WorldWideScience

Sample records for global flood model

  1. The Global Flood Model

    Williams, P.; Huddelston, M.; Michel, G.; Thompson, S.; Heynert, K.; Pickering, C.; Abbott Donnelly, I.; Fewtrell, T.; Galy, H.; Sperna Weiland, F.; Winsemius, H.; Weerts, A.; Nixon, S.; Davies, P.; Schiferli, D.

    2012-04-01

    Recently, a Global Flood Model (GFM) initiative has been proposed by Willis, UK Met Office, Esri, Deltares and IBM. The idea is to create a global community platform that enables better understanding of the complexities of flood risk assessment to better support the decisions, education and communication needed to mitigate flood risk. The GFM will provide tools for assessing the risk of floods, for devising mitigation strategies such as land-use changes and infrastructure improvements, and for enabling effective pre- and post-flood event response. The GFM combines humanitarian and commercial motives. It will benefit: - The public, seeking to preserve personal safety and property; - State and local governments, seeking to safeguard economic activity, and improve resilience; - NGOs, similarly seeking to respond proactively to flood events; - The insurance sector, seeking to understand and price flood risk; - Large corporations, seeking to protect global operations and supply chains. The GFM is an integrated and transparent set of modules, each composed of models and data. For each module, there are two core elements: a live "reference version" (a worked example) and a framework of specifications, which will allow development of alternative versions. In the future, users will be able to work with the reference version or substitute their own models and data. If these meet the specification for the relevant module, they will interoperate with the rest of the GFM. Some "crowd-sourced" modules could even be accredited and published to the wider GFM community. Our intent is to build on existing public, private and academic work, improve local adoption, and stimulate the development of multiple - but compatible - alternatives, so strengthening mankind's ability to manage flood impacts. The GFM is being developed and managed by a non-profit organization created for the purpose. The business model will be inspired from open source software (eg Linux): - for non-profit usage

  2. Validation of a Global Hydrodynamic Flood Inundation Model

    Bates, P. D.; Smith, A.; Sampson, C. C.; Alfieri, L.; Neal, J. C.

    2014-12-01

    In this work we present first validation results for a hyper-resolution global flood inundation model. We use a true hydrodynamic model (LISFLOOD-FP) to simulate flood inundation at 1km resolution globally and then use downscaling algorithms to determine flood extent and depth at 90m spatial resolution. Terrain data are taken from a custom version of the SRTM data set that has been processed specifically for hydrodynamic modelling. Return periods of flood flows along the entire global river network are determined using: (1) empirical relationships between catchment characteristics and index flood magnitude in different hydroclimatic zones derived from global runoff data; and (2) an index flood growth curve, also empirically derived. Bankful return period flow is then used to set channel width and depth, and flood defence impacts are modelled using empirical relationships between GDP, urbanization and defence standard of protection. The results of these simulations are global flood hazard maps for a number of different return period events from 1 in 5 to 1 in 1000 years. We compare these predictions to flood hazard maps developed by national government agencies in the UK and Germany using similar methods but employing detailed local data, and to observed flood extent at a number of sites including St. Louis, USA and Bangkok in Thailand. Results show that global flood hazard models can have considerable skill given careful treatment to overcome errors in the publicly available data that are used as their input.

  3. Usefulness and limitations of global flood risk models

    Ward, Philip; Jongman, Brenden; Salamon, Peter; Simpson, Alanna; Bates, Paul; De Groeve, Tom; Muis, Sanne; Coughlan de Perez, Erin; Rudari, Roberto; Mark, Trigg; Winsemius, Hessel

    2016-04-01

    Global flood risk models are now a reality. Initially, their development was driven by a demand from users for first-order global assessments to identify risk hotspots. Relentless upward trends in flood damage over the last decade have enhanced interest in such assessments. The adoption of the Sendai Framework for Disaster Risk Reduction and the Warsaw International Mechanism for Loss and Damage Associated with Climate Change Impacts have made these efforts even more essential. As a result, global flood risk models are being used more and more in practice, by an increasingly large number of practitioners and decision-makers. However, they clearly have their limits compared to local models. To address these issues, a team of scientists and practitioners recently came together at the Global Flood Partnership meeting to critically assess the question 'What can('t) we do with global flood risk models?'. The results of this dialogue (Ward et al., 2013) will be presented, opening a discussion on similar broader initiatives at the science-policy interface in other natural hazards. In this contribution, examples are provided of successful applications of global flood risk models in practice (for example together with the World Bank, Red Cross, and UNISDR), and limitations and gaps between user 'wish-lists' and model capabilities are discussed. Finally, a research agenda is presented for addressing these limitations and reducing the gaps. Ward et al., 2015. Nature Climate Change, doi:10.1038/nclimate2742

  4. A high-resolution global flood hazard model

    Sampson, Christopher C.; Smith, Andrew M.; Bates, Paul B.; Neal, Jeffrey C.; Alfieri, Lorenzo; Freer, Jim E.

    2015-09-01

    Floods are a natural hazard that affect communities worldwide, but to date the vast majority of flood hazard research and mapping has been undertaken by wealthy developed nations. As populations and economies have grown across the developing world, so too has demand from governments, businesses, and NGOs for modeled flood hazard data in these data-scarce regions. We identify six key challenges faced when developing a flood hazard model that can be applied globally and present a framework methodology that leverages recent cross-disciplinary advances to tackle each challenge. The model produces return period flood hazard maps at ˜90 m resolution for the whole terrestrial land surface between 56°S and 60°N, and results are validated against high-resolution government flood hazard data sets from the UK and Canada. The global model is shown to capture between two thirds and three quarters of the area determined to be at risk in the benchmark data without generating excessive false positive predictions. When aggregated to ˜1 km, mean absolute error in flooded fraction falls to ˜5%. The full complexity global model contains an automatically parameterized subgrid channel network, and comparison to both a simplified 2-D only variant and an independently developed pan-European model shows the explicit inclusion of channels to be a critical contributor to improved model performance. While careful processing of existing global terrain data sets enables reasonable model performance in urban areas, adoption of forthcoming next-generation global terrain data sets will offer the best prospect for a step-change improvement in model performance.

  5. Validation of individual and aggregate global flood hazard models for two major floods in Africa.

    Trigg, M.; Bernhofen, M.; Whyman, C.

    2017-12-01

    A recent intercomparison of global flood hazard models undertaken by the Global Flood Partnership shows that there is an urgent requirement to undertake more validation of the models against flood observations. As part of the intercomparison, the aggregated model dataset resulting from the project was provided as open access data. We compare the individual and aggregated flood extent output from the six global models and test these against two major floods in the African Continent within the last decade, namely severe flooding on the Niger River in Nigeria in 2012, and on the Zambezi River in Mozambique in 2007. We test if aggregating different number and combination of models increases model fit to the observations compared with the individual model outputs. We present results that illustrate some of the challenges of comparing imperfect models with imperfect observations and also that of defining the probability of a real event in order to test standard model output probabilities. Finally, we propose a collective set of open access validation flood events, with associated observational data and descriptions that provide a standard set of tests across different climates and hydraulic conditions.

  6. Assessing flood risk at the global scale: model setup, results, and sensitivity

    Ward, Philip J; Jongman, Brenden; Weiland, Frederiek Sperna; Winsemius, Hessel C; Bouwman, Arno; Ligtvoet, Willem; Van Beek, Rens; Bierkens, Marc F P

    2013-01-01

    Globally, economic losses from flooding exceeded $19 billion in 2012, and are rising rapidly. Hence, there is an increasing need for global-scale flood risk assessments, also within the context of integrated global assessments. We have developed and validated a model cascade for producing global flood risk maps, based on numerous flood return-periods. Validation results indicate that the model simulates interannual fluctuations in flood impacts well. The cascade involves: hydrological and hydraulic modelling; extreme value statistics; inundation modelling; flood impact modelling; and estimating annual expected impacts. The initial results estimate global impacts for several indicators, for example annual expected exposed population (169 million); and annual expected exposed GDP ($1383 billion). These results are relatively insensitive to the extreme value distribution employed to estimate low frequency flood volumes. However, they are extremely sensitive to the assumed flood protection standard; developing a database of such standards should be a research priority. Also, results are sensitive to the use of two different climate forcing datasets. The impact model can easily accommodate new, user-defined, impact indicators. We envisage several applications, for example: identifying risk hotspots; calculating macro-scale risk for the insurance industry and large companies; and assessing potential benefits (and costs) of adaptation measures. (letter)

  7. Assessing uncertainty in SRTM elevations for global flood modelling

    Hawker, L. P.; Rougier, J.; Neal, J. C.; Bates, P. D.

    2017-12-01

    The SRTM DEM is widely used as the topography input to flood models in data-sparse locations. Understanding spatial error in the SRTM product is crucial in constraining uncertainty about elevations and assessing the impact of these upon flood prediction. Assessment of SRTM error was carried out by Rodriguez et al (2006), but this did not explicitly quantify the spatial structure of vertical errors in the DEM, and nor did it distinguish between errors over different types of landscape. As a result, there is a lack of information about spatial structure of vertical errors of the SRTM in the landscape that matters most to flood models - the floodplain. Therefore, this study attempts this task by comparing SRTM, an error corrected SRTM product (The MERIT DEM of Yamazaki et al., 2017) and near truth LIDAR elevations for 3 deltaic floodplains (Mississippi, Po, Wax Lake) and a large lowland region (the Fens, UK). Using the error covariance function, calculated by comparing SRTM elevations to the near truth LIDAR, perturbations of the 90m SRTM DEM were generated, producing a catalogue of plausible DEMs. This allows modellers to simulate a suite of plausible DEMs at any aggregated block size above native SRTM resolution. Finally, the generated DEM's were input into a hydrodynamic model of the Mekong Delta, built using the LISFLOOD-FP hydrodynamic model, to assess how DEM error affects the hydrodynamics and inundation extent across the domain. The end product of this is an inundation map with the probability of each pixel being flooded based on the catalogue of DEMs. In a world of increasing computer power, but a lack of detailed datasets, this powerful approach can be used throughout natural hazard modelling to understand how errors in the SRTM DEM can impact the hazard assessment.

  8. What can'(t) we do with global flood risk models?

    Ward, P.; Jongman, B.; Salamon, P.; Simpson, A.; Bates, P. D.; de Groeve, T.; Muis, S.; Coughlan, E.; Rudari, R.; Trigg, M. A.; Winsemius, H.

    2015-12-01

    Global flood risk models are now a reality. Initially, their development was driven by a demand from users for first-order global assessments to identify risk hotspots. Relentless upward trends in flood damage over the last decade have enhanced interest in such assessments. The adoption of the Sendai Framework for Disaster Risk Reduction and the Warsaw International Mechanism for Loss and Damage Associated with Climate Change Impacts have made these efforts even more essential. As a result, global flood risk models are being used more and more in practice, by an increasingly large number of practitioners and decision-makers. However, they clearly have their limits compared to local models. To address these issues, a team of scientists and practitioners recently came together at the Global Flood Partnership meeting to critically assess the question 'What can('t) we do with global flood risk models?'. The results of this dialogue (Ward et al., 2013) will be presented, opening a discussion on similar broader initiatives at the science-policy interface in other natural hazards. In this contribution, examples are provided of successful applications of global flood risk models in practice (for example together with the World Bank, Red Cross, and UNISDR), and limitations and gaps between user 'wish-lists' and model capabilities are discussed. Finally, a research agenda is presented for addressing these limitations and reducing the gaps. Ward, P.J. et al., 2015. Nature Climate Change, doi:10.1038/nclimate2742.

  9. Multi-Model Projections of River Flood Risk in Europe under Global Warming

    Lorenzo Alfieri

    2018-01-01

    Full Text Available Knowledge on the costs of natural disasters under climate change is key information for planning adaptation and mitigation strategies of future climate policies. Impact models for large scale flood risk assessment have made leaps forward in the past few years, thanks to the increased availability of high resolution climate projections and of information on local exposure and vulnerability to river floods. Yet, state-of-the-art flood impact models rely on a number of input data and techniques that can substantially influence their results. This work compares estimates of river flood risk in Europe from three recent case studies, assuming global warming scenarios of 1.5, 2, and 3 degrees Celsius from pre-industrial levels. The assessment is based on comparing ensemble projections of expected damage and population affected at country level. Differences and common points between the three cases are shown, to point out main sources of uncertainty, strengths, and limitations. In addition, the multi-model comparison helps identify regions with the largest agreement on specific changes in flood risk. Results show that global warming is linked to substantial increase in flood risk over most countries in Central and Western Europe at all warming levels. In Eastern Europe, the average change in flood risk is smaller and the multi-model agreement is poorer.

  10. Global river flood hazard maps: hydraulic modelling methods and appropriate uses

    Townend, Samuel; Smith, Helen; Molloy, James

    2014-05-01

    Flood hazard is not well understood or documented in many parts of the world. Consequently, the (re-)insurance sector now needs to better understand where the potential for considerable river flooding aligns with significant exposure. For example, international manufacturing companies are often attracted to countries with emerging economies, meaning that events such as the 2011 Thailand floods have resulted in many multinational businesses with assets in these regions incurring large, unexpected losses. This contribution addresses and critically evaluates the hydraulic methods employed to develop a consistent global scale set of river flood hazard maps, used to fill the knowledge gap outlined above. The basis of the modelling approach is an innovative, bespoke 1D/2D hydraulic model (RFlow) which has been used to model a global river network of over 5.3 million kilometres. Estimated flood peaks at each of these model nodes are determined using an empirically based rainfall-runoff approach linking design rainfall to design river flood magnitudes. The hydraulic model is used to determine extents and depths of floodplain inundation following river bank overflow. From this, deterministic flood hazard maps are calculated for several design return periods between 20-years and 1,500-years. Firstly, we will discuss the rationale behind the appropriate hydraulic modelling methods and inputs chosen to produce a consistent global scaled river flood hazard map. This will highlight how a model designed to work with global datasets can be more favourable for hydraulic modelling at the global scale and why using innovative techniques customised for broad scale use are preferable to modifying existing hydraulic models. Similarly, the advantages and disadvantages of both 1D and 2D modelling will be explored and balanced against the time, computer and human resources available, particularly when using a Digital Surface Model at 30m resolution. Finally, we will suggest some

  11. Flood Inundation Modelling Under Uncertainty Using Globally and Freely Available Remote Sensing Data

    Yan, K.; Di Baldassarre, G.; Giustarini, L.; Solomatine, D. P.

    2012-04-01

    The extreme consequences of recent catastrophic events have highlighted that flood risk prevention still needs to be improved to reduce human losses and economic damages, which have considerably increased worldwide in recent years. Flood risk management and long term floodplain planning are vital for living with floods, which is the currently proposed approach to cope with floods. To support the decision making processes, a significant issue is the availability of data to build appropriate and reliable models, from which the needed information could be obtained. The desirable data for model building, calibration and validation are often not sufficient or available. A unique opportunity is offered nowadays by globally available data which can be freely downloaded from internet. This might open new opportunities for filling the gap between available and needed data, in order to build reliable models and potentially lead to the development of global inundation models to produce floodplain maps for the entire globe. However, there remains the question of what is the real potential of those global remote sensing data, characterized by different accuracy, for global inundation monitoring and how to integrate them with inundation models. This research aims at contributing to understand whether the current globally and freely available remote sensing data (e.g. SRTM, SAR) can be actually used to appropriately support inundation modelling. In this study, the SRTM DEM is used for hydraulic model building, while ENVISAT-ASAR satellite imagery is used for model validation. To test the usefulness of these globally and freely available data, a model based on the high resolution LiDAR DEM and ground data (high water marks) is used as benchmark. The work is carried out on a data-rich test site: the River Alzette in the north of Luxembourg City. Uncertainties are estimated for both SRTM and LiDAR based models. Probabilistic flood inundation maps are produced under the framework of

  12. From global circulation to flood loss: Coupling models across the scales

    Felder, Guido; Gomez-Navarro, Juan Jose; Bozhinova, Denica; Zischg, Andreas; Raible, Christoph C.; Ole, Roessler; Martius, Olivia; Weingartner, Rolf

    2017-04-01

    The prediction and the prevention of flood losses requires an extensive understanding of underlying meteorological, hydrological, hydraulic and damage processes. Coupled models help to improve the understanding of such underlying processes and therefore contribute the understanding of flood risk. Using such a modelling approach to determine potentially flood-affected areas and damages requires a complex coupling between several models operating at different spatial and temporal scales. Although the isolated parts of the single modelling components are well established and commonly used in the literature, a full coupling including a mesoscale meteorological model driven by a global circulation one, a hydrologic model, a hydrodynamic model and a flood impact and loss model has not been reported so far. In the present study, we tackle the application of such a coupled model chain in terms of computational resources, scale effects, and model performance. From a technical point of view, results show the general applicability of such a coupled model, as well as good model performance. From a practical point of view, such an approach enables the prediction of flood-induced damages, although some future challenges have been identified.

  13. Global off-line evaluation of the ISBA-TRIP flood model

    Decharme, B.; Alkama, R.; Faroux, S.; Douville, H. [GAME-CNRM/CNRS - Meteo-France, Toulouse (France); Papa, F. [NOAA-CREST, City College of New York, New York, NY (United States); Institut de Recherche pour le Developpement IRD-LEGOS, Toulouse (France); Prigent, C. [CNRS/Laboratoire d' Etudes du Rayonnement et de la Matiere en Astrophysique, Observatoire de Paris, Paris (France)

    2012-04-15

    This study presents an off-line global evaluation of the ISBA-TRIP hydrological model including a two-way flood scheme. The flood dynamics is indeed described through the daily coupling between the ISBA land surface model and the TRIP river routing model including a prognostic flood reservoir. This reservoir fills when the river height exceeds the critical river bankfull height and vice versa. The flood interacts with the soil hydrology through infiltration and with the overlying atmosphere through precipitation interception and free water surface evaporation. The model is evaluated over a relatively long period (1986-2006) at 1 resolution using the Princeton University 3-hourly atmospheric forcing. Four simulations are performed in order to assess the model sensitivity to the river bankfull height. The evaluation is made against satellite-derived global inundation estimates as well as in situ river discharge observations at 122 gauging stations. First, the results show a reasonable simulation of the global distribution of simulated floodplains when compared to satellite-derived estimates. At basin scale, the comparison reveals some discrepancies, both in terms of climatology and interannual variability, but the results remain acceptable for a simple large-scale model. In addition, the simulated river discharges are improved in term of efficiency scores for more than 50% of the 122 stations and deteriorated for 4% only. Two mechanisms mainly explain this positive impact: an increase in evapotranspiration that limits the annual discharge overestimation found when flooding is not taking into account and a smoothed river peak flow when the floodplain storage is significant. Finally, the sensitivity experiments suggest that the river bankfull depth is potentially tunable according to the river discharge scores to control the accuracy of the simulated flooded areas and its related increase in land surface evaporation. Such a tuning could be relevant at least for climate

  14. Characteristics and Future Changes of Great Mississippi Flood Events in a Global Coupled Climate Model

    van der Wiel, K.; Kapnick, S. B.; Vecchi, G.; Smith, J. A.

    2017-12-01

    The Mississippi-Missouri river catchment houses millions of people and much of the U.S. national agricultural production. Severe flooding events can therefore have large negative societal, natural and economic impacts. GFDL FLOR, a global coupled climate model (atmosphere, ocean, land, sea ice with integrated river routing module) is used to investigate the characteristics of great Mississippi floods with an average return period of 100 years. Model experiments under pre-industrial greenhouse gas forcing were conducted for 3400 years, such that the most extreme flooding events were explicitly modeled and the land and/or atmospheric causes could be investigated. It is shown that melt of snow pack and frozen sub-surface water in the Missouri and Upper Mississippi basins prime the river system, subsequently sensitizing it to above average precipitation in the Ohio and Tennessee basins. The months preceding the greatest flooding events are above average wet, leading to moist sub-surface conditions. Anomalous melt depends on the availability of frozen water in the catchment, therefore anomalous amounts of sub-surface frozen water and anomalous large snow pack in winter (Nov-Feb) make the river system susceptible for these great flooding events in spring (Feb-Apr). An additional experiment of 1200 years under transient greenhouse gas forcing (RCP4.5, 5 members) was done to investigate potential future change in flood risk. Based on a peak-over-threshold method, it is found that the number of great flooding events decreases in a warmer future. This decrease coincides with decreasing occurrence of large melt events, but is despite increasing numbers of large precipitation events. Though the model results indicate a decreasing risk for the greatest flooding events, the predictability of events might decrease in a warmer future given the changing characters of melt and precipitation.

  15. Compound simulation of fluvial floods and storm surges in a global coupled river-coast flood model: Model development and its application to 2007 Cyclone Sidr in Bangladesh

    Ikeuchi, Hiroaki; Hirabayashi, Yukiko; Yamazaki, Dai; Muis, Sanne; Ward, Philip J.; Winsemius, Hessel C.; Verlaan, Martin; Kanae, Shinjiro

    2017-08-01

    Water-related disasters, such as fluvial floods and cyclonic storm surges, are a major concern in the world's mega-delta regions. Furthermore, the simultaneous occurrence of extreme discharges from rivers and storm surges could exacerbate flood risk, compared to when they occur separately. Hence, it is of great importance to assess the compound risks of fluvial and coastal floods at a large scale, including mega-deltas. However, most studies on compound fluvial and coastal flooding have been limited to relatively small scales, and global-scale or large-scale studies have not yet addressed both of them. The objectives of this study are twofold: to develop a global coupled river-coast flood model; and to conduct a simulation of compound fluvial flooding and storm surges in Asian mega-delta regions. A state-of-the-art global river routing model was modified to represent the influence of dynamic sea surface levels on river discharges and water levels. We conducted the experiments by coupling a river model with a global tide and surge reanalysis data set. Results show that water levels in deltas and estuaries are greatly affected by the interaction between river discharge, ocean tides and storm surges. The effects of storm surges on fluvial flooding are further examined from a regional perspective, focusing on the case of Cyclone Sidr in the Ganges-Brahmaputra-Meghna Delta in 2007. Modeled results demonstrate that a >3 m storm surge propagated more than 200 km inland along rivers. We show that the performance of global river routing models can be improved by including sea level dynamics.

  16. What can('t) we do with global flood risk models?

    Ward, Philip; Jongman, Brenden; Salamon, Peter; Simpson, Alanna; Winsemius, Hessel

    2015-04-01

    In recent years, several global scale flood risk models have become available. Within the scientific community these have been, and are being, used to assess and map the current levels of risk faced by countries and societies. Increasingly, they are also being used to assess how that level of risk may change in the future, under scenarios of climate change and/or socioeconomic development. More and more, these 'quick and not so dirty' methods are also being used in practice, for a large range of uses and applications, and by an increasing range of practitioners and decision makers. For example, assessments can be used by: International Financing Institutes for prioritising investments in the most promising natural disaster risk reduction measures and strategies; intra-national institutes in the monitoring of progress on risk reduction activities; the (re-)insurance industry in assessing their risk portfolios and potential changes in those portfolios under climate change; by multinational companies in assessing risks to their regional investments and supply chains; and by international aid organisations for improved resource planning. However, global scale flood risk models clearly have their limits, and therefore both modellers and users need to critically address the question 'What can('t) we do with global flood risk models?'. This contribution is intended to start a dialogue between model developers, users, and decision makers to better answer this question. We will provide a number of examples of how the GLOFRIS global flood risk model has recently been used in several practical applications, and share both the positive and negative insights gained through these experiences. We wish to discuss similar experiences with other groups of modelers, users, and decision-makers, in order to better understand and harness the potential of this new generation of models, understand the differences in model approaches followed and their impacts on applicability, and develop

  17. Continental and global scale flood forecasting systems

    Emerton, Rebecca E.; Stephens, Elisabeth M.; Pappenberger, Florian; Pagano, Thomas P.; Weerts, A.H.; Wood, A.; Salamon, Peter; Brown, James D.; Hjerdt, Niclas; Donnelly, Chantal; Baugh, Calum A.; Cloke, Hannah L.

    2016-01-01

    Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not

  18. High resolution global flood hazard map from physically-based hydrologic and hydraulic models.

    Begnudelli, L.; Kaheil, Y.; McCollum, J.

    2017-12-01

    The global flood map published online at http://www.fmglobal.com/research-and-resources/global-flood-map at 90m resolution is being used worldwide to understand flood risk exposure, exercise certain measures of mitigation, and/or transfer the residual risk financially through flood insurance programs. The modeling system is based on a physically-based hydrologic model to simulate river discharges, and 2D shallow-water hydrodynamic model to simulate inundation. The model can be applied to large-scale flood hazard mapping thanks to several solutions that maximize its efficiency and the use of parallel computing. The hydrologic component of the modeling system is the Hillslope River Routing (HRR) hydrologic model. HRR simulates hydrological processes using a Green-Ampt parameterization, and is calibrated against observed discharge data from several publicly-available datasets. For inundation mapping, we use a 2D Finite-Volume Shallow-Water model with wetting/drying. We introduce here a grid Up-Scaling Technique (UST) for hydraulic modeling to perform simulations at higher resolution at global scale with relatively short computational times. A 30m SRTM is now available worldwide along with higher accuracy and/or resolution local Digital Elevation Models (DEMs) in many countries and regions. UST consists of aggregating computational cells, thus forming a coarser grid, while retaining the topographic information from the original full-resolution mesh. The full-resolution topography is used for building relationships between volume and free surface elevation inside cells and computing inter-cell fluxes. This approach almost achieves computational speed typical of the coarse grids while preserving, to a significant extent, the accuracy offered by the much higher resolution available DEM. The simulations are carried out along each river of the network by forcing the hydraulic model with the streamflow hydrographs generated by HRR. Hydrographs are scaled so that the peak

  19. Swiss Re Global Flood Hazard Zones: Know your flood risk

    Vinukollu, R. K.; Castaldi, A.; Mehlhorn, J.

    2012-12-01

    Floods, among all natural disasters, have a great damage potential. On a global basis, there is strong evidence of increase in the number of people affected and economic losses due to floods. For example, global insured flood losses have increased by 12% every year since 1970 and this is expected to further increase with growing exposure in the high risk areas close to rivers and coastlines. Recently, the insurance industry has been surprised by the large extent of losses, because most countries lack reliable hazard information. One example has been the 2011 Thailand floods where millions of people were affected and the total economic losses were 30 billion USD. In order to assess the flood risk across different regions and countries, the flood team at Swiss Re based on a Geomorphologic Regression approach, developed in house and patented, produced global maps of flood zones. Input data for the study was obtained from NASA's Shuttle Radar Topographic Mission (SRTM) elevation data, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) and HydroSHEDS. The underlying assumptions of the approach are that naturally flowing rivers shape their channel and flood plain according to basin inherent forces and characteristics and that the flood water extent strongly depends on the shape of the flood plain. On the basis of the catchment characteristics, the model finally calculates the probability of a location to be flooded or not for a defined return period, which in the current study was set to 100 years. The data is produced at a 90-m resolution for latitudes 60S to 60N. This global product is now used in the insurance industry to inspect, inform and/or insure the flood risk across the world.

  20. Enhancing Community Based Early Warning Systems in Nepal with Flood Forecasting Using Local and Global Models

    Dugar, Sumit; Smith, Paul; Parajuli, Binod; Khanal, Sonu; Brown, Sarah; Gautam, Dilip; Bhandari, Dinanath; Gurung, Gehendra; Shakya, Puja; Kharbuja, RamGopal; Uprety, Madhab

    2017-04-01

    Operationalising effective Flood Early Warning Systems (EWS) in developing countries like Nepal poses numerous challenges, with complex topography and geology, sparse network of river and rainfall gauging stations and diverse socio-economic conditions. Despite these challenges, simple real-time monitoring based EWSs have been in place for the past decade. A key constraint of these simple systems is the very limited lead time for response - as little as 2-3 hours, especially for rivers originating from steep mountainous catchments. Efforts to increase lead time for early warning are focusing on imbedding forecasts into the existing early warning systems. In 2016, the Nepal Department of Hydrology and Meteorology (DHM) piloted an operational Probabilistic Flood Forecasting Model in major river basins across Nepal. This comprised a low data approach to forecast water levels, developed jointly through a research/practitioner partnership with Lancaster University and WaterNumbers (UK) and the International NGO Practical Action. Using Data-Based Mechanistic Modelling (DBM) techniques, the model assimilated rainfall and water levels to generate localised hourly flood predictions, which are presented as probabilistic forecasts, increasing lead times from 2-3 hours to 7-8 hours. The Nepal DHM has simultaneously started utilizing forecasts from the Global Flood Awareness System (GLoFAS) that provides streamflow predictions at the global scale based upon distributed hydrological simulations using numerical ensemble weather forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts). The aforementioned global and local models have already affected the approach to early warning in Nepal, being operational during the 2016 monsoon in the West Rapti basin in Western Nepal. On 24 July 2016, GLoFAS hydrological forecasts for the West Rapti indicated a sharp rise in river discharge above 1500 m3/sec (equivalent to the river warning level at 5 meters) with 53

  1. The Aqueduct Global Flood Analyzer

    Iceland, Charles

    2015-04-01

    As population growth and economic growth take place, and as climate change accelerates, many regions across the globe are finding themselves increasingly vulnerable to flooding. A recent OECD study of the exposure of the world's large port cities to coastal flooding found that 40 million people were exposed to a 1 in 100 year coastal flood event in 2005, and the total value of exposed assets was about US 3,000 billion, or 5% of global GDP. By the 2070s, those numbers were estimated to increase to 150 million people and US 35,000 billion, or roughly 9% of projected global GDP. Impoverished people in developing countries are particularly at risk because they often live in flood-prone areas and lack the resources to respond. WRI and its Dutch partners - Deltares, IVM-VU University Amsterdam, Utrecht University, and PBL Netherlands Environmental Assessment Agency - are in the initial stages of developing a robust set of river flood and coastal storm surge risk measures that show the extent of flooding under a variety of scenarios (both current and future), together with the projected human and economic impacts of these flood scenarios. These flood risk data and information will be accessible via an online, easy-to-use Aqueduct Global Flood Analyzer. We will also investigate the viability, benefits, and costs of a wide array of flood risk reduction measures that could be implemented in a variety of geographic and socio-economic settings. Together, the activities we propose have the potential for saving hundreds of thousands of lives and strengthening the resiliency and security of many millions more, especially those who are most vulnerable. Mr. Iceland will present Version 1.0 of the Aqueduct Global Flood Analyzer and provide a preview of additional elements of the Analyzer to be released in the coming years.

  2. A global flash flood forecasting system

    Baugh, Calum; Pappenberger, Florian; Wetterhall, Fredrik; Hewson, Tim; Zsoter, Ervin

    2016-04-01

    The sudden and devastating nature of flash flood events means it is imperative to provide early warnings such as those derived from Numerical Weather Prediction (NWP) forecasts. Currently such systems exist on basin, national and continental scales in Europe, North America and Australia but rely on high resolution NWP forecasts or rainfall-radar nowcasting, neither of which have global coverage. To produce global flash flood forecasts this work investigates the possibility of using forecasts from a global NWP system. In particular we: (i) discuss how global NWP can be used for flash flood forecasting and discuss strengths and weaknesses; (ii) demonstrate how a robust evaluation can be performed given the rarity of the event; (iii) highlight the challenges and opportunities in communicating flash flood uncertainty to decision makers; and (iv) explore future developments which would significantly improve global flash flood forecasting. The proposed forecast system uses ensemble surface runoff forecasts from the ECMWF H-TESSEL land surface scheme. A flash flood index is generated using the ERIC (Enhanced Runoff Index based on Climatology) methodology [Raynaud et al., 2014]. This global methodology is applied to a series of flash floods across southern Europe. Results from the system are compared against warnings produced using the higher resolution COSMO-LEPS limited area model. The global system is evaluated by comparing forecasted warning locations against a flash flood database of media reports created in partnership with floodlist.com. To deal with the lack of objectivity in media reports we carefully assess the suitability of different skill scores and apply spatial uncertainty thresholds to the observations. To communicate the uncertainties of the flash flood system output we experiment with a dynamic region-growing algorithm. This automatically clusters regions of similar return period exceedence probabilities, thus presenting the at-risk areas at a spatial

  3. Flood modelling with global precipitation measurement (GPM) satellite rainfall data: a case study of Dehradun, Uttarakhand, India

    Sai Krishna, V. V.; Dikshit, Anil Kumar; Pandey, Kamal

    2016-05-01

    Urban expansion, water bodies and climate change are inextricably linked with each other. The macro and micro level climate changes are leading to extreme precipitation events which have severe consequences on flooding in urban areas. Flood simulations shall be helpful in demarcation of flooded areas and effective flood planning and preparedness. The temporal availability of satellite rainfall data at varying spatial scale of 0.10 to 0.50 is helpful in near real time flood simulations. The present research aims at analysing stream flow and runoff to monitor flood condition using satellite rainfall data in a hydrologic model. The satellite rainfall data used in the research was NASA's Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), which is available at 30 minutes temporal resolution. Landsat data was used for mapping the water bodies in the study area. Land use land cover (LULC) data was prepared using Landsat 8 data with maximum likelihood technique that was provided as an input to the HEC-HMS hydrological model. The research was applied to one of the urbanized cities of India, viz. Dehradun, which is the capital of Uttarakhand State. The research helped in identifying the flood vulnerability at the basin level on the basis of the runoff and various socio economic parameters using multi criteria analysis.

  4. Global SWOT Data Assimilation of River Hydrodynamic Model; the Twin Simulation Test of CaMa-Flood

    Ikeshima, D.; Yamazaki, D.; Kanae, S.

    2016-12-01

    CaMa-Flood is a global scale model for simulating hydrodynamics in large scale rivers. It can simulate river hydrodynamics such as river discharge, flooded area, water depth and so on by inputting water runoff derived from land surface model. Recently many improvements at parameters or terrestrial data are under process to enhance the reproducibility of true natural phenomena. However, there are still some errors between nature and simulated result due to uncertainties in each model. SWOT (Surface water and Ocean Topography) is a satellite, which is going to be launched in 2021, can measure open water surface elevation. SWOT observed data can be used to calibrate hydrodynamics model at river flow forecasting and is expected to improve model's accuracy. Combining observation data into model to calibrate is called data assimilation. In this research, we developed data-assimilated river flow simulation system in global scale, using CaMa-Flood as river hydrodynamics model and simulated SWOT as observation data. Generally at data assimilation, calibrating "model value" with "observation value" makes "assimilated value". However, the observed data of SWOT satellite will not be available until its launch in 2021. Instead, we simulated the SWOT observed data using CaMa-Flood. Putting "pure input" into CaMa-Flood produce "true water storage". Extracting actual daily swath of SWOT from "true water storage" made simulated observation. For "model value", we made "disturbed water storage" by putting "noise disturbed input" to CaMa-Flood. Since both "model value" and "observation value" are made by same model, we named this twin simulation. At twin simulation, simulated observation of "true water storage" is combined with "disturbed water storage" to make "assimilated value". As the data assimilation method, we used ensemble Kalman filter. If "assimilated value" is closer to "true water storage" than "disturbed water storage", the data assimilation can be marked effective. Also

  5. Global drivers of future river flood risk

    Winsemius, Hessel C.; Aerts, Jeroen C. J. H.; van Beek, Ludovicus P. H.; Bierkens, Marc F. P.; Bouwman, Arno; Jongman, Brenden; Kwadijk, Jaap C. J.; Ligtvoet, Willem; Lucas, Paul L.; van Vuuren, Detlef P.; Ward, Philip J.

    2016-04-01

    Understanding global future river flood risk is a prerequisite for the quantification of climate change impacts and planning effective adaptation strategies. Existing global flood risk projections fail to integrate the combined dynamics of expected socio-economic development and climate change. We present the first global future river flood risk projections that separate the impacts of climate change and socio-economic development. The projections are based on an ensemble of climate model outputs, socio-economic scenarios, and a state-of-the-art hydrologic river flood model combined with socio-economic impact models. Globally, absolute damage may increase by up to a factor of 20 by the end of the century without action. Countries in Southeast Asia face a severe increase in flood risk. Although climate change contributes significantly to the increase in risk in Southeast Asia, we show that it is dwarfed by the effect of socio-economic growth, even after normalization for gross domestic product (GDP) growth. African countries face a strong increase in risk mainly due to socio-economic change. However, when normalized to GDP, climate change becomes by far the strongest driver. Both high- and low-income countries may benefit greatly from investing in adaptation measures, for which our analysis provides a basis.

  6. Global Climate Model Simulated Hydrologic Droughts and Floods in the Nelson-Churchill Watershed

    Vieira, M. J. F.; Stadnyk, T. A.; Koenig, K. A.

    2014-12-01

    There is uncertainty surrounding the duration, magnitude and frequency of historical hydroclimatic extremes such as hydrologic droughts and floods prior to the observed record. In regions where paleoclimatic studies are less reliable, Global Climate Models (GCMs) can provide useful information about past hydroclimatic conditions. This study evaluates the use of Coupled Model Intercomparison Project 5 (CMIP5) GCMs to enhance the understanding of historical droughts and floods across the Canadian Prairie region in the Nelson-Churchill Watershed (NCW). The NCW is approximately 1.4 million km2 in size and drains into Hudson Bay in Northern Manitoba, Canada. One hundred years of observed hydrologic records show extended dry and wet periods in this region; however paleoclimatic studies suggest that longer, more severe droughts have occurred in the past. In Manitoba, where hydropower is the primary source of electricity, droughts are of particular interest as they are important for future resource planning. Twenty-three GCMs with daily runoff are evaluated using 16 metrics for skill in reproducing historic annual runoff patterns. A common 56-year historic period of 1950-2005 is used for this evaluation to capture wet and dry periods. GCM runoff is then routed at a grid resolution of 0.25° using the WATFLOOD hydrological model storage-routing algorithm to develop streamflow scenarios. Reservoir operation is naturalized and a consistent temperature scenario is used to determine ice-on and ice-off conditions. These streamflow simulations are compared with the historic record to remove bias using quantile mapping of empirical distribution functions. GCM runoff data from pre-industrial and future projection experiments are also bias corrected to obtain extended streamflow simulations. GCM streamflow simulations of more than 650 years include a stationary (pre-industrial) period and future periods forced by radiative forcing scenarios. Quantile mapping adjusts for magnitude

  7. Improving Global Flood Forecasting using Satellite Detected Flood Extent

    Revilla Romero, B.

    2016-01-01

    Flooding is a natural global phenomenon but in many cases is exacerbated by human activity. Although flooding generally affects humans in a negative way, bringing death, suffering, and economic impacts, it also has potentially beneficial effects. Early flood warning and forecasting systems, as well

  8. A Global Geospatial Database of 5000+ Historic Flood Event Extents

    Tellman, B.; Sullivan, J.; Doyle, C.; Kettner, A.; Brakenridge, G. R.; Erickson, T.; Slayback, D. A.

    2017-12-01

    A key dataset that is missing for global flood model validation and understanding historic spatial flood vulnerability is a global historical geo-database of flood event extents. Decades of earth observing satellites and cloud computing now make it possible to not only detect floods in near real time, but to run these water detection algorithms back in time to capture the spatial extent of large numbers of specific events. This talk will show results from the largest global historical flood database developed to date. We use the Dartmouth Flood Observatory flood catalogue to map over 5000 floods (from 1985-2017) using MODIS, Landsat, and Sentinel-1 Satellites. All events are available for public download via the Earth Engine Catalogue and via a website that allows the user to query floods by area or date, assess population exposure trends over time, and download flood extents in geospatial format.In this talk, we will highlight major trends in global flood exposure per continent, land use type, and eco-region. We will also make suggestions how to use this dataset in conjunction with other global sets to i) validate global flood models, ii) assess the potential role of climatic change in flood exposure iii) understand how urbanization and other land change processes may influence spatial flood exposure iv) assess how innovative flood interventions (e.g. wetland restoration) influence flood patterns v) control for event magnitude to assess the role of social vulnerability and damage assessment vi) aid in rapid probabilistic risk assessment to enable microinsurance markets. Authors on this paper are already using the database for the later three applications and will show examples of wetland intervention analysis in Argentina, social vulnerability analysis in the USA, and micro insurance in India.

  9. An experimental system for flood risk forecasting at global scale

    Alfieri, L.; Dottori, F.; Kalas, M.; Lorini, V.; Bianchi, A.; Hirpa, F. A.; Feyen, L.; Salamon, P.

    2016-12-01

    Global flood forecasting and monitoring systems are nowadays a reality and are being applied by an increasing range of users and practitioners in disaster risk management. Furthermore, there is an increasing demand from users to integrate flood early warning systems with risk based forecasts, combining streamflow estimations with expected inundated areas and flood impacts. To this end, we have developed an experimental procedure for near-real time flood mapping and impact assessment based on the daily forecasts issued by the Global Flood Awareness System (GloFAS). The methodology translates GloFAS streamflow forecasts into event-based flood hazard maps based on the predicted flow magnitude and the forecast lead time and a database of flood hazard maps with global coverage. Flood hazard maps are then combined with exposure and vulnerability information to derive flood risk. Impacts of the forecasted flood events are evaluated in terms of flood prone areas, potential economic damage, and affected population, infrastructures and cities. To further increase the reliability of the proposed methodology we integrated model-based estimations with an innovative methodology for social media monitoring, which allows for real-time verification of impact forecasts. The preliminary tests provided good results and showed the potential of the developed real-time operational procedure in helping emergency response and management. In particular, the link with social media is crucial for improving the accuracy of impact predictions.

  10. Development of a global river-coastal coupling model and its application to flood simulation in Asian mega-delta regions

    Ikeuchi, Hiroaki; Hirabayashi, Yukiko; Yamazaki, Dai; Muis, Sanne; Ward, Philip; Verlaan, Martin; Winsemius, Hessel; Kanae, Shinjiro

    2017-04-01

    The world's mega-delta regions and estuaries are susceptible to various water-related disasters, such as river flooding and storm surge. Moreover, simultaneous occurrence of them would be more devastating than a situation where they occur in isolation. Therefore, it is important to provide information about compound risks of fluvial and coastal floods at a large scale, both their statistical dependency as well as their combined resulting flooding in delta regions. Here we report on a first attempt to address this issue globally by developing a method to couple a global river model (CaMa-Flood) and a global tide and surge reanalysis (GTSR) dataset. A state-of-the-art global river routing model, CaMa-Flood, was modified to represent varying sea levels due to tides and storm surges as downstream boundary condition, and the GTSR dataset was post-processed to serve as inputs to the CaMa-Flood river routing simulation and a long-term simulation was performed to incorporate the temporal dependency between coastal tide and surge on the one hand, and discharge on the other. The coupled model was validated against observations, showing better simulation results of water levels in deltaic regions than simulation without GTSR. For example in the Ganges Delta, correlation coefficients were increased by 0.06, and root mean square errors were reduced by 0.22 m. Global coupling simulations revealed that storm surges affected river water levels in coastal regions worldwide, especially in low-lying flat areas with increases in water level larger than 0.5 m. By employing enhanced storm surge simulation with tropical storm tracks, we also applied the model to examine impacts of past hurricane and cyclone storm events on river flood inundation.

  11. Effects of climate variability on global scale flood risk

    Ward, P.; Dettinger, M. D.; Kummu, M.; Jongman, B.; Sperna Weiland, F.; Winsemius, H.

    2013-12-01

    research. We carried out the research by simulating daily river discharge using a global hydrological model (PCR-GLOBWB), forced with gridded climate reanalysis time-series. From this, we derived peak annual flood volumes for large-scale river basins globally. These were used to force a global inundation model (dynRout) to map inundation extent and depth for return periods between 2 and 1000 years, under El Niño conditions, neutral conditions, and La Niña conditions. Theses flood hazard maps were combined with global datasets on socioeconomic variables such as population and income to represent the socioeconomic exposure to flooding, and depth-damage curves to represent vulnerability.

  12. A framework for global river flood risk assessments

    Winsemius, H. C.; Van Beek, L. P. H.; Jongman, B.; Ward, P. J.; Bouwman, A.

    2013-05-01

    There is an increasing need for strategic global assessments of flood risks in current and future conditions. In this paper, we propose a framework for global flood risk assessment for river floods, which can be applied in current conditions, as well as in future conditions due to climate and socio-economic changes. The framework's goal is to establish flood hazard and impact estimates at a high enough resolution to allow for their combination into a risk estimate, which can be used for strategic global flood risk assessments. The framework estimates hazard at a resolution of ~ 1 km2 using global forcing datasets of the current (or in scenario mode, future) climate, a global hydrological model, a global flood-routing model, and more importantly, an inundation downscaling routine. The second component of the framework combines hazard with flood impact models at the same resolution (e.g. damage, affected GDP, and affected population) to establish indicators for flood risk (e.g. annual expected damage, affected GDP, and affected population). The framework has been applied using the global hydrological model PCR-GLOBWB, which includes an optional global flood routing model DynRout, combined with scenarios from the Integrated Model to Assess the Global Environment (IMAGE). We performed downscaling of the hazard probability distributions to 1 km2 resolution with a new downscaling algorithm, applied on Bangladesh as a first case study application area. We demonstrate the risk assessment approach in Bangladesh based on GDP per capita data, population, and land use maps for 2010 and 2050. Validation of the hazard estimates has been performed using the Dartmouth Flood Observatory database. This was done by comparing a high return period flood with the maximum observed extent, as well as by comparing a time series of a single event with Dartmouth imagery of the event. Validation of modelled damage estimates was performed using observed damage estimates from the EM

  13. A framework for global river flood risk assessments

    H. C. Winsemius

    2013-05-01

    Full Text Available There is an increasing need for strategic global assessments of flood risks in current and future conditions. In this paper, we propose a framework for global flood risk assessment for river floods, which can be applied in current conditions, as well as in future conditions due to climate and socio-economic changes. The framework's goal is to establish flood hazard and impact estimates at a high enough resolution to allow for their combination into a risk estimate, which can be used for strategic global flood risk assessments. The framework estimates hazard at a resolution of ~ 1 km2 using global forcing datasets of the current (or in scenario mode, future climate, a global hydrological model, a global flood-routing model, and more importantly, an inundation downscaling routine. The second component of the framework combines hazard with flood impact models at the same resolution (e.g. damage, affected GDP, and affected population to establish indicators for flood risk (e.g. annual expected damage, affected GDP, and affected population. The framework has been applied using the global hydrological model PCR-GLOBWB, which includes an optional global flood routing model DynRout, combined with scenarios from the Integrated Model to Assess the Global Environment (IMAGE. We performed downscaling of the hazard probability distributions to 1 km2 resolution with a new downscaling algorithm, applied on Bangladesh as a first case study application area. We demonstrate the risk assessment approach in Bangladesh based on GDP per capita data, population, and land use maps for 2010 and 2050. Validation of the hazard estimates has been performed using the Dartmouth Flood Observatory database. This was done by comparing a high return period flood with the maximum observed extent, as well as by comparing a time series of a single event with Dartmouth imagery of the event. Validation of modelled damage estimates was performed using observed damage estimates from

  14. Compound simulation of fluvial floods and storm surges in a global coupled river-coast flood model : Model development and its application to 2007 Cyclone Sidr in Bangladesh

    Ikeuchi, Hiroaki; Hirabayashi, Yukiko; Yamazaki, Dai; Muis, Sanne; Ward, Philip J.; Winsemius, Hessel C.; Verlaan, Martin; Kanae, Shinjiro

    2017-01-01

    Water-related disasters, such as fluvial floods and cyclonic storm surges, are a major concern in the world's mega-delta regions. Furthermore, the simultaneous occurrence of extreme discharges from rivers and storm surges could exacerbate flood risk, compared to when they occur separately. Hence, it

  15. Flooding Model as the Analysis of the Sea Level Increase as a Result of Global Warming in Coastal Area in Lampung

    Agung Kurniawan

    2017-08-01

    Full Text Available The melting of ice layers, as a direct impact on global warming, is indicated from a lesser thickness of ice layers is specifically causing an increase on the sea level. Lampung, as a province that has an ecosistem of regional coast, can be estimated to submerge. Flood modelling can be done to know the estimated flood range. The model of the flooded region is taken from Shuttle Radar Topography Mission(SRTM data, which is nomalized to get the visualisation of Digital Elevation Model (DEM. The purpose of this research is to know the estimated region of provincial coast of Lampung that is going to be flooded because of the raising of sea surface. This research uses flood inundation technique that uses one of the GIS mapping software. The result can be used as consideration to achieve policy in the building of regional coast. The regions that are flooded based on the scenario of the raising of two and three meter surface sea level are East Lampung Regency, West Lampung Regency, South Lampung Regency, Tanggamus Regency, Pesawaran Regency, and Bandar Lampung.

  16. Multi-model ensemble projections of European river floods and high flows at 1.5, 2, and 3 degrees global warming

    Thober, Stephan; Kumar, Rohini; Wanders, Niko; Marx, Andreas; Pan, Ming; Rakovec, Oldrich; Samaniego, Luis; Sheffield, Justin; Wood, Eric F.; Zink, Matthias

    2018-01-01

    Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 general circulation models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over the entirety of Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from -11% at 1.5 K up to -30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (impacts of global warming could be similar under 1.5 K and 2 K global warming, but have to account for significantly higher changes under 3 K global warming.

  17. Flood model for Brazil

    Palán, Ladislav; Punčochář, Petr

    2017-04-01

    Looking on the impact of flooding from the World-wide perspective, in last 50 years flooding has caused over 460,000 fatalities and caused serious material damage. Combining economic loss from ten costliest flood events (from the same period) returns a loss (in the present value) exceeding 300bn USD. Locally, in Brazil, flood is the most damaging natural peril with alarming increase of events frequencies as 5 out of the 10 biggest flood losses ever recorded have occurred after 2009. The amount of economic and insured losses particularly caused by various flood types was the key driver of the local probabilistic flood model development. Considering the area of Brazil (being 5th biggest country in the World) and the scattered distribution of insured exposure, a domain covered by the model was limited to the entire state of Sao Paolo and 53 additional regions. The model quantifies losses on approx. 90 % of exposure (for regular property lines) of key insurers. Based on detailed exposure analysis, Impact Forecasting has developed this tool using long term local hydrological data series (Agencia Nacional de Aguas) from riverine gauge stations and digital elevation model (Instituto Brasileiro de Geografia e Estatística). To provide most accurate representation of local hydrological behaviour needed for the nature of probabilistic simulation, a hydrological data processing focused on frequency analyses of seasonal peak flows - done by fitting appropriate extreme value statistical distribution and stochastic event set generation consisting of synthetically derived flood events respecting realistic spatial and frequency patterns visible in entire period of hydrological observation. Data were tested for homogeneity, consistency and for any significant breakpoint occurrence in time series so the entire observation or only its subparts were used for further analysis. The realistic spatial patterns of stochastic events are reproduced through the innovative use of d-vine copula

  18. ENSO impacts on flood risk at the global scale

    Ward, Philip; Dettinger, Michael; Jongman, Brenden; Kummu, Matti; Winsemius, Hessel

    2014-05-01

    We present the impacts of El Niño Southern Oscillation (ENSO) on society and the economy, via relationships between ENSO and the hydrological cycle. We also discuss ways in which this knowledge can be used in disaster risk management and risk reduction. This contribution provides the most recent results of an ongoing 4-year collaborative research initiative to assess and map the impacts of large scale interannual climate variability on flood hazard and risk at the global scale. We have examined anomalies in flood risk between ENSO phases, whereby flood risk is expressed in terms of indicators such as: annual expected damage; annual expected affected population; annual expected affected Gross Domestic Product (GDP). We show that large anomalies in flood risk occur during El Niño or La Niña years in basins covering large parts of the Earth's surface. These anomalies reach statistical significance river basins covering almost two-thirds of the Earth's surface. Particularly strong anomalies exist in southern Africa, parts of western Africa, Australia, parts of Central Eurasia (especially for El Niño), the western USA (especially La Niña anomalies), and parts of South America. We relate these anomalies to possible causal relationships between ENSO and flood hazard, using both modelled and observed data on flood occurrence and extremity. The implications for flood risk management are many-fold. In those regions where disaster risk is strongly influenced by ENSO, the potential predictably of ENSO could be used to develop probabilistic flood risk projections with lead times up to several seasons. Such data could be used by the insurance industry in managing risk portfolios and by multinational companies for assessing the robustness of their supply chains to potential flood-related interruptions. Seasonal forecasts of ENSO influence of peak flows could also allow for improved flood early warning and regulation by dam operators, which could also reduce overall risks

  19. Multi-model ensemble projections of European river floods and high flows at 1.5, 2, and 3 degree global warming

    Thober, S.; Kumar, R.; Wanders, N.; Marx, A.; Pan, M.; Rakovec, O.; Samaniego, L. E.; Sheffield, J.; Wood, E. F.; Zink, M.

    2017-12-01

    Severe river floods often result in huge economic losses and fatalities. Since 1980, almost 1500 such events have been reported in Europe. This study investigates climate change impacts on European floods under 1.5, 2, and 3 K global warming. The impacts are assessed employing a multi-model ensemble containing three hydrologic models (HMs: mHM, Noah-MP, PCR-GLOBWB) forced by five CMIP5 General Circulation Models (GCMs) under three Representative Concentration Pathways (RCPs 2.6, 6.0, and 8.5). This multi-model ensemble is unprecedented with respect to the combination of its size (45 realisations) and its spatial resolution, which is 5 km over entire Europe. Climate change impacts are quantified for high flows and flood events, represented by 10% exceedance probability and annual maxima of daily streamflow, respectively. The multi-model ensemble points to the Mediterranean region as a hotspot of changes with significant decrements in high flows from -11% at 1.5 K up to -30% at 3 K global warming mainly resulting from reduced precipitation. Small changes (< ±10%) are observed for river basins in Central Europe and the British Isles under different levels of warming. Projected higher annual precipitation increases high flows in Scandinavia, but reduced snow water equivalent decreases flood events in this region. The contribution by the GCMs to the overall uncertainties of the ensemble is in general higher than that by the HMs. The latter, however, have a substantial share of the overall uncertainty and exceed GCM uncertainty in the Mediterranean and Scandinavia. Adaptation measures for limiting the impacts of global warming could be similar under 1.5 K and 2 K global warming, but has to account for significantly higher changes under 3 K global warming.

  20. Global Flood Risk From Advanced Modeling and Remote Sensing in Collaboration With Google Earth Engine

    National Aeronautics and Space Administration — As predictive accuracy of the climate response to greenhouse emissions improves, measurements of sea level rise are being coupled with modeling to better understand...

  1. Flood damage curves for consistent global risk assessments

    de Moel, Hans; Huizinga, Jan; Szewczyk, Wojtek

    2016-04-01

    Assessing potential damage of flood events is an important component in flood risk management. Determining direct flood damage is commonly done using depth-damage curves, which denote the flood damage that would occur at specific water depths per asset or land-use class. Many countries around the world have developed flood damage models using such curves which are based on analysis of past flood events and/or on expert judgement. However, such damage curves are not available for all regions, which hampers damage assessments in those regions. Moreover, due to different methodologies employed for various damage models in different countries, damage assessments cannot be directly compared with each other, obstructing also supra-national flood damage assessments. To address these problems, a globally consistent dataset of depth-damage curves has been developed. This dataset contains damage curves depicting percent of damage as a function of water depth as well as maximum damage values for a variety of assets and land use classes (i.e. residential, commercial, agriculture). Based on an extensive literature survey concave damage curves have been developed for each continent, while differentiation in flood damage between countries is established by determining maximum damage values at the country scale. These maximum damage values are based on construction cost surveys from multinational construction companies, which provide a coherent set of detailed building cost data across dozens of countries. A consistent set of maximum flood damage values for all countries was computed using statistical regressions with socio-economic World Development Indicators from the World Bank. Further, based on insights from the literature survey, guidance is also given on how the damage curves and maximum damage values can be adjusted for specific local circumstances, such as urban vs. rural locations, use of specific building material, etc. This dataset can be used for consistent supra

  2. Spatial Scaling of Global Rainfall and Flood Extremes

    Devineni, Naresh; Lall, Upmanu; Xi, Chen; Ward, Philip

    2014-05-01

    Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration and spatial extent of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (up to 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances and floods. We present the first ever results on a global analysis of the scaling characteristics of extreme rainfall and flood event duration, volumes and contiguous flooded areas as a result of large scale organization of long duration rainfall events. Results are organized by latitude and with reference to the phases of ENSO, and reveal surprising invariance across latitude. Speculation as to the potential relation to the dynamical factors is presented

  3. Developing a Global Database of Historic Flood Events to Support Machine Learning Flood Prediction in Google Earth Engine

    Tellman, B.; Sullivan, J.; Kettner, A.; Brakenridge, G. R.; Slayback, D. A.; Kuhn, C.; Doyle, C.

    2016-12-01

    There is an increasing need to understand flood vulnerability as the societal and economic effects of flooding increases. Risk models from insurance companies and flood models from hydrologists must be calibrated based on flood observations in order to make future predictions that can improve planning and help societies reduce future disasters. Specifically, to improve these models both traditional methods of flood prediction from physically based models as well as data-driven techniques, such as machine learning, require spatial flood observation to validate model outputs and quantify uncertainty. A key dataset that is missing for flood model validation is a global historical geo-database of flood event extents. Currently, the most advanced database of historical flood extent is hosted and maintained at the Dartmouth Flood Observatory (DFO) that has catalogued 4320 floods (1985-2015) but has only mapped 5% of these floods. We are addressing this data gap by mapping the inventory of floods in the DFO database to create a first-of- its-kind, comprehensive, global and historical geospatial database of flood events. To do so, we combine water detection algorithms on MODIS and Landsat 5,7 and 8 imagery in Google Earth Engine to map discrete flood events. The created database will be available in the Earth Engine Catalogue for download by country, region, or time period. This dataset can be leveraged for new data-driven hydrologic modeling using machine learning algorithms in Earth Engine's highly parallelized computing environment, and we will show examples for New York and Senegal.

  4. Multivariate pluvial flood damage models

    Van Ootegem, Luc; Verhofstadt, Elsy; Van Herck, Kristine; Creten, Tom

    2015-01-01

    Depth–damage-functions, relating the monetary flood damage to the depth of the inundation, are commonly used in the case of fluvial floods (floods caused by a river overflowing). We construct four multivariate damage models for pluvial floods (caused by extreme rainfall) by differentiating on the one hand between ground floor floods and basement floods and on the other hand between damage to residential buildings and damage to housing contents. We do not only take into account the effect of flood-depth on damage, but also incorporate the effects of non-hazard indicators (building characteristics, behavioural indicators and socio-economic variables). By using a Tobit-estimation technique on identified victims of pluvial floods in Flanders (Belgium), we take into account the effect of cases of reported zero damage. Our results show that the flood depth is an important predictor of damage, but with a diverging impact between ground floor floods and basement floods. Also non-hazard indicators are important. For example being aware of the risk just before the water enters the building reduces content damage considerably, underlining the importance of warning systems and policy in this case of pluvial floods. - Highlights: • Prediction of damage of pluvial floods using also non-hazard information • We include ‘no damage cases’ using a Tobit model. • The damage of flood depth is stronger for ground floor than for basement floods. • Non-hazard indicators are especially important for content damage. • Potential gain of policies that increase awareness of flood risks

  5. Multivariate pluvial flood damage models

    Van Ootegem, Luc [HIVA — University of Louvain (Belgium); SHERPPA — Ghent University (Belgium); Verhofstadt, Elsy [SHERPPA — Ghent University (Belgium); Van Herck, Kristine; Creten, Tom [HIVA — University of Louvain (Belgium)

    2015-09-15

    Depth–damage-functions, relating the monetary flood damage to the depth of the inundation, are commonly used in the case of fluvial floods (floods caused by a river overflowing). We construct four multivariate damage models for pluvial floods (caused by extreme rainfall) by differentiating on the one hand between ground floor floods and basement floods and on the other hand between damage to residential buildings and damage to housing contents. We do not only take into account the effect of flood-depth on damage, but also incorporate the effects of non-hazard indicators (building characteristics, behavioural indicators and socio-economic variables). By using a Tobit-estimation technique on identified victims of pluvial floods in Flanders (Belgium), we take into account the effect of cases of reported zero damage. Our results show that the flood depth is an important predictor of damage, but with a diverging impact between ground floor floods and basement floods. Also non-hazard indicators are important. For example being aware of the risk just before the water enters the building reduces content damage considerably, underlining the importance of warning systems and policy in this case of pluvial floods. - Highlights: • Prediction of damage of pluvial floods using also non-hazard information • We include ‘no damage cases’ using a Tobit model. • The damage of flood depth is stronger for ground floor than for basement floods. • Non-hazard indicators are especially important for content damage. • Potential gain of policies that increase awareness of flood risks.

  6. Probabilistic, meso-scale flood loss modelling

    Kreibich, Heidi; Botto, Anna; Schröter, Kai; Merz, Bruno

    2016-04-01

    Flood risk analyses are an important basis for decisions on flood risk management and adaptation. However, such analyses are associated with significant uncertainty, even more if changes in risk due to global change are expected. Although uncertainty analysis and probabilistic approaches have received increased attention during the last years, they are still not standard practice for flood risk assessments and even more for flood loss modelling. State of the art in flood loss modelling is still the use of simple, deterministic approaches like stage-damage functions. Novel probabilistic, multi-variate flood loss models have been developed and validated on the micro-scale using a data-mining approach, namely bagging decision trees (Merz et al. 2013). In this presentation we demonstrate and evaluate the upscaling of the approach to the meso-scale, namely on the basis of land-use units. The model is applied in 19 municipalities which were affected during the 2002 flood by the River Mulde in Saxony, Germany (Botto et al. submitted). The application of bagging decision tree based loss models provide a probability distribution of estimated loss per municipality. Validation is undertaken on the one hand via a comparison with eight deterministic loss models including stage-damage functions as well as multi-variate models. On the other hand the results are compared with official loss data provided by the Saxon Relief Bank (SAB). The results show, that uncertainties of loss estimation remain high. Thus, the significant advantage of this probabilistic flood loss estimation approach is that it inherently provides quantitative information about the uncertainty of the prediction. References: Merz, B.; Kreibich, H.; Lall, U. (2013): Multi-variate flood damage assessment: a tree-based data-mining approach. NHESS, 13(1), 53-64. Botto A, Kreibich H, Merz B, Schröter K (submitted) Probabilistic, multi-variable flood loss modelling on the meso-scale with BT-FLEMO. Risk Analysis.

  7. A framework for global river flood risk assessments

    Winsemius, H.C.; van Beek, L.P.H.|info:eu-repo/dai/nl/14749799X; Jongman, B.; Ward, P.J.; Bouwman, A.

    2013-01-01

    There is an increasing need for strategic global assessments of flood risks in current and future conditions. In this paper, we propose a framework for global flood risk assessment for river floods, which can be applied in current conditions, as well as in future conditions due to climate and

  8. Prospects for development of unified global flood observation and prediction systems (Invited)

    Lettenmaier, D. P.

