| Summary: | The infiltration of melted snow water and rainwater into snow can drastically change the form of snow layers. This process is an important factor affecting wet snow avalanches. Accordingly, numerous field surveys and cold room experiments have been conducted to investigate the distribution of water in snow. The common methods of water content measurement (calorimetric and dielectric methods) are implemented by disturbing snow samples to measure them. However, the resolutions obtained are of the order of several centimeters, which hinders the continuous measurement of the water content of a particular sample. Magnetic resonance imaging (MRI), which is typically used in the medical field, can be used to generate a high-resolution three-dimensional (3D) image of the water distribution in samples without destructing them. The luminance of images produced by MRI depends on the volumetric water content of the sample, with luminance increasing with volumetric liquid water content. Therefore, the volumetric liquid water content of the sample can be estimated from its luminance value. Considering this concept, we developed a method to measure the volumetric liquid water content of wet snow samples using MR images. To evaluate the developed method, we prepared several wet snow samples and measured their various volumetric liquid water contents using MRI (θMRI) and the calorimetric method (θcal). θMRI, and θcal showed good correlation when compared, with values in the range 0.02–0.46. Therefore, our system can accurately and non-destructively measure water content. The developed method using MRI can measure 3D volumetric liquid water contents with a high resolution (2 mm). Using the developed method, we investigated the hysteresis of the water retention curve of snow based on the measurements of a wetting process (boundary wetting curve) and a drying process (boundary drying curve) of the water retention curve for each sample. Our results indicate the existence of hysteresis in the snow water retention curves and the possibility of modeling it by adopting contexts of soil physics.
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