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Evaluation of Double Fusion Satellite Rainfall Dataset in Establish Rainfall Thresholds for Landslide Occurrences Over Badung Regency-Bali

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Landslide: Susceptibility, Risk Assessment and Sustainability

Part of the book series: Advances in Natural and Technological Hazards Research ((NTHR,volume 52))

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Abstract

Rainfall stations provide reliable rainfall data, but their availability is limited in mountainous areas, complex terrain, and remote areas. Satellite rainfall datasets (SRDs) provide high-resolution worldwide rainfall estimation, which has the potential to be used in identifying rainfall conditions that trigger landslides. Landslides can be predicted through rainfall threshold modeling, serving as an early warning system. It is essential to validate the chosen threshold model to assess the accuracy of forecasting landslide occurrences triggered by rainfall events. This study aims to evaluate the effectiveness of a dual fusion approach, utilizing two SRDs, in establishing rainfall thresholds for landslide prediction in the Badung regency over the period from 2015 to 2022. Rainfall threshold analysis in this investigation focuses on cumulative rainfall events occurring 5, 7, 10, and 15 days prior to the onset of landslides. The first fusion was established through the application of the cumulative distribution functions method, involving a comparison between the SRDs and the datasets from rain gauges. Subsequently, the analysis transitioned to the second fusion, where a weighted correlation coefficient function was employed to assess the connections between rain gauges and individual SRDs. The results illustrate that the second fusion of SRDs yields an area under the curve value of 0.82 for a 15-day cumulative rainfall, surpassing the performance of the first fusion. The first quartile approach demonstrates the highest accuracy compared to alternative methods, providing a reliable estimation of landslide occurrences with minimal error.

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Acknowledgements

Thanks to the Regional Disaster Management Agency of Badung regency for furnishing the essential information and data for this study. Thanks to the Directorate of Research, Technology and Community Service of the Ministry of Education, Culture, Research and Technology for their financial support towards this research endeavor.

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Authors and Affiliations

  1. Department of Civil Engineering, Warmadewa University, Denpasar, Indonesia

    Putu Aryastana

  2. Master Program of Infrastructure and Environmental Engineering, Postgraduate Program, Warmadewa University, Denpasar, Indonesia

    Listya Dewi, Putu Ika Wahyuni & I. Nengah Sinarta

  3. Department of Physics, College of Science, Bicol University, Legazpi City, Philippines

    Jason Pajimola Punay

  4. Preparatory Center for Science and Technology, University Malaysia Sabah (UMS), Sabah, Malaysia

    Jackson Chang Hian Wui

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  1. Putu Aryastana
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  2. Listya Dewi
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  3. Putu Ika Wahyuni
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  4. I. Nengah Sinarta
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Correspondence to Putu Aryastana .

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Editors and Affiliations

  1. Department of Geography, KISS Deemed University, School of Tribal Resource Development, Bhubaneswar, India

    Gopal Krishna Panda

  2. Graduate School of Media and Governance, Keio University Shonan Fujisawa, Japan, Japan

    Rajib Shaw

  3. Department of Geography, The University of Burdwan, Bardhaman, India

    Subodh Chandra Pal

  4. Department of Geography, Bhatter College, Dantan (Vidyasagar Univ, Kharagpur, Paschim Medinipore,, India

    Uday Chatterjee

  5. Department of Geography, The University of Burdwan, Bardhaman, India

    Asish Saha

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Aryastana, P., Dewi, L., Wahyuni, P.I., Sinarta, I.N., Punay, J.P., Wui, J.C.H. (2024). Evaluation of Double Fusion Satellite Rainfall Dataset in Establish Rainfall Thresholds for Landslide Occurrences Over Badung Regency-Bali. In: Panda, G.K., Shaw, R., Pal, S.C., Chatterjee, U., Saha, A. (eds) Landslide: Susceptibility, Risk Assessment and Sustainability. Advances in Natural and Technological Hazards Research, vol 52. Springer, Cham. https://doi.org/10.1007/978-3-031-56591-5_22

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