A Probabilistic Analysis of Surface Water Flood Risk in London.

PubMed

Jenkins, Katie; Hall, Jim; Glenis, Vassilis; Kilsby, Chris

2018-06-01

Flooding in urban areas during heavy rainfall, often characterized by short duration and high-intensity events, is known as "surface water flooding." Analyzing surface water flood risk is complex as it requires understanding of biophysical and human factors, such as the localized scale and nature of heavy precipitation events, characteristics of the urban area affected (including detailed topography and drainage networks), and the spatial distribution of economic and social vulnerability. Climate change is recognized as having the potential to enhance the intensity and frequency of heavy rainfall events. This study develops a methodology to link high spatial resolution probabilistic projections of hourly precipitation with detailed surface water flood depth maps and characterization of urban vulnerability to estimate surface water flood risk. It incorporates probabilistic information on the range of uncertainties in future precipitation in a changing climate. The method is applied to a case study of Greater London and highlights that both the frequency and spatial extent of surface water flood events are set to increase under future climate change. The expected annual damage from surface water flooding is estimated to be to be £171 million, £343 million, and £390 million/year under the baseline, 2030 high, and 2050 high climate change scenarios, respectively. © 2017 Society for Risk Analysis.

Probabilistic flood damage modelling at the meso-scale

NASA Astrophysics Data System (ADS)

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.

Probabilistic Design Storm Method for Improved Flood Estimation in Ungauged Catchments

NASA Astrophysics Data System (ADS)

Berk, Mario; Å pačková, Olga; Straub, Daniel

2017-12-01

The design storm approach with event-based rainfall-runoff models is a standard method for design flood estimation in ungauged catchments. The approach is conceptually simple and computationally inexpensive, but the underlying assumptions can lead to flawed design flood estimations. In particular, the implied average recurrence interval (ARI) neutrality between rainfall and runoff neglects uncertainty in other important parameters, leading to an underestimation of design floods. The selection of a single representative critical rainfall duration in the analysis leads to an additional underestimation of design floods. One way to overcome these nonconservative approximations is the use of a continuous rainfall-runoff model, which is associated with significant computational cost and requires rainfall input data that are often not readily available. As an alternative, we propose a novel Probabilistic Design Storm method that combines event-based flood modeling with basic probabilistic models and concepts from reliability analysis, in particular the First-Order Reliability Method (FORM). The proposed methodology overcomes the limitations of the standard design storm approach, while utilizing the same input information and models without excessive computational effort. Additionally, the Probabilistic Design Storm method allows deriving so-called design charts, which summarize representative design storm events (combinations of rainfall intensity and other relevant parameters) for floods with different return periods. These can be used to study the relationship between rainfall and runoff return periods. We demonstrate, investigate, and validate the method by means of an example catchment located in the Bavarian Pre-Alps, in combination with a simple hydrological model commonly used in practice.

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

PubMed

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.

Proceedings, Seminar on Probabilistic Methods in Geotechnical Engineering

NASA Astrophysics Data System (ADS)

Hynes-Griffin, M. E.; Buege, L. L.

1983-09-01

Contents: Applications of Probabilistic Methods in Geotechnical Engineering; Probabilistic Seismic and Geotechnical Evaluation at a Dam Site; Probabilistic Slope Stability Methodology; Probability of Liquefaction in a 3-D Soil Deposit; Probabilistic Design of Flood Levees; Probabilistic and Statistical Methods for Determining Rock Mass Deformability Beneath Foundations: An Overview; Simple Statistical Methodology for Evaluating Rock Mechanics Exploration Data; New Developments in Statistical Techniques for Analyzing Rock Slope Stability.

A fluvial and pluvial probabilistic flood hazard analysis for Can Tho city, Vietnam

NASA Astrophysics Data System (ADS)

Apel, Heiko; Martinez, Oriol; Thi Chinh, Do; Viet Dung, Nguyen

2014-05-01

Can Tho city is the largest city and the economic heart of the Mekong Delta, Vietnam. Due to its economic importance and envisaged development goals the city grew rapidly in population size and extend over the last two decades. Large parts of the city are located in flood prone areas, and also the central parts of the city recently experienced an increasing number of flood events, both of fluvial and pluvial nature. As the economic power and asset values are constantly increasing, this poses a considerable risk for the city. The the aim of this study is to perform a flood hazard analysis considering both fluvial and pluvial floods and to derive probabilistic flood hazard maps. This requires in a first step an understanding of the typical flood mechanisms. Fluvial floods are triggered by a coincidence of high water levels during the annual flood period in the Mekong Delta with high tidal levels, which cause in combination short term inundations in Can Tho. Pluvial floods are triggered by typical tropical convective rain storms during the monsoon season. These two flood pathways are essentially independent in its sources and can thus be treated in the hazard analysis accordingly. For the fluvial hazard analysis we propose a bivariate frequency analysis of the Mekong flood characteristics, the annual maximum flood discharge Q and the annual flood volume V at the upper boundary of the Mekong Delta, the gauging station Kratie. This defines probabilities of exceedance of different Q-V pairs, which are transferred into synthetic flood hydrographs. The synthetic hydrographs are routed through a quasi-2D hydrodynamic model of the entire Mekong Delta in order to provide boundary conditions for a detailed hazard mapping of Can Tho. This downscaling step is necessary, because the huge complexity of the river and channel network does not allow for a proper definition of boundary conditions for Can Tho city by gauge data alone. In addition the available gauge data around Can Tho are too short for a meaningful frequency analysis. The detailed hazard mapping is performed by a 2D hydrodynamic model for Can Tho city. As the scenarios are derived in a Monte-Carlo framework, the final flood hazard maps are probabilistic, i.e. show the median flood hazard along with uncertainty estimates for each defined level of probabilities of exceedance. For the pluvial flood hazard a frequency analysis of the hourly rain gauge data of Can Tho is performed implementing a peak-over-threshold procedure. Based on this frequency analysis synthetic rains storms are generated in a Monte-Carlo framework for the same probabilities of exceedance as in the fluvial flood hazard analysis. Probabilistic flood hazard maps were then generated with the same 2D hydrodynamic model for the city. In a last step the fluvial and pluvial scenarios are combined assuming independence of the events. These scenarios were also transferred into hazard maps by the 2D hydrodynamic model finally yielding combined fluvial-pluvial probabilistic flood hazard maps for Can Tho. The derived set of maps may be used for an improved city planning or a flood risk analysis.

Enhancing Flood Prediction Reliability Using Bayesian Model Averaging

NASA Astrophysics Data System (ADS)

Liu, Z.; Merwade, V.

2017-12-01

Uncertainty analysis is an indispensable part of modeling the hydrology and hydrodynamics of non-idealized environmental systems. Compared to reliance on prediction from one model simulation, using on ensemble of predictions that consider uncertainty from different sources is more reliable. In this study, Bayesian model averaging (BMA) is applied to Black River watershed in Arkansas and Missouri by combining multi-model simulations to get reliable deterministic water stage and probabilistic inundation extent predictions. The simulation ensemble is generated from 81 LISFLOOD-FP subgrid model configurations that include uncertainty from channel shape, channel width, channel roughness and discharge. Model simulation outputs are trained with observed water stage data during one flood event, and BMA prediction ability is validated for another flood event. Results from this study indicate that BMA does not always outperform all members in the ensemble, but it provides relatively robust deterministic flood stage predictions across the basin. Station based BMA (BMA_S) water stage prediction has better performance than global based BMA (BMA_G) prediction which is superior to the ensemble mean prediction. Additionally, high-frequency flood inundation extent (probability greater than 60%) in BMA_G probabilistic map is more accurate than the probabilistic flood inundation extent based on equal weights.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Against all odds -- Probabilistic forecasts and decision making

NASA Astrophysics Data System (ADS)

Liechti, Katharina; Zappa, Massimiliano

2015-04-01

In the city of Zurich (Switzerland) the setting is such that the damage potential due to flooding of the river Sihl is estimated to about 5 billion US dollars. The flood forecasting system that is used by the administration for decision making runs continuously since 2007. It has a time horizon of max. five days and operates at hourly time steps. The flood forecasting system includes three different model chains. Two of those are run by the deterministic NWP models COSMO-2 and COSMO-7 and one is driven by the probabilistic NWP COSMO-Leps. The model chains are consistent since February 2010, so five full years are available for the evaluation for the system. The system was evaluated continuously and is a very nice example to present the added value that lies in probabilistic forecasts. The forecasts are available on an online-platform to the decision makers. Several graphical representations of the forecasts and forecast-history are available to support decision making and to rate the current situation. The communication between forecasters and decision-makers is quite close. To put it short, an ideal situation. However, an event or better put a non-event in summer 2014 showed that the knowledge about the general superiority of probabilistic forecasts doesn't necessarily mean that the decisions taken in a specific situation will be based on that probabilistic forecast. Some years of experience allow gaining confidence in the system, both for the forecasters and for the decision-makers. Even if from the theoretical point of view the handling during crisis situation is well designed, a first event demonstrated that the dialog with the decision-makers still lacks of exercise during such situations. We argue, that a false alarm is a needed experience to consolidate real-time emergency procedures relying on ensemble predictions. A missed event would probably also fit, but, in our case, we are very happy not to report about this option.

Future Impacts of Hydroelectric Power Development on Methylmercury Exposures of Canadian Indigenous Communities.

PubMed

Calder, Ryan S D; Schartup, Amina T; Li, Miling; Valberg, Amelia P; Balcom, Prentiss H; Sunderland, Elsie M

2016-12-06

Developing Canadian hydroelectric resources is a key component of North American plans for meeting future energy demands. Microbial production of the bioaccumulative neurotoxin methylmercury (MeHg) is stimulated in newly flooded soils by degradation of labile organic carbon and associated changes in geochemical conditions. We find all 22 Canadian hydroelectric facilities being considered for near-term development are located within 100 km of indigenous communities. For a facility in Labrador, Canada (Muskrat Falls) with planned completion in 2017, we probabilistically modeled peak MeHg enrichment relative to measured baseline conditions in the river to be impounded, downstream estuary, locally harvested fish, birds and seals, and three Inuit communities. Results show a projected 10-fold increase in riverine MeHg levels and a 2.6-fold increase in estuarine surface waters. MeHg concentrations in locally caught species increase 1.3 to 10-fold depending on time spent foraging in different environments. Mean Inuit MeHg exposure is forecasted to double following flooding and over half of the women of childbearing age and young children in the most northern community are projected to exceed the U.S. EPA's reference dose. Equal or greater aqueous MeHg concentrations relative to Muskrat Falls are forecasted for 11 sites across Canada, suggesting the need for mitigation measures prior to flooding.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Curtis L.; Prescott, Steven; Coleman, Justin

This report describes the current progress and status related to the Industry Application #2 focusing on External Hazards. For this industry application within the Light Water Reactor Sustainability (LWRS) Program Risk-Informed Safety Margin Characterization (RISMC) R&D Pathway, we will create the Risk-Informed Margin Management (RIMM) approach to represent meaningful (i.e., realistic facility representation) event scenarios and consequences by using an advanced 3D facility representation that will evaluate external hazards such as flooding and earthquakes in order to identify, model and analyze the appropriate physics that needs to be included to determine plant vulnerabilities related to external events; manage the communicationmore » and interactions between different physics modeling and analysis technologies; and develop the computational infrastructure through tools related to plant representation, scenario depiction, and physics prediction. One of the unique aspects of the RISMC approach is how it couples probabilistic approaches (the scenario) with mechanistic phenomena representation (the physics) through simulation. This simulation-based modeling allows decision makers to focus on a variety of safety, performance, or economic metrics. In this report, we describe the evaluation of various physics toolkits related to flooding representation. Ultimately, we will be coupling the flooding representation with other events such as earthquakes in order to provide coupled physics analysis for scenarios where interactions exist.« less

Future trends in flood risk in Indonesia - A probabilistic approach

NASA Astrophysics Data System (ADS)

Muis, Sanne; Guneralp, Burak; Jongman, Brenden; Ward, Philip

2014-05-01

Indonesia is one of the 10 most populous countries in the world and is highly vulnerable to (river) flooding. Catastrophic floods occur on a regular basis; total estimated damages were US 0.8 bn in 2010 and US 3 bn in 2013. Large parts of Greater Jakarta, the capital city, are annually subject to flooding. Flood risks (i.e. the product of hazard, exposure and vulnerability) are increasing due to rapid increases in exposure, such as strong population growth and ongoing economic development. The increase in risk may also be amplified by increasing flood hazards, such as increasing flood frequency and intensity due to climate change and land subsidence. The implementation of adaptation measures, such as the construction of dykes and strategic urban planning, may counteract these increasing trends. However, despite its importance for adaptation planning, a comprehensive assessment of current and future flood risk in Indonesia is lacking. This contribution addresses this issue and aims to provide insight into how socio-economic trends and climate change projections may shape future flood risks in Indonesia. Flood risk were calculated using an adapted version of the GLOFRIS global flood risk assessment model. Using this approach, we produced probabilistic maps of flood risks (i.e. annual expected damage) at a resolution of 30"x30" (ca. 1km x 1km at the equator). To represent flood exposure, we produced probabilistic projections of urban growth in a Monte-Carlo fashion based on probability density functions of projected population and GDP values for 2030. To represent flood hazard, inundation maps were computed using the hydrological-hydraulic component of GLOFRIS. These maps show flood inundation extent and depth for several return periods and were produced for several combinations of GCMs and future socioeconomic scenarios. Finally, the implementation of different adaptation strategies was incorporated into the model to explore to what extent adaptation may be able to decrease future risks. Preliminary results show that the urban extent in Indonesia is projected to increase within 211 to 351% over the period 2000-2030 (5 and 95 percentile). Mainly driven by this rapid urbanization, potential flood losses in Indonesia increase rapidly and are primarily concentrated on the island of Java. The results reveal the large risk-reducing potential of adaptation measures. Since much of the urban development between 2000 and 2030 takes place in flood-prone areas, strategic urban planning (i.e. building in safe areas) may significantly reduce the urban population and infrastructure exposed to flooding. We conclude that a probabilistic risk approach in future flood risk assessment is vital; the drivers behind risk trends (exposure, hazard, vulnerability) should be understood to develop robust and efficient adaptation pathways.

Analysis of flood hazard under consideration of dike breaches

NASA Astrophysics Data System (ADS)

Vorogushyn, S.; Apel, H.; Lindenschmidt, K.-E.; Merz, B.

2009-04-01

The study focuses on the development and application of a new modelling system which allows a comprehensive flood hazard assessment along diked river reaches under consideration of dike failures. The proposed Inundation Hazard Assessment Model (IHAM) represents a hybrid probabilistic-deterministic model. It comprises three models interactively coupled at runtime. These are: (1) 1D unsteady hydrodynamic model of river channel and floodplain flow between dikes, (2) probabilistic dike breach model which determines possible dike breach locations, breach widths and breach outflow discharges, and (3) 2D raster-based diffusion wave storage cell model of the hinterland areas behind the dikes. Due to the unsteady nature of the 1D and 2D coupled models, the dependence between hydraulic load at various locations along the reach is explicitly considered. The probabilistic dike breach model describes dike failures due to three failure mechanisms: overtopping, piping and slope instability caused by the seepage flow through the dike core (micro-instability). Dike failures for each mechanism are simulated based on fragility functions. The probability of breach is conditioned by the uncertainty in geometrical and geotechnical dike parameters. The 2D storage cell model driven by the breach outflow boundary conditions computes an extended spectrum of flood intensity indicators such as water depth, flow velocity, impulse, inundation duration and rate of water rise. IHAM is embedded in a Monte Carlo simulation in order to account for the natural variability of the flood generation processes reflected in the form of input hydrographs and for the randomness of dike failures given by breach locations, times and widths. The scenario calculations for the developed synthetic input hydrographs for the main river and tributary were carried out for floods with return periods of T = 100; 200; 500; 1000 a. Based on the modelling results, probabilistic dike hazard maps could be generated that indicate the failure probability of each discretised dike section for every scenario magnitude. Besides the binary inundation patterns that indicate the probability of raster cells being inundated, IHAM generates probabilistic flood hazard maps. These maps display spatial patterns of the considered flood intensity indicators and their associated return periods. The probabilistic nature of IHAM allows for the generation of percentile flood hazard maps that indicate the median and uncertainty bounds of the flood intensity indicators. The uncertainty results from the natural variability of the flow hydrographs and randomness of dike breach processes. The same uncertainty sources determine the uncertainty in the flow hydrographs along the study reach. The simulations showed that the dike breach stochasticity has an increasing impact on hydrograph uncertainty in downstream direction. Whereas in the upstream part of the reach the hydrograph uncertainty is mainly stipulated by the variability of the flood wave form, the dike failures strongly shape the uncertainty boundaries in the downstream part of the reach. Finally, scenarios of polder deployment for the extreme floods with T = 200; 500; 1000 a were simulated with IHAM. The results indicate a rather weak reduction of the mean and median flow hydrographs in the river channel. However, the capping of the flow peaks resulted in a considerable reduction of the overtopping failures downstream of the polder with a simultaneous slight increase of the piping and slope micro-instability frequencies explained by a more durable average impoundment. The developed IHAM simulation system represents a new scientific tool for studying fluvial inundation dynamics under extreme conditions incorporating effects of technical flood protection measures. With its major outputs in form of novel probabilistic inundation and dike hazard maps, the IHAM system has a high practical value for decision support in flood management.

Probabilistic modelling of flood events using the entropy copula

NASA Astrophysics Data System (ADS)

Li, Fan; Zheng, Qian

2016-11-01

The estimation of flood frequency is vital for the flood control strategies and hydraulic structure design. Generating synthetic flood events according to statistical properties of observations is one of plausible methods to analyze the flood frequency. Due to the statistical dependence among the flood event variables (i.e. the flood peak, volume and duration), a multidimensional joint probability estimation is required. Recently, the copula method is widely used for multivariable dependent structure construction, however, the copula family should be chosen before application and the choice process is sometimes rather subjective. The entropy copula, a new copula family, employed in this research proposed a way to avoid the relatively subjective process by combining the theories of copula and entropy. The analysis shows the effectiveness of the entropy copula for probabilistic modelling the flood events of two hydrological gauges, and a comparison of accuracy with the popular copulas was made. The Gibbs sampling technique was applied for trivariate flood events simulation in order to mitigate the calculation difficulties of extending to three dimension directly. The simulation results indicate that the entropy copula is a simple and effective copula family for trivariate flood simulation.

How much are you prepared to PAY for a forecast?

NASA Astrophysics Data System (ADS)

Arnal, Louise; Coughlan, Erin; Ramos, Maria-Helena; Pappenberger, Florian; Wetterhall, Fredrik; Bachofen, Carina; van Andel, Schalk Jan

2015-04-01

Probabilistic hydro-meteorological forecasts are a crucial element of the decision-making chain in the field of flood prevention. The operational use of probabilistic forecasts is increasingly promoted through the development of new novel state-of-the-art forecast methods and numerical skill is continuously increasing. However, the value of such forecasts for flood early-warning systems is a topic of diverging opinions. Indeed, the word value, when applied to flood forecasting, is multifaceted. It refers, not only to the raw cost of acquiring and maintaining a probabilistic forecasting system (in terms of human and financial resources, data volume and computational time), but also and most importantly perhaps, to the use of such products. This game aims at investigating this point. It is a willingness to pay game, embedded in a risk-based decision-making experiment. Based on a ``Red Cross/Red Crescent, Climate Centre'' game, it is a contribution to the international Hydrologic Ensemble Prediction Experiment (HEPEX). A limited number of probabilistic forecasts will be auctioned to the participants; the price of these forecasts being market driven. All participants (irrespective of having bought or not a forecast set) will then be taken through a decision-making process to issue warnings for extreme rainfall. This game will promote discussions around the topic of the value of forecasts for decision-making in the field of flood prevention.

Weighing costs and losses: A decision making game using probabilistic forecasts

NASA Astrophysics Data System (ADS)

Werner, Micha; Ramos, Maria-Helena; Wetterhall, Frederik; Cranston, Michael; van Andel, Schalk-Jan; Pappenberger, Florian; Verkade, Jan

2017-04-01

Probabilistic forecasts are increasingly recognised as an effective and reliable tool to communicate uncertainties. The economic value of probabilistic forecasts has been demonstrated by several authors, showing the benefit to using probabilistic forecasts over deterministic forecasts in several sectors, including flood and drought warning, hydropower, and agriculture. Probabilistic forecasting is also central to the emerging concept of risk-based decision making, and underlies emerging paradigms such as impact-based forecasting. Although the economic value of probabilistic forecasts is easily demonstrated in academic works, its evaluation in practice is more complex. The practical use of probabilistic forecasts requires decision makers to weigh the cost of an appropriate response to a probabilistic warning against the projected loss that would occur if the event forecast becomes reality. In this paper, we present the results of a simple game that aims to explore how decision makers are influenced by the costs required for taking a response and the potential losses they face in case the forecast flood event occurs. Participants play the role of one of three possible different shop owners. Each type of shop has losses of quite different magnitude, should a flood event occur. The shop owners are presented with several forecasts, each with a probability of a flood event occurring, which would inundate their shop and lead to those losses. In response, they have to decide if they want to do nothing, raise temporary defences, or relocate their inventory. Each action comes at a cost; and the different shop owners therefore have quite different cost/loss ratios. The game was played on four occasions. Players were attendees of the ensemble hydro-meteorological forecasting session of the 2016 EGU Assembly, professionals participating at two other conferences related to hydrometeorology, and a group of students. All audiences were familiar with the principles of forecasting and water-related risks, and one of the audiences comprised a group of experts in probabilistic forecasting. Results show that the different shop owners do take the costs of taking action and the potential losses into account in their decisions. Shop owners with a low cost/loss ratio were found to be more inclined to take actions based on the forecasts, though the absolute value of the losses also increased the willingness to take action. Little differentiation was found between the different groups of players.

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

2018-03-01

GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

How Confident can we be in Flood Risk Assessments?

NASA Astrophysics Data System (ADS)

Merz, B.

2017-12-01

Flood risk management should be based on risk analyses quantifying the risk and its reduction for different risk reduction strategies. However, validating risk estimates by comparing model simulations with past observations is hardly possible, since the assessment typically encompasses extreme events and their impacts that have not been observed before. Hence, risk analyses are strongly based on assumptions and expert judgement. This situation opens the door for cognitive biases, such as `illusion of certainty', `overconfidence' or `recency bias'. Such biases operate specifically in complex situations with many factors involved, when uncertainty is high and events are probabilistic, or when close learning feedback loops are missing - aspects that all apply to risk analyses. This contribution discusses how confident we can be in flood risk assessments, and reflects about more rigorous approaches towards their validation.

Methodological framework for the probabilistic risk assessment of multi-hazards at a municipal scale: a case study in the Fella river valley, Eastern Italian Alps

NASA Astrophysics Data System (ADS)

Hussin, Haydar; van Westen, Cees; Reichenbach, Paola

2013-04-01

Local and regional authorities in mountainous areas that deal with hydro-meteorological hazards like landslides and floods try to set aside budgets for emergencies and risk mitigation. However, future losses are often not calculated in a probabilistic manner when allocating budgets or determining how much risk is acceptable. The absence of probabilistic risk estimates can create a lack of preparedness for reconstruction and risk reduction costs and a deficiency in promoting risk mitigation and prevention in an effective way. The probabilistic risk of natural hazards at local scale is usually ignored all together due to the difficulty in acknowledging, processing and incorporating uncertainties in the estimation of losses (e.g. physical damage, fatalities and monetary loss). This study attempts to set up a working framework for a probabilistic risk assessment (PRA) of landslides and floods at a municipal scale using the Fella river valley (Eastern Italian Alps) as a multi-hazard case study area. The emphasis is on the evaluation and determination of the uncertainty in the estimation of losses from multi-hazards. To carry out this framework some steps are needed: (1) by using physically based stochastic landslide and flood models we aim to calculate the probability of the physical impact on individual elements at risk, (2) this is then combined with a statistical analysis of the vulnerability and monetary value of the elements at risk in order to include their uncertainty in the risk assessment, (3) finally the uncertainty from each risk component is propagated into the loss estimation. The combined effect of landslides and floods on the direct risk to communities in narrow alpine valleys is also one of important aspects that needs to be studied.

Large-scale testing of in-vessel debris cooling through external flooding of the reactor pressure vessel in the CYBL facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chu, T.Y.; Bentz, J.H.; Bergeron, K.D.

1994-04-01

The possibility of achieving in-vessel core retention by flooding the reactor cavity, or the ``flooded cavity``, is an accident management concept currently under consideration for advanced light water reactors (ALWR), as well as for existing light water reactors (LWR). The CYBL (CYlindrical BoiLing) facility is a facility specifically designed to perform large-scale confirmatory testing of the flooded cavity concept. CYBL has a tank-within-a-tank design; the inner 3.7 m diameter tank simulates the reactor vessel, and the outer tank simulates the reactor cavity. The energy deposition on the bottom head is simulated with an array of radiant heaters. The array canmore » deliver a tailored heat flux distribution corresponding to that resulting from core melt convection. The present paper provides a detailed description of the capabilities of the facility, as well as results of recent experiments with heat flux in the range of interest to those required for in-vessel retention in typical ALWRs. The paper concludes with a discussion of other experiments for the flooded cavity applications.« less

Confronting uncertainty in flood damage predictions

NASA Astrophysics Data System (ADS)

Schröter, Kai; Kreibich, Heidi; Vogel, Kristin; Merz, Bruno

2015-04-01

Reliable flood damage models are a prerequisite for the practical usefulness of the model results. Oftentimes, traditional uni-variate damage models as for instance depth-damage curves fail to reproduce the variability of observed flood damage. Innovative multi-variate probabilistic modelling approaches are promising to capture and quantify the uncertainty involved and thus to improve the basis for decision making. In this study we compare the predictive capability of two probabilistic modelling approaches, namely Bagging Decision Trees and Bayesian Networks. For model evaluation we use empirical damage data which are available from computer aided telephone interviews that were respectively compiled after the floods in 2002, 2005 and 2006, in the Elbe and Danube catchments in Germany. We carry out a split sample test by sub-setting the damage records. One sub-set is used to derive the models and the remaining records are used to evaluate the predictive performance of the model. Further we stratify the sample according to catchments which allows studying model performance in a spatial transfer context. Flood damage estimation is carried out on the scale of the individual buildings in terms of relative damage. The predictive performance of the models is assessed in terms of systematic deviations (mean bias), precision (mean absolute error) as well as in terms of reliability which is represented by the proportion of the number of observations that fall within the 95-quantile and 5-quantile predictive interval. The reliability of the probabilistic predictions within validation runs decreases only slightly and achieves a very good coverage of observations within the predictive interval. Probabilistic models provide quantitative information about prediction uncertainty which is crucial to assess the reliability of model predictions and improves the usefulness of model results.

Prepared to react? Assessing the functional capacity of the primary health care system in rural Orissa, India to respond to the devastating flood of September 2008.

PubMed

Phalkey, Revati; Dash, Shisir R; Mukhopadhyay, Alok; Runge-Ranzinger, Silvia; Marx, Michael

2012-01-01

Early detection of an impending flood and the availability of countermeasures to deal with it can significantly reduce its health impacts. In developing countries like India, public primary health care facilities are frontline organizations that deal with disasters particularly in rural settings. For developing robust counter reacting systems evaluating preparedness capacities within existing systems becomes necessary. The objective of the study is to assess the functional capacity of the primary health care system in Jagatsinghpur district of rural Orissa in India to respond to the devastating flood of September 2008. An onsite survey was conducted in all 29 primary and secondary facilities in five rural blocks (administrative units) of Jagatsinghpur district in Orissa state. A pre-tested structured questionnaire was administered face to face in the facilities. The data was entered, processed and analyzed using STATA(®) 10. Data from our primary survey clearly shows that the healthcare facilities are ill prepared to handle the flood despite being faced by them annually. Basic utilities like electricity backup and essential medical supplies are lacking during floods. Lack of human resources along with missing standard operating procedures; pre-identified communication and incident command systems; effective leadership; and weak financial structures are the main hindering factors in mounting an adequate response to the floods. The 2008 flood challenged the primary curative and preventive health care services in Jagatsinghpur. Simple steps like developing facility specific preparedness plans which detail out standard operating procedures during floods and identify clear lines of command will go a long way in strengthening the response to future floods. Performance critiques provided by the grass roots workers, like this one, should be used for institutional learning and effective preparedness planning. Additionally each facility should maintain contingency funds for emergency response along with local vendor agreements to ensure stock supplies during floods. The facilities should ensure that baseline public health standards for health care delivery identified by the Government are met in non-flood periods in order to improve the response during floods. Building strong public primary health care systems is a development challenge. The recovery phases of disasters should be seen as an opportunity to expand and improve services and facilities.

Prepared to react? Assessing the functional capacity of the primary health care system in rural Orissa, India to respond to the devastating flood of September 2008

PubMed Central

Phalkey, Revati; Dash, Shisir R.; Mukhopadhyay, Alok; Runge-Ranzinger, Silvia; Marx, Michael

2012-01-01

Background Early detection of an impending flood and the availability of countermeasures to deal with it can significantly reduce its health impacts. In developing countries like India, public primary health care facilities are frontline organizations that deal with disasters particularly in rural settings. For developing robust counter reacting systems evaluating preparedness capacities within existing systems becomes necessary. Objective The objective of the study is to assess the functional capacity of the primary health care system in Jagatsinghpur district of rural Orissa in India to respond to the devastating flood of September 2008. Methods An onsite survey was conducted in all 29 primary and secondary facilities in five rural blocks (administrative units) of Jagatsinghpur district in Orissa state. A pre-tested structured questionnaire was administered face to face in the facilities. The data was entered, processed and analyzed using STATA® 10. Results Data from our primary survey clearly shows that the healthcare facilities are ill prepared to handle the flood despite being faced by them annually. Basic utilities like electricity backup and essential medical supplies are lacking during floods. Lack of human resources along with missing standard operating procedures; pre-identified communication and incident command systems; effective leadership; and weak financial structures are the main hindering factors in mounting an adequate response to the floods. Conclusion The 2008 flood challenged the primary curative and preventive health care services in Jagatsinghpur. Simple steps like developing facility specific preparedness plans which detail out standard operating procedures during floods and identify clear lines of command will go a long way in strengthening the response to future floods. Performance critiques provided by the grass roots workers, like this one, should be used for institutional learning and effective preparedness planning. Additionally each facility should maintain contingency funds for emergency response along with local vendor agreements to ensure stock supplies during floods. The facilities should ensure that baseline public health standards for health care delivery identified by the Government are met in non-flood periods in order to improve the response during floods. Building strong public primary health care systems is a development challenge. The recovery phases of disasters should be seen as an opportunity to expand and improve services and facilities. PMID:22435044

Probabilistic mapping of flood-induced backscatter changes in SAR time series

NASA Astrophysics Data System (ADS)

Schlaffer, Stefan; Chini, Marco; Giustarini, Laura; Matgen, Patrick

2017-04-01

The information content of flood extent maps can be increased considerably by including information on the uncertainty of the flood area delineation. This additional information can be of benefit in flood forecasting and monitoring. Furthermore, flood probability maps can be converted to binary maps showing flooded and non-flooded areas by applying a threshold probability value pF = 0.5. In this study, a probabilistic change detection approach for flood mapping based on synthetic aperture radar (SAR) time series is proposed. For this purpose, conditional probability density functions (PDFs) for land and open water surfaces were estimated from ENVISAT ASAR Wide Swath (WS) time series containing >600 images using a reference mask of permanent water bodies. A pixel-wise harmonic model was used to account for seasonality in backscatter from land areas caused by soil moisture and vegetation dynamics. The approach was evaluated for a large-scale flood event along the River Severn, United Kingdom. The retrieved flood probability maps were compared to a reference flood mask derived from high-resolution aerial imagery by means of reliability diagrams. The obtained performance measures indicate both high reliability and confidence although there was a slight under-estimation of the flood extent, which may in part be attributed to topographically induced radar shadows along the edges of the floodplain. Furthermore, the results highlight the importance of local incidence angle for the separability between flooded and non-flooded areas as specular reflection properties of open water surfaces increase with a more oblique viewing geometry.

Mapping flood hazards under uncertainty through probabilistic flood inundation maps

NASA Astrophysics Data System (ADS)

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.

Communicating uncertainty in hydrological forecasts: mission impossible?

NASA Astrophysics Data System (ADS)

Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

2010-05-01

Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted scenarios, is essential. We believe that the efficient communication of uncertainty in hydro-meteorological forecasts is not a mission impossible. Questions remaining unanswered in probabilistic hydrological forecasting should not neutralize the goal of such a mission, and the suspense kept should instead act as a catalyst for overcoming the remaining challenges.

A framework for probabilistic pluvial flood nowcasting for urban areas

NASA Astrophysics Data System (ADS)

Ntegeka, Victor; Murla, Damian; Wang, Lipen; Foresti, Loris; Reyniers, Maarten; Delobbe, Laurent; Van Herk, Kristine; Van Ootegem, Luc; Willems, Patrick

2016-04-01

Pluvial flood nowcasting is gaining ground not least because of the advancements in rainfall forecasting schemes. Short-term forecasts and applications have benefited from the availability of such forecasts with high resolution in space (~1km) and time (~5min). In this regard, it is vital to evaluate the potential of nowcasting products for urban inundation applications. One of the most advanced Quantitative Precipitation Forecasting (QPF) techniques is the Short-Term Ensemble Prediction System, which was originally co-developed by the UK Met Office and Australian Bureau of Meteorology. The scheme was further tuned to better estimate extreme and moderate events for the Belgian area (STEPS-BE). Against this backdrop, a probabilistic framework has been developed that consists of: (1) rainfall nowcasts; (2) sewer hydraulic model; (3) flood damage estimation; and (4) urban inundation risk mapping. STEPS-BE forecasts are provided at high resolution (1km/5min) with 20 ensemble members with a lead time of up to 2 hours using a 4 C-band radar composite as input. Forecasts' verification was performed over the cities of Leuven and Ghent and biases were found to be small. The hydraulic model consists of the 1D sewer network and an innovative 'nested' 2D surface model to model 2D urban surface inundations at high resolution. The surface components are categorized into three groups and each group is modelled using triangular meshes at different resolutions; these include streets (3.75 - 15 m2), high flood hazard areas (12.5 - 50 m2) and low flood hazard areas (75 - 300 m2). Functions describing urban flood damage and social consequences were empirically derived based on questionnaires to people in the region that were recently affected by sewer floods. Probabilistic urban flood risk maps were prepared based on spatial interpolation techniques of flood inundation. The method has been implemented and tested for the villages Oostakker and Sint-Amandsberg, which are part of the larger city of Gent, Belgium. After each of the different above-mentioned components were evaluated, they were combined and tested for recent historical flood events. The rainfall nowcasting, hydraulic sewer and 2D inundation modelling and socio-economical flood risk results each could be partly evaluated: the rainfall nowcasting results based on radar data and rain gauges; the hydraulic sewer model results based on water level and discharge data at pumping stations; the 2D inundation modelling results based on limited data on some recent flood locations and inundation depths; the results for the socio-economical flood consequences of the most extreme events based on claims in the database of the national disaster agency. Different methods for visualization of the probabilistic inundation results are proposed and tested.

Developing an event-tree probabilistic tsunami inundation model for NE Atlantic coasts: Application to case studies

NASA Astrophysics Data System (ADS)

Omira, Rachid; Baptista, Maria Ana; Matias, Luis

2015-04-01

This study constitutes the first assessment of probabilistic tsunami inundation in the NE Atlantic region, using an event-tree approach. It aims to develop a probabilistic tsunami inundation approach for the NE Atlantic coast with an application to two test sites of ASTARTE project, Tangier-Morocco and Sines-Portugal. Only tsunamis of tectonic origin are considered here, taking into account near-, regional- and far-filed sources. The multidisciplinary approach, proposed here, consists of an event-tree method that gathers seismic hazard assessment, tsunami numerical modelling, and statistical methods. It presents also a treatment of uncertainties related to source location and tidal stage in order to derive the likelihood of tsunami flood occurrence and exceedance of a specific near-shore wave height during a given return period. We derive high-resolution probabilistic maximum wave heights and flood distributions for both test-sites Tangier and Sines considering 100-, 500-, and 1000-year return periods. We find that the probability that a maximum wave height exceeds 1 m somewhere along the Sines coasts reaches about 55% for 100-year return period, and is up to 100% for 1000-year return period. Along Tangier coast, the probability of inundation occurrence (flow depth > 0m) is up to 45% for 100-year return period and reaches 96% in some near-shore costal location for 500-year return period. Acknowledgements: This work is funded by project ASTARTE - Assessment, STrategy And Risk Reduction for Tsunamis in Europe. Grant 603839, 7th FP (ENV.2013.6.4-3 ENV.2013.6.4-3).

The state of the art of flood forecasting - Hydrological Ensemble Prediction Systems

NASA Astrophysics Data System (ADS)

Thielen-Del Pozo, J.; Pappenberger, F.; Salamon, P.; Bogner, K.; Burek, P.; de Roo, A.

2010-09-01

Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Because of the specific characteristics of each catchment, varying data availability and end-user demands, the design of the best flood forecasting system may differ from catchment to catchment. However, despite the differences in concept and data needs, there is one underlying issue that spans across all systems. There has been an growing awareness and acceptance that uncertainty is a fundamental issue of flood forecasting and needs to be dealt with at the different spatial and temporal scales as well as the different stages of the flood generating processes. Today, operational flood forecasting centres change increasingly from single deterministic forecasts to probabilistic forecasts with various representations of the different contributions of uncertainty. The move towards these so-called Hydrological Ensemble Prediction Systems (HEPS) in flood forecasting represents the state of the art in forecasting science, following on the success of the use of ensembles for weather forecasting (Buizza et al., 2005) and paralleling the move towards ensemble forecasting in other related disciplines such as climate change predictions. The use of HEPS has been internationally fostered by initiatives such as "The Hydrologic Ensemble Prediction Experiment" (HEPEX), created with the aim to investigate how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes. The advantages of quantifying the different contributions of uncertainty as well as the overall uncertainty to obtain reliable and useful flood forecasts also for extreme events, has become evident. However, despite the demonstrated advantages, worldwide the incorporation of HEPS in operational flood forecasting is still limited. The applicability of HEPS for smaller river basins was tested in MAP D-Phase, an acronym for "Demonstration of Probabilistic Hydrological and Atmospheric Simulation of flood Events in the Alpine region" which was launched in 2005 as a Forecast Demonstration Project of World Weather Research Programme of WMO, and entered a pre-operational and still active testing phase in 2007. In Europe, a comparatively high number of EPS driven systems for medium-large rivers exist. National flood forecasting centres of Sweden, Finland and the Netherlands, have already implemented HEPS in their operational forecasting chain, while in other countries including France, Germany, Czech Republic and Hungary, hybrids or experimental chains have been installed. As an example of HEPS, the European Flood Alert System (EFAS) is being presented. EFAS provides medium-range probabilistic flood forecasting information for large trans-national river basins. It incorporates multiple sets of weather forecast including different types of EPS and deterministic forecasts from different providers. EFAS products are evaluated and visualised as exceedance of critical levels only - both in forms of maps and time series. Different sources of uncertainty and its impact on the flood forecasting performance for every grid cell has been tested offline but not yet incorporated operationally into the forecasting chain for computational reasons. However, at stations where real-time discharges are available, a hydrological uncertainty processor is being applied to estimate the total predictive uncertainty from the hydrological and input uncertainties. Research on long-term EFAS results has shown the need for complementing statistical analysis with case studies for which examples will be shown.

Action-based flood forecasting for triggering humanitarian action

NASA Astrophysics Data System (ADS)

Coughlan de Perez, Erin; van den Hurk, Bart; van Aalst, Maarten K.; Amuron, Irene; Bamanya, Deus; Hauser, Tristan; Jongma, Brenden; Lopez, Ana; Mason, Simon; Mendler de Suarez, Janot; Pappenberger, Florian; Rueth, Alexandra; Stephens, Elisabeth; Suarez, Pablo; Wagemaker, Jurjen; Zsoter, Ervin

2016-09-01

Too often, credible scientific early warning information of increased disaster risk does not result in humanitarian action. With financial resources tilted heavily towards response after a disaster, disaster managers have limited incentive and ability to process complex scientific data, including uncertainties. These incentives are beginning to change, with the advent of several new forecast-based financing systems that provide funding based on a forecast of an extreme event. Given the changing landscape, here we demonstrate a method to select and use appropriate forecasts for specific humanitarian disaster prevention actions, even in a data-scarce location. This action-based forecasting methodology takes into account the parameters of each action, such as action lifetime, when verifying a forecast. Forecasts are linked with action based on an understanding of (1) the magnitude of previous flooding events and (2) the willingness to act "in vain" for specific actions. This is applied in the context of the Uganda Red Cross Society forecast-based financing pilot project, with forecasts from the Global Flood Awareness System (GloFAS). Using this method, we define the "danger level" of flooding, and we select the probabilistic forecast triggers that are appropriate for specific actions. Results from this methodology can be applied globally across hazards and fed into a financing system that ensures that automatic, pre-funded early action will be triggered by forecasts.

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

NASA Astrophysics Data System (ADS)

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 through Bayesian inference using Markov chain Monte Carlo (MCMC) sampling. With the ability to cope with incomplete information and use expert knowledge, as well as inherently providing quantitative uncertainty information, it is shown that loss models based on BNs are superior to deterministic approaches for pluvial flood risk assessment.

Flood risk assessment in France: comparison of extreme flood estimation methods (EXTRAFLO project, Task 7)

NASA Astrophysics Data System (ADS)

Garavaglia, F.; Paquet, E.; Lang, M.; Renard, B.; Arnaud, P.; Aubert, Y.; Carre, J.

2013-12-01

In flood risk assessment the methods can be divided in two families: deterministic methods and probabilistic methods. In the French hydrologic community the probabilistic methods are historically preferred to the deterministic ones. Presently a French research project named EXTRAFLO (RiskNat Program of the French National Research Agency, https://extraflo.cemagref.fr) deals with the design values for extreme rainfall and floods. The object of this project is to carry out a comparison of the main methods used in France for estimating extreme values of rainfall and floods, to obtain a better grasp of their respective fields of application. In this framework we present the results of Task 7 of EXTRAFLO project. Focusing on French watersheds, we compare the main extreme flood estimation methods used in French background: (i) standard flood frequency analysis (Gumbel and GEV distribution), (ii) regional flood frequency analysis (regional Gumbel and GEV distribution), (iii) local and regional flood frequency analysis improved by historical information (Naulet et al., 2005), (iv) simplify probabilistic method based on rainfall information (i.e. Gradex method (CFGB, 1994), Agregee method (Margoum, 1992) and Speed method (Cayla, 1995)), (v) flood frequency analysis by continuous simulation approach and based on rainfall information (i.e. Schadex method (Paquet et al., 2013, Garavaglia et al., 2010), Shyreg method (Lavabre et al., 2003)) and (vi) multifractal approach. The main result of this comparative study is that probabilistic methods based on additional information (i.e. regional, historical and rainfall information) provide better estimations than the standard flood frequency analysis. Another interesting result is that, the differences between the various extreme flood quantile estimations of compared methods increase with return period, staying relatively moderate up to 100-years return levels. Results and discussions are here illustrated throughout with the example of five watersheds located in the South of France. References : O. CAYLA : Probability calculation of design floods abd inflows - SPEED. Waterpower 1995, San Francisco, California 1995 CFGB : Design flood determination by the gradex method. Bulletin du Comité Français des Grands Barrages News 96, 18th congress CIGB-ICOLD n2, nov:108, 1994. F. GARAVAGLIA et al. : Introducing a rainfall compound distribution model based on weather patterns subsampling. Hydrology and Earth System Sciences, 14, 951-964, 2010. J. LAVABRE et al. : SHYREG : une méthode pour l'estimation régionale des débits de crue. application aux régions méditerranéennes françaises. Ingénierie EAT, 97-111, 2003. M. MARGOUM : Estimation des crues rares et extrêmes : le modèle AGREGEE. Conceptions et remières validations. PhD, Ecole des Mines de Paris, 1992. R. NAULET et al. : Flood frequency analysis on the Ardèche river using French documentary sources from the two last centuries. Journal of Hydrology, 313:58-78, 2005. E. PAQUET et al. : The SCHADEX method: A semi-continuous rainfall-runoff simulation for extreme flood estimation, Journal of Hydrology, 495, 23-37, 2013.

