Table of Content

20 July 2026, Volume 62 Issue 4

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A Smart Site Selection Model Integrating Multisource Spatiotemporal Knowledge Graphs and Graph Neural Networks

MAO Liangjian, LI Zhixu

2026, 62(4):  699-709.  DOI: 10.13209/j.0479-8023.2025.087

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To address the issues of high labor and time costs, neglect of geographic spatial interactions, and coarse handling of high-dimensional unstructured features in existing retail chain store site selection methods, this paper proposes a smart site selection model (SmartSite) that integrates multi‑source spatiotemporal knowledge graphs and graph neural networks (GNNs). Specifically, a multi‑source spatiotemporal database (MSSTDB) is first established to collect and standardize multi‑source spatiotemporal data. Subsequently, a multi‑source spatiotemporal knowledge graph (MSSTKG) is constructed to accurately extract spatiotemporal entities and their relationships, and a graph convolutional network (GCN) is employed to derive deep feature representations from geographic data. Finally, an attention mechanism is introduced to dynamically assign feature weights, thereby building an intelligent site selection model. The performance of the proposed model is validated through comparative experiments on benchmark datasets and ablation studies, and the model is further applied to a leading new retail chain enterprise's store location scenario. Experimental results show that, compared with traditional manual approaches and conventional data‑driven methods, the proposed model can effectively exploit the correlations inherent in geographic spatial data, significantly reduce site selection costs, and deliver substantial economic benefits, offering a reliable decision‑making reference for retail chain enterprises in store location planning.

Structural Bidirectional Encoding-Based Representation Learning on Mathematical Knowledge Graphs

JIN Langjunqing, SHANG Yarong, CHI Kaiqi, YU Chao

2026, 62(4):  710-718.  DOI: 10.13209/j.0479-8023.2025.088

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Most existing studies on knowledge graph representation learning simply characterize knowledge as entities and relations, and ignore complex relation learning and multi-associative knowledge chains. It is difficult to accurately build a subject knowledge system, which affects the generation of learning paths. Thus, we propose a structural Bidirectional Encoding-Based Representation Learning model (SBE) for disciplinary knowledge graphs. Graph data augmentation is used to characterize entities and relations as initialized vector sequences. Additionally, the model combines structured bidirectional encoding and decoding to accurately represent positional information in context and complex relationship chains. Moreover, an inference strategy is proposed based on counterfactual link generation. Experimental results demonstrate that the proposed model can enhance the accuracy of both link prediction and knowledge recommendation. Furthermore, a case study on middle school mathematics reveals that the SBE model can generate learning paths tailored to student needs and effectively improve the precision, comprehensiveness, and interpretability. 

RDF-MT Mapping Strategies and Verification under Multi-source Heterogeneous Scenarios

SHANG Jingyi, HOU Wenzhe, ZENG Weixin, ZHAO Xiang

2026, 62(4):  719-728.  DOI: 10.13209/j.0479-8023.2025.089

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To investigate the performance of the RDF-MT-based federated query framework in multi-source heterogeneous scenarios and analyze its mechanism for handling real-world data conflicts, a virtualized global view is constructed based on RDF-MT technology. For user-defined SPARQL global queries, the framework leverages the virtualized global view to enable adaptive query localization and cross-source data access. Experimental results on real-world datasets demonstrate that RDF-MT technology can effectively support virtualized cross-source querying and the unified representation of multi-source heterogeneous data, while exhibiting good scalability with increasing data volumes. To address data conflicts, the framework employs namespace isolation to distinguish semantically identical entities originating from different sources. During the plan execution phase, a “merge-then-join” strategy is adopted for multiple matched data sources, which can effectively mitigate the impact of conflicting data on query processing and offer a significant advantage in terms of time cost.

istribution Characteristics and Driving Factors of Phytoplankton Community in the Kuye River Basin

