Journal of Hydrology最新文献

{"title":"A knowledge-guided machine learning framework for reconstructing climate-driven subsurface water dynamics from time-lapse electrical resistivity tomography","authors":"Weiyu Guo, Hang Chen","doi":"10.1016/j.jhydrol.2026.136631","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136631","url":null,"abstract":"Understanding and anticipating climate-driven subsurface water dynamics is essential for assessing water availability and ecosystem function, yet it remains challenging in heterogeneous mountain environments. Time-lapse electrical resistivity tomography (TL-ERT) provides spatially distributed observations of subsurface change but has been used mainly to monitor subsurface change rather than to model its evolution. Here, we develop a knowledge-guided machine learning framework to reconstruct the spatiotemporal evolution of subsurface resistivity from daily meteorological forcing and continuous TL-ERT observations on a monitored hillslope. Before training, the TL-ERT data were corrected to a common reference temperature to remove the direct temperature dependence of resistivity, allowing temporal resistivity changes to be interpreted as a proxy for subsurface water-content change. Three neural architectures were evaluated within a shared recursive framework using structured loss terms that preserve reconstruction accuracy, local spatial structure, and coherent temporal variation. All models reproduced the dominant seasonal patterns, and the PredRNN-based architecture performed best, with an RMSE of 9.5 Ω·m over held-out test windows. Under rolling recursive reconstruction without subsequent ground-truth resistivity observations, the framework maintained seasonally coherent trajectories within the observed record. Under a + 4 °C warming scenario, the simulated temperature-corrected resistivity showed earlier shallow spring decreases about 12% and slight shallow summer increases, with weaker responses at depth. Through a water-content conversion, these changes are consistent with earlier spring wetting and shallow summer drying. These results provide a site-specific proof of concept that continuous TL-ERT observations combined with knowledge-guided machine learning can reconstruct the seasonal evolution of subsurface resistivity within the observed record and support scenario-based hydrologic interpretation.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"250 1","pages":"136631"},"PeriodicalIF":6.4,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149236203","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":"Complex behavior of an urban green infrastructure imaged using time-lapse electrical resistivity tomography and time-series clustering","authors":"Alexis Luzy, Adrien Dimech, François Duhaime, Janie Masse-Dufresne, Jean-Sébastien Dubé, Rose-Anne Farley, Rémi Clément, Maxime Paradis","doi":"10.1016/j.jhydrol.2026.136632","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136632","url":null,"abstract":"Urban green infrastructure (GI) is increasingly being implemented to manage stormwater, promote infiltration, and limit loads on drainage networks. However, their design still relies largely on large-scale hydrological performance, with limited attention to site-specific hydrogeological processes. Key mechanisms governing infiltration, solute transport, and seasonal dynamics remain poorly understood, especially in cold-climate cities using de-icing salts, which may threaten buried infrastructure, contribute to groundwater salinization, and degrade receiving ecosystems. Field observations are needed to improve understanding of these processes. This study presents one year of monitoring of water and chloride dynamics around an instrumented GI using high-resolution cross-borehole time-lapse electrical resistivity tomography (TL-ERT) at a roadside site in Laval, Quebec, Canada. Automated geoelectrical monitoring was conducted between October 2024 and November 2025 with four surveys per day, using commercial and open-source hardware. The geophysical approach was complemented by hydrogeological monitoring (water levels and sensors). A time-series clustering method was applied to the inverted dataset to identify distinct temporal behaviors of subsurface units. Results indicate infiltration linked to winter rainfall and spring snowmelt. Seasonal conductivity variations in winter and spring are interpreted as being largely influenced by pore-water conductivity associated with de-icing salt mobilization, while late summer and autumn changes are more consistent with VWC-driven responses. Overall, combining cross-borehole TL-ERT, time-series clustering, and hydrogeological instrumentation provides detailed insight into seasonal water and solute movement in small-scale, heterogeneous urban environments, where point monitoring is often limited. This approach is well suited for studying urban GI, while remaining dependent on auxiliary measurements for process attribution.