Journal of Hydrology最新文献

{"title":"Metagenomic insight reveals the microbial structure and function of nitrous oxide emission from agricultural ditches","authors":"Zhangmu Jing ,&nbsp;Qingqian Li ,&nbsp;Shengqiang Tu ,&nbsp;Yanjie Wei ,&nbsp;Peng Yuan ,&nbsp;Xiaoling Liu ,&nbsp;Hongjie Gao","doi":"10.1016/j.jhydrol.2026.135085","DOIUrl":"10.1016/j.jhydrol.2026.135085","url":null,"abstract":"<div><div>Nitrous oxide (N₂O) is a potent greenhouse gas, with agricultural activities representing its major source. However, the emission mechanism of nitrous oxide efficient by agricultural activities has not yet been fully studied. This study employs metagenomic analysis to elucidate the microbial community structure and functional potential associated with N₂O emissions in river and ditch systems of the Yangtze River Delta. The N₂O dissolved concentration in the rivers (0.08 ± 0.03 μmol N·L⁻¹) was significantly lower than that in the ditches (0.21 ± 0.14 μ mol N·L⁻¹) (<em>P</em> &lt; 0.05). According to eight wind-based models, agricultural ditches emissions were 3.53–4.70 times higher than those of the rivers. All models significantly overestimated fluxes (<em>P</em> &lt; 0.05), revealing a systematic overestimation of EF values when using the Intergovernmental Panel on Climate Change (IPCC) methodology. Particulate organic carbon supported microbial activity by providing energy and adhesion sites, while electrical conductivity (EC) served as an indicator of ion inputs from surrounding land use, serving as a critical abiotic driver of EF values in the ditches. The co-occurrence network showed that denitrification genes (<em>norB</em>, <em>nirS</em>, <em>nosZ</em>) formed a tightly clustered subnetwork exclusively in the ditches, indicating broader nitrification niches and stronger functional coupling among denitrifiers in these systems. Metagenomic evidence revealed that EF value correlated significantly with denitrification genes, notably <em>napAB</em>, <em>nirK</em>, <em>norBC</em> and <em>nirK</em>/<em>nosZ</em> (<em>P</em> &lt; 0.05), underscoring denitrification as the primary biotic driver of N₂O production. These findings demonstrate the value of metagenomic approaches in revealing microbial mechanisms behind N₂O emissions and support the development of more accurate, EF estimates for greenhouse gas inventories in agricultural landscapes.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135085"},"PeriodicalIF":6.3,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity and scale dependence of discretization and roughness in the hydrodynamic modeling of surface runoff caused by torrential rainfall","authors":"David Feldmann ,&nbsp;Patrick Laux ,&nbsp;Andreas Heckl ,&nbsp;Marinko Nujić ,&nbsp;Brian Böker ,&nbsp;Manfred Schindler ,&nbsp;Harald Kunstmann","doi":"10.1016/j.jhydrol.2026.135088","DOIUrl":"10.1016/j.jhydrol.2026.135088","url":null,"abstract":"<div><div>Hydrodynamic surface runoff simulations are an effective method for assessing flash flood risks. In engineering, the lack of observations for model calibration poses a challenge. Therefore, understanding the sensitivity to specific model parameters is crucial for reliable flood protection planning. This study analyzes how surface discretization and roughness affect surface runoff generation and depression storage in a hydrodynamic 2D-model in a southern German alpine region.</div><div>We compare the runoff generation across five discretization methodologies at 211 selected locations within the model domain. These locations are associated with subcatchments ranging in size from 0.2 to 4 km².</div><div>The discretization methodologies comprise a one-meter grid refined with survey data, a two-meter grid, a high-resolution and low-resolution irregular mesh and a four-meter grid. These are combined with seven different depth-dependent and constant roughness parameterizations.</div><div>The sensitivity analysis shows that a higher depth-dependent roughness is needed to achieve comparable results to those of a coarse resolution model. Significant differences were observed with varying roughness parameterizations and meshing approaches. Modest alterations to surface resolution have the potential to yield deviations of up to 20% in maximum runoff. Coarser resolution models tend to create artificial depressions, leading to unrealistic water storage on hillsides.</div><div>These findings aid in identifying the sources of sensitivity in hydrodynamic surface runoff modeling, especially in ungauged basins and provide guidance on specific model setups. This is particularly relevant given the continued use of coarse-resolution models due to computational constraints and the availability of various roughness parameterizations, while calibration data are scarce.