【Objective】Chestnut is a key economic tree species in northern China, possessing both nutritional and medicinal benefits. As one of Beijing's major specialty agricultural products, chestnut cultivation in Huairou District holds significant economic and ecological value. However, due to its high sensitivity to environmental conditions—such as elevation, temperature, precipitation, soil chemistry, and vegetation cover—its suitability for cultivation varies widely across the region. This research aims to assess the spatial suitability of chestnut cultivation in Huairou District using a comprehensive modeling framework. The main objective is to identify highly suitable and potential expansion areas, thereby supporting local agricultural optimization, ecological protection, and rural revitalization strategies.【Methods】A total of 439 chestnut distribution points were collected from official databases and field surveys. Sixty-two environmental covariates were assembled, including topographic (elevation, slope, river distance, topographic wetness index), climatic(19 bioclimatic variables from the WorldClim database), soil(physicochemical and trace element properties), and vegetation(NDVI)data. All spatial datasets were resampled to a 30-meter resolution. The Maximum Entropy(MaxEnt)model was employed to assess species-environment relationships. The model was optimized using the ENMeval package in R, evaluating 48 combinations of feature classes(e.g., linear, quadratic, hinge)and regularization multipliers (RM) ranging from 0.5 to 4. The best parameter configuration-linear and quadratic features (LQ) with RM=1-was selected based on delta. AICc values. Model performance was validated using the ar ea under the ROC curve (AUC), based on 10 bootstrap replicates. To improve model interpretability and address multicollinearity, Pearson Correlation Analysis was applied to filter environmental variables. Sixteen core variables were retained. Fuzzy membership functions were constructed for each variable, employing sigmoid, parabolic, or discrete functions based on their response curves. The entropy weight method was then used to calculate objective weights for each variable, further revised through expert consultation. For spatial evaluation, land use and soil type data were integrated to create 53,333 evaluation units. A composite suitability index was computed for each unit using a weighted summation method. The index was classified into three categories: highly suitable (≥ 0.701), moderately suitable (0.509-0.701), and unsuitable (＜0.509).【Results】The MaxEnt model achieved an AUC value of 0.918, indicating excellent predictive accuracy. Among the 16 key variables, the most influential were distance to river networks (26.3%), temperature seasonality (17.6%), elevation (9.4%), slope (9.3%), NDVI(7.5%), and parent material(6.8%). These variables reflect the importance of water availability, temperature stability, terrain constraints, and soil-forming processes in chestnut distribution. The suitability assessment indicated that 9.93% of Huairou District was classified as highly suitable for chestnut cultivation and 21.77% as moderately suitable, while the remaining 68.30% was deemed unsuitable. Overlay validation showed that 56.49% of existing chestnut plantations were located in highly suitable zones,36.61% in moderately suitable zones, and only 6.90% in unsuitable areas, indicating strong consistency between model predictions and actual planting patterns. Further analysis revealed approximately 54 900 hectares of potential chestnut development areas outside current cultivation zones, including 15 300 hectares of highly suitable land and 39 600 hectares of moderately suitable land.【Conclusion】This study demonstrates the effectiveness of an integrated MaxEnt-fuzzy evaluation-entropy weighting framework for agricultural suitability analysis at a regional scale. By incorporating 62 environmental covariates and optimizing modeling parameters, the study achieved high-precision mapping of chestnut suitability in a complex mountainous environment. The model not only accurately identified current optimal planting zones but also highlighted substantial development potential in underutilized areas. The results suggest that chestnut distribution in Huairou is strongly influenced by terrain, climate variability, and soil nutrient conditions. Particularly, factors such as proximity to water sources, elevation, and temperature seasonality are decisive. These insights are consistent with physiological knowledge of chestnut growth and provide robust guidance for regional agricultural planning. From an ecological perspective, the identified suitable zones overlap significantly with hilly and mountainous areas where chestnut plantations can contribute to water conservation, erosion control, and biodiversity enhancement. From a socio-economic perspective, the spatial zoning results can support targeted policy implementation, rural income generation, and sustainable land-use strategies under the framework of China's rural revitalization and ecological civilization initiatives. Overall, the study contributes a replicable and data-driven methodology for crop suitability analysis and offers valuable spatial decision support for stakeholders involved in land planning, agricultural modernization, and ecological restoration.

