Journal of Hydrology最新文献

{"title":"Within-reach temperature heterogeneity is limited in a southern Appalachian stream network, southeastern USA","authors":"Matthew J. Troia ,&nbsp;Anna L. Kaz ,&nbsp;Xingli Giam","doi":"10.1016/j.jhydrol.2025.133127","DOIUrl":"10.1016/j.jhydrol.2025.133127","url":null,"abstract":"<div><div>Stream temperature monitoring networks, combined with geospatial data and statistical modeling, facilitate temperature mapping at the spatial resolution of inter-confluence stream reaches and at continental spatial extents. Comparatively few monitoring efforts quantify spatiotemporal temperature heterogeneity within inter-confluence stream reaches. We measured within-reach temperature heterogeneity for six study reaches in a southern Appalachian stream network, southeastern USA. Within each reach, we logged temperature at 27 monitoring points every 15 min for three days during early summer and three days during late summer of 2018. Analysis of variance indicated that daily minimum, mean, and maximum water temperature metrics vary more among reaches than within reaches. For example, the difference in daily mean temperature from the warmest to coldest reach was 8.7 °C, whereas within-reach variation never exceeded 2.3 °C for any of the three daily temperature metrics. Mixed effects models indicated that most variation in the three daily water temperature metrics can be explained by reach-resolution covariates including elevation, watershed area, and forest cover. The limited within-reach temperature heterogeneity was driven by longitudinal position along the reach but surprisingly not by riparian canopy gaps, vertical stratification, or other factors. Our findings verify temperature mapping at the resolution of inter-confluence reaches effectively captures temperature gradients and indicate that thermally-sensitive organisms have limited access to fine-scale refuge in southern Appalachian streams. Generally, within-reach temperature heterogeneity should be quantified in more geographic and physiographic contexts to understand natural and anthropogenic drivers of this variation, validate reach-resolution temperature mapping, and forecast climate change refuges.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133127"},"PeriodicalIF":5.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696906","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":"Intelligent remote sensing canal system detection and irrigation water use estimation: A case study in the transboundary Mekong River Basin","authors":"Hongling Zhao ,&nbsp;Fuqiang Tian ,&nbsp;Keer Zhang ,&nbsp;Khosro Morovati ,&nbsp;Jingrui Sun","doi":"10.1016/j.jhydrol.2025.133110","DOIUrl":"10.1016/j.jhydrol.2025.133110","url":null,"abstract":"<div><div>Human activities significantly impact global water resource availability through alterations in terrestrial water cycle processes, with agricultural irrigation being a primary driver. Accurately quantifying irrigation water use is essential for understanding regional water resource dynamics, optimizing water resource allocation, and improving agricultural productivity. However, high-quality data on irrigation canal networks is often lacking at regional scales, hindering the precise delineation of river sources for irrigation. To address this, this study developed a large-scale canal system detection method using artificial intelligence (AI) techniques and large-scale satellite remote sensing images. The method enabled the identification of canal networks, clarified the irrigation intake points, and facilitated the calculation of irrigation water volumes supplied by various mainstream and tributaries in the basin. The Mekong River Basin, where riparian states heavily rely on tributaries for irrigation and face difficulties in acquiring canal data, is selected as the study area. The results show that the developed Convolutional Neural Network (CNN)-based method successfully detected 291 irrigation canals sourced from mainstream and tributaries of the Mekong River, with 43% of the main canals drawing directly from the mainstream and the remainder from tributaries. Spatial analysis reveals a higher canal density in the south compared to the north of the basin. Additionally, irrigation water use is markedly higher during the dry season from November to the following April, accounting for 69% of annual irrigation consumption, peaking in January and reaching a minimum in September. This research has the potential to address critical data gaps in irrigation in the Mekong River Basin, enhance the understanding of agricultural irrigation water use, and provide essential insights for effective water resource management and sustainable agricultural development.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133110"},"PeriodicalIF":5.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677806","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":"Experimental study on the mechanism and countermeasures of recharge plugging induced by soil particle migration","authors":"Shilong Zhou ,&nbsp;Xuesong Cheng ,&nbsp;Qinghan Li ,&nbsp;Gang Zheng ,&nbsp;Xinwang Zhang ,&nbsp;Yongsheng Ma ,&nbsp;Bing Li","doi":"10.1016/j.jhydrol.2025.133115","DOIUrl":"10.1016/j.jhydrol.2025.133115","url":null,"abstract":"<div><div>Groundwater recharge is often performed to alleviate the environmental impacts induced by dewatering in excavation engineering. However, the application and widespread adoption of this method are hindered by plugging issue in recharge wells (RWs). The current studies on plugging have focused on the influence of impurities in recharge water, and studies on the effects of soil particle migration caused by seepage are lacking. On the bases of a