Development of a coupled hydrological - hydrodynamic model for probabilistic catchment flood inundation modelling

NASA Astrophysics Data System (ADS)

Quinn, Niall; Freer, Jim; Coxon, Gemma; Dunne, Toby; Neal, Jeff; Bates, Paul; Sampson, Chris; Smith, Andy; Parkin, Geoff

2017-04-01

Computationally efficient flood inundation modelling systems capable of representing important hydrological and hydrodynamic flood generating processes over relatively large regions are vital for those interested in flood preparation, response, and real time forecasting. However, such systems are currently not readily available. This can be particularly important where flood predictions from intense rainfall are considered as the processes leading to flooding often involve localised, non-linear spatially connected hillslope-catchment responses. Therefore, this research introduces a novel hydrological-hydraulic modelling framework for the provision of probabilistic flood inundation predictions across catchment to regional scales that explicitly account for spatial variability in rainfall-runoff and routing processes. Approaches have been developed to automate the provision of required input datasets and estimate essential catchment characteristics from freely available, national datasets. This is an essential component of the framework as when making predictions over multiple catchments or at relatively large scales, and where data is often scarce, obtaining local information and manually incorporating it into the model quickly becomes infeasible. An extreme flooding event in the town of Morpeth, NE England, in 2008 was used as a first case study evaluation of the modelling framework introduced. The results demonstrated a high degree of prediction accuracy when comparing modelled and reconstructed event characteristics for the event, while the efficiency of the modelling approach used enabled the generation of relatively large ensembles of realisations from which uncertainty within the prediction may be represented. This research supports previous literature highlighting the importance of probabilistic forecasting, particularly during extreme events, which can be often be poorly characterised or even missed by deterministic predictions due to the inherent uncertainty in any model application. Future research will aim to further evaluate the robustness of the approaches introduced by applying the modelling framework to a variety of historical flood events across UK catchments. Furthermore, the flexibility and efficiency of the framework is ideally suited to the examination of the propagation of errors through the model which will help gain a better understanding of the dominant sources of uncertainty currently impacting flood inundation predictions.

Exploiting Synoptic-Scale Climate Processes to Develop Nonstationary, Probabilistic Flood Hazard Projections

NASA Astrophysics Data System (ADS)

Spence, C. M.; Brown, C.; Doss-Gollin, J.

2016-12-01

Climate model projections are commonly used for water resources management and planning under nonstationarity, but they do not reliably reproduce intense short-term precipitation and are instead more skilled at broader spatial scales. To provide a credible estimate of flood trend that reflects climate uncertainty, we present a framework that exploits the connections between synoptic-scale oceanic and atmospheric patterns and local-scale flood-producing meteorological events to develop long-term flood hazard projections. We demonstrate the method for the Iowa River, where high flow episodes have been found to correlate with tropical moisture exports that are associated with a pressure dipole across the eastern continental United States We characterize the relationship between flooding on the Iowa River and this pressure dipole through a nonstationary Pareto-Poisson peaks-over-threshold probability distribution estimated based on the historic record. We then combine the results of a trend analysis of dipole index in the historic record with the results of a trend analysis of the dipole index as simulated by General Circulation Models (GCMs) under climate change conditions through a Bayesian framework. The resulting nonstationary posterior distribution of dipole index, combined with the dipole-conditioned peaks-over-threshold flood frequency model, connects local flood hazard to changes in large-scale atmospheric pressure and circulation patterns that are related to flooding in a process-driven framework. The Iowa River example demonstrates that the resulting nonstationary, probabilistic flood hazard projection may be used to inform risk-based flood adaptation decisions.

Probabilistic mapping of urban flood risk: Application to extreme events in Surat, India

NASA Astrophysics Data System (ADS)

Ramirez, Jorge; Rajasekar, Umamaheshwaran; Coulthard, Tom; Keiler, Margreth

2016-04-01

Surat, India is a coastal city that lies on the banks of the river Tapti and is located downstream from the Ukai dam. Given Surat's geographic location, the population of five million people are repeatedly exposed to flooding caused by high tide combined with large emergency dam releases into the Tapti river. In 2006 such a flood event occurred when intense rainfall in the Tapti catchment caused a dam release near 25,000 m3 s-1 and flooded 90% of the city. A first step towards strengthening resilience in Surat requires a robust method for mapping potential flood risk that considers the uncertainty in future dam releases. Here, in this study we develop many combinations of dam release magnitude and duration for the Ukai dam. Afterwards we use these dam releases to drive a two dimensional flood model (CAESAR-Lisflood) of Surat that also considers tidal effects. Our flood model of Surat utilizes fine spatial resolution (30m) topography produced from an extensive differential global positioning system survey and measurements of river cross-sections. Within the city we have modelled scenarios that include extreme conditions with near maximum dam release levels (e.g. 1:250 year flood) and high tides. Results from all scenarios have been summarized into probabilistic flood risk maps for Surat. These maps are currently being integrated within the city disaster management plan for taking both mitigation and adaptation measures for different scenarios of flooding.

Opportunities of probabilistic flood loss models

NASA Astrophysics Data System (ADS)

Schröter, Kai; Kreibich, Heidi; Lüdtke, Stefan; Vogel, Kristin; Merz, Bruno

2016-04-01

Oftentimes, traditional uni-variate damage models as for instance depth-damage curves fail to reproduce the variability of observed flood damage. However, reliable flood damage models are a prerequisite for the practical usefulness of the model results. Innovative multi-variate probabilistic modelling approaches are promising to capture and quantify the uncertainty involved and thus to improve the basis for decision making. In this study we compare the predictive capability of two probabilistic modelling approaches, namely Bagging Decision Trees and Bayesian Networks and traditional stage damage functions. For model evaluation we use empirical damage data which are available from computer aided telephone interviews that were respectively compiled after the floods in 2002, 2005, 2006 and 2013 in the Elbe and Danube catchments in Germany. We carry out a split sample test by sub-setting the damage records. One sub-set is used to derive the models and the remaining records are used to evaluate the predictive performance of the model. Further we stratify the sample according to catchments which allows studying model performance in a spatial transfer context. Flood damage estimation is carried out on the scale of the individual buildings in terms of relative damage. The predictive performance of the models is assessed in terms of systematic deviations (mean bias), precision (mean absolute error) as well as in terms of sharpness of the predictions the reliability which is represented by the proportion of the number of observations that fall within the 95-quantile and 5-quantile predictive interval. The comparison of the uni-variable Stage damage function and the multivariable model approach emphasises the importance to quantify predictive uncertainty. With each explanatory variable, the multi-variable model reveals an additional source of uncertainty. However, the predictive performance in terms of precision (mbe), accuracy (mae) and reliability (HR) is clearly improved in comparison to uni-variable Stage damage function. Overall, Probabilistic models provide quantitative information about prediction uncertainty which is crucial to assess the reliability of model predictions and improves the usefulness of model results.

Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

NASA Astrophysics Data System (ADS)

Arnal, Louise; Ramos, Maria-Helena; Coughlan de Perez, Erin; Cloke, Hannah Louise; Stephens, Elisabeth; Wetterhall, Fredrik; van Andel, Schalk Jan; Pappenberger, Florian

2016-08-01

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecast uncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty in transforming the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called "How much are you prepared to pay for a forecast?". The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydro-meteorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants' willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers.

A geomorphic approach to 100-year floodplain mapping for the Conterminous United States

NASA Astrophysics Data System (ADS)

Jafarzadegan, Keighobad; Merwade, Venkatesh; Saksena, Siddharth

2018-06-01

Floodplain mapping using hydrodynamic models is difficult in data scarce regions. Additionally, using hydrodynamic models to map floodplain over large stream network can be computationally challenging. Some of these limitations of floodplain mapping using hydrodynamic modeling can be overcome by developing computationally efficient statistical methods to identify floodplains in large and ungauged watersheds using publicly available data. This paper proposes a geomorphic model to generate probabilistic 100-year floodplain maps for the Conterminous United States (CONUS). The proposed model first categorizes the watersheds in the CONUS into three classes based on the height of the water surface corresponding to the 100-year flood from the streambed. Next, the probability that any watershed in the CONUS belongs to one of these three classes is computed through supervised classification using watershed characteristics related to topography, hydrography, land use and climate. The result of this classification is then fed into a probabilistic threshold binary classifier (PTBC) to generate the probabilistic 100-year floodplain maps. The supervised classification algorithm is trained by using the 100-year Flood Insurance Rated Maps (FIRM) from the U.S. Federal Emergency Management Agency (FEMA). FEMA FIRMs are also used to validate the performance of the proposed model in areas not included in the training. Additionally, HEC-RAS model generated flood inundation extents are used to validate the model performance at fifteen sites that lack FEMA maps. Validation results show that the probabilistic 100-year floodplain maps, generated by proposed model, match well with both FEMA and HEC-RAS generated maps. On average, the error of predicted flood extents is around 14% across the CONUS. The high accuracy of the validation results shows the reliability of the geomorphic model as an alternative approach for fast and cost effective delineation of 100-year floodplains for the CONUS.

Evaluation of flood preparedness in government healthcare facilities in Eastern Province, Sri Lanka.

PubMed

Farley, Jessica M; Suraweera, Inoka; Perera, W L S P; Hess, Jeremy; Ebi, Kristie L

2017-01-01

Sri Lanka is vulnerable to floods and other hydro-meteorological disasters. Climate change is projected to increase the intensity of these events. This study aimed to assess the flood preparedness in healthcare facilities in Eastern Province. This was a cross-sectional, descriptive, mixed methods study conducted in Trincomalee District. Surveys were conducted in 31 government healthcare facilities, using a pre-tested, structured questionnaire covering the last 5 years. Seven in-depth interviews were conducted with randomly selected Medical Officers in Charge or their equivalent, and 3 interviews were conducted with Medical Offices of Health. Two general hospitals, 3 base hospitals, 11 divisional hospitals, and 15 primary care units were included. Six respondents (19.4%) reported flooding in their facility, and 19 (61.3%) reported flooding in their catchment area. For the health workforce, 77.4% of respondents reported not enough staff to perform normal service delivery during disasters, and 25.5% reported staff absenteeism due to flooding. Several respondents expressed a desire for more disaster-specific and general clinical training opportunities for themselves and their staff. Most respondents (80.7%) reported no delays in supply procurement during weather emergencies, but 61.3% reported insufficient supplies to maintain normal service delivery during disasters. Four facilities (12.9%) had disaster preparedness plans, and 4 (12.9%) had any staff trained on disaster preparedness or management within the last year. One quarter (25.8%) of respondents had received any written guidance on disaster preparedness from the regional, provincial, or national level in the last year. While there is a strong health system operating in Sri Lanka, improvements are needed in localized and appropriate disaster-related training, resources for continuing clinical education, and investments in workforce to strengthen flood and other disaster resilience within the government healthcare system in the study district.

A Global Geospatial Database of 5000+ Historic Flood Event Extents

NASA Astrophysics Data System (ADS)

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.

Developing an Event-Tree Probabilistic Tsunami Inundation Model for NE Atlantic Coasts: Application to a Case Study

NASA Astrophysics Data System (ADS)

Omira, R.; Matias, L.; Baptista, M. A.

2016-12-01

This study constitutes a preliminary assessment of probabilistic tsunami inundation in the NE Atlantic region. We developed an event-tree approach to calculate the likelihood of tsunami flood occurrence and exceedance of a specific near-shore wave height for a given exposure time. Only tsunamis of tectonic origin are considered here, taking into account local, regional, and far-field sources. The approach used here consists of an event-tree method that gathers probability models for seismic sources, tsunami numerical modeling, and statistical methods. It also includes a treatment of aleatoric uncertainties related to source location and tidal stage. Epistemic uncertainties are not addressed in this study. The methodology is applied to the coastal test-site of Sines located in the NE Atlantic coast of Portugal. We derive probabilistic high-resolution maximum wave amplitudes and flood distributions for the study test-site considering 100- and 500-year exposure times. We find that the probability that maximum wave amplitude exceeds 1 m somewhere along the Sines coasts reaches about 60 % for an exposure time of 100 years and is up to 97 % for an exposure time of 500 years. The probability of inundation occurrence (flow depth >0 m) varies between 10 % and 57 %, and from 20 % up to 95 % for 100- and 500-year exposure times, respectively. No validation has been performed here with historical tsunamis. This paper illustrates a methodology through a case study, which is not an operational assessment.

Hazard function analysis for flood planning under nonstationarity

NASA Astrophysics Data System (ADS)

Read, Laura K.; Vogel, Richard M.

2016-05-01

The field of hazard function analysis (HFA) involves a probabilistic assessment of the "time to failure" or "return period," T, of an event of interest. HFA is used in epidemiology, manufacturing, medicine, actuarial statistics, reliability engineering, economics, and elsewhere. For a stationary process, the probability distribution function (pdf) of the return period always follows an exponential distribution, the same is not true for nonstationary processes. When the process of interest, X, exhibits nonstationary behavior, HFA can provide a complementary approach to risk analysis with analytical tools particularly useful for hydrological applications. After a general introduction to HFA, we describe a new mathematical linkage between the magnitude of the flood event, X, and its return period, T, for nonstationary processes. We derive the probabilistic properties of T for a nonstationary one-parameter exponential model of X, and then use both Monte-Carlo simulation and HFA to generalize the behavior of T when X arises from a nonstationary two-parameter lognormal distribution. For this case, our findings suggest that a two-parameter Weibull distribution provides a reasonable approximation for the pdf of T. We document how HFA can provide an alternative approach to characterize the probabilistic properties of both nonstationary flood series and the resulting pdf of T.

The quality and value of seasonal precipitation forecasts for an early warning of large-scale droughts and floods in West Africa

NASA Astrophysics Data System (ADS)

Bliefernicht, Jan; Seidel, Jochen; Salack, Seyni; Waongo, Moussa; Laux, Patrick; Kunstmann, Harald

2017-04-01

Seasonal precipitation forecasts are a crucial source of information for an early warning of hydro-meteorological extremes in West Africa. However, the current seasonal forecasting system used by the West African weather services in the framework of the West African Climate Outlook forum (PRESAO) is limited to probabilistic precipitation forecasts of 1-month lead time. To improve this provision, we use an ensemble-based quantile-quantile transformation for bias correction of precipitation forecasts provided by a global seasonal ensemble prediction system, the Climate Forecast System Version 2 (CFS2). The statistical technique eliminates systematic differences between global forecasts and observations with the potential to preserve the signal from the model. The technique has also the advantage that it can be easily implemented at national weather services with low capacities. The statistical technique is used to generate probabilistic forecasts of monthly and seasonal precipitation amount and other precipitation indices useful for an early warning of large-scale drought and floods in West Africa. The evaluation of the statistical technique is done using CFS hindcasts (1982 to 2009) in a cross-validation mode to determine the performance of the precipitation forecasts for several lead times focusing on drought and flood events depicted over the Volta and Niger basins. In addition, operational forecasts provided by PRESAO are analyzed from 1998 to 2015. The precipitation forecasts are compared to low-skill reference forecasts generated from gridded observations (i.e. GPCC, CHIRPS) and a novel in-situ gauge database from national observation networks (see Poster EGU2017-10271). The forecasts are evaluated using state-of-the-art verification techniques to determine specific quality attributes of probabilistic forecasts such as reliability, accuracy and skill. In addition, cost-loss approaches are used to determine the value of probabilistic forecasts for multiple users in warning situations. The outcomes of the hindcasts experiment for the Volta basin illustrate that the statistical technique can clearly improve the CFS precipitation forecasts with the potential to provide skillful and valuable early precipitation warnings for large-scale drought and flood situations several months in ahead. In this presentation we give a detailed overview about the ensemble-based quantile-quantile-transformation, its validation and verification and the possibilities of this technique to complement PRESAO. We also highlight the performance of this technique for extremes such as the Sahel drought in the 80ties and in comparison to the various reference data sets (e.g. CFS2, PRESAO, observational data sets) used in this study.

Accouting for Greenhouse Gas Emissions from Reservoirs

NASA Astrophysics Data System (ADS)

Beaulieu, J. J.; Deemer, B. R.; Harrison, J. A.; Nietch, C. T.; Waldo, S.

2016-12-01

Nearly three decades of research has demonstrated that the impoundment of rivers and the flooding of terrestrial ecosystems behind dams can increase rates of greenhouse gas emission, particularly methane. The 2006 IPCC Guidelines for National Greenhouse Gas Inventories includes a methodology for estimating methane emissions from flooded lands, but the methodology was published as an appendix to be used as a `basis for future methodological development' due to a lack of data. Since the 2006 Guidelines were published there has been a 6-fold increase in the number of peer reviewed papers published on the topic including reports from reservoirs in India, China, Africa, and Russia. Furthermore, several countries, including Iceland, Switzerland, and Finland, have developed country specific methodologies for including flooded lands methane emissions in their National Greenhouse Gas Inventories. This presentation will include a review of the literature on flooded land methane emissions and approaches that have been used to upscale emissions for national inventories. We will also present ongoing research in the United States to develop a country specific methodology. In the U.S., research approaches include: 1) an effort to develop predictive relationships between methane emissions and reservoir characteristics that are available in national databases, such as reservoir size and drainage area, and 2) a national-scale probabilistic survey of reservoir methane emissions linked to the National Lakes Assessment.

Dealing with uncertainty in the probability of overtopping of a flood mitigation dam

NASA Astrophysics Data System (ADS)

Michailidi, Eleni Maria; Bacchi, Baldassare

2017-05-01

In recent years, copula multivariate functions were used to model, probabilistically, the most important variables of flood events: discharge peak, flood volume and duration. However, in most of the cases, the sampling uncertainty, from which small-sized samples suffer, is neglected. In this paper, considering a real reservoir controlled by a dam as a case study, we apply a structure-based approach to estimate the probability of reaching specific reservoir levels, taking into account the key components of an event (flood peak, volume, hydrograph shape) and of the reservoir (rating curve, volume-water depth relation). Additionally, we improve information about the peaks from historical data and reports through a Bayesian framework, allowing the incorporation of supplementary knowledge from different sources and its associated error. As it is seen here, the extra information can result in a very different inferred parameter set and consequently this is reflected as a strong variability of the reservoir level, associated with a given return period. Most importantly, the sampling uncertainty is accounted for in both cases (single-site and multi-site with historical information scenarios), and Monte Carlo confidence intervals for the maximum water level are calculated. It is shown that water levels of specific return periods in a lot of cases overlap, thus making risk assessment, without providing confidence intervals, deceiving.

Accounting For Greenhouse Gas Emissions From Flooded ...

EPA Pesticide Factsheets

Nearly three decades of research has demonstrated that the inundation of rivers and terrestrial ecosystems behind dams can lead to enhanced rates of greenhouse gas emissions, particularly methane. The 2006 IPCC Guidelines for National Greenhouse Gas Inventories includes a methodology for estimating methane emissions from flooded lands, but the methodology was published as an appendix to be used a ‘basis for future methodological development’ due to a lack of data. Since the 2006 Guidelines were published there has been a 6-fold increase in the number of peer reviewed papers published on the topic including reports from reservoirs in India, China, Africa, and Russia. Furthermore, several countries, including Iceland, Switzerland, and Finland, have developed country specific methodologies for including flooded lands methane emissions in their National Greenhouse Gas Inventories. This presentation will include a review of the literature on flooded land methane emissions and approaches that have been used to upscale emissions for national inventories. We will also present ongoing research in the United States to develop a country specific methodology. The research approaches include 1) an effort to develop predictive relationships between methane emissions and reservoir characteristics that are available in national databases, such as reservoir size and drainage area, and 2) a national-scale probabilistic survey of reservoir methane emissions. To inform th

Accounting for Greenhouse Gas Emissions from Reservoirs ...

EPA Pesticide Factsheets

Nearly three decades of research has demonstrated that the impoundment of rivers and the flooding of terrestrial ecosystems behind dams can increase rates of greenhouse gas emission, particularly methane. The 2006 IPCC Guidelines for National Greenhouse Gas Inventories includes a methodology for estimating methane emissions from flooded lands, but the methodology was published as an appendix to be used as a ‘basis for future methodological development’ due to a lack of data. Since the 2006 Guidelines were published there has been a 6-fold increase in the number of peer reviewed papers published on the topic including reports from reservoirs in India, China, Africa, and Russia. Furthermore, several countries, including Iceland, Switzerland, and Finland, have developed country specific methodologies for including flooded lands methane emissions in their National Greenhouse Gas Inventories. This presentation will include a review of the literature on flooded land methane emissions and approaches that have been used to upscale emissions for national inventories. We will also present ongoing research in the United States to develop a country specific methodology. In the U.S., research approaches include: 1) an effort to develop predictive relationships between methane emissions and reservoir characteristics that are available in national databases, such as reservoir size and drainage area, and 2) a national-scale probabilistic survey of reservoir methane em

Medium Range Flood Forecasting for Agriculture Damage Reduction

NASA Astrophysics Data System (ADS)

Fakhruddin, S. H. M.

2014-12-01

Early warning is a key element for disaster risk reduction. In recent decades, major advancements have been made in medium range and seasonal flood forecasting. This progress provides a great opportunity to reduce agriculture damage and improve advisories for early action and planning for flood hazards. This approach can facilitate proactive rather than reactive management of the adverse consequences of floods. In the agricultural sector, for instance, farmers can take a diversity of options such as changing cropping patterns, applying fertilizer, irrigating and changing planting timing. An experimental medium range (1-10 day) flood forecasting model has been developed for Bangladesh and Thailand. It provides 51 sets of discharge ensemble forecasts of 1-10 days with significant persistence and high certainty. This type of forecast could assist farmers and other stakeholders for differential preparedness activities. These ensembles probabilistic flood forecasts have been customized based on user-needs for community-level application focused on agriculture system. The vulnerabilities of agriculture system were calculated based on exposure, sensitivity and adaptive capacity. Indicators for risk and vulnerability assessment were conducted through community consultations. The forecast lead time requirement, user-needs, impacts and management options for crops were identified through focus group discussions, informal interviews and community surveys. This paper illustrates potential applications of such ensembles for probabilistic medium range flood forecasts in a way that is not commonly practiced globally today.

Probabilistic and deterministic evaluation of uncertainty in a local scale multi-risk analysis

NASA Astrophysics Data System (ADS)

Lari, S.; Frattini, P.; Crosta, G. B.

2009-04-01

We performed a probabilistic multi-risk analysis (QPRA) at the local scale for a 420 km2 area surrounding the town of Brescia (Northern Italy). We calculated the expected annual loss in terms of economical damage and life loss, for a set of risk scenarios of flood, earthquake and industrial accident with different occurrence probabilities and different intensities. The territorial unit used for the study was the census parcel, of variable area, for which a large amount of data was available. Due to the lack of information related to the evaluation of the hazards, to the value of the exposed elements (e.g., residential and industrial area, population, lifelines, sensitive elements as schools, hospitals) and to the process-specific vulnerability, and to a lack of knowledge of the processes (floods, industrial accidents, earthquakes), we assigned an uncertainty to the input variables of the analysis. For some variables an homogeneous uncertainty was assigned on the whole study area, as for instance for the number of buildings of various typologies, and for the event occurrence probability. In other cases, as for phenomena intensity (e.g.,depth of water during flood) and probability of impact, the uncertainty was defined in relation to the census parcel area. In fact assuming some variables homogeneously diffused or averaged on the census parcels, we introduce a larger error for larger parcels. We propagated the uncertainty in the analysis using three different models, describing the reliability of the output (risk) as a function of the uncertainty of the inputs (scenarios and vulnerability functions). We developed a probabilistic approach based on Monte Carlo simulation, and two deterministic models, namely First Order Second Moment (FOSM) and Point Estimate (PE). In general, similar values of expected losses are obtained with the three models. The uncertainty of the final risk value is in the three cases around the 30% of the expected value. Each of the models, nevertheless, requires different assumptions and computational efforts, and provides results with different level of detail.

Flash-flood early warning using weather radar data: from nowcasting to forecasting

NASA Astrophysics Data System (ADS)

Liechti, Katharina; Panziera, Luca; Germann, Urs; Zappa, Massimiliano

2013-04-01

In our study we explore the limits of radar-based forecasting for hydrological runoff prediction. Two novel probabilistic radar-based forecasting chains for flash-flood early warning are investigated in three catchments in the Southern Swiss Alps and set in relation to deterministic discharge forecast for the same catchments. The first probabilistic radar-based forecasting chain is driven by NORA (Nowcasting of Orographic Rainfall by means of Analogues), an analogue-based heuristic nowcasting system to predict orographic rainfall for the following eight hours. The second probabilistic forecasting system evaluated is REAL-C2, where the numerical weather prediction COSMO-2 is initialized with 25 different initial conditions derived from a four-day nowcast with the radar ensemble REAL. Additionally, three deterministic forecasting chains were analysed. The performance of these five flash-flood forecasting systems was analysed for 1389 hours between June 2007 and December 2010 for which NORA forecasts were issued, due to the presence of orographic forcing. We found a clear preference for the probabilistic approach. Discharge forecasts perform better when forced by NORA rather than by a persistent radar QPE for lead times up to eight hours and for all discharge thresholds analysed. The best results were, however, obtained with the REAL-C2 forecasting chain, which was also remarkably skilful even with the highest thresholds. However, for regions where REAL cannot be produced, NORA might be an option for forecasting events triggered by orographic forcing.

Flash-flood early warning using weather radar data: from nowcasting to forecasting

NASA Astrophysics Data System (ADS)

Liechti, K.; Panziera, L.; Germann, U.; Zappa, M.

2013-01-01

This study explores the limits of radar-based forecasting for hydrological runoff prediction. Two novel probabilistic radar-based forecasting chains for flash-flood early warning are investigated in three catchments in the Southern Swiss Alps and set in relation to deterministic discharge forecast for the same catchments. The first probabilistic radar-based forecasting chain is driven by NORA (Nowcasting of Orographic Rainfall by means of Analogues), an analogue-based heuristic nowcasting system to predict orographic rainfall for the following eight hours. The second probabilistic forecasting system evaluated is REAL-C2, where the numerical weather prediction COSMO-2 is initialized with 25 different initial conditions derived from a four-day nowcast with the radar ensemble REAL. Additionally, three deterministic forecasting chains were analysed. The performance of these five flash-flood forecasting systems was analysed for 1389 h between June 2007 and December 2010 for which NORA forecasts were issued, due to the presence of orographic forcing. We found a clear preference for the probabilistic approach. Discharge forecasts perform better when forced by NORA rather than by a persistent radar QPE for lead times up to eight hours and for all discharge thresholds analysed. The best results were, however, obtained with the REAL-C2 forecasting chain, which was also remarkably skilful even with the highest thresholds. However, for regions where REAL cannot be produced, NORA might be an option for forecasting events triggered by orographic precipitation.

Designing and operating infrastructure for nonstationary flood risk management

NASA Astrophysics Data System (ADS)

Doss-Gollin, J.; Farnham, D. J.; Lall, U.

2017-12-01

Climate exhibits organized low-frequency and regime-like variability at multiple time scales, causing the risk associated with climate extremes such as floods and droughts to vary in time. Despite broad recognition of this nonstationarity, there has been little theoretical development of ideas for the design and operation of infrastructure considering the regime structure of such changes and their potential predictability. We use paleo streamflow reconstructions to illustrate an approach to the design and operation of infrastructure to address nonstationary flood and drought risk. Specifically, we consider the tradeoff between flood control and conservation storage, and develop design and operation principles for allocating these storage volumes considering both a m-year project planning period and a n-year historical sampling record. As n increases, the potential uncertainty in probabilistic estimates of the return periods associated with the T-year extreme event decreases. As the duration m of the future operation period decreases, the uncertainty associated with the occurrence of the T-year event also increases. Finally, given the quasi-periodic nature of the system it may be possible to offer probabilistic predictions of the conditions in the m-year future period, especially if m is small. In the context of such predictions, one can consider that a m-year prediction may have lower bias, but higher variance, than would be associated with using a stationary estimate from the preceding n years. This bias-variance trade-off, and the potential for considering risk management for multiple values of m, provides an interesting system design challenge. We use wavelet-based simulation models in a Bayesian framework to estimate these biases and uncertainty distributions and devise a risk-optimized decision rule for the allocation of flood and conservation storage. The associated theoretical development also provides a methodology for the sizing of storage for new infrastructure under nonstationarity, and an examination of risk adaptation measures which consider both short term and long term options simultaneously.

Probabilistic Flood Mapping using Volunteered Geographical Information

NASA Astrophysics Data System (ADS)

Rivera, S. J.; Girons Lopez, M.; Seibert, J.; Minsker, B. S.

2016-12-01

Flood extent maps are widely used by decision makers and first responders to provide critical information that prevents economic impacts and the loss of human lives. These maps are usually obtained from sensory data and/or hydrologic models, which often have limited coverage in space and time. Recent developments in social media and communication technology have created a wealth of near-real-time, user-generated content during flood events in many urban areas, such as flooded locations, pictures of flooding extent and height, etc. These data could improve decision-making and response operations as events unfold. However, the integration of these data sources has been limited due to the need for methods that can extract and translate the data into useful information for decision-making. This study presents an approach that uses volunteer geographic information (VGI) and non-traditional data sources (i.e., Twitter, Flicker, YouTube, and 911 and 311 calls) to generate/update the flood extent maps in areas where no models and/or gauge data are operational. The approach combines Web-crawling and computer vision techniques to gather information about the location, extent, and water height of the flood from unstructured textual data, images, and videos. These estimates are then used to provide an updated flood extent map for areas surrounding the geo-coordinate of the VGI through the application of a Hydro Growing Region Algorithm (HGRA). HGRA combines hydrologic and image segmentation concepts to estimate a probabilistic flooding extent along the corresponding creeks. Results obtained for a case study in Austin, TX (i.e., 2015 Memorial Day flood) were comparable to those obtained by a calibrated hydrologic model and had good spatial correlation with flooding extents estimated by the Federal Emergency Management Agency (FEMA).

Design flood estimation in ungauged basins: probabilistic extension of the design-storm concept

NASA Astrophysics Data System (ADS)

Berk, Mario; Špačková, Olga; Straub, Daniel

2016-04-01

Design flood estimation in ungauged basins is an important hydrological task, which is in engineering practice typically solved with the design storm concept. However, neglecting the uncertainty in the hydrological response of the catchment through the assumption of average-recurrence-interval (ARI) neutrality between rainfall and runoff can lead to flawed design flood estimates. Additionally, selecting a single critical rainfall duration neglects the contribution of other rainfall durations on the probability of extreme flood events. In this study, the design flood problem is approached with concepts from structural reliability that enable a consistent treatment of multiple uncertainties in estimating the design flood. The uncertainty of key model parameters are represented probabilistically and the First-Order Reliability Method (FORM) is used to compute the flood exceedance probability. As an important by-product, the FORM analysis provides the most likely parameter combination to lead to a flood with a certain exceedance probability; i.e. it enables one to find representative scenarios for e.g., a 100 year or a 1000 year flood. Possible different rainfall durations are incorporated by formulating the event of a given design flood as a series system. The method is directly applicable in practice, since for the description of the rainfall depth-duration characteristics, the same inputs as for the classical design storm methods are needed, which are commonly provided by meteorological services. The proposed methodology is applied to a case study of Trauchgauer Ach catchment in Bavaria, SCS Curve Number (CN) and Unit hydrograph models are used for modeling the hydrological process. The results indicate, in accordance with past experience, that the traditional design storm concept underestimates design floods.

A hydro-meteorological ensemble prediction system for real-time flood forecasting purposes in the Milano area

NASA Astrophysics Data System (ADS)

Ravazzani, Giovanni; Amengual, Arnau; Ceppi, Alessandro; Romero, Romualdo; Homar, Victor; Mancini, Marco

2015-04-01

Analysis of forecasting strategies that can provide a tangible basis for flood early warning procedures and mitigation measures over the Western Mediterranean region is one of the fundamental motivations of the European HyMeX programme. Here, we examine a set of hydro-meteorological episodes that affected the Milano urban area for which the complex flood protection system of the city did not completely succeed before the occurred flash-floods. Indeed, flood damages have exponentially increased in the area during the last 60 years, due to industrial and urban developments. Thus, the improvement of the Milano flood control system needs a synergism between structural and non-structural approaches. The flood forecasting system tested in this work comprises the Flash-flood Event-based Spatially distributed rainfall-runoff Transformation, including Water Balance (FEST-WB) and the Weather Research and Forecasting (WRF) models, in order to provide a hydrological ensemble prediction system (HEPS). Deterministic and probabilistic quantitative precipitation forecasts (QPFs) have been provided by WRF model in a set of 48-hours experiments. HEPS has been generated by combining different physical parameterizations (i.e. cloud microphysics, moist convection and boundary-layer schemes) of the WRF model in order to better encompass the atmospheric processes leading to high precipitation amounts. We have been able to test the value of a probabilistic versus a deterministic framework when driving Quantitative Discharge Forecasts (QDFs). Results highlight (i) the benefits of using a high-resolution HEPS in conveying uncertainties for this complex orographic area and (ii) a better simulation of the most of extreme precipitation events, potentially enabling valuable probabilistic QDFs. Hence, the HEPS copes with the significant deficiencies found in the deterministic QPFs. These shortcomings would prevent to correctly forecast the location and timing of high precipitation rates and total amounts at the catchment scale, thus impacting heavily the deterministic QDFs. In contrast, early warnings would have been possible within a HEPS context for the Milano area, proving the suitability of such system for civil protection purposes.

44 CFR 206.252 - Insurance requirements for facilities damaged by flood.

Code of Federal Regulations, 2010 CFR

2010-10-01

... facilities damaged by flood. 206.252 Section 206.252 Emergency Management and Assistance FEDERAL EMERGENCY... Assistance Insurance Requirements § 206.252 Insurance requirements for facilities damaged by flood. (a) Where an insurable building damaged by flooding is located in a special flood hazard area identified for...

Framework for probabilistic flood risk assessment in an Alpine region

NASA Astrophysics Data System (ADS)

Schneeberger, Klaus; Huttenlau, Matthias; Steinberger, Thomas; Achleitner, Stefan; Stötter, Johann

2014-05-01

Flooding is among the natural hazards that regularly cause significant losses to property and human lives. The assessment of flood risk delivers crucial information for all participants involved in flood risk management and especially for local authorities and insurance companies in order to estimate the possible flood losses. Therefore a framework for assessing flood risk has been developed and is introduced with the presented contribution. Flood risk is thereby defined as combination of the probability of flood events and of potential flood damages. The probability of occurrence is described through the spatial and temporal characterisation of flood. The potential flood damages are determined in the course of vulnerability assessment, whereas, the exposure and the vulnerability of the elements at risks are considered. Direct costs caused by flooding with the focus on residential building are analysed. The innovative part of this contribution lies on the development of a framework which takes the probability of flood events and their spatio-temporal characteristic into account. Usually the probability of flooding will be determined by means of recurrence intervals for an entire catchment without any spatial variation. This may lead to a misinterpretation of the flood risk. Within the presented framework the probabilistic flood risk assessment is based on analysis of a large number of spatial correlated flood events. Since the number of historic flood events is relatively small additional events have to be generated synthetically. This temporal extrapolation is realised by means of the method proposed by Heffernan and Tawn (2004). It is used to generate a large number of possible spatial correlated flood events within a larger catchment. The approach is based on the modelling of multivariate extremes considering the spatial dependence structure of flood events. The input for this approach are time series derived from river gauging stations. In a next step the historic and synthetic flood events have to be spatially interpolated from point scale (i.e. river gauges) to the river network. Therefore, topological kriging (Top-kriging) proposed by Skøien et al. (2006) is applied. Top-kriging considers the nested structure of river networks and is therefore suitable to regionalise flood characteristics. Thus, the characteristics of a large number of possible flood events can be transferred to arbitrary locations (e.g. community level) at the river network within a study region. This framework has been used to generate a set of spatial correlated river flood events in the Austrian Federal Province of Vorarlberg. In addition, loss-probability-curves for each community has been calculated based on official inundation maps of public authorities, elements at risks and their vulnerability. One location along the river network within each community refers as interface between the set of flood events and the individual loss-probability relationships for the individual communities. Consequently, every flood event from the historic and synthetic generated dataset can be monetary evaluated. Thus, a time series comprising a large number of flood events and their corresponding monetary losses serves as basis for a probabilistic flood risk assessment. This includes expected annual losses and estimates of extreme event losses, which occur over the course of a certain time period. The gained results are essential decision-support for primary insurers, reinsurance companies and public authorities in order to setup a scale adequate risk management.

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

NASA Astrophysics Data System (ADS)

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% probability of exceeding the Medium Level Alert in two days. Rainfall stations upstream of the West Rapti catchment recorded heavy rainfall on 26 July, and localized forecasts from the probabilistic model at 8 am suggested that the water level would cross a pre-determined warning level in the next 3 hours. The Flood Forecasting Section at DHM issued a flood advisory, and disseminated SMS flood alerts to more than 13,000 at-risk people residing along the floodplains. Water levels crossed the danger threshold (5.4 meters) at 11 am, peaking at 8.15 meters at 10 pm. Extension of the warning lead time from probabilistic forecasts was significant in minimising the risk to lives and livelihoods as communities gained extra time to prepare, evacuate and respond. Likewise, longer timescale forecasts from GLoFAS could be potentially linked with no-regret early actions leading to improved preparedness and emergency response. These forecasting tools have contributed to enhance the effectiveness and efficiency of existing community based systems, increasing the lead time for response. Nevertheless, extensive work is required on appropriate ways to interpret and disseminate probabilistic forecasts having longer (2-14 days) and shorter (3-5 hours) time horizon for operational deployment as there are numerous uncertainties associated with predictions.

Inclusion of potential vorticity uncertainties into a hydrometeorological forecasting chain: application to a medium size basin of Mediterranean Spain

NASA Astrophysics Data System (ADS)

Amengual, A.; Romero, R.; Vich, M.; Alonso, S.

2009-06-01

The improvement of the short- and mid-range numerical runoff forecasts over the flood-prone Spanish Mediterranean area is a challenging issue. This work analyses four intense precipitation events which produced floods of different magnitude over the Llobregat river basin, a medium size catchment located in Catalonia, north-eastern Spain. One of them was a devasting flash flood - known as the "Montserrat" event - which produced 5 fatalities and material losses estimated at about 65 million euros. The characterization of the Llobregat basin's hydrological response to these floods is first assessed by using rain-gauge data and the Hydrologic Engineering Center's Hydrological Modeling System (HEC-HMS) runoff model. In second place, the non-hydrostatic fifth-generation Pennsylvania State University/NCAR mesoscale model (MM5) is nested within the ECMWF large-scale forecast fields in a set of 54 h period simulations to provide quantitative precipitation forecasts (QPFs) for each hydrometeorological episode. The hydrological model is forced with these QPFs to evaluate the reliability of the resulting discharge forecasts, while an ensemble prediction system (EPS) based on perturbed atmospheric initial and boundary conditions has been designed to test the value of a probabilistic strategy versus the previous deterministic approach. Specifically, a Potential Vorticity (PV) Inversion technique has been used to perturb the MM5 model initial and boundary states (i.e. ECMWF forecast fields). For that purpose, a PV error climatology has been previously derived in order to introduce realistic PV perturbations in the EPS. Results show the benefits of using a probabilistic approach in those cases where the deterministic QPF presents significant deficiencies over the Llobregat river basin in terms of the rainfall amounts, timing and localization. These deficiences in precipitation fields have a major impact on flood forecasts. Our ensemble strategy has been found useful to reduce the biases at different hydrometric sections along the watershed. Therefore, in an operational context, the devised methodology could be useful to expand the lead times associated with the prediction of similar future floods, helping to alleviate their possible hazardous consequences.

Inclusion of potential vorticity uncertainties into a hydrometeorological forecasting chain: application to a medium size basin of Mediterranean Spain

NASA Astrophysics Data System (ADS)

Amengual, A.; Romero, R.; Vich, M.; Alonso, S.

2009-01-01

The improvement of the short- and mid-range numerical runoff forecasts over the flood-prone Spanish Mediterranean area is a challenging issue. This work analyses four intense precipitation events which produced floods of different magnitude over the Llobregat river basin, a medium size catchment located in Catalonia, north-eastern Spain. One of them was a devasting flash flood - known as the "Montserrat" event - which produced 5 fatalities and material losses estimated at about 65 million euros. The characterization of the Llobregat basin's hydrological response to these floods is first assessed by using rain-gauge data and the Hydrologic Engineering Center's Hydrological Modeling System (HEC-HMS) runoff model. In second place, the non-hydrostatic fifth-generation Pennsylvania State University/NCAR mesoscale model (MM5) is nested within the ECMWF large-scale forecast fields in a set of 54 h period simulations to provide quantitative precipitation forecasts (QPFs) for each hydrometeorological episode. The hydrological model is forced with these QPFs to evaluate the reliability of the resulting discharge forecasts, while an ensemble prediction system (EPS) based on perturbed atmospheric initial and boundary conditions has been designed to test the value of a probabilistic strategy versus the previous deterministic approach. Specifically, a Potential Vorticity (PV) Inversion technique has been used to perturb the MM5 model initial and boundary states (i.e. ECMWF forecast fields). For that purpose, a PV error climatology has been previously derived in order to introduce realistic PV perturbations in the EPS. Results show the benefits of using a probabilistic approach in those cases where the deterministic QPF presents significant deficiencies over the Llobregat river basin in terms of the rainfall amounts, timing and localization. These deficiences in precipitation fields have a major impact on flood forecasts. Our ensemble strategy has been found useful to reduce the biases at different hydrometric sections along the watershed. Therefore, in an operational context, the devised methodology could be useful to expand the lead times associated with the prediction of similar future floods, helping to alleviate their possible hazardous consequences.

Engineering geology considerations for park planning, Antelope Island State Park, Davis County, Utah

USGS Publications Warehouse

Hecker, Suzanne; Case, William F.; King, Jon K.; Willis, Grant C.

2000-01-01

Report: 00-1 In the mid-1980s, historically high levels of Great Salt Lake caused damage to park facilities on Antelope Island and destroyed the causeway linking the park to the mainland. Information on the engineering geology of Antelope Islandcan be used to improve park facilities and reduce the risk from geologic hazards and poor construction conditions. Certain characteristics of the geologic environment need to be considered in park planning. During wet cycles, Great Salt Lake may reach static levels of 4,217 feet (1,285.3 m), and wave- and wind-elevated levels locally may reach 6.5 feet (2 m) higher. A probabilistic assessment of the earthquake ground-shaking hazard along the Wasatch Front indicates that peak ground accelerations of approximately 0.20 to 0.30 g have a one-in-ten chance of being exceeded in 50 years on the island. A slope-failure hazard exists locally in colluvial and Lake Bonneville deposits, along the modern shore, and beneath cliffs. Flash-flood and debris-flow hazards exist on alluvial fans. Areas in the southern two-thirds of the island may have a relatively high potential for radon emission. Particular soil types on the island may be expansive, compressible, erodible, impermeable, or susceptible to liquefaction or hydrocompaction. The distribution of most geologic hazards can be defined, and many locations on the island have conditions suitable for construction. Lacustrine sand and gravel deposits are wide-spread and have engineering characteristics that are generally favorable for foundations. However, facilities and roads built close to the modern shoreline may be susceptible to lake flooding and erosion, slope failures, shallow ground water, and burial by active sand dunes. Well-graded (poorly sorted) alluvial-fan deposits are generally most suitable for wastewater disposal, although they may be subject to flooding or be underlain by low-permeability, fine-grained lacustrine deposits.

Evaluation of flood preparedness in government healthcare facilities in Eastern Province, Sri Lanka

PubMed Central

Farley, Jessica M.; Suraweera, Inoka; Perera, W. L. S. P.; Hess, Jeremy; Ebi, Kristie L.

2017-01-01

ABSTRACT Background: Sri Lanka is vulnerable to floods and other hydro-meteorological disasters. Climate change is projected to increase the intensity of these events. Objective: This study aimed to assess the flood preparedness in healthcare facilities in Eastern Province. Design: This was a cross-sectional, descriptive, mixed methods study conducted in Trincomalee District. Surveys were conducted in 31 government healthcare facilities, using a pre-tested, structured questionnaire covering the last 5 years. Seven in-depth interviews were conducted with randomly selected Medical Officers in Charge or their equivalent, and 3 interviews were conducted with Medical Offices of Health. Results: Two general hospitals, 3 base hospitals, 11 divisional hospitals, and 15 primary care units were included. Six respondents (19.4%) reported flooding in their facility, and 19 (61.3%) reported flooding in their catchment area. For the health workforce, 77.4% of respondents reported not enough staff to perform normal service delivery during disasters, and 25.5% reported staff absenteeism due to flooding. Several respondents expressed a desire for more disaster-specific and general clinical training opportunities for themselves and their staff. Most respondents (80.7%) reported no delays in supply procurement during weather emergencies, but 61.3% reported insufficient supplies to maintain normal service delivery during disasters. Four facilities (12.9%) had disaster preparedness plans, and 4 (12.9%) had any staff trained on disaster preparedness or management within the last year. One quarter (25.8%) of respondents had received any written guidance on disaster preparedness from the regional, provincial, or national level in the last year. Conclusions: While there is a strong health system operating in Sri Lanka, improvements are needed in localized and appropriate disaster-related training, resources for continuing clinical education, and investments in workforce to strengthen flood and other disaster resilience within the government healthcare system in the study district. PMID:28612689

Application of Medium and Seasonal Flood Forecasts for Agriculture Damage Assessment

NASA Astrophysics Data System (ADS)

Fakhruddin, Shamsul; Ballio, Francesco; Menoni, Scira

2015-04-01

Early warning is a key element for disaster risk reduction. In recent decades, major advancements have been made in medium range and seasonal flood forecasting. This progress provides a great opportunity to reduce agriculture damage and improve advisories for early action and planning for flood hazards. This approach can facilitate proactive rather than reactive management of the adverse consequences of floods. In the agricultural sector, for instance, farmers can take a diversity of options such as changing cropping patterns, applying fertilizer, irrigating and changing planting timing. An experimental medium range (1-10 day) and seasonal (20-25 days) flood forecasting model has been developed for Thailand and Bangladesh. It provides 51 sets of discharge ensemble forecasts of 1-10 days with significant persistence and high certainty and qualitative outlooks for 20-25 days. This type of forecast could assist farmers and other stakeholders for differential preparedness activities. These ensembles probabilistic flood forecasts have been customized based on user-needs for community-level application focused on agriculture system. The vulnerabilities of agriculture system were calculated based on exposure, sensitivity and adaptive capacity. Indicators for risk and vulnerability assessment were conducted through community consultations. The forecast lead time requirement, user-needs, impacts and management options for crops were identified through focus group discussions, informal interviews and community surveys. This paper illustrates potential applications of such ensembles for probabilistic medium range and seasonal flood forecasts in a way that is not commonly practiced globally today.

