Bayesian Inference of Forest Road Collapse Frequency at Various Rainfall Intensities Using Low-Resolution Forest Road Register Data

• Published in: Journal of the Japanese Forest Society Vol. 105; no. 9; pp. 298 - 305
• Main Authors: Muneoka, Hiroko, Zushi, Kotaro, Shirasawa, Hiroaki, Suzuki, Hidenori
• Format: Journal Article
• Language: Japanese
• Published: The Japanese Forest Society 01.09.2023
• Subjects: analyzed precipitation data; Bayesian inference; forest road collapse; Forest Road Register
• ISSN: 1349-8509; 1882-398X
• DOI: 10.4005/jjfs.105.298

To predict future forest road collapses with the increasing influence of climate change, the relationship between the frequency of forest road collapse and rainfall intensity should be determined. Due to the long recurrence period between intense rainfalls, a long-term, broad-based record of forest road collapses is required. The Forest Road Register, which contains the records of the annual number of collapses on forest roads across Japan, is a good data source but does not identify the rainfall intensity that caused each collapse. Thus, we proposed an estimation method using Bayesian inference based on a general regression model to determine rainfall intensity and forest road collapse frequency using Forest Road Register data. To check the feasibility of the proposed method, we evaluated the model using either high- or low-resolution data for forest road collapse in Toyama Prefecture from 1998 to 2018. High resolution data included the date each collapse occurred; thus, the rainfall event that caused each collapse can be identified. Low resolution data included only the annual number of collapses of each road, just like the Forest Road Register does. The expected collapse frequencies were of the same order of magnitude in both models for rainfall events between 100 mm and 400 mm per 24 h. The proposed estimation method using low-resolution data sources is applicable to areas that have a similar or lower frequency of intense rainfall events than Toyama Prefecture. The applicability is also affected by road length registered as one road in the Forest Road Register.