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135088"},"PeriodicalIF":6.3,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Response of runoff and sediment transport process to climate change in the headwater regions of Yangtze River","authors":"Li Wang ,&nbsp;Fan Zhang ,&nbsp;Xiaonan Shi ,&nbsp;Chen Zeng ,&nbsp;Yao Chen ,&nbsp;Xing Xu ,&nbsp;Xudong Fu","doi":"10.1016/j.jhydrol.2026.135079","DOIUrl":"10.1016/j.jhydrol.2026.135079","url":null,"abstract":"<div><div>Runoff and sediment transport process in high mountain areas are sensitive to climate change and important for downstream ecosystem. This study employs the SWAT model and General Circulation Models (GCMs) with consideration of cryosphere processes to assess climate change impacts on runoff and sediment transport in the Tuotuo River (TTR) basin, headwaters of the Yangtze River. The 4800–––5200  m elevation zone, covering 65.4% of the basin, contributes disproportionately to runoff (73.3%) and soil erosion (83.8%). Total runoff comprises 33.4% surface runoff, 21.3% lateral runoff, and 45.3% groundwater. From 1986 to 2014, warming and increased precipitation led to rising trends in total runoff and sediment flux, driven by increases in groundwater and lateral runoff. In contrast, surface runoff declines due to enhanced infiltration from surface thawing, resulting in reduced overland erosion and sediment deposition. Under future climate scenarios (2025–––2100), continued warming and wetting will further enhance infiltration and change runoff generation, with surface runoff expected to peak earlier in June. Consequently, total runoff and sediment flux are projected to increase, while soil erosion and deposition are likely to decrease. Partial Least Squares Structural Equation Modeling (PLS-SEM) indicates that both precipitation and temperature positively influence total runoff and sediment flux. Precipitation increases surface and lateral runoff and indirectly promotes erosion and sediment transport. Temperature enhances groundwater, lateral runoff and sediment flux, but reduces surface runoff, erosion and deposition. These findings offer a scientific basis for developing adaptive soil and water conservation strategies under a changing climate.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135079"},"PeriodicalIF":6.3,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of vegetation greening on runoff under climate change in the Yarlung Tsangpo-Brahmaputra River basin","authors":"Haoyang Lyu ,&nbsp;Fuqiang Tian ,&nbsp;Yi Nan ,&nbsp;Liming Wang ,&nbsp;Mahmut Tudaji","doi":"10.1016/j.jhydrol.2026.135072","DOIUrl":"10.1016/j.jhydrol.2026.135072","url":null,"abstract":"<div><div>As a result of climate change and global warming, vegetation greening can influence the hydrological processes of river basins. This study evaluated the possible impact of vegetation greening under the CMIP6 SSP585 scenario on the runoff volume till 2100 at key sections of the Yarlung Tsangpo-Brahmaputra River, which is renowned for its abundant hydropower resources and the complex relations among riparian countries and regions. From 2020 to 2100, with the greening vegetation, annual runoff at Bahadurabad can decrease by 3 to 31 billion m³ on average. Water yield decline brought by vegetation greening frequently happens in upper and middle reaches of the basin. The decrease in runoff also shows significant seasonal characteristics. The main peak of runoff reduction usually occurs during the monsoon season from June to October. The sensitivity analysis shows that the greening of areas with less current vegetation distribution is the more significant factor causing runoff reduction than the increasing lushness of existing vegetation. Dominance of vegetation coverage (FVC) and lushness (LAI) can also vary in different areas of the basin. The findings of this study underscore the importance of accurately predicting the spatial distribution of vegetation species and their temporal dynamics in hydrological modeling. The enhanced understanding of runoff tendency under climate change and vegetation evolution would help supporting more precise management of water resources in large transboundary river basins, promoting basin-wide cooperation, and increasing the efficiency of climate adaptation.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135072"},"PeriodicalIF":6.3,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146110463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-resolution modelling of dissolved organic carbon dynamics in a boreal nested catchment: insights from the Krycklan-HYPE model","authors":"Renkui Guo, Andrea L. Popp, Martin Berggren, Junzhi Liu, Jiaojiao Liu, David Gustafsson, Zheng Duan","doi":"10.1016/j.jhydrol.2026.135039","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.135039","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"221 1","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AVFF-RI: an improved rainfall intensity measurement using common cameras","authors":"Manuel Fiallos-Salguero ,&nbsp;Soon-Thiam Khu ,&nbsp;Mingna Wang","doi":"10.1016/j.jhydrol.2026.135045","DOIUrl":"10.1016/j.jhydrol.2026.135045","url":null,"abstract":"<div><div>Rainfall measurements and modelling have faced a critical bottleneck due to data scarcity and limited performance of conventional methods, hindering precision in urban hydrology applications. In contrast, surveillance cameras have emerged as a cost-effective alternative for rainfall monitoring, although continuous detection remains computationally intensive due to the increasing variability and intensity of rainfall events. To tackle this, we propose AVFF-RI, a novel audio-visual fusion framework that leverages temporally resolved information from spatially distributed surveillance cameras for reliable rainfall estimation. The proposed framework is based on a two-stage approach for modality-specific pre-processing, followed by an adaptive fusion stage, which addresses the challenges of