HU Yaowu, YANG Zijie, TIAN Yucheng, WANG Yichu, WANG Jiawen

2026, 62(4):  729-738.  DOI: 10.13209/j.0479-8023.2026.045

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To explore the characteristics of the phytoplankton community and environmental driving mechanisms in arid river basins, a systematic investigation of phytoplankton was conducted in May 2023, focusing on three sections of the Kuye River basin (upstream: Wulanmulun River; tributary: Beiniuchuan River; downstream: Kuye River mainstream). A total of 60 species of phytoplankton were identified, belonging to six phyla and 41 genera, with Bacillariophyta and Chlorophyta as the dominant phyla. Significant differences in species diversity were observed among the three river sections, with the highest diversity in the Wulanmulun River and the lowest diversity in the Beiniuchuan River. The water quality index (WQI) showed the best water quality in the Beiniuchuan River and the worst in the Wulanmulun River. Notably, Ankistrodesmus spiralis and Ankistrodesmus acicularis were reliable indicators for evaluating water quality in the Kuye River basin. Redundancy analysis highlighted that conductivity (COND), water temperature (WT), and dissolved organic carbon (DOC) were key physicochemical factors shaping the phytoplankton community in this basin. Correlation analysis further indicated that the Scenedesmus dominant in the mainstream of the Kuye River was mainly affected by dissolved oxygen (DO) and nitrate-nitrogen (NO₃⁻-N); Cyclotella and Gomphonema abundant in the Wulanmulun River were mainly affected by NO₃⁻-N, ammonium-nitrogen (NH₄⁺-N), and the nitrogen/phosphorus ratio (N/P); while Diatoma, which prevailed in the Beiniuchuan River, was mainly affected by COND. 

Metagenomic Analysis Revealing the Community Structure and Nitrogen Metabolic Function of Eukaryotic Microbes Along the Bahe River

ZHAO Mingzhu, WANG Jiawen, WANG Yichu, ZHANG Guohua, LI Yinghao, YANG Zijie

2026, 62(4):  739-748.  DOI: 10.13209/j.0479-8023.2026.046

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This study employed metagenomic sequencing technology and multivariate statistical methods to systematically analyze the spatial distributions and environmental driving factors of eukaryotic microbial communities, as well as their nitrogen metabolism genes at 15 sites along the Ba River. The results indicated significant differences in the α diversity of eukaryotic microbes among the upper, middle and lower reaches, with higher diversity in the lower reaches rather than that in the upper reaches. In terms of community composition, Bacillariophyta (48.3%) was the dominant phylum, and the relative abundance of Ciliophora remarkably increased in the middle and lower reaches. Nitrogen metabolism in eukaryotes was dominated by assimilation in the upper reaches, with a gradual increase in the abundance of transport-related genes in the middle reaches, and denitrification intensified in the lower reaches. Furthermore, TP, NO₃^⁻-N and NH₄^⁺-N significantly affected the eukaryotic microbial community structure, while NH₄⁺-N, NO₃^⁻-N, Chl a, COND and salinity were the key factors driving the distribution of nitrogen metabolism genes. 

In Situ Metabolic Diagnosis and Targeted Sorting of Polyphosphate-Accumulating Organisms in Activated Sludge Based on Single-Cell Raman Spectroscopy

LIU Jia, REN Yishang, JING Xiaoyan

2026, 62(4):  749-757.  DOI: 10.13209/j.0479-8023.2026.039

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To address the current bottlenecks of lagging microscopic metabolic monitoring and difficulties in isolating key functional strains of the enhanced biological phosphorus removal (EBPR) process, we developed an integrated “in situ diagnosis-targeted sorting” strategy based on single-cell Raman spectroscopy (SCRS) and microfluidic cell sorting technologies. In situ spectral acquisition and intelligent threshold scanning analysis were performed on sludge from five typical steady-state aerobic batches, establishing an ecological response model linking the phosphorus metabolism phenotype with the environmental phosphorus load. Subsequently, based on the biological thresholds determined by the model, targeted sorting and 16S rRNA gene identification were conducted on the enriched sludge. The results revealed significant single-cell metabolic heterogeneity within the in situ community of polyphosphate-accumulating organisms (PAOs). By defining a threshold for the Raman peak intensity ratio of polyphosphate (Poly-P) to phenylalanine (Ratio), high-activity functional subpopulations could be precisely distinguished. Both the relative abundance of this subpopulation and its single-cell metabolic intensity showed a significant positive correlation with the real-time soluble orthophosphate (SOP) concentration in the aerobic tank, confirming a dual ecological response mechanism of “breadth mobilization” (abundance regulation) and “depth intensification” (activity regulation) adopted by PAOs to adapt to environmental substrate fluctuations. With the threshold Ratio >2.6, 15 pure functional strains exhibiting high polyphosphate accumulation activity were successfully isolated. Identification showed they encompassed a denitrifying PAO (Microvirgula aerodenitrificans), a dominant facultative PAO (Pseudomonas protegens), and classic PAOs (Acinetobacter spp.). The study achieves a microscopically quantifiable diagnosis of the wastewater phosphorus metabolic status and provides a precise technical pathway for the targeted exploration of uncultured functional microbial resources. 