self-designed model box, the mechanism of recharge plugging caused by particle migration in the process of recharge and mitigation measures were studied. The flow rate decreases with the recharge duration, and it presents a distribution pattern that an area with increased hydraulic conductivity near the RW and an area with decreased hydraulic conductivity far from the RW will occur in recharge process. The greater the recharge water pressure is, the greater the range of areas where the hydraulic conductivity decreases (approximately 2 m–2.2 m away from the RW) and the decreased ratio of hydraulic conductivity after stabilization (from 22 % to 31.5 %). The results of the analysis of the particle size distribution further indicate that seepage can cause the soil particles near the RW to migrate, leading to the accumulation of fine particles at positions away from the RW and eventually contributing to plugging. The soil particles in the model box can be quickly induced to migrate in the opposite direction by reverse recharge in the RW, which reduces the degree of plugging, providing a reference for alleviating RW plugging in engineering practice.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133115"},"PeriodicalIF":5.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677804","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":"Climate change impacts on flood hazards and surface-subsurface water interactions in the Lancang Mekong River Basin","authors":"Salik Bhusal ,&nbsp;Sangam Shrestha ,&nbsp;Tilasmi Aryal","doi":"10.1016/j.jhydrol.2025.133082","DOIUrl":"10.1016/j.jhydrol.2025.133082","url":null,"abstract":"<div><div>The Lancang Mekong River Basin is not only a vital water resource system supporting the livelihoods of millions of people, but it is also one of the most diverse ecosystems in the world, supporting a wide range of flora and fauna. The hydrological regime of the river is expected to undergo significant alterations due to climate change, leading to potential water availability alteration and flood hazards in the region. In this context, this study investigates the basin response to these shifts, particularly focusing on Cambodian Mekong floodplain of Lancang Mekong River Basin. By scrutinizing the surface–subsurface interactions, the research aims to comprehensively understand the dynamics of water flow in the region in the face of climate change. Multi-modelling approach with development of Soil and Water Assessment Tool (SWAT) hydrological model, MIKE FLOOD hydrodynamic model and GMS-MODFLOW groundwater model were used for projecting the flood hazard and quantifying the surface–subsurface interactions in Cambodian Mekong floodplain.</div><div>The results indicated that the hydrological regime of the basin is expected to undergo significant changes in the future, with an overall increase in average annual streamflow by 14.58 % to 17.27 % and groundwater recharge by 7.53 % to 12.99 % under SSP 2–4.5 and SSP 5–8.5 scenarios respectively while exhibiting spatial variability in magnitude of change. The increased streamflow will exacerbate flood hazard in the floodplain in the coming future due to climate change. Likewise, the Mekong River during flooding season is one of the major sources of recharge to the floodplain groundwater aquifer and receives water from the groundwater during dry season. This contribution to floodplain groundwater aquifer recharge during the flooding season is projected to increase in the near future.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133082"},"PeriodicalIF":5.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143739050","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":"Hydrological impact of small hydropower development on mountain rivers in Southwest China and the role of environmental flows","authors":"Xintong Li ,&nbsp;Wouter Buytaert ,&nbsp;Qi Tang ,&nbsp;Yuanming Wang ,&nbsp;Ruifeng Liang ,&nbsp;Kefeng Li","doi":"10.1016/j.jhydrol.2025.133078","DOIUrl":"10.1016/j.jhydrol.2025.133078","url":null,"abstract":"<div><div>Small- and medium-sized mountain rivers are often the locations of small hydropower plants (SHPs), which bring electricity to remote mountainous areas but also cause a range of environmental and ecological impacts. Alterations in hydrological regimes are the most direct impact of SHPs, which in turn triggers changes in physical, chemical, and biological conditions. Environmental agencies of many countries have taken measures to mitigate hydrological changes in these rivers, including requiring SHPs to release environmental flows. However, it remains unclear how effective these measures are in compensating for hydrological changes. In this study, we examined hydrological alterations in seven small mountain river basins in the Yangtze River using a combination of numerical simulation and statistical analysis. A framework was presented and applied to assess the impacts of SHPs and the effects of environmental flows. A total of 32 hydrological indicators were selected and calculated based on measured and modeled hydrological data, and the changes in these indicators were assessed using three indexes. The values of extreme and dynamic water conditions indicators were significantly changed after the SHPs were fully developed. Five indicators, including the number of low pulses, the number of high pulses, the duration of low pulses, the daily rise rate, and the number of flow reversals, were identified as the most unfavorable indicators. A constant environmental flow release of 10% of the long-term average flow, which is the current policy, had a limited impact on mitigating adverse hydrological changes. We therefore suggest the development of an environmental flow regime that better mimics natural flow variability, but not just based on a constant release threshold in small hydropower-developed rivers.