To systematically investigate the short-term consequences of sudden temperature fluctuations and address the challenges of frost damage in extreme environments, this study examined tunnel entrances in the Northeast China. Laboratory freeze-thaw/freezing tests and multi-field coupling simulations were conducted to assess the response of tunnel linings and adjacent rock in cold regions. This study reveals, for the first time, the spatial and temporal migration pattern of 'low temperature at the foot of the arch-high temperature at the arch', providing a reference for the anti-freezing design of tunnels in cold regions. The main conclusions are as follows: (1) High water content and repeated freeze-thaw cycles significantly affect the soil's stress-strain curves, hardening them under increasing confining pressure while accelerating soil strength degradation. Before the freeze-thaw cycle, a 3% increase in water content reduces the modulus of elasticity by approximately 40%. After 10 freeze-thaw cycles, the modulus reduction escalates to 33%-63%, with soil specimens exhibiting the most significant degradation at the optimal water content. (2) During the freezing process, the soil's stress-strain curves exhibit softening features, with failure strength and cohesion increasing nonlinearly as temperature decreases. The internal friction angle reveals no clear pattern, and the failure mode tends toward brittleness. (3) A sudden temperature decrease results in the lowest temperature at the arch foot of the secondary lining, while the highest is at the primary support's vault. After a sudden temperature increase, the lowest temperature shifts to the primary support's arch foot, while the highest shifts to the secondary lining's vault. Temperature changes in the surrounding rock are most pronounced within 0.5 m outside the lining. (4) Sudden temperature fluctuations induce short-term irreversible vertical displacement at the ground surface, expansion of horizontal clearance after temperature decrease, and convergence after the temperature increase. The vault and invert undergo cyclical uplift and settlement due to freezing and thawing. A temperature decrease of 20 degrees C leads to the maximum freeze-heave stress. Stress distribution in the lining shows tensile stress at the sidewalls (473 kPa) and compressive stress at the arch foot (1,005 kPa). Both values are below the material's strength limits, indicating structural safety under freeze-heave stress alone.
Frost heave phenomenon poses significant geohazard, threatening the safety of the infrastructure in cold regions as a result of freezing-thawing cycles. This threat the destabilizes the environment and complicates further construction. The paper aims to evaluate the uneven displacement associated with frost heave, focusing on the thermo-mechanical interactions that govern embankment stability and the potential benefits of the New Geocell Soil (NGCS) system. Field experiments were conducted to monitor thermal penetration, and microstructural analyses were performed to assess soil composition changes in response to thermal cycles. It is significantly correlated with the displacement, suggesting that temperature characteristics can be employed in assessments. The New Geocell soil system has been introduced to mitigate thermal effects and uneven frost heave. The identified alterations highlight essential weak zones for mechanical response evaluation at the top layer, with a significant increase in frost heave within the range of -2 degrees C to -1 C. This complicates traditional evaluation models and necessitates a deeper understanding of thermo-mechanical properties. The results indicate that frost heave below 1 mm showed substantial improvement when reinforced with NGCS. The embankment is strengthened before the New Geocell system fails. The study presents a reliable strategy with soil pressure decrease in the range of 0-250 kPa. The frost front is diminished and it further indicates that New Geocell reinforcement can adapt to migration of thermal response.
Petroleum extraction and transportation in cold regions often result in leakage accidents, which can cause severe environmental pollution. The prevalent freeze-thaw cycles in these areas significantly influence the migration and dispersion of petroleum. Therefore, understanding these processes is essential for effective environmental protection. The experimental results indicate that capillary action, liquid pressure, and particle adsorption primarily influence petroleum migration in the unfrozen zone. Under freeze-thaw cycles, proper temperature gradients facilitate petroleum migration from unfrozen to frozen zone, while extreme temperature gradients impede this migration. The migration processes of water and petroleum are interdependent and mutually restrictive. An increase in initial moisture content promotes petroleum migration. However, when the moisture content exceeds a certain threshold, a significant amount of pore water (or ice) occupies the pore space, which hinders petroleum migration. Additionally, as the number of freeze-thaw cycles increases, the capability of petroleum to migrate into the frozen zone significantly improves. These findings provide experimental methods and scientific evidence for further exploration of petroleum migration mechanisms in cold regions and the development of effective soil contamination remediation strategies.
