) is performed to estimate extreme storm surges along the French coasts of the Atlantic Ocean, the English Channel and the Southern part of the North Sea. An insight on the formation of physically homogeneous regions from a criterion of propagation of storms is provided. The treatment of the pairwise dependence structure within a given region through a spatial extreme value copula is also considered, leading to a model coupling physically-based RFA and spatial dependence to describe the probabilistic behavior of extreme storm surges.

scholarly journals Regional frequency analysis of extreme storm surges using the extremogram approach

2020 ◽  
Vol 20 (6) ◽  
pp. 1705-1717
Author(s):  
Marc Andreevsky ◽  
Yasser Hamdi ◽  
Samuel Griolet ◽  
Pietro Bernardara ◽  
Roberto Frau
Keyword(s):  
Frequency Analysis ◽  
Region Of Interest ◽  
Storm Surges ◽  
Accurate Estimate ◽  
Target Site ◽  
Regional Frequency Analysis ◽  
Extremal Dependence ◽  
Extreme Storm ◽  
Extremal Behavior ◽  
Regional Frequency

Abstract. To withstand coastal flooding, protection of coastal facilities and structures must be designed with the most accurate estimate of extreme storm surge return levels (SSRLs). However, because of the paucity of data, local statistical analyses often lead to poor frequency estimations. The regional frequency analysis (RFA) reduces the uncertainties associated with these estimations by extending the dataset from local (only available data at the target site) to regional (data at all the neighboring sites including the target site) and by assuming, at the scale of a region, a similar extremal behavior. In this work, the empirical spatial extremogram (ESE) approach is used. This is a graph representing all the coefficients of extremal dependence between a given target site and all the other sites in the whole region. It allows quantifying the pairwise closeness between sites based on the extremal dependence. The ESE approach, which should help with have more confidence in the physical homogeneity of the region of interest, is applied on a database of extreme skew storm surges (SSSs) and used to perform a RFA.

scholarly journals Regional Frequency Analysis of Precipitation Extremes and Its Spatio-Temporal Patterns in the Hanjiang River Basin, China

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 130 ◽  
Author(s):  
Wenlong Hao ◽  
Zhenchun Hao ◽  
Feifei Yuan ◽  
Qin Ju ◽  
Jie Hao
Keyword(s):  
River Basin ◽  
Frequency Analysis ◽  
Return Period ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Precipitation Extremes ◽  
Regional Frequency Analysis ◽  
Hanjiang River ◽  
Spatio Temporal ◽  
Regional Frequency

Extreme events such as rainstorms and floods are likely to increase in frequency due to the influence of global warming, which is expected to put considerable pressure on water resources. This paper presents a regional frequency analysis of precipitation extremes and its spatio-temporal pattern characteristics based on well-known index-flood L-moments methods and the application of advanced statistical tests and spatial analysis techniques. The results indicate the following conclusions. First, during the period between 1969 and 2015, the annual precipitation extremes at Fengjie station show a decreasing trend, but the Wuhan station shows an increasing trend, and the other 24 stations have no significant trend at a 5% confidence level. Secondly, the Hanjiang River Basin can be categorized into three homogenous regions by hierarchical clustering analysis with the consideration of topography and mean precipitation in these areas. The GEV, GNO, GPA and P III distributions fit better for most of the basin and MARE values range from 3.19% to 6.41% demonstrating that the best-fit distributions for each homogenous region is adequate in predicting the quantiles estimates. Thirdly, quantile estimates are reliable enough when the return period is less than 100 years, however estimates for a higher return period (e.g., 1000 years) become unreliable. Further, the uncertainty of quantiles estimations is growing with the growing return periods and the estimates based on R95P series have a smaller uncertainty to describe the extreme precipitation in the Hanjiang river basin (HJRB). Furthermore, In the HJRB, most of the extreme precipitation events (more than 90%) occur during the rainy season between May and October, and more than 30% of these extreme events concentrate in July, which is mainly impacted by the sub-tropical monsoon climate. Finally, precipitation extremes are mainly concentrated in the areas of Du River, South River and Daba Mountain in region I and Tianmen, Wuhan and Zhongxiang stations in region III, located in the upstream of Danjiangkou Reservoir and Jianghan Plain respectively. There areas provide sufficient climate conditions (e.g., humidity and precipitation) responsible for the occurring floods and will increase the risk of natural hazards to these areas.

scholarly journals Regional frequency analysis of extreme storm surges using the extremogram approach

2019 ◽  
Author(s):  
Marc Andreevsky ◽  
Yasser Hamdi ◽  
Samuel Griolet ◽  
Pietro Bernardara ◽  
Roberto Frau
Keyword(s):  
Frequency Analysis ◽  
Storm Surges ◽  
Accurate Estimate ◽  
Target Site ◽  
Regional Frequency Analysis ◽  
Homogeneous Region ◽  
Coastal Protection ◽  
Local Index ◽  
Extremal Behavior ◽  
Regional Frequency

Abstract. To resist marine submersion, coastal protection must be designed by taking into account the most accurate estimate of the return levels of extreme events, such as storm surges. However, because of the paucity of data, local statistical analyses often lead to poor frequency estimations. Regional Frequency Analysis (RFA) reduces the uncertainties associated with these estimations, by extending the dataset from local (only available data at the target site) to regional (data at all the neighboring sites including the target site) and by assuming, at the scale of a region, a similar extremal behavior. RFA, based on the index flood method, assumes that, in a homogeneous region, observations at sites, normalized by a local index, follow the same probability distribution. In this work, the spatial extremogram approach is used to form a physically homogeneous region centered on the target site. The approach is applied on a database of extreme skew storm surges and used to carry out a RFA.

