A Global Geospatial Database of 5000+ Historic Flood Event Extents

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Effects of climate variability on global scale flood risk

Science.gov (United States)

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.

The Aqueduct Global Flood Analyzer

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Spatial Scaling of Global Rainfall and Flood Extremes

Science.gov (United States)

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

ENSO impacts on flood risk at the global scale

Science.gov (United States)

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

Improving Global Flood Forecasting using Satellite Detected Flood Extent

NARCIS (Netherlands)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

An experimental system for flood risk forecasting at global scale

Science.gov (United States)

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.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

A framework for global river flood risk assessments

NARCIS (Netherlands)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

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.

A Global Drought and Flood Catalogue for the past 100 years

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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

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

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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.

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

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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.

A satellite and model based flood inundation climatology of Australia

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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.

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

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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.

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

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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.

Flood damage curves for consistent global risk assessments

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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

Downscaling Global Weather Forecast Outputs Using ANN for Flood Prediction

Directory of Open Access Journals (Sweden)

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.

Probabilistic, meso-scale flood loss modelling

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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.

Assessing uncertainty in SRTM elevations for global flood modelling

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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.

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

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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

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

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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.

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

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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

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

NARCIS (Netherlands)

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

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

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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.

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

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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.

Coastal and Riverine Flood Forecast Model powered by ADCIRC

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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

The credibility challenge for global fluvial flood risk analysis

NARCIS (Netherlands)

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

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

Science.gov (United States)

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.

Flash flood modelling for ungauged catchments

Science.gov (United States)

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

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

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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

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

Science.gov (United States)

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.

Probabilistic flood damage modelling at the meso-scale

Science.gov (United States)

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.

Global Rapid Flood Mapping System with Spaceborne SAR Data

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Developing a Malaysia flood model

Science.gov (United States)

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.

Floods in a changing climate

Science.gov (United States)

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...

Forecast-based Integrated Flood Detection System for Emergency Response and Disaster Risk Reduction (Flood-FINDER)

Science.gov (United States)

Arcorace, Mauro; Silvestro, Francesco; Rudari, Roberto; Boni, Giorgio; Dell'Oro, Luca; Bjorgo, Einar

2016-04-01

Most flood prone areas in the globe are mainly located in developing countries where making communities more flood resilient is a priority. Despite different flood forecasting initiatives are now available from academia and research centers, what is often missing is the connection between the timely hazard detection and the community response to warnings. In order to bridge the gap between science and decision makers, UN agencies play a key role on the dissemination of information in the field and on capacity-building to local governments. In this context, having a reliable global early warning system in the UN would concretely improve existing in house capacities for Humanitarian Response and the Disaster Risk Reduction. For those reasons, UNITAR-UNOSAT has developed together with USGS and CIMA Foundation a Global Flood EWS called "Flood-FINDER". The Flood-FINDER system is a modelling chain which includes meteorological, hydrological and hydraulic models that are accurately linked to enable the production of warnings and forecast inundation scenarios up to three weeks in advance. The system is forced with global satellite derived precipitation products and Numerical Weather Prediction outputs. The modelling chain is based on the "Continuum" hydrological model and risk assessments produced for GAR2015. In combination with existing hydraulically reconditioned SRTM data and 1D hydraulic models, flood scenarios are derived at multiple scales and resolutions. Climate and flood data are shared through a Web GIS integrated platform. First validation of the modelling chain has been conducted through a flood hindcasting test case, over the Chao Phraya river basin in Thailand, using multi temporal satellite-based analysis derived for the exceptional flood event of 2011. In terms of humanitarian relief operations, the EO-based services of flood mapping in rush mode generally suffer from delays caused by the time required for their activation, programming, acquisitions and

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Comparing flood loss models of different complexity

Science.gov (United States)

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.

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

NARCIS (Netherlands)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Flood model for Brazil

Science.gov (United States)

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

High-resolution flood modeling of urban areas using MSN_Flood

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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

Multivariate pluvial flood damage models

International Nuclear Information System (INIS)

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

Multivariate pluvial flood damage models

Energy Technology Data Exchange (ETDEWEB)

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.

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

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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

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

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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.

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

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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.

Flash flood modeling with the MARINE hydrological distributed model

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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�

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

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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

Flood Foresight: A near-real time flood monitoring and forecasting tool for rapid and predictive flood impact assessment

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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

Development of flood index by characterisation of flood hydrographs

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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

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

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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.

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

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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.

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

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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

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

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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.

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

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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.

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

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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.

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

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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.

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

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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.

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

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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.

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

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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

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

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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.

Modeling Compound Flood Hazards in Coastal Embayments

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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

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

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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.

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

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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.

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

Science.gov (United States)

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.

Flood Progression Modelling and Impact Analysis

DEFF Research Database (Denmark)

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...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Challenges of Modeling Flood Risk at Large Scales

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

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.

Urban flood simulation based on the SWMM model

Directory of Open Access Journals (Sweden)

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.

Modeling of Flood Risk for the Continental United States

Science.gov (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

Unstructured mesh adaptivity for urban flooding modelling

Science.gov (United States)

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.

Urban flood return period assessment through rainfall-flood response modelling

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Modeling Wettability Variation during Long-Term Water Flooding

Directory of Open Access Journals (Sweden)

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.

Tracing the value of data for flood loss modelling

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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.

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

NARCIS (Netherlands)

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.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

High-resolution urban flood modelling - a joint probability approach

Science.gov (United States)

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

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

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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.

Flooding and Flood Management

Science.gov (United States)

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.

A Socio-hydrological Flood Model for the Elbe

Science.gov (United States)

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.

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

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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.

Modeling flood events for long-term stability

International Nuclear Information System (INIS)

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

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

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

DEFF Research Database (Denmark)

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...

