Factors Influencing Changes of the Initial Stable Water Isotopes Composition in the Seasonal Snowpack of the South of Western Siberia, Russia

Stable water isotopes in snowpack and snowfalls are widely used for understanding hydrological processes occurring in the seasonally snow-covered territories. The present study examines the main factors influencing changes of the initial stable water isotopes composition in the seasonal snow cover of the south of Western Siberia. Studies of the isotopic composition of snow precipitation and snow cover, as well as experiments with them, were carried out during two cold seasons of 2019–2021, and laser spectroscopy PICARRO L2130-i (WS-CRDS) was used for the determination of water isotope composition (δ18O and δD). The main changes in the isotopic composition of the snow cover layers in the studied region are associated with the existence of a vertical temperature gradient between the layers and with the penetration of soil moisture into the bottom layers in the absence of soil freezing. During the winter period, the sublimation from the top layer of snow is observed only at the moments of a sharp increase in the daily air temperature. At the end of winter, the contrast between day and night air temperatures determines the direction of the shift in the isotopic composition of the top layer of snow relative to the initial snow precipitation.

Variability in Soil Moisture by Natural and Artificial Snow: A Case Study in Mt. Balwang Area, Gangwon-do, South Korea

Soil moisture is an important variable for understanding hydrological processes, and the year-round monitoring of soil moisture and temperature reflect the variations induced by snow cover and its melt. Herein, we monitored the soil moisture and temperature in high (two sites) and low (two sites) elevation regions with groundwater sampling near the Mt. Balwang area in Gangwon-do, South Korea from Sep 2020 to May 2021. This study aims to investigate the temporal and spatial variations in soil moisture and temperature due to snow (natural and artificial snow) and its melt. A ski resort has been operating in this area and has been producing artificial snow during winter periods; thus, the spring snowmelt comprises both natural and artificial snow. The effect of soil freezing and thawing, wind conditions, vegetation covers, the timing and intensity of snow cover and snowmelt were differed in the monitoring sites. The high elevation sites 1 and 2 exhibit the relatively longer and consistent snow cover than the low elevation sites. Particularly, site 2 show late (May 8) snow melting even this site is in south slope of the Mt. Balwang. The relatively steady and moist soil layers at sites 1, 2, and 3 during the warm period can be considered as influential points to groundwater recharge. Moreover, the differences between the mean δ18O (−9.89‰) of the artificial snow layers and other samples were low: in the order of surface water (0.04‰) >groundwater (−0.66 and −1.01‰) >natural snow (1.34 and −3.80‰). This indicates that the imprint of artificial snow derived from surface water and with decreasing amount of natural snow around the Mt. Balwang region, the results support the assumption that the potential influence of artificial snowmelt on groundwater quality. This study helps to understand the snow dynamic and its influence on the hydrological processes in this region by combining the hydro-chemical and isotopic analysis.

Evaluating Simplifications of Subsurface Process Representations for Field-scale Permafrost Hydrology Models

Permafrost degradation within a warming climate poses a significant environmental threat through both the permafrost carbon feedback and damage to human communities and infrastructure. Understanding this threat relies on better understanding and numerical representation of thermo-hydrological permafrost processes, and the subsequent accurate prediction of permafrost dynamics. All models include simplified assumptions, implying a tradeoff between model complexity and prediction accuracy. The main purpose of this work is to investigate this tradeoff when applying the following commonly made assumptions: (1) assuming equal density of ice and liquid water in frozen soil; (2) neglecting the effect of cryosuction in unsaturated freezing soil; and (3) neglecting advective heat transport during soil freezing and thaw. This study designed a set of 62 numerical experiments using the Advanced Terrestrial Simulator (ATS v1.2) to evaluate the effects of these choices on permafrost hydrological outputs, including both integrated and pointwise quantities. Simulations were conducted under different climate conditions and soil properties from three different sites in both column- and hillslope-scale configurations. Results showed that amongst the three physical assumptions, soil cryosuction is the most crucial yet commonly ignored process. Neglecting cryosuction, on average, can cause 10 % ~ 20 % error in predicting evaporation, 50 % ~ 60 % error in discharge, 10 % ~ 30 % error in thaw depth, and 10 % ~ 30 % error in soil temperature at 1 m beneath surface. The prediction error for subsurface temperature and water saturation is more obvious at hillslope scales due to the presence of lateral flux. By comparison, using equal ice-liquid density has a minor impact on most hydrological variables, but significantly affects soil water saturation with an averaged 5 % ~ 15 % error. Neglecting advective heat transport presents the least error, 5 % or even much lower, in most variables for a general Arctic tundra system, and can decrease the simulation time at hillslope scales by 40 % ~ 80 %. By challenging these commonly made assumptions, this work provides permafrost hydrology modelers important context for better choosing the appropriate process representation for a given modeling experiment.