    2013-12-01

    Floods are among the most damaging of natural hazards, with global flood losses in 2011 alone estimated to have exceeded $100B. Historically, flood economic damages have been highest in the developed world (due in part to encroachment on historical flood plains), but loss of life, and human impacts have been greatest in the developing world. However, as the 2011 Thailand floods show, industrializing countries, many of which do not have well developed flood protection systems, are increasingly vulnerable to economic damages as they become more industrialized. At present, unified global flood observation and prediction systems are in their infancy; notwithstanding that global weather forecasting is a mature field. The summary for this session identifies two evolving capabilities that hold promise for development of more sophisticated global flood forecast systems: global hydrologic models and satellite remote sensing (primarily of precipitation, but also of flood inundation). To this I would add the increasing sophistication and accuracy of global precipitation analysis (and forecast) fields from numerical weather prediction models. In this brief overview, I will review progress in all three areas, and especially the evolution of hydrologic data assimilation which integrates modeling and data sources. I will also comment on inter-governmental and inter-agency cooperation, and related issues that have impeded progress in the development and utilization of global flood observation and prediction systems.

  9. The credibility challenge for global fluvial flood risk analysis

    Trigg, M.A.; Birch, C.E.; Neal, J.C.; Bates, P.D.; Smith, A.; Sampson, C.C.; Yamazaki, D.; Hirabayashi, Y.; Pappenberger, F.; Dutra, E.; Ward, P.J.; Winsemius, H.C.; Salamon, P.; Dottori, F.; Rudari, R.; Kappes, M.S.; Simpson, A.L.; Hadzilacos, G.; Fewtrell, T.J.

    2016-01-01

    Quantifying flood hazard is an essential component of resilience planning, emergency response, and mitigation, including insurance. Traditionally undertaken at catchment and national scales, recently, efforts have intensified to estimate flood risk globally to better allow consistent and equitable

  10. Developing a Malaysia flood model

    Haseldine, Lucy; Baxter, Stephen; Wheeler, Phil; Thomson, Tina

    2014-05-01

    Faced with growing exposures in Malaysia, insurers have a need for models to help them assess their exposure to flood losses. The need for an improved management of flood risks has been further highlighted by the 2011 floods in Thailand and recent events in Malaysia. The increasing demand for loss accumulation tools in Malaysia has lead to the development of the first nationwide probabilistic Malaysia flood model, which we present here. The model is multi-peril, including river flooding for thousands of kilometres of river and rainfall-driven surface water flooding in major cities, which may cause losses equivalent to river flood in some high-density urban areas. The underlying hazard maps are based on a 30m digital surface model (DSM) and 1D/2D hydraulic modelling in JFlow and RFlow. Key mitigation schemes such as the SMART tunnel and drainage capacities are also considered in the model. The probabilistic element of the model is driven by a stochastic event set based on rainfall data, hence enabling per-event and annual figures to be calculated for a specific insurance portfolio and a range of return periods. Losses are estimated via depth-damage vulnerability functions which link the insured damage to water depths for different property types in Malaysia. The model provides a unique insight into Malaysian flood risk profiles and provides insurers with return period estimates of flood damage and loss to property portfolios through loss exceedance curve outputs. It has been successfully validated against historic flood events in Malaysia and is now being successfully used by insurance companies in the Malaysian market to obtain reinsurance cover.

  11. Global Rapid Flood Mapping System with Spaceborne SAR Data

    Yun, S. H.; Owen, S. E.; Hua, H.; Agram, P. S.; Fattahi, H.; Liang, C.; Manipon, G.; Fielding, E. J.; Rosen, P. A.; Webb, F.; Simons, M.

    2017-12-01

    As part of the Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards, at NASA's Jet Propulsion Laboratory and California Institute of Technology, we have developed an automated system that produces derived products for flood extent map generation using spaceborne SAR data. The system takes user's input of area of interest polygons and time window for SAR data search (pre- and post-event). Then the system automatically searches and downloads SAR data, processes them to produce coregistered SAR image pairs, and generates log amplitude ratio images from each pair. Currently the system is automated to support SAR data from the European Space Agency's Sentinel-1A/B satellites. We have used the system to produce flood extent maps from Sentinel-1 SAR data for the May 2017 Sri Lanka floods, which killed more than 200 people and displaced about 600,000 people. Our flood extent maps were delivered to the Red Cross to support response efforts. Earlier we also responded to the historic August 2016 Louisiana floods in the United States, which claimed 13 people's lives and caused over $10 billion property damage. For this event, we made synchronized observations from space, air, and ground in close collaboration with USGS and NOAA. The USGS field crews acquired ground observation data, and NOAA acquired high-resolution airborne optical imagery within the time window of +/-2 hours of the SAR data acquisition by JAXA's ALOS-2 satellite. The USGS coordinates of flood water boundaries were used to calibrate our flood extent map derived from the ALOS-2 SAR data, and the map was delivered to FEMA for estimating the number of households affected. Based on the lessons learned from this response effort, we customized the ARIA system automation for rapid flood mapping and developed a mobile friendly web app that can easily be used in the field for data collection. Rapid automatic generation of SAR-based global flood maps calibrated with independent observations from

  12. Case studies of extended model-based flood forecasting: prediction of dike strength and flood impacts

    Stuparu, Dana; Bachmann, Daniel; Bogaard, Tom; Twigt, Daniel; Verkade, Jan; de Bruijn, Karin; de Leeuw, Annemargreet

    2017-04-01

    Flood forecasts, warning and emergency response are important components in flood risk management. Most flood forecasting systems use models to translate weather predictions to forecasted discharges or water levels. However, this information is often not sufficient for real time decisions. A sound understanding of the reliability of embankments and flood dynamics is needed to react timely and reduce the negative effects of the flood. Where are the weak points in the dike system? When, how much and where the water will flow? When and where is the greatest impact expected? Model-based flood impact forecasting tries to answer these questions by adding new dimensions to the existing forecasting systems by providing forecasted information about: (a) the dike strength during the event (reliability), (b) the flood extent in case of an overflow or a dike failure (flood spread) and (c) the assets at risk (impacts). This work presents three study-cases in which such a set-up is applied. Special features are highlighted. Forecasting of dike strength. The first study-case focusses on the forecast of dike strength in the Netherlands for the river Rhine branches Waal, Nederrijn and IJssel. A so-called reliability transformation is used to translate the predicted water levels at selected dike sections into failure probabilities during a flood event. The reliability of a dike section is defined by fragility curves - a summary of the dike strength conditional to the water level. The reliability information enhances the emergency management and inspections of embankments. Ensemble forecasting. The second study-case shows the setup of a flood impact forecasting system in Dumfries, Scotland. The existing forecasting system is extended with a 2D flood spreading model in combination with the Delft-FIAT impact model. Ensemble forecasts are used to make use of the uncertainty in the precipitation forecasts, which is useful to quantify the certainty of a forecasted flood event. From global

  13. Coupling a global climatic model with insurance impact models for flood and drought: an estimation of the financial impact of climate change

    Tinard Pierre

    2016-01-01

    Full Text Available CCR, a French reinsurance company mostly involved in natural disasters coverage in France, has been developing tools for the estimation of its exposure to climatic risks for many years. Both a flood and a drought models were developed and calibrated on a large policies and claims database supplied every year with insurers’ data. More recently, CCR has been developing a stochastic approach in order to evaluate its financial exposure to extreme events. A large and realistic event set has been generated by applying extreme value statistic tools to simulate hazard and to estimate, using our impact models, the average annual losses and losses related to different return periods. These event sets have been simulated separately for flood and drought, with a hypothesis of independence, consistent with recent annual damage data. The newest development presented here consists in the use of the ARPEGE–Climat model performed by Météo-France to simulate two 200-years sets of hourly atmospheric time series reflecting both the current climate and the RCP 4.5 climate conditions circa year 2050. These climatic data constitute the input data for the flood and drought impact models to detect events and simulate the associated hazard and damages. Our two main goals are (1 to simulate simultaneously flood and drought events for the same simulated years and (2 to evaluate the financial impact of climate change.

  14. Downscaling Global Weather Forecast Outputs Using ANN for Flood Prediction

    Nam Do Hoai

    2011-01-01

    Full Text Available Downscaling global weather prediction model outputs to individual locations or local scales is a common practice for operational weather forecast in order to correct the model outputs at subgrid scales. This paper presents an empirical-statistical downscaling method for precipitation prediction which uses a feed-forward multilayer perceptron (MLP neural network. The MLP architecture was optimized by considering physical bases that determine the circulation of atmospheric variables. Downscaled precipitation was then used as inputs to the super tank model (runoff model for flood prediction. The case study was conducted for the Thu Bon River Basin, located in Central Vietnam. Study results showed that the precipitation predicted by MLP outperformed that directly obtained from model outputs or downscaled using multiple linear regression. Consequently, flood forecast based on the downscaled precipitation was very encouraging. It has demonstrated as a robust technology, simple to implement, reliable, and universal application for flood prediction through the combination of downscaling model and super tank model.

  15. Rapid-response flood mapping during Hurricanes Harvey, Irma and Maria by the Global Flood Partnership (GFP)

    Cohen, S.; Alfieri, L.; Brakenridge, G. R.; Coughlan, E.; Galantowicz, J. F.; Hong, Y.; Kettner, A.; Nghiem, S. V.; Prados, A. I.; Rudari, R.; Salamon, P.; Trigg, M.; Weerts, A.

    2017-12-01

    The Global Flood Partnership (GFP; https://gfp.jrc.ec.europa.eu) is a multi-disciplinary group of scientists, operational agencies and flood risk managers focused on developing efficient and effective global flood management tools. Launched in 2014, its aim is to establish a partnership for global flood forecasting, monitoring and impact assessment to strengthen preparedness and response and to reduce global disaster losses. International organizations, the private sector, national authorities, universities and research agencies contribute to the GFP on a voluntary basis and benefit from a global network focused on flood risk reduction. At the onset of Hurricane Harvey, GFP was `activated' using email requests via its mailing service. Soon after, flood inundation maps, based on remote sensing analysis and modeling, were shared by different agencies, institutions, and individuals. These products were disseminated, to varying degrees of effectiveness, to federal, state and local agencies via emails and data-sharing services. This generated a broad data-sharing network which was utilized at the early stages of Hurricane Irma's impact, just two weeks after Harvey. In this presentation, we will describe the extent and chronology of the GFP response to both Hurricanes Harvey, Irma and Maria. We will assess the potential usefulness of this effort for event managers in various types of organizations and discuss future improvements to be implemented.

  16. Modelling dynamic roughness during floods

    Paarlberg, Andries; Dohmen-Janssen, Catarine M.; Hulscher, Suzanne J.M.H.; Termes, A.P.P.

    2007-01-01

    In this paper, we present a dynamic roughness model to predict water levels during floods. Hysteresis effects of dune development are explicitly included. It is shown that differences between the new dynamic roughness model, and models where the roughness coefficient is calibrated, are most

  17. Comparing flood loss models of different complexity

    Schröter, Kai; Kreibich, Heidi; Vogel, Kristin; Riggelsen, Carsten; Scherbaum, Frank; Merz, Bruno

    2013-04-01

    Any deliberation on flood risk requires the consideration of potential flood losses. In particular, reliable flood loss models are needed to evaluate cost-effectiveness of mitigation measures, to assess vulnerability, for comparative risk analysis and financial appraisal during and after floods. In recent years, considerable improvements have been made both concerning the data basis and the methodological approaches used for the development of flood loss models. Despite of that, flood loss models remain an important source of uncertainty. Likewise the temporal and spatial transferability of flood loss models is still limited. This contribution investigates the predictive capability of different flood loss models in a split sample cross regional validation approach. For this purpose, flood loss models of different complexity, i.e. based on different numbers of explaining variables, are learned from a set of damage records that was obtained from a survey after the Elbe flood in 2002. The validation of model predictions is carried out for different flood events in the Elbe and Danube river basins in 2002, 2005 and 2006 for which damage records are available from surveys after the flood events. The models investigated are a stage-damage model, the rule based model FLEMOps+r as well as novel model approaches which are derived using data mining techniques of regression trees and Bayesian networks. The Bayesian network approach to flood loss modelling provides attractive additional information concerning the probability distribution of both model predictions and explaining variables.

  18. Flash flood modelling for ungauged catchments

    Garambois, P.-A.; Roux, H.; Larnier, K.; Dartus, D.

    2012-04-01

    Flash flood is a very intense and quick hydrologic response of a catchment to rainfall. This phenomenon has a high spatial-temporal variability as its generating storm, often hitting small catchments (few km2). Data collected by (Gaume et al. 2009) about 500 flash floods over the last 50 years showed that they could occur everywhere in Europe and more often in the Mediterranean regions, Alpine regions and continental Europe. Given the small spatial-temporal scales and high variability of flash floods, their prediction remains a hard exercise as the necessary data are often scarce. Flash flood prediction on ungauged catchments is one of the challenges of hydrological modelling as defined by (Sivapalan et al. 2003). Several studies have been headed up with the MARINE model (Modélisation de l'Anticipation du Ruissellement et des Inondations pour des évèNements Extrêmes) for the Gard region (France), (Roux et al. 2011), (Castaings et al. 2009). This physically based spatially distributed rainfall runoff model is dedicated to flash flood prediction. The study aims at finding a methodology for flash flood prediction at ungauged locations in the Cévennes-Vivarais region in particular. The regionalization method is based on multiple calibrations on gauged catchments in order to extract model structures (model + parameter values) for each catchment. Several mathematical methods (multiple regressions, transfer functions, krigging…) will then be tested to calculate a regional parameter set. The study also investigates the usability of additional hydrologic indices at different time scales to constrain model predictions from parameters obtained using these indices, and this independently of the model considered. These hydrologic indices gather information on hydrograph shape or catchment dynamic for instance. Results explaining global catchments behaviour are expected that way. The spatial-temporal variability of storms is also described through indices and linked with

  19. Quantifying the effect of autonomous adaptation to global river flood projections: application to future flood risk assessments

    Kinoshita, Youhei; Tanoue, Masahiro; Watanabe, Satoshi; Hirabayashi, Yukiko

    2018-01-01

    This study represents the first attempt to quantify the effects of autonomous adaptation on the projection of global flood hazards and to assess future flood risk by including this effect. A vulnerability scenario, which varies according to the autonomous adaptation effect for conventional disaster mitigation efforts, was developed based on historical vulnerability values derived from flood damage records and a river inundation simulation. Coupled with general circulation model outputs and future socioeconomic scenarios, potential future flood fatalities and economic loss were estimated. By including the effect of autonomous adaptation, our multimodel ensemble estimates projected a 2.0% decrease in potential flood fatalities and an 821% increase in potential economic losses by 2100 under the highest emission scenario together with a large population increase. Vulnerability changes reduced potential flood consequences by 64%-72% in terms of potential fatalities and 28%-42% in terms of potential economic losses by 2100. Although socioeconomic changes made the greatest contribution to the potential increased consequences of future floods, about a half of the increase of potential economic losses was mitigated by autonomous adaptation. There is a clear and positive relationship between the global temperature increase from the pre-industrial level and the estimated mean potential flood economic loss, while there is a negative relationship with potential fatalities due to the autonomous adaptation effect. A bootstrapping analysis suggests a significant increase in potential flood fatalities (+5.7%) without any adaptation if the temperature increases by 1.5 °C-2.0 °C, whereas the increase in potential economic loss (+0.9%) was not significant. Our method enables the effects of autonomous adaptation and additional adaptation efforts on climate-induced hazards to be distinguished, which would be essential for the accurate estimation of the cost of adaptation to

  20. Declining vulnerability to river floods and the global benefits of adaptation.

    Jongman, Brenden; Winsemius, Hessel C; Aerts, Jeroen C J H; Coughlan de Perez, Erin; van Aalst, Maarten K; Kron, Wolfgang; Ward, Philip J

    2015-05-05

    The global impacts of river floods are substantial and rising. Effective adaptation to the increasing risks requires an in-depth understanding of the physical and socioeconomic drivers of risk. Whereas the modeling of flood hazard and exposure has improved greatly, compelling evidence on spatiotemporal patterns in vulnerability of societies around the world is still lacking. Due to this knowledge gap, the effects of vulnerability on global flood risk are not fully understood, and future projections of fatalities and losses available today are based on simplistic assumptions or do not include vulnerability. We show for the first time (to our knowledge) that trends and fluctuations in vulnerability to river floods around the world can be estimated by dynamic high-resolution modeling of flood hazard and exposure. We find that rising per-capita income coincided with a global decline in vulnerability between 1980 and 2010, which is reflected in decreasing mortality and losses as a share of the people and gross domestic product exposed to inundation. The results also demonstrate that vulnerability levels in low- and high-income countries have been converging, due to a relatively strong trend of vulnerability reduction in developing countries. Finally, we present projections of flood losses and fatalities under 100 individual scenario and model combinations, and three possible global vulnerability scenarios. The projections emphasize that materialized flood risk largely results from human behavior and that future risk increases can be largely contained using effective disaster risk reduction strategies.

  1. A Cloud-Based Global Flood Disaster Community Cyber-Infrastructure: Development and Demonstration

    Wan, Zhanming; Hong, Yang; Khan, Sadiq; Gourley, Jonathan; Flamig, Zachary; Kirschbaum, Dalia; Tang, Guoqiang

    2014-01-01

    Flood disasters have significant impacts on the development of communities globally. This study describes a public cloud-based flood cyber-infrastructure (CyberFlood) that collects, organizes, visualizes, and manages several global flood databases for authorities and the public in real-time, providing location-based eventful visualization as well as statistical analysis and graphing capabilities. In order to expand and update the existing flood inventory, a crowdsourcing data collection methodology is employed for the public with smartphones or Internet to report new flood events, which is also intended to engage citizen-scientists so that they may become motivated and educated about the latest developments in satellite remote sensing and hydrologic modeling technologies. Our shared vision is to better serve the global water community with comprehensive flood information, aided by the state-of-the- art cloud computing and crowdsourcing technology. The CyberFlood presents an opportunity to eventually modernize the existing paradigm used to collect, manage, analyze, and visualize water-related disasters.

  2. Flood Progression Modelling and Impact Analysis

    Mioc, Darka; Anton, François; Nickerson, B.

    People living in the lower valley of the St. John River, New Brunswick, Canada, frequently experience flooding when the river overflows its banks during spring ice melt and rain. To better prepare the population of New Brunswick for extreme flooding, we developed a new flood prediction model...

  3. Tsengwen Reservoir Watershed Hydrological Flood Simulation Under Global Climate Change Using the 20 km Mesh Meteorological Research Institute Atmospheric General Circulation Model (MRI-AGCM

    Nobuaki Kimura

    2014-01-01

    Full Text Available Severe rainstorms have occurred more frequently in Taiwan over the last decade. To understand the flood characteristics of a local region under climate change, a hydrological model simulation was conducted for the Tsengwen Reservoir watershed. The model employed was the Integrated Flood Analysis System (IFAS, which has a conceptual, distributed rainfall-runoff analysis module and a GIS data-input function. The high-resolution rainfall data for flood simulation was categorized into three terms: 1979 - 2003 (Present, 2015 - 2039 (Near-future, and 2075 - 2099 (Future, provided by the Meteorological Research Institute atmospheric general circulation model (MRI-AGCM. Ten extreme rainfall (top ten events were selected for each term in descending order of total precipitation volume. Due to the small watershed area the MRI-AGCM3.2S data was downsized into higher resolution data using the Weather Research and Forecasting Model. The simulated discharges revealed that most of the Near-future and Future peaks caused by extreme rainfall increased compared to the Present peak. These ratios were 0.8 - 1.6 (Near-future/Present and 0.9 - 2.2 (Future/Present, respectively. Additionally, we evaluated how these future discharges would affect the reservoir¡¦s flood control capacity, specifically the excess water volume required to be stored while maintaining dam releases up to the dam¡¦s spillway capacity or the discharge peak design for flood prevention. The results for the top ten events show that the excess water for the Future term exceeded the reservoir¡¦s flood control capacity and was approximately 79.6 - 87.5% of the total reservoir maximum capacity for the discharge peak design scenario.

  4. A satellite and model based flood inundation climatology of Australia

    Schumann, G.; Andreadis, K.; Castillo, C. J.

    2013-12-01

    To date there is no coherent and consistent database on observed or simulated flood event inundation and magnitude at large scales (continental to global). The only compiled data set showing a consistent history of flood inundation area and extent at a near global scale is provided by the MODIS-based Dartmouth Flood Observatory. However, MODIS satellite imagery is only available from 2000 and is hampered by a number of issues associated with flood mapping using optical images (e.g. classification algorithms, cloud cover, vegetation). Here, we present for the first time a proof-of-concept study in which we employ a computationally efficient 2-D hydrodynamic model (LISFLOOD-FP) complemented with a sub-grid channel formulation to generate a complete flood inundation climatology of the past 40 years (1973-2012) for the entire Australian continent. The model was built completely from freely available SRTM-derived data, including channel widths, bank heights and floodplain topography, which was corrected for vegetation canopy height using a global ICESat canopy dataset. Channel hydraulics were resolved using actual channel data and bathymetry was estimated within the model using hydraulic geometry. On the floodplain, the model simulated the flow paths and inundation variables at a 1 km resolution. The developed model was run over a period of 40 years and a floodplain inundation climatology was generated and compared to satellite flood event observations. Our proof-of-concept study demonstrates that this type of model can reliably simulate past flood events with reasonable accuracies both in time and space. The Australian model was forced with both observed flow climatology and VIC-simulated flows in order to assess the feasibility of a model-based flood inundation climatology at the global scale.

  5. Assessing the value of the ATL13 inland water level product for the Global Flood Partnership

    Schumann, G.; Pappenberger, F.; Bates, P. D.; Neal, J. C.; Jasinski, M. F.

    2015-12-01

    This paper reports on the activities and first results of an our ICESat-2 Early Adopter (EA) project for inland water observations. Our team will assess the value of the ICESat-2 water level product using two flood model use cases, one over the California Bay Delta and one over the Niger Inland Delta. Application of the ALT13 product into routine operations will be ensured via an ALT13 database integrated into the pillar "Global Flood Service and Toolbox" (GFST) of the Global Flood Partnership (GFP). GFP is a cooperation framework between scientific organizations and flood disaster managers worldwide to develop flood observational and modelling infrastructure, leveraging on existing initiatives for better predicting and managing flood disaster impacts and flood risk globally. GFP is hosted as an Expert Working Group by the Global Disaster Alert and Coordination System (GDACS). The objective of this EA project is to make the ICESat-2 water level data available to the international GFP community. The EA team believes that the ALT13 product, after successful demonstration of its value in model calibration/validation and monitoring of large floodplain inundation dynamics, should be made easily accessible to the GFP. The GFST will host data outputs and tools from different flood models and for different applications and regions. All these models can benefit from ALT13 if made available to GFP through GFST. Here, we will introduce both test cases and their model setups and report on first preliminary "capabilities" test runs with the Niger model and ICESat-1 as well as radar altimeter data. Based on our results, we will also reflect on expected capabilities and potential of the ICESat-2 mission for river observations.

  6. Efficient pan-European river flood hazard modelling through a combination of statistical and physical models

    Paprotny, D.; Morales Napoles, O.; Jonkman, S.N.

    2017-01-01

    Flood hazard is currently being researched on continental and global scales, using models of increasing complexity. In this paper we investigate a different, simplified approach, which combines statistical and physical models in place of conventional rainfall-run-off models to carry out flood

  7. A global framework for future costs and benefits of river-flood protection in urban areas

    Ward, Philip J.; Jongman, Brenden; Aerts, Jeroen C. J. H.; Bates, Paul D.; Botzen, Wouter J. W.; Diaz Loaiza, Andres; Hallegatte, Stephane; Kind, Jarl M.; Kwadijk, Jaap; Scussolini, Paolo; Winsemius, Hessel C.

    2017-09-01

    Floods cause billions of dollars of damage each year, and flood risks are expected to increase due to socio-economic development, subsidence, and climate change. Implementing additional flood risk management measures can limit losses, protecting people and livelihoods. Whilst several models have been developed to assess global-scale river-flood risk, methods for evaluating flood risk management investments globally are lacking. Here, we present a framework for assessing costs and benefits of structural flood protection measures in urban areas around the world. We demonstrate its use under different assumptions of current and future climate change and socio-economic development. Under these assumptions, investments in dykes may be economically attractive for reducing risk in large parts of the world, but not everywhere. In some regions, economically efficient investments could reduce future flood risk below today’s levels, in spite of climate change and economic growth. We also demonstrate the sensitivity of the results to different assumptions and parameters. The framework can be used to identify regions where river-flood protection investments should be prioritized, or where other risk-reducing strategies should be emphasized.

  8. Top flooding modeling with MAAP4 code

    Brunet-Thibault, E.; Marguet, S.

    2006-01-01

    An engineering top flooding model was developed in MAAP4.04d.4, the severe accident code used in EDF, to simulate the thermal-hydraulic phenomena that should take place if emergency core cooling (ECC) water was injected in hot leg during quenching. In the framework of the ISTC (International Science and Technology Centre), a top flooding test was proposed in the PARAMETER facility (Podolsk, Russia). The MAAP calculation of the PARAMETER top flooding test is presented in this paper. A comparison between top and bottom flooding was made on the bundle test geometry. According to this study, top flooding appears to cool quickly and effectively the upper plenum internals. (author)

  9. Global assessment of river flood protection benefits and corresponding residual risks under climate change

    Lim, Wee Ho; Yamazaki, Dai; Koirala, Sujan; Hirabayashi, Yukiko; Kanae, Shinjiro; Dadson, Simon J.; Hall, Jim W.

    2016-04-01

    Global warming increases the water-holding capacity of the atmosphere and this could lead to more intense rainfalls and possibly increasing natural hazards in the form of flooding in some regions. This implies that traditional practice of using historical hydrological records alone is somewhat limited for supporting long-term water infrastructure planning. This has motivated recent global scale studies to evaluate river flood risks (e.g., Hirabayashi et al., 2013, Arnell and Gosling, 2014, Sadoff et al., 2015) and adaptations benefits (e.g., Jongman et al., 2015). To support decision-making in river flood risk reduction, this study takes a further step to examine the benefits and corresponding residual risks for a range of flood protection levels. To do that, we channelled runoff information of a baseline period (forced by observed hydroclimate conditions) and each CMIP5 model (historic and future periods) into a global river routing model called CaMa-Flood (Yamazaki et al., 2011). We incorporated the latest global river width data (Yamazaki et al., 2014) into CaMa-Flood and simulate the river water depth at a spatial resolution of 15 min x 15 min. From the simulated results of baseline period, we use the annual maxima river water depth to fit the Gumbel distribution and prepare the return period-flood risk relationship (involving population and GDP). From the simulated results of CMIP5 model, we also used the annual maxima river water depth to obtain the Gumbel distribution and then estimate the exceedance probability (historic and future periods). We apply the return period-flood risk relationship (above) to the exceedance probability and evaluate the flood protection benefits. We quantify the corresponding residual risks using a mathematical approach that is consistent with the modelling structure of CaMa-Flood. Globally and regionally, we find that the benefits of flood protection level peak somewhere between 20 and 500 years; residual risks diminish

  10. An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

    Adler, Robert

    2007-01-01

    Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of

  11. Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

    Hong, Yang; Adler, Robert F.; Huffman, George J.; Pierce, Harold

    2008-01-01

    Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

  12. Why are decisions in flood disaster management so poorly supported by information from flood models?

    Leskens, Anne; Brugnach, Marcela Fabiana; Hoekstra, Arjen Ysbert; Schuurmans, W.

    2014-01-01

    Flood simulation models can provide practitioners of Flood Disaster Management with sophisticated estimates of floods. Despite the advantages that flood simulation modeling may provide, experiences have proven that these models are of limited use. Until now, this problem has mainly been investigated

  13. First evaluation of the utility of GPM precipitation in global flood monitoring

    Wu, H.; Yan, Y.; Gao, Z.

    2017-12-01

    The Global Flood Monitoring System (GFMS) has been developed and used to provide real-time flood detection and streamflow estimates over the last few years with significant success shown by validation against global flood event data sets and observed streamflow variations (Wu et al., 2014). It has become a tool for various national and international organizations to appraise flood conditions in various areas, including where rainfall and hydrology information is limited. The GFMS has been using the TRMM Multi-satellite Precipitation Analysis (TMPA) as its main rainfall input. Now, with the advent of the Global Precipitation Measurement (GPM) mission there is an opportunity to significantly improve global flood monitoring and forecasting. GPM's Integrated Multi-satellitE Retrievals for GPM (IMERG) multi-satellite product is designed to take advantage of various technical advances in the field and combine that with an efficient processing system producing "early" (4 hrs) and "late" (12 hrs) products for operational use. Specifically, this study is focused on (1) understanding the difference between the new IMERG products and other existing satellite precipitation products, e.g., TMPA, CMORPH, and ground observations; (2) addressing the challenge in the usage of the IMERG for flood monitoring through hydrologic models, given that only a short period of precipitation data record has been accumulated since the lunch of GPM in 2014; and (3) comparing the statistics of flood simulation based on the DRIVE model with IMERG, TMPA, CMORPH etc. as precipitation inputs respectively. Derivation of a global threshold map is a necessary step to define flood events out of modelling results, which requires a relatively longer historic information. A set of sensitivity tests are conducted by adjusting IMERG's light, moderate, heavy rain to existing precipitation products with long-term records separately, to optimize the strategy of PDF matching. Other aspects are also examined

  14. On the reliable use of satellite-derived surface water products for global flood monitoring

    Hirpa, F. A.; Revilla-Romero, B.; Thielen, J.; Salamon, P.; Brakenridge, R.; Pappenberger, F.; de Groeve, T.

    2015-12-01

    Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response management. To this end, real-time flood forecasting and satellite-based detection systems have been developed at global scale. However, due to the limited availability of up-to-date ground observations, the reliability of these systems for real-time applications have not been assessed in large parts of the globe. In this study, we performed comparative evaluations of the commonly used satellite-based global flood detections and operational flood forecasting system using 10 major flood cases reported over three years (2012-2014). Specially, we assessed the flood detection capabilities of the near real-time global flood maps from the Global Flood Detection System (GFDS), and from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the operational forecasts from the Global Flood Awareness System (GloFAS) for the major flood events recorded in global flood databases. We present the evaluation results of the global flood detection and forecasting systems in terms of correctly indicating the reported flood events and highlight the exiting limitations of each system. Finally, we propose possible ways forward to improve the reliability of large scale flood monitoring tools.

  15. Unstructured mesh adaptivity for urban flooding modelling

    Hu, R.; Fang, F.; Salinas, P.; Pain, C. C.

    2018-05-01

    Over the past few decades, urban floods have been gaining more attention due to their increase in frequency. To provide reliable flooding predictions in urban areas, various numerical models have been developed to perform high-resolution flood simulations. However, the use of high-resolution meshes across the whole computational domain causes a high computational burden. In this paper, a 2D control-volume and finite-element flood model using adaptive unstructured mesh technology has been developed. This adaptive unstructured mesh technique enables meshes to be adapted optimally in time and space in response to the evolving flow features, thus providing sufficient mesh resolution where and when it is required. It has the advantage of capturing the details of local flows and wetting and drying front while reducing the computational cost. Complex topographic features are represented accurately during the flooding process. For example, the high-resolution meshes around the buildings and steep regions are placed when the flooding water reaches these regions. In this work a flooding event that happened in 2002 in Glasgow, Scotland, United Kingdom has been simulated to demonstrate the capability of the adaptive unstructured mesh flooding model. The simulations have been performed using both fixed and adaptive unstructured meshes, and then results have been compared with those published 2D and 3D results. The presented method shows that the 2D adaptive mesh model provides accurate results while having a low computational cost.

  16. Coastal and Riverine Flood Forecast Model powered by ADCIRC

    Khalid, A.; Ferreira, C.

    2017-12-01

    Coastal flooding is becoming a major threat to increased population in the coastal areas. To protect coastal communities from tropical storms & hurricane damages, early warning systems are being developed. These systems have the capability of real time flood forecasting to identify hazardous coastal areas and aid coastal communities in rescue operations. State of the art hydrodynamic models forced by atmospheric forcing have given modelers the ability to forecast storm surge, water levels and currents. This helps to identify the areas threatened by intense storms. Study on Chesapeake Bay area has gained national importance because of its combined riverine and coastal phenomenon, which leads to greater uncertainty in flood predictions. This study presents an automated flood forecast system developed by following Advanced Circulation (ADCIRC) Surge Guidance System (ASGS) guidelines and tailored to take in riverine and coastal boundary forcing, thus includes all the hydrodynamic processes to forecast total water in the Potomac River. As studies on tidal and riverine flow interaction are very scarce in number, our forecast system would be a scientific tool to examine such area and fill the gaps with precise prediction for Potomac River. Real-time observations from National Oceanic and Atmospheric Administration (NOAA) and field measurements have been used as model boundary feeding. The model performance has been validated by using major historical riverine and coastal flooding events. Hydrodynamic model ADCIRC produced promising predictions for flood inundation areas. As better forecasts can be achieved by using coupled models, this system is developed to take boundary conditions from Global WaveWatchIII for the research purposes. Wave and swell propagation will be fed through Global WavewatchIII model to take into account the effects of swells and currents. This automated forecast system is currently undergoing rigorous testing to include any missing parameters which

  17. Modeling Compound Flood Hazards in Coastal Embayments

    Moftakhari, H.; Schubert, J. E.; AghaKouchak, A.; Luke, A.; Matthew, R.; Sanders, B. F.

    2017-12-01

    Coastal cities around the world are built on lowland topography adjacent to coastal embayments and river estuaries, where multiple factors threaten increasing flood hazards (e.g. sea level rise and river flooding). Quantitative risk assessment is required for administration of flood insurance programs and the design of cost-effective flood risk reduction measures. This demands a characterization of extreme water levels such as 100 and 500 year return period events. Furthermore, hydrodynamic flood models are routinely used to characterize localized flood level intensities (i.e., local depth and velocity) based on boundary forcing sampled from extreme value distributions. For example, extreme flood discharges in the U.S. are estimated from measured flood peaks using the Log-Pearson Type III distribution. However, configuring hydrodynamic models for coastal embayments is challenging because of compound extreme flood events: events caused by a combination of extreme sea levels, extreme river discharges, and possibly other factors such as extreme waves and precipitation causing pluvial flooding in urban developments. Here, we present an approach for flood risk assessment that coordinates multivariate extreme analysis with hydrodynamic modeling of coastal embayments. First, we evaluate the significance of correlation structure between terrestrial freshwater inflow and oceanic variables; second, this correlation structure is described using copula functions in unit joint probability domain; and third, we choose a series of compound design scenarios for hydrodynamic modeling based on their occurrence likelihood. The design scenarios include the most likely compound event (with the highest joint probability density), preferred marginal scenario and reproduced time series of ensembles based on Monte Carlo sampling of bivariate hazard domain. The comparison between resulting extreme water dynamics under the compound hazard scenarios explained above provides an insight to the

  18. Probabilistic flood damage modelling at the meso-scale

    Kreibich, Heidi; Botto, Anna; Schröter, Kai; Merz, Bruno

    2014-05-01

    Decisions on flood risk management and adaptation are usually based on risk analyses. Such analyses are associated with significant uncertainty, even more if changes in risk due to global change are expected. Although uncertainty analysis and probabilistic approaches have received increased attention during the last years, they are still not standard practice for flood risk assessments. Most damage models have in common that complex damaging processes are described by simple, deterministic approaches like stage-damage functions. Novel probabilistic, multi-variate flood damage models have been developed and validated on the micro-scale using a data-mining approach, namely bagging decision trees (Merz et al. 2013). In this presentation we show how the model BT-FLEMO (Bagging decision Tree based Flood Loss Estimation MOdel) can be applied on the meso-scale, namely on the basis of ATKIS land-use units. The model is applied in 19 municipalities which were affected during the 2002 flood by the River Mulde in Saxony, Germany. The application of BT-FLEMO provides a probability distribution of estimated damage to residential buildings per municipality. Validation is undertaken on the one hand via a comparison with eight other damage models including stage-damage functions as well as multi-variate models. On the other hand the results are compared with official damage data provided by the Saxon Relief Bank (SAB). The results show, that uncertainties of damage estimation remain high. Thus, the significant advantage of this probabilistic flood loss estimation model BT-FLEMO is that it inherently provides quantitative information about the uncertainty of the prediction. Reference: Merz, B.; Kreibich, H.; Lall, U. (2013): Multi-variate flood damage assessment: a tree-based data-mining approach. NHESS, 13(1), 53-64.

  19. On the Use of Global Flood Forecasts and Satellite-Derived Inundation Maps for Flood Monitoring in Data-Sparse Regions

    Beatriz Revilla-Romero

    2015-11-01

    Full Text Available Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response decisions. Global-scale flood forecasting and satellite-based flood detection systems are currently operating, however their reliability for decision-making applications needs to be assessed. In this study, we performed comparative evaluations of several operational global flood forecasting and flood detection systems, using 10 major flood events recorded over 2012–2014. Specifically, we evaluated the spatial extent and temporal characteristics of flood detections from the Global Flood Detection System (GFDS and the Global Flood Awareness System (GloFAS. Furthermore, we compared the GFDS flood maps with those from NASA’s two Moderate Resolution Imaging Spectroradiometer (MODIS sensors. Results reveal that: (1 general agreement was found between the GFDS and MODIS flood detection systems, (2 large differences exist in the spatio-temporal characteristics of the GFDS detections and GloFAS forecasts, and (3 the quantitative validation of global flood disasters in data-sparse regions is highly challenging. Overall, satellite remote sensing provides useful near real-time flood information that can be useful for risk management. We highlight the known limitations of global flood detection and forecasting systems, and propose ways forward to improve the reliability of large-scale flood monitoring tools.

  20. A prediction and damage assessment model for snowmelt flood events in middle and high latitudes Region

    Qiao, C.; Huang, Q.; Chen, T.; Zhang, X.

    2017-12-01

    In the context of global warming, the snowmelt flood events in the mountainous area of the middle and high latitudes are increasingly frequent and create severe casualties and property damages. Carrying out the prediction and risk assessment of the snowmelt flood is of great importance in the water resources management, the flood warning and prevention. Based on the remote sensing and GIS techniques, the relationships of the variables influencing the snowmelt flood such as the snow area, the snow depth, the air temperature, the precipitation, the land topography and land covers are analyzed and a prediction and damage assessment model for snowmelt floods is developed. This model analyzes and predicts the flood submerging area, flood depth, flood grade, and the damages of different underlying surfaces in the study area in a given time period based on the estimation of snowmelt amount, the snowmelt runoff, the direction and velocity of the flood. Then it was used to predict a snowmelt flood event in the Ertis River Basin in northern Xinjiang, China, during March and June, 2005 and to assess its damages including the damages of roads, transmission lines, settlements caused by the floods and the possible landslides using the hydrological and meteorological data, snow parameter data, DEM data and land use data. A comparison was made between the prediction results from this model and observation data including the flood measurement and its disaster loss data, which suggests that this model performs well in predicting the strength and impact area of snowmelt flood and its damage assessment. This model will be helpful for the prediction and damage assessment of snowmelt flood events in the mountainous area in the middle and high latitudes in spring, which has great social and economic significance because it provides a relatively reliable method for snowmelt flood prediction and reduces the possible damages caused by snowmelt floods.

  1. A Global Drought and Flood Catalogue for the past 100 years

    Sheffield, J.; He, X.; Peng, L.; Pan, M.; Fisher, C. K.; Wood, E. F.

    2017-12-01

    Extreme hydrological events cause the most impacts of natural hazards globally, impacting on a wide range of sectors including, most prominently, agriculture, food security and water availability and quality, but also on energy production, forestry, health, transportation and fisheries. Understanding how floods and droughts intersect, and have changed in the past provides the basis for understanding current risk and how it may change in the future. To do this requires an understanding of the mechanisms associated with events and therefore their predictability, attribution of long-term changes in risk, and quantification of projections of changes in the future. Of key importance are long-term records of relevant variables so that risk can be quantified more accurately, given the growing acknowledgement that risk is not stationary under long-term climate variability and climate change. To address this, we develop a catalogue of drought and flood events based on land surface and hydrodynamic modeling, forced by a hybrid meteorological dataset that draws from the continuity and coverage of reanalysis, and satellite datasets, merged with global gauge databases. The meteorological dataset is corrected for temporal inhomogeneities, spurious trends and variable inter-dependencies to ensure long-term consistency, as well as realistic representation of short-term variability and extremes. The VIC land surface model is run for the past 100 years at 0.25-degree resolution for global land areas. The VIC runoff is then used to drive the CaMa-Flood hydrodynamic model to obtain information on flood inundation risk. The model outputs are compared to satellite based estimates of flood and drought conditions and the observational flood record. The data are analyzed in terms of the spatio-temporal characteristics of large-scale flood and drought events with a particular focus on characterizing the long-term variability in risk. Significant changes in risk occur on multi-decadal time

  2. Numerical modeling techniques for flood analysis

    Anees, Mohd Talha; Abdullah, K.; Nawawi, M. N. M.; Ab Rahman, Nik Norulaini Nik; Piah, Abd. Rahni Mt.; Zakaria, Nor Azazi; Syakir, M. I.; Mohd. Omar, A. K.

    2016-12-01

    Topographic and climatic changes are the main causes of abrupt flooding in tropical areas. It is the need to find out exact causes and effects of these changes. Numerical modeling techniques plays a vital role for such studies due to their use of hydrological parameters which are strongly linked with topographic changes. In this review, some of the widely used models utilizing hydrological and river modeling parameters and their estimation in data sparse region are discussed. Shortcomings of 1D and 2D numerical models and the possible improvements over these models through 3D modeling are also discussed. It is found that the HEC-RAS and FLO 2D model are best in terms of economical and accurate flood analysis for river and floodplain modeling respectively. Limitations of FLO 2D in floodplain modeling mainly such as floodplain elevation differences and its vertical roughness in grids were found which can be improve through 3D model. Therefore, 3D model was found to be more suitable than 1D and 2D models in terms of vertical accuracy in grid cells. It was also found that 3D models for open channel flows already developed recently but not for floodplain. Hence, it was suggested that a 3D model for floodplain should be developed by considering all hydrological and high resolution topographic parameter's models, discussed in this review, to enhance the findings of causes and effects of flooding.

  3. Flood modelling : Parameterisation and inflow uncertainty

    Mukolwe, M.M.; Di Baldassarre, G.; Werner, M.; Solomatine, D.P.

    2014-01-01

    This paper presents an analysis of uncertainty in hydraulic modelling of floods, focusing on the inaccuracy caused by inflow errors and parameter uncertainty. In particular, the study develops a method to propagate the uncertainty induced by, firstly, application of a stage–discharge rating curve

  4. Global warming may lead to catastrophic floods in the Himalayas

    Tveitdal, Svein; Bjoerke, Aake

    2002-01-01

    In Nepal, data from 49 surveillance stations show that there has been a distinct temperature increase since the middle of the 1970s, the greatest changes being on the highest summits. When lakes overfill and beaches threaten to break down, this is a result of the global warming that melts the glaciers. The glaciers in Bhutan are observed to decrease by 30 - 40 metres per year, in some years as much as 100 metres. In the village of Tribeni an advanced warning system has been established to warn the 10 000 inhabitants of a potential flood from Lake Tsho Rolpa 108 km upstream. Research from the Himalayas also point to another serious threat. The melting threatens not only human lives, tourism, foot paths, roads, bridges and power stations. Since the mountains are the water towers of the world, filling rivers and lakes with water upon which all life depends, continued shrinking of the world's glaciers as is now observed will cause many rivers and fresh-water systems to dry out. Researchers from the UN Unep programme and International Centre for Integrated Mountain Development have registered at least 44 glacier lakes that are increasing so fast that they may cause outburst floods within five years. Similar investigations are being planned in India, Pakistan and China

  5. Improving Flood Damage Assessment Models in Italy

    Amadio, M.; Mysiak, J.; Carrera, L.; Koks, E.

    2015-12-01

    The use of Stage-Damage Curve (SDC) models is prevalent in ex-ante assessments of flood risk. To assess the potential damage of a flood event, SDCs describe a relation between water depth and the associated potential economic damage over land use. This relation is normally developed and calibrated through site-specific analysis based on ex-post damage observations. In some cases (e.g. Italy) SDCs are transferred from other countries, undermining the accuracy and reliability of simulation results. Against this background, we developed a refined SDC model for Northern Italy, underpinned by damage compensation records from a recent flood event. Our analysis considers both damage to physical assets and production losses from business interruptions. While the first is calculated based on land use information, production losses are measured through the spatial distribution of Gross Value Added (GVA). An additional component of the model assesses crop-specific agricultural losses as a function of flood seasonality. Our results show an overestimation of asset damage from non-calibrated SDC values up to a factor of 4.5 for tested land use categories. Furthermore, we estimate that production losses amount to around 6 per cent of the annual GVA. Also, maximum yield losses are less than a half of the amount predicted by the standard SDC methods.

  6. Flood routing modelling with Artificial Neural Networks

    R. Peters

    2006-01-01

    Full Text Available For the modelling of the flood routing in the lower reaches of the Freiberger Mulde river and its tributaries the one-dimensional hydrodynamic modelling system HEC-RAS has been applied. Furthermore, this model was used to generate a database to train multilayer feedforward networks. To guarantee numerical stability for the hydrodynamic modelling of some 60 km of streamcourse an adequate resolution in space requires very small calculation time steps, which are some two orders of magnitude smaller than the input data resolution. This leads to quite high computation requirements seriously restricting the application – especially when dealing with real time operations such as online flood forecasting. In order to solve this problem we tested the application of Artificial Neural Networks (ANN. First studies show the ability of adequately trained multilayer feedforward networks (MLFN to reproduce the model performance.

  7. Mathematical modelling of flooding at Magela Creek

    Vardavas, I.

    1989-01-01

    The extent and frequency of the flooding at Magela Creek can be predicted from a mathematical/computer model describing the hydrological phases of surface runoff. Surface runoff involves complex water transfer processes over very inhomogeneous terrain. A simple mathematical model of these has been developed which includes the interception of rainfall by the plant canopy, evapotranspiration, infiltration of surface water into the soil, the storage of water in surface depressions, and overland and subsurface water flow. The rainfall-runoff model has then been incorporated into a more complex computer model to predict the amount of water that enters and leaves the Magela Creek flood plain, downstream of the mine. 2 figs., ills

  8. Enhancement of global flood damage assessments using building material based vulnerability curves

    Englhardt, Johanna; de Ruiter, Marleen; de Moel, Hans; Aerts, Jeroen

    2017-04-01

    This study discusses the development of an enhanced approach for flood damage and risk assessments using vulnerability curves that are based on building material information. The approach draws upon common practices in earthquake vulnerability assessments, and is an alternative for land-use or building occupancy approach in flood risk assessment models. The approach is of particular importance for studies where there is a large variation in building material, such as large scale studies or studies in developing countries. A case study of Ethiopia is used to demonstrate the impact of the different methodological approaches on direct damage assessments due to flooding. Generally, flood damage assessments use damage curves for different land-use or occupancy types (i.e. urban or residential and commercial classes). However, these categories do not necessarily relate directly to vulnerability of damage by flood waters. For this, the construction type and building material may be more important, as is used in earthquake risk assessments. For this study, we use building material classification data of the PAGER1 project to define new building material based vulnerability classes for flood damage. This approach will be compared to the widely applied land-use based vulnerability curves such as used by De Moel et al. (2011). The case of Ethiopia demonstrates and compares the feasibility of this novel flood vulnerability method on a country level which holds the potential to be scaled up to a global level. The study shows that flood vulnerability based on building material also allows for better differentiation between flood damage in urban and rural settings, opening doors to better link to poverty studies when such exposure data is available. Furthermore, this new approach paves the road to the enhancement of multi-risk assessments as the method enables the comparison of vulnerability across different natural hazard types that also use material-based vulnerability curves

  9. Developing Fast and Reliable Flood Models

    Thrysøe, Cecilie; Toke, Jens; Borup, Morten

    2016-01-01

    . A surrogate model is set up for a case study area in Aarhus, Denmark, to replace a MIKE FLOOD model. The drainage surrogates are able to reproduce the MIKE URBAN results for a set of rain inputs. The coupled drainage-surface surrogate model lacks details in the surface description which reduces its overall...... accuracy. The model shows no instability, hence larger time steps can be applied, which reduces the computational time by more than a factor 1400. In conclusion, surrogate models show great potential for usage in urban water modelling....

  10. 2 Dimensional Hydrodynamic Flood Routing Analysis on Flood Forecasting Modelling for Kelantan River Basin

    Azad Wan Hazdy

    2017-01-01

    Full Text Available Flood disaster occurs quite frequently in Malaysia and has been categorized as the most threatening natural disaster compared to landslides, hurricanes, tsunami, haze and others. A study by Department of Irrigation and Drainage (DID show that 9% of land areas in Malaysia are prone to flood which may affect approximately 4.9 million of the population. 2 Dimensional floods routing modelling demonstrate is turning out to be broadly utilized for flood plain display and is an extremely viable device for evaluating flood. Flood propagations can be better understood by simulating the flow and water level by using hydrodynamic modelling. The hydrodynamic flood routing can be recognized by the spatial complexity of the schematization such as 1D model and 2D model. It was found that most of available hydrological models for flood forecasting are more focus on short duration as compared to long duration hydrological model using the Probabilistic Distribution Moisture Model (PDM. The aim of this paper is to discuss preliminary findings on development of flood forecasting model using Probabilistic Distribution Moisture Model (PDM for Kelantan river basin. Among the findings discuss in this paper includes preliminary calibrated PDM model, which performed reasonably for the Dec 2014, but underestimated the peak flows. Apart from that, this paper also discusses findings on Soil Moisture Deficit (SMD and flood plain analysis. Flood forecasting is the complex process that begins with an understanding of the geographical makeup of the catchment and knowledge of the preferential regions of heavy rainfall and flood behaviour for the area of responsibility. Therefore, to decreases the uncertainty in the model output, so it is important to increase the complexity of the model.

  11. Flood frequency analysis of historical flood data under stationary and non-stationary modelling

    Machado, M. J.; Botero, B. A.; López, J.; Francés, F.; Díez-Herrero, A.; Benito, G.

    2015-06-01

    Historical records are an important source of information on extreme and rare floods and fundamental to establish a reliable flood return frequency. The use of long historical records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 yr flood record from the Tagus River in Aranjuez (central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their contribution within hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations in flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation (NAO) index. Over the systematic gauge record (1913-2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators, and (b) a time-varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, which incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency

  12. Projections of future floods and hydrological droughts in Europe under a +2°C global warming

    Roudier, Philippe; Andersson, Jafet C.M.; Donnelly, Chantal; Feyen, Luc; Greuell, Wouter; Ludwig, Fulco

    2016-01-01

    We present an assessment of the impacts of a +2°C global warming on extreme floods and hydrological droughts (1 in 10 and 1 in 100 year events) in Europe using eleven bias-corrected climate model simulations from CORDEX Europe and three hydrological models. The results show quite contrasted results

  13. Error Analysis of Satellite Precipitation-Driven Modeling of Flood Events in Complex Alpine Terrain

    Yiwen Mei

    2016-03-01

    Full Text Available The error in satellite precipitation-driven complex terrain flood simulations is characterized in this study for eight different global satellite products and 128 flood events over the Eastern Italian Alps. The flood events are grouped according to two flood types: rain floods and flash floods. The satellite precipitation products and runoff simulations are evaluated based on systematic and random error metrics applied on the matched event pairs and basin-scale event properties (i.e., rainfall and runoff cumulative depth and time series shape. Overall, error characteristics exhibit dependency on the flood type. Generally, timing of the event precipitation mass center and dispersion of the time series derived from satellite precipitation exhibits good agreement with the reference; the cumulative depth is mostly underestimated. The study shows a dampening effect in both systematic and random error components of the satellite-driven hydrograph relative to the satellite-retrieved hyetograph. The systematic error in shape of the time series shows a significant dampening effect. The random error dampening effect is less pronounced for the flash flood events and the rain flood events with a high runoff coefficient. This event-based analysis of the satellite precipitation error propagation in flood modeling sheds light on the application of satellite precipitation in mountain flood hydrology.

  14. Return period assessment of urban pluvial floods through modelling of rainfall–flood response

    Tuyls, Damian Murla; Thorndahl, Søren Liedtke; Rasmussen, Michael Robdrup

    2018-01-01

    Intense rainfall in urban areas can often generate severe flood impacts. Consequently, it is crucial to design systems to minimize potential flood damages. Traditional, simple design of urban drainage systems assumes agreement between rainfall return period and its consequent flood return period......; however, this does not always apply. Hydraulic infrastructures found in urban drainage systems can increase system heterogeneity and perturb the impact of severe rainfall response. In this study, a surface flood return period assessment was carried out at Lystrup (Denmark), which has received the impact...... of flooding in recent years. A 35 years' rainfall dataset together with a coupled 1D/2D surface and network model was used to analyse and assess flood return period response. Results show an ambiguous relation between rainfall and flood return periods indicating that linear rainfall–runoff relationships will...

  15. An Investigation on the Sensitivity of the Parameters of Urban Flood Model

    M, A. B.; Lohani, B.; Jain, A.

    2015-12-01

    Global climatic change has triggered weather patterns which lead to heavy and sudden rainfall in different parts of world. The impact of heavy rainfall is severe especially on urban areas in the form of urban flooding. In order to understand the effect of heavy rainfall induced flooding, it is necessary to model the entire flooding scenario more accurately, which is now becoming possible with the availability of high resolution airborne LiDAR data and other real time observations. However, there is not much understanding on the optimal use of these data and on the effect of other parameters on the performance of the flood model. This study aims at developing understanding on these issues. In view of the above discussion, the aim of this study is to (i) understand that how the use of high resolution LiDAR data improves the performance of urban flood model, and (ii) understand the sensitivity of various hydrological parameters on urban flood modelling. In this study, modelling of flooding in urban areas due to heavy rainfall is carried out considering Indian Institute of Technology (IIT) Kanpur, India as the study site. The existing model MIKE FLOOD, which is accepted by Federal Emergency Management Agency (FEMA), is used along with the high resolution airborne LiDAR data. Once the model is setup it is made to run by changing the parameters such as resolution of Digital Surface Model (DSM), manning's roughness, initial losses, catchment description, concentration time, runoff reduction factor. In order to realize this, the results obtained from the model are compared with the field observations. The parametric study carried out in this work demonstrates that the selection of catchment description plays a very important role in urban flood modelling. Results also show the significant impact of resolution of DSM, initial losses and concentration time on urban flood model. This study will help in understanding the effect of various parameters that should be part of a

  16. Petascale Diagnostic Assessment of the Global Portfolio Rainfall Space Missions' Ability to Support Flood Forecasting

    Reed, P. M.; Chaney, N.; Herman, J. D.; Wood, E. F.; Ferringer, M. P.

    2015-12-01

    This research represents a multi-institutional collaboration between Cornell University, The Aerospace Corporation, and Princeton University that has completed a Petascale diagnostic assessment of the current 10 satellite missions providing rainfall observations. Our diagnostic assessment has required four core tasks: (1) formally linking high-resolution astrodynamics design and coordination of space assets with their global hydrological impacts within a Petascale "many-objective" global optimization framework, (2) developing a baseline diagnostic evaluation of a 1-degree resolution global implementation of the Variable Infiltration Capacity (VIC) model to establish the required satellite observation frequencies and coverage to maintain acceptable global flood forecasts, (3) evaluating the limitations and vulnerabilities of the full suite of current satellite precipitation missions including the recently approved Global Precipitation Measurement (GPM) mission, and (4) conceptualizing the next generation spaced-based platforms for water cycle observation. Our team exploited over 100 Million hours of computing access on the 700,000+ core Blue Waters machine to radically advance our ability to discover and visualize key system tradeoffs and sensitivities. This project represents to our knowledge the first attempt to develop a 10,000 member Monte Carlo global hydrologic simulation at one degree resolution that characterizes the uncertain effects of changing the available frequencies of satellite precipitation on drought and flood forecasts. The simulation—optimization components of the work have set a theoretical baseline for the best possible frequencies and coverages for global precipitation given unlimited investment, broad international coordination in reconfiguring existing assets, and new satellite constellation design objectives informed directly by key global hydrologic forecasting requirements. Our research poses a step towards realizing the integrated

  17. Forecasting Global Rainfall for Points Using ECMWF's Global Ensemble and Its Applications in Flood Forecasting

    Pillosu, F. M.; Hewson, T.; Mazzetti, C.

    2017-12-01

    Prediction of local extreme rainfall has historically been the remit of nowcasting and high resolution limited area modelling, which represent only limited areas, may not be spatially accurate, give reasonable results only for limited lead times (based statistical post-processing software ("ecPoint-Rainfall, ecPR", operational in 2017) that uses ECMWF Ensemble (ENS) output to deliver global probabilistic rainfall forecasts for points up to day 10. Firstly, ecPR applies a new notion of "remote calibration", which 1) allows us to replicate a multi-centennial training period using only one year of data, and 2) provides forecasts for anywhere in the world. Secondly, the software applies an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals, and of where biases in the model can be improved upon. A long-term verification has shown that the post-processed rainfall has better reliability and resolution at every lead time if compared with ENS, and for large totals, ecPR outputs have the same skill at day 5 that the raw ENS has at day 1 (ROC area metric). ecPR could be used as input for hydrological models if its probabilistic output is modified accordingly to the inputs requirements for hydrological models. Indeed, ecPR does not provide information on where the highest total is likely to occur inside the gridbox, nor on the spatial distribution of rainfall values nearby. "Scenario forecasts" could be a solution. They are derived from locating the rainfall peak in sensitive positions (e.g. urban areas), and then redistributing the remaining quantities in the gridbox modifying traditional spatial correlation characterization methodologies (e.g. variogram analysis) in order to take account, for instance, of the type of rainfall forecast (stratiform, convective). Such an approach could be a turning point in the field of medium-range global real-time riverine flood forecasts. This presentation will

  18. Development of a flood-induced health risk prediction model for Africa

    Lee, D.; Block, P. J.

    2017-12-01

    Globally, many floods occur in developing or tropical regions where the impact on public health is substantial, including death and injury, drinking water, endemic disease, and so on. Although these flood impacts on public health have been investigated, integrated management of floods and flood-induced health risks is technically and institutionally limited. Specifically, while the use of climatic and hydrologic forecasts for disaster management has been highlighted, analogous predictions for forecasting the magnitude and impact of health risks are lacking, as is the infrastructure for health early warning systems, particularly in developing countries. In this study, we develop flood-induced health risk prediction model for African regions using season-ahead flood predictions with climate drivers and a variety of physical and socio-economic information, such as local hazard, exposure, resilience, and health vulnerability indicators. Skillful prediction of flood and flood-induced health risks can contribute to practical pre- and post-disaster responses in both local- and global-scales, and may eventually be integrated into multi-hazard early warning systems for informed advanced planning and management. This is especially attractive for areas with limited observations and/or little capacity to develop flood-induced health risk warning systems.

  19. Evaluation of various modelling approaches in flood routing simulation and flood area mapping

    Papaioannou, George; Loukas, Athanasios; Vasiliades, Lampros; Aronica, Giuseppe

    2016-04-01

    An essential process of flood hazard analysis and mapping is the floodplain modelling. The selection of the modelling approach, especially, in complex riverine topographies such as urban and suburban areas, and ungauged watersheds may affect the accuracy of the outcomes in terms of flood depths and flood inundation area. In this study, a sensitivity analysis implemented using several hydraulic-hydrodynamic modelling approaches (1D, 2D, 1D/2D) and the effect of modelling approach on flood modelling and flood mapping was investigated. The digital terrain model (DTMs) used in this study was generated from Terrestrial Laser Scanning (TLS) point cloud data. The modelling approaches included 1-dimensional hydraulic-hydrodynamic models (1D), 2-dimensional hydraulic-hydrodynamic models (2D) and the coupled 1D/2D. The 1D hydraulic-hydrodynamic models used were: HECRAS, MIKE11, LISFLOOD, XPSTORM. The 2D hydraulic-hydrodynamic models used were: MIKE21, MIKE21FM, HECRAS (2D), XPSTORM, LISFLOOD and FLO2d. The coupled 1D/2D models employed were: HECRAS(1D/2D), MIKE11/MIKE21(MIKE FLOOD platform), MIKE11/MIKE21 FM(MIKE FLOOD platform), XPSTORM(1D/2D). The validation process of flood extent achieved with the use of 2x2 contingency tables between simulated and observed flooded area for an extreme historical flash flood event. The skill score Critical Success Index was used in the validation process. The modelling approaches have also been evaluated for simulation time and requested computing power. The methodology has been implemented in a suburban ungauged watershed of Xerias river at Volos-Greece. The results of the analysis indicate the necessity of sensitivity analysis application with the use of different hydraulic-hydrodynamic modelling approaches especially for areas with complex terrain.

  20. Flash flood modeling with the MARINE hydrological distributed model

    Estupina-Borrell, V.; Dartus, D.; Ababou, R.

    2006-11-01

    Flash floods are characterized by their violence and the rapidity of their occurrence. Because these events are rare and unpredictable, but also fast and intense, their anticipation with sufficient lead time for warning and broadcasting is a primary subject of research. Because of the heterogeneities of the rain and of the behavior of the surface, spatially distributed hydrological models can lead to a better understanding of the processes and so on they can contribute to a better forecasting of flash flood. Our main goal here is to develop an operational and robust methodology for flash flood forecasting. This methodology should provide relevant data (information) about flood evolution on short time scales, and should be applicable even in locations where direct observations are sparse (e.g. absence of historical and modern rainfalls and streamflows in small mountainous watersheds). The flash flood forecast is obtained by the physically based, space-time distributed hydrological model "MARINE'' (Model of Anticipation of Runoff and INondations for Extreme events). This model is presented and tested in this paper for a real flash flood event. The model consists in two steps, or two components: the first component is a "basin'' flood module which generates flood runoff in the upstream part of the watershed, and the second component is the "stream network'' module, which propagates the flood in the main river and its subsidiaries. The basin flash flood generation model is a rainfall-runoff model that can integrate remotely sensed data. Surface hydraulics equations are solved with enough simplifying hypotheses to allow real time exploitation. The minimum data required by the model are: (i) the Digital Elevation Model, used to calculate slopes that generate runoff, it can be issued from satellite imagery (SPOT) or from French Geographical Institute (IGN); (ii) the rainfall data from meteorological radar, observed or anticipated by the French Meteorological Service (M

  1. Technical note: River modelling to infer flood management framework

    River hydraulic models have successfully identified the weaknesses and areas for improvement with respect to flooding in the Sarawak River system, and can also be used to support decisions on flood management measures. Often, the big question is 'how'. This paper demonstrates a theoretical flood management ...

  2. Hygrothermal modelling of flooding events within historic buildings

    Huijbregts, Z.; Schellen, H.L.; Schijndel, van A.W.M.; Blades, N.

    2014-01-01

    Flooding events pose a high risk to valuable monumental buildings and their interiors. Due to higher river discharges and sea level rise, flooding events may occur more often in future. Hygrothermal building simulation models can be applied to investigate the impact of a flooding event on the

  3. Hygrothermal modelling of flooding events within historic buildings

    Huijbregts, Z.; Schijndel, van A.W.M.; Schellen, H.L.; Blades, N.; Mahdavi, A.; Mertens, B.

