Environmental Modelling & Software最新文献_第7页

A dual-model framework combining nonlinear autoregressive with exogenous inputs (NARX) and LSTM networks for enhanced daily runoff prediction and error correction 结合非线性自回归和外源输入（NARX）和LSTM网络的双模型框架用于增强日径流预测和误差校正

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-06-11 DOI: 10.1016/j.envsoft.2025.106570

Weiyi Shi, Xinyu Wan, Fangzheng Zhao, Ruxia Deng

{"title":"A dual-model framework combining nonlinear autoregressive with exogenous inputs (NARX) and LSTM networks for enhanced daily runoff prediction and error correction","authors":"Weiyi Shi, Xinyu Wan, Fangzheng Zhao, Ruxia Deng","doi":"10.1016/j.envsoft.2025.106570","DOIUrl":"10.1016/j.envsoft.2025.106570","url":null,"abstract":"<div><div>To enhance the accuracy of daily runoff prediction, prediction and error-correction models were constructed based on a Nonlinear Autoregressive Network with Exogenous Inputs (NARX) and LSTM. Prediction model leverages the delay structure of the NARX-LSTM to capture the effects of preceding hydrometeorological factors. Error-correction model utilizes the NARX-LSTM to estimate the test set errors of the first model. To validate the model, it was applied to the Ting-jiang River Basin in China. The model's performance was assessed using four evaluation metrics. The results indicate that the Nash-Sutcliffe efficiency coefficient was improved by 18.1 %, 9.36 %, 9.02 % and 4.59 % for forecast horizons of 10, 20, 30 and 50 days, respectively, by using the error-correction model. Additionally, the peak prediction accuracy was improved by 30.5 % and 72.1 % on two sets, respectively. The developed NARX-LSTM error-correction model enhances the daily runoff prediction accuracy, extends the prediction lead time, and effectively mitigates peak value underestimation.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"192 ","pages":"Article 106570"},"PeriodicalIF":4.8,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144304865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigating aquitard heterogeneity by inverse groundwater modelling at a drinking water production site 利用地下水反演模型研究某饮用水产地的含水层非均质性

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-06-10 DOI: 10.1016/j.envsoft.2025.106554

Martijn D. van Leer , Willem J. Zaadnoordijk , Alraune Zech , Jasper Griffioen , Marc F.P. Bierkens

{"title":"Investigating aquitard heterogeneity by inverse groundwater modelling at a drinking water production site","authors":"Martijn D. van Leer , Willem J. Zaadnoordijk , Alraune Zech , Jasper Griffioen , Marc F.P. Bierkens","doi":"10.1016/j.envsoft.2025.106554","DOIUrl":"10.1016/j.envsoft.2025.106554","url":null,"abstract":"<div><div>This study investigates whether geostatistical properties of aquitards can be determined from data collected at a drinking water well field. A workflow adaptable to any drinking water extraction site with pumping and groundwater head data is developed. Using data from Budel, the Netherlands, a layered groundwater flow model is constructed and calibrated on hydraulic heads. A large number of realizations are generated for the aquitard, considering various heterogeneity parameters. These simulations are upscaled to the grid of the flow model, and their fit to observed heads is evaluated. Results show that optimal geostatistical parameters can be identified, even though many combinations reproduce observed heads. These parameters can be used to parameterize regional groundwater flow models. Particle tracking simulations show heterogeneity decreases contaminant breakthrough times while also decreasing the total flow through the aquitard. These findings emphasize the need to consider aquitard heterogeneity in risk assessments at drinking water production sites.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"192 ","pages":"Article 106554"},"PeriodicalIF":4.8,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Depth Estimation in Urban Flooding Using Surveillance Cameras and High-Resolution LiDAR Data 基于监控摄像机和高分辨率激光雷达数据的城市洪水深度估计

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-06-10 DOI: 10.1016/j.envsoft.2025.106572

Mahta Zamanizadeh , Mecit Cetin , Ali Shahabi , Navid Tahvildari

引用次数: 0

A numerical model for simulation of bedload transport in unsteady trans-critical river flow 非定常跨临界水流中河床输运的数值模拟模型

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-06-09 DOI: 10.1016/j.envsoft.2025.106531