Flooding

MedlinePlus

... flooding For communities, companies, or water and wastewater facilities: Flood Resilience Guide is your one-stop resource ... Zika Top of Page For water and wastewater facilities: For water and wastewater facilities : Suggested post-hurricane ...

Probabilistic Modeling of Settlement Risk at Land Disposal Facilities - 12304

DOE Office of Scientific and Technical Information (OSTI.GOV)

Foye, Kevin C.; Soong, Te-Yang

2012-07-01

The long-term reliability of land disposal facility final cover systems - and therefore the overall waste containment - depends on the distortions imposed on these systems by differential settlement/subsidence. The evaluation of differential settlement is challenging because of the heterogeneity of the waste mass (caused by inconsistent compaction, void space distribution, debris-soil mix ratio, waste material stiffness, time-dependent primary compression of the fine-grained soil matrix, long-term creep settlement of the soil matrix and the debris, etc.) at most land disposal facilities. Deterministic approaches to long-term final cover settlement prediction are not able to capture the spatial variability in the wastemore » mass and sub-grade properties which control differential settlement. An alternative, probabilistic solution is to use random fields to model the waste and sub-grade properties. The modeling effort informs the design, construction, operation, and maintenance of land disposal facilities. A probabilistic method to establish design criteria for waste placement and compaction is introduced using the model. Random fields are ideally suited to problems of differential settlement modeling of highly heterogeneous foundations, such as waste. Random fields model the seemingly random spatial distribution of a design parameter, such as compressibility. When used for design, the use of these models prompts the need for probabilistic design criteria. It also allows for a statistical approach to waste placement acceptance criteria. An example design evaluation was performed, illustrating the use of the probabilistic differential settlement simulation methodology to assemble a design guidance chart. The purpose of this design evaluation is to enable the designer to select optimal initial combinations of design slopes and quality control acceptance criteria that yield an acceptable proportion of post-settlement slopes meeting some design minimum. For this specific example, relative density, which can be determined through field measurements, was selected as the field quality control parameter for waste placement. This technique can be extended to include a rigorous performance-based methodology using other parameters (void space criteria, debris-soil mix ratio, pre-loading, etc.). As shown in this example, each parameter range, or sets of parameter ranges can be selected such that they can result in an acceptable, long-term differential settlement according to the probabilistic model. The methodology can also be used to re-evaluate the long-term differential settlement behavior at closed land disposal facilities to identify, if any, problematic facilities so that remedial action (e.g., reinforcement of upper and intermediate waste layers) can be implemented. Considering the inherent spatial variability in waste and earth materials and the need for engineers to apply sound quantitative practices to engineering analysis, it is important to apply the available probabilistic techniques to problems of differential settlement. One such method to implement probability-based differential settlement analyses for the design of landfill final covers has been presented. The design evaluation technique presented is one tool to bridge the gap from deterministic practice to probabilistic practice. (authors)« less

Preparing for floods: flood forecasting and early warning

NASA Astrophysics Data System (ADS)

Cloke, Hannah

2016-04-01

Flood forecasting and early warning has continued to stride ahead in strengthening the preparedness phases of disaster risk management, saving lives and property and reducing the overall impact of severe flood events. For example, continental and global scale flood forecasting systems such as the European Flood Awareness System and the Global Flood Awareness System provide early information about upcoming floods in real time to various decisionmakers. Studies have found that there are monetary benefits to implementing these early flood warning systems, and with the science also in place to provide evidence of benefit and hydrometeorological institutional outlooks warming to the use of probabilistic forecasts, the uptake over the last decade has been rapid and sustained. However, there are many further challenges that lie ahead to improve the science supporting flood early warning and to ensure that appropriate decisions are made to maximise flood preparedness.

A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1) for spatial prediction of floods

NASA Astrophysics Data System (ADS)

Tien Bui, Dieu; Hoang, Nhat-Duc

2017-09-01

In this study, a probabilistic model, named as BayGmmKda, is proposed for flood susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian framework constructed by a combination of a Gaussian mixture model (GMM), radial-basis-function Fisher discriminant analysis (RBFDA), and a geographic information system (GIS) database. In the Bayesian framework, GMM is used for modeling the data distribution of flood-influencing factors in the GIS database, whereas RBFDA is utilized to construct a latent variable that aims at enhancing the model performance. As a result, the posterior probabilistic output of the BayGmmKda model is used as flood susceptibility index. Experiment results showed that the proposed hybrid framework is superior to other benchmark models, including the adaptive neuro-fuzzy inference system and the support vector machine. To facilitate the model implementation, a software program of BayGmmKda has been developed in MATLAB. The BayGmmKda program can accurately establish a flood susceptibility map for the study region. Accordingly, local authorities can overlay this susceptibility map onto various land-use maps for the purpose of land-use planning or management.

An integrated approach to flood hazard assessment on alluvial fans using numerical modeling, field mapping, and remote sensing

USGS Publications Warehouse

Pelletier, J.D.; Mayer, L.; Pearthree, P.A.; House, P.K.; Demsey, K.A.; Klawon, J.K.; Vincent, K.R.

2005-01-01

Millions of people in the western United States live near the dynamic, distributary channel networks of alluvial fans where flood behavior is complex and poorly constrained. Here we test a new comprehensive approach to alluvial-fan flood hazard assessment that uses four complementary methods: two-dimensional raster-based hydraulic modeling, satellite-image change detection, fieldbased mapping of recent flood inundation, and surficial geologic mapping. Each of these methods provides spatial detail lacking in the standard method and each provides critical information for a comprehensive assessment. Our numerical model simultaneously solves the continuity equation and Manning's equation (Chow, 1959) using an implicit numerical method. It provides a robust numerical tool for predicting flood flows using the large, high-resolution Digital Elevation Models (DEMs) necessary to resolve the numerous small channels on the typical alluvial fan. Inundation extents and flow depths of historic floods can be reconstructed with the numerical model and validated against field- and satellite-based flood maps. A probabilistic flood hazard map can also be constructed by modeling multiple flood events with a range of specified discharges. This map can be used in conjunction with a surficial geologic map to further refine floodplain delineation on fans. To test the accuracy of the numerical model, we compared model predictions of flood inundation and flow depths against field- and satellite-based flood maps for two recent extreme events on the southern Tortolita and Harquahala piedmonts in Arizona. Model predictions match the field- and satellite-based maps closely. Probabilistic flood hazard maps based on the 10 yr, 100 yr, and maximum floods were also constructed for the study areas using stream gage records and paleoflood deposits. The resulting maps predict spatially complex flood hazards that strongly reflect small-scale topography and are consistent with surficial geology. In contrast, FEMA Flood Insurance Rate Maps (FIRMs) based on the FAN model predict uniformly high flood risk across the study areas without regard for small-scale topography and surficial geology. ?? 2005 Geological Society of America.

Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Wahl, Thomas; Plant, Nathaniel G.; Long, Joseph W.

2016-05-01

We assess erosion and flooding risk in the northern Gulf of Mexico by identifying interdependencies among oceanographic drivers and probabilistically modeling the resulting potential for coastal change. Wave and water level observations are used to determine relationships between six hydrodynamic parameters that influence total water level and therefore erosion and flooding, through consideration of a wide range of univariate distribution functions and multivariate elliptical copulas. Using these relationships, we explore how different our interpretation of the present-day erosion/flooding risk could be if we had seen more or fewer extreme realizations of individual and combinations of parameters in the past by simulating 10,000 physically and statistically consistent sea-storm time series. We find that seasonal total water levels associated with the 100 year return period could be up to 3 m higher in summer and 0.6 m higher in winter relative to our best estimate based on the observational records. Impact hours of collision and overwash—where total water levels exceed the dune toe or dune crest elevations—could be on average 70% (collision) and 100% (overwash) larger than inferred from the observations. Our model accounts for non-stationarity in a straightforward, non-parametric way that can be applied (with little adjustments) to many other coastlines. The probabilistic model presented here, which accounts for observational uncertainty, can be applied to other coastlines where short record lengths limit the ability to identify the full range of possible wave and water level conditions that coastal mangers and planners must consider to develop sustainable management strategies.

Improving Global Forecast System of extreme precipitation events with regional statistical model: Application of quantile-based probabilistic forecasts

NASA Astrophysics Data System (ADS)

Shastri, Hiteshri; Ghosh, Subimal; Karmakar, Subhankar

2017-02-01

Forecasting of extreme precipitation events at a regional scale is of high importance due to their severe impacts on society. The impacts are stronger in urban regions due to high flood potential as well high population density leading to high vulnerability. Although significant scientific improvements took place in the global models for weather forecasting, they are still not adequate at a regional scale (e.g., for an urban region) with high false alarms and low detection. There has been a need to improve the weather forecast skill at a local scale with probabilistic outcome. Here we develop a methodology with quantile regression, where the reliably simulated variables from Global Forecast System are used as predictors and different quantiles of rainfall are generated corresponding to that set of predictors. We apply this method to a flood-prone coastal city of India, Mumbai, which has experienced severe floods in recent years. We find significant improvements in the forecast with high detection and skill scores. We apply the methodology to 10 ensemble members of Global Ensemble Forecast System and find a reduction in ensemble uncertainty of precipitation across realizations with respect to that of original precipitation forecasts. We validate our model for the monsoon season of 2006 and 2007, which are independent of the training/calibration data set used in the study. We find promising results and emphasize to implement such data-driven methods for a better probabilistic forecast at an urban scale primarily for an early flood warning.

Probabilistic assessment of erosion and flooding risk in the northern Gulf of Mexico

USGS Publications Warehouse

Plant, Nathaniel G.; Wahl, Thomas; Long, Joseph W.

2016-01-01

We assess erosion and flooding risk in the northern Gulf of Mexico by identifying interdependencies among oceanographic drivers and probabilistically modeling the resulting potential for coastal change. Wave and water level observations are used to determine relationships between six hydrodynamic parameters that influence total water level and therefore erosion and flooding, through consideration of a wide range of univariate distribution functions and multivariate elliptical copulas. Using these relationships, we explore how different our interpretation of the present-day erosion/flooding risk could be if we had seen more or fewer extreme realizations of individual and combinations of parameters in the past by simulating 10,000 physically and statistically consistent sea-storm time series. We find that seasonal total water levels associated with the 100 year return period could be up to 3 m higher in summer and 0.6 m higher in winter relative to our best estimate based on the observational records. Impact hours of collision and overwash—where total water levels exceed the dune toe or dune crest elevations—could be on average 70% (collision) and 100% (overwash) larger than inferred from the observations. Our model accounts for non-stationarity in a straightforward, non-parametric way that can be applied (with little adjustments) to many other coastlines. The probabilistic model presented here, which accounts for observational uncertainty, can be applied to other coastlines where short record lengths limit the ability to identify the full range of possible wave and water level conditions that coastal mangers and planners must consider to develop sustainable management strategies.

Flooding Fragility Experiments and Prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Curtis L.; Tahhan, Antonio; Muchmore, Cody

2016-09-01

This report describes the work that has been performed on flooding fragility, both the experimental tests being carried out and the probabilistic fragility predictive models being produced in order to use the text results. Flooding experiments involving full-scale doors have commenced in the Portal Evaluation Tank. The goal of these experiments is to develop a full-scale component flooding experiment protocol and to acquire data that can be used to create Bayesian regression models representing the fragility of these components. This work is in support of the Risk-Informed Safety Margin Characterization (RISMC) Pathway external hazards evaluation research and development.

Global probabilistic projections of extreme sea levels show intensification of coastal flood hazard.

PubMed

Vousdoukas, Michalis I; Mentaschi, Lorenzo; Voukouvalas, Evangelos; Verlaan, Martin; Jevrejeva, Svetlana; Jackson, Luke P; Feyen, Luc

2018-06-18

Global warming is expected to drive increasing extreme sea levels (ESLs) and flood risk along the world's coastlines. In this work we present probabilistic projections of ESLs for the present century taking into consideration changes in mean sea level, tides, wind-waves, and storm surges. Between the year 2000 and 2100 we project a very likely increase of the global average 100-year ESL of 34-76 cm under a moderate-emission-mitigation-policy scenario and of 58-172 cm under a business as usual scenario. Rising ESLs are mostly driven by thermal expansion, followed by contributions from ice mass-loss from glaciers, and ice-sheets in Greenland and Antarctica. Under these scenarios ESL rise would render a large part of the tropics exposed annually to the present-day 100-year event from 2050. By the end of this century this applies to most coastlines around the world, implying unprecedented flood risk levels unless timely adaptation measures are taken.

The case for probabilistic forecasting in hydrology

NASA Astrophysics Data System (ADS)

Krzysztofowicz, Roman

2001-08-01

That forecasts should be stated in probabilistic, rather than deterministic, terms has been argued from common sense and decision-theoretic perspectives for almost a century. Yet most operational hydrological forecasting systems produce deterministic forecasts and most research in operational hydrology has been devoted to finding the 'best' estimates rather than quantifying the predictive uncertainty. This essay presents a compendium of reasons for probabilistic forecasting of hydrological variates. Probabilistic forecasts are scientifically more honest, enable risk-based warnings of floods, enable rational decision making, and offer additional economic benefits. The growing demand for information about risk and the rising capability to quantify predictive uncertainties create an unparalleled opportunity for the hydrological profession to dramatically enhance the forecasting paradigm.

100-Year flood–it's all about chance

USGS Publications Warehouse

Holmes, Robert R.; Dinicola, Karen

2010-01-01

In the 1960's, the United States government decided to use the 1-percent annual exceedance probability (AEP) flood as the basis for the National Flood Insurance Program. The 1-percent AEP flood was thought to be a fair balance between protecting the public and overly stringent regulation. Because the 1-percent AEP flood has a 1 in 100 chance of being equaled or exceeded in any 1 year, and it has an average recurrence interval of 100 years, it often is referred to as the '100-year flood'. The term '100-year flood' is part of the national lexicon, but is often a source of confusion by those not familiar with flood science and statistics. This poster is an attempt to explain the concept, probabilistic nature, and inherent uncertainties of the '100-year flood' to the layman.

Using ensemble rainfall predictions in a countrywide flood forecasting model in Scotland

NASA Astrophysics Data System (ADS)

Cranston, M. D.; Maxey, R.; Tavendale, A. C. W.; Buchanan, P.

2012-04-01

Improving flood predictions for all sources of flooding is at the centre of flood risk management policy in Scotland. With the introduction of the Flood Risk Management (Scotland) Act providing a new statutory basis for SEPA's flood warning responsibilities, the pressures on delivering hydrological science developments in support of this legislation has increased. Specifically, flood forecasting capabilities need to develop in support of the need to reduce the impact of flooding through the provision of actively disseminated, reliable and timely flood warnings. Flood forecasting in Scotland has developed significantly in recent years (Cranston and Tavendale, 2012). The development of hydrological models to predict flooding at a catchment scale has relied upon the application of rainfall runoff models utilising raingauge, radar and quantitative precipitation forecasts in the short lead time (less than 6 hours). Single or deterministic forecasts based on highly uncertain rainfall predictions have led to the greatest operational difficulties when communicating flood risk with emergency responders, therefore the emergence of probability-based estimates offers the greatest opportunity for managing uncertain predictions. This paper presents operational application of a physical-conceptual distributed hydrological model on a countrywide basis across Scotland. Developed by CEH Wallingford for SEPA in 2011, Grid-to-Grid (G2G) principally runs in deterministic mode and employs radar and raingauge estimates of rainfall together with weather model predictions to produce forecast river flows, as gridded time-series at a resolution of 1km and for up to 5 days ahead (Cranston, et al., 2012). However the G2G model is now being run operationally using ensemble predictions of rainfall from the MOGREPS-R system to provide probabilistic flood forecasts. By presenting a range of flood predictions on a national scale through this approach, hydrologists are now able to consider an objective measure of the likelihood of flooding impacts to help with risk based emergency communication.

44 CFR 206.252 - Insurance requirements for facilities damaged by flood.

Code of Federal Regulations, 2011 CFR

2011-10-01

... facilities damaged by flood. 206.252 Section 206.252 Emergency Management and Assistance FEDERAL EMERGENCY... Assistance Insurance Requirements § 206.252 Insurance requirements for facilities damaged by flood. (a) Where... insurance policy. (b) The reduction stated above shall not apply to a PNP facility which could not be...

44 CFR 206.253 - Insurance requirements for facilities damaged by disasters other than flood.

Code of Federal Regulations, 2010 CFR

2010-10-01

... facilities damaged by disasters other than flood. 206.253 Section 206.253 Emergency Management and Assistance... by disasters other than flood. (a) Prior to approval of a Federal grant for the restoration of a facility and its contents which were damaged by a disaster other than flood, the Grantee shall notify the...

44 CFR 206.253 - Insurance requirements for facilities damaged by disasters other than flood.

Code of Federal Regulations, 2011 CFR

2011-10-01

... facilities damaged by disasters other than flood. 206.253 Section 206.253 Emergency Management and Assistance... ASSISTANCE Public Assistance Insurance Requirements § 206.253 Insurance requirements for facilities damaged... facility and its contents which were damaged by a disaster other than flood, the Grantee shall notify the...

An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): assessing the added value of probabilistic forecasts

NASA Astrophysics Data System (ADS)

Addor, N.; Jaun, S.; Fundel, F.; Zappa, M.

2012-04-01

The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This model chain relies on deterministic (COSMO-7) and probabilistic (COSMO-LEPS) atmospheric forecasts, which are used to force a semi-distributed hydrological model (PREVAH) coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework with which we assessed the potential of deterministic and probabilistic discharge forecasts for flood mitigation. To study the suitability of HEPS for small-scale basins and to quantify the added value conveyed by the probability information, a 31-month reforecast was produced for the Sihl catchment (336 km2). Several metrics support the conclusion that the performance gain is of up to 2 days lead time for the catchment considered. Brier skill scores show that probabilistic hydrological forecasts outperform their deterministic counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. We finally highlight challenges for making decisions on the basis of hydrological predictions, and discuss the need for a tool to be used in addition to forecasts to compare the different mitigation actions possible in the Sihl catchment.

Use of documentary sources on past flood events for flood risk management and land planning

NASA Astrophysics Data System (ADS)

Cœur, Denis; Lang, Michel

2008-09-01

The knowledge of past catastrophic events can improve flood risk mitigation policy, with a better awareness against risk. As such historical information is usually available in Europe for the past five centuries, historians are able to understand how past society dealt with flood risk, and hydrologists can include information on past floods into an adapted probabilistic framework. In France, Flood Risk Mitigation Maps are based either on the largest historical known flood event or on the 100-year flood event if it is greater. Two actions can be suggested in terms of promoting the use of historical information for flood risk management: (1) the development of a regional flood data base, with both historical and current data, in order to get a good feedback on recent events and to improve the flood risk education and awareness; (2) the commitment to keep a persistent/perennial management of a reference network of hydrometeorological observations for climate change studies.

Linking Science of Flood Forecasts to Humanitarian Actions for Improved Preparedness and Effective Response

NASA Astrophysics Data System (ADS)

Uprety, M.; Dugar, S.; Gautam, D.; Kanel, D.; Kshetri, M.; Kharbuja, R. G.; Acharya, S. H.

2017-12-01

Advances in flood forecasting have provided opportunities for humanitarian responders to employ a range of preparedness activities at different forecast time horizons. Yet, the science of prediction is less understood and realized across the humanitarian landscape, and often preparedness plans are based upon average level of flood risk. Working under the remit of Forecast Based Financing (FbF), we present a pilot from Nepal on how available flood and weather forecast products are informing specific pre-emptive actions in the local preparedness and response plans, thereby supporting government stakeholders and humanitarian agencies to take early actions before an impending flood event. In Nepal, forecasting capabilities are limited but in a state of positive flux. Whilst local flood forecasts based upon rainfall-runoff models are yet to be operationalized, streamflow predictions from Global Flood Awareness System (GLoFAS) can be utilized to plan and implement preparedness activities several days in advance. Likewise, 3-day rainfall forecasts from Nepal Department of Hydrology and Meteorology (DHM) can further inform specific set of early actions for potential flash floods due to heavy precipitation. Existing community based early warning systems in the major river basins of Nepal are utilizing real time monitoring of water levels and rainfall together with localised probabilistic flood forecasts which has increased warning lead time from 2-3 hours to 7-8 hours. Based on these available forecast products, thresholds and trigger levels have been determined for different flood scenarios. Matching these trigger levels and assigning responsibilities to relevant actors for early actions, a set of standard operating procedures (SOPs) are being developed, broadly covering general preparedness activities and science informed anticipatory actions for different forecast lead times followed by the immediate response activities. These SOPs are currently being rolled out and tested by the Ministry of Home Affairs (MoHA) through its district emergency operation centres in West Nepal. Potential scale up and successful implementation of this science based approach would be instrumental to take forward global commitments on disaster risk reduction, climate change adaptation and sustainable goals in Nepal.

Assessment of global flood exposures - developing an appropriate approach

NASA Astrophysics Data System (ADS)

Millinship, Ian; Booth, Naomi

2015-04-01

Increasingly complex probabilistic catastrophe models have become the standard for quantitative flood risk assessments by re/insurance companies. On the one hand, probabilistic modelling of this nature is extremely useful; a large range of risk metrics can be output. However, they can be time consuming and computationally expensive to develop and run. Levels of uncertainty are persistently high despite, or perhaps because of, attempts to increase resolution and complexity. A cycle of dependency between modelling companies and re/insurers has developed whereby available models are purchased, models run, and both portfolio and model data 'improved' every year. This can lead to potential exposures in perils and territories that are not currently modelled being largely overlooked by companies, who may then face substantial and unexpected losses when large events occur in these areas. We present here an approach to assessing global flood exposures which reduces the scale and complexity of approach used and begins with the identification of hotspots where there is a significant exposure to flood risk. The method comprises four stages: i) compile consistent exposure information, ii) to apply reinsurance terms and conditions to calculate values exposed, iii) to assess the potential hazard using a global set of flood hazard maps, and iv) to identify potential risk 'hotspots' which include considerations of spatially and/or temporally clustered historical events, and local flood defences. This global exposure assessment is designed as a scoping exercise, and reveals areas or cities where the potential for accumulated loss is of significant interest to a reinsurance company, and for which there is no existing catastrophe model. These regions are then candidates for the development of deterministic scenarios, or probabilistic models. The key advantages of this approach will be discussed. These include simplicity and ability of business leaders to understand results, as well as ease and speed of analysis and the advantages this can offer in terms of monitoring changing exposures over time. Significantly, in many areas of the world, this increase in exposure is likely to have more of an impact on increasing catastrophe losses than potential anthropogenically driven changes in weather extremes.

Integrated Urban Flood Analysis considering Optimal Operation of Flood Control Facilities in Urban Drainage Networks

NASA Astrophysics Data System (ADS)

Moon, Y. I.; Kim, M. S.; Choi, J. H.; Yuk, G. M.

2017-12-01

eavy rainfall has become a recent major cause of urban area flooding due to the climate change and urbanization. To prevent property damage along with casualties, a system which can alert and forecast urban flooding must be developed. Optimal performance of reducing flood damage can be expected of urban drainage facilities when operated in smaller rainfall events over extreme ones. Thus, the purpose of this study is to execute: A) flood forecasting system using runoff analysis based on short term rainfall; and B) flood warning system which operates based on the data from pump stations and rainwater storage in urban basins. In result of the analysis, it is shown that urban drainage facilities using short term rainfall forecasting data by radar will be more effective to reduce urban flood damage than using only the inflow data of the facility. Keywords: Heavy Rainfall, Urban Flood, Short-term Rainfall Forecasting, Optimal operating of urban drainage facilities. AcknowledgmentsThis research was supported by a grant (17AWMP-B066744-05) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport of Korean government.

Probabilistic modelling of overflow, surcharge and flooding in urban drainage using the first-order reliability method and parameterization of local rain series.

PubMed

Thorndahl, S; Willems, P

2008-01-01

Failure of urban drainage systems may occur due to surcharge or flooding at specific manholes in the system, or due to overflows from combined sewer systems to receiving waters. To quantify the probability or return period of failure, standard approaches make use of the simulation of design storms or long historical rainfall series in a hydrodynamic model of the urban drainage system. In this paper, an alternative probabilistic method is investigated: the first-order reliability method (FORM). To apply this method, a long rainfall time series was divided in rainstorms (rain events), and each rainstorm conceptualized to a synthetic rainfall hyetograph by a Gaussian shape with the parameters rainstorm depth, duration and peak intensity. Probability distributions were calibrated for these three parameters and used on the basis of the failure probability estimation, together with a hydrodynamic simulation model to determine the failure conditions for each set of parameters. The method takes into account the uncertainties involved in the rainstorm parameterization. Comparison is made between the failure probability results of the FORM method, the standard method using long-term simulations and alternative methods based on random sampling (Monte Carlo direct sampling and importance sampling). It is concluded that without crucial influence on the modelling accuracy, the FORM is very applicable as an alternative to traditional long-term simulations of urban drainage systems.

Primary healthcare system capacities for responding to storm and flood-related health problems: a case study from a rural district in central Vietnam

PubMed Central

Van Minh, Hoang; Tuan Anh, Tran; Rocklöv, Joacim; Bao Giang, Kim; Trang, Le Quynh; Sahlen, Klas-Göran; Nilsson, Maria; Weinehall, Lars

2014-01-01

Background As a tropical depression in the East Sea, Vietnam is greatly affected by climate change and natural disasters. Knowledge of the current capacity of the primary healthcare system in Vietnam to respond to health issues associated with storms and floods is very important for policy making in the country. However, there has been little scientific research in this area. Objective This research was to assess primary healthcare system capacities in a rural district in central Vietnam to respond to such health issues. Design This was a cross-sectional descriptive study using quantitative and qualitative approaches. Quantitative methods used self-administered questionnaires. Qualitative methods (in-depth interviews and focus groups discussions) were used to broaden understanding of the quantitative material and to get additional information on actions taken. Results 1) Service delivery: Medical emergency services, especially surgical operations and referral systems, were not always available during the storm and flood seasons. 2) Governance: District emergency plans focus largely on disaster response rather than prevention. The plans did not clearly define the role of primary healthcare and had no clear information on the coordination mechanism among different sectors and organizations. 3) Financing: The budget for prevention and control of flood and storm activities was limited and had no specific items for healthcare activities. Only a little additional funding was available, but the procedures to get this funding were usually time-consuming. 4) Human resources: Medical rescue teams were established, but there were no epidemiologists or environmental health specialists to take care of epidemiological issues. Training on prevention and control of climate change and disaster-related health issues did not meet actual needs. 5) Information and research: Data that can be used for planning and management (including population and epidemiological data) were largely lacking. The district lacked a disease early-warning system. 6) Medical products and technology: Emergency treatment protocols were not available in every studied health facility. Conclusions The primary care system capacity in rural Vietnam is inadequate for responding to storm and flood-related health problems in terms of preventive and treatment healthcare. Developing clear facility preparedness plans, which detail standard operating procedures during floods and identify specific job descriptions, would strengthen responses to future floods. Health facilities should have contingency funds available for emergency response in the event of storms and floods. Health facilities should ensure that standard protocols exist in order to improve responses in the event of floods. Introduction of a computerized health information system would accelerate information and data processing. National and local policies need to be strengthened and developed in a way that transfers into action in local rural communities. PMID:25511879

Primary healthcare system capacities for responding to storm and flood-related health problems: a case study from a rural district in central Vietnam.

PubMed

Van Minh, Hoang; Tuan Anh, Tran; Rocklöv, Joacim; Bao Giang, Kim; Trang, Le Quynh; Sahlen, Klas-Göran; Nilsson, Maria; Weinehall, Lars

2014-01-01

As a tropical depression in the East Sea, Vietnam is greatly affected by climate change and natural disasters. Knowledge of the current capacity of the primary healthcare system in Vietnam to respond to health issues associated with storms and floods is very important for policy making in the country. However, there has been little scientific research in this area. This research was to assess primary healthcare system capacities in a rural district in central Vietnam to respond to such health issues. This was a cross-sectional descriptive study using quantitative and qualitative approaches. Quantitative methods used self-administered questionnaires. Qualitative methods (in-depth interviews and focus groups discussions) were used to broaden understanding of the quantitative material and to get additional information on actions taken. 1) Service delivery: Medical emergency services, especially surgical operations and referral systems, were not always available during the storm and flood seasons. 2) Governance: District emergency plans focus largely on disaster response rather than prevention. The plans did not clearly define the role of primary healthcare and had no clear information on the coordination mechanism among different sectors and organizations. 3) Financing: The budget for prevention and control of flood and storm activities was limited and had no specific items for healthcare activities. Only a little additional funding was available, but the procedures to get this funding were usually time-consuming. 4) Human resources: Medical rescue teams were established, but there were no epidemiologists or environmental health specialists to take care of epidemiological issues. Training on prevention and control of climate change and disaster-related health issues did not meet actual needs. 5) Information and research: Data that can be used for planning and management (including population and epidemiological data) were largely lacking. The district lacked a disease early-warning system. 6) Medical products and technology: Emergency treatment protocols were not available in every studied health facility. The primary care system capacity in rural Vietnam is inadequate for responding to storm and flood-related health problems in terms of preventive and treatment healthcare. Developing clear facility preparedness plans, which detail standard operating procedures during floods and identify specific job descriptions, would strengthen responses to future floods. Health facilities should have contingency funds available for emergency response in the event of storms and floods. Health facilities should ensure that standard protocols exist in order to improve responses in the event of floods. Introduction of a computerized health information system would accelerate information and data processing. National and local policies need to be strengthened and developed in a way that transfers into action in local rural communities.

PRA (Probabilistic Risk Assessment) Applications Program for inspection at Oconee Unit 3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gore, B.F.; Vo, T.V.; Harris, M.S.

1987-10-01

The extensive Oconee-3 PRA performed by EPRI has been analyzed to identify plant systems and components important to minimizing public risk, and to identify the primary failure modes of these components. This information has been tabulated, and correlated with inspection modules from the NRC Inspection and Enforcement Manual. The report presents a series of tables, organized by system and prioritized by public risk (in person-rem per year), which identify components associated with 98% of the inspectable risk due to plant operation. External events (earthquakes, tornadoes, fires and floods) are not addressed because inspections cannot directly minimize the risks from thesemore » events; however, flooding caused by the breach of internal systems is addressed. The systems addressed, in descending order of risk importance, are: Reactor Building Spray, R B Cooling, Condenser Circulating Water, Safety Relief Valves, Low Pressure Injection, Standby Shutdown Facility-High Pressure Injection, Low-Pressure Service Water, and Emergency Feedwater. This ranking is based on the Fussel-Vesely measure of risk importance, i.e., the fraction of the total risk which involves failures of the system of interest. 8 refs., 25 tabs.« less

Do probabilistic forecasts lead to better decisions?

NASA Astrophysics Data System (ADS)

Ramos, M. H.; van Andel, S. J.; Pappenberger, F.

2012-12-01

The last decade has seen growing research in producing probabilistic hydro-meteorological forecasts and increasing their reliability. This followed the promise that, supplied with information about uncertainty, people would take better risk-based decisions. In recent years, therefore, research and operational developments have also start putting attention to ways of communicating the probabilistic forecasts to decision makers. Communicating probabilistic forecasts includes preparing tools and products for visualization, but also requires understanding how decision makers perceive and use uncertainty information in real-time. At the EGU General Assembly 2012, we conducted a laboratory-style experiment in which several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision makers. Answers were collected and analyzed. In this paper, we present the results of this exercise and discuss if indeed we make better decisions on the basis of probabilistic forecasts.

Do probabilistic forecasts lead to better decisions?

NASA Astrophysics Data System (ADS)

Ramos, M. H.; van Andel, S. J.; Pappenberger, F.

2013-06-01

The last decade has seen growing research in producing probabilistic hydro-meteorological forecasts and increasing their reliability. This followed the promise that, supplied with information about uncertainty, people would take better risk-based decisions. In recent years, therefore, research and operational developments have also started focusing attention on ways of communicating the probabilistic forecasts to decision-makers. Communicating probabilistic forecasts includes preparing tools and products for visualisation, but also requires understanding how decision-makers perceive and use uncertainty information in real time. At the EGU General Assembly 2012, we conducted a laboratory-style experiment in which several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision-makers. Answers were collected and analysed. In this paper, we present the results of this exercise and discuss if we indeed make better decisions on the basis of probabilistic forecasts.

Flood Risk and Asset Management

DTIC Science & Technology

2012-09-01

use by third parties of results or methods presented in this report. The Company also stresses that various sections of this report rely on data...inundation probability  Levee contribution to risk The methods used in FRE have been applied to establish the National Flood Risk in England and...be noted that when undertaking high level probabilistic risk assessments in the UK, if a defence’s condition is unknown, grade 3 is applied with

Community-based early warning systems for flood risk mitigation in Nepal

NASA Astrophysics Data System (ADS)

Smith, Paul J.; Brown, Sarah; Dugar, Sumit

2017-03-01

This paper focuses on the use of community-based early warning systems for flood resilience in Nepal. The first part of the work outlines the evolution and current status of these community-based systems, highlighting the limited lead times currently available for early warning. The second part of the paper focuses on the development of a robust operational flood forecasting methodology for use by the Nepal Department of Hydrology and Meteorology (DHM) to enhance early warning lead times. The methodology uses data-based physically interpretable time series models and data assimilation to generate probabilistic forecasts, which are presented in a simple visual tool. The approach is designed to work in situations of limited data availability with an emphasis on sustainability and appropriate technology. The successful application of the forecast methodology to the flood-prone Karnali River basin in western Nepal is outlined, increasing lead times from 2-3 to 7-8 h. The challenges faced in communicating probabilistic forecasts to the last mile of the existing community-based early warning systems across Nepal is discussed. The paper concludes with an assessment of the applicability of this approach in basins and countries beyond Karnali and Nepal and an overview of key lessons learnt from this initiative.

Flood quantile estimation at ungauged sites by Bayesian networks

NASA Astrophysics Data System (ADS)

Mediero, L.; Santillán, D.; Garrote, L.

2012-04-01

Estimating flood quantiles at a site for which no observed measurements are available is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. The most common technique used is the multiple regression analysis, which relates physical and climatic basin characteristic to flood quantiles. Regression equations are fitted from flood frequency data and basin characteristics at gauged sites. Regression equations are a rigid technique that assumes linear relationships between variables and cannot take the measurement errors into account. In addition, the prediction intervals are estimated in a very simplistic way from the variance of the residuals in the estimated model. Bayesian networks are a probabilistic computational structure taken from the field of Artificial Intelligence, which have been widely and successfully applied to many scientific fields like medicine and informatics, but application to the field of hydrology is recent. Bayesian networks infer the joint probability distribution of several related variables from observations through nodes, which represent random variables, and links, which represent causal dependencies between them. A Bayesian network is more flexible than regression equations, as they capture non-linear relationships between variables. In addition, the probabilistic nature of Bayesian networks allows taking the different sources of estimation uncertainty into account, as they give a probability distribution as result. A homogeneous region in the Tagus Basin was selected as case study. A regression equation was fitted taking the basin area, the annual maximum 24-hour rainfall for a given recurrence interval and the mean height as explanatory variables. Flood quantiles at ungauged sites were estimated by Bayesian networks. Bayesian networks need to be learnt from a huge enough data set. As observational data are reduced, a stochastic generator of synthetic data was developed. Synthetic basin characteristics were randomised, keeping the statistical properties of observed physical and climatic variables in the homogeneous region. The synthetic flood quantiles were stochastically generated taking the regression equation as basis. The learnt Bayesian network was validated by the reliability diagram, the Brier Score and the ROC diagram, which are common measures used in the validation of probabilistic forecasts. Summarising, the flood quantile estimations through Bayesian networks supply information about the prediction uncertainty as a probability distribution function of discharges is given as result. Therefore, the Bayesian network model has application as a decision support for water resources and planning management.

Assessing and Mitigating Hurricane Storm Surge Risk in a Changing Environment

NASA Astrophysics Data System (ADS)

Lin, N.; Shullman, E.; Xian, S.; Feng, K.

2017-12-01

Hurricanes have induced devastating storm surge flooding worldwide. The impacts of these storms may worsen in the coming decades because of rapid coastal development coupled with sea-level rise and possibly increasing storm activity due to climate change. Major advances in coastal flood risk management are urgently needed. We present an integrated dynamic risk analysis for flooding task (iDraft) framework to assess and manage coastal flood risk at the city or regional scale, considering integrated dynamic effects of storm climatology change, sea-level rise, and coastal development. We apply the framework to New York City. First, we combine climate-model projected storm surge climatology and sea-level rise with engineering- and social/economic-model projected coastal exposure and vulnerability to estimate the flood damage risk for the city over the 21st century. We derive temporally-varying risk measures such as the annual expected damage as well as temporally-integrated measures such as the present value of future losses. We also examine the individual and joint contributions to the changing risk of the three dynamic factors (i.e., sea-level rise, storm change, and coastal development). Then, we perform probabilistic cost-benefit analysis for various coastal flood risk mitigation strategies for the city. Specifically, we evaluate previously proposed mitigation measures, including elevating houses on the floodplain and constructing flood barriers at the coast, by comparing their estimated cost and probability distribution of the benefit (i.e., present value of avoided future losses). We also propose new design strategies, including optimal design (e.g., optimal house elevation) and adaptive design (e.g., flood protection levels that are designed to be modified over time in a dynamic and uncertain environment).

Impact of Atmospheric Aerosols on Solar Photovoltaic Electricity Generation in China

NASA Astrophysics Data System (ADS)

Li, X.; Mauzerall, D. L.; Wagner, F.; Peng, W.; Yang, J.

2016-12-01

Hurricanes have induced devastating storm surge flooding worldwide. The impacts of these storms may worsen in the coming decades because of rapid coastal development coupled with sea-level rise and possibly increasing storm activity due to climate change. Major advances in coastal flood risk management are urgently needed. We present an integrated dynamic risk analysis for flooding task (iDraft) framework to assess and manage coastal flood risk at the city or regional scale, considering integrated dynamic effects of storm climatology change, sea-level rise, and coastal development. We apply the framework to New York City. First, we combine climate-model projected storm surge climatology and sea-level rise with engineering- and social/economic-model projected coastal exposure and vulnerability to estimate the flood damage risk for the city over the 21st century. We derive temporally-varying risk measures such as the annual expected damage as well as temporally-integrated measures such as the present value of future losses. We also examine the individual and joint contributions to the changing risk of the three dynamic factors (i.e., sea-level rise, storm change, and coastal development). Then, we perform probabilistic cost-benefit analysis for various coastal flood risk mitigation strategies for the city. Specifically, we evaluate previously proposed mitigation measures, including elevating houses on the floodplain and constructing flood barriers at the coast, by comparing their estimated cost and probability distribution of the benefit (i.e., present value of avoided future losses). We also propose new design strategies, including optimal design (e.g., optimal house elevation) and adaptive design (e.g., flood protection levels that are designed to be modified over time in a dynamic and uncertain environment).

How to pose the question matters: Behavioural Economics concepts in decision making on the basis of ensemble forecasts

NASA Astrophysics Data System (ADS)

Alfonso, Leonardo; van Andel, Schalk Jan

2014-05-01

Part of recent research in ensemble and probabilistic hydro-meteorological forecasting analyses which probabilistic information is required by decision makers and how it can be most effectively visualised. This work, in addition, analyses if decision making in flood early warning is also influenced by the way the decision question is posed. For this purpose, the decision-making game "Do probabilistic forecasts lead to better decisions?", which Ramos et al (2012) conducted at the EGU General Assembly 2012 in the city of Vienna, has been repeated with a small group and expanded. In that game decision makers had to decide whether or not to open a flood release gate, on the basis of flood forecasts, with and without uncertainty information. A conclusion of that game was that, in the absence of uncertainty information, decision makers are compelled towards a more risk-averse attitude. In order to explore to what extent the answers were driven by the way the questions were framed, in addition to the original experiment, a second variant was introduced where participants were asked to choose between a sure value (for either loosing or winning with a giving probability) and a gamble. This set-up is based on Kahneman and Tversky (1979). Results indicate that the way how the questions are posed may play an important role in decision making and that Prospect Theory provides promising concepts to further understand how this works.

Flood model for Brazil

NASA Astrophysics Data System (ADS)

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 scheme to generate probabilistic flood event set. The derived design flows for selected rivers inside model domain were used as an input for 2-dimensional hydrodynamic inundation modelling techniques (using the tool TUFLOW by BMT WBM) on mesh size 30 x 30 metres. Outputs from inundation modelling and stochastic event set were implemented in the Aon Benfield's platform ELEMENTS developed and managed internally by Impact Forecasting; Aon Benfield internal catastrophe model development center. The model was designed to evaluate potential financial impact caused by fluvial flooding on portfolios of insurance and/or reinsurance companies. The structure of presented model follows typical scheme of financial loss catastrophe model and combines hazard with exposure and vulnerability to produce potential financial loss expressed in the form of loss exceedance probability curve and many other insured perspectives, such as average annual loss, event or quantile loss tables and etc. Model can take financial inputs as well as provide split of results for exact specified location or related higher administrative units: municipalities and 5-digit postal codes.

Fews-Risk: A step towards risk-based flood forecasting

NASA Astrophysics Data System (ADS)

Bachmann, Daniel; Eilander, Dirk; de Leeuw, Annemargreet; Diermanse, Ferdinand; Weerts, Albrecht; de Bruijn, Karin; Beckers, Joost; Boelee, Leonore; Brown, Emma; Hazlewood, Caroline

2015-04-01

Operational flood prediction and the assessment of flood risk are important components of flood management. Currently, the model-based prediction of discharge and/or water level in a river is common practice for operational flood forecasting. Based on the prediction of these values decisions about specific emergency measures are made within operational flood management. However, the information provided for decision support is restricted to pure hydrological or hydraulic aspects of a flood. Information about weak sections within the flood defences, flood prone areas and assets at risk in the protected areas are rarely used in a model-based flood forecasting system. This information is often available for strategic planning, but is not in an appropriate format for operational purposes. The idea of FEWS-Risk is the extension of existing flood forecasting systems with elements of strategic flood risk analysis, such as probabilistic failure analysis, two dimensional flood spreading simulation and the analysis of flood impacts and consequences. Thus, additional information is provided to the decision makers, such as: • Location, timing and probability of failure of defined sections of the flood defence line; • Flood spreading, extent and hydraulic values in the hinterland caused by an overflow or a breach flow • Impacts and consequences in case of flooding in the protected areas, such as injuries or casualties and/or damages to critical infrastructure or economy. In contrast with purely hydraulic-based operational information, these additional data focus upon decision support for answering crucial questions within an operational flood forecasting framework, such as: • Where should I reinforce my flood defence system? • What type of action can I take to mend a weak spot in my flood defences? • What are the consequences of a breach? • Which areas should I evacuate first? This presentation outlines the additional required workflows towards risk-based flood forecasting systems. In a cooperation between HR Wallingford and Deltares, the extended workflows are being integrated into the Delft-FEWS software system. Delft-FEWS provides modules for managing the data handling and forecasting process. Results of a pilot study that demonstrates the new tools are presented. The value of the newly generated information for decision support during a flood event is discussed.