Spatial-Temporal Evolution of Wet-Bulb Temperature and Evaluation of Population High Moist-Heat Exposure Risk in Eastern China’s Monsoon Region

WANG Rui, LI Pengfei, ZHAO Xinyi

2026, 62(4):  758-768.  DOI: 10.13209/j.0479-8023.2026.056

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Based on ERA5 reanalysis data and downscaled CMIP6 model simulation data, the authors analyze the wet-bulb temperature changes and moist-heat conditions in the eastern China’s monsoon region from 1981 to 2020. It also predicts the changes under the SSP2-4.5 and SSP5-8.5 emission scenarios from 2046 to 2055 and evaluates the high moist-heat exposure risk for people. The results indicate that from 1981 to 2020, the wet-bulb temperature in the eastern China’s monsoon region generally increased. During the daytime, the annual maximum wet-bulb temperature significantly rose in the western and eastern coastal region, while it decreased in some southern regions. At night, the change was mainly characterized by an increase. The annual average wet-bulb temperature increased both during the day and at night. Moist-heat weather during the daytime mainly occurred in the southern region, followed by the northern region, with the least occurrence in the central region. The spatial pattern of high moist-heat weather showed a distribution of more in the north and less in the south. At night, moist-heat weather mainly occurred in the northern and eastern parts, with high moist-heat weather being extremely rare. Under the SSP2-4.5 and SSP5-8.5 scenarios, the frequency and distribution of various types of moist-heat weather in the future will change in a complex manner. The central, eastern, southern China and the southwestern parts of the study region are projected to experience a decrease in moist-heat weather but an increase in high moist-heat weather. In other regions, both types of moist-heat weather are expected to increase. There will be an increase of 0–50 days per year in the northern region, while most of the southern regions will experience an increase of 50–100 days per year. In the future, the population exposure risk to high moist-heat conditions is expected to be relatively low in the northern region. However, the southern region will face moderate to high exposure risks, where urgent measures need to be taken to address these challenges. 

Synoptic Classification of Compound Heat-Ozone Events in the Beijing-Tianjin-Hebei Region Using Self-Organizing Map

LIANG Qian, MIAO Yucong, LIU Pei

2026, 62(4):  769-780.  DOI: 10.13209/j.0479-8023.2026.053

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Based on multi-source environmental and meteorological datasets, this study quantifies the spatiotemporal characteristics of the heat index and surface ozone concentrations during the summers of 2022–2024 across the Beijing-Tianjin-Hebei (BTH) region and its surroundings. Results show that compound heat-O3 events frequently occur over the piedmont plains of southern Hebei. Using a self-organizing map (SOM) method to classify 850 hPa synoptic patterns, two typical circulation types are identified as being strongly associated with these compound events. These patterns induce warm advection near the top of the planetary boundary layer and suppress vertical mixing, while simultaneously directing warm and humid air from the south to accumulate within the semi-enclosed topography of the BTH region. This leads to enhanced heat risk and pollution levels. The study reveals key planetary boundary layer processes governed by the joint modulation of regional atmospheric circulation and terrain, offering valuable insights for improving early warning and risk mitigation of compound meteorological hazards.