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"166 1","pages":"136632"},"PeriodicalIF":6.4,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149236208","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 of mountain riverine air–water CO2 exchange estimates to elevation decompression and localized atmospheric CO2 variability","authors":"Xue Qiao, Hui Liu, Weiyang Xiao, Wenbin Hu, Hailiang Song, Yue Ding, Zhongjun Xu, Jie Du, Ya Tang","doi":"10.1016/j.jhydrol.2026.136633","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136633","url":null,"abstract":"Mountain rivers act as critical CO<ce:inf loc=\"post\">2</ce:inf> outgassing hotspots in the global carbon cycle. However, conventional air–water CO<ce:inf loc=\"post\">2</ce:inf> exchange estimates often rely on static atmospheric CO<ce:inf loc=\"post\">2</ce:inf> boundary conditions, which introduces potential uncertainties in topographically complex regions. Integrating multi-site spatial surveys across an 1,100 m elevation gradient and a one-year high-frequency in-situ monitoring campaign at a site in the subalpine Jiuzhaigou karst catchment, we decouple the independent effects of physical topography and micro-meteorology on riverine CO<ce:inf loc=\"post\">2</ce:inf> evasion. First, altitude-driven barometric decompression steepens the air–water CO<ce:inf loc=\"post\">2</ce:inf> partial pressure gradient. While atmospheric CO<ce:inf loc=\"post\">2</ce:inf> calculations do not universally assume standard sea-level pressure, failing to apply site-specific local barometric corrections can alter each site’s mean riverine CO<ce:inf loc=\"post\">2</ce:inf> exchange rate by up to 23.2 mmol m<ce:sup loc=\"post\">−2</ce:sup> h<ce:sup loc=\"post\">−1</ce:sup>, with the absolute magnitudes dependent on local turbulence. Independently, localized atmospheric CO<ce:inf loc=\"post\">2</ce:inf> pooling dynamically shifts the instantaneous air–water gradient. This pooling occurs not only at night but also during the daytime, driven by local microclimate, biological processes, and human activities. Second, despite substantial daytime photosynthetic CO<ce:inf loc=\"post\">2</ce:inf> drawdowns, the karst waters maintain continuous year-round outgassing. This persistent supersaturation is predominantly sustained by massive, continuous external groundwater and soil dissolved inorganic carbon inputs that consistently exceed evasion and assimilation rates. Ultimately, while boundary simplifications do not significantly impact annual cumulative CO<ce:inf loc=\"post\">2</ce:inf> emissions (0.02%−11% deviation), integrating dynamic barometric corrections and localized atmospheric CO<ce:inf loc=\"post\">2</ce:inf> monitoring is essential for accurately resolving high-frequency instantaneous outgassing kinetics in complex terrains.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"11 1","pages":"136633"},"PeriodicalIF":6.4,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149236204","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":"Occurrence-rate nonstationarity alters design rainfall return levels: A decomposed Poisson-GPD analysis across contrasting hydroclimatic regimes","authors":"Shubham Dixit, Kamlesh K. Pandey","doi":"10.1016/j.jhydrol.2026.136627","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136627","url":null,"abstract":"Climate-informed rainfall frequency analysis increasingly informs design rainfall estimation. Atmospheric processes favoring extreme rainfall occurrence may differ from those amplifying event magnitude, yet peaks-over-threshold (POT) models often treat occurrence as stationary while modeling nonstationary (NS) severity. Because POT return levels (RL) depend jointly on occurrence and excess magnitude, this choice can alter design estimates. We evaluated whether separating occurrence and severity changes return levels using daily rainfall at 15 climatically contrasting Indian locations. Occurrence and severity covariates were screened separately and used in Poisson occurrence and GPD severity models to compare stationary, NS-occurrence-only, NS-severity-only, and full NS-occurrence-severity formulations. Models allowing occurrence to vary received more support than stationary and severity-only formulations and reduced unexplained variability in exceedance counts. Nonstationary return levels were defined using fitted monthly occurrence and severity conditions over the evaluation period. Over 2001–2022, adding occurrence nonstationarity to the severity-only model lowered RL at 8 stations and raised it at 7. At Indore and Panaji, full occurrence-severity formulation also avoided implausibly large severity-only return levels, showing that occurrence modeling can affect magnitude and plausibility. Because nonstationary return levels depend on climatic conditions, sensitivity to alternative evaluation periods was examined. Occurrence covariates remained informative beyond seasonality, particularly for moisture transport, whereas severity covariates showed varied associations with thermodynamic, dynamic, and teleconnection-related variables. Overall, separating occurrence and severity showed that changes in exceedance frequency can materially influence design return levels and improve process interpretation of nonstationary rainfall-frequency estimates. Sensitivity checks consistently supported occurrence nonstationarity, although return-level effects were sometimes specification-dependent.