Exploring the Application of a Debris Flow Likelihood Regression Model in Mediterranean Post-Fire Environments, Using Field Observations-Based Validation

Michalis Diakakis (), Spyridon Mavroulis, Emmanuel Vassilakis and Vassiliki Chalvatzi
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Michalis Diakakis: Department of Dynamic Tectonic and Applied Geology, Faculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, 15784 Panepistimioupoli Zografou, Greece
Spyridon Mavroulis: Department of Dynamic Tectonic and Applied Geology, Faculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, 15784 Panepistimioupoli Zografou, Greece
Emmanuel Vassilakis: Department of Geography and Climatology, Faculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, 15784 Panepistimioupoli Zografou, Greece
Vassiliki Chalvatzi: Department of Dynamic Tectonic and Applied Geology, Faculty of Geology and Geoenvironment, National and Kapodistrian University of Athens, 15784 Panepistimioupoli Zografou, Greece

Land, 2023, vol. 12, issue 3, 1-18

Abstract: Post-fire geomorphic processes and associated risks are an important threat in Mediterranean environments. Currently, post-fire mass movement prediction has limited applications across the Mediterranean despite the abundance of both forest fires and landslide/debris flow disasters. This work applies a debris flow generation likelihood model to evaluate the probability of mass movement phenomena in different catchments of a burnt area, after a catastrophic fire near Schinos (Attica, Greece) in 2021. Then, it uses field observations from the area, recording mass movement phenomena after high-intensity rainfall events, to validate the results. The findings show that the model is successful in determining the probability of debris flow generation in the 21 basins of the study area, ranging from 0.05 to 0.893. The probability values show a statistically significant correlation (sig. = 0.001) with the actual debris flow occurrences in the area, and satisfactory results in terms of the model’s predictive ability, functioning well within the particular geo-environmental characteristics of the Mediterranean environment. The results establish the reliability of the approach as a tool to assess mass movement risks in a region with an abundance of post-fire related hazards and disastrous events.

Keywords: debris flow; post-fire; likelihood regression model; Mediterranean environment (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
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