Pipeline rights-of-way that cross mountainous regions are prone to natural occurring events that may affect the crossing pipelines’ integrity. Notably, pipelines on the coast of the state São Paulo, Brazil, crosses a tropical mountainous region called Serra do Mar, which is often subject to hazards caused by rainfall triggered landslides. Therefore, geotechnical risk management of these pipelines needs to account for the probability of occurrence of landslides that directly affects the pipeline right-of-way. Since the region that comprises the pipeline right-of-way is large and subject to many material and geometry heterogeneities, physical models that try to predict landslide occurrences are usually inviable. Hence, statistical models that relates meteorological indexes with landslides’ historical series are usually the chosen models to manage earth movement risks. In this regard, this paper shows a statistical model for rainfall triggered landslides developed to guarantee the safe operation of the pipelines in Serra do Mar, São Paulo, Brazil. The model consists of an empirical model fit using rainfall volume accumulated in 24 h and 72 h data associated with landslides data records of field inspections. The fit is used to generate probability of landslide occurrence zones (i.e. susceptibility zones) on a two-dimensional chart consisting of (72 h rainfall volume) X (24 h rainfall volume). Appropriate response actions are defined for these probability zones. The new model has successfully been employed to start pipeline rights-of-way field inspections. It also makes possible to continuously improve the susceptibility zones’ position, resulting in a more precise model when rainfall data increases.
A statistical model for pipeline rainfall triggered landslides risk management
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