The Loess Plateau plays a significant role in the implementation of China's Grain for Green Project due to severe ecological damage in the region. In order to monitor and evaluate the effects of Grain for Green Project, a study was conducted in Wuqi County, which is representative of the Loess Plateau. The study utilized remote sensing (RS) and geographic information system (GIS) technologies to analyze the spatial and temporal patterns of Grain for Green Project and assess its effects. The findings indicate that the Grain for Green Project resulted in notable improvements in Wuqi County from 2000 to 2018. Firstly, there was a significant increase in vegetation coverage, accompanied by a reduction in soil erosion intensity. Secondly, approximately 64 % of cropland was converted, leading to an expansion of forest and grassland areas. Thirdly, the focus of vegetation restoration was primarily on converting cropland to grassland, indicating its suitability for the county compared to forestation. Lastly, the conversion of steep cropland (>25(degrees)) was influenced by the density of less steep cropland (<25(degrees)). This study emphasizes the importance of guiding farmers in selecting appropriate vegetation restoration strategies and finding a balance between erosion control and agricultural production within the Grain for Green Project. Furthermore, the study recognizes that the project's significant effects are not solely attributed to land use conversion but also to the self-restoration of vegetation. This shift towards a self-restoration perspective is crucial for the future high-quality development of the Grain for Green Project.

Vegetation is a natural link between the atmosphere, soil, and water, and it significantly influences hydrological processes in the context of climate change. Under global warming, vegetation greening significantly aggravates the water conflicts between vegetation water use and water resources in water bodies in arid and semiarid regions. This study established an improved eco-hydrological coupled model with related accurately remotely sensed hydrological data (precipitation and soil moisture levels taken every 3 j with multiply verification) on a large spatio-temporal scale to determine the optimal vegetation coverage (M*), which explored the trade-off relationship between the water supply, based on hydrological balance processes, and the water demand, based on vegetation transpiration under the impact of climate change, in a semiarid basin. Results showed that the average annual actual vegetation coverage (M) in the Hailar River Basin from 1982 to 2012 was 0.62, and that the average optimal vegetation coverage (M*) was 0.56. In 67.23% of the region, M* was lower than M, which aggravated the water stress problem in the Hailar River Basin. By identifying the sensitivity of M* to vegetation characteristics and meteorological parameters, relevant suggestions for vegetation-type planting were proposed. Additionally, we also analyzed the dynamic threshold of vegetation under different climatic conditions, and we found that M was lower than M* under only four of the twenty-eight climatic conditions considered (rainfall increase by 10%, 20%, and 30% with no change in temperature, and rainfall increase by 20% with a temperature increase of 1 degrees C), thereby meeting the system equilibrium state under the condition of sustainable development. This study revealed the dynamic relationship between vegetation and hydrological processes under the effects of climate change and provided reliable recommendations to support vegetation management and ecological restoration in river basins. The remote sensing data help us to extend the model in a semiarid basin due to its accuracy.

Coal mining in arid western regions is damaging the fragile ecology, causing problems such as surface damage, vegetation destruction, and soil erosion. These issues are obstacles to the development of green coal, as mining activities can disrupt the distribution of surface vegetation, leading to its spread outside the mining area and affecting surrounding areas. Based on Landsat data, the binary pixel model was used to calculate the vegetation coverage (FVC) in mining area from 2005 to 2021. Through vegetation coverage classification and regression trend analysis, the temporal and spatial changes and evolution trends of vegetation disturbance caused by coal mining and climate were analyzed. Correlation analysis revealed the range of ecological disturbance caused by coal mining at the coal mine scale and mining area scale. The results show that the vegetation coverage of the mining area showed a decreasing trend from 2005 to 2021. Winter and spring precipitation was the primary factor affecting vegetation growth in the area, while coal mining had indirect and secondary effects on vegetation. Human activities played a significant role in improving vegetation, and between 2015 and 2018, the area of vegetation improvement increased by 133.41% compared to that of 2009-2014. Compared to the reference area, the impact range of vegetation disturbance in the mining area is 2.5-5 km, while the impact range of vegetation disturbance in the coal mine is less than 500 m. Therefore, this study provides a theoretical basis for studying the impact of mining activities on vegetation and boundary identification.

