Investigation of the best fit probability distribution for annual maximum rainfall in Kelantan River Basin

Ng, J L; Yap, S Y; Huang, Yuk Feng; Noh, Nur Ilya Farhana Md; Al-Mansob, Ramez A.; Razman, Ruzaimah

doi:10.1088/1755-1315/476/1/012118

Cited by 12 publications

(4 citation statements)

References 15 publications

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“…Thus, they can describe more climatic characteristics of the temperature. The result is consistent with the findings of [8,[12][13] that highlighted the efficiency of the three parameter distributions in fitting meteorological data.…”

Section: Resultssupporting

confidence: 91%

Statistical modelling of extreme temperature in Peninsular Malaysia

Chan

Noh

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Extreme temperature events bring significant effects on the environment and society. Consequently, investigating the best fit for extreme temperature data is important for hydrological study and event forecasting. The main aim of this study is to determine the best fit probability distribution for monthly and annual extreme temperatures. The maximum temperature data at monthly and annual time scales were obtained from MMD (Malaysia Meteorological department). The temperature data for 40 years were fitted to the 10 probability distributions for each station. The parameters of the distributions were estimated by the maximum likelihood method and L-moment method. Besides, three goodness of fit tests, namely Kolmogorov-Smirnov (K-S), Anderson-Darling (A2) and Chi-Squared Error (CSE) test were applied to evaluate the performances of the distributions. The best fit distribution was selected based on the lowest test scores from the summation of the three goodness of fit tests. The results of this study showed that Generalized Extreme Value distribution was selected as the best-fit distribution, followed by Log-Pearson 3, 3 Parameter Lognormal, Generalized Log Logistic and Gamma distributions. The results of this study can be used as a reference for development planners, agricultural sector, water management agencies in hydrological planning and disaster management.

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Section: Resultssupporting

confidence: 91%

Statistical modelling of extreme temperature in Peninsular Malaysia

Chan

Noh

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…This feature is very important for areas where hydrological observation often lacks an extended historical sequence. Reference (Ng et al, 2020) focused on a suitable probability distribution to examine the annual maximum atmospheric falls in hot regions of the Malaysian Peninsular. They explored the fitting of Gumbel, Gamma, log-Pearson type-III and GEV distributions to describe the maximum annual atmospheric falls in the river basin.…”

Section: Probability Distributions (Pds) Selectionmentioning

confidence: 99%

Determination of Suitable Probability Distribution of Rainfall in Pakistan Considering Multiplicity

Khan,

Mureed,

Anwar

et al. 2023

TEIEE

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Extreme rainfall events are occasional, and understanding their intensity and frequency is important for long-term planning and for public safety. The current study aims to investigate the stability of extreme precipitation events in different regions of Pakistan, their independence and the uniformity of their occurrence. A rainfall frequency analysis (RFA) was conducted based on information from 8 weather stations namely, the distribution and moments L of the annual maximum precipitation in Pakistan were investigated; Using goodness-of-fit criteria, the study determined the possible distribution of precipitation. Relatively Absolute Error (RAE) results are based on the most appropriate GUM distribution, revealed that the Sialkot, Multan, Faisalabad and DI Khan stations produce very low errors (0.266, 0.847, 0.075, 0.856, 1.671, 2.522, 3.659, 4.524). It was found that the most suitable distribution is LN distribution for Peshawar, Sibbi and Karachi Stations. The GEV distribution also performs well with small errors for various return periods (0.266, 0.847, 0.075, 0.856, 1.671, 2.522, 3.659, 4.524), corresponding to the return periods 2, 5, 25, 50, 100, 200, 500 and 1000 years. In contrast, P3 has the advantage of a return period of 10 years for all stations, as they all produce similar results for this particular return period. The current research provides valuable insights into estimating extreme rainfall at stations where rainfall data are available

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“…Peninsular Malaysia also experienced both Northeast and Southwest Monsoon. Peninsular Malaysia presents a distinct yearly cycle of wet and dry spells contributed by the tropical monsoon climate [16] [17]. The meteorological data, including the relative humidity (RH), solar radiation (Rs), wind speed at 2m height (u2), daily minimum (Tmin) and maximum temperature (Tmax) covering from year 2000-2019 were selected.…”

Section: Study Areamentioning

confidence: 99%

Innovative Trend Analysis of Reference Crop Evapotranspiration in Peninsular Malaysia

Yong

Huang

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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The inconsistencies in reference crop evapotranspiration (ET0) trends due to the occurrence of climate change have been detected over the world. This has substantially affected both the local and global water resources. The objective of this study is to investigate the historical trend of ET0 and its meteorological variables in Peninsular Malaysia. The meteorological data in daily scale, such as minimum, maximum and mean air temperature, relative humidity, wind speed and solar radiation covering the 2000-2019 period were obtained from Malaysian Meteorological Department and used to compute the ET0 estimation using FAO-56 Penman Monteith model. Then, innovative trend analysis was employed to detect the variations trends in ET0 and its meteorological variables. In the study area, the results showed that significant positive ET0 trends were found at Ipoh (8.09), Kuantan (15.10) and Subang (12.7620) stations respectively and no significant negative ET0 trend can be found. The finding of the study can be used to achieve support and improvement in the efficiency of irrigation regions and optimal water resources planning and utilization.

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Investigation of the best fit probability distribution for annual maximum rainfall in Kelantan River Basin

Cited by 12 publications

References 15 publications

Statistical modelling of extreme temperature in Peninsular Malaysia

Statistical modelling of extreme temperature in Peninsular Malaysia

Determination of Suitable Probability Distribution of Rainfall in Pakistan Considering Multiplicity

Innovative Trend Analysis of Reference Crop Evapotranspiration in Peninsular Malaysia

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