Conclusion: recommendations and findings of the RED SEED working group

Abstract

RED SEED stands for Risk Evaluation, Detection and Simulation during Effusive Eruption Disasters, and combines stakeholders from the remote sensing, modelling and response communities with experience in tracking volcanic effusive events. The group first met during a three day-long workshop held in Clermont Ferrand (France) between 28 and 30 May 2013. During each day, presentations were given reviewing the state of the art in terms of (a) volcano hot spot detection and parameterization, (b) operational satellite-based hot spot detection systems, (c) lava flow modelling and (d) response protocols during effusive crises. At the end of each presentation set, the four groups retreated to discuss and report on requirements for a truly integrated and operational response that satisfactorily combines remote sensors, modellers and responders during an effusive crisis. The results of collating the final reports, and follow-up discussions that have been on-going since the workshop, are given here. We can reduce our discussions to four main findings. (1) Hot spot detection tools are operational and capable of providing effusive eruption onset notice within 15 min. (2) Spectral radiance metrics can also be provided with high degrees of confidence. However, if we are to achieve a truly global system, more local receiving stations need to be installed with hot spot detection and data processing modules running on-site and in real time. (3) Models are operational, but need real-time input of reliable time-averaged discharge rate data and regular updates of digital elevation models if they are to be effective; the latter can be provided by the radar/photogrammetry community. (4) Information needs to be provided in an agreed and standard format following an ensemble approach and using models that have been validated and recognized as trustworthy by the responding authorities. All of this requires a sophisticated and centralized data collection, distribution and reporting hub that is based on a philosophy of joint ownership and mutual trust. While the next chapter carries out an exercise to explore the viability of the last point, the detailed recommendations behind these findings are detailed here.

Benchmarking computational fluid dynamics models of lava flow simulation for hazard assessment, forecasting, and risk management

“…Model validation and comparison is a necessary community exercise to test the codes used for studying lava flow behavior, constructing hazard assessments, and forecasting flow behavior during crises (Harris et al, 2016). In our study, we employ experimental data that capture the fundamental physics of lava flows as benchmarks for assessing the accuracy and speed of several different lava flow modeling codes.…”

Risk evaluation, detection and simulation during effusive eruption disasters

“…All detection algorithm outputs for these two cases are collated in Appendix C of Harris et al (2016). For linking with lava flow models, we agreed to Fig.…”

“…Located in the centre of France, immediately to the east of the Chaîne des Puys, this urban area covers 42.67 km 2 , has a population of 142 948, and contains 10 240 industrial, commercial and service establishments (source: INSEE 2007 andClermont Communauté en Chiffres 2008). While the results of these tests are collated in Appendix D of Harris et al (2016). Benchmarking of the same flow models is presented in Cordonnier et al (2015) for the Etna 2001 eruption, for which the dynamics and chronologies of flow emplacement are better known than for the Chaîne des Puys cases.…”

Modeling lava flow propagation over a flat landscape by using MrLavaLoba: the case of the 2014–2015 eruption at Holuhraun, Iceland

“…The Holuhraun eruption began in August 2014, when only an embryonic version of the MrLavaLoba code ex− isted [de' Michieli Vitturi and Tarquini 2018]. On the one hand, this was an evident drawback, because develop− ing the tool for performing the simulations during an ongoing crisis is not recommended [Harris et al, 2016]. On the other hand, the unusual characteristic of this eruption and the limited quality of the available topog− raphy at the onset of lava effusion (described later) were quite challenging, and stimulated the implemen− tation of specific modeling strategies.…”

“…Several lava flow simulation codes have been, and continue to be, developed [e.g. Cordonnier et al, 2016;Dietterich et al, 2017] and the scientific community is developing and promoting best practices to support further ad− vances and to better connect researchers and commu− nities vulnerable to lava flows [Harris, 2015;Harris et al, 2016;Mossoux et al, 2016].…”