Flood season segmentation based on the probability change-point analysis technique

Abstract

The segmentation of flood seasons has both theoretical and practical importance in hydrological sciences and water resources management. The probability change-point analysis technique is applied to segmenting a defined flood season into a number of sub-seasons. Two alternative sampling methods, annual maximum and peaks-over-threshold, are used to construct the new flow series. The series is assumed to follow the binomial distribution and is analysed with the probability change-point analysis technique. A Monte Carlo experiment is designed to evaluate the performance of proposed flood season segmentation models. It is shown that the change-point based models for flood season segmentation can rationally partition a flood season into appropriate sub-seasons. China's new Three Gorges Reservoir, located on the upper Yangtze River, was selected as a case study since a hydrological station with observed flow data from 1882 to 2003 is located 40 km downstream of the dam. The flood season of the reservoir can be reasonably divided into three sub-seasons: the pre-flood season (1 June–2 July); the main flood season (3 July–10 September); and the post-flood season (11–30 September). The results of flood season segmentation and the characteristics of flood events are reasonable for this region.

Citation Liu, P., Guo, S., Xiong, L. & Chen, L. (2010) Flood season segmentation based on the probability change-point analysis technique. Hydrol. Sci. J. 55(4), 540–554.     

Determination of flood seasonality from hydrological records / Détermination de la saisonnalité des crues à partir de séries hydrologiques

Abstract

Abstract The identification of flood seasonality is a procedure with many practical applications in hydrology and water resources management. Several statistical methods for capturing flood seasonality have emerged during the last decade. So far, however, little attention has been paid to the uncertainty involved in the use of these methods, as well as to the reliability of their estimates. This paper compares the performance of annual maximum (AM) and peaks-over-threshold (POT) sampling models in flood seasonality estimation. Flood seasonality is determined by two most frequently used methods, one based on directional statistics (DS) and the other on the distribution of monthly relative frequencies of flood occurrence (RF). The performance is evaluated for the AM and three common POT sampling models depending on the estimation method, flood seasonality type and sample record length. The results demonstrate that the POT models outperform the AM model in most analysed scenarios. The POT sampling provides significantly more information on flood seasonality than the AM sampling. For certain flood seasonality types, POT samples can lead to estimation uncertainty that is found in up to ten-times longer AM samples. The performance of the RF method does not depend on the flood seasonality type as much as that of the DS method, which performs poorly on samples generated from complex seasonality distributions.     

Statistical analysis of the largest possible earthquake magnitudes on the Ecuadorian coast for selected return periods

ABSTRACT

In this work, we have studied the largest earthquake magnitudes on the Ecuadorian coast by using the principles of Extreme Value Analysis based on its two approaches: Block Maxima and Peaks-over-Threshold. First, before modelling the recorded earthquakes, the K-means clustering technique was applied to determine a classification according to the level of magnitude of the earthquakes. Then, models based on the Extreme Value theory of earthquake magnitudes were developed for each of the four clusters that were found, and finally, the best-fitted models were those known as Fréchet and Gumbel ones. The zone with the greatest earthquake magnitudes on the Ecuadorian coast is located between the north of the province of Manabí and the south of the province of Esmeraldas, with a return period of 50 years for an earthquake with magnitude greater than 7.7 M_W.     

Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis

Abstract

Flood frequency analysis can be made by using two types of flood peak series, i.e. the annual maximum (AM) and peaks-over-threshold (POT) series. This study presents a comparison of the results of both methods for data from the Litija 1 gauging station on the Sava River in Slovenia. Six commonly used distribution functions and three different parameter estimation techniques were considered in the AM analyses. The results showed a better performance for the method of L-moments (ML) when compared with the conventional moments and maximum likelihood estimation. The combination of the ML and the log-Pearson type 3 distribution gave the best results of all the considered AM cases. The POT method gave better results than the AM method. The binomial distribution did not offer any noticeable improvement over the Poisson distribution for modelling the annual number of exceedences above the threshold.

Editor D. Koutsoyiannis

Citation Bezak, N., Brilly, M., and ?raj, M., 2014. Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis. Hydrological Sciences Journal, 59 (5), 959–977.     

Stochastic analysis of flood series

A stochastic model based on the renewal process was developed and used to analyse the characteristics of floods: the volume exceedence, the duration of the flood and the maximum annual flow. The model contains a method for determination of total annual volume exceedence and total annual duration of floods, as well as a method for calculation of maximum annual exceedence, maximum flood duration and maximum flow. The subset of the flood occurrence number in a given time interval is common for all analysed phenomena (volume exceedence, flood duration, maximum flow). The subset of given exceedences is common for total annual volume exceedence, as well as for maximum annual volume exceedence. The same holds for durations of individual floods. The model was then applied to analyse the floods on the Drina River at the Paunci hydrological station and on the Danube River at the Bezdan station.     

Pooled flood frequency analysis: a comparison based on peaks-over-threshold and annual maximum series

Despite some theoretical advantages of peaks-over-threshold (POT) series over annual maximum (AMAX) series, some practical aspects of flood frequency analysis using AMAX or POT series are still subject to debate. Only minor attention has been given to the POT method in the context of pooled frequency analysis. The objective of this research is to develop a framework to promote the implementation of pooled frequency modelling based on POT series. The framework benefits from a semi-automated threshold selection method. This study introduces a formalized and effective approach to construct homogeneous pooling groups. The proposed framework also offers means to compare the performance of pooled flood estimation based on AMAX or POT series. An application of the framework is presented for a large collection of Canadian catchments. The proposed POT pooling technique generally improved flood quantile estimation in comparison to the AMAX pooling scheme, and achieved smaller uncertainty associated with the quantile estimates.