Lahar risk assessment from source identification to potential impact analysis: the case of Vulcano Island, Italy

Lahars are rapid flows composed of water and volcaniclastic sediments, which have the potential to impact residential buildings and critical infrastructure as well as to disrupt critical services, especially in the absence of hazard-based land-use planning. Their destructive power is mostly associated with their velocity (related to internal flow properties and topographic interactions) and to their ability to bury buildings and structures (due to deposit thickness). The distance reached by lahars depends on their volume, on sediments/water ratio, as well as on the geometrical properties of the topography where they propagate. Here we present the assessment of risk associated with lahar using Vulcano island (Italy) as a case study. First, we estimated an initial lahar source volume considering the remobilisation by intense rain events of the tephra fallout on the slopes of the La Fossa cone (the active system on the island), where the tephra fallout is associated with the most likely scenario (e.g. long-lasting Vulcanian cycle). Second, we modelled and identified the potential syn-eruptive lahar impact areas on the northern sector of Vulcano, where residential and touristic facilities are located. We tested a range of parameters (e.g., entrainment capability, consolidation of tephra fallout deposit, friction angle) that can influence lahar propagation output both in terms of intensity of the event and extent of the inundation area. Finally, exposure and vulnerability surveys were carried out in order to compile exposure and risk maps for lahar-flow front velocity (semi-quantitative indicator-based risk assessment) and final lahar-deposit thickness (qualitative exposure-based risk assessment). Main outcomes show that the syn-eruptive lahar scenario with medium entrainment capability produces the highest impact associated with building burial by the final lahar deposit. Nonetheless, the syn-eruptive lahar scenario with low entrainment capacity is associated with higher runout and results in the highest impact associated with lahar-flow velocities. Based on our simulations, two critical infrastructures (telecommunication and power plant), as well as the main road crossing the island are exposed to potential lahar impacts (either due to lahar-flow velocity or lahar-deposit thickness or both). These results show that a risk-based spatial planning of the island could represent a valuable strategy to reduce the volcanic risk in the long term.

Novel Intelligent Pigging Tool For Deposit Inspection Using Electrical Tomography with High Computational Efficiency Enabled Through Neural Networks

Objectives/Scope Deposition inspection sensor based on electrical tomography has been proposed recently. In this work, a next generation electrical tomography sensor is introduced and a novel mathematical approach for the estimation of the deposit thickness is described. It is essential for the pipeline operators to keep the lines open for smooth flow and high flow efficiency. Deposit thickness, deposit type and location of deposit is required for optimal pipeline cleaning. The usage of chemicals as well as number of cleaning pig runs can be optimized based on the information that intelligent pig is giving. Methods, Procedures, Process In electrical tomography, electrodes are attached on the surface of the sensor and excitations are applied to some electrodes and responses are measured from other electrodes. The electrical properties of the medium are estimated based on these measurements. In pigging applications, the distribution of electrical properties between the PIG surface and metal pipe is estimated. The thickness and type of deposit (wax/scale) can be identified from the estimated electrical properties. In the proposed approach the estimation of the parameters is done by using a novel deep neural network based approach. In practice, number of measurements that are analyzed after each PIG run can be hundreds of thousands. The neural network based approach was chosen in order to achieve reasonable computational efficiency (computation time) in real applications with large amounts of data. Results, Observations, Conclusions The introduced sensor is for 12-inch lines and designed to be used when the oil line is filled with water. This sensor was tested in a laboratory test line with artificial deposit samples. After these tests and calibration, the sensor is deployed to be used in real pipe line inspections. The major challenges in pipe line runs include the movement of the sensor during measurements, electrical noise and changing excitations. In the neural network model, the position of the PIG is estimated simultaneously with the electrical properties and the effect of all these aforementioned uncertainties are also modelled. Based on the results conclusions can be drawn on the efficiency and performance using neural networks and the high suitability of electrical tomography for deposit mapping. Novel/Additive Information In this study, it is shown that intelligent pig based on the electrical tomography can be used reliable for deposit inspection. Furthermore, the computation approach based on the deep neural network is computationally efficient and it is tolerable for measurement noise and other uncertainties in real measurements.

Lahar Risk Assessment: the Case Study of Vulcano Island, Italy

Lahars are rapid flows composed of water and volcaniclastic sediments, which have the potential to impact residential buildings and critical infrastructure as well as to disrupt critical services, especially in absence of a hazard-based land-use planning. Their destructive power is mostly associated with their velocity (related to flow rheology and surrounding topography) and to their ability to bury buildings and structures (related to the deposit thickness). The distance reached by lahars depends on their volume, on sediments/water ratio, as well as on the overall characteristics of the path where they propagate. Here we present a novel strategy for the assessment of risk associated with lahar inundation related both to flow velocity and deposit thickness using Vulcano island (Italy) as a case study. First, a range of hazard scenarios has been identified that are related to the mobilization by intense rain events of tephra fallout deposited on the slopes of the La Fossa cone by a future Vulcanian eruption. Second, a numerical model has been used to identify the potential lahar impact areas on the northern sector of Vulcano, where both residential and touristic facilities are present. In this specific case we have used the Smoothed Particle Hydrodynamic (SPH) model that provides information on both flow velocity and deposit thickness. Finally, exposure and vulnerability surveys were carried out in order to compile risk maps for both lahar-flow velocity and final lahar-deposit thickness. Our analyses show the importance of carrying out accurate and detailed risk assessments exploring a variety of initial conditions in order to best quantify the potential damage and identify suitable mitigation strategies.

