scholarly journals Modeling of probability in obtaining intensity-duration-frequency relationships of rainfall occurrence for Pelotas, RS, Brazil

2019 ◽  
Vol 23 (7) ◽  
pp. 499-505
Author(s):  
Viviane R. Dorneles ◽  
Rita de C. F. Damé ◽  
Claudia F. A. Teixeira-Gandra ◽  
Patrick M. Veber ◽  
Gustavo B. Klumb ◽  
...  
Keyword(s):  
Empirical Model ◽  
Probability Distributions ◽  
Likelihood Method ◽  
Return Periods ◽  
Intense Rainfall ◽  
Maximum Rainfall ◽  
Rainfall Occurrence ◽  
Historical Series ◽  
Intensity Duration Frequency ◽  
Log Normal

ABSTRACT Based on historical series, for each locality, equations can characterize the relationship between intensity, duration and frequency of rainfall occurrence. The objective of this study was to present two equations that can describe the occurrence of intense rainfall in Pelotas, RS state, over the period 1982-2015. The two equations were denominated conventional and hybrid, depending on the probabilistic model used. Following the conventional methodology, the parameters of Normal, Log-Normal, Gumbel and Gamma probability distributions were adjusted by the maximum likelihood method for return periods of 2, 5, 10, 20, 25, 50 and 100 years. The maximum intensity values for the hybrid equation were obtained using the empirical model of Weibull, considering return periods of 2, 5, 10, 20 and 25 years. On the other hand, the same theoretical distributions used in the conventional equation were applied to return periods of 50 and 100 years. The Kolmogorov-Smirnov test was used to select the best fitting distribution for the data. In order to verify the information acquired through the Weibull empirical model in comparison to the theoretical distributions, the t-test was applied to the angular coefficients. Significant differences were not verified between the values of maximum rainfall intensities obtained using the two methodologies, for the pre-established durations and return periods. Thus, considering the maximum rainfall intensities values (durations of 5-1440 min) and return periods of 2-100 years in the municipality of Pelotas, RS, Brazil, both the hybrid and the conventional intense rainfall equations can be used.

scholarly journals Estimate of intense rainfall equation parameters for rainfall stations of the Paraíba State, Brazil

2017 ◽  
Vol 47 (1) ◽  
pp. 15-21
Author(s):  
Alcinei Ribeiro Campos ◽  
João Batista Lopes da Silva ◽  
Glenio Guimarães Santos ◽  
Rafael Felippe Ratke ◽  
Itauane Oliveira de Aquino
Keyword(s):  
Goodness Of Fit ◽  
Probability Distributions ◽  
Daily Rainfall ◽  
Water Source ◽  
Rainfall Data ◽  
Intense Rainfall ◽  
Probability Models ◽  
Temporal And Spatial Distribution ◽  
Intensity Duration Frequency ◽  
Log Normal

ABSTRACT Rainfall is the primary water source for hydrographic basins. Hence, the quantification and knowledge of its temporal and spatial distribution are indispensable in dimensioning hydraulic projects. This study aimed at assessing the fit of a series of rainfall data to different probability models, as well as estimating parameters of the intensity-duration-frequency (IDF) equation for rain stations of the Paraíba State, Brazil. The rainfall data of each station were obtained from the Brazilian Water Agency databanks. To estimate the maximum daily rainfall of each station and return period (5, 10, 15, 25, 50 and 100 years), the following probability distributions were used: Gumbel, Log-Normal II, Log-Normal III, Pearson III and Log-Pearson III. The estimation of rainfall in durations of 5-1,440 min was carried out by daily rainfall disaggregation. The adjustment of the IDF equation was performed via nonlinear multiple regression, using the nonlinear generalized reduced gradient interaction method. When compared to the data observed, the intense rainfall equations for most stations showed goodness of fit with coefficients of determination above 0.99, which supports the methodology applied in this study.

scholarly journals Development of Intensity Duration Frequency (IDF) Curves for Rainfall Prediction within the Middle Niger River Basin

