{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T23:46:09Z","timestamp":1773877569310,"version":"3.50.1"},"reference-count":57,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T00:00:00Z","timestamp":1763337600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000192","name":"National Oceanic and Atmospheric Administration","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000192","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100011531","name":"University of Alabama","doi-asserted-by":"publisher","award":["NA22NWS4320003"],"award-info":[{"award-number":["NA22NWS4320003"]}],"id":[{"id":"10.13039\/100011531","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Environmental Modelling & Software"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1016\/j.envsoft.2025.106786","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T11:17:57Z","timestamp":1763637477000},"page":"106786","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["A framework for the evaluation of flood inundation predictions over extensive benchmark databases"],"prefix":"10.1016","volume":"196","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2387-3889","authenticated-orcid":false,"given":"Dipsikha","family":"Devi","sequence":"first","affiliation":[]},{"given":"Supath","family":"Dhital","sequence":"additional","affiliation":[]},{"given":"Dinuke","family":"Munasinghe","sequence":"additional","affiliation":[]},{"given":"Sagy","family":"Cohen","sequence":"additional","affiliation":[]},{"given":"Anupal","family":"Baruah","sequence":"additional","affiliation":[]},{"given":"Yixian","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Dan","family":"Tian","sequence":"additional","affiliation":[]},{"given":"Carson","family":"Pruitt","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"7","key":"10.1016\/j.envsoft.2025.106786_bib1","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.3390\/rs10071091","article-title":"Quantitative remote sensing at ultra-high resolution with UAV spectroscopy: a review of sensor technology, measurement procedures, and data correction workflows","volume":"10","author":"Aasen","year":"2018","journal-title":"Remote Sens."},{"issue":"1","key":"10.1016\/j.envsoft.2025.106786_bib2","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1007\/s11069-013-0939-9","article-title":"Designing a flood forecasting and inundation-mapping system integrated with spatial data infrastructures for Turkey","volume":"71","author":"Ak\u0131nc\u0131","year":"2014","journal-title":"Nat. Hazards"},{"issue":"1","key":"10.1016\/j.envsoft.2025.106786_bib3","doi-asserted-by":"crossref","DOI":"10.1111\/jfr3.12871","article-title":"The assessment for selection and correction of RS\u2010based DEMs and 1D and 2D HEC\u2010RAS models for flood mapping in different river types","volume":"16","author":"Arash","year":"2023","journal-title":"J. Flood Risk Manag."},{"issue":"5","key":"10.1016\/j.envsoft.2025.106786_bib4","doi-asserted-by":"crossref","DOI":"10.1029\/2022WR032039","article-title":"Extending height above nearest drainage to model multiple fluvial sources in flood inundation mapping applications for the US National Water model","volume":"59","author":"Aristizabal","year":"2023","journal-title":"Water Resour. Res."},{"issue":"2","key":"10.1016\/j.envsoft.2025.106786_bib5","doi-asserted-by":"crossref","first-page":"1473","DOI":"10.5194\/hess-22-1473-2018","article-title":"Citizen observations contributing to flood modelling: opportunities and challenges","volume":"22","author":"Assump\u00e7\u00e3o","year":"2018","journal-title":"Hydrol. Earth Syst. Sci."},{"issue":"2","key":"10.1016\/j.envsoft.2025.106786_bib6","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1111\/j.1753-318X.2009.01029.x","article-title":"Sources of uncertainty in flood inundation maps","volume":"2","author":"Bales","year":"2009","journal-title":"J. Flood Risk Manag."