    2013-01-01

    Flooding events pose a high risk to valuable monumental buildings and their interiors. Due to higher river discharges and sea level rise, flooding events may occur more often in future. Hygrothermal building simulation models can be applied to investigate the impact of a flooding event on the

  4. Assessment of static flood modeling techniques: application to contrasting marshes flooded during Xynthia (western France

    J. F. Breilh

    2013-06-01

    Full Text Available This study aims to assess the performance of raster-based flood modeling methods on a wide diversity of coastal marshes. These methods are applied to the flooding associated with the storm Xynthia, which severely hit the western coast of France in February 2010. Static and semi-dynamic methods are assessed using a combination of LiDAR data, post-storm delineation of flooded areas and sea levels originating from both tide gauge measurements and storm surge modeling. Static methods are applied to 27 marshes showing a wide geomorphological diversity. It appears that these methods are suitable for marshes with a small distance between the coastline and the landward boundary of the marsh, which causes these marshes to flood rapidly. On the contrary, these methods overpredict flooded areas for large marshes where the distance between the coastline and the landward boundary of the marsh is large, because the flooding cannot be considered as instantaneous. In this case, semi-dynamic methods based on surge overflowing volume calculations can improve the flooding prediction significantly. This study suggests that static and semi-dynamic flood modeling methods can be attractive and quickly deployed to rapidly produce predictive flood maps of vulnerable areas under certain conditions, particularly for small distances between the coastline and the landward boundary of the low-lying coastal area.

  5. Rapid Global River Flood Risk Assessment under Climate and Socioeconomic Scenarios: An Extreme Case of Eurasian region

    Kwak, Young-joo; Magome, Jun; Hasegawa, Akira; Iwami, Yoichi

    2017-04-01

    Causing widespread devastation with massive economic damage and loss of human lives, flood disasters hamper economic growth and accelerate poverty particularly in developing countries. Globally, this trend will likely continue due to increase in flood magnitude and lack of preparedness for extreme events. In line with risk reduction efforts since the early 21st century, the monitors and governors of global river floods should pay attention to international scientific and policy communities for support to facilitate evidence-based policy making with a special interest in long-term changes due to climate change and socio-economic effects. Although advanced hydrological inundation models and risk models have been developed to reveal flood risk, hazard, exposure, and vulnerability at a river basin, it is obviously hard to identify the distribution and locations of continent-level flood risk based on national-level data. Therefore, we propose a methodological possibility for rapid global flood risk assessment with the results from its application to the two periods, i.e., Present (from 1980 to 2004) and Future (from 2075 to 2099). The method is particularly designed to effectively simplify complexities of a hazard area by calculating the differential inundation depth using GFID2M (global flood inundation depth 2-dimension model), despite low data availability. In this research, we addressed the question of which parts in the Eurasian region (8E to 180E, 0N to 60N) can be found as high-risk areas in terms of exposed population and economy in case of a 50-year return period flood. Economic losses were estimated according to the Shared Socioeconomic Pathways (SSP) scenario, and the flood scale was defined using the annual maximum daily river discharge under the extreme conditions of climate change simulated with MRI-AGCM3.2S based on the Representative Concentration Pathways (RCP8.5) emissions scenario. As a preliminary result, the total potential economic loss in the

  6. Global and Regional Real-time Systems for Flood and Drought Monitoring and Prediction

    Hong, Y.; Gourley, J. J.; Xue, X.; Flamig, Z.

    2015-12-01

    A Hydrometeorological Extreme Mapping and Prediction System (HyXtreme-MaP), initially built upon the Coupled Routing and Excess STorage (CREST) distributed hydrological model, is driven by real-time quasi-global TRMM/GPM satellites and by the US Multi-Radar Multi-Sensor (MRMS) radar network with dual-polarimetric upgrade to simulate streamflow, actual ET, soil moisture and other hydrologic variables at 1/8th degree resolution quasi-globally (http://eos.ou.edu) and at 250-meter 2.5-mintue resolution over the Continental United States (CONUS: http://flash.ou.edu).­ Multifaceted and collaborative by-design, this end-to-end research framework aims to not only integrate data, models, and applications but also brings people together (i.e., NOAA, NASA, University researchers, and end-users). This presentation will review the progresses, challenges and opportunities of such HyXTREME-MaP System used to monitor global floods and droughts, and also to predict flash floods over the CONUS.

  7. Floods

    Floods are common in the United States. Weather such as heavy rain, thunderstorms, hurricanes, or tsunamis can ... is breached, or when a dam breaks. Flash floods, which can develop quickly, often have a dangerous ...

  8. Modeling of Flood Risk for the Continental United States

    Lohmann, D.; Li, S.; Katz, B.; Goteti, G.; Kaheil, Y. H.; Vojjala, R.

    2011-12-01

    The science of catastrophic risk modeling helps people to understand the physical and financial implications of natural catastrophes (hurricanes, flood, earthquakes, etc.), terrorism, and the risks associated with changes in life expectancy. As such it depends on simulation techniques that integrate multiple disciplines such as meteorology, hydrology, structural engineering, statistics, computer science, financial engineering, actuarial science, and more in virtually every field of technology. In this talk we will explain the techniques and underlying assumptions of building the RMS US flood risk model. We especially will pay attention to correlation (spatial and temporal), simulation and uncertainty in each of the various components in the development process. Recent extreme floods (e.g. US Midwest flood 2008, US Northeast flood, 2010) have increased the concern of flood risk. Consequently, there are growing needs to adequately assess the flood risk. The RMS flood hazard model is mainly comprised of three major components. (1) Stochastic precipitation simulation module based on a Monte-Carlo analogue technique, which is capable of producing correlated rainfall events for the continental US. (2) Rainfall-runoff and routing module. A semi-distributed rainfall-runoff model was developed to properly assess the antecedent conditions, determine the saturation area and runoff. The runoff is further routed downstream along the rivers by a routing model. Combined with the precipitation model, it allows us to correlate the streamflow and hence flooding from different rivers, as well as low and high return-periods across the continental US. (3) Flood inundation module. It transforms the discharge (output from the flow routing) into water level, which is further combined with a two-dimensional off-floodplain inundation model to produce comprehensive flood hazard map. The performance of the model is demonstrated by comparing to the observation and published data. Output from

  9. Hydrometeorological network for flood monitoring and modeling

    Efstratiadis, Andreas; Koussis, Antonis D.; Lykoudis, Spyros; Koukouvinos, Antonis; Christofides, Antonis; Karavokiros, George; Kappos, Nikos; Mamassis, Nikos; Koutsoyiannis, Demetris

    2013-08-01

    Due to its highly fragmented geomorphology, Greece comprises hundreds of small- to medium-size hydrological basins, in which often the terrain is fairly steep and the streamflow regime ephemeral. These are typically affected by flash floods, occasionally causing severe damages. Yet, the vast majority of them lack flow-gauging infrastructure providing systematic hydrometric data at fine time scales. This has obvious impacts on the quality and reliability of flood studies, which typically use simplistic approaches for ungauged basins that do not consider local peculiarities in sufficient detail. In order to provide a consistent framework for flood design and to ensure realistic predictions of the flood risk -a key issue of the 2007/60/EC Directive- it is essential to improve the monitoring infrastructures by taking advantage of modern technologies for remote control and data management. In this context and in the research project DEUCALION, we have recently installed and are operating, in four pilot river basins, a telemetry-based hydro-meteorological network that comprises automatic stations and is linked to and supported by relevant software. The hydrometric stations measure stage, using 50-kHz ultrasonic pulses or piezometric sensors, or both stage (piezometric) and velocity via acoustic Doppler radar; all measurements are being temperature-corrected. The meteorological stations record air temperature, pressure, relative humidity, wind speed and direction, and precipitation. Data transfer is made via GPRS or mobile telephony modems. The monitoring network is supported by a web-based application for storage, visualization and management of geographical and hydro-meteorological data (ENHYDRIS), a software tool for data analysis and processing (HYDROGNOMON), as well as an advanced model for flood simulation (HYDROGEIOS). The recorded hydro-meteorological observations are accessible over the Internet through the www-application. The system is operational and its

  10. Characterizing Global Flood Wave Travel Times to Optimize the Utility of Near Real-Time Satellite Remote Sensing Products

    Allen, G. H.; David, C. H.; Andreadis, K. M.; Emery, C. M.; Famiglietti, J. S.

    2017-12-01

    Earth observing satellites provide valuable near real-time (NRT) information about flood occurrence and magnitude worldwide. This NRT information can be used in early flood warning systems and other flood management applications to save lives and mitigate flood damage. However, these NRT products are only useful to early flood warning systems if they are quickly made available, with sufficient time for flood mitigation actions to be implemented. More specifically, NRT data latency, or the time period between the satellite observation and when the user has access to the information, must be less than the time it takes a flood to travel from the flood observation location to a given downstream point of interest. Yet the paradigm that "lower latency is always better" may not necessarily hold true in river systems due to tradeoffs between data latency and data quality. Further, the existence of statistical breaks in the global distribution of flood wave travel time (i.e. a jagged statistical distribution) would represent preferable latencies for river-observation NRT remote sensing products. Here we present a global analysis of flood wave velocity (i.e. flow celerity) and travel time. We apply a simple kinematic wave model to a global hydrography dataset and calculate flow wave celerity and travel time during bankfull flow conditions. Bankfull flow corresponds to the condition of maximum celerity and thus we present the "worst-case scenario" minimum flow wave travel time. We conduct a similar analysis with respect to the time it takes flood waves to reach the next downstream city, as well as the next downstream reservoir. Finally, we conduct these same analyses, but with regards to the technical capabilities of the planned Surface Water and Ocean Topography (SWOT) satellite mission, which is anticipated to provide waterbody elevation and extent measurements at an unprecedented spatial and temporal resolution. We validate these results with discharge records from paired

  11. Has the magnitude of floods across the USA changed with global CO2 levels?

    Hirsch, Robert M.; Ryberg, Karen R.

    2012-01-01

    Statistical relationships between annual floods at 200 long-term (85–127 years of record) streamgauges in the coterminous United States and the global mean carbon dioxide concentration (GMCO2) record are explored. The streamgauge locations are limited to those with little or no regulation or urban development. The coterminous US is divided into four large regions and stationary bootstrapping is used to evaluate if the patterns of these statistical associations are significantly different from what would be expected under the null hypothesis that flood magnitudes are independent of GMCO2. In none of the four regions defined in this study is there strong statistical evidence for flood magnitudes increasing with increasing GMCO2. One region, the southwest, showed a statistically significant negative relationship between GMCO2 and flood magnitudes. The statistical methods applied compensate both for the inter-site correlation of flood magnitudes and the shorter-term (up to a few decades) serial correlation of floods.

  12. A new methodology for dynamic modelling of health risks arising from wastewater influenced urban flooding

    Jørgensen, Claus; Mark, Ole; Djordjevic, Slobodan; Hammond, Michael; Khan, David M.; Erichsen, Anders; Dorrit Enevoldsen, Ann; Heinicke, Gerald; Helwigh, Birgitte

    2015-04-01

    Indroduction Urban flooding due to rainfall exceeding the design capacity of drainage systems is a global problem and it has significant economic and social consequences. While the cost of the direct flood damages of urban flooding is well understood, the indirect damages, like the water borne diseases is in general still poorly understood. Climate changes are expected to increase the frequency of urban flooding in many countries which is likely to increase water borne diseases. Diarrheal diseases are most prevalent in developing countries, where poor sanitation, poor drinking water and poor surface water quality causes a high disease burden and mortality, especially during floods. The level of water borne diarrhea in countries with well-developed water and waste water infrastructure has been reduced to an acceptable level, and the population in general do not consider waste water as being a health risk. Hence, exposure to wastewater influenced urban flood water still has the potential to cause transmission of diarrheal diseases. When managing urban flooding and planning urban climate change adaptations, health risks are rarely taken into consideration. This paper outlines a novel methodology for linking dynamic urban flood modelling with Quantitative Microbial Risk Assessment (QMRA). This provides a unique possibility for understanding the interaction between urban flooding and the health risks caused by direct human contact with flood water and provides an option for reducing the burden of disease in the population through the use of intelligent urban flood risk management. Methodology We have linked hydrodynamic urban flood modelling with quantitative microbial risk assessment (QMRA) to determine the risk of infection caused by exposure to wastewater influenced urban flood water. The deterministic model MIKE Flood, which integrates the sewer network model in MIKE Urban and the 2D surface model MIKE21, was used to calculate the concentration of pathogens in the

  13. Flooding and Flood Management

    Brooks, K.N.; Fallon, J.D.; Lorenz, D.L.; Stark, J.R.; Menard, Jason; Easter, K.W.; Perry, Jim

    2011-01-01

    Floods result in great human disasters globally and nationally, causing an average of $4 billion of damages each year in the United States. Minnesota has its share of floods and flood damages, and the state has awarded nearly $278 million to local units of government for flood mitigation projects through its Flood Hazard Mitigation Grant Program. Since 1995, flood mitigation in the Red River Valley has exceeded $146 million. Considerable local and state funding has been provided to manage and mitigate problems of excess stormwater in urban areas, flooding of farmlands, and flood damages at road crossings. The cumulative costs involved with floods and flood mitigation in Minnesota are not known precisely, but it is safe to conclude that flood mitigation is a costly business. This chapter begins with a description of floods in Minneosta to provide examples and contrasts across the state. Background material is presented to provide a basic understanding of floods and flood processes, predication, and management and mitigation. Methods of analyzing and characterizing floods are presented because they affect how we respond to flooding and can influence relevant practices. The understanding and perceptions of floods and flooding commonly differ among those who work in flood forecasting, flood protection, or water resource mamnagement and citizens and businesses affected by floods. These differences can become magnified following a major flood, pointing to the need for better understanding of flooding as well as common language to describe flood risks and the uncertainty associated with determining such risks. Expectations of accurate and timely flood forecasts and our ability to control floods do not always match reality. Striving for clarity is important in formulating policies that can help avoid recurring flood damages and costs.

  14. Modelling climate impact on floods under future emission scenarios using an ensemble of climate model projections

    Wetterhall, F.; Cloke, H. L.; He, Y.; Freer, J.; Pappenberger, F.

    2012-04-01

    Evidence provided by modelled assessments of climate change impact on flooding is fundamental to water resource and flood risk decision making. Impact models usually rely on climate projections from Global and Regional Climate Models, and there is no doubt that these provide a useful assessment of future climate change. However, cascading ensembles of climate projections into impact models is not straightforward because of problems of coarse resolution in Global and Regional Climate Models (GCM/RCM) and the deficiencies in modelling high-intensity precipitation events. Thus decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs, such as selection of downscaling methods and application of Model Output Statistics (MOS). In this paper a grand ensemble of projections from several GCM/RCM are used to drive a hydrological model and analyse the resulting future flood projections for the Upper Severn, UK. The impact and implications of applying MOS techniques to precipitation as well as hydrological model parameter uncertainty is taken into account. The resultant grand ensemble of future river discharge projections from the RCM/GCM-hydrological model chain is evaluated against a response surface technique combined with a perturbed physics experiment creating a probabilisic ensemble climate model outputs. The ensemble distribution of results show that future risk of flooding in the Upper Severn increases compared to present conditions, however, the study highlights that the uncertainties are large and that strong assumptions were made in using Model Output Statistics to produce the estimates of future discharge. The importance of analysing on a seasonal basis rather than just annual is highlighted. The inability of the RCMs (and GCMs) to produce realistic precipitation patterns, even in present conditions, is a major caveat of local climate impact studies on flooding, and this should be a focus for future development.

  15. An Agent-Based Model of Evolving Community Flood Risk.

    Tonn, Gina L; Guikema, Seth D

    2017-11-17

    Although individual behavior plays a major role in community flood risk, traditional flood risk models generally do not capture information on how community policies and individual decisions impact the evolution of flood risk over time. The purpose of this study is to improve the understanding of the temporal aspects of flood risk through a combined analysis of the behavioral, engineering, and physical hazard aspects of flood risk. Additionally, the study aims to develop a new modeling approach for integrating behavior, policy, flood hazards, and engineering interventions. An agent-based model (ABM) is used to analyze the influence of flood protection measures, individual behavior, and the occurrence of floods and near-miss flood events on community flood risk. The ABM focuses on the following decisions and behaviors: dissemination of flood management information, installation of community flood protection, elevation of household mechanical equipment, and elevation of homes. The approach is place based, with a case study area in Fargo, North Dakota, but is focused on generalizable insights. Generally, community mitigation results in reduced future damage, and individual action, including mitigation and movement into and out of high-risk areas, can have a significant influence on community flood risk. The results of this study provide useful insights into the interplay between individual and community actions and how it affects the evolution of flood risk. This study lends insight into priorities for future work, including the development of more in-depth behavioral and decision rules at the individual and community level. © 2017 Society for Risk Analysis.

  16. Indirect Damage of Urban Flooding: Investigation of Flood-Induced Traffic Congestion Using Dynamic Modeling

    Jingxuan Zhu

    2018-05-01

    Full Text Available In many countries, industrialization has led to rapid urbanization. Increased frequency of urban flooding is one consequence of the expansion of urban areas which can seriously affect the productivity and livelihoods of urban residents. Therefore, it is of vital importance to study the effects of rainfall and urban flooding on traffic congestion and driver behavior. In this study, a comprehensive method to analyze the influence of urban flooding on traffic congestion was developed. First, a flood simulation was conducted to predict the spatiotemporal distribution of flooding based on Storm Water Management Model (SWMM and TELAMAC-2D. Second, an agent-based model (ABM was used to simulate driver behavior during a period of urban flooding, and a car-following model was established. Finally, in order to study the mechanisms behind how urban flooding affects traffic congestion, the impact of flooding on urban traffic was investigated based on a case study of the urban area of Lishui, China, covering an area of 4.4 km2. It was found that for most events, two-hour rainfall has a certain impact on traffic congestion over a five-hour period, with the greatest impact during the hour following the cessation of the rain. Furthermore, the effects of rainfall with 10- and 20-year return periods were found to be similar and small, whereas the effects with a 50-year return period were obvious. Based on a combined analysis of hydrology and transportation, the proposed methods and conclusions could help to reduce traffic congestion during flood seasons, to facilitate early warning and risk management of urban flooding, and to assist users in making informed decisions regarding travel.

  17. A Socio-hydrological Flood Model for the Elbe

    Barendrecht, M.; Viglione, A.; Kreibich, H.; Vorogushyn, S.; Merz, B.; Bloeschl, G.

    2017-12-01

    Long-term feedbacks between humans and floods may lead to complex phenomena such as coping strategies, levee effects, call effects, adaptation effects, and poverty traps. Dynamic coupled human-flood models are a promising tool to represent such phenomena and the feedbacks leading to them. These socio-hydrological models may play an important role in integrated flood risk management when they are applied to real world case studies. They can help develop hypotheses about the phenomena that have been observed in the case study of interest, by describing the interactions between the social and hydrological variables as well as other relevant variables, such as economic, environmental, political or technical, that play a role in the system. We discuss the case of Dresden where the 2002 flood, which was preceded by a period without floods but was less severe, resulted in a higher damage than the 2013 flood, which was preceded by the 2002 flood and a couple of less severe floods. The lower damage in 2013 may be explained by the fact that society has become aware of the flood risk and has adapted to it. Developing and applying a socio-hydrological flood model to the case of Dresden can help discover whether it is possible that the lower damage is caused by an adaptation effect, or if there are other feedbacks that can explain the observed phenomenon.

  18. Urban flood simulation based on the SWMM model

    L. Jiang

    2015-05-01

    Full Text Available China is the nation with the fastest urbanization in the past decades which has caused serious urban flooding. Flood forecasting is regarded as one of the important flood mitigation methods, and is widely used in catchment flood mitigation, but is not widely used in urban flooding mitigation. This paper, employing the SWMM model, one of the widely used urban flood planning and management models, simulates the urban flooding of Dongguan City in the rapidly urbanized southern China. SWMM is first set up based on the DEM, digital map and underground pipeline network, then parameters are derived based on the properties of the subcatchment and the storm sewer conduits; the parameter sensitivity analysis shows the parameter robustness. The simulated results show that with the 1-year return period precipitation, the studied area will have no flooding, but for the 2-, 5-, 10- and 20-year return period precipitation, the studied area will be inundated. The results show the SWMM model is promising for urban flood forecasting, but as it has no surface runoff routing, the urban flooding could not be forecast precisely.

  19. The dichotomous response of flood and storm extremes to rising global temperatures

    Sharma, A.; Wasko, C.

    2017-12-01

    Rising temperature have resulted in increases in short-duration rainfall extremes across the world. Additionally it has been shown (doi:10.1038/ngeo2456) that storms will intensify, causing derived flood peaks to rise even more. This leads us to speculate that flood peaks will increase as a result, complying with the storyline presented in past IPCC reports. This talk, however, shows that changes in flood extremes are much more complex. Using global data on extreme flow events, the study conclusively shows that while the very extreme floods may be rising as a result of storm intensification, the more frequent flood events are decreasing in magnitude. The study argues that changes in the magnitude of floods are a function of changes in storm patterns and as well as pre-storm or antecedent conditions. It goes on to show that while changes in storms dominate for the most extreme events and over smaller, more urbanised catchments, changes in pre-storm conditions are the driving factor in modulating flood peaks in large rural catchments. The study concludes by providing recommendations on how future flood design should proceed, arguing that current practices (or using a design storm to estimate floods) are flawed and need changing.

  20. Simulation of the 2008 Iowa Flood using HiResFlood-UCI Model with Remote Sensing Data

    Nguyen, P.; Thorstensen, A. R.; Hsu, K. L.; AghaKouchak, A.; Sanders, B. F.; Sorooshian, S.

    2014-12-01

    Precipitation is a key forcing variable in hydrological modeling of floods and being able to accurately observe precipitation is extremely important in mitigating flood impacts. The Global Precipitation Measurement (GPM) Mission, launched in Feb 2014 also presents an opportunity for high-quality real-time precipitation data and improved flood warnings. The PERSIANN-CCS developed by the scientists at the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine is one algorithm integrated in the IMERG of PMM/GPM. In this research, the high resolution coupled hydrologic/hydraulic model named HiResFlood-UCI was applied to simulate the historical 2008 Iowa flood in the Cedar River basin. HiResFlood-UCI is a coupling of the NWS's distributed hydrologic model HL-RDHM and the hydraulic model BreZo developed by the Computational Hydraulics Group at the University of California, Irvine. The model was forced with the real-time PERSIANN-CCS and NEXRAD Stage 2 precipitation data. Simulations were evaluated based on 2 criteria: hydrographs within the basin and the areal extent of the flooding. Streamflow hydrographs were compared at 7 USGS gages, and simulated inundation maps were evaluated using USDA AWiFS 56m resolution areal flood imagery. The results show reasonable simulated hydrographs compared to USGS streamflow observations when simulating with PERSIANN-CCS and NEXRAD Stage 2 as forcing inputs. The simulation driven by NEXRAD Stage 2 slightly outperforms the PERSIANN-CCS simulation as the latter marginally underestimated the observed hydrographs. The simulation in both cases shows a good agreement (0.672 and 0.727 CSI for Stage 2 and PERSIANN-CCS simulations respectively) with the AWiFS image over the most impacted area in the Cedar Rapids region. Since the PERSIANN-CCS simulation slightly underestimated the discharge, the probability of detection (0.925) is lower than that of the Stage 2 simulation (0.965). As a trade-off, the false

  1. Modeling flood events for long-term stability

    Schruben, T.; Portillo, R.

    1985-01-01

    The primary objective for the disposal of uranium mill tailings in the Uranium Mill Tailings Remedial Action (UMTRA) Project is isolation and stabilization to prevent their misuse by man and dispersal by natural forces such as wind, rain, and flood waters (40 CFR-192). Stabilization of sites that are located in or near flood plains presents unique problems in design for long-term performance. This paper discusses the process involved with the selection and hydrologic modeling of the design flood event; and hydraulic modeling with geomorphic considerations of the design flood event. The Gunnison, Colorado, and Riverton, Wyoming, sites will be used as examples in describing the process

  2. Global Near Real-Time Satellite-based Flood Monitoring and Product Dissemination

    Smith, M.; Slayback, D. A.; Policelli, F.; Brakenridge, G. R.; Tokay, M.

    2012-12-01

    Flooding is among the most destructive, frequent, and costly natural disasters faced by modern society, with several major events occurring each year. In the past few years, major floods have devastated parts of China, Thailand, Pakistan, Australia, and the Philippines, among others. The toll of these events, in financial costs, displacement of individuals, and deaths, is substantial and continues to rise as climate change generates more extreme weather events. When these events do occur, the disaster management community requires frequently updated and easily accessible information to better understand the extent of flooding and better coordinate response efforts. With funding from NASA's Applied Sciences program, we have developed, and are now operating, a near real-time global flood mapping system to help provide critical flood extent information within 24-48 hours after flooding events. The system applies a water detection algorithm to MODIS imagery received from the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard. The LANCE system typically processes imagery in less than 3 hours after satellite overpass, and our flood mapping system can output flood products within ½ hour of acquiring the LANCE products. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows an initial assessment of flooding extent by late afternoon, every day, and more robust assessments after accumulating imagery over a longer period; the MODIS sensors are optical, so cloud cover remains an issue, which is partly overcome by using multiple looks over one or more days. Other issues include the relatively coarse scale of the MODIS imagery (250 meters), the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extents. We have made progress on some of these issues

  3. Global Delivery Models

    Manning, Stephan; Larsen, Marcus M.; Bharati, Pratyush

    2013-01-01

    This article examines antecedents and performance implications of global delivery models (GDMs) in global business services. GDMs require geographically distributed operations to exploit both proximity to clients and time-zone spread for efficient service delivery. We propose and empirically show...

  4. A global classification of coastal flood hazard climates associated with large-scale oceanographic forcing.

    Rueda, Ana; Vitousek, Sean; Camus, Paula; Tomás, Antonio; Espejo, Antonio; Losada, Inigo J; Barnard, Patrick L; Erikson, Li H; Ruggiero, Peter; Reguero, Borja G; Mendez, Fernando J

    2017-07-11

    Coastal communities throughout the world are exposed to numerous and increasing threats, such as coastal flooding and erosion, saltwater intrusion and wetland degradation. Here, we present the first global-scale analysis of the main drivers of coastal flooding due to large-scale oceanographic factors. Given the large dimensionality of the problem (e.g. spatiotemporal variability in flood magnitude and the relative influence of waves, tides and surge levels), we have performed a computer-based classification to identify geographical areas with homogeneous climates. Results show that 75% of coastal regions around the globe have the potential for very large flooding events with low probabilities (unbounded tails), 82% are tide-dominated, and almost 49% are highly susceptible to increases in flooding frequency due to sea-level rise.

  5. TWO-DIMENSIONAL MODELLING OF ACCIDENTAL FLOOD WAVES PROPAGATION

    Lorand Catalin STOENESCU

    2011-01-01

    The study presented in this article describes a modern modeling methodology of the propagation of accidental flood waves in case a dam break; this methodology is applied in Romania for the first time for the pilot project „Breaking scenarios of Poiana Uzului dam”. The calculation programs used help us obtain a bidimensional calculation (2D) of the propagation of flood waves, taking into consideration the diminishing of the flood wave on a normal direction to the main direction; this diminishi...

  6. Flash Floods Simulation using a Physical-Based Hydrological Model at Different Hydroclimatic Regions

    Saber, Mohamed; Kamil Yilmaz, Koray

    2016-04-01

    Currently, flash floods are seriously increasing and affecting many regions over the world. Therefore, this study will focus on two case studies; Wadi Abu Subeira, Egypt as arid environment, and Karpuz basin, Turkey as Mediterranean environment. The main objective of this work is to simulate flash floods at both catchments considering the hydrometeorological differences between them which in turn effect their flash flood behaviors. An integrated methodology incorporating Hydrological River Basin Environmental Assessment Model (Hydro-BEAM) and remote sensing observations was devised. Global Satellite Mapping of Precipitation (GSMAP) were compared with the rain gauge network at the target basins to estimate the bias in an effort to further use it effectively in simulation of flash floods. Based on the preliminary results of flash floods simulation on both basins, we found that runoff behaviors of flash floods are different due to the impacts of climatology, hydrological and topographical conditions. Also, the simulated surface runoff hydrographs are reasonably coincide with the simulated ones. Consequently, some mitigation strategies relying on this study could be introduced to help in reducing the flash floods disasters at different climate regions. This comparison of different climatic basins would be a reasonable implication for the potential impact of climate change on the flash floods frequencies and occurrences.

  7. Tracing the value of data for flood loss modelling

    Schröter Kai

    2016-01-01

    Full Text Available Flood loss modelling is associated with considerable uncertainty. If prediction uncertainty of flood loss models is large, the reliability of model outcomes is questionable, and thus challenges the practical usefulness. A key problem in flood loss estimation is the transfer of models to geographical regions and to flood events that may differ from the ones used for model development. Variations in local characteristics and continuous system changes require regional adjustments and continuous updating with current evidence. However, acquiring data on damage influencing factors is usually very costly. Therefore, it is of relevance to assess the value of additional data in terms of model performance improvement. We use empirical flood loss data on direct damage to residential buildings available from computer aided telephone interviews that were compiled after major floods in Germany. This unique data base allows us to trace the changes in predictive model performance by incrementally extending the data base used to derive flood loss models. Two models are considered: a uni-variable stage damage function and RF-FLEMO, a multi-variable probabilistic model approach using Random Forests. Additional data are useful to improve model predictive performance and increase model reliability, however the gains also seem to depend on the model approach.

  8. Risk-trading in flood management: An economic model.

    Chang, Chiung Ting

    2017-09-15

    Although flood management is no longer exclusively a topic of engineering, flood mitigation continues to be associated with hard engineering options. Flood adaptation or the capacity to adapt to flood risk, as well as a demand for internalizing externalities caused by flood risk between regions, complicate flood management activities. Even though integrated river basin management has long been recommended to resolve the above issues, it has proven difficult to apply widely, and sometimes even to bring into existence. This article explores how internalization of externalities as well as the realization of integrated river basin management can be encouraged via the use of a market-based approach, namely a flood risk trading program. In addition to maintaining efficiency of optimal resource allocation, a flood risk trading program may also provide a more equitable distribution of benefits by facilitating decentralization. This article employs a graphical analysis to show how flood risk trading can be implemented to encourage mitigation measures that increase infiltration and storage capacity. A theoretical model is presented to demonstrate the economic conditions necessary for flood risk trading. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Taming global flood disasters. Lessons learned from Dutch experience

    Zevenbergen, C.; Herk, S.; Rijke, J.; Kabat, P.

    2013-01-01

    There is a growing international recognition that flood risk management in optima forma should be a programmed and flexible process of continuously improving management practices by active learning about the outcome of earlier and ongoing interventions and drivers of change. In the Netherlands, such

  10. Taming global flood disasters : lessons learned from Dutch experience

    Zevenbergen, C.; Van Herk, S.; Rijke, J.S.; Kabat, P.; Bloemen, P.; Ashley, R.; Speers, A.; Gersonius, B.; Veenbeek, W.

    2012-01-01

    There is a growing international recognition that flood risk management in optima forma should be a programmed and flexible process of continuously improving management practices by active learning about the outcome of earlier and ongoing interventions and drivers of change. In the Netherlands, such

  11. Numerical Analysis of Flood modeling of upper Citarum River under Extreme Flood Condition

    Siregar, R. I.

    2018-02-01

    This paper focuses on how to approach the numerical method and computation to analyse flood parameters. Water level and flood discharge are the flood parameters solved by numerical methods approach. Numerical method performed on this paper for unsteady flow conditions have strengths and weaknesses, among others easily applied to the following cases in which the boundary irregular flow. The study area is in upper Citarum Watershed, Bandung, West Java. This paper uses computation approach with Force2 programming and HEC-RAS to solve the flow problem in upper Citarum River, to investigate and forecast extreme flood condition. Numerical analysis based on extreme flood events that have occurred in the upper Citarum watershed. The result of water level parameter modeling and extreme flood discharge compared with measurement data to analyse validation. The inundation area about flood that happened in 2010 is about 75.26 square kilometres. Comparing two-method show that the FEM analysis with Force2 programs has the best approach to validation data with Nash Index is 0.84 and HEC-RAS that is 0.76 for water level. For discharge data Nash Index obtained the result analysis use Force2 is 0.80 and with use HEC-RAS is 0.79.

  12. Comparing the Performance of Commonly Available Digital Elevation Models in GIS-based Flood Simulation

    Ybanez, R. L.; Lagmay, A. M. A.; David, C. P.

    2016-12-01

    With climatological hazards increasing globally, the Philippines is listed as one of the most vulnerable countries in the world due to its location in the Western Pacific. Flood hazards mapping and modelling is one of the responses by local government and research institutions to help prepare for and mitigate the effects of flood hazards that constantly threaten towns and cities in floodplains during the 6-month rainy season. Available digital elevation maps, which serve as the most important dataset used in 2D flood modelling, are limited in the Philippines and testing is needed to determine which of the few would work best for flood hazards mapping and modelling. Two-dimensional GIS-based flood modelling with the flood-routing software FLO-2D was conducted using three different available DEMs from the ASTER GDEM, the SRTM GDEM, and the locally available IfSAR DTM. All other parameters kept uniform, such as resolution, soil parameters, rainfall amount, and surface roughness, the three models were run over a 129-sq. kilometer watershed with only the basemap varying. The output flood hazard maps were compared on the basis of their flood distribution, extent, and depth. The ASTER and SRTM GDEMs contained too much error and noise which manifested as dissipated and dissolved hazard areas in the lower watershed where clearly delineated flood hazards should be present. Noise on the two datasets are clearly visible as erratic mounds in the floodplain. The dataset which produced the only feasible flood hazard map is the IfSAR DTM which delineates flood hazard areas clearly and properly. Despite the use of ASTER and SRTM with their published resolution and accuracy, their use in GIS-based flood modelling would be unreliable. Although not as accessible, only IfSAR or better datasets should be used for creating secondary products from these base DEM datasets. For developing countries which are most prone to hazards, but with limited choices for basemaps used in hazards

  13. Flood Inundation Modelling in the Kuantan River Basin using 1D-2D Flood Modeller coupled with ASTER-GDEM

    Ng, Z. F.; Gisen, J. I.; Akbari, A.

    2018-03-01

    Topography dataset is an important input in performing flood inundation modelling. However, it is always difficult to obtain high resolution topography that provide accurate elevation information. Fortunately, there are some open source topography datasets available with reasonable resolution such as SRTM and ASTER-GDEM. In Malaysia particularly in Kuantan, the modelling research on the floodplain area is still lacking. This research aims to: a) to investigate the suitability of ASTER-GDEM to be applied in the 1D-2D flood inundation modelling for the Kuantan River Basin; b) to generate flood inundation map for Kuantan river basin. The topography dataset used in this study is ASTER-GDEM to generate physical characteristics of watershed in the basin. It is used to perform rainfall runoff modelling for hydrological studies and to delineate flood inundation area in the Flood Modeller. The results obtained have shown that a 30m resolution ASTER-GDEM is applicable as an input for the 1D-2D flood modelling. The simulated water level in 2013 has NSE of 0.644 and RSME of 1.259. As a conclusion, ASTER-GDEM can be used as one alternative topography datasets for flood inundation modelling. However, the flood level obtained from the hydraulic modelling shows low accuracy at flat urban areas.

  14. Hydrological and hydraulic models for determination of flood-prone and flood inundation areas

    Aksoy, Hafzullah; Sadan Ozgur Kirca, Veysel; Burgan, Halil Ibrahim; Kellecioglu, Dorukhan

    2016-05-01

    Geographic Information Systems (GIS) are widely used in most studies on water resources. Especially, when the topography and geomorphology of study area are considered, GIS can ease the work load. Detailed data should be used in this kind of studies. Because of, either the complication of the models or the requirement of highly detailed data, model outputs can be obtained fast only with a good optimization. The aim in this study, firstly, is to determine flood-prone areas in a watershed by using a hydrological model considering two wetness indexes; the topographical wetness index, and the SAGA (System for Automated Geoscientific Analyses) wetness index. The wetness indexes were obtained in the Quantum GIS (QGIS) software by using the Digital Elevation Model of the study area. Flood-prone areas are determined by considering the wetness index maps of the watershed. As the second stage of this study, a hydraulic model, HEC-RAS, was executed to determine flood inundation areas under different return period-flood events. River network cross-sections required for this study were derived from highly detailed digital elevation models by QGIS. Also river hydraulic parameters were used in the hydraulic model. Modelling technology used in this study is made of freely available open source softwares. Based on case studies performed on watersheds in Turkey, it is concluded that results of such studies can be used for taking precaution measures against life and monetary losses due to floods in urban areas particularly.

  15. Hydrological and hydraulic models for determination of flood-prone and flood inundation areas

    H. Aksoy

    2016-05-01

    Full Text Available Geographic Information Systems (GIS are widely used in most studies on water resources. Especially, when the topography and geomorphology of study area are considered, GIS can ease the work load. Detailed data should be used in this kind of studies. Because of, either the complication of the models or the requirement of highly detailed data, model outputs can be obtained fast only with a good optimization. The aim in this study, firstly, is to determine flood-prone areas in a watershed by using a hydrological model considering two wetness indexes; the topographical wetness index, and the SAGA (System for Automated Geoscientific Analyses wetness index. The wetness indexes were obtained in the Quantum GIS (QGIS software by using the Digital Elevation Model of the study area. Flood-prone areas are determined by considering the wetness index maps of the watershed. As the second stage of this study, a hydraulic model, HEC-RAS, was executed to determine flood inundation areas under different return period-flood events. River network cross-sections required for this study were derived from highly detailed digital elevation models by QGIS. Also river hydraulic parameters were used in the hydraulic model. Modelling technology used in this study is made of freely available open source softwares. Based on case studies performed on watersheds in Turkey, it is concluded that results of such studies can be used for taking precaution measures against life and monetary losses due to floods in urban areas particularly.

  16. High-resolution flood modeling of urban areas using MSN_Flood

    Michael Hartnett

    2017-07-01

    Full Text Available Although existing hydraulic models have been used to simulate and predict urban flooding, most of these models are inadequate due to the high spatial resolution required to simulate flows in urban floodplains. Nesting high-resolution subdomains within coarser-resolution models is an efficient solution for enabling simultaneous calculation of flooding due to tides, surges, and high river flows. MSN_Flood has been developed to incorporate moving boundaries around nested domains, permitting alternate flooding and drying along the boundary and in the interior of the domain. Ghost cells adjacent to open boundary cells convert open boundaries, in effect, into internal boundaries. The moving boundary may be multi-segmented and non-continuous, with recirculating flow across the boundary. When combined with a bespoke adaptive interpolation scheme, this approach facilitates a dynamic internal boundary. Based on an alternating-direction semi-implicit finite difference scheme, MSN_Flood was used to hindcast a major flood event in Cork City resulting from the combined pressures of fluvial, tidal, and storm surge processes. The results show that the model is computationally efficient, as the 2-m high-resolution nest is used only in the urban flooded region. Elsewhere, lower-resolution nests are used. The results also show that the model is highly accurate when compared with measured data. The model is capable of incorporating nested sub-domains when the nested boundary is multi-segmented and highly complex with lateral gradients of elevation and velocities. This is a major benefit when modelling urban floodplains at very high resolution.

  17. Community Based Flood Modeling in Southern and Baja California to Meet End User Needs for Decision-Making

    Sanders, B. F.

    2017-12-01

    Flooding of coastal and fluvial systems are the most significant natural hazards facing society, and damages have been escalating for decades globally and in the U.S. Almost all metropolitan areas are exposed to flood risk. The threat from river flooding is especially high in India and China, and coastal cities around the world are threatened by storm surge and rising sea levels. Several trends including rising sea levels, urbanization, deforestation, and rural-to-urban population shifts will increase flood exposure in the future. Flood impacts are escalating despite advances in hazards science and extensive effort to manage risks. The fundamental issue is not that flooding is becoming more severe, even though it is in some places, but rather that societies are become more vulnerable to flood impacts. A critical factor contributing to the escalation of flood impacts is that the most vulnerable sectors of communities are left out of processes to prepare for and respond to flooding. Furthermore, the translation of knowledge about flood hazards and vulnerabilities into actionable information for communities has not been effective. In Southern and Baja California, an interdisciplinary team of researchers has partnered with stakeholders in flood vulnerable communities to co-develop flood hazard information systems designed to meet end-user needs for decision-making. The initiative leveraged the power of advanced, fine-scale hydraulic models of flooding to craft intuitive visualizations of context-sensitive scenarios. This presentation will cover the ways by which the process of flood inundation modeling served as a focal point for knowledge development, as well as the unique visualizations that populate on-line information systems accessible here: http://floodrise.uci.edu/online-flood-hazard-viewers/

  18. Global ice sheet modeling

    Hughes, T.J.; Fastook, J.L.

    1994-05-01

    The University of Maine conducted this study for Pacific Northwest Laboratory (PNL) as part of a global climate modeling task for site characterization of the potential nuclear waste respository site at Yucca Mountain, NV. The purpose of the study was to develop a global ice sheet dynamics model that will forecast the three-dimensional configuration of global ice sheets for specific climate change scenarios. The objective of the third (final) year of the work was to produce ice sheet data for glaciation scenarios covering the next 100,000 years. This was accomplished using both the map-plane and flowband solutions of our time-dependent, finite-element gridpoint model. The theory and equations used to develop the ice sheet models are presented. Three future scenarios were simulated by the model and results are discussed

  19. Flood simulation model using XP-SWMM along Terengganu River ...

    Malaysia is one of the tropical countries in the world with heavy rainfall throughout the year and floods are the most common disaster in Malaysia. Flood simulation model was carried out along Terengganu River for dry and rainy seasons. The result of the simulation shows the water level reached its maximum level at the 1st ...

  20. High-resolution urban flood modelling - a joint probability approach

    Hartnett, Michael; Olbert, Agnieszka; Nash, Stephen

    2017-04-01

    The hydrodynamic modelling of rapid flood events due to extreme climatic events in urban environment is both a complex and challenging task. The horizontal resolution necessary to resolve complexity of urban flood dynamics is a critical issue; the presence of obstacles of varying shapes and length scales, gaps between buildings and the complex geometry of the city such as slopes affect flow paths and flood levels magnitudes. These small scale processes require a high resolution grid to be modelled accurately (2m or less, Olbert et al., 2015; Hunter et al., 2008; Brown et al., 2007) and, therefore, altimetry data of at least the same resolution. Along with availability of high-resolution LiDAR data and computational capabilities, as well as state of the art nested modelling approaches, these problems can now be overcome. Flooding and drying, domain definition, frictional resistance and boundary descriptions are all important issues to be addressed when modelling urban flooding. In recent years, the number of urban flood models dramatically increased giving a good insight into various modelling problems and solutions (Mark et al., 2004; Mason et al., 2007; Fewtrell et al., 2008; Shubert et al., 2008). Despite extensive modelling work conducted for fluvial (e.g. Mignot et al., 2006; Hunter et al., 2008; Yu and Lane, 2006) and coastal mechanisms of flooding (e.g. Gallien et al., 2011; Yang et al., 2012), the amount of investigations into combined coastal-fluvial flooding is still very limited (e.g. Orton et al., 2012; Lian et al., 2013). This is surprising giving the extent of flood consequences when both mechanisms occur simultaneously, which usually happens when they are driven by one process such as a storm. The reason for that could be the fact that the likelihood of joint event is much smaller than those of any of the two contributors occurring individually, because for fast moving storms the rainfall-driven fluvial flood arrives usually later than the storm surge

  1. Flood risk and adaptation strategies under climate change and urban expansion: A probabilistic analysis using global data.

    Muis, Sanne; Güneralp, Burak; Jongman, Brenden; Aerts, Jeroen C J H; Ward, Philip J

    2015-12-15

    An accurate understanding of flood risk and its drivers is crucial for effective risk management. Detailed risk projections, including uncertainties, are however rarely available, particularly in developing countries. This paper presents a method that integrates recent advances in global-scale modeling of flood hazard and land change, which enables the probabilistic analysis of future trends in national-scale flood risk. We demonstrate its application to Indonesia. We develop 1000 spatially-explicit projections of urban expansion from 2000 to 2030 that account for uncertainty associated with population and economic growth projections, as well as uncertainty in where urban land change may occur. The projections show that the urban extent increases by 215%-357% (5th and 95th percentiles). Urban expansion is particularly rapid on Java, which accounts for 79% of the national increase. From 2000 to 2030, increases in exposure will elevate flood risk by, on average, 76% and 120% for river and coastal floods. While sea level rise will further increase the exposure-induced trend by 19%-37%, the response of river floods to climate change is highly uncertain. However, as urban expansion is the main driver of future risk, the implementation of adaptation measures is increasingly urgent, regardless of the wide uncertainty in climate projections. Using probabilistic urban projections, we show that spatial planning can be a very effective adaptation strategy. Our study emphasizes that global data can be used successfully for probabilistic risk assessment in data-scarce countries. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Towards modelling flood protection investment as a coupled human and natural system

    O'Connell, P. E.; O'Donnell, G.

    2014-01-01

    Due to a number of recent high-profile flood events and the apparent threat from global warming, governments and their agencies are under pressure to make proactive investments to protect people living in floodplains. However, adopting a proactive approach as a universal strategy is not affordable. It has been argued that delaying expensive and essentially irreversible capital decisions could be a prudent strategy in situations with high future uncertainty. This paper firstly uses Monte Carlo simulation to explore the performance of proactive and reactive investment strategies using a rational cost-benefit approach in a natural system with varying levels of persistence/interannual variability in annual maximum floods. It is found that, as persistence increases, there is a change in investment strategy optimality from proactive to reactive. This could have implications for investment strategies under the increasingly variable climate that is expected with global warming. As part of the emerging holistic approaches to flood risk management, there is increasing emphasis on stakeholder participation in determining where and when flood protection investments are made, and so flood risk management is becoming more people-centred. As a consequence, multiple actors are involved in the decision-making process, and the social sciences are assuming an increasingly important role in flood risk management. There is a need for modelling approaches which can couple the natural and human system elements. It is proposed that coupled human and natural system (CHANS) modelling could play an important role in understanding the motivations, actions and influence of citizens and institutions and how these impact on the effective delivery of flood protection investment. A framework for using agent-based modelling of human activities leading to flood investments is outlined, and some of the challenges associated with implementation are discussed.

  3. Flood damage: a model for consistent, complete and multipurpose scenarios

    Menoni, Scira; Molinari, Daniela; Ballio, Francesco; Minucci, Guido; Mejri, Ouejdane; Atun, Funda; Berni, Nicola; Pandolfo, Claudia

    2016-12-01

    Effective flood risk mitigation requires the impacts of flood events to be much better and more reliably known than is currently the case. Available post-flood damage assessments usually supply only a partial vision of the consequences of the floods as they typically respond to the specific needs of a particular stakeholder. Consequently, they generally focus (i) on particular items at risk, (ii) on a certain time window after the occurrence of the flood, (iii) on a specific scale of analysis or (iv) on the analysis of damage only, without an investigation of damage mechanisms and root causes. This paper responds to the necessity of a more integrated interpretation of flood events as the base to address the variety of needs arising after a disaster. In particular, a model is supplied to develop multipurpose complete event scenarios. The model organizes available information after the event according to five logical axes. This way post-flood damage assessments can be developed that (i) are multisectoral, (ii) consider physical as well as functional and systemic damage, (iii) address the spatial scales that are relevant for the event at stake depending on the type of damage that has to be analyzed, i.e., direct, functional and systemic, (iv) consider the temporal evolution of damage and finally (v) allow damage mechanisms and root causes to be understood. All the above features are key for the multi-usability of resulting flood scenarios. The model allows, on the one hand, the rationalization of efforts currently implemented in ex post damage assessments, also with the objective of better programming financial resources that will be needed for these types of events in the future. On the other hand, integrated interpretations of flood events are fundamental to adapting and optimizing flood mitigation strategies on the basis of thorough forensic investigation of each event, as corroborated by the implementation of the model in a case study.

  4. Flood Modelling of Banjir Kanal Barat (Integration of Hydrology Model and GIS

    Muhammad Aris Marfai

    2004-01-01

    Full Text Available Hydrological modelling has an advantage on river flood study. Hydrological factors can be easily determined and calculated using hydrological model. HEC-RAS (Hydrological Engineering Centre-River Analysis System software is well known as hydrological modelling software for flood simulation and encroachment analysis of the floodplain area. For spatial performance and analysis of flood, the integration of the Geographic Information Systems (GIS and hydrological model is needed. The aims of this research are 1 to perform a flood encroachment using HEC-RAS software, and 2 to generate a flood hazard map. The methodology for this research omprise of 1 generating geometric data as a requirement of the data input on HEC-RAS hydrological model, 2 Hydrological data inputting, 3 generating of the flood encroachment analysis, and 4 transformation of flood encroachment into flood hazard map. The spatial pattern of the flood hazard is illustrated in a map. The result shows that hydrological model as integration with GIS can be used for flood hazard map generation. This method has advantages on the calculation of the hydrological factors of flood and spatial performance of the flood hazard map. For further analysis, the landuse map can be used on the overlay operation with the flood hazard map in order to obtain the impact of the flood on the landuse.

  5. Combining Satellite Measurements and Numerical Flood Prediction Models to Save Lives and Property from Flooding

    Saleh, F.; Garambois, P. A.; Biancamaria, S.

    2017-12-01

    Floods are considered the major natural threats to human societies across all continents. Consequences of floods in highly populated areas are more dramatic with losses of human lives and substantial property damage. This risk is projected to increase with the effects of climate change, particularly sea-level rise, increasing storm frequencies and intensities and increasing population and economic assets in such urban watersheds. Despite the advances in computational resources and modeling techniques, significant gaps exist in predicting complex processes and accurately representing the initial state of the system. Improving flood prediction models and data assimilation chains through satellite has become an absolute priority to produce accurate flood forecasts with sufficient lead times. The overarching goal of this work is to assess the benefits of the Surface Water Ocean Topography SWOT satellite data from a flood prediction perspective. The near real time methodology is based on combining satellite data from a simulator that mimics the future SWOT data, numerical models, high resolution elevation data and real-time local measurement in the New York/New Jersey area.

  6. Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

    Hasanzadeh Nafari, Roozbeh; Amadio, Mattia; Ngo, Tuan; Mysiak, Jaroslav

    2017-07-01

    The damage triggered by different flood events costs the Italian economy millions of euros each year. This cost is likely to increase in the future due to climate variability and economic development. In order to avoid or reduce such significant financial losses, risk management requires tools which can provide a reliable estimate of potential flood impacts across the country. Flood loss functions are an internationally accepted method for estimating physical flood damage in urban areas. In this study, we derived a new flood loss function for Italian residential structures (FLF-IT), on the basis of empirical damage data collected from a recent flood event in the region of Emilia-Romagna. The function was developed based on a new Australian approach (FLFA), which represents the confidence limits that exist around the parameterized functional depth-damage relationship. After model calibration, the performance of the model was validated for the prediction of loss ratios and absolute damage values. It was also contrasted with an uncalibrated relative model with frequent usage in Europe. In this regard, a three-fold cross-validation procedure was carried out over the empirical sample to measure the range of uncertainty from the actual damage data. The predictive capability has also been studied for some sub-classes of water depth. The validation procedure shows that the newly derived function performs well (no bias and only 10 % mean absolute error), especially when the water depth is high. Results of these validation tests illustrate the importance of model calibration. The advantages of the FLF-IT model over other Italian models include calibration with empirical data, consideration of the epistemic uncertainty of data, and the ability to change parameters based on building practices across Italy.

  7. Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures

    R. Hasanzadeh Nafari

    2017-07-01

    Full Text Available The damage triggered by different flood events costs the Italian economy millions of euros each year. This cost is likely to increase in the future due to climate variability and economic development. In order to avoid or reduce such significant financial losses, risk management requires tools which can provide a reliable estimate of potential flood impacts across the country. Flood loss functions are an internationally accepted method for estimating physical flood damage in urban areas. In this study, we derived a new flood loss function for Italian residential structures (FLF-IT, on the basis of empirical damage data collected from a recent flood event in the region of Emilia-Romagna. The function was developed based on a new Australian approach (FLFA, which represents the confidence limits that exist around the parameterized functional depth–damage relationship. After model calibration, the performance of the model was validated for the prediction of loss ratios and absolute damage values. It was also contrasted with an uncalibrated relative model with frequent usage in Europe. In this regard, a three-fold cross-validation procedure was carried out over the empirical sample to measure the range of uncertainty from the actual damage data. The predictive capability has also been studied for some sub-classes of water depth. The validation procedure shows that the newly derived function performs well (no bias and only 10 % mean absolute error, especially when the water depth is high. Results of these validation tests illustrate the importance of model calibration. The advantages of the FLF-IT model over other Italian models include calibration with empirical data, consideration of the epistemic uncertainty of data, and the ability to change parameters based on building practices across Italy.

  8. Floods in a changing climate

    Theresa K. Andersen; Marshall J. Shepherd

    2013-01-01

    Atmospheric warming and associated hydrological changes have implications for regional flood intensity and frequency. Climate models and hydrological models have the ability to integrate various contributing factors and assess potential changes to hydrology at global to local scales through the century. This survey of floods in a changing climate reviews flood...

  9. Two-dimensional Model of Ciliwung River Flood in DKI Jakarta for Development of the Regional Flood Index Map

    Adam Formánek

    2013-12-01

    Full Text Available The objective of this study was to present a sophisticated method of developing supporting material for flood control implementation in DKI Jakarta. High flow rates in the Ciliwung River flowing through Jakarta regularly causes extensive flooding in the rainy season. The affected area comprises highly densely populated villages. For developing an efficient early warning system in view of decreasing the vulnerability of the locations a flood index map has to be available. This study analyses the development of a flood risk map of the inundation area based on a two-dimensional modeling using FESWMS. The reference event used for the model was the most recent significant flood in 2007. The resulting solution represents flood characteristics such as inundation area, inundation depth and flow velocity. Model verification was performed by confrontation of the results with survey data. The model solution was overlaid with a street map of Jakarta. Finally, alternatives for flood mitigation measures are discussed.

  10. Simulated CONUS Flash Flood Climatologies from Distributed Hydrologic Models

    Flamig, Z.; Gourley, J. J.; Vergara, H. J.; Kirstetter, P. E.; Hong, Y.

    2016-12-01

    This study will describe a CONUS flash flood climatology created over the period from 2002 through 2011. The MRMS reanalysis precipitation dataset was used as forcing into the Ensemble Framework For Flash Flood Forecasting (EF5). This high resolution 1-sq km 5-minute dataset is ideal for simulating flash floods with a distributed hydrologic model. EF5 features multiple water balance components including SAC-SMA, CREST, and a hydrophobic model all coupled with kinematic wave routing. The EF5/SAC-SMA and EF5/CREST water balance schemes were used for the creation of dual flash flood climatologies based on the differing water balance principles. For the period from 2002 through 2011 the daily maximum streamflow, unit streamflow, and time of peak streamflow was stored along with the minimum soil moisture. These variables are used to describe the states of the soils right before a flash flood event and the peak streamflow that was simulated during the flash flood event. The results will be shown, compared and contrasted. The resulting model simulations will be verified on basins less than 1,000-sq km with USGS gauges to ensure the distributed hydrologic models are reliable. The results will also be compared spatially to Storm Data flash flood event observations to judge the degree of agreement between the simulated climatologies and observations.

  11. TWO-DIMENSIONAL MODELLING OF ACCIDENTAL FLOOD WAVES PROPAGATION

    Lorand Catalin STOENESCU

    2011-05-01

    Full Text Available The study presented in this article describes a modern modeling methodology of the propagation of accidental flood waves in case a dam break; this methodology is applied in Romania for the first time for the pilot project „Breaking scenarios of Poiana Uzului dam”. The calculation programs used help us obtain a bidimensional calculation (2D of the propagation of flood waves, taking into consideration the diminishing of the flood wave on a normal direction to the main direction; this diminishing of the flood wave is important in the case of sinuous courses of water or with urban settlements very close to the minor river bed. In the case of Poiana Uzului dam, 2 scenarios were simulated with the help of Ph.D. Eng. Dan Stematiu, plausible scenarios but with very little chances of actually producing. The results were presented as animations with flooded surfaces at certain time steps successively.

  12. On the performance of satellite precipitation products in riverine flood modeling: A review

    Maggioni, Viviana; Massari, Christian

    2018-03-01

    This work is meant to summarize lessons learned on using satellite precipitation products for riverine flood modeling and to propose future directions in this field of research. Firstly, the most common satellite precipitation products (SPPs) during the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) eras are reviewed. Secondly, we discuss the main errors and uncertainty sources in these datasets that have the potential to affect streamflow and runoff model simulations. Thirdly, past studies that focused on using SPPs for predicting streamflow and runoff are analyzed. As the impact of floods depends not only on the characteristics of the flood itself, but also on the characteristics of the region (population density, land use, geophysical and climatic factors), a regional analysis is required to assess the performance of hydrologic models in monitoring and predicting floods. The performance of SPP-forced hydrological models was shown to largely depend on several factors, including precipitation type, seasonality, hydrological model formulation, topography. Across several basins around the world, the bias in SPPs was recognized as a major issue and bias correction methods of different complexity were shown to significantly reduce streamflow errors. Model re-calibration was also raised as a viable option to improve SPP-forced streamflow simulations, but caution is necessary when recalibrating models with SPP, which may result in unrealistic parameter values. From a general standpoint, there is significant potential for using satellite observations in flood forecasting, but the performance of SPP in hydrological modeling is still inadequate for operational purposes.

  13. Application of BP Neural Network Algorithm in Traditional Hydrological Model for Flood Forecasting

    Jianjin Wang

    2017-01-01

    Full Text Available Flooding contributes to tremendous hazards every year; more accurate forecasting may significantly mitigate the damages and loss caused by flood disasters. Current hydrological models are either purely knowledge-based or data-driven. A combination of data-driven method (artificial neural networks in this paper and knowledge-based method (traditional hydrological model may booster simulation accuracy. In this study, we proposed a new back-propagation (BP neural network algorithm and applied it in the semi-distributed Xinanjiang (XAJ model. The improved hydrological model is capable of updating the flow forecasting error without losing the leading time. The proposed method was tested in a real case study for both single period corrections and real-time corrections. The results reveal that the proposed method could significantly increase the accuracy of flood forecasting and indicate that the global correction effect is superior to the second-order autoregressive correction method in real-time correction.

  14. Regionalizing global climate models

    Pitman, A.J.; Arneth, A.; Ganzeveld, L.N.

    2012-01-01

    Global climate models simulate the Earth's climate impressively at scales of continents and greater. At these scales, large-scale dynamics and physics largely define the climate. At spatial scales relevant to policy makers, and to impacts and adaptation, many other processes may affect regional and

  15. Hierarchical Modelling of Flood Risk for Engineering Decision Analysis

    Custer, Rocco

    protection structures in the hierarchical flood protection system - is identified. To optimise the design of protection structures, fragility and vulnerability models must allow for consideration of decision alternatives. While such vulnerability models are available for large protection structures (e...... systems, as well as the implementation of the flood risk analysis methodology and the vulnerability modelling approach are illustrated with an example application. In summary, the present thesis provides a characterisation of hierarchical flood protection systems as well as several methodologies to model...... and robust. Traditional risk management solutions, e.g. dike construction, are not particularly flexible, as they are difficult to adapt to changing risk. Conversely, the recent concept of integrated flood risk management, entailing a combination of several structural and non-structural risk management...

  16. Modeling Wettability Variation during Long-Term Water Flooding

    Renyi Cao

    2015-01-01

    Full Text Available Surface property of rock affects oil recovery during water flooding. Oil-wet polar substances adsorbed on the surface of the rock will gradually be desorbed during water flooding, and original reservoir wettability will change towards water-wet, and the change will reduce the residual oil saturation and improve the oil displacement efficiency. However there is a lack of an accurate description of wettability alternation model during long-term water flooding and it will lead to difficulties in history match and unreliable forecasts using reservoir simulators. This paper summarizes the mechanism of wettability variation and characterizes the adsorption of polar substance during long-term water flooding from injecting water or aquifer and relates the residual oil saturation and relative permeability to the polar substance adsorbed on clay and pore volumes of flooding water. A mathematical model is presented to simulate the long-term water flooding and the model is validated with experimental results. The simulation results of long-term water flooding are also discussed.

  17. Flooding Experiments and Modeling for Improved Reactor Safety

    Solmos, M.; Hogan, K.J.; VIerow, K.

    2008-01-01

    Countercurrent two-phase flow and 'flooding' phenomena in light water reactor systems are being investigated experimentally and analytically to improve reactor safety of current and future reactors. The aspects that will be better clarified are the effects of condensation and tube inclination on flooding in large diameter tubes. The current project aims to improve the level of understanding of flooding mechanisms and to develop an analysis model for more accurate evaluations of flooding in the pressurizer surge line of a Pressurized Water Reactor (PWR). Interest in flooding has recently increased because Countercurrent Flow Limitation (CCFL) in the AP600 pressurizer surge line can affect the vessel refill rate following a small break LOCA and because analysis of hypothetical severe accidents with the current flooding models in reactor safety codes shows that these models represent the largest uncertainty in analysis of steam generator tube creep rupture. During a hypothetical station blackout without auxiliary feedwater recovery, should the hot leg become voided, the pressurizer liquid will drain to the hot leg and flooding may occur in the surge line. The flooding model heavily influences the pressurizer emptying rate and the potential for surge line structural failure due to overheating and creep rupture. The air-water test results in vertical tubes are presented in this paper along with a semi-empirical correlation for the onset of flooding. The unique aspects of the study include careful experimentation on large-diameter tubes and an integrated program in which air-water testing provides benchmark knowledge and visualization data from which to conduct steam-water testing

  18. Potential of 3D City Models to assess flood vulnerability

    Schröter, Kai; Bochow, Mathias; Schüttig, Martin; Nagel, Claus; Ross, Lutz; Kreibich, Heidi

    2016-04-01

    Vulnerability, as the product of exposure and susceptibility, is a key factor of the flood risk equation. Furthermore, the estimation of flood loss is very sensitive to the choice of the vulnerability model. Still, in contrast to elaborate hazard simulations, vulnerability is often considered in a simplified manner concerning the spatial resolution and geo-location of exposed objects as well as the susceptibility of these objects at risk. Usually, area specific potential flood loss is quantified on the level of aggregated land-use classes, and both hazard intensity and resistance characteristics of affected objects are represented in highly simplified terms. We investigate the potential of 3D City Models and spatial features derived from remote sensing data to improve the differentiation of vulnerability in flood risk assessment. 3D City Models are based on CityGML, an application scheme of the Geography Markup Language (GML), which represents the 3D geometry, 3D topology, semantics and appearance of objects on different levels of detail. As such, 3D City Models offer detailed spatial information which is useful to describe the exposure and to characterize the susceptibility of residential buildings at risk. This information is further consolidated with spatial features of the building stock derived from remote sensing data. Using this database a spatially detailed flood vulnerability model is developed by means of data-mining. Empirical flood damage data are used to derive and to validate flood susceptibility models for individual objects. We present first results from a prototype application in the city of Dresden, Germany. The vulnerability modeling based on 3D City Models and remote sensing data is compared i) to the generally accepted good engineering practice based on area specific loss potential and ii) to a highly detailed representation of flood vulnerability based on a building typology using urban structure types. Comparisons are drawn in terms of

  19. Urban flood return period assessment through rainfall-flood response modelling

    Murla Tuyls, Damian; Thorndahl, Søren

    2017-04-01

    Intense rainfall can often cause severe floods, especially in urbanized areas, where population density or large impermeable areas are found. In this context, floods can generate a direct impact in a social-environmental-economic viewpoint. Traditionally, in design of Urban Drainage Systems (UDS), correlation between return period (RP) of a given rainfall and RP of its consequent flood has been assumed to be linear (e.g. DS/EN752 (2008)). However, this is not always the case. Complex UDS, where diverse hydraulic infrastructures are often found, increase the heterogeneity of system response, which may cause an alteration of the mentioned correlation. Consequently, reliability on future urban planning, design and resilience against floods may be also affected by this misassumption. In this study, an assessment of surface flood RP across rainfall RP has been carried out at Lystrup, a urbanized catchment area of 440ha and 10.400inhab. located in Jutland (Denmark), which has received the impact of several pluvial flooding in the last recent years. A historical rainfall dataset from the last 35 years from two different rain gauges located at 2 and 10 km from the study area has been provided by the Danish Wastewater Pollution Committee and the Danish Meteorological Institute (DMI). The most extreme 25 rainfall events have been selected through a two-step multi-criteria procedure, ensuring an adequate variability of rainfall, from extreme high peak storms with a short duration to moderate rainfall with longer duration. In addition, a coupled 1D/2D surface and network UDS model of the catchment area developed in an integrated MIKE URBAN and MIKE Flood model (DHI 2014), considering both permeable and impermeable areas, in combination with a DTM (2x2m res.) has been used to study and assess in detail flood RP. Results show an ambiguous relation between rainfall RP and flood response. Local flood levels, flood area and volume RP estimates should therefore not be neglected in

  20. Appropriate modelling of climate change impacts on river flooding

    Booij, Martijn J.