A Reverse Time Migration Imaging Method for Tunnel Ahead Detection Based on Time-Delay Stacking

ZHANG Donglin, WEN Jingchong, ZHOU Tong, NING Jieyuan, WANG Bingyu, WANG Qiuhan

2026, 62(4):  781-793.  DOI: 10.13209/j.0479-8023.2026.031

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To address low signal-to-noise ratio of seismic data and poor target visibility in underground engineering applications such as coal mining, hydraulic engineering, and subway construction, we propose a reverse time migration imaging method for tunnel ahead detection based on time-delay stacking. The method designs the relative time delays among the sources in a source array, so that the seismic wavefields generated by the individual sources are aligned in phase along a prescribed direction or at a target point, thereby enhancing coherent signals in reverse time migration imaging. The delays can be implemented physically by controlling the actual source firing times or mathematically by applying corresponding time shifts to independently acquired shot records; the former corresponds to physical implementation, while the latter corresponds to mathematical implementation. Numerical experiments adopting the latter implementation show that compared with the conventional prestack reverse time migration method, the proposed method further improves the signal-to-noise ratio of migration results and enhances diffraction-wave signals, providing a potential approach to tunnel ahead detection imaging under strong-noise conditions. 


Petrogenesis and Tectonic Implications of Late Carboniferous-Early Permian Igneous Rocks in the Bogda Region

ZHU Hexuan, ZHANG Yuanyuan, YANG Zhuang

2026, 62(4):  794-808.  DOI: 10.13209/j.0479-8023.2026.042

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This study focuses on the igneous rocks in the Bogda area along the southern margin of the Junggar Basin. Through geochemical analysis and zircon U-Pb dating, we reveal distinct differences in lithology and distribution of Late Carboniferous and Early Permian volcanic rocks between the northern and southern flanks of the Bogda Mountains. The findings suggest that the Late Carboniferous was characterized by post-collisional extension, while the Early Permian experienced intense extensional activity caused by lithospheric delamination. Late Carboniferous-Early Permian mafic rocks in the Bogda region exhibit significant depletion in high-field-strength elements (HFSE) such as Nb and Ta, slight depletion in Ti, and minor enrichment in Zr. The Nb/Ta and Zr/Hf ratios closely resemble primitive mantle values, reflecting typical mantle-derived magmatic characteristics. This suggests that crustal contamination was limited, while lithospheric contamination played a more dominant role. Late Carboniferous basalts show greater depletion in large-ion lithophile elements (LILE) and higher Mg# compared with Early Permian basalts. The Zr-TiO_₂ tectonic discrimination diagrams indicate that Late Carboniferous basalts exhibit MORB-like affinities, whereas Early Permian basalts are more enriched in large-ion lithophile elements and rare earth elements, showing intraplate basalt characteristics, indicating divergent dynamic mechanisms between the two stages. Following the closure of the North Tianshan Ocean in the Late Carboniferous, due to slab breakoff, post-collisional extension prevailed under a weakly extensional tectonic regime. By the Early Permian, the post-collisional extensional regime changed, and delamination of the subducted slab occurred beneath the Bogda area. With the influx of abundant slab-derived fluids, trace elements were progressively enriched in some mafic rocks, and geochemical indices of certain mafic rocks exhibited intraplate basalt characteristics. The two episodes of extension with contrasting dynamic mechanisms during the Late Carboniferous and Early Permian in the Bogda area impose important constraints on the nature of the southern margin of the Junggar Basin. 

Mineralization Characteristics of the Intrusions in the Wunugetushan Porphyry Cu-Mo Deposit, Inner Mongolia: Constrained by Geochronology, Oxygen Fugacity and Water Content