In the intricate and precise natural process of the hydrological cycle,precipitation plays a pivotal driving role as the core link in the mutual transformation between surface water and atmospheric water.From a hydrological perspective,precipitation is not only the most active input in the hydrological cycle but also the primary driving force behind watershed hydrological processes.Its spatiotemporal distribution characteristics directly influence the dynamic processes of hydrological elements such as surface runoff,infiltration,and evapotranspiration.Ac-curate precipitation data is crucial for advancing hydrological studies,supporting agricultural practices,improving flood prediction,enabling effective drought monitoring,and formulating strategies to adapt to climate change.However,the Loess Plateau region,with its complex terrain and strong spatial heterogeneity,Together with the sparse and unequal distribution of rainfall ground stations,makes large-scale and accurate studies on precipitation characteristics challenging.This study concentrated on the Loess Plateau,employing remote sensing and reanalysis datasets to derive spatially distributed precipitation data for the targeted area.A comparison was conducted among nine precipitation datasets against observed data to evaluate the feasibility of each product.Furthermore,the precipitation estimation capabilities of two mixing methodologies were analyzed.The analysis reveals that the GPM dataset delivers the most accurate outcomes,whereas both MERRA-2 and ERA5_Land consistently overestimate precipitation values.The incorporation of mixing techniques enhanced the precision of precipitation estimates;notably,the maximum R(Rmax)method produced interannual precipitation predictions with a maximum deviation of merely 10 mm from observed values,thus demonstrating its accuracy in interannual precipitation estimation within the Loess Plateau.Additionally,the Bayesian Model Averaging(BMA)method outperformed individual datasets in both spatial and temporal analyses.This method effectively estimates pre-cipitation in the Loess Plateau by transforming site-specific weight values into grid formats.According to BMA estimates,average annual rainfall from 2001 to 2018 was around 445.2 mm,with a linear annual increase of 2.79 mm throughout this timeframe.Understanding the spatial heterogeneity characteristics and dynamic vari-ation patterns of spatiotemporal precipitation is of significant theoretical and practical importance for formulating scientific soil and water conservation strategies and ecological restoration plans.In the Loess Plateau,a typical ecologically fragile region,precipitation,as a crucial hydro-meteorological element,directly influences the for-mation of surface runoff,the process of soil erosion,and the potential for vegetation recovery through its spatial and temporal distribution patterns.
In the northern Da Xing'anling Mountains of Northeast China, thermokarst lakes have undergone significant changes. These changes are particularly evident along the Highway X302, which stretches from Yakeshi in the south to Yitulihe in the north, across zones of discontinuous to patchy Xing'an permafrost (XAP). Thermokarst lakes are highly sensitive to both climate warming and human activities. However, changes in their areal extent and number over the past two decades remain unclear. To identify the drivers of thermokarst lake changes in the XAP region, this study analyzes the relationship among lake dynamics, climate change, and human activities. Rich data on lake changes were extracted using the modified normalized difference water index (MNDWI) from the Google Earth Engine (GEE) and verified against the Joint Research Centre (JRC) global surface water datasets. The results show a net increase in both the number and areal extent of thermokarst lakes along the Highway X302 from 2000 to 2020. Larger lakes (greater than 0.01 km2) expanded in surface area. Meanwhile, smaller lakes (less than 0.01 km2) increased in number. A bell-shaped trend was observed, with an initial increase in lake area followed by a decline around 2013. Before 2013, climate factors such as precipitation, air temperature, and potential evapotranspiration (PET) strongly influenced lake changes. After 2013, annual precipitation became the dominant driver of lake expansion. Human activities also contributed to changes in permafrost thermal regimes, further influencing lake dynamics. These findings provide valuable insights into the management of thermokarst lakes and wetlands in the region, and offer a reference for mitigating frost-related hazards along the Highway X302.