},{"issue":"4","key":"10.1016\/j.envsoft.2025.106786_bib7","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1080\/19479832.2019.1625977","article-title":"Remote sensing data quality model: from data sources to lifecycle phases","volume":"10","author":"Barsi","year":"2019","journal-title":"Int. J. Image Data Fusion"},{"issue":"2","key":"10.1016\/j.envsoft.2025.106786_bib8","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1007\/s11600-023-01063-y","article-title":"Holistic framework for flood hazard assessment in a trans-boundary basin","volume":"72","author":"Baruah","year":"2024","journal-title":"Acta Geophys."},{"key":"10.1016\/j.envsoft.2025.106786_bib9","doi-asserted-by":"crossref","DOI":"10.1016\/j.envsoft.2025.106581","article-title":"FIMserv v. 1.0: a tool for streamlining Flood Inundation Mapping (FIM) using the United States operational hydrological forecasting framework","author":"Baruah","year":"2025","journal-title":"Environ. Model. Software"},{"key":"10.1016\/j.envsoft.2025.106786_bib10","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2025.134086","article-title":"Predicting synthetic rating curve adjustment factors with explainable machine learning for enhancing the United States operational flood inundation mapping framework","author":"Baruah","year":"2025","journal-title":"J. Hydrol."},{"issue":"1","key":"10.1016\/j.envsoft.2025.106786_bib11","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1146\/annurev-fluid-030121-113138","article-title":"Flood inundation prediction","volume":"54","author":"Bates","year":"2022","journal-title":"Annu. Rev. Fluid Mech."},{"key":"10.1016\/j.envsoft.2025.106786_bib12","first-page":"1","article-title":"Deep learning methods for flood mapping: a review of existing applications and future research directions","volume":"2022","author":"Bentivoglio","year":"2022","journal-title":"Hydrol. Earth Syst. Sci. Discuss."},{"issue":"1","key":"10.1016\/j.envsoft.2025.106786_bib13","first-page":"47","article-title":"The convexity ratio and applications","volume":"76","author":"Bozeman","year":"2013","journal-title":"Sci. Math. Jpn."},{"issue":"4","key":"10.1016\/j.envsoft.2025.106786_bib14","doi-asserted-by":"crossref","first-page":"485","DOI":"10.5194\/nhess-6-485-2006","article-title":"Flood-risk mapping: contributions towards an enhanced assessment of extreme events and associated risks","volume":"6","author":"B\u00fcchele","year":"2006","journal-title":"Nat. Hazards Earth Syst. Sci."},{"issue":"1","key":"10.1016\/j.envsoft.2025.106786_bib15","doi-asserted-by":"crossref","first-page":"1657","DOI":"10.1038\/s41597-025-05941-6","article-title":"Merging remote sensing derived river slope datasets with high-resolution hydrofabrics for the United States","volume":"12","author":"Chen","year":"2025","journal-title":"Sci. Data"},{"issue":"8","key":"10.1016\/j.envsoft.2025.106786_bib59","doi-asserted-by":"crossref","DOI":"10.1029\/2024WR039574","article-title":"Toward robust evaluations of flood inundation predictions using remote sensing derived benchmark maps","volume":"61","author":"Cohen","year":"2025","journal-title":"Water Resour. Res."},{"issue":"9","key":"10.1016\/j.envsoft.2025.106786_bib16","doi-asserted-by":"crossref","first-page":"2053","DOI":"10.5194\/nhess-19-2053-2019","article-title":"The floodwater depth estimation tool (FwDET v2. 0) for improved remote sensing analysis of coastal flooding","volume":"19","author":"Cohen","year":"2019","journal-title":"Nat. Hazards Earth Syst. Sci."},{"issue":"2","key":"10.1016\/j.envsoft.2025.106786_bib18","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1111\/1752-1688.13184","article-title":"NOAA's National Water model: advancing operational hydrology through continental\u2010scale modeling","volume":"60","author":"Cosgrove","year":"2024","journal-title":"JAWRA J. Am Water Res. Associat."