Volcano inflation prior to an eruption: Numerical simulations based on a 1-D magma flow model in an open conduit
We numerically simulate volcanic inflation caused by magma ascent in a shallow conduit at volcanoes which repeatedly erupt, in order to understand the effect of volatile behavior on magma from geodetic data. Considering magma in which the relative velocities between melt and gas bubbles are negligible, we model magma flow in a one-dimensional open conduit with diffusive gas bubble growth. We calculate the ground displacements and tilts caused by spatio-temporal changes of magma pressure in the conduit. Our simulations show that magma without volatiles causes decelerated changes in volcanic inflation. Magma with gas bubble growth inflates the volcano with a constant, or accelerated, rate. Temporal changes of volcanic deformation are also affected by the magma pressure at the bottom of the conduit. When the pressure is small, the displacements and tilts increase in proportion to the 1.5th power of time. This time rate is similar to that predicted from a basic gas bubble growth model. When the pressure equals the lithostatic pressure, the effects of gas bubble growth relatively decrease and the displacements and tilts increase linearly with time.
Key wordsVolcano inflation 1-d conduit flow model bubble growth temporal change
Volatile behavior in magma plays an important role in eruption styles and intensities. To understand the physical processes in magma that control magma ascent and eruption styles, many studies have been conducted on the basis of laboratory experiments, numerical calculations and theoretical considerations. Theoretical and numerical models have examined bubble growth processes at micro scales, and clarified that the bubble growth rate mainly depends upon the amount of volatiles saturated in the melt and the physical properties of the melt such as the viscosity and diffusion coefficients of the volatiles in the melt (e.g., Sparks, 1978; Proussevitch et al., 1993; Proussevitch and Sahagian, 1996; Lensky et al., 2004). Laboratory experiments have clarified the volatile behavior and the physical properties of magma (e.g., Lyakhovsky et al., 1996; Okumura et al., 2008). For example, Lyakhovsky et al. (1996) performed a gas bubble growth experiment under high pressure and high temperature conditions, and measured the bubble radius and the number density of bubbles for a rhyolitic hydrated melt. Their experimental results are well explained by the theoretical bubble growth model presented by Proussevitch et al. (1993). They also showed that the bubble radius growth rate is proportional to the square root of time when the bubble growth process is subjected to the diffusion of volatiles.
Numerical simulations have investigated the macro-scale magma ascent processes in magmatic conduits to elucidate the mechanism of volcanic eruptions. For sustained Plinian type eruptions, steady-state magma flow models have revealed the importance of magma properties and conduit shape on the dynamics of magma flow and volcanic eruption styles (e.g., Wilson et al., 1980; Woods and Koyaguchi, 1994; Yoshida and Koyaguchi, 1999; De Michieli Vitturi et al., 2008). Non-sustained Vulcanian eruptions have also been studied by using time-dependent magma flow models (e.g., Barmin et al., 2002; Melnik and Sparks, 2002; Costa et al., 2007; Mason et al., 2006; Ida, 2007; Nakanishi and Koyaguchi, 2008; Anderson and Segall, 2011). Melnik and Sparks (2002) and Mason et al. (2006) showed that the substantivity of explosive eruptions is significantly affected by the volatile behavior in magma: when volatiles can diffuse fast enough in the magma, the eruption becomes a sustained Plinian eruption, while magma with a slow diffusion of volatiles turns an eruption into a short-lived Vulcanian explosion.
In addition to these laboratory and theoretical studies, analyses of geophysical data obtained at active volcanoes have been intensively conducted to capture â€˜in situ' mag-matic motion. For example, geodetic data analyses are useful for determining the locations and sizes of volcanic pressure sources by applying pressure source models (Mogi, 1958; Okada, 1985; Davis, 1986). Recent observations conducted at active craters have succeeded in detecting tiny inflation and deflation signals associated with small Vulca-nian or Strombolian explosions with high resolution. For example, at the Stromboli volcano, small inflations that accelerate with time are observed for repetitive explosions (Ripepe and Harris, 2008). At the Semeru volcano in Indonesia, accelerating inflations are also observed 200–300 s before small Vulcanian eruptions, while gas burst events follow the inflations for about 20 s with a constant rate (Nishi et al., 2007; Iguchi et al., 2008; Nishimura et al., 2012). Inflations prior to small Vulcanian eruptions are also observed at the Suwanosejima volcano, Japan (Iguchi et al., 2008). These inflations are thought to result from pressur-ization processes associated with magma ascent and/or gas flow in the shallow conduit.