Glacial lake outburst floods (GLOFs) have received substantial attention owing to their catastrophic potential. Thus, accurate susceptibility assessments are crucial for disaster prevention and mitigation. These assessments primarily depend on the characteristics of glacial lakes and their surrounding environments. While some studies highlight glacial lake area expansion as a key indicator, quantitative analyses remain limited. This study investigates 94 reported GLOF events in High Mountain Asia (HMA) since 1998, confirming 40 precise events through literature review, remote sensing imagery, and geomorphological analysis. By constructing year-by-year boundary data for these 40 glacial lakes and analyzing their area changes, we identified three key findings: (1) Relationship between lake size and outburst frequency: Smaller lakes are more prone to outbursts. The mean glacial lake area was 0.25 km2, with 42.5% being <0.1 km2 and only 2.5% >1 km2. (2) Complex area change patterns: Area changes before outbursts were categorized into four types: expanding, stable, shrinking, and fluctuating. Notably, 45% of lakes showed expansion trends, while 15.56% exhibited significant shrinkage. (3) Regional differences in susceptibility: In the Himalayas, pre-outburst area changes were highly variable, making area growth an unreliable indicator of GLOF susceptibility. Conversely, lakes in the Nyainqentanglha Mountains were either stable or expanding before outbursts, suggesting that continuous expansion could serve as a potential trigger and warrants close monitoring. These findings underscore the need for comprehensive, region-specific approaches to GLOF risk assessment, emphasizing the complexity of area changes and the importance of tailored monitoring strategies.
Allometric allocation of limiting nutrient elements at the organ level is a crucial strategy for plants to adapt to environmental changes.However,our understanding of intra-and inter-organ allocation patterns of nitrogen(N)and phosphorus(P)in desert grassland plants remains limited.A one-year pot experiment(June 2020 to August 2021)was conducted to investigate the N-P allometric scaling relationships within and between plant organs of dominant shrubs and herbaceous species cultivated in two soil types:desert eolian sand soil(DESS)and brown calcic soil(BCS).The results indicated that,overall,the leaves of both shrubs and herbaceous plants exhibited higher N and P contents compared to other plant organs.Notably,under BCS conditions,fine roots of Ammo-piptanthus mongolicus exhibited higher P content than leaves.For shrubs,N content in leaves changes faster than P content,while in other organs,P content increased faster than N content.The N-P allometric exponents for herbaceous leaves and roots were 0.47 and 0.56,respectively.Additionally,N and P contents in shrub leaves and fine roots were linearly positively correlated with soil total N and P contents.Generally,changes in soil type from DESS to BCS did not alter the N-P allometric scaling relationships within specific plant organs but did affect the N and P allocation in shrub fine roots.These findings enhance our understanding of N and P allocation strategies within and between major organs of desert plants.
By combining eight types of evapotranspiration datasets, the spatial and temporal variations in the evapotranspiration (ET) on the northern slope of the Kunlun Mountains were analyzed in uninhabited areas that lack observational data. The order of the average annual ET was ERA5_Land (312.32 mm/a) > CR (239.80 mm/a) > MOD16STM (211.87 mm/a) > GLADS (119.02 mm/a) > ETM (111.88 mm/a) > EB-ET (109.90 mm/a) > GLEAM (100.84 mm/a) > MERRA-2 (100.81 mm/a). The ET value from the ERA5_Land dataset was three times higher than that of the other five datasets. The ET values of the CR and MOD16STM datasets were twice that of the other five datasets. In terms of time, the correlation coefficient between the GLEAM and MERRA-2 datasets was the highest (R = 0.82). In terms of space, GLDAS and MERRA-2 had the highest multi-year average ET correlation coefficient (R = 0.80). The reduction in spatial scale resulted in clear differences in the multi-year average ET correlations among different products in the same region. In terms of time, the average annual ET of the basins on the northern slope of the Kunlun Mountains exhibited an overall increasing trend for all data sources, and the overall annual average change in the study area estimated by the eight datasets was 1.09 mm/a. The most rapid rates of increase were obtained from GLDAS (1.38 mm/a) and GLEAM (1.38 mm/a). In the CR, ERA5_Land, GLEAM, GLDAS, MERRA-2, ETM, MOD16STM, and EB-ET datasets, 46.46%, 41.47%, 87.30%, 40.30%, 49.10%, 47.13%, 57.16%, and 45.12% of the watersheds, respectively, showed a significantly increasing trend. The ET value of the Yarkand River Basin showed a significantly increasing trend for all eight data sources. The results of this study provide a scientific reference for the allocation of water resources on the northern slope of the Kunlun Mountains.
