Pengembangan Climate-Integrated Road Vulnerability Index untuk Menilai Dampak Hujan Ekstrem terhadap Infrastruktur Jalan
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Abstract
Perubahan iklim global telah meningkatkan intensitas hujan ekstrem yang secara signifikan memengaruhi kinerja dan ketahanan infrastruktur jalan, namun pendekatan penilaian kerusakan yang ada masih didominasi oleh analisis kondisi eksisting tanpa integrasi variabel iklim secara komprehensif. Kesenjangan ini membatasi kemampuan prediksi kerentanan jalan dalam menghadapi tekanan hidrometeorologis yang semakin kompleks. Penelitian ini bertujuan mengembangkan indeks risiko kerentanan infrastruktur jalan berbasis iklim yang mengintegrasikan variabel iklim ekstrem dan karakteristik struktural jalan. Penelitian dilakukan pada beberapa segmen jalan dengan panjang 500–1000 m menggunakan data curah hujan, kondisi drainase, material perkerasan, dan volume lalu lintas, serta data kerusakan jalan yang diukur melalui IRI. Analisis dilakukan menggunakan regresi linier, Analytical Hierarchy Process (AHP), dan pemodelan indeks risiko berbasis normalisasi. Hasil menunjukkan bahwa curah hujan ekstrem (>100 mm/hari) meningkatkan kerusakan jalan hingga 48% dengan koefisien regresi signifikan (β = 0,48; p < 0,01), serta 62% segmen jalan berada dalam kategori risiko tinggi. Temuan ini menegaskan dominasi faktor iklim dalam menentukan kerentanan jalan dan menunjukkan bahwa indeks yang dikembangkan mampu mengklasifikasikan risiko secara akurat. Secara keseluruhan, penelitian ini berkontribusi pada penguatan Infrastructure Resilience & Climate Risk Theory serta menyediakan alat analitis berbasis data untuk mendukung pengambilan keputusan dalam manajemen infrastruktur jalan yang berkelanjutan.
Abstract
Global climate change has intensified extreme rainfall events, significantly affecting the performance and resilience of road infrastructure; however, existing assessment approaches remain largely condition-based and fail to integrate climate variables fully. This gap limits the predictive capacity of vulnerability assessments under increasing hydrometeorological stress. This study aimed to develop a climate-integrated road vulnerability risk index that incorporates extreme climate variables and structural characteristics of road infrastructure. The study was conducted across multiple road segments (500–1000 m) using datasets on rainfall intensity, drainage conditions, pavement materials, traffic volume, and road damage, measured using the International Roughness Index (IRI). Data were analyzed using linear regression, Analytical Hierarchy Process (AHP), and normalized risk index modeling. The results showed that extreme rainfall (>100 mm/day) increased road deterioration by 48% (β = 0.48; p < 0.01), with 62% of road segments classified as high risk. These findings indicate the dominant role of climate factors in determining road vulnerability and demonstrate that the proposed index effectively classifies risk levels. Overall, this study advances Infrastructure Resilience & Climate Risk Theory and provides a data-driven analytical tool to support decision-making in sustainable road infrastructure management.
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