scholarly journals Characteristic of extreme rainfall in Makassar, Province of South Sulawesi

2019 ◽  
Vol 1341 ◽  
pp. 092017
Author(s):  
A Rahim ◽  
B Bakri ◽  
Anisa ◽  
A Mutholib ◽  
A Haerunnisa
2021 ◽  
Vol 5 (2) ◽  
pp. 124-130
Author(s):  
Rahmat Gernowo ◽  
Muhamad Irham Nurwidyanto

Indonesia's climate classification is divided into three rainfall patterns. The three patterns are Seasonal Pattern, Equatorial Pattern, and Local Pattern (Anti Seasonal). Flood Disaster Management based on extreme rainfall is very much needed, as the analysis was taken as a case study on January 22, 2019, a flood disaster occurred in South Sulawesi. The flood event indicated that there was heavy rain that flushed the South Sulawesi region for several days, which is classified as monsoonal rainfall. This study aims to analyze the characteristics of heavy rain with atmospheric anomalies during these events by calculating rainfall intensity to determine future flooding patterns and using the WRF model to analyze cloud distribution patterns and rainfall distribution. The method used in this research is Mononobe and Weather Research and Forecasting (WRF) using the Fabric Fritsch cumulus parameterization scheme. The analysis showed that the intensity and duration of rainfall of 2, 5 10, 25, and 50 years were obtained from the Mononobe model, as well as from the atmospheric dynamics data, there was rain for 3 consecutive days caused by cumulonimbus type rain clouds. Based on the WRF model, it can be seen that the CAPE value before the onset of rain is quite significant, thus supporting the growth of rain clouds as an important variable in flood disaster management in the South Sulawesi region in particular and the tropical zone in. general. Motivation/Background: Indonesia is included in a tropical climate where extreme rainfall is important to analyze. The majority of flood disasters in the tropics occur in decades of extreme atmosphere, this is an important reason in this study. Method: The Mononobe method can be used to calculate the distribution pattern of rainfall intensity throughout 2, 5, 10, 25, and 50 years, as a prediction of future rainfall intensity patterns. The WRF model is used to calculate the cloud distribution pattern and the spatial distribution of rainfall. Results: The results of this study obtained patterns of rainfall intensity and duration of 2, 5, 10, 25, and 50 years from the Mononobe model, as well as from the atmospheric dynamics data, there was rain for 3 consecutive days caused by cumulonimbus rain clouds. The pattern of cloud distribution and rainfall at the time of the incident at the WRF model research location. Conclusions: Analysis of the distribution pattern of rainfall intensity for the periods of 2, 5, 10, 25, and 50 years, as well as the distribution pattern of clouds and rainfall, is very necessary for disaster identification, especially hydrometeorology. This is very important as a variable in flood disaster management, especially in the tropics


2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly

Many people in Indonesia calculate design rainfall before calculating the design flooddischarge. The design rainfall with a certain return period will eventually be convertedinto a design flood discharge by combining it with the characteristics of the watershed.However, the lack of a network of rainfall recording stations makes many areas that arenot hydrologically measured (ungauged basin), so it is quite difficult to know thecharacteristics of rain in the area concerned. This study aims to analyze thecharacteristics of design rainfall in Lampung Province. The focus of the analysis is toinvestigate whether geographical factors influence the design rainfall that occurs in theparticular area. The data used in this study is daily rainfall data from 15 rainfallrecording stations spread in Lampung Province. The method of frequency analysis usedin this study is the Gumbel method. The research shows that the geographical location ofan area does not have significant effect on extreme rainfall events. The effect of risingearth temperatures due to natural exploitation by humans tends to be stronger as a causeof extreme events such as extreme rainfall.Keywords: Influence, geographical, factors, extreme, rainfall.


2020 ◽  
Vol 5 (10) ◽  
pp. 1281-1287
Author(s):  
F. B. Allechy ◽  
M. Youan Ta ◽  
V. H. N’Guessan Bi ◽  
F. A. Yapi ◽  
A. B. Koné ◽  
...  

The Lobo watershed located in the west-central part of Côte d'Ivoire is an area with high agricultural potential, influenced by climate variations and changes that reduce crop yields. The objective of this study is to analyse trends in ETCCDI extreme rainfall indices from rainfall data from 1984 to 2013 using ClimPACT2 software. This study shows that the trend of the indices: number of consecutive wet days (CWD), number of rainy days (R1mm) and the cumulative annual total rainfall (PRCPTOT) is decreasing. On the other hand, the number of consecutive dry days (CDD) is on the rise. In general, the whole basin has experienced a decrease in rainfall as well as wet sequences and an increase in dry sequences. These different trends observed in this study are more pronounced in the northern half of the watershed.


2020 ◽  
Vol 8 (2) ◽  
pp. 128-149
Author(s):  
Dini Maulana Lestari

This paper will discuss about the immaterial costs and production yields at one of the refined sugar factory companies in Makassar, South Sulawesi. The theory is based on the fact that Immaterial is a cost that is almsgiving, meaning costs that are outside of the basic costs of the company in producing production, so this research aims to find out: (1) what is the production cost needed to produce this production, (2) the maximum level of production at company from 2013 to 2017. This type of research is a quantitative study because it uses a questionnaire in the form of values ​​that are processed using the marginal cost approach formula. The results of the analysis show that (1) the maximum level of production costs occurred in 2016 amounting to 6,912 with an Immaterial cost of Rp. 2,481,796,800 and the total production produced is 359,077.3 tons (2) The required workforce with the total production produced is 359,077.3 tones of 180 people including the maximum production point which means that the lowest value is achieved (optimal).    


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