HOMOGENEITY ANALYSIS OF RAINFALL IN KELANTAN, MALAYSIA

2015 ◽  
Vol 76 (15) ◽  
Author(s):  
Ng Jing Lin ◽  
Samsuzana Abd Aziz ◽  
Huang Yuk Feng ◽  
Aimrun Wayayok ◽  
Md Rowshon Kamal
Keyword(s):  
River Basin ◽  
Monthly Rainfall ◽  
Rainfall Series ◽  
Rainfall Data ◽  
Seasonal Rainfall ◽  
Homogeneity Test ◽  
Ratio Test ◽  
Homogeneity Analysis ◽  
Standard Normal Homogeneity Test ◽  
Kelantan River Basin

Good quality of rainfall data is required for the hydrological studies, water resources planning and sustainable environmental management. Consequently, the assessment of the homogeneity of rainfall data at different region is becoming increasing popular in the past few decades. In this study, the homogeneity analysis of rainfall data was carried out in Kelantan River Basin, Malaysia. The methods, namely standard normal homogeneity test (SHNT), Buishand range test, Pettitt test and von Neumann ratio test were applied to the monthly, yearly and seasonal data. The historical rainfall data from 10 rainfall stations covering the study period from 28 to 60 years were selected. The four tests were applied to 120 monthly series, 10 yearly series and 40 seasonal series. ‘Useful’, ‘doubtful’ and ‘suspect’ were used to classify the results of the four tests. The results showed that 94.17% of the monthly rainfall series, 70% of yearly rainfall series and 97.5% of seasonal rainfall series are labelled ‘useful’. There is 5% of monthly rainfall series, 30% of yearly rainfall series and 1% of seasonal rainfall series are classified as ‘doubtful’. Meanwhile, there is only 0.83% of monthly rainfall series and no yearly rainfall series and seasonal rainfall series detected in the class ‘suspect’. Overall, the percentage of inhomogeneity detected in the monthly, yearly and seasonal rainfall data series of Kelantan River Basin is very small, thus most of the data is suitable to be used for further hydrological and variability analysis.

scholarly journals Inhomogeneity detection in the rainfall series for the Mae Klong River Basin, Thailand

2021 ◽  
Vol 11 (9) ◽  
Author(s):  
Alamgir Khalil
Keyword(s):  
River Basin ◽  
Curve Analysis ◽  
Rainfall Series ◽  
Rainfall Data ◽  
Homogeneity Test ◽  
Significance Level ◽  
Von Neumann ◽  
Standard Normal Homogeneity Test ◽  
Double Mass ◽  
Climate Studies

AbstractAn accurate and complete rainfall record is prerequisite for climate studies. The purpose of this research study was to evaluate the homogeneity of the rainfall series for the Mae Klong River Basin in Thailand. Monthly rainfall data of eight stations in the Mae Klong River Basin for the period 1971–2015 were used. The double mass curve analysis was used to check the consistency of rainfall data, whereas the absolute homogeneity was assessed using the Pettitt test, standard normal homogeneity test, Buishand test, and von Neumann test at a 5% significance level. The results of these tests were qualitatively classified as ‘useful’, ‘doubtful’, and ‘suspect’ according to the null hypothesis. Results of the monthly time series indicated the rainfall data as ‘useful’ for 75% of the stations, while two stations’ data were classified as ‘doubtful’ (Stn130221) and ‘suspect’ (Stn376401). On an annual scale, seven out of eight stations data were classified as ‘useful,’ while one station (Stn376401) data were classified as ‘suspect’. Double mass curve analysis technique was used for the adjustment of inhomogeneous data. The results of this study can help provide reliable rainfall data for climate studies in the basin.

scholarly journals Tropical rainfall trend and stationarity analysis

2020 ◽  
Vol 20 (7) ◽  
pp. 2471-2483
Author(s):  
Chun Kang Ng ◽  
Jing Lin Ng ◽  
Yuk Feng Huang ◽  
Yi Xun Tan ◽  
Majid Mirzaei
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
River Basin ◽  
Spatial Scales ◽  
Kendall Test ◽  
Temporal Analysis ◽  
Northern Region ◽  
Rainfall Series ◽  
Kelantan River Basin ◽  
Temporal And Spatial

