A COMPARATIVE STUDY ON PEAK FLOOD DISCHARGE ESTIMATES BY EXTREME VALUE FAMILY OF PROBABILITY DISTRIBUTIONS

2020 ◽  
Vol 16 (1) ◽  
pp. 1
Author(s):  
N. VIVEKANANDAN ◽  
Keyword(s):  
Comparative Study ◽  
Probability Distributions ◽  
Extreme Value ◽  
Flood Discharge ◽  
Peak Flood

On the Probability Distribution of Mooring Line Tensions in a Directional Environment

2011 ◽  
Author(s):  
Jan Mathisen ◽  
Siril Okkenhaug ◽  
Kjell Larsen
Keyword(s):  
Time Series ◽  
Probability Distributions ◽  
Extreme Value Distribution ◽  
Line Tension ◽  
Extreme Value ◽  
Mooring Line ◽  
Large Set ◽  
Short Term ◽  
Reliability Method ◽  
Line Design

A joint probabilistic model of the metocean environment is assembled, taking account of wind, wave and current and their respective heading angles. Mooring line tensions are computed in the time domain, for a large set of short-term stationary conditions, intended to span the domain of metocean conditions that contribute significantly to the probabilities of high tensions. Weibull probability distributions are fitted to local tension maxima extracted from each time series. Long time series of 30 hours duration are used to reduce statistical uncertainty. Short-term, Gumbel extreme value distributions of line tension are derived from the maxima distributions. A response surface is fitted to the distribution parameters for line tension, to allow interpolation between the metocean conditions that have been explicitly analysed. A second order reliability method is applied to integrate the short-term tension distributions over the probability of the metocean conditions and obtain the annual extreme value distribution of line tension. Results are given for the most heavily loaded mooring line in two mooring systems: a mobile drilling unit and a production platform. The effects of different assumptions concerning the distribution of wave heading angles in simplified analysis for mooring line design are quantified by comparison with the detailed calculations.

Peak Flood Discharge Confidence Limits

1969 ◽  
Vol 95 (1) ◽  
pp. 161-174
Author(s):  
Richard M. Shane ◽  
Walter R. Lynn
Keyword(s):  
Confidence Limits ◽  
Flood Discharge ◽  
Peak Flood

scholarly journals Geospatial Modelling of Watershed Peak Flood Discharge in Selangor, Malaysia

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2490 ◽  
Author(s):  
Ryan Cheah ◽  
Lawal Billa ◽  
Andy Chan ◽  
Fang Yenn Teo ◽  
Biswajeet Pradhan ◽  
...  
Keyword(s):  
Hydrological Modeling ◽  
Estimation Methods ◽  
Coefficient Of Determination ◽  
Storm Event ◽  
Storm Events ◽  
Unit Hydrograph ◽  
Runoff Simulation ◽  
Flood Discharge ◽  
Geospatial Modelling ◽  
Peak Flood

Conservative peak flood discharge estimation methods such as the rational method do not take into account the soil infiltration of the precipitation, thus leading to inaccurate estimations of peak discharges during storm events. The accuracy of estimated peak flood discharge is crucial in designing a drainage system that has the capacity to channel runoffs during a storm event, especially cloudbursts and in the analysis of flood prevention and mitigation. The aim of this study was to model the peak flood discharges of each sub-watershed in Selangor using a geographic information system (GIS). The geospatial modelling integrated the watershed terrain model, the developed Soil Conservation Service Curve Cumber (SCS-CN) and precipitation to develop an equation for estimation of peak flood discharge. Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) was used again to simulate the rainfall-runoff based on the Clark-unit hydrograph to validate the modelled estimation of peak flood discharge. The estimated peak flood discharge showed a coefficient of determination, r2 of 0.9445, when compared with the runoff simulation of the Clark-unit hydrograph. Both the results of the geospatial modelling and the developed equation suggest that the peak flood discharge of a sub-watershed during a storm event has a positive relationship with the watershed area, precipitation and Curve Number (CN), which takes into account the soil bulk density and land-use of the studied area, Selangor in Malaysia. The findings of the study present a comparable and holistic approach to the estimation of peak flood discharge in a watershed which can be in the absence of a hydrodynamic simulation model.

