Journal of Flood Risk Management最新文献

{"title":"Using Storage Ponds in Natural Flood Management Schemes in Practice: The Need for Fine-Tuning and Upscaling","authors":"Leo Peskett,&nbsp;Sarah Collins,&nbsp;Andrew Black,&nbsp;Matthew Arran,&nbsp;Alan MacDonald,&nbsp;Andy Young","doi":"10.1111/jfr3.70059","DOIUrl":"https://doi.org/10.1111/jfr3.70059","url":null,"abstract":"<p>There is increasing interest in installing water storage ponds as part of natural flood management (NFM) approaches being implemented globally. Despite decades of experience with constructing flood storage ponds within civil engineering disciplines, there remains little empirical evidence of their effectiveness in NFM. In NFM, ‘natural’ ponds use green infrastructure, are often smaller but more numerous, and are built and maintained by land managers rather than engineers. Here we investigate six flood storage ponds in the 69 km² Eddleston NFM pilot catchment in Scotland, UK, analysing impact on peak stream flows at different scales and pond designs. The ponds generally reduce peak stream flows where they have large available capacity, catchments are small (&lt; 1 km²), and events are low magnitude (&gt; 20% Annual Exceedance Probability (AEP)). No discernible flow reduction was observed at the largest pond and catchment (64 km²) for the largest (~21% AEP) event. There was significant variability between ponds, and gains can be made in engineering pond inlet/outlet structures, maintenance, and more widespread installation. The findings suggest that natural storage ponds have most potential to contribute to flood control in small catchments (&lt; 10 km²) and small flood events (&gt; 25% AEP), when they are carefully designed and maintained, and sufficient in number.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the Role of Hydrodynamics in Enhancing Height-Above-the-Nearest-Drainage Derived Synthetic Rating Curves: A Comparative Study in the Wu River Basin, Taiwan","authors":"Cheng-Wei Yu,&nbsp;Wun-Jhen Yang,&nbsp;Dongyu Feng","doi":"10.1111/jfr3.70057","DOIUrl":"https://doi.org/10.1111/jfr3.70057","url":null,"abstract":"<p>The conventional approach to generating synthetic rating curves (SRC) using the Height-Above-the-Nearest-Drainage (HAND) method typically relies on the assumption of uniform flow, such as Manning's equation, to establish stage-discharge ratings. The zero-physics application of the uniform flow equation is insufficient for capturing detailed hydraulic features (e.g., backwater effect) and neglects the hydraulic effects from adjacent channels. This lack of hydrodynamic computation can impact the accuracy and effectiveness of riverine flood risk estimation and management. To reduce this foreseeable error, we introduce the HAND-hd workflow, which integrates sophisticated hydrodynamic computations in the production of HAND-based SRC with hydrodynamic features (SRC_hd). The results indicate that SRC_hd demonstrates consistent agreement with both gauge observations and benchmark solutions. Additionally, the comparative analysis suggests that SRC_hd provides notable improvements in stage-discharge ratings over conventional HAND-based SRCs, particularly in channels with mild bed gradients, where it reduces water stage prediction errors and percent biases. In steeper channel segments, SRC_hd maintains comparable accuracy to conventional methods. The comprehensive evaluation in this study emphasizes the potential discrepancies and inaccuracies associated with the adoption of the uniform flow assumption in the conventional HAND-SRCs and addresses the necessity of including hydrodynamic physics in the application of HAND-based SRC (e.g., inundation map) in channels with mild gradients.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143883978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the Utilization of Machine Learning to Map Flood Susceptibility","authors":"Ali Pourzangbar,&nbsp;Peter Oberle,&nbsp;Andreas Kron,&nbsp;Mário J. Franca","doi":"10.1111/jfr3.70042","DOIUrl":"https://doi.org/10.1111/jfr3.70042","url":null,"abstract":"<p>This article provides an analysis of the utilization of Machine Learning (ML) models in Flood Susceptibility Mapping (FSM), based on selected publications from the past decade (2013–2023). Recognizing the challenge that some stages of ML modeling inherently rely on experience or trial-and-error approaches, this work aims at establishing a clear roadmap for the deployment of ML-based FSM frameworks. The critical aspects of ML-based FSM are identified, including data considerations, the model's development procedure, and employed algorithms. A comparative analysis of different ML models, alongside their practical applications, is made. Findings suggest that despite existing limitations, ML methods, when carefully designed and implemented, can be successfully utilized to determine areas at risk of flooding. We show that the effectiveness of ML-based FSM models is significantly influenced by data preprocessing, feature engineering, and the development of the model using the most impactful parameters, as well as the selection of the appropriate model type and configuration. Additionally, we introduce a structured roadmap for ML-based FSM, identification of overlooked conditioning factors, comparative model analysis, and integration of practical considerations, all aimed at enhancing modeling quality and effectiveness. This comprehensive analysis thereby serves as a critical resource for professionals in the field of FSM.