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All Journal AMPLITUDO: Journal of Science & Technology Innovation
Dyah Permata Sari
University of Surabaya
Agriculture, Biological Sciences & Forestry Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture

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Hybrid GNSS-Rainfall Decision Support for Staged Early Warning of Rainfall-Induced Slope Instability in Agricultural Landscapes: A Yarra Valley Prototype Supporting SDG 2 and SDG 11 Madlazim Madlazim; Muhammad Nurul Fahmi; Arie Realita; Baba Musta; Dyah Permata Sari; Khaista Rehman
AMPLITUDO : Journal of Science and Technology Innovation Vol. 5 No. 2 (2026): August
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/amplitudo.v5i2.736

Abstract

Early detection of rainfall-induced slope instability in agricultural terrain remains difficult because hydrological loading commonly precedes measurable ground movement. This study develops an explainable decision-support framework that integrates GNSS-derived detrended displacement, antecedent rainfall indicators, and a machine-learning anomaly score for staged warning in the Yarra Valley, Australia. A regional target-control GNSS architecture was implemented with four slope stations and two control stations, and a retrospective rainfall-driven event window in April 2025 with complete processing products was analysed. The workflow combines 24 h and 72 h rainfall accumulation, target-control displacement metrics, deformation gradients, and a weighted fusion index to distinguish background variability from physically plausible slope response. Cumulative rainfall increased before localized deformation emerged, and the lower slope sector showed stronger response than the upper sector. The fusion layer therefore supports escalation from normal to watch and, when rainfall and deformation thresholds are jointly exceeded, to warning. This prototype strengthens operational decision-making for agricultural slope management and provides a basis for multi-event validation and wider deployment
Co-Authors Arie Realita Baba Musta Khaista Rehman Madlazim Madlazim Muhammad Nurul Fahmi