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The creep characteristics of sliding zones strongly influence slope deformation and long-term stability, as well as the occurrence of landslide catastrophes. In this paper, large-scale triaxial creep tests were performed on the strongly weathered argillaceous sandstone sliding zone of the Huaipa landslide in the Henan Province, China, to study its creep characteristics and long-term strength in natural and saturated states. Three-dimensional numerical simulations were conducted to analyze the deformation creep law and catastrophic evolution mechanism of the slope after excavation and rainfall. The results show that the sliding zone underwent appreciable creep deformation prior to failure, and that the progression of specimen damage with an increasing stress level followed decay creep → steady creep → accelerated creep. The stress level played a decisive role in the creep deformation, with higher stress levels resulting in higher instantaneous displacement, creep displacement, and longer times required to reach steady creep. The stress level also determined the specimen's creep stage. When the stress level was low, the adjustment of the specimen's internal structure was dominated by air space compression and particle movement, whereas particle fragmentation mostly occurred at high stress levels. The long-term rock strength was approximately 62–66% of the instantaneous strength, the internal friction angle decreased by approximately 8° relative to the instantaneous strength, and the cohesion decreased by approximately 30%. The slope foot unloaded and deformed owing to the excavation of a bauxite mine at its front edge, after which the slope deformed via creep. The landslide disaster occurred when the deformation was significantly accelerated and the slope started to slide as a whole once the sliding zone became water saturated owing to continuous rainfall. The simulation results indicate that the landslide can be divided into a front edge bulging zone, central sliding zone, and trailing edge tension zone, which provides valuable insight on the creep deformation evolution process and the disaster mechanism of the landslide under the action of front edge excavation and rainfall. [ABSTRACT FROM AUTHOR]

Emergency management synergy capability is not only a "touchstone" to measure the operation effect of the emergency system of coal mine enterprises, it is an important symbol to reflect its level. In order to improve the level of emergency management in coal mines based on the PPRR theory of crisis management cycle, in this paper a hierarchical evaluation index system is constructed based on the emergency management process. A quantitative evaluation model of emergency synergy capacity is proposes based on the entropy–weighted elemental topology method to conduct evaluation and model validation for the case of J coal mine in Henan Province. The results show that the overall evaluation of the emergency management synergy capability of J Coal Mine is at a "good" level, with the emergency prevention synergy capability, emergency preparedness synergy capability, and recovery and reconstruction synergy capability at a "good" level and the emergency response synergy capability is at a "average" level. This indicates that the evaluation model is consistent with the current development of coal mining enterprises and has universal applicability. Therefore, this research can provide decision-making support for emergency management synergistic capacity building of coal mining enterprises to enhance the inherent driving force behind the early completion of the dual carbon task in the coal mining industry. [ABSTRACT FROM AUTHOR]

In view of the present situation of "learning difficulty" in health statistics, this paper proposes a video visualization technology based on the convolutional neural network, which updates parameters by calculating the gradient of loss function to obtain accurate or nearly accurate loss function. Taking the students from 2014 to 2017 in a university in Henan as the research object, this paper analyzes the video visualization technology and its application effect on the teaching of college students' health statistics from the aspects of students' course awareness, learning behavior, communication between teachers and students, knowledge mastery, and course satisfaction. The results show that the external model load difference between each explicit variable and latent variable is statistically significant. Learning behavior and communication between teachers and students have a direct impact on the mastery of knowledge, and the degree of influence from high to low is as follows: learning behavior and communication between teachers and students. The teaching effect model of health statistics based on video visualization technology of the convolutional neural network has certain practicability. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Straw burning is one of the important causes of environmental pollution in rural China. As an important green production technology, straw returning is beneficial to the improvement of rural environment and the sustainable development of agriculture. Based on the improved planned behavior theory, taking the survey data of 788 farmers in Shandong, Henan, Hubei, and Hunan provinces as samples, this paper uses a multi-group structural equation model to explore the driving mechanism of subjective cognition on the adoption behavior of farmers’ straw returning technology. The results show that behavioral attitude, subjective norm, and perceived behavioral control, which represent subjective cognition, all have significant driving effects on farmers’ intention to adopt straw returning technology. Behavioral intention plays a mediating role in the process of subjective cognition driving farmers’ adoption behavior of straw returning technology. Government support has a moderating role in the path from farmers’ behavioral intention to behavioral response. The subjective cognition of different types of farmers has a significant driving effect on the adoption intention of straw returning technology, but the driving strength weakens with the increase of the degree of farmers’ concurrent occupation. This study provides guidance for improving the government’s straw returning policy and regulating straw returning behavior. [ABSTRACT FROM AUTHOR]

Introduction: The impact of farm machinery outsourcing services (FMOS) on grain production has been extensively studied in the literature. However, whether FMOS would adjust cropping structures and ensure food security is little known. To address this research gap, we analyzed the impact of FMOS on the cropping structure adjustment and grain production of farmers. Methods: We estimate the impact of FMOS on grain production by using data collected from a survey of 3,863 wheat farmers in China. We employ the Extended Regression Model (ERM) to address selectivity bias. Results and discussion: The empirical results show that FMOS can adjust the cropping structure and increase the proportion of household food cultivation. Among all segments of FMOS, fertilizer application services drive the increase in grain acreage more significantly. We also find that large-scale households prefer to self-purchase farm machinery rather than FMOS, leading to an insignificant impact of FMOS on cropping structure. Therefore, in the process of promoting the development of FMOS, we should focus on the coordinated development of various types of FMOS, strengthen the popularization and application of fertilization services, and formulate a differentiated subsidy policy for heterogeneous farmers in terms of scale to better play the role of agricultural machinery in promoting grain production. [ABSTRACT FROM AUTHOR]

Although vegetation index time series from optical images are widely used for crop mapping, it remains difficult to obtain sufficient time-series data because of satellite revisit time and weather in some areas. To address this situation, this paper considered Wen County, Henan Province, Central China as the research area and fused multi-source features such as backscatter coefficient, vegetation index, and time series based on Sentinel-1 and -2 data to identify crops. Through comparative experiments, this paper studied the feasibility of identifying crops with multi-temporal data and fused data. The results showed that the accuracy of multi-temporal Sentinel-2 data increased by 9.2% compared with single-temporal Sentinel-2 data, and the accuracy of multi-temporal fusion data improved by 17.1% and 2.9%, respectively, compared with multi-temporal Sentinel-1 and Sentinel-2 data. Multi-temporal data well-characterizes the phenological stages of crop growth, thereby improving the classification accuracy. The fusion of Sentinel-1 synthetic aperture radar data and Sentinel-2 optical data provide sufficient time-series data for crop identification. This research can provide a reference for crop recognition in precision agriculture. [ABSTRACT FROM AUTHOR]