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70042","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards Equity? Advancing Rural Consideration in Flood Risk Management","authors":"Daniel W. A. Jones,&nbsp;Fiona Williams,&nbsp;Namrata Bhattacharya Mis,&nbsp;Philip M. Marren","doi":"10.1111/jfr3.70055","DOIUrl":"https://doi.org/10.1111/jfr3.70055","url":null,"abstract":"<p>Flood risk management (FRM) in England and Wales predominantly follows a utilitarian approach guided by cost–benefit analysis, with a corresponding focus on urban areas. This approach has been criticised for being unjust, as it neglects vulnerabilities that cannot be readily monetised, resulting in some of the most vulnerable flood-affected communities being excluded from FRM provision. This issue is especially pronounced in rural areas. Ironically, rural communities are often overlooked despite many contributing to the protection of urban settlements. In response to increasing research on social injustices in FRM and policy calls for more equitable approaches, greater consideration of rural flooding is required. Using the River Severn catchment as a case study, this paper employs a questionnaire survey of 176 rural residents to gather perspectives on their engagement with FRM agencies. Their responses were then discussed with FRM organisations active in the region through interviews. The combined perspectives of rural communities and FRM organisations reveal challenges and opportunities for achieving just consideration of rural areas in FRM. The findings emphasise the need for a more inclusive approach to FRM in the River Severn catchment and offer valuable lessons for other rural areas in the United Kingdom and beyond.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Special Issue From the Ninth International Conference on Flood Management","authors":"Slobodan P. Simonovic","doi":"10.1111/jfr3.70060","DOIUrl":"https://doi.org/10.1111/jfr3.70060","url":null,"abstract":"&lt;p&gt;The Ninth International Conference on Flood Management (ICFM9 https://www.icfm.world/ICFM-Conferences/ICFM9) was held in Tsukuba, Japan, from February 18 to 22, 2023, under the theme “River Basin Disaster Resilience and Sustainability by All – Integrated Flood Management in the Post-COVID-19 Era.” The increasing frequency and severity of torrential rainfall due to global climate change have led to greater human losses and economic damage. The number of people vulnerable to devastating floods continues to rise due to large-scale urbanization, population migrations to and growth in flood-prone areas, deforestation, climate change, and rising sea levels. During the COVID-19 pandemic, immediate attention was often focused on preventing further virus transmission; however, the threat of floods remains as urgent as ever. The primary objective of ICFM9 was to draw lessons from past experiences and enhance the resilience of societies to flooding.&lt;/p&gt;&lt;p&gt;Since the adoption of &lt;i&gt;The Sendai Framework for Disaster Risk Reduction (DRR) 2015–2030&lt;/i&gt; at the Third United Nations World Conference on DRR in March 2015, the international community has also agreed on &lt;i&gt;Transforming Our World: The 2030 Agenda for Sustainable Development&lt;/i&gt; in September 2015 and &lt;i&gt;The Paris Agreement on Climate Change&lt;/i&gt; in December 2015. To support and implement these agreements, strong, coordinated, and strategic actions are necessary to enhance climate and disaster resilience and sustainability. ICFM9 was designed to contribute to a deeper understanding of the challenges posed by our changing world and to explore solutions that will strengthen resilience against flood-related disasters.&lt;/p&gt;&lt;p&gt;Flood disaster resilience and sustainable development are fundamentally and structurally interconnected. Addressing these challenges requires a comprehensive approach that transcends disciplinary boundaries, promotes holistic and integrated strategies, and ensures effective planning, implementation, and evaluation. With this in mind, ICFM9 facilitated in-depth discussions on a wide range of issues from scientific, technological, social, and economic perspectives.