README file 
About the data set 
Title: Understanding Community Flood Resilience 
Creators: Sophie Laidlaw, School of Biological and Environmental Sciences, Liverpool John Moores University (ORCID 0009-0004-1681-4057), Sarah Percival, School of Biological and Environmental Sciences, Liverpool John Moores University (ORCID 0000-0002-8935-5822), Konstadinos Kiriakoulakis, School of Biological and Environmental Sciences, Liverpool John Moores University (ORCID 0000-0002-6136-5332)
The creators hold the rights for the dataset
Year of publication: 2025
Description 
Background: Flooding is one of the most complex natural hazards and is expected to affect more people than any other. To reduce these impacts, research has shifted to more dynamic resilience-based approaches, however, there is still a lack of understanding as to how to measure communities resilience to flooding.
Aim: To understand and analyse potential community flood resilience factors, through utilising lay knowledge from different community groups (Flood action groups, those that had been previously flooded, and those that had not previously experienced flooding). 
Design and method: Quali-quantitative analysis of questionnaires, containing both open and closed questions, with participants online and face to face in two contrasting areas (Kendal, Cumbria and Chester, Cheshire). 125 questionnaires were collected for analysis. These were analysed using qualitative methods, as well as using thematic coding to generate themes for open questions.
Results: Each group had differing opinions on the importance of each factor that was presented to the participants, as well as the additional factors they suggested. Whilst there are base flood resilience factors that would be applicable to all communities in England (i.e. land use and planning and mitigation), there are some factors that are specific to some communities (i.e. native language proficiency and flood defences).
Conclusions: It is suggested any future community flood resilience models are flexible, potentially adopting a ‘pick and mix’ approach. 
 This dataset should be cited as Laidlaw, Percival and Kiriakoulakis, 2025 using the DOI: 
https://doi.org/10.24377/LJMU.d.00000240
Contact details 
Sophie Laidlaw: S.M.Laidlaw@2017.ljmu.ac.uk
Terms of use 
Please cite : Laidlaw, S., Percival, S., and Kiriakoulakis, K (2025) Community Flood Resilience Data. [Data Collection] DOI 
 Project and funding information    
Project Title: Assessing community flood resilience factors from the community perspective. 
Contents  
UnderstandingCommunityFloodResilienceData.xlsx
UnderstandingCommunityFloodResilienceSurveys.pdf
Methods  
Initially, questionnaires were distributed online through a gatekeeper, to members of Flood action groups. The scope was then expanded to Kendal, Cumbria (Previously experienced severe flooding) and Chester (Not previously experienced flooding) with data collected using site visits. The surveys were also published on social media pages (i.e. Facebook and LinkedIn). The questionnaire assessed demographic data, the participants opinions on what community flood resilience means to them, this was then followed up with likert scale questions, assessing their opinions on existing community flood resilience factors, as well as open questions to further assess these options, and allow suggestions for any other factors. 125 questionnaires were completed and analysed using a mix of quantitative (correlation) and qualitative (thematic analysis) approaches. 
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