The Effect of Seasonal Floods on Health: Analysis of Six Years of National Health Data and Flood Maps

PubMed Central

Saulnier, Dell D.; Hanson, Claudia; Ir, Por; Mölsted Alvesson, Helle; von Schreeb, Johan

2018-01-01

There is limited knowledge on the effect of seasonal flooding on health over time. We quantified the short- and long-term effects of floods on selected health indicators at public healthcare facilities in 11 districts in Cambodia, a flood-prone setting. Counts of inpatient discharge diagnoses and outpatient consultations for diarrhea, acute respiratory infections, skin infections, injuries, noncommunicable diseases and vector-borne diseases were retrieved from public healthcare facilities for each month between January 2008 and December 2013. Flood water was mapped by month, in square kilometers, from satellite data. Poisson regression models with three lag months were constructed for the health problems in each district, controlled for seasonality and long-term trends. During times of flooding and three months after, there were small to moderate increases in visits to healthcare facilities for skin infections, acute respiratory infections, and diarrhea, while no association was seen at one to two months. The associations were small to moderate, and a few of our results were significant. We observed increases in care seeking for diarrhea, skin infections, and acute respiratory infections following floods, but the associations are uncertain. Additional research on previous exposure to flooding, using community- and facility-based data, would help identify expected health risks after floods in flood-prone settings. PMID:29614051

Assessment of extreme flood events in a changing climate for a long-term planning of socio-economic infrastructure in the Russian Arctic

NASA Astrophysics Data System (ADS)

Shevnina, Elena; Kourzeneva, Ekaterina; Kovalenko, Viktor; Vihma, Timo

2017-05-01

Climate warming has been more acute in the Arctic than at lower latitudes and this tendency is expected to continue. This generates major challenges for economic activity in the region. Among other issues is the long-term planning and development of socio-economic infrastructure (dams, bridges, roads, etc.), which require climate-based forecasts of the frequency and magnitude of detrimental flood events. To estimate the cost of the infrastructure and operational risk, a probabilistic form of long-term forecasting is preferable. In this study, a probabilistic model to simulate the parameters of the probability density function (PDF) for multi-year runoff based on a projected climatology is applied to evaluate changes in extreme floods for the territory of the Russian Arctic. The model is validated by cross-comparison of the modelled and empirical PDFs using observations from 23 sites located in northern Russia. The mean values and coefficients of variation (CVs) of the spring flood depth of runoff are evaluated under four climate scenarios, using simulations of six climate models for the period 2010-2039. Regions with substantial expected changes in the means and CVs of spring flood depth of runoff are outlined. For the sites located within such regions, it is suggested to account for the future climate change in calculating the maximal discharges of rare occurrence. An example of engineering calculations for maximal discharges with 1 % exceedance probability is provided for the Nadym River at Nadym.

Capturing spatial and temporal patterns of widespread, extreme flooding across Europe

NASA Astrophysics Data System (ADS)

Busby, Kathryn; Raven, Emma; Liu, Ye

2013-04-01

Statistical characterisation of physical hazards is an integral part of probabilistic catastrophe models used by the reinsurance industry to estimate losses from large scale events. Extreme flood events are not restricted by country boundaries which poses an issue for reinsurance companies as their exposures often extend beyond them. We discuss challenges and solutions that allow us to appropriately capture the spatial and temporal dependence of extreme hydrological events on a continental-scale, which in turn enables us to generate an industry-standard stochastic event set for estimating financial losses for widespread flooding. By presenting our event set methodology, we focus on explaining how extreme value theory (EVT) and dependence modelling are used to account for short, inconsistent hydrological data from different countries, and how to make appropriate statistical decisions that best characterise the nature of flooding across Europe. The consistency of input data is of vital importance when identifying historical flood patterns. Collating data from numerous sources inherently causes inconsistencies and we demonstrate our robust approach to assessing the data and refining it to compile a single consistent dataset. This dataset is then extrapolated using a parameterised EVT distribution to estimate extremes. Our method then captures the dependence of flood events across countries using an advanced multivariate extreme value model. Throughout, important statistical decisions are explored including: (1) distribution choice; (2) the threshold to apply for extracting extreme data points; (3) a regional analysis; (4) the definition of a flood event, which is often linked with reinsurance industry's hour's clause; and (5) handling of missing values. Finally, having modelled the historical patterns of flooding across Europe, we sample from this model to generate our stochastic event set comprising of thousands of events over thousands of years. We then briefly illustrate how this is applied within a probabilistic model to estimate catastrophic loss curves used by the reinsurance industry.

Off-site movement of pesticide-contaminated fill from agrichemical facilities during the 1993 flooding in Illinois

USGS Publications Warehouse

Roy, W.R.; Chou, S.-F.J.; Krapac, I.G.

1995-01-01

Twenty retail agrichemical facilities were flooded. There was a concern that pesticide-contaminated road fill at these facilities had been transported into residential areas by the flooding. Forty fill and flood- related sediment samples were collected at six facilities. No significant accumulation of sediments was present at any of the six facilities. At five of the six facilities, it did not appear that road fill had been transported off-site. Pesticides were detected in sediment samples collected off-site adjacent to five of the facilities. Of the 21 samples collected off-site, atrazine (2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazide) and metolachlor (2-chloro-6'-ethyl-N-(2-methoxy-1-methylethyl)acet-o-toluidine) were detected in 86 and 81% of the samples, respectively. When compared with on-site concentrations, off-site pesticide concentrations were either at similar levels, or were as much as three orders of magnitude less. The interpretation of the pesticide data was difficult and often inconclusive, because there were no background data on the occurrence and distribution of pesticides at each site before flooding.

Seismic risk assessment for Poiana Uzului (Romania) buttress dam on Uz river

NASA Astrophysics Data System (ADS)

Moldovan, Iren-Adelina; Toma-Danila, Dragos; Paerele, Cosmin Marian; Emilian Toader, Victorin; Petruta Constantin, Angela; Ghita, Cristian

2017-04-01

The most important specific requirements towards dams' safety is the seismic risk assessment. This objective will be accomplished by rating the dams into seismic risk classes using the theory of Bureau and Ballentine, 2002, and Bureau (2003), taking into account the maximum expected peak ground motions at dams' site, the structures vulnerability and the downstream risk characteristics. The maximum expected values for ground motions at dams' site have been obtained using probabilistic seismic hazard assessment approaches. The structural vulnerability was obtained from dams' characteristics (age, high, water volume) and the downstream risk was assessed using human, economical, touristic, historic and cultural heritage information from the areas that might be flooded in the case of a dam failure. A couple of flooding scenarios have been performed. The results of the work consist of local and regional seismic information, specific characteristics of dam, seismic hazard values for different return periods and risk classes. The studies realized in this paper have as final goal to provide in the near future the local emergency services with warnings of a potential dam failure and ensuing flood as a result of a large earthquake occurrence, allowing further public training for evacuation. Acknowledgments This work was partially supported by the Partnership in Priority Areas Program - PNII, under MEN-UEFISCDI, DARING Project no. 69/2014 and the Nucleu Program - PN 16-35, Project no. 03 01 and 01 06.

Real-time Ensemble Flow Forecasts for a 2017 Mock Operation Test Trial of Forecast Informed Reservoir Operations for Lake Mendocino in Mendocino County, California

NASA Astrophysics Data System (ADS)

Delaney, C.; Mendoza, J.; Jasperse, J.; Hartman, R. K.; Whitin, B.; Kalansky, J.

2017-12-01

Forecast informed reservoir operations (FIRO) is a methodology that incorporates short to mid-range precipitation and flow forecasts to inform the flood operations of reservoirs. The Ensemble Forecast Operations (EFO) alternative is a probabilistic approach of FIRO that incorporates 15-day ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, release decisions are made to manage forecasted risk of reaching critical operational thresholds. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to conduct a mock operation test trial of the EFO alternative for 2017. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The operational trial utilized real-time ESPs prepared by the CNRFC and observed flow information to simulate hydrologic conditions in Lake Mendocino and a 50-mile downstream reach of the Russian River to the City of Healdsburg. Results of the EFO trial demonstrate a 6% increase in reservoir storage at the end of trial period (May 10) relative to observed conditions. Additionally, model results show no increase in flows above flood stage for points downstream of Lake Mendocino. Results of this investigation and other studies demonstrate that the EFO alternative may be a viable flood control operations approach for Lake Mendocino and warrants further investigation through additional modeling and analysis.

Non-parametric data-based approach for the quantification and communication of uncertainties in river flood forecasts

NASA Astrophysics Data System (ADS)

Van Steenbergen, N.; Willems, P.

2012-04-01

Reliable flood forecasts are the most important non-structural measures to reduce the impact of floods. However flood forecasting systems are subject to uncertainty originating from the input data, model structure and model parameters of the different hydraulic and hydrological submodels. To quantify this uncertainty a non-parametric data-based approach has been developed. This approach analyses the historical forecast residuals (differences between the predictions and the observations at river gauging stations) without using a predefined statistical error distribution. Because the residuals are correlated with the value of the forecasted water level and the lead time, the residuals are split up into discrete classes of simulated water levels and lead times. For each class, percentile values are calculated of the model residuals and stored in a 'three dimensional error' matrix. By 3D interpolation in this error matrix, the uncertainty in new forecasted water levels can be quantified. In addition to the quantification of the uncertainty, the communication of this uncertainty is equally important. The communication has to be done in a consistent way, reducing the chance of misinterpretation. Also, the communication needs to be adapted to the audience; the majority of the larger public is not interested in in-depth information on the uncertainty on the predicted water levels, but only is interested in information on the likelihood of exceedance of certain alarm levels. Water managers need more information, e.g. time dependent uncertainty information, because they rely on this information to undertake the appropriate flood mitigation action. There are various ways in presenting uncertainty information (numerical, linguistic, graphical, time (in)dependent, etc.) each with their advantages and disadvantages for a specific audience. A useful method to communicate uncertainty of flood forecasts is by probabilistic flood mapping. These maps give a representation of the probability of flooding of a certain area, based on the uncertainty assessment of the flood forecasts. By using this type of maps, water managers can focus their attention on the areas with the highest flood probability. Also the larger public can consult these maps for information on the probability of flooding for their specific location, such that they can take pro-active measures to reduce the personal damage. The method of quantifying the uncertainty was implemented in the operational flood forecasting system for the navigable rivers in the Flanders region of Belgium. The method has shown clear benefits during the floods of the last two years.

Nonstationarity of daily rainfall annual maxima in Puglia (Southern Italy)

NASA Astrophysics Data System (ADS)

Totaro, Vincenzo; Gioia, Andrea; Iacobellis, Vito

2017-04-01

Extreme flood events occurring in the last decades, due to climatic conditions in rapid evolution and/or changes in land cover, has lead the scientific community to develop and improve probabilistic techniques in order to take into account these effects, as also requested by the EU Floods Directive 2007/60. In the recent literature are becoming more popular studies that investigate the nonstationarity of the variables usually treated in hydrology through the analysis of their trend behavior. In this context it is also useful to assess the impact that the climate and /or land cover modifications have on the performances of the probabilistic stationary models used to predict hydrological variables such as rainfall and flood peaks. Among several proposed approaches, we use the redefined concept of return period and risk by considering the variability over time of the position parameter of the GEV distribution, with the subsequent discussion about the implications of analytical and technical characters. The analysis was carried out on the time series of annual maximum of daily precipitation available for a broad number of rainfall gauged stations in Puglia (Southern Italy). The investigation, conducted at the regional scale, leads to the identification of areas with different significativity of the statistical tests usually performed in order to assess nonstationarity. The evaluated change of return period leads to considerations useful to redesign methods for regional analysis of flood frequency.

A Probabilistic Typhoon Risk Model for Vietnam

NASA Astrophysics Data System (ADS)

Haseemkunju, A.; Smith, D. F.; Brolley, J. M.

2017-12-01

Annually, the coastal Provinces of low-lying Mekong River delta region in the southwest to the Red River Delta region in Northern Vietnam is exposed to severe wind and flood risk from landfalling typhoons. On average, about two to three tropical cyclones with a maximum sustained wind speed of >=34 knots make landfall along the Vietnam coast. Recently, Typhoon Wutip (2013) crossed Central Vietnam as a category 2 typhoon causing significant damage to properties. As tropical cyclone risk is expected to increase with increase in exposure and population growth along the coastal Provinces of Vietnam, insurance/reinsurance, and capital markets need a comprehensive probabilistic model to assess typhoon risk in Vietnam. In 2017, CoreLogic has expanded the geographical coverage of its basin-wide Western North Pacific probabilistic typhoon risk model to estimate the economic and insured losses from landfalling and by-passing tropical cyclones in Vietnam. The updated model is based on 71 years (1945-2015) of typhoon best-track data and 10,000 years of a basin-wide simulated stochastic tracks covering eight countries including Vietnam. The model is capable of estimating damage from wind, storm surge and rainfall flooding using vulnerability models, which relate typhoon hazard to building damageability. The hazard and loss models are validated against past historical typhoons affecting Vietnam. Notable typhoons causing significant damage in Vietnam are Lola (1993), Frankie (1996), Xangsane (2006), and Ketsana (2009). The central and northern coastal provinces of Vietnam are more vulnerable to wind and flood hazard, while typhoon risk in the southern provinces are relatively low.

Developing a field facility for evaluating flood tolerance of hardwood seedlings and understory ground covers

Treesearch

J.W. Van Sambeek; Robert L. McGraw; John M. Kabrick; Mark V. Coggeshall; Irene M. Unger; Daniel C. Dey

2007-01-01

Information about the flood tolerance of most plants has been obtained from either observations following natural floods or pot studies with amended soils. To better evaluate and compare flood tolerance among hardwood seedlings and ground covers for use in riparian buffer and bottomland plantings, a large outdoor facility with natural floodplain soils is needed where...

GIS data for the Seaside, Oregon, Tsunami Pilot Study to modernize FEMA flood hazard maps

USGS Publications Warehouse

Wong, Florence L.; Venturato, Angie J.; Geist, Eric L.

2007-01-01

A Tsunami Pilot Study was conducted for the area surrounding the coastal town of Seaside, Oregon, as part of the Federal Emergency Management's (FEMA) Flood Insurance Rate Map Modernization Program (Tsunami Pilot Study Working Group, 2006). The Cascadia subduction zone extends from Cape Mendocino, California, to Vancouver Island, Canada. The Seaside area was chosen because it is typical of many coastal communities subject to tsunamis generated by far- and near-field (Cascadia) earthquakes. Two goals of the pilot study were to develop probabilistic 100-year and 500-year tsunami inundation maps using Probabilistic Tsunami Hazard Analysis (PTHA) and to provide recommendations for improving tsunami hazard assessment guidelines for FEMA and state and local agencies. The study was an interagency effort by the National Oceanic and Atmospheric Administration, U.S. Geological Survey, and FEMA, in collaboration with the University of Southern California, Middle East Technical University, Portland State University, Horning Geoscience, Northwest Hydraulics Consultants, and the Oregon Department of Geological and Mineral Industries. The pilot study model data and results are published separately as a geographic information systems (GIS) data report (Wong and others, 2006). The flood maps and GIS data are briefly described here.

Probabilistic flood warning using grand ensemble weather forecasts

NASA Astrophysics Data System (ADS)

He, Y.; Wetterhall, F.; Cloke, H.; Pappenberger, F.; Wilson, M.; Freer, J.; McGregor, G.

2009-04-01

As the severity of floods increases, possibly due to climate and landuse change, there is urgent need for more effective and reliable warning systems. The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. An ensemble of weather forecasts from one Ensemble Prediction System (EPS), when used on catchment hydrology, can provide improved early flood warning as some of the uncertainties can be quantified. EPS forecasts from a single weather centre only account for part of the uncertainties originating from initial conditions and stochastic physics. Other sources of uncertainties, including numerical implementations and/or data assimilation, can only be assessed if a grand ensemble of EPSs from different weather centres is used. When various models that produce EPS from different weather centres are aggregated, the probabilistic nature of the ensemble precipitation forecasts can be better retained and accounted for. The availability of twelve global EPSs through the 'THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for the design of an improved probabilistic flood forecasting framework. This work presents a case study using the TIGGE database for flood warning on a meso-scale catchment. The upper reach of the River Severn catchment located in the Midlands Region of England is selected due to its abundant data for investigation and its relatively small size (4062 km2) (compared to the resolution of the NWPs). This choice was deliberate as we hypothesize that the uncertainty in the forcing of smaller catchments cannot be represented by a single EPS with a very limited number of ensemble members, but only through the variance given by a large number ensembles and ensemble system. A coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts is set up to study the potential benefits of using the TIGGE database in early flood warning. Physically based and fully distributed LISFLOOD suite of models is selected to simulate discharge and flood inundation consecutively. The results show the TIGGE database is a promising tool to produce forecasts of discharge and flood inundation comparable with the observed discharge and simulated inundation driven by the observed discharge. The spread of discharge forecasts varies from centre to centre, but it is generally large, implying a significant level of uncertainties. Precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial variability of precipitation on a comparatively small catchment. This perhaps indicates the need to improve NWPs resolution and/or disaggregation techniques to narrow down the spatial gap between meteorology and hydrology. It is not necessarily true that early flood warning becomes more reliable when more ensemble forecasts are employed. It is difficult to identify the best forecast centre(s), but in general the chance of detecting floods is increased by using the TIGGE database. Only one flood event was studied because most of the TIGGE data became available after October 2007. It is necessary to test the TIGGE ensemble forecasts with other flood events in other catchments with different hydrological and climatic regimes before general conclusions can be made on its robustness and applicability.

A climate-based multivariate extreme emulator of met-ocean-hydrological events for coastal flooding

NASA Astrophysics Data System (ADS)

Camus, Paula; Rueda, Ana; Mendez, Fernando J.; Tomas, Antonio; Del Jesus, Manuel; Losada, Iñigo J.

2015-04-01

Atmosphere-ocean general circulation models (AOGCMs) are useful to analyze large-scale climate variability (long-term historical periods, future climate projections). However, applications such as coastal flood modeling require climate information at finer scale. Besides, flooding events depend on multiple climate conditions: waves, surge levels from the open-ocean and river discharge caused by precipitation. Therefore, a multivariate statistical downscaling approach is adopted to reproduce relationships between variables and due to its low computational cost. The proposed method can be considered as a hybrid approach which combines a probabilistic weather type downscaling model with a stochastic weather generator component. Predictand distributions are reproduced modeling the relationship with AOGCM predictors based on a physical division in weather types (Camus et al., 2012). The multivariate dependence structure of the predictand (extreme events) is introduced linking the independent marginal distributions of the variables by a probabilistic copula regression (Ben Ayala et al., 2014). This hybrid approach is applied for the downscaling of AOGCM data to daily precipitation and maximum significant wave height and storm-surge in different locations along the Spanish coast. Reanalysis data is used to assess the proposed method. A commonly predictor for the three variables involved is classified using a regression-guided clustering algorithm. The most appropriate statistical model (general extreme value distribution, pareto distribution) for daily conditions is fitted. Stochastic simulation of the present climate is performed obtaining the set of hydraulic boundary conditions needed for high resolution coastal flood modeling. References: Camus, P., Menéndez, M., Méndez, F.J., Izaguirre, C., Espejo, A., Cánovas, V., Pérez, J., Rueda, A., Losada, I.J., Medina, R. (2014b). A weather-type statistical downscaling framework for ocean wave climate. Journal of Geophysical Research, doi: 10.1002/2014JC010141. Ben Ayala, M.A., Chebana, F., Ouarda, T.B.M.J. (2014). Probabilistic Gaussian Copula Regression Model for Multisite and Multivariable Downscaling, Journal of Climate, 27, 3331-3347.

Attribution of UK Winter Floods to Anthropogenic Forcing

NASA Astrophysics Data System (ADS)

Schaller, N.; Alison, K.; Sparrow, S. N.; Otto, F. E. L.; Massey, N.; Vautard, R.; Yiou, P.; van Oldenborgh, G. J.; van Haren, R.; Lamb, R.; Huntingford, C.; Crooks, S.; Legg, T.; Weisheimer, A.; Bowery, A.; Miller, J.; Jones, R.; Stott, P.; Allen, M. R.

2014-12-01

Many regions of southern UK experienced severe flooding during the 2013/2014 winter. Simultaneously, large areas in the USA and Canada were struck by prolonged cold weather. At the time, the media and public asked whether the general rainy conditions over northern Europe and the cold weather over North America were caused by climate change. Providing an answer to this question is not trivial, but recent studies show that probabilistic event attribution is feasible. Using the citizen science project weather@home, we ran over 40'000 perturbed initial condition simulations of the 2013/2014 winter. These simulations fall into two categories: one set aims at simulating the world with climate change using observed sea surface temperatures while the second set is run with sea surface temperatures corresponding to a world that might have been without climate change. The relevant modelled variables are then downscaled by a hydrological model to obtain river flows. First results show that anthropogenic climate change led to a small but significant increase in the fractional attributable risk for 30-days peak flows for the river Thames. A single number can summarize the final result from probabilistic attribution studies indicating, for example, an increase, decrease or no change to the risk of the event occurring. However, communicating this to the public, media and other scientists remains challenging. The assumptions made in the chain of models used need to be explained. In addition, extreme events, like the UK floods of the 2013/2014 winter, are usually caused by a range of factors. While heavy precipitation events can be caused by dynamic and/or thermodynamic processes, floods occur only partly as a response to heavy precipitation. Depending on the catchment, they can be largely due to soil properties and conditions of the previous months. Probabilistic attribution studies are multidisciplinary and therefore all aspects need to be communicated properly.

Real-time updating of the flood frequency distribution through data assimilation

NASA Astrophysics Data System (ADS)

Aguilar, Cristina; Montanari, Alberto; Polo, María-José

2017-07-01

We explore the memory properties of catchments for predicting the likelihood of floods based on observations of average flows in pre-flood seasons. Our approach assumes that flood formation is driven by the superimposition of short- and long-term perturbations. The former is given by the short-term meteorological forcing leading to infiltration and/or saturation excess, while the latter is originated by higher-than-usual storage in the catchment. To exploit the above sensitivity to long-term perturbations, a meta-Gaussian model and a data assimilation approach are implemented for updating the flood frequency distribution a season in advance. Accordingly, the peak flow in the flood season is predicted in probabilistic terms by exploiting its dependence on the average flow in the antecedent seasons. We focus on the Po River at Pontelagoscuro and the Danube River at Bratislava. We found that the shape of the flood frequency distribution is noticeably impacted by higher-than-usual flows occurring up to several months earlier. The proposed technique may allow one to reduce the uncertainty associated with the estimation of flood frequency.

Hurricane Sandy's flood frequency increasing from year 1800 to 2100.

PubMed

Lin, Ning; Kopp, Robert E; Horton, Benjamin P; Donnelly, Jeffrey P

2016-10-25

Coastal flood hazard varies in response to changes in storm surge climatology and the sea level. Here we combine probabilistic projections of the sea level and storm surge climatology to estimate the temporal evolution of flood hazard. We find that New York City's flood hazard has increased significantly over the past two centuries and is very likely to increase more sharply over the 21st century. Due to the effect of sea level rise, the return period of Hurricane Sandy's flood height decreased by a factor of ∼3× from year 1800 to 2000 and is estimated to decrease by a further ∼4.4× from 2000 to 2100 under a moderate-emissions pathway. When potential storm climatology change over the 21st century is also accounted for, Sandy's return period is estimated to decrease by ∼3× to 17× from 2000 to 2100.

Hurricane Sandy’s flood frequency increasing from year 1800 to 2100

PubMed Central

Horton, Benjamin P.; Donnelly, Jeffrey P.

2016-01-01

Coastal flood hazard varies in response to changes in storm surge climatology and the sea level. Here we combine probabilistic projections of the sea level and storm surge climatology to estimate the temporal evolution of flood hazard. We find that New York City’s flood hazard has increased significantly over the past two centuries and is very likely to increase more sharply over the 21st century. Due to the effect of sea level rise, the return period of Hurricane Sandy’s flood height decreased by a factor of ∼3× from year 1800 to 2000 and is estimated to decrease by a further ∼4.4× from 2000 to 2100 under a moderate-emissions pathway. When potential storm climatology change over the 21st century is also accounted for, Sandy’s return period is estimated to decrease by ∼3× to 17× from 2000 to 2100. PMID:27790992

A probabilistic bridge safety evaluation against floods.

PubMed

Liao, Kuo-Wei; Muto, Yasunori; Chen, Wei-Lun; Wu, Bang-Ho

2016-01-01

To further capture the influences of uncertain factors on river bridge safety evaluation, a probabilistic approach is adopted. Because this is a systematic and nonlinear problem, MPP-based reliability analyses are not suitable. A sampling approach such as a Monte Carlo simulation (MCS) or importance sampling is often adopted. To enhance the efficiency of the sampling approach, this study utilizes Bayesian least squares support vector machines to construct a response surface followed by an MCS, providing a more precise safety index. Although there are several factors impacting the flood-resistant reliability of a bridge, previous experiences and studies show that the reliability of the bridge itself plays a key role. Thus, the goal of this study is to analyze the system reliability of a selected bridge that includes five limit states. The random variables considered here include the water surface elevation, water velocity, local scour depth, soil property and wind load. Because the first three variables are deeply affected by river hydraulics, a probabilistic HEC-RAS-based simulation is performed to capture the uncertainties in those random variables. The accuracy and variation of our solutions are confirmed by a direct MCS to ensure the applicability of the proposed approach. The results of a numerical example indicate that the proposed approach can efficiently provide an accurate bridge safety evaluation and maintain satisfactory variation.

Efficient Probabilistic Forecasting for High-Resolution Models through Clustered-State Data Assimilation

NASA Astrophysics Data System (ADS)

Hamidi, A.; Grossberg, M.; Khanbilvardi, R.

2016-12-01

Flood response in an urban area is the product of interactions of spatially and temporally varying rainfall and infrastructures. In urban areas, however, the complex sub-surface networks of tunnels, waste and storm water drainage systems are often inaccessible, pose challenges for modeling and prediction of the drainage infrastructure performance. The increased availability of open data in cities is an emerging information asset for a better understanding of the dynamics of urban water drainage infrastructure. This includes crowd sourced data and community reporting. A well-known source of this type of data is the non-emergency hotline "311" which is available in many US cities, and may contain information pertaining to the performance of physical facilities, condition of the environment, or residents' experience, comfort and well-being. In this study, seven years of New York City 311 (NYC311) call during 2010-2016 is employed, as an alternative approach for identifying the areas of the city most prone to sewer back up flooding. These zones are compared with the hydrologic analysis of runoff flooding zones to provide a predictive model for the City. The proposed methodology is an example of urban system phenomenology using crowd sourced, open data. A novel algorithm for calculating the spatial distribution of flooding complaints across NYC's five boroughs is presented in this study. In this approach, the features that represent reporting bias are separated from those that relate to actual infrastructure system performance. The sewer backup results are assessed with the spatial distribution of runoff in NYC during 2010-2016. With advances in radar technologies, a high spatial-temporal resolution data set for precipitation is available for most of the United States that can be implemented in hydrologic analysis of dense urban environments. High resolution gridded Stage IV radar rainfall data along with the high resolution spatially distributed land cover data are employed to investigate the urban pluvial flooding. The monthly results of excess runoff are compared with the sewer backup in NYC to build a predictive model of flood zones according to the 311 phone calls.

Characterizing uncertain sea-level rise projections to support investment decisions.

PubMed

Sriver, Ryan L; Lempert, Robert J; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions.

Characterizing uncertain sea-level rise projections to support investment decisions

PubMed Central

Lempert, Robert J.; Wikman-Svahn, Per; Keller, Klaus

2018-01-01

Many institutions worldwide are considering how to include uncertainty about future changes in sea-levels and storm surges into their investment decisions regarding large capital infrastructures. Here we examine how to characterize deeply uncertain climate change projections to support such decisions using Robust Decision Making analysis. We address questions regarding how to confront the potential for future changes in low probability but large impact flooding events due to changes in sea-levels and storm surges. Such extreme events can affect investments in infrastructure but have proved difficult to consider in such decisions because of the deep uncertainty surrounding them. This study utilizes Robust Decision Making methods to address two questions applied to investment decisions at the Port of Los Angeles: (1) Under what future conditions would a Port of Los Angeles decision to harden its facilities against extreme flood scenarios at the next upgrade pass a cost-benefit test, and (2) Do sea-level rise projections and other information suggest such conditions are sufficiently likely to justify such an investment? We also compare and contrast the Robust Decision Making methods with a full probabilistic analysis. These two analysis frameworks result in similar investment recommendations for different idealized future sea-level projections, but provide different information to decision makers and envision different types of engagement with stakeholders. In particular, the full probabilistic analysis begins by aggregating the best scientific information into a single set of joint probability distributions, while the Robust Decision Making analysis identifies scenarios where a decision to invest in near-term response to extreme sea-level rise passes a cost-benefit test, and then assembles scientific information of differing levels of confidence to help decision makers judge whether or not these scenarios are sufficiently likely to justify making such investments. Results highlight the highly-localized and context dependent nature of applying Robust Decision Making methods to inform investment decisions. PMID:29414978

Uncertainty estimation of long-range ensemble forecasts of snowmelt flood characteristics

NASA Astrophysics Data System (ADS)

Kuchment, L.

2012-04-01

Long-range forecasts of snowmelt flood characteristics with the lead time of 2-3 months have important significance for regulation of flood runoff and mitigation of flood damages at almost all large Russian rivers At the same time, the application of current forecasting techniques based on regression relationships between the runoff volume and the indexes of river basin conditions can lead to serious errors in forecasting resulted in large economic losses caused by wrong flood regulation. The forecast errors can be caused by complicated processes of soil freezing and soil moisture redistribution, too high rate of snow melt, large liquid precipitation before snow melt. or by large difference of meteorological conditions during the lead-time periods from climatologic ones. Analysis of economic losses had shown that the largest damages could, to a significant extent, be avoided if the decision makers had an opportunity to take into account predictive uncertainty and could use more cautious strategies in runoff regulation. Development of methodology of long-range ensemble forecasting of spring/summer floods which is based on distributed physically-based runoff generation models has created, in principle, a new basis for improving hydrological predictions as well as for estimating their uncertainty. This approach is illustrated by forecasting of the spring-summer floods at the Vyatka River and the Seim River basins. The application of the physically - based models of snowmelt runoff generation give a essential improving of statistical estimates of the deterministic forecasts of the flood volume in comparison with the forecasts obtained from the regression relationships. These models had been used also for the probabilistic forecasts assigning meteorological inputs during lead time periods from the available historical daily series, and from the series simulated by using a weather generator and the Monte Carlo procedure. The weather generator consists of the stochastic models of daily temperature and precipitation. The performance of the probabilistic forecasts were estimated by the ranked probability skill scores. The application of Monte Carlo simulations using weather generator has given better results then using the historical meteorological series.

Subseasonal to Seasonal Predictions of U.S. West Coast High Water Levels

NASA Astrophysics Data System (ADS)

Khouakhi, A.; Villarini, G.; Zhang, W.; Slater, L. J.

2017-12-01

Extreme sea levels pose a significant threat to coastal communities, ecosystems, and assets, as they are conducive to coastal flooding, coastal erosion and inland salt-water intrusion. As sea levels continue to rise, these sea level extremes - including occasional minor coastal flooding experienced during high tide (nuisance floods) - are of concern. Extreme sea levels are increasing at many locations around the globe and have been attributed largely to rising mean sea levels associated with intra-seasonal to interannual climate processes such as the El Niño-Southern Oscillation (ENSO). Here, intra-seasonal to seasonal probabilistic forecasts of high water levels are computed at the Toke Point tide gage station on the US west coast. We first identify the main climate drivers that are responsible for high water levels and examine their predictability using General Circulation Models (GCMs) from the North American Multi-Model Ensemble (NMME). These drivers are then used to develop a probabilistic framework for the seasonal forecasting of high water levels. We focus on the climate controls on the frequency of high water levels using the number of exceedances above the 99.5th percentile and above the nuisance flood level established by the National Weather Service. Our findings indicate good forecast skill at the shortest lead time, with the skill that decreases as we increase the lead time. In general, these models aptly capture the year-to-year variability in the observational records.

Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

NASA Astrophysics Data System (ADS)

Arnal, Louise; Ramos, Maria-Helena; Coughlan, Erin; Cloke, Hannah L.; Stephens, Elisabeth; Wetterhall, Fredrik; van Andel, Schalk-Jan; Pappenberger, Florian

2016-04-01

Forecast uncertainty is a twofold issue, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic forecasts over deterministic forecasts for a diversity of activities in the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. The setup and the results of a risk-based decision-making experiment, designed as a game on the topic of flood protection mitigation, called ``How much are you prepared to pay for a forecast?'', will be presented. The game was played at several workshops in 2015, including during this session at the EGU conference in 2015, and a total of 129 worksheets were collected and analysed. The aim of this experiment was to contribute to the understanding of the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants' willingness-to-pay for a forecast, the results of the game showed that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers. Balancing avoided costs and the cost (or the benefit) of having forecasts available for making decisions is not straightforward, even in a simplified game situation, and is a topic that deserves more attention from the hydrological forecasting community in the future.

Prediction of Flood Warning in Taiwan Using Nonlinear SVM with Simulated Annealing Algorithm

NASA Astrophysics Data System (ADS)

Lee, C.

2013-12-01

The issue of the floods is important in Taiwan. It is because the narrow and high topography of the island make lots of rivers steep in Taiwan. The tropical depression likes typhoon always causes rivers to flood. Prediction of river flow under the extreme rainfall circumstances is important for government to announce the warning of flood. Every time typhoon passed through Taiwan, there were always floods along some rivers. The warning is classified to three levels according to the warning water levels in Taiwan. The propose of this study is to predict the level of floods warning from the information of precipitation, rainfall duration and slope of riverbed. To classify the level of floods warning by the above-mentioned information and modeling the problems, a machine learning model, nonlinear Support vector machine (SVM), is formulated to classify the level of floods warning. In addition, simulated annealing (SA), a probabilistic heuristic algorithm, is used to determine the optimal parameter of the SVM model. A case study of flooding-trend rivers of different gradients in Taiwan is conducted. The contribution of this SVM model with simulated annealing is capable of making efficient announcement for flood warning and keeping the danger of flood from residents along the rivers.

Risk assessment of CST-7 proposed waste treatment and storage facilities Volume I: Limited-scope probabilistic risk assessment (PRA) of proposed CST-7 waste treatment & storage facilities. Volume II: Preliminary hazards analysis of proposed CST-7 waste storage & treatment facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sasser, K.

1994-06-01

In FY 1993, the Los Alamos National Laboratory Waste Management Group [CST-7 (formerly EM-7)] requested the Probabilistic Risk and Hazards Analysis Group [TSA-11 (formerly N-6)] to conduct a study of the hazards associated with several CST-7 facilities. Among these facilities are the Hazardous Waste Treatment Facility (HWTF), the HWTF Drum Storage Building (DSB), and the Mixed Waste Receiving and Storage Facility (MWRSF), which are proposed for construction beginning in 1996. These facilities are needed to upgrade the Laboratory`s storage capability for hazardous and mixed wastes and to provide treatment capabilities for wastes in cases where offsite treatment is not availablemore » or desirable. These facilities will assist Los Alamos in complying with federal and state requlations.« less

Environmental prediction, risk assessment and extreme events: adaptation strategies for the developing world

PubMed Central

Webster, Peter J.; Jian, Jun

2011-01-01

The uncertainty associated with predicting extreme weather events has serious implications for the developing world, owing to the greater societal vulnerability to such events. Continual exposure to unanticipated extreme events is a contributing factor for the descent into perpetual and structural rural poverty. We provide two examples of how probabilistic environmental prediction of extreme weather events can support dynamic adaptation. In the current climate era, we describe how short-term flood forecasts have been developed and implemented in Bangladesh. Forecasts of impending floods with horizons of 10 days are used to change agricultural practices and planning, store food and household items and evacuate those in peril. For the first time in Bangladesh, floods were anticipated in 2007 and 2008, with broad actions taking place in advance of the floods, grossing agricultural and household savings measured in units of annual income. We argue that probabilistic environmental forecasts disseminated to an informed user community can reduce poverty caused by exposure to unanticipated extreme events. Second, it is also realized that not all decisions in the future can be made at the village level and that grand plans for water resource management require extensive planning and funding. Based on imperfect models and scenarios of economic and population growth, we further suggest that flood frequency and intensity will increase in the Ganges, Brahmaputra and Yangtze catchments as greenhouse-gas concentrations increase. However, irrespective of the climate-change scenario chosen, the availability of fresh water in the latter half of the twenty-first century seems to be dominated by population increases that far outweigh climate-change effects. Paradoxically, fresh water availability may become more critical if there is no climate change. PMID:22042897

Decision-making under uncertainty: results from an experiment conducted at EGU 2012

NASA Astrophysics Data System (ADS)

Ramos, Maria-Helena; van Andel, Schalk Jan; Pappenberger, Florian

2013-04-01

Do probabilistic forecasts lead to better decisions? At the EGU General Assembly 2012, we conducted a laboratory-style experiment to address this question. Several cases of flood forecasts and a choice of actions to take were presented as part of a game to participants, who acted as decision makers. Participants were prompted to make decisions when forecasts were provided with and without uncertainty information. They had to decide whether to open or not a gate which was the inlet of a retention basin designed to protect a town. The rules were such that: if they decided to open the gate, the retention basin was flooded and the farmers in this basin demanded a compensation for flooding their land; if they decided not to open the gate and a flood occurred on the river, the town was flooded and they had to pay a fine to the town. Participants were encouraged to keep note of their individual decisions in a worksheet. About 100 worksheets were collected at the end of the game and the results of their evaluation are presented here. In general, they show that decisions are based on a combination of what is displayed by the expected (forecast) value and what is given by the uncertainty information. In the absence of uncertainty information, decision makers are compelled towards a more risk-averse attitude. Besides, more money was lost by a large majority of participants when they had to make decisions without uncertainty information. Limitations of the experiment setting are discussed, as well as the importance of the development of training tools to increase effectiveness in the use of probabilistic predictions to support decisions under uncertainty.

Urban sprawl and flooding in southern California

USGS Publications Warehouse

Rantz, S.E.

1970-01-01

The floods of January 1969 in south-coastal California provide a timely example of the effect of urban sprawl on flood damage. Despite recordbreaking, or near recordbreaking, stream discharges, damage was minimal in the older developed areas that are protected against inundation and debris damage by carefully planned flood-control facilities, including debris basins and flood-conveyance channels. By contrast, heavy damage occurred in areas of more recent urban sprawl, where the hazards of inundation and debris or landslide damage have not been taken into consideration, and where the improvement and development of drainage or flood-control facilities have not kept pace with expanding urbanization.

Decision-making and evacuation planning for flood risk management in the Netherlands.

PubMed

Kolen, Bas; Helsloot, Ira

2014-07-01

A traditional view of decision-making for evacuation planning is that, given an uncertain threat, there is a deterministic way of defining the best decision. In other words, there is a linear relation between threat, decision, and execution consequences. Alternatives and the impact of uncertainties are not taken into account. This study considers the 'top strategic decision-making' for mass evacuation owing to flooding in the Netherlands. It reveals that the top strategic decision-making process itself is probabilistic because of the decision-makers involved and their crisis managers (as advisers). The paper concludes that deterministic planning is not sufficient, and it recommends probabilistic planning that considers uncertainties in the decision-making process itself as well as other uncertainties, such as forecasts, citizens responses, and the capacity of infrastructure. This results in less optimistic, but more realistic, strategies and a need to pay attention to alternative strategies. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

NASA Astrophysics Data System (ADS)

Costa, Veber; Fernandes, Wilson

2017-11-01

Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods, including exceptionally large non-systematic events, were reasonably estimated with the proposed approach. In addition, by accounting for uncertainties in each modeling step, one is able to obtain a better understanding of the influential factors in large flood formation dynamics.

An operational procedure for rapid flood risk assessment in Europe

NASA Astrophysics Data System (ADS)

Dottori, Francesco; Kalas, Milan; Salamon, Peter; Bianchi, Alessandra; Alfieri, Lorenzo; Feyen, Luc

2017-07-01

The development of methods for rapid flood mapping and risk assessment is a key step to increase the usefulness of flood early warning systems and is crucial for effective emergency response and flood impact mitigation. Currently, flood early warning systems rarely include real-time components to assess potential impacts generated by forecasted flood events. To overcome this limitation, this study describes the benchmarking of an operational procedure for rapid flood risk assessment based on predictions issued by the European Flood Awareness System (EFAS). Daily streamflow forecasts produced for major European river networks are translated into event-based flood hazard maps using a large map catalogue derived from high-resolution hydrodynamic simulations. Flood hazard maps are then combined with exposure and vulnerability information, and the impacts of the forecasted flood events are evaluated in terms of flood-prone areas, economic damage and affected population, infrastructures and cities.An extensive testing of the operational procedure has been carried out by analysing the catastrophic floods of May 2014 in Bosnia-Herzegovina, Croatia and Serbia. The reliability of the flood mapping methodology is tested against satellite-based and report-based flood extent data, while modelled estimates of economic damage and affected population are compared against ground-based estimations. Finally, we evaluate the skill of risk estimates derived from EFAS flood forecasts with different lead times and combinations of probabilistic forecasts. Results highlight the potential of the real-time operational procedure in helping emergency response and management.

A simulation-based probabilistic design method for arctic sea transport systems

NASA Astrophysics Data System (ADS)

Martin, Bergström; Ove, Erikstad Stein; Sören, Ehlers

2016-12-01

When designing an arctic cargo ship, it is necessary to consider multiple stochastic factors. This paper evaluates the merits of a simulation-based probabilistic design method specifically developed to deal with this challenge. The outcome of the paper indicates that the incorporation of simulations and probabilistic design parameters into the design process enables more informed design decisions. For instance, it enables the assessment of the stochastic transport capacity of an arctic ship, as well as of its long-term ice exposure that can be used to determine an appropriate level of ice-strengthening. The outcome of the paper also indicates that significant gains in transport system cost-efficiency can be obtained by extending the boundaries of the design task beyond the individual vessel. In the case of industrial shipping, this allows for instance the consideration of port-based cargo storage facilities allowing for temporary shortages in transport capacity and thus a reduction in the required fleet size / ship capacity.

Rebounding from Tragedy

ERIC Educational Resources Information Center

Kennedy, Mike

2009-01-01

Some regions are prone to hurricanes, tornadoes, floods or earthquakes. Other tragedies, such as fires or acts of violence, can occur just about anywhere. Regardless of the specific type of disaster, schools and universities must be prepared to cope with crises that can disrupt operations, destroy facilities, and displace students and staff.…

Combining information from multiple flood projections in a hierarchical Bayesian framework

NASA Astrophysics Data System (ADS)

Le Vine, Nataliya

2016-04-01

This study demonstrates, in the context of flood frequency analysis, the potential of a recently proposed hierarchical Bayesian approach to combine information from multiple models. The approach explicitly accommodates shared multimodel discrepancy as well as the probabilistic nature of the flood estimates, and treats the available models as a sample from a hypothetical complete (but unobserved) set of models. The methodology is applied to flood estimates from multiple hydrological projections (the Future Flows Hydrology data set) for 135 catchments in the UK. The advantages of the approach are shown to be: (1) to ensure adequate "baseline" 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 diminish the importance of model consistency 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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Justin; Slaughter, Andrew; Veeraraghavan, Swetha

Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) is a finite element application that aims at analyzing the response of 3-D soil-structure systems to natural and man-made hazards such as earthquakes, floods and fire. MASTODON currently focuses on the simulation of seismic events and has the capability to perform extensive ‘source-to-site’ simulations including earthquake fault rupture, nonlinear wave propagation and nonlinear soil-structure interaction (NLSSI) analysis. MASTODON is being developed to be a dynamic probabilistic risk assessment framework that enables analysts to not only perform deterministic analyses, but also easily perform probabilistic or stochastic simulations for the purpose of risk assessment.

Multiscale control of flooding and riparian-forest composition in Lower Michigan, USA.

PubMed

Baker, Matthew E; Wiley, Michael J

2009-01-01

Despite general agreement that river-valley hydrology shapes riparian ecosystems, relevant processes are difficult to distinguish and often inadequately specified in riparian studies. We hypothesize that physical constraints imposed by broad-scale watershed characteristics and river valleys modify local site conditions in a predictable and probabilistic fashion. To test this hypothesis, we employ a series of structural equations that decompose occurrence of riparian ecotypes into regional temperature, catchment storm response, valley hydraulics, and local site wetness via a priori specification of factor structure and ask (1) Is there evidence for multiscale hydrologic control of riparian diversity across Lower Michigan? (2) Do representations of key constraints on flood dynamics distinguish regional patterns of riparian vegetation? (3) How important are these effects? Cross-correlation among geospatial predictors initially obscured much of the variation revealed through analysis of semipartial variance. Causal relationships implied by our model fit with observed variation in riparian conditions (chi-square P = 0.43) and accounted for between 84% and 99% of the occurrence probability of five riparian ecotypes at 94 locations. Results suggest strong variation in the effects of regional climate, and both the relative importance and spatial scale of hydrologic factors influencing riparian vegetation through explicit quantification of relative flood frequency, duration, intensity, and relative overall inundation. Although climate and hydrology are not the only determinants of riparian conditions, interactions of hydrologic sourcing and flood dynamics described by our spatial models drive a significant portion of the variation in riparian ecosystem character throughout Lower Michigan, USA.