2020 ◽  
Vol 4 (2) ◽  
pp. 382-397
Author(s):  
J. O. Ehiorobo ◽  
O.C. Izinyon ◽  
R. I. Ilaboya
Keyword(s):  
River Basin ◽  
Rainfall Intensity ◽  
Rainfall Data ◽  
Annual Maximum ◽  
Return Periods ◽  
Maximum Rainfall ◽  
Niger River ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Best Fit

Rainfall Intensity-Duration-Frequency (IDF) relationship remains one of the mostly used tools in hydrology and water resources engineering, especially for planning, design and operations of water resource projects. IDF relationship can provide adequate information about the intensity of rainfall at different duration for various return periods. The focus of this research was to develop IDF curves for the prediction of rainfall intensity within the middle Niger River Basin (Lokoja and Ilorin) using annual maximum daily rainfall data. Forty (40) year’s annual maximum rainfall data ranging from 1974 to 2013 was employed for the study. To ascertain the data quality, selected preliminary analysis technique including; descriptive statistics, test of homogeneity and outlier detection test were employed. To compute the three hours rainfall intensity, the ratio of rainfall amount and duration was used while the popular Gumbel probability distribution model was employed to calculate the rainfall frequency factor. To assess the best fit model that can be employed to predict rainfall intensity for various return periods at ungauged locations, four empirical IDF equations, namely; Talbot, Bernard, Kimijima and Sherman equations were employed. The model with the least calculated sum of minimized root mean square error (RMSE) was adopted as the best fit empirical model. Results obtained revealed that the Talbot model was the best fit model for Ilorin and Lokoja with calculated sum of minimized error of 1.32170E-07 and 8.953636E-08. This model was thereafter employed to predict the rainfall intensity for different durations at 2, 5, 10, 25, 50 and 100yrs return periods respectively.

scholarly journals Análise da adequação de eventos de precipitação extrema na Amazônia Ocidental em modelos estáticos: Rondônia

2015 ◽  
Vol 10 (3) ◽  
pp. 13
Author(s):  
Vinicius Alexandre Sikora de Souza ◽  
Marcos Leando Alves Nunes ◽  
Sandra Ferronatto Francener ◽  
Ana Lúcia Denardin da Rosa
Keyword(s):  
Extreme Rainfall ◽  
Hydraulic Structures ◽  
Font Size ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Historical Series ◽  
Kolmogorov Smirnov ◽  
Intensity Duration Frequency ◽  
Log Normal ◽  
Smirnov Test

<p><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman','serif'; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-ansi-language: PT-BR; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Este estudo objetivou estimar a função Intensidade-Duração-Frequência (IDF) de eventos pluviométricos extremos a partir dos dados de precipitação das estações pluviométricas instaladas no estado de Rondônia, de modo que posteriormente tais informações possam ser utilizadas no dimensionamento de obras hidráulicas. Utilizou-se 41 estações pluviométricas com séries históricas acima de 10 anos, disponibilizadas pela Agência Nacional de Águas (ANA). Essas séries passaram inicialmente pelo teste de aderência Kolmogorov-Smirnov (KS), a fim de verificar o ajuste das mesmas as </span><span style="font-size: 12pt; line-height: 115%; font-family: 'Times New Roman', serif;">distribuições: Normal, Log-Normal, Exponencial, Gama, Gumbel, Weibull e Logística</span><span style="font-size: 12pt; line-height: 115%; font-family: 'Times New Roman', serif;">. O trabalho denotou que o teste de aderência </span><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman','serif'; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-ansi-language: PT-BR; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Kolmogorov-Smirnov de forma geral forneceu uma expressiva aceitação na maioria das distribuições estatística testadas.</span></p><p> </p><p align="center"><strong><em>Analysis of fitness for extreme rainfall events in western amazon in static models: state Rondônia</em></strong></p><p> </p><p><strong>ABSTRACT: </strong>This study aimed to estimate the Intensity - Duration - Frequency (IDF) function extreme rainfall events from the data of precipitation of rainfall stations located in the State of Rondônia, so that such information can be later used in hydraulic structures. We used 41 rainfall stations with historical series over 10 years, provided by the National Water Agency (ANA). These series originally started by adherence Kolmogorov -Smirnov (KS) in order to check the fit of the same distributions: Normal, Log- Normal, Exponential, Gamma, Gumbel, Weibull and Logistics. Work denoted that the Kolmogorov - Smirnov test of adherence generally provided a significant acceptance in most of the tested statistical distributions.<strong></strong></p><p><span style="font-size: 12.0pt; line-height: 115%; font-family: 'Times New Roman','serif'; mso-fareast-font-family: Calibri; mso-fareast-theme-font: minor-latin; mso-ansi-language: PT-BR; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;"><br /></span></p>