Estimating carbon emissions and assessing their contribution are critical steps toward China's objective of reaching a "carbon peak" in 2030 and "carbon neutrality" in 2060. This paper selects relevant statistical data on carbon emissions from 2000 to 2018, combines the emission coefficient method and the Logarithmic Mean Divisia Index model (LMDI) to calculate carbon emissions, and analyses the driving force of carbon emission growth using Henan Province as a case study. Based on the partial least squares regression analysis model (PLS), the contributions of inter-provincial factors of carbon emission are analyzed. Finally, a county-level downscaling estimation model of carbon emission is further formulated to analyze the temporal and spatial distribution of carbon emissions and their evolution. The research results show that: 1) The effect of energy intensity is responsible for 82 percent of the increase in carbon emissions, whereas the effect of industrial structure is responsible for -8 percent of the increase in carbon emissions. 2) The proportion of secondary industry and energy intensity, which are 1.64 and 0.82, respectively, have the most evident explanatory effect on total carbon emissions; 3). Carbon emissions vary widely among counties, with high emissions in the central and northern regions and low emissions in the southern. However, their carbon emissions have constantly decreased over time. 4) The number of high-emission counties, their carbon emissions, and the degree of their discrepancies are gradually reduced. The findings serve as a foundation for relevant agencies to gain a macro-level understanding of the industrial landscape and to investigate the feasibility of carbon emission reduction programs. [ABSTRACT FROM AUTHOR]

Analyzing the working conditions of a dam using safety monitoring indices (SMIs) is a relatively intuitive and effective method for dam safety evaluation. Therefore, a reasonable and accurate method for determining the SMIs of a dam is of vital importance for dam safety assessment. However, the current methods for determining the SMIs of dams, especially roller-compacted concrete (RCC) dams, have many shortcomings, such as ignoring the construction process of the dam, the coupling effect among multiple physical fields, etc. In this paper, a novel SMI determination method considering the seepage–stress coupling effects was proposed for RCC dams with the assistance of a constructed seepage and stress coupling model so as to address the deficiency of existing RCC dams in determining SMIs. The coupled mathematical model was developed in COMSOL Multiphysics to establish a finite element analysis model of an RCC gravity dam in Henan Province, China. Moreover, the seepage anisotropy of the RCC construction layers was also considered in the model. Finally, the seepage, stress, and deformation characteristics of the RCC dam were analyzed based on the model, and the seepage and deformation SMIs of the dam were determined and compared with traditional methods. The results show that seepage, stress, and displacement fields are distributed similarly for both coupled and uncoupled models. However, in contrast to the uncoupled model, the hydraulic head contour distribution is more dispersed in the coupled model. Additionally, the stress and displacement simulated by the coupled model increase at different rates, with a more pronounced stress concentration near the dam heel. Comparing the seepage and stress SMIs of RCC dam obtained from different methods, it was found that the indices of dam seepage discharge and crest displacement that are calculated by considering the seepage–stress coupling effect and anisotropic characteristics of RCC construction layers are 34.78% and 31.98% lower than results obtained by ignoring these two effects, respectively. Therefore, it is crucial to consider the seepage–stress coupling effect and the anisotropic characteristics of RCC when determining the SMIs for RCC dams. [ABSTRACT FROM AUTHOR]

Water network construction is one of the important ways to solve complex water problems at present. It is crucial for the optimal allocation of water resources, flood control, disaster reduction, protection of water ecology, water security, and sustainable urban development. Accordingly, this study formulates an index system for assessing the efficacy of water network construction based on the Driving Force–Pressure–State–Influence–Response (DPSIR) model, taking into account the four dimensions of optimal allocation of water resources, flood control and disaster reduction in river basins, protection of water ecosystems, and intelligent water network management. The proposed index system comprises four key aspects, which are utilized to evaluate the effectiveness of water network construction efforts. Then, the game-weighting method and the matter-element extension method improved by the cloud theory established an evaluation model to evaluate and compare the water network construction effects of the two cities in Henan Province. Finally, the GM (1,1) model was used to evaluate the water network construction effects, and future trends were predicted. The results show the following: (1) On the whole, the effect of water network construction in the two cities is constantly improving; (2) There has been a significant improvement in the intelligent management of water networks. The main reason for this result is that the "Internet +" has promoted the intelligent construction of water networks; (3) The water ecological environment, flood control, and drainage capabilities continued to improve, which has largely guaranteed the basic security bottom line of urban development space; (4) The advancement and utilization of water resources has undergone gradual improvements over time, with key impact metrics centered on water supply safety factors and the development and utilization of water resources. As water supply sources continue to diversify, it is expected that the aforementioned situation will be ameliorated in the future; (5) The predicted value shows that the water network construction of the two cities can basically meet the planned value of each index when the water network construction reaches the planning level. This paper provides help to promote the sustainable use of water resources and ensure the sustainable development of cities. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality, the phase-out of coal from the energy structure has resulted in numerous old coal mines that possess abundant underground space resources suitable for underground pumped hydroelectric energy storage (UPHES). Site selection and estimation of potential are critical to the planning and implementation of UPHES in old coal mines. This paper introduces a two-step site selection concept, including a screening assessment followed by a comprehensive assessment, to determine suitable locations for UPHES. The screening indicators in the screening assessment comprise geological features, mine water disasters, and minimum installed capacity, while the analytic hierarchy process (AHP) is applied in the comprehensive assessment. Additionally, coal mines in Henan Province are preliminarily screened through the screening assessment and the potential for UPHES is thoroughly investigated. The estimated volume of the drifts and shafts in old coal mines is approximately 1.35 × 107 m3, while in producing coal mines, it is around 2.96 × 107 m3. Furthermore, the corresponding annual potential for UPHES is 1468.9 GWh and 3226.3 GWh, respectively. By consuming surplus wind and solar power, UPHES is able to reduce 4.68 × 105 tonnes of carbon dioxide (CO2) emissions. The study provides preliminary guidance for policy-makers in developing UPHES in old coal mines. [ABSTRACT FROM AUTHOR]