Developments of the European Flood Awareness System (EFAS)

NASA Astrophysics Data System (ADS)

Thiemig, Vera; Olav Skøien, Jon; Salamon, Peter; Pappenberger, Florian; Wetterhall, Fredrik; Holst, Bo; Asp, Sara-Sophia; Garcia Padilla, Mercedes; Garcia, Rafael J.; Schweim, Christoph; Ziese, Markus

2017-04-01

EFAS (http://www.efas.eu) is an operational system for flood forecasting and early warning for the entire Europe, which is fully operational as part of the Copernicus Emergency Management Service since 2012. The prime aim of EFAS is to gain time for preparedness measures before major flood events - particularly in trans-national river basins - strike. This is achieved by providing complementary, added value information to the national and regional services holding the mandate for flood warning as well as to the ERCC (European Response and Coordination Centre). Using a coherent model for all of Europe forced with a range of deterministic and ensemble weather forecasts, the system can give a probabilistic flood forecast for a medium range lead time (up to 10 days) independent of country borders. The system is under continuous development, and we will present the basic set up, some prominent examples of recent and ongoing developments (such as the rapid impact assessment, seasonal outlook and the extended domain) and the future challenges.

A probabilistic approach to modeling postfire erosion after the 2009 australian brushfires

USDA-ARS?s Scientific Manuscript database

Major concerns after bushfires and wildfires include increased flooding, erosion and debris flows due to loss of the protective forest floor layer, loss of water storage, and creation of water repellent soil conditions. To assist postfire assessment teams in their efforts to evaluate fire effects an...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bucknor, Matthew; Grabaskas, David; Brunett, Acacia J.

We report that many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended because of deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has beenmore » examining various methodologies for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Considering an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive Reactor Cavity Cooling System following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. Lastly, although this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability of the Reactor Cavity Cooling System (and the reactor system in general) for the postulated transient event.« less

Modeling of a Flooding Induced Station Blackout for a Pressurized Water Reactor Using the RISMC Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandelli, Diego; Prescott, Steven R; Smith, Curtis L

2011-07-01

In the Risk Informed Safety Margin Characterization (RISMC) approach we want to understand not just the frequency of an event like core damage, but how close we are (or are not) to key safety-related events and how might we increase our safety margins. The RISMC Pathway uses the probabilistic margin approach to quantify impacts to reliability and safety by coupling both probabilistic (via stochastic simulation) and mechanistic (via physics models) approaches. This coupling takes place through the interchange of physical parameters and operational or accident scenarios. In this paper we apply the RISMC approach to evaluate the impact of amore » power uprate on a pressurized water reactor (PWR) for a tsunami-induced flooding test case. This analysis is performed using the RISMC toolkit: RELAP-7 and RAVEN codes. RELAP-7 is the new generation of system analysis codes that is responsible for simulating the thermal-hydraulic dynamics of PWR and boiling water reactor systems. RAVEN has two capabilities: to act as a controller of the RELAP-7 simulation (e.g., system activation) and to perform statistical analyses (e.g., run multiple RELAP-7 simulations where sequencing/timing of events have been changed according to a set of stochastic distributions). By using the RISMC toolkit, we can evaluate how power uprate affects the system recovery measures needed to avoid core damage after the PWR lost all available AC power by a tsunami induced flooding. The simulation of the actual flooding is performed by using a smooth particle hydrodynamics code: NEUTRINO.« less

Ho Chi Minh City adaptation to increasing risk of coastal and fluvial floods

NASA Astrophysics Data System (ADS)

Scussolini, Paolo; Lasage, Ralph

2016-04-01

Coastal megacities in southeast Asia are a hotspot of vulnerability to floods. In such contexts, the combination of fast socio-economic development and of climate change impacts on precipitation and sea level generates concerns about the flood damage to people and assets. This work focuses on Ho Chi Minh City, Vietnam, for which we estimate the present and future direct risk from river and coastal floods. A model cascade is used that comprises the Saigon river basin and the urban network, plus the land-use-dependent damaging process. Changes in discharge for five return periods are simulated, enabling the probabilistic calculation of the expected annual economic damage to assets, for differnt scenarios of global emissions, local socio-economic growth, and land subsidence, up to year 2100. The implementation of a range of adaptation strategies is simulated, including building dykes, elevating, creating reservoirs, managing water and sediment upstream, flood-proofing, halting groundwater abstraction. Results are presented on 1) the relative weight of each future driver in determining the flood risk of Ho Chi Minh, and 2) the efficiency and feasibility of each adaptation strategy.

Increasing stress on disaster-risk finance due to large floods

NASA Astrophysics Data System (ADS)

Jongman, Brenden; Hochrainer-Stigler, Stefan; Feyen, Luc; Aerts, Jeroen C. J. H.; Mechler, Reinhard; Botzen, W. J. Wouter; Bouwer, Laurens M.; Pflug, Georg; Rojas, Rodrigo; Ward, Philip J.

2014-04-01

Recent major flood disasters have shown that single extreme events can affect multiple countries simultaneously, which puts high pressure on trans-national risk reduction and risk transfer mechanisms. So far, little is known about such flood hazard interdependencies across regions and the corresponding joint risks at regional to continental scales. Reliable information on correlated loss probabilities is crucial for developing robust insurance schemes and public adaptation funds, and for enhancing our understanding of climate change impacts. Here we show that extreme discharges are strongly correlated across European river basins. We present probabilistic trends in continental flood risk, and demonstrate that observed extreme flood losses could more than double in frequency by 2050 under future climate change and socio-economic development. We suggest that risk management for these increasing losses is largely feasible, and we demonstrate that risk can be shared by expanding risk transfer financing, reduced by investing in flood protection, or absorbed by enhanced solidarity between countries. We conclude that these measures have vastly different efficiency, equity and acceptability implications, which need to be taken into account in broader consultation, for which our analysis provides a basis.

Study on the evaluation method for fault displacement based on characterized source model

NASA Astrophysics Data System (ADS)

Tonagi, M.; Takahama, T.; Matsumoto, Y.; Inoue, N.; Irikura, K.; Dalguer, L. A.

2016-12-01

In IAEA Specific Safety Guide (SSG) 9 describes that probabilistic methods for evaluating fault displacement should be used if no sufficient basis is provided to decide conclusively that the fault is not capable by using the deterministic methodology. In addition, International Seismic Safety Centre compiles as ANNEX to realize seismic hazard for nuclear facilities described in SSG-9 and shows the utility of the deterministic and probabilistic evaluation methods for fault displacement. In Japan, it is required that important nuclear facilities should be established on ground where fault displacement will not arise when earthquakes occur in the future. Under these situations, based on requirements, we need develop evaluation methods for fault displacement to enhance safety in nuclear facilities. We are studying deterministic and probabilistic methods with tentative analyses using observed records such as surface fault displacement and near-fault strong ground motions of inland crustal earthquake which fault displacements arose. In this study, we introduce the concept of evaluation methods for fault displacement. After that, we show parts of tentative analysis results for deterministic method as follows: (1) For the 1999 Chi-Chi earthquake, referring slip distribution estimated by waveform inversion, we construct a characterized source model (Miyake et al., 2003, BSSA) which can explain observed near-fault broad band strong ground motions. (2) Referring a characterized source model constructed in (1), we study an evaluation method for surface fault displacement using hybrid method, which combines particle method and distinct element method. At last, we suggest one of the deterministic method to evaluate fault displacement based on characterized source model. This research was part of the 2015 research project `Development of evaluating method for fault displacement` by the Secretariat of Nuclear Regulation Authority (S/NRA), Japan.

An Application of the SSHAC Level 3 Process to the Probabilistic Seismic Hazard Analysis for Nuclear Facilities at the Hanford Site, Eastern Washington, USA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coppersmith , Kevin J.; Bommer, Julian J.; Bryce, Robert W.

Under the sponsorship of the US Department of Energy (DOE) and the electric utility Energy Northwest, the Pacific Northwest National Laboratory (PNNL) is conducting a probabilistic seismic hazard analysis (PSHA) within the framework of a SSHAC Level 3 procedure (Senior Seismic Hazard Analysis Committee; Budnitz et al., 1997). Specifically, the project is being conducted following the guidelines and requirements specified in NUREG-2117 (USNRC, 2012b) and consistent with approach given in the American Nuclear Standard ANSI/ANS-2.29-2008 Probabilistic Seismic Hazard Analysis. The collaboration between DOE and Energy Northwest is spawned by the needs of both organizations for an accepted PSHA with highmore » levels of regulatory assurance that can be used for the design and safety evaluation of nuclear facilities. DOE committed to this study after performing a ten-year review of the existing PSHA, as required by DOE Order 420.1C. The study will also be used by Energy Northwest as a basis for fulfilling the NRC’s 10CFR50.54(f) requirement that the western US nuclear power plants conduct PSHAs in conformance with SSHAC Level 3 procedures. The study was planned and is being carried out in conjunction with a project Work Plan, which identifies the purpose of the study, the roles and responsibilities of all participants, tasks and their associated schedules, Quality Assurance (QA) requirements, and project deliverables. New data collection and analysis activities are being conducted as a means of reducing the uncertainties in key inputs to the PSHA. It is anticipated that the results of the study will provide inputs to the site response analyses at multiple nuclear facility sites within the Hanford Site and at the Columbia Generating Station.« less

Ensemble Flow Forecasts for Risk Based Reservoir Operations of Lake Mendocino in Mendocino County, California: A Framework for Objectively Leveraging Weather and Climate Forecasts in a Decision Support Environment

NASA Astrophysics Data System (ADS)

Delaney, C.; Hartman, R. K.; Mendoza, J.; Whitin, B.

2017-12-01

Forecast informed reservoir operations (FIRO) is a methodology that incorporates short to mid-range precipitation and flow forecasts to inform the flood operations of reservoirs. The Ensemble Forecast Operations (EFO) alternative is a probabilistic approach of FIRO that incorporates ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, release decisions are made to manage forecasted risk of reaching critical operational thresholds. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to evaluate the viability of the EFO alternative to improve water supply reliability but not increase downstream flood risk. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The EFO alternative was simulated using a 26-year (1985-2010) ESP hindcast generated by the CNRFC. The ESP hindcast was developed using Global Ensemble Forecast System version 10 precipitation reforecasts processed with the Hydrologic Ensemble Forecast System to generate daily reforecasts of 61 flow ensemble members for a 15-day forecast horizon. Model simulation results demonstrate that the EFO alternative may improve water supply reliability for Lake Mendocino yet not increase flood risk for downstream areas. The developed operations framework can directly leverage improved skill in the second week of the forecast and is extendable into the S2S time domain given the demonstration of improved skill through a reliable reforecast of adequate historical duration and consistent with operationally available numerical weather predictions.

Numerical modelling of glacial lake outburst floods using physically based dam-breach models

NASA Astrophysics Data System (ADS)

Westoby, M. J.; Brasington, J.; Glasser, N. F.; Hambrey, M. J.; Reynolds, J. M.; Hassan, M. A. A. M.; Lowe, A.

2015-03-01

The instability of moraine-dammed proglacial lakes creates the potential for catastrophic glacial lake outburst floods (GLOFs) in high-mountain regions. In this research, we use a unique combination of numerical dam-breach and two-dimensional hydrodynamic modelling, employed within a generalised likelihood uncertainty estimation (GLUE) framework, to quantify predictive uncertainty in model outputs associated with a reconstruction of the Dig Tsho failure in Nepal. Monte Carlo analysis was used to sample the model parameter space, and morphological descriptors of the moraine breach were used to evaluate model performance. Multiple breach scenarios were produced by differing parameter ensembles associated with a range of breach initiation mechanisms, including overtopping waves and mechanical failure of the dam face. The material roughness coefficient was found to exert a dominant influence over model performance. The downstream routing of scenario-specific breach hydrographs revealed significant differences in the timing and extent of inundation. A GLUE-based methodology for constructing probabilistic maps of inundation extent, flow depth, and hazard is presented and provides a useful tool for communicating uncertainty in GLOF hazard assessment.

Effects of an Extreme Flood on Trace Elements in River Water-From Urban Stream to Major River Basin.

PubMed

Barber, Larry B; Paschke, Suzanne S; Battaglin, William A; Douville, Chris; Fitzgerald, Kevin C; Keefe, Steffanie H; Roth, David A; Vajda, Alan M

2017-09-19

Major floods adversely affect water quality through surface runoff, groundwater discharge, and damage to municipal water infrastructure. Despite their importance, it can be difficult to assess the effects of floods on streamwater chemistry because of challenges collecting samples and the absence of baseline data. This study documents water quality during the September 2013 extreme flood in the South Platte River, Colorado, USA. Weekly time-series water samples were collected from 3 urban source waters (municipal tap water, streamwater, and wastewater treatment facility effluent) under normal-flow and flood conditions. In addition, water samples were collected during the flood at 5 locations along the South Platte River and from 7 tributaries along the Colorado Front Range. Samples were analyzed for 54 major and trace elements. Specific chemical tracers, representing different natural and anthropogenic sources and geochemical behaviors, were used to compare streamwater composition before and during the flood. The results differentiate hydrological processes that affected water quality: (1) in the upper watershed, runoff diluted most dissolved constituents, (2) in the urban corridor and lower watershed, runoff mobilized soluble constituents accumulated on the landscape and contributed to stream loading, and (3) flood-induced groundwater discharge mobilized soluble constituents stored in the vadose zone.

Effects of an extreme flood on trace elements in river water—From urban stream to major river basin

USGS Publications Warehouse

Barber, Larry B.; Paschke, Suzanne; Battaglin, William A.; Douville, Chris; Fitzgerald, Kevin C.; Keefe, Steffanie H.; Roth, David A.; Vajda, Alan M.

2017-01-01

Major floods adversely affect water quality through surface runoff, groundwater discharge, and damage to municipal water infrastructure. Despite their importance, it can be difficult to assess the effects of floods on streamwater chemistry because of challenges collecting samples and the absence of baseline data. This study documents water quality during the September 2013 extreme flood in the South Platte River, Colorado, USA. Weekly time-series water samples were collected from 3 urban source waters (municipal tap water, streamwater, and wastewater treatment facility effluent) under normal-flow and flood conditions. In addition, water samples were collected during the flood at 5 locations along the South Platte River and from 7 tributaries along the Colorado Front Range. Samples were analyzed for 54 major and trace elements. Specific chemical tracers, representing different natural and anthropogenic sources and geochemical behaviors, were used to compare streamwater composition before and during the flood. The results differentiate hydrological processes that affected water quality: (1) in the upper watershed, runoff diluted most dissolved constituents, (2) in the urban corridor and lower watershed, runoff mobilized soluble constituents accumulated on the landscape and contributed to stream loading, and (3) flood-induced groundwater discharge mobilized soluble constituents stored in the vadose zone.

Leakage of radioactive materials from particle accelerator facilities by non-radiation disasters like fire and flooding and its environmental impacts

NASA Astrophysics Data System (ADS)

Lee, A.; Jung, N. S.; Mokhtari Oranj, L.; Lee, H. S.

2018-06-01

The leakage of radioactive materials generated at particle accelerator facilities is one of the important issues in the view of radiation safety. In this study, fire and flooding at particle accelerator facilities were considered as the non-radiation disasters which result in the leakage of radioactive materials. To analyse the expected effects at each disaster, the case study on fired and flooded particle accelerator facilities was carried out with the property investigation of interesting materials presented in the accelerator tunnel and the activity estimation. Five major materials in the tunnel were investigated: dust, insulators, concrete, metals and paints. The activation levels on the concerned materials were calculated using several Monte Carlo codes (MCNPX 2.7+SP-FISPACT 2007, FLUKA 2011.4c and PHITS 2.64+DCHAIN-SP 2001). The impact weight to environment was estimated for the different beam particles (electron, proton, carbon and uranium) and the different beam energies (100, 430, 600 and 1000 MeV/nucleon). With the consideration of the leakage path of radioactive materials due to fire and flooding, the activation level of selected materials, and the impacts to the environment were evaluated. In the case of flooding, dust, concrete and metal were found as a considerable object. In the case of fire event, dust, insulator and paint were the major concerns. As expected, the influence of normal fire and flooding at electron accelerator facilities would be relatively low for both cases.

Heavy rain prediction using deterministic and probabilistic models - the flash flood cases of 11-13 October 2005 in Catalonia (NE Spain)

NASA Astrophysics Data System (ADS)

Barrera, A.; Altava-Ortiz, V.; Llasat, M. C.; Barnolas, M.

2007-09-01

Between the 11 and 13 October 2005 several flash floods were produced along the coast of Catalonia (NE Spain) due to a significant heavy rainfall event. Maximum rainfall achieved values up to 250 mm in 24 h. The total amount recorded during the event in some places was close to 350 mm. Barcelona city was also in the affected area where high rainfall intensities were registered, but just a few small floods occurred, thanks to the efficient urban drainage system of the city. Two forecasting methods have been applied in order to evaluate their capability of prediction regarding extreme events: the deterministic MM5 model and a probabilistic model based on the analogous method. The MM5 simulation allows analysing accurately the main meteorological features with a high spatial resolution (2 km), like the formation of some convergence lines over the region that partially explains the maximum precipitation location during the event. On the other hand, the analogous technique shows a good agreement among highest probability values and real affected areas, although a larger pluviometric rainfall database would be needed to improve the results. The comparison between the observed precipitation and from both QPF (quantitative precipitation forecast) methods shows that the analogous technique tends to underestimate the rainfall values and the MM5 simulation tends to overestimate them.

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

PubMed

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.

A Vulnerability-Based, Bottom-up Assessment of Future Riverine Flood Risk Using a Modified Peaks-Over-Threshold Approach and a Physically Based Hydrologic Model

NASA Astrophysics Data System (ADS)

Knighton, James; Steinschneider, Scott; Walter, M. Todd

2017-12-01

There is a chronic disconnection among purely probabilistic flood frequency analysis of flood hazards, flood risks, and hydrological flood mechanisms, which hamper our ability to assess future flood impacts. We present a vulnerability-based approach to estimating riverine flood risk that accommodates a more direct linkage between decision-relevant metrics of risk and the dominant mechanisms that cause riverine flooding. We adapt the conventional peaks-over-threshold (POT) framework to be used with extreme precipitation from different climate processes and rainfall-runoff-based model output. We quantify the probability that at least one adverse hydrologic threshold, potentially defined by stakeholders, will be exceeded within the next N years. This approach allows us to consider flood risk as the summation of risk from separate atmospheric mechanisms, and supports a more direct mapping between hazards and societal outcomes. We perform this analysis within a bottom-up framework to consider the relevance and consequences of information, with varying levels of credibility, on changes to atmospheric patterns driving extreme precipitation events. We demonstrate our proposed approach using a case study for Fall Creek in Ithaca, NY, USA, where we estimate the risk of stakeholder-defined flood metrics from three dominant mechanisms: summer convection, tropical cyclones, and spring rain and snowmelt. Using downscaled climate projections, we determine how flood risk associated with a subset of mechanisms may change in the future, and the resultant shift to annual flood risk. The flood risk approach we propose can provide powerful new insights into future flood threats.

River flood seasonality in the Northeast United States and trends in annual timing

NASA Astrophysics Data System (ADS)

Collins, M. J.

2017-12-01

The New England and Mid-Atlantic regions of the Northeast United States have experienced climate-associated increases in both the magnitude and frequency of floods. However, a detailed understanding of flood seasonality across these regions, and how flood seasonality may have changed over the instrumental record, has not been established. The annual timing of river floods reflects the flood-generating mechanisms operating in a basin and many aquatic and riparian organisms are adapted to flood seasonality, as are human uses of river channels and floodplains. Changes in flood seasonality may indicate changes in flood-generating mechanisms, and their interactions, with important implications for habitats, floodplain infrastructure, and human communities. For example, changes in spring or fall flood timing may negatively or positively affect a vulnerable life stage for a migratory fish (e.g., egg setting) depending on whether floods occur more frequently before or after the life history event. In this study I apply an objective, probabilistic method for identifying flood seasons at a monthly resolution for 90 climate-sensitive watersheds in New England and the Mid-Atlantic (Hydrologic Unit Codes 01 and 02). Historical trends in flood timing during the year are also investigated. The analyses are based on partial duration flood series that are an average of 85 years long. The seasonality of flooding in these regions, and any historical changes, are considered in the context of other ongoing or expected phenological changes in the Northeast U.S. environment that affect flood generation—e.g., the timing of leaf-off/leaf-out for deciduous plants. How these factors interact will affect whether and how flood magnitudes and frequencies change in the future and associated impacts.

Running to Safety: Analysis of Disaster Susceptibility of Neighborhoods and Proximity of Safety Facilities in Silay City, Philippines

NASA Astrophysics Data System (ADS)

Patiño, C. L.; Saripada, N. A.; Olavides, R. D.; Sinogaya, J.

2016-06-01

Going on foot is the most viable option when emergency responders fail to show up in disaster zones at the quickest and most reasonable time. In the Philippines, the efficacy of disaster management offices is hampered by factors such as, but not limited to, lack of equipment and personnel, distance, and/or poor road networks and traffic systems. In several instances, emergency response times exceed acceptable norms. This study explores the hazard susceptibility, particularly to fire, flood, and landslides, of neighborhoods vis-à-vis their proximity to safety facilities in Silay City, Philippines. Imbang River exposes communities in the city to flooding while the mountainous terrain makes the city landslide prone. Building extraction was done to get the possible human settlements in the city. The building structures were extracted through image processing using a ruleset-based approach in the process of segmentation and classification of LiDAR derivatives and ortho-photos. Neighborhoods were then identified whether they have low to high susceptibility to disaster risks in terms of floods and landslides based on the hazards maps obtained from the Philippines' Mines and Geosciences Bureau (MGB). Service area analyses were performed to determine the safety facilities available to different neighborhoods at varying running times. Locations which are inaccessible or are difficult to run to because of distance and corresponding hazards were determined. Recommendations are given in the form of infrastructure installation, relocation of facilities, safety equipment and vehicle procurement, and policy changes for specific areas in Silay City.

Assessing economic impact of storm surge under projected sea level rise scenarios

NASA Astrophysics Data System (ADS)

Del Angel, D. C.; Yoskowitz, D.

2017-12-01

Global sea level is expected to rise 0.2-2m by the year 2100. Rising sea level is expected to have a number of impacts such as erosion, saltwater intrusion, and decline in coastal wetlands; all which have direct and indirect socio-economic impact to coastal communities. By 2050, 25% of the world's population will reside within flood-prone areas. These statistics raise a concern for the economic cost that sea level and flooding has on the growing coastal communities. Economic cost of storm surge inundation and rising seas may include loss or damage to public facilities and infrastructure that may become temporarily inaccessible, as well as disruptions to business and services. This goal of this project is to assess economic impacts of storms under four SLR scenarios including low, intermediate-low, intermediate-high, and high (0.2m, 0.5m, 1.2m and 2m, respectively) in the Northern Gulf of Mexico region. To assess flooding impact on communities from storm surge, this project utilizes HAZUS-MH software - a Geographic Information System (GIS)-based modeling tool developed by the Federal Emergency Management Agency - to estimate physical, economic, and social impacts of natural disasters such as floods, earthquakes and hurricanes. The HAZUS database comes integrated with aggregate and site specific inventory which includes: demographic data, general building stock, agricultural statistics, vehicle inventory, essential facilities, transportation systems, utility systems (among other sensitive facilities). User-defined inundation scenarios will serve to identify assets at risk and damage estimates will be generated using the Depth Damage Function included in the HAZUS software. Results will focus on 3 communities in the Gulf and highlight changes in storm flood impact. This approach not only provides a method for economic impact assessment but also begins to create a link between ecosystem services and natural and nature-based features such as wetlands, beaches and dunes. Results from this analysis can provide actionable information needed for policy development and planning for coastal communities.

40 CFR 267.18 - What are the standards for selecting the location of my facility?

Code of Federal Regulations, 2012 CFR

2012-07-01

... greater chance of flooding in any given year from any source. (2) “Washout” means the movement of hazardous waste from the active portion of the facility as a result of flooding. (3) “100-year flood” means...

40 CFR 267.18 - What are the standards for selecting the location of my facility?

Code of Federal Regulations, 2010 CFR

2010-07-01

... greater chance of flooding in any given year from any source. (2) “Washout” means the movement of hazardous waste from the active portion of the facility as a result of flooding. (3) “100-year flood” means...

40 CFR 267.18 - What are the standards for selecting the location of my facility?

Code of Federal Regulations, 2014 CFR

2014-07-01

... greater chance of flooding in any given year from any source. (2) “Washout” means the movement of hazardous waste from the active portion of the facility as a result of flooding. (3) “100-year flood” means...

40 CFR 267.18 - What are the standards for selecting the location of my facility?

Code of Federal Regulations, 2013 CFR

2013-07-01

... greater chance of flooding in any given year from any source. (2) “Washout” means the movement of hazardous waste from the active portion of the facility as a result of flooding. (3) “100-year flood” means...

40 CFR 267.18 - What are the standards for selecting the location of my facility?

Code of Federal Regulations, 2011 CFR

2011-07-01

... greater chance of flooding in any given year from any source. (2) “Washout” means the movement of hazardous waste from the active portion of the facility as a result of flooding. (3) “100-year flood” means...

A 2D simulation model for urban flood management

NASA Astrophysics Data System (ADS)

Price, Roland; van der Wielen, Jonathan; Velickov, Slavco; Galvao, Diogo

2014-05-01

The European Floods Directive, which came into force on 26 November 2007, requires member states to assess all their water courses and coast lines for risk of flooding, to map flood extents and assets and humans at risk, and to take adequate and coordinated measures to reduce the flood risk in consultation with the public. Flood Risk Management Plans are to be in place by 2015. There are a number of reasons for the promotion of this Directive, not least because there has been much urban and other infrastructural development in flood plains, which puts many at risk of flooding along with vital societal assets. In addition there is growing awareness that the changing climate appears to be inducing more frequent extremes of rainfall with a consequent increases in the frequency of flooding. Thirdly, the growing urban populations in Europe, and especially in the developing countries, means that more people are being put at risk from a greater frequency of urban flooding in particular. There are urgent needs therefore to assess flood risk accurately and consistently, to reduce this risk where it is important to do so or where the benefit is greater than the damage cost, to improve flood forecasting and warning, to provide where necessary (and possible) flood insurance cover, and to involve all stakeholders in decision making affecting flood protection and flood risk management plans. Key data for assessing risk are water levels achieved or forecasted during a flood. Such levels should of course be monitored, but they also need to be predicted, whether for design or simulation. A 2D simulation model (PriceXD) solving the shallow water wave equations is presented specifically for determining flood risk, assessing flood defense schemes and generating flood forecasts and warnings. The simulation model is required to have a number of important properties: -Solve the full shallow water wave equations using a range of possible solutions; -Automatically adjust the time step and keep it as large as possible while maintaining the stability of the flow calculations; -Operate on a square grid at any resolution while retaining at least some details of the ground topography of the basic grid, the storage, and the form roughness and conveyance of the ground surface; -Account for the overall average ground slope for particular coarse cells; -Have the facility to refine the grid locally; -Have the facility to treat ponds or lakes as single, irregular cells; -Permit prescribed inflows and arbitrary outflows across the boundaries of the model domain or internally, and sources and sinks at any interior cell; -Simulate runoff for spatial rainfall while permitting infiltration; -Use ground surface cover and soil type indices to determine surface roughness, interception and infiltration parameters; -Present results at the basic cell level; -Have the facility to begin a model run with monitored soil moisture data; -Have the facility to hot-start a simulation using dumped data from a previous simulation; -Operate with a graphics cards for parallel processing; -Have the facility to link directly to the urban drainage simulation software such as SWMM through an Open Modelling Interface; -Be linked to the Netherlands national rainfall database for continuous simulation of rainfall-runoff for particular polders and urban areas; -Make the engine available as Open Source together with benchmark datasets; PriceXD forms a key modelling component of an integrated urban water management system consisting of an on-line database and a number of complementary modelling systems for urban hydrology, groundwater, potable water distribution, wastewater and stormwater drainage (separate and combined sewerage), wastewater treatment, and surface channel networks. This will be a 'plug and play' system. By linking the models together, confidence in the accuracy of the above-ground damage and construction costs is comparable to the below-ground costs. What is more, PriceXD can be used to examine additional physical phenomenon such as the interaction between flood flows and flows to and from inlets distributed along the pipes of the underground network, and to optimize the removal of blockages and improve asset management. Finally, PriceXD is already an integral component on a number of operational projects and platforms, including the MyWater distributed platform and the HydroNET web portal, where it is already applied to realistic case studies on the Netherlands (namely the Rijnland area), facilitating the access to both the model execution and results, by abstracting most of the complexity out of the model setup and configuration.

Surging Seas Risk Finder: A Tool for Local-Scale Flood Risk Assessments in Coastal Cities

NASA Astrophysics Data System (ADS)

Kulp, S. A.; Strauss, B.

2015-12-01

Local decision makers in coastal cities require accurate, accessible, and thorough assessments of flood exposure risk within their individual municipality, in their efforts to mitigate against damage due to future sea level rise. To fill this need, we have developed Climate Central's Surging Seas Risk Finder, an interactive data toolkit which presents our sea level rise and storm surge analysis for every coastal town, city, county, and state within the USA. Using this tool, policy makers can easily zoom in on their local place of interest to receive a detailed flood risk assessment, which synthesizes a wide range of features including total population, socially vulnerable population, housing, property value, road miles, power plants, schools, hospitals, and many other critical facilities. Risk Finder can also be used to identify specific points of interest in danger of exposure at different flood levels. Additionally, this tool provides localized storm surge probabilities and sea level rise projections at tidal gauges along the coast, so that users can quickly understand the risk of flooding in their area over the coming decades.

Probabilistic flood forecasting tool for Andalusia (Spain). Application to September 2012 disaster event in Vera Playa.

NASA Astrophysics Data System (ADS)

García, Darío; Baquerizo, Asunción; Ortega, Miguel; Herrero, Javier; Ángel Losada, Miguel

2013-04-01

Torrential and heavy rains are frequent in Andalusia (Southern Spain) due to the characteristic Mediterranean climate (semi-arid areas). This, in combination with a massive occupation of floodable (river sides) and coastal areas, produces severe problems of management and damage to the population and social and economical activities when extreme events occur. Some of the most important problems are being produced during last years in Almería (Southeastern Andalusia). Between 27 and 28 September 2012 rainstorms characterized by 240mm in 24h (exceeding precipitation for a return period of 500 years) occurred. Antas River and Jático creek, that are normally dry, became raging torrents. The massive flooding of occupied areas resulted in eleven deaths and two missing in Andalucía, with a total estimated cost of all claims for compensation on the order of 197 million euros. This study presents a probabilistic flood forecasting tool including the effect of river and marine forcings. It is based on a distributed, physically-based hydrological model (WiMMed). For Almería the model has been calibrated with the largest event recorded in Cantoria gauging station (data since 1965) on 19 October 1973. It was then validated with the second strongest event (26 October 1977). Among the different results of the model, it can provide probability floods scenarios in Andalusia with up 10 days weather forecasts. The tool has been applied to Vera, a 15.000 inhabitants town located in the east of Almería along the Antas River at an altitude of 95 meters. Its main economic resource is the "beach and sun" based-tourism, which has experienced an enormous growth during last decades. Its coastal stretch has been completely built in these years, occupying floodable areas and constricting the channel and rivers mouths. Simulations of the model in this area for the 1973 event and published in March 2011 on the internet event already announced that the floods of September 2012 may occur.

Advanced Reactor Passive System Reliability Demonstration Analysis for an External Event

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bucknor, Matthew D.; Grabaskas, David; Brunett, Acacia J.

2016-01-01

Many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended due to deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has been examining various methodologiesmore » for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Centering on an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive reactor cavity cooling system following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. While this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability for the reactor cavity cooling system (and the reactor system in general) to the postulated transient event.« less

Advanced Reactor Passive System Reliability Demonstration Analysis for an External Event

DOE PAGES

Bucknor, Matthew; Grabaskas, David; Brunett, Acacia J.; ...

2017-01-24

We report that many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended because of deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has beenmore » examining various methodologies for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Considering an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive Reactor Cavity Cooling System following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. Lastly, although this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability of the Reactor Cavity Cooling System (and the reactor system in general) for the postulated transient event.« less

Annual timing of river floods in the Northeast United States: seasonal characterization and temporal trends

NASA Astrophysics Data System (ADS)

Collins, M. J.

2016-12-01

Increases in flood magnitude and frequency have been documented in climate-sensitive watersheds in the Northeast United States. Associated changes in inundation frequency and/or magnitude, or changes in stream channel form and function, can affect human uses of floodplain environments (e.g., dwellings or transportation infrastructure) as well as aquatic and riparian habitats. Historical changes in flood magnitude and frequency also have important implications for designing floodplain infrastructure and channel modifications because well-accepted statistical methods for design-flood prediction require flood records with stationary means and variances. Changes in flood timing during the year may also be impactful, but have not been studied in detail for the Northeast United States. For example, relatively modest shifts in the timing of winter/spring floods can affect the incidence of ice jam complications. Or, changes in spring or fall flood timing may positively or negatively affect a vulnerable life stage for a migratory fish (e.g., egg setting) depending on whether floods occur more frequently before or after the life history event. With this study I apply an objective, probabilistic method for identifying flood seasonality in climate-sensitive watersheds of the Mid-Atlantic and New England regions (Hydrologic Unit Codes 01 and 02). Temporal trends in the timing of floods within significant flood seasons at a site are then analyzed using a method that employs directional statistics. The analyses are based on partial duration flood series that are an average of 85 years long. Documented changes in flood timing during the year are considered in the context of both potential historical impacts and expectations for future flood timing given regional climate change projections.

Meteorology Assessment of Historic Rainfall for Los Alamos During September 2013

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bruggeman, David Alan; Dewart, Jean Marie

2016-02-12

DOE Order 420.1, Facility Safety, requires that site natural phenomena hazards be evaluated every 10 years to support the design of nuclear facilities. The evaluation requires calculating return period rainfall to determine roof loading requirements and flooding potential based on our on-site rainfall measurements. The return period rainfall calculations are done based on statistical techniques and not site-specific meteorology. This and future studies analyze the meteorological factors that produce the significant rainfall events. These studies provide the meteorology context of the return period rainfall events.

Floods in the Raccoon River basin, Iowa

USGS Publications Warehouse

Heinitz, Albert J.

1980-01-01

Evaluation of flood hazards, and the planning, design, and operation of various facilities on flood plains requires information on floods. This report provides information on flood stages and discharges, flood magnitude and frequency, bench mark data, and flood profiles for the Raccoon River and some of its tributaries. Ir covers the Raccoon River, the North Raccoon River to the northern boundary of Sac County and the lower reaches of the Middle and South Raccoon Rivers.

Risk-based zoning for urbanizing floodplains.

PubMed

Porse, Erik

2014-01-01

Urban floodplain development brings economic benefits and enhanced flood risks. Rapidly growing cities must often balance the economic benefits and increased risks of floodplain settlement. Planning can provide multiple flood mitigation and environmental benefits by combining traditional structural measures such as levees, increasingly popular landscape and design features (green infrastructure), and non-structural measures such as zoning. Flexibility in both structural and non-structural options, including zoning procedures, can reduce flood risks. This paper presents a linear programming formulation to assess cost-effective urban floodplain development decisions that consider benefits and costs of development along with expected flood damages. It uses a probabilistic approach to identify combinations of land-use allocations (residential and commercial development, flood channels, distributed runoff management) and zoning regulations (development zones in channel) to maximize benefits. The model is applied to a floodplain planning analysis for an urbanizing region in the Baja Sur peninsula of Mexico. The analysis demonstrates how (1) economic benefits drive floodplain development, (2) flexible zoning can improve economic returns, and (3) cities can use landscapes, enhanced by technology and design, to manage floods. The framework can incorporate additional green infrastructure benefits, and bridges typical disciplinary gaps for planning and engineering.

76 FR 59121 - Notice of Availability of the Record of Decision for the Final Environmental Impact Statement...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-23

... lined open channels; grade control structures; bridges and drainage crossings; building pads; and water quality control facilities (sedimentation control, flood control, debris, and water quality basins). The... facilities (sedimentation control, flood debris, and water quality basins); regular and ongoing maintenance...

Uncertainties in the palaeoflood record - interpreting geomorphology since 12 500 BP

NASA Astrophysics Data System (ADS)

Moloney, Jessica; Coulthard, Tom; Freer, Jim; Rogerson, Mike

2017-04-01

Recent floods in the UK have reinvigorated the national debate within academic and non-academic organisations of how we quantify risk and improve the resilience of communities to flooding. One critical aspect of that debate is to better understand and quantify the frequency of extreme floods occurring. The research presented in this study explores the challenges and uncertainties of using longer term palaeoflood data records to improve the quantification of flood risk. The frequency of floods has been studied on short (under 100 years) and long-time (over 200 years) scales. Long term flood frequency records rely on the radiocarbon dating and interpretation of geomorphological evidence within fluvial depositional environments. However, there are limitations with the methods used to do this. Notably, the use of probability distribution functions of fluvial deposits dates does not consider any other information, such as the geomorphological context of material and/ or the type of depositional environment. This study re-analyses 776 radiocarbon dated fluvial deposits from the UK, which have been compiled into a database, to interpret the geomorphological flood record. Initial findings indicate that even this large number of samples may be unsuitable for probabilistic methods and shows an unusual sensitivity to the number of records present in the database.

A probabilistic approach to modeling postfire erosion after the 2009 Australian bushfires

Treesearch

P. R. Robichaud; W. J. Elliot; F. B. Pierson; D. E. Hall; C. A. Moffet

2009-01-01

Major concerns after bushfires and wildfires include increased flooding, erosion and debris flows due to loss of the protective forest floor layer, loss of water storage, and creation of water repellent soil conditions. To assist postfire assessment teams in their efforts to evaluate fire effects and make postfire treatment decisions, a web-based Erosion Risk...

Staged decision making based on probabilistic forecasting

NASA Astrophysics Data System (ADS)

Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris

2016-04-01

Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in flood event management, the more damage can be reduced. And with decisions based on probabilistic forecasts, partial decisions can be made earlier in time (with a lower probability) and can be scaled up or down later in time when there is more certainty; whether the event takes place or not. Partial decisions are often more cheap, or shorten the final mitigation-time at the moment when there is more certainty. The proposed method is tested on Stonehaven, on the Carron River in Scotland. Decisions to implement demountable defences in the town are currently made based on a very short lead-time due to the absence of certainty. Application showed that staged decision making is possible and gives the decision maker more time to respond to a situation. The decision maker is able to take a lower regret decision with higher uncertainty and less related negative consequences. Although it is not possible to quantify intangible effects, it is part of the analysis to reduce these effects. Above all, the proposed approach has shown to be a possible improvement in economic terms and opens up possibilities of more flexible and robust decision making.

Amplification of flood frequencies with local sea level rise and emerging flood regimes

NASA Astrophysics Data System (ADS)

Buchanan, Maya K.; Oppenheimer, Michael; Kopp, Robert E.

2017-06-01

The amplification of flood frequencies by sea level rise (SLR) is expected to become one of the most economically damaging impacts of climate change for many coastal locations. Understanding the magnitude and pattern by which the frequency of current flood levels increase is important for developing more resilient coastal settlements, particularly since flood risk management (e.g. infrastructure, insurance, communications) is often tied to estimates of flood return periods. The Intergovernmental Panel on Climate Change’s Fifth Assessment Report characterized the multiplication factor by which the frequency of flooding of a given height increases (referred to here as an amplification factor; AF). However, this characterization neither rigorously considered uncertainty in SLR nor distinguished between the amplification of different flooding levels (such as the 10% versus 0.2% annual chance floods); therefore, it may be seriously misleading. Because both historical flood frequency and projected SLR are uncertain, we combine joint probability distributions of the two to calculate AFs and their uncertainties over time. Under probabilistic relative sea level projections, while maintaining storm frequency fixed, we estimate a median 40-fold increase (ranging from 1- to 1314-fold) in the expected annual number of local 100-year floods for tide-gauge locations along the contiguous US coastline by 2050. While some places can expect disproportionate amplification of higher frequency events and thus primarily a greater number of historically precedented floods, others face amplification of lower frequency events and thus a particularly fast growing risk of historically unprecedented flooding. For example, with 50 cm of SLR, the 10%, 1%, and 0.2% annual chance floods are expected respectively to recur 108, 335, and 814 times as often in Seattle, but 148, 16, and 4 times as often in Charleston, SC.

Predicting location-specific extreme coastal floods in the future climate by introducing a probabilistic method to calculate maximum elevation of the continuous water mass caused by a combination of water level variations and wind waves

NASA Astrophysics Data System (ADS)

Leijala, Ulpu; Björkqvist, Jan-Victor; Johansson, Milla M.; Pellikka, Havu

2017-04-01

Future coastal management continuously strives for more location-exact and precise methods to investigate possible extreme sea level events and to face flooding hazards in the most appropriate way. Evaluating future flooding risks by understanding the behaviour of the joint effect of sea level variations and wind waves is one of the means to make more comprehensive flooding hazard analysis, and may at first seem like a straightforward task to solve. Nevertheless, challenges and limitations such as availability of time series of the sea level and wave height components, the quality of data, significant locational variability of coastal wave height, as well as assumptions to be made depending on the study location, make the task more complicated. In this study, we present a statistical method for combining location-specific probability distributions of water level variations (including local sea level observations and global mean sea level rise) and wave run-up (based on wave buoy measurements). The goal of our method is to obtain a more accurate way to account for the waves when making flooding hazard analysis on the coast compared to the approach of adding a separate fixed wave action height on top of sea level -based flood risk estimates. As a result of our new method, we gain maximum elevation heights with different return periods of the continuous water mass caused by a combination of both phenomena, "the green water". We also introduce a sensitivity analysis to evaluate the properties and functioning of our method. The sensitivity test is based on using theoretical wave distributions representing different alternatives of wave behaviour in relation to sea level variations. As these wave distributions are merged with the sea level distribution, we get information on how the different wave height conditions and shape of the wave height distribution influence the joint results. Our method presented here can be used as an advanced tool to minimize over- and underestimation of the combined effect of sea level variations and wind waves, and to help coastal infrastructure planning and support smooth and safe operation of coastal cities in a changing climate.

A probabilistic approach of the Flash Flood Early Warning System (FF-EWS) in Catalonia based on radar ensemble generation

NASA Astrophysics Data System (ADS)

Velasco, David; Sempere-Torres, Daniel; Corral, Carles; Llort, Xavier; Velasco, Enrique

2010-05-01

Early Warning Systems (EWS) are commonly identified as the most efficient tools in order to improve the preparedness and risk management against heavy rains and Flash Floods (FF) with the objective of reducing economical losses and human casualties. In particular, flash floods affecting torrential Mediterranean catchments are a key element to be incorporated within operational EWSs. The characteristic high spatial and temporal variability of the storms requires high-resolution data and methods to monitor/forecast the evolution of rainfall and its hydrological impact in small and medium torrential basins. A first version of an operational FF-EWS has been implemented in Catalonia (NE Spain) under the name of EHIMI system (Integrated Tool for Hydrometeorological Forecasting) with the support of the Catalan Water Agency (ACA) and the Meteorological Service of Catalonia (SMC). Flash flood warnings are issued based on radar-rainfall estimates. Rainfall estimation is performed on radar observations with high spatial and temporal resolution (1km2 and 10 minutes) in order to adapt the warning scale to the 1-km grid of the EWS. The method is based on comparing observed accumulated rainfall against rainfall thresholds provided by the regional Intensity-Duration-Frequency (IDF) curves. The so-called "aggregated rainfall warning" at every river cell is obtained as the spatially averaged rainfall over its associated upstream draining area. Regarding the time aggregation of rainfall, the critical duration is thought to be an accumulation period similar to the concentration time of each cachtment. The warning is issued once the forecasted rainfall accumulation exceeds the rainfall thresholds mentioned above, which are associated to certain probability of occurrence. Finally, the hazard warning is provided and shown to the decision-maker in terms of exceeded return periods at every river cell covering the whole area of Catalonia. The objective of the present work includes the probabilistic component to the FF-EWS. As a first step, we have incorporated the uncertainty in rainfall estimates and forecasts based on an ensemble of equiprobable rainfall scenarios. The presented study has focused on a number of rainfall events and the performance of the FF-EWS evaluated in terms of its ability to produce probabilistic hazard warnings for decision-making support.

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

NASA Astrophysics Data System (ADS)

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.

Identifying Levee Breach Hotspots via Fine Resolution 2D Hydrodynamic Modeling - a Case Study in the Obion River

NASA Astrophysics Data System (ADS)

Bhuyian, M. N. M.; Kalyanapu, A. J.; Dullo, T. T.; VandenBerge, D.

