Patterns Of Spatiotemporal Variability Research Articles

Multi-scale temporal and spatial variations of soil heat flux under varying riparian forests: From a day to a year.

This study delves into the multi-scale temporal and spatial variations of soil heat flux (G) within riparian zones and its correlation with net radiation (Rn) across six riparian woodlands in Shanghai, each characterized by distinct vegetation types. The objective is to assess the complex interrelations between G and Rn, and how these relationships are influenced by varying vegetation and seasons. Over the course of a year, data on G and Rn is collected to investigate their dynamics. The multi-scale temporal patterns of G and its relationship with Rn are significantly influenced by both vegetation type and season, with the most pronounced variability observed seasonally, exhibiting distinct cycles for both broadleaf and conifer forests. The presence of shrubs is found to increase G, and the dominant temporal scales were found to vary within broadleaf forests. Additionally, G demonstrates a non-linear gradient with respect to the proximity to the river, with the river's influence on G diminishing at distances less than 11m in broadleaf and 6m in conifer woodlands. While the river enhances G and its hysteresis with Rn, vegetation characteristics dominate in dense canopies. This study underscores the importance of understanding the spatio-temporal variation patterns of soil heat flux and their response to different vegetation attributes. Such knowledge is vital for developing riparian soil heat flux models and informing riparian forest management strategies, especially in the context of climate change. The results provide insights into the complex interactions between soil heat flux, net radiation, and vegetation, offering a foundation for future research and management practices aimed at preserving and enhancing the ecological functions of riparian ecosystems.

Metabolomic characteristics and anthraquinones accumulation patterns of Rhubarb in different tissues and roots from different developmental stages

Rhubarb's multifaceted value in culinary and medicine is renowned, especially Rheum tanguticum (Rhubarb), whose bountiful content of anthraquinones (AQs) makes it increasingly attractive in the realms of dietary supplements and natural edible pigments. Current understanding of the spatiotemporal dynamics of AQs accumulation in Rhubarb remains limited, and the knowledge of other valuable metabolites is even more scarce. This gap limits the ability to fully explore Rhubarb's potential as a food ingredient and hinders its efficient use in food development, potentially leading to unnecessary resource waste. This study integrated widely targeted metabolomics and AQs quantification to determine the metabolic profiles in four tissues and the roots at three developmental stages in Rhubarb. The high levels of malic and citric acids in the stems paved the way for their use in flavored beverages and substantiated the practice of traditional consumption. The abundance of flavonoids in the leaves and seeds, and the AQs, phenolic acids of the seeds, which potentially bestowed upon them exceptional antioxidant capabilities, underscore the significant potential of edible product development. The widespread traditional use of roots was mirrored by the preferential accumulation of AQs, and the roots' value escalated in tandem with the time-accumulated increase of AQs. The root bark and root tip with high AQs should be given attention in production and not simply discarded. This research clarifies the chemical composition and spatiotemporal variation patterns of Rhubarb's characteristic components, offering valuable scientific insights for their efficient use and value enhancement in the food industry.

Spatiotemporal Variations and Driving Factors of Ecological Sensitivity in the West Qinling Mountains, China, Under the Optimal Scale