In this study, Henan Province was taken as the research object, the index of farmland input level from 2012 to 2022 was calculated and its change trend was analyzed based on the indicators such as rural employees and total mechanization power. The carbon emissions and the total amount of non-point source pollution from farmland were estimated according to factors such as material inputs, crop types, and solid waste. The synergy relationship between changes in farmland input level and changes in carbon emissions and non-point source pollution was analyzed using a synergy index model. The results showed that from 2012 to 2022 in Henan Province, the index of farmland input level was within the range of 0.147-0.892, with an overall increase in input level, mainly dominated by mechanization factors, and a slight decrease in the input of labor, pesticides, and fertilizers. The input level in the western and southern regions was slightly higher than that in the eastern and northern regions. The carbon emissions in the eastern counties were slightly higher than those in the western counties. The emissions of chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) were higher in the eastern and southern counties and relatively lower in the southwestern counties. A total of 54.97% of counties and districts had a mild imbalance between the level of farmland input and changes in carbon emissions, and 70.86% of counties and districts had a mild imbalance between the level of farmland input and changes in non-point source pollutant emissions. Identifying the synergistic relationship between the farmland input level and pollution reduction and carbon reduction plays a crucial role in promoting the low-carbon transformation and utilization of farmland resources in major grain-producing areas. The results provide a reference basis for the zoning governance of sustainable utilization of farmland in Henan Province.

Studying evolution characteristics and attribution analysis of hydrological drought in the Ganjiang River Basin in recent years can better prevent and control hydrological drought in Ganjiang River basin. Using monthly runoff data from Waizhou station in Ganjiang spanning from 1961 to 2020, this article first employs two mutation testing methods to comprehensively identify the year of runoff mutation. Afterward, we utilize the ABCD hydrological model, coupled with seven deep learning algorithms to simulate the streamflow change of Waizhou station in Ganjiang River basin. Finally, the standardized runoff index is applied to describe the hydrological drought, and we analyze the evolution characteristics of hydrological drought and quantitatively assess the effects of human interventions and climate change on hydrological drought in the Ganjiang River Basin. The insights drawn from this research can be summarized as follows: (1) The results of the mutation analysis method indicate that there was a significant mutation in runoff in 1991. (2) The ABCD model can perform well in simulating and predicting runoff, with accuracies reaching 0.82 and 0.88. (3) Combining the ABCD hydrological model with deep learning algorithms can improve the accuracy of simulating runoff changes in the Ganjiang River. Among them, the ABCD-random forest method has the highest accuracy, reaching 0.89 and 0.94. (4) Climate change has a stronger impact on monthly hydrological drought compared to human activities. (5) Climatic factors are the primary determinants of seasonal hydrological drought changes. The findings of this study could provide a valuable reference for the optimal use of water resources and the proactive management of hydrological disasters in the Ganjiang area.

China is at a critical stage in the coordinated promotion of ecological civilization construction, rural revitalization, and new urbanization strategies. How to scientifically coordinate the transformation of territorial spatial utilization (TSU), such as that of ecology–agriculture–urban spaces, and to build an ecological security pattern (ESP) has emerged as a critical task facing regional sustainability. To address the above problem, this study constructs a research framework to reveal the response characteristics of ESP to TSU transformation by adopting the source–surface–flow continuous field model and geographic grid analysis methods. Taking the Qinba–Dabie convergence area in China, with typical transitional characteristics and regional representativeness, as the study area, this study quantitatively analyzes the spatiotemporal evolution of the comprehensive index of TSU degree, as well as the ecological source, resistance, and flow indices across the whole territory. With the geographic grid method adopted to unify the spatial analysis grain between ESP and TSU transformations, this study further explores the response characteristics of ESP under TSU transformation. The main study findings are presented as follows: With the transformation of TSU, ESP elements such as the ecological source index, resistance index, and flow index exhibited significant spatial differentiation, and a nonlinear relationship could be observed between the TSU degree index and the ESP elements. On this basis, this study further explores and constructs a zoning method system for regional TSU control oriented to ESP, formulates targeted protection and restoration strategies, offering theoretical and practical references for the scientific compilation of territorial spatial planning and the conservation and restoration of ESP.

