Advances in Water Resources最新文献

{"title":"Integrating analytical solutions and U-Net model for predicting groundwater contaminant plumes in pump-and-treat systems","authors":"Xuehang Song ,&nbsp;Inci Demirkanli ,&nbsp;Zhangshuan Hou ,&nbsp;Xinming Lin ,&nbsp;Marinko Karanovic ,&nbsp;Matt Tonkin ,&nbsp;Delphine Appriou ,&nbsp;Rob Mackley","doi":"10.1016/j.advwatres.2025.105002","DOIUrl":"10.1016/j.advwatres.2025.105002","url":null,"abstract":"<div><div>Pump-and-treat (P&amp;T) is a common technique for groundwater remediation involving the extraction and treatment of contaminated water above ground. Optimizing the design and operation of the P&amp;T well network is essential for maximizing the system’s effectiveness and efficiency. However, this optimization often necessitates many model evaluations, leading to computationally demanding tasks. This study introduces a novel approach that integrates analytical solutions for groundwater dynamics with the U-Net deep learning framework to predict groundwater contaminant plume migration under dynamic pumping conditions. By incorporating the Thiem equation into the input preprocessing, the U-Net model transforms sparse well data into a continuous spatial field that captures the hydraulic impacts of pumping activities. This integration enables the model to leverage both deep learning capabilities and classical physics-based groundwater theories, enhancing prediction accuracy and computational efficiency. For example, in 2D synthetic cases, integrating analytical solutions reduced the RMSE from 2.76 µg/L to 0.7 µg/L. In a complex 3D heterogeneous model of the Hanford Site’s 200 West P&amp;T facility, our trained surrogate model completed a 12-year simulation in just 600 ms on a single CPU core, achieving an accumulative RMSE of &lt;1.6 µg/L—an improvement of over three orders of magnitude in simulation speed compared to a numerical model. These advancements support rapid evaluations of P&amp;T optimization scenarios, enabling timely and effective decision-making for well placement and system management. Our findings highlight the potential of advanced machine learning models to significantly enhance the efficiency and sustainability of groundwater remediation efforts, offering a novel application of the U-Net architecture in environmental science.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"202 ","pages":"Article 105002"},"PeriodicalIF":4.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071161","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}

{"title":"Predicting water movement in unsaturated soil using physics-informed deep operator networks","authors":"Qiang Ye ,&nbsp;Zijie Huang ,&nbsp;Qiang Zheng ,&nbsp;Lingzao Zeng","doi":"10.1016/j.advwatres.2025.105001","DOIUrl":"10.1016/j.advwatres.2025.105001","url":null,"abstract":"<div><div>Accurate modeling of soil water movement in the unsaturated zone is essential for effective soil and water resources management. Physics-informed neural networks (PINNs) offer promising potential for this purpose, but necessitate retraining upon changes in initial or boundary conditions, posing a challenge when adapting to variable natural conditions. To address this issue, inspired by the operator learning with more universal applicability than function learning, we develop a physics-informed deep operator network (PI-DeepONet), integrating physical principles and observed data, to simulate soil water movement under variable boundary conditions. In the numerical case, PI-DeepONet achieves the best performance among three modeling strategies when predicting soil moisture dynamics across different testing areas, especially for the extrapolation one. Guided by both data and physical mechanisms, PI-DeepONet demonstrates greater accuracy than HYDRUS in capturing spatio-temporal moisture variations in real-world scenario. Furthermore, PI-DeepONet successfully infers constitutive relationships and reconstructs missing boundary flux condition from limited data by incorporating known prior physical information, providing a unified solution for both forward and inverse problems. This study is the first to develop a PI-DeepONet specifically for modeling real-world soil water movement, highlighting its potential to improve predictive accuracy and reliability in vadose zone modeling by combining data-driven approaches with physical principles.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"202 ","pages":"Article 105001"},"PeriodicalIF":4.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144072382","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}