The variation in pile types can to some extent reduce frost jacking displacement of pile foundations in seasonal frost regions, yet further research is needed on the anti-jacking-up performance of different pile types under freeze-thaw cycles. This study conducted freeze-thaw cycle model tests under open-system conditions based on the proposed design concept of bamboo joint conical piles, analyzing variations in test fill temperature, moisture content, surface displacement, and pile-top displacement. The main findings are: (1) Pile type variation significantly affects pile foundation frost jacking, with bamboo joint conical piles demonstrating superior anti-jacking-up performance compared to straight piles and inferior performance to 9 degrees conical piles. Moreover, the anti-jacking-up performance of bamboo joint conical piles follows a pattern of initial enhancement followed by attenuation with increasing cone angle, where a 7 degrees cone angle provides optimal anti-jacking-up performance. (2) The moisture content of the soil fill increases with the number of freeze-thaw cycles in an open system environment, with the rate of increase decreasing over time, while the initial frozen core volume within the fill material tends to increase during the thawing phase. (3) The mechanisms underlying the frost heave and settlement of the fill surface and the frost jacking displacement at the pile top were clarified. The frost heave and settlement of the fill surface result from volume changes in the frozen soil due to the water-ice phase transition and the compaction effect on unfrozen soil. The thermal melting evolution of the frozen core in the fill material is the key factor determining the cumulative displacement at the pile top. (4) Differences in the thermophysical properties between the pile foundation and the fill material induce the migration of free water toward the vicinity of the pile, where the higher moisture content of the fill material is detrimental to the mitigation of frost jacking damage to the pile foundation. These findings provide a foundation for further elucidation of the frost jacking mechanism of bamboo joint conical piles in seasonally frozen regions under freeze-thaw cycles.
Continuous monitoring of high spatiotemporal resolution evapotranspiration (ET) is crucial for accurately assessing water resource management and irrigation efficiency at both global and regional scales. However, constraints such as satellite image transit time and cloud contamination can inhibit a single satellite to provide fine spatial resolution and continuous daily sequences of remote sensing data. In this study, we employed a coupled multi-scale fusion and interpolation method evapotranspiration model (CFIEM) framework integrated the remote sensing ET models, data fusion models, and the HANTS-GEE interpolation method to generate high-resolution surface feature parameters and hydrological variables. Landsat remote sensing parameters and MODIS-Landsat fusion data were adopted to simulate daily regional ET, and the simulated results were subsequently validated. The results revealed the strong consistency between the simulated CFIEM-ET and Landsat-ET values and measured data, with the R2 values of 0.83 and 0.73. Among the simulations across the sand dunes, grasslands, rice, and maize ecosystems, maize exhibited the most accurate simulation (R2 = 0.84), while the sand dunes demonstrated certain deviation (R2 = 0.72). The geographical detector analysis identified the net radiation (Rn) as the primary driver of multi-year ET variation, followed by the land surface temperature (LST) and leaf area index (LAI). This study sheds light on the interannual ET variation and its driving mechanisms in arid regions, laying a theoretical foundation and offering technical support for regional water resource management and desertification control.
