Search Results (474)

Climate change affects all sectors of human activity. Agricultural management is influenced by changes in temperature and precipitation distribution both during the growing season and in the non-growing period. The contribution of snowmelt erosion to the total annual loss of arable soil has not yet been sufficiently emphasized. Based on the USLE principle, an equation for soil loss caused by snowmelt was derived, and the erosion potential of snow was determined for the conditions in the Czech Republic. In the foothill area of Větřkovice, an analysis of changes in selected climatic characteristics in the years 1961–2020 was elaborated. It was shown that the area is warming and the number of days with temperatures below 0 °C is decreasing. The total annual precipitation decreased by 18 mm. Furthermore, the erosion potential was compared in two referential periods for both the entire Czech Republic and the Větřkovice area, and a case study of soil loss due to snowmelt erosion was prepared. Despite a slight reduction in the erosion potential in the model area, the erosion shear from snowmelt reaches values higher than the permissible limit. Full article

Climate change has increased the risk of snow drought, which is associated with a deficit in snowfall and snowpack. The objectives of this research are to improve drought identification in a warming climate by developing a new snow-based hydroclimatic aggregate drought index (SHADI) and to assess the impacts of snowpack and snowmelt in drought analyses. To derive the SHADI, an R-mode principal component analysis is performed on precipitation, snowpack, surface runoff, and soil water storage. Then, a joint probability distribution function of drought frequencies and drought classes, conditional expectation, and k-means clustering are used to categorize droughts. The SHADI was applied to the Red River of the North Basin (RRB), a typical cold climate region, to characterize droughts in a mostly dry period from 2003 to 2007. The SHADI was compared with the hydroclimatic aggregate drought index (HADI) and U.S. drought monitor (USDM) data. Cluster analysis was also utilized as a benchmark to compare the results of the HADI and SHADI. The SHADI showed better alignment with cluster analysis results than the HADI, closely matching the identified dry/wet conditions in the RRB. The major differences between the SHADI and HADI were observed in cold seasons and in transition periods (dry to wet or wet to dry). The derived variable threshold levels for different categories of drought based on the SHADI were close to, but different from, those of the HADI. The SHADI can be used for short-term lead prediction of droughts in cold climate regions and, in particular, can provide an early warning for drought in the warming climate. Full article

The rivers of the Himalayas heavily rely on the abundance of snow, which serves as a vital source of water to South Asian countries. However, its impact on the hydrological system of the region is mainly felt during the spring season. The melting of snow and consequent base flow significantly contribute to the incoming streamflow. This article examines the evaluation of the proportionate contribution to the total streamflow of Beas River up to Pandoh Dam through the snow melt. To analyze the snow melt, the snowmelt runoff model (SRM) has been utilized via dividing the study area into seven different elevation zones within a range of 853–6582 m and computing the percentage of snow cover, ranging from 15% to 90% across the basin. To validate the accuracy of the model, several metrics, such as coefficient of determination (R²) and volume difference (VD), are utilized. The R² reveals that over the span of ten years, the daily discharge simulations exhibited efficiency levels ranging from 0.704 to 0.795, with VD falling within the range of 1.47% to 20.68%. This study has revealed that a significant amount of streamflow originates during the summer and monsoon periods, with snowmelt ranging from 10% to 45%. This research provides crucial understanding of the impact of snowmelt on streamflow, supplying essential knowledge on freshwater supply in the area. Full article