Vegetation affects the water balance in the root zone, leading to changes in pore water pressure in the soil. Despite the tendency of numerical models to overlook the vegetation impact on the soil surface, this study concentrates on creating a unique boundary condition to model the intricate interactions among soil, vegetation, and the atmosphere by considering hydraulic hysteresis. Hence, a boundary condition is integrated into Code_Bright, a finite element program designed for conducting thermo-hydraulic-mechanical simulations, enabling the computation of energy and water balance equations. The canopy resistance formulation is refined through links with solar radiation, vapor pressure deficit, and saturation degree. The model also incorporates a bounding surface approach to capture the hysteretic patterns in soil-water retention curves. The model performance is assessed by monitoring data of a full-scale slope under atmospheric forces for nearly three years. The outcomes demonstrate that the model can reasonably predict the vegetation cover impact on the thermal behavior of slopes. The slope response to rainfall infiltration and its interaction with the atmosphere demonstrated that vegetation plays a significant role in thermo-hydraulic variables. Daily temperature fluctuations are notably intense at shallow depths, particularly within the root zone, while diminishing at greater depths. Due to the incidence angles of solar radiation, the model accurately predicts higher temperatures on south-facing slopes compared to north-facing slopes. In high temperatures and low rainfall durations, the influence of the vegetation layer to develop dryer soil conditions is also more substantial than the slope orientation.

Problems Statement and Purpose. The article investigates the degradation of ecosystems in the Kharkiv region due to military actions, specifically in Kupiansk and Izyum districts. The destruction of plant cover and natural landscapes, exacerbated by fires and other war-related damages, poses long-term ecological challenges. The purpose of the study is to assess these impacts through satellite monitoring using the Normalized Difference Vegetation Index (NDVI) to identify the most affected areas and plan for their ecological restoration. Materials and Methods of Research. The research utilizes satellite images from the Copernicus Sentinel-2 platform to analyze changes in NDVI values between 2021 and 2024. This methodology allows for the detection of vegetation degradation in the studied areas and employs Geographic Information Systems (GIS) to map and visualize the extent of environmental damage. NDVI indices are analyzed for variations over time, providing insights into the effects of military actions on the region's vegetation. Results. The results of the study indicate a dramatic reduction in NDVI values in the Kupiansk and Izyum districts, particularly in 2022, which coincided with the height of military activities in the region. NDVI values in 2022 showed a 48% decrease compared to 2021, reflecting the extensive loss of vegetation due to forest fires, bombings, and the movement of heavy military equipment, which caused both direct destruction and secondary effects such as soil compaction and erosion. In 2024, some recovery in NDVI values was observed, but these remained significantly lower than pre-war levels, indicating that full ecological recovery has not yet been achieved. The study further identified key ecological hotspots where vegetation loss was most severe, particularly in areas close to conflict zones, such as military bases and frontlines. The analysis showed that forested areas suffered the greatest damage, with significant portions of these ecosystems either destroyed or severely degraded. The GIS-based analysis also revealed a correlation between the intensity of military actions and the degree of vegetation loss, with the most severely affected areas being those that experienced sustained bombardment and heavy combat. The data suggest that the recovery of these areas will require substantial effort, including reforestation, soil remediation, and the implementation of erosion control measures to prevent further degradation. Conclusions. 1). The war has led to significant environmental damage in the Kharkiv region, with substantial loss of vegetation cover and ecosystem services. 2). The NDVI analysis highlights the most affected areas, showing both the immediate and lingering effects of war on plant cover. 3). Continued monitoring and a comprehensive ecological restoration strategy are necessary to restore the region's natural landscapes, with reforestation and soil recovery being critical components. This study provides a crucial foundation for further research on the ecological impacts of warfare and offers practical recommendations for the restoration of war-torn ecosystems in Ukraine. The findings can be applied to other conflict-affected regions, emphasizing the need for a proactive approach to environmental recovery in post-war scenarios.

