Volume 7, Issue 1, January 2019, Page: 21-26
A Logistic Model Predicting Occurrence Probability of Debris Flow
J. P. Wang, Civil Engineering, National Central University, Taoyuan, Taiwan, Republic of China
Yijie Wu, Civil Engineering, National Central University, Taoyuan, Taiwan, Republic of China
Received: Apr. 26, 2019;       Published: Apr. 28, 2019
DOI: 10.11648/j.ajce.20190701.14      View  29      Downloads  14
This paper presents a logistic model for predicting the occurrence probability of debris flows based on rainfall intensity and duration. The data from a total of 354 rainfall events were used to calibrate the model, among which 249 were triggering a debris flow while 105 were not. The model will be useful to the decision making of debris flow early warning in the future. That is, given the estimated occurrence probability = 70% subject to a combination of rainfall intensity and duration, there is a 30% probability that the early warning will be a false alarm. By contrast, if decision makers decide not to issue an early warning, then there is a 70% chance leading to a missed alarm. Subsequently, integrating the consequences of missed alarm and false alarm into the equation, the respective risks can be computed, based on which decision makers can make a more robust decision whether an early warning is needed or not by choosing the scenario with a lower risk.
Debris Flow, Logistic Regression, Occurrence Probability
To cite this article
J. P. Wang, Yijie Wu, A Logistic Model Predicting Occurrence Probability of Debris Flow, American Journal of Civil Engineering. Vol. 7, No. 1, 2019, pp. 21-26. doi: 10.11648/j.ajce.20190701.14
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