scholarly journals Extreme rainfall and IDF equations for Alagoas State, Brazil

2020 ◽  
Vol 15 (6) ◽  
pp. 1
Author(s):  
Álvaro José Back ◽  
Sabrina Baesso Cadorin ◽  
Sérgio Luciano Galatto
Keyword(s):  
Hydrological Modeling ◽  
Probability Distributions ◽  
Gumbel Distribution ◽  
Extreme Rainfall ◽  
Maximum Rainfall ◽  
Gev Distribution ◽  
Significance Level ◽  
Intensity Duration Frequency ◽  
Conservation Projects ◽  
Anderson Darling

Intensity-duration-frequency (IDF) equations have important applications in several engineering areas such as urban drainage designs, hydrological modeling, and soil conservation projects. This study analyzes the annual maximum series and fits IDF equations for 44 rainfall stations in Alagoas State, Brazil. We adjusted parameters of the Gumbel distribution (GD) and the Generalized Extreme Value (GEV) distribution. The fitting of the observed data to the probability distributions, as well as the selection of the best distribution, were based on the Kolmogorov-Smirnov and Anderson-Darling tests at a 5% significance level. The GEV distribution with parameters obtained by the L-moments method was considered the best in 73% of rainfall stations. The estimated IDF equations showed a good fit, with determination coefficients above 0.991. The maximum rainfall intensities have spatial variation following the climatic zones of the state. The fitted equations allow estimating rainfall intensities from 5 minutes to 24 hours with a return period of 2 to 100 years, and standard error of less than 6.83 mm h-1.

scholarly journals ESTIMATE OF THE INTENSITY-DURATION-FREQUENCY PARAMETERS OF INTENSE RAINFALL FOR THE STATE OF ALAGOAS, BRAZIL

2020 ◽  
Vol 28 ◽  
pp. 314-325
Author(s):  
João Batista Lopes da Silva ◽  
Nicole Lopes Bento ◽  
Gabriel Soares Lopes Gomes ◽  
Alcinei Ribeiro Campos ◽  
Danilo Paulúcio da Silva
Keyword(s):  
Return Period ◽  
Probabilistic Models ◽  
Daily Rainfall ◽  
The State ◽  
Data Series ◽  
Intense Rainfall ◽  
Maximum Rainfall ◽  
Rain Gauges ◽  
Intensity Duration Frequency ◽  
Using Data

The study of the rainfall characteristics is of fundamental importance since the frequency of floods has increased in several parts of Brazil due to anthropic impacts of climatic changes. Thus, this study aimed to determine the parameters of the intense rainfall equation (K, a, b, c) for 52 municipalities in the State of Alagoas using data from 164 rain gauges ta available from the National Water Agency (ANA). The data series were subjected to consistency analysis and further desegregation of maximum daily rainfall to durations of the 5; 10; 15; 20; 25; 30; 60; 360; 480; 600; 720 and 1,440 minutes and return period of 5; 10; 25; 50 and 100 years according to different probabilistic models. The adjustment of the parameters was carried out by means of non-linear regression, with R² greater than 0.949 for all the stations, considering for this purpose one station per municipality, totaling 51 municipalities of study. It was obtained that the maximum rainfall intensity predicted increases with the increase in the return period and decreases with the increase of the duration of the rain. The greater intensities were detected in the mesoregion of Eastern Alagoano and the lowest intensities in the mesoregion of Sertão Alagoano.

