133 research outputs found
Modelling, mapping and visualisation of flood inundation uncertainties
No full textFlood 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.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 , 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
Topographic data and roughness parameterisation effects on 1D flood inundation models
No full textA big responsibility lies in the hand of local authorities to exercise measures in preventing fatalities and damages during flood occurrences. However, the problem is how flooding can be prevented if nobody knows when and where it will be occurring, and how much water is expected. Therefore, the utilisation of flood models in such studies can be helpful in simulating what is anticipated to occur. In this study, the HEC-RAS steady flow model was used in calibrating different flood events in Testeboån river, which is situated in the municipality of Gävle in Sweden. The purpose is to provide inundation maps that show the water surface profiles for the various flood events that can help authorities in planning within the area. Moreover, the study would try to address certain issues, which concern one-dimensional models like HEC-RAS in terms of the effects of topographic data and the parameters used for friction coefficient. Various flood maps were produced to visualise the extents of the floods. In Oppala and Norra Åbyggeby, the big water extents for both the 100-year and the highest probable floods were visible in the forested areas and grasslands, although a few houses were within the predicted flooded areas. In Södra Åbyggeby, Varva, Forsby, and in the northern parts of Strömsbro and Stigslund, the majority of the residential places were not inundated during the 100-year flood calibration, but became flooded during the maximum probable flood. The southern portions of Strömsbro and Stigslund had lesser flood extents and houses were situated within the boundaries of the highest flood. In Näringen, there were also some areas close to the estuary that were flooded for both events. With the other calibrations performed, two factors that greatly affect the flood extents in the floodplain, particularly in flatter areas were topographic data and the parameters used as friction coefficient. The use of high resolution topographic data was important in improving the performance of the software. Nevertheless, it must be emphasised that in areas characterised by gentler slopes that bounded the channel and the floodplain, data completeness became significant whereby both ground data and bathymetric points must be present to avoid overestimation of the inundation extent. The water extents also varied with the use of the various Manning’s n for the overbanks, with the bigger value showing greater water extents. Else, in areas with steeper slopes and where the water was confined to the banks, the effect was minimal. Despite these shortcomings of one-dimensional models, HEC-RAS provided good inundation extents that were comparable to the actual extent of the 1977 flooding. Modelling real floods has its own difficulties due to the unpredictability of real-life flood behaviours, and more especially, there are time dependent factors that are involved. Although calibrating a flood event will not exactly determine what is to arise as they might either under- or overestimate such flooding occurrences, still, they give a standpoint of what is more or less to anticipate, and from this, planning measures can be undertaken
Effects of the absence/presence of river bathymetric data in DEMs used for hydraulic modelling and flood prediction
No full textPerformance and uncertainty estimation of 1- and 2-dimensional flood models
No full textPerformance-based measures are used to validate and quantify how likely the system’s results resemble that of the actual data. Its application in inundation studies is performed by comparing the extents of the predicted flood to the real event by measuring their overlap size and getting the percentage of this size to the union of both data. In this study, performances of 1- and 2-dimensional flow models were assessed when used with different topographic data sources, rasterisation cell sizes, mesh resolution and Manning’s values with the help of Geographic Information Systems (GIS). The Generalised Likelihood Uncertainty Estimation (GLUE) was also implemented to evaluate the behaviour and the uncertainties of the Hydrologic Engineering Center-River Analysis System (HEC-RAS) steady-flow model in delineating the inundation extents when various sets of friction coefficients for floodplain and channel were utilised as inputs. Although it was not possible to perform the GLUE procedure with Telemac-2D due to the simulation time, Manning’s n performances’ effects were evaluated using ten randomly selected sets of friction for the channel and floodplain. The LiDAR data, which had the highest resolution, performed well in all simulations, followed by Lantmäteriet data at 50 m resolution. The lowest resolution Digital Terrain Elevation Data (DTED) showed poor resemblance to the actual event and big misrepresentations of flooded areas. Rasterisation cell sizes in HEC-RAS showed minimal effect to the inundation limits when used between 1 m and 5 m, but performance started to deteriorate at 10 m (Lantmäteriet) and 20 m (LiDAR). The 10 m mesh resolution used for LiDAR behaved poorer than the 20 m mesh, which performed well in the different 2D simulations. For HEC-RAS, =0.033 to 0.05 performed well when paired