Fabien Souillé , Nicolas Claude , Magali Jodeau

{"title":"A numerical model for simulation of bedload transport in unsteady trans-critical river flow","authors":"Fabien Souillé , Nicolas Claude , Magali Jodeau","doi":"10.1016/j.envsoft.2025.106531","DOIUrl":"10.1016/j.envsoft.2025.106531","url":null,"abstract":"<div><div>We present a numerical model for the simulation of unsteady trans-critical flow with bedload transport in rivers. The approach uses second-order well-balanced finite volume methods to solve the Saint-Venant–Exner equations with rectangular cross-section in 1 dimension. The equations are treated as a non-conservative hyperbolic system with distinct wave speeds, influenced by sediment transport processes. Two finite volume approximate Riemann solvers are implemented, based on an augmented Roe solver and an adapted HLL solver that both deal with the Saint-Venant–Exner equations as a coupled system. The three source terms of the model (bottom, friction and width) are discretized in a way that preserves of lake at rest equilibrium and positivity of the water depth. Model stability is ensured by a Courant–Friedrichs–Lewy (CFL) condition which depends on the wave speeds of the coupled system. Finally second-order schemes are proposed, based on a modified Heun time scheme and linear state reconstructions at cell interfaces and slope limiters. The paper highlights the challenges of computing the Jacobian matrix for various sediment transport models. We propose using different approximations of the wave speeds and present exact solid flux derivatives for many classical sediment transport laws. We also propose approximate solid flux derivatives which allow a simple generalization of the numerical model to any law, enabling real life industrial applications. The model’s performance was validated against analytical and experimental data, proving its sturdiness and precision. We also compare our approach to other numerical methods and to the Mascaret industrial code and its 1-dimensional sediment transport module Courlis.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"192 ","pages":"Article 106531"},"PeriodicalIF":4.8,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of an alpine hydrological model considering the recharge of stream water to alluvial plain aquifers 考虑河流向冲积平原含水层补给的高寒水文模型的建立

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-06-07 DOI: 10.1016/j.envsoft.2025.106567

Jiaojiao Liu , Junzhi Liu , Meng Liu , Shaoyi Tian , Yongbo Liu , Wanhong Yang , Yonqin Liu

{"title":"Development of an alpine hydrological model considering the recharge of stream water to alluvial plain aquifers","authors":"Jiaojiao Liu , Junzhi Liu , Meng Liu , Shaoyi Tian , Yongbo Liu , Wanhong Yang , Yonqin Liu","doi":"10.1016/j.envsoft.2025.106567","DOIUrl":"10.1016/j.envsoft.2025.106567","url":null,"abstract":"<div><div>The recharge of stream water to alluvial plain aquifers is of significant importance for alpine hydrology, yet it has not been adequately represented in hydrological models, limiting the reliability of hydrological simulation and future projection. This study developed a watershed model that can simulate this process with moderate complexity. A parsimonious method was proposed to calculate the stream water recharge fluxes into aquifers at the mountain front area, relying on the storage dynamics of alluvial plain groundwater. The inter-subbasin groundwater movement in seasonally frozen ground areas was also simulated to represent the connectivity of aquifers. A small headwater catchment in the northeastern Qinghai-Tibet Plateau was selected to validate the model. The simulation results indicated that the developed model can well reproduce multi-faceted observations, such as soil temperature profiles, the groundwater dynamics at different locations, streamflow at the catchment outlet, and the contributions of groundwater. In this case study, approximately 75 % of stream water from the permafrost areas infiltrated into alluvial plain aquifers in the seasonally frozen ground areas, and then gradually released to river, maintaining base flow during dry periods. This process buffers the movement of water from glacier and permafrost to the catchment outlet, and may delay the impact of global warming on discharge at the catchment outlet. The model developed in this study provides a reliable tool for assessing the effects of climate change on hydrological processes in alpine watersheds.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"192 ","pages":"Article 106567"},"PeriodicalIF":4.8,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing forest ecosystem simulation in the TASC model through the integration of the DAYCENT forest model 通过整合DAYCENT森林模型，加强TASC模型中森林生态系统的模拟

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-06-07 DOI: 10.1016/j.envsoft.2025.106565