scholarly journals Intercomparison of estimators of extreme value family of distributions for rainfall frequency analysis

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 59-70
Author(s):  
N. VIVEKANANDAN
Keyword(s):  
Goodness Of Fit ◽  
Probability Distributions ◽  
Extreme Value ◽  
Qualitative Assessment ◽  
Likelihood Method ◽  
Extreme Value Analysis ◽  
Chi Square ◽  
Maximum Rainfall ◽  
Value Analysis ◽  
Family Of Distributions

Estimation of rainfall for a given return period is of utmost importance for planning and design of minor and major hydraulic structures. This can be achieved through Extreme Value Analysis (EVA) of rainfall by fitting Extreme Value family of Distributions (EVD) such as Generalized Extreme Value, Extreme Value Type-1, Extreme Value Type-2 and Generalized Pareto to the series of observed Annual 1-Day Maximum Rainfall (AMR) data. Based on the intended applications and the variate under consideration, Method of Moments (MoM), Maximum Likelihood Method (MLM) and L-Moments (LMO) are used for determination of parameters of probability distributions. The adequacy of fitting EVD to the AMR series was evaluated by quantitative assessment using Goodness-of-Fit (viz., Chi-square and Kolmogorov-Smirnov) and diagnostic test (viz., D-index) tests and qualitative assessment by the fitted curves of the estimated rainfall. The paper presents a study on intercomparison of EVD (using MoM, MLM and LMO) adopted in EVA of rainfall with illustrative example and the results obtained thereof. 

scholarly journals Evaluation of probability distributions in the analysis of minimum temperature series in Manaus – AM

2021 ◽  
Vol 10 (3) ◽  
pp. e46210313616
Author(s):  
Yana Miranda Borges ◽  
Breno Gabriel da Silva ◽  
Brian Alvarez Ribeiro de Melo ◽  
Robério Rebouças da Silva
Keyword(s):  
Probability Distributions ◽  
Information Criterion ◽  
Biological Species ◽  
Temperature Series ◽  
Likelihood Method ◽  
Historical Temperature ◽  
Anderson Darling ◽  
Log Normal ◽  
Von Mises ◽  
Best Fit

The relevance in studying climatological phenomena is based on the influence that variables of this nature exert on the world. Among the most observed variables, temperature stands out, whose effect of its variation may cause significant impacts, such as the proliferation of biological species, agricultural production, population health, etc. Probability distributions have been studied to verify the best fit to describe and/or predict the behavior of climate variables and, in this context, the present study evaluated, among six probability distributions, the best fit to describe a historical temperature series. minimum monthly mean. The series used in this study encompass a period of 38 years (1980 to 2018) separated by month from the weather station of the Manaus - AM station (OMM: 82331) obtained from INMET, totaling 459 observations. Difference-Sign and Turning Point tests were used to verify data independence and the maximum likelihood method to estimate the parameters. Kolmogorov-Smirnov, Anderson-Darling, Cramér-von Mises, Akaike Information Criterion and quantile-quantile plots were used to select the best fit distribution. Log-Normal, Gama, Weibull, Gumbel type II, Benini and Rice distributions were evaluated, with the best performing Rice, Log-Normal and Gumbel II distributions being highlighted.

Effect of Turbulence Variation on Extreme Loads Prediction for Wind Turbines

2002 ◽  
Author(s):  
Patrick J. Moriarty ◽  
William E. Holley ◽  
Sandy Butterfield
Keyword(s):  
Normal Distribution ◽  
Empirical Model ◽  
Probability Distributions ◽  
Joint Probability ◽  
Parametric Model ◽  
Turbulence Level ◽  
Extreme Loads ◽  
Aeroelastic Simulations ◽  
Log Normal