WANG Lingyue, LAI Yong, SHI Qianxiong

2026, 62(4):  809-818.  DOI: 10.13209/j.0479-8023.2026.021

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Using laser ablation-inductively coupled plasma mass spectrometry (LA-ICP-MS), U-Pb dating and in-situ trace element analysis were performed on magmatic zircons from monzogranite porphyry and quartz porphyry in the Wunugetushan mining area, Inner Mongolia, to constrain the nature of the ore-forming magma and explore the main controlling factors of porphyry mineralization. The results show that the zircon U-Pb age of the monzogranite porphyry is 180.9±0.67 Ma, consistent with the previously reported molybdenite Re-Os age (≈180 Ma); the zircon U-Pb age of the quartz porphyry is 202.6±1.4 Ma, indicating that it is a pre-mineralization intrusion. Zircons from the syn-mineralization monzogranite porphyry exhibit significant positive Ce and Eu anomalies and high oxygen fugacity (ƒ_O2 is from −14.6 to −12.9, ΔFMQ is from +2.3 to +3.5), whereas zircons from the barren quartz porphyry show lower Ce and Eu anomalies and lower oxygen fugacity (ƒ_O2 is from −17.1 to −9.8, ΔFMQ is from −0.5 to +2.0). Both monzogranite porphyry and quartz porphyry zircons display high 10000×δEu/Y ratios and low Dy/Yb ratios, reflecting similar magmatic water contents. The zircon geochemical characteristics indicate that the primary magma of the ore-bearing monzogranite porphyry is characterized by high oxygen fugacity and water richness, whereas the primary magma of the barren quartz porphyry has relatively high water content but low oxygen fugacity, revealing the critical control of magmatic oxygen fugacity on porphyry mineralization potential. In the context of regional tectonic evolution, the Early Jurassic syn-mineralization period of the Wunugetushan deposit was likely influenced by the subduction of the Mongol-Okhotsk Ocean, with resulting partial melting generating the high oxygen fugacity, water-rich magma essential for mineralization. 

Geochemical Characteristics of the Ediacaran-Cambrian Boundary Strata in Bayan Gorge, Western Mongolia: Implications for Paleoeceanic Redox Prior to the Cambrian Explosion

ZHENG Aonan, LIU Jianbo, Ezaki Yoichi, Adachi Natsuko, Altanshagaid Gundsambuu, Batkhuyag Enkhbaatard, Dorj Dorjnamjaa

2026, 62(4):  819-837.  DOI: 10.13209/j.0479-8023.2026.043

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We conducted high-resolution geochemical analyses on carbonate rocks from the Ediacaran-Cambrian (E-C) boundary strata at the Bayan Gorge section, western Mongolia. The dataset includes rare earth elements (REE), major and trace elements, inorganic carbon and oxygen isotopes. Evaluating the preservation of primary REE signals against diagenetic alteration and detrital input, we reconstructed the temporal evolution of local seawater redox conditions. The results reveal a transient but significant oxygenation event during the early Fortunian Stage of the Cambrian, followed by pronounced redox fluctuations. The redox proxy (Ce/Ce*)_SN decreased markedly following the BACE (Basal Cambrian Carbon Isotope Excursion) event, reaching a minimum value of 0.57, indicative of rapid seawater oxidation. Subsequently, (Ce/Ce*)_SN values gradually increased to near 1.0, reflecting a return to more reducing conditions. The Th/U ratio exhibits a synchronous trend with Ce anomalies, further supporting a scenario of rapid redox oscillations and phased changes in seawater redox state. This study provides the first high-resolution redox record across the E-C boundary from western Mongolia, filling a critical geographic gap in global redox reconstructions. This study offers new geochemical evidence for understanding the environmental dynamics that preceded the Cambrian Explosion.

Some Ideas on the Development of New Energy Geography

LI Shuangcheng, ZHANG Yajuan, WANG Zheng, LIU Laibao, LI Delong, LI Yan, WANG Yang