    2002-01-01

    Global climate change is likely to increase temperatures, change precipitation patterns and probably raise the frequency of extreme events. Impacts of climate change on river flooding may be considerable and may cause enormous economical, social and environmental damage and even loss of lives. This

  1. Flood damage in Italy: towards an assessment model of reconstruction costs

    Sterlacchini, Simone; Zazzeri, Marco; Genovese, Elisabetta; Modica, Marco; Zoboli, Roberto

    2016-04-01

    Recent decades in Italy have seen a very rapid expansion of urbanisation in terms of physical assets, while demographics have remained stable. Both the characteristics of Italian soil and anthropic development, along with repeated global climatic stress, have made the country vulnerable to floods, the intensity of which is increasingly alarming. The combination of these trends will contribute to large financial losses due to property damage in the absence of specific mitigation strategies. The present study focuses on the province of Sondrio in Northern Italy (area of about 3,200 km²), which is home to more than 180,000 inhabitants and the population is growing slightly. It is clearly a hot spot for flood exposure, as it is primarily a mountainous area where floods and flash floods hit frequently. The model we use for assessing potential flood damage determines risk scenarios by overlaying flood hazard maps and economic asset data. In Italy, hazard maps are provided by Regional Authorities through the Hydrogeological System Management Plan (PAI) based on EU Flood Directive guidelines. The PAI in the study area includes both the large plain and the secondary river system and considers three hazard scenarios of Low, Medium and High Frequency associated with return periods of 20, 200 and 500 years and related water levels. By an overlay of PAI maps and residential areas, visualized on a GIS, we determine which existing built-up areas are at risk for flood according to each scenario. Then we investigate the value of physical assets potentially affected by floods in terms of market values, using the database of the Italian Property Market Observatory (OMI), and in terms of reconstruction costs, by considering synthetic cost indexes of predominant building types (from census information) and PAI water height. This study illustrates a methodology to assess flood damage in urban settlements and aims to determine general guidelines that can be extended throughout Italy

  2. Global Hail Model

    Werner, A.; Sanderson, M.; Hand, W.; Blyth, A.; Groenemeijer, P.; Kunz, M.; Puskeiler, M.; Saville, G.; Michel, G.

    2012-04-01

    Hail risk models are rare for the insurance industry. This is opposed to the fact that average annual hail losses can be large and hail dominates losses for many motor portfolios worldwide. Insufficient observational data, high spatio-temporal variability and data inhomogenity have hindered creation of credible models so far. In January 2012, a selected group of hail experts met at Willis in London in order to discuss ways to model hail risk at various scales. Discussions aimed at improving our understanding of hail occurrence and severity, and covered recent progress in the understanding of microphysical processes and climatological behaviour and hail vulnerability. The final outcome of the meeting was the formation of a global hail risk model initiative and the launch of a realistic global hail model in order to assess hail loss occurrence and severities for the globe. The following projects will be tackled: Microphysics of Hail and hail severity measures: Understand the physical drivers of hail and hailstone size development in different regions on the globe. Proposed factors include updraft and supercooled liquid water content in the troposphere. What are the thresholds drivers of hail formation around the globe? Hail Climatology: Consider ways to build a realistic global climatological set of hail events based on physical parameters including spatial variations in total availability of moisture, aerosols, among others, and using neural networks. Vulnerability, Exposure, and financial model: Use historical losses and event footprints available in the insurance market to approximate fragility distributions and damage potential for various hail sizes for property, motor, and agricultural business. Propagate uncertainty distributions and consider effects of policy conditions along with aggregating and disaggregating exposure and losses. This presentation provides an overview of ideas and tasks that lead towards a comprehensive global understanding of hail risk for

  3. Modelling the interaction between flooding events and economic growth

    Grames, Johanna; Fürnkranz-Prskawetz, Alexia; Grass, Dieter; Viglione, Alberto; Blöschl, Günter

    2016-04-01

    Recently socio-hydrology models have been proposed to analyze the interplay of community risk-coping culture, flooding damage and economic growth. These models descriptively explain the feedbacks between socio-economic development and natural disasters such as floods. Complementary to these descriptive models, we develop a dynamic optimization model, where the inter-temporal decision of an economic agent interacts with the hydrological system. This interdisciplinary approach matches with the goals of Panta Rhei i.e. to understand feedbacks between hydrology and society. It enables new perspectives but also shows limitations of each discipline. Young scientists need mentors from various scientific backgrounds to learn their different research approaches and how to best combine them such that interdisciplinary scientific work is also accepted by different science communities. In our socio-hydrology model we apply a macro-economic decision framework to a long-term flood-scenario. We assume a standard macro-economic growth model where agents derive utility from consumption and output depends on physical capital that can be accumulated through investment. To this framework we add the occurrence of flooding events which will destroy part of the capital. We identify two specific periodic long term solutions and denote them rich and poor economies. Whereas rich economies can afford to invest in flood defense and therefore avoid flood damage and develop high living standards, poor economies prefer consumption instead of investing in flood defense capital and end up facing flood damages every time the water level rises. Nevertheless, they manage to sustain at least a low level of physical capital. We identify optimal investment strategies and compare simulations with more frequent and more intense high water level events.

  4. Surrogate modeling of joint flood risk across coastal watersheds

    Bass, Benjamin; Bedient, Philip

    2018-03-01

    This study discusses the development and performance of a rapid prediction system capable of representing the joint rainfall-runoff and storm surge flood response of tropical cyclones (TCs) for probabilistic risk analysis. Due to the computational demand required for accurately representing storm surge with the high-fidelity ADvanced CIRCulation (ADCIRC) hydrodynamic model and its coupling with additional numerical models to represent rainfall-runoff, a surrogate or statistical model was trained to represent the relationship between hurricane wind- and pressure-field characteristics and their peak joint flood response typically determined from physics based numerical models. This builds upon past studies that have only evaluated surrogate models for predicting peak surge, and provides the first system capable of probabilistically representing joint flood levels from TCs. The utility of this joint flood prediction system is then demonstrated by improving upon probabilistic TC flood risk products, which currently account for storm surge but do not take into account TC associated rainfall-runoff. Results demonstrate the source apportionment of rainfall-runoff versus storm surge and highlight that slight increases in flood risk levels may occur due to the interaction between rainfall-runoff and storm surge as compared to the Federal Emergency Management Association's (FEMAs) current practices.

  5. Quantifying invertebrate resistance to floods: a global-scale meta-analysis.

    McMullen, Laura E; Lytle, David A

    2012-12-01

    Floods are a key component of the ecology and management of riverine ecosystems around the globe, but it is not clear whether floods have predictable effects on organisms that can allow us to generalize across regions and continents. To address this, we conducted a global-scale meta-analysis to investigate effects of natural and managed floods on invertebrate resistance, the ability of invertebrates to survive flood events. We considered 994 studies for inclusion in the analysis, and after evaluation based on a priori criteria, narrowed our analysis to 41 studies spanning six of the seven continents. We used the natural-log-ratio of invertebrate abundance before and within 10 days after flood events because this measure of effect size can be directly converted to estimates of percent survival. We conducted categorical and continuous analyses that examined the contribution of environmental and study design variables to effect size heterogeneity, and examined differences in effect size among taxonomic groups. We found that invertebrate abundance was lowered by at least one-half after flood events. While natural vs. managed floods were similar in their effect, effect size differed among habitat and substrate types, with pools, sand, and boulders experiencing the strongest effect. Although sample sizes were not sufficient to examine all taxonomic groups, floods had a significant, negative effect on densities of Coleoptera, Eumalacostraca, Annelida, Ephemeroptera, Diptera, Plecoptera, and Trichoptera. Results from this study provide guidance for river flow regime prescriptions that will be applicable across continents and climate types, as well as baseline expectations for future empirical studies of freshwater disturbance.

  6. Global, Daily, Near Real-Time Satellite-based Flood Monitoring and Product Dissemination

    Slayback, D. A.; Policelli, F. S.; Brakenridge, G. R.; Tokay, M. M.; Smith, M. M.; Kettner, A. J.

    2013-12-01

    Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is expected to increase in frequency and damage with climate change and population growth. Some of 2013's major floods have impacted the New York City region, the Midwest, Alberta, Australia, various parts of China, Thailand, Pakistan, and central Europe. The toll of these events, in financial costs, displacement of individuals, and deaths, is substantial and continues to rise as climate change generates more extreme weather events. When these events do occur, the disaster management community requires frequently updated and easily accessible information to better understand the extent of flooding and better coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide critical flood extent information within 24-48 hours of events. The system applies a water detection algorithm to MODIS imagery received from the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows an initial daily assessment of flooding extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters), the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extents. We have made progress on many of these issues, and are working to develop higher resolution flood detection using alternate sensors, including Landsat and various radar sensors. Although these

  7. Assessment of channel changes, model of historical floods, and effects of backwater on flood stage, and flood mitigation alternatives for the Wichita River at Wichita Falls, Texas

    Winters, Karl E.; Baldys, Stanley

    2011-01-01

    In cooperation with the City of Wichita Falls, the U.S. Geological Survey assessed channel changes on the Wichita River at Wichita Falls, Texas, and modeled historical floods to investigate possible causes and potential mitigation alternatives to higher flood stages in recent (2007 and 2008) floods. Extreme flooding occurred on the Wichita River on June 30, 2007, inundating 167 homes in Wichita Falls. Although a record flood stage was reached in June 2007, the peak discharge was much less than some historical floods at Wichita Falls. Streamflow and stage data from two gages on the Wichita River and one on Holliday Creek were used to assess the interaction of the two streams. Changes in the Wichita River channel were evaluated using historical aerial and ground photography, comparison of recent and historical cross sections, and comparison of channel roughness coefficients with those from earlier studies. The floods of 2007 and 2008 were modeled using a one-dimensional step-backwater model. Calibrated channel roughness was larger for the 2007 flood compared to the 2008 flood, and the 2007 flood peaked about 4 feet higher than the 2008 flood. Calibration of the 1941 flood yielded a channel roughness coefficient (Manning's n) of 0.030, which represents a fairly clean natural channel. The step-backwater model was also used to evaluate the following potential mitigation alternatives: (1) increasing the capacity of the bypass channel near River Road in Wichita Falls, Texas; (2) removal of obstructions near the Scott Avenue and Martin Luther King Junior Boulevard bridges in Wichita Falls, Texas; (3) widening of aggraded channel banks in the reach between Martin Luther King Junior Boulevard and River Road; and (4) reducing channel bank and overbank roughness. Reductions in water-surface elevations ranged from 0.1 foot to as much as 3.0 feet for the different mitigation alternatives. The effects of implementing a combination of different flood-mitigation alternatives were

  8. Challenges of Modeling Flood Risk at Large Scales

    Guin, J.; Simic, M.; Rowe, J.

    2009-04-01

    Flood risk management is a major concern for many nations and for the insurance sector in places where this peril is insured. A prerequisite for risk management, whether in the public sector or in the private sector is an accurate estimation of the risk. Mitigation measures and traditional flood management techniques are most successful when the problem is viewed at a large regional scale such that all inter-dependencies in a river network are well understood. From an insurance perspective the jury is still out there on whether flood is an insurable peril. However, with advances in modeling techniques and computer power it is possible to develop models that allow proper risk quantification at the scale suitable for a viable insurance market for flood peril. In order to serve the insurance market a model has to be event-simulation based and has to provide financial risk estimation that forms the basis for risk pricing, risk transfer and risk management at all levels of insurance industry at large. In short, for a collection of properties, henceforth referred to as a portfolio, the critical output of the model is an annual probability distribution of economic losses from a single flood occurrence (flood event) or from an aggregation of all events in any given year. In this paper, the challenges of developing such a model are discussed in the context of Great Britain for which a model has been developed. The model comprises of several, physically motivated components so that the primary attributes of the phenomenon are accounted for. The first component, the rainfall generator simulates a continuous series of rainfall events in space and time over thousands of years, which are physically realistic while maintaining the statistical properties of rainfall at all locations over the model domain. A physically based runoff generation module feeds all the rivers in Great Britain, whose total length of stream links amounts to about 60,000 km. A dynamical flow routing

  9. FLOOD HAZARD MAP IN THE CITY OF BATNA (ALGERIA BY HYDRAULIC MODELING APPROCH

    Guellouh SAMI

    2016-06-01

    Full Text Available In the light of the global climatic changes that appear to influence the frequency and the intensity of floods, and whose damages are still growing; understanding the hydrological processes, their spatiotemporal setting and their extreme shape, became a paramount concern to local communities in forecasting terms. The aim of this study is to map the floods hazard using a hydraulic modeling method. In fact, using the operating Geographic Information System (GIS, would allow us to perform a more detailed spatial analysis about the extent of the flooding risk, through the approval of the hydraulic modeling programs in different frequencies. Based on the results of this analysis, decision makers can implement a strategy of risk management related to rivers overflowing through the city of Batna.

  10. Coping with Future Coastal Floods in Denmark—Advancing the Use of Global Frameworks

    Jebens, Martin; Sørensen, Carlo Sass

    2017-01-01

    The main aim of Disaster Risk Management and Climate Change Adaptation is to lower the risk for the population and the society at large. Risk assessments constitute an important part of flood risk management and their quality is crucial to well-informed decision making. This requires an in......-depth understanding of the society and its vulnerabilities. Often attention to the flood risk and vulnerability in developed countries is absent due to the assumption that society can cope with disaster; For Denmark, a mixed methods’ research inquiry reveals that this is not always the case. In a critique of current...... Danish approaches to deal with Disaster Risk Management and Climate Change Adaptation including coordination and planning, the paper proposes a new pathway for coping with the risks of coastal floods: Global frameworks like the Hyogo and Sendai tailored to suit Danish conditions may serve to mainstream...

  11. Global Near Real-Time MODIS and Landsat Flood Mapping and Product Delivery

    Policelli, F. S.; Slayback, D. A.; Tokay, M. M.; Brakenridge, G. R.

    2014-12-01

    Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is increasing in frequency and damage (deaths, displacements, and financial costs) as populations increase and climate change generates more extreme weather events. When major flooding events occur, the disaster management community needs frequently updated and easily accessible information to better understand the extent of flooding and coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide flood extent information within 24-48 hours of events. The principal element of the system applies a water detection algorithm to MODIS imagery, which is processed by the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows the system to deliver an initial daily assessment of flood extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters) for some events, the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extent. We are working on improvements to address these limitations. We have also begun delivery of near real time water maps at 30 m resolution from Landsat imagery. Although Landsat is not available daily globally, but only every 8 days if imagery from both operating platforms (Landsat 7 and 8) is accessed, it can provide useful higher resolution data on water extent when a clear acquisition coincides with an active

  12. Probabilistic, multi-variate flood damage modelling using random forests and Bayesian networks

    Kreibich, Heidi; Schröter, Kai

    2015-04-01

    Decisions on flood risk management and adaptation are increasingly based on risk analyses. Such analyses are associated with considerable uncertainty, even more if changes in risk due to global change are expected. Although uncertainty analysis and probabilistic approaches have received increased attention recently, they are hardly applied in flood damage assessments. Most of the damage models usually applied in standard practice have in common that complex damaging processes are described by simple, deterministic approaches like stage-damage functions. This presentation will show approaches for probabilistic, multi-variate flood damage modelling on the micro- and meso-scale and discuss their potential and limitations. Reference: Merz, B.; Kreibich, H.; Lall, U. (2013): Multi-variate flood damage assessment: a tree-based data-mining approach. NHESS, 13(1), 53-64. Schröter, K., Kreibich, H., Vogel, K., Riggelsen, C., Scherbaum, F., Merz, B. (2014): How useful are complex flood damage models? - Water Resources Research, 50, 4, p. 3378-3395.

  13. Modelling the interaction between flooding events and economic growth

    Grames, Johanna; Grass, Dieter; Prskawetz, Alexia; Blöschl, Günther

    2015-04-01

    Socio-hydrology describes the interaction between the socio-economy, water and population dynamics. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre, 2013, Viglione, 2014). These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. This is the first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events: Investments in defense capital can avoid floods even when the water level is high, but on the other hand such investment competes with investment in productive capital and hence may reduce the level of consumption. When floods occur, the flood damage therefore depends on the existing defense capital. The aim is to find an optimal tradeoff between investments in productive versus defense capital such as to optimize the stream of consumption in the long-term. We assume a non-autonomous exogenous periodic rainfall function (Yevjevich et.al. 1990, Zakaria 2001) which implies that the long-term equilibrium will be periodic . With our model we aim to derive mechanisms that allow consumption smoothing in the long term, and at the same time allow for optimal investment in flood defense to maximize economic output. We choose an aggregate welfare function that depends on the consumption level of the society as the objective function. I.e. we assume a social planer with perfect foresight that maximizes the aggregate welfare function. Within our model framework we can also study whether the path and level of defense capital (that protects people from floods) is related to the time preference rate of the social planner. Our model also allows to investigate how the frequency

  14. Development of flood index by characterisation of flood hydrographs

    Bhattacharya, Biswa; Suman, Asadusjjaman

    2015-04-01

    In recent years the world has experienced deaths, large-scale displacement of people, billions of Euros of economic damage, mental stress and ecosystem impacts due to flooding. Global changes (climate change, population and economic growth, and urbanisation) are exacerbating the severity of flooding. The 2010 floods in Pakistan and the 2011 floods in Australia and Thailand demonstrate the need for concerted action in the face of global societal and environmental changes to strengthen resilience against flooding. Due to climatological characteristics there are catchments where flood forecasting may have a relatively limited role and flood event management may have to be trusted upon. For example, in flash flood catchments, which often may be tiny and un-gauged, flood event management often depends on approximate prediction tools such as flash flood guidance (FFG). There are catchments fed largely by flood waters coming from upstream catchments, which are un-gauged or due to data sharing issues in transboundary catchments the flow of information from upstream catchment is limited. Hydrological and hydraulic modelling of these downstream catchments will never be sufficient to provide any required forecasting lead time and alternative tools to support flood event management will be required. In FFG, or similar approaches, the primary motif is to provide guidance by synthesising the historical data. We follow a similar approach to characterise past flood hydrographs to determine a flood index (FI), which varies in space and time with flood magnitude and its propagation. By studying the variation of the index the pockets of high flood risk, requiring attention, can be earmarked beforehand. This approach can be very useful in flood risk management of catchments where information about hydro-meteorological variables is inadequate for any forecasting system. This paper presents the development of FI and its application to several catchments including in Kentucky in the USA

  15. Appropriate hydrological modelling of climate change on river flooding

    Booij, Martijn J.; Rizzoli, A.E.; Jakeman, A.J.

    2002-01-01

    How good should a river basin model be to assess the impact of climate change on river flooding for a specific geographical area? The determination of such an appropriate model should reveal which physical processes should be incorporated and which data and mathematical process descriptions should

  16. An Assessment of Capacity, Gaps and Opportunities toward Building a Global Early Warning System for Flood Disasters

    Hong, Y.; Adler, R.; Huffman, G.

    2007-12-01

    Many governmental emergency management agencies or non-governmental organizations need real-time information on emerging disasters for preparedness and response. However, progress in warnings for hydrologic disasters has been constrained by the difficulty of measuring spatiotemporal variability of rainfall fluxes continuously over space and time, due largely to insufficient ground monitoring networks, long delay in data transmission and absence of data sharing protocols among many geopolitically trans-boundary basins. In addition, in-situ gauging stations are often washed away by the very floods they are designed to monitor, making reconstruction of gauges a common post-flood activity around the world. In reality, remote sensing precipitation estimates may be the only source of rainfall information available over much of the globe, particularly for vulnerable countries in the tropics where abundant extreme rain storms and severe flooding events repeat every year. Building on progress in remote sensing technology, researchers have improved the accuracy, coverage, and resolution of rainfall estimates by combining imagery from infrared, passive microwave, and weather radar sensors. Today, remote sensing imagery acquired and processed in real time can provide near-real-time rainfall fluxes at relatively fine spatiotemporal scales (kilometers to tens of kilometers and 30-minute to 3-hour). These new suites of rainfall products have the potential to support daily decision-making in analysis of hydrologic hazards. This talk will address several key issues, including remote sensing rainfall retrieval and data assimilation, for hydrologists to develop alternative satellite-based flood warning systems that may supplement in-situ infrastructure when conventional data sources are denied due to natural or administrative causes. This talk will also assess a module-structure global flood prediction system that has been running at real-time by integrating remote sensing forcing

  17. Global Volcano Model

    Sparks, R. S. J.; Loughlin, S. C.; Cottrell, E.; Valentine, G.; Newhall, C.; Jolly, G.; Papale, P.; Takarada, S.; Crosweller, S.; Nayembil, M.; Arora, B.; Lowndes, J.; Connor, C.; Eichelberger, J.; Nadim, F.; Smolka, A.; Michel, G.; Muir-Wood, R.; Horwell, C.

    2012-04-01

    Over 600 million people live close enough to active volcanoes to be affected when they erupt. Volcanic eruptions cause loss of life, significant economic losses and severe disruption to people's lives, as highlighted by the recent eruption of Mount Merapi in Indonesia. The eruption of Eyjafjallajökull, Iceland in 2010 illustrated the potential of even small eruptions to have major impact on the modern world through disruption of complex critical infrastructure and business. The effects in the developing world on economic growth and development can be severe. There is evidence that large eruptions can cause a change in the earth's climate for several years afterwards. Aside from meteor impact and possibly an extreme solar event, very large magnitude explosive volcanic eruptions may be the only natural hazard that could cause a global catastrophe. GVM is a growing international collaboration that aims to create a sustainable, accessible information platform on volcanic hazard and risk. We are designing and developing an integrated database system of volcanic hazards, vulnerability and exposure with internationally agreed metadata standards. GVM will establish methodologies for analysis of the data (eg vulnerability indices) to inform risk assessment, develop complementary hazards models and create relevant hazards and risk assessment tools. GVM will develop the capability to anticipate future volcanism and its consequences. NERC is funding the start-up of this initiative for three years from November 2011. GVM builds directly on the VOGRIPA project started as part of the GRIP (Global Risk Identification Programme) in 2004 under the auspices of the World Bank and UN. Major international initiatives and partners such as the Smithsonian Institution - Global Volcanism Program, State University of New York at Buffalo - VHub, Earth Observatory of Singapore - WOVOdat and many others underpin GVM.

  18. Assimilation of flood extent data with 2D flood inundation models for localised intense rainfall events

    Neal, J. C.; Wood, M.; Bermúdez, M.; Hostache, R.; Freer, J. E.; Bates, P. D.; Coxon, G.

    2017-12-01

    Remote sensing of flood inundation extent has long been a potential source of data for constraining and correcting simulations of floodplain inundation. Hydrodynamic models and the computing resources to run them have developed to the extent that simulation of flood inundation in two-dimensional space is now feasible over large river basins in near real-time. However, despite substantial evidence that there is useful information content within inundation extent data, even from low resolution SAR such as that gathered by Envisat ASAR in wide swath mode, making use of the information in a data assimilation system has proved difficult. He we review recent applications of the Ensemble Kalman Filter (EnKF) and Particle Filter for assimilating SAR data, with a focus on the River Severn UK and compare these with complementary research that has looked at the internal error sources and boundary condition errors using detailed terrestrial data that is not available in most locations. Previous applications of the EnKF to this reach have focused on upstream boundary conditions as the source of flow error, however this description of errors was too simplistic for the simulation of summer flood events where localised intense rainfall can be substantial. Therefore, we evaluate the introduction of uncertain lateral inflows to the ensemble. A further limitation of the existing EnKF based methods is the need to convert flood extent to water surface elevations by intersecting the shoreline location with a high quality digital elevation model (e.g. LiDAR). To simplify this data processing step, we evaluate a method to directly assimilate inundation extent as a EnKF model state rather than assimilating water heights, potentially allowing the scheme to be used where high-quality terrain data are sparse.

  19. Interactive modelling with stakeholders in two cases in flood management

    Leskens, Johannes; Brugnach, Marcela

    2013-04-01

    New policies on flood management called Multi-Level Safety (MLS), demand for an integral and collaborative approach. The goal of MLS is to minimize flood risks by a coherent package of protection measures, crisis management and flood resilience measures. To achieve this, various stakeholders, such as water boards, municipalities and provinces, have to collaborate in composing these measures. Besides the many advances this integral and collaborative approach gives, the decision-making environment becomes also more complex. Participants have to consider more criteria than they used to do and have to take a wide network of participants into account, all with specific perspectives, cultures and preferences. In response, sophisticated models are developed to support decision-makers in grasping this complexity. These models provide predictions of flood events and offer the opportunity to test the effectiveness of various measures under different criteria. Recent model advances in computation speed and model flexibility allow stakeholders to directly interact with a hydrological hydraulic model during meetings. Besides a better understanding of the decision content, these interactive models are supposed to support the incorporation of stakeholder knowledge in modelling and to support mutual understanding of different perspectives of stakeholders To explore the support of interactive modelling in integral and collaborate policies, such as MLS, we tested a prototype of an interactive flood model (3Di) with respect to a conventional model (Sobek) in two cases. The two cases included the designing of flood protection measures in Amsterdam and a flood event exercise in Delft. These case studies yielded two main results. First, we observed that in the exploration phase of a decision-making process, stakeholders participated actively in interactive modelling sessions. This increased the technical understanding of complex problems and the insight in the effectiveness of various

  20. Influence of ENSO on coastal flood hazard and exposure at the global-scale

    Muis, S.; Haigh, I. D.; Guimarães Nobre, G.; Aerts, J.; Ward, P.

    2017-12-01

    The El Niño-Southern Oscillation (ENSO) is the dominant signal of interannual climate variability. The unusually warm (El Niño) and cold (La Niña) oceanic and atmospheric conditions in the tropical Pacific drives interannual variability in both mean and extreme sea levels, which in turn may influence the probabilities and impacts of coastal flooding. We assess the influence of ENSO on coastal flood hazard and exposure using daily timeseries from the Global Time and Surge Reanalysis (GTSR) dataset (Muis et al., 2016). As the GTSR timeseries do not include steric effects (i.e. density differences), we improve the GTSR timeseries by adding steric sea levels. Evaluation against observed sea levels shows that the including steric sea levels leads to a much better representation of the seasonal and interannual variability. We show that sea level anomalies occur during ENSO years with higher sea levels during La Niña in the South-Atlantic, Indian Ocean and the West Pacific, whereas sea levels are lower in the east Pacific. The pattern is generally inversed for El Niño. We also find an effect of ENSO in the number of people exposed to coastal flooding. Although the effect is minor at the global-scale, it may be important for flood risk management to consider at the national or sub national levels. Previous studies at the global-scale have used tide gauge observation to assess the influence of ENSO on extreme sea levels. The advantage of our approach over observations is that GTSR provides a consistent dataset with a full global coverage for the period 1979-2014. This allows us to assess ENSO's influence on sea level extremes anywhere in the world. Furthermore, it enables us to also calculate the impacts of extreme sea levels in terms of coastal flooding and exposed population. ReferencesMuis et al (2016) A global reanalysis of storm surges and extreme sea levels. Nature Communications.7:11969. doi:10.1038/ncomms11969.

  1. Simulating floods : On the application of a 2D-hydraulic model for flood hazard and risk assessment

    Alkema, D.

    2007-01-01

    Over the last decades, river floods in Europe seem to occur more frequently and are causing more and more economic and emotional damage. Understanding the processes causing flooding and the development of simulation models to evaluate countermeasures to control that damage are important issues. This

  2. Outburst Flood Simulation Model for Optimizing the Solo River Floods Emergency Response Activities

    Yuli Priyana

    2016-08-01

    Full Text Available This study aims to develop flood inundation based on several flood level. The results of this study are: (a land use in the study area is divided into (1 urban area (the Business Area which includes regional administrative center, shopping area, and office area, (2 residential areas (single home region, the region multi- unit house (residence, settlement areas and apartments, (3 industrial estate (industrial estates are less dense and dense industrial area, (4 the surface area covered with vegetation (forest - thicket, meadow area, and the area of land productive rice fields and fields, (5 the area of open land and vacant land that is intended (the city park , cemetery and park area, and (6 transportation area and the pavement surface area (area train station and bus terminal region, (b the preparation of spatial database in this study in the form of data or data vector altitude of Digital Elevation Model (DEM. District of Jebres there are 56 points of elevation and District of Pasar Kliwon there are 48 points of elevation. Elevation of the study area ranged from 88,9 mpdal up to 127.65 mdpal and (c the higher the flood inundation scenarios impact on land use in the study area are also getting bigger. Most obvious impact under scenario 2 m area of 296 601 m , while the smallest impact under scenario 1 m with an area of 77 693 m 2 2 impact. Extensive simulation results based on the total impact amounts to 544 756 m.

  3. Remote sensing estimates of impervious surfaces for pluvial flood modelling

    Kaspersen, Per Skougaard; Drews, Martin

    This paper investigates the accuracy of medium resolution (MR) satellite imagery in estimating impervious surfaces for European cities at the detail required for pluvial flood modelling. Using remote sensing techniques enables precise and systematic quantification of the influence of the past 30...

  4. Modelling of ammonia volatilisation in fertilised and flooded rice systems

    Khairudin, Nurulhuda

    2017-01-01

    In flooded rice systems that are broadcast with urea, significant amounts of nitrogen (N) may be lost to the atmosphere in the form of ammonia (NH3). Many models with different complexities with regards to describing the process of NH3 volatilisation and the overall N dynamics in the systems are

  5. Climate change and the global pattern of moraine-dammed glacial lake outburst floods

    S. Harrison

    2018-04-01

    Full Text Available Despite recent research identifying a clear anthropogenic impact on glacier recession, the effect of recent climate change on glacier-related hazards is at present unclear. Here we present the first global spatio-temporal assessment of glacial lake outburst floods (GLOFs focusing explicitly on lake drainage following moraine dam failure. These floods occur as mountain glaciers recede and downwaste. GLOFs can have an enormous impact on downstream communities and infrastructure. Our assessment of GLOFs associated with the rapid drainage of moraine-dammed lakes provides insights into the historical trends of GLOFs and their distributions under current and future global climate change. We observe a clear global increase in GLOF frequency and their regularity around 1930, which likely represents a lagged response to post-Little Ice Age warming. Notably, we also show that GLOF frequency and regularity – rather unexpectedly – have declined in recent decades even during a time of rapid glacier recession. Although previous studies have suggested that GLOFs will increase in response to climate warming and glacier recession, our global results demonstrate that this has not yet clearly happened. From an assessment of the timing of climate forcing, lag times in glacier recession, lake formation and moraine-dam failure, we predict increased GLOF frequencies during the next decades and into the 22nd century.

  6. Climate change and the global pattern of moraine-dammed glacial lake outburst floods

    Harrison, Stephan; Kargel, Jeffrey S.; Huggel, Christian; Reynolds, John; Shugar, Dan H.; Betts, Richard A.; Emmer, Adam; Glasser, Neil; Haritashya, Umesh K.; Klimeš, Jan; Reinhardt, Liam; Schaub, Yvonne; Wiltshire, Andy; Regmi, Dhananjay; Vilímek, Vít

    2018-04-01

    Despite recent research identifying a clear anthropogenic impact on glacier recession, the effect of recent climate change on glacier-related hazards is at present unclear. Here we present the first global spatio-temporal assessment of glacial lake outburst floods (GLOFs) focusing explicitly on lake drainage following moraine dam failure. These floods occur as mountain glaciers recede and downwaste. GLOFs can have an enormous impact on downstream communities and infrastructure. Our assessment of GLOFs associated with the rapid drainage of moraine-dammed lakes provides insights into the historical trends of GLOFs and their distributions under current and future global climate change. We observe a clear global increase in GLOF frequency and their regularity around 1930, which likely represents a lagged response to post-Little Ice Age warming. Notably, we also show that GLOF frequency and regularity - rather unexpectedly - have declined in recent decades even during a time of rapid glacier recession. Although previous studies have suggested that GLOFs will increase in response to climate warming and glacier recession, our global results demonstrate that this has not yet clearly happened. From an assessment of the timing of climate forcing, lag times in glacier recession, lake formation and moraine-dam failure, we predict increased GLOF frequencies during the next decades and into the 22nd century.

  7. Recent changes in flood damage in the United States from observations and ACME model

    Leng, G.; Leung, L. R.

    2017-12-01

    Despite efforts to mitigate flood hazards in flood-prone areas, survey- and report-based flood databases show that flood damage has increased and emerged as one of the most costly disaster in the United States since the 1990s. Understanding the mechanism driving the changes in flood damage is therefore critical for reducing flood risk. In this study, we first conduct a comprehensive analysis of the changing characteristics of flood damage at local, state and country level. Results show a significant increasing trend in the number of flood hazards, causing economic losses of up to $7 billion per year. The ratio of flood events that caused tangible economical cost to the total flood events has exhibited a non-significant increasing trend before 2007 followed by a significant decrease, indicating a changing vulnerability to floods. Analysis also reveals distinct spatial and temporal patterns in the threshold intensity of flood hazards with tangible economical cost. To understand the mechanism behind the increasing flood damage, we develop a flood damage economic model coupled with the integrated hydrological modeling system of ACME that features a river routing model with an inundation parameterization and a water use and regulation model. The model is evaluated over the country against historical records. Several numerical experiments are then designed to explore the mechanisms behind the recent changes in flood damage from the perspective of flood hazard, exposure and vulnerability, which constitute flood damage. The role of human activities such as reservoir operations and water use in modifying regional floods are also explored using the new tool, with the goal of improving understanding and modeling of vulnerability to flood hazards.

  8. Modelling Inland Flood Events for Hazard Maps in Taiwan

    Ghosh, S.; Nzerem, K.; Sassi, M.; Hilberts, A.; Assteerawatt, A.; Tillmanns, S.; Mathur, P.; Mitas, C.; Rafique, F.

    2015-12-01

    Taiwan experiences significant inland flooding, driven by torrential rainfall from plum rain storms and typhoons during summer and fall. From last 13 to 16 years data, 3,000 buildings were damaged by such floods annually with a loss US$0.41 billion (Water Resources Agency). This long, narrow island nation with mostly hilly/mountainous topography is located at tropical-subtropical zone with annual average typhoon-hit-frequency of 3-4 (Central Weather Bureau) and annual average precipitation of 2502mm (WRA) - 2.5 times of the world's average. Spatial and temporal distributions of countrywide precipitation are uneven, with very high local extreme rainfall intensities. Annual average precipitation is 3000-5000mm in the mountainous regions, 78% of it falls in May-October, and the 1-hour to 3-day maximum rainfall are about 85 to 93% of the world records (WRA). Rivers in Taiwan are short with small upstream areas and high runoff coefficients of watersheds. These rivers have the steepest slopes, the shortest response time with rapid flows, and the largest peak flows as well as specific flood peak discharge (WRA) in the world. RMS has recently developed a countrywide inland flood model for Taiwan, producing hazard return period maps at 1arcsec grid resolution. These can be the basis for evaluating and managing flood risk, its economic impacts, and insured flood losses. The model is initiated with sub-daily historical meteorological forcings and calibrated to daily discharge observations at about 50 river gauges over the period 2003-2013. Simulations of hydrologic processes, via rainfall-runoff and routing models, are subsequently performed based on a 10000 year set of stochastic forcing. The rainfall-runoff model is physically based continuous, semi-distributed model for catchment hydrology. The 1-D wave propagation hydraulic model considers catchment runoff in routing and describes large-scale transport processes along the river. It also accounts for reservoir storage

  9. iFLOOD: A Real Time Flood Forecast System for Total Water Modeling in the National Capital Region

    Sumi, S. J.; Ferreira, C.

    2017-12-01

    Extreme flood events are the costliest natural hazards impacting the US and frequently cause extensive damages to infrastructure, disruption to economy and loss of lives. In 2016, Hurricane Matthew brought severe damage to South Carolina and demonstrated the importance of accurate flood hazard predictions that requires the integration of riverine and coastal model forecasts for total water prediction in coastal and tidal areas. The National Weather Service (NWS) and the National Ocean Service (NOS) provide flood forecasts for almost the entire US, still there are service-gap areas in tidal regions where no official flood forecast is available. The National capital region is vulnerable to multi-flood hazards including high flows from annual inland precipitation events and surge driven coastal inundation along the tidal Potomac River. Predicting flood levels on such tidal areas in river-estuarine zone is extremely challenging. The main objective of this study is to develop the next generation of flood forecast systems capable of providing accurate and timely information to support emergency management and response in areas impacted by multi-flood hazards. This forecast system is capable of simulating flood levels in the Potomac and Anacostia River incorporating the effects of riverine flooding from the upstream basins, urban storm water and tidal oscillations from the Chesapeake Bay. Flood forecast models developed so far have been using riverine data to simulate water levels for Potomac River. Therefore, the idea is to use forecasted storm surge data from a coastal model as boundary condition of this system. Final output of this validated model will capture the water behavior in river-estuary transition zone far better than the one with riverine data only. The challenge for this iFLOOD forecast system is to understand the complex dynamics of multi-flood hazards caused by storm surges, riverine flow, tidal oscillation and urban storm water. Automated system

  10. Modeling urban coastal flood severity from crowd-sourced flood reports using Poisson regression and Random Forest

    Sadler, J. M.; Goodall, J. L.; Morsy, M. M.; Spencer, K.

    2018-04-01

    Sea level rise has already caused more frequent and severe coastal flooding and this trend will likely continue. Flood prediction is an essential part of a coastal city's capacity to adapt to and mitigate this growing problem. Complex coastal urban hydrological systems however, do not always lend themselves easily to physically-based flood prediction approaches. This paper presents a method for using a data-driven approach to estimate flood severity in an urban coastal setting using crowd-sourced data, a non-traditional but growing data source, along with environmental observation data. Two data-driven models, Poisson regression and Random Forest regression, are trained to predict the number of flood reports per storm event as a proxy for flood severity, given extensive environmental data (i.e., rainfall, tide, groundwater table level, and wind conditions) as input. The method is demonstrated using data from Norfolk, Virginia USA from September 2010 to October 2016. Quality-controlled, crowd-sourced street flooding reports ranging from 1 to 159 per storm event for 45 storm events are used to train and evaluate the models. Random Forest performed better than Poisson regression at predicting the number of flood reports and had a lower false negative rate. From the Random Forest model, total cumulative rainfall was by far the most dominant input variable in predicting flood severity, followed by low tide and lower low tide. These methods serve as a first step toward using data-driven methods for spatially and temporally detailed coastal urban flood prediction.

  11. Analysis of the flood extent extraction model and the natural flood influencing factors: A GIS-based and remote sensing analysis

    Lawal, D U; Matori, A N; Yusuf, K W; Hashim, A M; Balogun, A L

    2014-01-01

    Serious floods have hit the State of Perlis in 2005, 2010, as well as 2011. Perlis is situated in the northern part of Peninsula Malaysia. The floods caused great damage to properties and human lives. There are various methods used in an attempt to provide the most reliable ways to reduce the flood risk and damage to the optimum level by identifying the flood vulnerable zones. The purpose of this paper is to develop a flood extent extraction model based on Minimum Distance Algorithm and to overlay with the natural flood influencing factors considered herein in order to examine the effect of each factor in flood generation. GIS spatial database was created from a geological map, SPOT satellite image, and the topographical map. An attribute database was equally created from field investigations and historical flood areas reports of the study area. The results show a great correlation between the flood extent extraction model and the flood factors

  12. Modeling Flood Hazard Zones at the Sub-District Level with the Rational Model Integrated with GIS and Remote Sensing Approaches

    Daniel Asare-Kyei

    2015-07-01

    Full Text Available Robust risk assessment requires accurate flood intensity area mapping to allow for the identification of populations and elements at risk. However, available flood maps in West Africa lack spatial variability while global datasets have resolutions too coarse to be relevant for local scale risk assessment. Consequently, local disaster managers are forced to use traditional methods such as watermarks on buildings and media reports to identify flood hazard areas. In this study, remote sensing and Geographic Information System (GIS techniques were combined with hydrological and statistical models to delineate the spatial limits of flood hazard zones in selected communities in Ghana, Burkina Faso and Benin. The approach involves estimating peak runoff concentrations at different elevations and then applying statistical methods to develop a Flood Hazard Index (FHI. Results show that about half of the study areas fall into high intensity flood zones. Empirical validation using statistical confusion matrix and the principles of Participatory GIS show that flood hazard areas could be mapped at an accuracy ranging from 77% to 81%. This was supported with local expert knowledge which accurately classified 79% of communities deemed to be highly susceptible to flood hazard. The results will assist disaster managers to reduce the risk to flood disasters at the community level where risk outcomes are first materialized.

  13. Modelling the interaction between flooding events and economic growth

    J. Grames

    2015-06-01

    Full Text Available Socio-hydrology describes the interaction between the socio-economy and water. Recent models analyze the interplay of community risk-coping culture, flooding damage and economic growth (Di Baldassarre et al., 2013; Viglione et al., 2014. These models descriptively explain the feedbacks between socio-economic development and natural disasters like floods. Contrary to these descriptive models, our approach develops an optimization model, where the intertemporal decision of an economic agent interacts with the hydrological system. In order to build this first economic growth model describing the interaction between the consumption and investment decisions of an economic agent and the occurrence of flooding events, we transform an existing descriptive stochastic model into an optimal deterministic model. The intermediate step is to formulate and simulate a descriptive deterministic model. We develop a periodic water function to approximate the former discrete stochastic time series of rainfall events. Due to the non-autonomous exogenous periodic rainfall function the long-term path of consumption and investment will be periodic.

  14. Synchronous drought and flooding in southern Chinese Loess Plateau in phase with the variation of global temperature

    Yu, X.; Kang, Z.

    2017-12-01

    Drought and flooding, usually occurring in the catchment scale, are the main natural threats to human livelihood due to the extreme variation of precipitation in spatiotemporal scales. Within the context of global warming, the risk of flood and drought tends to increase in different regions. Understanding the mechanism of the regional occurrence of flood and drought is of enormous importance for the predicting studies and taking corresponding measures. However, the instrumental records are too short to conduct a prediction. Here, we present a historical-archive-based high-resolution dataset of drought and flooding back to AD 1646 in the southern Chinese Loess Plateau. This sequence, integrated with the modern meteorological observation data, shows that the frequency of drought and flooding in the study region is synchronous on a decadal scale, and they are in phase with the increase in both global and regional temperature. During the warm period, the ENSO activity was found to be increase, resulting in the anomaly distribution of precipitation in different seasons in southern Chinese Loess Plateau, which is the reason for the temperature dependence of flooding and drought in this region. If global temperature continues to rise in the future, the risk of both drought and flooding in the study area would also increase.

  15. Development and Evaluation of an Integrated Hydrological Modeling Framework for Monitoring and Understanding Floods and Droughts

    Yang, Z. L.; Wu, W. Y.; Lin, P.; Maidment, D. R.

    2017-12-01

    Extreme water events such as catastrophic floods and severe droughts have increased in recent decades. Mitigating the risk to lives, food security, infrastructure, energy supplies, as well as numerous other industries posed by these extreme events requires informed decision-making and planning based on sound science. We are developing a global water modeling capability by building models that will provide total operational water predictions (evapotranspiration, soil moisture, groundwater, channel flow, inundation, snow) at unprecedented spatial resolutions and updated frequencies. Toward this goal, this talk presents an integrated global hydrological modeling framework that takes advantage of gridded meteorological forcing, land surface modeling, channeled flow modeling, ground observations, and satellite remote sensing. Launched in August 2016, the National Water Model successfully incorporates weather forecasts to predict river flows for more than 2.7 million rivers across the continental United States, which transfers a "synoptic weather map" to a "synoptic river flow map" operationally. In this study, we apply a similar framework to a high-resolution global river network database, which is developed from a hierarchical Dominant River Tracing (DRT) algorithm, and runoff output from the Global Land Data Assimilation System (GLDAS) to a vector-based river routing model (The Routing Application for Parallel Computation of Discharge, RAPID) to produce river flows from 2001 to 2016 using Message Passing Interface (MPI) on Texas Advanced Computer Center's Stampede system. In this simulation, global river discharges for more than 177,000 rivers are computed every 30 minutes. The modeling framework's performance is evaluated with various observations including river flows at more than 400 gauge stations globally. Overall, the model exhibits a reasonably good performance in simulating the averaged patterns of terrestrial water storage, evapotranspiration and runoff. The

  16. Exploring the Role of Social Media and Individual Behaviors in Flood Evacuation Processes: An Agent-Based Modeling Approach

    Du, Erhu; Cai, Ximing; Sun, Zhiyong; Minsker, Barbara

    2017-11-01

    Flood warnings from various information sources are important for individuals to make evacuation decisions during a flood event. In this study, we develop a general opinion dynamics model to simulate how individuals update their flood hazard awareness when exposed to multiple information sources, including global broadcast, social media, and observations of neighbors' actions. The opinion dynamics model is coupled with a traffic model to simulate the evacuation processes of a residential community with a given transportation network. Through various scenarios, we investigate how social media affect the opinion dynamics and evacuation processes. We find that stronger social media can make evacuation processes more sensitive to the change of global broadcast and neighbor observations, and thus, impose larger uncertainty on evacuation rates (i.e., a large range of evacuation rates corresponding to sources of information). For instance, evacuation rates are lower when social media become more influential and individuals have less trust in global broadcast. Stubborn individuals can significantly affect the opinion dynamics and reduce evacuation rates. In addition, evacuation rates respond to the percentage of stubborn agents in a nonlinear manner, i.e., above a threshold, the impact of stubborn agents will be intensified by stronger social media. These results highlight the role of social media in flood evacuation processes and the need to monitor social media so that misinformation can be corrected in a timely manner. The joint impacts of social media, quality of flood warnings, and transportation capacity on evacuation rates are also discussed.

  17. Flood Mapping: Assessing the uncertainty associated with flood inundation modelling. A case study of the Mora River, Sweden

    Åberg, Isabelle

    2017-01-01

    Expansion of cities and major infrastructure projects lead to changes in land use and river flows. The probability of flooding is expected to increase in the future as a result of these changes in combination with climate change. Hydraulic models can be used to obtain simulated water levels to investigate the risk of flooding and identify areas that might potentially be flooded due to climate change. Since a model is a simplification of the reality it is important to be aware of a model’s unc...

  18. Combining Empirical and Stochastic Models for Extreme Floods Estimation

    Zemzami, M.; Benaabidate, L.

    2013-12-01

    Hydrological models can be defined as physical, mathematical or empirical. The latter class uses mathematical equations independent of the physical processes involved in the hydrological system. The linear regression and Gradex (Gradient of Extreme values) are classic examples of empirical models. However, conventional empirical models are still used as a tool for hydrological analysis by probabilistic approaches. In many regions in the world, watersheds are not gauged. This is true even in developed countries where the gauging network has continued to decline as a result of the lack of human and financial resources. Indeed, the obvious lack of data in these watersheds makes it impossible to apply some basic empirical models for daily forecast. So we had to find a combination of rainfall-runoff models in which it would be possible to create our own data and use them to estimate the flow. The estimated design floods would be a good choice to illustrate the difficulties facing the hydrologist for the construction of a standard empirical model in basins where hydrological information is rare. The construction of the climate-hydrological model, which is based on frequency analysis, was established to estimate the design flood in the Anseghmir catchments, Morocco. The choice of using this complex model returns to its ability to be applied in watersheds where hydrological information is not sufficient. It was found that this method is a powerful tool for estimating the design flood of the watershed and also other hydrological elements (runoff, volumes of water...).The hydrographic characteristics and climatic parameters were used to estimate the runoff, water volumes and design flood for different return periods.

  19. Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location-Specific Premiums in the Netherlands.

    Ermolieva, T; Filatova, T; Ermoliev, Y; Obersteiner, M; de Bruijn, K M; Jeuken, A

    2017-01-01

    As flood risks grow worldwide, a well-designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood-loss-sharing program involving private insurance based on location-specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS-based flood model and a stochastic optimization procedure with respect to location-specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile-related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures. © 2016 Society for Risk Analysis.

  20. Calibration of a rainfall-runoff hydrological model and flood simulation using data assimilation

    Piacentini, A.; Ricci, S. M.; Thual, O.; Coustau, M.; Marchandise, A.

    2010-12-01

    velocity travel before the flood peak. These optimal values are used for a new simulation of the event in forecast mode (under the assumption of perfect rain-fall). On both catchments, it was shown over a significant number of flood events, that the data assimilation procedure improves the flood peak forecast. The improvement is globally more important for the Gardon d'Anduze catchment where the flood events are stronger. The peak can be forecasted up to 36 hours head of time assimilating very few observations (up to 4) during the rise of the water level. For multiple peaks events, the assimilation of the observations from the first peak leads to a significant improvement of the second peak simulation. It was also shown that the flood rise is often faster in reality than it is represented by the model. In this case and when the flood peak is under estimated in the simulation, the use of the first observations can be misleading for the data assimilation algorithm. The careful estimation of the observation and background error variances enabled the satisfying use of the data assimilation in these complex cases even though it does not allow the model error correction.

  1. Modeling Waves and Coastal Flooding along the Connecticut Coast

    Cifuentes-Lorenzen, A.; Howard-Strobel, M. M.; Fake, T.; McCardell, G.; O'Donnell, J.; Asthita, M.

    2015-12-01

    We have used a hydrodynamic- wave coupled numerical model (FVCOM-SWAVE) to simulate flooding at the Connecticut coastline during severe storms. The model employed a one-way nesting scheme and an unstructured grid. The parent domain spanned most of the southern New England shelf and the fine resolution grid covered Long Island Sound (LIS) and extended across the Connecticut coast to the 10m elevation contour. The model results for sea level, current and wave statistics from the parent grid have been tested with data from several field campaigns at different locations spanning the western, central and eastern portions of LIS. Waves are fetch limited and improvements to the model-data comparison required modifications to spectral coefficients in the wave model. Finally, the nested results were validated with two field campaigns in shallow water environments (i.e. New Haven and Old Saybrook). To assess the spatial variability of storm wave characteristics the domain was forced with the hindcast winds obtained from meteorological models (NAM and WRF) for 13 severe weather events that affected LIS in the past 15 years. We have also forced the system with a simulation of Superstorm Sandy in a warmer climate to assess the impact a climate change on the character of flooding. The nested grid is currently being used to map flooding risks under severe weather events including the effects of precipitation on river flow and discharge.

  2. The Open Global Glacier Model

    Marzeion, B.; Maussion, F.

    2017-12-01

    Mountain glaciers are one of the few remaining sub-systems of the global climate system for which no globally applicable, open source, community-driven model exists. Notable examples from the ice sheet community include the Parallel Ice Sheet Model or Elmer/Ice. While the atmospheric modeling community has a long tradition of sharing models (e.g. the Weather Research and Forecasting model) or comparing them (e.g. the Coupled Model Intercomparison Project or CMIP), recent initiatives originating from the glaciological community show a new willingness to better coordinate global research efforts following the CMIP example (e.g. the Glacier Model Intercomparison Project or the Glacier Ice Thickness Estimation Working Group). In the recent past, great advances have been made in the global availability of data and methods relevant for glacier modeling, spanning glacier outlines, automatized glacier centerline identification, bed rock inversion methods, and global topographic data sets. Taken together, these advances now allow the ice dynamics of glaciers to be modeled on a global scale, provided that adequate modeling platforms are available. Here, we present the Open Global Glacier Model (OGGM), developed to provide a global scale, modular, and open source numerical model framework for consistently simulating past and future global scale glacier change. Global not only in the sense of leading to meaningful results for all glaciers combined, but also for any small ensemble of glaciers, e.g. at the headwater catchment scale. Modular to allow combinations of different approaches to the representation of ice flow and surface mass balance, enabling a new kind of model intercomparison. Open source so that the code can be read and used by anyone and so that new modules can be added and discussed by the community, following the principles of open governance. Consistent in order to provide uncertainty measures at all realizable scales.

  3. LiDAR and IFSAR-Based Flood Inundation Model Estimates for Flood-Prone Areas of Afghanistan

    Johnson, W. C.; Goldade, M. M.; Kastens, J.; Dobbs, K. E.; Macpherson, G. L.

    2014-12-01

    Extreme flood events are not unusual in semi-arid to hyper-arid regions of the world, and Afghanistan is no exception. Recent flashfloods and flashflood-induced landslides took nearly 100 lives and destroyed or damaged nearly 2000 homes in 12 villages within Guzargah-e-Nur district of Baghlan province in northeastern Afghanistan. With available satellite imagery, flood-water inundation estimation can be accomplished remotely, thereby providing a means to reduce the impact of such flood events by improving shared situational awareness during major flood events. Satellite orbital considerations, weather, cost, data licensing restrictions, and other issues can often complicate the acquisition of appropriately timed imagery. Given the need for tools to supplement imagery where not available, complement imagery when it is available, and bridge the gap between imagery based flood mapping and traditional hydrodynamic modeling approaches, we have developed a topographic floodplain model (FLDPLN), which has been used to identify and map river valley floodplains with elevation data ranging from 90-m SRTM to 1-m LiDAR. Floodplain "depth to flood" (DTF) databases generated by FLDPLN are completely seamless and modular. FLDPLN has been applied in Afghanistan to flood-prone areas along the northern and southern flanks of the Hindu Kush mountain range to generate a continuum of 1-m increment flood-event models up to 10 m in depth. Elevation data used in this application of FLDPLN included high-resolution, drone-acquired LiDAR (~1 m) and IFSAR (5 m; INTERMAP). Validation of the model has been accomplished using the best available satellite-derived flood inundation maps, such as those issued by Unitar's Operational Satellite Applications Programme (UNOSAT). Results provide a quantitative approach to evaluating the potential risk to urban/village infrastructure as well as to irrigation systems, agricultural fields and archaeological sites.

  4. Modeling urban flood risk territories for Riga city

    Piliksere, A.; Sennikovs, J.; Virbulis, J.; Bethers, U.; Bethers, P.; Valainis, A.

    2012-04-01

    Riga, the capital of Latvia, is located on River Daugava at the Gulf of Riga. The main flooding risks of Riga city are: (1) storm caused water setup in South part of Gulf of Riga (storm event), (2) water level increase caused by Daugava River discharge maximums (spring snow melting event) and (3) strong rainfall or rapid snow melting in densely populated urban areas. The first two flooding factors were discussed previously (Piliksere et al, 2011). The aims of the study were (1) the identification of the flood risk situations in densely populated areas, (2) the quantification of the flooding scenarios caused by rain and snow melting events of different return periods nowadays, in the near future (2021-2050), far future (2071-2100) taking into account the projections of climate change, (3) estimation of groundwater level for Riga city, (4) the building and calibration of the hydrological mathematical model based on SWMM (EPA, 2004) for the domain potentially vulnerable for rain and snow melt flooding events, (5) the calculation of rain and snow melting flood events with different return periods, (6) mapping the potentially flooded areas on a fine grid. The time series of short term precipitation events during warm time period of year (id est. rain events) were analyzed for 35 year long time period. Annual maxima of precipitation intensity for events with different duration (5 min; 15 min; 1h; 3h; 6h; 12h; 1 day; 2 days; 4 days; 10 days) were calculated. The time series of long term simultaneous precipitation data and observations of the reduction of thickness of snow cover were analyzed for 27 year long time period. Snow thawing periods were detected and maximum of snow melting intensity for events with different intensity (1day; 2 days; 4 days; 7 days; 10 days) were calculated. According to the occurrence probability six scenarios for each event for nowadays, near and far future with return period once in 5, 10, 20, 50, 100 and 200 years were constructed based on

  5. Flood risk in a changing world - a coupled transdisciplinary modelling framework for flood risk assessment in an Alpine study area

    Huttenlau, Matthias; Schneeberger, Klaus; Winter, Benjamin; Pazur, Robert; Förster, Kristian; Achleitner, Stefan; Bolliger, Janine

    2017-04-01

    Devastating flood events have caused substantial economic damage across Europe during past decades. Flood risk management has therefore become a topic of crucial interest across state agencies, research communities and the public sector including insurances. There is consensus that mitigating flood risk relies on impact assessments which quantitatively account for a broad range of aspects in a (changing) environment. Flood risk assessments which take into account the interaction between the drivers climate change, land-use change and socio-economic change might bring new insights to the understanding of the magnitude and spatial characteristic of flood risks. Furthermore, the comparative assessment of different adaptation measures can give valuable information for decision-making. With this contribution we present an inter- and transdisciplinary research project aiming at developing and applying such an impact assessment relying on a coupled modelling framework for the Province of Vorarlberg in Austria. Stakeholder engagement ensures that the final outcomes of our study are accepted and successfully implemented in flood management practice. The study addresses three key questions: (i) What are scenarios of land- use and climate change for the study area? (ii) How will the magnitude and spatial characteristic of future flood risk change as a result of changes in climate and land use? (iii) Are there spatial planning and building-protection measures which effectively reduce future flood risk? The modelling framework has a modular structure comprising modules (i) climate change, (ii) land-use change, (iii) hydrologic modelling, (iv) flood risk analysis, and (v) adaptation measures. Meteorological time series are coupled with spatially explicit scenarios of land-use change to model runoff time series. The runoff time series are combined with impact indicators such as building damages and results are statistically assessed to analyse flood risk scenarios. Thus, the

  6. Flood extent and water level estimation from SAR using data-model integration

    Ajadi, O. A.; Meyer, F. J.

    2017-12-01

    Synthetic Aperture Radar (SAR) images have long been recognized as a valuable data source for flood mapping. Compared to other sources, SAR's weather and illumination independence and large area coverage at high spatial resolution supports reliable, frequent, and detailed observations of developing flood events. Accordingly, SAR has the potential to greatly aid in the near real-time monitoring of natural hazards, such as flood detection, if combined with automated image processing. This research works towards increasing the reliability and temporal sampling of SAR-derived flood hazard information by integrating information from multiple SAR sensors and SAR modalities (images and Interferometric SAR (InSAR) coherence) and by combining SAR-derived change detection information with hydrologic and hydraulic flood forecast models. First, the combination of multi-temporal SAR intensity images and coherence information for generating flood extent maps is introduced. The application of least-squares estimation integrates flood information from multiple SAR sensors, thus increasing the temporal sampling. SAR-based flood extent information will be combined with a Digital Elevation Model (DEM) to reduce false alarms and to estimate water depth and flood volume. The SAR-based flood extent map is assimilated into the Hydrologic Engineering Center River Analysis System (Hec-RAS) model to aid in hydraulic model calibration. The developed technology is improving the accuracy of flood information by exploiting information from data and models. It also provides enhanced flood information to decision-makers supporting the response to flood extent and improving emergency relief efforts.

  7. Towards large scale stochastic rainfall models for flood risk assessment in trans-national basins

    Serinaldi, F.; Kilsby, C. G.

    2012-04-01

    While extensive research has been devoted to rainfall-runoff modelling for risk assessment in small and medium size watersheds, less attention has been paid, so far, to large scale trans-national basins, where flood events have severe societal and economic impacts with magnitudes quantified in billions of Euros. As an example, in the April 2006 flood events along the Danube basin at least 10 people lost their lives and up to 30 000 people were displaced, with overall damages estimated at more than half a billion Euros. In this context, refined analytical methods are fundamental to improve the risk assessment and, then, the design of structural and non structural measures of protection, such as hydraulic works and insurance/reinsurance policies. Since flood events are mainly driven by exceptional rainfall events, suitable characterization and modelling of space-time properties of rainfall fields is a key issue to perform a reliable flood risk analysis based on alternative precipitation scenarios to be fed in a new generation of large scale rainfall-runoff models. Ultimately, this approach should be extended to a global flood risk model. However, as the need of rainfall models able to account for and simulate spatio-temporal properties of rainfall fields over large areas is rather new, the development of new rainfall simulation frameworks is a challenging task involving that faces with the problem of overcoming the drawbacks of the existing modelling schemes (devised for smaller spatial scales), but keeping the desirable properties. In this study, we critically summarize the most widely used approaches for rainfall simulation. Focusing on stochastic approaches, we stress the importance of introducing suitable climate forcings in these simulation schemes in order to account for the physical coherence of rainfall fields over wide areas. Based on preliminary considerations, we suggest a modelling framework relying on the Generalized Additive Models for Location, Scale

  8. Quasi-continuous stochastic simulation framework for flood modelling

    Moustakis, Yiannis; Kossieris, Panagiotis; Tsoukalas, Ioannis; Efstratiadis, Andreas

    2017-04-01

    Typically, flood modelling in the context of everyday engineering practices is addressed through event-based deterministic tools, e.g., the well-known SCS-CN method. A major shortcoming of such approaches is the ignorance of uncertainty, which is associated with the variability of soil moisture conditions and the variability of rainfall during the storm event.In event-based modeling, the sole expression of uncertainty is the return period of the design storm, which is assumed to represent the acceptable risk of all output quantities (flood volume, peak discharge, etc.). On the other hand, the varying antecedent soil moisture conditions across the basin are represented by means of scenarios (e.g., the three AMC types by SCS),while the temporal distribution of rainfall is represented through standard deterministic patterns (e.g., the alternative blocks method). In order to address these major inconsistencies,simultaneously preserving the simplicity and parsimony of the SCS-CN method, we have developed a quasi-continuous stochastic simulation approach, comprising the following steps: (1) generation of synthetic daily rainfall time series; (2) update of potential maximum soil moisture retention, on the basis of accumulated five-day rainfall; (3) estimation of daily runoff through the SCS-CN formula, using as inputs the daily rainfall and the updated value of soil moisture retention;(4) selection of extreme events and application of the standard SCS-CN procedure for each specific event, on the basis of synthetic rainfall.This scheme requires the use of two stochastic modelling components, namely the CastaliaR model, for the generation of synthetic daily data, and the HyetosMinute model, for the disaggregation of daily rainfall to finer temporal scales. Outcomes of this approach are a large number of synthetic flood events, allowing for expressing the design variables in statistical terms and thus properly evaluating the flood risk.