Copyright of Coal Geology & Exploration is the property of Xian Research Institute of China Coal Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Regional land-use change is the leading cause of ecosystem carbon stock change; it is essential to investigate the response of LUCC to carbon stock to achieve the strategic goal of "double carbon" in a region. This paper proposes a residual network algorithm, the Residual Multi-module Fusion Network (R-MFNet), to address the problems of blurred feature boundary information, low classification accuracy, and high noise, which are often encountered in traditional classification methods. The network algorithm uses an R-ASPP module to expand the receptive field of the feature map to extract sufficient and multi-scale target features; it uses the attention mechanism to assign weights to the multi-scale information of each channel and space. It can fully preserve the remote sensing image features extracted by the convolutional layer through the residual connection. Using this classification network method, the classification of three Landsat-TM/OLI images of Zhengzhou City (the capital of Henan Province) from 2001 to 2020 was realized (the years that the three images were taken are 2001, 2009, and 2020). Compared with SVM, 2D-CNN, and deep residual networks (ResNet), the overall accuracy of the test dataset is increased by 10.07%, 3.96%, and 1.33%, respectively. The classification achieved using this method is closer to the real land surface, and its accuracy is higher than that of the finished product data obtained using the traditional classification method, providing high-precision land-use classification data for the subsequent carbon storage estimation research. Based on the land-use classification data and the carbon density data corrected by meteorological data (temperature and precipitation data), the InVEST model is used to analyze the land-use change and its impact on carbon storage in the region. The results showed that, from 2001 to 2020, the carbon stock in the study area showed a downward trend, with a total decrease of 1.48 × 10 7 t. Over the course of this 19-year period, the farmland area in Zhengzhou decreased by 1101.72 km 2 , and the built land area increased sharply by 936.16 km 2 . The area of land transfer accounted for 29.26% of the total area of Zhengzhou City from 2001 to 2009, and 31.20% from 2009 to 2020. The conversion of farmland to built land is the primary type of land transfer and the most important reason for decreasing carbon stock. The research results can provide support, in the form of scientific data, for land-use management decisions and carbon storage function protections in Zhengzhou and other cities around the world undergoing rapid urbanization. [ABSTRACT FROM AUTHOR]

In recent years, the survival and development of traditional villages in China have been serious challenges. Rural tourism is regarded as an important way to solve rural problems, and the combination of rural culture and tourism has become a new power point for rural development. Therefore, it is necessary to explore the spatial distribution structure between traditional villages and rural tourism. In this paper, rural tourism was represented by the rural tourism characteristic village (RTCV), and Henan Province, China, was taken as a study area to analyze the distribution pattern and spatial correlation of rural tourism and traditional village (TV) and discuss the relationship between the spatial correlation and regional natural environment and socioeconomic factors. The results show that the coupling of the spatial correlation between RTCVs and TVs in Henan was clear. They could be divided into 5 regions based on geographical factors. In addition, the research summarized 4 typical spatial structures between TVs and RTCVs in Henan based on the regional symbiosis theory, and the spatial pattern formation mechanism of TVs and RTCVs was discussed based on three driving mechanisms. The spatial structure of the two can provide reference value for other developing countries and regions to achieve sustainable rural development. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The quality of cultivated land determines the production capacity of cultivated land and the level of regional development, and also directly affects the food security and ecological safety of the country. This paper starts from the perspective of spatial pattern of cultivated land quality and uses spatial autocorrelation analysis to study the spatial aggregation characteristics and differences of cultivated land quality in Henan Province at the county level scale, and also uses bivariate spatial autocorrelation to analyze the influence of neighboring influences on the quality of cultivated land in the target area. The spatial autoregressive model was used to further analyze the driving factors affecting the quality of cultivated land, and the influence of cultivated land area index was coupled in the process of rating analysis, which was finally used as a basis to propose more precise measures for the protection of cultivated land zoning. The results show that: (1) The quality of cultivated land in Henan Province has a strong spatial correlation (global Moran's I≈0.710) and shows an obvious aggregation pattern in spatial distribution; positive correlation types (high-high and low-low) are concentrated in north-central and western mountainous areas of Henan Province, respectively; negative correlation types are discrete. The negative correlation types are distributed in a discrete manner. (2) The bivariate spatial autocorrelation results show that Slope (Moran's I≈-0.505), Irrigation guarantee rate (IGR, 0.354), Urbanization rate (-0.255), Total agricultural machinery power (TAMP, 0.331) and Pesticide use (0.214) are the main influencing factors. (3) According to the absolute values of the regression coefficients, it can be seen that the magnitude of the influence of different factors on the quality of cultivated land is: Slope (0.089) >IGR (0.025) > Urbanization rate (0.002) > TAMP (0.001) > Pesticide use (1.96e-006). (4) Based on the spatial pattern presented by the spatial autocorrelation results, we proposed corresponding protection zoning measures to provide more scientific reference decisions and technical support for the implementation of refined cultivated land management in Henan Province. [ABSTRACT FROM AUTHOR]

The traditional design flood estimation method assumes that the flood peak and the flood volume are at the same frequency, without considering the correlation between the two flood characteristics. Furthermore, when the design flood region composition under a specific return period is estimated, although the traditional method is from the most unfavorable point of view, it is impossible to quantitatively describe the correlation between the floods in each subarea. Therefore, in this paper, Copula function is used to deduce the design flood peak and flood volume at different frequencies which consider the combined effects of flood peak and flood volume, and then obtains the design flood process at different frequencies. The marginal distribution of flood components in each area is established and the most suitable Copula function between components in each area and design section is preferred which consider the spatial correlation between each flood zone and Huayuankou section, and then explore the most likely design flood region composition. It shows that the design results obtained by considering the correlation between flood elements in this study are slightly higher than those deduced by traditional methods under the same return period. The method in this paper can qualitatively and quantitatively describe the design flood region composition in the study area so as to obtain the design flood results that consider both the correlation of flood characteristics and spatial correlation at the same time, which are more objective and more consistent with the actual situation of design flood region composition in the basin. [ABSTRACT FROM AUTHOR]

