A stochastic study of floods in Canada: frequency analysis and regionalization

1991 ◽  
Vol 18 (2) ◽  
pp. 225-236 ◽  
Author(s):  
Daniel Caissie ◽  
Nassir El-Jabi
Keyword(s):  
Frequency Analysis ◽  
Extreme Values ◽  
Flood Frequency ◽  
Independent Random Variables ◽  
Time Interval ◽  
Partial Duration Series ◽  
Stream Discharge ◽  
Index Flood ◽  
One Year

Peak stream discharge is a hydrologic parameter that is very important for the determination of flood risk, design of engineering works, and management of water resources. In this study, some 237 stream records across Canada were analyzed using the theory of stochastic processes applied to extreme values. This model, based on partial duration series analysis, was applied to each stream record, considering the time of occurrence of floods to be a Poisson process. In addition, exceedances (values above a given discharge level or truncation level) were considered to be independent random variables identically distributed over a one-year time interval. After this frequency analysis of each stream record, a regionalization of the flood frequency characteristics in Canada was performed using two different approaches: multiple regression analysis and index-flood method. A comparison of the two approaches was carried out by examining mean relative error and root-mean-square error. It was determined that the level of difficulty in applying the stochastic flood model was not the same across Canada. Moreover, error associated with the index-flood method is mainly due to error in estimating low return floods. Key words: flood, partial duration series, regional hydrology, index-flood method, low return flood.

scholarly journals Determination of return period for flood frequency analysis using normal and related distributions

2017 ◽  
Vol 890 ◽  
pp. 012162 ◽  
Author(s):  
Wan Husna Aini Wan Deraman ◽  
Noor Julailah Abd Mutalib ◽  
Nur Zahidah Mukhtar
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Flood Frequency ◽  
Flood Frequency Analysis

A comparison of index flood estimation procedures for ungauged catchments

2002 ◽  
Vol 29 (5) ◽  
pp. 734-741 ◽  
Author(s):  
Patrick L Grover ◽  
Donald H Burn ◽  
Juraj M Cunderlik
Keyword(s):  
Parameter Estimation ◽  
Frequency Analysis ◽  
Ordinary Least Squares ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Data Series ◽  
Frequency Curve ◽  
Estimation Techniques ◽  
Index Flood ◽  
Parameter Estimation Techniques

Flood frequency analysis is used by water resources professionals to estimate the probability of exceedence associated with a flood of a given magnitude. The estimation of flood frequencies is important because they are used in the planning and design of hydraulic structures, in flood-plain management, and in reservoir operation. The index flood method is commonly used to develop a flood frequency curve that relates flood magnitude to flood rarity. This method involves scaling a dimensionless flood frequency curve by the index flood. The index flood is a middle-sized flood for which the mean or median of the flood data series is typically used. When the catchment of interest is ungauged, statistical models, such as multiple regression, are often used to relate the index flood to catchment descriptors. In this study six different parameter estimation techniques and three regionalization techniques are compared in terms of ability to predict the index flood for an ungauged catchment. A case study employing a split-sample experiment with data from catchments in Ontario, Canada, was used to evaluate the approaches. The models were assessed using three performance indices to evaluate the capability to predict the index flood for 20 stations. The dimensionless nonlinear model outperformed all of the other parameter estimation techniques for each of the three indices selected. The performance was improved through the use of geostatistical residual mapping, however, the improvement was small. The residual mapping was found to greatly improve the estimates obtained using ordinary least-squares regression.Key words: index flood, flood frequency analysis, regression, residual mapping, geostatistics.

scholarly journals Effectiveness and Optimization of Harbour Tug Fleet

2018 ◽  
Vol 19 (2) ◽  
pp. 140-150
Author(s):  
Oleksandr Bondarenko ◽  
Valery Nekrasov ◽  
Oleksii Yastreba
Keyword(s):  
Low Cost ◽  
Random Variables ◽  
Weather Conditions ◽  
Time Interval ◽  
Fleet Composition ◽  
Conditional Time ◽  
Economic Indexes ◽  
One Year ◽  
Selection Of