It is quite important to quantitatively relate the geodetic data that capture macro-scale magma behavior with micro-scale phenomena in the magma to elucidate the magma dynamics and eruption mechanisms. Simple models, including the interaction between gas bubbles in the magma and the surrounding elastic rock, are presented by, for example, Nishimura (2004) and Shimomura et al. (2006). These results are used to understand the inflation processes, or oscillating crack motions, detected by geodetic and seismic observations (Chouet et al., 2006; Voight et al., 2006). Relationships between geodetic data and magma ascent, including macro-scale phenomena, have also been theoretically examined. Nishimura (2006) showed that magma ascent without out-gassing causes accelerated volcanic inflation that may lead to explosive eruptions. Magma ascent with out-gassing gradually inflates the volcano and causes non-explosive eruptions. His results suggest that geodetic measurements are useful in capturing micro-scale phenomena in magma that may control eruption styles.
The present study focuses on repetitive eruptions, such as Vulcanian type, to understand the relationship between micro-scale phenomena in magma and inflation processes prior to eruptions. These eruptions occur over a relatively short time interval, and the conduit system is considered to be open so that magma ascent is not significantly affected by the surrounding rocks. Nishimura (2009) recently studied volcanic inflation associated with such repetitive eruptions, and separately examined the inflations for three basic processes of magma ascent: Poiseuille flow, gas bubble growth due to diffusive gas flow, and rising gas bubble. However, the real magma ascent process in a volcanic conduit is a composite phenomenon consisting of these basic processes. Hence, it is necessary to examine magma flow that includes the expansion of gas phases in an open conduit. At a shallow depth in the conduit, there are two primary mechanisms that can expand the volume of gas phases: diffusive flow of water molecules from saturated melt to gas bubbles, and pressure differences between the gas and the surrounding melt. The present study examines magma flow mainly including the former mechanism, which may occur at volcanoes characterized by a viscous magma (e.g. andesitic magma) in which the relative velocity between the gas bubbles and the melt is taken to be negligibly small. We formulate the basic equations of two-phase magma flow to represent the magma ascent, including the Poiseuille flow and diffusive bubble growth processes, to study the temporal changes of volcanic inflation prior to eruptions. Since the melt and gas bubbles are supposed to ascend at the same speed, our model does not target the eruptions of low-viscous magma. First, we present a two-phase magma flow model in a one-dimensional open conduit using the basic equations of magma flow. Sub-sequently, we calculate temporal changes of volcanic deformation using the spatio-temporal distribution of magma pressure in the conduit that is calculated by the magma flow model. Simulating the magma ascent for different parameters of magma properties related to the bubble growth process, we discuss the relationship between the magma properties in the conduit to volcanic deformation.
2.1 Magma ascent process in repetitive eruptions
Magma motions in a conduit have often been studied by one-dimensional non-steady two-phase magma flow models (Melnik and Sparks, 2002; Mason et al., 2006; Ida, 2007). These models suppose that diffusive gas flow is the dominant process that expands the volume of the gas phase, and that the relative velocities between the gas phase and the melt is negligibly small. The present study also assumes these conditions. For instance, the gas bubbles need to be characterized with a radius of less than about 10-1 m, for a magma with a viscosity of 104–105 Pa s, because relative velocities between the gas bubbles and the melt are estimated to be less than 10–5–10–4 m/s from Stokes' law. We further neglect nucleation and the coalescence of gas bubbles, and out-gassing processes from the magma into the surrounding medium, in our model. These are important basic processes for magma dynamics at a shallow depth; however, this paper is a first attempt to formulate relationships between magma flow models and ground deformation. Hence, we do not take into account these processes in the present study.
