Inundation Model Using UAV-derived Digital Elevation Data and PCRaster Dynamic Model in An Excessive Rainfall Event

  • Dwi Setyo Aji Diploma Penginderaan Jauh dan Sistem Informasi Geografis, Departemen Teknologi Kebumian, Sekolah Vokasi, Universitas Gadjah Mada, Indonesia
  • Warsini Handayani Diploma Penginderaan Jauh dan Sistem Informasi Geografis, Departemen Teknologi Kebumian, Sekolah Vokasi, Universitas Gadjah Mada, Indonesia
  • Retnadi Heru Jatmiko Departemen Sains Informasi Geografi, Fakultas Geografi, Universitas Gadjah Mada, Indonesia
  • Agung Kurniawan Diploma Penginderaan Jauh dan Sistem Informasi Geografis, Departemen Teknologi Kebumian, Sekolah Vokasi, Universitas Gadjah Mada, Indonesia
Keywords: UAV, Geographic Information System (GIS), Excessive Rainfall, Model

Abstract

Extreme weather reportedly occurred on 28th November 2017 caused by a cyclone called Cempaka. Categorized as extreme weather since this event triggered an excessive rainfall reaching 246.8 mm in a 24-hour. Consequently, some areas in Yogyakarta Special Region are inundated. This research attempts to model the inundation of excessive rainfall using GIS software, PCRaster. The study area is concentrated in Selopamioro and Sriharjo, where Opak and Oyo rivers meet. Elevation model and rainfall data are used as the principal data to model the inundation. Elevation model is derived from the Unmanned Aerial Vehicle (UAV)  image, while, the rainfall data of a-24-hour hourly data from the Meteorological Agency is also used as an input. The elevation model works as a flow direction model and the rainfall amount plays as the flowing material. The original states of water of the river are not considered, thus the study merely describes how the certain amount of rainfall adds to the level height of terrain and modeled for 24 hours. The result maps are the area that experience of a-24-hour high intensity of rainfall. The study depicts the additional water level caused by rainfall and the concentration of excessive rainfall in the study area. This information is beneficial in order to alarm a similar future event.

 

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Published
2018-12-27