Flood Inundation Modeling Using Geomorphic Approaches, UAV, and GIS

Dhoni Wicaksono; Lufti Gita Iriani; Hendy Fatchurohman; Taufik Hery Purwanto; Dwi Setyo Aji; Warsini Handayani; Alfiatun Nur Khasanah

doi:10.30871/jagi.v4i1.2047

Dhoni Wicaksono Department of Geoinformatics Vocational School Universitas Gadjah Mada
Lufti Gita Iriani Geo-Information for Spatial Planning and Disaster Risk Management, Graduate School Universitas Gadjah Mada
Hendy Fatchurohman Department of Geo-Informatics, Vocational School, Universitas Gadjah Mada
Taufik Hery Purwanto Department of Geo-Informatics, Vocational School, Universitas Gadjah Mada
Dwi Setyo Aji Department of Geo-Informatics, Vocational School, Universitas Gadjah Mada
Warsini Handayani Department of Geo-Informatics, Vocational School, Universitas Gadjah Mada
Alfiatun Nur Khasanah Department of Geo-Informatics, Vocational School, Universitas Gadjah Mada

DOI: https://doi.org/10.30871/jagi.v4i1.2047

Keywords: flood, tropical cyclone, geomorphic, UAV, GIS

Abstract

Flood is one of the most frequently occurring natural disasters in Indonesia. At the end of 2017, Tropical Cyclones Cempaka and Dahlia formed over the Indian Ocean, inducing extreme rains and floods in some parts of Java Island. The Special Region of Yogyakarta was among the most affected areas, especially along the Oyo River section in Imogiri District. This research was designed to identify and map the flood-prone areas in the district as part of flood mitigation measures. For this purpose, The Unmanned Aerial Vehicle (UAV) technology was used to not only provide a detailed and up-to-date description but also produce aerial photographs (orthoimages) and Digital Elevation Model (DEM). These two products were inputted to the inundation modeling developed with a geomorphic approach and simulated in a Geographic Information System (GIS). In terms of accuracy, the resulting models were quite reliable for mapping on a detailed scale and only slightly deviated from the traced inundation in the field. Also, five areas (sub-village) were found with the highest vulnerability to floods, namely, Trukan, Butuh, Dogongan, Siluk Satu, and Kedung Miri.

Downloads

Download data is not yet available.

References

Aji, D. S., Handayani, W., Heru, J. R., & Kurniawan, A. (2018). Inundation Model Using UAV-derived Digital Elevation Data and PCRaster Dynamic Model in An Excessive Rainfall Event. Journal of Applied Geospatial Information (JAGI), 2(2). https://doi.org/10.1016/0167-5273(87)90020-9

Araújo, P. V. N., Amaro, V. E., Silva, R. M., & Lopes, A. B. (2019). Delimitation of flood areas based on a calibrated a DEM and geoprocessing: Case study on the Uruguay River, Itaqui, southern Brazil. Natural Hazards and Earth System Sciences, 19(1), 237–250. https://doi.org/10.5194/nhess-19-237-2019

Fatkhuroyan. (2019). Perbandingan Sebaran Curah Hujan Hasil Observasi Satelit GPM Dengan Model Cuaca WRF(Studi Kasus: Siklon Tropis Cempaka Dan Dahlia, 27 Nov – 3 Des 2017). Seminar Nasional Geomatika, 3, 1063. https://doi.org/10.24895/sng.2018.3-0.998

Jaud, M., Grasso, F., Le Dantec, N., Verney, R., Delacourt, C., Ammann, J., Deloffre, J., & Grandjean, P. (2016). Potential of UAVs for monitoring mudflat morphodynamics (Application to the Sein e Estuary, France). ISPRS International Journal of Geo-Information, 5(4). https://doi.org/10.3390/ijgi5040050

Jung, Y., Kim, D., Kim, D., Kim, M., & Lee, S. O. (2014). Simplified flood inundation mapping based on flood elevation-discharge rating curves using satellite images in gauged watersheds. Water, 6(5), 1280–1299. https://doi.org/10.3390/w6051280

Langhammer, J., Bernsteinová, J., & Miřijovský, J. (2017). Building a high-precision 2D hydrodynamic flood model using UAV photogrammetry and sensor network monitoring. Water, 9(11), 1–22. https://doi.org/10.3390/w9110861

Manfreda, S., Nardi, F., Samela, C., Grimaldi, S., Taramasso, A. C., Roth, G., & Sole, A. (2014). Investigation on the use of geomorphic approaches for the delineation of flood prone areas. Journal of Hydrology, 517, 863–876. https://doi.org/10.1016/j.jhydrol.2014.06.009

Mourato, S., Fernandez, P., Pereira, L., & Moreira, M. (2017). Improving a DSM Obtained by Unmanned Aerial Vehicles for Flood Modelling. IOP Conference Series: Earth and Environmental Science, 95(2). https://doi.org/10.1088/1755-1315/95/2/022014

Muhammad Najib Habibie, Sri Noviati, H. H. (2018). Pengaruh Siklon Tropis Cempaka Terhadap Curah Hujan Harian di Wilayah Jawa dan Madura. Meteorologi Dan Geofisika, 19(01), 1–11.

Mulyana, E., Prayoga, M. B. R., Yananto, A., Wirahma, S., Aldrian, E., Harsoyo, B., Seto, T. H., & Sunarya, Y. (2018). Tropical cyclones characteristic in southern Indonesia and the impact on extreme rainfall event. MATEC Web of Conferences, 229. https://doi.org/10.1051/matecconf/201822902007

Samela, C., Albano, R., Sole, A., & Manfreda, S. (2018). A GIS tool for cost-effective delineation of flood-prone areas. Computers, Environment and Urban Systems, 70, 43–52. https://doi.org/10.1016/j.compenvurbsys.2018.01.013

Samrin, F., Irwana, I., Trismidianto, & Hasanah, N. (2019). Analysis of the Meteorological Condition of Tropical Cyclone Cempaka and Its Effect on Heavy Rainfall in Java Island. IOP Conference Series: Earth and Environmental Science, 303(1). https://doi.org/10.1088/1755-1315/303/1/012065.

Tempo. 2017. Data Rinci Wilayah Terdampak Bencana di Daerah Istimewa Yogyakarta. Retrieved on January 10, 2020, from: https://nasional.tempo.co/read/1186651/data-rinci-wilayah-terdampak-bencana-di-di-yogyakarta.

Wicaksono, D. & Alfiatun N.K. 2018. Pemetaan Dampak Siklon Tropis Cempaka di Kabupaten Bantul pada Skala Makro dan Mikro Memanfaatkan Teknologi GIS dan UAV. Seminar Nasional Teknologi Terapan 2018 (Proceeding).

Wicaksono, D. & Alfiatun N.K. 2019. Pemetaan Partisipatif Kawasan Rawan Banjir Bandang Sungai Oyo di Kecamatan Imogiri. Seminar Nasional Teknologi Terapan 2019 (Proceeding).