Sijal Dangol , Xuesong Zhang , Rajith Mukundan , Rakesh Gelda

{"title":"Enhancing forest ecosystem simulation in the TASC model through the integration of the DAYCENT forest model","authors":"Sijal Dangol , Xuesong Zhang , Rajith Mukundan , Rakesh Gelda","doi":"10.1016/j.envsoft.2025.106565","DOIUrl":"10.1016/j.envsoft.2025.106565","url":null,"abstract":"<div><div>Forest ecosystems play a crucial role in sequestering atmospheric carbon in the form of biomass and soil organic carbon, while also providing high quality water supply through water and nutrient cycling. The lack of state-of-the-art forest growth processes in the Terrestrial and Aquatic Sciences Convergence (TASC) model limits its capability to support watershed management in forested watersheds. To address this gap, we integrated the DAYCENT model-based forest growth algorithms into the TASC model (TASC-Forest) to provide detailed representation of forest growth dynamics, such as biomass production, allocation, death, and decomposition of leaf litter, root, and woody components. We optimized parameters related to tree growth, soil properties, and hydrologic processes, and evaluated the improved model's ability to simulate monthly net ecosystem exchange (NEE), ecosystem respiration, and evapotranspiration (ET) observed at seven AmeriFlux sites. The results show that the TASC-Forest generally performs well in simulating NEE, ecosystem respiration, and ET across multiple forest biomes: deciduous, evergreen, and mixed. The TASC-Forest substantially outperformed the TASC model in simulating NEE and ET. The <em>KGE</em> values increased from 0.61 and 0.48 to 0.82 and 0.76 for NEE, and from 0.56 and 0.48 to 0.84 and 0.80 for ET during calibration and validation, respectively, across seven forest sites. Sensitivity analysis indicates that forest productivity and ET are most sensitive to parameters regulating temperature and soil moisture effects on tree growth, and soil moisture control parameters. The enhanced TASC model will serve as a valuable tool for the integrated assessment and management of carbon, nutrient, and water cycling, particularly in forested ecosystems.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"192 ","pages":"Article 106565"},"PeriodicalIF":4.8,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel cross-model framework for modelling urban multi-hydrological processes based on hydrogeographic elements in urban areas 基于城市水文地理要素的城市多水文过程跨模型建模

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-06-06 DOI: 10.1016/j.envsoft.2025.106536

Haocheng Wang , Zhuo Zhang , Songshan Yue , Fei Guo , Yongning Wen , Min Chen , Guonian Lü

{"title":"A novel cross-model framework for modelling urban multi-hydrological processes based on hydrogeographic elements in urban areas","authors":"Haocheng Wang , Zhuo Zhang , Songshan Yue , Fei Guo , Yongning Wen , Min Chen , Guonian Lü","doi":"10.1016/j.envsoft.2025.106536","DOIUrl":"10.1016/j.envsoft.2025.106536","url":null,"abstract":"<div><div>Urban flooding is one of the most pervasive disasters globally, rendering flood simulation within urban area crucial for effective damage reduction and emergency planning. Recent studies have primarily addressed two fundamental challenges in hydrodynamic modeling: resolving the complex flow patterns arising from urban spatial heterogeneity and advancing cross-model coupling techniques for better prediction accuracy. To comprehensively consider the spatially heterogeneous factors in urban areas and to facilitate multi-model coupling, we present a novel cross-model modelling framework, which comprises a standardized model encapsulation, calling, and coupling method based on urban hydrogeographic elements, an innovative concept proposed to resolve the multi-hydrological processes in urban areas. In addition, we provided the mathematic models and solutions for the hydrodynamic functions of the total seven hydrogeographic elements as well as the computational method of the flow exchanges between pipe network, land surface and river. Last, as a case to validate the functionality and usability of our modelling framework, we integrated three state-of-the-art hydrologic/hydrodynamic models: SWMM (Storm Water Management Model), LISFLOOD-FP, and FVCOM (Finite Volume Community Ocean Model) models within the framework and simulated the urban pluvial flooding process in Fenhu District, Suzhou City.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"192 ","pages":"Article 106536"},"PeriodicalIF":4.8,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A seamless geo-flow modelling workflow to tackle structural uncertainty using LoopStructural and MODFLOW 无缝地流建模工作流程，以解决结构不确定性使用LoopStructural和MODFLOW

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-06-06 DOI: 10.1016/j.envsoft.2025.106557

Kerry Bardot , Lachlan Grose , Itsuo Camargo , Guillaume Pirot , Adam Siade , Jon-Phillippe Pigois , Clive Hampton , James McCallum

{"title":"A seamless geo-flow modelling workflow to tackle structural uncertainty using LoopStructural and MODFLOW","authors":"Kerry Bardot , Lachlan Grose , Itsuo Camargo , Guillaume Pirot , Adam Siade , Jon-Phillippe Pigois , Clive Hampton , James McCallum","doi":"10.1016/j.envsoft.2025.106557","DOIUrl":"10.1016/j.envsoft.2025.106557","url":null,"abstract":"<div><div>Despite being one of the biggest sources of uncertainty in groundwater models, geological structural uncertainty is rarely addressed, primarily due to a lack of workflows that can generate multiple structural realisations and integrate these directly with its flow model counterpart. We present a streamlined workflow which combines LoopStructural for building complex geological models and MODFLOW 6 for flow modelling. Key features of the workflow include the use of unstructured gridding, which efficiently adapts to each structural interpretation, a full-connectivity flow formulation, and the use of structural parameters. A case study is used to demonstrate how the workflow can be used to address uncertainty in fault displacement and sub-cropping location of an aquifer. Furthermore, we demonstrate how the workflow may be used to inverse model structural parameters to tackle structural uncertainty alongside parameter uncertainty during the history matching process, negating the need for traditional Bayesian Model Averaging approaches.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"192 ","pages":"Article 106557"},"PeriodicalIF":4.8,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144280632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A two-stage trained hybrid Unet-ConvLSTM2D for enhanced precipitation nowcasting 用于增强降水临近预报的两阶段训练混合Unet-ConvLSTM2D