We simulate an open conduit and changes in the conduit radius caused by magma pressure. In the shallow part of the conduit (< 1 km), magma pressure variations are predicted to be less than tens of MPa from the lithostatic pressure. Assuming a rigidity of surrounding rocks of 1–10 GPa at a depth of 1 km, we estimate the changes of the circular conduit radius to be 0.025–0.25%. Even when the conduit shape is elliptical, with an aspect ratio of 10, the radius change is 2.5%. These values are negligibly small compared with changes in the magma flow within the conduit, so that we may reasonably assume a conduit with a constant radius.
2.2 Governing equations of magma flow in an open conduit
Notations used in this study.
Bulk magma density
Ex-solved volatile density
Magma ascent velocity
Mass flux of volatile
Universal gas constant
Bulk modulus of melt
Bubble number density
Diffusivity of volatile in melt
2.3 Governing equations of gas bubble growth process in magma
2.4 Initial and boundary conditions
Pressure waves, caused by a withdrawal of magma at the top of the conduit due to an eruption, do not reach the deeper portion of the conduit when the magma viscosity is high and the bulk modulus of the magma is small (Nishimura, 2009). Hence, we suppose that the pressure at the bottom of the conduit p0 is constant. The pressure above the magma head depth in the open conduit is also set to be constant ph. The melt pressure linearly increases with depth.
2.5 Normalization of the governing equations
Scale units used in this study.
τp = 8ηf h/ρrga2
pr = ρrgh
h/τp = ρrga2 /8ηf
We solve these dimensionless equations by using the finite difference method. For the numerical calculation, the dimensionless coordinate is divided into equally spaced grid points. The number of grid points covering the whole conduit is always set to be 100. The discrete variables at each grid point are calculated as a function of time by integrating the dimensionless differential equations (22)–(24) with the fourth-order Runge-Kutta method. The magma head depth, which moves upward with time, is not always located at a grid point. The grid point just below the magma head depth is used for the calculation, and the dimension-less variables at the top grid point are determined by linearly interpolating the values at the boundary of the magma head and the values at the grid just beneath the highest grid. The magma head depth is calculated by using the magma velocity at the top grid point, which is determined from Eq. (25). When the magma head reaches the ground surface, the calculation is stopped.
2.6 Calculation of volcanic deformation
3. Simulation Results
3.1 Model parameters
Typical values and variations of magma properties and conduit sizes used in this study.
2.5×103 kg m–3
Bulk modulus of melt
8.31 J K–1 mol–1
105 Pa s
104–105 Pa s
Gas bubble number density
Initial pressure difference
3.2 General characteristics of magma ascent and volcano deformation
3.3 Effects of the model parameters
To examine the effects of the model parameters on the deformation, we simulate the magma ascent by changing one parameter and fixing the others. The temporal changes of the volcanic deformation at r′ = 1.0 are examined to omit the effect of depth change of the magma head.