Light-absorbing particles, which are vital components of aerosols, can cause significant snow albedo darkening and accelerate melting. However, restricted by the poor quality of remote sensing-based aerosol products in High Mountain Asia (HMA), previous studies have seldom reported the long-term pattern of aerosols. In this study, we analyzed the spatial and temporal distribution characteristics of AOD in HMA and surrounding areas using Moderate Resolution Imaging Spectroradiometer and Ozone Monitoring Instrument data from 2004 to 2023. The Mann-Kendall test was applied to analyze the temporal trend and abrupt changes in AOD, while Rotated Empirical Orthogonal Function was used to identify subregions and investigate spatiotemporal variations. Moreover, random forest and XGBoost-Shap models were employed to quantify the contributions of the aerosols to changes in snow albedo and melting. The results indicate that the annual (monthly) average highest and lowest AOD occurred in 2021 (April) and 2022 (September) between 2004 and 2023, respectively. The AOD first increased and then decreased during our study period and an abrupt decline was detected in 2013. The REOF model revealed three regions in HMA (northern, southwestern, and southeastern parts) with strong variations in AOD load, which are strongly correlated with atmospheric circulation and monsoon driving. Specifically, REOF1, REOF2, and REOF3 are primarily associated with frequent dust events during springtime atmospheric circulation and anthropogenic emission transport during the monsoon season. Aerosol types were divided into four types, BC aerosol, DUST aerosol, MIX aerosol, and clean conditions, whose proportions were 16.7%, 16.1%, 6.6%, and 60.6%, respectively. The clean conditions constituted the main aerosol type in the region. The AOD notably decreased snow albedo (17.8%) and increased snowmelt (9.0%); we highlight the contribution of AOD to the intensification of snowmelt. These results could provide guidance for further studies on the relationship between snowmelt and AOD. Full article

Spring snowmelt has a significant impact on the hydrological cycle in seasonally frozen soil areas. However, scholars hold differing, and even opposing, views on the role of snowmelt during the thawing period in groundwater recharge. To explore the potential recharge effects of spring snowmelt on groundwater in seasonal frozen soil areas, this study investigated the vadose zone dynamics controlled by soil freeze–thaw processes and snowmelt infiltration in the Northeast of China for 194 days from 31 October 2020 to 12 May 2021. Responses of groundwater level and soil moisture to snowmelt infiltration show that most snowmelt was infiltrated under the site despite the ground being frozen. During the unstable thawing period, surface snow had already melted, and preferential flow in frozen soil enabled the recharge groundwater by snowmelt (rainfall), resulting in a significant rise in groundwater levels within a short time. The calculated and simulated snowmelt (rainfall) infiltration coefficient revealed that during the spring snowmelt period, the recharge capacity of snowmelt or rainfall to groundwater at the site is 3.2 times during the stable thawing period and 4.5 times during the non-freezing period. Full article

The Muji spring travertines, located in the Muji Basin in the eastern Pamirs Plateau, represent a typical spring deposit found on plateaus that is characterized by arid and semi-arid climatic conditions. However, its formation mechanisms remain poorly understood. This study aims to explore the recharge processes of the spring, the sedimentary environment, and the genetics of Muji spring travertines through a comparative analysis of conventional hydrochemistry, H-O stable isotope analysis of both spring and river water, and petrographic observation, as well as in situ analysis of major and trace elements present in calcite within travertines. The basin is surrounded by mountains with a topography that facilitates groundwater convergence within it. Carbonate-bearing strata are extensively developed around the basin, which serves as a crucial material foundation for travertine development. It infiltrates underground through fractures and faults, interacting with carbonate rocks to produce significant amounts of HCO₃⁻, Ca²⁺, and Mg²⁺. The observed range of isotopic compositions (δ²H, −102.27‰ to −96.43‰; δ¹⁸O, −14.90‰ to −14.36‰) in water samples suggests that their primary origin was from glacial and snowmelt sources. The concentration of HCO₃⁻ in spring water samples exhibits significant variability, with the highest value being 1646 mg·L⁻¹, which deviates significantly from the typical composition of karst groundwater. During its migration, groundwater undergoes the dissolution of gaseous CO₂ derived from deep metamorphic processes, leading to variable degrees of mixing with geothermal groundwater containing elevated concentrations of dissolved components that enhance the dissolution potential of carbonate rocks. Eventually, upwelling occurs along the Southwestern Boundary Fault of Muji, resulting in the formation of linear springs characterized by CO₂ escape. The Muji laminated travertines exhibit distinct white and dark laminae, and radial coated grains consisting of micritic and sparry layers. Chemical composition analyses reveal significant differences in the trace and rare-earth element composition, as well as the Mg/Ca ratio, of the two types of travertines. Specifically, the micritic laminae of the pisoid (Mg/Ca = 0.019; Sr = 530 × 10⁻⁶; Ba = 64.6 × 10⁻⁶) and the dark laminae of the laminated travertine (Mg/Ca = 0.014; Sr = 523 × 10⁻⁶; Ba = 48.1 × 10⁻⁶) exhibit generally higher Mg/Ca ratios and Sr, Ba contents than the neighboring sparry laminae (Mg/Ca = 0.012; Sr = 517 × 10⁻⁶; Ba = 36.6 × 10⁻⁶) and white laminae (Mg/Ca = 0.006; Sr = 450 × 10⁻⁶; Ba = 35.6 × 10⁻⁶). The development of laminated travertines and radial coated grains here is attributed to periodic changes in groundwater recharge induced by seasonal temperature fluctuations, as evidenced by the structural characteristics of the two types of travertines and the trace element analysis of different layers. Algae play a role in forming the dark laminae of laminated travertines and the micritic laminae of pisoids. Full article

