scholarly journals Intensity-duration-frequency of maximum rainfall in Mato Grosso State

2020 ◽  
Vol 15 (1) ◽  
pp. 1
Author(s):  
Marlus Sabino ◽  
Adilson Pacheco de Souza ◽  
Eduardo Morgan Uliana ◽  
Luana Lisboa ◽  
Frederico Terra de Almeida ◽  
...  
Keyword(s):  
Extreme Value Distribution ◽  
Absolute Error ◽  
Efficiency Index ◽  
Generalized Extreme Value Distribution ◽  
Return Periods ◽  
Maximum Rainfall ◽  
Mato Grosso ◽  
Significance Level ◽  
Weather Stations ◽  
Intensity Duration Frequency

 Intensive rainfall is an important meteorological variable that is of technical interest in hydraulic projects. This study therefore generated Intensity-Duration-Frequency equations (IDF) for 14 weather stations in Mato Grosso State, based on pluviograph analysis. Annual maximum rainfall data regarding 10-to-1440-minute long rainfall events were collected from digitized daily pluviographs. Data adherence to the generalized extreme value distribution (GEV) was checked through the Kolmogorov-Smirnov test at a 20% significance level. Next, the maximum probable rainfall for return periods such as 2, 5, 10, 20, 30, 50 and 100 years was calculated and the IDF equations were adjusted. The performance of the IDF equations was evaluated based on mean absolute error (MAE), root mean square error (RMSE), bias, Willmott's concordance index and Nash-Sutcliffe efficiency index (ENS). Adjusting the IDF equations was only possible for rainfall durations ranging from 10 to 360 min at each station due to the low frequency of longer rainfalls.  High variation was present in parameters of the IDF equation and in maximum rainfall intensity between stations. The satisfactory performance of the models, as attested to by statistical indices, allows using IDF equations adjusted for rainfall durations from 10 to 360 min, and return periods from 2 to 100 years, in the regions of the Mato Grosso weather stations.

scholarly journals Heavy rainfall equations for Santa Catarina, Brazil

2011 ◽  
Vol 35 (6) ◽  
pp. 2127-2134 ◽  
Author(s):  
Álvaro José Back ◽  
Alan Henn ◽  
José Luiz Rocha Oliveira
Keyword(s):  
Coastal Region ◽  
Daily Rainfall ◽  
Rain Gauge ◽  
Annual Maximum ◽  
Santa Catarina ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Significance Level ◽  
Intensity Duration Frequency ◽  
Annual Maximum Rainfall

Knowledge of intensity-duration-frequency (IDF) relationships of rainfall events is extremely important to determine the dimensions of surface drainage structures and soil erosion control. The purpose of this study was to obtain IDF equations of 13 rain gauge stations in the state of Santa Catarina in Brazil: Chapecó, Urussanga, Campos Novos, Florianópolis, Lages, Caçador, Itajaí, Itá, Ponte Serrada, Porto União, Videira, Laguna and São Joaquim. The daily rainfall data charts of each station were digitized and then the annual maximum rainfall series were determined for durations ranging from 5 to 1440 min. Based on these, with the Gumbel-Chow distribution, the maximum rainfall was estimated for durations ranging from 5 min to 24 h, considering return periods of 2, 5, 10, 20, 25, 50, and 100 years,. Data agreement with the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test, at 5 % significance level. For each rain gauge station, two IDF equations of rainfall events were adjusted, one for durations from 5 to 120 min and the other from 120 to 1440 min. The results show a high variability in maximum intensity of rainfall events among the studied stations. Highest values of coefficients of variation in the annual maximum series of rainfall were observed for durations of over 600 min at the stations of the coastal region of Santa Catarina.

scholarly journals Maximum rainfall probability distributions pattern in Haryana –A case study

2016 ◽  
Vol 8 (4) ◽  
pp. 2029-2036
Author(s):  
Manoj Kumar ◽  
Chander Shekhar ◽  
Veena Manocha
Keyword(s):  
Probability Distribution ◽  
Coefficient Of Variation ◽  
Probability Distributions ◽  
Monsoon Season ◽  
Daily Rainfall ◽  
Extreme Value Distribution ◽  
Generalized Extreme Value Distribution ◽  
Data Set ◽  
Maximum Rainfall ◽  
Maximum Daily Rainfall

The present study has been undertaken to fit best probability distribution of rainfall in Ambala District of Haryana State. The analysis showed that the maximum daily rainfall among the years ranged between 41mm (1980) to 307.9mm (2009) indicating a very large variation during the period of study. The mean of maximum daily rainfall of all years annually is 112.13mm. The means of monthly and weekly values ranged from 33.10-88.92mm and 8.77- 46.28 mm, respectively. The maximum daily rainfall in a year/monsoon season was307.9 mm and monthly maximum daily rainfall in monsoon season ranged from 105 -307.9mm. The weekly maximum daily rainfall ranged from48 mm-307.9 mm. It was also observed that the minimum among the maximum daily rainfall was 41mm for annual, 34mm for season and 0 in all the months and weeks. The maximum value of coefficient of variation was observed in the first week which indicated a large fluctuation in the rainfall data set and minimum value of coefficient of variation 0.464 was observed for the whole year which shows that fluctuation was minimum for the whole year. Generalized extreme value distribution was found to be best fit probability distribution for most of the periods.

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.