The ongoing development of the economy and society has increasingly intensified the imbalance between the supply and demand of land resources. Achieving coordinated development between socio-economic growth and the “Production-Living-Ecological” functions of land-use is therefore a key foundation for high-quality regional development. In light of this, this study focuses on Henan Province at the county level. Building on a theoretical framework that examines the relationship between socio-economic development and the “Production-Living-Ecological” functions of land-use, we employed methods including the entropy method, linear weighting method, mechanical equilibrium model, and curve estimation model. These were used to explore the evolution characteristics and interactive relationship between socio-economic development and the “Production-Living-Ecological” functions at the county level in Henan Province. The findings reveal that: (1) The socio-economic development level of counties in Henan showed an overall upward trend during the study period, with the average value rising from 0.2320 in 2010 to 0.2702 in 2023. High-level areas were mainly concentrated in the central region around Zhengzhou. (2) The overall level of the “Production-Living-Ecological” functions of land-use in Henan’s counties followed a gradually increasing trend, with a relatively stable evolution process. The functional levels in northern, central, and eastern Henan were notably higher than those in the western and southern regions. (3) There is a significant positive correlation between the socio-economic development level of counties in Henan and the comprehensive level of the “Production-Living-Ecological” functions of land-use. Moreover, socio-economic development exerts a one-way influence on the functional level of “Production-Living-Ecological” in land-use. Identifying the interactive relationship between socio-economic factors and these land-use functions can provide quantitative references and a decision-making basis for rationally adjusting the “Production-Living-Ecological” functions across different stages of development.

Rural settlements are reflections of rural production relations and social connections. It is crucial to integrate regional development goals with rural social ties (blood and geographical kinship) to optimize rural settlement patterns and achieve rural revitalization. In this context, this study systematically analyzed rural system resilience (RSR) and rural socio-spatial kinships (SSK). It proposed a rural settlement reconstruction scheme that uses RSR to determine development directions at administrative village level and SSK to guide reconstruction at natural village level. The results demonstrated the following findings. RSR exhibited a spatially diffusive effect driven by central nodes, with high value areas typically concentrated around township government centers. SSK spatial distribution correlated with villages identified by residents as high vitality key settlements. The restructuring scheme categorizes administrative villages into four types: adaptation transformation type, FA enhancement type, ES enhancement type, and general existence type. Natural villages are classified as central village, general village, and relocation merge village. Furthermore, this study discussed that SSK fosters endogenous rural dynamics through a "social kinship foundation-spatial kinship expansion" evolutionary pathway, with corresponding differentiated restructuring strategies proposed. This study has promoted our understanding of RSR and SSK in the reconstruction of rural settlements, and can provide planning guidance and practical insights for rural revitalization.

Studying the impact of future land use changes on regional ecosystem services (ES) is crucial for sustainable development planning in the region. However, there is a lack of research specifically targeting Henan Province under different future scenarios. Therefore, this study simulates four ES functions-water yield (WY), carbon storage (CS), habitat quality (HQ), and nutrient delivery ratio (NDR)-for the historical period in Henan Province. It also constructs a Comprehensive Ecosystem Service (CES) Index. Additionally, the study predicts the spatial and temporal distribution characteristics of various ES and CES under two different Shared Socioeconomic Pathways (SSP) scenarios for the future. The results of the study showed that: (1) The high simulation accuracy of the FLUS model indicates that the FLUS model is suitable for land use simulation in the study area. (2) Under the SSP2-4.5 scenario, the area of construction land expansion is the largest, and the HQ, CS, water production capacity, and water purification capacity of Henan Province all decrease. Under the SSP5-8.5 scenario, the area of cultivated land increased the most, and all three decreased except for the water production capacity, which increased. (3) Under the SSP2-4.5 scenario, the area of CES decline is the largest, and the severe decline in CES mainly occurs in areas where forest land is encroached upon by urban land, followed by areas encroached upon by rural settlements, and the encroachment of arable land by construction land leads to a mild decline in CES, which accounts for the largest proportion of the area. Under the SSP5-8.5 scenario, Henan Province has the largest area of CES rise, and most of it is dominated by mild rise, but the mean CES in 2050 is still lower compared to 2020. The results of the study can provide a reference basis for the formulation of sustainable development policies in Henan Province and provide new ideas for the study of the impacts of land use change on ES under different scenarios in the future.

