DOI: https://doi.org/10.14710/geoplanning.11.2.69-84

Utilizing Open Access Spatial Data for Flood Risk Mapping: A Case Study in the Upper Solo Watershed

*J Jumadi orcid  -  Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Danardono Danardono orcid  -  Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Kuswaji Dwi Priyono orcid  -  Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Efri Roziaty orcid  -  Faculty of Education, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Heni Masruroh orcid  -  Malang State University, Malang, Indonesia
Arif Rohman orcid  -  Institute Technology Sumatera, Lampung, Indonesia
Choirul Amin orcid  -  Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Hamim Zaky Hadibasyir orcid  -  Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, Indonesia
Vidya N. Fikriyah orcid  -  Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, Netherlands
Muhammad Nawaz orcid  -  National University of Singapore, Singapore
Farha Sattar orcid  -  Charles Darwin University, Darwin, Australia
Aynaz Lotfata orcid  -  University of California, Davis, United States

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Abstract

Indonesia is experiencing a rise in natural disasters due to its geographical position within a tropical region, with the Upper Solo River watershed exhibiting a heightened risk of flooding. This region has already suffered numerous floods due to excessive precipitation and insufficient drainage. Susceptibility, hazard, and risk studies have been conducted to investigate this phenomenon but have been limited to specific regions within the catchment area. This study aims to construct a GIS-based flood risk model using Open-Access Spatial Data (OASD) based on diverse physical characteristics, urbanization levels, and population. We used several OASD, including SRTM, Sentinel 2 MSI, GPM v6, NASA-USDA Enhanced SMAP Global Soil Moisture Data, GHS-SMOD R2023A - Global Human Settlement Layers, and GHSL: Global Population Surfaces 1975-2030 (P2023A). The model integrates the risk parameters to identify flood risk using a weighted overlay in ArcGIS. The results demonstrate spatial heterogeneity in flood risk throughout the watershed. The result also reveals that Surakarta City, with a high proportion of its area in the 'High' (57.3%) and 'Very High' (29.54%) risk categories, is at the highest risk of flooding within the watershed. The study enhances understanding of this topic by comprehensively evaluating flood hazards, vulnerabilities, and risks. It highlights the significance of utilizing low-cost OASD to improve flood preparedness and response strategies.

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Keywords: Natural Hazard, Flood, Risk, GIS, Solo River Watershed

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Section: Original Research
Language : EN
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