UTILIZING A MODIFIED GFI METHOD TO IDENTIFY FLOOD PRONE AREAS DURING THE LA NINA PHENOMENON (CASE STUDY: EASTERN INDONESIA)

• Main Author: Haikal Fikri, Muhammad
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/68381
• Institution: Institut Teknologi Bandung

La Nina is often associated with increased rainfall and flooding in Indonesia, particularly in the Eastern part of Indonesia. However, the relatively long La Nina period and the impact on a wide area, often makes it difficult to identify areas with the potential for flooding in detail. Mapping of flood threats using empirical methods, one of which is the Geomorphology Flood Index (GFI), has developed in the last decade giving hope that it can be implemented to identify flood-prone areas due to La Nina events. However, in general, empirical methods do not involve rain data in their calculations. This study proposes the IP-A extreme rain index which is used as input into the Modified GFI to estimate flood-prone areas during La Nina events. IP-A is calculated based on the maximum rainfall in each case, rainfall with a return period of 5 (P5) and 100 years (P100). There are four maximum rainfalls tested in this study, namely: daily maximum (RX1), five daily (RX5), seven daily (RX7), and ten daily (RX10). Global Precipitation Measurement (GPM) data was used to estimate the four maximum rainfall values spatially in two cases of strong La Nina events, the 2008 case and the 2010 case. The results of the modified GFI calculation show that the RX1 data produces a larger flood area than RX5, RX7, and RX10, which indicates that the potential for flooding during La Nina events is more influenced by the increase in daily rainfall. The application of this method has successfully confirmed that the 2010 La Nina case resulted in a larger flood area than the 2008 La Nina case (1.12 times). In addition, this study also shows that La Nina has the potential to generate flooding between 14.86% and 13.22% in 2010 and 2008 La Nina cases, respectively, when compared to floods with a return period of 100 years.