This study selected the five indicators of soil erosion, climate environment, geological hazards, biodiversity, and human disturbances and uses the entropy weight method to calculate the ecological sensitivity of the West Qinling Mountains from 2000 to 2020. The analysis produced a spatiotemporal distribution of ecological sensitivity over the 20-year period. An equal step size of 500 m was used to progressively increase the spatial scale from 500 m to 6 km. The optimal scale for the spatial differentiation of ecological sensitivity in the West Qinling Mountains was determined by analyzing the characteristics of changes at different scales, response mechanisms, and optimal parameters for geographical detector spatial scale identification. Based on this scale, the change in intensity and pattern and the influencing factors of ecological sensitivity were analyzed. The results show the following: (1) The 5.5 km spatial scale balances the requirements of accuracy, spatial heterogeneity, and data adequacy, making it the optimal scale for analyzing the spatiotemporal variation patterns of ecological sensitivity in the West Qinling Mountains. (2) From 2000 to 2020, the mean ecological sensitivity in the West Qinling Mountains exhibited a decreasing trend, indicating an improvement in the ecological environment. Spatially, the ecological sensitivity of the West Qinling Mountains showed a spatial distribution pattern of “low in the west and high in the east, low in the south and high in the north”. During the study period, the ecological sensitivity in the West Qinling region remained generally stable, with no high-frequency changes observed. (3) Population density is the primary driving factor of spatial differentiation of ecological sensitivity in the West Qinling Mountains, while GDP serves as a secondary factor. Overall, socioeconomic factors have the most significant impact on ecological sensitivity. (4) Over 75% of the ecological sensitivity trends exhibit patterns of perennial unchanged and fluctuating unchanged trends, with areas of fluctuating increase smaller than areas of fluctuating decrease. Regions of perennial high sensitivity are primarily concentrated in the northeastern part of the West Qinling Mountains, while areas with increased fluctuation in ecological sensitivity are mainly located in the western and southern parts of the West Qinling Mountains. Future efforts should focus on these regions.

Patterns of spatiotemporal variations in the hydrochemistry and controlling factors of bedrock aquifers in the northern region of the Linhuan mining area

Systematically studying the hydrochemical evolution of bedrock groundwater in mining areas during mining process is crucial for effective groundwater resource management and coal mine production. The spatiotemporal characteristics and hydrochemical evolution patterns of the Permian fractured sandstone aquifer (PA) and the Carboniferous Taiyuan Formation limestone aquifer (CTA), both of which are directly associated with coal mining in the northern Linhuan mining area, China, were investigated using multivariate statistical analyses, hydrochemical graphical methods, ion ratio analysis, and a conceptual model. 72 groundwater samples, collected before and after mining, were classified into four groups by hierarchical cluster analysis (HCA). Principal component analysis (PCA) and ion ratio analysis indicated that water-rock interactions involve mineral dissolution (carbonates, gypsum, dolomite, silicates), cation exchange, and common ion effects. Hydrochemical evolution is influenced by bedrock paleotopography, aquifer hydraulic conductivity, and mining drainage. Paletopographic differences significantly influence water-rock interactions and spatial variability in hydrochemistry, with ion concentrations in groundwater increasing as paleotopographic elevation decreases. The pattern of hydraulic conductivity reflects the control exerted by variations in aquifer characteristics on mineral dissolution, leading to minor changes in hydrochemical characteristics. Mining activities disrupt the aquifer's reducing environment, resulting in a significant increase in groundwater SO42− concentration. These findings provide insights and a solid theoretical foundation for studying the hydrochemical variations patterns of groundwater and these control mechanisms in the hidden coal fields of North China.

Spatiotemporal Variation Characteristics and Source Identification of Nitrogen in the Baiyangdian Lake Water, China

To study the characteristics and sources of nitrogen in the Baiyangdian Lake, this research conducted water quality monitoring during three hydrological periods (normal period, flood period, and dry period), and 165 pieces of routine water quality monitoring data were collected from the three national control sections for Baiyangdian Lake and its inflow rivers. By integrating water chemical analysis with multivariate statistical techniques, the study comprehensively investigated the spatiotemporal variation patterns of nitrogen in Baiyangdian Lake and identified the sources of nitrogen pollution. The results showed that the concentration of total nitrogen (TN) was highest during the dry period, reaching an average of 0.924 mg/L, and 31.3% of the sites exceeded the national Grade III surface water quality standard, reflecting a potential risk of nitrogen pollution. Based on the ion ratio method and principal component analysis (PCA), the main sources of nitrogen pollution in Baiyangdian Lake were identified as manure and domestic sewage, with agricultural fertilizers also having a certain impact on water nitrogen pollution. In addition, the study also compared the nitrogen concentration in Baiyangdian Lake with several important lakes in China. The results showed that the concentrations of TN and ammonium nitrogen (NH4+-N) in Baiyangdian Lake are lower than those in lakes in areas with similar human activity intensity, indicating that the water quality of Baiyangdian is relatively good. This study can provide a scientific basis for water quality management and pollution prevention for Baiyangdian Lake.

