Search Results (60)

The construction of the Archaeological Site Prediction Model (ASPM) and quantitative research on the driving mechanisms of influencing factors are key to better understanding the multidimensional interactions between ancient humans and the environment. They also constitute an essential technical approach for guiding field archaeological survey and excavation. This study aims to develop a highly stable, accurate, and interpretable predictive model for archaeological sites in the Chongqing Three Gorges region (CQTGR). BP neural network prediction (BPNN) has been applied in various fields, but its random initial weights and thresholds often lead to suboptimal accuracy and weak interpretability. To address these issues, this study constructs BPNN optimized with a Bayesian algorithm to enhance its accuracy. Additionally, it integrates the SHAP model to quantitatively identify nonlinear interactions and threshold effects of influencing factors, thereby improving its interpretability. The results indicate that: (1) The BPNN-based prediction model outperforms other conventional models. After hyperparameter optimization using the Bayesian algorithm, the AUC (area under the ROC curve) on the test set increases by 0.0812, reaching a final value of 0.8815. This indicates that the optimization model is effective and that the model exhibits strong predictive capability. (2) Archaeological sites exhibit a tiered and linear corridor distribution pattern along the Yangtze River and its major tributaries. This pattern can be divided into five concentric tiers radiating outward from the core of the main river systems. High-probability zones are particularly clustered in the low-lying and flat river valleys. (3) The distribution of archaeological sites is comprehensively influenced by both the natural environment and human activities. Elevation and river systems are key driving factors, with NDVI and land use also exerting significant influence. The major factors demonstrate notable threshold and interaction effects. Areas where the interaction between factors exhibits positive enhancement are often the core areas of archaeological site distribution. This research not only provides a precise scientific basis for the preventive protection and monitoring of potential distribution areas of archaeological sites but also offers decision support for the spatial conservation planning of these sites. Full article

The long-term stability of submerged sandbars and protected shorelines in large alluvial rivers depends on the serviceability of flexible mattresses installed on the riverbed. Distributed fiber optic sensing is one of the few practical methods for monitoring deformation along these underwater systems over engineering-scale distances. Yet BOTDR-derived strain-difference profiles are often heavily contaminated by noise and rarely have reliable clean references. To address this issue, this study develops TrendBlend-BSFormer, a blind self-supervised denoising framework for in situ BOTDR strain data from underwater flexible mattresses. The framework combines four key features: blind-spot masking, a one-dimensional encoder decoder backbone, a Transformer bottleneck for long-range spatial dependence, and a multi-scale trend-detail blending branch with dual signal-noise heads. The framework was validated using annual and daily BOTDR field data from the Yudaizhou shoreline protection project in the Yangtze River, containing 9343 and 9875 valid measurement points, respectively. TrendBlend-BSFormer achieved pseudo-SNR/RMSE/MAE values of 14.22 dB, 15.03 με and 12.05 με for the annual data set and 5.32 dB, 8.02 με and 6.45 με for the daily data set, improving the pseudo-SNR by 1.45 dB and 2.95 dB relative to the published BiLSTM-CNN benchmark. It also reduced the high-frequency energy ratio from 0.172 to 0.011 for the annual data and from 0.424 to 0.112 for the daily data. The denoised profiles suppress isolated spikes while preserving mechanically plausible peaks, valleys, and short-range fluctuations, indicating that blind self-supervised denoising can provide a more physically credible strategy for BOTDR-based monitoring in complex underwater environments. Full article