{"title":"The role of phase interference in steady-state two-phase flow in porous media","authors":"Jiafan Guo ,&nbsp;Zhechao Wang ,&nbsp;Liping Qiao ,&nbsp;Hao Feng","doi":"10.1016/j.advwatres.2025.104981","DOIUrl":"10.1016/j.advwatres.2025.104981","url":null,"abstract":"<div><div>When two fluids flow simultaneously in a porous medium at a low flow rate, known as steady-state two-phase flow, the total pressure drop deviates from a linear relationship with the Darcy flux. This deviation is primarily caused by the capillary pressure drop induced by interphase interference at pore throats. This study aims to estimate the capillary pressure drop based on fluid–fluid interfacial area at the pore scale. Recognizing that steady-state two phase flow typically exhibits discontinuous behavior, we proposed a simple equation to explain the relationship between total pressure drop, viscous pressure drop, and capillary pressure drop. Experiments were conducted in transparent micromodels to investigate the effects of flow rate, average viscosity and pore structure under both drainage and imbibition conditions. The results indicate a linear relationship between capillary pressure drop and the specific interfacial area of the moving wetting and moving non-wetting phase. Additionally, the slope of the capillary pressure drop-specific interfacial area curve is only related to the flow rate. Moreover, we established and verified the relationship between the specific interfacial area and relative permeability. This study provides new insights into the nonlinear relationship between Darcy flux and pressure drop in two-phase flow.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"202 ","pages":"Article 104981"},"PeriodicalIF":4.0,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143934989","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}

{"title":"Free convection in fractured porous media: A numerical study","authors":"Arash Andrea Roknian,&nbsp;Anna Scotti,&nbsp;Alessio Fumagalli","doi":"10.1016/j.advwatres.2025.104988","DOIUrl":"10.1016/j.advwatres.2025.104988","url":null,"abstract":"<div><div>The objective of this study is to better understand the influence of fractures on the possibility of free convection in porous media. Fractures are ubiquitous in porous media and criteria based on upscaled permeability are known to fail for fractured porous media. To this aim, we introduce a novel method for the assessment of convective stability through the eigenvalue analysis of the linearized numerical problem instead of solving the problem in time until a steady state is reached. The new method is shown to be in agreement with existing literature cases both in simple and complex fracture configurations. With respect to direct simulation in time, the results of the eigenvalue method lack information about the strength of convection and the steady state solution, they however provide detailed (quantitative) information about the behavior of the solution near the initial equilibrium condition. Furthermore, not having to solve a time-dependent problem makes the method computationally very efficient. The results of this work allow us to determine the dominant convective modes in 2D and 3D and to shed light on the role of the porous matrix in convective circuits.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"202 ","pages":"Article 104988"},"PeriodicalIF":4.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931452","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}

{"title":"Revisiting overland runoff modeling: Mixed flows and pseudo-kinematic waves","authors":"Oscar Castro-Orgaz ,&nbsp;Juan V. Giraldez ,&nbsp;Willi H. Hager ,&nbsp;Francisco N. Cantero-Chinchilla","doi":"10.1016/j.advwatres.2025.104999","DOIUrl":"10.1016/j.advwatres.2025.104999","url":null,"abstract":"<div><div>Overland flow resulting from the rainfall-runoff transformation is an important hydrological process in agricultural and urban watersheds, occurring in the form of a thin fluid sheet moving on rough and relatively steep terrain. Mixed flows involving moving critical points are frequent, especially in urban drainage, but a method to deal with these flows is so far not available. In this work a new and robust solution method for the computation of equilibrium mixed flows is presented, resulting in solutions not available so far. Based on these results, the convergence features to mixed flows of a dynamic wave model developed are investigated choosing suitable tailwater boundary conditions. The new solution method developed for mixed flows reveals that pseudo-uniform flow profiles are closer to dynamic wave profiles than kinematic profiles. It allowed the definition of a new kinematic-wave truncation of the momentum equation, the pseudo-kinematic wave, suitable for unsteady rainfall-runoff modeling. The new shallow water wave approach proposed is closer to dynamic waves than the standard kinematic approach and permits to simulate unsteady overland flows more accurately over a wider range of conditions, e.g. for <em>k</em>F₀² &gt; 5 and F₀ &lt; 2. The dynamic wave model presented is compared with experiments, other computational solutions, and two new analytical solutions developed, one for steady flows and another for unsteady flows. The steady mixed flow profiles are compared with experiments and results of the dynamic wave model, detailing the formation of critical points. Dynamic, kinematic and pseudo-kinematic waves are extensively compared for flow conditions where the kinematic wave is invalid. Finally, the roll wave development, which is not detailed so far in overland flow under rainfall, is considered to settle an upper validity limit of the new pseudo-kinematic wave approach.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"202 ","pages":"Article 104999"},"PeriodicalIF":4.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143901738","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}