ambient noise, visual obstructions, and environmental conditions. The pre-processing stage includes a denoising network to isolate rainfall acoustic features from audio recordings, and a dual-stream detection scheme to extract rain streaks while removing visual distractors. Thus, these enhanced features are fused using a tailored multimodal regression model, improved with a bidirectional GRU-based adaptive fusion strategy that dynamically weights modality relevance and captures spatial and temporal dependencies. The framework evaluation was across varying rainfall events and conditions at two locations, demonstrating the AVFF-RI robustness, with R² ranging from 0.87 to 0.91 and mean absolute percentage errors ranging from 5.9% to 13.7%. Compared to unimodal and alternative fusion models, AVFF-RI exhibited lower error metrics and better generalization, underlining its effectiveness through late adaptive fusion and attention-guided weighting. This study highlights the viability of scalable rainfall estimation using widely deployed surveillance infrastructure, contributing to urban hydrology and disaster response systems.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"668 ","pages":"Article 135045"},"PeriodicalIF":6.3,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146095901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Land cover influences microclimate and non-rainfall water inputs in temperate agricultural environment","authors":"Jannis Groh ,&nbsp;Thomas Pütz ,&nbsp;Daniel Beysens ,&nbsp;Joan Cuxart ,&nbsp;Nurit Agam ,&nbsp;Werner Küpper ,&nbsp;Paul D. Colaizzi ,&nbsp;Harry Vereecken ,&nbsp;Horst H. Gerke ,&nbsp;Wulf Amelung","doi":"10.1016/j.jhydrol.2026.135040","DOIUrl":"10.1016/j.jhydrol.2026.135040","url":null,"abstract":"<div><div>Non-rainfall water inputs (NRWI) from dew, fog, frost, rime and soil water vapour adsorption (WVA) are key components of the terrestrial water cycle, but their individual contribution to the water budget is unclear due to a lack of suitable methods for identification and quantification. Here, we present a refined method to quantify and partition NRWI using weighing lysimeters. The method’s novelty lies in the variables used to determine when dew and frost (leaf-wetness), fog and rime (air visibility) occur. We applied this methodology to grassland and arable land lysimeters and compared it to the established method that relies on relative humidity and estimated dew-point temperature to quantify and partition NRWI.</div><div>Our results showed large differences between the refined and established method. The established method predicted larger amounts of dew (55<!--> <!-->%) and WVA (2522<!--> <!-->%), but no fog. NRWI mostly came from dew. Dew rates per event were generally higher on arable land, but the total amount of dew was larger on grassland due to higher frequency of dew formation. Dew amount differences could be attributed to land cover type, which promoted dew formation in the grassland while the arable ecosystem largely lost water through evapotranspiration (e.g. stomatal conductance, canopy-structure). We conclude that land cover type is a key control for microclimate (surface temperature, relative humidity), which significantly affects dew formation, while effects on fog or WVA are weaker. These effects are better determined by lysimeter assessment with a visibility and leaf-wetness device than by other existing NRWI identification systems.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135040"},"PeriodicalIF":6.3,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146095902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing SWAT with mechanistic plant hydraulics: development and application in the Hanjiang River Basin","authors":"Xiaoqiang Wei ,&nbsp;Shuai Xie ,&nbsp;Boyu Zhang ,&nbsp;Lingcheng Li ,&nbsp;Quan Zhang","doi":"10.1016/j.jhydrol.2026.135066","DOIUrl":"10.1016/j.jhydrol.2026.135066","url":null,"abstract":"<div><div>Plant transpiration plays a critical role in global water and energy cycles, requiring better process understanding as climate change intensifies drought stress and alters plant responses. Most hydrological models such as the widely-used SWAT lack representation of plant hydraulics, the mechanistic processes controlling plant water regulation and transpiration. This study developed SWAT-PHS by integrating a plant hydraulics scheme (PHS) into SWAT hydrological model, enabling explicit simulation of root water uptake, sap flow, storage and transpiration at 30-minute timescales for watershed-scale modeling. In the Hanjiang River Basin, SWAT-PHS mitigated overestimation of runoff during the rainy season and underestimation during the dry season, reducing the overall simulation error by 29% across the entire simulation period. The model can simulate reasonable plant water dynamics, including diurnal transpiration patterns and drought responses showing declining transpiration flux, hydraulic buffering through stem water storage, and depth-dependent root water uptake strategies. Sensitivity analysis shows that SWAT-PHS captured mechanistic relationships between plant hydraulic traits and transpiration, with root distribution and stem capacitance positively affecting annual transpiration while vulnerability parameters showed negative effects. This work provides a pathway for improving hydrologic modeling and water resource management by better representing plant water regulation under climate change and expected intensifying water stress conditions.