Spatial analysis of return period based copula on extreme rainfall data in South Sulawesi

Abstract Extreme rainfall is the main factor triggering flooding in various regions of the world including Indonesia. The increase in intensity and duration of current extreme rainfall is predicted as a result of global climate change. This paper aims to analyze the impact of extreme rainfall to the peak discharge of flood hydrographs at a watershed outlet in Palu, Sulawesi, Indonesia. Maximum daily rainfall data for the period 1990-1999 recorded at the Palu Meteorological Station, Central Sulawesi were selected using the Annual Maximum Series Method, and grouped into two types. Type I is the maximum daily rainfall data with extreme events and Type II is the maximum daily rainfall data without extreme events. Frequency analysis was applied to the two data groups using the best distribution method of: Normal, Normal Log, Pearson III Log, and Gumbel to obtain the design rainfall of each data group. In the next stage, the design rainfall transformation into a flood hydrograph is performed using the Nakayasu Synthetic Unit Hydrograph based on a number of return periods in one of the rivers flowing into Palu Bay, namely the Poboya River. The analysis results show that the design rainfall graphs with both extreme rainfall and without extreme rainfall are identical at the low return period and divergent at the high return period with a difference of up to 21.6% at the 1000-year return period. Correspondingly, extreme rainfall has a greater impact at the peak of the flood hydrograph with increasing return periods ranging from -1.28% to 26.81% over the entire return period.

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Simulating rainfall IDF curve for flood warnings in the Ca Mau coastal area under the impacts of climate change

International Journal of Climate Change Strategies and Management ◽

10.1108/ijccsm-06-2020-0067 ◽

2020 ◽

Vol 12 (5) ◽

pp. 705-715

Author(s):

Seung Kyu Lee ◽

Truong An Dang

Keyword(s):

Return Period ◽

Extreme Rainfall ◽

Rainfall Data ◽

Data Series ◽

Homogeneity Test ◽

Content Type ◽

Pettitt Test ◽

Standard Normal Homogeneity Test ◽

Intensity Duration Frequency ◽

The Right

Purpose The purpose of this study is to evaluate the rainfall intensities and their limits for durations from 0.25 to 8 h with return periods from 2 to 100 years for Ca Mau City in Vietnam. Design/methodology/approach First, the quality of the historical rainfall data series in 44 years (1975–2018) at Ca Mau station was assessed using the standard normal homogeneity test and the Pettitt test. Second, the appraised rainfall data series are used to establish the rainfall intensity-duration-frequency curve for the study area. Findings Based on the findings, a two-year return period, the extreme rainfall intensities (ERIs) ranged from 9.1 mm/h for 8 h rainstorms to 91.2 mm/h for 0.25 h. At a 100-year return period, the ERIs ranged from 18.4 mm/h for 8 h rainstorms to 185.8 mm/h for 0.25 h. The results also show that the narrowest uncertainty level between the lower and upper limits recorded 1.6 mm at 8 h for the two-year return period while the widest range is at 42.5 mm at 0.25 h for the 100-year return period. In general, the possibility of high-intensity rainfall values compared to the extreme rainfall intensities is approximately 2.0% at the 100-year return period. Originality/value The results of the rainfall IDF curves can provide useful information for policymakers to make the right decisions in controlling and minimizing flooding in the study area.

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STUDI PENGEMBANGAN MODEL HIDROGRAF SATUAN SISTETIS SNYDER UNTUK SUNGAI –SUNGAI DI SULAWESI SELATAN

GANEC SWARA ◽

10.35327/gara.v13i1.72 ◽

2019 ◽

Vol 13 (1) ◽

pp. 126

Author(s):

MUHAMAD YAMIN

Keyword(s):

Model Verification ◽

Rainfall Data ◽

Peak Time ◽

Reliability Testing ◽

Unit Hydrograph ◽

Observation Unit ◽

Discharge Data ◽

Watershed Characteristics ◽

Testing Model ◽

South Sulawesi

This study aims to analyze the parameters that influence the Snyder synthetic unit hydrograph method. The study was conducted on 11 watersheds in South Sulawesi Province, 8 watersheds for modeling and 3 other watersheds for reliability testing (model verification). With rainfall data, the discharge data and watershed characteristics obtained from each watershed were analyzed for parameters that affected the hydrograph breakdown of the Snyder HSS method. Then compared to the hydrograph of the observation unit which was analyzed by the Collins method. After calibration was done with the NASH criteria obtained Peak Time (Tp) = 97.996%; Peak Discharge (Qp) = 98.331% and Basic Time (Tb) = 99.700%. The curved delineation of the hydrograph uses the auxiliary point W, which gives the result of volume deviation, namely: 7.980%, 9.227%; 6.855%; 4.966%; 10.972% and 9.843% are relatively small when compared to the model using Alexejeyev Arch with deviations: 22.362%; 29.991%; 26,319%; 19.602%; 29,786% and 17,633%.

