Introduction: Permafrost and seasonally frozen soil are widely distributed on the Qinghai-Tibetan Plateau, and the freezing-thawing cycle can lead to frequent phase changes in soil water, which can have important impacts on ecosystems.Methods: To understand the process of soil freezing-thawing and to lay the foundation for grassland ecosystems to cope with complex climate change, this study analyzed and investigated the hydrothermal data of Xainza Station on the Northern Tibet from November 2019 to October 2021.Results and Discussion: The results showed that the fluctuation of soil temperature showed a cyclical variation similar to a sine (cosine) curve; the deep soil temperature change was not as drastic as that of the shallow soil, and the shallow soil had the largest monthly mean temperature in September and the smallest monthly mean temperature in January. The soil water content curve was U-shaped; with increased soil depth, the maximum and minimum values of soil water content had a certain lag compared to that of the shallow soil. The daily freezing-thawing of the soil lasted 179 and 198 days and the freezing-thawing process can be roughly divided into the initial freezing period (November), the stable freezing period (December-early February), the early ablation period (mid-February to March), and the later ablation period (March-end of April), except for the latter period when the average temperature of the soil increased with the increase in depth. The trend of water content change with depth at all stages of freezing-thawing was consistent, and negative soil temperature was one of the key factors affecting soil moisture. This study is important for further understanding of hydrothermal coupling and the mechanism of the soil freezing-thawing process.

Forest fires have significantly impacted the permafrost environment, and many research programs looking at this have been undertaken at higher latitudes. However, their impacts have not yet been systematically studied and evaluated in the northern part of northeast China at mid-latitudes. This study simultaneously measured ecological and geocryological changes at various sites in the boreal forest at different stages after forest fires (chronosequence approach) in the northern Da Xing'anling (Hinggan) Mountains, Northeast China. We obtained results through field investigations, monitoring and observations, remote sensing interpretations, and laboratory tests. The results show that forest fires have resulted in a decreased Normalized Difference Vegetation Index (NDVI) and soil moisture contents in the active layer, increased active layer thickness (ALT) and ground temperatures, and the release of a large amount of C and N from the soils in the active layer and at shallow depths of permafrost. NDVI and species biodiversity have gradually increased in the years since forest fires. However, the vegetation has not fully recovered to the climax community structures and functions of the boreal forest ecosystems. For example, ground temperatures, ALT, and soil C and N contents have been slowly recovering in the 30years after the forest fires, but they have not yet been restored to pre-fire levels. This study provides important scientific bases for assessment of the impacts of forest fires on the boreal forest ecosystems in permafrost regions, environmental restoration and management, and changes in the carbon stock of soils at shallow (<3m) depths in the Da Xingan'ling Mountains in northeast China.

Helicoverpa armigera causes serious damage to most crops around the world. However, the impacts of snow thickness on the H. armigera overwintering pupae are little known. A field experiment was employed in 2012-2015 at Urumqi, China. At soil depths of 5, 10, and 15 cm, overwintering pupae were embedded with four treatments: no snow cover (NSC), snow cover (SC), increasing snow thickness to 1.5 times the thickness of SC (ISSC-1), and to two times the thickness of SC (ISSC-2). Results suggested that snow cover and increasing snow thickness both significantly increased soil temperatures, which helped to decrease the mortality of overwintering pupae (MOP) of H. armigera. However, the MOP did not always decrease with increases in snow thickness. The MOPs in NSC and ISSC-1 were the highest and the lowest, respectively, though ISSC-2 had much thicker snow thickness than ISSC-1. A maximum snow thickness of 60 cm might lead to the lowest MOP. The longer the snow cover duration (SCD) at a soil depth of 10 cm in March and April was, the higher the MOP was. A thicker snow cover layer led to a higher soil moisture content (SMC) and a lower diurnal soil temperature range (DSTR). The highest and the lowest MOP were at a depth of 15 and 10 cm, respectively. The SMC at the depths of 10 and 15 cm had significant effects on MOP. A lower accumulated temperature (a 0 A degrees C) led to a higher MOP. The DSTR in March of approximately 4.5 A degrees C might cause the lowest MOP. The largest influence factor for the MOPs at depths of 5 and 10 cm and the combined data were the SCDs during the whole experimental period, and for the MOPs at a depth of 15 cm was the soil temperature in November.

Hydrological processes in high altitude mountainous regions differ from those in more temperate regions, primarily due to such influences as cold temperatures, large and rapid change in surface energy balance during snowmelt, a long period at low-temperature environmental condition and the existence of permafrost. A physically based, semi-distributed water balance model to quantitatively simulate the hydrological processes and stream flow, as well as to estimate the potential consequences of projected global warming on stream Row for such high altitude mountainous regions was constructed. Distributed meteorological data from the interpolation of the point measurements by means of a digital elevation model (DEM) of the basin, such as air temperature, precipitation, snowfall ratio, wind speed, etc., have been used as model input. Several other hydrological parameters, such as soil moisture content and evapotranspiration, which are essential in simulation of river runoff in a water balance state, were estimated by the combination of Landsat TM and a DEM with the utilization of the distributed meteorological data. The model uses only a few crucial parameters for calibration, and the model structure is based upon estimating the stream flow components. Simulated results of spatially distributed soil moisture content, evapotranspiration and monthly discharge yield reasonable agreement, both spatially and temporally, to the field observations or the estimated results by the other approaches. This physically based model has the potential to project stream flow under the possible climate scenarios. Copyright (C) 2000 John Wiley & Sons, Ltd.