Earth observation reveals the shifting patterns of China's lake colour driven by climate change and land cover

Water colour has been recognized as one of the most important Essential Climate Variables of the lake ecosystem, as it is directly related to changes in water constituents and almost all of the lake's ecological changes could alter water colour. Given the high retrieval accuracy from existing Earth observation satellite data, water colour, in terms of Forel Ule Index (FUI), can be a realistic indicator to track the long-term changes in the lake ecosystem and further explore the lake response to environmental changes. This paper aims to comprehensively investigate the spatiotemporal variation patterns of FUI in 159 large lakes (≥25 km2) across China during 2000–2022 based on the MODIS data and detect the climatic and anthropogenic driving forces of these changes. The 23 years of MODIS records revealed an overall downward trend of lake FUI across China, indicating the lakes in China shifted to bluer colour during the past two decades. Through driving factor analyses, the complicated interplay among lake colour, lake morphology, regional climate shifts and human interference dynamics was uncovered. In the long term, it was found the pronounced change in lake colour in the western lake zones was primarily attributed to climate warming and humidification, whereas that in the eastern lake zones was mainly related to the alterations in regional land cover during the past two decades. Seasonally, lake basin's air temperature was identified as the main factor impacting the seasonal patterns of lake colour, followed by wind speed and runoff. Spatially, there was high spatial variability in lake colour across China, which was mainly associated with lake elevation and lake basin's precipitation rate, although the factors exhibited considerable divergence across different zones. Based upon the above findings, the implications for lake environment protection and management in different regions of China were further discussed.

Modeling and Application of Drought Monitoring with Adaptive Spatial Heterogeneity Using Eco–Geographic Zoning: A Case Study of Drought Monitoring in Yunnan Province, China

Drought, characterized by frequent occurrences, an extended duration, and a wide range of destruction, has become one of the natural disasters posing a significant threat to both socioeconomic progress and agricultural livelihoods. Large-scale geographical environments often exhibit obvious spatial heterogeneity, leading to significant spatial differences in drought’s development and outcomes. However, traditional drought monitoring models have not taken into account the impact of regional spatial heterogeneity on drought, resulting in evaluation results that do not match the actual situation. In response to the above-mentioned issues, this study proposes the establishment of ecological–geographic zoning to adapt to the spatially stratified heterogeneous characteristics of large-scale drought monitoring. First, based on the principles of ecological and geographical zoning, an appropriate index system was selected to carry out ecological and geographical zoning for Yunnan Province. Second, based on the zoning results and using data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) and the Tropical Rainfall Measuring Mission (TRMM) 3B43, the vegetation condition index (VCI), the temperature condition index (TCI), the precipitation condition index (TRCI), and three topographic factors including the digital elevation model (DEM), slope (SLOPE), and aspect (ASPECT) were selected as model parameters. Multiple linear regression models were then used to establish integrated drought monitoring frameworks at different eco–geographical zoning scales. Finally, the standardized precipitation evapotranspiration index (SPEI) was used to evaluate the monitoring effects of the model, and the spatiotemporal variation patterns and characteristics of winter and spring droughts in Yunnan Province from 2008–2019 were further analyzed. The results show that (1) compared to the traditional non-zonal models, the drought monitoring model constructed based on ecological–geographic zoning has a higher correlation and greater accuracy with the SPEI and (2) Yunnan Province experiences periodic and seasonal drought patterns, with spring being the peak period of drought occurrence and moderate drought and light drought being the main types of drought in Yunnan Province. Therefore, we believe that ecological–geographic zoning can better adapt to geographical spatial heterogeneity characteristics, and the zonal drought monitoring model constructed can more effectively identify the actual occurrence of drought in large regions. This research finding can provide reference for the formulation of drought response policies in large-scale regions.