2017-12-01

The Obion River, located in North-West Tennessee was channelized in last century to increase flow capacity and reduce flooding. Upstream of the river mainly consists of multiple tributaries that merge near Rives. The lowest water level (LWL) downstream of Rives has increased about four feet since 1980. It is estimated that this phenomenon could reduce 20% of channel conveyance if water surface slope is assumed same as channel slope. Reduction in conveyance would result in a frequent exposure to flood stage and higher stage for a given flood. Bed level change and exposure to flood stage are critical to levee safety. In the Obion River, levee breach was responsible for flooding in instances even when flood stage was lower than the levee crest. In such a circumstance, accurate simulation of inundation extent via conventional flood model is challenging because, the flood models consider ground data as static and cannot accommodate breaching unless the location of breaching is specified. Therefore, the objective of this study is to propose an approach for determining hotspots of levee breach via fine resolution hydrodynamic modeling to reduce uncertainty in flood inundation modeling. A two-dimensional LiDAR based hydrodynamic model for the Obion River would be used to determine levee breach hotspots using simulated flow parameters (i.e. current velocity, change in stage, time of exposure to high stage etc.) for a design flood event. Identifying breaching hotspots would allow determining probabilistic flood extent under probable breaching conditions. This should reduce uncertainty in inundation mapping in a channelized riverine system.

Development of a flood early warning system and communication with end-users: the Vipava/Vipacco case study in the KULTURisk FP7 project

NASA Astrophysics Data System (ADS)

Grossi, Giovanna; Caronna, Paolo; Ranzi, Roberto

2014-05-01

Within the framework of risk communication, the goal of an early warning system is to support the interaction between technicians and authorities (and subsequently population) as a prevention measure. The methodology proposed in the KULTURisk FP7 project aimed to build a closer collaboration between these actors, in the perspective of promoting pro-active actions to mitigate the effects of flood hazards. The transnational (Slovenia/ Italy) Soča/Isonzo case study focused on this concept of cooperation between stakeholders and hydrological forecasters. The DIMOSHONG_VIP hydrological model was calibrated for the Vipava/Vipacco River (650 km2), a tributary of the Soča/Isonzo River, on the basis of flood events occurred between 1998 and 2012. The European Centre for Medium-Range Weather Forecasts (ECMWF) provided the past meteorological forecasts, both deterministic (1 forecast) and probabilistic (51 ensemble members). The resolution of the ECMWF grid is currently about 15 km (Deterministic-DET) and 30 km (Ensemble Prediction System-EPS). A verification was conducted to validate the flood-forecast outputs of the DIMOSHONG_VIP+ECMWF early warning system. Basic descriptive statistics, like event probability, probability of a forecast occurrence and frequency bias were determined. Some performance measures were calculated, such as hit rate (probability of detection) and false alarm rate (probability of false detection). Relative Opening Characteristic (ROC) curves were generated both for deterministic and probabilistic forecasts. These analysis showed a good performance of the early warning system, in respect of the small size of the sample. A particular attention was spent to the design of flood-forecasting output charts, involving and inquiring stakeholders (Alto Adriatico River Basin Authority), hydrology specialists in the field, and common people. Graph types for both forecasted precipitation and discharge were set. Three different risk thresholds were identified ("attention", "pre-alarm" or "alert", "alarm"), with an "icon-style" representation, suitable for communication to civil protection stakeholders or the public. Aiming at showing probabilistic representations in a "user-friendly" way, we opted for the visualization of the single deterministic forecasted hydrograph together with the 5%, 25%, 50%, 75% and 95% percentiles bands of the Hydrological Ensemble Prediction System (HEPS). HEPS is generally used for 3-5 days hydrological forecasts, while the error due to incorrect initial data is comparable to the error due to the lower resolution with respect to the deterministic forecast. In the short term forecasting (12-48 hours) the HEPS-members show obviously a similar tendency; in this case, considering its higher resolution, the deterministic forecast is expected to be more effective. The plot of different forecasts in the same chart allows the use of model outputs from 4/5 days to few hours before a potential flood event. This framework was built to help a stakeholder, like a mayor, a civil protection authority, etc, in the flood control and management operations, and was designed to be included in a wider decision support system.

Geomorphic change caused by outburst floods and debris flows at Mount Rainier, Washington, with emphasis on Tahoma Creek valley

USGS Publications Warehouse

Walder, J.S.; Driedger, C.L.

1994-01-01

Debris flows have caused rapid geomorphic change in several glacierized drainages on Mount Rainier, Washington. Nearly all of these flows began as glacial outburst floods, then transformed to debris flows by incorporating large masses of sediment in channel reaches where streams have incised proglacial sediments and stagnant glacier ice. This stagnant ice is a relic of advanced glacier positions achieved during the mid-nineteenth century Little Ice Age maximum and the readvance of the 1960's and 1970's. Debris flows have been especially important agents of geomorphic change along Tahoma Creek, which drains South Tahoma Glacier. Debris flows in Tahoma Creek valley have transported downstream about 107 m3 Of sediment since 1967, causing substantial aggradation and damage to roads and facilities in Mount Rainier National Park. The average denudation rate in the upper part of the Tahoma Creek drainage basin in the same period has been extraordinarily high: more than 20 millimeters per year, a value exceeded only rarely in basins affected by debris flows. However, little or none of this sediment has yet passed out of the Tahoma Creek drainage basin. Outburst floods from South Tahoma Glacier form by release of subglacially stored water. The volume of stored water discharged during a typical outburst flood would form a layer several tens of millimeters thick over the bed of the entire glacier, though it is more likely that large linked cavities account for most of the storage. Statistical analysis shows that outburst floods usually occur during periods of atypically hot or rainy weather in summer or early autumn, and that the probability of an outburst increases with temperature (a proxy measure of ablation rate) or rainfall rate. On the basis of these results, we suggest that outburst floods are triggered when rapid input of water to the glacier bed causes transient increase in water pressure, thereby destabilizing the linked-cavity system. The probabilistic nature of the relation between water-input rate and outburst-flood occurrence suggests that the connections between englacial conduits, basal cavities and main meltwater channels may vary temporally. The correlation between outburst floods and meteorological factors casts doubt on an earlier hypothesis that melting around geothermal vents triggers outburst floods from South Tahoma Glacier. The likelihood that outburst floods from South Tahoma Glacier will trigger debris flows should decrease with time, as the deeply incised reach of Tahoma Creek widens by normal slope processes and stagnant ice decays. Drawing analogies to the geomorphic evolution of a reach of Tahoma Creek first incised by an outburst flood in 1967, we suggest the present period of debris-flow activity along Tahoma Creek will last about 25 years, that is, until about the year 2010. Comparison of geomorphic change at Tahoma Creek to that in two other glacierized alphine basins indicates that debris-rich stagnant ice can be an importantsource of sediment to debris flows as long as floods are frequent or channel slope is great.

Limited-scope probabilistic safety analysis for the Los Alamos Meson Physics Facility (LAMPF)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharirli, M.; Rand, J.L.; Sasser, M.K.

1992-01-01

The reliability of instrumentation and safety systems is a major issue in the operation of accelerator facilities. A probabilistic safety analysis was performed or the key safety and instrumentation systems at the Los Alamos Meson Physics Facility (LAMPF). in Phase I of this unique study, the Personnel Safety System (PSS) and the Current Limiters (XLs) were analyzed through the use of the fault tree analyses, failure modes and effects analysis, and criticality analysis. Phase II of the program was done to update and reevaluate the safety systems after the Phase I recommendations were implemented. This paper provides a brief reviewmore » of the studies involved in Phases I and II of the program.« less

Limited-scope probabilistic safety analysis for the Los Alamos Meson Physics Facility (LAMPF)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharirli, M.; Rand, J.L.; Sasser, M.K.

1992-12-01

The reliability of instrumentation and safety systems is a major issue in the operation of accelerator facilities. A probabilistic safety analysis was performed or the key safety and instrumentation systems at the Los Alamos Meson Physics Facility (LAMPF). in Phase I of this unique study, the Personnel Safety System (PSS) and the Current Limiters (XLs) were analyzed through the use of the fault tree analyses, failure modes and effects analysis, and criticality analysis. Phase II of the program was done to update and reevaluate the safety systems after the Phase I recommendations were implemented. This paper provides a brief reviewmore » of the studies involved in Phases I and II of the program.« less

A Bayesian Surrogate for Regional Skew in Flood Frequency Analysis

NASA Astrophysics Data System (ADS)

Kuczera, George

1983-06-01

The problem of how to best utilize site and regional flood data to infer the shape parameter of a flood distribution is considered. One approach to this problem is given in Bulletin 17B of the U.S. Water Resources Council (1981) for the log-Pearson distribution. Here a lesser known distribution is considered, namely, the power normal which fits flood data as well as the log-Pearson and has a shape parameter denoted by λ derived from a Box-Cox power transformation. The problem of regionalizing λ is considered from an empirical Bayes perspective where site and regional flood data are used to infer λ. The distortive effects of spatial correlation and heterogeneity of site sampling variance of λ are explicitly studied with spatial correlation being found to be of secondary importance. The end product of this analysis is the posterior distribution of the power normal parameters expressing, in probabilistic terms, what is known about the parameters given site flood data and regional information on λ. This distribution can be used to provide the designer with several types of information. The posterior distribution of the T-year flood is derived. The effect of nonlinearity in λ on inference is illustrated. Because uncertainty in λ is explicitly allowed for, the understatement in confidence limits due to fixing λ (analogous to fixing log skew) is avoided. Finally, it is shown how to obtain the marginal flood distribution which can be used to select a design flood with specified exceedance probability.

Urban flood early warning systems: approaches to hydrometeorological forecasting and communicating risk

NASA Astrophysics Data System (ADS)

Cranston, Michael; Speight, Linda; Maxey, Richard; Tavendale, Amy; Buchanan, Peter

2015-04-01

One of the main challenges for the flood forecasting community remains the provision of reliable early warnings of surface (or pluvial) flooding. The Scottish Flood Forecasting Service has been developing approaches for forecasting the risk of surface water flooding including capitalising on the latest developments in quantitative precipitation forecasting from the Met Office. A probabilistic Heavy Rainfall Alert decision support tool helps operational forecasters assess the likelihood of surface water flooding against regional rainfall depth-duration estimates from MOGREPS-UK linked to historical short-duration flooding in Scotland. The surface water flood risk is communicated through the daily Flood Guidance Statement to emergency responders. A more recent development is an innovative risk-based hydrometeorological approach that links 24-hour ensemble rainfall forecasts through a hydrological model (Grid-to-Grid) to a library of impact assessments (Speight et al., 2015). The early warning tool - FEWS Glasgow - presents the risk of flooding to people, property and transport across a 1km grid over the city of Glasgow with a lead time of 24 hours. Communication of the risk was presented in a bespoke surface water flood forecast product designed based on emergency responder requirements and trialled during the 2014 Commonwealth Games in Glasgow. The development of new approaches to surface water flood forecasting are leading to improved methods of communicating the risk and better performance in early warning with a reduction in false alarm rates with summer flood guidance in 2014 (67%) compared to 2013 (81%) - although verification of instances of surface water flooding remains difficult. However the introduction of more demanding hydrometeorological capabilities with associated greater levels of uncertainty does lead to an increased demand on operational flood forecasting skills and resources. Speight, L., Cole, S.J., Moore, R.J., Pierce, C., Wright, B., Golding, B., Cranston, M., Tavendale, A., Ghimire, S., and Dhondia, J. (2015) Developing surface water flood forecasting capabilities in Scotland: an operational pilot for the 2014 Commonwealth Games in Glasgow. Journal of Flood Risk Management, In Press.

Understanding flood-induced water chemistry variability extracting temporal patterns with the LDA method

NASA Astrophysics Data System (ADS)

Aubert, A. H.; Tavenard, R.; Emonet, R.; De Lavenne, A.; Malinowski, S.; Guyet, T.; Quiniou, R.; Odobez, J.; Merot, P.; Gascuel-odoux, C.

2013-12-01

Studying floods has been a major issue in hydrological research for years, both in quantitative and qualitative hydrology. Stream chemistry is a mix of solutes, often used as tracers, as they originate from various sources in the catchment and reach the stream by various flow pathways. Previous studies (for instance (1)) hypothesized that stream chemistry reaction to a rainfall event is not unique but varies seasonally, and according to the yearly meteorological conditions. Identifying a typology of flood temporal chemical patterns is a way to better understand catchment processes at the flood and seasonal time scale. We applied a probabilistic model (Latent Dirichlet Allocation or LDA (2)) mining recurrent sequential patterns from a dataset of floods. A set of 472 floods was automatically extracted from a daily 12-year long record of nitrate, dissolved organic carbon, sulfate and chloride concentrations. Rainfall, discharge, water table depth and temperature are also considered. Data comes from a long-term hydrological observatory (AgrHys, western France) located at Kervidy-Naizin. From each flood, a document has been generated that is made of a set of "hydrological words". Each hydrological word corresponds to a measurement: it is a triplet made of the considered variable, the time at which the measurement is made (relative to the beginning of the flood), and its magnitude (that can be low, medium or high). The documents and the number of pattern to be mined are used as input data to the LDA algorithm. LDA relies on spotting co-occurrences (as an alternative to the more traditional study of correlation) between words that appear within the flood documents. It has two nice properties that are its ability to easily deal with missing data and its additive property that allows a document to be seen as a mixture of several flood patterns. The output of LDA is a set of patterns easily represented in graphics. These patterns correspond to typical reactions to rainfall events. The patterns themselves are carefully studied, as well as their repartition along the year and along the 12 years of the dataset. We would recommend the use of such model to any study based on patterns or signature extraction. It could be well suited to compare different geographical locations and analyzing the resulting different pattern distributions. (1) Aubert, A.H., Gascuel-Odoux, C., Gruau, G., Akkal, N., Faucheux, M., Fauvel, Y., Grimaldi, C., Hamon, Y., Jaffrezic, A., Lecoz Boutnik, M., Molenat, J., Petitjean, P., Ruiz, L., Merot, Ph. (2013), Solute transport dynamics in small, shallow groundwater-dominated agricultural catchments: insights from a high-frequency, multisolute 10 yr-long monitoring study. Hydrol. Earth Syst. Sci., 17(4): 1379-1391. (2) Aubert, A.H., Tavenard, R, Emonet, R., de Lavenne, A., Malinowski, S., Guyet, T., Quiniou, R., Odobez, J.-M., Merot, Ph., Gascuel-Odoux, C., submitted to WRR. Clustering with a probabilistic method newly applied in hydrology: application on flood events from water quality time-series.

A Bayesian Network approach for flash flood risk assessment

NASA Astrophysics Data System (ADS)

Boutkhamouine, Brahim; Roux, Hélène; Pérès, François

2017-04-01

Climate change is contributing to the increase of natural disasters such as extreme weather events. Sometimes, these events lead to sudden flash floods causing devastating effects on life and property. Most recently, many regions of the French Mediterranean perimeter have endured such catastrophic flood events; Var (October 2015), Ardèche (November 2014), Nîmes (October 2014), Hérault, Gard and Languedoc (September 2014), and Pyrenees mountains (Jun 2013). Altogether, it resulted in dozens of victims and property damages amounting to millions of euros. With this heavy loss in mind, development of hydrological forecasting and warning systems is becoming an essential element in regional and national strategies. Flash flood forecasting but also monitoring is a difficult task because small ungauged catchments ( 10 km2) are often the most destructive ones as for the extreme flash flood event of September 2002 in the Cévennes region (France) (Ruin et al., 2008). The problem of measurement/prediction uncertainty is particularly crucial when attempting to develop operational flash-flood forecasting methods. Taking into account the uncertainty related to the model structure itself, to the model parametrization or to the model forcing (spatio-temporal rainfall, initial conditions) is crucial in hydrological modelling. Quantifying these uncertainties is of primary importance for risk assessment and decision making. Although significant improvements have been made in computational power and distributed hydrologic modelling, the issue dealing with integration of uncertainties into flood forecasting remains up-to-date and challenging. In order to develop a framework which could handle these uncertainties and explain their propagation through the model, we propose to explore the potential of graphical models (GMs) and, more precisely, Bayesian Networks (BNs). These networks are Directed Acyclic Graphs (DAGs) in which knowledge of a certain phenomenon is represented by influencing variables. Each node of the graph corresponds to a variable and arcs represent the probabilistic dependencies between these variables. Both the quantification of the strength of these probabilistic dependencies and the computation of inferences are based on Bayes' theorem. In order to use BNs for the assessment of the flooding risks, the modelling work is divided into two parts. First, identifying all the factors controlling the flood generation. The qualitative explanation of this issue is then reached by establishing the cause and effect relationships between these factors. These underlying relationships are represented in what we call Conditional Probabilities Tables (CPTs). The next step is to estimate these CPTs using information coming from network of sensors, databases and expertise. By using this basic cognitive structure, we will be able to estimate the magnitude of flood risk in a small geographical area with a homogeneous hydrological system. The second part of our work will be dedicated to the estimation of this risk on the scale of a basin. To do so, we will create a spatio-temporal model able to take in consideration both spatial and temporal variability of all factors involved in the flood generation. Key words: Flash flood forecasting - Uncertainty modelling - flood risk management -Bayesian Networks.

Simulation of infiltration facilities using the SEEP/W model and quantification of flood runoff reduction effect by the decrease in CN.

PubMed

Yoo, Chulsang; Ku, Jung Mo; Jun, Changhyun; Zhu, Ju Hua

2016-01-01

In this study, four infiltration facilities (permeable pavement, infiltration gutter, infiltration trench, and infiltration well) have been investigated and compared with their flood runoff reduction effect. The SEEP/W model was used to estimate the infiltration amount of each facility, and the flood runoff reduction effect was quantified by the decrease in curve number (CN). As a result of this study, we found that: (1) the infiltration could be successfully simulated by the SEEP/W model, whose result could also be quantified effectively by the decrease in CN; (2) among the four infiltration facilities considered in this study, the infiltration well and infiltration trench were found to be most efficient and economical; (3) finally, the intervention effect of the nearby infiltration facility was found not so significant. In an extreme case where the infiltration wells were located at 1 m interval, the intervention effect was found to be just 1%.

Flood risk assessment of land pollution hotspots

NASA Astrophysics Data System (ADS)

Masi, Matteo; Arrighi, Chiara; Iannelli, Renato

2017-04-01

Among the risks caused by extreme events, the potential spread of pollutants stored in land hotspots due to floods is an aspect that has been rarely examined with a risk-based approach. In this contribution, an attempt to estimate pollution risks related to flood events of land pollution hotspots was carried out. Flood risk has been defined as the combination of river flood hazard, hotspots exposure and vulnerability to contamination of the area, i.e. the expected severity of the environmental impacts. The assessment was performed on a geographical basis, using geo-referenced open data, available from databases of land management institutions, authorities and agencies. The list of land pollution hotspots included landfills and other waste handling facilities (e.g., temporary storage, treatment and recycling sites), municipal wastewater treatment plants, liquid waste treatment facilities and contaminated sites. The assessment was carried out by combining geo-referenced data of pollution hotspots with flood hazard maps. We derived maps of land pollution risk based on geographical and geological properties and source characteristics available from environmental authorities. These included information about soil particle size, soil hydraulic conductivity, terrain slope, type of stored pollutants, the type of facility, capacity, size of the area, land use, etc. The analysis was carried out at catchment scale. The case study of the Arno river basin in Tuscany (central Italy) is presented.

River flood risk in Jakarta under scenarios of future change

NASA Astrophysics Data System (ADS)

Budiyono, Yus; Aerts, Jeroen C. J. H.; Tollenaar, Daniel; Ward, Philip J.

2016-03-01

Given the increasing impacts of flooding in Jakarta, methods for assessing current and future flood risk are required. In this paper, we use the Damagescanner-Jakarta risk model to project changes in future river flood risk under scenarios of climate change, land subsidence, and land use change. Damagescanner-Jakarta is a simple flood risk model that estimates flood risk in terms of annual expected damage, based on input maps of flood hazard, exposure, and vulnerability. We estimate baseline flood risk at USD 186 million p.a. Combining all future scenarios, we simulate a median increase in risk of +180 % by 2030. The single driver with the largest contribution to that increase is land subsidence (+126 %). We simulated the impacts of climate change by combining two scenarios of sea level rise with simulations of changes in 1-day extreme precipitation totals from five global climate models (GCMs) forced by the four Representative Concentration Pathways (RCPs). The results are highly uncertain; the median change in risk due to climate change alone by 2030 is a decrease by -46 %, but we simulate an increase in risk under 12 of the 40 GCM-RCP-sea level rise combinations. Hence, we developed probabilistic risk scenarios to account for this uncertainty. If land use change by 2030 takes places according to the official Jakarta Spatial Plan 2030, risk could be reduced by 12 %. However, if land use change in the future continues at the same rate as the last 30 years, large increases in flood risk will take place. Finally, we discuss the relevance of the results for flood risk management in Jakarta.

Coastal flood implications of 1.5°C, 2°C and 2.5°C global mean temperature stabilization targets for small island nations

NASA Astrophysics Data System (ADS)

Rasmussen, D.; Buchanan, M. K.; Kopp, R. E.; Oppenheimer, M.

2017-12-01

Sea-level rise (SLR) is magnifying the frequency and severity of flooding in coastal regions. The rate and amount of global-mean SLR is a function of the trajectory of the global mean surface temperature (GMST). Therefore, temperature stabilization targets (e.g., 1.5°C or 2°C, as from the Paris Agreement) have important implications for regulating coastal flood risk. Quantifying the differences in the impact from SLR between these and other GMST stabilization targets is necessary for assessing the benefits and harms of mitigation goals. Low-lying small island nations are particularly vulnerable to inundation and coastal flooding from SLR because building protective and resilient infrastructure may not be physically or economically feasible. For small island nations, keeping GMST below a specified threshold may be the only option for maintaining habitability. Here, we assess differences in the return levels of coastal floods for small island nations between 1.5°C, 2.0°C, and 2.5°C GMST stabilization. We employ probabilistic, localized SLR projections and long-term hourly tide gauge records to construct estimates of local flood risk. We then estimate the number of small island nations' inhabitants at risk for permanent inundation under different GMST stabilization targets.

Allowances for evolving coastal flood risk under uncertain local sea-level rise

NASA Astrophysics Data System (ADS)

Buchanan, M. K.; Kopp, R. E.; Oppenheimer, M.; Tebaldi, C.

2015-12-01

Sea-level rise (SLR) causes estimates of flood risk made under the assumption of stationary mean sea level to be biased low. However, adjustments to flood return levels made assuming fixed increases of sea level are also inaccurate when applied to sea level that is rising over time at an uncertain rate. To accommodate both the temporal dynamics of SLR and their uncertainty, we develop an Average Annual Design Life Level (AADLL) metric and associated SLR allowances [1,2]. The AADLL is the flood level corresponding to a time-integrated annual expected probability of occurrence (AEP) under uncertainty over the lifetime of an asset; AADLL allowances are the adjustment from 2000 levels that maintain current risk. Given non-stationary and uncertain SLR, AADLL flood levels and allowances provide estimates of flood protection heights and offsets for different planning horizons and different levels of confidence in SLR projections in coastal areas. Allowances are a function primarily of local SLR and are nearly independent of AEP. Here we employ probabilistic SLR projections [3] to illustrate the calculation of AADLL flood levels and allowances with a representative set of long-duration tide gauges along U.S. coastlines. [1] Rootzen et al., 2014, Water Resources Research 49: 5964-5972. [2] Hunter, 2013, Ocean Engineering 71: 17-27. [3] Kopp et al., 2014, Earth's Future 2: 383-406.

Forensic hydro-meteorological analysis of an extreme flash flood: The 2016-05-29 event in Braunsbach, SW Germany.

PubMed

Bronstert, Axel; Agarwal, Ankit; Boessenkool, Berry; Crisologo, Irene; Fischer, Madlen; Heistermann, Maik; Köhn-Reich, Lisei; López-Tarazón, José Andrés; Moran, Thomas; Ozturk, Ugur; Reinhardt-Imjela, Christian; Wendi, Dadiyorto

2018-07-15

The flash-flood in Braunsbach in the north-eastern part of Baden-Wuerttemberg/Germany was a particularly strong and concise event which took place during the floods in southern Germany at the end of May/early June 2016. This article presents a detailed analysis of the hydro-meteorological forcing and the hydrological consequences of this event. A specific approach, the "forensic hydrological analysis" was followed in order to include and combine retrospectively a variety of data from different disciplines. Such an approach investigates the origins, mechanisms and course of such natural events if possible in a "near real time" mode, in order to follow the most recent traces of the event. The results show that it was a very rare rainfall event with extreme intensities which, in combination with catchment properties, led to extreme runoff plus severe geomorphological hazards, i.e. great debris flows, which together resulted in immense damage in this small rural town Braunsbach. It was definitely a record-breaking event and greatly exceeded existing design guidelines for extreme flood discharge for this region, i.e. by a factor of about 10. Being such a rare or even unique event, it is not reliably feasible to put it into a crisp probabilistic context. However, one can conclude that a return period clearly above 100years can be assigned for all event components: rainfall, peak discharge and sediment transport. Due to the complex and interacting processes, no single flood cause or reason for the very high damage can be identified, since only the interplay and the cascading characteristics of those led to such an event. The roles of different human activities on the origin and/or intensification of such an extreme event are finally discussed. Copyright © 2018. Published by Elsevier B.V.

Annual flood sensitivities to El Niño-Southern Oscillation at the global scale

USGS Publications Warehouse

Ward, Philip J.; Eisner, S.; Flörke, M.; Dettinger, Michael D.; Kummu, M.

2013-01-01

Floods are amongst the most dangerous natural hazards in terms of economic damage. Whilst a growing number of studies have examined how river floods are influenced by climate change, the role of natural modes of interannual climate variability remains poorly understood. We present the first global assessment of the influence of El Niño–Southern Oscillation (ENSO) on annual river floods, defined here as the peak daily discharge in a given year. The analysis was carried out by simulating daily gridded discharges using the WaterGAP model (Water – a Global Assessment and Prognosis), and examining statistical relationships between these discharges and ENSO indices. We found that, over the period 1958–2000, ENSO exerted a significant influence on annual floods in river basins covering over a third of the world's land surface, and that its influence on annual floods has been much greater than its influence on average flows. We show that there are more areas in which annual floods intensify with La Niña and decline with El Niño than vice versa. However, we also found that in many regions the strength of the relationships between ENSO and annual floods have been non-stationary, with either strengthening or weakening trends during the study period. We discuss the implications of these findings for science and management. Given the strong relationships between ENSO and annual floods, we suggest that more research is needed to assess relationships between ENSO and flood impacts (e.g. loss of lives or economic damage). Moreover, we suggest that in those regions where useful relationships exist, this information could be combined with ongoing advances in ENSO prediction research, in order to provide year-to-year probabilistic flood risk forecasts.

Global coastal flood hazard mapping

NASA Astrophysics Data System (ADS)

Eilander, Dirk; Winsemius, Hessel; Ward, Philip; Diaz Loaiza, Andres; Haag, Arjen; Verlaan, Martin; Luo, Tianyi

2017-04-01

Over 10% of the world's population lives in low-lying coastal areas (up to 10m elevation). Many of these areas are prone to flooding from tropical storm surges or extra-tropical high sea levels in combination with high tides. A 1 in 100 year extreme sea level is estimated to expose 270 million people and 13 trillion USD worth of assets to flooding. Coastal flood risk is expected to increase due to drivers such as ground subsidence, intensification of tropical and extra-tropical storms, sea level rise and socio-economic development. For better understanding of the hazard and drivers to global coastal flood risk, a globally consistent analysis of coastal flooding is required. In this contribution we present a comprehensive global coastal flood hazard mapping study. Coastal flooding is estimated using a modular inundation routine, based on a vegetation corrected SRTM elevation model and forced by extreme sea levels. Per tile, either a simple GIS inundation routine or a hydrodynamic model can be selected. The GIS inundation method projects extreme sea levels to land, taking into account physical obstructions and dampening of the surge level land inwards. For coastlines with steep slopes or where local dynamics play a minor role in flood behavior, this fast GIS method can be applied. Extreme sea levels are derived from the Global Tide and Surge Reanalysis (GTSR) dataset. Future sea level projections are based on probabilistic sea level rise for RCP 4.5 and RCP 8.5 scenarios. The approach is validated against observed flood extents from ground and satellite observations. The results will be made available through the online Aqueduct Global Flood Risk Analyzer of the World Resources Institute.

What is the Value Added to Adaptation Planning by Probabilistic Projections of Climate Change?

NASA Astrophysics Data System (ADS)

Wilby, R. L.

2008-12-01

Probabilistic projections of climate change offer new sources of risk information to support regional impacts assessment and adaptation options appraisal. However, questions continue to surround how best to apply these scenarios in a practical context, and whether the added complexity and computational burden leads to more robust decision-making. This paper provides an overview of recent efforts in the UK to 'bench-test' frameworks for employing probabilistic projections ahead of the release of the next generation, UKCIP08 projections (in November 2008). This is involving close collaboration between government agencies, research and stakeholder communities. Three examples will be cited to illustrate how probabilistic projections are already informing decisions about future flood risk management in London, water resource planning in trial river basins, and assessments of risks from rising water temperatures to Atlantic salmon stocks in southern England. When compared with conventional deterministic scenarios, ensemble projections allow exploration of a wider range of management options and highlight timescales for implementing adaptation measures. Users of probabilistic scenarios must keep in mind that other uncertainties (e.g., due to impacts model structure and parameterisation) should be handled in an equally rigorous way to those arising from climate models and emission scenarios. Finally, it is noted that a commitment to long-term monitoring is also critical for tracking environmental change, testing model projections, and for evaluating the success (or not) of any scenario-led interventions.

Development and application of an atmospheric-hydrologic-hydraulic flood forecasting model driven by TIGGE ensemble forecasts

NASA Astrophysics Data System (ADS)

Bao, Hongjun; Zhao, Linna

2012-02-01

A coupled atmospheric-hydrologic-hydraulic ensemble flood forecasting model, driven by The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data, has been developed for flood forecasting over the Huaihe River. The incorporation of numerical weather prediction (NWP) information into flood forecasting systems may increase forecast lead time from a few hours to a few days. A single NWP model forecast from a single forecast center, however, is insufficient as it involves considerable non-predictable uncertainties and leads to a high number of false alarms. The availability of global ensemble NWP systems through TIGGE offers a new opportunity for flood forecast. The Xinanjiang model used for hydrological rainfall-runoff modeling and the one-dimensional unsteady flow model applied to channel flood routing are coupled with ensemble weather predictions based on the TIGGE data from the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Met Office (UKMO), and the US National Centers for Environmental Prediction (NCEP). The developed ensemble flood forecasting model is applied to flood forecasting of the 2007 flood season as a test case. The test case is chosen over the upper reaches of the Huaihe River above Lutaizi station with flood diversion and retarding areas. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The Muskingum method is used for flood routing in the flood diversion area. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE ensemble forecasts. The results demonstrate satisfactory flood forecasting with clear signals of probability of floods up to a few days in advance, and show that TIGGE ensemble forecast data are a promising tool for forecasting of flood inundation, comparable with that driven by raingauge observations.

Empirical estimation of the conditional probability of natech events within the United States.

PubMed

Santella, Nicholas; Steinberg, Laura J; Aguirra, Gloria Andrea

2011-06-01

Natural disasters are the cause of a sizeable number of hazmat releases, referred to as "natechs." An enhanced understanding of natech probability, allowing for predictions of natech occurrence, is an important step in determining how industry and government should mitigate natech risk. This study quantifies the conditional probabilities of natechs at TRI/RMP and SICS 1311 facilities given the occurrence of hurricanes, earthquakes, tornadoes, and floods. During hurricanes, a higher probability of releases was observed due to storm surge (7.3 releases per 100 TRI/RMP facilities exposed vs. 6.2 for SIC 1311) compared to category 1-2 hurricane winds (5.6 TRI, 2.6 SIC 1311). Logistic regression confirms the statistical significance of the greater propensity for releases at RMP/TRI facilities, and during some hurricanes, when controlling for hazard zone. The probability of natechs at TRI/RMP facilities during earthquakes increased from 0.1 releases per 100 facilities at MMI V to 21.4 at MMI IX. The probability of a natech at TRI/RMP facilities within 25 miles of a tornado was small (∼0.025 per 100 facilities), reflecting the limited area directly affected by tornadoes. Areas inundated during flood events had a probability of 1.1 releases per 100 facilities but demonstrated widely varying natech occurrence during individual events, indicating that factors not quantified in this study such as flood depth and speed are important for predicting flood natechs. These results can inform natech risk analysis, aid government agencies responsible for planning response and remediation after natural disasters, and should be useful in raising awareness of natech risk within industry. © 2011 Society for Risk Analysis.

Power Scaling of the Size Distribution of Economic Loss and Fatalities due to Hurricanes, Earthquakes, Tornadoes, and Floods in the USA

NASA Astrophysics Data System (ADS)

Tebbens, S. F.; Barton, C. C.; Scott, B. E.

2016-12-01

Traditionally, the size of natural disaster events such as hurricanes, earthquakes, tornadoes, and floods is measured in terms of wind speed (m/sec), energy released (ergs), or discharge (m3/sec) rather than by economic loss or fatalities. Economic loss and fatalities from natural disasters result from the intersection of the human infrastructure and population with the size of the natural event. This study investigates the size versus cumulative number distribution of individual natural disaster events for several disaster types in the United States. Economic losses are adjusted for inflation to 2014 USD. The cumulative number divided by the time over which the data ranges for each disaster type is the basis for making probabilistic forecasts in terms of the number of events greater than a given size per year and, its inverse, return time. Such forecasts are of interest to insurers/re-insurers, meteorologists, seismologists, government planners, and response agencies. Plots of size versus cumulative number distributions per year for economic loss and fatalities are well fit by power scaling functions of the form p(x) = Cx-β; where, p(x) is the cumulative number of events with size equal to and greater than size x, C is a constant, the activity level, x is the event size, and β is the scaling exponent. Economic loss and fatalities due to hurricanes, earthquakes, tornadoes, and floods are well fit by power functions over one to five orders of magnitude in size. Economic losses for hurricanes and tornadoes have greater scaling exponents, β = 1.1 and 0.9 respectively, whereas earthquakes and floods have smaller scaling exponents, β = 0.4 and 0.6 respectively. Fatalities for tornadoes and floods have greater scaling exponents, β = 1.5 and 1.7 respectively, whereas hurricanes and earthquakes have smaller scaling exponents, β = 0.4 and 0.7 respectively. The scaling exponents can be used to make probabilistic forecasts for time windows ranging from 1 to 1000 years. Forecasts show that on an annual basis, in the United States, the majority of events with 10 fatalities and greater are related to floods and tornadoes; while events with 100 fatalities and greater are less frequent and are dominated by hurricanes and earthquakes. Disaster mitigation strategies need to account for these differences.

Performance assessment of deterministic and probabilistic weather predictions for the short-term optimization of a tropical hydropower reservoir

NASA Astrophysics Data System (ADS)

Mainardi Fan, Fernando; Schwanenberg, Dirk; Alvarado, Rodolfo; Assis dos Reis, Alberto; Naumann, Steffi; Collischonn, Walter

2016-04-01

Hydropower is the most important electricity source in Brazil. During recent years, it accounted for 60% to 70% of the total electric power supply. Marginal costs of hydropower are lower than for thermal power plants, therefore, there is a strong economic motivation to maximize its share. On the other hand, hydropower depends on the availability of water, which has a natural variability. Its extremes lead to the risks of power production deficits during droughts and safety issues in the reservoir and downstream river reaches during flood events. One building block of the proper management of hydropower assets is the short-term forecast of reservoir inflows as input for an online, event-based optimization of its release strategy. While deterministic forecasts and optimization schemes are the established techniques for the short-term reservoir management, the use of probabilistic ensemble forecasts and stochastic optimization techniques receives growing attention and a number of researches have shown its benefit. The present work shows one of the first hindcasting and closed-loop control experiments for a multi-purpose hydropower reservoir in a tropical region in Brazil. The case study is the hydropower project (HPP) Três Marias, located in southeast Brazil. The HPP reservoir is operated with two main objectives: (i) hydroelectricity generation and (ii) flood control at Pirapora City located 120 km downstream of the dam. In the experiments, precipitation forecasts based on observed data, deterministic and probabilistic forecasts with 50 ensemble members of the ECMWF are used as forcing of the MGB-IPH hydrological model to generate streamflow forecasts over a period of 2 years. The online optimization depends on a deterministic and multi-stage stochastic version of a model predictive control scheme. Results for the perfect forecasts show the potential benefit of the online optimization and indicate a desired forecast lead time of 30 days. In comparison, the use of actual forecasts with shorter lead times of up to 15 days shows the practical benefit of actual operational data. It appears that the use of stochastic optimization combined with ensemble forecasts leads to a significant higher level of flood protection without compromising the HPP's energy production.

Combined fluvial and pluvial urban flood hazard analysis: method development and application to Can Tho City, Mekong Delta, Vietnam

NASA Astrophysics Data System (ADS)

Apel, H.; Trepat, O. M.; Hung, N. N.; Chinh, D. T.; Merz, B.; Dung, N. V.

2015-08-01

Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas, and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either fluvial or pluvial flood hazard, studies of combined fluvial and pluvial flood hazard are hardly available. Thus this study aims at the analysis of fluvial and pluvial flood hazard individually, but also at developing a method for the analysis of combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as example. In this tropical environment the annual monsoon triggered floods of the Mekong River can coincide with heavy local convective precipitation events causing both fluvial and pluvial flooding at the same time. Fluvial flood hazard was estimated with a copula based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. Pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data, and a stochastic rain storm generator. Inundation was simulated by a 2-dimensional hydrodynamic model implemented on a Graphical Processor Unit (GPU) for time-efficient flood propagation modelling. All hazards - fluvial, pluvial and combined - were accompanied by an uncertainty estimation considering the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and ways for their usage in flood risk management are outlined.

Bayesian flood forecasting methods: A review

NASA Astrophysics Data System (ADS)

Han, Shasha; Coulibaly, Paulin

2017-08-01

Over the past few decades, floods have been seen as one of the most common and largely distributed natural disasters in the world. If floods could be accurately forecasted in advance, then their negative impacts could be greatly minimized. It is widely recognized that quantification and reduction of uncertainty associated with the hydrologic forecast is of great importance for flood estimation and rational decision making. Bayesian forecasting system (BFS) offers an ideal theoretic framework for uncertainty quantification that can be developed for probabilistic flood forecasting via any deterministic hydrologic model. It provides suitable theoretical structure, empirically validated models and reasonable analytic-numerical computation method, and can be developed into various Bayesian forecasting approaches. This paper presents a comprehensive review on Bayesian forecasting approaches applied in flood forecasting from 1999 till now. The review starts with an overview of fundamentals of BFS and recent advances in BFS, followed with BFS application in river stage forecasting and real-time flood forecasting, then move to a critical analysis by evaluating advantages and limitations of Bayesian forecasting methods and other predictive uncertainty assessment approaches in flood forecasting, and finally discusses the future research direction in Bayesian flood forecasting. Results show that the Bayesian flood forecasting approach is an effective and advanced way for flood estimation, it considers all sources of uncertainties and produces a predictive distribution of the river stage, river discharge or runoff, thus gives more accurate and reliable flood forecasts. Some emerging Bayesian forecasting methods (e.g. ensemble Bayesian forecasting system, Bayesian multi-model combination) were shown to overcome limitations of single model or fixed model weight and effectively reduce predictive uncertainty. In recent years, various Bayesian flood forecasting approaches have been developed and widely applied, but there is still room for improvements. Future research in the context of Bayesian flood forecasting should be on assimilation of various sources of newly available information and improvement of predictive performance assessment methods.

HyRAM V1.0 User Guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groth, Katrina M.; Zumwalt, Hannah Ruth; Clark, Andrew Jordan

2016-03-01

Hydrogen Risk Assessment Models (HyRAM) is a prototype software toolkit that integrates data and methods relevant to assessing the safety of hydrogen fueling and storage infrastructure. The HyRAM toolkit integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, and characterizing the impact of hydrogen hazards, including thermal effects from jet fires and thermal pressure effects from deflagration. HyRAM version 1.0 incorporates generic probabilities for equipment failures for nine types of components, and probabilistic models for the impact of heat flux on humans and structures, with computationally and experimentally validated models of various aspects of gaseous hydrogen releasemore » and flame physics. This document provides an example of how to use HyRAM to conduct analysis of a fueling facility. This document will guide users through the software and how to enter and edit certain inputs that are specific to the user-defined facility. Description of the methodology and models contained in HyRAM is provided in [1]. This User’s Guide is intended to capture the main features of HyRAM version 1.0 (any HyRAM version numbered as 1.0.X.XXX). This user guide was created with HyRAM 1.0.1.798. Due to ongoing software development activities, newer versions of HyRAM may have differences from this guide.« less

Quantitative risk analysis of oil storage facilities in seismic areas.

PubMed

Fabbrocino, Giovanni; Iervolino, Iunio; Orlando, Francesca; Salzano, Ernesto

2005-08-31

Quantitative risk analysis (QRA) of industrial facilities has to take into account multiple hazards threatening critical equipment. Nevertheless, engineering procedures able to evaluate quantitatively the effect of seismic action are not well established. Indeed, relevant industrial accidents may be triggered by loss of containment following ground shaking or other relevant natural hazards, either directly or through cascade effects ('domino effects'). The issue of integrating structural seismic risk into quantitative probabilistic seismic risk analysis (QpsRA) is addressed in this paper by a representative study case regarding an oil storage plant with a number of atmospheric steel tanks containing flammable substances. Empirical seismic fragility curves and probit functions, properly defined both for building-like and non building-like industrial components, have been crossed with outcomes of probabilistic seismic hazard analysis (PSHA) for a test site located in south Italy. Once the seismic failure probabilities have been quantified, consequence analysis has been performed for those events which may be triggered by the loss of containment following seismic action. Results are combined by means of a specific developed code in terms of local risk contour plots, i.e. the contour line for the probability of fatal injures at any point (x, y) in the analysed area. Finally, a comparison with QRA obtained by considering only process-related top events is reported for reference.

Flood disaster preparedness: a retrospect from Grand Forks, North Dakota.

PubMed

Siders, C; Jacobson, R

1998-01-01

Natural disasters often come without warning. The clinical, financial, and business risks can be enormous. Grand Forks' (ND) healthcare systems experienced a flooding disaster of unprecedented proportions in April of 1997. Planned and practiced disaster and evacuation procedures can significantly reduce a healthcare facilities' risk to life, health, and safety. This article retrospectively analyzes disaster preparation and the complete evacuation of the facilities' patients.

Assessing the need for an update of a probabilistic seismic hazard analysis using a SSHAC Level 1 study and the Seismic Hazard Periodic Reevaluation Methodology

DOE PAGES

Payne, Suzette J.; Coppersmith, Kevin J.; Coppersmith, Ryan; ...

2017-08-23

A key decision for nuclear facilities is evaluating the need for an update of an existing seismic hazard analysis in light of new data and information that has become available since the time that the analysis was completed. We introduce the newly developed risk-informed Seismic Hazard Periodic Review Methodology (referred to as the SHPRM) and present how a Senior Seismic Hazard Analysis Committee (SSHAC) Level 1 probabilistic seismic hazard analysis (PSHA) was performed in an implementation of this new methodology. The SHPRM offers a defensible and documented approach that considers both the changes in seismic hazard and engineering-based risk informationmore » of an existing nuclear facility to assess the need for an update of an existing PSHA. The SHPRM has seven evaluation criteria that are employed at specific analysis, decision, and comparison points which are applied to seismic design categories established for nuclear facilities in United States. The SHPRM is implemented using a SSHAC Level 1 study performed for the Idaho National Laboratory, USA. The implementation focuses on the first six of the seven evaluation criteria of the SHPRM which are all provided from the SSHAC Level 1 PSHA. Finally, to illustrate outcomes of the SHPRM that do not lead to the need for an update and those that do, the example implementations of the SHPRM are performed for nuclear facilities that have target performance goals expressed as the mean annual frequency of unacceptable performance at 1x10 -4, 4x10 -5 and 1x10 -5.« less

Assessing the need for an update of a probabilistic seismic hazard analysis using a SSHAC Level 1 study and the Seismic Hazard Periodic Reevaluation Methodology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Payne, Suzette J.; Coppersmith, Kevin J.; Coppersmith, Ryan

A key decision for nuclear facilities is evaluating the need for an update of an existing seismic hazard analysis in light of new data and information that has become available since the time that the analysis was completed. We introduce the newly developed risk-informed Seismic Hazard Periodic Review Methodology (referred to as the SHPRM) and present how a Senior Seismic Hazard Analysis Committee (SSHAC) Level 1 probabilistic seismic hazard analysis (PSHA) was performed in an implementation of this new methodology. The SHPRM offers a defensible and documented approach that considers both the changes in seismic hazard and engineering-based risk informationmore » of an existing nuclear facility to assess the need for an update of an existing PSHA. The SHPRM has seven evaluation criteria that are employed at specific analysis, decision, and comparison points which are applied to seismic design categories established for nuclear facilities in United States. The SHPRM is implemented using a SSHAC Level 1 study performed for the Idaho National Laboratory, USA. The implementation focuses on the first six of the seven evaluation criteria of the SHPRM which are all provided from the SSHAC Level 1 PSHA. Finally, to illustrate outcomes of the SHPRM that do not lead to the need for an update and those that do, the example implementations of the SHPRM are performed for nuclear facilities that have target performance goals expressed as the mean annual frequency of unacceptable performance at 1x10 -4, 4x10 -5 and 1x10 -5.« less

Site Specific Probable Maximum Precipitation Estimates and Professional Judgement

NASA Astrophysics Data System (ADS)

Hayes, B. D.; Kao, S. C.; Kanney, J. F.; Quinlan, K. R.; DeNeale, S. T.