},{"issue":"3","key":"10.1016\/j.envsoft.2025.106786_bib19","doi-asserted-by":"crossref","first-page":"1989","DOI":"10.1007\/s11069-022-05253-7","article-title":"Characterization of dam-impacted flood hydrograph and its degree of severity as a potential hazard","volume":"112","author":"Devi","year":"2022","journal-title":"Nat. Hazards"},{"key":"10.1016\/j.envsoft.2025.106786_bib20","article-title":"FIMPEF: a framework for automatic evaluation of flood inundation mapping predictions over large and scalable benchmark datasets","author":"Devi","year":"2024","journal-title":"AGU24"},{"key":"10.1016\/j.envsoft.2025.106786_bib21","article-title":"Msfootprint: a Python package for extracting Microsoft's global building footprints based on user-defined boundaries","author":"Dhital","year":"2025","journal-title":"Zenodo"},{"issue":"2","key":"10.1016\/j.envsoft.2025.106786_bib22","doi-asserted-by":"crossref","DOI":"10.1029\/2022WR033168","article-title":"Physics\u2010informed neural networks of the saint\u2010venant equations for downscaling a large\u2010scale River model","volume":"59","author":"Feng","year":"2023","journal-title":"Water Resour. Res."},{"issue":"2","key":"10.1016\/j.envsoft.2025.106786_bib23","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1111\/1752-1688.12476","article-title":"AutoRAPID: a model for prompt streamflow estimation and flood inundation mapping over regional to continental extents","volume":"53","author":"Follum","year":"2017","journal-title":"JAWRA J. Am Water Res. Associat."},{"issue":"2","key":"10.1016\/j.envsoft.2025.106786_bib24","doi-asserted-by":"crossref","first-page":"625","DOI":"10.5194\/nhess-20-625-2020","article-title":"Improved accuracy and efficiency of flood inundation mapping of low-, medium-, and high-flow events using the AutoRoute model","volume":"20","author":"Follum","year":"2020","journal-title":"Nat. Hazards Earth Syst. Sci."},{"issue":"5","key":"10.1016\/j.envsoft.2025.106786_bib25","doi-asserted-by":"crossref","first-page":"1493","DOI":"10.5194\/nhess-18-1493-2018","article-title":"Low cost, multiscale and multi-sensor application for flooded area mapping","volume":"18","author":"Giordan","year":"2018","journal-title":"Nat. Hazards Earth Syst. Sci."},{"issue":"4","key":"10.1016\/j.envsoft.2025.106786_bib26","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1111\/1752-1688.12783","article-title":"Error assessment for height above the nearest drainage inundation mapping","volume":"55","author":"Godbout","year":"2019","journal-title":"JAWRA J. Am Water Res. Associat."},{"key":"10.1016\/j.envsoft.2025.106786_bib27","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2022.128170","article-title":"Spatial scale evaluation of forecast flood inundation maps","volume":"612","author":"Hooker","year":"2022","journal-title":"J. Hydrol."},{"issue":"2","key":"10.1016\/j.envsoft.2025.106786_bib28","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1080\/19475683.2018.1450787","article-title":"A near real-time flood-mapping approach by integrating social media and post-event satellite imagery","volume":"24","author":"Huang","year":"2018","journal-title":"Annals GIS"},{"issue":"11","key":"10.1016\/j.envsoft.2025.106786_bib29","doi-asserted-by":"crossref","first-page":"2405","DOI":"10.5194\/nhess-19-2405-2019","article-title":"An integrated evaluation of the national water model (NWM)\u2013height above nearest drainage (HAND) flood mapping methodology","volume":"19","author":"Johnson","year":"2019","journal-title":"Nat. Hazards Earth Syst. Sci."},{"issue":"6","key":"10.1016\/j.envsoft.2025.106786_bib30","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1007\/s40745-021-00366-5","article-title":"Feature selection in imbalanced data","volume":"10","author":"Kamalov","year":"2023","journal-title":"Annals Data Sci."},{"key":"10.1016\/j.envsoft.2025.106786_bib31","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2024.114439","article-title":"Towards robust validation strategies for EO flood maps","volume":"315","author":"Landwehr","year":"2024","journal-title":"Rem. Sens. Environ."},{"issue":"1","key":"10.1016\/j.envsoft.2025.106786_bib32","doi-asserted-by":"crossref","first-page":"98","DOI":"10.3390\/rs11010098","article-title":"Flood hazard mapping and assessment on the Angkor world heritage site, Cambodia","volume":"11","author":"Liu","year":"2019","journal-title":"Remote Sens."},{"issue":"5","key":"10.1016\/j.envsoft.2025.106786_bib33","doi-asserted-by":"crossref","first-page":"1731","DOI":"10.5194\/nhess-12-1731-2012","article-title":"FIM FRAME: a method for assessing and improving emergency plans for floods","volume":"12","author":"Lumbroso","year":"2012","journal-title":"Nat. Hazards Earth Syst. Sci."