Predicting streamflow is essential for managing water resources, especially in basins and watersheds where snowmelt plays a major role in river discharge. This study evaluates the advanced deep learning models for accurate monthly and peak streamflow forecasting in the Gilgit River Basin. The models utilized were LSTM, BiLSTM, GRU, CNN, and their hybrid combinations (CNN-LSTM, CNN-BiLSTM, CNN-GRU, and CNN-BiGRU). Our research measured the model’s accuracy through root mean square error (RMSE), mean absolute error (MAE), Nash–Sutcliffe efficiency (NSE), and the coefficient of determination (R²). The findings indicated that the hybrid models, especially CNN-BiGRU and CNN-BiLSTM, achieved much better performance than traditional models like LSTM and GRU. For instance, CNN-BiGRU achieved the lowest RMSE (71.6 in training and 95.7 in testing) and the highest R² (0.962 in training and 0.929 in testing). A novel aspect of this research was the integration of MODIS-derived snow-covered area (SCA) data, which enhanced model accuracy substantially. When SCA data were included, the CNN-BiLSTM model’s RMSE improved from 83.6 to 71.6 during training and from 108.6 to 95.7 during testing. In peak streamflow prediction, CNN-BiGRU outperformed other models with the lowest absolute error (108.4), followed by CNN-BiLSTM (144.1). This study’s results reinforce the notion that combining CNN’s spatial feature extraction capabilities with the temporal dependencies captured by LSTM or GRU significantly enhances model accuracy. The demonstrated improvements in prediction accuracy, especially for extreme events, highlight the potential for these models to support more informed decision-making in flood risk management and water allocation. Full article

The snow melting and runoff process in the black soil area of Northeast China has led to soil quality degradation in farmland, posing a threat to sustainable agricultural development. To investigate the regulatory effect of tillage layer construction on the infiltration characteristics of snowmelt water, a typical black soil in Northeast China was selected as the research object. Based on field experiments, four protective tillage treatments (CK: control treatment; SB: sub-soiling treatment; BC: biochar regulation treatment; SB + BC: sub-soiling tillage and biochar composite treatment) were set up, and the evolution of soil physical structure, soil thawing rate, snow melting infiltration characteristics, and the feedback effect of frozen layer evolution on snowmelt infiltration were analyzed. The research results indicate that sub-soiling and the application of biochar effectively regulate soil aggregate particle size and increase soil total porosity. Among them, at the 0–10 cm soil layer, the soil mean weight diameter (MWD) values under SB, BC, and SB + BC treatment conditions increased by 6.25%, 16.67%, and 19.35%, respectively, compared to the CK treatment. Sub-soiling increases the frequency of energy exchange between the soil and the environment, while biochar enhances soil heat storage performance and accelerates the melting rate of frozen soil layers. Therefore, under the SB + BC treatment conditions, the maximum soil freezing rate increased by 21.92%, 5.67%, and 25.12% compared to the CK, SB, and BC treatments, respectively. In addition, sub-soiling and biochar treatment effectively improved the penetration performance of snowmelt water into frozen soil layers, significantly enhancing the soil’s ability to store snowmelt water. Overall, it can be concluded that biochar regulation has a good improvement effect on the infiltration capacity of surface soil snowmelt water. Sub-soiling can enhance the overall snowmelt water holding capacity, and the synergistic effect of biochar and deep tillage is the best. These research results have important guiding significance for the rational construction of a protective tillage system model and the improvement of the utilization efficiency of snowmelt water resources in black soil areas. Full article