{"title":"SPH modelling of mass detachment processes in overtopped dams. The limits of Froude similarity","authors":"Carlos Alberto D. Fraga Filho ,&nbsp;Rui M.L. Ferreira ,&nbsp;Rui Aleixo ,&nbsp;Ricardo Canelas ,&nbsp;Silvia Amaral ,&nbsp;Teresa Viseu","doi":"10.1016/j.advwatres.2025.104987","DOIUrl":"10.1016/j.advwatres.2025.104987","url":null,"abstract":"<div><div>We apply Smooth Particle Hydrodynamics (SPH) to simulate mass detachments in an overtopped and breached earth dam. SPH is able to model free surface flows at prototype and laboratory model scales. The flow over the overtopped dam is gravity-driven. Froude similarity is thus employed to scale results from models to prototypes, even if there are fluid-wall interactions. In particular, the processes that govern the interaction between a detached solid from the dam body and the breach flow may not obey Froude similarity. In this paper, we discuss how the geometric scale conditions the effects of mass detachments on the flow field of a breached dam and how SPH simulation tools express these scaling issues. The Navier–Stokes equations for weakly compressible and Newtonian fluids in isothermal flows were used for the water flow. Flow-dam interaction was resolved with dynamic boundary conditions. All simulations were conducted with DualSPHysics, employing the Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) scheme. The detached soil mass was modelled as a rigid block. The interaction between the detached block and the fluid flow through the breach was attained by coupling DualSPHysics with the non-smooth multi-body dynamics model (Chrono-Engine). The surface velocity field, determined with Particle Tracking Velocimetry (PTV) during the mass detachment, was used to assess the quality of the SPH solution. The numerical and the observed velocity fields show a reasonable agreement in the time-lapse that encompasses the detachment of the block. However, there are differences in the curvature of streamlines as the flow approaches the breach, suggesting a closer look at the hypotheis of the SPH simulation tool. The impact of the falling block on the flow field varies significantly with the size of the modelled dam. The block is not entirely transported out of the breach in the reduced model. This configures a breakdown of Froude similarity in the sense that hydrodynamic actions on the model are disproportionately smaller in the model relative to the prototype. While there may be physical reasons at play, we note that ensuring mass conservation in the model led to a smaller initial resolution that may have affected how forces are transmitted between the SPH and Chrono simulation tools.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"202 ","pages":"Article 104987"},"PeriodicalIF":4.0,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143918142","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}

