Water Resources Research最新文献

Impact of Surface Cover Types and Coverage on Hydraulic Parameters of Overland Flow

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2025-04-10 DOI: 10.1029/2024wr039133

Kai Zhang, Ning Li, Suhua Fu, Dike Feng

{"title":"Impact of Surface Cover Types and Coverage on Hydraulic Parameters of Overland Flow","authors":"Kai Zhang, Ning Li, Suhua Fu, Dike Feng","doi":"10.1029/2024wr039133","DOIUrl":"https://doi.org/10.1029/2024wr039133","url":null,"abstract":"Surface cover influences the hydraulic parameters of overland flow, subsequently affecting soil erosion. Therefore, exploring the flow dynamic mechanisms under different surface cover types is crucial. A series of flume experiments were conducted to investigate the impact of surface cover on the hydraulic parameters of overland flow. The specific experimental conditions were as follows: one slope gradient (15°) and one flow discharge (1.0 × 10−3 m3 s−1), four cover types (corn residue, rock fragment, sweet potato, and corn stem), and seven coverage percentages ranging from 0% to 70%. The results indicated that the cover of non-submerged state was the most effective at reducing flow velocity, with cover of submerged state being the least effective. Under the four cover conditions, flow velocity, Froude number, flow depth, and shear stress exhibited significant power function relationships with coverage (R2 > 0.91). The relationships between Reynolds number and stream power with coverage were not significant under corn residue and rock fragment cover (P > 0.05), but showed significant power function relationships under sweet potato cover (R2 > 0.88). The cover type alters the form of the cover and the flow submergence degree, leading to the change of hydraulic radius, thereby influencing the hydraulic parameters of overland flow. The findings provide scientific evidence for understanding the flow dynamic mechanisms under surface cover and improving the predictive accuracy of soil erosion process models.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"99 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143813930","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}

引用次数: 0

Operational Interval Extraction Based on Long-Short Term Memory Networks for Building More Feasible Reservoir Operation Models

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2025-04-09 DOI: 10.1029/2024wr038147

Yalian Zheng, Pan Liu, Qian Cheng, Huan Xu, Xinran Luo, Weibo Liu, Xiao Li, Hao Ye, Hongxuan Lei, Wei Zhang

{"title":"Operational Interval Extraction Based on Long-Short Term Memory Networks for Building More Feasible Reservoir Operation Models","authors":"Yalian Zheng, Pan Liu, Qian Cheng, Huan Xu, Xinran Luo, Weibo Liu, Xiao Li, Hao Ye, Hongxuan Lei, Wei Zhang","doi":"10.1029/2024wr038147","DOIUrl":"https://doi.org/10.1029/2024wr038147","url":null,"abstract":"Advances in data analytics create an opportunity to enhance reservoir operation. A challenge arising is how to utilize operational data to form realistic constraints of the reservoir operation practice. To address this issue, a novel approach is proposed to extract operational intervals of reservoir outflow by a deep learning method, namely the physics-guided long-short term memory network. The knowledge-informed reservoir operation (KIRO) model was built by adding derived operational intervals of outflow as constraints for the traditional reservoir operation (TRO) model. KIRO couples (a) an optimization model to search for optimal operation schemes, and (b) operational intervals of reservoir operators' decisions based on realistic factors. China's Qingjiang cascade reservoir including Shuibuya, Geheyan, and Gaobazhou reservoirs is used as a case study. Results show that KIRO can yield more physically feasible operation schemes than TRO due to its additional constraints. Specifically, KIRO avoids excessive reservoir water level fluctuations and outflow variations compared with TRO. Moreover, the extracted operational interval can help uncover implicit demands of real-world operation, for example, the KIRO model accurately identified the cascade reservoir unit maintenance events from 31 January 2019, to 31 March 2019, and the operation schemes were aligned more closely with the power demands. This study provides a new method for building more feasible reservoir operation models based on deep learning.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"10 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143806188","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}

引用次数: 0

Data Enabled Predictive Control for Water Distribution Systems Optimization

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2025-04-09 DOI: 10.1029/2024wr039059

Gal Perelman, Avi Ostfeld

引用次数: 0

Visual-Analytics Bridge Complexity and Accessibility for Robust Urban Water Planning

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2025-04-09 DOI: 10.1029/2024wr037633

