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Evolution and Critical Evaluation of Deterministic Physically Based Rainfall-Induced Landslide Susceptibility Mapping: A Mixed Review

Authors

Sachinthaka, Rajitha
Kalatehjari, Roohollah
Brook, Martin S

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Item type

Journal Article

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Publisher

Springer Science and Business Media LLC

Abstract

Physically-based models play a critical role in assessing rainfall-induced landslide susceptibility, offering valuable insights into landslide hazard prediction and risk mitigation. This study conducts a scientometric and systematic review of deterministic, physically-based, rainfall-induced landslide susceptibility mapping, synthesising research trends and advancements in this domain. A comprehensive literature search, conducted through the Scopus database following PRISMA guidelines, identifying 70 key studies for in-depth analysis. The findings reveal significant progress, including the integration of climate change projections, enhanced real-time monitoring systems, and advancements in high-resolution data processing. Despite these developments, challenges persist in achieving a balance between model complexity and practical applicability. This review highlights the need for standardised validation protocols, robust uncertainty analysis, and interdisciplinary approaches that merge physical modelling with machine learning techniques. By evaluating the evolution and current state of deterministic physically-based landslide modelling, this study provides a valuable reference for researchers and practitioners, contributing to the advancement of more reliable and accessible landslide susceptibility assessments.

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Keywords

0401 Atmospheric Sciences, 0406 Physical Geography and Environmental Geoscience, 1701 Psychology, Strategic, Defence & Security Studies, 3709 Physical geography and environmental geoscience

Source

Natural Hazards, ISSN: 0921-030X (Print); 1573-0840 (Online), Springer Science and Business Media LLC. doi: 10.1007/s11069-025-07634-0

Rights statement

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.