Abstract Climate change is most likely to cause changes to the temporal and spatial variability of rainfall. A trend analysis to investigate the rainfall pattern can detect changes over temporal and spatial scales for a rainfall series. In this study, trend analysis using the Mann–Kendall test and Sen's slope estimator was conducted in the Kelantan River Basin, Malaysia. The Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test was applied to evaluate the stationarity of the rainfall series. This basin annually faces onslaughts of varying year-end flooding conditions. The trend analysis was applied for monthly, seasonal and yearly rainfall series between 1989 and 2018. The temporal analysis results showed that both increasing and decreasing trends were detected for all rainfall series. The spatial analysis results indicated that the northern region of the Kelantan River Basin showed an increasing trend, whilst the southwest region showed a decreasing trend. It was found that almost all the rainfall series were stationary except at two rainfall stations during the Inter Monsoon 1, Inter Monsoon 2 and yearly rainfall series. Results obtained from this study can be used as reference for water resources planning and climate change assessment.

scholarly journals ANALISIS CURAH HUJAN BULANAN DI KOTA AMBON MENGGUNAKAN MODEL HETEROSKEDASTISITAS: SARIMA-GARCH

2020 ◽  
Vol 13 (1) ◽  
pp. 68-79
Author(s):  
Lexy Janzen Sinay ◽  
Ferry Kondo Lembang ◽  
Salmon Notje Aulele ◽  
Dominique Mustamu
Keyword(s):  
White Noise ◽  
Secondary Data ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
The Other ◽  
Seasonal Rainfall ◽  
Volatility Clustering ◽  
Arch Effect ◽  
Data Form ◽  
Sample Data

Non-linear characteritics in rainfall allow volatility clustering. This condition occurs in Ambon City with seasonal rainfall patterns. The aims of this research are to find the best model and to forecast monthly rainfall in Ambon City using heteroscedasticity model. This research examines secondary data from BMKG for monthly rainfall data in Ambon City from January 2005 – December 2018. The data is divided into two parts. First part, is called in-sample data, consist of data form January 2005 – December 2017. Second part, is called out-sample data, consist data from Januari 2018 – December 2018. The research used SARIMA–GARCH to model the data. The results are the  is the best model and the residual model satisfied assumptions of normality, white noise, and there is no ARCH effect. The MAPE value in simulation using in-sample data is 0.73%. On the other side, the MAPE value of forecast results is 30%.

scholarly journals Assessing Inhomogeneities in Extreme Annual Rainfall Data Series by Multifractal Approach

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1030 ◽  
Author(s):  
Amanda García-Marín ◽  
Javier Estévez ◽  
Renato Morbidelli ◽  
Carla Saltalippi ◽  
José Ayuso-Muñoz ◽  
...  
Keyword(s):  
Central Italy ◽  
Extreme Rainfall ◽  
Break Point ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Data Series ◽  
Homogeneity Test ◽  
Umbria Region ◽  
Standard Normal Homogeneity Test ◽  
Break Points

Testing the homogeneity in extreme rainfall data series is an important step to be performed before applying the frequency analysis method to obtain quantile values. In this work, six homogeneity tests were applied in order to check the existence of break points in extreme annual 24-h rainfall data at eight stations located in the Umbria region (Central Italy). Two are parametric tests (the standard normal homogeneity test and Buishand test) whereas the other four are non-parametric (the Pettitt, Sequential Mann–Kendal, Mann–Whitney U, and Cumulative Sum tests). No break points were detected at four of the stations analyzed. Where inhomogeneities were found, the multifractal approach was applied in order to check if they were real or not by comparing the split and whole data series. The generalized fractal dimension functions Dq and the multifractal spectra f(α) were obtained, and their main parameters were used to decide whether or not a break point existed.

scholarly journals Homogeneity Analysis of Rainfall Series in the Upper Blue Nile River Basin, Ethiopia

2019 ◽  
Vol 3 (9) ◽  
pp. 46-53
Author(s):  
Radwa Elzeiny ◽  
Mossad Khadr ◽  
Shreen Zahran ◽  
Ebrahim Rashwan
Keyword(s):  
River Basin ◽  
Rainfall Series ◽  
Nile River ◽  
Homogeneity Analysis ◽  
Blue Nile ◽  
Nile River Basin ◽  
Blue Nile River Basin

Spatio-temporal trend and homogeneity analysis of gridded and gauge precipitation in Indravati River basin, India