Abstract Determination of efficiency and optimization harbour tug fleet is based on simulation of fleet work and usage for this the methods of ship dynamics and probability theory. Visiting the port transport vessels of possible types is considered as random stream of given intensity. This stream is distributed over the berths. Productivities of berths are given random variables. Random variables are also characteristics of weather conditions in the harbour basin. Tug fleet is represented by the collection of existing port tugs of different types. Work of tugs is determined by operations of approaching to ships, escorting theirs in the near-port waters, posting on the approach channels, transportation within the port waters, berthing, unberthing and going out the ship from the port with the repetition of functioning operations in reverse order. Selection of tugs to service the next arriving or departing ship is dependent from the intensity of the current weather conditions in the port and busyness of tugs in operations with other ships. Work fleet is considered on the conditional time interval of one year. In this time the efficiency of the tug fleet is defined by economic indexes of fulfilment of all towing operations and operations on maintenance tugs. Optimization of the fleet composition is carried out according to the criteria required minimum total bollard pull, low cost and high profit. Based on performed research a program for calculating the efficiency and optimization of the port towing fleet is composed. The program can be adapted to any port with whatever types of tugs.

scholarly journals A Comparative Flood Frequency Analysis of High-Flow between Annual Maximum and Partial Duration Series at Sungai Langat Basin

2021 ◽  
Vol 50 (7) ◽  
pp. 1843-1856
Author(s):  
Firdaus Mohamad Hamzah ◽  
Hazrina Tajudin ◽  
Othman Jaafar
Keyword(s):  
Frequency Analysis ◽  
Threshold Value ◽  
Flood Frequency ◽  
High Flow ◽  
Flood Frequency Analysis ◽  
Annual Maximum ◽  
Partial Duration Series ◽  
Flood Impacts ◽  
Generalized Pareto ◽  
Flood Estimation

Flood frequency analysis should consider small and frequent floods. Despite the complexities in partial duration series implementation, it can give a better flood estimation in a way that it does not exclude any significant high flow events, even if it is not the highest event of the year. This study employs the streamflow data recorded at Kajang station, Sungai Langat, Malaysia over a 36-year period spanning from 1978 to 2013. The paper attempts to conduct flood frequency analysis using two approaches, annual maximum and partial duration series. The optimal threshold value is selected to be 48.7 m3/s, where the dispersion index stabilizes at around 1, DI = 1 . The results have shown that generalized extreme value (GEV) distribution describes the annual maximum data while the lognormal (LN3) and generalized Pareto (GPA) distribution is chosen as the best fit distribution at Kajang station for a partial duration series. There is a slight difference between estimated streamflow magnitude when using GPA and LN3 for selected return periods, while a considerable difference was observed when using annual maximum at a higher return period. As a conclusion, PDS gives more relevant magnitude estimation rather than AMS. Flood frequency plays an important role in understanding the nature and magnitude of high flow, which in turn can assist relevant agencies in the design of hydrological structures and reduce flood impacts.

scholarly journals Technical Note: Flood frequency study using partial duration series coupled with entropy principle

2021 ◽  
Author(s):  
Sonali Swetapadma ◽  
Chandra Shekhar Prasad Ojha
Keyword(s):  
Frequency Analysis ◽  
Predictive Ability ◽  
Technical Note ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Bootstrap Sampling ◽  
Design Flood ◽  
Distribution Models ◽  
Discharge Data ◽  
Partial Duration Series

Abstract. Quality discharge measurements and frequency analysis are two major prerequisites for defining a design flood. Flood frequency analysis (FFA) utilizes a comprehensive understanding of the probabilistic behavior of extreme events but has certain limitations regarding the sampling method and choice of distribution models. Entropy as a modern-day tool has found several applications in FFA, mainly in the derivation of probability distributions and their parameter estimation as per the principle of maximum entropy (POME) theory. The present study explores a new dimension to this area of research, where POME theory is applied in the partial duration series (PDS) modeling of FFA to locate the optimum threshold and the respective distribution models. The proposed methodology is applied to the Waimakariri River at the Old Highway Bridge site in New Zealand, as it has one of the best quality discharge data. The catchment also has a history of significant flood events in the last few decades. The degree of fitness of models to the exceedances is compared with the standardized statistical approach followed in literature. Also, the threshold estimated from this study is matched with some previous findings. Various return period quantiles are calculated, and their predictive ability is tested by bootstrap sampling. An overall analysis of results shows that entropy can be also be used as an effective tool for threshold identification in PDS modeling of flood frequency studies.

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