As a mountain–water city in the upper Yangtze River region, Chongqing is characterized by complex river-valley terrain, dense riverside development, extreme summer heat, high humidity, and frequent calm-wind conditions. Existing studies on waterfront thermal comfort mainly focus on plain cities, whereas mountainous riverside parks remain insufficiently understood. This study investigated summer thermal comfort in three riverside parks in Chongqing—Jiulongtan Park, Coral Park, and Jiangtan Park—through field measurements of air temperature, black globe temperature, wind speed, relative humidity, and Thermal Radiation, combined with thermal sensation vote (TSV) and thermal comfort vote (TCV) surveys. Results showed that the maximum air temperature reached 43.7 °C and the maximum black globe temperature reached 61.6 °C. The hydrophilic layer recorded the highest wind speed (1.64 ± 0.39 m/s), while the elastic layer showed high PET values (36.00–46.10 °C). Regression analysis indicated neutral PET values of 32.49–35.74 °C. Correlation analysis showed that PET, mean thermal sensation vote (MTSV), and mean thermal comfort vote (MTCV) were positively correlated with air temperature, black globe temperature, mean radiant temperature (T_mrt), and relative humidity. In contrast, PET was negatively correlated with wind speed. This study reveals the coupled effects of river-valley terrain, elevation stratification, waterfront microclimate, and landscape elements on outdoor thermal comfort, providing a scientific basis for optimizing shading, ventilation, and hydrophilic spaces in hot-humid mountain–water cities. Full article

Anthropogenic night light (ANL) provides a unique observable for the spatially explicit mapping of human-modified landscapes in the form of lighted infrastructure. Since 2013, the Visible Infrared Imaging Radiometer Suite (VIIRS) Day Night Band (DNB) on the Suomi NPP satellite has provided more than a decade of near-daily observations of anthropogenic night light. The objective of this study is to quantify changes in ANL in developed eastern China post-2013 using VIIRS DNB monthly mean brightness composites. Specifically, to constrain sub-annual and interannual changes in night light brightness to distinguish between apparent and actual change of ANL sources, and then conduct a spatiotemporal analysis of observed changes to identify areas of human activity, urban development and rural electrification. This analysis is based on a combination of time-sequential bitemporal brightness distributions and quantification of the spatiotemporal evolution of night light using Empirical Orthogonal Function (EOF) analysis. Bitemporal brightness distributions show that bright (>~1 nW/cm²/sr) ANL is heteroskedastic, with temporal variability diminishing with increasing brightness. Hence, brighter lights are more temporally stable. In contrast, dimmer (<~1 nW/cm²/sr) ANL is much more variable on monthly time scales. The same patterns of heteroskedasticity and variability of the lower tail of the brightness distribution are observed in year-to-year distributions. However, year-to-year brightness increases vary somewhat among different years. While bivariate distributions quantify aggregate changes on both subannual and interannual time scales, spatiotemporal analysis quantifies spatial variations in the year-to-year temporal evolution of ANL. The spatial distribution of brightening (and, much less commonly, dimming) revealed by the EOF analysis indicates that most of the brightening since 2013 has occurred at the peripheries of large cities and throughout the networks of smaller settlements on the North China Plain, the Yangtze River Valley, and the Sichuan Basin. A particularly unusual pattern of sequential brightening and dimming is observed on the Loess Plateau north of Xi’an, where extensive terrace construction has occurred. All aspects of this analysis highlight the difference between apparent and actual changes in night light sources. This is important because many users of VIIRS night light attribute all observed changes in imaged night light to actual changes in anthropogenic light sources—without consideration of low luminance variability related to the imaging process itself. Full article

The analysis of changing trends of river runoff and sediment discharge and the exploration of their causes are of great significance for formulating sustainable development measures for river basin systems. Based on methods such as trend test, mutation detection, and regression analysis, this study conducts a systematic comparative research on the water–sediment processes in the river reach where large-scale cascaded reservoirs connected end to end are located in the upper Yangtze River, and obtains the following key research progress: For the study reach (between Sanduizi and Xiangjiaba Stations), during the period of 1966–2023, the change rates of annual incoming and outgoing runoff were 2.88 × 10⁸ m³·yr⁻¹ and −0.186 × 10⁸ m³·yr⁻¹, respectively, accounting for 0.017% and 0.013% of the annual average runoff. The changing trends were not significant. During the same period, the change rates of Suspended Sediment Load (SSL) at the inlet and outlet of this river reach were −8.0 × 10⁵ t·yr⁻¹ and −46 × 10⁵ t·yr⁻¹, respectively, accounting for 1.25% and 2.45% of their respective annual average sediment discharge. The SSL showed a significant decreasing trend, which was particularly characterized by a sharp reduction at the outlet. The massive sediment retention and multi-mode operation of cascaded reservoirs are the fundamental reasons for the variation in the water–sediment relationship and the sharp decrease in annual SSL in this reach, and they also lead to an obvious adjustment of water and sediment in the river basin that “cuts peaks and fills valleys” within a year. Climate change and other human activities have reduced the sediment input in the study reach. Looking forward to the next few decades, climate factors will remain the dominant factor affecting the inter-annual variation in runoff in the study area. In contrast, human activities such as reservoir operation will continue to fully control the sediment output of the river reach and also restrict the annual distribution of water and sediment. The results of this study can provide a reference for predicting the changing trends of water and sediment in similar river reaches with cascaded reservoir groups and formulating effective river management measures. Full article