In boreal regions, wildfires have a major impact on vegetation and permafrost. The ecosystem-protected Xing'an permafrost is sensitive to warming climate and wildfires, particularly on the southern margin of boreal coniferous forest and patchy permafrost zone. However, it remains unclear how fire disturbances are linked with changes in ecosystem composition and soil nutrients in the permafrost zones of Northeast China. Here, 13 years after the fire in the Yile'huli mountain knots, we investigated the parameters like vegetation cover, ground temperatures, active layer thickness, and soil carbon and nitrogen storage at burned and unburned sites of shrub wetlands. The fire resulted in ground warming of 0.1-5.0 degrees C at depths of 1.0-20.0 m and active layer deepening of 0.5 m, and gravimetric soil moisture content increasing of 26%-266%. Fire also increased the number of herbs and tall shrubs. After the fire, graminoids and tall shrubs increased significantly, and the species of herbs increased by five species. However, dwarf shrubs like Ledum palustre and Vaccinium uliginosum were missing from the burned site. A massive loss of total organic carbon (TOC) (248.40 t C/hm2) and nitrogen (TN) (11.87 t N/ hm2) was observed by comparing their storage at burned and unburned sites. These results highlighted that the post-fire responses of vegetation cover and TOC and TN storage were dependent on the thermal regimes of nearsurface permafrost and active layer, recovery of vegetation and organic layer, and soil moisture content. This study can provide an important reference for carbon storage and emission in boreal shrub wetlands under a warming climate and increasing fire disturbances.

Hydrological processes in mid-latitude mountainous regions are greatly affected by changes in vegetation cover that induced by the climate change. However, studies on hydrological processes in mountainous regions are limited, be-cause of difficulties in building and maintaining basin-wide representative hydrological stations. In this study, a new method, remote sensing technology for monitoring river discharge by combining satellite remote sensing, un-manned aerial vehicles and hydrological surveying, was used for evaluating the runoff processes in the Changbai Mountains, one of the mid-latitude mountainous regions in the eastern part of Northeast China. Based on this method, the impact of vegetation cover change on hydrological processes was revealed by combining the data of hydrological processes, meteorology, and vegetation cover. The results showed a decreasing trend in the monitored river discharge from 2000 to 2021, with an average rate of -5.13 x 105 m3 yr-1. At the monitoring mainly influenced by precipitation, the precipitation-induced proportion of changes in river discharge to annual average river discharge and its change significance was only 6.5 % and 0.23, respectively, showing the precipitation change was not the cause for the decrease in river discharge. A negative impact of evapotranspiration on river discharge was found, and the decrease in river discharge was proven to be caused by the increasing evapotranspiration, which was induced by the drastically increased vegetation cover under a warming climate. Our findings suggested that increases in vege-tation cover due to climate change could reshape hydrological processes in mid-latitude mountainous regions, leading to an increase in evapotranspiration and a subsequent decrease in river discharge.

Soil hydrological properties not only directly influenced soil water content, evapotranspiration, infiltration, and runoff, but also made these factors of concern in arid and semi-arid regions. Prior research has focused on the temporal and spatial variation in soil hydrological properties and the impacts of climate change, ecosystem changes over time or human activities on soil hydrological properties. However, studies conducted on the differences in soil hydrological properties between shady and sunny slopes have seldom been conducted, especially in the permafrost region of the Qinghai-Tibetan Plateau. To investigate the variation in soil hydrological properties on shady and sunny slopes, we chose the Zuomaokongqu watershed of Fenghuo Mountain, which is located on the Qinghai-Tibetan Plateau, as the study area. Three experimental sites were selected in the study area, and the distance between experimental sites was 100m. Based on the differences in altitude and vegetation coverage, five sunny slope sample points and three shady slope sample points were selected in each experimental site. At each of these sample points, the soil water content, soil-saturated conductivity, soil water-retention curve, soil physico-chemical properties, aboveground biomass, and underground biomass were examined in the top 0-50cm of the active layer. The results showed that the soil hydrological properties of shady slopes differed significantly from those of sunny slopes. The soil water content of sunny slopes was 20.9% less than that of shady slopes. The soil-saturated water content of sunny slopes was 12.2% less than that of shady slopes. The soil water content of sunny slopes at -0.3Mpa and -0.7Mpa matric potential was 23.5% and 21.4% less than that of shady slopes, respectively. It was indicated that the soil water-retention capacity of sunny slopes was lower than that of shady slopes. However, the soil-saturated conductivity of sunny slopes was 84.5% larger than that of shady slopes and exceeded the range of soil-saturated conductivity, which was useful for plant growth. Meanwhile, the vegetation coverage on sunny slopes was lower than that on shady slopes, but the soil sand content showed the opposite relationship. Pearson's coefficient analysis results showed that vegetation coverage and soil desertification, which are affected by permafrost degradation, were the main factors influencing soil hydrological properties on shady and sunny slopes. These results will help determine appropriate hydraulic parameters for hydrological models in mountain areas.

