Volcanic gas dispersal can be a serious threat to people living near active volcanoes since it can have short- and long-term effects on human health, and severely damage crops and agricultural land. In recent decades, reliable computational models have significantly advanced, and now they may represent a valuable tool to make quantitative and testable predictions, supporting gas dispersal forecasting and hazard assessments for public safety. Before applying a specific modelling tool into hazard quantification, its calibration and its sensitivity to initial and boundary conditions should be carefully tested against available data, in order to produce unbiased hazard quantifications. In this study, we provided a number of prototypical tests aimed to validate the modelling of gas dispersal from a hazard perspective. The tests were carried out at La Soufrière de Guadeloupe volcano, one of the most active gas emitters in the Lesser Antilles. La Soufrière de Guadeloupe has shown quasi-permanent degassing of a low-temperature hydrothermal nature since its last magmatic eruption in 1530 CE, when the current dome was emplaced. We focused on the distribution of CO2 and H2S discharged from the three main present-day fumarolic sources at the summit, using the measurements of continuous gas concentrations collected in the period March–April 2017. We developed a new probabilistic implementation of the Eulerian code DISGAS-2.0 for passive gas dispersion coupled with the mass-consistent Diagnostic Wind Model, using local wind measurements and atmospheric stability information from a local meteorological station and ERA5 reanalysis data. We found that model outputs were not significantly affected by the type of wind data but rather upon the relative positions of fumaroles and measurement stations. Our results reproduced the statistical variability in daily averages of observed data over the investigated period within acceptable ranges, indicating the potential usefulness of DISGAS-2.0 as a tool for reproducing the observed fumarolic degassing and for quantifying gas hazard at La Soufrière. The adopted testing procedure allows for an aware application of simulation tools for quantifying the hazard, and thus we think that this kind of testing should actually be the first logical step to be taken when applying a simulator to assess (gas) hazard in any other volcanic contexts.
Testing gas dispersion modelling: A case study at La Soufrière volcano (Guadeloupe, Lesser Antilles)
Massaro S.;Moretti R.;
2021
Abstract
Volcanic gas dispersal can be a serious threat to people living near active volcanoes since it can have short- and long-term effects on human health, and severely damage crops and agricultural land. In recent decades, reliable computational models have significantly advanced, and now they may represent a valuable tool to make quantitative and testable predictions, supporting gas dispersal forecasting and hazard assessments for public safety. Before applying a specific modelling tool into hazard quantification, its calibration and its sensitivity to initial and boundary conditions should be carefully tested against available data, in order to produce unbiased hazard quantifications. In this study, we provided a number of prototypical tests aimed to validate the modelling of gas dispersal from a hazard perspective. The tests were carried out at La Soufrière de Guadeloupe volcano, one of the most active gas emitters in the Lesser Antilles. La Soufrière de Guadeloupe has shown quasi-permanent degassing of a low-temperature hydrothermal nature since its last magmatic eruption in 1530 CE, when the current dome was emplaced. We focused on the distribution of CO2 and H2S discharged from the three main present-day fumarolic sources at the summit, using the measurements of continuous gas concentrations collected in the period March–April 2017. We developed a new probabilistic implementation of the Eulerian code DISGAS-2.0 for passive gas dispersion coupled with the mass-consistent Diagnostic Wind Model, using local wind measurements and atmospheric stability information from a local meteorological station and ERA5 reanalysis data. We found that model outputs were not significantly affected by the type of wind data but rather upon the relative positions of fumaroles and measurement stations. Our results reproduced the statistical variability in daily averages of observed data over the investigated period within acceptable ranges, indicating the potential usefulness of DISGAS-2.0 as a tool for reproducing the observed fumarolic degassing and for quantifying gas hazard at La Soufrière. The adopted testing procedure allows for an aware application of simulation tools for quantifying the hazard, and thus we think that this kind of testing should actually be the first logical step to be taken when applying a simulator to assess (gas) hazard in any other volcanic contexts.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