  9. Global Delivery Models

    Manning, Stephan; Møller Larsen, Marcus; Bharati, Pratyush

    -zone spread allowing for 24/7 service delivery and access to resources. Based on comprehensive data we show that providers are likely to establish GDM configurations when clients value access to globally distributed talent pools and speed of service delivery, and in particular when services are highly...

  10. Global Delivery Models

    Manning, Stephan; Møller Larsen, Marcus; Bharati, Pratyush M.

    2015-01-01

    antecedents and contingencies of setting up GDM structures. Based on comprehensive data we show that providers are likely to establish GDM location configurations when clients value access to globally distributed talent and speed of service delivery, in particular when services are highly commoditized...

  11. AutoRoute Rapid Flood Inundation Model

    2013-03-01

    cross-section data does not exist. As such, the AutoRoute model is not meant to be as accurate as models such as HEC - RAS (U.S. Army Engineer...such as HEC - RAS assume that the defined low point of cross sections must be connected. However, in this approach the channel is assumed to be defined...Res. 33(2): 309-319. U.S. Army Engineer Hydrologic Engineering Center. 2010. “ HEC - RAS : River Analysis System, User’s Manual, Version 4.1.” Davis

  12. Effects of global warming on floods and droughts in the Caribbean

    Narayan, Kailas

    2004-01-01

    The Caribbean islands stretch in an arc from Cuba, south of Florida, to Trinidad and Tobago, north of the South American coast. The islands range in size from 100,000 square kilometers to 100 square kilometers, with populations ranging from ten million to less than ten thousand people. There is a wide range of rainfall in the region, occurring mainly from the Inter-Tropical convergence Zone, Tropical Waves and Hurricanes. There are also extended periods of droughts in the dry season. As a result the islands suffer from droughts as well as floods. These phenomena can have devastating results on the economies of the islands, resulting in extreme hardships for the population as well as forced shifting of population centers. Change of precipitation patterns as a result of Global warming can only worsen the situation. In this paper the author attempts an investigation into the effects of global warming and the resulting impacts in terms of droughts, floods on the Caribbean islands and on coastal areas of continental countries in the Caribbean. Vulnerability and risks are also investigated in terms of these phenomena. (Author)

  13. An Integrated Modelling Framework to Assess Flood Risk under Urban Development and Changing Climate

    that combines a model for the socio-economic development of cities (DANCE4WATER) with an urban flood model. The urban flood model is a 1D-2D spatially distributed hydrologic and hydraulic model that, for a given urban layout, simulates flow in the sewer system and the surface flow in the catchment (MIKE FLOOD......). The socio-economic model computes urban layouts that are transferred to the hydraulic model in the form of changes of impervious area and potential flow paths on the surface. Estimates of flood prone areas, as well as the expected annual damage due to flooding, are returned to the socio-economic model...... as an input for further refinement of the scenarios for the urban development. Our results in an Australian case study suggest that urban development is a major driver for flood risk and vice versa that flood risk can be significantly reduced if it is accounted for in the development of the cities...

  14. A new methodology for modelling of health risk from urban flooding exemplified by cholera

    Mark, Ole; Jørgensen, Claus; Hammond, Michael

    2016-01-01

    outlines a novel methodology for linking dynamic urban flood modelling with quantitative microbial risk assessment (QMRA). This provides a unique possibility for understanding the interaction between urban flooding and health risk caused by direct human contact with the flood water and hence gives...... and mortality, especially during floods. At present, there are no software tools capable of combining hydrodynamic modelling and health risk analyses, and the links between urban flooding and the health risk for the population due to direct contact with the flood water are poorly understood. The present paper...... an option for reducing the burden of disease in the population by use of intelligent urban flood risk management. The model linking urban flooding and health risk is applied to Dhaka City in Bangladesh, where waterborne diseases including cholera are endemic. The application to Dhaka City is supported...

  15. Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

    Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

    2016-12-01

    One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

  16. Global nuclear material control model

    Dreicer, J.S.; Rutherford, D.A.

    1996-01-01

    The nuclear danger can be reduced by a system for global management, protection, control, and accounting as part of a disposition program for special nuclear materials. The development of an international fissile material management and control regime requires conceptual research supported by an analytical and modeling tool that treats the nuclear fuel cycle as a complete system. Such a tool must represent the fundamental data, information, and capabilities of the fuel cycle including an assessment of the global distribution of military and civilian fissile material inventories, a representation of the proliferation pertinent physical processes, and a framework supportive of national or international perspective. They have developed a prototype global nuclear material management and control systems analysis capability, the Global Nuclear Material Control (GNMC) model. The GNMC model establishes the framework for evaluating the global production, disposition, and safeguards and security requirements for fissile nuclear material

  17. Physiologically-based toxicokinetic models help identifying the key factors affecting contaminant uptake during flood events

    Brinkmann, Markus; Eichbaum, Kathrin [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Kammann, Ulrike [Thünen-Institute of Fisheries Ecology, Palmaille 9, 22767 Hamburg (Germany); Hudjetz, Sebastian [Department of Ecosystem Analysis, Institute for Environmental Research,ABBt – Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Cofalla, Catrina [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Buchinger, Sebastian; Reifferscheid, Georg [Federal Institute of Hydrology (BFG), Department G3: Biochemistry, Ecotoxicology, Am Mainzer Tor 1, 56068 Koblenz (Germany); Schüttrumpf, Holger [Institute of Hydraulic Engineering and Water Resources Management, RWTH Aachen University, Mies-van-der-Rohe-Straße 1, 52056 Aachen (Germany); Preuss, Thomas [Department of Environmental Biology and Chemodynamics, Institute for Environmental Research,ABBt- Aachen Biology and Biotechnology, RWTH Aachen University, Worringerweg 1, 52074 Aachen (Germany); and others

    2014-07-01

    Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios.

  18. Physiologically-based toxicokinetic models help identifying the key factors affecting contaminant uptake during flood events

    Brinkmann, Markus; Eichbaum, Kathrin; Kammann, Ulrike; Hudjetz, Sebastian; Cofalla, Catrina; Buchinger, Sebastian; Reifferscheid, Georg; Schüttrumpf, Holger; Preuss, Thomas

    2014-01-01

    Highlights: • A PBTK model for trout was coupled with a sediment equilibrium partitioning model. • The influence of physical exercise on pollutant uptake was studies using the model. • Physical exercise during flood events can increase the level of biliary metabolites. • Cardiac output and effective respiratory volume were identified as relevant factors. • These confounding factors need to be considered also for bioconcentration studies. - Abstract: As a consequence of global climate change, we will be likely facing an increasing frequency and intensity of flood events. Thus, the ecotoxicological relevance of sediment re-suspension is of growing concern. It is vital to understand contaminant uptake from suspended sediments and relate it to effects in aquatic biota. Here we report on a computational study that utilizes a physiologically based toxicokinetic model to predict uptake, metabolism and excretion of sediment-borne pyrene in rainbow trout (Oncorhynchus mykiss). To this end, data from two experimental studies were compared with the model predictions: (a) batch re-suspension experiments with constant concentration of suspended particulate matter at two different temperatures (12 and 24 °C), and (b) simulated flood events in an annular flume. The model predicted both the final concentrations and the kinetics of 1-hydroxypyrene secretion into the gall bladder of exposed rainbow trout well. We were able to show that exhaustive exercise during exposure in simulated flood events can lead to increased levels of biliary metabolites and identified cardiac output and effective respiratory volume as the two most important factors for contaminant uptake. The results of our study clearly demonstrate the relevance and the necessity to investigate uptake of contaminants from suspended sediments under realistic exposure scenarios

  19. High resolution modelling of wind fields for optimization of empirical storm flood predictions

    Brecht, B.; Frank, H.

    2014-05-01

    High resolution wind fields are necessary to predict the occurrence of storm flood events and their magnitude. Deutscher Wetterdienst (DWD) created a catalogue of detailed wind fields of 39 historical storms at the German North Sea coast from the years 1962 to 2011. The catalogue is used by the Niedersächsisches Landesamt für Wasser-, Küsten- und Naturschutz (NLWKN) coastal research center to improve their flood alert service. The computation of wind fields and other meteorological parameters is based on the model chain of the DWD going from the global model GME via the limited-area model COSMO with 7 km mesh size down to a COSMO model with 2.2 km. To obtain an improved analysis COSMO runs are nudged against observations for the historical storms. The global model GME is initialised from the ERA reanalysis data of the European Centre for Medium-Range Weather Forecasts (ECMWF). As expected, we got better congruency with observations of the model for the nudging runs than the normal forecast runs for most storms. We also found during the verification process that different land use data sets could influence the results considerably.

  20. Viscoelastic Flow Modelling for Polymer Flooding

    de, Shauvik; Padding, Johan; Peters, Frank; Kuipers, Hans; Multi-scale Modelling of Multi-phase Flows Team

    2015-11-01

    Polymer liquids are used in the oil industry to improve the volumetric sweep and displacement efficiency of oil from a reservoir. Surprisingly, it is not only the viscosity but also the elasticity of the displacing fluid that determine the displacement efficiency. The main aim of our work is to obtain a fundamental understanding of the effect of fluid elasticity, by developing an advanced computer simulation methodology for the flow of non-Newtonian fluids through porous media. We simulate a 3D unsteady viscoelastic flow through a converging diverging geometry of realistic pore dimension using computational fluid dynamics (CFD).The primitive variables velocity, pressure and extra stresses are used in the formulation of models. The viscoelastic stress part is formulated using a FENE-P type of constitutive equation, which can predict both shear and elongational stress properties during this flow. A Direct Numerical Simulation (DNS) approach using Finite volume method (FVM) with staggered grid has been applied. A novel second order Immersed boundary method (IBM) has been incorporated to mimic porous media. The effect of rheological parameters on flow characteristics has also been studied. The simulations provide an insight into 3D flow asymmetry at higher Deborah numbers. Micro-Particle Image Velocimetry experiments are carried out to obtain further insights. These simulations present, for the first time, a detailed computational study of the effects of fluid elasticity on the imbibition of an oil phase.

  1. Citizen observations contributing to flood modelling: opportunities and challenges

    T. H. Assumpção

    2018-02-01

    Full Text Available Citizen contributions to science have been successfully implemented in many fields, and water resources is one of them. Through citizens, it is possible to collect data and obtain a more integrated decision-making process. Specifically, data scarcity has always been an issue in flood modelling, which has been addressed in the last decades by remote sensing and is already being discussed in the citizen science context. With this in mind, this article aims to review the literature on the topic and analyse the opportunities and challenges that lie ahead. The literature on monitoring, mapping and modelling, was evaluated according to the flood-related variable citizens contributed to. Pros and cons of the collection/analysis methods were summarised. Then, pertinent publications were mapped into the flood modelling cycle, considering how citizen data properties (spatial and temporal coverage, uncertainty and volume are related to its integration into modelling. It was clear that the number of studies in the area is rising. There are positive experiences reported in collection and analysis methods, for instance with velocity and land cover, and also when modelling is concerned, for example by using social media mining. However, matching the data properties necessary for each part of the modelling cycle with citizen-generated data is still challenging. Nevertheless, the concept that citizen contributions can be used for simulation and forecasting is proved and further work lies in continuing to develop and improve not only methods for collection and analysis, but certainly for integration into models as well. Finally, in view of recent automated sensors and satellite technologies, it is through studies as the ones analysed in this article that the value of citizen contributions, complementing such technologies, is demonstrated.

  2. Citizen observations contributing to flood modelling: opportunities and challenges

    Assumpção, Thaine H.; Popescu, Ioana; Jonoski, Andreja; Solomatine, Dimitri P.

    2018-02-01

    Citizen contributions to science have been successfully implemented in many fields, and water resources is one of them. Through citizens, it is possible to collect data and obtain a more integrated decision-making process. Specifically, data scarcity has always been an issue in flood modelling, which has been addressed in the last decades by remote sensing and is already being discussed in the citizen science context. With this in mind, this article aims to review the literature on the topic and analyse the opportunities and challenges that lie ahead. The literature on monitoring, mapping and modelling, was evaluated according to the flood-related variable citizens contributed to. Pros and cons of the collection/analysis methods were summarised. Then, pertinent publications were mapped into the flood modelling cycle, considering how citizen data properties (spatial and temporal coverage, uncertainty and volume) are related to its integration into modelling. It was clear that the number of studies in the area is rising. There are positive experiences reported in collection and analysis methods, for instance with velocity and land cover, and also when modelling is concerned, for example by using social media mining. However, matching the data properties necessary for each part of the modelling cycle with citizen-generated data is still challenging. Nevertheless, the concept that citizen contributions can be used for simulation and forecasting is proved and further work lies in continuing to develop and improve not only methods for collection and analysis, but certainly for integration into models as well. Finally, in view of recent automated sensors and satellite technologies, it is through studies as the ones analysed in this article that the value of citizen contributions, complementing such technologies, is demonstrated.

  3. Relating climate change policy to poverty policy: assessing the global exposure of the poor to floods and droughts

    Winsemius, Hessel; Jongman, Brenden; Veldkamp, Ted; Hallegatte, Stéphane; Bangalore, Mook; Ward, Philip

    2016-04-01

    Prior to the COP21 conference in Paris this year, the World Bank published a report called "Shockwaves - Managing the Impacts of Climate Change on Poverty". The report flagged that ending poverty and stabilizing climate change should be jointly tackled and that without a good joint policy, a further 100 million people could become trapped in poverty by 2050. As part of the "Shockwaves" report, we investigated whether low-income households are disproportionately overrepresented in hazard-prone areas compared to households with higher income. Furthermore, the hazardous conditions under which poor households are exposed to now may become worse due to climate change with resulting increases in intensity and frequency of floods and droughts. We also show how the amount of affected people to these natural hazards change in the future if nothing is done. We use recent advances in the global spatial modeling of flood and drought hazard and a large sample of household surveys containing asset and income data to explore the relationships.

  4. Future changes in extreme precipitation in the Rhine basin based on global and regional climate model simulations

    Pelt, van S.C.; Beersma, J.J.; Buishand, T.A.; Hurk, van den B.J.J.M.; Kabat, P.

    2012-01-01

    Probability estimates of the future change of extreme precipitation events are usually based on a limited number of available global climate model (GCM) or regional climate model (RCM) simulations. Since floods are related to heavy precipitation events, this restricts the assessment of flood risks.

  5. 3D GIS FOR FLOOD MODELLING IN RIVER VALLEYS

    P. Tymkow

    2016-06-01

    Full Text Available The objective of this study is implementation of system architecture for collecting and analysing data as well as visualizing results for hydrodynamic modelling of flood flows in river valleys using remote sensing methods, tree-dimensional geometry of spatial objects and GPU multithread processing. The proposed solution includes: spatial data acquisition segment, data processing and transformation, mathematical modelling of flow phenomena and results visualization. Data acquisition segment was based on aerial laser scanning supplemented by images in visible range. Vector data creation was based on automatic and semiautomatic algorithms of DTM and 3D spatial features modelling. Algorithms for buildings and vegetation geometry modelling were proposed or adopted from literature. The implementation of the framework was designed as modular software using open specifications and partially reusing open source projects. The database structure for gathering and sharing vector data, including flood modelling results, was created using PostgreSQL. For the internal structure of feature classes of spatial objects in a database, the CityGML standard was used. For the hydrodynamic modelling the solutions of Navier-Stokes equations in two-dimensional version was implemented. Visualization of geospatial data and flow model results was transferred to the client side application. This gave the independence from server hardware platform. A real-world case in Poland, which is a part of Widawa River valley near Wroclaw city, was selected to demonstrate the applicability of proposed system.

  6. Hydrodynamic modelling and global datasets: Flow connectivity and SRTM data, a Bangkok case study.

    Trigg, M. A.; Bates, P. B.; Michaelides, K.

    2012-04-01

    The rise in the global interconnected manufacturing supply chains requires an understanding and consistent quantification of flood risk at a global scale. Flood risk is often better quantified (or at least more precisely defined) in regions where there has been an investment in comprehensive topographical data collection such as LiDAR coupled with detailed hydrodynamic modelling. Yet in regions where these data and modelling are unavailable, the implications of flooding and the knock on effects for global industries can be dramatic, as evidenced by the recent floods in Bangkok, Thailand. There is a growing momentum in terms of global modelling initiatives to address this lack of a consistent understanding of flood risk and they will rely heavily on the application of available global datasets relevant to hydrodynamic modelling, such as Shuttle Radar Topography Mission (SRTM) data and its derivatives. These global datasets bring opportunities to apply consistent methodologies on an automated basis in all regions, while the use of coarser scale datasets also brings many challenges such as sub-grid process representation and downscaled hydrology data from global climate models. There are significant opportunities for hydrological science in helping define new, realistic and physically based methodologies that can be applied globally as well as the possibility of gaining new insights into flood risk through analysis of the many large datasets that will be derived from this work. We use Bangkok as a case study to explore some of the issues related to using these available global datasets for hydrodynamic modelling, with particular focus on using SRTM data to represent topography. Research has shown that flow connectivity on the floodplain is an important component in the dynamics of flood flows on to and off the floodplain, and indeed within different areas of the floodplain. A lack of representation of flow connectivity, often due to data resolution limitations, means

  7. Flood Hazard Mapping by Using Geographic Information System and Hydraulic Model: Mert River, Samsun, Turkey

    Vahdettin Demir

    2016-01-01

    Full Text Available In this study, flood hazard maps were prepared for the Mert River Basin, Samsun, Turkey, by using GIS and Hydrologic Engineering Centers River Analysis System (HEC-RAS. In this river basin, human life losses and a significant amount of property damages were experienced in 2012 flood. The preparation of flood risk maps employed in the study includes the following steps: (1 digitization of topographical data and preparation of digital elevation model using ArcGIS, (2 simulation of flood lows of different return periods using a hydraulic model (HEC-RAS, and (3 preparation of flood risk maps by integrating the results of (1 and (2.

  8. Urban flood return period assessment through rainfall-flood response modelling

    Murla, Damian; Thorndahl, Søren Liedtke

    Intense rainfall can often cause severe floods, especially in urbanized areas, where population density or large impermeable areas are found. In this context, floods can generate a direct impact in a social-environmental-economic viewpoint. Traditionally, in design of Urban Drainage Systems (UDS......), correlation between return period (RP) of a given rainfall and RP of its consequent flood has been assumed to be linear (e.g.DS/EN752 (2008)). However, this is not always the case. Complex UDS, where diverse hydraulic infrastructures are often found, increase the heterogeneity of system response, which may...... cause an alteration of the mentioned correlation. Consequently, reliability on future urban planning, design and resilience against floods may be also affected by this misassumption. In this study, an assessment of surface flood RP across rainfall RP has been carried out at Lystrup, a urbanized...

  9. Using remotely sensed data and stochastic models to simulate realistic flood hazard footprints across the continental US

    Bates, P. D.; Quinn, N.; Sampson, C. C.; Smith, A.; Wing, O.; Neal, J. C.

    2017-12-01

    Remotely sensed data has transformed the field of large scale hydraulic modelling. New digital elevation, hydrography and river width data has allowed such models to be created for the first time, and remotely sensed observations of water height, slope and water extent has allowed them to be calibrated and tested. As a result, we are now able to conduct flood risk analyses at national, continental or even global scales. However, continental scale analyses have significant additional complexity compared to typical flood risk modelling approaches. Traditional flood risk assessment uses frequency curves to define the magnitude of extreme flows at gauging stations. The flow values for given design events, such as the 1 in 100 year return period flow, are then used to drive hydraulic models in order to produce maps of flood hazard. Such an approach works well for single gauge locations and local models because over relatively short river reaches (say 10-60km) one can assume that the return period of an event does not vary. At regional to national scales and across multiple river catchments this assumption breaks down, and for a given flood event the return period will be different at different gauging stations, a pattern known as the event `footprint'. Despite this, many national scale risk analyses still use `constant in space' return period hazard layers (e.g. the FEMA Special Flood Hazard Areas) in their calculations. Such an approach can estimate potential exposure, but will over-estimate risk and cannot determine likely flood losses over a whole region or country. We address this problem by using a stochastic model to simulate many realistic extreme event footprints based on observed gauged flows and the statistics of gauge to gauge correlations. We take the entire USGS gauge data catalogue for sites with > 45 years of record and use a conditional approach for multivariate extreme values to generate sets of flood events with realistic return period variation in

  10. Rice in cropping systems - Modelling transitions between flooded and non-flooded soil environments

    Gaydon, D.S.; Probert, M.E.; Buresh, R.J.; Meinke, H.B.; Suriadi, A.; Dobermann, A.; Bouman, B.A.M.; Timsina, J.

    2012-01-01

    Water shortages in many rice-growing regions, combined with growing global imperatives to increase food production, are driving research into increased water use efficiency and modified agricultural practices in rice-based cropping systems. Well-tested cropping systems models that capture

  11. Flash flooding: Toward an Interdisciplinary and Integrated Strategy for Disaster Reduction in a Global Environmental Change Perspective

    Ruin, Isabelle

    2014-05-01

    How do people answer to heavy precipitation and flood warnings? How do they adapt their daily schedule and activity to the fast evolution of the environmental circumstances? More generally, how do social processes interact with physical ones? Such questions address the dynamical interactions between hydro-meteorological variables, human perception and representation of the environment, and actual individual and social behavioral responses. It also poses the question of scales and hierarchy issues through seamless interactions between smaller and larger scales. These questions are relevant for both social and physical scientists. They are more and more pertinently addressed in the Global Environmental Change perspective through the concepts of Coupled Human And Natural Systems (CHANS), resilience or panarchy developped in the context of interdisciplinary collaborations. Nevertheless those concepts are complex and not easy to handle, specially when facing with operational goals. One of the main difficulty to advance these integrated approaches is the access to empirical data informing the processes at various scales. In fact, if physical and social processes are well studied by distinct disciplines, they are rarely jointly explored within similar spatial and temporal resolutions. Such coupled observation and analysis poses methodological challenges, specially when dealing with responses to short-fuse and extreme weather events. In fact, if such coupled approach is quite common to study large scale phenomenon like global change (for instance using historical data on green house gaz emissions and the evolution of temperatures worldwide), it is rarer for studing smaller nested sets of scales of human-nature systems where finer resolution data are sparse. Another problem arise from the need to produce comparable analysis on different case studies where social, physical and even cultural contexts may be diverse. Generic and robust framework for data collection, modeling

  12. Coupling meteorological and hydrological models for flood forecasting

    Bartholmes

    2005-01-01

    Full Text Available This paper deals with the problem of analysing the coupling of meteorological meso-scale quantitative precipitation forecasts with distributed rainfall-runoff models to extend the forecasting horizon. Traditionally, semi-distributed rainfall-runoff models have been used for real time flood forecasting. More recently, increased computer capabilities allow the utilisation of distributed hydrological models with mesh sizes from tenths of metres to a few kilometres. On the other hand, meteorological models, providing the quantitative precipitation forecast, tend to produce average values on meshes ranging from slightly less than 10 to 200 kilometres. Therefore, to improve the quality of flood forecasts, the effects of coupling the meteorological and the hydrological models at different scales were analysed. A distributed hydrological model (TOPKAPI was developed and calibrated using a 1x1 km mesh for the case of the river Po closed at Ponte Spessa (catchment area c. 37000 km2. The model was then coupled with several other European meteorological models ranging from the Limited Area Models (provided by DMI and DWD with resolutions from 0.0625° * 0.0625°, to the ECMWF ensemble predictions with a resolution of 1.85° * 1.85°. Interesting results, describing the coupled model behaviour, are available for a meteorological extreme event in Northern Italy (Nov. 1994. The results demonstrate the poor reliability of the quantitative precipitation forecasts produced by meteorological models presently available; this is not resolved using the Ensemble Forecasting technique, when compared with results obtainable with measured rainfall.

  13. "Know What to Do If You Encounter a Flash Flood": Mental Models Analysis for Improving Flash Flood Risk Communication and Public Decision Making.

    Lazrus, Heather; Morss, Rebecca E; Demuth, Julie L; Lazo, Jeffrey K; Bostrom, Ann

    2016-02-01

    Understanding how people view flash flood risks can help improve risk communication, ultimately improving outcomes. This article analyzes data from 26 mental models interviews about flash floods with members of the public in Boulder, Colorado, to understand their perspectives on flash flood risks and mitigation. The analysis includes a comparison between public and professional perspectives by referencing a companion mental models study of Boulder-area professionals. A mental models approach can help to diagnose what people already know about flash flood risks and responses, as well as any critical gaps in their knowledge that might be addressed through improved risk communication. A few public interviewees mentioned most of the key concepts discussed by professionals as important for flash flood warning decision making. However, most interviewees exhibited some incomplete understandings and misconceptions about aspects of flash flood development and exposure, effects, or mitigation that may lead to ineffective warning decisions when a flash flood threatens. These include important misunderstandings about the rapid evolution of flash floods, the speed of water in flash floods, the locations and times that pose the greatest flash flood risk in Boulder, the value of situational awareness and environmental cues, and the most appropriate responses when a flash flood threatens. The findings point to recommendations for ways to improve risk communication, over the long term and when an event threatens, to help people quickly recognize and understand threats, obtain needed information, and make informed decisions in complex, rapidly evolving extreme weather events such as flash floods. © 2015 Society for Risk Analysis.

  14. Estimating design flood and HEC-RAS modelling approach for flood analysis in Bojonegoro city

    Prastica, R. M. S.; Maitri, C.; Hermawan, A.; Nugroho, P. C.; Sutjiningsih, D.; Anggraheni, E.

    2018-03-01

    Bojonegoro faces flood every year with less advanced prevention development. Bojonegoro city development could not peak because the flood results material losses. It affects every sectors in Bojonegoro: education, politics, economy, social, and infrastructure development. This research aims to analyse and to ensure that river capacity has high probability to be the main factor of flood in Bojonegoro. Flood discharge analysis uses Nakayasu synthetic unit hydrograph for period of 5 years, 10 years, 25 years, 50 years, and 100 years. They would be compared to the water maximum capacity that could be loaded by downstream part of Bengawan Solo River in Bojonegoro. According to analysis result, Bengawan Solo River in Bojonegoro could not able to load flood discharges. Another method used is HEC-RAS analysis. The conclusion that shown by HEC-RAS analysis has the same view. It could be observed that flood water loading is more than full bank capacity elevation in the river. To conclude, the main factor that should be noticed by government to solve flood problem is river capacity.

  15. Surface water flood risk and management strategies for London: An Agent-Based Model approach

    Jenkins Katie

    2016-01-01

    Full Text Available Flooding is recognised as one of the most common and costliest natural disasters in England. Flooding in urban areas during heavy rainfall is known as ‘surface water flooding’, considered to be the most likely cause of flood events and one of the greatest short-term climate risks for London. In this paper we present results from a novel Agent-Based Model designed to assess the interplay between different adaptation options, different agents, and the role of flood insurance and the flood insurance pool, Flood Re, in the context of climate change. The model illustrates how investment in adaptation options could reduce London’s surface water flood risk, today and in the future. However, benefits can be outweighed by continued development in high risk areas and the effects of climate change. Flood Re is beneficial in its function to provide affordable insurance, even under climate change. However, it offers no additional benefits in terms of overall risk reduction, and will face increasing pressure due to rising surface water flood risk in the future. The modelling approach and findings are highly relevant for reviewing the proposed Flood Re scheme, as well as for wider discussions on the potential of insurance schemes, and broader multi-sectoral partnerships, to incentivise flood risk management in the UK and internationally.

  16. Flood Hazard Mapping using Hydraulic Model and GIS: A Case Study in Mandalay City, Myanmar

    Kyu Kyu Sein

    2016-01-01

    Full Text Available This paper presents the use of flood frequency analysis integrating with 1D Hydraulic model (HECRAS and Geographic Information System (GIS to prepare flood hazard maps of different return periods in Ayeyarwady River at Mandalay City in Myanmar. Gumbel’s distribution was used to calculate the flood peak of different return periods, namely, 10 years, 20 years, 50 years, and 100 years. The flood peak from frequency analysis were input into HEC-RAS model to find the corresponding flood level and extents in the study area. The model results were used in integrating with ArcGIS to generate flood plain maps. Flood depths and extents have been identified through flood plain maps. Analysis of 100 years return period flood plain map indicated that 157.88 km2 with the percentage of 17.54% is likely to be inundated. The predicted flood depth ranges varies from greater than 0 to 24 m in the flood plains and on the river. The range between 3 to 5 m were identified in the urban area of Chanayetharzan, Patheingyi, and Amarapua Townships. The highest inundated area was 85 km2 in the Amarapura Township.

  17. Flood risk and adaptation strategies under climate change and urban expansion: A probabilistic analysis using global data

    Muis, S.; Güneralp, B.; Jongman, B.; Aerts, J.C.J.H.; Ward, P.J.

    2015-01-01

    An accurate understanding of flood risk and its drivers is crucial for effective risk management. Detailed risk projections, including uncertainties, are however rarely available, particularly in developing countries. This paper presents a method that integrates recent advances in global-scale

  18. The Global Tsunami Model (GTM)

    Lorito, S.; Basili, R.; Harbitz, C. B.; Løvholt, F.; Polet, J.; Thio, H. K.

    2017-12-01

    The tsunamis occurred worldwide in the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but often disastrous tsunamis and the importance of a comprehensive and consistent methodology for quantifying the hazard. In the last few years, several methods for probabilistic tsunami hazard analysis have been developed and applied to different parts of the world. In an effort to coordinate and streamline these activities and make progress towards implementing the Sendai Framework of Disaster Risk Reduction (SFDRR) we have initiated a Global Tsunami Model (GTM) working group with the aim of i) enhancing our understanding of tsunami hazard and risk on a global scale and developing standards and guidelines for it, ii) providing a portfolio of validated tools for probabilistic tsunami hazard and risk assessment at a range of scales, and iii) developing a global tsunami hazard reference model. This GTM initiative has grown out of the tsunami component of the Global Assessment of Risk (GAR15), which has resulted in an initial global model of probabilistic tsunami hazard and risk. Started as an informal gathering of scientists interested in advancing tsunami hazard analysis, the GTM is currently in the process of being formalized through letters of interest from participating institutions. The initiative has now been endorsed by the United Nations International Strategy for Disaster Reduction (UNISDR) and the World Bank's Global Facility for Disaster Reduction and Recovery (GFDRR). We will provide an update on the state of the project and the overall technical framework, and discuss the technical issues that are currently being addressed, including earthquake source recurrence models, the use of aleatory variability and epistemic uncertainty, and preliminary results for a probabilistic global hazard assessment, which is an update of the model included in UNISDR GAR15.

  19. Dynamic building risk assessment theoretic model for rainstorm-flood utilization ABM and ABS

    Lai, Wenze; Li, Wenbo; Wang, Hailei; Huang, Yingliang; Wu, Xuelian; Sun, Bingyun

    2015-12-01

    Flood is one of natural disasters with the worst loss in the world. It needs to assess flood disaster risk so that we can reduce the loss of flood disaster. Disaster management practical work needs the dynamic risk results of building. Rainstorm flood disaster system is a typical complex system. From the view of complex system theory, flood disaster risk is the interaction result of hazard effect objects, rainstorm flood hazard factors, and hazard environments. Agent-based modeling (ABM) is an important tool for complex system modeling. Rainstorm-flood building risk dynamic assessment method (RFBRDAM) was proposed using ABM in this paper. The interior structures and procedures of different agents in proposed meth had been designed. On the Netlogo platform, the proposed method was implemented to assess the building risk changes of the rainstorm flood disaster in the Huaihe River Basin using Agent-based simulation (ABS). The results indicated that the proposed method can dynamically assess building risk of the whole process for the rainstorm flood disaster. The results of this paper can provide one new approach for flood disaster building risk dynamic assessment and flood disaster management.

  20. Hurricane Harvey Riverine Flooding: Part 1 - Reconstruction of Hurricane Harvey Flooding for Harris County, TX using a GPU-accelerated 2D flood model for post-flood hazard analysis

    Kalyanapu, A. J.; Dullo, T. T.; Gangrade, S.; Kao, S. C.; Marshall, R.; Islam, S. R.; Ghafoor, S. K.

    2017-12-01

    Hurricane Harvey that made landfall in the southern Texas this August is one of the most destructive hurricanes during the 2017 hurricane season. During its active period, many areas in coastal Texas region received more than 40 inches of rain. This downpour caused significant flooding resulting in about 77 casualties, displacing more than 30,000 people, inundating hundreds of thousands homes and is currently estimated to have caused more than $70 billion in direct damage. One of the significantly affected areas is Harris County where the city of Houston, TX is located. Covering over two HUC-8 drainage basins ( 2702 mi2), this county experienced more than 80% of its annual average rainfall during this event. This study presents an effort to reconstruct flooding caused by extreme rainfall due to Hurricane Harvey in Harris County, Texas. This computationally intensive task was performed at a 30-m spatial resolution using a rapid flood model called Flood2D-GPU, a graphics processing unit (GPU) accelerated model, on Oak Ridge National Laboratory's (ORNL) Titan Supercomputer. For this task, the hourly rainfall estimates from the National Center for Environmental Prediction Stage IV Quantitative Precipitation Estimate were fed into the Variable Infiltration Capacity (VIC) hydrologic model and Routing Application for Parallel computation of Discharge (RAPID) routing model to estimate flow hydrographs at 69 locations for Flood2D-GPU simulation. Preliminary results of the simulation including flood inundation extents, maps of flood depths and inundation duration will be presented. Future efforts will focus on calibrating and validating the simulation results and assessing the flood damage for better understanding the impacts made by Hurricane Harvey.

  1. Linking Earth Observations and Models to Societal Information Needs: The Case of Coastal Flooding

    Buzzanga, B. A.; Plag, H. P.

    2016-12-01

    Coastal flooding is expected to increase in many areas due to sea level rise (SLR). Many societal applications such as emergency planning and designing public services depend on information on how the flooding spectrum may change as a result of SLR. To identify the societal information needs a conceptual model is needed that identifies the key stakeholders, applications, and information and observation needs. In the context of the development of the Global Earth Observation System of Systems (GEOSS), which is implemented by the Group on Earth Observations (GEO), the Socio-Economic and Environmental Information Needs Knowledge Base (SEE-IN KB) is developed as part of the GEOSS Knowledge Base. A core function of the SEE-IN KB is to facilitate the linkage of societal information needs to observations, models, information and knowledge. To achieve this, the SEE-IN KB collects information on objects such as user types, observational requirements, societal goals, models, and datasets. Comprehensive information concerning the interconnections between instances of these objects is used to capture the connectivity and to establish a conceptual model as a network of networks. The captured connectivity can be used in searches to allow users to discover products and services for their information needs, and providers to search for users and applications benefiting from their products. It also allows to answer "What if?" questions and supports knowledge creation. We have used the SEE-IN KB to develop a conceptual model capturing the stakeholders in coastal flooding and their information needs, and to link these elements to objects. We show how the knowledge base enables the transition of scientific data to useable information by connecting individuals such as city managers to flood maps. Within the knowledge base, these same users can request information that improves their ability to make specific planning decisions. These needs are linked to entities within research

  2. Three dimensional numerical modeling of flow and pollutant transport in a flooding area of 2008 US Midwest Flood

    This paper presents the development and application of a three-dimensional numerical model for simulating the flow field and pollutant transport in a flood zone near the confluence of the Mississippi River and Iowa River in Oakville, Iowa. Due to a levee breaching along the Iowa River during the US ...

  3. Use of a dam break model to assess flooding at Haddam Neck Nuclear Power Plant

    Scherrer, J.S.; Chery, D.L. Jr.

    1984-01-01

    Because of their proximity to necessary supplies of cooling water, nuclear power plants are susceptible to riverine flooding. Greater flood hazards exist where plants are located downstream of larger dams. The consequences of the Quabbin Reservoir dam failure on the Haddam Neck Nuclear Power Plant situated on the Connecticut River were investigated using a dam break flood routing model. Reasons for selecting a particular model are presented and the input assumption for the modeling process are developed. Relevant information concerning the level of manpower involvement is presented. The findings of this analysis demonstrate that the plant is adequately protected from the consequences of the postulated flood event

  4. Flood-inundation and flood-mitigation modeling of the West Branch Wapsinonoc Creek Watershed in West Branch, Iowa

    Cigrand, Charles V.

    2018-03-26

    The U.S. Geological Survey (USGS) in cooperation with the city of West Branch and the Herbert Hoover National Historic Site of the National Park Service assessed flood-mitigation scenarios within the West Branch Wapsinonoc Creek watershed. The scenarios are intended to demonstrate several means of decreasing peak streamflows and improving the conveyance of overbank flows from the West Branch Wapsinonoc Creek and its tributary Hoover Creek where they flow through the city and the Herbert Hoover National Historic Site located within the city.Hydrologic and hydraulic models of the watershed were constructed to assess the flood-mitigation scenarios. To accomplish this, the models used the U.S. Army Corps of Engineers Hydrologic Engineering Center-Hydrologic Modeling System (HEC–HMS) version 4.2 to simulate the amount of runoff and streamflow produced from single rain events. The Hydrologic Engineering Center-River Analysis System (HEC–RAS) version 5.0 was then used to construct an unsteady-state model that may be used for routing streamflows, mapping areas that may be inundated during floods, and simulating the effects of different measures taken to decrease the effects of floods on people and infrastructure.Both models were calibrated to three historic rainfall events that produced peak streamflows ranging between the 2-year and 10-year flood-frequency recurrence intervals at the USGS streamgage (05464942) on Hoover Creek. The historic rainfall events were calibrated by using data from two USGS streamgages along with surveyed high-water marks from one of the events. The calibrated HEC–HMS model was then used to simulate streamflows from design rainfall events of 24-hour duration ranging from a 20-percent to a 1-percent annual exceedance probability. These simulated streamflows were incorporated into the HEC–RAS model.The unsteady-state HEC–RAS model was calibrated to represent existing conditions within the watershed. HEC–RAS model simulations with the

  5. Uncertainty Analysis of Multi-Model Flood Forecasts

    Erich J. Plate

    2015-12-01

    Full Text Available This paper demonstrates, by means of a systematic uncertainty analysis, that the use of outputs from more than one model can significantly improve conditional forecasts of discharges or water stages, provided the models are structurally different. Discharge forecasts from two models and the actual forecasted discharge are assumed to form a three-dimensional joint probability density distribution (jpdf, calibrated on long time series of data. The jpdf is decomposed into conditional probability density distributions (cpdf by means of Bayes formula, as suggested and explored by Krzysztofowicz in a series of papers. In this paper his approach is simplified to optimize conditional forecasts for any set of two forecast models. Its application is demonstrated by means of models developed in a study of flood forecasting for station Stung Treng on the middle reach of the Mekong River in South-East Asia. Four different forecast models were used and pairwise combined: forecast with no model, with persistence model, with a regression model, and with a rainfall-runoff model. Working with cpdfs requires determination of dependency among variables, for which linear regressions are required, as was done by Krzysztofowicz. His Bayesian approach based on transforming observed probability distributions of discharges and forecasts into normal distributions is also explored. Results obtained with his method for normal prior and likelihood distributions are identical to results from direct multiple regressions. Furthermore, it is shown that in the present case forecast accuracy is only marginally improved, if Weibull distributed basic data were converted into normally distributed variables.

  6. Flood susceptibility analysis through remote sensing, GIS and frequency ratio model

    Samanta, Sailesh; Pal, Dilip Kumar; Palsamanta, Babita

    2018-05-01

    Papua New Guinea (PNG) is saddled with frequent natural disasters like earthquake, volcanic eruption, landslide, drought, flood etc. Flood, as a hydrological disaster to humankind's niche brings about a powerful and often sudden, pernicious change in the surface distribution of water on land, while the benevolence of flood manifests in restoring the health of the thalweg from excessive siltation by redistributing the fertile sediments on the riverine floodplains. In respect to social, economic and environmental perspective, flood is one of the most devastating disasters in PNG. This research was conducted to investigate the usefulness of remote sensing, geographic information system and the frequency ratio (FR) for flood susceptibility mapping. FR model was used to handle different independent variables via weighted-based bivariate probability values to generate a plausible flood susceptibility map. This study was conducted in the Markham riverine precinct under Morobe province in PNG. A historical flood inventory database of PNG resource information system (PNGRIS) was used to generate 143 flood locations based on "create fishnet" analysis. 100 (70%) flood sample locations were selected randomly for model building. Ten independent variables, namely land use/land cover, elevation, slope, topographic wetness index, surface runoff, landform, lithology, distance from the main river, soil texture and soil drainage were used into the FR model for flood vulnerability analysis. Finally, the database was developed for areas vulnerable to flood. The result demonstrated a span of FR values ranging from 2.66 (least flood prone) to 19.02 (most flood prone) for the study area. The developed database was reclassified into five (5) flood vulnerability zones segmenting on the FR values, namely very low (less that 5.0), low (5.0-7.5), moderate (7.5-10.0), high (10.0-12.5) and very high susceptibility (more than 12.5). The result indicated that about 19.4% land area as `very high

  7. Predicting the microbial exposure risks in urban floods using GIS, building simulation, and microbial models.

    Taylor, Jonathon; Biddulph, Phillip; Davies, Michael; Lai, Ka man

    2013-01-01

    London is expected to experience more frequent periods of intense rainfall and tidal surges, leading to an increase in the risk of flooding. Damp and flooded dwellings can support microbial growth, including mould, bacteria, and protozoa, as well as persistence of flood-borne microorganisms. The amount of time flooded dwellings remain damp will depend on the duration and height of the flood, the contents of the flood water, the drying conditions, and the building construction, leading to particular properties and property types being prone to lingering damp and human pathogen growth or persistence. The impact of flooding on buildings can be simulated using Heat Air and Moisture (HAM) models of varying complexity in order to understand how water can be absorbed and dry out of the building structure. This paper describes the simulation of the drying of building archetypes representative of the English building stock using the EnergyPlus based tool 'UCL-HAMT' in order to determine the drying rates of different abandoned structures flooded to different heights and during different seasons. The results are mapped out using GIS in order to estimate the spatial risk across London in terms of comparative flood vulnerability, as well as for specific flood events. Areas of South and East London were found to be particularly vulnerable to long-term microbial exposure following major flood events. Copyright © 2012 Elsevier Ltd. All rights reserved.

  8. Advances in flash floods understanding and modelling derived from the FloodScale project in South-East France

    Braud Isabelle

    2016-01-01

    Full Text Available The Mediterranean area is prone to intense rainfall events triggering flash floods, characterized by very short response times that sometimes lead to dramatic consequences in terms of casualties and damages. These events can affect large territories, but their impact may be very local in catchments that are generally ungauged. These events remain difficult to predict and the processes leading to their generation still need to be clarified. The HyMeX initiative (Hydrological Cycle in the Mediterranean Experiment, 2010-2020 aims at increasing our understanding of the water cycle in the Mediterranean basin, in particular in terms of extreme events. In order to better understand processes leading to flash floods, a four-year experiment (2012-2015 was conducted in the Cévennes region (South-East France as part of the FloodScale project. Both continuous and opportunistic measurements during floods were conducted in two large catchments (Ardèche and Gard rivers with nested instrumentation from the hillslopes to catchments of about 1, 10, 100 to 1000 km2 covering contrasted geology and land use. Continuous measurements include distributed rainfall, stream water level, discharge, water temperature and conductivity and soil moisture measurements. Opportunistic measurements include surface soil moisture and geochemistry sampling during events and gauging of floods using non-contact methods: portable radars to measure surface water velocity or image sequence analysis using LS-PIV (Large Scale Particle Image Velocimetry. During the period 2012-2014, and in particular during autumn 2014, several intense events affected the catchments and provided very rich data sets. Data collection was complemented with modelling activity aiming at simulating observed processes. The modelling strategy was setup through a wide range of scales, in order to test hypotheses about physical processes at the smallest scales, and aggregated functioning hypothesis at the largest

  9. Hydrological Modelling using HEC-HMS for Flood Risk Assessment of Segamat Town, Malaysia

    Romali, N. S.; Yusop, Z.; Ismail, A. Z.

    2018-03-01

    This paper presents an assessment of the applicability of using Hydrologic Modelling System developed by the Hydrologic Engineering Center (HEC-HMS) for hydrological modelling of Segamat River. The objective of the model application is to assist in the assessment of flood risk by providing the peak flows of 2011 Segamat flood for the generation of flood mapping of Segamat town. The capability of the model was evaluated by comparing the historical observed data with the simulation results of the selected flood events. The model calibration and validation efficiency was verified using Nash-Sutcliffe model efficiency coefficient. The results demonstrate the interest to implement the hydrological model for assessing flood risk where the simulated peak flow result is in agreement with historical observed data. The model efficiency of the calibrated and validated exercises is 0.90 and 0.76 respectively, which is acceptable.

  10. Using integrated modeling for generating watershed-scale dynamic flood maps for Hurricane Harvey

    Saksena, S.; Dey, S.; Merwade, V.; Singhofen, P. J.

    2017-12-01

    Hurricane Harvey, which was categorized as a 1000-year return period event, produced unprecedented rainfall and flooding in Houston. Although the expected rainfall was forecasted much before the event, there was no way to identify which regions were at higher risk of flooding, the magnitude of flooding, and when the impacts of rainfall would be highest. The inability to predict the location, duration, and depth of flooding created uncertainty over evacuation planning and preparation. This catastrophic event highlighted that the conventional approach to managing flood risk using 100-year static flood inundation maps is inadequate because of its inability to predict flood duration and extents for 500-year or 1000-year return period events in real-time. The purpose of this study is to create models that can dynamically predict the impacts of rainfall and subsequent flooding, so that necessary evacuation and rescue efforts can be planned in advance. This study uses a 2D integrated surface water-groundwater model called ICPR (Interconnected Channel and Pond Routing) to simulate both the hydrology and hydrodynamics for Hurricane Harvey. The methodology involves using the NHD stream network to create a 2D model that incorporates rainfall, land use, vadose zone properties and topography to estimate streamflow and generate dynamic flood depths and extents. The results show that dynamic flood mapping captures the flood hydrodynamics more accurately and is able to predict the magnitude, extent and time of occurrence for extreme events such as Hurricane Harvey. Therefore, integrated modeling has the potential to identify regions that are more susceptible to flooding, which is especially useful for large-scale planning and allocation of resources for protection against future flood risk.

  11. Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

    Haer, Toon; Aerts, Jeroen

    2015-04-01

    Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

  12. THE FLOOD RISK IN THE LOWER GIANH RIVER: MODELLING AND FIELD VERIFICATION

    NGUYEN H. D.

    2016-03-01

    Full Text Available Problems associated with flood risk definitely represent a highly topical issue in Vietnam. The case of the lower Gianh River in the central area of Vietnam, with a watershed area of 353 km2, is particularly interesting. In this area, periodically subject to flood risk, the scientific question is strongly linked to risk management. In addition, flood risk is the consequence of the hydrological hazard of an event and the damages related to this event. For this reason, our approach is based on hydrodynamic modelling using Mike Flood to simulate the runoff during a flood event. Unfortunately the data in the studied area are quite limited. Our computation of the flood risk is based on a three-step modelling process, using rainfall data coming from 8 stations, cross sections, the topographic map and the land-use map. The first step consists of creating a 1-D model using Mike 11, in order to simulate the runoff in the minor river bed. In the second step, we use Mike 21 to create a 2-D model to simulate the runoff in the flood plain. The last step allows us to couple the two models in order to precisely describe the variables for the hazard analysis in the flood plain (the water level, the speed, the extent of the flooding. Moreover the model is calibrated and verified using observational data of the water level at hydrologic stations and field control data (on the one hand flood height measurements, on the other hand interviews with the community and with the local councillors. We then generate GIS maps in order to improve flood hazard management, which allows us to create flood hazard maps by coupling the flood plain map and the runoff speed map. Our results show that: the flood peak, caused by typhoon Nari, reached more than 6 m on October 16th 2013 at 4 p.m. (its area was extended by 149 km². End that the typhoon constitutes an extreme flood hazard for 11.39%, very high for 10.60%, high for 30.79%, medium for 31.91% and a light flood hazard for 15

  13. Global scale groundwater flow model

    Sutanudjaja, Edwin; de Graaf, Inge; van Beek, Ludovicus; Bierkens, Marc

    2013-04-01

    As the world's largest accessible source of freshwater, groundwater plays vital role in satisfying the basic needs of human society. It serves as a primary source of drinking water and supplies water for agricultural and industrial activities. During times of drought, groundwater sustains water flows in streams, rivers, lakes and wetlands, and thus supports ecosystem habitat and biodiversity, while its large natural storage provides a buffer against water shortages. Yet, the current generation of global scale hydrological models does not include a groundwater flow component that is a crucial part of the hydrological cycle and allows the simulation of groundwater head dynamics. In this study we present a steady-state MODFLOW (McDonald and Harbaugh, 1988) groundwater model on the global scale at 5 arc-minutes resolution. Aquifer schematization and properties of this groundwater model were developed from available global lithological model (e.g. Dürr et al., 2005; Gleeson et al., 2010; Hartmann and Moorsdorff, in press). We force the groundwtaer model with the output from the large-scale hydrological model PCR-GLOBWB (van Beek et al., 2011), specifically the long term net groundwater recharge and average surface water levels derived from routed channel discharge. We validated calculated groundwater heads and depths with available head observations, from different regions, including the North and South America and Western Europe. Our results show that it is feasible to build a relatively simple global scale groundwater model using existing information, and estimate water table depths within acceptable accuracy in many parts of the world.

  14. Demand analysis of flood insurance by using logistic regression model and genetic algorithm

    Sidi, P.; Mamat, M. B.; Sukono; Supian, S.; Putra, A. S.

    2018-03-01

    Citarum River floods in the area of South Bandung Indonesia, often resulting damage to some buildings belonging to the people living in the vicinity. One effort to alleviate the risk of building damage is to have flood insurance. The main obstacle is not all people in the Citarum basin decide to buy flood insurance. In this paper, we intend to analyse the decision to buy flood insurance. It is assumed that there are eight variables that influence the decision of purchasing flood assurance, include: income level, education level, house distance with river, building election with road, flood frequency experience, flood prediction, perception on insurance company, and perception towards government effort in handling flood. The analysis was done by using logistic regression model, and to estimate model parameters, it is done with genetic algorithm. The results of the analysis shows that eight variables analysed significantly influence the demand of flood insurance. These results are expected to be considered for insurance companies, to influence the decision of the community to be willing to buy flood insurance.

  15. Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model.

    Yang, Weichao; Xu, Kui; Lian, Jijian; Bin, Lingling; Ma, Chao

    2018-05-01

    Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision. Copyright © 2018 Elsevier Ltd. All rights reserved.

  16. Realistic modelling of external flooding scenarios - A multi-disciplinary approach

    Brinkman, J.L.

    2014-01-01

    Extreme phenomena, such as storm surges or high river water levels, may endanger the safety of nuclear power plants (NPPs) by inundation of the plant site with subsequent damage on safety-related buildings. Flooding may result in simultaneous failures of safety-related components, such as service water pumps and electrical equipment. In addition, the accessibility of the plant may be impeded due to flooding of the plant environment. These consequences are so severe that, (re)assessments of flood risk and flood protection measures should be based on accurate state-of-the-art methods. Dutch nuclear regulations require that a nuclear power plant shall withstand all external initiating events with a return period lower than one million years. For external flooding, this requirement is the basis of the so-called nuclear design level (nucleair ontwerp peil, NOP) of the buildings for external flooding, i.e. the water level at which a system - among others, the nuclear island and the ultimate heat sink - should still function properly. In determining the NOP, the mean water level, wave height and wave behaviour during storm surges are taken into account. This concept could also be used to implement external flooding in a PSA, by assuming that floods exceeding NOP levels directly lead to core damage. However, this straightforward modelling ignores some important aspects: the first is the mitigating effect of the external flood protection as dikes or dunes; the second aspect is that although water levels lower than NOP will not directly lead to core damage, they could do so indirectly as a result of combinations of system loss by flooding and random failure of required safety systems that have to bring the plant in a safe, stable state. Time is a third aspect: failure mechanisms need time to develop and time (via duration of the flood) determines the amount of water on site. This paper describes a PSA approach that takes the (structural) reliability of the external defences

  17. Flood Inundation Mapping and Management using RISAT-1 derived Flood Inundation Areas, Cartosat-1 DEM and a River Flow Model

    Kuldeep, K.; Garg, P. K.; Garg, R. D.

    2017-12-01

    The frequent occurrence of repeated flood events in many regions of the world causing damage to human life and property has augmented the need for effective flood risk management. Microwave satellite data is becoming an indispensable asset for monitoring of many environmental and climatic applications as numerous space-borne synthetic aperture radar (SAR) sensors are offering the data with high spatial resolutions and multi-polarization capabilities. The implementation and execution of Flood mapping, monitoring and management applications has become easier with the availability of SAR data which has obvious advantages over optical data due to its all weather, day and night capabilities. In this study, the exploitation of the SAR dataset for hydraulic modelling and disaster management has been highlighted using feature extraction techniques for water area identification and water level extraction within the floodplain. The availability of high precision digital elevation model generated from the Cartosat-1 stereo pairs has enhanced the capability of retrieving the water depth maps by incorporating the SAR derived flood extent maps. This paper illustrates the flood event on June 2013 in Yamuna River, Haryana, India. The water surface profile computed by combining the topographic data with the RISAT-1 data accurately reflects the true water line. Water levels that were computed by carrying out the modelling using hydraulic model in HECRAS also suggest that the water surface profiles provided by the combined use of topographic data and SAR accurately reflect the true water line. The proposed approach has also been found better in extraction of inundation within vegetated areas.

  18. The framework of a UAS-aided flash flood modeling system for coastal regions

    Zhang, H.; Xu, H.

    2016-02-01

    Flash floods cause severe economic damage and are one of the leading causes of fatalities connected with natural disasters in the Gulf Coast region. Current flash flood modeling systems rely on empirical hydrological models driven by precipitation estimates only. Although precipitation is the driving factor for flash floods, soil moisture, urban drainage system and impervious surface have been recognized to have significant impacts on the development of flash floods. We propose a new flash flooding modeling system that integrates 3-D hydrological simulation with satellite and multi-UAS observations. It will have three advantages over existing modeling systems. First, it will incorporate 1-km soil moisture data through integrating satellite images from European SMOS mission and NASA's SMAP mission. The utilization of high-resolution satellite images will provide essential information to determine antecedent soil moisture condition, which is an essential control on flood generation. Second, this system is able to adjust flood forecasting based on real-time inundation information collected by multi-UAS. A group of UAS will be deployed during storm events to capture the changing extent of flooded areas and water depth at multiple critical locations simultaneously. Such information will be transmitted to a hydrological model to validate and improve flood simulation. Third, the backbone of this system is a state-of-the-art 3-D hydrological model that assimilates the hydrological information from satellites and multi-UAS. The model is able to address surface water-groundwater interactions and reflect the effects of various infrastructures. Using Web-GIS technologies, the modeling results will be available online as interactive flood maps accessible to the public. To support the development and verification of this modeling system, surface and subsurface hydrological observations will be conducted in a number of small watersheds in the Coastal Bend region. We envision this

  19. Coupling Modelling of Urban Development and Flood Risk – An Attempt for a Combined Software Framework

    Löwe, Roland; Sto Domingo, Nina; Urich, Christian

    2015-01-01

    to use the results of the hydraulic simulation to condition DANCE4WATER and to account for flood risk in the simulated urban development. In an Australian case study, we demonstrate that future flood risk can be significantly reduced while maintaining the overall speed of urban development.......We have developed a setup that couples the urban development model DANCE4WATER with the 1D-2D hydraulic model MIKE FLOOD. The setup makes it possible to assess the impact of urban development and infrastructural change scenarios on flood risk in an automated manner. In addition, it permits us...

  20. Dynamic model of forest area on flood zone of Padang City, West Sumatra Province-Indonesia

    Dewata, Indang; Iswandi, U.

    2018-05-01

    The flood disaster has caused many harm to human life, and the change of watershed characteristic is one of the factors causing the flood disaster. The increase of deforestation due to the increase of water causes the occurrence of flood disaster in the rainy season. The research objective was to develop a dynamic model of forest on flood hazard zone using powersim 10.1. In model development, there are three scenarios: optimistic, moderate, and pessimistic. The study shows that in Padang there are about 13 percent of high flood hazard zones. Deforestation of 4.5 percent/year is one cause that may increased the flooding intensity in Padang. There will be 14 percent of total forest area when management policy of forest absence in 2050.

  1. 2D Modeling of Flood Propagation due to the Failure of Way Ela Natural Dam

    Yakti Bagus Pramono

    2018-01-01

    Full Text Available A dam break induced-flood propagation modeling is needed to reduce the losses of any potential dam failure. On the 25 July 2013, there was a dam break generated flood due to the failure of Way Ela Natural Dam that severely damaged houses and various public facilities. This study simulated the flooding induced by the failure of Way Ela Natural Dam. A two-dimensional (2D numerical model, HEC-RAS v.5, is used to simulate the overland flow. The dam failure itself is simulated using HECHMSv.4. The results of this study, the flood inundation, flood depth, and flood arrival time are verified by using available secondary data. These informations are very important to propose mitigation plans with respect to possible dam break in the future.

  2. A Dynamic Model for Roll Motion of Ships Due to Flooding

    Xia, Jinzhu; Jensen, Jørgen Juncher; Pedersen, Preben Terndrup

    1997-01-01

    A dynamic model is presented of the roll motion of damaged RoRo vessels which couples the internal cross-flooding flow and the air action in the equalizing compartment. The cross flooding flow and the air motion are modelled by a modified Bernoulli equation, where artificial damping is introduced...... to avoid modal instability based on the original Bernoulli equation. The fluid action of the flooded water on the ship is expressed by its influence on the moment of inertia of the ship and the heeling moment, which is a couple created by the gravitational force of the flooded water and the change...... of buoyancy of the ship.Two limiting flooding cases are examined in the present analysis: The sudden ingress of a certain amount of water to the damaged compartment with no further water exchange between the sea and the flooded compartment during the roll motion, and the continuous ingress of water through...

  3. The Importance of Precise Digital Elevation Models (DEM) in Modelling Floods

    Demir, Gokben; Akyurek, Zuhal

    2016-04-01

    Digital elevation Models (DEM) are important inputs for topography for the accurate modelling of floodplain hydrodynamics. Floodplains have a key role as natural retarding pools which attenuate flood waves and suppress flood peaks. GPS, LIDAR and bathymetric surveys are well known surveying methods to acquire topographic data. It is not only time consuming and expensive to obtain topographic data through surveying but also sometimes impossible for remote areas. In this study it is aimed to present the importance of accurate modelling of topography for flood modelling. The flood modelling for Samsun-Terme in Blacksea region of Turkey is done. One of the DEM is obtained from the point observations retrieved from 1/5000 scaled orthophotos and 1/1000 scaled point elevation data from field surveys at x-sections. The river banks are corrected by using the orthophotos and elevation values. This DEM is named as scaled DEM. The other DEM is obtained from bathymetric surveys. 296 538 number of points and the left/right bank slopes were used to construct the DEM having 1 m spatial resolution and this DEM is named as base DEM. Two DEMs were compared by using 27 x-sections. The maximum difference at thalweg of the river bed is 2m and the minimum difference is 20 cm between two DEMs. The channel conveyance capacity in base DEM is larger than the one in scaled DEM and floodplain is modelled in detail in base DEM. MIKE21 with flexible grid is used in 2- dimensional shallow water flow modelling. The model by using two DEMs were calibrated for a flood event (July 9, 2012). The roughness is considered as the calibration parameter. From comparison of input hydrograph at the upstream of the river and output hydrograph at the downstream of the river, the attenuation is obtained as 91% and 84% for the base DEM and scaled DEM, respectively. The time lag in hydrographs does not show any difference for two DEMs and it is obtained as 3 hours. Maximum flood extents differ for the two DEMs

  4. Modeling of reservoir operation in UNH global hydrological model

    Shiklomanov, Alexander; Prusevich, Alexander; Frolking, Steve; Glidden, Stanley; Lammers, Richard; Wisser, Dominik

    2015-04-01

    Climate is changing and river flow is an integrated characteristic reflecting numerous environmental processes and their changes aggregated over large areas. Anthropogenic impacts on the river flow, however, can significantly exceed the changes associated with climate variability. Besides of irrigation, reservoirs and dams are one of major anthropogenic factor affecting streamflow. They distort hydrological regime of many rivers by trapping of freshwater runoff, modifying timing of river discharge and increasing the evaporation rate. Thus, reservoirs is an integral part of the global hydrological system and their impacts on rivers have to be taken into account for better quantification and understanding of hydrological changes. We developed a new technique, which was incorporated into WBM-TrANS model (Water Balance Model-Transport from Anthropogenic and Natural Systems) to simulate river routing through large reservoirs and natural lakes based on information available from freely accessible databases such as GRanD (the Global Reservoir and Dam database) or NID (National Inventory of Dams for US). Different formulations were applied for unregulated spillway dams and lakes, and for 4 types of regulated reservoirs, which were subdivided based on main purpose including generic (multipurpose), hydropower generation, irrigation and water supply, and flood control. We also incorporated rules for reservoir fill up and draining at the times of construction and decommission based on available data. The model were tested for many reservoirs of different size and types located in various climatic conditions using several gridded meteorological data sets as model input and observed daily and monthly discharge data from GRDC (Global Runoff Data Center), USGS Water Data (US Geological Survey), and UNH archives. The best results with Nash-Sutcliffe model efficiency coefficient in the range of 0.5-0.9 were obtained for temperate zone of Northern Hemisphere where most of large

  5. [Light response characteristics of photosynthesis and model comparison of Distylium chinense in different flooding durations].

    Liu, Ze-bin; Cheng, Rui-mei; Xiao, Wen-fa; Guo, Quan-shui; Wang, Na

    2015-04-01

    The light responses of photosynthesis of two-year-old Distytum chinense seedlings subjected to a simulated reservoir flooding environment in autumn and winter seasons were measured by using a Li-6400 XT portable photosynthesis system, and the light response curves were fitted and analyzed by three models of the rectangular hyperbola, non-rectangular hyperbola and modified rectangular hyperbola to investigate the applicability of different light response models for the D. chinense in different flooding durations and the adaption regulation of light response parameters to flooding stress. The results showed that the fitting effect of the non-rectangular hyperbola model for light response process of D. chinense under normal growth condition and under short-term flooding (15 days of flooding) was better than that of the other two models, while the fitting effect of the modified rectangular hyperbola model for light response process of D. chinense under longer-term flooding (30, 45 and 60 days of flooding) was better than that of the other two models. The modified rectangular hyperbola model gave the best fitted results of light compensation point (LCP) , maximum net photosynthetic rate (P(n max)) and light saturation point (LSP), and the non-rectangular hyperbola model gave the best fitted result of dark respiration rate (R(d)). The apparent quantum yield (Φ), P(n max) and LSP of D. chinense gradually decreased, and the LCP and R(d) of D. chinense gradually increased in early flooding (30 days), but D. chinense gradually produced adaptability for flooding as the flooding duration continued to increase, and various physiological indexes were gradually stabilized. Thus, this species has adaptability to some degree to the flooding environment.