In cold region, freeze-thaw cycles induced by extreme temperature fluctuations represent a significant threat to the stability of tunnel surrounding rocks. Investigating this phenomenon is essential for ensuring tunnel safety. This study employs prefabricated fractured basalt and subjects it to multiple freeze-thaw cycles. The microstructural changes in rock pores were analyzed using nuclear magnetic resonance (NMR) technology, while mechanical property alterations were determined through triaxial compression tests. A freeze-thaw damage model is developed to simulate and verify the findings. The results indicate that freeze-thaw cycles considerably decrease the triaxial compressive strength and elastic modulus of basalt, augmenting the number of cracks during the compression failure process. NMR technology demonstrates that freeze-thaw cycles facilitate the expansion and interconnection of pores, thereby enhancing rock porosity. Furthermore, the freeze-thaw damage model illustrates a significant nonlinear progression of basalt damage under various confining pressures and freeze-thaw cycles. The alignment of the research findings with experimental data confirms the accuracy and efficacy of the model.
The Qaidam Basin, situated on the Qinghai-Tibetan Plateau, ranks among the highest deserts in the world. Dust derived from this basin are carried to neighboring regions by atmospheric circulation, resulting in accelerated glacier melting, earlier onset and prolonged duration monsoon, and modification of atmospheric temperature structure, thereby influencing climate patterns. Therefore, it is crucial to understand the characteristics of dust emissions in the Qaidam Basin. However, previous studies have often relied on satellite remote sensing data or models that lack validations. Hence, we use a dust emission model validated with extensive measured data from the Qinghai-Tibetan Plateau to simulate the spatiotemporal distribution of dust emissions in the Qaidam Basin from 1982 to 2020. And, the Classification and Regression Trees (CART) machine learning method is used for multi-factor comprehensive analysis to identify the dominant factors affecting dust emissions and to determine the configuration of factors that have the most significant impact. We found that the dust emissions in the Qaidam Basin showed a slightly increasing trend over the past 40 years. The internal variability of dust emissions and external factors such as meteorological conditions and surface characteristics contributed to a notable increase in dust emissions during the early 2000s. Meanwhile, the annual cyclic variation in meteorological conditions is the reason for the higher dust emissions in spring and early summer and lower ones in the other seasons in this region. The spatial distribution of dust emissions exhibits significant variation with altitude, and in the piedmont alluvial fans that locate the transition zones between the mountains and the basins the dust emission rates generally higher than the other places. The surface soil moisture (SM) and the wind speed at 10-m height (WS) are the dominant factors influencing dust emission, and their mechanisms of affecting dust emission are different. SM plays a crucial role in the initial stage of dust lifting, while WS has a continuous and more significant influence throughout the entire dust emission process. Among the combinations of multiple influencing factors, the one where SM is less than or equal to 0.113 mm3/mm3, WS is greater than 5.159 m/s, and air temperature (AT) is greater than-12.488 degrees C is the most conducive to dust emission. We provide new insights into dust emission in the Qaidam region, offering directions for future research to focus on the different mechanisms of various influencing factors in the dust emission process, as well as on the changes in dust emissions under different configurations of multiple factors.
Permafrost degradation on the Qinghai-Tibet Plateau has led to the rapid development of thermokarst lakes,but their distribution along the Qinghai-Tibet Railway(QTR)has not been fully studied.In this study,we established the Landsat,Sentinel-2A and GF-1 image datasets and a 50 km wide transect along the QTR,and used ENVI software to extract lake data.The distribution characteristics of thermokarst lakes at different distances from the QTR in 2022 were analyzed.The spatiotemporal evolution of thermokarst lakes and their relationship with cli-matic factors from 1991 to 2022 were examined.The results showed that,from 1991 to 2022,the number and area of thermokarst lakes in the study area increased by about 3,892 and 70.08 km2,respectively.It was found that climate warming and intensified precipitation are the main reasons for the increase in the number and area of thermokarst lakes in the study area.This study provides basic support for an in-depth understanding of the long-term interannual changes of the thermokarst lakes along the QTR and the maintenance of the QTR.