{"title":"Pore-scale investigations of particle migration by fluid–particle interactions in immiscible two-phase flow systems: A three-dimensional X-ray microtomography study","authors":"Sotheavuth Sin ,&nbsp;Muhammad Nasir ,&nbsp;Kailin Wang ,&nbsp;Anindityo Patmonoaji ,&nbsp;Wilson Susanto ,&nbsp;Bowen Wang ,&nbsp;Shintaro Matsushita ,&nbsp;Tetsuya Suekane","doi":"10.1016/j.advwatres.2025.104998","DOIUrl":"10.1016/j.advwatres.2025.104998","url":null,"abstract":"<div><div>Understanding of particle migration by fluid–particle interactions in immiscible two-phase flow systems in porous media is crucial for subsurface applications. However, pore-scale investigations of particle migration in immiscible two-phase flow systems remain limited for three-dimensional (3D) porous media because of the complexities of fluid flow in such media. Here, we employed microfocus X-ray computed tomography (CT) to investigate the effects of interfacial tension and viscous force on particle migration during fluid–particle interactions in strong drainage and imbibition for the pore-scale process. A mixture of two differently sized particles was used as a 3D heterogeneous porous medium. The experimental conditions cover the logarithmic values of the capillary number (Log<em>Ca</em>) range between −7.476 and −4.777 and of a fixed viscosity ratio (Log<em>M</em>) of −0.867, which are used to simulate the carbon dioxide (CO₂) sequestration. The results show that particle migration significantly proceeded throughout the medium for strong drainage compared to strong imbibition. At a low injection flow rate or Log<em>Ca</em>, interfacial tension strongly influenced particle accumulation, altering pore networks. The combined effects of interfacial tension and viscous force enhanced particle migration with an increase in Log<em>Ca</em>. In strong drainage, the particles migrated with the interface expansion between the two phases. However, in strong imbibition, they were displaced along with the fluid flow because of the presence of film formations. The findings of this study improve the understanding of particle migration by fluid–particle interactions under different injection flow rates and wettability conditions in 3D heterogeneous porous media.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"202 ","pages":"Article 104998"},"PeriodicalIF":4.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143890551","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}

{"title":"Dynamics of fluid flow in natural fracture networks","authors":"Cuong Mai Bui ,&nbsp;Stephan K. Matthäi","doi":"10.1016/j.advwatres.2025.104979","DOIUrl":"10.1016/j.advwatres.2025.104979","url":null,"abstract":"<div><div>In complex fracture networks, dynamic fluid-flow patterns arise already at flow velocities in the centimetre-per-second (cm/s) range. Yet, these phenomena get ignored or underestimated when such flows are modelled using Stokes’ equation or the steady-state Darcy’s law approximations of the Navier–Stokes equation (NSE).</div><div>Here we apply Detached-Eddy Simulation to solve the NSE in interconnected rock fractures, carrying out an investigation of transient flow phenomena. Our field-data-based numerical simulation-derived results reveal that fracture flow becomes unsteady at cm/s velocities. Dynamic eddies emerge across several length scales, increasing the tortuosity of the flow and altering the fluid distribution in fracture branches. Pressure fluctuations are detectable at the network scale, reaching magnitudes of <span><math><mrow><mo>∼</mo><mn>10</mn><mtext>%</mtext></mrow></math></span> of the total pressure drop. The contribution of inertial losses to the hydraulic head gradient across the network increases substantially with the onset of non-stationary eddies, confirming that they are the primary source of flow nonlinearity.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"202 ","pages":"Article 104979"},"PeriodicalIF":4.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143881822","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}

