Flood is one of the major natural disasters in Australia. It breaks down transportation and communication systems, disrupts businesses and causes damage to properties, loss of stock, crops and also loss of human lives. Better understanding of the impacts resulting from floods and other natural hazards can help to reduce the damages or losses. Flood damage assessment procedures estimate the impact of flood in monetary terms to help decision makers develop new policies, programs and development plans. This study examines different techniques, procedures and underpinning philosophies that have been used in some major emergency management and insurance organizations in the world such as RAM, ANUFLOOD, and HAZUS and NHRC. From this examination the study finds that none of them are suitable for mitigation and emergency purposes in producing economic flood damage estimation at fine resolution with high accuracy. From this perspective the study develops a rigorous procedure for property level economic flood damage assessment. The assessment procedures are embedded within GIS (Geographic Information System) technology which can model and analyse the multidimensional phenomenon of flood and damage characteristics of residential buildings. The damage estimation procedures developed in this study include flood modelling, collection and organisation of building inventory data; adopting a set of stage-damage curves; and measuring damage at property level. The quality of damage estimates derived from the procedures is highly influenced by quality of input data. The study also includes the implementation of the damage assessment procedure on the study area (a segment of Kororoit Creek and its adjacent area). The study uses data from a number of sources including Melbourne Water, NEXIS, VICMAP, a quick survey and literature. The developed procedure will help many practitioners in flood loss assessment and natural hazard risk management to face the challenges they have in establishing damage estimates with high accuracy.

Extreme rainfall events and consequent floods are being observed more frequently in the Western Black Sea region in Turkey as climate changes. In this study, application of a flood early warning system is intended by using and calibrating a combined model system. A regional-scale hydro-meteorological model system, consisting of Weather Research and Forecasting (WRF) model, NOAH land surface model and fully distributed NOAH-Hydro hydrologic models, is used for simulations of 25 heavy-rainfall and major flooding events observed in the Western Black Sea region between years 2000 and 2011. The performance of WRF model system in simulating precipitation is tested with 3-dimensional variational (3DVAR) data assimilation scheme. WRF-derived precipitation with and without data assimilation and Multi Precipitation Estimates (MPE) are used in NOAH-Hydro model to simulate streamflow for flood events. Statistical precipitation analyses show that WRF model with 3DVAR improved precipitation up to 12% with respect to no-assimilation. MPE algorithm generally underestimates rainfall and it also showed lower performance than WRF model with and without data assimilation. Depending on reliability of precipitation inputs, NOAH-Hydro model produces reasonable flood hydrographs both in structure and volume. After model calibration is performed using assimilated precipitation inputs in Bartin Basin, NOAH-Hydro model reduced the average error in streamflow by 23.24% and 53.57% with calibration for testing events. With calibrated parameters, NOAH-Hydro model forced by WRF non-assimilated precipitation input also reduced the error in streamflow but with lower rates (16.67% and 40.72%). With a proper model calibration and reliable precipitation inputs, hydrologic modeling system is capable of simulating flood events.

<p>A 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.</p><p> </p><p>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.</p><p> </p><p>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.</p><p> </p><p>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 <em>n</em> 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.</p><p> </p><p>Despite these shortcomings of one-dimensional models, HEC-RAS provided good inundation extents that were comparable to the actual extent of the 1977 flooding.</p><p> </p><p>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.</p>

Extreme rainfall events and consequent floods are being observed more frequently in the Western Black Sea region in Turkey as climate changes. In this study, application of a flood early warning system is intended by using and calibrating a combined model system. A regional-scale hydro-meteorological model system, consisting of Weather Research and Forecasting (WRF) model, NOAH land surface model and fully distributed NOAH-Hydro hydrologic models, is used for simulations of 25 heavy-rainfall and major flooding events observed in the Western Black Sea region between years 2000 and 2011. The performance of WRF model system in simulating precipitation is tested with 3-dimensional variational (3DVAR) data assimilation scheme. WRF-derived precipitation with and without data assimilation and Multi Precipitation Estimates (MPE) are used in NOAH-Hydro model to simulate streamflow for flood events. Statistical precipitation analyses show that WRF model with 3DVAR improved precipitation up to 12% with respect to no-assimilation. MPE algorithm generally underestimates rainfall and it also showed lower performance than WRF model with and without data assimilation. Depending on reliability of precipitation inputs, NOAH-Hydro model produces reasonable flood hydrographs both in structure and volume. After model calibration is performed using assimilated precipitation inputs in Bartin Basin, NOAH-Hydro model reduced the average error in streamflow by 23.24% and 53.57% with calibration for testing events. With calibrated parameters, NOAH-Hydro model forced by WRF non-assimilated precipitation input also reduced the error in streamflow but with lower rates (16.67% and 40.72%). With a proper model calibration and reliable precipitation inputs, hydrologic modeling system is capable of simulating flood events.

