The FLOOD DISASTER MANAGEMENT BASED ON EXTREME TROPICAL RAINFALL IN DECADES OF CLIMATE CHANGE IN INDONESIA

Abstract

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