Modeling the geomorphologic susceptibility to debris flow initiation with geomorphometric parameters and fuzzy logic in the mountainous region of Serra do Mar (state of Paraná, Brazil).
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| Title: | Modeling the geomorphologic susceptibility to debris flow initiation with geomorphometric parameters and fuzzy logic in the mountainous region of Serra do Mar (state of Paraná, Brazil). |
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| Authors: | Silveira, Ricardo Michael Pinheiro1 (AUTHOR) ricardomichael@ufpr.br, Silveira, Claudinei Taborda1 (AUTHOR) claudineits@ufpr.br |
| Source: | Natural Hazards. Jun2025, Vol. 121 Issue 10, p11855-11883. 29p. |
| Subject Terms: | *Geomorphological mapping, *Debris avalanches, *Digital elevation models, *Fuzzy logic, *Histograms |
| Abstract: | The study proposes a model that identifies the areas that are most susceptible to the debris flow initiation, using geomorphometric techniques and fuzzy logic. The reference event occurred in March 2011, in the mountainous region of Serra do Mar in the state of Paraná, in southern Brazil, in which the accumulated rainfall volume was 241.8 mm in 24 h. Supported by an inventory of scars, the debris flow initiation areas were randomly divided between reference and validation samples, with the respective representation of 75% and 25%. Two DEMs (Topogrid 10 m and ALOS/PALSAR RTC 12.5 m derived from the resampled SRTM) were compared and four geomorphometric attributes were calculated for each: slope, contributing area, topographic position index and elevation amplitude, whose frequency histograms were used as a reference for the fuzzification. Twelve scenarios were obtained, using six options for the overlays, with five different fuzzy operators. In degree of membership, Topogrid DEM was superior to ALOS/PALSAR RTC DEM (resampled SRTM) in all operators, with an overall mean of 91% and 85%, respectively. In conclusion, the fuzzy operator Product in the Topogrid DEM resulted in the best scenario, with a high prediction rate (79%) and a low overestimation rate (3%). Individually, the contributing area was the geomorphometric attribute more successful (92% predictive and 5% overestimation) in Topodrid DEM. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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