  6. Merging information from multi-model flood projections in a hierarchical Bayesian framework

    Le Vine, Nataliya

    2016-04-01

    Multi-model ensembles are becoming widely accepted for flood frequency change analysis. The use of multiple models results in large uncertainty around estimates of flood magnitudes, due to both uncertainty in model selection and natural variability of river flow. The challenge is therefore to extract the most meaningful signal from the multi-model predictions, accounting for both model quality and uncertainties in individual model estimates. The study demonstrates the potential of a recently proposed hierarchical Bayesian approach to combine information from multiple models. The approach facilitates explicit treatment of shared multi-model discrepancy as well as the probabilistic nature of the flood estimates, by treating the available models as a sample from a hypothetical complete (but unobserved) set of models. The advantages of the approach are: 1) to insure an adequate 'baseline' conditions with which to compare future changes; 2) to reduce flood estimate uncertainty; 3) to maximize use of statistical information in circumstances where multiple weak predictions individually lack power, but collectively provide meaningful information; 4) to adjust multi-model consistency criteria when model biases are large; and 5) to explicitly consider the influence of the (model performance) stationarity assumption. Moreover, the analysis indicates that reducing shared model discrepancy is the key to further reduction of uncertainty in the flood frequency analysis. The findings are of value regarding how conclusions about changing exposure to flooding are drawn, and to flood frequency change attribution studies.

  7. Hydrodynamic modelling of extreme flood events in the Kashmir valley in India

    Jain, Manoj; Parvaze, Sabah

    2017-04-01

    Floods are one of the most predominant, costly and deadly hazards of all natural vulnerabilities. Every year, floods exert a heavy toll on human life and property in many parts of the world. The prediction of river stages and discharge during flood extremes plays a vital role in planning structural and non-structural measures of flood management. The predictions are also valuable to prepare the flood inundation maps and river floodplain zoning. In the Kashmir Valley, floods occur mainly and very often in the Jhelum Basin mostly due to extreme precipitation events and rugged mountainous topography of the basin. These floods cause extreme damage to life and property in the valley from time to time. Excessive rainfall, particularly in higher sub-catchments causes the snow to melt resulting in excessive runoff downhill to the streams causing floods in the Kashmir Valley where Srinagar city is located. However, very few hydrological studies have been undertaken for the Jhelum Basin mainly due to non-availability of hydrological data due to very complex mountainous terrain. Therefore, the present study has been conducted to model the extreme flood events in the Jhelum Basin in Kashmir Valley. An integrated NAM and MIKE 11 HD model has been setup for Jhelum basin up to Ram Munshi Bagh gauging site and then four most extreme historical flood events in the time series has been analyzed separately including the most recent and most extreme flood event of 2014. In September 2014, the Kashmir Valley witnessed the most severe flood in the past 60 years due to catastrophic rainfall from 1st to 6th September wherein the valley received unprecedented rainfall of more than 650 mm in just 3 days breaking record of many decades. The MIKE 11 HD and NAM model has been calibrated using 21 years (1985-2005) data and validated using 9 years (2006-2014) data. The efficiency indices of the model for calibration and validation period is 0.749 and 0.792 respectively. The model simulated

  8. Modeling the dynamics of internal flooding - verification analysis

    Filipov, K.

    2011-01-01

    The results from conducted software WATERFOW's verification analysis, developed for the purposes of reactor building internal flooding analysis have been presented. For the purpose of benchmarking the integrated code MELCOR is selected. Considering the complex structure of reactor building, the sample tests were used to cover the characteristic points of the internal flooding analysis. The inapplicability of MELCOR to the internal flooding study has been proved

  9. Impact of modelling scale on probabilistic flood risk assessment: the Malawi case

    Rudari Roberto

    2016-01-01

    Full Text Available In the early months of 2015, destructive floods hit Malawi, causing deaths and economic losses. Flood risk assessment outcomes can be used to increase scientific-supported awareness of risk. The recent increase in availability of high resolution data such as TanDEM-X at 12m resolution makes possible the use of detailed physical based flood hazard models in risk assessment. Nonetheless the scale of hazard modelling still remains an issue, which requires a compromise between level of detail and computational efforts. This work presents two different approaches on hazard modelling. Both methods rely on 32-years of numeric weather re-analysis and rainfall-runoff transformation through a fully distributed WFLOW-type hydrological model. The first method, applied at national scale, uses fast post-processing routines, which estimate flood water depth at a resolution of about 1×1km. The second method applies a full 2D hydraulic model to propagate water discharge into the flood plains and best suites for small areas where assets are concentrated. At the 12m resolution, three hot spots with a model area of approximately 10×10 km are analysed. Flood hazard maps obtained with both approaches are combined with flood impact models at the same resolution to generate indicators for flood risk. A quantitative comparison of the two approaches is presented in order to show the effects of modelling scale on both hazard and impact losses.

  10. Flood Water Crossing: Laboratory Model Investigations for Water Velocity Reductions

    Kasnon N.

    2014-01-01

    Full Text Available The occurrence of floods may give a negative impact towards road traffic in terms of difficulties in mobilizing traffic as well as causing damage to the vehicles, which later cause them to be stuck in the traffic and trigger traffic problems. The high velocity of water flows occur when there is no existence of objects capable of diffusing the water velocity on the road surface. The shape, orientation and size of the object to be placed beside the road as a diffuser are important for the effective flow attenuation of water. In order to investigate the water flow, a laboratory experiment was set up and models were constructed to study the flow velocity reduction. The velocity of water before and after passing through the diffuser objects was investigated. This paper focuses on laboratory experiments to determine the flow velocity of the water using sensors before and after passing through two best diffuser objects chosen from a previous flow pattern experiment.

  11. 1D and 2D urban dam-break flood modelling in Istanbul, Turkey

    Ozdemir, Hasan; Neal, Jeffrey; Bates, Paul; Döker, Fatih

    2014-05-01

    Urban flood events are increasing in frequency and severity as a consequence of several factors such as reduced infiltration capacities due to continued watershed development, increased construction in flood prone areas due to population growth, the possible amplification of rainfall intensity due to climate change, sea level rise which threatens coastal development, and poorly engineered flood control infrastructure (Gallegos et al., 2009). These factors will contribute to increased urban flood risk in the future, and as a result improved modelling of urban flooding according to different causative factor has been identified as a research priority (Gallegos et al., 2009; Ozdemir et al. 2013). The flooding disaster caused by dam failures is always a threat against lives and properties especially in urban environments. Therefore, the prediction of dynamics of dam-break flows plays a vital role in the forecast and evaluation of flooding disasters, and is of long-standing interest for researchers. Flooding occurred on the Ayamama River (Istanbul-Turkey) due to high intensity rainfall and dam-breaching of Ata Pond in 9th September 2009. The settlements, industrial areas and transportation system on the floodplain of the Ayamama River were inundated. Therefore, 32 people were dead and millions of Euros economic loses were occurred. The aim of this study is 1 and 2-Dimensional flood modelling of the Ata Pond breaching using HEC-RAS and LISFLOOD-Roe models and comparison of the model results using the real flood extent. The HEC-RAS model solves the full 1-D Saint Venant equations for unsteady open channel flow whereas LISFLOOD-Roe is the 2-D shallow water model which calculates the flow according to the complete Saint Venant formulation (Villanueva and Wright, 2006; Neal et al., 2011). The model consists a shock capturing Godunov-type scheme based on the Roe Riemann solver (Roe, 1981). 3 m high resolution Digital Surface Model (DSM), natural characteristics of the pond

  12. Coupled modelling of subsurface water flux for an integrated flood risk management

    T. Sommer

    2009-07-01

    Full Text Available Flood events cause significant damage not only on the surface but also underground. Infiltration of surface water into soil, flooding through the urban sewer system and, in consequence, rising groundwater are the main causes of subsurface damage. The modelling of flooding events is an important part of flood risk assessment. The processes of subsurface discharge of infiltrated water necessitate coupled modelling tools of both, surface and subsurface water fluxes. Therefore, codes for surface flooding, for discharge in the sewerage system and for groundwater flow were coupled with each other. A coupling software was used to amalgamate the individual programs in terms of mapping between the different model geometries, time synchronization and data exchange. The coupling of the models was realized on two scales in the Saxon capital of Dresden (Germany. As a result of the coupled modelling it could be shown that surface flooding dominates processes of any flood event. Compared to flood simulations without coupled modelling no substantial changes of the surface inundation area could be determined. Regarding sewerage, the comparison between the influx of groundwater into sewerage and the loading due to infiltration by flood water showed infiltration of surface flood water to be the main reason for sewerage overloading. Concurrent rainfalls can intensify the problem. The infiltration of the sewerage system by rising groundwater contributes only marginally to the loading of the sewerage and the distribution of water by sewerage has only local impacts on groundwater rise. However, the localization of risk areas due to rising groundwater requires the consideration of all components of the subsurface water fluxes. The coupled modelling has shown that high groundwater levels are the result of a multi-causal process that occurs before and during the flood event.

  13. Collaborative modelling for active involvement of stakeholders in urban flood risk management

    M. Evers

    2012-09-01

    Full Text Available This paper presents an approach to enhance the role of local stakeholders in dealing with urban floods. The concept is based on the DIANE-CM project (Decentralised Integrated Analysis and Enhancement of Awareness through Collaborative Modelling and Management of Flood Risk of the 2nd ERANET CRUE funding initiative. The main objective of the project was to develop and test an advanced methodology for enhancing the resilience of local communities to flooding. Through collaborative modelling, a social learning process was initiated that enhances the social capacity of the stakeholders due to the interaction process. The other aim of the project was to better understand how data from hazard and vulnerability analyses and improved maps, as well as from the near real-time flood prediction, can be used to initiate a public dialogue (i.e. collaborative mapping and planning activities in order to carry out more informed and shared decision-making processes and to enhance flood risk awareness. The concept of collaborative modelling was applied in two case studies: (1 the Cranbrook catchment in the UK, with focus on pluvial flooding; and (2 the Alster catchment in Germany, with focus on fluvial flooding. As a result of the interactive and social learning process, supported by sociotechnical instruments, an understanding of flood risk was developed amongst the stakeholders and alternatives for flood risk management for the respective case study area were jointly developed and ranked as a basis for further planning and management.

  14. Paleoflood Data, Extreme Floods and Frequency: Data and Models for Dam Safety Risk Scenarios

    England, J. F.; Godaire, J.; Klinger, R.

    2007-12-01

    Extreme floods and probability estimates are crucial components in dam safety risk analysis and scenarios for water-resources decision making. The field-based collection of paleoflood data provides needed information on the magnitude and probability of extreme floods at locations of interest in a watershed or region. The stratigraphic record present along streams in the form of terrace and floodplain deposits represent direct indicators of the magnitude of large floods on a river, and may provide 10 to 100 times longer records than conventional stream gaging records of large floods. Paleoflood data is combined with gage and historical streamflow estimates to gain insights to flood frequency scaling, model extrapolations and uncertainty, and provide input scenarios to risk analysis event trees. We illustrate current data collection and flood frequency modeling approaches via case studies in the western United States, including the American River in California and the Arkansas River in Colorado. These studies demonstrate the integration of applied field geology, hydraulics, and surface-water hydrology. Results from these studies illustrate the gains in information content on extreme floods, provide data- based means to separate flood generation processes, guide flood frequency model extrapolations, and reduce uncertainties. These data and scenarios strongly influence water resources management decisions.

  15. Modeling Flood & Drought Scenario for Water Management in Porali River Basin, Balochistan

    Shoaib Ahmed

    2013-12-01

    Full Text Available Recent history shows that floods have become a frequently occurring disaster in Balochistan, especially during monsoon season. Two rivers, river Porali and river Kud overflows, inundating its banks and causing destruction to cultivated land and property. This study is an attempt to identify flood prone areas of Porali river basin for future flood scenario and propose possible reservoir locations for excess flood water storage. Computer-based models Hydrological Simulation Program-FORTRAN (HSPF and HEC-river analysis system (HEC-RAS are used as tools to simulate existing and future flood and drought scenarios. Models are calibrated and validated using data from 3 weather stations, namely Wadh, Bela, and Uthal and stream flow data from two gauging stations. The highest and the lowest 10 years of precipitation data are extracted, from historic dataset of all stations, to attain future flooding and drought scenarios, respectively. Flood inundation map is generated highlighting agricultural prone land and settlements of the watershed. Using Digital Elevation Model (DEM and volume of water calculated from the flood scenario, possible locations for reservoirs are marked that can store excess water for the use in drought years. Flow and volume of water has also been simulated for drought scenario. Analyses show that 3 × 109 m3 of water available due to immense flooding that is sufficient for the survival for one drought year, as the volume of water for latter scenario is 2.9 × 108m3.

  16. Challenges of citizen science contributions to modelling hydrodynamics of floods

    Assumpção, Thaine Herman; Popescu, Ioana; Jonoski, Andreja; Solomatine, Dimitri P.

    2017-04-01

    Citizen science is an established mechanism in many fields of science, including ecology, biology and astronomy. Citizen participation ranges from collecting and interpreting data towards designing experiments with scientists and cooperating with water management authorities. In the environmental sciences, its potential has begun to be explored in the past decades and many studies on the applicability to water resources have emerged. Citizen Observatories are at the core of several EU-funded projects such as WeSenseIt, GroundTruth, GroundTruth 2.0 and SCENT (Smart Toolbox for Engaging Citizens into a People-Centric Observation Web) that already resulted in valuable contributions to the field. Buytaert et al. (2014) has already reviewed the role of citizen science in hydrology. The work presented here aims to complement it, reporting and discussing the use of citizen science for modelling the hydrodynamics of floods in a variety of studies. Additionally, it highlights the challenges that lie ahead to utilize more fully the citizen science potential contribution. In this work, focus is given to each component of hydrodynamic models: water level, velocity, flood extent, roughness and topography. It is addressed how citizens have been contributing to each aspect, mainly considering citizens as sensors and citizens as data interpreters. We consider to which kind of model (1D or 2D) the discussed approaches contribute and what their limitations and potential uses are. We found that although certain mechanisms are well established (e.g. the use of Volunteer Geographic Information for soft validation of land-cover and land-use maps), the applications in a modelling context are rather modest. Also, most studies involving models are limited to replacing traditional data with citizen data. We recommend that citizen science continue to be explored in modelling frameworks, in different case studies, taking advantage of the discussed mechanisms and of new sensor technologies

  17. Benchmarking flood models from space in near real-time: accommodating SRTM height measurement errors with low resolution flood imagery

    Schumann, G.; di Baldassarre, G.; Alsdorf, D.; Bates, P. D.

    2009-04-01

    In February 2000, the Shuttle Radar Topography Mission (SRTM) measured the elevation of most of the Earth's surface with spatially continuous sampling and an absolute vertical accuracy greater than 9 m. The vertical error has been shown to change with topographic complexity, being less important over flat terrain. This allows water surface slopes to be measured and associated discharge volumes to be estimated for open channels in large basins, such as the Amazon. Building on these capabilities, this paper demonstrates that near real-time coarse resolution radar imagery of a recent flood event on a 98 km reach of the River Po (Northern Italy) combined with SRTM terrain height data leads to a water slope remarkably similar to that derived by combining the radar image with highly accurate airborne laser altimetry. Moreover, it is shown that this space-borne flood wave approximation compares well to a hydraulic model and thus allows the performance of the latter, calibrated on a previous event, to be assessed when applied to an event of different magnitude in near real-time. These results are not only of great importance to real-time flood management and flood forecasting but also support the upcoming Surface Water and Ocean Topography (SWOT) mission that will routinely provide water levels and slopes with higher precision around the globe.

  18. Low probability flood-risk modeling for New York City.

    Aerts, J.C.J.H.; Lin, N.; Botzen, W.J.W.; Emanuel, K.; de Moel, H.

    2013-01-01

    The devastating impact by Hurricane Sandy (2012) again showed New York City (NYC) is one of the most vulnerable cities to coastal flooding around the globe. The low-lying areas in NYC can be flooded by nor'easter storms and North Atlantic hurricanes. The few studies that have estimated potential

  19. An agent-based model of flood risk and insurance

    Dubbelboer, J.; Nikolic, I.; Jenkins, K.; Hall, J

    2017-01-01

    Flood risk emerges from the dynamic interaction between natural hazards and human vulnerability. Methods for the quantification of flood risk are well established, but tend to deal with human and economic vulnerability as being static or changing with an exogenously defined trend. In this paper

  20. Flood hazard mapping of Palembang City by using 2D model

    Farid, Mohammad; Marlina, Ayu; Kusuma, Muhammad Syahril Badri

    2017-11-01

    Palembang as the capital city of South Sumatera Province is one of the metropolitan cities in Indonesia that flooded almost every year. Flood in the city is highly related to Musi River Basin. Based on Indonesia National Agency of Disaster Management (BNPB), the level of flood hazard is high. Many natural factors caused flood in the city such as high intensity of rainfall, inadequate drainage capacity, and also backwater flow due to spring tide. Furthermore, anthropogenic factors such as population increase, land cover/use change, and garbage problem make flood problem become worse. The objective of this study is to develop flood hazard map of Palembang City by using two dimensional model. HEC-RAS 5.0 is used as modelling tool which is verified with field observation data. There are 21 sub catchments of Musi River Basin in the flood simulation. The level of flood hazard refers to Head Regulation of BNPB number 2 in 2012 regarding general guideline of disaster risk assessment. The result for 25 year return per iod of flood shows that with 112.47 km2 area of inundation, 14 sub catchments are categorized in high hazard level. It is expected that the hazard map can be used for risk assessment.

  1. GEM - The Global Earthquake Model

    Smolka, A.

    2009-04-01

    Over 500,000 people died in the last decade due to earthquakes and tsunamis, mostly in the developing world, where the risk is increasing due to rapid population growth. In many seismic regions, no hazard and risk models exist, and even where models do exist, they are intelligible only by experts, or available only for commercial purposes. The Global Earthquake Model (GEM) answers the need for an openly accessible risk management tool. GEM is an internationally sanctioned public private partnership initiated by the Organisation for Economic Cooperation and Development (OECD) which will establish an authoritative standard for calculating and communicating earthquake hazard and risk, and will be designed to serve as the critical instrument to support decisions and actions that reduce earthquake losses worldwide. GEM will integrate developments on the forefront of scientific and engineering knowledge of earthquakes, at global, regional and local scale. The work is organized in three modules: hazard, risk, and socio-economic impact. The hazard module calculates probabilities of earthquake occurrence and resulting shaking at any given location. The risk module calculates fatalities, injuries, and damage based on expected shaking, building vulnerability, and the distribution of population and of exposed values and facilities. The socio-economic impact module delivers tools for making educated decisions to mitigate and manage risk. GEM will be a versatile online tool, with open source code and a map-based graphical interface. The underlying data will be open wherever possible, and its modular input and output will be adapted to multiple user groups: scientists and engineers, risk managers and decision makers in the public and private sectors, and the public-at- large. GEM will be the first global model for seismic risk assessment at a national and regional scale, and aims to achieve broad scientific participation and independence. Its development will occur in a

  2. Spatial Modeling of Flood Duration in Amazonian Floodplains Through Radar Remote Sensing and Generalized Linear Models

    Ferreira-Ferreira, J.; Francisco, M. S.; Silva, T. S. F.

    2017-12-01

    Amazon floodplains play an important role in biodiversity maintenance and provide important ecosystem services. Flood duration is the prime factor modulating biogeochemical cycling in Amazonian floodplain systems, as well as influencing ecosystem structure and function. However, due to the absence of accurate terrain information, fine-scale hydrological modeling is still not possible for most of the Amazon floodplains, and little is known regarding the spatio-temporal behavior of flooding in these environments. Our study presents an new approach for spatial modeling of flood duration, using Synthetic Aperture Radar (SAR) and Generalized Linear Modeling. Our focal study site was Mamirauá Sustainable Development Reserve, in the Central Amazon. We acquired a series of L-band ALOS-1/PALSAR Fine-Beam mosaics, chosen to capture the widest possible range of river stage heights at regular intervals. We then mapped flooded area on each image, and used the resulting binary maps as the response variable (flooded/non-flooded) for multiple logistic regression. Explanatory variables were accumulated precipitation 15 days prior and the water stage height recorded in the Mamirauá lake gauging station observed for each image acquisition date, Euclidean distance from the nearest drainage, and slope, terrain curvature, profile curvature, planform curvature and Height Above the Nearest Drainage (HAND) derived from the 30-m SRTM DEM. Model results were validated with water levels recorded by ten pressure transducers installed within the floodplains, from 2014 to 2016. The most accurate model included water stage height and HAND as explanatory variables, yielding a RMSE of ±38.73 days of flooding per year when compared to the ground validation sites. The largest disagreements were 57 days and 83 days for two validation sites, while remaining locations achieved absolute errors lower than 38 days. In five out of nine validation sites, the model predicted flood durations with

  3. An Open-Book Modular Watershed Modeling Framework for Rapid Prototyping of GPM- based Flood Forecasting in International River Basins

    Katiyar, N.; Hossain, F.

    2006-05-01

    Floods have always been disastrous for human life. It accounts for about 15 % of the total death related to natural disasters. There are around 263 transboundary river basins listed by UNESCO, wherein at least 30 countries have more than 95% of their territory locked in one or more such transboundary basins. For flood forecasting in the lower riparian nations of these International River Basins (IRBs), real-time rainfall data from upstream nations is naturally the most critical factor governing the forecasting effectiveness. However, many upstream nations fail to provide data to the lower riparian nations due to a lack of in-situ rainfall measurement infrastructure or a lack of a treaty for real-time sharing of rainfall data. A potential solution is therefore to use satellites that inherently measure rainfall across political boundaries. NASA's proposed Global Precipitation Measurement (GPM) mission appears very promising in providing this vital rainfall information under the data- limited scenario that will continue to prevail in most IRBs. However, satellite rainfall is associated with uncertainty and hence, proper characterization of the satellite rainfall error propagation in hydrologic models for flood forecasting is a critical priority that should be resolved in the coming years in anticipation of GPM. In this study, we assess an open book modular watershed modeling approach for estimating the expected error in flood forecasting related to GPM rainfall data. Our motivation stems from the critical challenge in identifying the specific IRBs that would benefit from a pre-programmed satellite-based forecasting system in anticipation of GPM. As the number of flood-prone IRBs is large, conventional data-intensive implementation of existing physically-based distributed hydrologic models on case-by-case IRBs is considered time-consuming for completing such a global assessment. A more parsimonious approach is justified at the expense of a tolerable loss of detail and

  4. Integrating a Typhoon Event Database with an Optimal Flood Operation Model on the Real-Time Flood Control of the Tseng-Wen Reservoir

    Chen, Y. W.; Chang, L. C.

    2012-04-01

    Typhoons which normally bring a great amount of precipitation are the primary natural hazard in Taiwan during flooding season. Because the plentiful rainfall quantities brought by typhoons are normally stored for the usage of the next draught period, the determination of release strategies for flood operation of reservoirs which is required to simultaneously consider not only the impact of reservoir safety and the flooding damage in plain area but also for the water resource stored in the reservoir after typhoon becomes important. This study proposes a two-steps study process. First, this study develop an optimal flood operation model (OFOM) for the planning of flood control and also applies the OFOM on Tseng-wun reservoir and the downstream plain related to the reservoir. Second, integrating a typhoon event database with the OFOM mentioned above makes the proposed planning model have ability to deal with a real-time flood control problem and names as real-time flood operation model (RTFOM). Three conditions are considered in the proposed models, OFOM and RTFOM, include the safety of the reservoir itself, the reservoir storage after typhoons and the impact of flooding in the plain area. Besides, the flood operation guideline announced by government is also considered in the proposed models. The these conditions and the guideline can be formed as an optimization problem which is solved by the genetic algorithm (GA) in this study. Furthermore, a distributed runoff model, kinematic-wave geomorphic instantaneous unit hydrograph (KW-GIUH), and a river flow simulation model, HEC-RAS, are used to simulate the river water level of Tseng-wun basin in the plain area and the simulated level is shown as an index of the impact of flooding. Because the simulated levels are required to re-calculate iteratively in the optimization model, applying a recursive artificial neural network (recursive ANN) instead of the HEC-RAS model can significantly reduce the computational burden of

  5. Dam break modelling, risk assessment and uncertainty analysis for flood mitigation

    Zagonjolli, M.

    2007-01-01

    In this thesis a range of modelling techniques is explored to deal effectively with flood risk management. In particular, attention is paid to floods caused by failure of hydraulic structures such as dams and dikes. The methods considered here are applied for simulating dam and dike failure events,

  6. An agent-based modelling framework to explore the role of social media and stubborn people on evacuation rates during flooding events

    Du, E.; Cai, X.; Minsker, B. S.; Sun, Z.

    2017-12-01

    Flood warnings from various information sources are important for individuals to make evacuation decisions during a flood event. In this study, we develop a general opinion dynamics model to simulate how individuals update their flood hazard awareness when exposed to multiple information sources, including global broadcast, social media, and observations of neighbors' actions. The opinion dynamics model is coupled with a traffic model to simulate the evacuation processes of a residential community with a given transportation network. Through various scenarios, we investigate how social media affect the opinion dynamics and evacuation processes. We find that stronger social media can make evacuation processes more sensitive to the change of global broadcast and neighbor observations, and thus, impose larger uncertainty on evacuation rates (i.e., a large range of evacuation rates corresponding to sources of information). For instance, evacuation rates are lower when social media become more influential and individuals have less trust in global broadcast. Stubborn individuals can significantly affect the opinion dynamics and reduce evacuation rates. In addition, evacuation rates respond to the percentage of stubborn agents in a non-linear manner, i.e., above a threshold, the impact of stubborn agents will be intensified by stronger social media. These results highlight the role of social media in flood evacuation processes and the need to monitor social media so that misinformation can be corrected in a timely manner. The joint impacts of social media, quality of flood warnings and transportation capacity on evacuation rates are also discussed.

  7. A web GIS based integrated flood assessment modeling tool for coastal urban watersheds

    Kulkarni, A. T.; Mohanty, J.; Eldho, T. I.; Rao, E. P.; Mohan, B. K.

    2014-03-01

    Urban flooding has become an increasingly important issue in many parts of the world. In this study, an integrated flood assessment model (IFAM) is presented for the coastal urban flood simulation. A web based GIS framework has been adopted to organize the spatial datasets for the study area considered and to run the model within this framework. The integrated flood model consists of a mass balance based 1-D overland flow model, 1-D finite element based channel flow model based on diffusion wave approximation and a quasi 2-D raster flood inundation model based on the continuity equation. The model code is written in MATLAB and the application is integrated within a web GIS server product viz: Web Gram Server™ (WGS), developed at IIT Bombay, using Java, JSP and JQuery technologies. Its user interface is developed using open layers and the attribute data are stored in MySQL open source DBMS. The model is integrated within WGS and is called via Java script. The application has been demonstrated for two coastal urban watersheds of Navi Mumbai, India. Simulated flood extents for extreme rainfall event of 26 July, 2005 in the two urban watersheds of Navi Mumbai city are presented and discussed. The study demonstrates the effectiveness of the flood simulation tool in a web GIS environment to facilitate data access and visualization of GIS datasets and simulation results.

  8. Coupling Radar Rainfall Estimation and Hydrological Modelling For Flash-flood Hazard Mitigation

    Borga, M.; Creutin, J. D.

    Flood risk mitigation is accomplished through managing either or both the hazard and vulnerability. Flood hazard may be reduced through structural measures which alter the frequency of flood levels in the area. The vulnerability of a community to flood loss can be mitigated through changing or regulating land use and through flood warning and effective emergency response. When dealing with flash-flood hazard, it is gener- ally accepted that the most effective way (and in many instances the only affordable in a sustainable perspective) to mitigate the risk is by reducing the vulnerability of the involved communities, in particular by implementing flood warning systems and community self-help programs. However, both the inherent characteristics of the at- mospheric and hydrologic processes involved in flash-flooding and the changing soci- etal needs provide a tremendous challenge to traditional flood forecasting and warning concepts. In fact, the targets of these systems are traditionally localised like urbanised sectors or hydraulic structures. Given the small spatial scale that characterises flash floods and the development of dispersed urbanisation, transportation, green tourism and water sports, human lives and property are exposed to flash flood risk in a scat- tered manner. This must be taken into consideration in flash flood warning strategies and the investigated region should be considered as a whole and every section of the drainage network as a potential target for hydrological warnings. Radar technology offers the potential to provide information describing rain intensities almost contin- uously in time and space. Recent research results indicate that coupling radar infor- mation to distributed hydrologic modelling can provide hydrologic forecasts at all potentially flooded points of a region. Nevertheless, very few flood warning services use radar data more than on a qualitative basis. After a short review of current under- standing in this area, two

  9. Quantifying Uncertainty in Flood Inundation Mapping Using Streamflow Ensembles and Multiple Hydraulic Modeling Techniques

    Hosseiny, S. M. H.; Zarzar, C.; Gomez, M.; Siddique, R.; Smith, V.; Mejia, A.; Demir, I.

    2016-12-01

    The National Water Model (NWM) provides a platform for operationalize nationwide flood inundation forecasting and mapping. The ability to model flood inundation on a national scale will provide invaluable information to decision makers and local emergency officials. Often, forecast products use deterministic model output to provide a visual representation of a single inundation scenario, which is subject to uncertainty from various sources. While this provides a straightforward representation of the potential inundation, the inherent uncertainty associated with the model output should be considered to optimize this tool for decision making support. The goal of this study is to produce ensembles of future flood inundation conditions (i.e. extent, depth, and velocity) to spatially quantify and visually assess uncertainties associated with the predicted flood inundation maps. The setting for this study is located in a highly urbanized watershed along the Darby Creek in Pennsylvania. A forecasting framework coupling the NWM with multiple hydraulic models was developed to produce a suite ensembles of future flood inundation predictions. Time lagged ensembles from the NWM short range forecasts were used to account for uncertainty associated with the hydrologic forecasts. The forecasts from the NWM were input to iRIC and HEC-RAS two-dimensional software packages, from which water extent, depth, and flow velocity were output. Quantifying the agreement between output ensembles for each forecast grid provided the uncertainty metrics for predicted flood water inundation extent, depth, and flow velocity. For visualization, a series of flood maps that display flood extent, water depth, and flow velocity along with the underlying uncertainty associated with each of the forecasted variables were produced. The results from this study demonstrate the potential to incorporate and visualize model uncertainties in flood inundation maps in order to identify the high flood risk zones.

  10. Large-watershed flood simulation and forecasting based on different-resolution distributed hydrological model

    Li, J.

    2017-12-01

    Large-watershed flood simulation and forecasting is very important for a distributed hydrological model in the application. There are some challenges including the model's spatial resolution effect, model performance and accuracy and so on. To cope with the challenge of the model's spatial resolution effect, different model resolution including 1000m*1000m, 600m*600m, 500m*500m, 400m*400m, 200m*200m were used to build the distributed hydrological model—Liuxihe model respectively. The purpose is to find which one is the best resolution for Liuxihe model in Large-watershed flood simulation and forecasting. This study sets up a physically based distributed hydrological model for flood forecasting of the Liujiang River basin in south China. Terrain data digital elevation model (DEM), soil type and land use type are downloaded from the website freely. The model parameters are optimized by using an improved Particle Swarm Optimization(PSO) algorithm; And parameter optimization could reduce the parameter uncertainty that exists for physically deriving model parameters. The different model resolution (200m*200m—1000m*1000m ) are proposed for modeling the Liujiang River basin flood with the Liuxihe model in this study. The best model's spatial resolution effect for flood simulation and forecasting is 200m*200m.And with the model's spatial resolution reduction, the model performance and accuracy also become worse and worse. When the model resolution is 1000m*1000m, the flood simulation and forecasting result is the worst, also the river channel divided based on this resolution is differs from the actual one. To keep the model with an acceptable performance, minimum model spatial resolution is needed. The suggested threshold model spatial resolution for modeling the Liujiang River basin flood is a 500m*500m grid cell, but the model spatial resolution with a 200m*200m grid cell is recommended in this study to keep the model at a best performance.

  11. Socio-hydrological modelling of floods: investigating community resilience, adaptation capacity and risk

    Ciullo, Alessio; Viglione, Alberto; Castellarin, Attilio

    2016-04-01

    Changes in flood risk occur because of changes in climate and hydrology, and in societal exposure and vulnerability. Research on change in flood risk has demonstrated that the mutual interactions and continuous feedbacks between floods and societies has to be taken into account in flood risk management. The present work builds on an existing conceptual model of an hypothetical city located in the proximity of a river, along whose floodplains the community evolves over time. The model reproduces the dynamic co-evolution of four variables: flooding, population density of the flooplain, amount of structural protection measures and memory of floods. These variables are then combined in a way to mimic the temporal change of community resilience, defined as the (inverse of the) amount of time for the community to recover from a shock, and adaptation capacity, defined as ratio between damages due to subsequent events. Also, temporal changing exposure, vulnerability and probability of flooding are also modelled, which results in a dynamically varying flood-risk. Examples are provided that show how factors such as collective memory and risk taking attitude influence the dynamics of community resilience, adaptation capacity and risk.

  12. Takaful Models and Global Practices

    Akhter, Waheed

    2010-01-01

    There is a global interest in Islamic finance in general and Takāful in particular. The main feature that differentiates Takāful services from conventional ones is Sharī‟ah compliance nature of these services. Investors are taking keen interest in this potential market as Muslims constitute about one fourth of the world population (Muslim population, 2006). To streamline operations of a Takāful company, management and Sharī‟ah experts have developed different operational models for Takāful bu...

  13. Rainfall-runoff modelling and palaeoflood hydrology applied to reconstruct centennial scale records of flooding and aquifer recharge in ungauged ephemeral rivers

    G. Benito

    2011-04-01

    Full Text Available In this study we propose a multi-source data approach for quantifying long-term flooding and aquifer recharge in ungauged ephemeral rivers. The methodology is applied to the Buffels River, at 9000 km2 the largest ephemeral river in Namaqualand (NW South Africa, a region with scarce stream flow records limiting research investigating hydrological response to global change. Daily discharge and annual flood series (1965–2006 were estimated from a distributed rainfall-runoff hydrological model (TETIS using rainfall gauge records located within the catchment. The model was calibrated and validated with data collected during a two year monitoring programme (2005–2006 at two stream flow stations, one each in the upper and lower reaches of the catchment. In addition to the modelled flow records, non-systematic flood data were reconstructed using both sedimentary and documentary evidence. The palaeoflood record identified at least 25 large floods during the last 700 yr; with the largest floods reaching a minimum discharge of 255 m3 s−1 (450 yr return period in the upper basin, and 510 m3 s−1 (100 yr return period in the lower catchment. Since AD 1925, the flood hydrology of the Buffels River has been characterised by a decrease in the magnitude and frequency of extreme floods, with palaeoflood discharges (period 1500–1921 five times greater than the largest modelled floods during the period 1965–2006. Large floods generated the highest hydrograph volumes, however their contribution to aquifer recharge is limited as this depends on other factors such as flood duration and storage capacity of the unsaturated zone prior to the flood. Floods having average return intervals of 5–10 yr (120–140 m3 s−1 and flowing for 12 days are able to fully saturate the Spektakel aquifer in the lower Buffels River basin. Alluvial aquifer storage capacity limiting potential recharge

  14. Comparison of 2D numerical models for river flood hazard assessment: simulation of the Secchia River flood in January, 2014

    Shustikova, Iuliia; Domeneghetti, Alessio; Neal, Jeffrey; Bates, Paul; Castellarin, Attilio

    2017-04-01

    Hydrodynamic modeling of inundation events still brings a large array of uncertainties. This effect is especially evident in the models run for geographically large areas. Recent studies suggest using fully two-dimensional (2D) models with high resolution in order to avoid uncertainties and limitations coming from the incorrect interpretation of flood dynamics and an unrealistic reproduction of the terrain topography. This, however, affects the computational efficiency increasing the running time and hardware demands. Concerning this point, our study evaluates and compares numerical models of different complexity by testing them on a flood event that occurred in the basin of the Secchia River, Northern Italy, on 19th January, 2014. The event was characterized by a levee breach and consequent flooding of over 75 km2 of the plain behind the dike within 48 hours causing population displacement, one death and economic losses in excess of 400 million Euro. We test the well-established TELEMAC 2D, and LISFLOOD-FP codes, together with the recently launched HEC-RAS 5.0.3 (2D model), all models are implemented using different grid size (2-200 m) based on the 1 m digital elevation model resolution. TELEMAC is a fully 2D hydrodynamic model which is based on the finite-element or finite-volume approach. Whereas HEC-RAS 5.0.3 and LISFLOOD-FP are both coupled 1D-2D models. All models are calibrated against observed inundation extent and maximum water depths, which are retrieved from remotely sensed data and field survey reports. Our study quantitatively compares the three modeling strategies highlighting differences in terms of the ease of implementation, accuracy of representation of hydraulic processes within floodplains and computational efficiency. Additionally, we look into the different grid resolutions in terms of the results accuracy and computation time. Our study is a preliminary assessment that focuses on smaller areas in order to identify potential modeling schemes

  15. Sensitivity and uncertainty in flood inundation modelling – concept of an analysis framework

    T. Weichel

    2007-01-01

    Full Text Available After the extreme flood event of the Elbe in 2002 the definition of flood risk areas by law and their simulation became more important in Germany. This paper describes a concept of an analysis framework to improve the localisation and duration of validity of flood inundation maps. The two-dimensional finite difference model TrimR2D is used and linked to a Monte-Carlo routine for parameter sampling as well as to selected performance measures. The purpose is the investigation of the impact of different spatial resolutions and the influence of changing land uses in the simulation of flood inundation areas. The technical assembling of the framework is realised and beside the model calibration, first tests with different parameter ranges were done. Preliminary results show good correlations with observed data, but the investigation of shifting land uses reflects only poor changes in the flood extension.

  16. Satellite-based Flood Modeling Using TRMM-based Rainfall Products

    Greg Easson

    2007-12-01

    Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

  17. Forecasting flood-prone areas using Shannon's entropy model

    2Department of Water Engineering, Faculty of Agriculture, Lorestan University, ... decision tree methods for determining flood sus- .... a system to prevent disorder, instability, distur- ..... using support vector machine and GIS at the Golestan.

  18. Hydrodynamic models of the possibility of flooding Zaporizhya NPP site beyond the extreme earthquakes and hurricanes

    Skalozubov, V.I.; Gablaya, T.V.; Vashchenko, V.N.; Gerasimenko, T.V.; Kozlov, I.L.

    2014-01-01

    We propose a hydrodynamic model of possible flooding of the industrial site at Zaporozh'e NPP design basis earthquakes and hurricane. In contrast to the quasi-stationary approach of stress tests in the proposed model takes into account the dynamic nature of the processes of flooding, as well as a direct impact of external influences on extreme Kakhovske reservoir. As a result of hydrodynamic modeling, the possible conditions and criteria for the flooding of the industrial site at Zaporozhe extreme external influences

  19. Global sea-level rise is recognised, but flooding from anthropogenic land subsidence is ignored around northern Manila Bay, Philippines.

    Rodolfo, Kelvin S; Siringan, Fernando P

    2006-03-01

    Land subsidence resulting from excessive extraction of groundwater is particularly acute in East Asian countries. Some Philippine government sectors have begun to recognise that the sea-level rise of one to three millimetres per year due to global warming is a cause of worsening floods around Manila Bay, but are oblivious to, or ignore, the principal reason: excessive groundwater extraction is lowering the land surface by several centimetres to more than a decimetre per year. Such ignorance allows the government to treat flooding as a lesser problem that can be mitigated through large infrastructural projects that are both ineffective and vulnerable to corruption. Money would be better spent on preventing the subsidence by reducing groundwater pumping and moderating population growth and land use, but these approaches are politically and psychologically unacceptable. Even if groundwater use is greatly reduced and enlightened land-use practices are initiated, natural deltaic subsidence and global sea-level rise will continue to aggravate flooding, although at substantially lower rates.

  20. An expanded model: flood-inundation maps for the Leaf River at Hattiesburg, Mississippi, 2013

    Storm, John B.

    2014-01-01

    Digital flood-inundation maps for a 6.8-mile reach of the Leaf River at Hattiesburg, Mississippi (Miss.), were created by the U.S. Geological Survey (USGS) in cooperation with the City of Hattiesburg, City of Petal, Forrest County, Mississippi Emergency Management Agency, Mississippi Department of Homeland Security, and the Emergency Management District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Leaf River at Hattiesburg, Miss. (station no. 02473000). Current conditions for estimating near-real-time areas of inundation by use of USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relations at the Leaf River at Hattiesburg, Miss. streamgage (02473000) and documented high-water marks from recent and historical floods. The hydraulic model was then used to determine 13 water-surface profiles for flood stages at 1.0-foot intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system (GIS

  1. Global change and relative sea level rise at Venice: what impact in term of flooding

    Carbognin, Laura; Tosi, Luigi [Institute of Marine Sciences, National Research Council, Venice (Italy); Teatini, Pietro [Institute of Marine Sciences, National Research Council, Venice (Italy); University of Padova, Department of Mathematical Methods and Models for Scientific Applications, Padua (Italy); Tomasin, Alberto [Institute of Marine Sciences, National Research Council, Venice (Italy); University Ca' Foscari in Venice, Venice (Italy)

    2010-11-15

    Relative sea level rise (RSLR) due to climate change and geodynamics represents the main threat for the survival of Venice, emerging today only 90 cm above the Northern Adriatic mean sea level (msl). The 25 cm RSLR occurred over the 20th century, consisting of about 12 cm of land subsidence and 13 cm of sea level rise, has increased the flood frequency by more than seven times with severe damages to the urban heritage. Reasonable forecasts of the RSLR expected to the century end must be investigated to assess the suitability of the Mo.S.E. project planned for the city safeguarding, i.e., the closure of the lagoon inlets by mobile barriers. Here we consider three RSLR scenarios as resulting from the past sea level rise recorded in the Northern Adriatic Sea, the IPCC mid-range A1B scenario, and the expected land subsidence. Available sea level measurements show that more than 5 decades are required to compute a meaningful eustatic trend, due to pseudo-cyclic 7-8 year long fluctuations. The period from 1890 to 2007 is characterized by an average rate of 0.12 {+-} 0.01 cm/year. We demonstrate that linear regression is the most suitable model to represent the eustatic process over these 117 year. Concerning subsidence, at present Venice is sinking due to natural causes at 0.05 cm/year. The RSLR is expected to range between 17 and 53 cm by 2100, and its repercussions in terms of flooding frequency are associated here to each scenario. In particular, the frequency of tides higher than 110 cm, i.e., the value above which the gates would close the lagoon to the sea, will increase from the nowadays 4 times per year to a range between 20 and 250. These projections provide a large spread of possible conditions concerning the survival of Venice, from a moderate nuisance to an intolerable aggression. Hence, complementary solutions to Mo.S.E. may well be investigated. (orig.)

  2. Building a High-Precision 2D Hydrodynamic Flood Model Using UAV Photogrammetry and Sensor Network Monitoring

    Jakub Langhammer

    2017-11-01

    Full Text Available This paper explores the potential of the joint application of unmanned aerial vehicle (UAV-based photogrammetry and an automated sensor network for building a hydrodynamic flood model of a montane stream. UAV-based imagery was used for three-dimensional (3D photogrammetric reconstruction of the stream channel, achieving a resolution of 1.5 cm/pixel. Automated ultrasonic water level gauges, operating with a 10 min interval, were used as a source of hydrological data for the model calibration, and the MIKE 21 hydrodynamic model was used for building the flood model. Three different horizontal schematizations of the channel—an orthogonal grid, curvilinear grid, and flexible mesh—were used to evaluate the effect of spatial discretization on the results. The research was performed on Javori Brook, a montane stream in the Sumava (Bohemian Forest Mountains, Czech Republic, Central Europe, featuring a fast runoff response to precipitation events and that is located in a core zone of frequent flooding. The studied catchments have been, since 2007, equipped with automated water level gauges and, since 2013, under repeated UAV monitoring. The study revealed the high potential of these data sources for applications in hydrodynamic modeling. In addition to the ultra-high levels of spatial and temporal resolution, the major contribution is in the method’s high operability, enabling the building of highly detailed flood models even in remote areas lacking conventional monitoring. The testing of the data sources and model setup indicated the limitations of the UAV reconstruction of the stream bathymetry, which was completed by the geodetic-grade global navigation satellite system (GNSS measurements. The testing of the different model domain schematizations did not indicate the substantial differences that are typical for conventional low-resolution data, proving the high reliability of the tested modeling workflow.

  3. Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

    Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

    2017-10-01

    Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

  4. Using HAZUS-MH for modelling past coastal flooding events in Japan

    Robinson, T.; Charvet, I.; Gunasekera, R.

    2012-04-01

    In regions at risk from natural hazards, the ability to pre-determine the vulnerability and exposure of buildings (residential, commercial, industrial and government) from multiple hazard scenarios, allows policy makers and businesses to put forward appropriate policies, planning and intervention methods to mitigate the financial impact. For this purpose, a number of catastrophe models have been developed to provide the decision makers with quantitative risk assessments based on science and engineering knowledge. One of the most sophisticated open source models currently available is HAZUS-MH. The software is a powerful tool for analysing potential losses from floods, hurricane winds, and earthquakes. It was initially designed by FEMA to work with US datasets and has proven to be a great resource for disaster management at both national and local level in order to plan and increase the awareness of the recovery process after a natural disaster. Methodologies have been introduced to export the HAZUS-MH model for global applications. However, currently the international community have been slow to act on this technology breakthrough. The applications of this project will focus on adapting the HAZUS-HM model to provide a reliable vulnerability assessment of Japan's building stock from tsunami flooding. A review of the different methodologies will be carried out and presented as guidance on the best practice. The numerical assessment reports will be compared to real scenarios based on field observations, financial bulletins and government reports. A sensitivity analysis will be carried out on the generation of bespoke datasets based on the quality and density of the available regional data. These results will be compared against results using proxy US datasets. In addition, the significance of regional building standards and practices will be incorporated into the model through the development of new damage functions. The level of confidence and sensitivity (building

  5. Tree-based flood damage modeling of companies: Damage processes and model performance

    Sieg, Tobias; Vogel, Kristin; Merz, Bruno; Kreibich, Heidi

    2017-07-01

    Reliable flood risk analyses, including the estimation of damage, are an important prerequisite for efficient risk management. However, not much is known about flood damage processes affecting companies. Thus, we conduct a flood damage assessment of companies in Germany with regard to two aspects. First, we identify relevant damage-influencing variables. Second, we assess the prediction performance of the developed damage models with respect to the gain by using an increasing amount of training data and a sector-specific evaluation of the data. Random forests are trained with data from two postevent surveys after flood events occurring in the years 2002 and 2013. For a sector-specific consideration, the data set is split into four subsets corresponding to the manufacturing, commercial, financial, and service sectors. Further, separate models are derived for three different company assets: buildings, equipment, and goods and stock. Calculated variable importance values reveal different variable sets relevant for the damage estimation, indicating significant differences in the damage process for various company sectors and assets. With an increasing number of data used to build the models, prediction errors decrease. Yet the effect is rather small and seems to saturate for a data set size of several hundred observations. In contrast, the prediction improvement achieved by a sector-specific consideration is more distinct, especially for damage to equipment and goods and stock. Consequently, sector-specific data acquisition and a consideration of sector-specific company characteristics in future flood damage assessments is expected to improve the model performance more than a mere increase in data.

  6. Stimulating household flood risk mitigation investments through insurance and subsidies: an Agent-Based Modelling approach

    Haer, Toon; Botzen, Wouter; de Moel, Hans; Aerts, Jeroen

    2015-04-01

    In the period 1998-2009, floods triggered roughly 52 billion euro in insured economic losses making floods the most costly natural hazard in Europe. Climate change and socio/economic trends are expected to further aggrevate floods losses in many regions. Research shows that flood risk can be significantly reduced if households install protective measures, and that the implementation of such measures can be stimulated through flood insurance schemes and subsidies. However, the effectiveness of such incentives to stimulate implementation of loss-reducing measures greatly depends on the decision process of individuals and is hardly studied. In our study, we developed an Agent-Based Model that integrates flood damage models, insurance mechanisms, subsidies, and household behaviour models to assess the effectiveness of different economic tools on stimulating households to invest in loss-reducing measures. Since the effectiveness depends on the decision making process of individuals, the study compares different household decision models ranging from standard economic models, to economic models for decision making under risk, to more complex decision models integrating economic models and risk perceptions, opinion dynamics, and the influence of flood experience. The results show the effectiveness of incentives to stimulate investment in loss-reducing measures for different household behavior types, while assuming climate change scenarios. It shows how complex decision models can better reproduce observed real-world behaviour compared to traditional economic models. Furthermore, since flood events are included in the simulations, the results provide an analysis of the dynamics in insured and uninsured losses for households, the costs of reducing risk by implementing loss-reducing measures, the capacity of the insurance market, and the cost of government subsidies under different scenarios. The model has been applied to the City of Rotterdam in The Netherlands.

  7. Probabilistic, Multivariable Flood Loss Modeling on the Mesoscale with BT-FLEMO.

    Kreibich, Heidi; Botto, Anna; Merz, Bruno; Schröter, Kai

    2017-04-01

    Flood loss modeling is an important component for risk analyses and decision support in flood risk management. Commonly, flood loss models describe complex damaging processes by simple, deterministic approaches like depth-damage functions and are associated with large uncertainty. To improve flood loss estimation and to provide quantitative information about the uncertainty associated with loss modeling, a probabilistic, multivariable Bagging decision Tree Flood Loss Estimation MOdel (BT-FLEMO) for residential buildings was developed. The application of BT-FLEMO provides a probability distribution of estimated losses to residential buildings per municipality. BT-FLEMO was applied and validated at the mesoscale in 19 municipalities that were affected during the 2002 flood by the River Mulde in Saxony, Germany. Validation was undertaken on the one hand via a comparison with six deterministic loss models, including both depth-damage functions and multivariable models. On the other hand, the results were compared with official loss data. BT-FLEMO outperforms deterministic, univariable, and multivariable models with regard to model accuracy, although the prediction uncertainty remains high. An important advantage of BT-FLEMO is the quantification of prediction uncertainty. The probability distribution of loss estimates by BT-FLEMO well represents the variation range of loss estimates of the other models in the case study. © 2016 Society for Risk Analysis.

  8. Probabilistic flood inundation mapping at ungauged streams due to roughness coefficient uncertainty in hydraulic modelling

    Papaioannou, George; Vasiliades, Lampros; Loukas, Athanasios; Aronica, Giuseppe T.

    2017-04-01

    Probabilistic flood inundation mapping is performed and analysed at the ungauged Xerias stream reach, Volos, Greece. The study evaluates the uncertainty introduced by the roughness coefficient values on hydraulic models in flood inundation modelling and mapping. The well-established one-dimensional (1-D) hydraulic model, HEC-RAS is selected and linked to Monte-Carlo simulations of hydraulic roughness. Terrestrial Laser Scanner data have been used to produce a high quality DEM for input data uncertainty minimisation and to improve determination accuracy on stream channel topography required by the hydraulic model. Initial Manning's n roughness coefficient values are based on pebble count field surveys and empirical formulas. Various theoretical probability distributions are fitted and evaluated on their accuracy to represent the estimated roughness values. Finally, Latin Hypercube Sampling has been used for generation of different sets of Manning roughness values and flood inundation probability maps have been created with the use of Monte Carlo simulations. Historical flood extent data, from an extreme historical flash flood event, are used for validation of the method. The calibration process is based on a binary wet-dry reasoning with the use of Median Absolute Percentage Error evaluation metric. The results show that the proposed procedure supports probabilistic flood hazard mapping at ungauged rivers and provides water resources managers with valuable information for planning and implementing flood risk mitigation strategies.

  9. Adaptation and Mitigation Model for People to Restore Their Ecosystem from Flood in Semarang, Indonesia

    Muzakar Isa

    2015-12-01

    Full Text Available The northern coast of Central Java province is considered as the critical area of flood path. Semarang as capital city of this province with its junction area of Kendal and Demak always suffering from flood due to rain and or high tide seawater. It is realised that infrastructures’ capacity for flood control, awareness of people and other multi-factors are significantly contributed on the flood problem in these area. Mixed-methods of quantitative and qualitative are employed to analyze the data. The study found that there was a decline in quality of - people’s life, environment and its ecosystem. Awareness and responsiveness of people and also the other stakeholders are not progressive to overcome the problem of flood. This study is trying to contribute in outlining a model of adaptation and mitigation for the people to restore their ecosystem from the perspective of economist.

  10. Modeling Flood Insurance Penetration in the European Non-Life Market: An Overview

    Mohan, P.; Thomson, M.-K.; Das, A.

    2012-04-01

    Non-life property insurance plays a significant role in assessing and managing economic risk. Understanding the exposure, or property at risk, helps insurers and reinsurers to better categorize and manage their portfolios. However, the nature of the flood peril, in particular adverse selection, has led to a complex system of different insurance covers and policies across Europe owing to its public and private distinctions based on premiums provided as ex ante or ex post, socio-economic characterization and various compensation schemes. To model this significant level of complexity within the European flood insurance market requires not only extensive data research, close understanding of insurance companies and associations as well as historic flood events, but also careful evaluation of the flood hazard in terms of return periods and flood extents, and the economic/ financial background of the geographies involved. This abstract explores different approaches for modeling the flood insurance penetration rates in Europe depending on the information available and complexity involved. For countries which have either a regulated market with mandatory or high penetration rate, as for example found in the UK, France and Switzerland, or indeed countries with negligible insurance cover such as Luxembourg, assumptions about the penetration rates can be made at country level. However, in countries with a private insurance market, the picture becomes inherently more complex. For example in both Austria and Germany, flood insurance is generally restricted, associated with high costs to the insured or not available at all in high risk areas. In order to better manage flood risk, the Austria and German government agencies produced the risk classification systems HORA and ZÜRS, respectively, which categorize risk into four risk zones based on the exceedance probability of a flood occurrence. Except for regions that have preserved mandatory flood inclusion from past policies

  11. Floods and Flash Flooding

    Floods and flash flooding Now is the time to determine your area’s flood risk. If you are not sure whether you ... If you are in a floodplain, consider buying flood insurance. Do not drive around barricades. If your ...

  12. Modeling of global biomass policies

    Gielen, Dolf; Fujino, Junichi; Hashimoto, Seiji; Moriguchi, Yuichi

    2003-01-01

    This paper discusses the BEAP model and its use for the analysis of biomass policies for CO 2 emission reduction. The model considers competing land use, trade and leakage effects, and competing emission reduction strategies. Two policy scenarios are presented. In case of a 2040 time horizon the results suggest that a combination of afforestation and limited use of biomass for energy and materials constitutes the most attractive set of strategies. In case of a 'continued Kyoto' scenario including afforestation permit trade, the results suggest 5.1 Gt emission reduction based on land use change in 2020, two thirds of the total emission reduction by then. In case of global emission reduction, land use, land use change and forestry (LULUCF) accounts for one quarter of the emission reduction. However these results depend on the modeling time horizon. In case of a broader time horizon, maximized biomass production is more attractive than LULUCF. This result can be interpreted as a warning against a market based trading scheme for LULUCF credits. The model results suggest that the bioenergy market is dominated by transportation fuels and heating, and to a lesser extent feedstocks. Bioelectricity does not gain a significant market share in case competing CO 2 -free electricity options such as CO 2 capture and sequestration and nuclear are considered. To some extent trade in agricultural food products such as beef and cereals will be affected by CO 2 policies

  13. Modeling of global biomass policies

    Gielen, D.; Fujino, Junichi; Hashimoto, Seiji; Moriguchi, Yuichi

    2003-01-01

    This paper discusses the BEAP model and its use for the analysis of biomass policies for CO 2 emission reduction. The model considers competing land use, trade and leakage effects, and competing emission reduction strategies. Two policy scenarios are presented. In case of a 2040 time horizon the results suggest that a combination of afforestation and limited use of biomass for energy and materials constitutes the most attractive set of strategies. In case of a 'continued Kyoto' scenario including afforestation permit trade, the results suggest 5.1 Gt emission reduction based on land use change in 2020, two thirds of the total emission reduction by then. In case of global emission reduction, land use, land use change and forestry (LULUCF) accounts for one quarter of the emission reduction. However these results depend on the modeling time horizon. In case of a broader time horizon, maximized biomass production is more attractive than LULUCF. This result can be interpreted as a warning against a market based trading scheme for LULUCF credits. The model results suggest that the bioenergy market is dominated by transportation fuels and heating, and to a lesser extent feedstocks. Bioelectricity does not gain a significant market share in case competing CO 2 -free electricity options such as CO 2 capture and sequestration and nuclear are considered. To some extent trade in agricultural food products such as beef and cereals will be affected by CO 2 policies. (Author)

  14. Improvements in fast-response flood modeling: desktop parallel computing and domain tracking

    Judi, David R [Los Alamos National Laboratory; Mcpherson, Timothy N [Los Alamos National Laboratory; Burian, Steven J [UNIV. OF UTAH

    2009-01-01

    It is becoming increasingly important to have the ability to accurately forecast flooding, as flooding accounts for the most losses due to natural disasters in the world and the United States. Flood inundation modeling has been dominated by one-dimensional approaches. These models are computationally efficient and are considered by many engineers to produce reasonably accurate water surface profiles. However, because the profiles estimated in these models must be superimposed on digital elevation data to create a two-dimensional map, the result may be sensitive to the ability of the elevation data to capture relevant features (e.g. dikes/levees, roads, walls, etc...). Moreover, one-dimensional models do not explicitly represent the complex flow processes present in floodplains and urban environments and because two-dimensional models based on the shallow water equations have significantly greater ability to determine flow velocity and direction, the National Research Council (NRC) has recommended that two-dimensional models be used over one-dimensional models for flood inundation studies. This paper has shown that two-dimensional flood modeling computational time can be greatly reduced through the use of Java multithreading on multi-core computers which effectively provides a means for parallel computing on a desktop computer. In addition, this paper has shown that when desktop parallel computing is coupled with a domain tracking algorithm, significant computation time can be eliminated when computations are completed only on inundated cells. The drastic reduction in computational time shown here enhances the ability of two-dimensional flood inundation models to be used as a near-real time flood forecasting tool, engineering, design tool, or planning tool. Perhaps even of greater significance, the reduction in computation time makes the incorporation of risk and uncertainty/ensemble forecasting more feasible for flood inundation modeling (NRC 2000; Sayers et al

  15. Flood Risk Zoning by Using 2D Hydrodynamic Modeling: A Case Study in Jinan City

    Tao Cheng

    2017-01-01

    Full Text Available Climate change and rapid urbanization have aggravated the rainstorm flood in Jinan City during the past decades. Jinan City is higher in the south and lower in the north with a steep slope inclined from the south to the north. This results in high-velocity overland flow and deep waterlogging, which poses a tremendous threat to pedestrians and vehicles. Therefore, it is vital to investigate the rainstorm flood and further perform flood risk zoning. This study is carried out in the “Sponge City Construction” pilot area of Jinan City, where the InfoWorks ICM 2D hydrodynamic model is utilized for simulating historical and designed rainfall events. The model is validated with observations, and the causes for errors are analyzed. The simulated water depth and flow velocity are recorded for flood risk zoning. The result shows that the InfoWorks ICM 2D model performed well. The flood risk zoning result shows that rainfalls with larger recurrence intervals generate larger areas of moderate to extreme risk. Meanwhile, the zoning results for the two historical rainfalls show that flood with a higher maximum hourly rainfall intensity is more serious. This study will provide scientific support for the flood control and disaster reduction in Jinan City.

  16. Catastrophe loss modelling of storm-surge flood risk in eastern England.

    Muir Wood, Robert; Drayton, Michael; Berger, Agnete; Burgess, Paul; Wright, Tom

    2005-06-15

    Probabilistic catastrophe loss modelling techniques, comprising a large stochastic set of potential storm-surge flood events, each assigned an annual rate of occurrence, have been employed for quantifying risk in the coastal flood plain of eastern England. Based on the tracks of the causative extratropical cyclones, historical storm-surge events are categorized into three classes, with distinct windfields and surge geographies. Extreme combinations of "tide with surge" are then generated for an extreme value distribution developed for each class. Fragility curves are used to determine the probability and magnitude of breaching relative to water levels and wave action for each section of sea defence. Based on the time-history of water levels in the surge, and the simulated configuration of breaching, flow is time-stepped through the defences and propagated into the flood plain using a 50 m horizontal-resolution digital elevation model. Based on the values and locations of the building stock in the flood plain, losses are calculated using vulnerability functions linking flood depth and flood velocity to measures of property loss. The outputs from this model for a UK insurance industry portfolio include "loss exceedence probabilities" as well as "average annualized losses", which can be employed for calculating coastal flood risk premiums in each postcode.

  17. Debates—Perspectives on socio-hydrology: Modeling flood risk as a public policy problem

    Gober, Patricia; Wheater, Howard S.

    2015-06-01

    Socio-hydrology views human activities as endogenous to water system dynamics; it is the interaction between human and biophysical processes that threatens the viability of current water systems through positive feedbacks and unintended consequences. Di Baldassarre et al. implement socio-hydrology as a flood risk problem using the concept of social memory as a vehicle to link human perceptions to flood damage. Their mathematical model has heuristic value in comparing potential flood damages in green versus technological societies. It can also support communities in exploring the potential consequences of policy decisions and evaluating critical policy tradeoffs, for example, between flood protection and economic development. The concept of social memory does not, however, adequately capture the social processes whereby public perceptions are translated into policy action, including the pivotal role played by the media in intensifying or attenuating perceived flood risk, the success of policy entrepreneurs in keeping flood hazard on the public agenda during short windows of opportunity for policy action, and different societal approaches to managing flood risk that derive from cultural values and economic interests. We endorse the value of seeking to capture these dynamics in a simplified conceptual framework, but favor a broader conceptualization of socio-hydrology that includes a knowledge exchange component, including the way modeling insights and scientific results are communicated to floodplain managers. The social processes used to disseminate the products of socio-hydrological research are as important as the research results themselves in determining whether modeling is used for real-world decision making.

  18. Flooding Simulation of Extreme Event on Barnegat Bay by High-Resolution Two Dimensional Hydrodynamic Model

    Wang, Y.; Ramaswamy, V.; Saleh, F.

    2017-12-01

    Barnegat Bay located on the east coast of New Jersey, United States and is separated from the Atlantic Ocean by the narrow Barnegat Peninsula which acts as a barrier island. The bay is fed by several rivers which empty through small estuaries along the inner shore. In terms of vulnerability from flooding, the Barnegat Peninsula is under the influence of both coastal storm surge and riverine flooding. Barnegat Bay was hit by Hurricane Sandy causing flood damages with extensive cross-island flow at many streets perpendicular to the shoreline. The objective of this work is to identify and quantify the sources of flooding using a two dimensional inland hydrodynamic model. The hydrodynamic model was forced by three observed coastal boundary conditions, and one hydrologic boundary condition from United States Geological Survey (USGS). The model reliability was evaluated with both FEMA spatial flooding extend and USGS High water marks. Simulated flooding extent showed good agreement with the reanalysis spatial inundation extents. Results offered important perspectives on the flow of the water into the bay, the velocity and the depth of the inundated areas. Using such information can enable emergency managers and decision makers identify evacuation and deploy flood defenses.