Exploring the spatiotemporal evolution and driving forces for the green transition of cultivated land (GTCL) has become an important part of the deepening research on cultivated land use transition, and has significant implications for addressing the environmental issues of agriculture development. This study took the cities in Henan province, the main grain-producing area in central China, as the research objects, and established an evaluation system for GTCL based on the subsystems of spatial, functional, and mode transition. The entropy weight method and spatial autocorrelation model were used to measure the index of GTCL and analyze the spatial pattern; then, the geographic detector model was used to explore the driving forces. The index of GTCL from 2010 to 2020 showed stable growth, exhibiting significant spatial heterogeneity with a decrease from southeast to northwest. The growth of the three subsystems of GTCL is inconsistent, with the order of index value growth being functional transition, mode transition, and spatial transition. The global Moran’s index of the index of GTCL in cities in Henan province showed positive values, indicating significant spatial dependence and spillover effects. The population density, urbanization rate, per capita GDP, and irrigation index have always been important driving forces for GTCL, and agricultural modernization would promote the GTCL in the main grain-producing areas. The research results provide a reference for exploring the path of GTCL, promoting green utilization of cultivated land and sustainable agricultural development in China’s major grain-producing areas.

Non-point source pollution (NPSP) originates from domestic agricultural pollutants and deforestation. Agricultural NPSP discharges into rivers and oceans through precipitation and soil runoff. Awareness and research regarding NPSP and its harmful effects on human health and the environment are increasing. The Diffuse Pollution Estimation with Remote Sensing (DPeRS) model, a distributed NPSP model proposed by Chinese researchers, seeks to predict agricultural NPSP and includes modules estimating nitrogen and phosphorus balance, vegetation coverage, dissolved pollution, and absorbed pollution. By applying the DPeRS model, the present work aims to predict the distribution of all nitrogen and phosphorus pollutants in Henan Province, China in 2021. We used statistical yearbook, remotely sensed, and hydrological data as input. To facilitate uncertainty characterization in pollution predictions, we performed sensitivity analysis, which identified the model input variables that contributed most to uncertainty in model output. Specifically, we used ArcGIS for processing data for nitrogen and phosphorus balance equations, an ENVI 5.3 software system for deriving vegetation cover, and the RUSLE soil erosion model for predicting absorption pollution. Dissolved pollution was estimated using a unified approach to estimating agricultural runoff, urban runoff, rural resident, and livestock pollutants. Absorbed pollution was estimated by considering the soil erosion model and precipitation. Moreover, Sobol’s method was applied for sensitivity analysis. We found that regardless of the accumulation of nitrogen or phosphorus, indicators of the dissolved pollution of Zhoukou were relatively high. Sensitivity analysis of the models for estimating dissolved pollution and absorbed pollution revealed that the top four influential variables for dissolved pollution were standard runoff coefficient ε0, natural factor correction coefficient Ni, the newly produced TN pollutants per area QiN, and runoff coefficient ε. For absorbed pollution, influential variables were rainfall erosion factor R, water and soil conservation factor P, slope degree factor S, and slope length factor L. The total discharges of Henan Province were 9546.4649 t, 1061.8940 t, 6031.4577 t, and 3587.6113 t for TN, TP, NH4+-N, and COD, respectively, in 2021. This paper provides a valuable reference for understanding the status of NPSP in Henan province. The DPeRS approach presented in this paper provides strong support for policymakers in the field of environmental management in China. This study confirmed that the DPeRS model can be feasibly applied to larger areas for NPSP prediction enhanced with sensitivity analysis due to its fast computation and reliance on accessible and simple data sources.