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135066"},"PeriodicalIF":6.3,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146095899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying the uncertainty contribution in runoff projection and the time scale effects","authors":"Zhanling Li ,&nbsp;Yingtao Ye ,&nbsp;Cheng Xie ,&nbsp;Xiaoyan Zhai","doi":"10.1016/j.jhydrol.2026.135067","DOIUrl":"10.1016/j.jhydrol.2026.135067","url":null,"abstract":"<div><div>Quantifying the uncertainty contribution in hydrological projections from various factors has received much attention in hydrological science. However, how the contributions respond to the changes of hydrological forecasting period has not received enough attention so far. This study focused on quantifying the uncertainty contributions of different factors to hydrological projections and exploring their time scale effects. Taking the upper Heihe River Basin (UHRB) and the upper Yalong River Basin (UYRB) as the study areas, this study employed the time-series analysis of variance method to explore the contributions of four modeling chain factors and the internal variability of hydrological system to the uncertainty of runoff projection. The results indicate that, for short-term hydrological forecasting of less than 20 years, the internal variability of the system is the main source of uncertainty, basically explaining more than 50% of the total uncertainty in Qmean, Q10, and Q90 projections for both basins. As the time scale increases, the contribution from the internal variability gradually weakens, and that from the modeling chain strengthens. When the time scale reaches 35 years, the impacts of the internal variability and the modeling chain on forecast results reach a relatively balanced state. For the 75-year long-term hydrological forecasting, the modeling chain is the main source of uncertainty, explaining 80–87% of the total uncertainty in Qmean, Q10, and Q90 projections for both basins. In the modeling chain, the general circulation model contributes most to the total uncertainty for the UYRB and the forecast model contributes most for the UHRB.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135067"},"PeriodicalIF":6.3,"publicationDate":"2026-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146095900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global quantification of the bidirectional dependence between vegetation productivity and multi-layer soil moisture","authors":"Ying Liu,&nbsp;Jiumeilin Shi,&nbsp;Hui Yue,&nbsp;Xu Wang","doi":"10.1016/j.jhydrol.2026.135065","DOIUrl":"10.1016/j.jhydrol.2026.135065","url":null,"abstract":"<div><div>Soil moisture serves as a crucial water source for vegetation growth, while vegetation dynamics in turn regulate soil moisture through processes such as evapotranspiration and canopy interception. Quantitatively characterizing this mutual feedback is essential for optimizing hydrological processes and promoting coordinated vegetation–water management. However, the bidirectional interactions between soil moisture and vegetation productivity across different climate zones, vegetation types, and soil depths remain poorly understood. Based on Global Solar Induced Chlorophyll Fluorescence, soil moisture, the average air temperature at 2 m, and solar radiation datasets, this study employed trend analysis, causal inference, and multiple linear regression to explore the Granger causality between vegetation productivity and multi-layer soil moisture under different environmental conditions. Results revealed widespread bidirectional dependence between vegetation productivity and soil moisture across all soil layers, with interaction strength declining from 79.84% in the surface layer (0–10 cm) to 72.04% in the deep layer (100–200 cm). The magnitude of this bidirectional coupling varied significantly across climate zones: dependence peaked in surface soils within temperate regions (82.52%), while tropical zones exhibited maxima in the shallow (82.99%) and deep (78.05%) layers. Boreal zones showed the strongest dependence in the middle soil layer (76.25%). Furthermore, driven by differences in transpiration rates and water retention capacity, woody plants demonstrated higher average bidirectional dependence (79.4%) than herbaceous plants (75.75%), whereas shrubland vegetation exhibited relatively lower dependence (74%). Considering the spatial distribution of climate and vegetation types, tropical zones (dominated by evergreen broadleaf forests) and boreal zones (dominated by shrublands) both showed peak bidirectional dependence in the shallow soil layer. Other climate zones, primarily influenced by grassland vegetation, exhibited peak dependence within the surface soil layer. This study reveals the variability in bidirectional dependence between vegetation productivity and multilayer soil moisture across different climatic zones and vegetation types, which will provide a robust theoretical foundation for improving regional soil moisture regulation and guiding ecosystem restoration under changing climatic conditions.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"669 ","pages":"Article 135065"},"PeriodicalIF":6.3,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}