Based on the MEPDG method, the operation process of MEPDG was analyzed and the MEPDG correction method applied to the remaining life prediction of airport pavement was obtained. According to the theory of structural reliability, the performance function of airport pavement was obtained based on the limit state equation represented by flexural stress. Considering the characteristics of airport cement concrete pavement design, the calculation formula of the number of allowable load actions was obtained based on reliability by NCHRP126 fatigue equation without considering the temperature stress when the flexural fatigue strength of pavement plate cement concrete was less than 1.25 times of the design strength. Based on the actual situation of local civil airport runways in Henan Province, the proposed MEPDG correction method was used to analyze the flexural stress of the actual operating airport runway pavement at 95% reliability level based on the mechanical numerical model of airport runway, and the number of allowable load actions of three aircraft models was obtained. Given the impact of pass-to-coverage ratio P/C, the cumulative damage factor CDF of the major aircraft models was calculated; the annual average growth rate of different aircraft models in the airport pavement evaluation stage was obtained based on the trend extension method. According to the predicted average annual cumulative damage, the remaining life of pavement was predicted. Compared with the actual conditions of the airport, the remaining life predicted in this paper was consistent with the actual life, which verifies the effect of the prediction of the remaining life of airport runway considering the impact of reliability and damage accumulation. [ABSTRACT FROM AUTHOR]

As new urbanization constantly develops, the county economy plays a vital role between country and city, and high economic resilience is necessary to support and safeguard for smooth functioning of the county development. The paper constructs the index system of county economic resilience in Henan Province from three dimensions: risk resistance ability, self-stability, and sustainable development ability, and to empirically analyze the economic resilience of 104 counties and cities in the province from 2013 to 2020 using the entropy weight-normal cloud model. The results show that Henan counties' economic resilience increases slowly over time and decreases spatially from the center to the surrounding region, with Zhengzhou as the main center and Luoyang and Sanmenxia as the subcenter; risk resistance ability and self-stabilization are more influential than the sustainable development ability; the key indicators affecting economic resilience are GDP per capita, retail sales of social consumer goods per capita, financial self-sufficiency rate, education expenditure per capita, and population mobility. Therefore, the counties in Henan should find the right positioning to improve economic resilience; central cities such as Zhengzhou and Luoyang should play their strong functions, while strengthening support for peripheral counties. [ABSTRACT FROM AUTHOR]

Crop-type mapping is the foundation of grain security and digital agricultural management. Accuracy, efficiency and large-scale scene consistency are required to perform crop classification from remote sensing images. Many current remote-sensing crop extraction methods based on deep learning cannot account for adaptation effects in large-scale, complex scenes. Therefore, this study proposes a novel adaptive feature-fusion network for crop classification using single-temporal Sentinel-2 images. The selective patch module implemented in the network can adaptively integrate the features of different patch sizes to assess complex scenes better. TabNet was used simultaneously to extract spectral information from the center pixels of the patches. Multitask learning was used to supervise the extraction process to improve the weight of the spectral characteristics while mitigating the negative impact of a small sample size. In the network, superpixel optimization was applied to post-process the classification results to improve the crop edges. By conducting the crop classification of peanut, rice, and corn based on Sentinel-2 images in 2022 in Henan Province, China, the novel method proposed in this paper was more accurate, indicated by an F1 score of 96.53%, than other mainstream methods. This indicates our model's potential for application in crop classification in large scenes. [ABSTRACT FROM AUTHOR]

Social media has become an essential channel for the public to create and obtain information during emergencies. As the theme of public concern for emergencies changes over time, there is a lack of research on its dynamic evolution from its latent stage. This paper selects the Henan rainstorm event as a case study and extracts the theme characteristics by combining the life cycle theory and Latent Dirichlet Allocation (LDA) model. It integrates the Term Frequency–Inverse Document Frequency (TF-IDF) and Pointwise Mutual Information (PMI) algorithms as the theme-coding data source to build a dynamic theme propagation model for emergencies. Our research results showed that the theme coding effectively verified the assumption of latent development trends. The dynamic theme model could reveal the theme characteristics of different time series stages of emergencies, analyze the law of the theme evolution of the network's public opinion, and provide practical and theoretical insights for the emergency management of urban cities. [ABSTRACT FROM AUTHOR]

UAV (unmanned aerial vehicle) remote sensing provides the feasibility of high-throughput phenotype nondestructive acquisition at the field scale. However, accurate remote sensing of crop physicochemical parameters from UAV optical measurements still needs to be further studied. For this purpose, we put forward a crop phenotype inversion framework based on the optimal estimation (OE) theory in this paper, originating from UAV low-altitude hyperspectral/multispectral data. The newly developed unified linearized vector radiative transfer model (UNL-VRTM), combined with the classical PROSAIL model, is used as the forward model, and the forward model was verified by the wheat canopy reflectance data, collected using the FieldSpec Handheld in Qi County, Henan Province. To test the self-consistency of the OE-based framework, we conducted forward simulations for the UAV multispectral sensors (DJI P4 Multispectral) with different observation geometries and aerosol loadings, and a total of 801 sets of validation data were obtained. In addition, parameter sensitivity analysis and information content analysis were performed to determine the contribution of crop parameters to the UAV measurements. Results showed that: (1) the forward model has a strong coupling between vegetation canopy and atmosphere environment, and the modeling process is reasonable. (2) The OE-based inversion framework can make full use of the available radiometric spectral information and had good convergence and self-consistency. (3) The UAV multispectral observations can support the synchronous retrieval of LAI (leaf area index) and Cab (chlorophyll a and b content) based on the proposed algorithm. The proposed inversion framework is expected to be a new way for phenotypic parameter extraction of crops in field environments and had some potential and feasibility for UAV remote sensing. [ABSTRACT FROM AUTHOR]