Understanding the patterns and drivers of agricultural non-point source pollution is crucial for regional ecological governance. Here, we focused on simulating non-point source nitrogen pollution in agricultural areas of the north intensive farming area. Utilizing the InVEST model, ArcGIS hot spot analysis tool, and geodetector, we deeply analyzed the sources, loss loads, key source areas, and driving factors of agricultural non-point source nitrogen pollution from 2000 to 2020. The results showed that： ① Agricultural nitrogen input intensity in the north intensive farming area exhibited a decreasing trend from 2000 to 2020, with a spatial pattern of "low in the north and high in the south," primarily driven by nitrogen fertilizer application and livestock breeding. ② Nitrogen emission intensity in each city decreased significantly over the study period, showing an overall spatial pattern of "low in the northwest and high in the southeast." ③ The scope of key source areas experienced a shift from initial narrowing to subsequent expansion. ④ Rainfall emerged as the primary driving force influencing the spatial variation in agricultural nitrogen emission intensity, with its interaction with DEM and slope further accentuating the differentiation. The results of this study can provide a scientific basis for regional agricultural environmental protection policies, thereby promoting the healthy and sustainable development of the agricultural ecosystem.

By simulating the layout of the “Production–Living–Ecological space” under various scenarios in the future and exploring the trend of future land use changes, it is of great significance to optimize the land use structure and ecological environment of the region. Based on the existing land use data and combined with the PLUS model, the article predicts the land demand and distribution of the PLES in the future 2040 and 2060 and then studies the contribution rate of the area changes of each land type to the change of regional ecological environment quality. The results show that (1) agricultural production land is the main type of land use in Anyang City from 1980 to 2020, and the conversion type of land use is mainly manifested as the conversion of agricultural production land to living land. (2) In all three scenarios, the main changes between 2020 and 2060 are the contraction of production land and the expansion of living land. The change rate of the ecological protection scenario is the smallest, and the decrease rate of the urban development scenario is the largest. (3) In 2060, all three scenarios show varying degrees of reduction in the Ecological environment quality index (EQI) compared to 2020. At the same time, the change in regional environmental quality is closely related to the change in agricultural land. (4) The regional ecological environment quality is the result of multi-factors, among which annual precipitation has the strongest explanatory power, and all factors show synergistic effects. The present study is intended to provide a reference for optimizing the pattern of the PLES in the region and improving the regional environmental quality.

Considering Henan Province as the research area, based on land use data with a resolution of 30 m in 2000, 2010, and 2020, we analyzed the distribution of the production-living-ecological space and the quality of the ecological environment in Henan Province using land transfer matrices and an eco-environmental effect model. Furthermore, based on 2020 land use data, the PLUS model was used to simulate land use data for the years 2030, 2040, and 2050 under three scenarios： natural development, production priority, and ecological priority. Finally, we calculated the ecological environment quality index and ecological contribution rate. The results showed that： ① From 2000 to 2020, the area of production space decreased by 4 879 km2, the area of living space increased by 19%, and the area of ecological space increased by 1.9%. ② From 2000 to 2020, the eco-environmental quality index increased from 0.364 6 in 2000 to 0.366 5 in 2010 and then decreased to 0.365 7 in 2020, which was at a medium level. ③ From 2030 to 2050, the distribution of production-living-ecological space will remain unchanged, and the trend under the natural development and ecological priority scenarios will remain unchanged. ④ From 2020 to 2050, Henan Province had the best ecological environment under the ecological priority scenario, and the ecological environment quality index was predicted to be 0.365 7 in 2030, 0.366 0 in 2040, and 0.366 5 in 2050. The distribution of production-living-ecological space is of great importance for the future development of the earth's space and the construction of an ecological environment.

With the rapid development of the economy and rapid population growth, the destruction of the environment by humans is growing, and the discharge of various pollutants has seriously threatened the regional ecological security. First, based on the 2010 Beijing-Tianjin-Hebei land use data, the PLUS model was used to simulate the 2020 land use data and the accuracy of the simulation results was verified with the real data. The land use data of 2030-2050 under the sustainable development scenario （SSP119）, natural development scenario （SSP245）, and economic development scenario （SSP585） were simulated. Then, based on the InVEST model, the spatio-temporal changes of nitrogen pollution in the Beijing-Tianjin-Hebei Region from 2000 to 2020 and in the future under the SSP119, SSP245, and SSP585 scenarios from 2030 to 2050 were estimated. The results showed that the total nitrogen loads in the Beijing-Tianjin-Hebei Region were 41 300, 41 000, and 40 900 tons in 2000, 2010, and 2020, respectively and the total nitrogen load in the Beijing-Tianjin-Hebei Region showed a decreasing trend from 2000 to 2020. Compared with that in 2020, the total nitrogen load in the Beijing-Tianjin-Hebei Region in 2050 under the SSP119 scenario increased by 2 000 tons, the total nitrogen load in the Beijing-Tianjin-Hebei Region in 2050 under the SSP245 scenario increased by 3 200 tons, and the total nitrogen load in the Beijing-Tianjin-Hebei Region in 2050 under the SSP585 scenario decreased by 300 tons. Compared with the SSP245 and SSP119 scenarios, the development of SSP585 was more conducive to the reduction of nitrogen pollution in the Beijing-Tianjin-Hebei Region.

