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Visualisation and evaluation of flood uncertainties based on ensemble modelling
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS. (Geospatial informationsteknik)ORCID iD: 0000-0002-3906-6088
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS. (Geospatial informationsteknik)ORCID iD: 0000-0002-3884-3084
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Division of Visual Information and Interaction, Department of Information Technology, Uppsala University, Uppsala, Sweden. (Geospatial informationsteknik)ORCID iD: 0000-0003-0085-5829
2016 (English)In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 30, no 2, p. 240-262Article in journal (Refereed) Published
Abstract [en]

This study evaluates how users incorporate visualisation of flood uncertainty information in decision-making. An experiment was conducted where participants were given the task to decide building locations, taking into account homeowners’ preferences as well as dilemmas imposed by flood risks at the site. Two general types of visualisations for presenting uncertainties from ensemble modelling were evaluated: (1) uncertainty maps, which used aggregated ensemble results; and (2) performance bars showing all individual simulation outputs from the ensemble. Both were supplemented with either two-dimensional (2D) or three-dimensional (3D) contextual information, to give an overview of the area.The results showed that the type of uncertainty visualisation was highly influential on users’ decisions, whereas the representation of the contextual information (2D or 3D) was not. Visualisation with performance bars was more intuitive and effective for the task performed than the uncertainty map. It clearly affected users’ decisions in avoiding certain-to-be-flooded areas. Patterns to which the distances were decided from the homeowners’ preferred positions and the uncertainties were similar, when the 2D and 3D map models were used side by side with the uncertainty map. On the other hand, contextual information affected the time to solve the task. With the 3D map, it took the participants longer time to decide the locations, compared with the other combinations using the 2D model.Designing the visualisation so as to provide more detailed information made respondents avoid dangerous decisions. This has also led to less variation in their overall responses.

Place, publisher, year, edition, pages
Taylor & Francis, 2016. Vol. 30, no 2, p. 240-262
Keywords [en]
visualisation, uncertainty, flood, ensemble modelling, decision-making
National Category
Computer and Information Sciences Oceanography, Hydrology and Water Resources
Identifiers
URN: urn:nbn:se:hig:diva-20124DOI: 10.1080/13658816.2015.1085539ISI: 000365550900006Scopus ID: 2-s2.0-84948086666OAI: oai:DiVA.org:hig-20124DiVA, id: diva2:847157
Note

Finasierat via European Union (EU) through Tillvaxtverket [GLOBES 2 project] projektnummer: 170430

Available from: 2015-08-19 Created: 2015-08-19 Last updated: 2018-12-03Bibliographically approved
In thesis
1. Modelling, mapping and visualisation of flood inundation uncertainties
Open this publication in new window or tab >>Modelling, mapping and visualisation of flood inundation uncertainties
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Flood maps showing extents of predicted flooding for a given extreme event have wide usage in all types of spatial planning tasks, as well as serving as information material for the public. However, the production processes that these maps undergo (including the different data, methods, models and decisions from the persons generating them), which include both Geographic Information Systems (GIS) and hydraulic modelling, affect the map’s content, and will be reflected in the final map. A crisp flood boundary, which is a common way of representing the boundary in flood maps, may therefore not be the best representation to be used. They provide a false implication that these maps are correct and that the flood extents are absolute, despite the effects of the entire modelling in the prediction output. Hence, this research attempts to determine how flood prediction outputs can be affected by uncertainties in the modelling process. In addition, it tries to evaluate how users understand, utilise and perceive flood uncertainty information. 

Three main methods were employed in the entire research: uncertainty modelling and analyses; map and geovisualisation development; and user assessment. The studies in this work showed that flood extents produced were influenced by the Digital Elevation Model (DEM) resolution and the Manning’s  used. This effect was further increased by the topographic characteristic of the floodplain. However, the performance measure used, which quantify how well a model produces result in relation to a reference floor boundary, had also biases in quantifying outputs. Determining the optimal model output, therefore, depended on outcomes of the goodness-of-fit measures used.