Spatiotemporal Variation Patterns of Drought in Liaoning Province, China, Based on Copula Theory

Liaoning Province, a crucial agricultural region in Northeast China, has endured frequent drought disasters in recent years, significantly affecting both agricultural production and the ecological environment. Conducting drought research is of paramount importance for formulating scientific drought monitoring and prevention strategies, ensuring agricultural production and ecological safety. This study developed a Comprehensive Joint Drought Index (CJDI) using the empirical Copula function to systematically analyze drought events in Liaoning Province from 1981 to 2020. Through the application of MK trend tests, Morlet wavelet analysis, and run theory, the spatiotemporal variation patterns and recurrence characteristics of drought in Liaoning Province were thoroughly investigated. The results show that, compared to the three classic drought indices, Standardized Precipitation Index (SPI), Evaporative Demand Drought Index (EDDI), and Standardized Precipitation Evapotranspiration Index (SPEI), CJDI has the highest accuracy in monitoring actual drought events. From 1981 to 2020, drought intensity in all regions of Liaoning Province (east, west, south, and north) exhibited an upward trend, with the western region experiencing the most significant increase, as evidenced by an MK test Z-value of −4.53. Drought events in Liaoning Province show clear seasonality, with the most significant periodic fluctuations in spring (main cycles of 5–20 years, longer cycles of 40–57 years), while the frequency and variability of drought events in autumn and winter are lower. Mild droughts frequently occur in Liaoning Province, with joint and co-occurrence recurrence periods ranging from 1.0 to 1.8 years. Moderate droughts have shorter joint recurrence periods in the eastern region (1.2–1.4 years) and longer in the western and southern regions (1.4–2.2 years), with the longest co-occurrence recurrence period in the southern region (3.0–4.0 years). Severe and extreme droughts are less frequent in Liaoning Province. This study provides a scientific foundation for drought monitoring and prevention in Liaoning Province and serves as a valuable reference for developing agricultural production strategies to adapt to climate change.

Monitoring and Law Analysis of Secondary Deformation on the Surface of Multi-Coal Seam Mining in Closed Mines

A large number of mines have been closed due to resource depletion, failure to meet safety production requirements, and other reasons. To effectively ensure the safety of the ecological environment above these closed mines along with the safety of engineering construction, it is necessary to monitor the secondary deformation of closed mines. Based on TerraSAR-X, Sentinel-1A data, and InSAR technology, this study obtained high-density secondary surface deformation data on the Jiahe Coal Mine and Pangzhuang Coal Mine in the western Xuzhou area. Combining mining geological data, we analyzed the spatiotemporal variation patterns and mechanisms of secondary deformation in multi-seam mining of closed mines. It was found that when mining multiple seams involves large interlayer spacing, the secondary deformation pattern shows a “W” shape. In this situation, the deformation can be divided into five stages: subsidence, uplift, re-subsidence, re-uplift, and relative stability. This study provides technical support for the evaluation and prevention of secondary deformation hazards in closed mines.

Contributions of Soil Moisture and Vegetation on Surface-Air Temperature Difference during the Rapid Warming Period