Flood hazards resulting from short-term severe precipitation have caused serious social and economic losses and have posed extraordinary threats to the safety of lives and property. Vulnerability, which reflects the degree of the adverse impact of flooding on a city, the sensitivity of the environment, and the extent to which rescues are possible during flooding, is one of the significant factors of the disaster risk assessment. Because of this, this paper proposes an Environmental Vulnerability Analysis Model (EVAM), based on comprehensively evaluating multi-source remote sensing data. The EVAM includes a two-stage, short-term flood vulnerability assessment. In the first stage, the flood's areal extension and land-use classification are extracted, based on the U-NET++ network, using multi-source satellite remote sensing images. The results from the first stage are used in the second stage of vulnerability assessment. In the second stage, combining multi-source data with associated feature extraction results establishes the Exposure–Sensitivity–Adaptive capacity framework. The short-term flood vulnerability index is leveraged through the analytic hierarchy process (AHP) and the entropy method is calculated for an environmental vulnerability evaluation. This novel proposed framework for short-term flood vulnerability evaluation is demonstrated for the Henan Province. The experimental results show that the proportion of vulnerable cities in the Henan Province ranging from high to low is 22.22%, 22.22%, 38.89%, and 16.67%, respectively. The relevant conclusions can provide a scientific basis for regional flood control and risk management as well as corresponding data support for post-disaster reconstruction in disaster regions. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Rock & Mineral Analysis is the property of Editorial Board of Rock & Mineral Analysis and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The sustainable development of the Yellow River Basin (YRB) is regarded as a national strategy for China. Previous literature has focused on the green efficiency measurement of YRB, ignoring its evolution process and influential mechanism. This paper tries to disclose the spatial-temporal evolution of green efficiency and its influential mechanism of the YRB region by proposing a novel integrated DEA-Tobit model to fill the gap. Based on the development path of the YRB region, the multi-period two-stage DEA model is adopted to evaluate the green development efficiency (GDE) from provincial and urban dimensions. In addition, the panel Tobit model is developed to investigate the influential factors of the GDE for the YRB region. The GDE in the YRB region shows an unbalanced state where the downstream is best, followed by the middle and upstream. The unbalanced development also exists within the province. Both Henan and Shandong Province achieved the optimal value, while cities in these two provinces show lower green efficiency. The results also show that economic development, technological innovation and foreign capital utilization obviously affect the GDE of the YRB region positively, while industrial structure, urbanization levels and environmental regulation have negative effects. [ABSTRACT FROM AUTHOR]

Although there is a consensus on religious revival in China, it must be noted that popular religion and institutional religions such as Buddhism and Daoism adopt different strategies to survive the state's regulations. Many temples that used to facilitate the worship of local deities have to establish some form of intangible cultural heritage or emphasize the deity's history and folklore to de-religionize. During this process, a temple may earn its lawful place to survive, but risks its communality in the village. Based on studies of rural and urban temples in Henan and Shandong provinces, in this paper, I attempt to understand people's religiosity and how they conduct the human–deity exchange under social transformation. Popular religion is characterized by the pursuit of efficacy and its embeddedness in rural life. The traditional binary exchange with deities could be used to maintain a relationship with deities as well as offer urgent solutions, while three-party chains of exchange not only constitute a religious gift economy but also offer a religious agent to seek answers. I argue that temples are marginalized and excluded from village life, so people need to find new means by which to continue their religious practices beyond what the state sponsors, and this has led to the flowing of sacred places. [ABSTRACT FROM AUTHOR]

A method based on capacitively coupled contactless conductivity detection (C4D), which has been proven effective for the rapid detection of available soil potassium content, was firstly proposed to apply to soil nutrient detection. By combining a detection signal spectrum analysis, geographic information system (GIS) data, and a cluster analysis, a soil nutrient management system to match the detection device was developed. This system included six modules: soil sample information management, electrophoresis analysis, quantitative calculation, nutrient result viewing, cluster analysis, and nutrient distribution map generation. The soil samples, which were collected from an experimental field in Xuchang City of Henan Province, were analyzed using the C4D and flame photometer methods. The results showed that the detection results for the soil samples obtained via the two methods were in good agreement. C4D technology was feasible for the detection of the soil available nutrients and had the advantages of a high timeliness, low sample volume, and low pollution. The soil nutrient management system adopted the hierarchical clustering method to classify the grid cells of the experimental field according to the nutrient detection results. A soil nutrient distribution map displayed the spatial difference in nutrients. This paper provides a systematic solution for soil nutrient zone management that includes nutrient detection, signal analysis, data management for the nutrient zone, and field nutrient distribution map generation to support decision making in variable fertilization. [ABSTRACT FROM AUTHOR]

Air pollution is the result of comprehensive evolution of a dynamic and complex system composed of emission sources, topography, meteorology and other environmental factors. The establishment of spatiotemporal evolution model is of great significance for the study of air pollution mechanism, trend prediction, identification of pollution sources and pollution control. In this paper, the air pollution system is described based on cellular automata and restricted agents, and a Swarm Intelligence based Air Pollution SpatioTemporal Evolution (SI-APSTE) model is constructed. Then the spatiotemporal evolution analysis method of air pollution is studied. Taking Henan Province before and after COVID-19 pandemic as an example, the NO2 products of TROPOMI and OMI were analysed based on SI-APSTE model. The tropospheric NO2 Vertical Column Densities (VCDs) distribution characteristics of spatiotemporal variation of Henan province before COVID-19 pandemic were studied. Then the tropospheric NO2 VCDs of TROPOMI was used to study the pandemic period, month-on-month and year-on-year in 18 urban areas of Henan Province. The results show that SI-APSTE model can effectively analyse the spatiotemporal evolution of air pollution by using environmental big data and swarm intelligence, and also can establish a theoretical basis for pollution source identification and trend prediction. [ABSTRACT FROM AUTHOR]

In deep mines, since the broken surrounding rocks & high-stress level of a roadway being near a coal seam, the creep characteristics of surrounding rocks should be considered as the main influencing factor in the selection for the roadway's location of the lower coal seam. Both VI15 and VI16-17 coal seams of the Pingdingshan No. 4 Coal Mine, in China, Henan province, are close coal seams with a depth of around 900 m. According to the traditional formula calculation results, when the lower coal seam roadway is staggered 10 m to the upper coal seam goaf, the roadway pressure behaviour is significant, and the support becomes difficult. In this paper, the properties of surrounding rock were tested and the influence of lower coal seam on the stress state of surrounding rock is analysed by numerical simulation, and systematic analysis on the stress and creep characteristics of the surrounding rock of the mining roadway and its effects on the deformation is performed. The results demonstrated that the roadway's locations in the lower coal seam can be initially divided into three zones: the zone with accelerated creep, the transition creep zone and the insignificant creep zone. The authors believed that the roadway layout in an insignificant creep zone can achieve a better supporting effect. Based on the geological conditions of the roadway 23070 of the VI16-17 coal seam of the Pingdingshan No. 4 Coal Mine, combined with the above analysis, a reasonable location of roadway (internal offset of 30 m) was determined using numerical simulation method. The reliability of the research results is verified by field measurement. The above results can provide a reference for selecting the roadway's location under similar conditions. [ABSTRACT FROM AUTHOR]