The Utilization of Regression and Analysis of Variance to Model Hurricane Storm Surge Sedimentation on Coastal Marshes along the Northern Gulf of Mexico Coastline

<p>Coastal marshes along the northern Gulf of Mexico coastline provide very important ecosystem services such as serving as habitat for a variety of flora and fauna and providing flood protection for inland areas. A growing body of research has documented how hurricane storm surge sedimentation has increased the elevation of coastal marshes along the northern Gulf of Mexico coastline. This study investigates spatial variations in sediment distribution on McFaddin National Wildlife Refuge, Texas, USA, which is in the geographic region that was impacted by the right-front quadrant of Hurricane Ike. This research builds upon a prior study on hurricane storm surge sedimentation in which the sediment deposits from hurricanes’ Audrey, Carla, Rita, and Ike were identified on a marsh transect on McFaddin National Wildlife Refuge. The purpose of this study was to discover how hurricane storm surge sedimentation spatially varies in relation to the landfall location of Hurricane Ike. Fieldwork conducted in 2017-2018 involved digging shallow pits on four coastal marsh transects between Sabine Pass, Texas and High Island, Texas. Elevations were measured at each pit site along all four transects using a telescopic lens and stadia rod. The transects extend 880-1630 meters, with pit sites beginning near the coastline and extending landward. Results obtained in the field indicate that the Hurricane Ike sediment deposit has been found on all four transects, and that the deposit decreases in thickness moving landward along each transect. Furthermore, the observational results of this study were used in Regression Analyses to model hurricane storm surge sediment deposit thickness based on pit site distance inland, pit site elevation, and distance from the landfall of Hurricane Ike. Moreover, Analysis of Variance revealed whether distance inland, distance from landfall location, and the interaction between distance inland and distance from landfall location had any significant effect on storm surge deposit thickness. Actual sediment deposit thicknesses measured in the field were compared to the Regression and Analysis of Variance results. Results show that the Power Law Curve from the Regression Analyses was the most robust predictor of pit site sediment thickness based on distance inland, with an R<sup>2</sup> value of 0.538. Additionally, the Regression and Analysis of Variance results revealed that transect distance from the landfall location of Hurricane Ike was the only independent variable that could not predict or explain storm surge deposit thickness; which is very likely due to all four transects being in the right-front quadrant of landfalling Hurricane Ike. The findings of this study provide improved understanding of the spatial relationship between storm surge sedimentation and storm surge heights, valuable knowledge about the sedimentary response of coastal marshes subject to storm surge deposition, and useful guidance to public policy aimed at combating the effects of sea-level rise on coastal marshes along the northern Gulf of Mexico coastline.</p><p> </p>

Frictional hysteresis and particle deposition in granular free-surface flows

Shallow granular avalanches on slopes close to repose exhibit hysteretic behaviour. For instance, when a steady-uniform granular flow is brought to rest it leaves a deposit of thickness $h_{stop}(\unicode[STIX]{x1D701})$ on a rough slope inclined at an angle $\unicode[STIX]{x1D701}$ to the horizontal. However, this layer will not spontaneously start to flow again until it is inclined to a higher angle $\unicode[STIX]{x1D701}_{start}$, or the thickness is increased to $h_{start}(\unicode[STIX]{x1D701})>h_{stop}(\unicode[STIX]{x1D701})$. This simple phenomenology leads to a rich variety of flows with co-existing regions of solid-like and fluid-like granular behaviour that evolve in space and time. In particular, frictional hysteresis is directly responsible for the spontaneous formation of self-channelized flows with static levees, retrogressive failures as well as erosion–deposition waves that travel through the material. This paper is motivated by the experimental observation that a travelling-wave develops, when a steady uniform flow of carborundum particles on a bed of larger glass beads, runs out to leave a deposit that is approximately equal to $h_{stop}$. Numerical simulations using the friction law originally proposed by Edwards et al. (J. Fluid Mech., vol. 823, 2017, pp. 278–315) and modified here, demonstrate that there are in fact two travelling waves. One that marks the trailing edge of the steady-uniform flow and another that rapidly deposits the particles, directly connecting the point of minimum dynamic friction (at thickness $h_{\ast }$) with the deposited layer. The first wave moves slightly faster than the second wave, and so there is a slowly expanding region between them in which the flow thins and the particles slow down. An exact inviscid solution for the second travelling wave is derived and it is shown that for a steady-uniform flow of thickness $h_{\ast }$ it produces a deposit close to $h_{stop}$ for all inclination angles. Numerical simulations show that the two-wave structure deposits layers that are approximately equal to $h_{stop}$ for all initial thicknesses. This insensitivity to the initial conditions implies that $h_{stop}$ is a universal quantity, at least for carborundum particles on a bed of larger glass beads. Numerical simulations are therefore able to capture the complete experimental staircase procedure, which is commonly used to determine the $h_{stop}$ and $h_{start}$ curves by progressively increasing the inclination of the chute. In general, however, the deposit thickness may depend on the depth of the flowing layer that generated it, so the most robust way to determine $h_{stop}$ is to measure the deposit thickness from a flow that was moving at the minimum steady-uniform velocity. Finally, some of the pathologies in earlier non-monotonic friction laws are discussed and it is explicitly shown that with these models either steadily travelling deposition waves do not form or they do not leave the correct deposit depth $h_{stop}$.