2018 ◽  
Vol 11 (1) ◽  
pp. 178-199 ◽  
Author(s):  
Ch. Praveenkumar ◽  
V. Jothiprakash
Keyword(s):  
River Basin ◽  
Time Scales ◽  
Time Scale ◽  
India Meteorological Department ◽  
Rainfall Data ◽  
Trend Test ◽  
Poor Correlation ◽  
Homogeneity Analysis ◽  
Grid Data ◽  
Spatio Temporal

Abstract The study aims to analyze spatio-temporal variations in rainfall data over Indravati River basin, India. Three rainfall data sets, Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), India Meteorological Department (IMD) grid, and IMD gauge were used. Data from 2001 to 2013 were analyzed for three time scales, namely, daily, monthly, and annual. Analysis showed good correlation between IMD gauge and TMPA grid rainfall at monthly time scale, poor correlation is observed at daily and annual time scales. Mann–Kendall (MK) trend test reveals a significant increasing trend of IMD gauge and IMD grid data, whereas TMPA rainfall is free from trends at the majority of stations for daily time scale. Nevertheless, both IMD grid as well as TMPA grid rainfall can be considered as a better representative of rainfall, since it is attained from observed rainfall data over the country. The Pettitt and standard normal homogeneity tests show that TMPA rainfall has a more non-homogeneous nature, whereas IMD grid rainfall and IMD gauge rainfall data are homogeneous. Overall, the trend and homogeneity analysis indicate that TMPA grid and IMD grid rainfall is in line with IMD gauge data, however IMD grid rainfall has the edge over TMPA grid data.

Homogeneity and trends in long-term rainfall data, Kelantan River Basin, Malaysia

2016 ◽  
Vol 14 (2) ◽  
pp. 151-163 ◽  
Author(s):  
Faizah Che Ros ◽  
Hiroyuki Tosaka ◽  
Lariyah Mohd Sidek ◽  
Hidayah Basri
Keyword(s):  
River Basin ◽  
Rainfall Data ◽  
Kelantan River Basin

scholarly journals Analysis of Precipitation and Temperature Extremes over the Muda River Basin, Malaysia

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 283 ◽  
Author(s):  
Mou Leong Tan ◽  
Narimah Samat ◽  
Ngai Weng Chan ◽  
Anisah Jessica Lee ◽  
Cheng Li
Keyword(s):  
River Basin ◽  
Climate Extremes ◽  
Quality Data ◽  
Maximum Temperature ◽  
Homogeneity Test ◽  
Temperature Extremes ◽  
Monthly Precipitation ◽  
Northeast Monsoon ◽  
Standard Normal Homogeneity Test ◽  
Precipitation And Temperature

Trends in precipitation and temperature extremes of the Muda River Basin (MRB) in north-western Peninsular Malaysia were analyzed from 1985 to 2015. Daily climate data from eight stations that passed high quality data control and four homogeneity tests (standard normal homogeneity test, Pettitt test, Buishand range test, and von Neumann ratio test) were used to calculate 22 Expert Team on Climate Change Detection and Indices (ETCCDI) extreme indices. Non-parametric Mann–Kendall, modified Mann–Kendall and Sens’ slope tests were applied to detect the trend and magnitude changes of the climate extremes. Overall, the results indicate that monthly precipitation tended to increase significantly in January (17.01 mm/decade) and December (23.23 mm/decade), but decrease significantly in May (26.21 mm/decade), at a 95% significance level. Monthly precipitation tended to increase in the northeast monsoon, but decrease in the southwest monsoon. Mann–Kendall test detected insignificant trends in most of the annual climate extremes, except the extremely wet days (R99p), mean of maximum temperature (TXmean), mean of minimum temperature (TNmean), cool days (TX10p), cool nights (TN10p), warm days (TX90p) and warm nights (TN90p) indices. The number of heavy (R10mm), very heavy (R20mm), and violent (R50mm) precipitation days changed at magnitudes of 0~2.73, −2.14~3.33, and −1.67~1.29 days/decade, respectively. Meanwhile, the maximum 1-day (Rx1d) and 5-day (Rx5d) precipitation amount indices changed from −10.18 to 3.88 mm/decade and −21.09 to 24.69 mm/decade, respectively. At the Ampangan Muda station, TNmean (0.32 °C/decade) increased at a higher rate compared to TXmean (0.22 °C/decade). The number of the cold days and nights tended to decrease, while an opposite trend was found in the warmer days and nights.

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