In the context of rising temperatures and increasing humidity in Northwest China, substantial gaps remain in understanding the mechanisms of land–atmosphere cloud–precipitation coupling across the northeastern Tibetan Plateau (TP), Loess Plateau (LP), and Huangshui Valley (HV). This study addresses these gaps by investigating cloud properties and precipitation patterns utilizing the Fengyun-4 Satellite Quantitative Precipitation Estimation Product (FY4A-QPE) and ERA5 datasets. We specifically focus on Lanzhou, a pivotal city within the LP, and Xining, which epitomizes the HV. Our findings reveal that diurnal variations in precipitation are significantly less pronounced in the eastern regions compared to northeastern TP. This discrepancy is attributed to marked diurnal fluctuations in convective available potential energy (CAPE) and wind shear between 200 and 500 hPa. While both cities share similar wind shear patterns and moisture transport directions, Xining benefits from enhanced snowmelt and effective water retention in surrounding mountains, resulting in higher precipitation levels. Conversely, Lanzhou suffers from moisture deficits, with dry, hot winds exacerbating the situation. Notably, precipitation in Xining is strongly correlated with CAPE, influenced by diurnal variability, and intensified by valley and lake–land breezes, which drive afternoon convection. In contrast, Lanzhou’s precipitation exhibits a weak relationship with CAPE, as even elevated values fail to generate significant cloud formation due to insufficient moisture. The ongoing trends of warming and humidification may lead to improved precipitation patterns, especially in the HV, with potential ecological benefits. However, concentrated rainfall during summer afternoons and midnights raises concerns regarding extreme weather events, highlighting the susceptibility of the HV to geological hazards. This research underscores the need to further explore the uncertainties inherent in precipitation dynamics in these regions. Full article

Seasonal variations of drainage waters and ochreous products of their discharge from the closed abandoned old gallery at the Grantcharitsa scheelite deposit (Bulgaria) were studied by field and laboratory methods for the period 2019–2023. The drainage is generated under anoxic conditions and is inherently diluted (EC = 100–202 µS/cm) with S (6–12 mg/L), Si (6–22 mg/L), Na (6–10 mg/L), Fe (0.2–3.3 mg/L), and W (0.19–3.5 µg/L), at a pH 4.4–6.5 and temperature 7–11.5 °C, with dissolved oxygen DO (2.1–7.7 mg/L). The concentrations of Fe and W and the pH of the water are variable and reach their maximum values during the dry (autumn) season. It was found that such parameters as pH, Eh, DO, Fe and W content change dramatically at a distance of up to 3 m from the water outlet; the values of pH, DO and Eh are sharply increased with a simultaneous nearly 5–6-times reduction in iron and tungsten content. The decrease in the contents of these elements is associated with the precipitation of ochreous material consisting of nanoscale ferrihydrite with an intermediate structural ordering between 2-line and 6-line ferrihydrite (major phase), hematite, goethite, quartz, montmorillonite and magnetite. The formation of ferrihydrite occurs as a result of abiotic and biotic processes with the participation of iron-oxidizing bacteria. Besides Fe₂O₃ (55.5–64.0 wt.%), the ochreous sediment contains SiO₂ (12.0–16.4 wt.%), SO₃ (1.3–2.4 wt.%), Al₂O₃ (3.1–6.8 wt.%) and WO₃ (0.07–0.11 wt.%). It has been shown that drainage waters and ochreous sediments do not inherently have a negative impact on the environment. The environmental problem arises with intense snowmelt and heavy rainfall, as a result of which the accumulated sediments are washed away and carried in the form of suspensions into the water systems. It is suggested that by providing atmospheric oxygen access to the closed gallery (via local boreholes), it is possible to stop the generation of iron-enriched drainage. Full article