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133078"},"PeriodicalIF":5.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696958","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":"Improved model of runoff-seepage coupling in unsaturated soil based on fractal theory","authors":"Xiaodong Zhang ,&nbsp;Qunjie Peng ,&nbsp;Siqi Yang ,&nbsp;Min Liu ,&nbsp;Li Wu ,&nbsp;Lianheng Zhao","doi":"10.1016/j.jhydrol.2025.133120","DOIUrl":"10.1016/j.jhydrol.2025.133120","url":null,"abstract":"<div><div>The Green-Ampt model is widely used in rainfall infiltration analysis of unsaturated soil where fewer parameters are involved. However, the slope surface water is assumed to be constant, and the area above the wetting front is saturated. This has its limitations. In this paper, an improved Green-Ampt model is proposed based on fractal theory considering soil pore characteristics. In the proposed model, the infiltration transition zone is included, the real-time dynamic change of the slope infiltration rate is determined through the runoff-seepage coupling to obtain infiltration profile model at different times. Compared with the existing theoretical results and data from ponded infiltration column tests, the model presented in this paper can accurately calculate the cumulative infiltration of the soil and surface runoff to verify the model’s validity. A set of parametric analyses are conducted to study effect of seepage in unsaturated soil. The results show that The soil’s pore distribution affects the slope’s infiltration profile and the timing of surface runoff generation. The depth of the infiltration zone increases with the increase of the saturated hydraulic conductivity and the soil particle pore size, while it decreases with the increase of the slope angle. At the same time, the runoff-seepage coupling effect cannot be ignored; the generation of surface runoff is delayed with the increase of the slope angle, saturated hydraulic conductivity, and soil particle pore size, which further affects the infiltration rate of the soil. The improved model can effectively analyze the influence of soil pore characteristics on infiltration and is suitable for different soils, especially for silty clay and silty soil.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133120"},"PeriodicalIF":5.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716322","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 hourly streamflow simulation in karst basins: Development of the modified DK-XAJ-EW hydrological model integrating epikarst water storage function dynamics","authors":"Wenzhe Yang ,&nbsp;Lihua Chen ,&nbsp;Wenju Huang ,&nbsp;Yan Qian ,&nbsp;Wenming Zhang","doi":"10.1016/j.jhydrol.2025.133170","DOIUrl":"10.1016/j.jhydrol.2025.133170","url":null,"abstract":"<div><div>The water storage function of the epikarst plays a critical role in influencing the precipitation-streamflow response in karst basins; however, this dynamic is often inadequately represented by a single saturation excess runoff generation mechanism. To effectively capture the spatial heterogeneity of the epikarst’s water storage capacity and its temporal dynamics in redistributing runoff, we developed a reservoir model module. This module performs storage calculations for runoff derived from the saturation excess mechanism, employing an exponential equation to represent the spatial variability of epikarst water storage. By integrating this module with the runoff generation and separation modules of the DK-XAJ model, we quantitatively describe both the vertical and lateral runoff processes within the epikarst, accounting for their temporal evolution driven by spatial heterogeneity, resulting in the modified DK-XAJ-EW model. RSA analysis shows that epikarst reservoir parameters enhance hydrological simulations across various objective functions. The DK-XAJ-EW model outperforms the DK-XAJ model in simulating hourly streamflow and flood events, with improvements in NSE, KGE, R², and RRE values of 0.12, 0.12, 0.12, and 1.05%, respectively. It more accurately simulates surface runoff, interflow, rapid-conduit runoff, and slow-matrix runoff, improving flood event simulations with rapid and slow rise-recession patterns. The average absolute RPE decreased from 13.3% to 6.4% for rapid events and from 19.2% to 6.7% for slow events, while the average absolute PTE decreased from 2 hours to 0.5 hours for rapid events and from 7.5 hours to 3 hours for slow events, highlighting the importance of epikarst water storage in modelling precipitation-streamflow dynamics. The results indicate that the DK-XAJ-EW model provides important insights for refining hydrological predictions in karst basins and has considerable potential for enhancing the accuracy of flood forecasting in these complex environments.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"658 ","pages":"Article 133170"},"PeriodicalIF":5.