The formation, development, and spatial distribution of CUHIs are influenced by urban spatial heterogeneity, yet the scale and seasonal dependencies of the effects of urban morphology modulation on CUHIs have not been fully explored, needing further study. Based on multi-source data for the Yangtze-Huaihe River Valley (YHRV), this study employs the XGBoost model to systematically investigate the effects of two-dimensional (2D)/three-dimensional (3D) urban morphological indicators on CUHIs and their inherent scale–seasonal dependencies. Results show significant provincial heterogeneity in YHRV’s CUHIs: Shanghai exhibits the highest CUHI intensity (CUHII) across all seasons, with a peak of 1.55 °C in winter, followed by Zhejiang and Jiangsu. Seasonally, winter CUHII averages 0.6–0.8 °C (the highest), followed by autumn, while spring and summer have lower values. The effect of the modulation of urban morphology on CUHIs exhibits distinct spatiotemporal dependence: in winter and autumn, CUHII is mainly dominated by the percentage of landscape (PLAND) and largest patch index (LPI) at the 4 km buffer scale (correlation coefficients r = 0.475 and 0.406 for winter); in spring and summer, the 2 km buffer scale shows a more balanced regulatory role of multiple urban morphological indicators. Notably, 2D indicators of urban morphology are consistently more influential in regulating CUHIs than 3D indicators. The Hefei station case effectively validates the model’s sensitivity to changes in urban morphology. This study provides a quantitative basis for season–scale collaborative regulation of urban thermal environments in the YHRV. Future research will integrate climatic factors into XGBoost via screening, reconstruction, and interaction quantification to enhance its predictability for transient heat island processes. Full article

Urban particulate matter (PM) pollution critically impacts public health and climate. However, traditional ground-based monitoring fails to resolve vertical PM distribution, limiting understanding of transport and stratification-coupled mechanisms. Vertical profiles collected by an unmanned aerial vehicle (UAV) over Hangzhou, a core megacity in China’s Yangtze River Delta, reveal the spatiotemporal heterogeneity and multi-scale drivers of regional PM pollution during two intensive ten-day campaigns capturing peak pollution scenarios (winter: 17–26 January 2019; summer: 21–30 August 2019). Results show stark seasonal differences: winter PM₁ and PM_2.5 averages were 2.6- and 2.7-fold higher (p < 0.0001) than summer. Diurnal patterns were bimodal in winter and unimodal (single valley) in summer. Vertically consistent PM₁ and PM_2.5 distributions featured sharp morning (08:00) concentration increases within specific layers (winter: 250–325 m; summer: 350–425 m). Analysis demonstrates multi-scale coupling of synoptic systems, boundary layer processes, and vertical wind structure governing pollution. Key mechanisms include a winter “Transport-Accumulation-Reactivation” cycle driven by cold air, and summer typhoon circulation influences. We identify hygroscopic growth triggered by inversion-high humidity coupling and sea-breeze-driven secondary aerosol formation. Leveraging UAV-based vertical profiling over Hangzhou, this study pioneers a three-dimensional dissection of layer-coupled PM dynamics in the Yangtze River Delta, offering a scalable paradigm for aerial–ground networks to achieve precision stratified control strategies in megacities. Full article

