IDENTIFICATION OF FLOOD PRONENESS INDEX VARIATIONS DURING THE MADDEN-JULIAN OSCILLATION (MJO) PHENOMENON USING THE MODIFIED GEOMORPHOLOGY FLOOD INDEX (GFI) (CASE STUDY: WESTERN INDONESIA)

• Main Author: Auranda Br. Siregar, Meiliana
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/68380
• Institution: Institut Teknologi Bandung

The Madden Julian Oscillation (MJO) propagation affects the occurrence of extreme rainfall that can trigger flooding. However, studies on the increase in extreme rainfall and its impact on increasing flood areas have not been widely studied. In addition, the description of potential flooding due to MJO efficiently in a large area can be done using an empirical approach. One of the empirical methods currently available is the Geomorphology Flood Index (GFI). The GFI calculation was modified by entering rainfall data to estimate the flood inundation area during the MJO. This study proposes the IP-A extreme rain index which is used as input into the Modified GFI to estimate flood-prone areas during the MJO. IP-A is calculated based on daily maximum rainfall (RX1) in each case, rainfall with return periods of 5 (P5) and 100 years (P100). Global Precipitation Measurement (GPM) data is used in this study to spatially calculate RX1, P5, and P100. Three strong MJO cases were selected to apply Modified GFI based on Real-time Multivariate MJO Index (RMMI) data and BNPB flood events. The results of this study indicate that the three strong MJO events produce different extreme rain patterns and flood-prone areas. In the MJO events in March 2005 and December 2018, extreme rains tended to fly around the islands of Kalimantan and Sumatra, respectively. While the MJO incident in February 2020, extreme rain occurred evenly in the western part of Indonesia. As a result, the MJO events in March 2005, October 2018, and February 2020 have the potential to trigger floods covering an area of 219.8 million km2, 4.2 million km2, and 17.3 million km2, respectively. The results of this study have the potential to quickly estimate the potential for flooding in a large area when an MJO occurs.