Non-Stationary Frequency Analysis of Extreme Water Level: Application of Annual Maximum Series and Peak-over Threshold Approaches

2017 ◽  
Vol 31 (7) ◽  
pp. 2065-2083 ◽  
Author(s):  
Ali Razmi ◽  
Saeed Golian ◽  
Zahra Zahmatkesh
Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 15
Author(s):  
Luis Mediero

Currently, there is general concern about the non-stationary behaviour of flood series. Consequently, several studies have been conducted to identify large-scale patterns of change in such flood series. In Spain, a general decreasing trend was found in the period 1959–2009. However, a multi-temporal trend analysis, with varying starting and ending years, showed that trend signs depended on the period considered. Flood oscillations could influence the results, especially when flood-rich and flood-poor periods are located at the beginning or end of the series. In Spain, a flood- rich period in 1950–1970 seemed to lead to the generalised decreasing trend, as it was located at the beginning of the flood series. Nevertheless, the multi-temporal test can only find potential flood- rich and flood-poor periods qualitatively. A methodology has been developed to identify statistically significant flood-rich and flood-poor periods. The expected variability of floods under the stationarity assumption is compared with the variability of floods in observed flood series. The methodology is applied to the longest streamflow series available in Spain. Seven gauging stations located in near-natural catchments, with continuous observations in the period 1942–2014, are selected. Both annual maximum and peak-over-threshold series are considered. Flood-rich and flood-poor periods in terms of flood magnitudes and the annual count of exceedances over a given threshold are identified. A flood-rich period in the beginning of the series and a flood-poor period at its end are identified in most of the selected sites. Accordingly, a flood-rich period placed at the beginning of the series, followed by a flood-poor period, influence the generalised decreasing trend in the flood series previously found in Spain.


Author(s):  
A. I. Agbonaye ◽  
O. C. Izinyon

Rainfall frequency analysis is the estimation of how often rainfall of specified magnitude will occur. Such analyses are helpful in defining policies relating to water resources management. It serves as the source of data for flood hazard mitigation and the design of hydraulic structures aimed at reducing losses due to floods action. In this study rainfall frequency analysis for three (3) cities in South Eastern Nigeria were carried out using annual maximum series of daily rainfall data for the stations. The objective of the study was to select the probability distribution model from among six commonly used probability distribution models namely: Generalized Extreme value distribution (GEV), Extreme value type I distribution (EVI), Generalized Pareto distribution (GPA), Pearson Type III (PIII), log Normal (LN) and Log Pearson Type III (LP111) distributions. These distributions were applied to annual maximum series of daily precipitation data at each station using the parameters of the distributions estimated by the method of moments. The best fit probability distribution model at each location was selected based on the results of seven goodness of fit tests entry: root mean square error (RMSE), relative root mean square error (RRMSE), mean absolute deviation index (MADI) and probability plot correlation coefficient (PPCC), Maximum Absolute Error (MAE), Chi square test and D- Index and a scoring and ranking scheme. Our results indicate that the best fit probability distribution model at all study locations is GEV and this was used to forecast rainfall return values for the stations for return periods of between 5years and 500years. The values obtained are useful for planning, design and management of hydraulic structures for flood mitigation and prevention of flood damage at the location.


Author(s):  
Dongxiao Yin ◽  
David F. Muñoz ◽  
Roham Bakhtyar ◽  
Z. George Xue ◽  
Hamed Moftakhari ◽  
...  

2013 ◽  
Vol 81 ◽  
pp. 51-66 ◽  
Author(s):  
A. Arns ◽  
T. Wahl ◽  
I.D. Haigh ◽  
J. Jensen ◽  
C. Pattiaratchi

2014 ◽  
Vol 18 (11) ◽  
pp. 4391-4401 ◽  
Author(s):  
J. L. Salinas ◽  
A. Castellarin ◽  
S. Kohnová ◽  
T. R. Kjeldsen

Abstract. This study aims to better understand the effect of catchment scale and climate on the statistical properties of regional flood frequency distributions. A database of L-moment ratios of annual maximum series (AMS) of peak discharges from Austria, Italy and Slovakia, involving a total of 813 catchments with more than 25 yr of record length is presented, together with mean annual precipitation (MAP) and basin area as catchment descriptors surrogates of climate and scale controls. A purely data-based investigation performed on the database shows that the generalized extreme value (GEV) distribution provides a better representation of the averaged sample L-moment ratios compared to the other distributions considered, for catchments with medium to higher values of MAP independently of catchment area, while the three-parameter lognormal distribution is probably a more appropriate choice for drier (lower MAP) intermediate-sized catchments, which presented higher skewness values. Sample L-moment ratios do not follow systematically any of the theoretical two-parameter distributions. In particular, the averaged values of L-coefficient of skewness (L-Cs) are always larger than Gumbel's fixed L-Cs. The results presented in this paper contribute to the progress in defining a set of "process-driven" pan-European flood frequency distributions and to assess possible effects of environmental change on its properties.


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