With digital information technology based on limited data, disaster simulation review is an important guideline for analyzing disaster mechanisms, planning post-disaster reconstruction, and improving defense capability. Taking the "7.20" flash flood in the Wangzongdian river basin as a research area, a hydrological-hydrodynamic model was established using limited measured data. The results showed that the extreme rainstorm caused flooding in mountainous areas and the collapse of subgrade water damming, and the high-level flood quickly flowed into Wangzongdian Village in a short distance, which was the main cause of this serious disaster. Considering the collapse due to the congestion of the upstream bridge, the simulated flood flow in Wangzongdian Village reached 782 m3/s, which was basically consistent with the post-disaster survey results, with a relative error of only +8%. The modeling strategy proposed in this paper is applicable in the review of sudden heavy rainstorms and flash floods and can provide technical guidance for future flash flood simulation review analysis in other areas. [ABSTRACT FROM AUTHOR]

Unbalanced and inadequate development has led to challenges such as resource shortage, ecological fragility, and economic backwardness in the water-receiving area of Henan Province, which has hindered the high-quality development of the region. This research aims to construct a high-quality development regulation model. The single-indicator quantification–multi-indicator synthesis–multicriteria integration (SMI-P) method was used to evaluate the level of regional development; using the method of embedded system dynamics, the regulation model was constructed and applied. The results show that (1) from 2011 to 2020, the degree of regional high-quality development showed an increasing trend, rising from a low level (0.34) to a medium level (0.57), an increase of one level, but the level of high-quality development still has a lot of room for improvement and faces great challenges; (2) the development of a resource–ecology–economy–social system was in a state of non-harmonious balance, and the proportion of contributions of each system was very different, but the system was developing towards a state of harmony and balance; (3) based on the constructed high-quality development regulation model, the key constraints affecting the high-quality development of the Yellow River water supply area in Henan Province are per capita water consumption, per capita energy consumption, carbon emissions per capita, GDP per capita, etc. The model constructed in this paper can improve the quality development level through the application of examples. The high-quality development degree of the study area was increased from 0.57 to 0.8. [ABSTRACT FROM AUTHOR]

Near-zero carbon emission power (NZCEP) plants, consisting of gas-fired units; wind turbines; power-to-gas (P2G); and carbon capture, utilization and storage (CCUS) systems, have recently received a lot of attention due to their enormous benefits in reducing carbon emissions and increasing the consumption of renewable energy. However, a complex environment of interest and a combination of risks makes their development very slow. This paper establishes a risk analysis framework for NZCEP considering multi-stakeholder participation. Firstly, a synthetic risk factor system was constructed based on stakeholders' interests. Subsequently, interval type II trapezoidal fuzzy numbers were used and final weights were calculated from both subjective and objective aspects. Finally, we applied an acronym in Portuguese of the interactive and multi-criteria decision-making (TODIM) method to site selection to achieve a balance of interests of all stakeholders. In addition, a case study was conducted. The case result demonstrates that Zhengzhou in Henan Province is the best choice for a NZCEP power plant. A further finding is that government plays an important role in the development of NZCEP plants, with site selection results being the most sensitive to changes in the government's risk appetite. Moreover, human resources are an important factor in the siting of an NZCEP plant. [ABSTRACT FROM AUTHOR]

Ongoing environmental issues and degradation provoke the implementation of relevant incentives to overcome them without restrictions of economic growth. Considering the Chinese sustainable development policy, each province should provide the effective ecological regulations that consider the dynamic changes of the economic and ecological indicators of the province's development. In this case, the paper aims to analyze the relationship between economic growth and environmental quality. The object of the investigation is the Henan provinces of China from 1994 to 2020. The study applied a vector autoregression model between the one-way and two-way relationship analysis, Granger causality test, cointegration test, and impulse response function. The findings confirm that GDP growth causes exhaust gas production and that SO2 will also influence wastewater. The results of the co-consolidation analysis showed that if the production of industrial solid waste gas and SO2 volume increased by 1% each, GDP per capita would increase by 0.22% and 0.35%, respectively. The findings of the variance decomposition of the GDP per capita in the first phase are all due to their perturbation term. The other influencing factors have no influence. Over time, GDP per capita is less and less affected and significantly enhanced by wastewater, exhaust gas, and SO2. [ABSTRACT FROM AUTHOR]

Clarifying the influencing factors of energy consumption in underground production processes of coal mine is the premise and foundation for the coal mining industry to control the energy consumption and intensity to achieve the goal of carbon peak and carbon neutrality. This paper aims to investigate and compare the differences in energy consumption and carbon emissions between a mining‐separating‐backfilling integrated coal mine (MSBICM) and a traditional coal mine and explore the effects of the main production links underground on carbon emission intensity in coal mines. Hence, taking an MSBICM in Henan province as an example, this study constructed an energy consumption and carbon emission model of the mine using system dynamics (SD) method. Based on this model, the energy consumption of the main production logistics system and auxiliary production system in MSBICM was simulated and analyzed. In addition, this study made a comparative analysis of the energy consumption of the different production links in the two types of coal mines. The results showed that: (1) the comprehensive mechanized coal mining with solid filling system and ventilation system were the subsystems with the highest and lowest energy consumption in MSBICM respectively. (2) The influence rates of raw coal mining, gangue filling, coal‐gangue separating, and material transportation on carbon emission intensity in coal mine were 1.09%, 1.34%, 1.09%, and 5.13%, respectively. (3) Under the same production and filling targets, energy consumption of underground transportation systems in MSBICM was found to be 336.66 tons of standard coal less than that in traditional coal mine. This study has helped clarify the complex relationships among the factors that influence energy consumption in coal mines and provided a reference for implementing dual control of energy consumption to promote low‐carbon mining of coal resources. [ABSTRACT FROM AUTHOR]

Mitigating carbon emissions has become a pressing concern in the process of economic development across China due to China's key strategic goal of reaching peak carbon and carbon neutrality. Henan Province, which is located in the Central Plains, has less forest area and coverage than other areas of the nation, but consumes plenty of energy. Therefore, the quantification of Henan's potential carbon sink is crucial for the province's response to climate change due to the national commitment to carbon reduction targets. This research estimated the carbon sink of tree forest vegetation in Henan Province from 2019 to 2060 based on the CO2FIX model using data from the 9th Forest Inventory Report and the forest planning targets of Henan Province. The results show the following: (1) The carbon sink of existing arbor forests is mainly composed of ecological public welfare forests, and a small-year fluctuation in the carbon sink will result from the rotation of commercial forests. (2) The peak carbon sink years for existing forests and new afforestation are between the young and middle ages of the trees, and the peak of the carbon sink in Henan Province as a whole was in 2032. (3) More than 72.4% of the overall carbon sink in Henan Province's arbor forest vegetation comes from the above-ground portion. (4) The energy substitution effect of traditional and improved cookstoves is significantly enhanced during the main cutting period of the existing commercial arbor forest in Henan Province. [ABSTRACT FROM AUTHOR]