The conventional measuring methods (runoff plots and soil morphological comparison) and models (WaTEM/SEDEM and regional model of Russian State Hydrological Institute (SHI)) were tested with regard to the Southern Cis-Ural region of Russia, along with data from rainfall simulation for assessing soil erosion. Compared with conventional methods, which require long-running field observations, using erosion models and rainfall simulation is less time-consuming and is found to be fairly accurate for assessing long-term average rates of soil erosion and deposition. In this context, ¹³⁷Cs can also be used as a marker of soil redistribution on the slope. The data of soil loss and sedimentation rates obtained by using conventional measuring methods were in agreement with the data based on the used contemporary modeling approaches. According to the erosion model calculations and data on the fallout of radionuclides in the Southern Cis-Ural (54°50–25′ N and 55°44–50′ E), the average long-term annual soil losses were ~1.3 t·ha⁻¹ yr⁻¹ in moderate (5°) arable slopes and ~0.2 t·ha⁻¹ yr⁻¹ in meadows. In forests, surface erosion is negligible, or its rates are similar to the rate of soil formation of clay–illuvial chernozems. The rates of soil erosion and sediment deposition on the arable land obtained using different methods were found to be very close. All the methods, including the WaTEM/SEDEM, allowed us to measure both soil erosion and intra-slope sedimentation. The regional SHI model fairly accurately assesses soil erosion in the years when erosion events occurred; however, soil erosion as a result of snowmelt did not occur every year, which should be taken into account when modeling. The concentrations of ¹³⁷Cs in the topsoil layer (0–20 cm) varied from 0.9 to 9.8 Bq·kg⁻¹, and the ¹³⁷Cs inventories were 1.6–5.1 kBq·m⁻², with the highest values found under the forest. The air dose rate in the forest was higher than in open areas and above the average of 0.12 μSv·h⁻¹ on the slope (0.1 μSv·h⁻¹ in the meadow and 0.08 μSv·h⁻¹ on the arable land), with the value increasing from the watershed to the lower part of the slope in all the areas. The γ-background level in the studied ecosystems did not exceed the maximum permissible levels. Full article

The future of the ecologically fragile areas on the Qinghai-Tibet Plateau (QTP) is a matter of concern. With the implementation of the Western Development Strategy, the Lanzhou-Xining Urban Agglomeration (LXUA) has encountered conflicts and compromises between urban expansion, ecological protection, and farmland protection policies in the rapid development of the past 2 decades. These deeply affect the land use layout, making the ecological sustainable development of the ecologically fragile areas of the QTP a complex and urgent issue. Exploring the impact of different policy-led land use patterns on regional ecosystem services is of great significance for the sustainable development of ecologically fragile areas and the formulation of relevant policies. Following the logical main line of “history-present-future”, the Patch-level Land Use Simulation (PLUS) model, which explores potential factors of historical land use, and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model were used to construct three future scenarios for the modernization stage in 2031 dominated by different land use policies in this study. These scenarios include the Business-as-Usual Scenario (BS), the Cropland Protection Scenario (CP), and the Ecological Protection Scenario (EP). The study analyzed and predicted land use changes in the LXUA from 2001 to 2031 and assessed carbon storage, habitat quality at different time points, and water yield in 2021. The results indicated that land use changes from 2001 to 2021 reflect the impacts and conflicts among the Western Development Strategy, ecological protection policies, and cropland preservation policies. In 2031, construction land continues to increase under all three scenarios, expanding northwards around Lanzhou, consistent with the actual “northward expansion” trend of Lanzhou City. Changes in other land uses are in line with the directions guided by land use policy. By 2031, carbon storage and habitat quality decline under all scenarios, with the highest values observed in the EP scenario, the lowest carbon storage in the BS scenario, and the lowest habitat quality in the CP scenario. Regarding water yield, the LXUA primarily relies on alpine snowmelt, with construction land overlapping high evapotranspiration areas. Based on the assessment of ecosystem services, urban expansion, delineation of ecological red lines, and improvement of cropland quality in the LXUA were proposed. These findings and recommendations can provide a scientific basis for policy makers and planning managers in the future. Full article