Scientific evaluation of ecological security pattern (ESP) quality provides a crucial foundation for regional ecological protection and spatial planning. Addressing the problem that current research on ESP quality generally lacks a systematic evaluation framework and excessively relies on qualitative descriptions, this study aims to explore a scientific and quantitative evaluation method for ESP quality. By combining landscape pattern and ecological network analysis, this study develops an evaluation framework for regional ESP quality that encompasses 12 key factors and utilizes parallel coordinate plots for visualization. Applying this framework, this study quantified the spatiotemporal evolution characteristics of ESP quality in the Taihang–Qinling intersection zone, China, from 2000 to 2020. The findings were as follows: (1) Both the number and total area of ecological sources increased markedly, accompanied by heightened spatial heterogeneity of the ecological resistance surface. The number of ecological corridors rose, although their total length decreased. Ecological strategic points increased substantially. (2) Despite the increase in the scale of ecological sources and the number of corridors, considering the comprehensive impact of multiple evaluation factors, the overall ESP quality declined across the region. In particular, the Taihang and Qinling Mountain regions experienced degradation, whereas the Songji Mountains region showed improvement. (3) This study discussed an ecological protection and restoration scheme comprising the Taihang ecological barrier region, the Songji ecological restoration region, and the Qinling ecological conservation region, and formulated region-specific optimization strategies. Overall, the proposed evaluation framework and local quality analysis methods of ESP in this study offer new perspectives for advancing ecological planning research.

Analyzing the spatial relationship between urban spatial patterns and the thermal environment and quantifying zoning to regulate the urban thermal environment according to local conditions is essential. Previous research on the spatial heterogeneity of factors influencing thermal environments is lacking, and there are shortcomings in the actionability of thermal environment regulation. This study takes the main urban area of Wuhan as an example, based on multi-source spatial data such as Landsat-8 remote sensing images, urban land classification, and buildings, integrates geodetectors and a geographically weighted regression model (MGWR) to investigate the mechanism of the influence of the urban form on the thermal environment under the control unit at the global and local levels, and finally utilizes the K-mean clustering approach to perform impact zoning. First, the high-temperature areas in the main urban area of Wuhan are mainly located in the core area of the old city of Hankou and the Wuchang District, which are located on both sides of the Yangtze River, as well as in the industrial zones northeast and southwest of the city. In terms of land-use types, industrial, logistics and warehousing, and street and transportation had higher average surface temperatures, whereas water area, green space and square, and agricultural and forestry had lower average surface temperatures. Second, the three-dimensional (3D) building indicator had a greater overall impact on the thermal environment than the two-dimensional (2D) urban land-use type indicator. Building density (q = 0.479) was the dominant factor affecting the thermal environment. While the share of water area in 2D form had the strongest explanatory power, the other indicators were relatively weaker. Third, there was spatial heterogeneity in the impact of indicators on the thermal environment, with strong locally driven characteristics for indicators such as vegetation cover, percentage of industrial land area, and building density (BD). Finally, according to the MGWR regression coefficients of each indicator, the main urban area of Wuhan was divided into four types of impact zones, and the intensity and direction of the impact of indicators in different impact zones changed, which confirms the necessity of a zoning policy. 3D buildings form the dominant zone and the BD strong dominant zone are suggested to adjust the urban building form as the main goal, the percentage of water area and BD co-dominant zones are suggested to optimize the urban blue-green space as the main regulation goal to improve its cooling efficiency, and the integrated transition zone is suggested to synergistically optimize the 2D/3D urban spatial form. In conclusion, from the perspective of planning practice, combined with the different impact characteristics of each control area, we propose a differentiated control strategy combining "planning units + planning indicators," which provides a practical approach to optimize the climate-friendly urban form.