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Flooding Experiments and Modeling for Improved Reactor Safety

International Nuclear Information System (INIS)

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

Large Scale Flood Risk Analysis using a New Hyper-resolution Population Dataset

Science.gov (United States)

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

2017-12-01

Here we present the first national scale flood risk analyses, using high resolution Facebook Connectivity Lab population data and data from a hyper resolution flood hazard model. In recent years the field of large scale hydraulic modelling has been transformed by new remotely sensed datasets, improved process representation, highly efficient flow algorithms and increases in computational power. These developments have allowed flood risk analysis to be undertaken in previously unmodeled territories and from continental to global scales. Flood risk analyses are typically conducted via the integration of modelled water depths with an exposure dataset. Over large scales and in data poor areas, these exposure data typically take the form of a gridded population dataset, estimating population density using remotely sensed data and/or locally available census data. The local nature of flooding dictates that for robust flood risk analysis to be undertaken both hazard and exposure data should sufficiently resolve local scale features. Global flood frameworks are enabling flood hazard data to produced at 90m resolution, resulting in a mis-match with available population datasets which are typically more coarsely resolved. Moreover, these exposure data are typically focused on urban areas and struggle to represent rural populations. In this study we integrate a new population dataset with a global flood hazard model. The population dataset was produced by the Connectivity Lab at Facebook, providing gridded population data at 5m resolution, representing a resolution increase over previous countrywide data sets of multiple orders of magnitude. Flood risk analysis undertaken over a number of developing countries are presented, along with a comparison of flood risk analyses undertaken using pre-existing population datasets.

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

Science.gov (United States)

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

An Agent-Based Model of Evolving Community Flood Risk.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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/

Top flooding modeling with MAAP4 code

International Nuclear Information System (INIS)

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)

Effects of global warming on floods and droughts in the Caribbean

International Nuclear Information System (INIS)

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)

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

Science.gov (United States)

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

An Approach to Flooding Inundation Combining the Streamflow Prediction Tool (SPT) and Downscaled Soil Moisture

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

Flood characteristics of the Haor area in Bangladesh

Science.gov (United States)

Suman, Asadusjjaman; Bhattacharya, Biswa

2013-04-01

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. Bangladesh is a country, which is frequently suffering from flooding. The current research is conducted in the framework of a project, which focuses on the flooding issues in the Haor region in the north-east of Bangladesh. A haor is a saucer-shaped depression, which is used during the dry period (December to mid-May) for agriculture and as a fishery during the wet period (June-November), and thereby presents a very interesting socio-economic perspective of flood risk management. Pre-monsoon flooding till mid-May causes agricultural loss and lot of distress whereas monsoon flooding brings benefits. The area is bordering India, thereby presenting trans-boundary issues as well, and is fed by some flashy Indian catchments. The area is drained mainly through the Surma-Kushiyara river system. The terrain generally is flat and the flashy characteristics die out within a short distance from the border. Limited studies on the region, particularly with the help of numerical models, have been carried out in the past. Therefore, an objective of the current research was to set up numerical models capable of reasonably emulating the physical system. Such models could, for example, associate different gauges to the spatio-temporal variation of hydrodynamic variables and help in carrying out a systemic study on the impact of climate changes. A 1D2D model, with one-dimensional model for the rivers (based on MIKE 11 modelling tool from Danish Hydraulic Institute) and a two

Hygrothermal modelling of flooding events within historic buildings

NARCIS (Netherlands)

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

Hygrothermal modelling of flooding events within historic buildings

NARCIS (Netherlands)

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

The impact of bathymetry input on flood simulations

Science.gov (United States)

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.

Modelling the interaction between flooding events and economic growth

Science.gov (United States)

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

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

Science.gov (United States)

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.

Modelling dynamic roughness during floods

NARCIS (Netherlands)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Modelling the interaction between flooding events and economic growth

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

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

DEFF Research Database (Denmark)

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...

Hierarchical Modelling of Flood Risk for Engineering Decision Analysis

DEFF Research Database (Denmark)

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...

Numerical modeling techniques for flood analysis

Science.gov (United States)

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.

Surrogate modeling of joint flood risk across coastal watersheds

Science.gov (United States)

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.

The critical role of the routing scheme in simulating peak river discharge in global hydrological models

Science.gov (United States)

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.

Simulated CONUS Flash Flood Climatologies from Distributed Hydrologic Models

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

Determining the Financial Impact of Flood Hazards in Ungaged Basins

Science.gov (United States)

Cotterman, K. A.; Gutenson, J. L.; Pradhan, N. R.; Byrd, A.

2017-12-01

Many portions of the Earth lack adequate authoritative or in situ data that is of great value in determining natural hazard vulnerability from both anthropogenic and physical perspective. Such locations include the majority of developing nations, which do not possess adequate warning systems and protective infrastructure. The lack of warning and protection from natural hazards make these nations vulnerable to the destructive power of events such as floods. The goal of this research is to demonstrate an initial workflow with which to characterize flood financial hazards with global datasets and crowd-sourced, non-authoritative data in ungagged river basins. This workflow includes the hydrologic and hydraulic response of the watershed to precipitation, characterized by the physics-based modeling application Gridded Surface-Subsurface Hydrologic Analysis (GSSHA) model. In addition, data infrastructure and resources are available to approximate the human impact of flooding. Open source, volunteer geographic information (VGI) data can provide global coverage of elements at risk of flooding. Additional valuation mechanisms can then translate flood exposure into percentage and financial damage to each building. The combinations of these tools allow the authors to remotely assess flood hazards with minimal computational, temporal, and financial overhead. This combination of deterministic and stochastic modeling provides the means to quickly characterize watershed flood vulnerability and will allow emergency responders and planners to better understand the implications of flooding, both spatially and financially. In either a planning, real-time, or forecasting scenario, the system will assist the user in understanding basin flood vulnerability and increasing community resiliency and preparedness.

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

Science.gov (United States)

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.

Coastal and river flood risk analyses for guiding economically optimal flood adaptation policies: a country-scale study for Mexico

Science.gov (United States)

Haer, Toon; Botzen, W. J. Wouter; van Roomen, Vincent; Connor, Harry; Zavala-Hidalgo, Jorge; Eilander, Dirk M.; Ward, Philip J.