As a result of no direct measurement data, accurate stream flow prediction in ungauged basins has remained a challenge in water resource management and flood forecasting. To meet this challenge, advanced hydrological models can be integrated with remote sensing and machine learning techniques. Hydrological models are used to understand the dynamics of streamflow patterns while remotely sensed information provides real-time information on land surface conditions as well as weather parameters thus enhancing the accuracy of these models. Using classical approaches, machine learning methods enable the analysis of complex datasets to detect interrelations or patterns that may not be obvious. Therefore, an integrated approach is crucial for improving flow predictions in ungauged basins that ultimately support effective water management and flood mitigation strategies.This can become even more complicated with climate change as shown by Morocco's high sensitivity to irregular rainfall patterns brought about by climate variations. One such place is the Ouzoud watershed, which stretches 315.6 km2 across Central High Atlas Mountains and is characterized by frequent flooding leading to socio-economic impacts. This study aims at assessing streamflow prediction methods particularly the Quantile-Quantile Plot (QPPQ) method endorsed by USGS for its applicability in predicting streamflow at ungauged locations.The study area includes both gauged and ungauged watersheds such as the Bernat River, Lakhdar River, Ghassaf River, and Tassaouet River, with Ouzoud River being the only ungauged basin. The geological setting is characterized by carbonate rocks (limestone) throughout the catchment. Mediterranean climate mountainous conditions prevail in this region that experience significant rainfall variations. Other watersheds within the survey site are those of Tassaout and Bernat which have different geological and climatic influences on streamflow patterns.The QPPQ method entails estimating the Flow Duration Curve (FDC) for the catchment of interest, identifying matching donor sites in terms of hydrological characteristics, transferring non-excessive probabilities from these donor sites and mapping these probabilities to streamflow estimates. The performance of the QPPQ method is assessed based on several statistical criteria including Correlation Coefficient (CC), Coefficient of Determination (R2), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Nash-Sutcliffe Efficiency (NSE), and Kling-Gupta Efficiency (KGE). For instance, the CC value of 0.55 at Bernat River Sgatt station means that there exists a moderate linear relationship between predicted and observed streamflows while R2 value at 0.36 indicates that about 36 % of the explained variation in observed flow is covered by predicted ones. Meanwhile, MAE=22.50 mirrors an average absolute prediction error while RMSE equals 55.01 in this case refers to the square root of mean squared prediction errors. Furthermore, NSE gives information concerning how far off the model's results are from the actual data with NSE=0.36 denoting a moderate fit and KGE which equals 0.34 showing good agreement in overall terms.Together, these measures expose the strengths and weaknesses of QPPQ as a streamflow prediction technique. Although the method gives some useful indications, it should be improved further by integrating it with more data sources and processes to increase the accuracy of its predictions and make them more reliable for ungauged basins.
Sand rice (Agriophyllum squarrosum), a pioneering annual plant thriving in deserts and sandy regions throughout the Asian interior, is believed to be a potential food and forage crop due to its significant nutritional and medicinal values. Previous metabolomics analyses have revealed that sand rice contains abundant flavonoid components, which are known for their wide applications in cosmetics, food, and pharmaceuticals. To optimize the use of flavonoids in sand rice, in this study, the response surface methodology (RSM) was selected to determine the optimal ultrasonic-assisted extraction (UAE) criteria for flavonoids extraction from the aerial part of sand rice firstly. Statistical analyses unveiled the optimum parameters for flavonoids extraction from sand rice could be 62% of ethanol concentration, 1:43 solid-toliquid ratio, 160 W for ultrasound power, and 52 degrees C for extraction temperature with extraction time of 12 min. Under this condition, the experiment optimum total flavonoid yield could reach at 15.24 mg/g, which was correspond to the maximum predicted value of RSM with 15.22 mg/g. Subsequently, the antifungal efficacy of these extracts was evaluated against three common plant pathogenic fungi, showing a significant inhibitory effect with the highest rate of inhibition reaching 25.3% at a concentration of 4 mg/mL, underscoring its potential as a natural antimicrobial agent. This study will not only provide a powerful method to extract flavonoids from a desert resource plant, but also pave the way for industrial development and application of the promising desert plants with high nutritional and medicinal values.