To elucidate the characteristics of nitrogen non-point source pollution in Henan Province under the influence of climate change, this study initially utilized the InVEST model to simulate the temporal and spatial distribution of the N non-point source pollution load in Henan Province from 2000 to 2020, subsequently coupling the FLUS model with the InVEST model, nitrogen point source pollution load, and its spatial distribution in Henan Province from 2030 to 2050 under SSP2-4.5 and SSP5-8.5 climate scenarios. The findings of the study indicated that： ① Between 2000 and 2020, the total nitrogen output and load in Henan Province initially increased before decreasing, maintaining an overall downward trend. ② In terms of spatial distribution, the nitrogen output load from 2000 to 2020 displayed a pattern of "high in the plains, low in hilly areas," indicating a strong correlation between nitrogen non-point source pollution and topography. ③ Under the SSP2-4.5 scenario, the total nitrogen output and load were projected to increase annually from 2030 to 2050, with a complex overall change pattern； under the SSP5-8.5 scenario, the total nitrogen output and load were anticipated to decrease initially before increasing, with a consistent overall change pattern. Based on these results and in conjunction with the practical situation of Henan Province, it is hoped that this research can provide a theoretical foundation for the prevention and control of future non-point source pollution in the province.

Exploring the multifunctional trade-off and synergy relationship of cultivated land is of great significance for protecting cultivated land resources, ensuring food security, maintaining ecological security, and promoting high-quality development in the Yellow River Basin. Based on the selection of 379 counties with concentrated distribution of cultivated land, this study comprehensively evaluates the three-dimensional functional level of “production-society-ecology” of cultivated land from 2010 to 2020. The coupling coordination degree model, land system function trade-off degree model, and K-means clustering analysis method are used to analyze the trade-off and synergy relationship between cultivated land functions and divide the functional zones in the Yellow River Basin. 1) In the last 10 years, the levels of cultivated land production, social, and ecological functions in the Yellow River Basin are in the range of 0.01–0.47, 0.04 to 0.23, and 0.03 to 0.23, respectively. The production function is at a stable level, while the overall level of social and ecological functions has slightly improved. 2) The level of multifunctional coupling and coordination of cultivated land ranges from 0.22 to 0.65. Only 31.13% of counties have a high coupling degree between multiple functions. The production-ecological function in the upstream regions show a coordinated development trend. The social-ecological function in the midstream regions is well coordinated, and the production-social function and production-ecological function in downstream regions towards collaborative development. 3) According to the dominant functional types and the characteristics of multifunctional coupling and coordination, the cultivated land of Yellow River Basin is divided into 7 multifunctional zones, involving 149 with multifunctional advantage zones, 19 with P-S functional composite zones, 21 with P-E functional composite zones, 21 with S-E functional composite zones, 74 with social functional dominant zones, 29 with ecological functional dominant zones, 44 with grain functional dominant zones, and 22 with remediation key zones. The results can provide decision support for differentiated management of cultivated land in the Yellow River Basin and mutual promotion between functions.

Ensuring food security amidst increasing non-grain utilization of cultivated land is a critical challenge in major grain-producing regions. This study analyzes the spatio-temporal evolution and driving mechanisms of non-grain cultivated land in Henan Province, China, from 2012 to 2023, using spatial autocorrelation, multiple linear regression, geographically and temporally weighted regression model, and cluster analysis. Results show that the non-grain ratio exhibited a fluctuating yet overall increasing trend, from 27.47% in 2012 to 25.91% in 2017 and reaching 30.28% in 2023, with higher values in the northern and southwestern counties of the province. Spatial clustering patterns remained relatively stable, characterized by a “high–high clustering in the southwest and low–low clustering in the north,” which was further substantiated by significant Global Moran’s I values (0.362 in 2012 and 0.307 in 2023). Key drivers included per capita level of agricultural mechanization, labor force per unit of cultivated land area, output value per unit of cultivated land area, and per capita disposable income of rural residents. PCA and K-means clustering identified three zonal types: agricultural production support (45.10% of counties), agricultural production weakening (35.29% of counties), and economically location-guided (19.61% of counties). The findings underscore the need for differentiated policies—such as precision subsidies, land consolidation, and ecological farming practices. This study provides a scientific basis for zonal governance of non-grain cultivated land in grain-producing areas.