&lt;/p&gt;&lt;p&gt;The conference emphasized the necessity of adopting a comprehensive and forward-thinking approach to flood risk reduction, resilience building, and adaptive management. Its key messages reflected a growing recognition of the importance of integrated, inclusive, and science-driven strategies for managing flood risks in an era of increasing uncertainty. The ICFM9 highlighted the urgency of adopting holistic, data-driven, and socially inclusive approaches to flood management. Strengthening the link between science and decision-making, promoting open data sharing, enhancing flood modeling, integrating knowledge across disciplines, fostering skilled professionals, and prioritizing social equity will collectively shape a more resilient future in the face of escalating flood risks.&lt;/p&gt;&lt;p&gt;One of the central themes highlighted at","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preserving the Past in a Changing Climate: An Approach to Assess the Impact of Urban Flooding in Cultural Heritage Cities","authors":"Paolo Tamagnone,&nbsp;Marco Lompi,&nbsp;Enrica Caporali","doi":"10.1111/jfr3.70043","DOIUrl":"https://doi.org/10.1111/jfr3.70043","url":null,"abstract":"<p>Urban floods are increasing due to the intensification of precipitation extremes in a changing climate and to the intensive expansion of urbanscapes. Therefore, flood hazards can potentially increase losses to historical buildings and cultural heritage. In this context, this study proposes a methodology to assess the impact of climate change on urban flooding at the district and building scale. The methodology is applied in the Santa Croce District, where an extensive collection of masterpieces of the city of Florence (Italy) is preserved and exposed, especially in the National Central Library. The flood hazard assessment is obtained by using a dual drainage hydraulic model to quantify the flooded area within the buildings due to the overflow of sewer systems. An ensemble of 34 climate model projections based on output from Phase 6 of the Climate Model Intercomparison Project (CMIP6) in two emission scenarios, or Shared Socioeconomic Pathways (SSP245 and SSP585) and two time windows (2021–2050, Near Future, and 2071–2100, Far Future) are considered as input of the model. The results show that the flood hazard will increase in all climate scenarios, especially in the SSP585 at the end of the century.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143875569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wildfire-Induced Enhancement in Downstream Flood Discharge in Watersheds of California","authors":"Wasitha Dilshan,&nbsp;Yusuke Hiraga,&nbsp;So Kazama","doi":"10.1111/jfr3.70054","DOIUrl":"https://doi.org/10.1111/jfr3.70054","url":null,"abstract":"<p>Global climate change is increasingly associated with the prevalence of extreme precipitation and large wildfires. The influence of large wildfires on downstream flood discharge is concerning, particularly from a flood risk management perspective, where understanding the impact at a watershed scale is still fairly limited. This study investigates the impacts of wildfires on downstream flood discharge in 30 Californian watersheds. We employed the Soil and Water Assessment Tool (SWAT) to simulate daily discharge over 20 years, achieving robust model performance <i>R</i>² values of 0.67–0.86 and Nash–Sutcliffe efficiency (NSE) values of 0.65–0.86. The differences between the observed flood discharge volume and the simulated unburned scenario, including model errors (i.e., flood discharge enhancement), during the post-fire years were assessed. Substantial post-fire discharge increases, with an average 17.1% increment in 83.3% of watersheds, were found during the first post-fire year. Statistically significant positive correlations (<i>p</i> &lt; 0.01) were found between the enhancement in discharge volume and the percentage of burned watershed area. We quantified wildfire impacts by adjusting the curve number (CN) in the SWAT model, with CN values increasing by increments ranging from 16.5% to 30% of their original values, depending on burn severity and land use type. A novel relationship between wildfire area burned and CN increment could be described by the equation %CN increment = 0.39 × wildfire area burned % + β, which highlights the proportional increase in CN due to wildfire area burned. The study also showed that incorporating historical wildfire activity significantly raised the probable maximum flood, with discharge volume increases between 3.74% and 25.9%. These wildfire-induced increases are on par with California's climate change projections (10%–50%), underscoring the need to factor in wildfire effects in flood risk assessments and water management strategies at this type of location.