2015-12-01

State and federal regulatory authorities currently rely upon the US National Weather Service Hydrometeorological Reports (HMRs) to determine probable maximum precipitation (PMP) estimates (i.e., rainfall depths and durations) for estimating flooding hazards for relatively broad regions in the US. PMP estimates for the contributing watersheds upstream of vulnerable facilities are used to estimate riverine flooding hazards while site-specific estimates for small water sheds are appropriate for individual facilities such as nuclear power plants. The HMRs are often criticized due to their limitations on basin size, questionable applicability in regions affected by orographic effects, their lack of consist methods, and generally by their age. HMR-51 for generalized PMP estimates for the United States east of the 105th meridian, was published in 1978 and is sometimes perceived as overly conservative. The US Nuclear Regulatory Commission (NRC), is currently reviewing several flood hazard evaluation reports that rely on site specific PMP estimates that have been commercially developed. As such, NRC has recently investigated key areas of expert judgement via a generic audit and one in-depth site specific review as they relate to identifying and quantifying actual and potential storm moisture sources, determining storm transposition limits, and adjusting available moisture during storm transposition. Though much of the approach reviewed was considered a logical extension of HMRs, two key points of expert judgement stood out for further in-depth review. The first relates primarily to small storms and the use of a heuristic for storm representative dew point adjustment developed for the Electric Power Research Institute by North American Weather Consultants in 1993 in order to harmonize historic storms for which only 12 hour dew point data was available with more recent storms in a single database. The second issue relates to the use of climatological averages for spatially interpolating 100-year dew point values rather than a more gauge-based approach. Site specific reviews demonstrated that both issues had potential for lowering the PMP estimate significantly by affecting the in-place and transposed moisture maximization value and, in turn, the final controlling storm for a given basin size and PMP estimate.

Flood hazard assessment for french NPPs

NASA Astrophysics Data System (ADS)

Rebour, Vincent; Duluc, Claire-Marie; Guimier, Laurent

2015-04-01

This paper presents the approach for flood hazard assessment for NPP which is on-going in France in the framework of post-Fukushima activities. These activities were initially defined considering both European "stress tests" of NPPs pursuant to the request of the European Council, and the French safety audit of civilian nuclear facilities in the light of the Fukushima Daiichi accident. The main actors in that process are the utility (EDF is, up to date, the unique NPP's operator in France), the regulatory authority (ASN) and its technical support organization (IRSN). This paper was prepared by IRSN, considering official positions of the other main actors in the current review process, it was not officially endorsed by them. In France, flood hazard to be considered for design basis definition (for new NPPs and for existing NPPs in periodic safety reviews conducted every 10 years) was revised before Fukushima-Daichi accident, due to le Blayais NPP December 1999 experience (partial site flooding and loss of some safety classified systems). The paper presents in the first part an overview of the revised guidance for design basis flood. In order to address design extension conditions (conditions that could result from natural events exceeding the design basis events), a set of flooding scenarios have been defined by adding margins on the scenarios that are considered for the design. Due to the diversity of phenomena to be considered for flooding hazard, the margin assessment is specific to each flooding scenario in terms of parameter to be penalized and of degree of variation of this parameter. The general approach to address design extension conditions is presented in the second part of the paper. The next parts present the approach for five flooding scenarios including design basis scenario and additional margin to define design extension scenarios.

Increasing stress on disaster risk finance due to large floods

NASA Astrophysics Data System (ADS)

Jongman, Brenden; Hochrainer-Stigler, Stefan; Feyen, Luc; Aerts, Jeroen; Mechler, Reinhard; Botzen, Wouter; Bouwer, Laurens; Pflug, Georg; Rojas, Rodrigo; Ward, Philip

2014-05-01

Recent major flood disasters have shown that single extreme events can affect multiple countries simultaneously, which puts high pressure on trans-national risk reduction and risk transfer mechanisms. To date, little is known about such flood hazard interdependencies across regions, and the corresponding joint risks at regional to continental scales. Reliable information on correlated loss probabilities is crucial for developing robust insurance schemes and public adaptation funds, and for enhancing our understanding of climate change impacts. Here we show that extreme discharges are strongly correlated across European river basins and that these correlations can, or should, be used in national to continental scale risk assessment. We present probabilistic trends in continental flood risk, and demonstrate that currently observed extreme flood losses could more than double in frequency by 2050 under future climate change and socioeconomic development. The results demonstrate that accounting for tail dependencies leads to higher estimates of extreme losses than estimates based on the traditional assumption of independence between basins. We suggest that risk management for these increasing losses is largely feasible, and we demonstrate that risk can be shared by expanding risk transfer financing, reduced by investing in flood protection, or absorbed by enhanced solidarity between countries. We conclude that these measures have vastly different efficiency, equity and acceptability implications, which need to be taken into account in broader consultation, for which our analysis provides a basis.

Strong influence of El Niño Southern Oscillation on flood risk around the world

USGS Publications Warehouse

Ward, Philip J.; Jongman, B; Kummu, M.; Dettinger, Mike; Sperna Weiland, F.C; Winsemius, H.C

2014-01-01

El Niño Southern Oscillation (ENSO) is the most dominant interannual signal of climate variability and has a strong influence on climate over large parts of the world. In turn, it strongly influences many natural hazards (such as hurricanes and droughts) and their resulting socioeconomic impacts, including economic damage and loss of life. However, although ENSO is known to influence hydrology in many regions of the world, little is known about its influence on the socioeconomic impacts of floods (i.e., flood risk). To address this, we developed a modeling framework to assess ENSO’s influence on flood risk at the global scale, expressed in terms of affected population and gross domestic product and economic damages. We show that ENSO exerts strong and widespread influences on both flood hazard and risk. Reliable anomalies of flood risk exist during El Niño or La Niña years, or both, in basins spanning almost half (44%) of Earth’s land surface. Our results show that climate variability, especially from ENSO, should be incorporated into disaster-risk analyses and policies. Because ENSO has some predictive skill with lead times of several seasons, the findings suggest the possibility to develop probabilistic flood-risk projections, which could be used for improved disaster planning. The findings are also relevant in the context of climate change. If the frequency and/or magnitude of ENSO events were to change in the future, this finding could imply changes in flood-risk variations across almost half of the world’s terrestrial regions.

Strong influence of El Niño Southern Oscillation on flood risk around the world

PubMed Central

Ward, Philip J.; Jongman, Brenden; Kummu, Matti; Dettinger, Michael D.; Sperna Weiland, Frederiek C.; Winsemius, Hessel C.

2014-01-01

El Niño Southern Oscillation (ENSO) is the most dominant interannual signal of climate variability and has a strong influence on climate over large parts of the world. In turn, it strongly influences many natural hazards (such as hurricanes and droughts) and their resulting socioeconomic impacts, including economic damage and loss of life. However, although ENSO is known to influence hydrology in many regions of the world, little is known about its influence on the socioeconomic impacts of floods (i.e., flood risk). To address this, we developed a modeling framework to assess ENSO’s influence on flood risk at the global scale, expressed in terms of affected population and gross domestic product and economic damages. We show that ENSO exerts strong and widespread influences on both flood hazard and risk. Reliable anomalies of flood risk exist during El Niño or La Niña years, or both, in basins spanning almost half (44%) of Earth’s land surface. Our results show that climate variability, especially from ENSO, should be incorporated into disaster-risk analyses and policies. Because ENSO has some predictive skill with lead times of several seasons, the findings suggest the possibility to develop probabilistic flood-risk projections, which could be used for improved disaster planning. The findings are also relevant in the context of climate change. If the frequency and/or magnitude of ENSO events were to change in the future, this finding could imply changes in flood-risk variations across almost half of the world’s terrestrial regions. PMID:25331867

From science into practice: modelling hot spots for corporate flood risk and emergency management with high-resolution digital terrain data

NASA Astrophysics Data System (ADS)

Pfurtscheller, Clemens; Vetter, Michael; Werthmann, Markus

2010-05-01

In times of increasing scarcity of private or public resources and uncertain changes in natural environment caused by climate variations, prevention and risk management against floods and coherent processes in mountainous regions, like debris flows or log jams, should be faced as a main challenge for globalised enterprises whose production facilities are located in flood-prone areas. From an entrepreneurial perspective, vulnerability of production facilities which causes restrictions or a total termination of production processes has to be optimised by means of cost-benefit-principles. Modern production enterprises are subject to globalisation and accompanying aspects, like short order and delivery periods, interlinking production processes and just-in-time manufacturing, so a breakdown of production provokes substantial financial impacts, unemployment and a decline of gross regional product. The aim of the presented project is to identify weak and critical points of the corporate emergency planning ("hot spots") and to assess possible losses triggered by mountainous flood processes using high-resolution digital terrain models (DTM) from airborne LiDAR (ALS). We derive flood-hot spots and model critical locations where the risk of natural hazards is very high. To model those hot spots a flood simulation based on an ALS-DTM has to be calculated. Based on that flood simulation, the flood heights of the overflowed locations which are lower than a threshold are mapped as flood-hot-spots. Then the corporate critical infrastructure, e.g. production facilities or lifelines, which are affected by the flooding, can be figured out. After the identification of hot spots and possible damage potential, the implementation of the results into corporate risk and emergency management guarantees the transdisciplinary approach involving stakeholders, risk and safety management officers and corporate fire brigade. Thus, the interdisciplinary analysis, including remote sensing techniques, like LiDAR, and economic assessment of natural hazards, combining with corporate acting secures production, guarantees income and helps to stabilise region's wealth after major flood events. Beyond that, the assessment of hot spots could be raised as locational issue for greenfield strategy or company foundation.

42 CFR 412.25 - Excluded hospital units: Common requirements.

Code of Federal Regulations, 2013 CFR

2013-10-01

... physical facility or because of catastrophic events such as fires, floods, earthquakes, or tornadoes. (c... (ii) Because of catastrophic events such as fires, floods, earthquakes, or tornadoes. (5) For cost...

42 CFR 412.25 - Excluded hospital units: Common requirements.

Code of Federal Regulations, 2010 CFR

2010-10-01

... physical facility; or (ii) Because of catastrophic events such as fires, floods, earthquakes, or tornadoes... as fires, floods, earthquakes, or tornadoes. (5) For cost reporting periods beginning on or after...

42 CFR 412.25 - Excluded hospital units: Common requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... physical facility or because of catastrophic events such as fires, floods, earthquakes, or tornadoes. (c... (ii) Because of catastrophic events such as fires, floods, earthquakes, or tornadoes. (5) For cost...

42 CFR 412.25 - Excluded hospital units: Common requirements.

Code of Federal Regulations, 2014 CFR

2014-10-01

... physical facility or because of catastrophic events such as fires, floods, earthquakes, or tornadoes. (c... (ii) Because of catastrophic events such as fires, floods, earthquakes, or tornadoes. (5) For cost...

42 CFR 412.25 - Excluded hospital units: Common requirements.

Code of Federal Regulations, 2012 CFR

2012-10-01

... physical facility or because of catastrophic events such as fires, floods, earthquakes, or tornadoes. (c... (ii) Because of catastrophic events such as fires, floods, earthquakes, or tornadoes. (5) For cost...

New developments at the Flood Forecasting Centre: operational flood risk assessment and guidance

NASA Astrophysics Data System (ADS)

Pilling, Charlie

2017-04-01

The Flood Forecasting Centre (FFC) is a partnership between the UK Met Office, the Environment Agency and Natural Resources Wales. The FFC was established in 2009 to provide an overview of flood risk across England and Wales and to provide flood guidance services primarily for the emergency response community. The FFC provides forecasts for all natural sources of flooding, these being fluvial, surface water, coastal and groundwater. This involves an assessment of possible hydrometeorological events and their impacts over the next five days. During times of heightened flood risk, the close communication between the FFC, the Environment Agency and Natural Resources Wales allows mobilization and deployment of staff and flood defences. Following a number of severe flood events during winters 2013-14 and 2015-16, coupled with a drive from the changing landscape in national incident response, there is a desire to identify flood events at even longer lead time. This earlier assessment and mobilization is becoming increasingly important and high profile within Government. For example, following the exceptional flooding across the north of England in December 2015 the Environment Agency have invested in 40 km of temporary barriers that will be moved around the country to help mitigate against the impacts of large flood events. Efficient and effective use of these barriers depends on identifying the broad regions at risk well in advance of the flood, as well as scaling the magnitude and duration of large events. Partly in response to this, the FFC now produce a flood risk assessment for a month ahead. In addition, since January 2017, the 'new generation' daily flood guidance statement includes an assessment of flood risk for the 6 to 10 day period. Examples of both these new products will be introduced, as will some of the new developments in science and technical capability that underpin these assessments. Examples include improvements to fluvial forecasting from 'fluvial decider', and downscaled hydrometeorological data that generates probabilistic river flows at 6 days lead time using the Delft-FEWS / Grid-to-Grid modelling system. Advances in coastal forecasting from surge and wave ensembles and also the longer range 'coastal decider' approach will also be presented.

Estimating earthquake-induced failure probability and downtime of critical facilities.

PubMed

Porter, Keith; Ramer, Kyle

2012-01-01

Fault trees have long been used to estimate failure risk in earthquakes, especially for nuclear power plants (NPPs). One interesting application is that one can assess and manage the probability that two facilities - a primary and backup - would be simultaneously rendered inoperative in a single earthquake. Another is that one can calculate the probabilistic time required to restore a facility to functionality, and the probability that, during any given planning period, the facility would be rendered inoperative for any specified duration. A large new peer-reviewed library of component damageability and repair-time data for the first time enables fault trees to be used to calculate the seismic risk of operational failure and downtime for a wide variety of buildings other than NPPs. With the new library, seismic risk of both the failure probability and probabilistic downtime can be assessed and managed, considering the facility's unique combination of structural and non-structural components, their seismic installation conditions, and the other systems on which the facility relies. An example is offered of real computer data centres operated by a California utility. The fault trees were created and tested in collaboration with utility operators, and the failure probability and downtime results validated in several ways.

Flood information for flood-plain planning

USGS Publications Warehouse

Bue, Conrad D.

1967-01-01

Floods are natural and normal phenomena. They are catastrophic simply because man occupies the flood plain, the highwater channel of a river. Man occupies flood plains because it is convenient and profitable to do so, but he must purchase his occupancy at a price-either sustain flood damage, or provide flood-control facilities. Although large sums of money have been, and are being, spent for flood control, flood damage continues to mount. However, neither complete flood control nor abandonment of the flood plain is practicable. Flood plains are a valuable resource and will continue to be occupied, but the nature and degree of occupancy should be compatible with the risk involved and with the degree of protection that is practicable to provide. It is primarily to meet the needs for defining the risk that the flood-inundation maps of the U.S. Geological Survey are prepared.

Flood type specific construction of synthetic design hydrographs

NASA Astrophysics Data System (ADS)

Brunner, Manuela I.; Viviroli, Daniel; Sikorska, Anna E.; Vannier, Olivier; Favre, Anne-Catherine; Seibert, Jan

2017-02-01

Accurate estimates of flood peaks, corresponding volumes, and hydrographs are required to design safe and cost-effective hydraulic structures. In this paper, we propose a statistical approach for the estimation of the design variables peak and volume by constructing synthetic design hydrographs for different flood types such as flash-floods, short-rain floods, long-rain floods, and rain-on-snow floods. Our approach relies on the fitting of probability density functions to observed flood hydrographs of a certain flood type and accounts for the dependence between peak discharge and flood volume. It makes use of the statistical information contained in the data and retains the process information of the flood type. The method was tested based on data from 39 mesoscale catchments in Switzerland and provides catchment specific and flood type specific synthetic design hydrographs for all of these catchments. We demonstrate that flood type specific synthetic design hydrographs are meaningful in flood-risk management when combined with knowledge on the seasonality and the frequency of different flood types.

Application of a medium-range global hydrologic probabilistic forecast scheme to the Ohio River Basin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.

2011-08-15

A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatialmore » scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.« less

Physical, Structural and Operational Vulnerability of Critical Facilities in Valle de Chalco Solidaridad, Estado de Mexico, Mexico. Case of study: Avándaro, San Isidro and El Triunfo

NASA Astrophysics Data System (ADS)

Garcia Payne, D. G.; Novelo-Casanova, D. A.; Ponce-Pacheco, A. B.; Espinosa-Campos, O.; Huerta-Parra, M.; Reyes-Pimentel, T.; Rodriguez, F.; Benitez-Olivares, I.

2010-12-01

Valle de Chalco Solidaridad is located in Mexico City Metropolitan Area in Estado de Mexico, Mexico. In this town there is a sewage canal called “La Compañía”. A wall of this canal collapsed on February 5, 2010 due to heavy rains creating the flooding of four surrounding communities. It is important to point out that this area is frequently exposed to floods. In this work, we consider a critical facility as an essential structure for performance, health care and welfare within a community or/and as a place that can be used as shelter in case of emergency or disaster. Global vulnerability (the sum of the three measured vulnerabilities) of the 25 critical facilities identified in the locations of Avándaro, San Isidro and El Triunfo was assessed using the Community Vulnerability Assessment Tool developed by the National Oceanic and Atmospheric Administration (NOAA). For each critical facility we determined its operational, structural and physical vulnerabilities. For our analysis, we considered the four main natural hazards to which Valle de Chalco is exposed: earthquakes, floods, landslides and sinking. We considered five levels of vulnerability using a scale from 1 to 5, where values range from very low to very high vulnerability, respectively. A critical facilities database was generated by collecting general information for three categories: schools, government and church. Each facility was evaluated considering its location in relation to identified high-risk areas. Our results indicate that in average, the global vulnerability of all facilities is low, however, there are particular cases in which this global vulnerability is high. The average operational vulnerability of the three communities is moderate. The global structural vulnerability (sum of the structural vulnerability for the four analyzed hazards) is moderate. In particular, the structural vulnerability to earthquakes is low, to landslides is very low, to flooding is moderate and to sinking is low. Due to the location of the critical facilities, its global physical vulnerability (sum of the physical vulnerability to the four analyzed hazards) is moderate. Only three facilities have very high physical vulnerability to floods. Churches (six facilities) have the highest operational vulnerability, whereas its structural vulnerability is the lowest. Schools (13 facilities) have the lowest operational vulnerability, nevertheless, there are two schools with very high vulnerability. Regarding the six government facilities, we identified that their structural vulnerability range from moderate to high. As a result of this work, we believe in the importance of strengthening the culture of civil protection within the critical facilities of the communities of Valle de Chalco.

Overview of environmental and hydrogeologic conditions at McGrath, Alaska

USGS Publications Warehouse

Dorava, J.M.

1994-01-01

The remote village of McGrath along the Kuskokwim River in southwestern Alaska has long cold winters and short summers. The village is located on the flood plain of the Kuskokwim River and obtains drinking water for its 533 residents from the Kuskokwim River. Surface spills and disposal of hazardous materials combined with frequent flooding of the Kuskokwim River could affect the quality of the drinking water. Alternative drinking-water sources are available but at greater cost than existing supplies. The Federal Aviation Administration (FAA) owns or operates airport support facilities in McGrath and wishes to consider the subsistence lifestyle of the residents and the quality of the current environ- ment when evaluating options for remediation of environmental contamination at their facilities. This report describes the history, socioeconomics, physical setting, ground- and surface-water hydrology, geology, climate, vegetation, soils, and flood potential of the areas surrounding the FAA facilities near McGrath.

Establishing a rainfall threshold for flash flood warnings based on the DFFG method in Yunnan province, China

NASA Astrophysics Data System (ADS)

Ma, M.; Wang, H.; Chen, Y.; Tang, G.; Hong, Z.; Zhang, K.; Hong, Y.

2017-12-01

Flash floods, one of the deadliest natural hazards worldwide due to their multidisciplinary nature, rank highly in terms of heavy damage and casualties. Such as in the United States, flash flood is the No.1 cause of death and the No. 2 most deadly weather-related hazard among all storm-related hazards, with approximately 100 lives lost each year. According to China Floods and Droughts Disasters Bullet in 2015 (http://www.mwr.gov.cn/zwzc/hygb/zgshzhgb), about 935 deaths per year on average were caused by flash floods from 2000 to 2015, accounting for 73 % of the fatalities due to floods. Therefore, significant efforts have been made toward understanding flash flood processes as well as modeling and forecasting them, it still remains challenging because of their short response time and limited monitoring capacity. This study advances the use of high-resolution Global Precipitation Measurement forecasts (GPMs), disaster data obtained from the government officials in 2011 and 2016, and the improved Distributed Flash Flood Guidance (DFFG) method combining the Distributed Hydrologic Model and Soil Conservation Service Curve Numbers. The objectives of this paper are (1) to examines changes in flash flood occurrence, (2) to estimate the effect of the rainfall spatial variability ,(2) to improve the lead time in flash floods warning and get the rainfall threshold, (3) to assess the DFFG method applicability in Dongchuan catchments, and (4) to yield the probabilistic information about the forecast hydrologic response that accounts for the locational uncertainties of the GPMs. Results indicate: (1) flash flood occurrence increased in the study region, (2) the occurrence of predicted flash floods show high sensitivity to total infiltration and soil water content, (3) the DFFG method is generally capable of making accurate predictions of flash flood events in terms of their locations and time of occurrence, and (4) the accumulative rainfall over a certain time span is an appropriate threshold for flash flood warnings. Finally, the article highlights the importance of accurately simulating the hydrological processes and high-resolution satellite rainfall data on the accurate forecasting of rainfall triggered flash flood events.

Probabilistic calibration of the distributed hydrological model RIBS applied to real-time flood forecasting: the Harod river basin case study (Israel)

NASA Astrophysics Data System (ADS)

Nesti, Alice; Mediero, Luis; Garrote, Luis; Caporali, Enrica

2010-05-01

An automatic probabilistic calibration method for distributed rainfall-runoff models is presented. The high number of parameters in hydrologic distributed models makes special demands on the optimization procedure to estimate model parameters. With the proposed technique it is possible to reduce the complexity of calibration while maintaining adequate model predictions. The first step of the calibration procedure of the main model parameters is done manually with the aim to identify their variation range. Afterwards a Monte-Carlo technique is applied, which consists on repetitive model simulations with randomly generated parameters. The Monte Carlo Analysis Toolbox (MCAT) includes a number of analysis methods to evaluate the results of these Monte Carlo parameter sampling experiments. The study investigates the use of a global sensitivity analysis as a screening tool to reduce the parametric dimensionality of multi-objective hydrological model calibration problems, while maximizing the information extracted from hydrological response data. The method is applied to the calibration of the RIBS flood forecasting model in the Harod river basin, placed on Israel. The Harod basin has an extension of 180 km2. The catchment has a Mediterranean climate and it is mainly characterized by a desert landscape, with a soil that is able to absorb large quantities of rainfall and at the same time is capable to generate high peaks of discharge. Radar rainfall data with 6 minute temporal resolution are available as input to the model. The aim of the study is the validation of the model for real-time flood forecasting, in order to evaluate the benefits of improved precipitation forecasting within the FLASH European project.

The multi temporal/multi-model approach to predictive uncertainty assessment in real-time flood forecasting

NASA Astrophysics Data System (ADS)

Barbetta, Silvia; Coccia, Gabriele; Moramarco, Tommaso; Brocca, Luca; Todini, Ezio

2017-08-01

This work extends the multi-temporal approach of the Model Conditional Processor (MCP-MT) to the multi-model case and to the four Truncated Normal Distributions (TNDs) approach, demonstrating the improvement on the single-temporal one. The study is framed in the context of probabilistic Bayesian decision-making that is appropriate to take rational decisions on uncertain future outcomes. As opposed to the direct use of deterministic forecasts, the probabilistic forecast identifies a predictive probability density function that represents a fundamental knowledge on future occurrences. The added value of MCP-MT is the identification of the probability that a critical situation will happen within the forecast lead-time and when, more likely, it will occur. MCP-MT is thoroughly tested for both single-model and multi-model configurations at a gauged site on the Tiber River, central Italy. The stages forecasted by two operative deterministic models, STAFOM-RCM and MISDc, are considered for the study. The dataset used for the analysis consists of hourly data from 34 flood events selected on a time series of six years. MCP-MT improves over the original models' forecasts: the peak overestimation and the rising limb delayed forecast, characterizing MISDc and STAFOM-RCM respectively, are significantly mitigated, with a reduced mean error on peak stage from 45 to 5 cm and an increased coefficient of persistence from 0.53 up to 0.75. The results show that MCP-MT outperforms the single-temporal approach and is potentially useful for supporting decision-making because the exceedance probability of hydrometric thresholds within a forecast horizon and the most probable flooding time can be estimated.

Is probabilistic bias analysis approximately Bayesian?

PubMed Central

MacLehose, Richard F.; Gustafson, Paul

2011-01-01

Case-control studies are particularly susceptible to differential exposure misclassification when exposure status is determined following incident case status. Probabilistic bias analysis methods have been developed as ways to adjust standard effect estimates based on the sensitivity and specificity of exposure misclassification. The iterative sampling method advocated in probabilistic bias analysis bears a distinct resemblance to a Bayesian adjustment; however, it is not identical. Furthermore, without a formal theoretical framework (Bayesian or frequentist), the results of a probabilistic bias analysis remain somewhat difficult to interpret. We describe, both theoretically and empirically, the extent to which probabilistic bias analysis can be viewed as approximately Bayesian. While the differences between probabilistic bias analysis and Bayesian approaches to misclassification can be substantial, these situations often involve unrealistic prior specifications and are relatively easy to detect. Outside of these special cases, probabilistic bias analysis and Bayesian approaches to exposure misclassification in case-control studies appear to perform equally well. PMID:22157311

Simulation of extreme reservoir level distribution with the SCHADEX method (EXTRAFLO project)

NASA Astrophysics Data System (ADS)

Paquet, Emmanuel; Penot, David; Garavaglia, Federico

2013-04-01

The standard practice for the design of dam spillways structures and gates is to consider the maximum reservoir level reached for a given hydrologic scenario. This scenario has several components: peak discharge, flood volumes on different durations, discharge gradients etc. Within a probabilistic analysis framework, several scenarios can be associated with different return times, although a reference return level (e.g. 1000 years) is often prescribed by the local regulation rules or usual practice. Using continuous simulation method for extreme flood estimation is a convenient solution to provide a great variety of hydrological scenarios to feed a hydraulic model of dam operation: flood hydrographs are explicitly simulated by a rainfall-runoff model fed by a stochastic rainfall generator. The maximum reservoir level reached will be conditioned by the scale and the dynamics of the generated hydrograph, by the filling of the reservoir prior to the flood, and by the dam gates and spillway operation during the event. The simulation of a great number of floods will allow building a probabilistic distribution of maximum reservoir levels. A design value can be chosen at a definite return level. An alternative approach is proposed here, based on the SCHADEX method for extreme flood estimation, proposed by Paquet et al. (2006, 2013). SCHADEX is a so-called "semi-continuous" stochastic simulation method in that flood events are simulated on an event basis and are superimposed on a continuous simulation of the catchment saturation hazard using rainfall-runoff modelling. The SCHADEX process works at the study time-step (e.g. daily), and the peak flow distribution is deduced from the simulated daily flow distribution by a peak-to-volume ratio. A reference hydrograph relevant for extreme floods is proposed. In the standard version of the method, both the peak-to-volume and the reference hydrograph are constant. An enhancement of this method is presented, with variable peak-to-volume ratios and hydrographs applied to each simulated event. This allows accounting for different flood dynamics, depending on the season, the generating precipitation event, the soil saturation state, etc. In both cases, a hydraulic simulation of dam operation is performed, in order to compute the distribution of maximum reservoir levels. Results are detailed for an extreme return level, showing that a 1000 years return level reservoir level can be reached during flood events whose components (peaks, volumes) are not necessarily associated with such return level. The presentation will be illustrated by the example of a fictive dam on the Tech River at Reynes (South of France, 477 km²). This study has been carried out within the EXTRAFLO project, Task 8 (https://extraflo.cemagref.fr/). References: Paquet, E., Gailhard, J. and Garçon, R. (2006), Evolution of the GRADEX method: improvement by atmospheric circulation classification and hydrological modeling, La Houille Blanche, 5, 80-90. doi:10.1051/lhb:2006091. Paquet, E., Garavaglia, F., Garçon, R. and Gailhard, J. (2012), The SCHADEX method: a semi-continuous rainfall-runoff simulation for extreme food estimation, Journal of Hydrology, under revision

Probabilistic Radiological Performance Assessment Modeling and Uncertainty

NASA Astrophysics Data System (ADS)

Tauxe, J.

2004-12-01

A generic probabilistic radiological Performance Assessment (PA) model is presented. The model, built using the GoldSim systems simulation software platform, concerns contaminant transport and dose estimation in support of decision making with uncertainty. Both the U.S. Nuclear Regulatory Commission (NRC) and the U.S. Department of Energy (DOE) require assessments of potential future risk to human receptors of disposal of LLW. Commercially operated LLW disposal facilities are licensed by the NRC (or agreement states), and the DOE operates such facilities for disposal of DOE-generated LLW. The type of PA model presented is probabilistic in nature, and hence reflects the current state of knowledge about the site by using probability distributions to capture what is expected (central tendency or average) and the uncertainty (e.g., standard deviation) associated with input parameters, and propagating through the model to arrive at output distributions that reflect expected performance and the overall uncertainty in the system. Estimates of contaminant release rates, concentrations in environmental media, and resulting doses to human receptors well into the future are made by running the model in Monte Carlo fashion, with each realization representing a possible combination of input parameter values. Statistical summaries of the results can be compared to regulatory performance objectives, and decision makers are better informed of the inherently uncertain aspects of the model which supports their decision-making. While this information may make some regulators uncomfortable, they must realize that uncertainties which were hidden in a deterministic analysis are revealed in a probabilistic analysis, and the chance of making a correct decision is now known rather than hoped for. The model includes many typical features and processes that would be part of a PA, but is entirely fictitious. This does not represent any particular site and is meant to be a generic example. A practitioner could, however, start with this model as a GoldSim template and, by adding site specific features and parameter values (distributions), use this model as a starting point for a real model to be used in real decision making.

Assessing Flood Risk at Nuclear Power Plants with an Uncertain Climate

NASA Astrophysics Data System (ADS)

Wigmosta, M. S.; Vail, L. W.

2011-12-01

In 2010 a tsunami severely damaged the Fukushima Dai-ichi Nuclear Power Plant in Japan. As a result, the U.S. Nuclear Regulatory Commission directed that a systematic and methodical review of Commission processes and regulations be performed to determine whether the agency should make additional improvements to its regulatory system and to make recommendations to the Commission. Two of the recommendations of the Task Force created to inform the Commission were: establish a logical, systematic, and coherent regulatory framework for adequate protection that appropriately balances defense-in-depth and risk considerations and that the NRC require licensees to reevaluate and upgrade as necessary the design-basis flooding protection of structures, systems, and components for each operating reactor. These recommendations came at the same time as technical discussions about updating approaches to evaluate flood hazard were underway. These discussions included: consideration of climate nonstationarity in flood assessments; transitioning from PMP/PMF assessments to probabilistic flood analyses to better align with risk-informed decision making; and systematic consideration of combined events in flood risk analysis. There is no scientific basis to assume that shifts in long-term mean precipitation and temperature (such as is commonly derived from climate models) relate to flood probability. Flood mechanisms are often more complex and reflect climate pattern anomalies more than mean annual shifts. Instead of discounting historical data due to climatic nonstationarity, it is important to better understand the climate patterns that have triggered floods in the past and to look to climate forecasts to understand the likely changes in the frequency of those historical climate patterns with climate change. It is equally important to have a better understanding of whether climate change will result in flood-generating climate systems heretofore unknown in the particular locale. This presentation will provide a roadmap to ensuring that the flood hazards of existing and future nuclear power plants are well defined.

The Generation of a Stochastic Flood Event Catalogue for Continental USA

NASA Astrophysics Data System (ADS)

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; and presents future developments to the modelling approach.

Quantifying the impact of Teleconnections on Hydrologic Regimes in Texas

NASA Astrophysics Data System (ADS)

Bhatia, N.; Singh, V. P.; Srivastav, R. K.

2016-12-01

Climate change is being alleged to have led to the increased frequency of extreme flooding events and the resulting damages are severe, especially where the flood-plain population densities are higher. Much research in the field of hydroclimatology is focusing on improving real-time flood forecasting models. Recent studies show that, in the state of Texas, extreme regional floods are actually triggered by abruptly higher precipitation intensities. Such intensities are further driven by sea-surface temperature and pressure anomalies, defined by certain patterns of teleconnections. In this study, climate variability is defined on the basis of five major Atlantic and Pacific Ocean related teleconnections: (i) Atlantic Multidecadal Oscillation (AMO), (ii) North Atlantic Oscillation (NAO), (iii) Pacific Decadal Oscillation (PDO), (iv) Pacific North American Pattern (PNA), and (v) Southern Oscillation Index (SOI). Hydrologic extremes will be modeled using probabilistic distributions. Leave-One-Out-Test (LOOT) will be employed to address the outliers in the extremes, and to eventually obtain the robust correlation coefficient. The variation in the effect of most correlated teleconnection with respect to hydrologic attributes will be investigated for the entire state. This study will attempt to identify potential teleconnection inputs for data-driven hydrologic models under varying climatic conditions.

FGC Webinar: From Fires to Floods and Everything In Between

EPA Pesticide Factsheets

Federal Green Challenge presentations from the April 2018 'Billion Dollar Weather Events' webinar From Fires to Floods and Everything in Between: How Federal Facilities Can Thrive in an Era of Billion Dollar Weather Events.

Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta, Vietnam

NASA Astrophysics Data System (ADS)

Apel, Heiko; Martínez Trepat, Oriol; Nghia Hung, Nguyen; Thi Chinh, Do; Merz, Bruno; Viet Dung, Nguyen

2016-04-01

Many urban areas experience both fluvial and pluvial floods, because locations next to rivers are preferred settlement areas and the predominantly sealed urban surface prevents infiltration and facilitates surface inundation. The latter problem is enhanced in cities with insufficient or non-existent sewer systems. While there are a number of approaches to analyse either a fluvial or pluvial flood hazard, studies of a combined fluvial and pluvial flood hazard are hardly available. Thus this study aims to analyse a fluvial and a pluvial flood hazard individually, but also to develop a method for the analysis of a combined pluvial and fluvial flood hazard. This combined fluvial-pluvial flood hazard analysis is performed taking Can Tho city, the largest city in the Vietnamese part of the Mekong Delta, as an example. In this tropical environment the annual monsoon triggered floods of the Mekong River, which can coincide with heavy local convective precipitation events, causing both fluvial and pluvial flooding at the same time. The fluvial flood hazard was estimated with a copula-based bivariate extreme value statistic for the gauge Kratie at the upper boundary of the Mekong Delta and a large-scale hydrodynamic model of the Mekong Delta. This provided the boundaries for 2-dimensional hydrodynamic inundation simulation for Can Tho city. The pluvial hazard was estimated by a peak-over-threshold frequency estimation based on local rain gauge data and a stochastic rainstorm generator. Inundation for all flood scenarios was simulated by a 2-dimensional hydrodynamic model implemented on a Graphics Processing Unit (GPU) for time-efficient flood propagation modelling. The combined fluvial-pluvial flood scenarios were derived by adding rainstorms to the fluvial flood events during the highest fluvial water levels. The probabilities of occurrence of the combined events were determined assuming independence of the two flood types and taking the seasonality and probability of coincidence into account. All hazards - fluvial, pluvial and combined - were accompanied by an uncertainty estimation taking into account the natural variability of the flood events. This resulted in probabilistic flood hazard maps showing the maximum inundation depths for a selected set of probabilities of occurrence, with maps showing the expectation (median) and the uncertainty by percentile maps. The results are critically discussed and their usage in flood risk management are outlined.

Environmental risk analysis of oil handling facilities in port areas. Application to Tarragona harbor (NE Spain).

PubMed

Valdor, Paloma F; Gómez, Aina G; Puente, Araceli

2015-01-15

Diffuse pollution from oil spills is a widespread problem in port areas (as a result of fuel supply, navigation and loading/unloading activities). This article presents a method to assess the environmental risk of oil handling facilities in port areas. The method is based on (i) identification of environmental hazards, (ii) characterization of meteorological and oceanographic conditions, (iii) characterization of environmental risk scenarios, and (iv) assessment of environmental risk. The procedure has been tested by application to the Tarragona harbor. The results show that the method is capable of representing (i) specific local pollution cases (i.e., discriminating between products and quantities released by a discharge source), (ii) oceanographic and meteorological conditions (selecting a representative subset data), and (iii) potentially affected areas in probabilistic terms. Accordingly, it can inform the design of monitoring plans to study and control the environmental impact of these facilities, as well as the design of contingency plans. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Impact of Climate Change on New York City's Coastal Flood Hazard: Increasing Flood Heights from the Pre-Industrial to 2300 CE

NASA Astrophysics Data System (ADS)

Garner, A. J.; Mann, M. E.; Emanuel, K.; Kopp, R. E.; Lin, N.; Alley, R. B.; Horton, B.; Deconto, R. M.; Donnelly, J. P.; Pollard, D.

2017-12-01

The flood hazard in New York City depends on both storm surges and rising sea levels. We combine modeled storm surges with probabilistic sea-level rise projections to assess future coastal inundation in New York City from the pre-industrial through 2300 CE. The storm surges are derived from large sets of synthetic tropical cyclones, downscaled from RCP 8.5 runs of three CMIP5 models. The sea-level rise projections include the collapse of the Antarctic ice sheet to assess future coastal inundation. CMIP5 models indicate that there will be minimal change in storm-surge heights from 2010 to 2100 or 2300, because the predicted strengthening of the strongest storms will be compensated by storm tracks moving offshore at the latitude of New York City. However, projected sea-level rise causes overall flood heights associated with tropical cyclones in New York City in coming centuries to increase greatly compared to pre-industrial or modern flood heights. We find that the 1-in-500-year flood event increases from 3.4 m above mean tidal level during 1970-2005 to 3.9 - 4.8 m above mean tidal level by 2080-2100, and ranges from 2.8 - 13.0 m above mean tidal level by 2280-2300. Further, we find that the return period of a 2.25 m flood has decreased from 500 years prior to 1800 to 25 years during 1970-2005, and further decreases to 5 years by 2030 - 2045 in 95% of our simulations.

Impact of climate change on New York City's coastal flood hazard: Increasing flood heights from the preindustrial to 2300 CE.

PubMed

Garner, Andra J; Mann, Michael E; Emanuel, Kerry A; Kopp, Robert E; Lin, Ning; Alley, Richard B; Horton, Benjamin P; DeConto, Robert M; Donnelly, Jeffrey P; Pollard, David

2017-11-07

The flood hazard in New York City depends on both storm surges and rising sea levels. We combine modeled storm surges with probabilistic sea-level rise projections to assess future coastal inundation in New York City from the preindustrial era through 2300 CE. The storm surges are derived from large sets of synthetic tropical cyclones, downscaled from RCP8.5 simulations from three CMIP5 models. The sea-level rise projections account for potential partial collapse of the Antarctic ice sheet in assessing future coastal inundation. CMIP5 models indicate that there will be minimal change in storm-surge heights from 2010 to 2100 or 2300, because the predicted strengthening of the strongest storms will be compensated by storm tracks moving offshore at the latitude of New York City. However, projected sea-level rise causes overall flood heights associated with tropical cyclones in New York City in coming centuries to increase greatly compared with preindustrial or modern flood heights. For the various sea-level rise scenarios we consider, the 1-in-500-y flood event increases from 3.4 m above mean tidal level during 1970-2005 to 4.0-5.1 m above mean tidal level by 2080-2100 and ranges from 5.0-15.4 m above mean tidal level by 2280-2300. Further, we find that the return period of a 2.25-m flood has decreased from ∼500 y before 1800 to ∼25 y during 1970-2005 and further decreases to ∼5 y by 2030-2045 in 95% of our simulations. The 2.25-m flood height is permanently exceeded by 2280-2300 for scenarios that include Antarctica's potential partial collapse. Copyright © 2017 the Author(s). Published by PNAS.

Impact of climate change on New York City’s coastal flood hazard: Increasing flood heights from the preindustrial to 2300 CE

PubMed Central

Mann, Michael E.; Emanuel, Kerry A.; Alley, Richard B.; Horton, Benjamin P.; DeConto, Robert M.; Donnelly, Jeffrey P.; Pollard, David

2017-01-01

The flood hazard in New York City depends on both storm surges and rising sea levels. We combine modeled storm surges with probabilistic sea-level rise projections to assess future coastal inundation in New York City from the preindustrial era through 2300 CE. The storm surges are derived from large sets of synthetic tropical cyclones, downscaled from RCP8.5 simulations from three CMIP5 models. The sea-level rise projections account for potential partial collapse of the Antarctic ice sheet in assessing future coastal inundation. CMIP5 models indicate that there will be minimal change in storm-surge heights from 2010 to 2100 or 2300, because the predicted strengthening of the strongest storms will be compensated by storm tracks moving offshore at the latitude of New York City. However, projected sea-level rise causes overall flood heights associated with tropical cyclones in New York City in coming centuries to increase greatly compared with preindustrial or modern flood heights. For the various sea-level rise scenarios we consider, the 1-in-500-y flood event increases from 3.4 m above mean tidal level during 1970–2005 to 4.0–5.1 m above mean tidal level by 2080–2100 and ranges from 5.0–15.4 m above mean tidal level by 2280–2300. Further, we find that the return period of a 2.25-m flood has decreased from ∼500 y before 1800 to ∼25 y during 1970–2005 and further decreases to ∼5 y by 2030–2045 in 95% of our simulations. The 2.25-m flood height is permanently exceeded by 2280–2300 for scenarios that include Antarctica’s potential partial collapse. PMID:29078274

Impact of climate change on New York City's coastal flood hazard: Increasing flood heights from the preindustrial to 2300 CE

NASA Astrophysics Data System (ADS)

Garner, Andra J.; Mann, Michael E.; Emanuel, Kerry A.; Kopp, Robert E.; Lin, Ning; Alley, Richard B.; Horton, Benjamin P.; DeConto, Robert M.; Donnelly, Jeffrey P.; Pollard, David

2017-11-01

The flood hazard in New York City depends on both storm surges and rising sea levels. We combine modeled storm surges with probabilistic sea-level rise projections to assess future coastal inundation in New York City from the preindustrial era through 2300 CE. The storm surges are derived from large sets of synthetic tropical cyclones, downscaled from RCP8.5 simulations from three CMIP5 models. The sea-level rise projections account for potential partial collapse of the Antarctic ice sheet in assessing future coastal inundation. CMIP5 models indicate that there will be minimal change in storm-surge heights from 2010 to 2100 or 2300, because the predicted strengthening of the strongest storms will be compensated by storm tracks moving offshore at the latitude of New York City. However, projected sea-level rise causes overall flood heights associated with tropical cyclones in New York City in coming centuries to increase greatly compared with preindustrial or modern flood heights. For the various sea-level rise scenarios we consider, the 1-in-500-y flood event increases from 3.4 m above mean tidal level during 1970–2005 to 4.0–5.1 m above mean tidal level by 2080–2100 and ranges from 5.0–15.4 m above mean tidal level by 2280–2300. Further, we find that the return period of a 2.25-m flood has decreased from ˜500 y before 1800 to ˜25 y during 1970–2005 and further decreases to ˜5 y by 2030–2045 in 95% of our simulations. The 2.25-m flood height is permanently exceeded by 2280–2300 for scenarios that include Antarctica's potential partial collapse.

An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios

NASA Astrophysics Data System (ADS)

Addor, N.; Jaun, S.; Fundel, F.; Zappa, M.