Ecological environment assessment, which forms the basis for the survival and development of human society, is a crucial measure for the sustainable development of society and economy. However, current quantitative assessment models such as EI, EQI, RSEI et al. are insufficient to meet the requirements of dynamic research in large areas, long time series and dense time intervals. Therefore, in this paper, we constructed the comprehensive ecological environment quality index model SCEQI that can meet these needs by applying the remote sensing big data as the data source. The SCEQI aggregated the ecological indices NDVI, NDBSI, Lst and Wet by full-sequence dynamic dimensionless, automated principal component analysis and multi-temporal average method. In order to verify the spatial and temporal accuracy of the model, we took Henan Province as an example to compare the result of SCEQI with that of EI, EQI, RSEI and proved that SCEQI performed better in both time and space. Also, we verified the superiority of time, space, and precision of SCEQI with profiles, samples, and cluster analysis. [ABSTRACT FROM AUTHOR]

Establishment of a watershed ecological compensation mechanism between multiple subjects is an effective means to realize the collaborative governance of water pollution and maintain the security of water ecology. This paper breaks through the conventional upstream and downstream perspectives of watershed ecological compensation design research and combines them with uncertainty factors. The watershed ecological compensation mechanism for the mainstream and branches was established based on the evolutionary game and the random process. Then, taking the midstream of the Yellow River as an example, some constraint conditions and influencing factors were explored. Results show that: (1) The branch government (i.e., the Shanxi provincial government) is the key to establishing an ecological compensation mechanism between the river mainstream and branches. (2) The proportion of pollution transferred by other branches, the initial probability and the random factors are the main factors affecting the decision-making of branch governments (Shanxi and Shaanxi provincial governments). (3) The compensation and reward of the mainstream government to the branch government and the compensation of the branch government to the mainstream government are the main factors affecting the decision-making of mainstream and branch governments (Shanxi–Henan provincial governments, Shaanxi–Henan provincial governments). The study may provide scientific guidance for the construction of a watershed ecological compensation mechanism between mainstream and multiple branches. [ABSTRACT FROM AUTHOR]

Carbon ecological compensation is essential to coordinate regional environmental protection, reduce the gap between the economic development of protected areas and beneficiary areas, and achieve carbon neutrality. This paper proposed a theoretical framework for ecological compensation using the theories of carbon balance, externality, ecosystem services, and carbon trading mechanisms. Based on the analysis of the ecological compensation priority sequence in Henan Province, the suppliers and consumers of carbon sequestration were identified, and cross-regional ecological compensation was realized through ecosystem services flow. The results showed that the carbon sequestration supply in Henan Province was characterized as being high in the west and low in the east, while the demand was the opposite. Affected by the suitable environmental conditions, many areas had an ecological surplus pattern, and the carbon sequestration supply was more significant than the demand. Central and south-western Henan Province were distinct ecological compensation payment areas and receiving areas, respectively. Nanyang, which had the largest carbon sequestration flow and the largest ecological contribution to other regions, received the highest ecological compensation fund of CNY 4.069 billion. This study can provide decision support for carbon ecological compensation in the context of carbon neutrality. [ABSTRACT FROM AUTHOR]

To overcome the limitations of long-term prediction of PM2.5 concentration, a multi-factor information flow causality analysis method is used to screen suitable meteorological and air pollutant-related factors and concatenate them with a PM2.5 sequence as the dataset. A modal decomposition algorithm is used as a module to be integrated into the autoformer (transformer improved with autocorrelation mechanism) model to improve it, and the modal autoformer (empirical modal decomposition combined with autoformer) is proposed. The constructed model decomposes the sequence into several components by using the modal decomposition module and uses the self-correlation mechanism and decomposition structure to decompose and extract features of different components at the time-feature level. Based on the matching method, the model is adjusted for different component features to improve the long-term prediction effect. The model is applied to three cities in Henan Province, Zhengzhou, Luoyang, and Zhumadian, as examples for experiments, and gated neural unit (GRU), informer, autoformer, and modal GRU (empirical modal decomposition combined with GRU model) are constructed for comparative verification. The results show that the modal autoformer can better cope with the complex characteristics of long-term prediction of the PM2.5 time series, has strong spatial adaptability and that its various indicators are optimal for the three cities, with R2 values being all above 0.96, where the highest is 0.987 in Zhengzhou; MAPE (Mean absolute percentage error) values all being less than 10, where the best is 7.602 in Zhumadian; and MAE (Mean absolute error) values all being less than 4. The prediction effect is stable enough, showing its feasibility and adaptability in long-term prediction. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As the domestic interprovincial migrants, Uygur traders have been engaged in the Hetian jade trade from Xinjiang Uygur Autonomous Region to the city of Nanyang in Henan Province. Having lived in the private rented houses around the market in the early days, they moved into the government-built public rental housing in 2017, an independently managed community. They have maintained their past residential pattern of living around the market, and gradually develop the community into an inter-embedded multi-ethnic community together with other ethnic groups. Through the history of the formation of the Uygur community in Nanyang Stone Town, this paper presents the process of interaction between the ethnic minority migrants and the local community, examines the responses and influence of the market, society, government, and individuals in this process, aiming to understand how the minority community was formed, to deepen understanding of the "inter-embedded multi-ethnic community", and, in turn, to promote research and reflection on the development of the ethnic community during urbanization in China. This study suggests that such communities surrounding the market are socially extended based on inter-embedded livelihood. The open national market is the core of the social structure of inter-embedded ethnic groups, and market exchange is one of the main relations generated in the current interactions between the ethnic groups. The government's efforts to build inter-embedded communities are conducive to transforming the relationships among ethnic groups from limited interaction to comprehensive and balanced development. Moreover, the improvement of common living environments and increase in exchanges are conducive to upgrading interactions between individuals to extensive and in-depth exchanges among different ethnic groups. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