The difference (DIF) between land surface temperature (Ts) and near surface air temperature (Ta) is the key indicator of the energy budget of the land surface, which has a more complex process than the individual Ts or Ta. However, the spatiotemporal variations and influencing factors of DIF remain incomplete. The contribution of vegetation and soil moisture (SM) as key driving factors to DIF is not yet clear. Here, we analyzed the spatiotemporal variation patterns of DIF in China from 2011 to 2023 using in situ Ts and Ta data. A convergent cross-mapping method was employed to explore the causal relationship between SM, NDVI and DIF, and subsequently calculated the contribution of NDVI and SM variations to DIF under different climatic backgrounds. The results indicate that during the study period, DIF values were all above 0 °C and showed a significant increasing trend with a national mean slope of 0.02 °C/a. In general, vegetation and SM have a driving effect on DIF, with vegetation contributing more to DIF (0.11) than SM (0.08) under different surface properties. The background values of SM and temperature have a significant effect on the spatial and temporal distribution of DIF, as well as the correlation of vegetation and soil moisture to DIF. The study outcomes contribute to a better understanding of the coupling relationship between the land surface and atmosphere, which are also crucial for addressing climate change and ecological environmental management.

Temporal and spatial evolution of net primary productivity in the Three-River Headwaters Region under phenological changes and anthropogenic influence.

Understanding the spatiotemporal changes in net primary productivity (NPP) and the driving factors behind these changes in climate-vulnerable regions is crucial for ecological conservation. This study simulates the actual NPP (NPPA) and climate potential NPP (NPPC) in the Three-River Headwaters Region from 2000 to 2020. The Theil-Sen Median method and Mann-Kendall mutation analyses are employed to explore their spatiotemporal variation patterns, while geographic weighted regression and machine learning are used to investigate the influence of anthropogenic activities and climatic factors on NPPA, the results indicate that the average NPPA across the entire region over multiple years is 382.506 , which is 0.132 times the average annual NPPC over the past 21years, showing an overall distribution pattern of low in the northwest and high in the southeast. The annual increase in NPPA from 2000 to 2020 is approximately 1.034 . The source region of the Yangtze River shows the largest improvement in vegetation, with 74.1% of the area showing improvement. Between 2002 and 2003, the annual NPPA in the Three-River Headwaters Region experienced a sudden change, lagging behind the NPPC change by 1year, and after 2005, the upward trend in NPPA became more pronounced. The impact of anthropogenic activities on NPPA shifted from positive to negative to positive from 2000 to 2020, with significant impact areas mainly concentrated in the northeast and a few areas in the central and southern parts. The proportion of areas with extremely significant impact increased from 1.9% in 2000 to 3.7% in 2020. Over the past 21years, the main factors influencing NPPA changes in the Three-River Headwaters Region have been soil moisture and precipitation, with the influence of different climate factors on NPP changing over time. Additionally, NPP is more sensitive to changes in altitude in low-altitude areas. This study can provide more accurate theoretical support for ecological environment assessment and subsequent protection efforts in the Three-River Headwaters Region.

Windbreak and sand fixation service flow simulation in the terminal lake basin of inland rivers in arid regions: A case study of the Aral Sea basin

Research on windbreak and sand fixation (WSF) services aids in soil conservation, and ecological protection. Over the past 50 years, the Aral Sea's shrinkage has intensified wind erosion, leading to significant sand and dust emissions in Central Asia (CA). This study uses the Revised wind erosion equation (RWEQ) model and the hybrid single particle Lagrangian integrated trajectory model (HYSPLIT) model to simulate the spatiotemporal variation pattern of WSF services in the Aral Sea basin (ASB). From the perspective of sand and dust transmission paths, the flow trajectory and benefit areas of WSF services are identified, the spatiotemporal correlation between the WSF service supply areas and benefit areas is established, and the potential impact of WSF services on beneficiary areas is quantitatively assessed. The results show the amount of wind erosion and the amount of WSF in the ASB from 2000 to 2019 showed a fluctuating trend of “first increasing and then decreasing”. In terms of spatial distribution, areas with large amounts of WSF are mainly distributed in the lower reaches of the Syr Darya River and the sand dunes in the northwest of the Kizilkum Desert. WSF services mainly flow through the Kizilkum Desert, Karakum Desert, Moyinkum Desert, Kazakh Hills, and the Junggar Basin and Tarim Basin in China. Generally, it flows to the northeast and southwest. In the past 20 years, the largest areas benefiting from the flow of WSF services are mainly distributed in Uzbekistan, Kyrgyzstan, and Tajikistan. The trajectory distribution frequency shows a decreasing trend from the center to the periphery. The grassland areas constituted the largest beneficiary areas in the ASB of CA, with both the beneficiary population and real GDP exhibiting an upward trend. This study holds significant importance for enhancing the management of ecosystem services in sandy regions and for establishing ecological compensation mechanisms.

Multi-scale remote sensing retrieval model for land surface emissivity and its impact on land surface temperature estimation

ABSTRACT As a fundamental parameter of the surface radiation process, land surface emissivity (LSE) is the most direct factor affecting the land surface temperature (LST) retrieval accuracy. Based on the measured data from 2017 to 2023, the characteristics of LSE changes were analysed, different timescale LSE retrieval models were developed, and the impact of LSE on pixel scale observational LST acquisition was evaluated by using unmanned aerial vehicle (UAV) remote sensing images. The results show that with changes in atmospheric environmental conditions, the LSE changes are relatively less pronounced at 3.99 µm and 4.02 µm in the mid-infrared band and at 10.8 µm and 11.8 µm in the thermal infrared band than in the other bands. At the timescale above day, the LSE is significant correlation with the normalized differential vegetation index (NDVI). Vegetation is the main parameter that dominates the LSE change under heterogeneous underlying surfaces. On a daily timescale, LSE exhibits typical diurnal variation characteristics, and the amplitude of diurnal variation is influenced mainly by shallow soil water and heat conditions. The developed LSE model based on Fengyun-4A (FY-4A) satellite remote-sensing data can effectively reproduce the daily variation characteristics of LST and avoid the ‘jumping’ phenomenon that may occur in the NDVI threshold method. The root-mean-square error (RMSE) between the retrieved LST and in situ data is reduced to 3.78°C, and the retrieval accuracy is better than that of the published LST product. When using UAVs to obtain pixel-scale LSTs, dry bare soil is more sensitive to LSE. When the LSE increases from 0.95 to 1.0, the average LST obtained by the UAV deviates by approximately 1.0°C. This study preliminarily provides some spatiotemporal variation patterns of LSE and lays a foundation for the later-modified LST retrieval algorithms.

RS-AAT with distributed permeable pipes and alkaline water: Enhancing concrete durability through chloride reduction, pH optimization, and pore structure improvement

Reverse-seepage and Saturation based Active Anti-corrosion Technology (RS-AAT) is a novel and environmentally-friendly approach that enhances the ability of unsaturated concrete in marine alternating wet-dry areas to resist chloride ion intrusion. Comprehending its influence on ions transport and the pore structure within the concrete is vital for assessing the rationality of the technique and further predicting its service life. In this study, cross-section specimens of cast in situ concrete piles with RS-AAT were exposed to a chloride wet-dry cycling environment for 150 days. Spatiotemporal variation patterns of chloride ion content, pore fluid pH, and pore structure in the concrete cover were investigated by free chloride titration, pH determination, and mercury intrusion porosimetry (MIP). The findings indicate that RS-AAT can effectively inhibit chloride ion intrusion into the protective layer of concrete. Moreover, implementing alkaline water in RS-AAT elevates the pore fluid pH and improves the compactness of the pore structure, especially diminishing the harmful pore ratio. Besides, increasing the number of distributed permeable pipes reinforces these effects and reduces the technology's dependence on water pressure. This insight demonstrates the viability of using alkaline water and distributed permeable pipes in RS-AAT to bolster the resistance of concrete structures to chloride ion erosion in an environmentally sustainable manner.