2018-06-01

Many countries around the world face increasing impacts from flooding due to socio-economic development in flood-prone areas, which may be enhanced in intensity and frequency as a result of climate change. With increasing flood risk, it is becoming more important to be able to assess the costs and benefits of adaptation strategies. To guide the design of such strategies, policy makers need tools to prioritize where adaptation is needed and how much adaptation funds are required. In this country-scale study, we show how flood risk analyses can be used in cost-benefit analyses to prioritize investments in flood adaptation strategies in Mexico under future climate scenarios. Moreover, given the often limited availability of detailed local data for such analyses, we show how state-of-the-art global data and flood risk assessment models can be applied for a detailed assessment of optimal flood-protection strategies. Our results show that especially states along the Gulf of Mexico have considerable economic benefits from investments in adaptation that limit risks from both river and coastal floods, and that increased flood-protection standards are economically beneficial for many Mexican states. We discuss the sensitivity of our results to modelling uncertainties, the transferability of our modelling approach and policy implications. This article is part of the theme issue `Advances in risk assessment for climate change adaptation policy'.

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

Science.gov (United States)

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

Risk-trading in flood management: An economic model.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Technical note: River modelling to infer flood management framework

African Journals Online (AJOL)

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 ...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

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

International Nuclear Information System (INIS)

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

Appropriate modelling of climate change impacts on river flooding

NARCIS (Netherlands)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Improving Flood Damage Assessment Models in Italy

Science.gov (United States)

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.

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

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

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

Science.gov (United States)

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.

Interactive modelling with stakeholders in two cases in flood management

Science.gov (United States)

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

Modeling and simulation of surfactant-polymer flooding using a new hybrid method

Science.gov (United States)

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.

Potential of 3D City Models to assess flood vulnerability

Science.gov (United States)

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

Satellite-based Flood Modeling Using TRMM-based Rainfall Products

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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

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

International Nuclear Information System (INIS)

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

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

Energy Technology Data Exchange (ETDEWEB)

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.

Dissemination of satellite-based river discharge and flood data

Science.gov (United States)

Kettner, A. J.; Brakenridge, G. R.; van Praag, E.; de Groeve, T.; Slayback, D. A.; Cohen, S.

2014-12-01

In collaboration with NASA Goddard Spaceflight Center and the European Commission Joint Research Centre, the Dartmouth Flood Observatory (DFO) daily measures and distributes: 1) river discharges, and 2) near real-time flood extents with a global coverage. Satellite-based passive microwave sensors and hydrological modeling are utilized to establish 'remote-sensing based discharge stations', and observed time series cover 1998 to the present. The advantages over in-situ gauged discharges are: a) easy access to remote or due to political reasons isolated locations, b) relatively low maintenance costs to maintain a continuous observational record, and c) the capability to obtain measurements during floods, hazardous conditions that often impair or destroy in-situ stations. Two MODIS instruments aboard the NASA Terra and Aqua satellites provide global flood extent coverage at a spatial resolution of 250m. Cloud cover hampers flood extent detection; therefore we ingest 6 images (the Terra and Aqua images of each day, for three days), in combination with a cloud shadow filter, to provide daily global flood extent updates. The Flood Observatory has always made it a high priority to visualize and share its data and products through its website. Recent collaborative efforts with e.g. GeoSUR have enhanced accessibility of DFO data. A web map service has been implemented to automatically disseminate geo-referenced flood extent products into client-side GIS software. For example, for Latin America and the Caribbean region, the GeoSUR portal now displays current flood extent maps, which can be integrated and visualized with other relevant geographical data. Furthermore, the flood state of satellite-observed river discharge sites are displayed through the portal as well. Additional efforts include implementing Open Geospatial Consortium (OGC) standards to incorporate Water Markup Language (WaterML) data exchange mechanisms to further facilitate the distribution of the satellite

Mathematical modelling of flooding at Magela Creek

International Nuclear Information System (INIS)

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

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

TWO-DIMENSIONAL MODELLING OF ACCIDENTAL FLOOD WAVES PROPAGATION

OpenAIRE

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...

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

Directory of Open Access Journals (Sweden)

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.

Modeling of reservoir operation in UNH global hydrological model

Science.gov (United States)

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

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

International Nuclear Information System (INIS)

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

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

Science.gov (United States)

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.

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

NARCIS (Netherlands)

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

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

Science.gov (United States)

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

Doubling of coastal flooding frequency within decades due to sea-level rise

Science.gov (United States)

Vitousek, Sean; Barnard, Patrick L.; Fletcher, Charles H.; Frazer, Neil; Erikson, Li; Storlazzi, Curt D.

2017-01-01

Global climate change drives sea-level rise, increasing the frequency of coastal flooding. In most coastal regions, the amount of sea-level rise occurring over years to decades is significantly smaller than normal ocean-level fluctuations caused by tides, waves, and storm surge. However, even gradual sea-level rise can rapidly increase the frequency and severity of coastal flooding. So far, global-scale estimates of increased coastal flooding due to sea-level rise have not considered elevated water levels due to waves, and thus underestimate the potential impact. Here we use extreme value theory to combine sea-level projections with wave, tide, and storm surge models to estimate increases in coastal flooding on a continuous global scale. We find that regions with limited water-level variability, i.e., short-tailed flood-level distributions, located mainly in the Tropics, will experience the largest increases in flooding frequency. The 10 to 20 cm of sea-level rise expected no later than 2050 will more than double the frequency of extreme water-level events in the Tropics, impairing the developing economies of equatorial coastal cities and the habitability of low-lying Pacific island nations.

Doubling of coastal flooding frequency within decades due to sea-level rise.