Marta Zaniolo, Meagan S. Mauter, Sarah M. Fletcher

{"title":"Visual-Analytics Bridge Complexity and Accessibility for Robust Urban Water Planning","authors":"Marta Zaniolo, Meagan S. Mauter, Sarah M. Fletcher","doi":"10.1029/2024wr037633","DOIUrl":"https://doi.org/10.1029/2024wr037633","url":null,"abstract":"Urban water resources planning is complicated by unprecedented uncertainty in supply and demand. Real-world planning often simplifies the full range of uncertainty faced by a system into a limited set of deterministic scenarios to enhance accessibility for decision-makers and the public. However, overlooking uncertainty can expose the system to failures. On the other end of the spectrum, academically developed tools for scenario analysis rigorously quantify the combined effects of multiple sources of uncertainty, but the practical application of these models is limited by the challenges of information visualization and communication of results. In short, municipal water supply planners lack access to planning frameworks that effectively integrate a rigorous treatment of uncertainty with accessible, user-friendly visual and interactive tools to enhance user accessibility. In this work, we fill this gap by proposing Visual-Robust Decision Making, and demonstrate an application for the city of Santa Barbara (SB), CA. Santa Barbara faces multiple uncertainties from pending state and federal regulations to changing hydrology and water demand. The city seeks to increase its water portfolio robustness by expanding its seawater desalination plant, but must decide how much capacity to add. We introduce computational tools that assess uncertainty across nine uncertain drivers identified with the help of water planners in SB. To allow public participation in the desalination expansion decision, we develop interactive visual-analytics to aid decision-makers and stakeholders in navigating complex scenario analysis outcomes. Our results quantify the tradeoffs between increased capacity and system robustness and aim to enhance participation and uncertainty characterization of urban water planning efforts.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"60 1 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143814189","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}

引用次数: 0

Reducing Flood Insurance Costs by Employing Geographic Risk Complementarity

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2025-04-09 DOI: 10.1029/2024wr038128

Shibo Cui, Jiaqing Wang, Shiruo Hu, Yanyun Wang, Xiaoxiao Wang, Jianshi Zhao

{"title":"Reducing Flood Insurance Costs by Employing Geographic Risk Complementarity","authors":"Shibo Cui, Jiaqing Wang, Shiruo Hu, Yanyun Wang, Xiaoxiao Wang, Jianshi Zhao","doi":"10.1029/2024wr038128","DOIUrl":"https://doi.org/10.1029/2024wr038128","url":null,"abstract":"Flood insurance is an important financial measure for flood risk management. However, a significant protection gap in flood insurance exists in many countries due to high flood insurance costs. Reducing flood insurance costs for both policyholders and insurance companies is crucial for implementing flood insurance. This study introduces the concept of geographic complementarity of flood risk to reduce overall insurance costs and allocate individual premiums via the portfolio theory and the cooperative game theory. Furthermore, we introduce expected utility theory to verify the effectiveness of reduced costs on individual willingness to pay (WTP) for flood insurance. The proposed approach is illustrated in China. The results show that there are low correlation coefficients of flood losses across different regions in China, indicating high geographic risk complementarity. Compared with independent insurance in each province, national flood insurance can reduce total premiums by 15.5% and total risk reserves by 62.7%, as well as increasing WTP rates from 12.4% to 23.6%. The provinces of the Coastland River Basin show the greatest decrease in premiums when pooling regional or national flood risk, compared with purchasing insurance by provinces separately. In summary, geographic complementarity in flood risk has significant effects on flood insurance costs and WTP rates, implying that China has great potential to employ this characteristic to implement a national or cross-provincial flood insurance program. Furthermore, the proposed comprehensive approach can also offer new insights for enhancing catastrophe insurance affordability in more countries.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"11 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143814186","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}

引用次数: 0

The Response to Hydrological Regime Change of Nitrogen Transformation Processes at the Sediment-Water Interface of Seasonal Floodplain Lakes: Insights From the Yangtze River-Poyang Lake System

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2025-04-08 DOI: 10.1029/2024wr037972