The effect of varying turbulence levels on long-term loads extrapolation techniques was examined using a joint probability density function of both mean wind speed and turbulence level for loads calculations. The turbulence level has a dramatic effect on the statistics of moment maxima extracted from aeroelastic simulations. Maxima from simulations at lower turbulence levels are more deterministic and become dominated by the stochastic component as turbulence level increases. Short-term probability distributions were calculated using four different moment-based fitting methods. Several hundred of these distributions were used to calculate a long-term probability function. From the long-term probability, 1- and 50-year extreme loads were estimated. As an alternative, using a normal distribution of turbulence level produced a long-term load comparable to that of a log-normal distribution and may be more straightforward to implement. A parametric model of the moments was also used to estimate the extreme loads. The parametric model predicted nearly identical loads to the empirical model and required less data. An input extrapolation technique was also examined. Extrapolating the turbulence level prior to input into the aeroelastic code simplifies the loads extrapolation procedure but, in this case, produces loads lower than the empirical model and may be non-conservative in general.

scholarly journals Selection of Hydrological Probability Distributions for Extreme Rainfall Events in the Regions of Colombia

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1397 ◽  
Author(s):  
Óscar E. Coronado-Hernández ◽  
Ernesto Merlano-Sabalza ◽  
Zaid Díaz-Vergara ◽  
Jairo R. Coronado-Hernández
Keyword(s):  
Frequency Analysis ◽  
Probability Distributions ◽  
Extreme Rainfall ◽  
Return Periods ◽  
Extreme Rainfall Events ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Moments Method ◽  
Engineering Projects ◽  
Selection Of

Frequency analysis of extreme events is used to estimate the maximum rainfall associated with different return periods and is used in planning hydraulic structures. When carrying out this type of analysis in engineering projects, the hydrological distributions that best fit the trend of maximum 24 h rainfall data are unknown. This study collected maximum 24 h rainfall records from 362 stations distributed throughout Colombia, with the goal of guiding hydraulic planners by suggesting the probability distributions they should use before beginning their analysis. The generalized extreme value (GEV) probability distribution, using the weighted moments method, presented the best fits of frequency analysis of maximum daily precipitation for various return periods for selected rainfall stations in Colombia.

scholarly journals Daily rainfall disaggregation for Tocantins State, Brazil

2017 ◽  
Vol 12 (4) ◽  
pp. 605 ◽  
Author(s):  
Virgilio Lourenço da Silva Neto ◽  
Marcelo Ribeiro Viola ◽  
Demetrius David da Silva ◽  
Carlos Rogério de Mello ◽  
Silvio Bueno Pereira ◽  
...  
Keyword(s):  
Probability Distribution ◽  
Short Duration ◽  
Daily Rainfall ◽  
Hydraulic Structures ◽  
Return Periods ◽  
Intense Rainfall ◽  
Chi Square ◽  
Historical Series ◽  
Kolmogorov Smirnov ◽  
Comparison Of The Results

In order to design effective Brazilian hydraulic structures, it is necessary to obtain data relating to short-duration intense rainfall from historical series of daily rainfall. This recurring need can be fulfilled by rainfall disaggregation methodology. The objective of this study was to determine the intense rainfall disaggregation constants for the State of Tocantins and to compare these constants with those obtained for other regions of Brazil. For the modeling of the frequency of intense rainfall of different durations of less than 24 hours, the Gumbel probability distribution (GPD) was employed using rainfall series from 10 locations in Tocantins state. The results showed that the GPD was adequate by the Kolmogorov-Smirnov and Chi-square tests. The disaggregation constants presented low variability values for different return periods (from 10 to 100 years); the values for Tocantins state are: h12h/h24h=0.93, h6h/h24h=0.86, h4h/h24h=0.82, h3h/h24h=0.78, h2h/h24h=0.72, h1h/h24h=0.61, h50min/h1h=0.92, h40min/h1h=0.83, h30min/h1h=0.68, h20min/h30min=0.76 e h10min/h30min=0.46. The comparison of the results with those from studies developed for other Brazilian regions showed variations of up to -62.30%, allowing us to conclude that the use of local constants is important in the process of rainfall disaggregation.

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