2026, 62(4):  838-850.  DOI: 10.13209/j.0479-8023.2025.050

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Based on the development history of energy geography and its energy transition, this article proposes some ideas for the development of new energy geography from the perspective of geography. Firstly, the definition of new energy geography is provided. Continuing the disciplinary connotation of traditional energy geography, it is defined as the applied geography that studies the spatial and temporal characteristics, exploitation potential and influencing factors, process and pattern of production and consumption, and socio-economic and ecological effects of new energy resources such as wind and photovoltaics. Secondly, the scientific logic of constructing new energy geography is elaborated. We believe that, compared with traditional fossil energy, factors affecting wind and photovoltaic resources and their development and utilization have a high degree of spatiotemporal heterogeneity due to the influence of atmospheric circulation, solar radiation, and underlying surface processes, making them the most geographically characteristic research objects. Thirdly, key geographical characteristics of new energy including scale dependence and regional differentiation are proposed. Scale dependence is reflected in the multi-scale spatiotemporal variation of wind and solar resources, the feedback effects between atmospheric processes at different scales and wind farms, as well as the scale effects on the degree and scope of impacts on ecological environment, economic viability, and social acceptance. As physical entities, new energy infrastructure is always situated in specific geographical environments, exhibiting significant regional differentiation characteristics in terms of the climate and ecological effects of its production and operation under the constraints of atmospheric processes. On this basis, some priority research topics under the framework of new energy geography are proposed, including the underpinning land surface processes mechanism forming the spatiotemporal distribution of wind and solar energy, the geographical spatial characteristics of wind and solar energy production and consumption, the impact of the resilience and robustness of new energy supply on socio-economic systems, the impact of future climate change on new energy systems, the climate effects of large-scale new energy construction, the ecological environment and health effects of new energy construction, and the perception of new energy landscapes and cultures. Finally, the technologies and methods of new energy geography research, including geospatial inversion, climate model analysis, energy simulation, ecological environment response analysis, multi-scale dynamic simulation and artificial intelligence technology, are proposed. 

Spatiotemporal Patterns and Driving Factors of Cropland Abandonment in Zhangjiakou City

XU Tong, HUANG Jingyu, XU Yongqin, JI Zhengxin, XU Yueqing

2026, 62(4):  851-861.  DOI: 10.13209/j.0479-8023.2026.049

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In response to the growing threat of intensified cropland abandonment to food security in the mountainous areas of northern Hebei, this study selected Zhangjiakou City as the study area. Based on the Google Earth Engine (GEE) platform and Sentinel-2 remote sensing imagery, the continuous change detection and classification (CCDC) algorithm was employed to identify the spatiotemporal patterns, occurrence frequency, and trajectory characteristics of abandoned cropland from 2019 to 2023, and to explore the driving factors of cropland abandonment. The results were as follows. 1) During the study period, the total area of abandoned cropland in Zhangjiakou increased from 329.12 km² to 449.41 km², showing a fluctuating upward trend, with an average annual abandonment rate of 4.18%. Spatially, cropland abandonment in the Bashang Plateau region was relatively concentrated, followed by the central and southern river valley basins, while the eastern mountainous and hilly areas had the least, showing clear regional differentiation and a predominantly high–high spatial clustering pattern. 2) In terms of frequency, cropland abandoned twice was dominant, followed by cropland abandoned three times, while cropland abandoned once or more than three times accounted for a relatively small proportion. The latitudinal distribution of abandonment frequency showed a “two-peak and one-trough” pattern, whereas the longitudinal distribution displayed “more in the west and fewer in the east, with multiple peaks and valleys”. 3) In terms of trajectory, newly abandoned cropland was dominant, mostly distributed in the eastern mountainous and hilly region. Reclaimed abandoned cropland ranked second, concentrated in the Yuxian–Yangyuan basin. Fluctuating and regular abandonment ranked third and fourth, respectively, both mainly occurring in the Bashang Plateau. 4) Elevation, slope, and GDP exhibited promoting effects on cropland abandonment in most areas, while population size and distance to roads were predominantly inhibitory. The influencing intensity of each driving factor decreased sequentially in the order of GDP, population size, elevation, slope, and distance to roads.

Bibliometric Analysis of Research on Land Use and Carbon Budget Based on CiteSpace

WANG Qiaoling, LI Shuangcheng

2026, 62(4):  862-872.  DOI: 10.13209/j.0479-8023.2026.047

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Based on the Web of Science core collection, this study analyzed literature published between 1992 and 2024 to identify the current status and development trends in land use and carbon budget research. The results revealed a transition from fundamental theoretical construction to multidisciplinary integration, with research themes expanding from core concepts such as “carbon budget” and “carbon sequestration” to policy-driven topics including “carbon neutrality” and “urbanization.” Key research directions include forest carbon sinks, soil carbon stocks, remote sensing applications, and regional land-use optimization. The research paradigm gradually evolved from a single-disciplinary focus toward comprehensive governance and practice-oriented applications. Looking ahead, with the advancement of carbon neutrality strategies and the growing demand for global climate governance, future research will increasingly rely on remote sensing technologies, big data modeling, and interdisciplinary collaboration to support systematic land-use optimization and carbon reduction pathways, thereby providing robust scientific support for low-carbon and sustainable development.

