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.

 

References

Aber J S, Marzolff I, Ries J B .2010. Small-Format Aerial Photography: Principles, Techniques and Geoscience Application (The Netherlands: Elsevier)

Aji, Dwi Setyo., Warsini Handayani, Retnadi Heru Jatmiko, Agung Kurniawan. (2018). Mapping of Cempaka Cyclone Impacted Area Using Unmanned Aerial Vehicled (UAV) Data and Participatory Mapping. Seminar Nasional Teknologi Terapan 2018 (Proceeding)

Asdak, C. (2007) . Hidrologi dan Pengelolaan Daerah Aliran Sungai. Yogyakarta: Gadjah Mada University Press.

Clarke, K. C. (1986). Advances In Geographic Information System. Compute Environment Urban System, 175-184.

Gindraux, S., Boesch, R., Farinotti, D. 2017. Accuracy Assessment of Digital Surface Models from Unmanned Aerial Vehicles’ Imagery on Glaciers. Journal Remote Sens. 2017, 9, 186.

Handayani, W., Ayuningtyas, E.A., Rosaji, F.S.C., Setiawan, B.A., Argadyanto, B. 2017. Unmanned Aerial Vehicle (UAV) Data Acquisition for Archaeological Site Identification and Mapping. IOP Conf. Ser.: Earth Environ. Sci. 98 012017

Marfai, M.A., Ahmad, Cahyadi., Achmad, A.K., Luthfi, A.H.&Dela, R.T. (2015). Pemetaan Partisipatif untuk Estimasi Kerugian Akibat Banjir Rob di Kabupaten Pekalongan. Seminar Nasional Geografi UMS.

Mutreja, K.N. (1986). Applied Hydrology. New Delhi: McGraw-Hill Publishing Company Limited.

Rini, D., 2017. “Cempaka" Meluruh, Siklon Tropis "DAHLIA" Lahir, Waspada Bencana Hidrometeorologi Menghadang. [Online] Available at: http://www.bmkg.go.id/press-release/?p=cempaka-meluruh-dahlia-lahir-waspada-bencana-hidrometeorologi-menghadang&tag=press-release&lang=ID [Accessed 13 March 2018].

Rokhmana, C.A., Utomo, S. 2016. The Low-Cost UAV-Based Remote Sensing System Capabilities for Large Scale Cadaster Mapping. IOP Conf. Series: Earth and Environmental Science 47 (2016) 012005. doi:10.1088/1755-1315/47/1/012005.

Rosaji, S.C.R., Handayani. W., Nurteisa, Y.T., Suharyadi., R., Widartono, B.S. 2013. Aerial/Terrestrial Videography: Alternatif Teknologi Penginderaan Jauh untuk Survey dan Akuisisi data Spatial. Prosiding. Simposium Nasional Sains Geoinformasi III – 2013, ISBN 978-979-98521-4-4.

Santise, M., Fornari, M., Forlani, G., Roncella, R. 2014. Evaluation of DEM generation accuracy from UAS imagery. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-5, 2014.

Serifoglu, C., Gungor, O., Yilmaz, V. (2016). Performance Evaluation of Different Ground Filtering Algorithms for UAV-Based Point Clouds. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLI-B1, 2016. DOI:10.5194. XXIII ISPRS Congress, Prague, Czech Republic.

Sillmann, J., Thorarinsdottir, T., Keenlyside, N., Schaller, N., Alexander, L. V, Hegerl, G., … Zwiers, F. W. (2017). Understanding , modeling and predicting weather and climate extremes : Challenges and opportunities. Weather and Climate Extremes, 18(October), 65–74. https://doi.org/10.1016/j.wace.2017.10.003
The PCRaster Research and Development Team (a). (2018). Dynamic modelling.
http://pcraster.geo.uu.nl/pcraster/4.2.0/documentation/pcraster_manual/sphinx/secintro.html
The PCRaster Research and Development Team (b). (2018). Introduction to the PCRaster Package: Concepts, Package Layout. http://pcraster.geo.uu.nl/pcraster/4.2.0/documentation/pcraster_manual/sphinx/secintro.html

Zhang, S., & Pan, B. (2014). An urban storm-inundation simulation method based on GIS. Journal of Hydrology Vol. 517, 260-268.
Published
2018-12-27