Long-Term Statistical Analysis of Typhoon Wave Heights With Poisson-Maximum Entropy Distribution

2009 ◽  
Author(s):  
Sheng Dong ◽  
Wei Liu ◽  
Lizhen Zhang ◽  
C. Guedes Soares
Keyword(s):  
Maximum Entropy ◽  
Wave Height ◽  
Estimation Accuracy ◽  
Threshold Method ◽  
Compound Distribution ◽  
Typhoon Wave ◽  
Peak Over Threshold ◽  
Peak Over Threshold Method ◽  
Maximum Entropy Distribution

Using the maximum typhoon wave height series observed at Nakagusukuwan Observation Station in Japan, a novel compound distribution, Poisson-maximum entropy distribution, is proposed to calculate typhoon wave height return values. In this paper, both the Annual Maximum method and Peak Over Threshold method are adopted for long-term wave height analysis. Calculation results by Peak Over Threshold method show that the choice of threshold slightly affects the return values of wave height under the same long statistical series. For a relatively short sample by the Peak Over Threshold method, the estimation accuracy is still higher under the condition that the maximum typhoon wave height is included in the statistical sample.

scholarly journals Study on reservoir time-varying design flood of inflow based on Poisson process with time-dependent parameters

2018 ◽  
Vol 379 ◽  
pp. 119-123
Author(s):  
Jiqing Li ◽  
Jing Huang ◽  
Jianchang Li
Keyword(s):  
Poisson Process ◽  
Flood Control ◽  
Time Dependent ◽  
Model Parameters ◽  
Time Varying ◽  
Design Flood ◽  
Threshold Method ◽  
Peak Over Threshold ◽  
Peak Over Threshold Method ◽  
The Relationship

Abstract. The time-varying design flood can make full use of the measured data, which can provide the reservoir with the basis of both flood control and operation scheduling. This paper adopts peak over threshold method for flood sampling in unit periods and Poisson process with time-dependent parameters model for simulation of reservoirs time-varying design flood. Considering the relationship between the model parameters and hypothesis, this paper presents the over-threshold intensity, the fitting degree of Poisson distribution and the design flood parameters are the time-varying design flood unit period and threshold discriminant basis, deduced Longyangxia reservoir time-varying design flood process at 9 kinds of design frequencies. The time-varying design flood of inflow is closer to the reservoir actual inflow conditions, which can be used to adjust the operating water level in flood season and make plans for resource utilization of flood in the basin.

scholarly journals Analysis of extreme hydrological Events on THE danube using the Peak Over Threshold method

2010 ◽  
Vol 58 (2) ◽  
pp. 88-101 ◽  
Author(s):  
Veronika Bačová-Mitková ◽  
Milan Onderka
Keyword(s):  
Danube River ◽  
Data Series ◽  
Time Data ◽  
Threshold Method ◽  
Series Length ◽  
Discharge Data ◽  
Peak Over Threshold ◽  
Peak Over Threshold Method ◽  
Daily Discharge ◽  
Extreme Hydrological Events

Analysis of extreme hydrological Events on THE danube using the Peak Over Threshold methodThe Peak Over Threshold Method (POT) was used as an alternative technique to the traditional analysis of annual discharge maxima of the Danube River. The POT method was applied to a time-series of daily discharge values covering a period of 60 years (1931-1990) at the following gauge stations: Achleiten, Kienstock, Wien, Bratislava and Nagymaros. The first part of the paper presents the use of the POT method and how it was applied to daily discharges. All mean daily discharges exceeding a defined threshold were considered in the POT analysis. Based on the POT waves independence criteria the maximum daily discharge data were selected. Two theoretical log-normal (LN) and Log-Pearson III (LP3) distributions were used to calculate the probability of exceeding annual maximum discharges. Performance of the POT method was compared to the theoretical distributions (LN, LP3). The influence of the data series length on the estimation of theN-year discharges by POT method was carried out too. Therefore, with regard to later regulations along the Danube channel bank the 40, 20 and 10-year time data series were chosen in early of the 60-year period and second analysed time data series were selected from the end of the 60-year period. Our results suggest that the POT method can provide adequate and comparable estimates ofN-year discharges for more stations with short temporal coverage.

Predictions of Extreme Values of Significant Wave Height

2003 ◽  
Author(s):  
C. Guedes Soares ◽  
R. G. Ferreira ◽  
Manuel G. Scotto
Keyword(s):  
Extreme Value Theory ◽  
Significant Wave Height ◽  
Extreme Values ◽  
Value Theory ◽  
Environmental Data ◽  
Threshold Method ◽  
Peak Over Threshold ◽  
Peak Over Threshold Method ◽  
Low Probability ◽  
Quantile Estimates

This paper provides an overview of different methods of extrapolating environmental data to low probability levels based on the extreme value theory. It discusses the Annual Maxima method and the Peak Over Threshold method, using unified terminology and notation. Furthermore, it describes a method based on the r largest order statistics that has the advantage of providing more accurate parameters and quantile estimates than the Annual Maxima method. Several examples illustrate the methodology and reveal strengths and weaknesses of the various approaches.

Return Value Estimation of Significant Wave Heights With Maximum Entropy Distribution

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
S. Dong ◽  
W. Liu ◽  
L. Z. Zhang ◽  
C. Guedes Soares
Keyword(s):  
Maximum Entropy ◽  
North Sea ◽  
Significant Wave ◽  
The North ◽  
Compound Distribution ◽  
Wave Heights ◽  
The North Sea ◽  
Significant Wave Heights ◽  
Maximum Entropy Distribution ◽  
Return Value

The maximum entropy distribution is proposed to fit the long term and extreme distribution of significant wave heights from which return value estimates are derived. The maximum entropy distribution is applied to data from two sites of different characteristics, namely from Japan characterized by the occurrence of typhoons and from the North Sea with continuous variation of sea state intensity. The compound distribution, Poisson-maximum entropy distribution, is described and adopted to model the data from these two locations. It is shown that in the case of continuous data from the North Sea, this model does not bring any advantage over the direct application of the maximum entropy distribution to adjust the significant wave heights larger than different thresholds. For this case the maximum entropy distribution provides good fits.

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