Are you seeking a probabilistic method for assessing landslide hazard, for purposes such as land use planning and landslide hazard zonation? It is essential to take into account the spatial, temporal, and magnitude probabilities of landslide occurrence. You can utilize TRIGRS with a probabilistic approach, such as the Monte Carlo method, for this purpose.
I have developed a Python program for applying Monte Carlo simulation in landslide susceptibility or hazard assessment, utilizing the physically-based model TRIGRS. This approach is highly valuable as it incorporates uncertainty into the assessment process. The program identifies areas susceptible to shallow landslide occurrence in terms of the probability of failure (pf). An illustrative example featuring a Monte Carlo simulation comprising 10,000 iterations, with soil mechanical and hydraulic parameters treated as random variables, is demonstrated in a tropical mountain basin located in Envigado, Colombia. The details of this methodology’s implementation are elaborated upon in a research article:
Figure 1. Location of the Envigado (Colombia) basin for landslide assessment.
Figure 2. Failure probability (Pf) calculated after 1,000 Monte Carlo simulations using TRIGRS.
Video presentation: