Search Results (1,393)

The 2008 Wenchuan earthquake released vast quantities of loose material, significantly influencing post-earthquake material dynamics, particularly through recurrent debris flow disasters that posed long-term threats to the earthquake-affected area. To explore the transport and involvement of loose materials in debris flow events within earthquake-affected basins, this study focuses on a representative area near the Wenchuan epicenter, creating a multi-temporal database of active landslides and channel materials pre- and post-earthquake, quantitatively assessing material transport and source replenishment in debris flow basins, and categorizing debris flows based on channel material activity, post-earthquake historical activity, and sustainability of activity. This study revealed that pre-earthquake material activity was concentrated in the watershed’s upper regions, while post-earthquake materials were progressively transported from the central to the lower regions, with many small co-seismic landslides ceasing activity. The supply area ratio from active landslides capable of recharging debris flows, i.e., those connected to channels, consistently remained at approximately 72%, with the peak area of channel material activity comprising approximately 2.5% of the total watershed area. Channel material activity areas serve as valuable indicators for hazard assessment in regions lacking historical debris flow data, with the watershed area predominantly determining the sustainability of post-earthquake debris flow activity. Full article

The effectiveness of ecological security patterns (ESPs) in maintaining regional ecological stability and promoting sustainable development is widely recognized. However, limited research has focused on the early warning of risks inherent in ESPs. In this study, the Guangdong–Hong Kong–Macao Greater Bay Area (GHKMGBA) is taken as the study area, and ecological security risk zones are delineated by combining the landscape ecological risk index and habitat quality, and a multi-level ESP is constructed based on the circuit theory. The PLUS model was employed to simulate future built-up land expansion under different scenarios, which were then extracted and overlaid with the multi-level ESP to enable the multi-scenario early warning of ESP risks. The results showed the following: The ESP in the central plains and coastal areas of the GHKMGBA exhibits a high level of ecological security risk, whereas the peripheral forested areas face less threat, which is crucial for regional ecological stability. The ESP, comprising ecological sources, corridors, and pinch points, is crucial for maintaining regional ecological flow stability, with tertiary corridors under significant stress and risk in all scenarios, requiring focused restoration and enhancement efforts. There are significant differences in risk early warning severity within the ESP across various development scenarios. Under the ecological protection scenario, the ESP will have the best early warning situation, effectively protecting ecological land and reducing ecological damage, providing a valuable reference for regional development policies. However, it must not overlook economic development and still needs to further seek a balance between economic growth and ecological protection. Full article

Understanding the spatiotemporal evolution patterns of Populus euphratica Oliv. (P. euphratica) forests in the Tarim Basin (TB) and their influencing factors is crucial for regional ecological security and high-quality development. However, there is currently a lack of large-area, long-term systematic monitoring. This study utilized multi-source medium and high-resolution remote sensing images from the Landsat series and Sentinel-2, applying a Random Forest classification model to obtain distribution data of P. euphratica forests and shrublands in 14 areas of the TB from 1990 to 2020. We analyzed the effects of river distance, water transfer, and farmland on their distribution. Results indicated that both P. euphratica forests and shrublands decreased during the first 20 years and increased during the last 10 years. Within 1.5 km of river water transfer zones, P. euphratica forests more frequently converted to shrublands, while both forests and shrublands showed recovery in low-frequency water transfer areas. Farmland encroachment was most significant beyond 3 km from rivers. To effectively protect P. euphratica forests, we recommend intermittent low-frequency water transfers within 3 km of rivers and stricter management of agricultural expansion beyond 3 km. These measures will help maintain a balanced ecosystem and promote the long-term sustainability of P. euphratica forests. Full article

Coupling solar-induced chlorophyll fluorescence (SIF) with gross primary productivity (GPP) for ecological function integration research presents numerous uncertainties, especially in ecologically fragile and climate-sensitive arid regions. Therefore, evaluating the suitability of SIF data for estimating GPP and the feasibility of improving its accuracy in the northern region of Xinjiang is of profound significance for revealing the spatial distribution patterns of GPP and the strong coupling relationship between GPP and SIF in arid regions, achieving the goal of “carbon neutrality” in arid regions. This study is based on multisource SIF satellite data and GPP observation data from sites in three typical ecosystems (cultivated and farmlands, pasture grasslands, and desert vegetation). Two precision improvement methods (canopy and linear) are used to couple multiple indicators to determine the suitability of multisource SIF data for GPP estimation and the operability of accuracy improvement methods in arid regions reveal the spatial characteristics of SIF (GPP). The results indicate the following. (1) The interannual variation of GPP shows an inverted “U” shape, with peaks values in June and July. The cultivated and farmland areas have the highest peak value among the sites (0.35 gC/m²/month). (2) The overall suitability ranking of multisource SIF satellite products for GPP estimation in arid regions is RTSIF > CSIF > SIF_OCO2_005 > GOSIF. RTSIF shows better suitability in the pasture grassland and cultivated and farmland areas (R² values of 0.85 and 0.84, respectively). (3) The canopy method is suitable for areas with a high leaf area proportion (R² improvement range: 0.05–0.06), while the linear method is applicable across different surface types (R² improvement range: 0.01–0.13). However, the improvement effect of the linear method is relatively weaker in areas with high vegetation cover. (4) Combining land use data, the overall improvement of SIF (GPP) is approximately 0.11%, and the peak values of its are mainly distributed in the northern and southern slopes of the Tianshan Mountains, while the low values are primarily found in the Gurbantunggut Desert. The annual mean value of SIF (GPP) is about 0.13 mW/m²/nm/sr. This paper elucidates the applicability of SIF for GPP estimation and the feasibility of improving its accuracy, laying the theoretical foundation for the spatiotemporal coupling study of GPP and SIF in an arid region, and providing practical evidence for achieving carbon neutrality goals. Full article

The Xinjiang region is prone to frequent and complex wind and sand disasters, which present a significant challenge to the sustainable development of local areas. This research uses multi-source data to analyze the spatial distribution of the aeolian environment in Xinjiang, establishes a four-level zoning scheme, and proposes recommendations for ecological management and engineering and control. Results indicate that (1) Xinjiang’s aeolian environment and its types exhibit spatial heterogeneity. The aeolian environment types display a high concentration in the eastern region and a low concentration in the western region. Furthermore, the aeolian environment types are concentrated in the basin region. Moreover, the aeolian environment types exhibit a meridional distribution pattern. (2) A four-level zoning system for aeolian environments in Xinjiang was developed, comprising two first-level zones, seven s-level subzones, 22 third-level wind zones, and 31 fourth-level subdivisions. (3) A structural model for a highway sand control system is proposed for aeolian environment types of subdivisions, including fixing-based, combined blocking and fixing, wind-blocking and sand-transferring, and combined blocking and fixing–transferring. The aeolian environment regionalization program proposed in this study can be a scientific reference for relevant departments in formulating and implementing sand prevention and control planning. Full article

How rural land transfer affects the growth of non-agricultural income and the changes in its sources are important research topics. This study uses the micro-data from the China Family Panel Studies (CFPS) spanning from 2014 to 2020 and empirically analyzes the impact of rural land transfer on the growth of non-agricultural income, based on a multi-dimensional decomposition of rural household income structure. This study found that (1) land transfer has a significant promoting effect on the growth of non-agricultural income. Transferring out land is conducive to increasing wage income and transfer income, while transferring in land compensates for the decrease in operating income by achieving a higher operating income, ultimately leading to an increase in total income. (2) The effect of land transfer on the growth of non-agricultural income is higher in the Eastern region than in the Central and Western regions. The higher the education level of family members, the greater the income-increasing effect of land transfer on farmers. (3) Mechanism analysis shows that land transfer increases farmers’ opportunities for migrant work and improves farmers’ operational efficiency, which are the main channels for the growth in non-agricultural income. This study demonstrates that land circulation will promote farmers’ income growth and prosperity through rental income, share cooperation and dividends, labor transfer and wage income, industrial chain extension and value-added income, and policy support and subsidies. Full article

With the gradual emergence of trends such as the asynchronous interconnection of power grids and the increasing penetration of renewable energy, the issues of ultra-low-frequency oscillations and low-frequency stability in power grids have become more prominent, posing serious challenges to the safety and stability of systems. The voltage-source converter-based HVDC (VSC-HVDC) interconnection is an effective solution to the frequency stability problems faced by regional power grids. VSC-HVDC can participate in system frequency stability control through a frequency limit controller (FLC). This paper first analyses the basic principles of how VSC-HVDC participates in system frequency stability control. Then, in response to the frequency stability control requirements of the sending and receiving power systems, a droop FLC strategy is designed. Furthermore, a multi-objective optimization method for the parameters of the droop FLC is proposed. Finally, a large-scale electromagnetic transient simulation model of the VSC-HVDC interconnected power system is constructed to verify the effectiveness of the proposed droop FLC method. Full article

With the increase in the number of Global Navigation Satellite System (GNSS) satellites and their operating frequencies, richer observation data are provided for the tightly coupled Global Navigation Satellite System/Inertial Navigation System (GNSS/INS). In this paper, we propose an efficient and robust combined navigation scheme to address the key issues of system accuracy, robustness, and computational efficiency. The tightly combined system fuses multi-source data such as the pseudo-range, the pseudo-range rate, and dual-antenna observations from the GNSS and the horizontal attitude angle from the vertical gyro (VG) in order to realize robust navigation in a sparse satellite observation environment. In addition, to cope with the high computational load faced by the system when the satellite observation conditions are good, we propose a weighted quasi-optimal satellite selection algorithm that reduces the computational burden of the navigation system by screening the observable satellites while ensuring the accuracy of the observation data. Finally, we comprehensively evaluate the proposed system through simulation experiments. The results show that, compared with the loosely coupled navigation system, our system has a significant improvement in state estimation accuracy and still provides reliable attitude estimation in regions with poor satellite observation conditions. In addition, in comparison experiments with the optimal satellite selection algorithm, our proposed satellite selection algorithm demonstrates greater advantages in terms of computational efficiency and engineering practicability. Full article

Direct air capture (DAC) systems that capture carbon dioxide (CO₂) directly from the atmosphere are garnering considerable attention for their potential role as negative emission technologies in achieving net-zero CO₂ emission goals. Common DAC technologies are based either on liquid–solvent (L-DAC) or solid–sorbent (S-DAC) to capture CO₂. A comprehensive multi-factor comparative economic analysis of the deployment of L-DAC and S-DAC facilities across various United States (U.S.) cities is presented in this paper. The analysis considers the influence of various factors on the favorability of DAC deployment, including local climatic conditions such as temperature, humidity, and CO₂ concentrations; the availability of energy sources to power the DAC system; and costs for the transport and storage of the captured CO₂ along with the consideration of the regional market and policy drivers. The deployment analysis in over 70 continental U.S. cities shows that L-DAC and S-DAC complement each other spatially, as their performance and operational costs vary in different climates. L-DAC is more suited to the hot, humid Southeast, while S-DAC is preferrable in the colder, drier Rocky Mountain region. Strategic deployment based on regional conditions and economics is essential for promoting the commercial adoptability of DAC, which is a critical technology to meet the CO₂ reduction targets. Full article