At present, there is a huge gap between supply and demand of old-age services in rural areas of China. Developing rural mutual old-age services is of great significance to remedy the gap. Based on the survey data of 1200 rural residents in Hubei and Henan provinces, this paper adopts binary logistic regression model to analyze the influence of special trust and general trust on rural residents' willingness to participate in mutual care for the aged. The results show that both special trust and general trust have an impact on rural residents' willingness to participate in mutual support for the elderly, but the effect of special trust on rural residents' willingness to participate in mutual support for the elderly is not significant. General trust has a significant promoting effect on rural residents' willingness to participate in mutual care for the aged. Chinese rural residents' trust in village cadres has a significant promoting effect on their willingness to participate in mutual assistance for the aged. The trust of ordinary friends significantly inhibited their willingness to participate. The educational level, living style, and economic status of Chinese rural residents have a positive impact on their willingness to participate in mutual care for the aged. Age, marital status, health status, and intergenerational relationship are inversely correlated with willingness to participate. [ABSTRACT FROM AUTHOR]

Annual monitoring of the spatial distribution of cultivated land is important for maintaining the ecological environment, achieving a status quo of land resource management, and guaranteeing agricultural production. With the gradual development of remote sensing technology, it has become a common practice to obtain cultivated land boundary information on a large scale with the help of satellite Earth observation images. Traditional land use classification methods are affected by multiple types of land cover, which leads to a decrease in the accuracy of cultivated land mapping. In contrast, although the current advanced methods (such as deep learning) can obtain more accurate cultivated land mapping results than traditional methods, such methods often require the use of a massive amount of training samples, large computing power, and highly complex model tuning processes, increasing the cost of mapping and requiring the involvement of more professionals. This has hindered the promotion of related methods in mapping institutions. This paper proposes a method based on time series vector features (MTVF), which uses vector thinking to establish the features. The advantage of this method is that the introduction of vector features enlarges the differences between the different land cover types, which overcomes the loss of mapping accuracy caused by the influences of the spectra of different ground objects and ensures the calculation efficiency. Moreover, the MTVF uses a traditional method (random forest) as the classification core, which makes the MTVF less demanding than advanced methods in terms of the number of training samples. Sentinel-2 satellite images were used to carry out cultivated land mapping for 2020 in northern Henan Province, China. The results show that the MTVF has the potential to accurately identify cultivated land. Furthermore, the overall accuracy, producer accuracy, and user accuracy of the overall study area and four sub-study areas were all greater than 90%. In addition, the cultivated land mapping accuracy of the MTVF is significantly better than that of the maximum likelihood, support vector machine, and artificial neural network methods. [ABSTRACT FROM AUTHOR]

In July 2021, an extreme precipitation event occurred in Henan, China, causing tremendous damage and deaths; so, it is very important to study the observation technology of extreme precipitation. Surface rain gauge precipitation observations have high accuracy but low resolution and coverage. Satellite remote sensing has high spatial resolution and wide coverage, but has large precipitation accuracy and distribution errors. Therefore, how to merge the above two kinds of precipitation observations effectively to obtain heavy precipitation products with more accurate geographic distributions has become an important but difficult scientific problem. In this paper, a new information fusion method for improving the position accuracy of satellite precipitation estimations is used based on the idea of registration and warping in image processing. The key point is constructing a loss function that includes a term for measuring two information field differences and a term for a warping field constraint. By minimizing the loss function, the purpose of position error correction of quantitative precipitation estimation from FY-4A and Integrated Multisatellite Retrievals of GPM are achieved, respectively, using observations from surface rain gauge stations. The errors of different satellite precipitation products relative to ground stations are compared and analyzed before and after position correction, using the '720' extreme precipitation in Henan, China, as an example. The experimental results show that the final run has the best performance and FY-4A has the worse performance. After position corrections, the precipitation products of the three satellites are improved, among which FY-4A has the largest improvement, IMERG final run has the smallest improvement, and IMERG late run has the best performance and the smallest error. Their mean absolute errors are reduced by 23%, 14%, and 16%, respectively, and their correlation coefficients with rain gauge stations are improved by 63%, 9%, and 16%, respectively. The error decomposition model is used to examine the contributions of each error component to the total error. The results show that the new method improves the precipitation products of GPM primarily in terms of hit bias. However, it does not significantly reduce the hit bias of precipitation products of FY-4A while it reduces the total error by reducing the number of false alarms. [ABSTRACT FROM AUTHOR]

The return of rural migrant workers through increasing agricultural income by expanding farming scale is significant for rural sustainable development without rural population loss. This paper selected six representative counties in Henan Province, China's major grain-producing province, to conduct a questionnaire survey, investigated the incomes of farmers from farming and migrant workers, calculated moderate farming scale under different opportunity costs, and also estimated the agricultural population that can be supported by arable land resources. Results are as follows: (1) Under the traditional planting mode, annual per capita income of farmers in farming was USD 342.18, which was substantially lower than USD 5255.63 in migrant workers. This huge income gap has led to continuous rural population loss. (2) Under the opportunity cost of farming income equal to migrant workers income, moderate farming scales of the six selected counties were 1.39, 1.17, 1.22, 1.08, 1.34, and 1.01 ha, respectively. Under the 0.8x and 0.6x opportunity cost, corresponding moderate farming scales were 1.11, 0.94, 1.11, 0.86, 1.07, and 1.34 ha; and 0.84, 0.70, 0.73, 0.65, 0.80 and 1.01 ha, respectively. (3) On the basis of the three moderate farming scales and status quo of arable land resources, agricultural populations that can be supported by rural Henan Province were 8.0386 million, 10.0479 million and 13.3942 million, respectively. Findings can guide the formulation of rural revitalization strategic measures and the preparation of village territorial spatial planning. [ABSTRACT FROM AUTHOR]

Numerical weather prediction (NWP) has become an important method of predicting extreme weather events, but orography is one of the key factors affecting the performance of NWPs. In this paper, based on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) elevation data, a method for constructing a global orographic dataset suitable for NWP spectral models is investigated. The Yin-He global spectrum model (YHGSM) is used to simulate the early and peak periods of the extreme rainfall event on 20 July 2021 in Henan Province, China, and the heavy rain in Beijing in order to verify the effectiveness and superiority of the proposed orographic construction method. It is demonstrated that in a few cases the direct two-dimensional filter can sometimes simulate more intense rainfall, but in general, the bidirectional one-dimensional filter is better than the direct two-dimensional filter in orographic processing, and the bidirectional one-dimensional filter can filter out more of the small-scale orographic information. The effect of the higher orographic resolution before conversion to spectral space is not very obvious, but it is demonstrated that the simulation results are better for the heavy-rainfall level. In conclusion, in most cases, the simulations conducted using the new global orographic dataset based on ASTER data are better than those obtained using the model's original orography, especially for torrential and extreme rainfall. These conclusions provide a reference for future predictions of and research on extreme rainfall events. [ABSTRACT FROM AUTHOR]