  19. Holistic flood risk assessment using agent-based modelling: the case of Sint Maarten Island

    Abayneh Abebe, Yared; Vojinovic, Zoran; Nikolic, Igor; Hammond, Michael; Sanchez, Arlex; Pelling, Mark

    2015-04-01

    Floods in coastal regions are regarded as one of the most dangerous and harmful disasters. Though commonly referred to as natural disasters, coastal floods are also attributable to various social, economic, historical and political issues. Rapid urbanisation in coastal areas combined with climate change and poor governance can lead to a significant increase in the risk of pluvial flooding coinciding with fluvial and coastal flooding posing a greater risk of devastation in coastal communities. Disasters that can be triggered by hydro-meteorological events are interconnected and interrelated with both human activities and natural processes. They, therefore, require holistic approaches to help understand their complexity in order to design and develop adaptive risk management approaches that minimise social and economic losses and environmental impacts, and increase resilience to such events. Being located in the North Atlantic Ocean, Sint Maarten is frequently subjected to hurricanes. In addition, the stormwater catchments and streams on Sint Maarten have several unique characteristics that contribute to the severity of flood-related impacts. Urban environments are usually situated in low-lying areas, with little consideration for stormwater drainage, and as such are subject to flash flooding. Hence, Sint Maarten authorities drafted policies to minimise the risk of flood-related disasters on the island. In this study, an agent-based model is designed and applied to understand the implications of introduced policies and regulations, and to understand how different actors' behaviours influence the formation, propagation and accumulation of flood risk. The agent-based model built for this study is based on the MAIA meta-model, which helps to decompose, structure and conceptualize socio-technical systems with an agent-oriented perspective, and is developed using the NetLogo simulation environment. The agents described in this model are households and businesses, and

  20. A global hydrographic array for early detection of floods and droughts

    Brakenridge, G.; Nghiem, S.; Caquard, S.

    An array of over 700 20 km-long river gaging reaches, distributed world-wide, is imaged by the SeaWinds radar scatterometer aboard QuikSCAT every 2.5 days. Strongly negative HH/VV polarity ratios indicate large amounts of surface water. We set individual reach thresholds so that the transition from bankfull to overbank river flow can be identified according to changes in this ratio. Similarly, the wide-swath MODIS optical sensors provide frequent repeat coverage of the reaches at much higher spatial resolution (250 m). In this case, several reach water surface area thresholds can be identified: low flow or drought conditions, normal in-channel flow, overbank flow, and extreme flood conditions. Sustained data collection for the reaches by both sensors allows the radar response to changing surface water to be defined, and allows evaluation of the sensitivity of the MODIS data to river discharge changes. New approaches, such as ``unmixing'' analysis of mixed water/land MODIS pixels can extend detection limits to smaller rivers and streams. It is now possible for wide-area, frequent revisit terrestrial remote sensing to provide human society with early warning of both floods and droughts and by direct observation of the runoff component of the Earth's hydrologic cycle. Examples of both radar and optical approaches towards this end are at the web sites below: http://www.dartmouth.edu/˜ floods/Modisrapidresponse.html http://www.dartmouth.edu/˜ floods/sensorweb/SensorWebindex.html http://www.dartmouth.edu/˜ floods/Quikscat/Regional2/CurrentTisza.jpg} In particular, early flood detection results are obtained over an extensive region in eastern Europe including the Tisza River basin, Romania, Hungary, and adjacent nations. Flood detection maps are updated weekly at the web site. The combination of QuikSCAT and MODIS takes advantage of the large-area coverage of these sensors together with the high temporal resolution of QuikSCAT and the high spatial resolution of MODIS

  1. Development of high-resolution multi-scale modelling system for simulation of coastal-fluvial urban flooding

    Comer, Joanne; Indiana Olbert, Agnieszka; Nash, Stephen; Hartnett, Michael

    2017-02-01

    Urban developments in coastal zones are often exposed to natural hazards such as flooding. In this research, a state-of-the-art, multi-scale nested flood (MSN_Flood) model is applied to simulate complex coastal-fluvial urban flooding due to combined effects of tides, surges and river discharges. Cork city on Ireland's southwest coast is a study case. The flood modelling system comprises a cascade of four dynamically linked models that resolve the hydrodynamics of Cork Harbour and/or its sub-region at four scales: 90, 30, 6 and 2 m. Results demonstrate that the internalization of the nested boundary through the use of ghost cells combined with a tailored adaptive interpolation technique creates a highly dynamic moving boundary that permits flooding and drying of the nested boundary. This novel feature of MSN_Flood provides a high degree of choice regarding the location of the boundaries to the nested domain and therefore flexibility in model application. The nested MSN_Flood model through dynamic downscaling facilitates significant improvements in accuracy of model output without incurring the computational expense of high spatial resolution over the entire model domain. The urban flood model provides full characteristics of water levels and flow regimes necessary for flood hazard identification and flood risk assessment.

  2. Towards the optimal fusion of high-resolution Digital Elevation Models for detailed urban flood assessment

    Leitão, J. P.; de Sousa, L. M.

    2018-06-01

    Newly available, more detailed and accurate elevation data sets, such as Digital Elevation Models (DEMs) generated on the basis of imagery from terrestrial LiDAR (Light Detection and Ranging) systems or Unmanned Aerial Vehicles (UAVs), can be used to improve flood-model input data and consequently increase the accuracy of the flood modelling results. This paper presents the first application of the MBlend merging method and assesses the impact of combining different DEMs on flood modelling results. It was demonstrated that different raster merging methods can have different and substantial impacts on these results. In addition to the influence associated with the method used to merge the original DEMs, the magnitude of the impact also depends on (i) the systematic horizontal and vertical differences of the DEMs, and (ii) the orientation between the DEM boundary and the terrain slope. The greater water depth and flow velocity differences between the flood modelling results obtained using the reference DEM and the merged DEMs ranged from -9.845 to 0.002 m, and from 0.003 to 0.024 m s-1 respectively; these differences can have a significant impact on flood hazard estimates. In most of the cases investigated in this study, the differences from the reference DEM results were smaller for the MBlend method than for the results of the two conventional methods. This study highlighted the importance of DEM merging when conducting flood modelling and provided hints on the best DEM merging methods to use.

  3. Uncertainty and sensitivity analysis of flood risk management decisions based on stationary and nonstationary model choices

    Rehan Balqis M.

    2016-01-01

    Full Text Available Current practice in flood frequency analysis assumes that the stochastic properties of extreme floods follow that of stationary conditions. As human intervention and anthropogenic climate change influences in hydrometeorological variables are becoming evident in some places, there have been suggestions that nonstationary statistics would be better to represent the stochastic properties of the extreme floods. The probabilistic estimation of non-stationary models, however, is surrounded with uncertainty related to scarcity of observations and modelling complexities hence the difficulty to project the future condition. In the face of uncertain future and the subjectivity of model choices, this study attempts to demonstrate the practical implications of applying a nonstationary model and compares it with a stationary model in flood risk assessment. A fully integrated framework to simulate decision makers’ behaviour in flood frequency analysis is thereby developed. The framework is applied to hypothetical flood risk management decisions and the outcomes are compared with those of known underlying future conditions. Uncertainty of the economic performance of the risk-based decisions is assessed through Monte Carlo simulations. Sensitivity of the results is also tested by varying the possible magnitude of future changes. The application provides quantitative and qualitative comparative results that satisfy a preliminary analysis of whether the nonstationary model complexity should be applied to improve the economic performance of decisions. Results obtained from the case study shows that the relative differences of competing models for all considered possible future changes are small, suggesting that stationary assumptions are preferred to a shift to nonstationary statistics for practical application of flood risk management. Nevertheless, nonstationary assumption should also be considered during a planning stage in addition to stationary assumption

  4. Nested 1D-2D approach for urban surface flood modeling

    Murla, Damian; Willems, Patrick

    2015-04-01

    Floods in urban areas as a consequence of sewer capacity exceedance receive increased attention because of trends in urbanization (increased population density and impermeability of the surface) and climate change. Despite the strong recent developments in numerical modeling of water systems, urban surface flood modeling is still a major challenge. Whereas very advanced and accurate flood modeling systems are in place and operation by many river authorities in support of flood management along rivers, this is not yet the case in urban water management. Reasons include the small scale of the urban inundation processes, the need to have very high resolution topographical information available, and the huge computational demands. Urban drainage related inundation modeling requires a 1D full hydrodynamic model of the sewer network to be coupled with a 2D surface flood model. To reduce the computational times, 0D (flood cones), 1D/quasi-2D surface flood modeling approaches have been developed and applied in some case studies. In this research, a nested 1D/2D hydraulic model has been developed for an urban catchment at the city of Gent (Belgium), linking the underground sewer (minor system) with the overland surface (major system). For the overland surface flood modelling, comparison was made of 0D, 1D/quasi-2D and full 2D approaches. The approaches are advanced by considering nested 1D-2D approaches, including infiltration in the green city areas, and allowing the effects of surface storm water storage to be simulated. An optimal nested combination of three different mesh resolutions was identified; based on a compromise between precision and simulation time for further real-time flood forecasting, warning and control applications. Main streets as mesh zones together with buildings as void regions constitute one of these mesh resolution (3.75m2 - 15m2); they have been included since they channel most of the flood water from the manholes and they improve the accuracy of

  5. Spatial Analytic Hierarchy Process Model for Flood Forecasting: An Integrated Approach

    Matori, Abd Nasir; Yusof, Khamaruzaman Wan; Hashim, Mustafa Ahmad; Lawal, Dano Umar; Balogun, Abdul-Lateef

    2014-01-01

    Various flood influencing factors such as rainfall, geology, slope gradient, land use, soil type, drainage density, temperature etc. are generally considered for flood hazard assessment. However, lack of appropriate handling/integration of data from different sources is a challenge that can make any spatial forecasting difficult and inaccurate. Availability of accurate flood maps and thorough understanding of the subsurface conditions can adequately enhance flood disasters management. This study presents an approach that attempts to provide a solution to this drawback by combining Geographic Information System (GIS)-based Analytic Hierarchy Process (AHP) model as spatial forecasting tools. In achieving the set objectives, spatial forecasting of flood susceptible zones in the study area was made. A total number of five set of criteria/factors believed to be influencing flood generation in the study area were selected. Priority weights were assigned to each criterion/factor based on Saaty's nine point scale of preference and weights were further normalized through the AHP. The model was integrated into a GIS system in order to produce a flood forecasting map

  6. INVESTIGATION OF QUANTIFICATION OF FLOOD CONTROL AND WATER UTILIZATION EFFECT OF RAINFALL INFILTRATION FACILITY BY USING WATER BALANCE ANALYSIS MODEL

    文, 勇起; BUN, Yuki

    2013-01-01

    In recent years, many flood damage and drought attributed to urbanization has occurred. At present infiltration facility is suggested for the solution of these problems. Based on this background, the purpose of this study is investigation of quantification of flood control and water utilization effect of rainfall infiltration facility by using water balance analysis model. Key Words : flood control, water utilization , rainfall infiltration facility

  7. A framework for the selection and ensemble development of flood vulnerability models

    Figueiredo, Rui; Schröter, Kai; Kreibich, Heidi; Martina, Mario

    2017-04-01

    Effective understanding and management of flood risk requires comprehensive risk assessment studies that consider not only the hazard component, but also the impacts that the phenomena may have on the built environment, economy and society. This integrated approach has gained importance over recent decades, and with it so has the scientific attention given to flood vulnerability models describing the relationships between flood intensity metrics and damage to physical assets, also known as flood loss models. Despite considerable progress in this field, many challenges persist. Flood damage mechanisms are complex and depend on multiple variables, which can have different degrees of importance depending on the application setting. In addition, data required for the development and validation of such models tend to be scarce, particularly in data poor regions. These issues are reflected in the large amount of flood vulnerability models that are available in the literature today, as well as in their high heterogeneity: they are built with different modelling approaches, in different geographic contexts, utilizing different explanatory variables, and with varying levels of complexity. Notwithstanding recent developments in this area, uncertainty remains high, and large disparities exist among models. For these reasons, identifying which model or models, given their properties, are appropriate for a given context is not straightforward. In the present study, we propose a framework that guides the structured selection of flood vulnerability models and enables ranking them according to their suitability for a certain application, based on expert judgement. The approach takes advantage of current state of the art and most up-to-date knowledge on flood vulnerability processes. Given the heterogeneity and uncertainty currently present in flood vulnerability models, we propose the use of a model ensemble. With this in mind, the proposed approach is based on a weighting scheme

  8. Coarse Resolution SAR Imagery to Support Flood Inundation Models in Near Real Time

    Di Baldassarre, Giuliano; Schumann, Guy; Brandimarte, Luigia; Bates, Paul

    2009-11-01

    In recent years, the availability of new emerging data (e.g. remote sensing, intelligent wireless sensors, etc) has led to a sudden shift from a data-sparse to a data-rich environment for hydrological and hydraulic modelling. Furthermore, the increased socioeconomic relevance of river flood studies has motivated the development of complex methodologies for the simulation of the hydraulic behaviour of river systems. In this context, this study aims at assessing the capability of coarse resolution SAR (Synthetic Aperture Radar) imagery to support and quickly validate flood inundation models in near real time. A hydraulic model of a 98km reach of the River Po (Italy), previously calibrated on a high-magnitude flood event with extensive and high quality field data, is tested using a SAR flood image, acquired and processed in near real time, during the June 2008 low-magnitude event. Specifically, the image is an acquisition by the ENVISAT-ASAR sensor in wide swath mode and has been provided through ESA (European Space Agency) Fast Registration system at no cost 24 hours after the acquisition. The study shows that the SAR image enables validation and improvement of the model in a time shorter than the flood travel time. This increases the reliability of model predictions (e.g. water elevation and inundation width along the river reach) and, consequently, assists flood management authorities in undertaking the necessary prevention activities.

  9. Risk assessment of flood disaster and forewarning model at different spatial-temporal scales

    Zhao, Jun; Jin, Juliang; Xu, Jinchao; Guo, Qizhong; Hang, Qingfeng; Chen, Yaqian

    2018-05-01

    Aiming at reducing losses from flood disaster, risk assessment of flood disaster and forewarning model is studied. The model is built upon risk indices in flood disaster system, proceeding from the whole structure and its parts at different spatial-temporal scales. In this study, on the one hand, it mainly establishes the long-term forewarning model for the surface area with three levels of prediction, evaluation, and forewarning. The method of structure-adaptive back-propagation neural network on peak identification is used to simulate indices in prediction sub-model. Set pair analysis is employed to calculate the connection degrees of a single index, comprehensive index, and systematic risk through the multivariate connection number, and the comprehensive assessment is made by assessment matrixes in evaluation sub-model. The comparison judging method is adopted to divide warning degree of flood disaster on risk assessment comprehensive index with forewarning standards in forewarning sub-model and then the long-term local conditions for proposing planning schemes. On the other hand, it mainly sets up the real-time forewarning model for the spot, which introduces the real-time correction technique of Kalman filter based on hydrological model with forewarning index, and then the real-time local conditions for presenting an emergency plan. This study takes Tunxi area, Huangshan City of China, as an example. After risk assessment and forewarning model establishment and application for flood disaster at different spatial-temporal scales between the actual and simulated data from 1989 to 2008, forewarning results show that the development trend for flood disaster risk remains a decline on the whole from 2009 to 2013, despite the rise in 2011. At the macroscopic level, project and non-project measures are advanced, while at the microcosmic level, the time, place, and method are listed. It suggests that the proposed model is feasible with theory and application, thus

  10. A new modelling framework and mitigation measures for increased resilience to flooding

    Valyrakis, Manousos; Alexakis, Athanasios; Solley, Mark

    2015-04-01

    Flooding in rivers and estuaries is amongst the most significant challenges our society has yet to tackle effectively. Use of floodwall systems is one of the potential measures that can be used to mitigate the detrimental socio-economical and ecological impacts and alleviate the associated costs of flooding. This work demonstrates the utility of such systems for a case study via appropriate numerical simulations, in addition to conducting scaled flume experiments towards obtaining a better understanding of the performance and efficiency of the flood-wall systems. At first, the results of several characteristic inundation modeling scenarios and flood mitigation options, for a flood-prone region in Scotland. In particular, the history and hydrology of the area are discussed and the assumptions and hydraulic model input (model geometry including instream hydraulic structures -such as bridges and weirs- river and floodplain roughness, initial and boundary conditions) are presented, followed by the model results. Emphasis is given on the potential improvements brought about by mitigating flood risk using flood-wall systems. Further, the implementation of the floodwall in mitigating flood risk is demonstrated via appropriate numerical modeling, utilizing HEC-RAS to simulate the effect of a river's rising stage during a flood event, for a specific area. The later part of this work involves the design, building and utilization of a scaled physical model of a flood-wall system. These experiments are carried out at one of the research flumes in the Water Engineering laboratory of the University of Glasgow. These involve an experimental investigation where the increase of force applied on the floodwall is measured for different degrees of deflection of the water in the stream, under the maximum flow discharge that can be carried through without exceeding the floodwall height (and accounting for the effect of super-elevation). These results can be considered upon the

  11. Numerical Well Testing Interpretation Model and Applications in Crossflow Double-Layer Reservoirs by Polymer Flooding

    Haiyang Yu

    2014-01-01

    Full Text Available This work presents numerical well testing interpretation model and analysis techniques to evaluate formation by using pressure transient data acquired with logging tools in crossflow double-layer reservoirs by polymer flooding. A well testing model is established based on rheology experiments and by considering shear, diffusion, convection, inaccessible pore volume (IPV, permeability reduction, wellbore storage effect, and skin factors. The type curves were then developed based on this model, and parameter sensitivity is analyzed. Our research shows that the type curves have five segments with different flow status: (I wellbore storage section, (II intermediate flow section (transient section, (III mid-radial flow section, (IV crossflow section (from low permeability layer to high permeability layer, and (V systematic radial flow section. The polymer flooding field tests prove that our model can accurately determine formation parameters in crossflow double-layer reservoirs by polymer flooding. Moreover, formation damage caused by polymer flooding can also be evaluated by comparison of the interpreted permeability with initial layered permeability before polymer flooding. Comparison of the analysis of numerical solution based on flow mechanism with observed polymer flooding field test data highlights the potential for the application of this interpretation method in formation evaluation and enhanced oil recovery (EOR.

  12. Thermo-hydrodynamical modelling of a flooded deep mine reservoir - Case of the Lorraine Coal Basin

    Reichart, Guillaume

    2015-01-01

    Since 2006, cessation of dewatering in Lorraine Coal Basin (France) led to the flooding of abandoned mines, resulting in a new hydrodynamic balance in the area. Recent researches concerning geothermal exploitation of flooded reservoirs raised new questions, which we propose to answer. Our work aimed to understand the thermos-hydrodynamic behaviour of mine water in a flooding or flooded system. Firstly, we synthesized the geographical, geological and hydrogeological contexts of the Lorraine Coal Basin, and we chose a specific area for our studies. Secondly, temperature and electric conductivity log profiles were measured in old pits of the Lorraine Coal Basin, giving a better understanding of the water behaviour at a deep mine shaft scale. We were able to build a thermos-hydrodynamic model and simulate water behaviour at this scale. Flow regime stability is also studied. Thirdly, a hydrodynamic spatialized meshed model was realized to study the hydrodynamic behaviour of a mine reservoir as a whole. Observed water-table rise was correctly reproduced: moreover, the model can be used in a predictive way after the flooding. Several tools were tested, improved or developed to ease the study of flooded reservoirs, as three-dimensional up-scaling of hydraulic conductivities and a coupled spatialized meshed model with a pipe network. (author) [fr

  13. Analysing the Effects of Flood-Resilience Technologies in Urban Areas Using a Synthetic Model Approach

    Reinhard Schinke

    2016-11-01

    Full Text Available Flood protection systems with their spatial effects play an important role in managing and reducing flood risks. The planning and decision process as well as the technical implementation are well organized and often exercised. However, building-related flood-resilience technologies (FReT are often neglected due to the absence of suitable approaches to analyse and to integrate such measures in large-scale flood damage mitigation concepts. Against this backdrop, a synthetic model-approach was extended by few complementary methodical steps in order to calculate flood damage to buildings considering the effects of building-related FReT and to analyse the area-related reduction of flood risks by geo-information systems (GIS with high spatial resolution. It includes a civil engineering based investigation of characteristic properties with its building construction including a selection and combination of appropriate FReT as a basis for derivation of synthetic depth-damage functions. Depending on the real exposition and the implementation level of FReT, the functions can be used and allocated in spatial damage and risk analyses. The application of the extended approach is shown at a case study in Valencia (Spain. In this way, the overall research findings improve the integration of FReT in flood risk management. They provide also some useful information for advising of individuals at risk supporting the selection and implementation of FReT.

  14. Two dimensional modelling of flood flows and suspended sediment transport: the case of Brenta River

    D'Alpaos, L.; Martini, P.; Carniello, L.

    2003-04-01

    The paper deals with numerical modelling of flood waves and suspended sediment in plain river basins. The two dimensional depth integrated momentum and continuity equations, modified to take into account of the bottom irregularities that strongly affect the hydrodynamic and the continuity in partially dry areas (for example, during the first stages of a plain flooding and in tidal flows), are solved with a standard Galerkin finite element method using a semi-implicit numerical scheme and considering the role both of the small channel network and the regulation dispositive on the flooding wave propagation. Transport of suspended sediment and bed evolution are coupled with the flood propagation through the convection-dispersion equation and the Exner's equation. Results of a real case study are presented in which the effects of extreme flood of Brenta River (Italy) are examinated. The flooded areas (urban and rural areas) are identified and a mitigation solution based on a diversion channel flowing into Venice Lagoon is proposed. We show that this solution strongly reduces the flood risk in the downstream areas and can provide an important sediment source to the Venice Lagoon. Finally, preliminary results of the sediment dispersion in the Venice Lagoon are presented.

  15. Calibration of HEC-Ras hydrodynamic model using gauged discharge data and flood inundation maps

    Tong, Rui; Komma, Jürgen

    2017-04-01

    The estimation of flood is essential for disaster alleviation. Hydrodynamic models are implemented to predict the occurrence and variance of flood in different scales. In practice, the calibration of hydrodynamic models aims to search the best possible parameters for the representation the natural flow resistance. Recent years have seen the calibration of hydrodynamic models being more actual and faster following the advance of earth observation products and computer based optimization techniques. In this study, the Hydrologic Engineering River Analysis System (HEC-Ras) model was set up with high-resolution digital elevation model from Laser scanner for the river Inn in Tyrol, Austria. 10 largest flood events from 19 hourly discharge gauges and flood inundation maps were selected to calibrate the HEC-Ras model. Manning roughness values and lateral inflow factors as parameters were automatically optimized with the Shuffled complex with Principal component analysis (SP-UCI) algorithm developed from the Shuffled Complex Evolution (SCE-UA). Different objective functions (Nash-Sutcliffe model efficiency coefficient, the timing of peak, peak value and Root-mean-square deviation) were used in single or multiple way. It was found that the lateral inflow factor was the most sensitive parameter. SP-UCI algorithm could avoid the local optimal and achieve efficient and effective parameters in the calibration of HEC-Ras model using flood extension images. As results showed, calibration by means of gauged discharge data and flood inundation maps, together with objective function of Nash-Sutcliffe model efficiency coefficient, was very robust to obtain more reliable flood simulation, and also to catch up with the peak value and the timing of peak.

  16. Use of MLCM3 Software for Flash Flood Modeling and Forecasting

    Inna Pivovarova; Daria Sokolova; Artur Batyrov; Vadim Kuzmin; Ngoc Anh Tran; DinhKha Dang; Kirill V. Shemanaev

    2018-01-01

    Accurate and timely flash floods forecasting, especially, in ungauged and poorly gauged basins, is one of the most important and challenging problems to be solved by the international hydrological community. In changing climate and variable anthropogenic impact on river basins, as well as due to low density of surface hydrometeorological network, flash flood forecasting based on “traditional” physically based, or conceptual, or statistical hydrological models often becomes inefficient. Unfort...

  17. Flood damage: a model for consistent, complete and multipurpose scenarios

    S. Menoni

    2016-12-01

    implemented in ex post damage assessments, also with the objective of better programming financial resources that will be needed for these types of events in the future. On the other hand, integrated interpretations of flood events are fundamental to adapting and optimizing flood mitigation strategies on the basis of thorough forensic investigation of each event, as corroborated by the implementation of the model in a case study.

  18. Assessing surface water flood risk and management strategies under future climate change: Insights from an Agent-Based Model.

    Jenkins, K; Surminski, S; Hall, J; Crick, F

    2017-10-01

    Climate change and increasing urbanization are projected to result in an increase in surface water flooding and consequential damages in the future. In this paper, we present insights from a novel Agent Based Model (ABM), applied to a London case study of surface water flood risk, designed to assess the interplay between different adaptation options; how risk reduction could be achieved by homeowners and government; and the role of flood insurance and the new flood insurance pool, Flood Re, in the context of climate change. The analysis highlights that while combined investment in property-level flood protection and sustainable urban drainage systems reduce surface water flood risk, the benefits can be outweighed by continued development in high risk areas and the effects of climate change. In our simulations, Flood Re is beneficial in its function to provide affordable insurance, even under climate change. However, the scheme does face increasing financial pressure due to rising surface water flood damages. If the intended transition to risk-based pricing is to take place then a determined and coordinated strategy will be needed to manage flood risk, which utilises insurance incentives, limits new development, and supports resilience measures. Our modelling approach and findings are highly relevant for the ongoing regulatory and political approval process for Flood Re as well as for wider discussions on the potential of insurance schemes to incentivise flood risk management and climate adaptation in the UK and internationally. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. GIS-based flood risk model evaluated by Fuzzy Analytic Hierarchy Process (FAHP)

    Sukcharoen, Tharapong; Weng, Jingnong; Teetat, Charoenkalunyuta

    2016-10-01

    Over the last 2-3 decades, the economy of many countries around the world has been developed rapidly but it was unbalanced development because of expecting on economic growth only. Meanwhile it lacked of effective planning in the use of natural resources. This can significantly induce climate change which is major cause of natural disaster. Hereby, Thailand has also suffered from natural disaster for ages. Especially, the flood which is most hazardous disaster in Thailand can annually result in the great loss of life and property, environment and economy. Since the flood management of country is inadequate efficiency. It is unable to support the flood analysis comprehensively. This paper applied Geographic Information System and Multi-Criteria Decision Making to create flood risk model at regional scale. Angthong province in Thailand was used as the study area. In practical process, Fuzzy logic technique has been used to improve specialist's assessment by implementing with Fuzzy membership because human decision is flawed under uncertainty then AHP technique was processed orderly. The hierarchy structure in this paper was categorized the spatial flood factors into two levels as following: 6 criteria (Meteorology, Geology, Topography, Hydrology, Human and Flood history) and 8 factors (Average Rainfall, Distance from Stream, Soil drainage capability, Slope, Elevation, Land use, Distance from road and Flooded area in the past). The validity of the pair-wise comparison in AHP was shown as C.R. value which indicated that the specialist judgment was reasonably consistent. FAHP computation result has shown that the first priority of criteria was Meteorology. In addition, the Rainfall was the most influencing factor for flooding. Finally, the output was displayed in thematic map of Angthong province with flood risk level processed by GIS tools. The map was classified into: High Risk, Moderate Risk and Low Risk (13.20%, 75.58%, and 11.22% of total area).

  20. Incorporating institutions and collective action into a sociohydrological model of flood resilience

    Yu, David J.; Sangwan, Nikhil; Sung, Kyungmin; Chen, Xi; Merwade, Venkatesh

    2017-02-01

    Stylized sociohydrological models have mainly used social memory aspects such as community awareness or sensitivity to connect hydrologic change and social response. However, social memory alone does not satisfactorily capture the details of how human behavior is translated into collective action for water resources governance. Nor is it the only social mechanism by which the two-way feedbacks of sociohydrology can be operationalized. This study contributes toward bridging of this gap by developing a sociohydrological model of a flood resilience that includes two additional components: (1) institutions for collective action, and (2) connections to an external economic system. Motivated by the case of community-managed flood protection systems (polders) in coastal Bangladesh, we use the model to understand critical general features that affect long-term resilience of human-flood systems. Our findings suggest that occasional adversity can enhance long-term resilience. Allowing some hydrological variability to enter into the polder can increase its adaptive capacity for resilience through the preservation of social norm for collective action. Further, there are potential trade-offs associated with optimization of flood resistance through structural measures. By reducing sensitivity to floods, the system may become more fragile under the double impact of floods and economic change.

  1. Hydraulic correction method (HCM) to enhance the efficiency of SRTM DEM in flood modeling

    Chen, Huili; Liang, Qiuhua; Liu, Yong; Xie, Shuguang

    2018-04-01

    Digital Elevation Model (DEM) is one of the most important controlling factors determining the simulation accuracy of hydraulic models. However, the currently available global topographic data is confronted with limitations for application in 2-D hydraulic modeling, mainly due to the existence of vegetation bias, random errors and insufficient spatial resolution. A hydraulic correction method (HCM) for the SRTM DEM is proposed in this study to improve modeling accuracy. Firstly, we employ the global vegetation corrected DEM (i.e. Bare-Earth DEM), developed from the SRTM DEM to include both vegetation height and SRTM vegetation signal. Then, a newly released DEM, removing both vegetation bias and random errors (i.e. Multi-Error Removed DEM), is employed to overcome the limitation of height errors. Last, an approach to correct the Multi-Error Removed DEM is presented to account for the insufficiency of spatial resolution, ensuring flow connectivity of the river networks. The approach involves: (a) extracting river networks from the Multi-Error Removed DEM using an automated algorithm in ArcGIS; (b) correcting the location and layout of extracted streams with the aid of Google Earth platform and Remote Sensing imagery; and (c) removing the positive biases of the raised segment in the river networks based on bed slope to generate the hydraulically corrected DEM. The proposed HCM utilizes easily available data and tools to improve the flow connectivity of river networks without manual adjustment. To demonstrate the advantages of HCM, an extreme flood event in Huifa River Basin (China) is simulated on the original DEM, Bare-Earth DEM, Multi-Error removed DEM, and hydraulically corrected DEM using an integrated hydrologic-hydraulic model. A comparative analysis is subsequently performed to assess the simulation accuracy and performance of four different DEMs and favorable results have been obtained on the corrected DEM.

  2. A radar-based hydrological model for flash flood prediction in the dry regions of Israel

    Ronen, Alon; Peleg, Nadav; Morin, Efrat

    2014-05-01

    Flash floods are floods which follow shortly after rainfall events, and are among the most destructive natural disasters that strike people and infrastructures in humid and arid regions alike. Using a hydrological model for the prediction of flash floods in gauged and ungauged basins can help mitigate the risk and damage they cause. The sparsity of rain gauges in arid regions requires the use of radar measurements in order to get reliable quantitative precipitation estimations (QPE). While many hydrological models use radar data, only a handful do so in dry climate. This research presents a robust radar-based hydro-meteorological model built specifically for dry climate. Using this model we examine the governing factors of flash floods in the arid and semi-arid regions of Israel in particular and in dry regions in general. The hydrological model built is a semi-distributed, physically-based model, which represents the main hydrological processes in the area, namely infiltration, flow routing and transmission losses. Three infiltration functions were examined - Initial & Constant, SCS-CN and Green&Ampt. The parameters for each function were found by calibration based on 53 flood events in three catchments, and validation was performed using 55 flood events in six catchments. QPE were obtained from a C-band weather radar and adjusted using a weighted multiple regression method based on a rain gauge network. Antecedent moisture conditions were calculated using a daily recharge assessment model (DREAM). We found that the SCS-CN infiltration function performed better than the other two, with reasonable agreement between calculated and measured peak discharge. Effects of storm characteristics were studied using synthetic storms from a high resolution weather generator (HiReS-WG), and showed a strong correlation between storm speed, storm direction and rain depth over desert soils to flood volume and peak discharge.

  3. Analysis the Accuracy of Digital Elevation Model (DEM) for Flood Modelling on Lowland Area

    Zainol Abidin, Ku Hasna Zainurin Ku; Razi, Mohd Adib Mohammad; Bukari, Saifullizan Mohd

    2018-04-01

    Flood is one type of natural disaster that occurs almost every year in Malaysia. Commonly the lowland areas are the worst affected areas. This kind of disaster is controllable by using an accurate data for proposing any kinds of solutions. Elevation data is one of the data used to produce solutions for flooding. Currently, the research about the application of Digital Elevation Model (DEM) in hydrology was increased where this kind of model will identify the elevation for required areas. University of Tun Hussein Onn Malaysia is one of the lowland areas which facing flood problems on 2006. Therefore, this area was chosen in order to produce DEM which focussed on University Health Centre (PKU) and drainage area around Civil and Environment Faculty (FKAAS). Unmanned Aerial Vehicle used to collect aerial photos data then undergoes a process of generating DEM according to three types of accuracy and quality from Agisoft PhotoScan software. The higher the level of accuracy and quality of DEM produced, the longer time taken to generate a DEM. The reading of the errors created while producing the DEM shows almost 0.01 different. Therefore, it has been identified there are some important parameters which influenced the accuracy of DEM.

  4. BN-FLEMOps pluvial - A probabilistic multi-variable loss estimation model for pluvial floods

    Roezer, V.; Kreibich, H.; Schroeter, K.; Doss-Gollin, J.; Lall, U.; Merz, B.

    2017-12-01

    Pluvial flood events, such as in Copenhagen (Denmark) in 2011, Beijing (China) in 2012 or Houston (USA) in 2016, have caused severe losses to urban dwellings in recent years. These floods are caused by storm events with high rainfall rates well above the design levels of urban drainage systems, which lead to inundation of streets and buildings. A projected increase in frequency and intensity of heavy rainfall events in many areas and an ongoing urbanization may increase pluvial flood losses in the future. For an efficient risk assessment and adaptation to pluvial floods, a quantification of the flood risk is needed. Few loss models have been developed particularly for pluvial floods. These models usually use simple waterlevel- or rainfall-loss functions and come with very high uncertainties. To account for these uncertainties and improve the loss estimation, we present a probabilistic multi-variable loss estimation model for pluvial floods based on empirical data. The model was developed in a two-step process using a machine learning approach and a comprehensive database comprising 783 records of direct building and content damage of private households. The data was gathered through surveys after four different pluvial flood events in Germany between 2005 and 2014. In a first step, linear and non-linear machine learning algorithms, such as tree-based and penalized regression models were used to identify the most important loss influencing factors among a set of 55 candidate variables. These variables comprise hydrological and hydraulic aspects, early warning, precaution, building characteristics and the socio-economic status of the household. In a second step, the most important loss influencing variables were used to derive a probabilistic multi-variable pluvial flood loss estimation model based on Bayesian Networks. Two different networks were tested: a score-based network learned from the data and a network based on expert knowledge. Loss predictions are made

  5. Report 2: Guidance document on practices to model and implement external flooding hazards in extended PSA

    Rebour, V.; Georgescu, G.; Leteinturier, D.; Raimond, E.; La Rovere, S.; Bernadara, P.; Vasseur, D.; Brinkman, H.; Groudev, P.; Ivanov, I.; Turschmann, M.; Sperbeck, S.; Potempski, S.; Hirata, K.; Kumar, Manorma

    2016-01-01

    This report provides a review of existing practices to model and implement external flooding hazards in existing level 1 PSA. The objective is to identify good practices on the modelling of initiating events (internal and external hazards) with a perspective of development of extended PSA and implementation of external events modelling in extended L1 PSA, its limitations/difficulties as far as possible. The views presented in this report are based on the ASAMPSA-E partners' experience and available publications. The report includes discussions on the following issues: - how to structure a L1 PSA for external flooding events, - information needed from geosciences in terms of hazards modelling and to build relevant modelling for PSA, - how to define and model the impact of each flooding event on SSCs with distinction between the flooding protective structures and devices and the effect of protection failures on other SSCs, - how to identify and model the common cause failures in one reactor or between several reactors, - how to apply HRA methodology for external flooding events, - how to credit additional emergency response (post-Fukushima measures like mobile equipment), - how to address the specific issues of L2 PSA, - how to perform and present risk quantification. (authors)

  6. Modeled changes in 100 year Flood Risk and Asset Damages within Mapped Floodplains of the Contiguous United States

    Wobus, C. W.; Gutmann, E. D.; Jones, R.; Rissing, M.; Mizukami, N.; Lorie, M.; Mahoney, H.; Wood, A.; Mills, D.; Martinich, J.

    2017-12-01

    A growing body of recent work suggests that the extreme weather events that drive inland flooding are likely to increase in frequency and magnitude in a warming climate, thus increasing monetary damages from flooding in the future. We use hydrologic projections based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) to estimate changes in the frequency of modeled 1% annual exceedance probability flood events at 57,116 locations across the contiguous United States (CONUS). We link these flood projections to a database of assets within mapped flood hazard zones to model changes in inland flooding damages throughout the CONUS over the remainder of the 21st century, under two greenhouse gas (GHG) emissions scenarios. Our model generates early 21st century flood damages that reasonably approximate the range of historical observations, and trajectories of future damages that vary substantially depending on the GHG emissions pathway. The difference in modeled flood damages between higher and lower emissions pathways approaches $4 billion per year by 2100 (in undiscounted 2014 dollars), suggesting that aggressive GHG emissions reductions could generate significant monetary benefits over the long-term in terms of reduced flood risk. Although the downscaled hydrologic data we used have been applied to flood impacts studies elsewhere, this research expands on earlier work to quantify changes in flood risk by linking future flood exposure to assets and damages at a national scale. Our approach relies on a series of simplifications that could ultimately affect damage estimates (e.g., use of statistical downscaling, reliance on a nationwide hydrologic model, and linking damage estimates only to 1% AEP floods). Although future work is needed to test the sensitivity of our results to these methodological choices, our results suggest that monetary damages from inland flooding could be substantially reduced through more aggressive GHG mitigation policies.

  7. The critical role of the routing scheme in simulating peak river discharge in global hydrological models

    Zhao, F.; Veldkamp, T.; Frieler, K.; Schewe, J.; Ostberg, S.; Willner, S. N.; Schauberger, B.; Gosling, S.; Mueller Schmied, H.; Portmann, F. T.; Leng, G.; Huang, M.; Liu, X.; Tang, Q.; Hanasaki, N.; Biemans, H.; Gerten, D.; Satoh, Y.; Pokhrel, Y. N.; Stacke, T.; Ciais, P.; Chang, J.; Ducharne, A.; Guimberteau, M.; Wada, Y.; Kim, H.; Yamazaki, D.

    2017-12-01

    Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge—which is crucial in flood simulations—has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971-2010) within the ISIMIP2a project. The runoff simulations were used as input for the global river routing model CaMa-Flood. The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about 2/3 of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.

  8. Modeling Flood Plain Hydrology and Forest Productivity of Congaree Swamp, South Carolina

    Doyle, Thomas W.

    2009-01-01

    An ecological field and modeling study was conducted to examine the flood relations of backswamp forests and park trails of the flood plain portion of Congaree National Park, S.C. Continuous water level gages were distributed across the length and width of the flood plain portion - referred to as 'Congaree Swamp' - to facilitate understanding of the lag and peak flood coupling with stage of the Congaree River. A severe and prolonged drought at study start in 2001 extended into late 2002 before backswamp zones circulated floodwaters. Water levels were monitored at 10 gaging stations over a 4-year period from 2002 to 2006. Historical water level stage and discharge data from the Congaree River were digitized from published sources and U.S. Geological Survey (USGS) archives to obtain long-term daily averages for an upstream gage at Columbia, S.C., dating back to 1892. Elevation of ground surface was surveyed for all park trails, water level gages, and additional circuits of roads and boundaries. Rectified elevation data were interpolated into a digital elevation model of the park trail system. Regression models were applied to establish time lags and stage relations between gages at Columbia, S.C., and gages in the upper, middle, and lower reaches of the river and backswamp within the park. Flood relations among backswamp gages exhibited different retention and recession behavior between flood plain reaches with greater hydroperiod in the lower reach than those in the upper and middle reaches of the Congaree Swamp. A flood plain inundation model was developed from gage relations to predict critical river stages and potential inundation of hiking trails on a real-time basis and to forecast the 24-hour flood In addition, tree-ring analysis was used to evaluate the effects of flood events and flooding history on forest resources at Congaree National Park. Tree cores were collected from populations of loblolly pine (Pinus taeda), baldcypress (Taxodium distichum), water

  9. Urban micro-scale flood risk estimation with parsimonious hydraulic modelling and census data

    C. Arrighi

    2013-05-01

    Full Text Available The adoption of 2007/60/EC Directive requires European countries to implement flood hazard and flood risk maps by the end of 2013. Flood risk is the product of flood hazard, vulnerability and exposure, all three to be estimated with comparable level of accuracy. The route to flood risk assessment is consequently much more than hydraulic modelling of inundation, that is hazard mapping. While hazard maps have already been implemented in many countries, quantitative damage and risk maps are still at a preliminary level. A parsimonious quasi-2-D hydraulic model is here adopted, having many advantages in terms of easy set-up. It is here evaluated as being accurate in flood depth estimation in urban areas with a high-resolution and up-to-date Digital Surface Model (DSM. The accuracy, estimated by comparison with marble-plate records of a historic flood in the city of Florence, is characterized in the downtown's most flooded area by a bias of a very few centimetres and a determination coefficient of 0.73. The average risk is found to be about 14 € m−2 yr−1, corresponding to about 8.3% of residents' income. The spatial distribution of estimated risk highlights a complex interaction between the flood pattern and the building characteristics. As a final example application, the estimated risk values have been used to compare different retrofitting measures. Proceeding through the risk estimation steps, a new micro-scale potential damage assessment method is proposed. This is based on the georeferenced census system as the optimal compromise between spatial detail and open availability of socio-economic data. The results of flood risk assessment at the census section scale resolve most of the risk spatial variability, and they can be easily aggregated to whatever upper scale is needed given that they are geographically defined as contiguous polygons. Damage is calculated through stage–damage curves, starting from census data on building type and

  10. Modelling MIZ dynamics in a global model

    Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto

    2016-04-01

    Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.

  11. On global and regional spectral evaluation of global geopotential models

    Ustun, A; Abbak, R A

    2010-01-01

    Spectral evaluation of global geopotential models (GGMs) is necessary to recognize the behaviour of gravity signal and its error recorded in spherical harmonic coefficients and associated standard deviations. Results put forward in this wise explain the whole contribution of gravity data in different kinds that represent various sections of the gravity spectrum. This method is more informative than accuracy assessment methods, which use external data such as GPS-levelling. Comparative spectral evaluation for more than one model can be performed both in global and local sense using many spectral tools. The number of GGMs has grown with the increasing number of data collected by the dedicated satellite gravity missions, CHAMP, GRACE and GOCE. This fact makes it necessary to measure the differences between models and to monitor the improvements in the gravity field recovery. In this paper, some of the satellite-only and combined models are examined in different scales, globally and regionally, in order to observe the advances in the modelling of GGMs and their strengths at various expansion degrees for geodetic and geophysical applications. The validation of the published errors of model coefficients is a part of this evaluation. All spectral tools explicitly reveal the superiority of the GRACE-based models when compared against the models that comprise the conventional satellite tracking data. The disagreement between models is large in local/regional areas if data sets are different, as seen from the example of the Turkish territory

  12. An Observation Task Chain Representation Model for Disaster Process-Oriented Remote Sensing Satellite Sensor Planning: A Flood Water Monitoring Application

    Chao Yang

    2018-03-01

    Full Text Available An accurate and comprehensive representation of an observation task is a prerequisite in disaster monitoring to achieve reliable sensor observation planning. However, the extant disaster event or task information models do not fully satisfy the observation requirements for the accurate and efficient planning of remote-sensing satellite sensors. By considering the modeling requirements for a disaster observation task, we propose an observation task chain (OTChain representation model that includes four basic OTChain segments and eight-tuple observation task metadata description structures. A prototype system, namely OTChainManager, is implemented to provide functions for modeling, managing, querying, and visualizing observation tasks. In the case of flood water monitoring, we use a flood remote-sensing satellite sensor observation task for the experiment. The results show that the proposed OTChain representation model can be used in modeling process-owned flood disaster observation tasks. By querying and visualizing the flood observation task instances in the Jinsha River Basin, the proposed model can effectively express observation task processes, represent personalized observation constraints, and plan global remote-sensing satellite sensor observations. Compared with typical observation task information models or engines, the proposed OTChain representation model satisfies the information demands of the OTChain and its processes as well as impels the development of a long time-series sensor observation scheme.

  13. Flood Modeling Using a Synthesis of Multi-Platform LiDAR Data

    Ryan M. Csontos

    2013-09-01

    Full Text Available This study examined the utility of a high resolution ground-based (mobile and terrestrial Light Detection and Ranging (LiDAR dataset (0.2 m point-spacing supplemented with a coarser resolution airborne LiDAR dataset (5 m point-spacing for use in a flood inundation analysis. The techniques for combining multi-platform LiDAR data into a composite dataset in the form of a triangulated irregular network (TIN are described, and quantitative comparisons were made to a TIN generated solely from the airborne LiDAR dataset. For example, a maximum land surface elevation difference of 1.677 m and a mean difference of 0.178 m were calculated between the datasets based on sample points. Utilizing the composite and airborne LiDAR-derived TINs, a flood inundation comparison was completed using a one-dimensional steady flow hydraulic modeling analysis. Quantitative comparisons of the water surface profiles and depth grids indicated an underestimation of flooding extent, volume, and maximum flood height using the airborne LiDAR data alone. A 35% increase in maximum flood height was observed using the composite LiDAR dataset. In addition, the extents of the water surface profiles generated from the two datasets were found to be statistically significantly different. The urban and mountainous characteristics of the study area as well as the density (file size of the high resolution ground based LiDAR data presented both opportunities and challenges for flood modeling analyses.

  14. Prospects and requirements for an operational modelling unit in flood crisis situations

    Anders Katharina

    2016-01-01

    Full Text Available Dike failure events pose severe flood crisis situations on areas in the hinterland of dikes. In recent decades the importance of being prepared for dike breaches has been increasingly recognized. However, the pre-assessment of inundation resulting from dike breaches is possible only based on scenarios, which might not reflect the situation of a real event. This paper presents a setup and workflow that allows to model dike breachinduced inundation operationally, i.e. when an event is imminent or occurring. A comprehensive system setup of an operational modelling unit has been developed and implemented in the frame of a federal project in Saxony-Anhalt, Germany. The modelling unit setup comprises a powerful methodology of flood modelling and elaborated operational guidelines for crisis situations. Nevertheless, it is of fundamental importance that the modelling unit is instated prior to flood events as a permanent system. Moreover the unit needs to be fully integrated in flood crisis management. If these crucial requirements are met, a modelling unit is capable of fundamentally supporting flood management with operational prognoses of adequate quality even in the limited timeframe of crisis situations.

  15. Modeling multi-source flooding disaster and developing simulation framework in Delta

    Liu, Y.; Cui, X.; Zhang, W.

    2016-12-01

    Most Delta regions of the world are densely populated and with advanced economies. However, due to impact of the multi-source flooding (upstream flood, rainstorm waterlogging, storm surge flood), the Delta regions is very vulnerable. The academic circles attach great importance to the multi-source flooding disaster in these areas. The Pearl River Delta urban agglomeration in south China is selected as the research area. Based on analysis of natural and environmental characteristics data of the Delta urban agglomeration(remote sensing data, land use data, topographic map, etc.), hydrological monitoring data, research of the uneven distribution and process of regional rainfall, the relationship between the underlying surface and the parameters of runoff, effect of flood storage pattern, we use an automatic or semi-automatic method for dividing spatial units to reflect the runoff characteristics in urban agglomeration, and develop an Multi-model Ensemble System in changing environment, including urban hydrologic model, parallel computational 1D&2D hydrodynamic model, storm surge forecast model and other professional models, the system will have the abilities like real-time setting a variety of boundary conditions, fast and real-time calculation, dynamic presentation of results, powerful statistical analysis function. The model could be optimized and improved by a variety of verification methods. This work was supported by the National Natural Science Foundation of China (41471427); Special Basic Research Key Fund for Central Public Scientific Research Institutes.

  16. Multi-model ensembles for assessment of flood losses and associated uncertainty

    Figueiredo, Rui; Schröter, Kai; Weiss-Motz, Alexander; Martina, Mario L. V.; Kreibich, Heidi

    2018-05-01

    Flood loss modelling is a crucial part of risk assessments. However, it is subject to large uncertainty that is often neglected. Most models available in the literature are deterministic, providing only single point estimates of flood loss, and large disparities tend to exist among them. Adopting any one such model in a risk assessment context is likely to lead to inaccurate loss estimates and sub-optimal decision-making. In this paper, we propose the use of multi-model ensembles to address these issues. This approach, which has been applied successfully in other scientific fields, is based on the combination of different model outputs with the aim of improving the skill and usefulness of predictions. We first propose a model rating framework to support ensemble construction, based on a probability tree of model properties, which establishes relative degrees of belief between candidate models. Using 20 flood loss models in two test cases, we then construct numerous multi-model ensembles, based both on the rating framework and on a stochastic method, differing in terms of participating members, ensemble size and model weights. We evaluate the performance of ensemble means, as well as their probabilistic skill and reliability. Our results demonstrate that well-designed multi-model ensembles represent a pragmatic approach to consistently obtain more accurate flood loss estimates and reliable probability distributions of model uncertainty.

  17. Development of a hydraulic model and flood-inundation maps for the Wabash River near the Interstate 64 Bridge near Grayville, Illinois

    Boldt, Justin A.

    2018-01-16

    A two-dimensional hydraulic model and digital flood‑inundation maps were developed for a 30-mile reach of the Wabash River near the Interstate 64 Bridge near Grayville, Illinois. The flood-inundation maps, which can be accessed through the U.S. Geological Survey (USGS) Flood Inundation Mapping Science web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Wabash River at Mount Carmel, Ill (USGS station number 03377500). Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS AHPS site MCRI2). The NWS AHPS forecasts peak stage information that may be used with the maps developed in this study to show predicted areas of flood inundation.Flood elevations were computed for the Wabash River reach by means of a two-dimensional, finite-volume numerical modeling application for river hydraulics. The hydraulic model was calibrated by using global positioning system measurements of water-surface elevation and the current stage-discharge relation at both USGS streamgage 03377500, Wabash River at Mount Carmel, Ill., and USGS streamgage 03378500, Wabash River at New Harmony, Indiana. The calibrated hydraulic model was then used to compute 27 water-surface elevations for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from less than the action stage (9 ft) to the highest stage (35 ft) of the current stage-discharge rating curve. The simulated water‑surface elevations were then combined with a geographic information system digital elevation model, derived from light detection and ranging data, to delineate the area flooded at each water

  18. Evolutionary modelling of the macro-economic impacts of catastrophic flood events

    Safarzynska, K.E.; Brouwer, R.; Hofkes, M.

    2013-01-01

    This paper examines the possible contribution of evolutionary economics to macro-economic modelling of flood impacts to provide guidance for future economic risk modelling. Most macro-economic models start from a neoclassical economic perspective and focus on equilibrium outcomes, either in a static

  19. Combining empirical approaches and error modelling to enhance predictive uncertainty estimation in extrapolation for operational flood forecasting. Tests on flood events on the Loire basin, France.

    Berthet, Lionel; Marty, Renaud; Bourgin, François; Viatgé, Julie; Piotte, Olivier; Perrin, Charles

    2017-04-01

    An increasing number of operational flood forecasting centres assess the predictive uncertainty associated with their forecasts and communicate it to the end users. This information can match the end-users needs (i.e. prove to be useful for an efficient crisis management) only if it is reliable: reliability is therefore a key quality for operational flood forecasts. In 2015, the French flood forecasting national and regional services (Vigicrues network; www.vigicrues.gouv.fr) implemented a framework to compute quantitative discharge and water level forecasts and to assess the predictive uncertainty. Among the possible technical options to achieve this goal, a statistical analysis of past forecasting errors of deterministic models has been selected (QUOIQUE method, Bourgin, 2014). It is a data-based and non-parametric approach based on as few assumptions as possible about the forecasting error mathematical structure. In particular, a very simple assumption is made regarding the predictive uncertainty distributions for large events outside the range of the calibration data: the multiplicative error distribution is assumed to be constant, whatever the magnitude of the flood. Indeed, the predictive distributions may not be reliable in extrapolation. However, estimating the predictive uncertainty for these rare events is crucial when major floods are of concern. In order to improve the forecasts reliability for major floods, an attempt at combining the operational strength of the empirical statistical analysis and a simple error modelling is done. Since the heteroscedasticity of forecast errors can considerably weaken the predictive reliability for large floods, this error modelling is based on the log-sinh transformation which proved to reduce significantly the heteroscedasticity of the transformed error in a simulation context, even for flood peaks (Wang et al., 2012). Exploratory tests on some operational forecasts issued during the recent floods experienced in

  20. Hydraulic description of a flood event with optical remote sensors: a constructive constraint on modelling uncertainties

    Battiston, Stéphanie; Allenbach, Bernard

    2010-05-01

    compartments; high resolution optical imagery allow the exhaustive inventory of breaches and overflows; turbidity variations and draw-off give information on stream directions. These facts are of primary interest to help in deriving a firm understanding of the flooding processes, but also comprise a powerful source for the necessary parameterization and/or calibration of hydraulic models. Thus the accuracy of flood extents derived from remote sensing data could, on the one hand, be valuable inputs to historical flood info-bases within overall risk-linked databases, and on the other hand, test the validity of hydrological modelling, while helping to lift equifinality uncertainties. These first investigations highlight that space imagery of events constitutes an unrivalled tool for flood disaster observation. This 2D record is complementary to all field measurements and the integration of "space derived flood products" is valuable for all stages of risk management. This potential of EO optical sensors for flood monitoring is also confirmed in a detailed analysis making a qualitative and quantitative evaluation of the results, confronting ten optical and radar remote sensing platforms with field observations.

  1. Spherical Process Models for Global Spatial Statistics

    Jeong, Jaehong; Jun, Mikyoung; Genton, Marc G.

    2017-01-01

    Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture

  2. Integrating Global Open Geo-Information for Major Disaster Assessment: A Case Study of the Myanmar Flood

    Suju Li

    2017-07-01

    Full Text Available Major disasters typically impact large areas, cause considerable damages, and result in significant human and economic losses. The timely and accurate estimation of impacts and damages is essential to better understand disaster conditions and to support emergency response operations. Geo-information drawn from various sources at multi spatial-temporal scales can be used for disaster assessments through a synthesis of hazard, exposure, and post disaster information based on pertinent approaches. Along with the increased availability of open sourced data and cooperation initiatives, more global scale geo-information, including global land cover datasets, has been produced and can be integrated with other information for disaster dynamic damage assessment (e.g., impact estimation immediately after a disaster occurs, physical damage assessment during the emergency response stage, and comprehensive assessment following an emergency response. Residential areas and arable lands affected by the flood disaster occurring from July to August 2015 in Myanmar were assessed based on satellite images, GlobeLand30 data, and other global open sourced information as a study case. The results show that integrating global open geo-information could serve as a practical and efficient means of assessing damage resulting from major disasters worldwide, especially at the early emergency response stage.

  3. Agent based models for testing city evacuation strategies under a flood event as strategy to reduce flood risk

    Medina, Neiler; Sanchez, Arlex; Nokolic, Igor; Vojinovic, Zoran

    2016-04-01

    This research explores the uses of Agent Based Models (ABM) and its potential to test large scale evacuation strategies in coastal cities at risk from flood events due to extreme hydro-meteorological events with the final purpose of disaster risk reduction by decreasing human's exposure to the hazard. The first part of the paper corresponds to the theory used to build the models such as: Complex adaptive systems (CAS) and the principles and uses of ABM in this field. The first section outlines the pros and cons of using AMB to test city evacuation strategies at medium and large scale. The second part of the paper focuses on the central theory used to build the ABM, specifically the psychological and behavioral model as well as the framework used in this research, specifically the PECS reference model is cover in this section. The last part of this section covers the main attributes or characteristics of human beings used to described the agents. The third part of the paper shows the methodology used to build and implement the ABM model using Repast-Symphony as an open source agent-based modelling and simulation platform. The preliminary results for the first implementation in a region of the island of Sint-Maarten a Dutch Caribbean island are presented and discussed in the fourth section of paper. The results obtained so far, are promising for a further development of the model and its implementation and testing in a full scale city

  4. Model of Ciliwung River Flood Diversion Tunnel Using HEC-RAS Software

    Nugroho Joko

    2018-01-01

    Full Text Available As a coastal city which lies in lowland area, Jakarta is prone to flooding. One major river which flow through Jakarta is Ciliwung River. There are alternatives to reduce flood risk, such as: river capacity improvement, existing natural reservoir and polder system improvement, upstream reservoir construction, city drainage improvement, flood channel construction and flood diversion. This paper presents capacity analysis of a proposed flood diversion of Ciliwung River to Cipinang River. Cipinang River has its downstream end at Eastern Flood Canal (Kanal Banjir Timur, KBT. This diversion is based on the available capacity of KBT. A 1-D numerical hydraulic model using HEC-RAS based on a proposed design is used to assess the performance of the diversion system in any combination of upstream and downstream boundary condition. Simulations were done for steady condition. The results show that capacity of the system can be achieved for certain condition at upstream and downstream boundary. The effects at the downstream reach of Ciliwung and Cipinang River due to the diversion are also obtained.

  5. Economic impacts of climate change. Flooding and salinity in scenarios, models and cases

    Jonkhoff, W.; Koops, O.; Van der Krogt, R.; Oude Essink, G.; Rietveld, E.

    2008-07-01

    In this report, climatic and economic scenarios are combined and future risks are calculated for the consequences of climate change, such as a rising sea level, flooding, extreme draughts and salinity. The calculation of these economic effects of climate change are based on climate scenarios of the KNMI (Royal Dutch Meteorological Institute), TNO's RAEM model (Spatial General Economic Model), the high tide information system of the Dutch Ministry of Waterways and Public Works and the Space scanner of the Environmental Assessment Agency. Next to information on scenarios and models, this report also addresses damage calculations of flooding near Lopik and Ter Heide. The report ends with policy recommendations for adaptation policy. [mk] [nl

  6. Probabilistic common cause failure modeling for auxiliary feedwater system after the introduction of flood barriers

    Zheng, Xiaoyu; Yamaguchi, Akira; Takata, Takashi

    2013-01-01

    Causal inference is capable of assessing common cause failure (CCF) events from the viewpoint of causes' risk significance. Authors proposed the alpha decomposition method for probabilistic CCF analysis, in which the classical alpha factor model and causal inference are integrated to conduct a quantitative assessment of causes' CCF risk significance. The alpha decomposition method includes a hybrid Bayesian network for revealing the relationship between component failures and potential causes, and a regression model in which CCF parameters (global alpha factors) are expressed by explanatory variables (causes' occurrence frequencies) and parameters (decomposed alpha factors). This article applies this method and associated databases needed to predict CCF parameters of auxiliary feedwater (AFW) system when defense barriers against internal flood are introduced. There is scarce operation data for functionally modified safety systems and the utilization of generic CCF databases is of unknown uncertainty. The alpha decomposition method has the potential of analyzing the CCF risk of modified AFW system reasonably based on generic CCF databases. Moreover, the sources of uncertainty in parameter estimation can be studied. An example is presented to demonstrate the process of applying Bayesian inference in the alpha decomposition process. The results show that the system-specific posterior distributions for CCF parameters can be predicted. (author)

  7. Regional models for distributed flash-flood nowcasting: towards an estimation of potential impacts and damages

    Le Bihan Guillaume

    2016-01-01

    Full Text Available Flash floods monitoring systems developed up to now generally enable a real-time assessment of the potential flash-floods magnitudes based on highly distributed hydrological models and weather radar records. The approach presented here aims to go one step ahead by offering a direct assessment of the potential impacts of flash floods on inhabited areas. This approach is based on an a priori analysis of the considered area in order (1 to evaluate based on a semi-automatic hydraulic approach (Cartino method the potentially flooded areas for different discharge levels, and (2 to identify the associated buildings and/or population at risk based on geographic databases. This preliminary analysis enables to build a simplified impact model (discharge-impact curve for each river reach, which can be used to directly estimate the importance of potentially affected assets based on the outputs of a distributed rainfall-runoff model. This article presents a first case study conducted in the Gard region (south eastern France. The first validation results are presented in terms of (1 accuracy of the delineation of the flooded areas estimated based on the Cartino method and using a high resolution DTM, and (2 relevance and usefulness of the impact model obtained. The impacts estimated at the event scale will now be evaluated in a near future based on insurance claim data provided by CCR (Caisse Centrale de Réassurrance.

  8. Adaptive methods for flood forecasting using linear regression models in the upper basin of Senegal River

    Sambou, Soussou

    2004-01-01

    In flood forecasting modelling, large basins are often considered as hydrological systems with multiple inputs and one output. Inputs are hydrological variables such rainfall, runoff and physical characteristics of basin; output is runoff. Relating inputs to output can be achieved using deterministic, conceptual, or stochastic models. Rainfall runoff models generally lack of accuracy. Physical hydrological processes based models, either deterministic or conceptual are highly data requirement demanding and by the way very complex. Stochastic multiple input-output models, using only historical chronicles of hydrological variables particularly runoff are by the way very popular among the hydrologists for large river basin flood forecasting. Application is made on the Senegal River upstream of Bakel, where the River is formed by the main branch, Bafing, and two tributaries, Bakoye and Faleme; Bafing being regulated by Manantaly Dam. A three inputs and one output model has been used for flood forecasting on Bakel. Influence of the lead forecasting, and of the three inputs taken separately, then associated two by two, and altogether has been verified using a dimensionless variance as criterion of quality. Inadequacies occur generally between model output and observations; to put model in better compliance with current observations, we have compared four parameter updating procedure, recursive least squares, Kalman filtering, stochastic gradient method, iterative method, and an AR errors forecasting model. A combination of these model updating have been used in real time flood forecasting.(Author)

  9. Hurricanes Harvey and Irma - High-Resolution Flood Mapping and Monitoring from Sentinel SAR with the Depolarization Reduction Algorithm for Global Observations of InundatioN (DRAGON)

    Nghiem, S. V.; Brakenridge, G. R.; Nguyen, D. T.