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"12 1","pages":"136627"},"PeriodicalIF":6.4,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149236212","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":"Spatiotemporal evolution and drivers of compound dry-hot and wet-hot events in a changing climate","authors":"Chao Wang, Fanli Sun, Shuzhe Huang, Wei Wang","doi":"10.1016/j.jhydrol.2026.136629","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136629","url":null,"abstract":"Compound dry-hot events (CDHEs) and compound wet-hot events (CWHEs) are two contrasting types of compound heat extremes with different impacts. However, their global evolution and changes under climate change, as well as their attribution to thermal and precipitation factors, remain insufficiently compared within a consistent framework. This study assesses CDHEs and CWHEs from 1961 to 2100 using multi-model CMIP6 simulations under the historical period and four SSP scenarios. We analyze changes in several indicators and use a copula-based return-period decomposition to separate the effects of hot conditions, precipitation anomalies, and their dependence structure. Diagnostic land-atmosphere analyses using vapor pressure deficit, relative humidity, and soil moisture are conducted to explore associated physical pathways. Results show that both CDHEs and CWHEs have intensified since the 1990s, but with distinct spatial patterns. CDHEs increase more strongly in arid and semi-arid regions, whereas CWHEs intensify more rapidly in humid climatic zones and high-latitude regions. Future projections indicate continued increases in compound heat risks under all SSPs, especially under high-emission scenarios. By the late 21st century, CWHEs are projected to become increasingly dominant, with faster increases in severity and duration than CDHEs. The decomposition analysis shows that hot conditions are the dominant driver, and the diagnostic analysis further identifies vapor pressure deficit as the most consistent predictor associated with both event types. These findings highlight the growing importance of wet-heat hazards and provide a basis for differentiated adaptation strategies under continued warming.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"34 1","pages":"136629"},"PeriodicalIF":6.4,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149236211","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":"Process-based modeling of managed aquifer recharge in a hillslope-valley system under two contrasting climatic regimes","authors":"Xinying Ling, Menberu B. Meles, Scott A. Bradford, Hoori Ajami","doi":"10.1016/j.jhydrol.2026.136628","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136628","url":null,"abstract":"Managed aquifer recharge (MAR) is increasingly used to enhance groundwater storage, yet its effectiveness has mainly been studied in flat agricultural and flood-plain areas, not hillslope regions. In this study, we investigated groundwater dynamics in response to pumping and MAR in an idealized hillslope-valley system under two contrasting climatic regimes based on Modesto (244 mm yr⁻<ce:sup loc=\"post\">1</ce:sup>) and Camino (941 mm yr⁻<ce:sup loc=\"post\">1</ce:sup>), California. A physically-based, fully coupled MIKE SHE model was developed to simulate coupled overland flow, unsaturated-zone, and groundwater flow. Long-term simulations were conducted to establish dynamic equilibrium under natural (undeveloped) conditions, followed by pumping and MAR scenarios (injection wells, surface MAR-release, and surface MAR-hold) to evaluate groundwater responses to different management strategies. The subsurface storage reached dynamic equilibrium within 180 years (dry climate) and 140 years (wet climate) under natural climate forcing conditions. Human-impacted scenarios required additional time for subsurface storage adjustment (90–130 years under dry conditions and 30–70 years under wet conditions). Pumping near the river had a negligible influence on groundwater levels but reduced streamflow, whereas pumping in the valley and especially the hillslope led to extensive cones of depression due to differences in aquifer response time and groundwater storage, respectively. Under the simulated conditions, hillslope MAR produced a faster groundwater response due to larger hydraulic gradients and increased lateral flow, while MAR in valley and floodplain regions was limited by groundwater travel times and surface water interactions, respectively. The short-term groundwater responses varied systematically among MAR approaches. Injection wells produced rapid, localized groundwater mounding; surface MAR application with runoff release caused small mounding due to runoff losses; and surface MAR with ponding generated higher groundwater mounding due to prolonged ponding. Hillslope MAR further enhanced recoverable storage in the valley. This is particularly important in overexploited valley aquifers. MAR effectiveness should be assessed over decadal to centennial timescales, as short-term assessments can substantially overestimate sustainable groundwater recovery. These findings provide a process-based framework for evaluating long-term MAR performance and designing sustainable groundwater extraction and recharge strategies.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"4 1","pages":"136628"},"PeriodicalIF":6.4,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149236213","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":"Uncertainty in streamflow simulation performance arising from precipitation inputs and hydrological models under different flow regimes and catchment conditions","authors":"Yongjing Wan, Jie Chen, Daiyuan Li, Jingjing Sun, Yuanlin Qiu, Mingming Wang, Shihua Zhang","doi":"10.1016/j.jhydrol.2026.136607","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136607","url":null,"abstract":"Hydrological simulations are inherently affected by uncertainties arising from precipitation inputs and hydrological models. The relative importance of those uncertainty sources across different flow regimes and catchment conditions remains poorly understood. This study used six gridded daily precipitation datasets to force five widely applied conceptual hydrological models over 379 catchments in China. Nine