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Spatial Interpolation on Rainfall Data over Peninsular Malaysia Using Ordinary Kriging

Jurnal Teknologi ◽

10.11113/jt.v63.1912 ◽

2013 ◽

Vol 63 (2) ◽

Cited By ~ 1

Author(s):

Suhaila Jamaludin ◽

Hanisah Suhaimi

Keyword(s):

Spatial Analysis ◽

Ordinary Kriging ◽

Spatial Interpolation ◽

Rainfall Intensity ◽

Peninsular Malaysia ◽

Rainfall Data ◽

Kriging Method ◽

Intensity Index ◽

Dry Conditions ◽

Two Indices

This study presents the spatial analysis of the rainfall data over Peninsular Malaysia. 70 rainfall stations were utilized in this study. Due to the limited number of rainfall stations, the Ordinary Kriging method which is one of the techniques in Spatial Interpolation was used to estimate the values of the rainfall data and to map their spatial distribution. This spatial analysis was analysed according to the two indices that describe the wet events and another two indices that characterize dry conditions. Large areas at the east experienced high rainfall intensity compared to the areas in the west, northwest and southwest. The small value that has been obtained in Aridity Intensity Index (AII) reflects that the high amount of rainfall in the eastern areas is not contributed by low-intensity events (less than 25th percentile). In terms of number of consecutive dry days, Northwestern areas in Peninsular Malaysia recorded the highest value. This finding explains the occurrence of a large number of floods and soil erosions in the eastern areas.

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Interevent Time Distribution of Renewal Point Process, Case Study: Extreme Rainfall in South Sulawesi

Journal of Physics Conference Series ◽

10.1088/1742-6596/979/1/012090 ◽

2018 ◽

Vol 979 ◽

pp. 012090

Author(s):

Nurtiti Sunusi

Keyword(s):

Point Process ◽

Time Distribution ◽

Extreme Rainfall ◽

South Sulawesi ◽

Interevent Time

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Characteristic of extreme rainfall in Makassar, Province of South Sulawesi

Journal of Physics Conference Series ◽

10.1088/1742-6596/1341/9/092017 ◽

2019 ◽

Vol 1341 ◽

pp. 092017

Author(s):

A Rahim ◽

B Bakri ◽

Anisa ◽

A Mutholib ◽

A Haerunnisa

Keyword(s):

Extreme Rainfall ◽

South Sulawesi

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Bangladesh; GIS; Meteorological drought; Rainfall data; Spatial analysis; SPI

Journal of Earth Science & Climatic Change ◽

10.4172/2157-7617.1000457 ◽

2018 ◽

Vol 09 (03) ◽

Cited By ~ 1

Author(s):

Abdullah Al Mamun ◽

Md Niaz Farhat Rahman ◽

Md Abdullah Aziz ◽

Md Abdul Qayum ◽

Md Ismail Hossain ◽

...

Keyword(s):

Spatial Analysis ◽

Meteorological Drought ◽

Rainfall Data

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Modelling Catchment Rainfall Using Sum of Correlated Gamma Variables

Jurnal Teknologi ◽

10.11113/jt.v63.1918 ◽

2013 ◽

Vol 63 (2) ◽

Author(s):

Zakaria, R. ◽

Howlett, P. G. ◽

Piantadosi, J. ◽

Boland, J. W. ◽

Moslim, N. H.

Keyword(s):

Spatial Analysis ◽

Random Variables ◽

Monthly Rainfall ◽

Rainfall Data ◽

Weighted Sum ◽

Statistical Parameters ◽

Dependent Random Variables ◽

Rainfall Model

One of the major difficulties in simulating rainfall is the need to accurately represent rainfall accumulations. An accurate simulation of monthly rainfall should also provide an accurate simulation of yearly rainfall by summing the monthly totals. A major problem in this regard is that rainfall distributions for successive months may not be independent. Thus the rainfall accumulation problem must be represented as the summation of dependent random variables. This study is aimed to show if the statistical parameters for several stations within a particular catchment is known, then a weighted sum is used to determine a rainfall model for the entire local catchment. A spatial analysis for the sum of rainfall volumes from four selected meteorological stations within the same region using the monthly rainfall data is conducted. The sum of n correlated gamma variables is used to model the sum of monthly rainfall totals from four stations when there is significant correlation between the stations.

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