Science.gov (United States)

Vitousek, Sean; Barnard, Patrick L; Fletcher, Charles H; Frazer, Neil; Erikson, Li; Storlazzi, Curt D

2017-05-18

Global climate change drives sea-level rise, increasing the frequency of coastal flooding. In most coastal regions, the amount of sea-level rise occurring over years to decades is significantly smaller than normal ocean-level fluctuations caused by tides, waves, and storm surge. However, even gradual sea-level rise can rapidly increase the frequency and severity of coastal flooding. So far, global-scale estimates of increased coastal flooding due to sea-level rise have not considered elevated water levels due to waves, and thus underestimate the potential impact. Here we use extreme value theory to combine sea-level projections with wave, tide, and storm surge models to estimate increases in coastal flooding on a continuous global scale. We find that regions with limited water-level variability, i.e., short-tailed flood-level distributions, located mainly in the Tropics, will experience the largest increases in flooding frequency. The 10 to 20 cm of sea-level rise expected no later than 2050 will more than double the frequency of extreme water-level events in the Tropics, impairing the developing economies of equatorial coastal cities and the habitability of low-lying Pacific island nations.

The Generation of a Stochastic Flood Event Catalogue for Continental USA

Science.gov (United States)

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

2017-12-01

Recent advances in the acquisition of spatiotemporal environmental data and improvements in computational capabilities has enabled the generation of large scale, even global, flood hazard layers which serve as a critical decision-making tool for a range of end users. However, these datasets are designed to indicate only the probability and depth of inundation at a given location and are unable to describe the likelihood of concurrent flooding across multiple sites.Recent research has highlighted that although the estimation of large, widespread flood events is of great value to flood mitigation and insurance industries, to date it has been difficult to deal with this spatial dependence structure in flood risk over relatively large scales. Many existing approaches have been restricted to empirical estimates of risk based on historic events, limiting their capability of assessing risk over the full range of plausible scenarios. Therefore, this research utilises a recently developed model-based approach to describe the multisite joint distribution of extreme river flows across continental USA river gauges. Given an extreme event at a site, the model characterises the likelihood neighbouring sites are also impacted. This information is used to simulate an ensemble of plausible synthetic extreme event footprints from which flood depths are extracted from an existing global flood hazard catalogue. Expected economic losses are then estimated by overlaying flood depths with national datasets defining asset locations, characteristics and depth damage functions. The ability of this approach to quantify probabilistic economic risk and rare threshold exceeding events is expected to be of value to those interested in the flood mitigation and insurance sectors.This work describes the methodological steps taken to create the flood loss catalogue over a national scale; highlights the uncertainty in the expected annual economic vulnerability within the USA from extreme river flows

Modelling the interaction between flooding events and economic growth

Directory of Open Access Journals (Sweden)

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.

Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

Directory of Open Access Journals (Sweden)

Jinyin Ye

2016-01-01

Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

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

OpenAIRE

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...

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

Science.gov (United States)

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

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

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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.

An Observation Task Chain Representation Model for Disaster Process-Oriented Remote Sensing Satellite Sensor Planning: A Flood Water Monitoring Application

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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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Modeling natural wetlands: A new global framework built on wetland observations

Science.gov (United States)

Matthews, E.; Romanski, J.; Olefeldt, D.

2015-12-01

Natural wetlands are the world's largest methane (CH4) source, and their distribution and CH4 fluxes are sensitive to interannual and longer-term climate variations. Wetland distributions used in wetland-CH4 models diverge widely, and these geographic differences contribute substantially to large variations in magnitude, seasonality and distribution of modeled methane fluxes. Modeling wetland type and distribution—closely tied to simulating CH4 emissions—is a high priority, particularly for studies of wetlands and CH4 dynamics under past and future climates. Methane-wetland models either prescribe or simulate methane-producing areas (aka wetlands) and both approaches result in predictable over- and under-estimates. 1) Monthly satellite-derived inundation data include flooded areas that are not wetlands (e.g., lakes, reservoirs, and rivers), and do not identify non-flooded wetlands. 2) Models simulating methane-producing areas overwhelmingly rely on modeled soil moisture, systematically over-estimating total global area, with regional over- and under-estimates, while schemes to model soil-moisture typically cannot account for positive water tables (i.e., flooding). Interestingly, while these distinct hydrological approaches to identify wetlands are complementary, merging them does not provide critical data needed to model wetlands for methane studies. We present a new integrated framework for modeling wetlands, and ultimately their methane emissions, that exploits the extensive body of data and information on wetlands. The foundation of the approach is an existing global gridded data set comprising all and only wetlands, including vegetation information. This data set is augmented with data inter alia on climate, inundation dynamics, soil type and soil carbon, permafrost, active-layer depth, growth form, and species composition. We investigate this enhanced wetland data set to identify which variables best explain occurrence and characteristics of observed

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

Simulating Catchment Scale Afforestation for Mitigating Flooding

Science.gov (United States)

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.

Modelling Inland Flood Events for Hazard Maps in Taiwan

Science.gov (United States)

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

Flood routing modelling with Artificial Neural Networks

Directory of Open Access Journals (Sweden)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

TWO-DIMENSIONAL MODELLING OF ACCIDENTAL FLOOD WAVES PROPAGATION

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

DEFF Research Database (Denmark)

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...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Global warming may lead to catastrophic floods in the Himalayas

International Nuclear Information System (INIS)

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

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

NARCIS (Netherlands)

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Internationally coordinated multi-mission planning is now critical to sustain the space-based rainfall observations needed for managing floods globally

International Nuclear Information System (INIS)

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)

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

NARCIS (Netherlands)

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

Flood hazard mapping of Palembang City by using 2D model

Science.gov (United States)

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.

A study of Water flooding modeling for DMFC at cathode channel

International Nuclear Information System (INIS)

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

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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

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

Directory of Open Access Journals (Sweden)

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

Effects of Flood Control Strategies on Flood Resilience Under Sociohydrological Disturbances

Science.gov (United States)

Sung, Kyungmin; Jeong, Hanseok; Sangwan, Nikhil; Yu, David J.