Zhongtian Zhang, Guangqiu Jin, Hongwu Tang, Haiyu Yuan, Hexiang Chen, Qi Zhang

{"title":"The Response to Hydrological Regime Change of Nitrogen Transformation Processes at the Sediment-Water Interface of Seasonal Floodplain Lakes: Insights From the Yangtze River-Poyang Lake System","authors":"Zhongtian Zhang, Guangqiu Jin, Hongwu Tang, Haiyu Yuan, Hexiang Chen, Qi Zhang","doi":"10.1029/2024wr037972","DOIUrl":"https://doi.org/10.1029/2024wr037972","url":null,"abstract":"Poyang Lake, the largest freshwater lake in China and a globally significant wetland, is intricately connected to the hydrological dynamics of the Yangtze River via a complex river-lake exchange system. This system generates to unique seasonal fluctuations, forming a distinctive seasonal lake system, which influences hydrological and hydrodynamic processes across floodplains. Recent years have witnessed significant alterations in the hydrological patterns of the Yangtze River, notably in water levels, thereby impacting the nutrient dynamics such as nitrogen transformation at the sediment-water interface of Poyang Lake. This study establishes a coupled model integrating hydrodynamics and nitrogen transformation to elucidate the impacts of the hydrological regime of Yangtze River on nitrogen transformation in Poyang Lake after the operation of Three Gorges Dam. Findings reveal spatiotemporal variations in both hydraulics and nitrogen transformation within the seasonal lake system. Notably, the recharge rate between surface water and groundwater experiences a substantial shift, surpassing 60%. Furthermore, the nitrification rate at the sediment-water interface escalates by 28.5%, and the denitrification rate increases by 21.3% owing to pronounced alterations in the hydrological regime. However, this intensified transformation does not translate to enhanced efficiency, as the nitrogen transformation efficiency declines to 72.3% of its original rate. This research provides a theoretical framework for understanding the ecological and environmental impacts of human interventions on Poyang Lake and highlights the implications for managing other floodplains and seasonal lakes globally, such as lakes on floodplains of Amazon River and Mekong River, which face similar challenges in hydrological dynamics and ecosystem health.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"20 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143798046","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}

引用次数: 0

How Alluvial Storage Controls Spatiotemporal Water Balance Partitioning in Intermittent and Ephemeral Stream Systems

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2025-04-08 DOI: 10.1029/2024wr037256

E. Zarate, M. S. Andersen, G. C. Rau, R. I. Acworth, H. Rutlidge, A. M. MacDonald, M. O. Cuthbert

{"title":"How Alluvial Storage Controls Spatiotemporal Water Balance Partitioning in Intermittent and Ephemeral Stream Systems","authors":"E. Zarate, M. S. Andersen, G. C. Rau, R. I. Acworth, H. Rutlidge, A. M. MacDonald, M. O. Cuthbert","doi":"10.1029/2024wr037256","DOIUrl":"https://doi.org/10.1029/2024wr037256","url":null,"abstract":"The hydrological dynamics of intermittent rivers and ephemeral streams (IRES) impacts the availability of water to riparian ecosystems, the height of downstream runoff peaks, and the replenishment of groundwater systems. Despite its significance, the influence of superficial geology on IRES flow processes remains an area of limited understanding. Here we first present a comprehensive data set encompassing streamflow and groundwater levels from an intermittent stream situated in New South Wales, Australia. We then use targeted geophysical investigations to show how the configurations of superficial geology control the streamflow and groundwater responses. The analysis reveals that periods of stable stream stage consistently occur after episodic surges in streamflow, followed by recession and channel desiccation. The duration of the stable phases exhibits an upstream-to-downstream pattern, reaching a maximum of 44 ± 3 days upstream and then abruptly declining further downstream. There is remarkable consistency in the duration of these stable flow periods, irrespective of the size of preceding streamflow peaks. We propose two primary controls of this behavior: (a) variability in permeability contrasts between channel alluvium and surrounding geological deposits, and (b) longitudinal fluctuations in the volume of the recent channel alluvial reservoir. The interplay of these controls generates a “goldilocks zone,” which optimizes riparian water availability and the potential for groundwater recharge in IRES landscapes. These geological controls may reflect a continuum present in other dryland catchments with widespread implications for groundwater recharge and stream classification based on flow occurrence and duration.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"25 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143798002","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}

引用次数: 0

Predicting Morphological Changes Along a Macrotidal Coastline Using a Two-Stage Machine Learning Model

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2025-04-08 DOI: 10.1029/2024wr037523

Pavitra Kumar, Nicoletta Leonardi

{"title":"Predicting Morphological Changes Along a Macrotidal Coastline Using a Two-Stage Machine Learning Model","authors":"Pavitra Kumar, Nicoletta Leonardi","doi":"10.1029/2024wr037523","DOIUrl":"https://doi.org/10.1029/2024wr037523","url":null,"abstract":"Understanding and predicting coastal change is of the foremost importance to protect coastal communities and coastal assets. This study analyzes field data from 125 locations along the Morecambe coastline, consisting of beach transects collected twice a year for more than a decade (2007–2022). Wave data at these 125 locations were simulated using the hydrodynamic Delft3D model, with full coupling of the Delft3D FLOW and WAVE modules. To model the sediment volume changes observed along the Morecambe coastline, this study proposes a two-stage machine learning model that incorporates beach behavior classification and deep learning techniques to predict changes in sediment volumes along coastal environments. The first stage of the model, developed using a random forest classifier, classifies beach behavior into four categories: eroding, accreting, stable, or undergoing short-term fluctuations. The second stage of the model developed using LSTM and sequence-to-sequence models, uses the output of the first stage to predict the change in sediment volume after erosion/accretion. The random forest classifier achieves testing accuracy of 0.74. LSTM model achieved a testing regression of 0.92 for one-step-ahead (6 months) predictions of change in sediment volume time series, while sequence-to-sequence model achieved the testing regression of 0.96 for three-time-ahead (1.5 years) predictions and 0.88 for ten-time-step-ahead (5 years) prediction.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"66 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143798045","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}