scholarly journals Hybrid Approach to Delineation of Homogeneous Regions for Regional Precipitation Frequency Analysis

2009 ◽  
Vol 57 (4) ◽  
pp. 226-249 ◽  
Author(s):  
Ladislav Gaál ◽  
Ján Szolgay ◽  
Milan Lapin ◽  
Pavol Faško
Keyword(s):  
Distribution Function ◽  
Frequency Analysis ◽  
Regional Distribution ◽  
Hybrid Approach ◽  
Heavy Precipitation ◽  
Regional Frequency Analysis ◽  
Precipitation Frequency ◽  
Precipitation Analysis ◽  
Homogeneous Regions ◽  
Regional Frequency

Hybrid Approach to Delineation of Homogeneous Regions for Regional Precipitation Frequency AnalysisRegional frequency analysis of heavy precipitation amounts based on the estimation of the parameters of a regional distribution function usingL-moments is adopted for the specific geographical-climatological settings of Slovakia. The paper focuses on the first step of the regionalL-moment algorithm (Hosking, Wallis, 1997), which is the delineation of homogeneous regions. Objective and process-based logical pooling techniques are used to form homogeneous pooling groups of rainfall gauging stations for regional frequency analysis ofk-day precipitation amounts (k= 1 to 5 days). Even though the delineation of homo-geneous regions by means of objective methods is generally accepted and recommended in the literature, it is concluded here that such a pooling of similar sites should not be carried out automatically in precipitation analysis. Instead, a combination of physical/geomorphological considerations and objective methods should be preferred.

The index rainfall in the regional frequency analysis of extreme events in Tuscany (Italy)

2008 ◽  
Vol 19 (7) ◽  
pp. 714-724 ◽  
Author(s):  
Enrica Caporali ◽  
Elisabetta Cavigli ◽  
Alessandra Petrucci
Keyword(s):  
Frequency Analysis ◽  
Extreme Events ◽  
Regional Frequency Analysis ◽  
Index Rainfall ◽  
Regional Frequency

scholarly journals Regional frequency analysis of daily maximum rainfall in Haryana

MAUSAM ◽  
2021 ◽  
Vol 72 (4) ◽  
pp. 835-846
Author(s):  
MOHIT NAIN ◽  
B. K. HOODA
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Regional Distribution ◽  
Rain Gauge ◽  
Quantile Estimation ◽  
Regional Frequency Analysis ◽  
Daily Maximum ◽  
Maximum Rainfall ◽  
L Moments ◽  
Regional Frequency

This paper is sets-out for the regional frequency analysis of daily maximum rainfall from the 27 rain gauge stations in Haryana using L-moments. As the distribution of rainfall varies spatially in Haryana, the 27 rain gauge stations are grouped into three clusters namely, cluster C1, C2 and C3 using Ward’s clustering method and homogeneity of clusters was confirmed using L-moments-based Heterogeneity measure (H). Using goodness-of-fit measure ( DIST Z ) and L-moment ratios diagram, suitable regional frequency distributions were selected among five candidate distributions;Generalized Logistic (GLO), Generalized Extreme Value (GEV),Generalized Normal (GNO), Generalized Pareto (GPA), and Pearson Type-3 (PE3) for each cluster. Results showed that PE3 and GNO were good fitted regional distribution for the cluster C1 and GEV, PE3 and GNO fitted for cluster C2 while for cluster C3; GLO and GEV were good fitted regional distribution. To select a robust distribution among good fitted distributions accuracy measures calculated using Monte Carlo simulations for each cluster. The simulation result showed that PE3 was the best choice for quantile estimation for cluster C1. For cluster C2, PE3 was the best choicefor a large return period and GEV was best for a small return period. For cluster C3, GEV was the most suitable distribution for quantile estimation. Using these robust distributions rainfall quantiles were estimated at each rain gauge station from 2 to 100 year return periods. These estimated rainfall quantiles may be rough guideline for planning and designing hydraulic structures by policy makers and structural engineers.

scholarly journals Homogenous regions based on extremogram for regional frequency analysis of extreme skew storm surges

2017 ◽  
Author(s):  
Marc Andreewsky ◽  
Samuel Griolet ◽  
Yasser Hamdi ◽  
Pietro Bernardara ◽  
Roberto Frau
Keyword(s):  
Frequency Analysis ◽  
Storm Surges ◽  
Accurate Estimate ◽  
Target Site ◽  
Regional Frequency Analysis ◽  
Homogeneous Region ◽  
Coastal Protection ◽  
Local Index ◽  
Extremal Behavior ◽  
Regional Frequency

Abstract. To resist marine submersion, coastal protection must be designed by taking into account the most accurate estimate of the return levels of extreme events, such as storm surges. However, because of the paucity of data, local statistical analyses often lead to poor frequency estimations. Regional Frequency Analysis (RFA) reduces the uncertainties associated with these estimations, by extending the dataset from local (only available data at the target site) to regional (data at all the neighboring sites including the target site) and by assuming, at the scale of a region, a similar extremal behavior. RFA, based on the index flood method, assumes that, in a homogeneous region, observations at sites, normalized by a local index, follow the same probability distribution. In this work, the spatial extremogram approach is used to form a physically homogeneous region centered on the target site. The approach is applied on a database of extreme skew storm surges and used to carry out a RFA.

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