{"title":"Gradient-based estimation of spatially distributed parameters of a shallow water 2D rainfall-runoff model","authors":"Léo Pujol ,&nbsp;Shangzhi Chen ,&nbsp;Pierre-André Garambois","doi":"10.1016/j.advwatres.2025.104978","DOIUrl":"10.1016/j.advwatres.2025.104978","url":null,"abstract":"<div><div>This contribution presents a gradient-based inverse modeling approach for the inference of distributed infiltration parameters in a 2D shallow water hydraulic model. It describes the implementation of rain and infiltration mass source terms in the DassFlow direct-inverse modeling platform and their validation against experimental data. Synthetic experiments are used to showcase the complexity of the inverse problems posed by the inference of infiltration parameters through hydraulic signature analysis, stochastic parameter space exploration and inverse modeling with distributed or multi-variate controls. To address spatial uncertainty in the context of sparse observations, spatial constraints are imposed to sought infiltration parameters in the form of homogeneous areas, or patches, sharing the resolution of available soil maps. They are also introduced in the form of a parameter model based on pedotransfer functions, which are used to reduce the dimensionality of the inverse problem and impose spatial coherence to the inferred distributed parameters. This upgrade of the direct model enables integrating a priori knowledge of parameter distribution carried by physical descriptor maps into the assimilation process, hence providing a spatially regularizing effect. Inference results for a fully distributed parametrization without regularization, which is achieved by solving of a high-dimensional inverse problem, are also presented. The methodology is applied to real catchments within the Réal Collobrier hydrological observatory in southeastern France, monitored by INRAE. In a model containing high-resolution topography and rain data, real downstream discharge observations are assimilated to infer distributed infiltration parameters maps, including through regionalized pedotransfer functions. This leads to the inference of effective infiltration model parameters that provide a better fit to real flow observations.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"202 ","pages":"Article 104978"},"PeriodicalIF":4.0,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143886633","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}

{"title":"Field-scale soil moisture dynamics predicted by deep learning","authors":"Sahar Bakhshian ,&nbsp;Negar Zarepakzad ,&nbsp;Hannes Nevermann ,&nbsp;Cathy Hohenegger ,&nbsp;Dani Or ,&nbsp;Nima Shokri","doi":"10.1016/j.advwatres.2025.104976","DOIUrl":"10.1016/j.advwatres.2025.104976","url":null,"abstract":"<div><div>Soil moisture plays a critical role in land–atmosphere interactions. Prediction of its dynamics is still a grand challenge. While in-situ measurements using sensors offer highly temporally resolved and accurate information compared to satellite observations, existing sensor networks are sparse and scarce. Here we propose a deep learning model for bridging the gap between infrequent satellite observations and sparse in-situ sensor network to improve near-term soil moisture predictions. The Long Short-Term Memory (LSTM)-based deep learning model was used to forecast soil moisture dynamics using soil parameters and climatic variables (e.g. air temperature, relative humidity, pressure, wind speed, turbulent fluxes, solar and terrestrial waves) collected from a dense network of sensors in a field located in Germany in an area of about 20 hectares. The dynamic time-lagged cross-correlation between soil moisture and other co-located soil and climatic features was calculated and a set of optimal predictors for training the LSTM model was selected. To efficiently learn the long-term dependency of soil moisture on its historical trends and to improve the prediction capability of the model, we optimized the LSTM structure, hyperparameters, and the size of the sliding window based on the goodness of fit (<span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> score) of the model. We also examined the feasibility of employing the model developed using temporal data from one location for the prediction of soil moisture at other locations across the landscape. The results illustrate the robustness and efficiency of the proposed model for the spatio-temporal prediction of soil moisture. <strong>Plain Language Summary</strong> Understanding and monitoring soil moisture dynamics is crucial affecting ecosystem health, climate and extreme weather patterns, and the agricultural sector. However, predicting the temporal and spatial variation of soil moisture is challenging because of the complex interactions between the land and atmosphere. While soil moisture measurement with in-situ ground-based sensors provide a high level of temporal frequency in comparison to satellite data, the implementation of dense monitoring networks to capture spatial variability of soil moisture is not economically viable. To address this problem, we utilized machine learning techniques to predict temporal and spatial variation of soil moisture using data we measured in a field in Germany. The developed model was examined against the experimental data with the results illustrating that AI-based solutions could offer a powerful tool to predict soil moisture dynamics.</div></div>","PeriodicalId":7614,"journal":{"name":"Advances in Water Resources","volume":"201 ","pages":"Article 104976"},"PeriodicalIF":4.0,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143873023","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}