},{"key":"10.1016\/j.envsoft.2025.106786_bib34","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.1007\/s11069-017-3083-0","article-title":"Assessing flood hazard using flood marks and analytic hierarchy process approach: a case study for the 2013 flood event in Quang Nam, Vietnam","volume":"90","author":"Luu","year":"2018","journal-title":"Nat. Hazards"},{"issue":"2","key":"10.1016\/j.envsoft.2025.106786_bib35","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1111\/1752-1688.12474","article-title":"Conceptual framework for the national flood interoperability experiment","volume":"53","author":"Maidment","year":"2017","journal-title":"J. Am. Water Resour. Assoc."},{"issue":"8","key":"10.1016\/j.envsoft.2025.106786_bib36","doi-asserted-by":"crossref","first-page":"3041","DOI":"10.1109\/TGRS.2011.2178030","article-title":"Near real-time flood detection in urban and rural areas using high-resolution synthetic aperture radar images","volume":"50","author":"Mason","year":"2012","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"key":"10.1016\/j.envsoft.2025.106786_bib37","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.isprsjprs.2016.04.011","article-title":"Remote sensing methods for power line corridor surveys","volume":"119","author":"Matikainen","year":"2016","journal-title":"ISPRS J. Photogrammetry Remote Sens."},{"issue":"7","key":"10.1016\/j.envsoft.2025.106786_bib38","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1061\/(ASCE)1084-0699(2008)13:7(608)","article-title":"Uncertainty in flood inundation mapping: current issues and future directions","volume":"13","author":"Merwade","year":"2008","journal-title":"J. Hydrol. Eng."},{"key":"10.1016\/j.envsoft.2025.106786_bib39","article-title":"A post-processing machine learning framework for bias-correcting National Water model outputs by accounting for dominant streamflow drivers","volume":"190","author":"Neisary","year":"2025","journal-title":"Environ. Model. Software"},{"issue":"15","key":"10.1016\/j.envsoft.2025.106786_bib40","doi-asserted-by":"crossref","first-page":"4013","DOI":"10.5194\/hess-26-4013-2022","article-title":"Flood forecasting with machine learning models in an operational framework","volume":"26","author":"Nevo","year":"2022","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"10.1016\/j.envsoft.2025.106786_bib41","series-title":"AGU Fall Meeting Abstracts","article-title":"Comparative analysis of flood inundation mapping techniques: evaluating hydrodynamic and terrain-based models for enhanced precision and efficiency using remote sensing","author":"Nikrou","year":"2024"},{"issue":"1\u20132","key":"10.1016\/j.envsoft.2025.106786_bib42","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.jhydrol.2011.03.051","article-title":"Height above the nearest Drainage\u2013a hydrologically relevant new terrain model","volume":"404","author":"Nobre","year":"2011","journal-title":"J. Hydrol."},{"key":"10.1016\/j.envsoft.2025.106786_bib43","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1007\/s11069-016-2382-1","article-title":"Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach","volume":"83","author":"Papaioannou","year":"2016","journal-title":"Nat. Hazards"},{"key":"10.1016\/j.envsoft.2025.106786_bib44","article-title":"GVAL: a python package for model agnostic geospatial evaluations using open-source, cloud-native technologies","volume":"2023","author":"Petrochenkov","year":"2023"},{"key":"10.1016\/j.envsoft.2025.106786_bib45","series-title":"105th AMS Annual Meeting","article-title":"Improvements in continental-scale flood inundation mapping at NOAA's office of water prediction","author":"Pruitt","year":"2025"},{"key":"10.1016\/j.envsoft.2025.106786_bib46","series-title":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","first-page":"3057","article-title":"Proper comparison among methods using a confusion matrix","author":"Salmon","year":"2015"},{"issue":"12","key":"10.1016\/j.envsoft.2025.106786_bib47","doi-asserted-by":"crossref","DOI":"10.1029\/2024EF005164","article-title":"Flooding is not like filling a