Simulation of Spatio-Temporal Distributions of Winter Soil Temperature Taking Account of Snow-melting and Soil Freezing-Thawing Processes

Abstract

Soil temperature is one of the most important environmental factors that govern hydrological and biogeochemical processes related to diffuse pollution. In this study, considering the snowmelting and the soil freezing-thawing processes, a set of computer codes to estimate winter soil temperature has been developed for CAMEL (Chemicals, Agricultural Management and Erosion Losses), a distributed watershed model. The model was calibrated and validated against the field measurements for three months at 4 sites across the study catchment in a rural area of Yeoju, Korea. The degree of agreement between the simulated and the observed soil temperature is good for the soil surface (R 2 0.71∼0.95, RMSE 0.89～1.49℃). As for the subsurface soils, however, the simulation results are not as good as for the soil surface (R 2 0.51～0.97, RMSE 0.51～5.08℃) which is considered resulting from vertically-homogeneous soil textures assumed in the model. The model well simulates the blanket effect of snowpack and the latent heat flux in the soil freezing-thawing processes. Although there is some discrepancy between the simulated and the observed soil temperature due to limitations of the model structure and the lack of data, the model reasonably well simulates the temporal and spatial distributions of the soil temperature and the snow water equivalent in accordance with the land uses and the topography of the study catchment.keywords : soil temperature, snow water equivalent, snow-melting, soil freezing-thawing, distributed watershed model

Assimilation of airborne gamma observations provides utility for snow estimation in forested environments

“…Jennings et al (2018) found that rain-snow Tair thresholds exhibited significant spatial variability across the Northern Hemisphere with the warmest thresholds in continental and mountain areas while with the coolest thresholds in maritime areas and lowlands. This implies that the high Tair threshold (i.e., 2.5℃) used in Noah-MP may lead to the overestimated snowfall, and subsequently the overestimated snow depth and SWE as the study area is characterized by Simplified snow layering schemes (i.e., single snow layer) with the assumption of the same snow density for the entire snow column cause rapid snowmelt (e.g., Kwon et al, 2014;Suzuki and Zupanski, 2018). Although the snowpack in Noah-MP can have up to three snow layers, it may not be enough to accurately reproduce the energy budget within the snowpack in the study area.…”