Crustal Apparent Density Variations in the Middle Segment of the North Tianshan Mountains and Their Tectonic Significance

In this study, we collected mobile gravity observations in the middle segment of the North Tianshan Mountains from August 2016 to July 2022 and carried out classical adjustment calculations under the constraint of the absolute gravity datum to obtain the spatiotemporal variation pattern of the local gravity field. We used equivalent source inversion to obtain the spatiotemporal variation characteristics of crustal apparent density. We also extracted the coseismic deformation field from SAR data, using the 2016 Hutubi earthquake as an example, and constructed a model of the seismogenic fault. The gravity monitoring network in the study area performed well in resolving the earthquake source parameters. Both the time-varying gravity field and equivalent apparent density variation pattern show prominent zoning characteristics with a smoothly evolving spatial distribution over time. The variation trends of the gravity field and equivalent apparent density are in line with the orientation of tectonic structures, and their anomalous signals can be detected before and after an earthquake. The constructed seismogenic structure of the 2016 Hutubi earthquake indicates a typical thrust earthquake, probably occurring on a north-dipping blind fault beneath a region with intense crustal deformation. The subsurface tectonic system reflected by this earthquake can be informatively extended to the entire middle segment of the North Tianshan Mountains by subsurface configuration. Our findings can serve as a reference for analyzing the source characteristics of the time-varying gravity field and interpreting anomalous pre-seismic signals, and aid in understanding earthquake preparation zones and the mode of crustal tectonic movements.

Increasing gross primary productivity under soil warming and wetting on the Tibetan Plateau

The soil freeze-thaw process has undergone significant changes on the Tibetan Plateau (TP) in the context of global change, resulting in the changes of soil physical and chemical properties, thereby affecting the vegetation phenology and photosynthesis through affecting the utilization capacity of CO2 and light by vegetation. However, little is known about how soil temperature (ST) and soil moisture (SM) affect the gross primary productivity (GPP) on the TP at different seasons and elevations. In this study, the spatiotemporal variation patterns of GPP, ST, and SM were analyzed based on the Community Land Model version 5.0 (CLM5.0) simulations in order to illustrate the impacts of ST and SM in surface (0–10 cm) and root zone soil (0–100 cm) on GPP between 1979 and 2020. The results showed that the CLM5.0-based GPP and ST were in good agreement with in situ observations. ST, SM and GPP increased at the rates of 0.04 °C a−1, 2.4 × 10−4mm3 mm−3 a−1, and 5.36 g C m−2 a−2, respectively. SM dominated the variations of GPP in winter (64.3%), while ST almost was the dominant factor in other periods, especially spring (99.9%) and autumn (94.7%). The explanatory power of ST and SM for GPP increased with elevation, especially for ST. The relative contributions of ST and SM to GPP at different time scales in root zone soil were similar to those in surface soil. This study provided a new understanding of how soil freeze-thaw affected GPP changes on the TP in the context of the intensification of warming and humidification.

Imaging small geological structure in coal mines based on reflected acoustic logging of underground cross-seam boreholes

Accurate identification of small geological structures is the key and difficult point in coal mine geological survey. The reflected acoustic logging technology has the advantages of large detection range and high imaging resolution, and can realize the accurate investigation of small structural interfaces. Therefore, the idea of identifying small geological structures in coal mines by using cross-seam boreholes reflected acoustic logging is proposed. By placing acoustic logging tools in underground cross-seam boreholes, waveforms generated at coal-rock interfaces around the borehole are collected. The reflection wave information is then inverted to obtain interface images of small structures. First, COMSOL Multiphysics software is utilized to build finite element models for reflected acoustic logging in coal-bearing formations containing coal seam fractures, small normal faults, and coal seam thinning zones, respectively. Then forward modeling is conducted to analyze the spatiotemporal variation patterns of the full waveform signals and velocity snapshots. Finally, the reflected acoustic logging data is inverted to realize the offset imaging of small structures in coal mines. The forward modeling results show that: the arrival times of reflected waves varying with the source longitudinal coordinates exhibit good consistency with the interface morphology of borehole vicinity small structures. The inversion results show that: when fractures exist in the coal seam, the imaged dip angle of the fracture is 54.14°, with an error rate of 2.07% compared to the analytical model, and the imaged fracture length is 15.32 m, with an error rate of 4.57%. When small faults exist in the coal seam, the imaged dip angle of the fault plane is 70.63°, with an error rate of 1.41% compared to the analytical model, and the imaged fault plane length is 13.75 m, with an error rate of 3.03%. When thinning zones exist in the coal seam, the imaged dip angles of the upper and lower interfaces of the thinning zone are 44.61° and 57.80°, with error rates of 0.31% and 0.40% respectively compared to the analytical model. The imaged lengths of the upper and lower interfaces are 9.32 m and 18.73 m respectively, with error rates of 0.32% and 1.08% respectively. Acoustic reflection logging technology can effectively invert the locations and morphological characteristics of small structures in coal mines. This study can provide fundamental theoretical support for the application of acoustic reflection logging technology in cross-seam boreholes for identification of small structures in coal seams.