2018-04-01

A community capacity to cope with flood hazards, or community flood resilience, emerges from the interplay of hydrological and social processes. This interplay can be significantly influenced by the flood control strategy adopted by a society, i.e., how a society sets its desired flood protection level and strives to achieve this goal. And this interplay can be further complicated by rising land-sea level differences, seasonal water level fluctuations, and economic change. But not much research has been done on how various forms of flood control strategies affect human-flood interactions under these disturbances and therefore flood resilience in the long run. The current study is an effort to address these issues by developing a conceptual model of human-flood interaction mediated by flood control strategies. Our model extends the existing model of Yu et al. (2017), who investigated the flood resilience of a community-based flood protection system in coastal Bangladesh. The major extensions made in this study are inclusions of various forms of flood control strategies (both adaptive and nonadaptive ones), the challenge of rising land-sea level differences, and various high tide level scenarios generated from modifying the statistical variances and averages. Our results show that adaptive forms of flood control strategies tend to outperform nonadaptive ones for maintaining the model community's flood protection system. Adaptive strategies that dynamically adjust target flood protection levels through close monitoring of flood damages and social memories of flood risk can help the model community deal with various disturbances.

Simulating a 40-year flood event climatology of Australia with a view to ocean-land teleconnections

Science.gov (United States)

Schumann, Guy J.-P.; Andreadis, Konstantinos; Stampoulis, Dimitrios; Bates, Paul

2015-04-01

We develop, for the first time, a proof-of-concept version for a high-resolution global flood inundation model to generate a flood inundation climatology of the past 40 years (1973-2012) for the entire Australian continent at a native 1 km resolution. The objectives of our study includes (1) deriving an inundation climatology for a continent (Australia) as a demonstrator case to understand the requirements for expanding globally; (2) developing a test bed to assess the potential and value of current and future satellite missions (GRACE, SMAP, ICESat-2, AMSR-2, Sentinels and SWOT) in flood monitoring; and (3) answering science questions such as the linking of inundation to ocean circulation teleconnections. We employ the LISFLOOD-FP hydrodynamic model to generate a flood inundation climatology. The model will be built from freely available SRTM-derived data (channel widths, bank heights and floodplain topography corrected for vegetation canopy using ICESat canopy heights). Lakes and reservoirs are represented and channel hydraulics are resolved using actual channel data with bathymetry inferred from hydraulic geometry. Simulations are run with gauged flows and floodplain inundation climatology are compared to observations from GRACE, flood maps from Landsat, SAR, and MODIS. Simulations have been completed for the entire Australian continent. Additionally, changes in flood inundation have been correlated with indices related to global ocean circulation, such as the El Niño Southern Oscillation index. We will produce data layers on flood event climatology and other derived (default) products from the proposed model including channel and floodplain depths, flow direction, velocity vectors, floodplain water volume, shoreline extent and flooded area. These data layers will be in the form of simple vector and raster formats. Since outputs will be large in size we propose to upload them onto Google Earth under the GEE API license.

Development of Probabilistic Flood Inundation Mapping For Flooding Induced by Dam Failure

Science.gov (United States)

Tsai, C.; Yeh, J. J. J.

2017-12-01

A primary function of flood inundation mapping is to forecast flood hazards and assess potential losses. However, uncertainties limit the reliability of inundation hazard assessments. Major sources of uncertainty should be taken into consideration by an optimal flood management strategy. This study focuses on the 20km reach downstream of the Shihmen Reservoir in Taiwan. A dam failure induced flood herein provides the upstream boundary conditions of flood routing. The two major sources of uncertainty that are considered in the hydraulic model and the flood inundation mapping herein are uncertainties in the dam break model and uncertainty of the roughness coefficient. The perturbance moment method is applied to a dam break model and the hydro system model to develop probabilistic flood inundation mapping. Various numbers of uncertain variables can be considered in these models and the variability of outputs can be quantified. The probabilistic flood inundation mapping for dam break induced floods can be developed with consideration of the variability of output using a commonly used HEC-RAS model. Different probabilistic flood inundation mappings are discussed and compared. Probabilistic flood inundation mappings are hoped to provide new physical insights in support of the evaluation of concerning reservoir flooded areas.

A Dynamic Model for Roll Motion of Ships Due to Flooding

DEFF Research Database (Denmark)

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...

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Mapping flood hazards under uncertainty through probabilistic flood inundation maps

Science.gov (United States)

Stephens, T.; Bledsoe, B. P.; Miller, A. J.; Lee, G.

2017-12-01

Changing precipitation, rapid urbanization, and population growth interact to create unprecedented challenges for flood mitigation and management. Standard methods for estimating risk from flood inundation maps generally involve simulations of floodplain hydraulics for an established regulatory discharge of specified frequency. Hydraulic model results are then geospatially mapped and depicted as a discrete boundary of flood extents and a binary representation of the probability of inundation (in or out) that is assumed constant over a project's lifetime. Consequently, existing methods utilized to define flood hazards and assess risk management are hindered by deterministic approaches that assume stationarity in a nonstationary world, failing to account for spatio-temporal variability of climate and land use as they translate to hydraulic models. This presentation outlines novel techniques for portraying flood hazards and the results of multiple flood inundation maps spanning hydroclimatic regions. Flood inundation maps generated through modeling of floodplain hydraulics are probabilistic reflecting uncertainty quantified through Monte-Carlo analyses of model inputs and parameters under current and future scenarios. The likelihood of inundation and range of variability in flood extents resulting from Monte-Carlo simulations are then compared with deterministic evaluations of flood hazards from current regulatory flood hazard maps. By facilitating alternative approaches of portraying flood hazards, the novel techniques described in this presentation can contribute to a shifting paradigm in flood management that acknowledges the inherent uncertainty in model estimates and the nonstationary behavior of land use and climate.

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

DEFF Research Database (Denmark)

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...

Floods and droughts: friends or foes?