Under global warming, persistent extreme heat events (PHEs) in China have increased significantly in both frequency and intensity, posing severe threats to agriculture and socioeconomic development. Combining observational analysis (1961–2019) and numerical simulations, this study investigates the distinct impacts of Northwest Pacific (NWP) and North Atlantic (NA) sea surface temperature (SST) anomalies on PHEs over China. Key findings include the following: (1) PHEs exhibit heterogeneous spatial distribution, with the Yangtze-Huai River Valley as the hotspot showing the highest frequency and intensity. A regime shift occurred post-2000, marked by a threefold increase in extreme indices (+3σ to +4σ). (2) Observational analyses reveal significant but independent correlations between PHEs and SST anomalies in the tropical NWP and mid-high latitude NA. (3) Numerical experiments demonstrate that NWP warming triggers a meridional dipole response (warming in southern China vs. cooling in the north) via the Pacific–Japan teleconnection pattern, characterized by an eastward-retreated and southward-shifted sub-tropical high (WPSH) coupled with an intensified South Asian High (SAH). In contrast, NA warming induces uniform warming across eastern China through a Eurasian Rossby wave train that modulates the WPSH northward. (4) Thermodynamically, NWP forcing dominates via asymmetric vertical motion and advection processes, while NA forcing primarily enhances large-scale subsidence and shortwave radiation. This study elucidates region-specific oceanic drivers of extreme heat, advancing mechanistic understanding for improved heatwave predictability. Full article

This study presents a comprehensive analysis of the microphysical structures of Meiyu heavy rainfall (near-surface rainfall intensity > 8 mm/h) across different life stages in the Yangtze-Huaihe River Valley (YHRV). We classified the heavy rainfall events into three life stages of developing, mature, and dissipating using ERA5 reanalysis and IMERG precipitation estimates, and examined vertical microphysical structures using Dual-frequency Precipitation Radar (DPR) data from the Global Precipitation Measurement (GPM) satellite during the Meiyu period from 2014 to 2023. The results showed that convective heavy rainfall during the mature stage exhibits peak radar reflectivity and surface rainfall rates, with the largest near-surface mass weighted diameter (D_m ≈ 1.8 mm) and the smallest droplet concentration (dBN_w ≈ 38). Downdrafts in the dissipating stage preferentially remove large ice particles, whereas sustained moisture influx stabilizes droplet concentrations. Stratiform heavy rainfall, characterized by weak updrafts, displays narrower particle size distributions. During dissipation, particle breakups dominate, reducing D_m while increasing dBN_w. The analysis of the relationship between microphysical parameters and rainfall rate revealed that convective heavy rainfall shows synchronized growth of D_m and dBN_w during the developing stage, with D_m peaking at about 2.1 mm near 70 mm/h before stabilizing in the mature stage, followed by small-particle dominance in the dissipating stage. In contrast, stratiform rainfall exhibits a “small size, high concentration” regime, where the rainfall rate correlates primarily with increasing dBN_w. Additionally, convective heavy rainfall demonstrates about 22% higher precipitation efficiency than stratiform systems, while stratiform rainfall shows a 25% efficiency surge during the dissipation stage compared to other stages. Full article