The Northern Da Xing'anling Mountains are an important ecological barrier in China and are highly sensitive to global climate change. Gaining an in-depth understanding of the climate change characteristics in this high-latitude, cold region is crucial for protecting ecological security and responding to global climate change. This paper uses precipitation and average temperature data from 1980 to 2019, and applies methods such as wavelet analysis, cross-wavelet transform, wavelet coherence, and singular value decomposition (SVD) with heterogeneous correlation to study the climate change in the Northern Da Xing'anling Mountains over the past 40 years and its response to the El Ni (n) over tildeo phenomenon. The results show that: (1) The temperature in the Northern Da Xing'anling Mountains has shown a significant increasing trend, with a temperature trend rate of 0.30 degrees C/10a (p<0.01). Spatially, the annual average temperature and temperature change rate exhibit latitudinal zonality, with the highest temperature occurring near the Zhalantun station in the southeastern part of the Northern Da Xing'anling Mountains, and the greatest temperature change rate observed near Xiao'ergou. The annual precipitation in the Northern Da Xing'anling Mountains ranges from 250 to 650 mm, with no obvious trend in precipitation variation. Overall, there is a decreasing trend, with a precipitation trend rate of -5.09 mm/10a (p>0.01). Precipitation shows a gradual decrease from east to west, and the spatial distribution of the precipitation trend rate is consistent with the trend in precipitation change. (2) Morlet wavelet analysis shows that the annual average temperature in the Northern Da Xing'anling Mountains exhibits scale variations of 21 years and 8 years at the 40-year scale, while annual precipitation shows no obvious periodic characteristics. (3) The heterogeneous correlation chart in singular value decomposition indicates that the climate in the Northern Da Xing'anling Mountains is significantly influenced by the El Ni (n) over tildeo phenomenon. Among them, the temperature in XinBaragLeft Banner, Right Banner, and Manzhouli, as well as the southwestern area of Zhalantun, shows a strong response to El Ni (n) over tildeo events, while precipitation is notably affected in areas near Mohe, Tahe, Huzhong, and Xinlin. (4) According to the cross-wavelet and wavelet coherence analysis, the sea surface temperature in the Nino3.4 region exhibits significant resonance with the temperature in the Northern Da Xing'anling Mountains at 10-17 months and 18-62 months cycles, and there is a correlation between precipitation and temperature at different time periods and cyclical scales.
Based on ERA5-Land hourly temperature reanalysis (1991-2020), this study quantifies spatiotemporal warming patterns in the Yarlung Zangbo River Basin (YZRB) through EOF analysis, extreme indices (ETCCDI), and Mann-Kendall test. The basin is partitioned into upstream (above Lazi, >4,500 m) and midstream-downstream (below Lazi, 140-4,500 m) based on EOF analysis. The results indicate the following: (1) Pronounced thermal stratification with >20 degrees C annual range in upstream (-15 degrees C winter to 5 degrees C summer) versus <15 degrees C variation in midstream-downstream where winter temperatures remain above -5 degrees C; (2) The basin-wide annual mean temperature (T-ave) increased at 0.32 degrees C/decade, slower than the minimum temperature (T-min) rise (0.36 degrees C/decade). The most pronounced warming occurred in winter, with T-ave surging at 0.76 degrees C/decade (p<0.01). (3) Asymmetric shifts in extremes are observed: in central midstream-downstream, warm nights (TN90p) escalated by 7.37 days/decade (p<0.01), whereas cold days (TX10p) decreased markedly (-7.14 days/decade, p<0.01).