Science.gov (United States)

Prudhomme, Christel

2017-04-01

Water hazards are some of the biggest threats to lives and livelihoods globally, causing serious damages to society and infrastructure. But floods and droughts are an essential part of the hydrological regime that ensures fundamental ecosystem functions, providing natural ways to bring in nutrients, flush out pollutants and enabling soils, rivers and lakes natural biodiversity to thrive. Traditionally, floods and droughts are too often considered separately, with scientific advance in process understanding, modelling, statistical characterisation and impact assessment are often done independently, possibly delaying the development of innovative methods that could be applied to both. This talk will review some of the key characteristics of floods and droughts, highlighting differences and commonalties, losses and benefits, with the aim of identifying future key research challenges faced by both current and next generation of hydrologists.

Modeling urban flood risk territories for Riga city

Science.gov (United States)

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

Urban flood return period assessment through rainfall-flood response modelling

DEFF Research Database (Denmark)

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...

Extreme weather: Subtropical floods and tropical cyclones

Science.gov (United States)

Shaevitz, Daniel A.

Extreme weather events have a large effect on society. As such, it is important to understand these events and to project how they may change in a future, warmer climate. The aim of this thesis is to develop a deeper understanding of two types of extreme weather events: subtropical floods and tropical cyclones (TCs). In the subtropics, the latitude is high enough that quasi-geostrophic dynamics are at least qualitatively relevant, while low enough that moisture may be abundant and convection strong. Extratropical extreme precipitation events are usually associated with large-scale flow disturbances, strong ascent, and large latent heat release. In the first part of this thesis, I examine the possible triggering of convection by the large-scale dynamics and investigate the coupling between the two. Specifically two examples of extreme precipitation events in the subtropics are analyzed, the 2010 and 2014 floods of India and Pakistan and the 2015 flood of Texas and Oklahoma. I invert the quasi-geostrophic omega equation to decompose the large-scale vertical motion profile to components due to synoptic forcing and diabatic heating. Additionally, I present model results from within the Column Quasi-Geostrophic framework. A single column model and cloud-revolving model are forced with the large-scale forcings (other than large-scale vertical motion) computed from the quasi-geostrophic omega equation with input data from a reanalysis data set, and the large-scale vertical motion is diagnosed interactively with the simulated convection. It is found that convection was triggered primarily by mechanically forced orographic ascent over the Himalayas during the India/Pakistan flood and by upper-level Potential Vorticity disturbances during the Texas/Oklahoma flood. Furthermore, a climate attribution analysis was conducted for the Texas/Oklahoma flood and it is found that anthropogenic climate change was responsible for a small amount of rainfall during the event but the

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

Science.gov (United States)

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.

A Robust Response of Precipitation to Global Warming from CMIP5 Models

Science.gov (United States)

Lau, K. -M.; Wu, H. -T.; Kim, K. -M.

2012-01-01

How precipitation responds to global warming is a major concern to society and a challenge to climate change research. Based on analyses of rainfall probability distribution functions of 14 state-of-the-art climate models, we find a robust, canonical global rainfall response to a triple CO2 warming scenario, featuring 100 250% more heavy rain, 5-10% less moderate rain, and 10-15% more very light or no-rain events. Regionally, a majority of the models project a consistent response with more heavy rain events over climatologically wet regions of the deep tropics, and more dry events over subtropical and tropical land areas. Results suggest that increased CO2 emissions induce basic structural changes in global rain systems, increasing risks of severe floods and droughts in preferred geographic locations worldwide.

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

Directory of Open Access Journals (Sweden)

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.

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Development of a hydraulic model and flood-inundation maps for the Wabash River near the Interstate 64 Bridge near Grayville, Illinois

Science.gov (United States)

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

Prospects and requirements for an operational modelling unit in flood crisis situations

Directory of Open Access Journals (Sweden)

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.

Combining Empirical and Stochastic Models for Extreme Floods Estimation

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Flood modelling : Parameterisation and inflow uncertainty

NARCIS (Netherlands)

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

Assessment of the potential forecasting skill of a global hydrological model in reproducing the occurrence of monthly flow extremes

Directory of Open Access Journals (Sweden)

N. Candogan Yossef

2012-11-01

Full Text Available As an initial step in assessing the prospect of using global hydrological models (GHMs for hydrological forecasting, this study investigates the skill of the GHM PCR-GLOBWB in reproducing the occurrence of past extremes in monthly discharge on a global scale. Global terrestrial hydrology from 1958 until 2001 is simulated by forcing PCR-GLOBWB with daily meteorological data obtained by downscaling the CRU dataset to daily fields using the ERA-40 reanalysis. Simulated discharge values are compared with observed monthly streamflow records for a selection of 20 large river basins that represent all continents and a wide range of climatic zones.

We assess model skill in three ways all of which contribute different information on the potential forecasting skill of a GHM. First, the general skill of the model in reproducing hydrographs is evaluated. Second, model skill in reproducing significantly higher and lower flows than the monthly normals is assessed in terms of skill scores used for forecasts of categorical events. Third, model skill in reproducing flood and drought events is assessed by constructing binary contingency tables for floods and droughts for each basin. The skill is then compared to that of a simple estimation of discharge from the water balance (P−E.

