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Statistical emulators are a key tool for rapidly producing probabilistic hazard analysis of geophysical processes. Given output data computed for a relatively small number of parameter inputs, an emulator interpolates the data, providing the expected value of the output at untried inputs and an estimate of error at that point. In this work, we propose to fit Gaussian Process emulators to the output from a volcanic ash transport model, Ash3d. Our goal is to predict the simulated volcanic ash thickness from Ash3d at a location of interest using the emulator. Our approach is motivated by two challenges to fitting emulators—characterizing the input wind field and interactions between that wind field and variable grain sizes. We resolve these challenges by using physical knowledge on tephra dispersal. We propose new physically motivated variables as inputs and use normalized output as the response for fitting the emulator. Subsetting based on the initial conditions is also critical in our emulator construction. Simulation studies characterize the accuracy and efficiency of our emulator construction and also reveal its current limitations. Our work represents the first emulator construction for volcanic ash transport models with considerations of the simulated physical process. 

Effective volcanic hazard management in regions where populations live in close proximity to persistent volcanic activity involves understanding the dynamic nature of hazards, and associated risk. Emphasis until now has been placed on identification and forecasting of the escalation phase of activity, in order to provide adequate warning of what might be to come. However, understanding eruption hiatus and post-eruption unrest hazards, or how to quantify residual hazard after the end of an eruption, is also important and often key to timely post-eruption recovery. Unfortunately, in many cases when the level of activity lessens, the hazards, although reduced, do not necessarily cease altogether. This is due to both the imprecise nature of determination of the “end” of an eruptive phase as well as to the possibility that post-eruption hazardous processes may continue to occur. An example of the latter is continued dome collapse hazard from lava domes which have ceased to grow, or sector collapse of parts of volcanic edifices, including lava dome complexes. We present a new probabilistic model for forecasting pyroclastic density currents (PDCs) from lava dome collapse that takes into account the heavy-tailed distribution of the lengths of eruptive phases, the periods of quiescence, and the forecast window of interest. In the hazard analysis, we also consider probabilistic scenario models describing the flow’s volume and initial direction. Further, with the use of statistical emulators, we combine these models with physics-based simulations of PDCs at Soufrière Hills Volcano to produce a series of probabilistic hazard maps for flow inundation over 5, 10, and 20 year periods. The development and application of this assessment approach is the first of its kind for the quantification of periods of diminished volcanic activity. As such, it offers evidence-based guidance for dome collapse hazards that can be used to inform decision-making around provisions of access and reoccupation in areas around volcanoes that are becoming less active over time. 

Abstract. We detail a new prediction-oriented procedure aimed at volcanic hazardassessment based on geophysical mass flow models constrained withheterogeneous and poorly defined data. Our method relies on an itemizedapplication of the empirical falsification principle over an arbitrarily wideenvelope of possible input conditions. We thus provide a first step towards aobjective and partially automated experimental design construction. Inparticular, instead of fully calibrating model inputs on past observations,we create and explore more general requirements of consistency, and then weseparately use each piece of empirical data to remove those input values thatare not compatible with it. Hence, partial solutions are defined to the inverseproblem. This has several advantages compared to a traditionally posedinverse problem: (i) the potentially nonempty inverse images of partialsolutions of multiple possible forward models characterize the solutions tothe inverse problem; (ii) the partial solutions can provide hazard estimatesunder weaker constraints, potentially including extreme cases that areimportant for hazard analysis; (iii) if multiple models are applicable,specific performance scores against each piece of empirical information canbe calculated. We apply our procedure to the case study of the Atenquiquevolcaniclastic debris flow, which occurred on the flanks of Nevado de Colimavolcano (Mexico), 1955. We adopt and compare three depth-averaged modelscurrently implemented in the TITAN2D solver, available from https://vhub.org(Version 4.0.0 – last access: 23 June 2016). The associated inverse problemis not well-posed if approached in a traditional way. We show that our procedurecan extract valuable information for hazard assessment, allowing the explorationof the impact of synthetic flows that are similar to those that occurred in thepast but different in plausible ways. The implementation of multiple models isthus a crucial aspect of our approach, as they can allow the covering of otherplausible flows. We also observe that model selection is inherently linked tothe inversion problem.

 

Abstract. Plume-SPH provides the first particle-based simulation ofvolcanic plumes. Smoothed particle hydrodynamics (SPH) has several advantagesover currently used mesh-based methods in modeling of multiphase freeboundary flows like volcanic plumes. This tool will provide more accurateeruption source terms to users of volcanic ash transport anddispersion models (VATDs), greatly improving volcanic ash forecasts. The accuracy ofthese terms is crucial for forecasts from VATDs, and the 3-D SPH modelpresented here will provide better numerical accuracy. As an initial effortto exploit the feasibility and advantages of SPH in volcanic plume modeling,we adopt a relatively simple physics model (3-D dusty-gas dynamic modelassuming well-mixed eruption material, dynamic equilibrium and thermodynamicequilibrium between erupted material and air that entrained into the plume,and minimal effect of winds) targeted at capturing the salient features of avolcanic plume. The documented open-source code is easily obtained andextended to incorporate other models of physics of interest to the largecommunity of researchers investigating multiphase free boundary flows ofvolcanic or other origins.

The Plume-SPH code (https://doi.org/10.5281/zenodo.572819) also incorporates several newly developed techniques inSPH needed to address numerical challenges in simulating multiphasecompressible turbulent flow. The code should thus be also of general interestto the much larger community of researchers using and developing SPH-basedtools. In particular, the SPH−ε turbulence model is used to capturemixing at unresolved scales. Heat exchange due to turbulence is calculated bya Reynolds analogy, and a corrected SPH is used to handle tensile instabilityand deficiency of particle distribution near the boundaries. We alsodeveloped methodology to impose velocity inlet and pressure outlet boundaryconditions, both of which are scarce in traditional implementations of SPH.

The core solver of our model is parallelized with the message passinginterface (MPI) obtaining good weak and strong scalability using novel techniquesfor data management using space-filling curves (SFCs), object creationtime-based indexing and hash-table-based storage schemes. These techniques areof interest to researchers engaged in developing particles in cell-typemethods. The code is first verified by 1-D shock tube tests, then bycomparing velocity and concentration distribution along the central axis andon the transverse cross with experimental results of JPUE (jet or plume thatis ejected from a nozzle into a uniform environment). Profiles of severalintegrated variables are compared with those calculated by existing 3-D plumemodels for an eruption with the same mass eruption rate (MER) estimated forthe Mt. Pinatubo eruption of 15 June 1991. Our results are consistent withexisting 3-D plume models. Analysis of the plume evolution processdemonstrates that this model is able to reproduce the physics of plumedevelopment.