FlowDIR: a MATLAB tool for rapidly and probabilistically forecasting the travel directions of volcanic flows

Journal of Applied Volcanology

Methodology

Sébastien Biass¹  Eleanor Tennant²  Susanna F. Jenkins³ 

[1] Department of Earth Sciences, University of Geneva, Geneva, Switzerland;Earth Observatory of Singapore @ NTU, Interdisciplinary Graduate Programme, Nanyang Technological University, Singapore, Singapore;Earth Observatory of Singapore and Asian School of the Environment, Nanyang Technological University, 639798, Singapore, Singapore;

关键词: Volcanic hazards;    Hazard models;    Hazardous flows;    Topography;   

DOI  :  10.1186/s13617-023-00136-3

 received in 2022-06-30, accepted in 2023-09-26,  发布年份 2023

来源: Springer

【 摘 要 】

We present FlowDIR, a MATLAB tool that rapidly and objectively quantifies future travel direction probabilities for topographically controlled hazardous flows, based on analysis of summit topography. FlowDIR can achieve probabilistic forecasts of future travel directions in minutes and provides a basis for choosing the starting co-ordinates required by empirical flow models. In this work we describe the development of FlowDIR, perform a sensitivity analysis to determine the influence of input parameters on forecasted probabilities, and demonstrate its effectiveness in the retrospective forecasting of travel directions for block-and-ash flows and lava flows at three volcanoes with different summit morphologies (Shinmoedake, Colima and Merapi). In all case studies, the higher probability flow directions identified using FlowDIR agreed with the travel direction of historically observed flows. Given its intuitive outputs and rapid execution time, FlowDIR can be used to supplement existing modelling strategies for hazard assessment of topographically controlled hazardous flows prior to and during crisis. We demonstrate this by coupling FlowDIR output probabilities with an empirical hazard model to estimate probability of block-and-ash flow inundation at Gede volcano, Indonesia.

【 授权许可】

CC BY   
© Springer-Verlag GmbH Germany, part of Springer Nature 2023

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