Study on the spatiotemporal variation of the Yangtze estuarine tidal species

Owing to the nonlinear influence of river discharge, estuarine tides are nonstationary and more complicated than oceanic tides. This study investigated the spatiotemporal variation pattern of the Yangtze estuarine tides by considering tidal species separated using the Variational Mode Decomposition (VMD) model. The separated tidal species were compared with tidal species reconstructed using the NS_TIDE model. The results showed that the subtidal (D0) amplitude increased landward because of the enhanced influence of river discharge and river-tide interactions; diurnal (D1) and semi-diurnal (D2) tidal amplitudes consistently decayed landward because of frictional dissipation and nonlinear energy transfer to other tidal constituents; while quarter-diurnal (D4) and six-diurnal (D6) tidal amplitudes initially increased and then decreased in the landward direction because of the transformation of the dominant role of river discharge from nonlinear energy transfer to frictional dissipation. The spatiotemporal variations in different tidal species can illustrate other tidal processes, such as seasonal differences in tidal duration asymmetry. Although the VMD model neglects the separation of each tidal constituent, it can provide reasonable information, even when NS_TIDE may provide implausible results during the flood season because of the highly nonstationary conditions.

Spatiotemporal variation pattern and spatial coupling relationship between NDVI and LST in Mu Us Sandy Land

Spatiotemporal variation pattern and spatial coupling relationship between NDVI and LST in Mu Us Sandy Land

Spatiotemporal distribution and influencing factors of impervious surface evaporation in the Baiyangdian catchment from 1980 to 2020

AbstractEvaporation from impervious surfaces plays a vital role in the catchment water cycle. Exploring the spatiotemporal variation patterns and influencing mechanisms of impervious surface evaporation at the catchment scale can improve the understanding and evaluation of the evaporation process. This study downloaded 0.5 m resolution images of the Baiyangdian catchment (BYD) from Google Earth and used deep learning to identify impervious surfaces. This was used to revise impervious surfaces of the China land cover dataset in 1985 and 1990–2020. Potential evaporation (PET) from three types of impervious surfaces (roofs, ground affected or not affected by the building height) was calculated by modifying the parameters of the Penman–Monteith equation, and daily precipitation and water‐storage capacity of impervious surfaces were taken into account to estimate impervious surface evaporation (E). The results showed that E values of the three types of impervious surfaces were between 72.1 and 178.2 mm/year and all exhibited the spatial distribution of high in the northwest and low in the southeast of the BYD in 1980–2020. Compared with that in 1980, in 2020, the cumulative evaporation (EAP) increased by 134.4%. The ratio of EAP to cumulative precipitation ranged from 3.0% to 6.9%, increasing significantly in a fluctuating manner. The increments in precipitation days and impervious surface area played a major role in the increase of EAP, and the decrease in precipitation was the fundamental reason for the increase in the proportion of impervious surface evaporation and water resource pressure in the BYD. Excluding the continuous evaporation from the remaining water can likely lead to underestimating the impervious surface evaporation. This study provides an efficient and reasonable novel approach for calculating impervious surface evaporation in long series and large‐scale catchments.