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738861","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 basin water balance considering water-economic society-ecology nexus","authors":"Qingsong Wu ,&nbsp;Qiting Zuo ,&nbsp;Lekai Zhang ,&nbsp;Yihu Ji ,&nbsp;Zhizhuo Zhang","doi":"10.1016/j.jhydrol.2025.133067","DOIUrl":"10.1016/j.jhydrol.2025.133067","url":null,"abstract":"<div><div>This study proposes a set of methods for quantifying Basin water balance (BWB) in the context of the Water-Economic society-Ecology nexus. Firstly, a theoretical analysis of BWB is conducted, identifying three key aspects that should be considered: Water budget balance (WBB), Water supply–demand balance of economic society (ESWSDB), and Water use balance between economic society and ecology (EEWUB). Secondly, a distributed human-water relationship simulation model was developed, which aligns with the dual water cycle processes of nature and society. Thirdly, targeted methods for various aspects of BWB, along with a comprehensive approach for quantifying BWB, are proposed. Finally, the Qin River Basin in China was selected for a case study covering the period from 2001 to 2022, revealing the state and characteristics of BWB across multiple scales, levels, and dimensions. Results show that: a) during the study period, the WBB of the basin was generally in a slight imbalance state, characterized by decreasing water storage, with the imbalance deteriorating progressively from upstream to downstream; b) the average balance index of ESWSDB is 0.161, indicating an overall trend towards water surplus, but with significant differences in balance state and index across different basin zones; c) the average balance index of EEWUB was −0.168, indicating a slight water deficit on the ecological side, with river runoff during average and low-flow years being insufficient to simultaneously meet both economic-social and ecological water needs; d) overall, the BWB state still has room for improvement and is largely influenced by the WBB and ESWSDB during periods of poor balance state. Findings can enhance the understanding of BWB and offer valuable insights for global water balance quantification, contributing to the management of human-water relationship.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133067"},"PeriodicalIF":5.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677809","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":"Fractional derivatives in advection-dispersion equations: A comparative study","authors":"Amit Kumar Pandey","doi":"10.1016/j.jhydrol.2025.133010","DOIUrl":"10.1016/j.jhydrol.2025.133010","url":null,"abstract":"<div><div>Fractional derivatives capture the heterogeneity of aquifer mediums better than ordinary derivatives; however, due to the global nonacceptance of any general definition, their perfect applications are still questionable. As an effective alternative to the Riemann-Liouville fractional derivative (R-L FD), the present work modeled the fractional advection–dispersion equation (FADE) for spatially varying transport parameters by employing the conformable fractional derivative (CFD) and improved Riemann-Liouville-type conformable fractional derivative (IR-L CFD). In the proposed model, the first order spatial, time derivatives are replaced with the CFD, the IR-L CFD of order <span><math><mrow><mn>0</mn><mo>&lt;</mo><mi>δ</mi><mo>⩽</mo><mn>1</mn></mrow></math></span>. Also, <span><math><mrow><mi>D</mi><mo>∝</mo><msup><mi>v</mi><mi>n</mi></msup><mo>;</mo><mn>1</mn><mo>⩽</mo><mi>n</mi><mo>⩽</mo><mn>2</mn></mrow></math></span> (<span><math><mi>D</mi></math></span>-dispersion, <span><math><mi>v</mi></math></span>-seepage velocity) is considered for capturing the maximum possible orders of the medium heterogeneity. The FADE is solved by homotopy analysis method (HAM) in the presence of spatially increasing non-linear source of contamination. Initially, the groundwater is considered uniformly polluted.</div><div>The performances of the IR-L CFD and CFD are compared using experimental data available in the literature; the findings demonstrate that both CFD and IRLCFD may be used successfully to estimate the fate of pollutants in heterogeneous media; however, the IR-L CFD approximates the R-L FD more accurately than the CFD. Also, the accuracy of the results yielded by the FADE involving the CFD and the IR-L CFD notably relies on the nature of the solute transport parameters. The obtained solutions can be used to verify numerical solutions. The presented model can get solutions of FADEs with rigorous transport conditions that are not solvable otherwise.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133010"},"PeriodicalIF":5.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716319","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":"Unraveling the water quality-ecosystem nexus using Kalman filter-driven models and feature analysis under uncertainty","authors":"Mojtaba Poursaeid","doi":"10.1016/j.jhydrol.2025.133092","DOIUrl":"10.1016/j.jhydrol.2025.133092","url":null,"abstract":"<div><div>Many factors impact water quality (WQ), such as climate change and population growth. Thus, the present work aims to propose an accurate and potent solution for the WQ instabilities challenge in the South Platte River in United States. The data driven model based on the machine learning model tuned with Kalman filter (KF) was considered to reduce input data noise. The least absolute shrinkage and selection operator (LASSO) algorithm were used to analyze the importance of features and select the best inputs. The US Geological Survey (USGS) archive provided the primary database related to 2023–2024, with over 38,000 samples. The random forest (RF) was combined with KF and LASSO to reduce noise and analyze the importance of features due to the high number of samples. Artificial neural network (ANN), linear regression (LR), and support vector machine (SVM) were developed to compare the accuracy of the proposed model. The proposed model had the highest coefficient of determination values, which were between 0.95 and 0.99. Modeling the indicators revealed that some WQ variations could negatively affect aquatic ecosystems.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"657 ","pages":"Article 133092"},"PeriodicalIF":5.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143677808","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}