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Flood map boundary sensitivity due to combined effects of DEM resolution and roughness in relation to model performance
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS. (Geospatial Information Science)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 Information Science)ORCID iD: 0000-0002-3884-3084
2019 (English)In: Geomatics, Natural Hazards and Risk, ISSN 1947-5705, E-ISSN 1947-5713, Vol. 10, no 1, p. 1613-1647Article in journal (Refereed) Published
Abstract [en]

In comprehending flood model results, we performed sensitivity analyses and evaluated how different combinations of digital elevation model (DEM) resolution and Manning’s roughness affect flood maps produced from a 2D hydraulic model. Moreover, we analysed how the estimation of accuracy can further be influenced by the performance measure and the area’s topography. Various combinations of DEM and Manning’s n produced different results, in terms of quantified performance in relation to actual flood extent and the generated flood boundaries. High-resolution DEMs performed better with higher Manning’s n, while lower n values were better for lower resolution DEMs. Furthermore, although lower resolution DEMs (25 and 50 m) received higher quantified performances, there are more discrepancies in the flood maps and water surface elevations (WSE) produced by them. The current statistical estimators of model performance do not necessarily provide an accurate estimate of which combination of DEM resolution and roughness are more suitable for application to modelling. Different statistical estimates have different assumptions, which can affect the model selection. Therefore, a more holistic approach towards model selection should be adopted that gives equal importance to statistical estimators, as well as the quality of flood inundation extents.

Place, publisher, year, edition, pages
2019. Vol. 10, no 1, p. 1613-1647
Keywords [en]
DEM, flood, GIS, goodness of fit, hydraulic modelling, Manning’s n, sensitivity analysis
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:hig:diva-28426DOI: 10.1080/19475705.2019.1604573ISI: 000472604200001Scopus ID: 2-s2.0-85069489814OAI: oai:DiVA.org:hig-28426DiVA, id: diva2:1261623
Available from: 2018-11-08 Created: 2018-11-08 Last updated: 2019-08-07Bibliographically 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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