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dc.contributor.authorFlack, DLA
dc.contributor.authorSkinner, CJ
dc.contributor.authorHawkness-Smith, L
dc.contributor.authorO'Donnell, G
dc.contributor.authorThompson, RJ
dc.contributor.authorWaller, JA
dc.contributor.authorChen, AS
dc.contributor.authorMoloney, J
dc.contributor.authorLargeron, C
dc.contributor.authorXia, X
dc.contributor.authorBlenkinsop, S
dc.contributor.authorChampion, AJ
dc.contributor.authorPerks, MT
dc.contributor.authorQuinn, N
dc.contributor.authorSpeight, LJ
dc.date.accessioned2019-04-10T12:46:50Z
dc.date.issued2019-04-08
dc.description.abstractRecent surface-water and flash floods have caused millions of pounds worth of damage in the UK. These events form rapidly and are difficult to predict due to their short-lived and localised nature. The interdisciplinary Flooding From Intense Rainfall (FFIR) programme investigated the feasibility of enhancing the integration of an end-to-end forecasting system for flash and surface-water floods to help increase the lead time for warnings for these events. Here we propose developments to the integration of an operational end-to-end forecasting system based on the findings of the FFIR programme. The suggested developments include methods to improve radar-derived rainfall rates and understanding of the uncertainty in the position of intense rainfall in weather forecasts; the addition of hydraulic modelling components; and novel education techniques to help lead to effective dissemination of flood warnings. We make recommendations for future advances such as research into the propagation of uncertainty throughout the forecast chain. We further propose the creation of closer bonds to the end users to allow for an improved, integrated, end-to-end forecasting system that is easily accessible for users and end users alike, and will ultimately help mitigate the impacts of flooding from intense rainfall by informed and timely action.en_GB
dc.identifier.citationVol. 11 (4), article 725en_GB
dc.identifier.doi10.3390/w11040725
dc.identifier.urihttp://hdl.handle.net/10871/36779
dc.language.isoenen_GB
dc.publisherMDPIen_GB
dc.rights© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectfloodingen_GB
dc.subjectintense rainfallen_GB
dc.subjectend-to-end forecastingen_GB
dc.subjectpublic outreachen_GB
dc.subjectradaren_GB
dc.subjecthydraulic modellingen_GB
dc.subjectnumerical weather predictionen_GB
dc.subjectdata assimilationen_GB
dc.titleRecommendations for Improving Integration in National End-to-End Flood Forecasting Systems: An Overview of the FFIR (Flooding From Intense Rainfall) Programmeen_GB
dc.typeArticleen_GB
dc.date.available2019-04-10T12:46:50Z
dc.descriptionThis is the final version. Available on open access from MDPI via the DOI in this recorden_GB
dc.identifier.eissn2073-4441
dc.identifier.journalWateren_GB
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2019-04-02
rioxxterms.funderNatural Environment Research Councilen_GB
rioxxterms.funderNatural Environment Research Councilen_GB
rioxxterms.identifier.projectNE/K00896X/1en_GB
rioxxterms.identifier.projectNE/K008900/1en_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2019-04-08
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-04-10T09:30:50Z
refterms.versionFCDAM
refterms.dateFOA2019-04-10T12:46:53Z
refterms.panelBen_GB
rioxxterms.funder.projectae8f9d68-ad66-489b-8741-7973b70b95a6en_GB
rioxxterms.funder.projectda190f89-82f1-444a-a23e-83228482d6fben_GB


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© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).