 In this research, several ways were suggested on how uncertainties can be visualised based on the data derived from the uncertainty assessment and by characterising the uncertainty information. These can be through: dual-ended maps; flood probability maps; sequential maps either highlighting the degrees of certainty (certainty map) or degrees of uncertainty (uncertainty map) in the data; binary maps; overlain flood boundaries from different calibration results; and performance bars. Different mapping techniques and visual variables were used for their representation. These mapping techniques employed, as well as the design of graphical representation, helped facilitate understanding the information by the users, especially when tested during the evaluations. Note though that there were visualisations, which the user found easier to comprehend depending on the task given. Each of these visualisations had also its advantages and disadvantages in communicating flood uncertainty information, as shown in the assessments conducted. Another important aspect that came out in the study was how the users’ background influence decision-making when using these maps. Users’ willingness to take risks depended not only on the map, but their perceptions on the risk itself. However, overall, users found the uncertainty maps to be useful to be incorporated in planning tasks.

Abstract [sv]

Översvämningskartor som visar utbredningen av förutspådda översvämningar för vissa extrema händelser har stor användning i all typ av samhällsplanering, samt fungerar som informationsmaterial för allmänheten. Men, de produktionsprocesser som dessa kartor genomgår (inkluderande olika data, metoder, modeller och beslut från de personer som genererar dessa) och som innefattar både geografiska informationssystem (GIS) och hydraulisk modellering, påverkar kartornas innehåll, vilket även återspeglas i de slutliga kartornas utseende. En skarp översvämningsgräns, som är det vanliga sättet att visa gränsen i översvämningskartor, är därför antagligen inte det bästa sättet att representera utbredningen. Sådana gränser ger en falsk trygghet i att dessa kartor är korrekta och att översvämningsutbredningen är absolut, trots att hela processen att producera dem innebär osäkerheter. Denna studie försöker därför undersöka hur översvämningskartering påverkas av osäkerheter i modelleringsprocesser och hur dessa osäkerheter kan representeras, visualiseras och kommuniceras i kartorna. Dessutom försöker studien utvärdera hur olika användare förstår, använder och uppfattar översvämningskartor som innehåller osäkerhetsinformation.

Tre huvudmetoder har använts i denna studie: osäkerhetsmodellering och analys, kart- och geovisualiseringsutveckling samt användarstudier. Resultaten visar att översvämningsgränserna påverkades både av de digitala höjdmodellernas upplösning (cellstorlek) och markens friktion, representerat av Mannings 𝑛, men också av markens topografi. För att kvantifiera skillnaderna mellan modell och referensöversvämningsyta och därefter kunna välja den mest optimala modellen användes olika valideringsmetoder. Dessa lider dock också av olika brister, vilket gör att resultaten varierar beroende på den valideringsmetod som används.

I denna studie föreslås flera sätt att visualisera osäkerheter baserat på resultaten från osäkerhetsmodellering och karaktären av osäkerhetsinformation. Dessa utgörs av kartor med divergerande färgramp (sk. dual-ended colour maps), sekventiella kartor (som framhäver graden av säkerhet, respektive osäkerhet), binära kartor, överlagring av översvämningsgränser från olika modeller samt värdestaplar. Olika karteringsmetoder och visuella variabler användes för att representera informationen. Resultat från en användarstudie visade att dessa, samt utformningen av den grafiska representationen, underlättade förståelsen av informationen. Beroende på uppgiften finns det visualisering som är lättare eller svårare att förstå för kartanvändarna. Varje visualisering hade också för- och nackdelar med att kommunicera översvämningsosäkerhetsinformation. En annan viktig aspekt som kom fram i studien var hur användarnas bakgrund påverkar beslutsfattandet när de använde de olika kartorna. Användarnas vilja att ta risker berodde inte bara på kartan, utan också på deras uppfattning av risken i sig. Sammantaget visade det sig emellertid att osäkerhetskartorna är användbara för planeringsuppgifter.

Place, publisher, year, edition, pages
Gävle: Gävle University Press, 2018. p. 109
Series
Studies in the Research Profile Built Environment. Doctoral thesis ; 10
Keywords
cartography, flood, hydraulic modelling, GIS, map, uncertainty, visualisation, GIS, hydraulisk modellering, karta, kartografi, osäkerhet, visualisering, översvämning
National Category
Computer and Information Sciences Other Earth and Related Environmental Sciences Civil Engineering
Identifiers
urn:nbn:se:hig:diva-27995 (URN)978-91-88145-33-8 (ISBN)978-91-88145-34-5 (ISBN)
Public defence
2018-12-10, Lilla Jadwigasalen (12:108), Kungsbäcksvägen 47, Gävle, 15:00 (English)
Opponent
Supervisors
Available from: 2018-11-13 Created: 2018-10-10 Last updated: 2018-11-13

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Lim, Nancy JoyBrandt, S. AndersSeipel, Stefan

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