Labile soil organic matter (SOM) plays a crucial role in nutrient and carbon cycling, particularly in permafrost ecosystems. Understanding its variation is therefore very important. In the present study, we evaluated the seasonal patterns of labile SOM from April 2013 to March 2014 under alpine swamp meadow (ASM), meadow (AM), steppe (AS) and desert (AD) vegetation in permafrost regions of the China's Qinghai-Tibet Plateau. The fractions (0 to 10 cm depth) included dissolved organic carbon (DOC), light-fraction carbon (LFC) and nitrogen (LFN), and microbial biomass carbon (MBC) and nitrogen (MBN). These fractions showed dramatic seasonal patterns in ASM and AM soils, but were relatively stable in AD soil. Soil DOC concentrations in the ASM, AM, and AD soils increased from April to May 2013, then increased again from July to August 2013 and from February to March 2014. The LFC and LFN concentrations in all four vegetation types were higher from June to August 2013. The highest MBC and MBN concentrations in the ASM, AM, and AS soils all occurred in the summer and the ASM soil showed a second peak in October or November 2013. Seasonal changes in climatic factors, vegetation types, and permafrost features were great causes of labile SOM variations in this study. Throughout the entire sampling period, the ASM soil generally had the highest labile SOM, followed by the AM, AS, and AD soils; thus, the ASM soil is the best system conserving soil nutrient (especially labile fractions) and microbial activity. Correlation analysis indicated that these fractions were not related to soil moisture and temperature in AS or AD soils, but soil temperature and moisture were significantly related to MBC and MBN in AM soil and DOC in ASM soil. Thus, the response of the labile SOM fractions in this high-altitude permafrost soils to climate change depended strongly on vegetation types. (C) 2015 Elsevier B.V. All rights reserved.

Understanding the interaction between the soil thermal-water regime and variations in vegetation cover is a key issue in land surface research and in predicting the responses of alpine ecosystems in permafrost regions to climate changes. Alpine meadows and swamps were selected to investigate the effects of changes in the soil moisture and temperature dynamics in the active layer. The differences in soil temperature and moisture in areas with different amounts of vegetation coverage were evaluated using active layer soil water and temperature indexes from a field investigation that was conducted from the years 2005-2009. Declines in vegetation cover in alpine meadows resulted in an increase in the soil-thawing temperature and moisture, a decrease in the soil-freezing temperature and moisture, and an advance in the onset of seasonal changes in the soil temperature. Changes in the vegetation cover had distinct effects on soil thermal and water dynamics in alpine swamps and meadows. The annual variations of active soil temperature and moisture dynamics were controlled by the synergic influences of climate and vegetation cover changes. We found that as the vegetation cover decreased, the sensitivity of the soil to climate changes increased with greater shifts in the annual soil temperature and water dynamics. An empirical Boltzmann formula for the soil water-temperature relationship was identified to understand how vegetation cover inhibited or drove permafrost changes by varying the soil water-thermal coupling cycle. The results confirmed that vegetation cover was one of the most important factors that control the soil water and thermal cycles in permafrost. The degradation of vegetation could accelerate the effects of climate change on the permafrost environment. (C) 2012 Elsevier B.V. All rights reserved.