SCALING GEV DISTRIBUTION OF GAUGED AND UNGAUGED ANNUAL MAXIMUM RAINFALLS IN JAPAN AND THAILAND

Author(s):  
C. CHALEERAKTRAKOON ◽  
T. REAUNGROJANA ◽  
K. WATANABE
Author(s):  
Daniel Maposa ◽  
James J. Cochran ◽  
Maseka Lesaoana

In this article we fit a time-dependent generalised extreme value (GEV) distribution to annual maximum flood heights at three sites: Chokwe, Sicacate and Combomune in the lower Limpopo River basin of Mozambique. A GEV distribution is fitted to six annual maximum time series models at each site, namely: annual daily maximum (AM1), annual 2-day maximum (AM2), annual 5-day maximum (AM5), annual 7-day maximum (AM7), annual 10-day maximum (AM10) and annual 30-day maximum (AM30). Non-stationary time-dependent GEV models with a linear trend in location and scale parameters are considered in this study. The results show lack of sufficient evidence to indicate a linear trend in the location parameter at all three sites. On the other hand, the findings in this study reveal strong evidence of the existence of a linear trend in the scale parameter at Combomune and Sicacate, whilst the scale parameter had no significant linear trend at Chokwe. Further investigation in this study also reveals that the location parameter at Sicacate can be modelled by a nonlinear quadratic trend; however, the complexity of the overall model is not worthwhile in fit over a time-homogeneous model. This study shows the importance of extending the time-homogeneous GEV model to incorporate climate change factors such as trend in the lower Limpopo River basin, particularly in this era of global warming and a changing climate.Keywords: nonstationary extremes; annual maxima; lower Limpopo River; generalised extreme value


2017 ◽  
Vol 13 (4-1) ◽  
pp. 394-399
Author(s):  
Noratiqah Mohd Ariff ◽  
Abdul Aziz Jemain ◽  
Mohd Aftar Abu Bakar

Intensity-duration-frequency (IDF) curves represent the relationship between storm intensity, storm duration and return period. The IDF curves available are mostly done by fitting series of annual maximum rainfall intensity to parametric distributions. However, the length of annual rainfall records, especially for small scaled data, are not always enough. Rainfall records of less than 50 years are usually deemed insufficient to unequivocally identify the probability distribution of the annual rainfall. Thus, this study introduces an alternative approach that replaces the need for parametric fitting by using empirical distribution based on plotting positions to represent annual maximum rainfall series. Subsequently, these plotting positions are used to build IDF curves. The IDF curves found are then compared to the IDF curves yielded from the parametric GEV distribution which is a common basis for IDF curves. This study indicates that IDF curves obtained using plotting positions are similar to IDF curves found using GEV distribution for storm events. Hence, researchers could model and subsequently build IDF curves for annual rainfall records of less than 50 years by using plotting positions and avoid any probability distribution fitting of insufficient data.


2013 ◽  
Vol 10 (5) ◽  
pp. 6321-6358 ◽  
Author(s):  
J. L. Salinas ◽  
A. Castellarin ◽  
S. Kohnová ◽  
T. R. Kjeldsen

Abstract. This study addresses the question of the existence of a parent flood frequency distribution on a European scale and aims to better understand the effect of catchment scale and climate on the statistical properties of regional flood frequency distributions. A new database of L-moment ratios of annual maximum series (AMS) of peak discharges from 4105 catchments was compiled by joining 13 national datasets. Using this database and additional Monte Carlo simulations, the Generalised Extreme Value (GEV) distribution appears as a potential pan-European flood frequency distribution, being the 3-parameter statistical model with the closest resemblance to the estimated average of the sample L-moment ratios, but failing to represent the kurtosis dispersion, especially for high skewness values. A more detailed investigation performed on a subset of the database (Austria, Italy and Slovakia, involving a total of 813 catchments with more than 25 yr of record length) confirms that the GEV distribution provides a better representation of the averaged sample L-moment ratios compared to the other distributions considered, for catchments with medium to high values of mean annual precipitation (MAP) independently of catchment area, while the 3-parameter Lognormal distribution is probably a more appropriate choice for dry (low MAP) intermediate-sized catchments, which presented higher skewness values. Sample L-moment ratios do not follow systematically any of the theoretical 2-parameter distributions. In particular, the averaged values of L-coefficient of skewness (L-Cs) are always larger than Gumbel's fixed L-Cs. The results presented in this paper contribute to progress towards the definition of a set of pan-European flood frequency distributions and to assess possible effects of environmental change on its properties.


2012 ◽  
Vol 518-523 ◽  
pp. 4139-4143
Author(s):  
Yang Li ◽  
Song Bai Song

This paper aims to study the use of higher probability moments (PWMs) for flood frequency analysis. By estimating the parameters of GEV distribution and matching higher PWMs to annual maximum flow series in northern Shaanxi. The results show that higher PWMs describe the data reasonably better than lower PWMs in flood analysis. This method involves no more complication than lower PWMs that be commonly used, and is suitable for flood frequency analysis.


1984 ◽  
Vol 16 (8-9) ◽  
pp. 93-100
Author(s):  
D M Hershfield

Storm data and climatological quantities from both dense raingage networks and individual stations are used to elucidate some of the important problems in developing drainage design criteria for small areas. Examples are presented displaying the variability of rainfall rates for very short durations of time over very small areas. An “average” time distribution curve is presented along with relationships between rainfall amounts for durations from 2- to 60-min. One example outlines a procedure for estimating and comparing six quantities from series of annual maximum rainfalls for several short durations. The quantities include a frequency factor, 100-yr value, the probable maximum rainfall, and the observed world maximum rainfalls.


2021 ◽  
Vol 5 (3) ◽  
pp. 481-497
Author(s):  
Mansour Almazroui ◽  
Fahad Saeed ◽  
Sajjad Saeed ◽  
Muhammad Ismail ◽  
Muhammad Azhar Ehsan ◽  
...  

AbstractThis paper presents projected changes in extreme temperature and precipitation events by using Coupled Model Intercomparison Project phase 6 (CMIP6) data for mid-century (2036–2065) and end-century (2070–2099) periods with respect to the reference period (1985–2014). Four indices namely, Annual maximum of maximum temperature (TXx), Extreme heat wave days frequency (HWFI), Annual maximum consecutive 5-day precipitation (RX5day), and Consecutive Dry Days (CDD) were investigated under four socioeconomic scenarios (SSP1-2.6; SSP2-4.5; SSP3-7.0; SSP5-8.5) over the entire globe and its 26 Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions. The projections show an increase in intensity and frequency of hot temperature and precipitation extremes over land. The intensity of the hottest days (as measured by TXx) is projected to increase more in extratropical regions than in the tropics, while the frequency of extremely hot days (as measured by HWFI) is projected to increase more in the tropics. Drought frequency (as measured by CDD) is projected to increase more over Brazil, the Mediterranean, South Africa, and Australia. Meanwhile, the Asian monsoon regions (i.e., South Asia, East Asia, and Southeast Asia) become more prone to extreme flash flooding events later in the twenty-first century as shown by the higher RX5day index projections. The projected changes in extremes reveal large spatial variability within each SREX region. The spatial variability of the studied extreme events increases with increasing greenhouse gas concentration (GHG) and is higher at the end of the twenty-first century. The projected change in the extremes and the pattern of their spatial variability is minimum under the low-emission scenario SSP1-2.6. Our results indicate that an increased concentration of GHG leads to substantial increases in the extremes and their intensities. Hence, limiting CO2 emissions could substantially limit the risks associated with increases in extreme events in the twenty-first century.


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