Characterization of the Spatio-Temporal Evolution of Landslide Susceptibility in Yunnan Province

ZHU Yilin, PENG Shuangyun, LIN Zhiqiang, LI Ting, PAN Xianchun

2026, 62(4):  873-888.  DOI: 10.13209/j.0479-8023.2025.112

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Based on six periods of landslide inventory data in Yunnan Province from 1986 to 2016, a weighted information value-logistic regression (WIV-LR) model integrated with geodetector was developed, and the spatio-temporal evolution of the resulting landslide susceptibility maps was analyzed. The results indicate that: 1) WIV-LR model demonstrated good predictive performance for all six periods, with AUC values ranging from 0.781 to 0.873. 2) The spatio-temporal evolution of landslide susceptibility exhibited clear and systematic patterns, characterized by a continuous expansion of high-susceptibility areas (with their proportion increasing from 35.52% to 50.27%), a concentration of high-susceptibility zones in western, central, and southern Yunnan, and a regular migration of the susceptibility centroid, showing a southward shift, followed by an eastward movement and a subsequent return toward the northwest. 3) Geodetector analysis revealed the driving mechanisms underlying these evolutionary patterns, indicating that the most influential factors exhibited stage-dependent characteristics, with seismic intensity playing a dominant role during the T1 period, rainfall exerting a stronger influence during the T4 period, and the impact of human activities becoming increasingly significant in later periods. 4) The spatio-temporal evolution of landslide susceptibility exhibited a high degree of consistency with the dynamic changes in key influencing factors. These findings provide a scientific reference for the dynamic identification and prevention of landslide risks in regions characterized by similarly complex geological environments.

Hierarchical Characteristics of Streamflow in Typical Sub-basins of the Yellow River

LI Zhenqi, LIU Changhui, WANG Yichu

2026, 62(4):  889-900.  DOI: 10.13209/j.0479-8023.2026.026

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This study focuses on typical 5th-order sub-basins within the Yellow River Basin, integrating climatic, underlying surface, and streamflow data to examine how river network structure affects the hierarchical characteristics of streamflow. Based on Horton’s laws, this study reveals that the streamflow ratio (R_Q) exhibits statistically significant self-similarity within stream levels 1–3 in the 5th-order sub-basins, consistent with the self-similar ranges of structural parameters such as bifurcation ratio (R_B), length ratio (R_L), and area ratio (R_A). Among these, R_A serves as a key reference template for streamflow hierarchy, with 75% of the sub-basins showing an  ratio between 0.95 and 1.05. Additionally, 65% of the sub-basins have  values below 1, indicating that under semi-arid climatic conditions, the growth of streamflow with stream order is generally slower than the areal expansion rate of contributing sub-basins. Further analysis demonstrates significant positive correlations (R > 0.5, p < 0.05) between  and precipitation, aridity index, and soil moisture, suggesting that sub-basins with higher rainfall and more substantial groundwater recharge exhibit a more pronounced increase in streamflow with stream order and drainage area. These findings highlight the synergistic influence of river network structure and basin characteristics on streamflow hierarchy, offering insights for water resource management in basins with diverse river network morphologies.

Research on Efficiency Morphology of Homestead Utilization and Ecological Association Morphology Based on Town and Village Divisions: A Case Study of 235 Villages in Jinghai District, Tianjin City