    2017-12-01

    Hurricane Harvey inflicted historical catastrophic flooding across extensive regions around Houston and southeast Texas after making landfall on 25 August 2017. The Federal Emergency Management Agency (FEMA) requested urgent supports for flood mapping and monitoring in an emergency response to the extreme flood situation. An innovative satellite remote sensing method, called the Depolarization Reduction Algorithm for Global Observations of inundatioN (DRAGON), has been developed and implemented for use with Sentinel synthetic aperture radar (SAR) satellite data at a resolution of 10 meters to identify, map, and monitor inundation including pre-existing water bodies and newly flooded areas. Results from this new method are hydrologically consistent and have been verified with known surface waters (e.g., coastal ocean, rivers, lakes, reservoirs, etc.), with clear-sky high-resolution WorldView images (where waves can be seen on surface water in inundated areas within a small spatial coverage), and with other flood maps from the consortium of Global Flood Partnership derived from multiple satellite datasets (including clear-sky Landsat and MODIS at lower resolutions). Figure 1 is a high-resolution (4K UHD) image of a composite inundation map for the region around Rosharon (in Brazoria County, south of Houston, Texas). This composite inundation map reveals extensive flooding on 29 August 2017 (four days after Hurricane Harvey made landfall), and the inundation was still persistent in most of the west and south of Rosharon one week later (5 September 2017) while flooding was reduced in the east of Rosharon. Hurricane Irma brought flooding to a number of areas in Florida. As of 10 September 2017, Sentinel SAR flood maps reveal inundation in the Florida Panhandle and over lowland surfaces on several islands in the Florida Keys. However, Sentinel SAR results indicate that flooding along the Florida coast was not extreme despite Irma was a Category-5 hurricane that might

  10. Flash Flood Prediction by Coupling KINEROS2 and HEC-RAS Models for Tropical Regions of Northern Vietnam

    Hong Quang Nguyen

    2015-11-01

    Full Text Available Northern Vietnam is a region prone to heavy flash flooding events. These often have devastating effects on the environment, cause economic damage and, in the worst case scenario, cost human lives. As their frequency and severity are likely to increase in the future, procedures have to be established to cope with this threat. As the prediction of potential flash floods represents one crucial element in this circumstance, we will present an approach that combines the two models KINEROS2 and HEC-RAS in order to accurately predict their occurrence. We used a documented event on 23 June 2011 in the Nam Khat and the larger adjacent Nam Kim watershed to calibrate the coupled model approach. Afterward, we evaluated the performance of the coupled models in predicting flow velocity (FV, water levels (WL, discharge (Q and streamflow power (P during the 3–5 days following the event, using two different precipitation datasets from the global spectral model (GSM and the high resolution model (HRM. Our results show that the estimated Q and WL closely matched observed data with a Nash–Sutcliffe simulation efficiency coefficient (NSE of around 0.93 and a coefficient of determination (R2 at above 0.96. The resulting analyses reveal strong relationships between river geometry and FV, WL and P. Although there were some minor errors in forecast results, the model-predicted Q and WL corresponded well to the gauged data.

  11. Development of river flood model in lower reach of urbanized river basin

    Yoshimura, Kouhei; Tajima, Yoshimitsu; Sanuki, Hiroshi; Shibuo, Yoshihiro; Sato, Shinji; Lee, SungAe; Furumai, Hiroaki; Koike, Toshio

    2014-05-01

    Japan, with its natural mountainous landscape, has demographic feature that population is concentrated in lower reach of elevation close to the coast, and therefore flood damage with large socio-economic value tends to occur in low-lying region. Modeling of river flood in such low-lying urbanized river basin is complex due to the following reasons. In upstream it has been experienced urbanization, which changed land covers from natural forest or agricultural fields to residential or industrial area. Hence rate of infiltration and runoff are quite different from natural hydrological settings. In downstream, paved covers and construct of sewerage system in urbanized areas affect direct discharges and it enhances higher and faster flood peak arrival. Also tidal effect from river mouth strongly affects water levels in rivers, which must be taken into account. We develop an integrated river flood model in lower reach of urbanized areas to be able to address above described complex feature, by integrating model components: LSM coupled distributed hydrological model that models anthropogenic influence on river discharges to downstream; urban hydrological model that simulates run off response in urbanized areas; Saint Venant's equation approximated river model that integrates upstream and urban hydrological models with considering tidal effect from downstream. These features are integrated in a common modeling framework so that model interaction can be directly performed. The model is applied to the Tsurumi river basin, urbanized low-lying river basin in Yokohama and model results show that it can simulate water levels in rivers with acceptable model errors. Furthermore the model is able to install miscellaneous water planning constructs, such as runoff reduction pond in urbanized area, flood control field along the river channel, levee, etc. This can be a useful tool to investigate cost performance of hypothetical water management plan against impact of climate change in

  12. Global model structures for ∗-modules

    Böhme, Benjamin

    2018-01-01

    We extend Schwede's work on the unstable global homotopy theory of orthogonal spaces and L-spaces to the category of ∗-modules (i.e., unstable S-modules). We prove a theorem which transports model structures and their properties from L-spaces to ∗-modules and show that the resulting global model...... structure for ∗-modules is monoidally Quillen equivalent to that of orthogonal spaces. As a consequence, there are induced Quillen equivalences between the associated model categories of monoids, which identify equivalent models for the global homotopy theory of A∞-spaces....

  13. A study of Water flooding modeling for DMFC at cathode channel

    Dong, Sang Keun; Yoo, Ki Soo; Lee, Dae Keun; Chung, Myung Kyoon

    2007-01-01

    The present paper addresses the water flooding model validation in cathode channel for DMFC. Water flooding not only reduces DMFC stack performance but also causes O 2 starve that damages membrane at cathode channel. Although the water flooding problem is critical in operating DMFC, it has not been resolved yet since the effect of temperature, H 2 O vapor and liquid partial pressure effects on the H 2 O vapor saturation is very complex. Therefore, the operating feasible range in the dynamic control of DMFC is inevitably narrow. In order to be able to dynamically control the DMFC to prevent water flooding problem at cathode channel, 3D numerical model was validated by comparison with experimental result. We performed numerical simulation for a wide range of Vcell - current density for 1 layer-1 cell DMFC and the results were compared with experimental data. It was found that the 3D simulation model for the DMFC can be used to accurately predict the water flooding at cathode channel

  14. Simplification of one-dimensional hydraulic networks by automated processes evaluated on 1D/2D deterministic flood models

    Davidsen, Steffen; Löwe, Roland; Thrysøe, Cecilie

    2017-01-01

    Evaluation of pluvial flood risk is often based on computations using 1D/2D urban flood models. However, guidelines on choice of model complexity are missing, especially for one-dimensional (1D) network models. This study presents a new automatic approach for simplification of 1D hydraulic networ...

  15. Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique

    Daniel Maposa

    2016-05-01

    Full Text Available In this article we fit a time-dependent generalised extreme value (GEV distribution to annual maximum flood heights at three sites: Chokwe, Sicacate and Combomune in the lower Limpopo River basin of Mozambique. A GEV distribution is fitted to six annual maximum time series models at each site, namely: annual daily maximum (AM1, annual 2-day maximum (AM2, annual 5-day maximum (AM5, annual 7-day maximum (AM7, annual 10-day maximum (AM10 and annual 30-day maximum (AM30. Non-stationary time-dependent GEV models with a linear trend in location and scale parameters are considered in this study. The results show lack of sufficient evidence to indicate a linear trend in the location parameter at all three sites. On the other hand, the findings in this study reveal strong evidence of the existence of a linear trend in the scale parameter at Combomune and Sicacate, whilst the scale parameter had no significant linear trend at Chokwe. Further investigation in this study also reveals that the location parameter at Sicacate can be modelled by a nonlinear quadratic trend; however, the complexity of the overall model is not worthwhile in fit over a time-homogeneous model. This study shows the importance of extending the time-homogeneous GEV model to incorporate climate change factors such as trend in the lower Limpopo River basin, particularly in this era of global warming and a changing climate. Keywords: nonstationary extremes; annual maxima; lower Limpopo River; generalised extreme value

  16. Geophysical Global Modeling for Extreme Crop Production Using Photosynthesis Models Coupled to Ocean SST Dipoles

    Kaneko, D.

    2016-12-01

    Climate change appears to have manifested itself along with abnormal meteorological disasters. Instability caused by drought and flood disasters is producing poor harvests because of poor photosynthesis and pollination. Fluctuations of extreme phenomena are increasing rapidly because amplitudes of change are much greater than average trends. A fundamental cause of these phenomena derives from increased stored energy inside ocean waters. Geophysical and biochemical modeling of crop production can elucidate complex mechanisms under seasonal climate anomalies. The models have progressed through their combination with global climate reanalysis, environmental satellite data, and harvest data on the ground. This study examined adaptation of crop production to advancing abnormal phenomena related to global climate change. Global environmental surface conditions, i.e., vegetation, surface air temperature, and sea surface temperature observed by satellites, enable global modeling of crop production and monitoring. Basic streams of the concepts of modeling rely upon continental energy flow and carbon circulation among crop vegetation, land surface atmosphere combining energy advection from ocean surface anomalies. Global environmental surface conditions, e.g., vegetation, surface air temperature, and sea surface temperature observed by satellites, enable global modeling of crop production and monitoring. The method of validating the modeling relies upon carbon partitioning in biomass and grains through carbon flow by photosynthesis using carbon dioxide unit in photosynthesis. Results of computations done for this study show global distributions of actual evaporation, stomata opening, and photosynthesis, presenting mechanisms related to advection effects from SST anomalies in the Pacific, Atlantic, and Indian oceans on global and continental croplands. For North America, climate effects appear clearly in severe atmospheric phenomena, which have caused drought and forest fires

  17. Initial assessment of a multi-model approach to spring flood forecasting in Sweden

    Olsson, J.; Uvo, C. B.; Foster, K.; Yang, W.

    2015-06-01

    Hydropower is a major energy source in Sweden and proper reservoir management prior to the spring flood onset is crucial for optimal production. This requires useful forecasts of the accumulated discharge in the spring flood period (i.e. the spring-flood volume, SFV). Today's SFV forecasts are generated using a model-based climatological ensemble approach, where time series of precipitation and temperature from historical years are used to force a calibrated and initialised set-up of the HBV model. In this study, a number of new approaches to spring flood forecasting, that reflect the latest developments with respect to analysis and modelling on seasonal time scales, are presented and evaluated. Three main approaches, represented by specific methods, are evaluated in SFV hindcasts for three main Swedish rivers over a 10-year period with lead times between 0 and 4 months. In the first approach, historically analogue years with respect to the climate in the period preceding the spring flood are identified and used to compose a reduced ensemble. In the second, seasonal meteorological ensemble forecasts are used to drive the HBV model over the spring flood period. In the third approach, statistical relationships between SFV and the large-sale atmospheric circulation are used to build forecast models. None of the new approaches consistently outperform the climatological ensemble approach, but for specific locations and lead times improvements of 20-30 % are found. When combining all forecasts in a weighted multi-model approach, a mean improvement over all locations and lead times of nearly 10 % was indicated. This demonstrates the potential of the approach and further development and optimisation into an operational system is ongoing.

  18. The influence of digital elevation model resolution on overland flow networks for modelling urban pluvial flooding.

    Leitão, J P; Boonya-Aroonnet, S; Prodanović, D; Maksimović, C

    2009-01-01

    This paper presents the developments towards the next generation of overland flow modelling of urban pluvial flooding. Using a detailed analysis of the Digital Elevation Model (DEM) the developed GIS tools can automatically generate surface drainage networks which consist of temporary ponds (floodable areas) and flow paths and link them with the underground network through inlets. For different commercially-available Rainfall-Runoff simulation models, the tool will generate the overland flow network needed to model the surface runoff and pluvial flooding accurately. In this paper the emphasis is placed on a sensitivity analysis of ponds and preferential overland flow paths creation. Different DEMs for three areas were considered in order to compare the results obtained. The DEMs considered were generated using different acquisition techniques and hence represent terrain with varying levels of resolution and accuracy. The results show that DEMs can be used to generate surface flow networks reliably. As expected, the quality of the surface network generated is highly dependent on the quality and resolution of the DEMs and successful representation of buildings and streets.

  19. A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments

    H. Roux

    2011-09-01

    Full Text Available A spatially distributed hydrological model, dedicated to flood simulation, is developed on the basis of physical process representation (infiltration, overland flow, channel routing. Estimation of model parameters requires data concerning topography, soil properties, vegetation and land use. Four parameters are calibrated for the entire catchment using one flood event. Model sensitivity to individual parameters is assessed using Monte-Carlo simulations. Results of this sensitivity analysis with a criterion based on the Nash efficiency coefficient and the error of peak time and runoff are used to calibrate the model. This procedure is tested on the Gardon d'Anduze catchment, located in the Mediterranean zone of southern France. A first validation is conducted using three flood events with different hydrometeorological characteristics. This sensitivity analysis along with validation tests illustrates the predictive capability of the model and points out the possible improvements on the model's structure and parameterization for flash flood forecasting, especially in ungauged basins. Concerning the model structure, results show that water transfer through the subsurface zone also contributes to the hydrograph response to an extreme event, especially during the recession period. Maps of soil saturation emphasize the impact of rainfall and soil properties variability on these dynamics. Adding a subsurface flow component in the simulation also greatly impacts the spatial distribution of soil saturation and shows the importance of the drainage network. Measures of such distributed variables would help discriminating between different possible model structures.

  20. Nitrogen dynamics in flooded soil systems: An overview on concepts and performance of models

    Khairudin, Nurul; Gaydon, Donald S.; Jing, Qi; Zakaria, Mohamad P.; Struik, Paul C.; Keesman, Karel J.

    2018-01-01

    Extensive modelling studies on nitrogen (N) dynamics in flooded soil systems have been published. Consequently, many N dynamics models are available for users to select from. With the current research trend, inclined towards multi-disciplinary research, and with substantial progress in understanding

  1. Flood vulnerability assessment of residential buildings by explicit damage process modelling

    Custer, Rocco; Nishijima, Kazuyoshi

    2015-01-01

    The present paper introduces a vulnerability modelling approach for residential buildings in flood. The modelling approach explicitly considers relevant damage processes, i.e. water infiltration into the building, mechanical failure of components in the building envelope and damage from water...

  2. Boosting flood warning schemes with fast emulator of detailed hydrodynamic models

    Bellos, V.; Carbajal, J. P.; Leitao, J. P.

    2017-12-01

    Floods are among the most destructive catastrophic events and their frequency has incremented over the last decades. To reduce flood impact and risks, flood warning schemes are installed in flood prone areas. Frequently, these schemes are based on numerical models which quickly provide predictions of water levels and other relevant observables. However, the high complexity of flood wave propagation in the real world and the need of accurate predictions in urban environments or in floodplains hinders the use of detailed simulators. This sets the difficulty, we need fast predictions that meet the accuracy requirements. Most physics based detailed simulators although accurate, will not fulfill the speed demand. Even if High Performance Computing techniques are used (the magnitude of required simulation time is minutes/hours). As a consequence, most flood warning schemes are based in coarse ad-hoc approximations that cannot take advantage a detailed hydrodynamic simulation. In this work, we present a methodology for developing a flood warning scheme using an Gaussian Processes based emulator of a detailed hydrodynamic model. The methodology consists of two main stages: 1) offline stage to build the emulator; 2) online stage using the emulator to predict and generate warnings. The offline stage consists of the following steps: a) definition of the critical sites of the area under study, and the specification of the observables to predict at those sites, e.g. water depth, flow velocity, etc.; b) generation of a detailed simulation dataset to train the emulator; c) calibration of the required parameters (if measurements are available). The online stage is carried on using the emulator to predict the relevant observables quickly, and the detailed simulator is used in parallel to verify key predictions of the emulator. The speed gain given by the emulator allows also to quantify uncertainty in predictions using ensemble methods. The above methodology is applied in real

  3. Flood Zoning Simulation by HEC-RAS Model (Case Study: Johor River-Kota Tinggi Region)

    ShahiriParsa, Ahmad; Heydari, Mohammad; Sadeghian, Mohammad Sadegh; Moharrampour, Mahdi

    2015-01-01

    Flooding of rivers has caused many human and financial losses. Hence, studies and research on the nature of the river is inevitable.However, the behavior of rivers hasmany complexities and in this respect, computer models are efficient tools in order to study and simulate the behavior of rivers with the least possible cost. In this paper, one-dimensional model HEC-RAS was used to simulate the flood zoning in the Kota Tinggi district in Johor state. Implementation processes of the zoning on ca...

  4. An Approach to Flooding Inundation Combining the Streamflow Prediction Tool (SPT) and Downscaled Soil Moisture

    Cotterman, K. A.; Follum, M. L.; Pradhan, N. R.; Niemann, J. D.

    2017-12-01

    Flooding impacts numerous aspects of society, from localized flash floods to continental-scale flood events. Many numerical flood models focus solely on riverine flooding, with some capable of capturing both localized and continental-scale flood events. However, these models neglect flooding away from channels that are related to excessive ponding, typically found in areas with flat terrain and poorly draining soils. In order to obtain a holistic view of flooding, we combine flood results from the Streamflow Prediction Tool (SPT), a riverine flood model, with soil moisture downscaling techniques to determine if a better representation of flooding is obtained. This allows for a more holistic understanding of potential flood prone areas, increasing the opportunity for more accurate warnings and evacuations during flooding conditions. Thirty-five years of near-global historical streamflow is reconstructed with continental-scale flow routing of runoff from global land surface models. Elevation data was also obtained worldwide, to establish a relationship between topographic attributes and soil moisture patterns. Derived soil moisture data is validated against observed soil moisture, increasing confidence in the ability to accurately capture soil moisture patterns. Potential flooding situations can be examined worldwide, with this study focusing on the United States, Central America, and the Philippines.

  5. Flood Catastrophe Model for Designing Optimal Flood Insurance Program : Estimating Location-Specific Premiums in the Netherlands

    Ermolieva, T.; Filatova, Tatiana; Ermoliev, Y.; Obersteiner, M.; de Bruijn, K.M.; Jeuken, A.

    2017-01-01

    As flood risks grow worldwide, a well-designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article

  6. Flood Foresight: A near-real time flood monitoring and forecasting tool for rapid and predictive flood impact assessment

    Revilla-Romero, Beatriz; Shelton, Kay; Wood, Elizabeth; Berry, Robert; Bevington, John; Hankin, Barry; Lewis, Gavin; Gubbin, Andrew; Griffiths, Samuel; Barnard, Paul; Pinnell, Marc; Huyck, Charles

    2017-04-01

    The hours and days immediately after a major flood event are often chaotic and confusing, with first responders rushing to mobilise emergency responders, provide alleviation assistance and assess loss to assets of interest (e.g., population, buildings or utilities). Preparations in advance of a forthcoming event are becoming increasingly important; early warning systems have been demonstrated to be useful tools for decision markers. The extent of damage, human casualties and economic loss estimates can vary greatly during an event, and the timely availability of an accurate flood extent allows emergency response and resources to be optimised, reduces impacts, and helps prioritise recovery. In the insurance sector, for example, insurers are under pressure to respond in a proactive manner to claims rather than waiting for policyholders to report losses. Even though there is a great demand for flood inundation extents and severity information in different sectors, generating flood footprints for large areas from hydraulic models in real time remains a challenge. While such footprints can be produced in real time using remote sensing, weather conditions and sensor availability limit their ability to capture every single flood event across the globe. In this session, we will present Flood Foresight (www.floodforesight.com), an operational tool developed to meet the universal requirement for rapid geographic information, before, during and after major riverine flood events. The tool provides spatial data with which users can measure their current or predicted impact from an event - at building, basin, national or continental scales. Within Flood Foresight, the Screening component uses global rainfall predictions to provide a regional- to continental-scale view of heavy rainfall events up to a week in advance, alerting the user to potentially hazardous situations relevant to them. The Forecasting component enhances the predictive suite of tools by providing a local

  7. Improving a DSM Obtained by Unmanned Aerial Vehicles for Flood Modelling

    Mourato, Sandra; Fernandez, Paulo; Pereira, Luísa; Moreira, Madalena

    2017-12-01

    According to the EU flood risks directive, flood hazard map must be used to assess the flood risk. These maps can be developed with hydraulic modelling tools using a Digital Surface Runoff Model (DSRM). During the last decade, important evolutions of the spatial data processing has been developed which will certainly improve the hydraulic models results. Currently, images acquired with Red/Green/Blue (RGB) camera transported by Unmanned Aerial Vehicles (UAV) are seen as a good alternative data sources to represent the terrain surface with a high level of resolution and precision. The question is if the digital surface model obtain with this data is adequate enough for a good representation of the hydraulics flood characteristics. For this purpose, the hydraulic model HEC-RAS was run with 4 different DSRM for an 8.5 km reach of the Lis River in Portugal. The computational performance of the 4 modelling implementations is evaluated. Two hydrometric stations water level records were used as boundary conditions of the hydraulic model. The records from a third hydrometric station were used to validate the optimal DSRM. The HEC-RAS results had the best performance during the validation step were the ones where the DSRM with integration of the two altimetry data sources.

  8. A Review of Flood Loss Models as Basis for Harmonization and Benchmarking.

    Tina Gerl

    Full Text Available Risk-based approaches have been increasingly accepted and operationalized in flood risk management during recent decades. For instance, commercial flood risk models are used by the insurance industry to assess potential losses, establish the pricing of policies and determine reinsurance needs. Despite considerable progress in the development of loss estimation tools since the 1980s, loss estimates still reflect high uncertainties and disparities that often lead to questioning their quality. This requires an assessment of the validity and robustness of loss models as it affects prioritization and investment decision in flood risk management as well as regulatory requirements and business decisions in the insurance industry. Hence, more effort is needed to quantify uncertainties and undertake validations. Due to a lack of detailed and reliable flood loss data, first order validations are difficult to accomplish, so that model comparisons in terms of benchmarking are essential. It is checked if the models are informed by existing data and knowledge and if the assumptions made in the models are aligned with the existing knowledge. When this alignment is confirmed through validation or benchmarking exercises, the user gains confidence in the models. Before these benchmarking exercises are feasible, however, a cohesive survey of existing knowledge needs to be undertaken. With that aim, this work presents a review of flood loss-or flood vulnerability-relationships collected from the public domain and some professional sources. Our survey analyses 61 sources consisting of publications or software packages, of which 47 are reviewed in detail. This exercise results in probably the most complete review of flood loss models to date containing nearly a thousand vulnerability functions. These functions are highly heterogeneous and only about half of the loss models are found to be accompanied by explicit validation at the time of their proposal. This paper

  9. A Review of Flood Loss Models as Basis for Harmonization and Benchmarking.

    Gerl, Tina; Kreibich, Heidi; Franco, Guillermo; Marechal, David; Schröter, Kai

    2016-01-01

    Risk-based approaches have been increasingly accepted and operationalized in flood risk management during recent decades. For instance, commercial flood risk models are used by the insurance industry to assess potential losses, establish the pricing of policies and determine reinsurance needs. Despite considerable progress in the development of loss estimation tools since the 1980s, loss estimates still reflect high uncertainties and disparities that often lead to questioning their quality. This requires an assessment of the validity and robustness of loss models as it affects prioritization and investment decision in flood risk management as well as regulatory requirements and business decisions in the insurance industry. Hence, more effort is needed to quantify uncertainties and undertake validations. Due to a lack of detailed and reliable flood loss data, first order validations are difficult to accomplish, so that model comparisons in terms of benchmarking are essential. It is checked if the models are informed by existing data and knowledge and if the assumptions made in the models are aligned with the existing knowledge. When this alignment is confirmed through validation or benchmarking exercises, the user gains confidence in the models. Before these benchmarking exercises are feasible, however, a cohesive survey of existing knowledge needs to be undertaken. With that aim, this work presents a review of flood loss-or flood vulnerability-relationships collected from the public domain and some professional sources. Our survey analyses 61 sources consisting of publications or software packages, of which 47 are reviewed in detail. This exercise results in probably the most complete review of flood loss models to date containing nearly a thousand vulnerability functions. These functions are highly heterogeneous and only about half of the loss models are found to be accompanied by explicit validation at the time of their proposal. This paper exemplarily presents

  10. A Review of Flood Loss Models as Basis for Harmonization and Benchmarking

    Kreibich, Heidi; Franco, Guillermo; Marechal, David

    2016-01-01

    Risk-based approaches have been increasingly accepted and operationalized in flood risk management during recent decades. For instance, commercial flood risk models are used by the insurance industry to assess potential losses, establish the pricing of policies and determine reinsurance needs. Despite considerable progress in the development of loss estimation tools since the 1980s, loss estimates still reflect high uncertainties and disparities that often lead to questioning their quality. This requires an assessment of the validity and robustness of loss models as it affects prioritization and investment decision in flood risk management as well as regulatory requirements and business decisions in the insurance industry. Hence, more effort is needed to quantify uncertainties and undertake validations. Due to a lack of detailed and reliable flood loss data, first order validations are difficult to accomplish, so that model comparisons in terms of benchmarking are essential. It is checked if the models are informed by existing data and knowledge and if the assumptions made in the models are aligned with the existing knowledge. When this alignment is confirmed through validation or benchmarking exercises, the user gains confidence in the models. Before these benchmarking exercises are feasible, however, a cohesive survey of existing knowledge needs to be undertaken. With that aim, this work presents a review of flood loss–or flood vulnerability–relationships collected from the public domain and some professional sources. Our survey analyses 61 sources consisting of publications or software packages, of which 47 are reviewed in detail. This exercise results in probably the most complete review of flood loss models to date containing nearly a thousand vulnerability functions. These functions are highly heterogeneous and only about half of the loss models are found to be accompanied by explicit validation at the time of their proposal. This paper exemplarily

  11. A state of the art on the flooding phenomena and countercurrent flow limiting modeling

    Jeong, Young Jong; Chang, Won Pyo [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1996-07-01

    Countercurrent flow limiting phenomenon and its modeling for vertical and nearly horizontal pipes has been reviewed in two phase flow. A number of analytical and empirical model have been developed for flooding in the vertical pipes and annulars. These may be classified as stability theory, envelope theory, static equilibrium theory, slug formation theory, Wallis correlation, and Kutateladze correlation. The theories and empirical correlations are reviewed and comparison with the various experimental data. The scatter of the experimental data is large because of the different flooding condition and because of the influence of the experimental conditions. Application of flooding for PWR best estimate system codes is reviewed. The codes provide the user options to implement CCFL correlation for the specific geometry. The codes can accommodate generally Wallis, Kutateladze, or Bankoff correlation. 4 tabs., 36 figs., 52 refs. (Author).

  12. A state of the art on the flooding phenomena and countercurrent flow limiting modeling

    Jeong, Young Jong; Chang, Won Pyo

    1996-07-01

    Countercurrent flow limiting phenomenon and its modeling for vertical and nearly horizontal pipes has been reviewed in two phase flow. A number of analytical and empirical model have been developed for flooding in the vertical pipes and annulars. These may be classified as stability theory, envelope theory, static equilibrium theory, slug formation theory, Wallis correlation, and Kutateladze correlation. The theories and empirical correlations are reviewed and comparison with the various experimental data. The scatter of the experimental data is large because of the different flooding condition and because of the influence of the experimental conditions. Application of flooding for PWR best estimate system codes is reviewed. The codes provide the user options to implement CCFL correlation for the specific geometry. The codes can accommodate generally Wallis, Kutateladze, or Bankoff correlation. 4 tabs., 36 figs., 52 refs. (Author)

  13. Feedbacks among Floods, Pioneer Woody Vegetation, and Channel Change in Sand-Bed Rivers: Insights from Field Studies of Controlled Flood Releases and Models

    Wilcox, A. C.; Shafroth, P. B.; Lightbody, A.; Stella, J. C.; Bywater-Reyes, S.; Kiu, L.; Skorko, K.

    2012-04-01

    To investigate feedbacks between flow, geomorphic processes, and pioneer riparian vegetation in sand-bed rivers, we are combining field, hydraulic modeling, and laboratory simulations. Field studies have examined the response of woody riparian seedlings and channel morphology to prescribed dam-released floods that have been designed in part to maintain a native riparian woodland system on the Bill Williams River, Arizona, USA. Through monitoring of floods over a 7-year period, we have observed temporal and spatial variations in channel response. Floods have produced geomorphic and vegetation responses that varied with distance downstream of a dam, with scour and associated seedling mortality closer to the dam and aggradation and burial-induced mortality in a downstream reach with greater sediment supply. We also have observed that as vegetation grows beyond the seedling stage, its stabilizing effect on bars and its drag effect on flow progressively increases, such that floods of similar sizes but at different times may produce markedly different downstream responses as a function of vegetation characteristics. We also observed greater mortality among nonnative Tamarix spp. (tamarisk) seedlings than among native Salix gooddingii (Goodding's willow) seedlings, likely as a result of the greater first-year growth of willow relative to tamarisk. Combining field observations with modeling predictions of local hydraulics for the flood events we have studied is being used to draw linkages between hydraulics, channel change, and plant response at the patch and bar scale. In addition, mechanistic linkages are being examined using a field-scale laboratory stream channel, where seedlings of Tamarix spp. (tamarisk) and Populus fremontii (cottonwood) were planted and subjected to floods with varying sediment feed rate and plant configurations. The floods conveyed by our model channel were generally insufficient to scour the woody seedlings we planted, but changes in bar size and

  14. A Participatory Modeling Application of a Distributed Hydrologic Model in Nuevo Leon, Mexico for the 2010 Hurricane Alex Flood Event

    Baish, A. S.; Vivoni, E. R.; Payan, J. G.; Robles-Morua, A.; Basile, G. M.

    2011-12-01

    A distributed hydrologic model can help bring consensus among diverse stakeholders in regional flood planning by producing quantifiable sets of alternative futures. This value is acute in areas with high uncertainties in hydrologic conditions and sparse observations. In this study, we conduct an application of the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS) in the Santa Catarina basin of Nuevo Leon, Mexico, where Hurricane Alex in July 2010 led to catastrophic flooding of the capital city of Monterrey. Distributed model simulations utilize best-available information on the regional topography, land cover, and soils obtained from Mexican government agencies or analysis of remotely-sensed imagery from MODIS and ASTER. Furthermore, we developed meteorological forcing for the flood event based on multiple data sources, including three local gauge networks, satellite-based estimates from TRMM and PERSIANN, and the North American Land Data Assimilation System (NLDAS). Remotely-sensed data allowed us to quantify rainfall distributions in the upland, rural portions of the Santa Catarina that are sparsely populated and ungauged. Rural areas had significant contributions to the flood event and as a result were considered by stakeholders for flood control measures, including new reservoirs and upland vegetation management. Participatory modeling workshops with the stakeholders revealed a disconnect between urban and rural populations in regard to understanding the hydrologic conditions of the flood event and the effectiveness of existing and potential flood control measures. Despite these challenges, the use of the distributed flood forecasts developed within this participatory framework facilitated building consensus among diverse stakeholders and exploring alternative futures in the basin.

  15. Global Health Innovation Technology Models

    Kimberly Harding

    2016-04-01

    Full Text Available Chronic technology and business process disparities between High Income, Low Middle Income and Low Income (HIC, LMIC, LIC research collaborators directly prevent the growth of sustainable Global Health innova‐ tion for infectious and rare diseases. There is a need for an Open Source-Open Science Architecture Framework to bridge this divide. We are proposing such a framework for consideration by the Global Health community, by utiliz‐ ing a hybrid approach of integrating agnostic Open Source technology and healthcare interoperability standards and Total Quality Management principles. We will validate this architecture framework through our programme called Project Orchid. Project Orchid is a conceptual Clinical Intelligence Exchange and Virtual Innovation platform utilizing this approach to support clinical innovation efforts for multi-national collaboration that can be locally sustainable for LIC and LMIC research cohorts. The goal is to enable LIC and LMIC research organizations to acceler‐ ate their clinical trial process maturity in the field of drug discovery, population health innovation initiatives and public domain knowledge networks. When sponsored, this concept will be tested by 12 confirmed clinical research and public health organizations in six countries. The potential impact of this platform is reduced drug discovery and public health innovation lag time and improved clinical trial interventions, due to reliable clinical intelligence and bio-surveillance across all phases of the clinical innovation process.

  16. A Sharable and Efficient Metadata Model for Heterogeneous Earth Observation Data Retrieval in Multi-Scale Flood Mapping

    Nengcheng Chen

    2015-07-01

    Full Text Available Remote sensing plays an important role in flood mapping and is helping advance flood monitoring and management. Multi-scale flood mapping is necessary for dividing floods into several stages for comprehensive management. However, existing data systems are typically heterogeneous owing to the use of different access protocols and archiving metadata models. In this paper, we proposed a sharable and efficient metadata model (APEOPM for constructing an Earth observation (EO data system to retrieve remote sensing data for flood mapping. The proposed model contains two sub-models, an access protocol model and an enhanced encoding model. The access protocol model helps unify heterogeneous access protocols and can achieve intelligent access via a semantic enhancement method. The enhanced encoding model helps unify a heterogeneous archiving metadata model. Wuhan city, one of the most important cities in the Yangtze River Economic Belt in China, is selected as a study area for testing the retrieval of heterogeneous EO data and flood mapping. The past torrential rain period from 25 March 2015 to 10 April 2015 is chosen as the temporal range in this study. To aid in comprehensive management, mapping is conducted at different spatial and temporal scales. In addition, the efficiency of data retrieval is analyzed, and validation between the flood maps and actual precipitation was conducted. The results show that the flood map coincided with the actual precipitation.

  17. Estimation of antecedent wetness conditions for flood modelling in northern Morocco

    Y. Tramblay

    2012-11-01

    Full Text Available In northern Morocco are located most of the dams and reservoirs of the country, while this region is affected by severe rainfall events causing floods. To improve the management of the water regulation structures, there is a need to develop rainfall–runoff models to both maximize the storage capacity and reduce the risks caused by floods. In this study, a model is developed to reproduce the flood events for a 655 km2 catchment located upstream of the 6th largest dam in Morocco. Constrained by data availability, a standard event-based model combining a SCS-CN (Soil Conservation Service Curve Number loss model and a Clark unit hydrograph was developed for hourly discharge simulation using 16 flood events that occurred between 1984 and 2008. The model was found satisfactory to reproduce the runoff and the temporal evolution of floods, even with limited rainfall data. Several antecedent wetness conditions estimators for the catchment were compared with the initial condition of the model. Theses estimators include an antecedent discharge index, an antecedent precipitation index and a continuous daily soil moisture accounting model (SMA, based on precipitation and evapotranspiration. The SMA model performed the best to estimate the initial conditions of the event-based hydrological model (R2 = 0.9. Its daily output has been compared with ASCAT and AMSR-E remote sensing data products, which were both able to reproduce with accuracy the daily simulated soil moisture dynamics at the catchment scale. This same approach could be implemented in other catchments of this region for operational purposes. The results of this study suggest that remote sensing data are potentially useful to estimate the soil moisture conditions in the case of ungauged catchments in Northern Africa.

  18. Investigating compound flooding in an estuary using hydrodynamic modelling: a case study from the Shoalhaven River, Australia

    Kumbier, Kristian; Carvalho, Rafael C.; Vafeidis, Athanasios T.; Woodroffe, Colin D.

    2018-02-01

    Many previous modelling studies have considered storm-tide and riverine flooding independently, even though joint-probability analysis highlighted significant dependence between extreme rainfall and extreme storm surges in estuarine environments. This study investigates compound flooding by quantifying horizontal and vertical differences in coastal flood risk estimates resulting from a separation of storm-tide and riverine flooding processes. We used an open-source version of the Delft3D model to simulate flood extent and inundation depth due to a storm event that occurred in June 2016 in the Shoalhaven Estuary, south-eastern Australia. Time series of observed water levels and discharge measurements are used to force model boundaries, whereas observational data such as satellite imagery, aerial photographs, tidal gauges and water level logger measurements are used to validate modelling results. The comparison of simulation results including and excluding riverine discharge demonstrated large differences in modelled flood extents and inundation depths. A flood risk assessment accounting only for storm-tide flooding would have underestimated the flood extent of the June 2016 storm event by 30 % (20.5 km2). Furthermore, inundation depths would have been underestimated on average by 0.34 m and by up to 1.5 m locally. We recommend considering storm-tide and riverine flooding processes jointly in estuaries with large catchment areas, which are known to have a quick response time to extreme rainfall. In addition, comparison of different boundary set-ups at the intermittent entrance in Shoalhaven Heads indicated that a permanent opening, in order to reduce exposure to riverine flooding, would increase tidal range and exposure to both storm-tide flooding and wave action.

  19. Identification of hydrological model parameters for flood forecasting using data depth measures

    Krauße, T.; Cullmann, J.

    2011-03-01

    The development of methods for estimating the parameters of hydrological models considering uncertainties has been of high interest in hydrological research over the last years. Besides the very popular Markov Chain Monte Carlo (MCMC) methods which estimate the uncertainty of model parameters in the settings of a Bayesian framework, the development of depth based sampling methods, also entitled robust parameter estimation (ROPE), have attracted an increasing research interest. These methods understand the estimation of model parameters as a geometric search of a set of robust performing parameter vectors by application of the concept of data depth. Recent studies showed that the parameter vectors estimated by depth based sampling perform more robust in validation. One major advantage of this kind of approach over the MCMC methods is that the formulation of a likelihood function within a Bayesian uncertainty framework gets obsolete and arbitrary purpose-oriented performance criteria defined by the user can be integrated without any further complications. In this paper we present an advanced ROPE method entitled the Advanced Robust Parameter Estimation by Monte Carlo algorithm (AROPEMC). The AROPEMC algorithm is a modified version of the original robust parameter estimation algorithm ROPEMC developed by Bárdossy and Singh (2008). AROPEMC performs by merging iterative Monte Carlo simulations, identifying well performing parameter vectors, the sampling of robust parameter vectors according to the principle of data depth and the application of a well-founded stopping criterion applied in supervised machine learning. The principals of the algorithm are illustrated by means of the Rosenbrock's and Rastrigin's function, two well known performance benchmarks for optimisation algorithms. Two case studies demonstrate the advantage of AROPEMC compared to state of the art global optimisation algorithms. A distributed process-oriented hydrological model is calibrated and

  20. HYbrid Coordinate Ocean Model (HYCOM): Global

    National Oceanic and Atmospheric Administration, Department of Commerce — Global HYbrid Coordinate Ocean Model (HYCOM) and U.S. Navy Coupled Ocean Data Assimilation (NCODA) 3-day, daily forecast at approximately 9-km (1/12-degree)...

  1. ASTER Global Digital Elevation Model V002

    National Aeronautics and Space Administration — The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) was developed jointly by the U.S. National...

  2. The impact of bathymetry input on flood simulations

    Khanam, M.; Cohen, S.

    2017-12-01

    Flood prediction and mitigation systems are inevitable for improving public safety and community resilience all over the worldwide. Hydraulic simulations of flood events are becoming an increasingly efficient tool for studying and predicting flood events and susceptibility. A consistent limitation of hydraulic simulations of riverine dynamics is the lack of information about river bathymetry as most terrain data record water surface elevation. The impact of this limitation on the accuracy on hydraulic simulations of flood has not been well studies over a large range of flood magnitude and modeling frameworks. Advancing our understanding of this topic is timely given emerging national and global efforts for developing automated flood predictions systems (e.g. NOAA National Water Center). Here we study the response of flood simulation to the incorporation of different bathymetry and floodplain surveillance source. Different hydraulic models are compared, Mike-Flood, a 2D hydrodynamic model, and GSSHA, a hydrology/hydraulics model. We test a hypothesis that the impact of inclusion/exclusion of bathymetry data on hydraulic model results will vary in its magnitude as a function of river size. This will allow researcher and stake holders more accurate predictions of flood events providing useful information that will help local communities in a vulnerable flood zone to mitigate flood hazards. Also, it will help to evaluate the accuracy and efficiency of different modeling frameworks and gage their dependency on detailed bathymetry input data.

  3. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.

    Khosravi, Khabat; Pham, Binh Thai; Chapi, Kamran; Shirzadi, Ataollah; Shahabi, Himan; Revhaug, Inge; Prakash, Indra; Tien Bui, Dieu

    2018-06-15

    Floods are one of the most damaging natural hazards causing huge loss of property, infrastructure and lives. Prediction of occurrence of flash flood locations is very difficult due to sudden change in climatic condition and manmade factors. However, prior identification of flood susceptible areas can be done with the help of machine learning techniques for proper timely management of flood hazards. In this study, we tested four decision trees based machine learning models namely Logistic Model Trees (LMT), Reduced Error Pruning Trees (REPT), Naïve Bayes Trees (NBT), and Alternating Decision Trees (ADT) for flash flood susceptibility mapping at the Haraz Watershed in the northern part of Iran. For this, a spatial database was constructed with 201 present and past flood locations and eleven flood-influencing factors namely ground slope, altitude, curvature, Stream Power Index (SPI), Topographic Wetness Index (TWI), land use, rainfall, river density, distance from river, lithology, and Normalized Difference Vegetation Index (NDVI). Statistical evaluation measures, the Receiver Operating Characteristic (ROC) curve, and Freidman and Wilcoxon signed-rank tests were used to validate and compare the prediction capability of the models. Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively. These techniques have proven successful in quickly determining flood susceptible areas. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. A hydro-sedimentary modeling system for flash flood propagation and hazard estimation under different agricultural practices

    Kourgialas, N. N.; Karatzas, G. P.

    2014-03-01

    A modeling system for the estimation of flash flood flow velocity and sediment transport is developed in this study. The system comprises three components: (a) a modeling framework based on the hydrological model HSPF, (b) the hydrodynamic module of the hydraulic model MIKE 11 (quasi-2-D), and (c) the advection-dispersion module of MIKE 11 as a sediment transport model. An important parameter in hydraulic modeling is the Manning's coefficient, an indicator of the channel resistance which is directly dependent on riparian vegetation changes. Riparian vegetation's effect on flood propagation parameters such as water depth (inundation), discharge, flow velocity, and sediment transport load is investigated in this study. Based on the obtained results, when the weed-cutting percentage is increased, the flood wave depth decreases while flow discharge, velocity and sediment transport load increase. The proposed modeling system is used to evaluate and illustrate the flood hazard for different riparian vegetation cutting scenarios. For the estimation of flood hazard, a combination of the flood propagation characteristics of water depth, flow velocity and sediment load was used. Next, a well-balanced selection of the most appropriate agricultural cutting practices of riparian vegetation was performed. Ultimately, the model results obtained for different agricultural cutting practice scenarios can be employed to create flood protection measures for flood-prone areas. The proposed methodology was applied to the downstream part of a small Mediterranean river basin in Crete, Greece.

  5. The determination of risk areas for muddy floods based on a worst-case erosion modelling

    Saathoff, Ulfert; Schindewolf, Marcus; Annika Arévalo, Sarah

    2013-04-01

    Soil erosion and muddy floods are a frequently occurring hazard in the German state of Saxony, because of the topography and the high relief energy together with the high proportion of arable land. Still, the events are rather heterogeneously distributed and we do not know where damage is likely to occur. The goal of this study is to locate hot spots for the risk of muddy floods, with the objective to prevent high economic damage in future. We applied a soil erosion and deposition map of Saxony, calculated with the process based soil erosion model EROSION 3D. This map shows the potential soil erosion and transported sediment for worst case soil conditions and a 10 year rain storm event. Furthermore, a map of the current landuse in the state is used. From the landuse map, we extracted those areas that are especially vulnerable to muddy floods, like residential and industrial areas, infrastructural facilities (e.g. power plants, hospitals) and highways. In combination with the output of the soil erosion model, the amount of sediment, that enters each single landuse entity, is calculated. Based on this data, a state-wide map with classified risks is created. The results are furthermore used to identify the risk of muddy floods for each single municipality in Saxony. The results are evaluated with data of real occurred muddy flood events with documented locations during the period between 2000 and 2010. Additionally, plausibility tests are performed for selected areas (examination of landuse, topography and soil). The results prove to be plausible and most of the documented events can be explained by the modelled risk map. The created map can be used by different institutions like city and traffic planners, to estimate the risk of muddy flood occurrence at specific locations. Furthermore, the risk map can serve insurance companies to evaluate the insurance risk of a building. To make them easily accessible, the risk map will be published online via a web GIS

  6. Modelling the effectiveness of grass buffer strips in managing muddy floods under a changing climate

    Mullan, Donal; Vandaele, Karel; Boardman, John; Meneely, John; Crossley, Laura H.

    2016-10-01

    Muddy floods occur when rainfall generates runoff on agricultural land, detaching and transporting sediment into the surrounding natural and built environment. In the Belgian Loess Belt, muddy floods occur regularly and lead to considerable economic costs associated with damage to property and infrastructure. Mitigation measures designed to manage the problem have been tested in a pilot area within Flanders and were found to be cost-effective within three years. This study assesses whether these mitigation measures will remain effective under a changing climate. To test this, the Water Erosion Prediction Project (WEPP) model was used to examine muddy flooding diagnostics (precipitation, runoff, soil loss and sediment yield) for a case study hillslope in Flanders where grass buffer strips are currently used as a mitigation measure. The model was run for present day conditions and then under 33 future site-specific climate scenarios. These future scenarios were generated from three earth system models driven by four representative concentration pathways and downscaled using quantile mapping and the weather generator CLIGEN. Results reveal that under the majority of future scenarios, muddy flooding diagnostics are projected to increase, mostly as a consequence of large scale precipitation events rather than mean changes. The magnitude of muddy flood events for a given return period is also generally projected to increase. These findings indicate that present day mitigation measures may have a reduced capacity to manage muddy flooding given the changes imposed by a warming climate with an enhanced hydrological cycle. Revisions to the design of existing mitigation measures within existing policy frameworks are considered the most effective way to account for the impacts of climate change in future mitigation planning.

  7. Research on Multi Hydrological Models Applicability and Modelling Data Uncertainty Analysis for Flash Flood Simulation in Hilly Area

    Ye, L.; Wu, J.; Wang, L.; Song, T.; Ji, R.

    2017-12-01

    Flooding in small-scale watershed in hilly area is characterized by short time periods and rapid rise and recession due to the complex underlying surfaces, various climate type and strong effect of human activities. It is almost impossible for a single hydrological model to describe the variation of flooding in both time and space accurately for all the catchments in hilly area because the hydrological characteristics can vary significantly among different catchments. In this study, we compare the performance of 5 hydrological models with varying degrees of complexity for simulation of flash flood for 14 small-scale watershed in China in order to find the relationship between the applicability of the hydrological models and the catchments characteristics. Meanwhile, given the fact that the hydrological data is sparse in hilly area, the effect of precipitation data, DEM resolution and their interference on the uncertainty of flood simulation is also illustrated. In general, the results showed that the distributed hydrological model (HEC-HMS in this study) performed better than the lumped hydrological models. Xinajiang and API models had good simulation for the humid catchments when long-term and continuous rainfall data is provided. Dahuofang model can simulate the flood peak well while the runoff generation module is relatively poor. In addition, the effect of diverse modelling data on the simulations is not simply superposed, and there is a complex interaction effect among different modelling data. Overall, both the catchment hydrological characteristics and modelling data situation should be taken into consideration in order to choose the suitable hydrological model for flood simulation for small-scale catchment in hilly area.

  8. A Global Stock and Bond Model

    Connor, Gregory

    1996-01-01

    Factor models are now widely used to support asset selection decisions. Global asset allocation, the allocation between stocks versus bonds and among nations, usually relies instead on correlation analysis of international equity and bond indexes. It would be preferable to have a single integrated framework for both asset selection and asset allocation. This framework would require a factor model applicable at an asset or country level, as well as at a global level,...

  9. Internationally coordinated multi-mission planning is now critical to sustain the space-based rainfall observations needed for managing floods globally

    Reed, Patrick M; Herman, Jonathan D; Chaney, Nathaniel W; Wood, Eric F; Ferringer, Matthew P

    2015-01-01

    At present 4 of 10 dedicated rainfall observing satellite systems have exceeded their design life, some by more than a decade. Here, we show operational implications for flood management of a ‘collapse’ of space-based rainfall observing infrastructure as well as the high-value opportunities for a globally coordinated portfolio of satellite missions and data services. Results show that the current portfolio of rainfall missions fails to meet operational data needs for flood management, even when assuming a perfectly coordinated data product from all current rainfall-focused missions (i.e., the full portfolio). In the full portfolio, satellite-based rainfall data deficits vary across the globe and may preclude climate adaptation in locations vulnerable to increasing flood risks. Moreover, removing satellites that are currently beyond their design life (i.e., the reduced portfolio) dramatically increases data deficits globally and could cause entire high intensity flood events to be unobserved. Recovery from the reduced portfolio is possible with internationally coordinated replenishment of as few as 2 of the 4 satellite systems beyond their design life, yielding rainfall data coverages that outperform the current full portfolio (i.e., an optimized portfolio of eight satellites can outperform ten satellites). This work demonstrates the potential for internationally coordinated satellite replenishment and data services to substantially enhance the cost-effectiveness, sustainability and operational value of space-based rainfall observations in managing evolving flood risks. (letter)

  10. Understanding the radar backscattering from flooded and nonflooded Amazonian forests: results from canopy backscatter modeling

    Wang, Y.; Hess, L.L.; Filoso, S.; Melack, J.M.

    1995-01-01

    To understand the potential of using multiwavelength imaging radars to detect flooding in Amazonian floodplain forests, we simulated the radar backscatter from a floodplain forest with a flooded or nonflooded ground condition at C-, L-, and P-bands. Field measurements of forest structure in the Anavilhanas archipelago of the Negro River, Brazil, were used as inputs to the model. Given the same wavelength or incidence angle, the ratio of backscatter from the flooded forest to that from the nonflooded forest was higher at HH polarization than at VV polarization. Given the same wavelength or polarization, the ratio was larger at small incidence angles than at large incidence angles. Given the same polarization or incidence angle, the ratio was larger at a long wavelength than at a short wavelength. As the surface soil moisture underneath the nonflooded forest increased from 10% to 50% of volumetric moisture, the flooded/nonflooded backscatter ratio decreased; the decreases were small at C- and L-band but large at P-band. When the leaf size was comparable to or larger than the wavelength of C-band, the leaf area index (LAI) had a large effect on the simulated C-band (not L-band or P-band) backscatter from the flooded and nonflooded forests. (author)

  11. The HEC RAS model of regulated stream for purposes of flood risk reduction

    Fijko Rastislav

    2016-06-01

    Full Text Available The work highlights the modeling of water flow in open channels using 1D mathematical model HEC-RAS in the area of interest Lopuchov village in eastern Slovakia. We created a digital model from a geodetic survey, which was used to show the area of inundation in ArcGIS software. We point out the modeling methodology with emphasis to collection of the data and their relevance for determination of boundary conditions in 3D model of the study area in GIS platform. The BIM objects can be exported to the defined model of the area. The obtained results were used for simulation of flooding. The results give to us clearly and distinctly defined areas of inundation, which we used in the processing of Cost benefit analysis. We used the developed model for stating the potential damages in flood vulnerable areas.

  12. The HEC RAS model of regulated stream for purposes of flood risk reduction

    Fijko, Rastislav; Zeleňáková, Martina

    2016-06-01

    The work highlights the modeling of water flow in open channels using 1D mathematical model HEC-RAS in the area of interest Lopuchov village in eastern Slovakia. We created a digital model from a geodetic survey, which was used to show the area of inundation in ArcGIS software. We point out the modeling methodology with emphasis to collection of the data and their relevance for determination of boundary conditions in 3D model of the study area in GIS platform. The BIM objects can be exported to the defined model of the area. The obtained results were used for simulation of flooding. The results give to us clearly and distinctly defined areas of inundation, which we used in the processing of Cost benefit analysis. We used the developed model for stating the potential damages in flood vulnerable areas.

  13. A global central banker competency model

    David W. Brits

    2014-07-01

    Full Text Available Orientation: No comprehensive, integrated competency model exists for central bankers. Due to the importance of central banks in the context of the ongoing global financial crisis, it was deemed necessary to design and validate such a model. Research purpose: To craft and validate a comprehensive, integrated global central banker competency model (GCBCM and to assess whether central banks using the GCBCM for training have a higher global influence. Motivation for the study: Limited consensus exists globally about what constitutes a ‘competent’ central banker. A quantitatively validated GCBCM would make a significant contribution to enhancing central banker effectiveness, and also provide a solid foundation for effective people management. Research approach, design and method: A blended quantitative and qualitative research approach was taken. Two sets of hypotheses were tested regarding the relationships between the GCBCM and the training offered, using the model on the one hand, and a central bank’s global influence on the other. Main findings: The GCBCM was generally accepted across all participating central banks globally, although some differences were found between central banks with higher and lower global influence. The actual training offered by central banks in terms of the model, however, is generally limited to technical-functional skills. The GCBCM is therefore at present predominantly aspirational. Significant differences were found regarding the training offered. Practical/managerial implications: By adopting the GCBCM, central banks would be able to develop organisation-specific competency models in order to enhance their organisational capabilities and play their increasingly important global role more effectively. Contribution: A generic conceptual framework for the crafting of a competency model with evaluation criteria was developed. A GCBCM was quantitatively validated.

  14. Modelling the Impacts of Changing Land Cover/Land Use and Climate on Flooding in the Elk River Watershed, British Columbia

    Barnes, C. C.; Byrne, J. M.; Hopkinson, C.; MacDonald, R. J.; Johnson, D. L.

    2015-12-01

    The Elk River is a mountain watershed located along the eastern border of British Columbia, Canada. The Elk River is confined by railway bridges, roads, and urban areas. Flooding has been a concern in the valley for more than a century. The most recent major flood event occurred in 2013 affecting several communities. River modifications such as riprapped dykes, channelization, and dredging have occurred in an attempt to reduce inundation, with limited success. Significant changes in land cover/land use (LCLU) such as natural state to urban, forestry practices, and mining from underground to mountaintop/valley fill have changed terrain and ground surfaces thereby altering water infiltration and runoff processes in the watershed. Future climate change in this region is expected to alter air temperature and precipitation as well as produce an earlier seasonal spring freshet potentially impacting future flood events. The objective of this research is to model historical and future hydrological conditions to identify flood frequency and risk under a range of climate and LCLU change scenarios in the Elk River watershed. Historic remote sensing data, forest management plans, and mining industry production/post-mining reclamation plans will be used to create a predictive past and future LCLU time series. A range of future air temperature and precipitation scenarios will be developed based on accepted Global Climate Modelling (GCM) research to examine how the hydrometeorological conditions may be altered under a range of future climate scenarios. The GENESYS (GENerate Earth SYstems Science input) hydrometeorological model will be used to simulate climate and LCLU to assess historic and potential future flood frequency and magnitude. Results will be used to create innovative flood mitigation, adaptation, and management strategies for the Elk River with the intent of being wildlife friendly and non-destructive to ecosystems and habitats for native species.

  15. Modeling and simulation of surfactant-polymer flooding using a new hybrid method

    Daripa, Prabir; Dutta, Sourav

    2017-04-01

    Chemical enhanced oil recovery by surfactant-polymer (SP) flooding has been studied in two space dimensions. A new global pressure for incompressible, immiscible, multicomponent two-phase porous media flow has been derived in the context of SP flooding. This has been used to formulate a system of flow equations that incorporates the effect of capillary pressure and also the effect of polymer and surfactant on viscosity, interfacial tension and relative permeabilities of the two phases. The coupled system of equations for pressure, water saturation, polymer concentration and surfactant concentration has been solved using a new hybrid method in which the elliptic global pressure equation is solved using a discontinuous finite element method and the transport equations for water saturation and concentrations of the components are solved by a Modified Method Of Characteristics (MMOC) in the multicomponent setting. Numerical simulations have been performed to validate the method, both qualitatively and quantitatively, and to evaluate the relative performance of the various flooding schemes for several different heterogeneous reservoirs.

  16. Artificial intelligence and finite element modelling for monitoring flood defence structures

    Pyayt, A.L.; Mokhov, I.I.; Kozionov, A.; Kusherbaeva, V.; Melnikova, N.B.; Krzhizhanovskaya, V.V.; Meijer, R.J.

    2011-01-01

    We present a hybrid approach to monitoring the stability of flood defence structures equipped with sensors. This approach combines the finite element modelling with the artificial intelligence for real-time signal processing and anomaly detection. This combined method has been developed for the

  17. The effect of coupling hydrologic and hydrodynamic models on probable maximum flood estimation

    Felder, Guido; Zischg, Andreas; Weingartner, Rolf

    2017-07-01

    Deterministic rainfall-runoff modelling usually assumes stationary hydrological system, as model parameters are calibrated with and therefore dependant on observed data. However, runoff processes are probably not stationary in the case of a probable maximum flood (PMF) where discharge greatly exceeds observed flood peaks. Developing hydrodynamic models and using them to build coupled hydrologic-hydrodynamic models can potentially improve the plausibility of PMF estimations. This study aims to assess the potential benefits and constraints of coupled modelling compared to standard deterministic hydrologic modelling when it comes to PMF estimation. The two modelling approaches are applied using a set of 100 spatio-temporal probable maximum precipitation (PMP) distribution scenarios. The resulting hydrographs, the resulting peak discharges as well as the reliability and the plausibility of the estimates are evaluated. The discussion of the results shows that coupling hydrologic and hydrodynamic models substantially improves the physical plausibility of PMF modelling, although both modelling approaches lead to PMF estimations for the catchment outlet that fall within a similar range. Using a coupled model is particularly suggested in cases where considerable flood-prone areas are situated within a catchment.

  18. A spatiotemporal optimization model for the evacuation of the population exposed to flood hazard

    Alaeddine, H.; Serrhini, K.; Maizia, M.

    2015-03-01

    Managing the crisis caused by natural disasters, and especially by floods, requires the development of effective evacuation systems. An effective evacuation system must take into account certain constraints, including those related to traffic network, accessibility, human resources and material equipment (vehicles, collecting points, etc.). The main objective of this work is to provide assistance to technical services and rescue forces in terms of accessibility by offering itineraries relating to rescue and evacuation of people and property. We consider in this paper the evacuation of an urban area of medium size exposed to the hazard of flood. In case of inundation, most people will be evacuated using their own vehicles. Two evacuation types are addressed in this paper: (1) a preventive evacuation based on a flood forecasting system and (2) an evacuation during the disaster based on flooding scenarios. The two study sites on which the developed evacuation model is applied are the Tours valley (Fr, 37), which is protected by a set of dikes (preventive evacuation), and the Gien valley (Fr, 45), which benefits from a low rate of flooding (evacuation before and during the disaster). Our goal is to construct, for each of these two sites, a chronological evacuation plan, i.e., computing for each individual the departure date and the path to reach the assembly point (also called shelter) according to a priority list established for this purpose. The evacuation plan must avoid the congestion on the road network. Here we present a spatiotemporal optimization model (STOM) dedicated to the evacuation of the population exposed to natural disasters and more specifically to flood risk.

  19. Regional forecasting with global atmospheric models

    Crowley, T.J.; North, G.R.; Smith, N.R.

    1994-05-01

    The scope of the report is to present the results of the fourth year's work on the atmospheric modeling part of the global climate studies task. The development testing of computer models and initial results are discussed. The appendices contain studies that provide supporting information and guidance to the modeling work and further details on computer model development. Complete documentation of the models, including user information, will be prepared under separate reports and manuals

  20. Modeling urbanized watershed flood response changes with distributed hydrological model: key hydrological processes, parameterization and case studies

    Chen, Y.

    2017-12-01

    Urbanization is the world development trend for the past century, and the developing countries have been experiencing much rapider urbanization in the past decades. Urbanization brings many benefits to human beings, but also causes negative impacts, such as increasing flood risk. Impact of urbanization on flood response has long been observed, but quantitatively studying this effect still faces great challenges. For example, setting up an appropriate hydrological model representing the changed flood responses and determining accurate model parameters are very difficult in the urbanized or urbanizing watershed. In the Pearl River Delta area, rapidest urbanization has been observed in China for the past decades, and dozens of highly urbanized watersheds have been appeared. In this study, a physically based distributed watershed hydrological model, the Liuxihe model is employed and revised to simulate the hydrological processes of the highly urbanized watershed flood in the Pearl River Delta area. A virtual soil type is then defined in the terrain properties dataset, and its runoff production and routing algorithms are added to the Liuxihe model. Based on a parameter sensitive analysis, the key hydrological processes of a highly urbanized watershed is proposed, that provides insight into the hydrological processes and for parameter optimization. Based on the above analysis, the model is set up in the Songmushan watershed where there is hydrological data observation. A model parameter optimization and updating strategy is proposed based on the remotely sensed LUC types, which optimizes model parameters with PSO algorithm and updates them based on the changed LUC types. The model parameters in Songmushan watershed are regionalized at the Pearl River Delta area watersheds based on the LUC types of the other watersheds. A dozen watersheds in the highly urbanized area of Dongguan City in the Pearl River Delta area were studied for the flood response changes due to

  1. Simulating Catchment Scale Afforestation for Mitigating Flooding

    Barnes, M. S.; Bathurst, J. C.; Quinn, P. F.; Birkinshaw, S.

    2016-12-01

    After the 2013-14, and the more recent 2015-16, winter floods in the UK there were calls to 'forest the uplands' as a solution to reducing flood risk across the nation. However, the role of forests as a natural flood management practice remains highly controversial, due to a distinct lack of robust evidence into its effectiveness in reducing flood risk during extreme events. This project aims to improve the understanding of the impacts of upland afforestation on flood risk at the sub-catchment and full catchment scales. This will be achieved through an integrated fieldwork and modelling approach, with the use of a series of process based hydrological models to scale up and examine the effects forestry can have on flooding. Furthermore, there is a need to analyse the extent to which land management practices, catchment system engineering and the installation of runoff attenuation features (RAFs), such as engineered log jams, in headwater catchments can attenuate flood-wave movement, and potentially reduce downstream flood risk. Additionally, the proportion of a catchment or riparian reach that would need to be forested in order to achieve a significant impact on reducing downstream flooding will be defined. The consequential impacts of a corresponding reduction in agriculturally productive farmland and the potential decline of water resource availability will also be considered in order to safeguard the UK's food security and satisfy the global demand on water resources.

  2. An application of a hydraulic model simulator in flood risk assessment under changing climatic conditions

    Doroszkiewicz, J. M.; Romanowicz, R. J.

    2016-12-01

    The standard procedure of climate change impact assessment on future hydrological extremes consists of a chain of consecutive actions, starting from the choice of GCM driven by an assumed CO2 scenario, through downscaling of climatic forcing to a catchment scale, estimation of hydrological extreme indices using hydrological modelling tools and subsequent derivation of flood risk maps with the help of a hydraulic model. Among many possible sources of uncertainty, the main are the uncertainties related to future climate scenarios, climate models, downscaling techniques and hydrological and hydraulic models. Unfortunately, we cannot directly assess the impact of these different sources of uncertainties on flood risk in future due to lack of observations of future climate realizations. The aim of this study is an assessment of a relative impact of different sources of uncertainty on the uncertainty of flood risk maps. Due to the complexity of the processes involved, an assessment of total uncertainty of maps of inundation probability might be very computer time consuming. As a way forward we present an application of a hydraulic model simulator based on a nonlinear transfer function model for the chosen locations along the river reach. The transfer function model parameters are estimated based on the simulations of the hydraulic model at each of the model cross-sections. The study shows that the application of a simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. Biala Tarnowska catchment, situated in southern Poland is used as a case study. Future discharges at the input to a hydraulic model are obtained using the HBV model and climate projections obtained from the EUROCORDEX project. The study describes a cascade of uncertainty related to different stages of the process of derivation of flood risk maps under changing climate conditions. In this context it takes into account the

  3. Future Coastal Population Growth and Exposure to Sea-Level Rise and Coastal Flooding - A Global Assessment

    Neumann, Barbara; Vafeidis, Athanasios T.; Zimmermann, Juliane; Nicholls, Robert J.

    2015-01-01

    Coastal zones are exposed to a range of coastal hazards including sea-level rise with its related effects. At the same time, they are more densely populated than the hinterland and exhibit higher rates of population growth and urbanisation. As this trend is expected to continue into the future, we investigate how coastal populations will be affected by such impacts at global and regional scales by the years 2030 and 2060. Starting from baseline population estimates for the year 2000, we assess future population change in the low-elevation coastal zone and trends in exposure to 100-year coastal floods based on four different sea-level and socio-economic scenarios. Our method accounts for differential growth of coastal areas against the land-locked hinterland and for trends of urbanisation and expansive urban growth, as currently observed, but does not explicitly consider possible displacement or out-migration due to factors such as sea-level rise. We combine spatially explicit estimates of the baseline population with demographic data in order to derive scenari