Waste slag and rubber particles are commonly used to modify concrete, offering benefits such as reduced cement consumption and lower greenhouse gas emissions during cement production. In this study, these two environmentally friendly, sustainable waste materials were proposed for the preparation of mortar intended for snow-melting pavements. A series of experiments were conducted to evaluate the performance of the material and to determine whether its compressive and flexural strengths meet the requirements of pavement specifications. The mortar’s suitability for snow-melting pavements was assessed based on its thermal conductivity, impermeability, and freeze–thaw resistance. The results indicate that slag, when used in different volume fractions, can enhance the compressive and flexural strength of the mortar. Slag also provides excellent thermal conductivity, impermeability, and resistance to freeze–thaw cycles, contributing to the overall performance of snow-melting pavements. When the slag content was 20%, the performance was optimal, with the compressive strength and flexural strength reaching 58.5 MPa and 8.1 MPa, respectively. The strength loss rate under freeze–thaw cycles was 8.03%, the thermal conductivity reached 2.2895 W/(m * K), and the impermeability pressure value reached 0.5 MPa. Conversely, the addition of rubber particles was found to decrease the material’s mechanical and thermal properties. However, when used in small amounts, rubber particles improved the mortar’s impermeability and resistance to freeze–thaw cycles. When the rubber content was 5% by volume, the impermeability pressure value reached 0.5 MPa, which was 166.7% lower than that of ordinary cement mortar. Under freeze–thaw cycles, the strength loss rate of the test block with a rubber content of 25% volume fraction was 9.83% lower than that of ordinary cement mortar. Full article

This paper explores the application of conceptual hydrological models in optimizing the operation of hydroelectric power plants (HPPs) in steppe regions, a crucial aspect of promoting low-carbon energy solutions. The study aims to identify the most suitable conceptual hydrological model for predicting reservoir inflows from multiple catchments in a steppe region, where spring runoff dominates the annual water volume and requires careful consideration of snowfall. Two well-known conceptual models, HBV and GR6J-CemaNeige, which incorporate snow-melting processes, were evaluated. The research also investigated the best approach to preprocessing historical data to enhance model accuracy. Furthermore, the study emphasizes the importance of accurately defining low-water periods to ensure reliable HPP operation through more accurate inflow forecasting. A hypothesis was proposed to explore the relationship between atmospheric circulation and the definition of low-water periods; however, the findings did not support this hypothesis. Overall, the results suggest that combining the conceptual models under consideration can lead to more accurate forecasts, underscoring the need for integrated approaches in managing HPP reservoirs and promoting sustainable energy production. Full article

This paper investigates the ability of a relatively low cost, commercially available uncrewed aerial vehicle (UAV), the DJI Mavic 3 Multispectral, to perform cryospheric research. The performance of this UAV, where applicable, is compared to a similar but higher cost system, the DJI Matrice 350, equipped with a Micasense RedEdge-MX Multispectral dual-camera system. The Mavic 3 Multispectral was tested at three field sites: the Lemon Creek Glacier, Juneau Icefield, AK; the Easton Glacier, Mt. Baker, WA; and Bagley Basin, Mt. Baker, WA. This UAV proved capable of mapping the spatial distribution of red snow algae on the surface of the Lemon Creek Glacier using both spectral indices and a random forest supervised classification method. The UAV was able to assess the timing of snowmelt and changes in suncup morphology on snow-covered areas within the Bagley Basin. Finally, the UAV was able to classify glacier surface features using a random forest algorithm with an overall accuracy of 68%. The major advantages of this UAV are its low weight, which allows it to be easily transported into the field, its low cost compared to other alternatives, and its ease of use. One limitation would be the omission of a blue multispectral band, which would have allowed it to more easily classify glacial ice and snow features. Full article