Hydro-Meteorological Landslide Inventory for Sustainable Urban Management in a Coastal Region of Brazil

Paulo Rodolpho Pereira Hader (), Isabela Taici Lopes Gonçalves Horta, Victor Arroyo da Silva do Valle and Clemente Irigaray ()
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Paulo Rodolpho Pereira Hader: Department of Civil Engineering, University of Granada, 18071 Granada, Spain
Isabela Taici Lopes Gonçalves Horta: São Carlos School of Engineering, University of São Paulo, São Carlos 13566-590, Brazil
Victor Arroyo da Silva do Valle: Civil Protection and Defence Department, Santos City Hall, Santos 11013-550, Brazil
Clemente Irigaray: Department of Civil Engineering, University of Granada, 18071 Granada, Spain

Sustainability, 2025, vol. 17, issue 16, 1-29

Abstract: Comprehensive, standardised, multi-temporal inventories of rainfall-induced landslides linked to soil moisture remain scarce, especially in tropical regions. Addressing this gap, we present a multi-source urban inventory for Brazil’s Baixada Santista region (1988–2024). A key advance is the introduction of geographical and temporal confidence classifications, which indicates precisely how each landslide’s location and occurrence date are known, thereby addressing a previously overlooked criterion in Brazil’s landslide data treatment. The inventory comprises 2534 records categorised by spatial (G1–G3) and temporal (T1–T3) confidence. Notable findings include the following: (i) confidence classifications enhance inventory reliability for research and early warning, though precise temporal data remains challenging; (ii) multi-source integration with UAV validation is key to robust inventories in urban tropical regions; (iii) soil moisture complements rainfall-based warnings, but requires local calibration for satellite-derived estimates; (iv) data gaps and biases underscore the need for standardised landslide documentation; and (v) the framework is transferable, providing a scalable model for Brazil and worldwide. Despite limitations, the inventory provides a foundation for (i) susceptibility and hazard modelling; (ii) empirical thresholds for early warning; and (iii) climate-related trend analyses. Overall, the framework offers a sustainable, practical, transferable method for worldwide and contributes to strengthening disaster information systems and early warning capacities.

Keywords: landslide catalogue; rainfall; soil moisture; landslide prediction; early warning systems (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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