We have presented a magma ascent model in an open conduit and examined the basic behavior of volcanic deformations for various model parameters. First, we examine whether or not our model can explain the geodetic and seismic data observed at active volcanoes. Interval times of eruptions and tilt amplitudes observed at the Semeru volcano, Indonesia, are about 3 to 30 minutes, and about 1–10 nanoradian at a distance of 500 m away from the active vent (figure 5 of Iguchi et al., 2008). At the Suwanose-jima volcano, Japan, uplifts start about 120 s before explosions and about 30 × 10–6 m vertical uplifts are observed at a distance of 500 m (station SWC-UD, in Iguchi et al., 2008, Fig. 4). These volcanoes erupt basaltic-andesitic magma which has a viscosity of about 104–105 Pa s. Also, an analysis of the explosion earthquakes uses a conduit radius of 10 m (Nishimura, 1998), but recent activities of Suwanose-jima are small, so we assume a conduit radius, a, of 5 m. The eruption size of the Semeru volcano is also similar to that of Suwanosejima. Tameguri et al. (2004) determined the initial phase of the explosion earthquakes at about 500 m, so we tentatively set the conduit length to be 1000 m. The pressure at the bottom, p0, is set to be 20 MPa, which is obtained from the magma static pressure at that depth. Thus, using typical model parameters of the magma properties shown in Table 3, we estimate the magma ascent time to be 13.5 minutes and the maximum amplitude of tilt to be 3 nanoradian at r = 500 m for c0 = 0.5%. Also, assuming zm0 = 400 m, and ηf = 8 × 104 Pa s, the duration time of the magma ascent and the vertical displacement are estimated to be 120 s and 30 × 10–6 m, respectively, at r = 500 m. These estimated values are reasonably matched with the observations. However, as indicated in Eqs. (27) and (28), the amplitude of deformation is proportional to the square of the conduit radius and increases with the conduit length. Also, the magma ascending time depends on the Poiseuille flow time, τp, that is mainly affected by conduit radius, magma viscosity and the length of the conduit. We may be able to assume a reasonable conduit length for the volcanic eruptions, where dense geodetic observation data are available, and determine the viscosity by analyzing the volcanic samples. Such data enable us to discuss in more detail the magma ascent process of a volcanic eruption by carrying out these kinds of observation. Also, considering the characteristics of temporal changes of volcano deformation, such as acceleration or non-acceleration, we may further discuss the magma ascent processes at active volcanoes and estimate the physical magma parameters.
Our model has simplified the magma process in the conduit by using mathematical representations for bubble growth and fluid motions that are often used in previous studies. The model mainly includes the main driving forces of magma ascent: the volume expansions of gas bubbles and the pressure gradient in the fluid. However, we did not consider, for example, out-gassing from the magma in the conduit (Ida, 2007), or fragmentations of the magma (e.g., Melnik, 2000; Koyaguchi et al., 2008), because these processes are complex and are still under investigation. Also, several studies based on geophysical observation data present a model consisting of a gas pocket at a very shallow depth just beneath a lava dome, or cap rocks, for Vulcanian eruptions (e.g., Ishihara, 1990). These processes require to be modeled to further examine various kinds of volcano inflations at active volcanoes. We have calculated the volcano deformation assuming that the displacements of the conduit wall due to magma pressure is much smaller than the conduit radius. But, when the conduit is like a thin dike, it is necessary to include the interaction of magma flow and conduit deformation. In addition, finite element methods, or boundary element methods, are useful for calculating the deformation of volcanoes with a steep topography.
The magma pressure at the bottom of the conduit strongly affects the rate of the temporal changes in volcanic deformation. When the pressure at the bottom of the conduit is small, the pressure gradient decreases, and the volume expansion due to the gas bubble growth becomes dominant in the magma ascent process. As a result, the displacements and tilt increase, are proportional to the 1.5th power of time. On the other hand, when the pressure at the bottom of the conduit is large, the displacements and tilt increase linearly proportional to the lapse time. This is probably because the magma ascent process is dominated by the mag-matic pressure gradient in the conduit.
The ratio of the characteristic time-scale parameter (τp/τv) affects the temporal changes of volcanic deformation, when the pressure gradient of the magma in the conduit is small. When τp/τv < 1, the effect of gas bubble growth processes decreases due to the viscous resistance of the melt, and displacements and tilt increase and are proportional to the lapse time.
When volatiles are not included in the magma, the magma ascent velocity decreases with time and the deformation decelerates, since the driving force, which is the pressure gradient, becomes weak with the magma ascent.
The initial conditions regarding the pressure difference between the gas bubble and the melt, and the magma head depth, change the magma ascent time and the amplitude of the volcanic deformation with little affect on the time rate of displacements and tilt.
Careful comments from an anonymous reviewer and Phil Dawson improved this manuscript. We appreciate Nobuo Geshi for editorial efforts. This study is supported by the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan (No. 21540427). R. Kawaguchi was partly supported by the International Advanced Research and the Education Organization (IAREO) and Global COE program of Tohoku University.
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