Diversity of Remote Sensing-Based Variable Inputs Improves the Estimation of Seasonal Maximum Freezing Depth

The maximum soil freezing depth (MSFD) is an important indicator of the thermal state of seasonally frozen ground. Its variation has important implications for the water cycle, ecological processes, climate and engineering stability. This study tested three aspects of data-driven predictions of MSFD in the Qinghai-Tibet Plateau (QTP), including comparison of three popular statistical/machine learning techniques, differences between remote sensing variables and reanalysis data as input conditions, and transportability of the model built by reanalysis data. The results show that support vector regression (SVR) performs better than random forest (RF), k-nearest neighbor (KNN) and the ensemble mean of the three models. Compared with the climate predictors, the remote sensing predictors are helpful for improving the simulation accuracy of the MSFD at both decadal and annual scales (at the annual and decadal scales, the root mean square error (RMSE) is reduced by 2.84 and 1.99 cm, respectively). The SVR model with climate predictor calibration using the in situ MSFD at the baseline period (2001–2010) can be used to simulate the MSFD over historical periods (1981–1990 and 1991–2000). This result indicates the good transferability of the well-trained machine learning model and its availability to simulate the MSFD of the past and the future when remote sensing predictors are not available.

The Promotion Mechanism of Frozen Stagnant Water on the Sliding in the Loess Landslide Zone of Heifangtai

Freeze-thaw cycles can significantly change the hydrologic and thermal state of slopes in cold regions and affect their stability. Landslides occur continuously in the slip area of seasonally frozen soil area during the freezing period. The freeze-thaw action and the difference in the characteristics of the underlying surface of the slope are important factors inducing landslides. Taking Heifangtai slope in Gansu Province as an example, the freezing-thawing characteristics of the slope surfaces under different underlying surface conditions were analyzed by field monitoring. A thermohydromechanical coupling model was established to reconstruct the frozen stagnant water process of the Heifangtai landslide zone, and the impact of freeze-thaw action on the loess landslide zone was studied. The results show that differences in the underlying surface led to different freezing-thawing characteristics between the unsaturated area and the groundwater overflow zone. During the freezing period, the soil freezing depth was greater, and the freezing duration was longer in the unsaturated area. The frozen stagnant water effect of the Heifangtai loess landslide zone is obvious. The maximum difference in the groundwater level between February and August could reach nearly 1 m. Meanwhile, the frozen stagnant water process of the Heifangtai landslide zone has a slip-promoting action on the slope. The factor of safety declined during the freezing period and increased during the thawing period. It reached a minimum of 1.42 in February.

PECULIARITIES OF ESTATE OF THE NATIONAL GEODESIC NETWORK IN THE CENTRAL REGION OF UKRAINE

A common feature of NGN in the central region of Ukraine is aging. The differences are determined by the peculiarities of fixing its points on the locallity place. The choice of a specific type of geodetic signal was determined by local physical and geographical features of the location of the point, such as: soil properties, depth of soil freezing, visibility conditions, etc. On the territory of Poltava and Kirovohrad regions there are 70 types of centers, benchmarks and brands, which are fixed points of the planimetric, altitude and gravimetric networks. At the same time, only 9 types significantly prevail of distribution: soil centers and benchmarks for areas with shallow (up to 1.5 m) seasonal soil freezing of types 1, 1op, 2, 2op, 146, 160 and 160 Late; wall benchmarks type 143 and wall beacons type 144. The peculiarity of the central region of Ukraine is the presence of points that are both points of the planimetric NGN 1, 2 and 3 classes, and altitude NGN I or II classes. Thus such points are fixed either by the ground centers, or ground benchmarks, or horizontal beacons. Because of the lack of geodetic information on a significant part of the points of the planned and altitude networks, the condition of the NGN of the central region of Ukraine cannot be considered satisfactory at present. For the requirements of monitoring, it is proposed to expand the content of maps of construction, survey and updating of geodetic points with data on the rights of ownership or use of land locations of points and their cadastral numbers. It is also necessary to update the data on those points in the central region of Ukraine, the inspection of which was realized before 2010. The indicator of admissibility of losses of points of NGN which should be defined separately for networks of 1, 2 and 3 classes is offered. If according to the results of the calculation the actual amount of points is less than the minimum allowable for the corresponding class, and the indicator of admissibility of losses of points has a minus sign, then the corresponding network does not meet the technical parameters. Loss of points in this case is not allowed, and lost points must be restored. The results of the calculation of this indicator for the central region of Ukraine indicate the need to restore 6 points of the planimetric network of the 2 class in the Kirovohrad region and the inadmissibility of further losses of points of this class.