ZHANG Yu, XU Hengzhou

2026, 62(4):  901-914.  DOI: 10.13209/j.0479-8023.2025.086

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 To construct a measurement model for efficiency morphology of homestead utilization (EMHU) and ecological association morphology (EAM), taking town and village as two research scales, this paper explores the spatial differentiation of EMHU and EAM from three perspectives including policy, resource and location orientation, so as to offer references for the sustainable utilization of homestead resources. Taking 235 villages in Jinghai District, Tianjin as the study case, unexpected output super-efficiency SBM model, ecological environment index and coupling coordination model are adopted. Research results show that: 1) from the perspective of policy guidance, the average EMHU value of characteristic towns is better than that of ordinary towns, and EAM shows the opposite trend. The EMHU and EAM of characteristic towns are mainly concentrated in low levels; the EMHU distribution of general towns is relatively balanced, and the EAM is mainly distributed in high levels. 2) From the perspective of resource orientation, the average EMHU value of industry-led towns is better than that of culture-led towns, and vice versa for EAM. The EMHU of industry-led towns is evenly distributed, with EAM mainly concentrated in low-level areas, and vice versa for culture-led towns. 3) Overall, the EMHU of culture-led towns in characteristic towns is higher than that of industry-led towns in general towns, while in general towns the EAM of medium industry-led towns is the strongest, and the EAM of industry-led towns among characteristic towns is the weakest. 4) From the perspective of village division, the increase in location advantages will cause EMHU and EAM to show a positive U-curve. The trends of EMHU and EAM at different scales and different perspectives are traceable, and show obvious spatial differentiation. Different scales and different perspectives should be considered when promoting the harmonious coexistence of rural life and ecology to realize rural revitalization. 

Spatio-Temporal Characteristics and Influencing Factors of Methane Emissions from the Irrawaddy River in Yunnan

DAI Xiaoqian, LIANG Ni, YANG Pinghong, ZHANG Liwei, ZHOU Yongqiang

2026, 62(4):  915-923.  DOI: 10.13209/j.0479-8023.2026.048

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Although numerous studies have investigated CH₄ emissions from river systems globally, observational data remain scarce for transboundary rivers in southwestern China. Focusing on the Yunnan section of the Irrawaddy River, this study carried out cross-seasonal sampling from October 2022 to December 2023. Dissolved CH₄ concentrations in the river surface water were measured using the headspace equilibrium technique, while diffusive CH₄ fluxes across the water–air interface were quantified using the floating chamber method. The spatiotemporal distribution patterns of CH₄ and their controlling factors were systematically analyzed. The results showed that riverine CH₄ concentrations ranged from 5.6 to 476.5 nmol/L, with a mean concentration of 64.0±98.4 nmol/L. The river was consistently supersaturated with CH₄ relative to the atmosphere (mean: 2213%±3498%; range: 162%–17024%). Diffusive CH₄ fluxes ranged from 0.004 to 1.22 mmol/(m²∙d), with a mean flux of 0.26±0.22 mmol/(m²∙d). CH₄ concentrations were higher in spring and summer, yet lower in autumn and winter. Diffusive fluxes exhibited a distinct seasonal pattern, being highest in spring and lowest in summer. Analysis of environmental drivers revealed that dissolved organic carbon (DOC), acting as a carbon substrate, was present at low concentrations, potentially limiting CH₄ production. Concurrently, suspended sediments in the water column appeared to inhibit the diffusive release of CH₄. Comparative analysis with CH₄ observations from other subtropical rivers indicated that both the concentration and diffusive flux of CH₄ in the Yunnan section of the Irrawaddy River were relatively low overall. Consequently, this river section functions as a weak source of atmospheric CH₄. 

Will Artificial Intelligence (AI) Completely Replace Humans? II. Task-Process-Based Model of Human-AI Division of Labor and Collaboration

WANG Haizhen, ZHANG Yan

2026, 62(4):  924-940.  DOI: 10.13209/j.0479-8023.2026.023

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Current human-AI collaboration (HAIC) research suffers from fragmented collaborative taxonomies and a lack of systematic alignment with task characteristics. To address these gaps, this study constructs a modular HAIC design framework grounded in the task-process model. On the basis of analyzing ten critical task characteristics, the framework defines eleven fundamental collaborative sub-patterns spanning task input, processing, and output stages, while clarifying their underlying combination rules. Finally, utilizing six representative team tasks — such as new product development and multidisciplinary consultation — we demonstrate how to sequentially select and adapt collaborative sub-patterns based on specific multi-stage and multi-dimensional task features. By providing a comprehensive, multi-feature, and modular theoretical collaboration framework, this research integrates fragmented collaborative models and advances HAIC design to an operational level. These findings offer both theoretical support and a practical roadmap for organizations to systematically plan and optimize human-AI collaborative workflows.