The water resources in various river basins across China are becoming increasingly severe due to the combined effects of climate change and human activities. Evaporation plays a crucial role in redistributing water resources within local areas. Analyzing the actual evapotranspiration (ETa) changes of six major rivers in China is essential for effective water resource management. This article first employed three mutation methods (the M-K analysis, the Pettitt analysis, and the Bernaola Galvan segmentation algorithm) to identify the runoff mutation years of six major rivers in China. Subsequently, the ABCD and DWBM hydrological models were utilized to estimate monthly, seasonal, and annual ETa scales. Then, the trend of ETa changes was analyzed using the Trend-Free Pre- Whitening Mann-Kendall (TFPW-MK) analysis method. Finally, a multi-time scale Budyko model was constructed to quantitatively assess the impacts of climate change and human activities on changes in ETa. The results indicated that: (1) The Nash coefficient and KGE coefficient for the ABCD and DWBM models during both the base and mutation periods of each watershed were generally above 0.7, with most values exceeding 0.8, signifying a high level of accuracy in the simulation results. (2) On a monthly scale, climate change was the primary factor influencing ETa changes in the Upper reaches of the Yangtze River Basin (UYRB) from January to May, the Middle and Upper reaches of the Songhua River Basin (MUSRB) from January to March, the Upper reaches of the Huaihe River Basin (UHRB) from January to June, and the Upper reaches of the Pearl River Basin (UPRB) from January to December. Human activities were the predominant driving force in the monthly ETa changes in the Source Regions of the Yellow River Basin (SRYRB). Except for April and May, ETa of the Source Regions of the Lancang River Basin (SRLRB) in other months were predominantly affected by human activities. (3) On a seasonal scale, climate change played a leading role on the spring and winter ETa changes in UYRB and the seasonal ETa changes in SRYRB were primarily driven by human activities. And the seasonal ETa changes in UPRB were predominantly affected by climate change. With the exception of winter, the ETa changes of MUSRB in other seasons were mainly attributed to human activities. In UHRB, except for autumn, climate change was the primary driving force in ETa changes in other seasons. In SRLRB, except for spring, human activities exhibited a dominant effect on ETa changes in other seasons. (4) On an annual scale, the impacts of climate change and human activities on annual ETa changes in UYRB were approximately equal. The annual ETa changes in SRYRB, MUSRB, and SRLRB were predominantly caused by human activities. In UHRB and UPRB, climate change played a leading role in annual ETa changes.

As the typical megacity in the Central Plains, the simulation and prediction of Zhengzhou’s future land use and ecosystem carbon storage are of great significance for regional green and coordinated development. Based on land use data and CMIP6 data, the study simulated land use types from 2030 to 2050 through plus model. Then the InVEST model is used to estimate its ecosystem carbon storage. The results show that: (1) Arable land is the main type of land use in Zhengzhou from 2000 to 2020. During the period, the conversion between land use type is mainly manifested as the conversion of arable land into construction land. The distribution of the built-up area has changed from one center with multiple scattered dots to one center with a radial spider-web-like pattern. (2) In 2050, arable land in the SSP126 scenario is the only one of the three scenarios to decline, but the area of forest land and so on in this scenario is the largest of the three. The area changes trend of each land use type in the two scenarios of SSP245 and SSP585 are relatively consistent. (3) The areas with high ecosystem carbon storage value are mainly distributed in the forest area in the west of the study area. The regional ecosystem carbon storage value of SSP126 scenario in 2050 is the highest, which is 5.7762 × 107t. The ecosystem carbon storage value of SSP585 scenario decreased the most, with a total reduction of 0.6667 × 107t. (4) The spatiotemporal variation of ecosystem carbon storage in Zhengzhou is the result of natural and social factors, among which the average annual temperature is the strongest explanation. This study provides a theoretical basis for the scientific formulation of land use planning in Zhengzhou, as well as the coordinated development of man and nature.