The results show that the model has skill in all three types of assessments. After bias correction the model skill in simulating hydrographs is improved considerably. For most basins it is higher than that of the climatology. The skill is highest in reproducing monthly anomalies. The model also has skill in reproducing floods and droughts, with a markedly higher skill in floods. The model skill far exceeds that of the water balance estimate. We conclude that the prospect for using PCR-GLOBWB for monthly and seasonal forecasting of the occurrence of hydrological extremes is positive. We argue that this conclusion applies equally to other similar GHMs and

Exploitation of Documented Historical Floods for Achieving Better Flood Defense

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Slobodan Kolaković

2016-01-01

Full Text Available Establishing Base Flood Elevation for a stream network corresponding to a big catchment is feasible by interdisciplinary approach, involving stochastic hydrology, river hydraulics, and computer aided simulations. A numerical model calibrated by historical floods has been exploited in this study. The short presentation of the catchment of the Tisza River in this paper is followed by the overview of historical floods which hit the region in the documented period of 130 years. Several well documented historical floods provided opportunity for the calibration of the chosen numerical model. Once established, the model could be used for investigation of different extreme flood scenarios and to establish the Base Flood Elevation. The calibration has shown that the coefficient of friction in case of the Tisza River is dependent both on the actual water level and on the preceding flood events. The effect of flood plain maintenance as well as the activation of six potential detention ponds on flood mitigation has been examined. Furthermore, the expected maximum water levels have also been determined for the case if the ever observed biggest 1888 flood hit the region again. The investigated cases of flood superposition highlighted the impact of tributary Maros on flood mitigation along the Tisza River.

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

African Journals Online (AJOL)

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 ...

Developing Fast and Reliable Flood Models

DEFF Research Database (Denmark)

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....

Quasi-continuous stochastic simulation framework for flood modelling

Science.gov (United States)

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.

Multi-model ensembles for assessment of flood losses and associated uncertainty

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Modeling multi-source flooding disaster and developing simulation framework in Delta

Science.gov (United States)

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.

Recent advances in flood forecasting and flood risk assessment

Directory of Open Access Journals (Sweden)

G. Arduino

2005-01-01

Full Text Available Recent large floods in Europe have led to increased interest in research and development of flood forecasting systems. Some of these events have been provoked by some of the wettest rainfall periods on record which has led to speculation that such extremes are attributable in some measure to anthropogenic global warming and represent the beginning of a period of higher flood frequency. Whilst current trends in extreme event statistics will be difficult to discern, conclusively, there has been a substantial increase in the frequency of high floods in the 20th century for basins greater than 2x105 km2. There is also increasing that anthropogenic forcing of climate change may lead to an increased probability of extreme precipitation and, hence, of flooding. There is, therefore, major emphasis on the improvement of operational flood forecasting systems in Europe, with significant European Community spending on research and development on prototype forecasting systems and flood risk management projects. This Special Issue synthesises the most relevant scientific and technological results presented at the International Conference on Flood Forecasting in Europe held in Rotterdam from 3-5 March 2003. During that meeting 150 scientists, forecasters and stakeholders from four continents assembled to present their work and current operational best practice and to discuss future directions of scientific and technological efforts in flood prediction and prevention. The papers presented at the conference fall into seven themes, as follows.

Study of flood defense structural measures priorities using Compromise Programming technique

Science.gov (United States)

Lim, D.; Jeong, S.

2017-12-01

Recent climate change of global warming has led to the frequent occurrence of heavy regional rainfalls. As such, inundation vulnerability increases in urban areas with high population density due to the low runoff carrying capacity. This study selects a sample area (Janghang-eup, the Republic of Korea), which is one of the most vulnerable areas to flooding, analyzing the urban flood runoff model (XP-SWMM) and using the MCDM (Multi-Criteria Decision Making) technique to establish flood protection structural measures. To this end, we compare the alternatives and choose the optimal flood defense measure: our model is utilized with three flood prevention structural measures; (i) drainage pipe construction; (ii) water detention; and (iii) flood pumping station. Dividing the target area into three small basins, we propose flood evaluations for an inundation decrease by studying the flooded area, the maximum inundation depth, the damaged residential area, and the construction cost. In addition, Compromise Programming determines the priority of the alternatives. As a consequent, this study suggests flood pumping station for Zone 1 and drainage pipe construction for Zone 2 and Zone 3, respectively, as the optimal flood defense alternative. Keywords : MCDM; Compromise Programming; Urban Flood Prevention; This research was supported by a grant [MPSS-DP-2013-62] through the Disaster and Safety Management Institute funded by Ministry of Public Safety and Security of Korean government.

Discover Floods Educators Guide

Science.gov (United States)

Project WET Foundation, 2009

2009-01-01

Now available as a Download! This valuable resource helps educators teach students about both the risks and benefits of flooding through a series of engaging, hands-on activities. Acknowledging the different roles that floods play in both natural and urban communities, the book helps young people gain a global understanding of this common--and…

The economic costs of natural disasters globally from 1900-2015: historical and normalised floods, storms, earthquakes, volcanoes, bushfires, drought and other disasters

Science.gov (United States)

Daniell, James; Wenzel, Friedemann; Schaefer, Andreas

2016-04-01

For the first time, a breakdown of natural disaster losses from 1900-2015 based on over 30,000 event economic losses globally is given based on increased analysis within the CATDAT Damaging Natural Disaster databases. Using country-CPI and GDP deflator adjustments, over 7 trillion (2015-adjusted) in losses have occurred; over 40% due to flood/rainfall, 26% due to earthquake, 19% due to storm effects, 12% due to drought, 2% due to wildfire and under 1% due to volcano. Using construction cost indices, higher percentages of flood losses are seen. Depending on how the adjustment of dollars are made to 2015 terms (CPI vs. construction cost indices), between 6.5 and 14.0 trillion USD (2015-adjusted) of natural disaster losses have been seen from 1900-2015 globally. Significant reductions in economic losses have been seen in China and Japan from 1950 onwards. An AAL of around 200 billion in the last 16 years has been seen equating to around 0.25% of Global GDP or around 0.1% of Net Capital Stock per year. Normalised losses have also been calculated to examine the trends in vulnerability through time for economic losses. The normalisation methodology globally using the exposure databases within CATDAT that were undertaken previously in papers for the earthquake and volcano databases, are used for this study. The original event year losses are adjusted directly by capital stock change, very high losses are observed with respect to floods over time (however with improved flood control structures). This shows clear trends in the improvement of building stock towards natural disasters and a decreasing trend in most perils for most countries.

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

Science.gov (United States)

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

A Review of Flood Loss Models as Basis for Harmonization and Benchmarking.

