Stochastic Modeling of the Eruption History of Nyiragongo Volcano in the Virunga Volcanic Province, Western Branch of the East African Rift System

Abstract

The modeling of statistical distribution of the eruptive frequency provides basic information to quantitatively assess the volcanic hazard and constrain the physics of the eruptive process. Here, we discuss the statistics of the time series of lateral eruptions of the Nyiragongo volcano in the Virunga Volcanic Province, western branch of the East African Rift System. We examine eruption data with a volcanic explosivity index of at least 1 listed in the Global Volcanism Network Bulletins. After investigating the completeness, stationarity, and independence of the eruption time series, we employ five distribution models (Brownian passage time, gamma, log-logistic, lognormal, and Weibull) to fit the repose time. First, we identify a clear tendency for events to cluster in time. We hypothesize two clusters, the ‘pre-1927’ cluster related to the intracraterial and volcanic activity of the lava lake, and the ‘post-1977’ cluster mainly related to lateral eruptions (i.e. those potentially generating lava flows). Using the maximum likelihood estimations, we evaluate the model parameters with a 95% confidence interval. Next, we use the Akaike Information Criterion to determine the most suitable distribution and we perform the Bayesian Model Averaging approach to assess uncertainty issues in model selection process. The results suggest that the BPT distribution provides the best fit for data of lateral eruptions (post-1977). Then we estimate the time-dependent probability of the occurrence of a lateral eruption for the 50-year period between 2022 and 2072. The estimates reach 50.79%, 88.61%, 97.59%, 99.50%, and 99.89% for 2032, 2042, 2052, 2062, and 2072 years, respectively.