Japan Geoscience Union Meeting 2022

Presentation information

[J] Poster

S (Solid Earth Sciences ) » S-GD Geodesy

[S-GD02] Geodesy and Global Geodetic Observing System

Wed. Jun 1, 2022 11:00 AM - 1:00 PM Online Poster Zoom Room (20) (Ch.20)

convener:Yusuke Yokota(Institute of Industrial Science, The University of Tokyo), convener:Yuta Mitsui(Department of Geosciences, Shizuoka University), Koji Matsuo(Geospatial Information Authority of Japan), Chairperson:Yusuke Yokota(Institute of Industrial Science, The University of Tokyo), Koji Matsuo(Geospatial Information Authority of Japan), Yuta Mitsui(Department of Geosciences, Shizuoka University)

11:00 AM - 1:00 PM

[SGD02-P02] Determination of soil parameters utilizing continuous gravity data observed at NAOJ Mizusawa

*Sota Oki1, Takahito Kazama1, Yoshiaki Tamura2 (1.Graduate School of Science, Kyoto University, 2.Mizusawa VLBI Observatory, National Astronomical Observatory of Japan)

Keywords:hydrological gravity disturbance, superconducting gravimeter, soil moisture, groundwater, soil physics, Van Genuchten model

Gravity measurement is one of the most effective methods to understand mass redistributions associated with solid-earth phenomena. Solid-earth gravity signals are typically as small as approximately 10 μGal, so gravity disturbances such as hydrological effects should be corrected from observed gravity data adequately. For example, Kazama et al. (2015) reproduced the 20-μGal hydrological gravity disturbance observed at Asama Volcano using a physical hydrology model, and derived the 5-μGal volcanic gravity signal by subtracting the calculated gravity disturbance from the observed gravity data.

In order to correct hydrological gravity disturbances accurately, physical characteristics of soil such as permeability (K) and diffusivity (D) should be set adequately in hydrological models. K and D vary with soil moisture (θ(x,y,z,t)) exponentially, and the function shapes of K(θ) and D(θ) can be expressed using five parameters (Kmax, θmax, θmin, n, α) according to Van Genuchten (1980). However, three parameters of (θmin, n, α) are difficult to measure for actual soil, whereas saturated permeability (Kmax) and effective porosity (θmax) can be easily measured. If these parameters are estimated utilizing continuous gravity data itself, hydrological gravity disturbances can be modeled without any difficult soil tests.

We were thus motivated to determine the soil parameters of Van Genuchten (1980) from continuous gravity data. We here estimated the soil parameters at Isawa Fan (Iwate Prefecture, northern Japan) as follows, because the hydrological gravity change has been observed by a superconducting gravimeter at the Mizusawa campus, National Astronomical Observatory of Japan from 2017 to 2021 (Tamura et al., 2022). We first calculated the spatiotemporal variation in soil moisture (θ(z,t)) using G-WATER [1D] (Kazama et al., 2012); the measured value of (Kmax, θmax) and arbitrary values of (θmin, n, α) were set as initial soil parameters. We then calculated the hydrological gravity change (gcal(t)) by the spatial integral of θ(z,t), and compared gcal(t) with the observed gravity change (gobs(t)). We repeated these calculations with changing the values of (θmin, n, α), and searched for an optimal set of (θmin, n, α) so as to minimize the RMS residual between gobs(t) and gcal(t).

Consequently, the optimal values were obtained to be (θmin, n, α) = (0.0 [m3/m3], 1.5, 4.0 [/m]). These values agree with typical ones for silty soil (e.g., Leij et al., 1996), and this result is also consistent with the fact that the soil at the Mizusawa campus is classified as silt or clay according to the soil test by Kazama et al. (2012). Moreover, the minimum RMS of the gravity residual was calculated to be 0.60 μGal, which is 40 % smaller than that in the previous study (1.0 μGal; Kazama et al., 2012). In these respects, we succeeded in reproducing the soil parameters and consequent hydrological gravity change for Isawa Fan accurately.

In contrast, the optimal parameter values were obtained from the continuous observation data of soil moisture to be (θmin, n, α) = (0.0 [m3/m3], 1.5, 0.5 [/m]); the α’s value for the soil moisture data is significantly different from that for the gravity data. We also found that the RMS residual for soil moisture changes drastically with the slight variation of α. This fact indicates that the α’s sensitivity to soil moisture is stronger than that to gravity change. Therefore, we will define an evaluation function which considers the residuals of both soil moisture and gravity, and search for an optimal parameter set to explain both of the soil moisture and gravity data at the same time.