scholarly journals A review: regiopnal frequency analysis of annual maximum rainfall in Monsoon region of pakistan using l-moments

2013 ◽  
Vol 1 (3) ◽  
Author(s):  
Amina Shahzadi
Keyword(s):  
Frequency Analysis ◽  
Annual Maximum ◽  
Monsoon Region ◽  
Maximum Rainfall ◽  
L Moments ◽  
Annual Maximum Rainfall

scholarly journals A New Look at Storm Separation Technique in Estimation of Probable Maximum Precipitation in Mountainous Areas

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1177
Author(s):  
Yifan Liao ◽  
Bingzhang Lin ◽  
Xiaoyang Chen ◽  
Hui Ding
Keyword(s):  
Extreme Rainfall ◽  
Separation Technique ◽  
Annual Maximum ◽  
Return Periods ◽  
Mountainous Areas ◽  
Maximum Rainfall ◽  
Probable Maximum Precipitation ◽  
Maximum Precipitation ◽  
L Moments ◽  
Annual Maximum Rainfall

Storm separation is a key step when carrying out storm transposition analysis for Probable Maximum Precipitation (PMP) estimation in mountainous areas. The World Meteorological Organization (WMO) has recommended the step-duration-orographic-intensification-factor (SDOIF) method since 2009 as an effective storm separation technique to identify the amounts of precipitation caused by topography from those caused by atmospheric dynamics. The orographic intensification factors (OIFs) are usually developed based on annual maximum rainfall series under such assumption that the mechanism of annual maximum rainfalls is close to that of the PMP-level rainfall. In this paper, an alternative storm separation technique using rainfall quantiles, instead of annual maximum rainfalls, with rare return periods estimated via Regional L-moments Analysis (RLMA) to calculate the OIFs is proposed. Based on Taiwan’s historical 4- and 24-h precipitation data, comparisons of the OIFs obtained from annual maximum rainfalls with that from extreme rainfall quantiles at different return periods, as well as the PMP estimates of Hong Kong from transposing the different corresponding separated nonorographic rainfalls, were conducted. The results show that the OIFs obtained from rainfall quantiles with certain rare probabilities are more stable and reasonable in terms of stability and spatial distribution pattern.

scholarly journals Annual maximum rainfall prediction using frequency analysis for Roorkee, Uttarakhand, India

MAUSAM ◽  
2021 ◽  
Vol 72 (2) ◽  
pp. 359-372
Author(s):  
LOVEPREET KAUR ◽  
ANVESHA ANVESHA ◽  
MANISH KUMAR ◽  
SUMAN LATA VERMA ◽  
PRAVENDRA KUMAR
Keyword(s):  
Frequency Analysis ◽  
Annual Maximum ◽  
Maximum Rainfall ◽  
Rainfall Prediction ◽  
Annual Maximum Rainfall

Frequency analysis of annual maximum rainfall series of fifteen meteorological observatories of Sindh, Pakistan

2021 ◽  
Vol 14 (9) ◽  
Author(s):  
Zamir Hussain ◽  
Imran Rafi Khan ◽  
Maryum Nisar ◽  
Uzma Nawaz ◽  
Muhammad Shafeeq ul Rehman Khan
Keyword(s):  
Frequency Analysis ◽  
Rainfall Series ◽  
Annual Maximum ◽  
Maximum Rainfall ◽  
Annual Maximum Rainfall

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 Evaluation of Rainfall Temporal Distribution Models with Annual Maximum Rainfall Events in Seoul, Korea

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1468 ◽  
Author(s):  
Wooyoung Na ◽  
Chulsang Yoo
Keyword(s):  
Root Mean Square Error ◽  
Peak Flow ◽  
Temporal Distribution ◽  
Mean Square ◽  
Annual Maximum ◽  
Block Method ◽  
Maximum Rainfall ◽  
Rainfall Events ◽  
Pattern Correlation ◽  
Annual Maximum Rainfall

This study evaluated five models of rainfall temporal distribution (i.e., the Yen and Chow model, Mononobe model, alternating block method, Huff model, and Keifer and Chu model), with the annual maximum rainfall events selected from Seoul, Korea, from 1961 to 2016. Three different evaluation measures were considered: the absolute difference between the rainfall peaks of the model and the observed, the root mean square error, and the pattern correlation coefficient. Also, sensitivity analysis was conducted to determine whether the model, or the randomness of the rainfall temporal distribution, had the dominant effect on the runoff peak flow. As a result, the Keifer and Chu model was found to produce the most similar rainfall peak to the observed, the root mean square error was smaller for the Yen and Chow model and the alternating block method, and the pattern correlation was larger for the alternating block method. Overall, the best model to approximate the annual maximum rainfall events observed in Seoul, Korea, was found to be the alternating block method. Finally, the sensitivity of the runoff peak flow to the model of rainfall temporal distribution was found to be much higher than that to the randomness of the rainfall temporal distribution. In particular, in small basins with a high curve number (CN) value, the sensitivity of the runoff peak flow to the randomness of the rainfall temporal distribution was found to be insignificant.

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