The Jinjingzui gold (Au) deposit is located in the central part of Edong, China. The theoretical gold reserves are large with significant potential for mining and future development. This deposit is the only Au-bearing deposit discovered in the Middle-Lower Yangtze River Valley Metallogenic Belt, which has existing ore bodies that are mainly diorite. Re–Os dating of molybdenite from the Jinjingzui deposit confirm that the deposit formed in the Lower Cretaceous period, with an isochron age of 138.5 ± 2.7 Ma. The geochemical data of the rocks indicate that the diorite contains 54.75% to 56.66% SiO₂, 5.68% to 8.94% Fe₂O₃, 2.05% to 2.19% MgO, and 1.06% to 1.08% TiO₂, and with enrichment of large-ion lithophile elements (e.g., Rb and Ba). High-field-strength elements U-Nb–Ti displayed strong negative anomalies. Six pyrites from the Jinjingzui Au deposit δ³⁴S_V-PDB(‰) ranged from −2.4% to −8.4%, with an average value of −3.1%, and ²⁰⁶Pb~²⁰⁴Pb, ²⁰⁷Pb~²⁰⁴Pb, ²⁰⁸Pb~²⁰⁴Pb contents ranged from 17.77–18.58, 15.48–15.67 to 37.91–39.05, with average values of 18.14, 15.59 and 38.49, respectively. These values indicate that the metallic components originated from the upper mantle and lower crust. The Re concentrations in the molybdenites are significantly higher than those in other ores within the district (847.91~2018.58 × 10⁻⁶), suggesting a significant mantle component was involved in the mineralization process. Full article

A new meteorological station (DMS) was established at the Morning Glory summit in Zhejiang Province to provide regional background information on atmospheric composition in the Yangtze River Delta (YRD) region, China. This study investigated the first carbon monoxide (CO) records at DMS from September 2020 to January 2022. The annual average concentration of CO was 233.4 ± 3.8 ppb, which exceeded the measurements recorded at the other Asian background sites. The winter CO concentration remained elevated but peaked in March in the early spring due to the combined effect of regional emissions within the YRD and transportation impacts of North China and Southeast Asia sources. The diurnal cycle had a nocturnal peak and a morning valley but with a distinct afternoon climb, as the metropolis in the YRD contributed to a local concentration enhancement. The back trajectory analysis and the Weighted Potential Sources Contribution Function (WPSCF) maps highlighted emissions from Anhui, Jiangxi, Zhejiang, and Jiangsu provinces as significant sources. Due to well-mixed air conditions and fewer anthropogenic influences, DMS records closely aligned with the CO averages derived from the Copernicus Atmospheric Monitoring Service (CAMS) covering the YRD, confirming its representativeness for regional CO levels. This study underscored DMS as a valuable station for monitoring and understanding CO spatiotemporal characteristics in the YRD region. Full article

Extensive and profound landscape alterations significantly contribute to ecological vulnerability in environmentally delicate regions. Existing research primarily emphasizes ecological risks caused by landscape alterations, while overlooking vulnerable characteristics of landscape functions; particularly lacking are studies on the driving mechanism of landscape ecological risk through the reciprocal relationship between landscape pattern risk and function risk. Based on these issues, this paper constructed a landscape pattern risk index (LPRI), a landscape function risk index (LFRI), and a landscape ecological risk index (LERI) in the counties of the dry–hot valley of the Jinsha River in southwest China. By employing a coupling degree and a coordination model, we analyzed temporal and spatial variations in the interaction between two types of ecological risk, thereby revealing the driving mechanisms of landscape ecological risk. The results indicated that the average LPRI values of the study area were 0.373, 0.327, and 0.427, respectively, while the average LFRI values were 0.451, 0.356, and 0.442 in 2000, 2010, and 2020, respectively. More than 90% of the study area exhibited a medium coupling relationship between the two types of ecological risks. The area proportion of the coupling coordination regions has increased from 25.58% to 31.07% from 2010 to 2020. The two types of risk exhibited a low level of constraint inhibition. Extremely evident expansion of high pattern–function risk areas and the area increase of coupling coordination region resulted in the acceleration of regional landscape ecological risk level. Increasing competition between market-driven land-use activities and ecological regulations from the government has rendered the diversification of landscape ecological risk sources and its underlying mechanisms intricate. This study serves as a model reference for assessing landscape ecological risk and a theoretical basis for sustainable landscape management and ecological regulation in the Yangtze River basin. Full article