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70054","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling the Effectiveness of Vegetative Nature-Based Solutions for Coastal Flood Risk Mitigation","authors":"Yengi Emmanuel Daro Justine,&nbsp;Avidesh Seenath","doi":"10.1111/jfr3.70046","DOIUrl":"https://doi.org/10.1111/jfr3.70046","url":null,"abstract":"<p>Traditional grey solutions, such as seawalls, are increasingly recognised as being unsustainable for long-term coastal flood risk management, due to high costs and negative environmental impacts. In response, vegetative nature-based coastal solutions (NBCS), such as saltmarshes, are being increasingly proposed as a more sustainable alternative with wider environmental benefits. However, there is considerable uncertainty on the longevity of such solutions under sea-level rise. We, therefore, examine the effectiveness of vegetative NBCS for mitigating coastal flood risk through scenario modelling using a verified <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mtext>LISFLOOD-FP</mtext>\u0000 </mrow>\u0000 <annotation>$$ LISFLOODhbox{-} FP $$</annotation>\u0000 </semantics></math> model for Absecon Island in New Jersey, USA. Specifically, we simulate various experimental vegetative NBCS scenarios, each designed to represent a saltmarsh system (young, mid-age, and old), under alternative sea-level conditions. Our results show that these solutions have a marginal influence on flood extent, depth, velocity, and timing under current and future projected sea-level conditions. These findings suggest that reliance on vegetative NBCS <i>may not</i> be sustainable for long-term coastal flood risk management, particularly under climate change. We discuss the wider implications of these findings and identify future research pathways towards improving and informing more robust coastal flood risk management decisions.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70046","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expert-Derived Flood Damage Curves for Critical Infrastructure Network Components","authors":"James H. Williams,&nbsp;Huong Ngan Vu,&nbsp;Ryan Paulik,&nbsp;Conrad Zorn,&nbsp;Liam Wotherspoon","doi":"10.1111/jfr3.70045","DOIUrl":"https://doi.org/10.1111/jfr3.70045","url":null,"abstract":"<p>Flood impact assessment is limited by a scarcity of damage curves for critical infrastructure network components. This study presents a judgement-based methodology for developing critical infrastructure network component flood damage curves. The 12 semi-structured workshops record responses for estimated minimum and maximum damage ratios at 0.5, 1, 2 and 3 m water depths. The 46 responses, weighted by participant expertise level, are aggregated into a discrete minimum and maximum damage curve for each component. Damage curves are presented for 34 infrastructure network components across the transportation, energy, water, and telecommunication sectors. These damage curves are benchmarked against relevant flood damage curves from previous studies, providing insight on how flood damage models compare internationally and across methods. While the synthesised flood damage curves allow for nationally consistent risk assessments, this study highlights the need for flood damage curves that represent local risk contexts for infrastructure network components to facilitate locally applicable risk assessments that inform risk management.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70045","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143861542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Implementation of a Machine Learning-Based Flood Forecasting System in Kasese District, Uganda","authors":"Edward Miiro,&nbsp;Ismael Kato,&nbsp;Zuhra Nantege,&nbsp;Samuel Ssendi,&nbsp;Khasim Bassajjalaba","doi":"10.1111/jfr3.70039","DOIUrl":"https://doi.org/10.1111/jfr3.70039","url":null,"abstract":"<p>This study aimed to develop a proof-of-concept prototype of a machine learning system to forecast and mitigate the effect of floods in Kasese District. The researchers used a participatory design science approach. The researchers conducted document reviews and brainstorming to obtain past climate data from the representatives of affected communities, the Makerere University Department of Meteorology, and the Uganda National Meteorological Authority. Qualitative data were transcribed from recordings of the brainstorming sessions and notes from literature. The data were then summarized in tables and analyzed using Visual Network Analysis (VNA) with Word Clouds and Gephi Open Source Software. We employed a combination of C++ programming, sensors wired to Arduino 2 and 3 Integrated Development Environment System to build the prototype. Two machine learning algorithms, including linear regression and K-nearest neighbours (KNN) were used to learn from collected hydrological data and make necessary predictions. Using sensors, we were able to read water levels, temperature, and humidity. The prototype successfully demonstrated the ability to send early-warning alerts to users, contributing to both theoretical advancements in disaster risk reduction and practical tools for mitigating flood-related losses in Uganda. The researchers recommend further study to validate the use of this system and evaluate its efficacy and predictive accuracy in averting floods in affected areas.</p>","PeriodicalId":49294,"journal":{"name":"Journal of Flood Risk Management","volume":"18 2","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.70039","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}