performance metrics were used to represent different flow regimes, and a two-way analysis of variance method (ANOVA) was applied to quantify the relative contributions of those uncertainty sources to streamflow simulation performances. Results show substantial discrepancies in precipitation magnitude among those datasets, while model calibrations partially compensate for these biases. Attributions of hydrological simulation uncertainties exhibit flow-regime dependence. For metrics represented to high-flow performances, the contribution associated with hydrological model choice is dominant, which accounts for approximately 40–80% of total uncertainty. In contrast, the primary contribution shifts to precipitation input for metrics of low flow performances, explaining 40–70% of the total uncertainty. For metrics of the mid-flow performances, precipitation inputs, hydrological models, and their interaction contribute comparably to total uncertainty. Moreover, uncertainty in hydrological simulation performance is significantly related to catchment characteristics with larger uncertainty in smaller and more arid catchments. In terms of relative contribution, the contribution associated with precipitation forcing choice increases with mean slope and runoff coefficient but decreases with catchment area and aridity index, whereas the contribution associated with hydrological model choice decreases with mean slope and elevation. The contribution associated with the interaction increases with mean elevation, catchment area, and elongation ratio, but decreases with runoff coefficient. This study provides new insights into the flow-regime dependence and catchment-related variability of uncertainty in hydrological simulation performance and offers guidance for selecting modeling strategies.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"7 1","pages":"136607"},"PeriodicalIF":6.4,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149236218","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":"Bivariate regional frequency analysis of extreme rainfall depth and intensity: comparing annual maxima and r-Largest approaches with simulated annealing regionalization across South Korea","authors":"Adisa Hammed Akinsoji, Qudus Adeyi, Rahmon Abiodun Salau, Deepak Chaulagain, Kyung Sook Choi","doi":"10.1016/j.jhydrol.2026.136614","DOIUrl":"https://doi.org/10.1016/j.jhydrol.2026.136614","url":null,"abstract":"Extreme rainfall in South Korea has intensified under recent climate variability, yet national infrastructure design standards still rely on univariate analyses of pre-2000 data that treat rainfall depth and intensity as independent, understating joint flood risk. This study addresses that gap with a bivariate regional frequency analysis (BRFA) of multi-duration extreme rainfall, jointly modeling event depth and mean intensity across accumulation durations of 6, 12, 24, and 48 h using 41 years of hourly records from 61 KMA ASOS stations. Two sampling approaches are compared: annual maxima (AMx) with residual-based decorrelation, and r-Largest, retaining the five largest IETD-separated monsoon events per year without decorrelation. Simulated Annealing optimization of the bivariate L-comoments H<ce:inf loc=\"post\">1</ce:inf> statistic delineated six homogeneous regions (H<ce:inf loc=\"post\">1</ce:inf> = 0.105–0.916, all satisfying H<ce:inf loc=\"post\">1</ce:inf> &lt; 1.0) pooling 2,501 station-years. GUM dominated AMx marginal selection at 6–12 h and PE3 at 24–48 h; PE3 and Exponential dominated r-Largest. The Gaussian copula prevailed under AMx (54.2%); Frank (41.7%), and GUM (25.0%) prevailed under r-Largest. Critically, exponential back-transformation in the AMx decorrelation procedure amplifies intensity estimation errors (per-site NSE = −97.5), while r-Largest yields physically realistic intensity estimates (RMSE 2–16 mm h<ce:sup loc=\"post\">−1</ce:sup>). Regional 100-year depth quantiles of 160–233 mm at 6 h and 271–372 mm at 24 h exceed the current Korean national standards by 15–25%, warranting revisions to design standards for agricultural drainage and hydraulic infrastructure.","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"21 1","pages":"136614"},"PeriodicalIF":6.4,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149236217","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":"Corrigendum to “A causality-informed and copula-based framework for predictive assessment of downstream water-quality risks under extreme scenarios” [J. Hydrol., 669, Part B (2026) 135123]","authors":"Quan Zhou,&nbsp;Jiajia Zhang,&nbsp;Tian Lan,&nbsp;Yongqin David Chen,&nbsp;Siye Wei,&nbsp;Xiuwen Ren,&nbsp;Wenjing Wang,&nbsp;Chunju Zheng,&nbsp;Renren Wu","doi":"10.1016/j.jhydrol.2026.136318","DOIUrl":"10.1016/j.jhydrol.2026.136318","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"679 ","pages":"Article 136318"},"PeriodicalIF":7.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148895175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “PINN framework for urban flood depth prediction: integrating data-driven insights with physical constraints” [J. Hydrol. 665 (2026) 134693]","authors":"Wenli Liu,&nbsp;Qian Wu,&nbsp;Zihan Liu,&nbsp;Xu Zheng,&nbsp;Tianxiang Liu,&nbsp;Han Gao","doi":"10.1016/j.jhydrol.2026.136316","DOIUrl":"10.1016/j.jhydrol.2026.136316","url":null,"abstract":"","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"679 ","pages":"Article 136316"},"PeriodicalIF":7.3,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148984879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}