with =0.02 to 0.10. It was apparent, therefore, that the channel’s Manning’s n affected the performances of the floodplain’s . Furthermore, the study also showed that using heterogeneous roughness values corresponding to the different land use classes is not as effective as using single channel and floodplain’s Manning. The dependence of the floodplain’s roughness to the channel’s friction values had also been manifested by Telemac, even though it required lower values than the 1D simulator. = 0.007 to 0.019 and =0.01 to 0.04 gave good performance to the 2D system. In terms of the overall model performance, HEC-RAS 1D exhibited good results for Testeboån. Even when the average distances to the actual data were estimated, the breadths were shorter compared to the most optimal output of the two-dimensional simulator, which showed more overestimated areas, despite the fact that the overlap size with the 1977 actual event was better than HEC-RAS. It could be because the measures-of-fit took into consideration the areal sizes that were over- and under-predicted aside from the overlap sizes between the observed and modelled results. This could be the same reason with the mean distances produced, wherein higher values were computed for Telemac-2D due to its bigger gap from the actual flood as brought by the enlargement in the flood extents. But it was also made known in the study that such ambiguities in the model performance were further contributed by the characteristics of the floodplain’s topography of being flat. Testeboån’s inclination to the banks was averaged at 0.027 m/m, with the central portion at 0.002 m/m. The middle portion of the floodplain was illustrated to contain more uncertain regions, where water extents changed easily as the parameters were altered. Distances greater than 200 m were also mostly located within these inclination values or within 0.005 to 0.006 m/m. The response of distance to the floodplain’s gradient improved when the slope value became higher, and this had been particularly noticed between 0 to 50 m
Quantification, classification and mapping of spatial uncertainties of floods
No full textIn flood modelling studies, spatial uncertainties may be visualised differently. This will rely on the characteristics of the information produced from the quantification method applied, which may vary depending on the type of model uncertainty taken into account. It is important to be able to characterise and generally classify the different types of spatial uncertainty information in hydraulic model results, because this can help determine how they can be best represented and visualised.In this paper, two methods of quantifying uncertainties were employed to derive uncertainty information. The first was ensemble-based modelling, which combined the results of 100 simulations considering the effects of the Digital Elevation Model (DEM) and Manning’s roughness coefficient to the model output. Each result from the individual model run was assessed on how likely it depicted the spatial extent of an observed flood event. Afterwards, the results were weighted and aggregated. In the second method, the most optimal output based on a series of calibrations from one-dimensional flood modelling was used and applied with the empirical disparity-distance equation to account for further errors brought about by the resolution of the underlying DEM and the slope. The equation was implemented with an algorithm that created uncertainty zones based on the 95% prediction confidence. The resulting information from the two quantification methods were then classified, discretised and visualised using different map types, visual variables, and overlay techniques.Based on these results, four types of uncertainty information for flood modelling were produced that can be classified according to the characteristics of the data they show: (1) diverging, which is distinguished by two opposing conditions (certain to be dry and flooded) and a middle condition (highly uncertain); (2) sequential, where values range from lowest (uncertain) to highest (certain); (3) multiple calibration results, which show simultaneously the flood extents produced using different parameters for comparative purposes; and, (4) inundation zones which identify areas that are both certain and uncertain to be flooded.The results from both diverging and sequential uncertainty information were presented as continuous and discrete data in choropleth and graduated symbol maps. The gradation from uncertain-to-certain conditions was displayed using lightest-to-darkest colour and/or smallest-to-largest point symbols. With certainty/uncertainty zone, the binary statuses were represented in choropleth maps as: (a) blue/red colours; (b) organised/disorganised arrangements; and, (c) fine/coarse grain textures. For multiple calibration results, isopleths maps were used with a combination of at least two visual variables (size, shape, colour) to emphasise the differences in the lines, and facilitate visual comparison of results.Furthermore, since giving geographic context to flood uncertainty is an important aspect in the visualisation, three types of overlay were considered: map pairs, sequential and bivariate representations. Sequential representation worked well for all map types. Bivariate maps, on the other hand, were best for uncertainty represented as [one-coloured] symbol, texture, arrangement and linear features, which do not obscure the information behind. The background map had also to be displayed with increased transparency to prevent its dominance over the uncertainty data. Map pairs were the most suitable for choropleth maps using fill colour in order to avoid problems caused by colour blending when two maps are overlain. Classification of the uncertainty information facilitated the choice of data representation. Even when using other quantification methods, hydraulic modellers can adopt the suggested visualisation using similar characteristic data. This can be an initial step in producing guidelines for flood uncertainty visualisation. Moreover, testing the effectiveness of these visualisations can be the next relevant step to see how the information is communicated, interpreted and used, e.g. in spatial planning, flood risk management and insurance policies.</p