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-06-06 DOI: 10.1016/j.envsoft.2025.106532

Farah Naz , Lei She , Chenghong Zhang , Jie Shao

{"title":"A two-stage trained hybrid Unet-ConvLSTM2D for enhanced precipitation nowcasting","authors":"Farah Naz , Lei She , Chenghong Zhang , Jie Shao","doi":"10.1016/j.envsoft.2025.106532","DOIUrl":"10.1016/j.envsoft.2025.106532","url":null,"abstract":"<div><div>Current precipitation nowcasting models such as ConvLSTM, ConvGRU, PredRNN, and PFST-LSTM face challenges in capturing complex spatiotemporal patterns and preserving fine spatial details. These models often struggle with high-intensity precipitation events and lose accuracy over longer lead time. Although PFST-LSTM addresses spatial alignment and feature preservation and SAC-LSTM enhances long-range spatial dependency modeling through self-attention, they are constrained by increased computational complexity. In this study, we propose a hybrid Unet-ConvLSTM2D model that combines Unet’s superior spatial feature extraction capabilities with ConvLSTM2D’s temporal sequence modeling strengths. By introducing time-distributed layers in each Unet block, the model effectively handles temporal sequences while retaining high-resolution spatial features. The model is trained using a two-stage approach: pre-training on the moving-MNIST++ dataset to learn basic temporal dynamics, followed by fine-tuning on the CIKM AnalytiCup 2017 dataset to adapt to real-world meteorological data. Experimental results demonstrate that the proposed model significantly outperforms existing methods, with average improvements of 3.73% in critical success index (CSI) and 3.63% in Heidke skill score (HSS) across all dBZ thresholds, along with a 4.72% reduction in mean squared error (MSE).</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"192 ","pages":"Article 106532"},"PeriodicalIF":4.8,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An interpretable and scalable model for rapid flood extent forecasting using satellite imagery and machine learning with rotated EOF analysis 一个可解释和可扩展的模型，用于快速洪水范围预测，使用卫星图像和旋转EOF分析的机器学习

IF 4.8 2区环境科学与生态学

Environmental Modelling & Software Pub Date : 2025-06-06 DOI: 10.1016/j.envsoft.2025.106562

Hung-Hsien Wan , Hyongki Lee , Tien Le Thuy Du , Amirhossein Rostami , Chi-Hung Chang , Kel N. Markert , E. James Nelson , Gustavious P. Williams , Sanmei Li , William Straka III , Sean R. Helfrich , Franz J. Meyer

{"title":"An interpretable and scalable model for rapid flood extent forecasting using satellite imagery and machine learning with rotated EOF analysis","authors":"Hung-Hsien Wan , Hyongki Lee , Tien Le Thuy Du , Amirhossein Rostami , Chi-Hung Chang , Kel N. Markert , E. James Nelson , Gustavious P. Williams , Sanmei Li , William Straka III , Sean R. Helfrich , Franz J. Meyer","doi":"10.1016/j.envsoft.2025.106562","DOIUrl":"10.1016/j.envsoft.2025.106562","url":null,"abstract":"<div><div>Data-driven models offer a promising alternative for flood forecasting, addressing the computational and data challenges of traditional hydrodynamic models. Current machine learning (ML) models often underutilize spatial data—particularly historical inundation extents from satellite imagery—and lack interpretability. This study introduces Forecasting Inundation Extents using Rotated Empirical Orthogonal Function (FIER) 2.0, an enhanced model that incorporates binary inundation maps and advanced ML methods, including Long Short-Term Memory and Temporal Convolutional Networks. These improvements enable FIER 2.0 to leverage diverse satellite images, capture inundation dynamics, enhance prediction accuracy, and increase model interpretability. Testing on Cambodia's Tonle Sap Lake floodplain showed a 25 % improvement in the Critical Success Index during flood retreats and a 16 % increase at flood onset, with consistent performance across flood magnitudes using only 70 training images. Overall, FIER 2.0 represents a scalable, efficient, and interpretable solution for accurate prediction of inundation extents in data-constrained environments.</div></div>","PeriodicalId":310,"journal":{"name":"Environmental Modelling & Software","volume":"192 ","pages":"Article 106562"},"PeriodicalIF":4.8,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0