Analiza temperaturilor maxime și minime anuale în Chișinău

2019 ◽  
Author(s):  
Valentin Raileanu ◽  
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Extreme Values ◽  
Extreme Value Distribution ◽  
Likelihood Estimation ◽  
Generalized Extreme Value Distribution ◽  
Return Periods ◽  
R Software ◽  
Data Format ◽  
Return Levels

The article briefly describes the fields of application of the theory of extreme values, including climatology. The data format and the analysis methods of the annual maxima and minima temperatures in Chisinau are presented. Free R software and the GUI in2extRemes graphical package are used. Estimating the parameters of the Generalized Extreme Value distribution and return levels vs return periods is done using the Maximum Likelihood Estimation (MLE) method.

scholarly journals Duration-frequency relationships of heavy rainfall in Santa Catarina, Brazil

2012 ◽  
Vol 36 (3) ◽  
pp. 1015-1022 ◽  
Author(s):  
Álvaro José Back ◽  
José Luiz Rocha Oliveira ◽  
Alan Henn
Keyword(s):  
Return Period ◽  
Return Periods ◽  
Santa Catarina ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Rainfall Duration ◽  
Kolmogorov Smirnov ◽  
Weather Stations ◽  
The Relationship ◽  
Smirnov Test

The purpose of this study was to adjust equations that establish relationships between rainfall events with different duration and data from weather stations in the state of Santa Catarina, Brazil. In this study, the relationships between different duration heavy rainfalls from 13 weather stations of Santa Catarina were analyzed. From series of maximum annual rainfalls, and using the Gumbel-Chow distribution, the maximum rainfall for durations between 5 min and 24 h were estimated considering return periods from 2 to 100 years. The data fit to the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test at 5 % significance. The coefficients of Bell's equation were adjusted to estimate the relationship between rainfall duration t (min) and the return period T (y) in relation to the maximum rainfall with a duration of 1 hour and a 10 year return period. Likewise, the coefficients of Bell's equation were adjusted based on the maximum rainfall with a duration of 1 day and a 10 year return period. The results showed that these relationships are viable to estimate short-duration rainfall events at locations where there are no rainfall records.

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 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 Spatial Characteristics of Flooded Areas in the Mun and Chi River Basins in Northeastern Thailand

2019 ◽  
Vol 14 (9) ◽  
pp. 1337-1345 ◽  
Author(s):  
Shingo Zenkoji ◽  
Shigehiko Oda ◽  
Taichi Tebakari ◽  
Boonlert Archevarahuprok ◽  
◽  
...  
Keyword(s):  
Extreme Value Distribution ◽  
Kendall Test ◽  
Generalized Extreme Value Distribution ◽  
Annual Rainfall ◽  
Spatial Characteristics ◽  
Significance Level ◽  
Inundation Area ◽  
Inundation Depth ◽  
Rainfall Change

The objectives of this study are to conduct an analysis on rainfall change tendencies, calculate the inundation in the basins of Mun and Chi Rivers in the northeastern region of Thailand, and clarify the flood risk in the long term, taking the spatial characteristics of flooding into consideration. To grasp the rainfall change tendencies, two statistical analyses are conducted using the Mann-Kendall test and the generalized extreme value distribution. The inundation analysis is conducted using the Rainfall-Runoff-Inundation (RRI) model. As a result of the statistical analysis on the rainfall characteristics, it can be observed that the annual rainfall has significant increasing tendencies at the significance level of 5% in a wide area of the upper reaches. In addition, inundation calculation indicates that the maximum inundation depth and inundation area have increased in recent years.

scholarly journals Calculation and Evaluation of an Air-Freezing Index for the 1981–2010 Climate Normals Period in the Coterminous United States

2015 ◽  
Vol 54 (1) ◽  
pp. 69-76 ◽  
Author(s):  
Rocky Bilotta ◽  
Jesse E. Bell ◽  
Ethan Shepherd ◽  
Anthony Arguez
Keyword(s):  
United States ◽  
Return Period ◽  
Winter Season ◽  
Extreme Value Distribution ◽  
Cold Season ◽  
Shallow Foundation ◽  
Generalized Extreme Value Distribution ◽  
Reference Network ◽  
Distribution Analysis ◽  
Return Periods

AbstractThe air-freezing index (AFI) is a common metric for determining the freezing severity of the winter season and estimating frost depth for midlatitude regions, which is useful for determining the depth of shallow foundation construction. AFI values represent the seasonal magnitude and duration of below-freezing air temperature. Departures of the daily mean temperature above or below 0°C (32°F) are accumulated over each August–July cold season; the seasonal AFI value is defined as the difference between the highest and lowest extrema points. Return periods are computed using generalized extreme value distribution analysis. This research replaces the methodology used by the National Oceanic and Atmospheric Administration to calculate AFI return periods for the 1951–80 time period, applying the new methodology to the 1981–2010 climate normals period. Seasonal AFI values and return period values were calculated for 5600 stations across the coterminous United States (CONUS), and the results were validated using U.S. Climate Reference Network temperature data. Return period values are typically 14%–18% lower across CONUS during 1981–2010 versus a recomputation of 1951–80 return periods with the new methodology. For the 100-yr (2 yr) return periods, about 59% (83%) of stations show a decrease of more than 10% in the more recent period, whereas 21% (2%) show an increase of more than 10%, indicating a net reduction in winter severity that is consistent with observed climate change.

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