The growing concerns about floods have highlighted the need for accurate and detailed precipitation data as extreme precipitation occurrences can lead to catastrophic floods, resulting in significant economic losses and casualties. Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM IMERG) is a commonly used high-resolution gridded precipitation dataset and is recognized as trustworthy alternative sources of precipitation data. The aim of this study is to comprehensively evaluate the performance of GPM IMERG Early (IMERG-E), Late (IMERG-L), and Final Run (IMERG-F) in precipitation estimation and their capability in detecting extreme rainfall indices over southwestern Iran during 2001–2020. The Asfezari gridded precipitation data, which are developed using a dense of ground-based observation, were utilized as the reference dataset. The findings indicate that IMERG-F performs reasonably well in capturing many extreme precipitation events (defined by various indices). All three products showed a better performance in capturing fixed and non-threshold precipitation indices across the study region. The findings also revealed that both IMERG-E and IMERG-L have problems in rainfall estimation over elevated areas showing values of overestimations. Examining the effect of land cover type on the accuracy of the precipitation products suggests that both IMERG-E and IMERG-L show large and highly unrealistic overestimations over inland water bodies and permanent wetlands. The results of the current study highlight the potential of IMERG-F as a valuable source of data for precipitation monitoring in the region. Full article

Against the backdrop of global warming and vegetation restoration, research on the evapotranspiration mechanism of the Yellow River basin has become a hot topic. The Budyko-Fu model is widely used to estimate basin-scale evapotranspiration, and its crucial parameter $\mathsf{\omega }$ is used to characterize the underlying surface and climate characteristics of different basins. However, most studies only use factors such as the normalized difference vegetation index (NDVI), which represents the greenness of vegetation, to quantify the relationship between $\mathsf{\omega }$ and the underlying surface, thereby neglecting richer vegetation information. In this study, we used long time-series multi-source remote sensing data from 1988 to 2015 and stepwise regression to establish dynamic estimation models of parameter $\mathsf{\omega }$ for three subwatersheds of the upper Yellow River and quantify the contribution of underlying surface factors and climate factors to this parameter. In particular, vegetation optical depth (VOD) was introduced to represent plant biomass to improve the applicability of the model. The results showed that the dynamic estimation models of parameter $\mathsf{\omega }$ established for the three subwatersheds were reasonable (R² = 0.60, 0.80, and 0.40), and parameter $\mathsf{\omega }$ was significantly correlated with the VOD and standardized precipitation evapotranspiration index (SPEI) in all watersheds. The dominant factors affecting the parameter in the different subwatersheds also differed, with underlying surface factors mainly affecting the parameter in the watershed before Longyang Gorge (BLG) (contributing 64% to 76%) and the watershed from Lanzhou to Hekou Town (LHT) (contributing 63% to 83%) and climate factors mainly affecting the parameter in the watershed from Longyang Gorge to Lanzhou (LGL) (contributing 75% to 93%). The results of this study reveal the changing mechanism of evapotranspiration in the Yellow River watershed and provide an important scientific basis for regional water balance assessment, global change response, and sustainable development. Full article

Using multi-source observation data including automatic stations, radar, satellite, new detection equipment, and the Fifth Generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA-5) data, along with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) platform, an analysis was conducted on a rainstorm process that occurred in Nanjing on 15 June 2020, with the aim of providing reference for future urban flood control planning and heavy rainfall forecasting and early warning. The results showed that this rainstorm process was generated under the background of an eastward-moving northeast cold vortex and a southward retreat of the Western Pacific Subtropical High. Intense precipitation occurred near the region of large top brightness temperature (TBB) gradient values or the center of low TBB values on the northern side of the convective cloud cluster. During the heavy precipitation period, the differential propagation phase shift rate (K_DP), differential reflectivity factor (Z_DR), and zero-lag correlation coefficient (ρ_HV) detected by the S-band dual-polarization radar all increased significantly. The vertical structure of the wind field detected by the wind profile radar provided a good indication of changes in precipitation intensity, showing a strong correspondence between the timing of maximum precipitation and the intrusion of upper-level cold air. The abrupt increase in the integrated liquid water content observed by the microwave radiometer can serve as an important indicator of the onset of stronger precipitation. During the Meiyu season in Nanjing, convective precipitation was mainly composed of small to medium raindrops with diameters less than 3 mm, with falling velocities of raindrops mainly clustering between 2 and 6 m·s⁻¹. The rainstorm process featured four water vapor transport channels: the mid-latitude westerly channel, the Indian Ocean channel, the South China Sea channel, and the Pacific Ocean channel. During heavy rainfall, the Pacific Ocean water vapor channel was the main channel at the middle and lower levels, while the South China Sea water vapor channel was the main channel at the upper level, both accounting for a trajectory proportion of 34.2%. Full article