A 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.

Floods are one of the most common types of natural disasters. They annually affect vast amounts of people and cause severe economic losses. While fluvial, coastal, and flash floods are well studied, pluvial floods (rain related) have received modest attention from researchers and decision-makers in comparison. There are several reasons for this, one is that it has been considered a fixed problem with infrastructure and other engineered solutions and another is that they are generally undramatic and small-scale. However, as cities expand, the environment’s ability to retain and dispose of excess water is inhibited and as the frequency of extreme weather events is expected to increase due to climate change, the risk associated with pluvial floods has become increasingly recognized. Commercial and open-source Urban pluvial flood models tend to require advanced modelling expertise, considerable computational power, large amounts of input data and are often expensive. Consequently, there is less knowledge of flood inundation caused by pluvial floods compared to other types. This thesis investigates the Bluespot model, which aims to provide an approachable tool to generate an overview of the effects of pluvial floods in urban areas. The model requires few input data and is relatively simple to perform. Results from the model are compared to the August 2021 flood event in Gävle, Sweden.The study finds that results ranged from accurate to over- and underestimated. Slope and incoming water were found to affect the outcome most. Blue spots without the influence of streams or other waterways, with a distinct slope were mapped with accuracy and showed consistency with coarser resolutions. Consequently, underpasses in the road network were mapped with especially good consistency. Further, blue spots within close distance to large flow accumulation were underestimated and the accuracy tended to decrease with a coarser resolution. The model cannot account for water outside blue spots, thus, when large volumes of water accumulate and spread beyond these boarders it generates poor results. These areas were found to be efficiently indicated by generating a heatmap from high-flow accumulation points. Thus, indicating low confidence and where a hydraulic flood model should be performed. Depending on the scope a 1-3m resolution is recommended for investigating effects on property etc and a 5-10m resolution is sufficient for investigating underpasses, however, a finer resolution will generate more accurate results.

Pluvial flooding originating from extreme rainfall is problematic and an increasing issue in Sweden. Higher requirements on adapting cities in urban areas to these challenges have been placed on both municipalities and the county administration. Thus, an increased need for water modelling, both in existing and planned areas have emerged. The Danish Hydrological Institute (DHI) has developed several models and tools to simulate floods and heavy rains, of which MIKE 21 is one. MIKE 21 is a dynamic model consisting of hydrological calculations in each cell, requiring modelling skills and long simulation time, but is proven to be a good and credible model. SCALGO Live, on the other hand, is a static tool simulated by raster-based algorithms and capable of giving fast results directly on the platform. However, compared to MIKE 21, SCALGO Live is not as evaluated nor is its use as widespread for simulating floods and heavy rain events. This study aims to investigate how inundation in twenty urban areas caused by cloudbursts is simulated in both programs to examine how well the result coming from SCALGO Live, is equivalent to the result from the MIKE 21-model. The comparison is made in both depth and spread using three comparative indexes, two statistical equations and one map, showing the extension of the inundation in both models. To make the models comparable, the model in MIKE 21 is made as equivalent as possible with SCALGO Live before simulation and the purpose is to investigate whether there is any type of area where the two different models are equivalent. The result shows that the flooded areas from SCALGO Live are in good agreement in most areas with the MIKE 21-model, but that the depth in the depression zones is somewhat overestimated, compared with the highest value in MIKE 21. The MIKE 21-model has a greater spread upstream, showing flowpaths if compared directly with the flooded areas from SCALGO Live, but if activating the flow accumulation tool in SCALGO Live, the differences are reduced but cannot be quantified in this study. The differences between the models increase with a higher resolution, longer flowpaths and a larger catchment, at least for the confined catchments. To conclude, SCALGO Live is best suited for smaller confined catchments where there are no long or complex flowpaths. SCALGO Live also works well at an early stage in the planning process and as a platform for combining detailed data and results. However, for the more complex areas, MIKE 21 is better suited, since various parameters can be considered.