bath","volume":"12","author":"Sanders","year":"2024","journal-title":"Earths Future"},{"key":"10.1016\/j.envsoft.2025.106786_bib48","doi-asserted-by":"crossref","first-page":"1629","DOI":"10.1007\/s11069-021-04892-6","article-title":"GIS derived synthetic rating curves and HAND model to support on-the-fly flood mapping","volume":"109","author":"Scriven","year":"2021","journal-title":"Nat. Hazards"},{"key":"10.1016\/j.envsoft.2025.106786_bib49","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/j.rse.2018.11.008","article-title":"Near-real-time non-obstructed flood inundation mapping using synthetic aperture radar","volume":"221","author":"Shen","year":"2019","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.envsoft.2025.106786_bib50","doi-asserted-by":"crossref","DOI":"10.1016\/j.envsoft.2019.104561","article-title":"A toolbox to quickly prepare flood inundation models for LISFLOOD-FP simulations","volume":"123","author":"Sosa","year":"2020","journal-title":"Environ. Model. Software"},{"key":"10.1016\/j.envsoft.2025.106786_bib51","doi-asserted-by":"crossref","DOI":"10.1111\/jfr3.12572","article-title":"Improving flood risk map accuracy using high\u2010density LiDAR data and the HEC\u2010RAS river analysis system: a case study from north\u2010eastern Romania","volume":"13","author":"Stoleriu","year":"2020","journal-title":"J. Flood Risk Manag."},{"key":"10.1016\/j.envsoft.2025.106786_bib52","series-title":"IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium","first-page":"5901","article-title":"Bigearthnet: a large-scale benchmark archive for remote sensing image understanding","author":"Sumbul","year":"2019"},{"key":"10.1016\/j.envsoft.2025.106786_bib53","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.envsoft.2017.01.006","article-title":"Flood inundation modelling: a review of methods, recent advances and uncertainty analysis","volume":"90","author":"Teng","year":"2017","journal-title":"Environ. Model. Software"},{"key":"10.1016\/j.envsoft.2025.106786_bib54","series-title":"Chapman Conference on Remote Sensing of the Water Cycle","article-title":"Enhancing satellite image-derived flood maps with hydrologically guided region growing method and high-resolution DEMs","author":"Tian","year":"2024"},{"key":"10.1016\/j.envsoft.2025.106786_bib55","doi-asserted-by":"crossref","DOI":"10.1016\/j.jhydrol.2024.130742","article-title":"Prediction of flood risk levels of urban flooded points though using machine learning with unbalanced data","volume":"630","author":"Wang","year":"2024","journal-title":"J. Hydrol."},{"issue":"9","key":"10.1016\/j.envsoft.2025.106786_bib56","doi-asserted-by":"crossref","first-page":"7968","DOI":"10.1002\/2017WR020917","article-title":"Validation of a 30 m resolution flood hazard model of the conterminous United States","volume":"53","author":"Wing","year":"2017","journal-title":"Water Resour. Res."},{"issue":"12","key":"10.1016\/j.envsoft.2025.106786_bib57","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1029\/2018WR023457","article-title":"GeoFlood: large\u2010scale flood inundation mapping based on high\u2010resolution terrain analysis","volume":"54","author":"Zheng","year":"2018","journal-title":"Water Resour. Res."}],"container-title":["Environmental Modelling & Software"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815225004700?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815225004700?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T16:47:42Z","timestamp":1773852462000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1364815225004700"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":57,"alternative-id":["S1364815225004700"],"URL":"https:\/\/doi.org\/10.1016\/j.envsoft.2025.106786","relation":{},"ISSN":["1364-8152"],"issn-type":[{"value":"1364-8152","type":"print"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A framework for the evaluation of flood inundation predictions over extensive benchmark databases","name":"articletitle","label":"Article Title"},{"value":"Environmental Modelling & Software","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.envsoft.2025.106786","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"106786"}}