Expressway systems play a vital role in facilitating intercity travels for both passengers and freights, which are also a significant source of vehicle emissions within the transportation sector. This study investigates vehicle emissions from expressway systems using the COPERT model to develop multi-year emission inventories for different pollutants, covering the past and future trends from 2005 to 2030. Thereinto, an integrated SARIMA-SVR method is designed to portray the temporal variation of vehicle population, and the possible future trends of expressway vehicle emissions are predicted through policy scenario analysis. The Jiang–Zhe–Hu Region of China is taken as the case study to analyze emission control in expressway systems. The results indicate that (1) carbon monoxide (CO) and volatile organic compounds (VOCs) present a general upward trend primarily originating from passenger vehicles, while nitrogen oxides (NOx) and inhalable particles (PM) display a slowing upward trend with fluctuations mainly sourcing from freight vehicles; (2) vehicle population constraint is an effective emission control policy, but upgrading the medium- and long-haul transportation structure is necessary to meet the continuous growth of intercity trips. Expressway vehicle emission reduction effectiveness can be further enhanced by curtailing the update frequency of emission standards, along with the scrapping of high-emission vehicles. Full article

When analyzing microscopic time-lapse observations, frame alignment is an essential task to visually understand the morphological and translation dynamics of cells and tissue. While in traditional single-sample microscopy, the region of interest (RoI) is fixed, multi-sample microscopy often uses a single microscope that scans multiple samples over a long period of time by laterally relocating the sample stage. Hence, the relocation of the optics induces a statistical RoI offset and can introduce jitter as well as drift, which results in a misaligned RoI for each sample’s time-lapse observation (stage drift). We introduce a robust approach to automatically align all frames within a time-lapse observation and compensate for frame drift. In this study, we present a sub-pixel precise alignment approach based on recurrent all-pairs field transforms (RAFT); a deep network architecture for optical flow. We show that the RAFT model pre-trained on the Sintel dataset performed with near perfect precision for registration tasks on a set of ten contextually unrelated time-lapse observations containing 250 frames each. Our approach is robust for elastically undistorted and translation displaced (x,y) microscopic time-lapse observations and was tested on multiple samples with varying cell density, obtained using different devices. The approach only performed well for registration and not for tracking of the individual image components like cells and contaminants. We provide an open-source command-line application that corrects for stage drift and jitter. Full article

Timely and accurate predictions of winter wheat yields are key to ensuring food security. In this research, winter wheat yield prediction models for six provinces were established using a random forest (RF) model. Two methods were employed to analyze feature variables. RF partial dependence plots were generated to demonstrate the nonlinear relationships between the feature variables and yield, and bivariate Moran’s I was considered to identify the spatial associations between variables. Results showed that when environmental data from key growth periods were used for prediction model establishment, the root mean square error (RMSE) varied between 200 and 700 kg/ha, and the coefficient of determination (R²) exceeded 0.5. Feature variable analysis results indicated that the longitude, latitude, topography and normalized difference vegetation index (NDVI) were important variables. Below the threshold, the yield gradually increased with increasing NDVI. Bivariate Moran’s I results showed that there was zonal distribution of meteorological elements. Within a large spatial range, the change in environmental variables due to the latitude and longitude should be accounted for in modeling, but the influence of collinearity between the feature variables should be eliminated via variable importance analysis. Full article