The Lujiang–Chuzhou Metallogenic Area is an important component of the Middle–Lower Yangtze River Valley Metallogenic Belt. Despite being an important copper–gold deposit in this area, the Shanlixu skarn Cu-Au deposit has not yet been systematically studied. According to LA-ICP-MS zircon U-Pb dating, the quartz monzonite porphyry from the Shanlixu deposit is aged 137.5 ± 1.7 Ma: while it differs from the timing of the magmatism and related mineralization in the Lujiang–Chuzhou Area, it is consistent with magmatic activity elsewhere in the Middle–Lower Yangtze River Valley Metallogenic Belt. The Ce⁴⁺/Ce³⁺ values of zircon in the quartz monzonite porphyry vary from 204.5 to 886.5, indicating that the intrusion might have formed in an environment with high oxygen fugacity. Additionally, the quartz monzonite porphyry exhibits high contents of Al₂O₃, Sr, Ba, and Mg^# (Mg^# = Mg²⁺/(Mg²⁺ + Fe²⁺)) and low ratios of Y, Nb, Ta, and K₂O/Na₂O, showing geochemical characteristics similar to those of adakitic rocks. Based on these characteristics, it is suggested that the intrusion might have been derived from the partial melting of subducted oceanic crust under a continental arc margin setting. Furthermore, it is strongly indicated that the quartz monzonite porphyry from the Shanlixu deposit, in the Lujiang–Chuzhou Area, is closely related to Cu-Au mineralization, as suggested by the age of the intrusion, which is approximately 137 Ma. These findings provide a new direction for research and exploration in this region. Full article

Nanling County, situated on the southern bank of the Yangtze River’s middle and lower reaches in China, and has not yet carried out hydrogeochemical geological surveys. This study is pivotal in ensuring the reliability of the drinking water supply, particularly during emergencies. Utilizing an array of analytical methods—statistical analysis, Shularev classification, Piper trilinear diagram, Gibbs diagram, ion ratio method, and mineral saturation index—this research elucidates the hydrogeochemical characteristics and principal water–salt interactions in Nanling’s shallow groundwater. Our findings, derived from the Shularev classification and Piper trilinear diagram, reveal that, in the southern mountainous and river valley plain regions, the primary hydrogeochemical type of groundwater is HCO₃-Ca. Conversely, in the northern area of Sanli Town and the adjoining plain, groundwater predominantly falls under the HCO₃-Na•Ca category, with some regions showing the characteristics of HCO₃•Cl-Ca, HCO₃•Cl-Na•Ca, and, occasionally, HCO₃•SO₄-Na•Ca. According to the Gibbs diagram analysis, the predominant source of groundwater in this region is attributed to water–rock dissolution processes occurring during groundwater runoff. The increase in Na⁺, Ca²⁺, Cl⁻, HCO₃⁻, and SO₄²⁻ concentrations in the water–rock interaction in the study area is mainly due to the dissolution of rock salt, gypsum, calcite, and dolomite, and the alternating cation adsorption occurs during the reaction. Finally, the mineral saturation index points to the ongoing dissolution of gypsum, calcite, and dolomite, until a state of precipitation–dissolution equilibrium is reached. This comprehensive study provides vital insights into the hydrogeochemical dynamics of Nanling County’s groundwater, contributing significantly to our understanding of regional water quality and its management. Full article

The accumulation of arsenic (As) in rice poses a significant threat to food safety and human health. Breeding rice varieties with low As accumulation is an effective strategy for mitigating the health risks associated with arsenic-contaminated rice. However, the genetic mechanisms underlying As accumulation in rice grains remain incompletely understood. We evaluated the As accumulation capacity of 313 diverse rice accessions grown in As-contaminated soils with varying As concentrations. Six rice lines with low As accumulation were identified. Additionally, a genome-wide association studies (GWAS) analysis identified 5 QTLs significantly associated with As accumulation, with qAs4 being detected in both of the experimental years. Expression analysis demonstrated that the expression of LOC_Os04g50680, which encodes an MYB transcription factor, was up-regulated in the low-As-accumulation accessions compared to the high-As-accumulation accessions after As treatment. Therefore, LOC_Os04g50680 was selected as a candidate gene for qAs4. These findings provide insights for exploiting new functional genes associated with As accumulation and facilitating the development of low-As-accumulation rice varieties through marker-assisted breeding. Full article