Based on compressive strength analysis, ultrasonic velocity testing and microstructural damage of three groups of concrete sprayed with inorganic coatings with different mix ratios were carried out under the freeze and thaw cycles (F-T). The strength attenuations of three groups of concrete were investigated, and a linear regression model showing the relationship model between acoustic parameters of three groups of concrete and their physicomechanical properties were constructed, and the micro-mechanism behind the strength decay of concrete was explained via scanning electron microscopy. The results show that in case of the same F-T cycles concrete sprayed inorganic coating adding a polypropylene fibre leads to a good anti-freezing performance. The trend in ultrasonic velocity decay in concrete under the F-T cycles is consistent with the trend in compression strength change. The ultrasonic velocity (UV) of the concrete shows a great correlation with compression strength: the greater the compression strength of concrete, the higher the UV. The losses in compressive strength of concrete in the three kinds (A, B and C, A is with silica fume, B is plain concrete, C is with polypropylene fibres) after 300 freeze-thaw cycles are 54.55%, 62.25% and 22.26%, respectively, which of ultrasonic compressive wave velocities are 13.81%, 16.65% and 3.77%, respectively. Concrete strength decreases during the freeze-thaw process; this is microscopically manifested as large pores, an increase in cracks, and the development of scattered primary pores affecting the centralised connectivity. The cracks of A group have a width of 5-10 mu m, which of B group have a width of 5-20 mu m), which of C group have a width of 1-2 mu m. The whole process of F-T is the process of generating and enlarging cracks in the inner microstructure of the concrete, which results in a markedly reduction in the mechanical characteristics of concrete.
Agricultural trade promotes the transfer of water resources, which has an impact on regional water scarcity, particularly in arid regions. Nevertheless, the understanding of how agricultural trade influences water scarcity and the populations under different water scarcity levels is still insufficient. This study examines the impact of domestic agricultural (food crop) trade on water scarcity in Northwest China by integrating a grid-based dynamic water balance model with a linear programming model. The results indicate that the agricultural blue water (surface and groundwater) footprint and green water (soil water) footprint in the Northwest region peaked in 2014, with the green water footprint being 17% higher than the blue water footprint. The increase in trade volume has effectively alleviated water scarcity in Northwest China, with green water playing a greater role than blue water, especially in Shaanxi and Ningxia. As trade volumes rise, the population facing mild water scarcity continues to grow after trade, with increases of 4.56%, 6.70%, and 5.36% in 2000, 2010 and 2014. Agricultural trade significantly alleviates the pressure of severe water scarcity and boosts the region's population carrying capacity. This study provides scientific evidence to support stronger coordination of water resources between regions, especially agricultural water trade between water-rich and water-scarce areas, and to inform the formulation of rational allocation policies for balancing regional water resource distribution and benefits.
Freeze-thaw cycles (FTCs) are the significant factors that affect the bearing capacity of foundations and stability of structures in cold regions, posing challenges for the construction of water conservancy projects. Therefore, seeking improved materials that can enhance the engineering properties of soil is one of the hotspots in research. Until now, research on the improvement of soil properties by carbon nanotubes is still lacking, particularly regarding the evolution of macro and micro characteristics of the improved soil under FTCs. To clarify the above issues and provide scientific evidence for the application of multi-walled carbon nanotubes (MWCNTs) in engineering projects in cold regions, MWCNTs are utilized as the improvement material in this study, and a series of FTCs tests are conducted on the improved soil. The relationships between shear strength, particle gradation, pore structure, and FTCs are analyzed. Additionally, the optimal dosage of MWCNTs is determined, and the ability of the soil to resist FTCs is investigated under the optimal dosage conditions. The results show that 0.5 wt% MWCNTs can effectively improve the shear strength of soil. Moreover, FTCs reduce the shear strength by altering the particle gradation and pore structure, while the resistance of treated soil to FTCs is significantly enhanced. This study reveals the effects of MWCNTs in enhancing the engineering properties and freeze-thaw resistance of soils, providing a reference for the selection of materials for improving foundation soils in practical engineering.