Directory of Open Access Journals (Sweden)

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

A Review of Flood Loss Models as Basis for Harmonization and Benchmarking.

Science.gov (United States)

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

A Review of Flood Loss Models as Basis for Harmonization and Benchmarking

Science.gov (United States)

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

Improving a DSM Obtained by Unmanned Aerial Vehicles for Flood Modelling

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

New mechanism under International Flood Initiative toward robustness for flood management in the Asia Pacific region

Science.gov (United States)

Murase, M.; Yoshitani, J.; Takeuchi, K.; Koike, T.

2015-12-01

Climate change is likely to result in increases in the frequency or intensity of extreme weather events. It is imperative that a good understanding is developed of how climate change affects the events that are reflected in hydrological extremes such as floods and how practitioners in water resources management deal with them. Since there is still major uncertainty as to how the impact of climate change affect actual water resources management, it is important to build robustness into management schemes and communities. Flood management under such variety of uncertainty favors the flexible and adaptive implementation both in top-down and bottom-up approaches. The former uses projections of global or spatially downscaled models to drive resource models and project resource impacts. The latter utilizes policy or planning tools to identify what changes in climate would be most threatening to their long-range operations. Especially for the bottom-up approaches, it is essential to identify the gap between what should be done and what has not been achieved for disaster risks. Indicators or index are appropriate tools to measure such gaps, but they are still in progress to cover the whole world. The International Flood Initiative (IFI), initiated in January 2005 by UNESCO and WMO in close cooperation with UNU and ISDR, IAHS and IAHR, has promoted an integrated approach to flood management to take advantage of floods and use of flood plains while reducing the social, environmental and economic risks. Its secretariat is located in ICHARM. The initiative objective is to support national platforms to practice evidence-based disaster risk reduction through mobilizing scientific and research networks at national, regional and international levels. The initiative is now preparing for a new mechanism to facilitate the integrated approach for flood management on the ground regionally in the Asia Pacific (IFI-AP) through monitoring, assessment and capacity building.

Towards a Flood Severity Index

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Kettner, A.; Chong, A.; Prades, L.; Brakenridge, G. R.; Muir, S.; Amparore, A.; Slayback, D. A.; Poungprom, R.

2017-12-01

Flooding is the most common natural hazard worldwide, affecting 21 million people every year. In the immediate moments following a flood event, humanitarian actors like the World Food Program need to make rapid decisions ( 72 hrs) on how to prioritize affected areas impacted by such an event. For other natural disasters like hurricanes/cyclones and earthquakes, there are industry-recognized standards on how the impacted areas are to be classified. Shake maps, quantifying peak ground motion, from for example the US Geological Survey are widely used for assessing earthquakes. Similarly, cyclones are tracked by Joint Typhoon Warning Center (JTWC) and Global Disaster Alert and Coordination System (GDACS) who release storm nodes and tracks (forecasted and actual), with wind buffers and classify the event according to the Saffir-Simpson Hurricane Wind Scale. For floods, the community is usually able to acquire unclassified data of the flood extent as identified from satellite imagery. Most often no water discharge hydrograph is available to classify the event into recurrence intervals simply because there is no gauging station, or the gauging station was unable to record the maximum discharge due to overtopping or flood damage. So, the question remains: How do we methodically turn a flooded area into classified areas of different gradations of impact? Here, we present a first approach towards developing a global applicable flood severity index. The flood severity index is set up such that it considers relatively easily obtainable physical parameters in a short period of time like: flood frequency (relating the current flood to historical events) and magnitude, as well as land cover, slope, and where available pre-event simulated flood depth. The scale includes categories ranging from very minor flooding to catastrophic flooding. We test and evaluate the postulated classification scheme against a set of past flood events. Once a severity category is determined, socio

Estimation of antecedent wetness conditions for flood modelling in northern Morocco

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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.

Analysis of coastal protection under rising flood risk

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Megan J. Lickley

2014-01-01

Full Text Available Infrastructure located along the U.S. Atlantic and Gulf coasts is exposed to rising risk of flooding from sea level rise, increasing storm surge, and subsidence. In these circumstances coastal management commonly based on 100-year flood maps assuming current climatology is no longer adequate. A dynamic programming cost–benefit analysis is applied to the adaptation decision, illustrated by application to an energy facility in Galveston Bay. Projections of several global climate models provide inputs to estimates of the change in hurricane and storm surge activity as well as the increase in sea level. The projected rise in physical flood risk is combined with estimates of flood damage and protection costs in an analysis of the multi-period nature of adaptation choice. The result is a planning method, using dynamic programming, which is appropriate for investment and abandonment decisions under rising coastal risk.

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

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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.

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

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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.

Floods and human health: a systematic review.

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Alderman, Katarzyna; Turner, Lyle R; Tong, Shilu

2012-10-15

Floods are the most common type of disaster globally, responsible for almost 53,000 deaths in the last decade alone (23:1 low- versus high-income countries). This review assessed recent epidemiological evidence on the impacts of floods on human health. Published articles (2004-2011) on the quantitative relationship between floods and health were systematically reviewed. 35 relevant epidemiological studies were identified. Health outcomes were categorized into short- and long-term and were found to depend on the flood characteristics and people's vulnerability. It was found that long-term health effects are currently not well understood. Mortality rates were found to increase by up to 50% in the first year post-flood. After floods, it was found there is an increased risk of disease outbreaks such as hepatitis E, gastrointestinal disease and leptospirosis, particularly in areas with poor hygiene and displaced populations. Psychological distress in survivors (prevalence 8.6% to 53% two years post-flood) can also exacerbate their physical illness. There is a need for effective policies to reduce and prevent flood-related morbidity and mortality. Such steps are contingent upon the improved understanding of potential health impacts of floods. Global trends in urbanization, burden of disease, malnutrition and maternal and child health must be better reflected in flood preparedness and mitigation programs. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.

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

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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

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

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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.

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

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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