A comparative study of alternative extreme-value volatility estimators

2005 ◽  
Vol 25 (9) ◽  
pp. 873-892 ◽  
Author(s):  
Turan G. Bali ◽  
David Weinbaum
Keyword(s):  
Comparative Study ◽  
Extreme Value

scholarly journals Quantifying the contribution of flood intensity indicators with the projection pursuit model

2017 ◽  
Vol 49 (1) ◽  
pp. 60-71 ◽  
Author(s):  
Lina Wang ◽  
Yanqing Lian ◽  
Xiaohong Chen
Keyword(s):  
Southern China ◽  
Projection Pursuit ◽  
Flood Events ◽  
Flood Duration ◽  
Flood Discharge ◽  
Wujiang River ◽  
Flood Volume ◽  
Projection Pursuit Model ◽  
Flood Intensity ◽  
Peak Flood

Abstract Identifying the various factors that affect the intensity of a flood event, such as its duration and volume, is essential for strategic planning and flood management. Further, quantifying the impacts of these major factors on flood intensity using the contribution rate is essential, but technically challenging. In this study, the authors have adopted the projection pursuit model to quantify the contribution rates of peak flood stage and peak flood discharge, flood duration, and total flood volume (the maximum 12-, 24-, and 72-hour flood volumes) in the Wujiang River in Southern China. This study showed that peak flood discharge and total flood volume were the two dominant factors impacting flood intensity. Although flood duration can be a major factor for some flood events, it contributed the least to flood intensity for most of the historic flood events studied. Likewise, the maximum 24-hour and 72-hour flood volumes contributed little to flood intensity. Findings from this study not only demonstrated the successful adoption of the projection pursuit model for contribution rates, but also provided critical information for planning and managing the regional hydraulic resources in the Wujiang River.

scholarly journals Calibration of NSRP Models from Extreme Value Distributions

Hydrology ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. 89 ◽  
Author(s):  
De Luca ◽  
Galasso
Keyword(s):  
High Resolution ◽  
Probability Distributions ◽  
Mathematical Expression ◽  
Extreme Value ◽  
Extreme Value Distributions ◽  
Data Set ◽  
Maximum Rainfall ◽  
High Resolution Data ◽  
Frequency Distributions ◽  
Annual Maximum Rainfall

In this work, the authors investigated the feasibility of calibrating a model which is suitable for the generation of continuous high-resolution rainfall series, by using only data from annual maximum rainfall (AMR) series, which are usually longer than continuous high-resolution data, or they are the unique available data set for many locations. In detail, the basic version of the Neyman–Scott Rectangular Pulses (NSRP) model was considered, and numerical experiments were carried out, in order to analyze which parameters can mostly influence the extreme value frequency distributions, and whether heavy rainfall reproduction can be improved with respect to the usual calibration with continuous data. The obtained results were highly promising, as the authors found acceptable relationships among extreme value distributions and statistical properties of intensity and duration for the pulses. Moreover, the proposed procedure is flexible, and it is clearly applicable for a generic rainfall generator, in which probability distributions and shape of the pulses, and extreme value distributions can assume any mathematical expression.

scholarly journals Frequency Analysis of Low Flows

1985 ◽  
Vol 16 (2) ◽  
pp. 105-128 ◽  
Author(s):  
G. V. Loganathan ◽  
C. Y. Kuo ◽  
T. C. McCormick
Keyword(s):  
Lower Bounds ◽  
Frequency Analysis ◽  
Probability Distributions ◽  
Flow Analysis ◽  
Extreme Value ◽  
Low Flow ◽  
Type Iii ◽  
Low Flows ◽  
Pearson Type

The transformations (i) SMEMAX (ii) Modified SMEMAX (iii) Power and Probability Distributions (iv) Weibull (α,β,γ) or Extreme value type III (v) Weibull (α,β,0) (vi) Log Pearson Type III (vii) Log Boughton are considered for the low flow analysis. Also, different parameter estimating procedures are considered. Both the Weibull and log Pearson can have positive lower bounds and thus their use in fitting low flow probabilities may not be physically justifiable. A new derivation generalizing the SMEMAX transformation is proposed. A new estimator for the log Boughton distribution is presented. It is found that the Boughton distribution with Cunnane's plotting position provides a good fit to low flows for Virginia streams.

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