Thresholds of Instability: Precipitation, Landslides, and Early Warning Systems in Brazil — Oak Academic Publishing
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Thresholds of Instability: Precipitation, Landslides, and Early Warning Systems in Brazil
Environmental Engineering Department, Institute of Science and Technology, São Paulo State University, São José dos Campos, Brazil
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Environmental Engineering Department, Institute of Science and Technology, São Paulo State University, São José dos Campos, Brazil
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Cemaden—National Center for Monitoring and Early Warning of Natural Disasters, General Coordination of Research and Development, São José dos Campos, Brazil
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Environmental Engineering Department, Institute of Science and Technology, São Paulo State University, São José dos Campos, Brazil
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Cemaden—National Center for Monitoring and Early Warning of Natural Disasters, General Coordination of Research and Development, São José dos Campos, Brazil
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Cemaden—National Center for Monitoring and Early Warning of Natural Disasters, General Coordination of Research and Development, São José dos Campos, Brazil
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Department of Mathematical Sciences, University of Bath, Bath, UK
1 Environmental Engineering Department, Institute of Science and Technology, São Paulo State University, São José dos Campos, Brazil
2 Environmental Engineering Department, Institute of Science and Technology, São Paulo State University, São José dos Campos, Brazil
3 Cemaden—National Center for Monitoring and Early Warning of Natural Disasters, General Coordination of Research and Development, São José dos Campos, Brazil
4 Environmental Engineering Department, Institute of Science and Technology, São Paulo State University, São José dos Campos, Brazil
5 Cemaden—National Center for Monitoring and Early Warning of Natural Disasters, General Coordination of Research and Development, São José dos Campos, Brazil
6 Cemaden—National Center for Monitoring and Early Warning of Natural Disasters, General Coordination of Research and Development, São José dos Campos, Brazil
7 Department of Mathematical Sciences, University of Bath, Bath, UK
Rainfall accumulation thresholds are crucial for issuing landslide warnings by identi fying when soil saturation from rain could potentially trigger a landslide. Two essential types of thresholds are considered: environmental and opera tional. The environmental threshold indicates the minimum rainfall level req uired to potentially initiate a landslide. Conversely, the operational thre shold is set lower to enable agencies to issue alerts before reaching environme ntal thresholds. Establishing these thresholds improves the accuracy o f landslide predictions in terms of location and timing. This study introduces an innovative approach for determining these thresholds. Our approach employs cluster analysis and historical landslide data from the Metropolitan Region of Recife, Pernambuco State, Brazil. We applied our defined values to a significant landslide event in 2022, validating their robustness as the foundation for the operational threshold used by Cemaden, Brazil’s National Center for Monitoring and Early Warning of Natural Disasters.
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