Cookbooks for Beginners - More than The Joy of Cooking
No full textTeens Cook and Teens Cook Dessert by Megan and Jill Carle (ISBN 1580085849 and ISBN 1580087523)My Turn to Cook by Miranda Shearer (ISBN 0304363235)Help! My Apartment Has a Kitchen Cookbook by Kevin and Nancy Mills (ISBN 0618711759)How to Boil Water from the Food Network Kitchens (ISBN 0696226863)Cooking Up a Storm: The Teen Survival Cookbook by Sam Stern (ISBN 076362988X)Cooking Outside the Pizza Box by Jean Patterson and Danae Campbell (ISBN 0764124951)Clueless in the Kitchen by Evelyn Raab (ISBN 1552092240)The Teen’s Vegetarian Cookbook by Judy Krizmanic (ISBN 0670874264
Color map design for visualization in flood risk assessment
No full textVisualizations of flood maps from simulation models are widely used for assessing the likelihood of flood hazards in spatial planning. The choice of a suitable type of visualization as well as efficient color maps is critical to avoid errors or bias when interpreting the data. Based on a review of previous flood uncertainty visualization techniques, this paper identifies areas of improvements and suggests criteria for the design of a task-specific color scale in flood map visualization. We contribute a novel color map design for visualizing probabilities and uncertainties from flood simulation ensembles. A user study encompassing 83 participants was carried out to evaluate the effects of this new color map on user’s decisions in a spatial planning task. We found that the type of visualization makes a difference when it comes to identification of non-hazardous sites in the flood risk map and when accepting risks in more uncertain areas. In comparison with two other existing visualization techniques, we observed that the new design was superior both in terms of task compliance and efficiency. In regions with uncertain flood statuses, users were biased toward accepting less risky locations with our new color map design
Hunger & Thirst: Food Literature
No full textSonya Huber is a contributing author, The God of Hunger.
Book description: More than eighty contributors offer up unique views of food and drink, what we hunger for, what pains us or sustains us, what brings us joy as individuals, as family, as culture. This collection of poetry, fiction, non-fiction, and art invites you to sit at the collective table we share as the human community.https://digitalcommons.fairfield.edu/english-books/1026/thumbnail.jp
Assessment of how uncertainty representation in flood maps can affect geographic-based decisions
No full textFlood maps that show predicted flood extents will always be uncertain regardless of how the modelling is conducted. It is therefore important that these uncertainties are represented and communicated in the maps, and that map users understand the presented information. Through an online user survey, this study evaluates how users make geographic decisions based on nine flood uncertainty maps, represented and designed according to data scheme and semantics associated with their values (dual-ended, sequential and binary), and applied with different mapping techniques (continuous surface, choropleth and graduated symbol mapping). The results show that the type of map and the visual variable used for representation (in terms of colours and values) became important when deciding locations. Higher decision confidence was shown when dual-ended and sequential probability maps were used. Medium-to-dark blue regions in these maps made participants avoid locations, while white, brown and the lightest blue colours made them select locations. The usage of a sequential map represented by grey scale colour showed to be less intuitive for the participants, leading to lower task performance and less confidence in decisions. Despite the different backgrounds of participants, comprehension of the uncertainty maps and the tasks did not vary much from each other. Differences among them were observed in location preferences and time to solve the tasks. The user group that had the most professional experience with maps and GIS was most conservative in their site choices, and took longest time to solve the tasks. Students, on the other hand, opted to take more risk in their decisions and preferred more uncertain locations. Apparently, the effectiveness of the flood uncertainty maps used in this study varied mainly on the representations used. Appropriate design made them comprehendible by different users. However, making decisions based on these maps, as well as confidence in decisions and time to solve the task, may also be dependent on other factors such as domain knowledge, line of work, practical experience in handing problems or making decisions, and possibly culture
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