Damages caused by urban pluvial floods are believed to increase due to climate change and urbanization as more citizens are impacted in densely populated cities and extreme rainfalls occur more frequently with higher intensities. To prepare cities for these calamities, urban pluvial flood models are created to provide knowledge about how an extreme rainfall event could inundate the studied city. However, due to the scarcity of observation data from these rainfall events, flood models are seldom calibrated which is necessary to ensure their accuracy.  To improve the feasibility of calibrations an emerging data source was tested, crowdsourced images from citizens. Citizens’ observations have become increasingly available due to the increase of mobile phones and the development of social media enabling citizens to document and upload their observations to the public. Researchers could use these observations as an unconventional data source to calibrate models and reduce the knowledge gap regarding urban floods. The aim of this study was to explore and increase our understanding of how citizen’s observations can be used to calibrate an urban pluvial flood model. A case study about the cloudburst event in Malmö was conducted to study this topic. During that event, more than 100 mm of rain fell over a period of 6 hours in the city and caused 60 million euros of damages.  A total of 297 images depicting the flood caused by the cloudburst event were gathered from social media platforms, newspapers archives, and by inquiring citizens. Images were screened and analysed: water levels were estimated in 66 images and were then used to calibrate a 2D flood model. Furthermore, a sensitivity analysis of the calibrated results was conducted by calculating the RMSE for different subsets and compare it with the RMSE for the full dataset of citizens’ observations. This was done to study how different characteristics, such as timestamp and source as well as sample size and location of the images influences the calibration procedure. After the model was calibrated, the importance of spatial variability in the rainfall input was tested by comparing the flood model output between the spatially varied observed rainfall and a Chicago Design Storm rainfall, which lacks spatial variability.  It was concluded that images from citizens can be used to calibrate an urban pluvial flood model, but the procedure is time-consuming. However, it was also evident that images directly inquired from citizens reduced the time needed as their local knowledge could be integrated. The calibration procedure was also sensitive to the quality of the observations, especially when the images were photographed in relation to the rainfall event. Even though the study had limitations it demonstrates new possibilities to calibrate urban pluvial flood models. / Konsekvenserna av översvämningar från skyfall i städer, så kallade pluviala översvämningar, förväntas öka på grund av urbanisering och klimatförändringar. Det är för att fler påverkas av översvämningar i tätbyggda städer samt att skyfall förväntas öka, både i intensitet och frekvens. Med hjälp av skyfallsmodeller kan dock förståelsen för hur extrema regn översvämmar städer öka. Med denna kunskap kan åtgärder för att minimera konsekvenserna implementeras, såsom blågrön infrastruktur. Däremot finns det en brist av observationsdata från pluviala översvämningar och vilket medför att dessa modeller ytterst sällan kalibreras. Kalibrering är viktig för att säkerställa tillförlitliga modeller.  För att öka möjligheten att kalibrera dessa modeller undersöktes hur observationer från medborgare kan implementeras. Dessa observationer är en relativ oprövad metod men har blivit alltmer tillgängliga tack vare allt bättre mobiltelefonkameror och utvecklingen av sociala medier, vilket gör det enkelt för medborgare att dokumentera och ladda upp sina observationer till allmänheten. Syftet med denna studie är därför att öka förståelsen för hur bilder från medborgare kan användas för att möjliggöra kalibreringen av översvämningsmodeller. En fallstudie över ett skyfall i Malmö 2014 används för att utvärdera denna metod. Under detta skyfall regnade det mer än 100 mm vilket orsakade skador för cirka 600 miljoner kronor.  Totalt samlades 297 bilder som föreställde översvämningen som orsakades av skyfallet. Bilderna samlades ifrån sociala media, tidningsbildarkiv och genom att fråga medborgare efter bilder. Vattennivåerna uppskattades i 66 bilder och de användes sedan för att kalibrera en 2D- skyfallsmodell. Utöver kalibreringen genomfördes en känslighetsanalys av de kalibrerade resultaten genom att jämföra medelfelet för olika subgrupper av bilderna mot medelfelet för alla bilder. Detta gjordes för att studera hur olika egenskaper, såsom när bilden togs och deras ursprung samt bildernas urvalsstorlek och placering påverkar kalibreringsprocessen. Efter att modellen kalibrerats testades också betydelsen av spatial variation i nederbörden genom att jämföra de simulerade vattennivåerna mellan den spatialt varierade historiska regnet och ett syntetiskt CDS-regn som saknar variation.  Utifrån det drogs slutsatsen att bilder från medborgare kan användas för att kalibrera en skyfallsmodell, men metoden är tidskrävande. Dock var det tydligt att bilder som direkt efterfrågades från medborgarna minskade arbetsbördan då deras lokalkännedom kunde inkluderas. Kalibreringen var också känslig för observationerna datakvalitet, särskilt när bilderna fotograferades i förhållande till regnet. Även om studien hade begränsningar visar den att det finns stora möjligheter att kalibrera skyfallsmodeller med observationer från medborgare.