引用次数: 0

Constraining the Modern Hydrological Balance of Bear Lake, Utah-Idaho: Insights From Stable Isotopes (δ18O and δ2H)

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2025-04-07 DOI: 10.1029/2024wr038264

M. J. Custado, C. A. Gagnon, B. Belanger, N. Sekhon, J. Bernstein-Schalet, C. W. Kinsley, W. D. Sharp, J. L. Oster, D. E. Ibarra

{"title":"Constraining the Modern Hydrological Balance of Bear Lake, Utah-Idaho: Insights From Stable Isotopes (δ18O and δ2H)","authors":"M. J. Custado, C. A. Gagnon, B. Belanger, N. Sekhon, J. Bernstein-Schalet, C. W. Kinsley, W. D. Sharp, J. L. Oster, D. E. Ibarra","doi":"10.1029/2024wr038264","DOIUrl":"https://doi.org/10.1029/2024wr038264","url":null,"abstract":"Freshwater lakes are vital water resources, especially in the context of a changing climate. Supplementing existing hydrological methods to monitor lake levels may greatly improve resource management, particularly in drought-prone regions. In this study, we performed dual-isotope (δ18O and δ2H) calculations to model the hydrological balance of Bear Lake, Utah-Idaho. The lake is a critical water resource and site for paleoclimate studies of the latest Pleistocene. Using the Craig-Gordon isotopic mass balance model, we simultaneously constrained unknown fluxes, including groundwater discharge and particularly evaporation, which is typically under-constrained due to inconsistencies across existing methods. Data from community databases and sampling campaigns in 2022 and 2023 were utilized to derive an evaporation rate of 2.18 × 108 m3/yr (±4.94 × 106 m3/yr, 1σ using δ18O; ±3.47 × 106 m3/yr, 1σ using δ2H) at a calculated relative humidity of 0.62 above the lake. Detailed analysis of the sensitivity of the model revealed that parameters related to atmospheric moisture, particularly humidity and its isotopic composition, significantly influence evaporation estimates. Using carbonate-based isotope data, we leveraged this sensitivity to provide insights in the evaporation and humidity at Bear Lake during different time periods. This study shows the potential of using modern water isotopic composition to aid with interpreting carbonate-based paleoclimate data sets and informing current and future water resource management practices.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"6 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143789855","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}

引用次数: 0

Hindcasting Maximum Water Depths in Coastal Watersheds: The Importance of Incorporating Off-Channel Data and Their Uncertainties in Machine Learning Models

IF 5.4 1区地球科学

Water Resources Research Pub Date : 2025-04-06 DOI: 10.1029/2024wr039244

Maryam Pakdehi, Ebrahim Ahmadisharaf

{"title":"Hindcasting Maximum Water Depths in Coastal Watersheds: The Importance of Incorporating Off-Channel Data and Their Uncertainties in Machine Learning Models","authors":"Maryam Pakdehi, Ebrahim Ahmadisharaf","doi":"10.1029/2024wr039244","DOIUrl":"https://doi.org/10.1029/2024wr039244","url":null,"abstract":"In the absence of adequate observations on the off-channel areas, flood models are typically trained and validated against stream water depths. This approach can be efficient for physics-based models, which incorporate the underlying physical processes, but the efficiency for data-driven models like machine learning (ML) algorithms is unclear. The existing off-channel observations like high-water marks (HWMs) are also subject to uncertainty. This paper addressed three research questions: (a) how useful are ML models, trained with stream gauges, for hindcasting water depths in the off-channel areas? (b) how does incorporating the uncertainty of HWMs improve the model performance? and (c) does the uncertainty incorporation improve the model transferability to other watersheds and events? To answer these questions, we evaluated the performance of ML models across three large coastal watersheds in the US during three hurricanes—Michael, Ida and Ian. The model was developed under three scenarios, which differed in terms of the flood observational data (stream gauges and HWMs) used for their training and validation. A loss function was proposed to incorporate the uncertainty of observations. We found that ML models trained solely by stream gauges performed well only for stream hindcasts. Satisfactory hindcasts on off-channel areas were obtained by incorporating the HWMs' uncertainty via the loss function. This uncertainty incorporation reduced the model bias and resulted in the best transferability to other coastal watersheds and flood events. Our study provides insights about developing transferable ML models for hindcasting water depths on streams and off-channel areas in coastal watersheds during extreme events.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"183 1","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143789749","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}

引用次数: 0