2011-07-01

The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This model chain relies on limited-area atmospheric forecasts provided by the deterministic model COSMO-7 and the probabilistic model COSMO-LEPS. These atmospheric forecasts are used to force a semi-distributed hydrological model (PREVAH), coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework with which to compare the potential of deterministic and probabilistic discharge forecasts for flood mitigation. To study the suitability of HEPS for small-scale basins and to quantify the added-value conveyed by the probability information, a reforecast was made for the period June 2007 to December 2009 for the Sihl catchment (336 km2). Several metrics support the conclusion that the performance gain can be of up to 2 days lead time for the catchment considered. Brier skill scores show that overall COSMO-LEPS-based hydrological forecasts outperforms their COSMO-7-based counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts, as shown by comparisons with a reference run driven by observed meteorological parameters. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. The two most intense events of the study period are investigated utilising a novel graphical representation of probability forecasts, and are used to generate high discharge scenarios. They highlight challenges for making decisions on the basis of hydrological predictions, and indicate the need for a tool to be used in addition to forecasts to compare the different mitigation actions possible in the Sihl catchment. No definitive conclusion on the model chain capacity to forecast flooding events endangering the city of Zurich could be drawn because of the under-sampling of extreme events. Further research on the form of the reforecasts needed to infer on floods associated to return periods of several decades, centuries, is encouraged.

Black swans, power laws, and dragon-kings: Earthquakes, volcanic eruptions, landslides, wildfires, floods, and SOC models

NASA Astrophysics Data System (ADS)

Sachs, M. K.; Yoder, M. R.; Turcotte, D. L.; Rundle, J. B.; Malamud, B. D.

2012-05-01

Extreme events that change global society have been characterized as black swans. The frequency-size distributions of many natural phenomena are often well approximated by power-law (fractal) distributions. An important question is whether the probability of extreme events can be estimated by extrapolating the power-law distributions. Events that exceed these extrapolations have been characterized as dragon-kings. In this paper we consider extreme events for earthquakes, volcanic eruptions, wildfires, landslides and floods. We also consider the extreme event behavior of three models that exhibit self-organized criticality (SOC): the slider-block, forest-fire, and sand-pile models. Since extrapolations using power-laws are widely used in probabilistic hazard assessment, the occurrence of dragon-king events have important practical implications.

A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

NASA Astrophysics Data System (ADS)

Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

2018-02-01

Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.

Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

PubMed

Orhan, A Emin; Ma, Wei Ji

2017-07-26

Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

Flood of October 8, 1962, on Bachman Branch and Joes Creek at Dallas, Texas

USGS Publications Warehouse

Ruggles, Frederick H.

1966-01-01

This report presents hydrologic data that enable the user to define areas susceptible to flooding and to evaluate the flood hazard along Bachman Branch and Joes Creek. The data provide a technical basis for making sound decisions concerning the use of flood-plain lands. The report will be useful for preparing building and zoning regulations, locating waste disposal facilities, purchasing unoccupied land, developing recreational areas, and managing surface water in relation to ground-water resources. This is one of the series of reports delineating the flood hazard on streams in the Dallas area.

The use of sediment deposition maps as auxiliary data for hydraulic model calibration

NASA Astrophysics Data System (ADS)

Mukolwe, Micah; Di Baldassarre, Giuliano; Solomatine, Dimitri

2013-04-01

One aspect of the French disaster mitigation setup is the statutory Risk Prevention Plans (PPR, Plans de Prévention des Risques); i.e. spatial identification of potential disasters and mitigation measures. The maps are categorised into three zones depicting increasing disaster severity and potential mitigation measures (RTM, 1999). Taking the example of the city of Barcelonnette, in South France (French Alps), floods have been the most frequent occurring natural hazard (Flageollet et al., 1996). Consequently, a case is put forward for the need for accurate flood extent delineation to support the decision making process. For this study, the Barcelonnette case study was considered, whereby the last devastating flooding was in June 1957 (Weber, 1994). Contrary to the recent advances in the proliferation of data to support flood inundation studies (Bates, 2012; Bates, 2004; Di Baldassarre and Uhlenbrook, 2012; Schumann et al., 2009), constraints are faced when analysing flood inundation events that occurred before the 1970's. In absence of frequent flooding, the analysis of historical flood extents may play an important role in shaping the awareness of local stakeholders and support land-use and urban planning. This study is part of a probabilistic flood mapping (e.g. Di Baldassarre et al., 2010, Horrit, 2006) of the valley carried out in a Monte-Carlo framework, while taking into account the peak flow and the parametric uncertainty. The simulations were carried out using the sub-grid channel model extension of the LISFLOOD-FP hydraulic model (Bates et al, 2010; Neal et al., 2012). Sediment deposition maps (Lecarpentier, 1963) were used to analyse the model performance, additionally the graduation of the sediment deposition sizes showed the flood propagation and was used to analyse the model runs. However, there still remains the challenge of quantifying the uncertainty in the sediment deposition map and the actual flood extent.

[Potential vulnerability to flooding at public health facilities in four northern regions of Peru].

PubMed

Hernández-Vásquez, Akram; Arroyo-Hernández, Hugo; Bendezú-Quispe, Guido; Díaz-Seijas, Deysi; Vilcarromero, Stalin; Rubilar-González, Juan; Gutierrez-Lagos, Edith

2016-03-01

In order to determine the potential vulnerability of public health facilities in four northern regions of Peru to the possible effects of El Niño-Southern Oscillation (ENSO) phenomenon. An exploratory spatial analysis was performed using the geo-referenced points for at-risk areas based on the activation of gullies that were reported by the National Water Authority, and the location of the four regional public health facilities of the Ministry of Health. Concentric areas of influence were simulate from the points of risk towards the public health facilities using radii of 200, 1000 and 1500 meters. The Tumbes region would be the most affected with 37.2% of its health facilities being affected by floods and landslides. The I-2 and I-3 categories of health facilities appeared to be the most affected with 28.9% and 31.6% respectively. Therefore, public health facilities near the risk zones may be affected by the ENSO.

Multi-dimensional perspectives of flood risk - using a participatory framework to develop new approaches to flood risk communication

NASA Astrophysics Data System (ADS)

Rollason, Edward; Bracken, Louise; Hardy, Richard; Large, Andy

2017-04-01

Flooding is a major hazard across Europe which, since, 1998 has caused over €52 million in damages and displaced over half a million people. Climate change is predicted to increase the risks posed by flooding in the future. The 2007 EU Flood Directive cemented the use of flood risk maps as a central tool in understanding and communicating flood risk. Following recent flooding in England, an urgent need to integrate people living at risk from flooding into flood management approaches, encouraging flood resilience and the up-take of resilient activities has been acknowledged. The effective communication of flood risk information plays a major role in allowing those at risk to make effective decisions about flood risk and increase their resilience, however, there are emerging concerns over the effectiveness of current approaches. The research presented explores current approaches to flood risk communication in England and the effectiveness of these methods in encouraging resilient actions before and during flooding events. The research also investigates how flood risk communications could be undertaken more effectively, using a novel participatory framework to integrate the perspectives of those living at risk. The research uses co-production between local communities and researchers in the environmental sciences, using a participatory framework to bring together local knowledge of flood risk and flood communications. Using a local competency group, the research explores what those living at risk from flooding want from flood communications in order to develop new approaches to help those at risk understand and respond to floods. Suggestions for practice are refined by the communities to co-produce recommendations. The research finds that current approaches to real-time flood risk communication fail to forecast the significance of predicted floods, whilst flood maps lack detailed information about how floods occur, or use scientific terminology which people at risk find confusing or lacking in realistic grounding. This means users do not have information they find useful to make informed decisions about how to prepare for and respond to floods. Working together with at-risk participants, the research has developed new approaches for communicating flood risk. These approaches focus on understanding flood mechanisms and dynamics, to help participants imagine their flood risk and link potential scenarios to reality, and provide forecasts of predicted flooding at a variety of scales, allowing participants to assess the significance of predicted flooding and make more informed judgments on what action to take in response. The findings presented have significant implications for the way in which flood risk is communicated, changing the focus of mapping from probabilistic future scenarios to understanding flood dynamics and mechanisms. Such ways of communicating flood risk embrace how people would like to see risk communicated, and help those at risk grow their resilience. Communicating in such a way has wider implications for flood modelling and data collection. However, these represent potential opportunities to build more effective local partnerships for assessing and managing flood risks.

Natural disasters: forecasting economic and life losses

USGS Publications Warehouse

Nishenko, Stuart P.; Barton, Christopher C.

1997-01-01

Events such as hurricanes, earthquakes, floods, tsunamis, volcanic eruptions, and tornadoes are natural disasters because they negatively impact society, and so they must be measured and understood in human-related terms. At the U.S. Geological Survey, we have developed a new method to examine fatality and dollar-loss data, and to make probabilistic estimates of the frequency and magnitude of future events. This information is vital to large sectors of society including disaster relief agencies and insurance companies.

Climate and change: simulating flooding impacts on urban transport network

NASA Astrophysics Data System (ADS)

Pregnolato, Maria; Ford, Alistair; Dawson, Richard

2015-04-01

National-scale climate projections indicate that in the future there will be hotter and drier summers, warmer and wetter winters, together with rising sea levels. The frequency of extreme weather events is expected to increase, causing severe damage to the built environment and disruption of infrastructures (Dawson, 2007), whilst population growth and changed demographics are placing new demands on urban infrastructure. It is therefore essential to ensure infrastructure networks are robust to these changes. This research addresses these challenges by focussing on the development of probabilistic tools for managing risk by modelling urban transport networks within the context of extreme weather events. This paper presents a methodology to investigate the impacts of extreme weather events on urban environment, in particular infrastructure networks, through a combination of climate simulations and spatial representations. By overlaying spatial data on hazard thresholds from a flood model and a flood safety function, mitigated by potential adaptation strategies, different levels of disruption to commuting journeys on road networks are evaluated. The method follows the Catastrophe Modelling approach and it consists of a spatial model, combining deterministic loss models and probabilistic risk assessment techniques. It can be applied to present conditions as well as future uncertain scenarios, allowing the examination of the impacts alongside socio-economic and climate changes. The hazard is determined by simulating free surface water flooding, with the software CityCAT (Glenis et al., 2013). The outputs are overlapped to the spatial locations of a simple network model in GIS, which uses journey-to-work (JTW) observations, supplemented with speed and capacity information. To calculate the disruptive effect of flooding on transport networks, a function relating water depth to safe driving car speed has been developed by combining data from experimental reports (Morris et al., 2011) safety literature (Great Britain Department for Transport, 1999), analysis of videos of cars driving through floodwater, and expert judgement. A preliminary analysis has been run in the Tyne & Wear (in North-East England) region to demonstrate how the analysis can be used to assess the disruptions for commuter journeys due to flooding and will be demonstrated in this paper. The research will also investigate the effectiveness of adaptation strategies for extreme rainfall events, such as permeable surfaces and roof storages for buildings. Multiple scenarios (from the every-day-rainfall to the extreme weather phenomena) will be modelled, with different rainfall rates, rainfall durations and return periods. The comparison between the scenarios in which no interventions are adopted and those improved by one of the adaptation option will be compared to determine the cost-effectiveness of the solution considered. Integrating spatial analysis of transport use with an urban flood model and flood safety function enables the investigation of the impacts of extreme weather on infrastructure networks. Further work will develop the analysis in a number of ways (i) testing a range of flood events with different severity and frequency, (ii) exploration of the influence of climate and socio-economic change (iii) analysis of multiple hazard events and (iv) consideration of cascading disruption across different infrastructure networks.

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

NASA Astrophysics Data System (ADS)

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.

Probabilistic tsunami hazard assessment at Seaside, Oregon, for near-and far-field seismic sources

USGS Publications Warehouse

Gonzalez, F.I.; Geist, E.L.; Jaffe, B.; Kanoglu, U.; Mofjeld, H.; Synolakis, C.E.; Titov, V.V.; Areas, D.; Bellomo, D.; Carlton, D.; Horning, T.; Johnson, J.; Newman, J.; Parsons, T.; Peters, R.; Peterson, C.; Priest, G.; Venturato, A.; Weber, J.; Wong, F.; Yalciner, A.

2009-01-01

The first probabilistic tsunami flooding maps have been developed. The methodology, called probabilistic tsunami hazard assessment (PTHA), integrates tsunami inundation modeling with methods of probabilistic seismic hazard assessment (PSHA). Application of the methodology to Seaside, Oregon, has yielded estimates of the spatial distribution of 100- and 500-year maximum tsunami amplitudes, i.e., amplitudes with 1% and 0.2% annual probability of exceedance. The 100-year tsunami is generated most frequently by far-field sources in the Alaska-Aleutian Subduction Zone and is characterized by maximum amplitudes that do not exceed 4 m, with an inland extent of less than 500 m. In contrast, the 500-year tsunami is dominated by local sources in the Cascadia Subduction Zone and is characterized by maximum amplitudes in excess of 10 m and an inland extent of more than 1 km. The primary sources of uncertainty in these results include those associated with interevent time estimates, modeling of background sea level, and accounting for temporal changes in bathymetry and topography. Nonetheless, PTHA represents an important contribution to tsunami hazard assessment techniques; viewed in the broader context of risk analysis, PTHA provides a method for quantifying estimates of the likelihood and severity of the tsunami hazard, which can then be combined with vulnerability and exposure to yield estimates of tsunami risk. Copyright 2009 by the American Geophysical Union.

Flood Impacts on People: from Hazard to Risk Maps

NASA Astrophysics Data System (ADS)

Arrighi, C.; Castelli, F.

2017-12-01

The mitigation of adverse consequences of floods on people is crucial for civil protection and public authorities. According to several studies, in the developed countries the majority of flood-related fatalities occurs due to inappropriate high risk behaviours such as driving and walking in floodwaters. In this work both the loss of stability of vehicles and pedestrians in floodwaters are analysed. Flood hazard is evaluated, based on (i) a 2D inundation model of an urban area, (ii) 3D hydrodynamic simulations of water flows around vehicles and human body and (iii) a dimensional analysis of experimental activity. Exposure and vulnerability of vehicles and population are assessed exploiting several sources of open GIS data in order to produce risk maps for a testing case study. The results show that a significant hazard to vehicles and pedestrians exists in the study area. Particularly high is the hazard to vehicles, which are likely to be swept away by flood flow, possibly aggravate damages to structures and infrastructures and locally alter the flood propagation. Exposure and vulnerability analysis identifies some structures such as schools and public facilities, which may attract several people. Moreover, some shopping facilities in the area, which attract both vehicular and pedestrians' circulation are located in the highest flood hazard zone.The application of the method demonstrates that, at municipal level, such risk maps can support civil defence strategies and education to active citizenship, thus contributing to flood impact reduction to population.

Probabilistic evaluation of uncertainties and risks in aerospace components

NASA Technical Reports Server (NTRS)

Shah, A. R.; Shiao, M. C.; Nagpal, V. K.; Chamis, C. C.

1992-01-01

A methodology is presented for the computational simulation of primitive variable uncertainties, and attention is given to the simulation of specific aerospace components. Specific examples treated encompass a probabilistic material behavior model, as well as static, dynamic, and fatigue/damage analyses of a turbine blade in a mistuned bladed rotor in the SSME turbopumps. An account is given of the use of the NESSES probabilistic FEM analysis CFD code.

Uncertainty in Predicted Neighborhood-Scale Green Stormwater Infrastructure Performance Informed by field monitoring of Hydrologic Abstractions

NASA Astrophysics Data System (ADS)

Smalls-Mantey, L.; Jeffers, S.; Montalto, F. A.

2013-12-01

Human alterations to the environment provide infrastructure for housing and transportation but have drastically changed local hydrology. Excess stormwater runoff from impervious surfaces generates erosion, overburdens sewer infrastructure, and can pollute receiving bodies. Increased attention to green stormwater management controls is based on the premise that some of these issues can be mitigated by capturing or slowing the flow of stormwater. However, our ability to predict actual green infrastructure facility performance using physical or statistical methods needs additional validation, and efforts to incorporate green infrastructure controls into hydrologic models are still in their infancy stages. We use more than three years of field monitoring data to derive facility specific probability density functions characterizing the hydrologic abstractions provided by a stormwater treatment wetland, streetside bioretention facility, and a green roof. The monitoring results are normalized by impervious area treated, and incorporated into a neighborhood-scale agent model allowing probabilistic comparisons of the stormwater capture outcomes associated with alternative urban greening scenarios. Specifically, we compare the uncertainty introduced into the model by facility performance (as represented by the variability in the abstraction), to that introduced by both precipitation variability, and spatial patterns of emergence of different types of green infrastructure. The modeling results are used to update a discussion about the potential effectiveness of urban green infrastructure implementation plans.

Flood Gives Birth to Dream School.

ERIC Educational Resources Information Center

Freeman, Laurie

1996-01-01

Forced by flooding of the Mississippi River to relocate their entire town, residents of tiny Valmeyer, Illinois, built an upgraded, improved school. The new facility serves elementary, middle, and high school students in three separate wings and is equipped to participate in distance learning. (MLF)

Spatial and Temporal Flood Risk Assessment for Decision Making Approach

NASA Astrophysics Data System (ADS)

Azizat, Nazirah; Omar, Wan-Mohd-Sabki Wan

2018-03-01

Heavy rainfall, adversely impacting inundation areas, depends on the magnitude of the flood. Significantly, location of settlements, infrastructure and facilities in floodplains result in many regions facing flooding risks. A problem faced by the decision maker in an assessment of flood vulnerability and evaluation of adaptation measures is recurrent flooding in the same areas. Identification of recurrent flooding areas and frequency of floods should be priorities for flood risk management. However, spatial and temporal variability become major factors of uncertainty in flood risk management. Therefore, dynamic and spatial characteristics of these changes in flood impact assessment are important in making decisions about the future of infrastructure development and community life. System dynamics (SD) simulation and hydrodynamic modelling are presented as tools for modelling the dynamic characteristics of flood risk and spatial variability. This paper discusses the integration between spatial and temporal information that is required by the decision maker for the identification of multi-criteria decision problems involving multiple stakeholders.

230Th/U ages Supporting Hanford Site-Wide Probabilistic Seismic Hazard Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paces, James B.

This product represents a USGS Administrative Report that discusses samples and methods used to conduct uranium-series isotope analyses and resulting ages and initial 234U/238U activity ratios of pedogenic cements developed in several different surfaces in the Hanford area middle to late Pleistocene. Samples were collected and dated to provide calibration of soil development in surface deposits that are being used in the Hanford Site-Wide probabilistic seismic hazard analysis conducted by AMEC. The report includes description of sample locations and physical characteristics, sample preparation, chemical processing and mass spectrometry, analytical results, and calculated ages for individual sites. Ages of innermost rindsmore » on a number of samples from five sites in eastern Washington are consistent with a range of minimum depositional ages from 17 ka for cataclysmic flood deposits to greater than 500 ka for alluvium at several sites.« less

230Th/U ages Supporting Hanford Site‐Wide Probabilistic Seismic Hazard Analysis

USGS Publications Warehouse

Paces, James B.

2014-01-01

This product represents a USGS Administrative Report that discusses samples and methods used to conduct uranium-series isotope analyses and resulting ages and initial 234U/238U activity ratios of pedogenic cements developed in several different surfaces in the Hanford area middle to late Pleistocene. Samples were collected and dated to provide calibration of soil development in surface deposits that are being used in the Hanford Site-Wide probabilistic seismic hazard analysis conducted by AMEC. The report includes description of sample locations and physical characteristics, sample preparation, chemical processing and mass spectrometry, analytical results, and calculated ages for individual sites. Ages of innermost rinds on a number of samples from five sites in eastern Washington are consistent with a range of minimum depositional ages from 17 ka for cataclysmic flood deposits to greater than 500 ka for alluvium at several sites.

A probabilistic storm transposition approach for estimating exceedance probabilities of extreme precipitation depths

NASA Astrophysics Data System (ADS)

Foufoula-Georgiou, E.

1989-05-01

A storm transposition approach is investigated as a possible tool of assessing the frequency of extreme precipitation depths, that is, depths of return period much greater than 100 years. This paper focuses on estimation of the annual exceedance probability of extreme average precipitation depths over a catchment. The probabilistic storm transposition methodology is presented, and the several conceptual and methodological difficulties arising in this approach are identified. The method is implemented and is partially evaluated by means of a semihypothetical example involving extreme midwestern storms and two hypothetical catchments (of 100 and 1000 mi2 (˜260 and 2600 km2)) located in central Iowa. The results point out the need for further research to fully explore the potential of this approach as a tool for assessing the probabilities of rare storms, and eventually floods, a necessary element of risk-based analysis and design of large hydraulic structures.

Comparison of a Traditional Probabilistic Risk Assessment Approach with Advanced Safety Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Curtis L; Mandelli, Diego; Zhegang Ma

2014-11-01

As part of the Light Water Sustainability Program (LWRS) [1], the purpose of the Risk Informed Safety Margin Characterization (RISMC) [2] Pathway research and development (R&D) is to support plant decisions for risk-informed margin management with the aim to improve economics, reliability, and sustain safety of current NPPs. In this paper, we describe the RISMC analysis process illustrating how mechanistic and probabilistic approaches are combined in order to estimate a safety margin. We use the scenario of a “station blackout” (SBO) wherein offsite power and onsite power is lost, thereby causing a challenge to plant safety systems. We describe themore » RISMC approach, illustrate the station blackout modeling, and contrast this with traditional risk analysis modeling for this type of accident scenario. We also describe our approach we are using to represent advanced flooding analysis.« less

Unexpected flood loss correlations across Europe

NASA Astrophysics Data System (ADS)

Booth, Naomi; Boyd, Jessica

2017-04-01

Floods don't observe country borders, as highlighted by major events across Europe that resulted in heavy economic and insured losses in 1999, 2002, 2009 and 2013. Flood loss correlations between some countries occur along multi-country river systems or between neighbouring nations affected by the same weather systems. However, correlations are not so obvious and whilst flooding in multiple locations across Europe may appear independent, for a re/insurer providing cover across the continent, these unexpected correlations can lead to high loss accumulations. A consistent, continental-scale method that allows quantification and comparison of losses, and identifies correlations in loss between European countries is therefore essential. A probabilistic model for European river flooding was developed that allows estimation of potential losses to pan-European property portfolios. By combining flood hazard and exposure information in a catastrophe modelling platform, we can consider correlations between river basins across Europe rather than being restricted to country boundaries. A key feature of the model is its statistical event set based on extreme value theory. Using historical river flow data, the event set captures spatial and temporal patterns of flooding across Europe and simulates thousands of events representing a full range of possible scenarios. Some known correlations were identified, such as between neighbouring Belgium and Luxembourg where 28% of events that affect either country produce a loss in both. However, our model identified some unexpected correlations including between Austria and Poland, and Poland and France, which are geographically distant. These correlations in flood loss may be missed by traditional methods and are key for re/insurers with risks in multiple countries. The model also identified that 46% of European river flood events affect more than one country. For more extreme events with a return period higher than 200 years, all events impact more than one country. These tail events also demonstrate that it is unlikely for the market to experience an extreme event which does not affect at least five European countries.

Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

NASA Astrophysics Data System (ADS)

Kreibich, Heidi; Schröter, Kai; Merz, Bruno

2016-05-01

Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB).In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.

Probabilistic description of probable maximum precipitation

NASA Astrophysics Data System (ADS)

Ben Alaya, Mohamed Ali; Zwiers, Francis W.; Zhang, Xuebin

2017-04-01

Probable Maximum Precipitation (PMP) is the key parameter used to estimate probable Maximum Flood (PMF). PMP and PMF are important for dam safety and civil engineering purposes. Even if the current knowledge of storm mechanisms remains insufficient to properly evaluate limiting values of extreme precipitation, PMP estimation methods are still based on deterministic consideration, and give only single values. This study aims to provide a probabilistic description of the PMP based on the commonly used method, the so-called moisture maximization. To this end, a probabilistic bivariate extreme values model is proposed to address the limitations of traditional PMP estimates via moisture maximization namely: (i) the inability to evaluate uncertainty and to provide a range PMP values, (ii) the interpretation that a maximum of a data series as a physical upper limit (iii) and the assumption that a PMP event has maximum moisture availability. Results from simulation outputs of the Canadian Regional Climate Model CanRCM4 over North America reveal the high uncertainties inherent in PMP estimates and the non-validity of the assumption that PMP events have maximum moisture availability. This later assumption leads to overestimation of the PMP by an average of about 15% over North America, which may have serious implications for engineering design.

Energy Efficient Probabilistic Broadcasting for Mobile Ad-Hoc Network

NASA Astrophysics Data System (ADS)

Kumar, Sumit; Mehfuz, Shabana

2017-06-01

In mobile ad-hoc network (MANETs) flooding method is used for broadcasting route request (RREQ) packet from one node to another node for route discovery. This is the simplest method of broadcasting of RREQ packets but it often results in broadcast storm problem, originating collisions and congestion of packets in the network. A probabilistic broadcasting is one of the widely used broadcasting scheme for route discovery in MANETs and provides solution for broadcasting storm problem. But it does not consider limited energy of the battery of the nodes. In this paper, a new energy efficient probabilistic broadcasting (EEPB) is proposed in which probability of broadcasting RREQs is calculated with respect to remaining energy of nodes. The analysis of simulation results clearly indicate that an EEPB route discovery scheme in ad-hoc on demand distance vector (AODV) can increase the network lifetime with a decrease in the average power consumption and RREQ packet overhead. It also decreases the number of dropped packets in the network, in comparison to other EEPB schemes like energy constraint gossip (ECG), energy aware gossip (EAG), energy based gossip (EBG) and network lifetime through energy efficient broadcast gossip (NEBG).

Safety management of an underground-based gravitational wave telescope: KAGRA

NASA Astrophysics Data System (ADS)

Ohishi, Naoko; Miyoki, Shinji; Uchiyama, Takashi; Miyakawa, Osamu; Ohashi, Masatake

2014-08-01

KAGRA is a unique gravitational wave telescope with its location underground and use of cryogenic mirrors. Safety management plays an important role for secure development and operation of such a unique and large facility. Based on relevant law in Japan, Labor Standard Act and Industrial Safety and Health Law, various countermeasures are mandated to avoid foreseeable accidents and diseases. In addition to the usual safety management of hazardous materials, such as cranes, organic solvents, lasers, there are specific safety issues in the tunnel. Prevention of collapse, flood, and fire accidents are the most critical issues for the underground facility. Ventilation is also important for prevention of air pollution by carbon monoxide, carbon dioxide, organic solvents and radon. Oxygen deficiency should also be prevented.

APSIC Guidelines for environmental cleaning and decontamination.

PubMed

Ling, Moi Lin; Apisarnthanarak, Anucha; Thu, Le Thi Anh; Villanueva, Victoria; Pandjaitan, Costy; Yusof, Mohamad Yasim

2015-01-01

This document is an executive summary of APSIC Guidelines for Environmental Cleaning and Decontamination. It describes best practices in routine cleaning and decontamination in healthcare facilities as well as in specific settings e.g. management of patients with isolation precautions, food preparation areas, construction and renovation, and following a flood. It recommends the implementation of environmental hygiene program to keep the environment safe for patients, staff and visitors visiting a healthcare facility. Objective assessment of cleanliness and quality is an essential component of this program as a method for identifying quality improvement opportunities. Recommendations for safe handling of linen and bedding; as well as occupational health and safety issues are included in the guidelines. A training program is vital to ensure consistent adherence to best practices.

Flood elevations for the Soleduck River at Sol Duc Hot Springs, Clallam County, Washington

USGS Publications Warehouse

Nelson, L.M.

1983-01-01

Elevations and inundation areas of a 100-year flood of the Soleduck River, Washington, were determined by the U.S. Geological Survey for the area in the vicinity of the Sol Duc Hot Springs resort, a public facility in the Olympic National Park that under Federal law must be located beyond or protected from damage by a 100-year flood. Results show that most flooding could be eliminated by raising parts of an existing dike. In general, little flood damage is expected, except at the southern end of an undeveloped airstrip that could become inundated and hazardous due to flow from a tributary. The airstrip is above the 100-year flood of the Soleduck River.

A Methodology to Support Decision Making in Flood Plan Mitigation

NASA Astrophysics Data System (ADS)

Biscarini, C.; di Francesco, S.; Manciola, P.

2009-04-01

The focus of the present document is on specific decision-making aspects of flood risk analysis. A flood is the result of runoff from rainfall in quantities too great to be confined in the low-water channels of streams. Little can be done to prevent a major flood, but we may be able to minimize damage within the flood plain of the river. This broad definition encompasses many possible mitigation measures. Floodplain management considers the integrated view of all engineering, nonstructural, and administrative measures for managing (minimizing) losses due to flooding on a comprehensive scale. The structural measures are the flood-control facilities designed according to flood characteristics and they include reservoirs, diversions, levees or dikes, and channel modifications. Flood-control measures that modify the damage susceptibility of floodplains are usually referred to as nonstructural measures and may require minor engineering works. On the other hand, those measures designed to modify the damage potential of permanent facilities are called non-structural and allow reducing potential damage during a flood event. Technical information is required to support the tasks of problem definition, plan formulation, and plan evaluation. The specific information needed and the related level of detail are dependent on the nature of the problem, the potential solutions, and the sensitivity of the findings to the basic information. Actions performed to set up and lay out the study are preliminary to the detailed analysis. They include: defining the study scope and detail, the field data collection, a review of previous studies and reports, and the assembly of needed maps and surveys. Risk analysis can be viewed as having many components: risk assessment, risk communication and risk management. Risk assessment comprises an analysis of the technical aspects of the problem, risk communication deals with conveying the information and risk management involves the decision process. In the present paper we propose a novel methodology for supporting the priority setting in the assessment of such issues, beyond the typical "expected value" approach. Scientific contribution and management aspects are merged to create a simplified method for plan basin implementation, based on risk and economic analyses. However, the economic evaluation is not the sole criterion for flood-damage reduction plan selection. Among the different criteria that are relevant to the decision process, safety and quality of human life, economic damage, expenses related with the chosen measures and environmental issues should play a fundamental role on the decisions made by the authorities. Some numerical indices, taking in account administrative, technical, economical and risk aspects, are defined and are combined together in a mathematical formula that defines a Priority Index (PI). In particular, the priority index defines a ranking of priority interventions, thus allowing the formulation of the investment plan. The research is mainly focused on the technical factors of risk assessment, providing quantitative and qualitative estimates of possible alternatives, containing measures of the risk associated with those alternatives. Moreover, the issues of risk management are analyzed, in particular with respect to the role of decision making in the presence of risk information. However, a great effort is devoted to make this index easy to be formulated and effective to allow a clear and transparent comparison between the alternatives. Summarizing this document describes a major- steps for incorporation of risk analysis into the decision making process: framing of the problem in terms of risk analysis, application of appropriate tools and techniques to obtain quantified results, use of the quantified results in the choice of structural and non-structural measures. In order to prove the reliability of the proposed methodology and to show how risk-based information can be incorporated into a flood analysis process, its application to some middle italy river basins is presented. The methodology assessment is performed by comparing different scenarios and showing that the optimal decision stems from a feasibility evaluation.

The impact of flooding on people living with HIV: a case study from the Ohangwena Region, Namibia.

PubMed

Anthonj, Carmen; Nkongolo, Odon T; Schmitz, Peter; Hango, Johannes N; Kistemann, Thomas

2015-01-01

Floods are a disaster situation for all affected populations and especially for vulnerable groups within communities such as children, orphans, women, and people with chronic diseases such as HIV and AIDS. They need functioning health care, sanitation and hygiene, safe water, and healthy food supply, and are critically dependent on their social care and support networks. A study carried out in the Ohangwena region, Namibia, where HIV prevalence is high and extensive flooding frequently occurs, aims to provide a deeper understanding of the impact that flooding has on people living with HIV (PLWHIV) as well as on HIV service providers in the region. The qualitative research applying grounded theory included semi-structured interviews with PLWHIV, focus group discussions with HIV service providers, and a national feedback meeting. The findings were interpreted using the sustainable livelihoods framework, the natural hazard research approach, and health behaviour theories. The study reveals that flooding poses major problems to PLWHIV in terms of their everyday lives, affecting livelihoods, work, income, and living conditions. The factors threatening them under normal conditions - poverty, malnutrition, unsafe water, sanitation and hygiene, limited access to health facilities, a weak health status, and stigma - are intensified by flood-related breakdown of infrastructure, insecurity, malnutrition, and diseases evolving over the course of a flood. A potential dual risk exists for their health: the increased risk both of infection and disease due to the inaccessibility of health services and antiretroviral treatment. A HIV and Flooding Framework was developed to display the results. This study demonstrates that vulnerabilities and health risks of PLWHIV will increase in a disaster situation like flooding if access to HIV prevention, treatment, care and support are not addressed and ensured. The findings and the HIV and Flooding Framework are not specific to Ohangwena and can be transferred to any flood-affected region that has a high HIV prevalence and relies mainly on subsistence agriculture. They serve as a model case for analysing vulnerabilities related to health and health service provision under disaster conditions. The impact will vary according to the physical, geographical, climatological, social, and behavioural characteristics of the region and the people affected. In the Ohangwena region, a disaster risk management mechanism is already in place which addresses people with HIV during flooding. However, preparedness could be improved further by applying the HIV and Flooding Framework.

Study on the flood simulation techniques for estimation of health risk in Dhaka city, Bangladesh

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Suetsugi, T.; Sunada, K.; ICRE

2011-12-01

Although some studies have been carried out on the spread of infectious disease with the flooding, the relation between flooding and the infectious expansion has not been clarified yet. The improvement of the calculation precision of inundation and its relation with the infectious disease, surveyed epidemiologically, are therefore investigated in a case study in Dhaka city, Bangladesh. The inundation was computed using a flood simulation model that is numerical 2D-model. The "sensitivity to inundation" of hydraulic factors such as drainage channel, dike, and the building occupied ratio was examined because of the lack of digital data set related to flood simulation. Each element in the flood simulation model was incorporated progressively and results were compared with the calculation result as inspection materials by the inundation classification from the existing study (Mollah et al., 2007). The results show that the influences by ''dyke'' and "drainage channel" factors are remarkable to water level near each facility. The inundation level and duration have influence on wide areas when "building occupied ratio" is also considered. The correlation between maximum inundation depth and health risk (DALY, Mortality, Morbidity) was found, but the validation of the inundation model for this case has not been performed yet. The flood simulation model needs to be validated by observed inundation depth. The drainage facilities such as sewer network or the pumping system will be also considered in the further research to improve the precision of the inundation model.

28 CFR 91.55 - Categorical exclusions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... within or potentially affect any of the following: a 100-year flood plain, a wetland, important farmland... expand facilities that: (1) Are located in a floodplain; (2) Will affect a wetland; (3) Will affect a... correctional agency has contracted with the private vendor to build the facility, operate the facility, or...

Challenges Ahead for Nuclear Facility Site-Specific Seismic Hazard Assessment in France: The Alternative Energies and the Atomic Energy Commission (CEA) Vision

NASA Astrophysics Data System (ADS)

Berge-Thierry, C.; Hollender, F.; Guyonnet-Benaize, C.; Baumont, D.; Ameri, G.; Bollinger, L.

2017-09-01

Seismic analysis in the context of nuclear safety in France is currently guided by a pure deterministic approach based on Basic Safety Rule ( Règle Fondamentale de Sûreté) RFS 2001-01 for seismic hazard assessment, and on the ASN/2/01 Guide that provides design rules for nuclear civil engineering structures. After the 2011 Tohohu earthquake, nuclear operators worldwide were asked to estimate the ability of their facilities to sustain extreme seismic loads. The French licensees then defined the `hard core seismic levels', which are higher than those considered for design or re-assessment of the safety of a facility. These were initially established on a deterministic basis, and they have been finally justified through state-of-the-art probabilistic seismic hazard assessments. The appreciation and propagation of uncertainties when assessing seismic hazard in France have changed considerably over the past 15 years. This evolution provided the motivation for the present article, the objectives of which are threefold: (1) to provide a description of the current practices in France to assess seismic hazard in terms of nuclear safety; (2) to discuss and highlight the sources of uncertainties and their treatment; and (3) to use a specific case study to illustrate how extended source modeling can help to constrain the key assumptions or parameters that impact upon seismic hazard assessment. This article discusses in particular seismic source characterization, strong ground motion prediction, and maximal magnitude constraints, according to the practice of the French Atomic Energy Commission. Due to increases in strong motion databases in terms of the number and quality of the records in their metadata and the uncertainty characterization, several recently published empirical ground motion prediction models are eligible for seismic hazard assessment in France. We show that propagation of epistemic and aleatory uncertainties is feasible in a deterministic approach, as in a probabilistic way. Assessment of seismic hazard in France in the framework of the safety of nuclear facilities should consider these recent advances. In this sense, the opening of discussions with all of the stakeholders in France to update the reference documents (i.e., RFS 2001-01; ASN/2/01 Guide) appears appropriate in the short term.

Flooding and intestinal illness due to Clostridium difficile infection: a case-crossover analysis of Massachusetts data, 2003-2007

EPA Science Inventory

Background. Climate change has contributed to a rise in extreme weather events, including heavier rainfalls. Floods can cause water bodies to overflow, damage water treatment and drinking water infrastructure, overwhelm sewage treatment facilities, and result in discharges of un...

44 CFR 60.22 - Planning considerations for flood-prone areas.

Code of Federal Regulations, 2010 CFR

2010-10-01

... land in relation to the hazards involved, and (iii) does not increase the danger to human life; (2) Prohibit nonessential or improper installation of public utilities and public facilities in flood-prone... public purposes consistent with a policy of minimization of future property losses; (4) Acquisition of...

High pressure gas flow, storage, and displacement in fractured rock—Experimental setup development and application

NASA Astrophysics Data System (ADS)

Hadi Mosleh, M.; Turner, M.; Sedighi, M.; Vardon, P. J.

2017-01-01

This paper presents the design, development, and application of a laboratory setup for the experimental investigations of gas flow and reactions in a fractured rock. The laboratory facility comprises (i) a high pressure manometric sorption apparatus, where equilibrium and kinetic phenomena of adsorption and desorption can be examined, (ii) a high pressure triaxial core flooding system where the chemical reactive transport properties or processes can be explored, and (iii) an ancillary system including pure and mixed gas supply and analysis units. Underground conditions, in terms of pore pressure, confining pressure, and temperature, can be replicated using the triaxial core flooding system developed for depths up to 2 km. Core flooding experiments can be conducted under a range of gas injection pressures up to 20 MPa and temperatures up to 338 K. Details of the design considerations and the specification for the critical measuring instruments are described. The newly developed laboratory facility has been applied to study the adsorption of N2, CH4, and CO2 relevant to applications in carbon sequestration in coal and enhanced coalbed methane recovery. Under a wide range of pressures, the flow of helium in a core sample was studied and the evolution of absolute permeability at different effective stress conditions has been investigated. A comprehensive set of high resolution data has been produced on anthracite coal samples from the South Wales coalfield, using the developed apparatus. The results of the applications provide improved insight into the high pressure flow and reaction of various gas species in the coal samples from the South Wales coalfield.

Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans

NASA Astrophysics Data System (ADS)

Wong, Tony E.; Keller, Klaus

2017-10-01

Future sea-level rise drives severe risks for many coastal communities. Strategies to manage these risks hinge on a sound characterization of the uncertainties. For example, recent studies suggest that large fractions of the Antarctic ice sheet (AIS) may rapidly disintegrate in response to rising global temperatures, leading to potentially several meters of sea-level rise during the next few centuries. It is deeply uncertain, for example, whether such an AIS disintegration will be triggered, how much this would increase sea-level rise, whether extreme storm surges intensify in a warming climate, or which emissions pathway future societies will choose. Here, we assess the impacts of these deep uncertainties on projected flooding probabilities for a levee ring in New Orleans, LA. We use 18 scenarios, presenting probabilistic projections within each one, to sample key deeply uncertain future projections of sea-level rise, radiative forcing pathways, storm surge characterization, and contributions from rapid AIS mass loss. The implications of these deep uncertainties for projected flood risk are thus characterized by a set of 18 probability distribution functions. We use a global sensitivity analysis to assess which mechanisms contribute to uncertainty in projected flood risk over the course of a 50-year design life. In line with previous work, we find that the uncertain storm surge drives the most substantial risk, followed by general AIS dynamics, in our simple model for future flood risk for New Orleans.

Using cost-benefit concepts in design floods improves communication of uncertainty

NASA Astrophysics Data System (ADS)

Ganora, Daniele; Botto, Anna; Laio, Francesco; Claps, Pierluigi

2017-04-01

Flood frequency analysis, i.e. the study of the relationships between the magnitude and the rarity of high flows in a river, is the usual procedure adopted to assess flood hazard, preliminary to the plan/design of flood protection measures. It grounds on the fit of a probability distribution to the peak discharge values recorded in gauging stations and the final estimates over a region are thus affected by uncertainty, due to the limited sample availability and of the possible alternatives in terms of the probabilistic model and the parameter estimation methods used. In the last decade, the scientific community dealt with this issue by developing a number of methods to quantify such uncertainty components. Usually, uncertainty is visually represented through confidence bands, which are easy to understand, but are not yet demonstrated to be useful for design purposes: they usually disorient decision makers, as the design flood is no longer univocally defined, making the decision process undetermined. These considerations motivated the development of the uncertainty-compliant design flood estimator (UNCODE) procedure (Botto et al., 2014) that allows one to select meaningful flood design values accounting for the associated uncertainty by considering additional constraints based on cost-benefit criteria. This method suggests an explicit multiplication factor that corrects the traditional (without uncertainty) design flood estimates to incorporate the effects of uncertainty in the estimate at the same safety level. Even though the UNCODE method was developed for design purposes, it can represent a powerful and robust tool to help clarifying the effects of the uncertainty in statistical estimation. As the process produces increased design flood estimates, this outcome demonstrates how uncertainty leads to more expensive flood protection measures, or insufficiency of current defenses. Moreover, the UNCODE approach can be used to assess the "value" of data, as the costs of flood prevention can get down by reducing uncertainty with longer observed flood records. As the multiplication factor is dimensionless, some examples of application provided show how this approach allows simple comparisons of the effects of uncertainty in different catchments, helping to build ranking procedures for planning purposes. REFERENCES Botto, A., Ganora, D., Laio, F., and Claps, P.: Uncertainty compliant design flood estimation, Water Resources Research, 50, doi:10.1002/2013WR014981, 2014.

Evaluating sub-seasonal skill in probabilistic forecasts of Atmospheric Rivers and associated extreme events

NASA Astrophysics Data System (ADS)

Subramanian, A. C.; Lavers, D.; Matsueda, M.; Shukla, S.; Cayan, D. R.; Ralph, M.

2017-12-01

Atmospheric rivers (ARs) - elongated plumes of intense moisture transport - are a primary source of hydrological extremes, water resources and impactful weather along the West Coast of North America and Europe. There is strong demand in the water management, societal infrastructure and humanitarian sectors for reliable sub-seasonal forecasts, particularly of extreme events, such as floods and droughts so that actions to mitigate disastrous impacts can be taken with sufficient lead-time. Many recent studies have shown that ARs in the Pacific and the Atlantic are modulated by large-scale modes of climate variability. Leveraging the improved understanding of how these large-scale climate modes modulate the ARs in these two basins, we use the state-of-the-art multi-model forecast systems such as the North American Multi-Model Ensemble (NMME) and the Subseasonal-to-Seasonal (S2S) database to help inform and assess the probabilistic prediction of ARs and related extreme weather events over the North American and European West Coasts. We will present results from evaluating probabilistic forecasts of extreme precipitation and AR activity at the sub-seasonal scale. In particular, results from the comparison of two winters (2015-16 and 2016-17) will be shown, winters which defied canonical El Niño teleconnection patterns over North America and Europe. We further extend this study to analyze probabilistic forecast skill of AR events in these two basins and the variability in forecast skill during certain regimes of large-scale climate modes.

Potential advantages associated with implementing a risk-based inspection program by a nuclear facility

NASA Astrophysics Data System (ADS)

McNeill, Alexander, III; Balkey, Kenneth R.

1995-05-01

The current inservice inspection activities at a U.S. nuclear facility are based upon the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code, Section XI. The Code selects examination locations based upon a sampling criteria which includes component geometry, stress, and usage among other criteria. This can result in a significant number of required examinations. As a result of regulatory action each nuclear facility has conducted probabilistic risk assessments (PRA) or individual plant examinations (IPE), producing plant specific risk-based information. Several initiatives have been introduced to apply this new plant risk information. Among these initiatives is risk-based inservice inspection. A code case has been introduced for piping inspections based upon this new risk- based technology. This effort brought forward to the ASME Section XI Code committee, has been initiated and championed by the ASME Research Task Force on Risk-Based Inspection Guidelines -- LWR Nuclear Power Plant Application. Preliminary assessments associated with the code case have revealed that potential advantages exist in a risk-based inservice inspection program with regard to a number of exams, risk, personnel exposure, and cost.

Automating Flood Hazard Mapping Methods for Near Real-time Storm Surge Inundation and Vulnerability Assessment

NASA Astrophysics Data System (ADS)

Weigel, A. M.; Griffin, R.; Gallagher, D.

2015-12-01

Storm surge has enough destructive power to damage buildings and infrastructure, erode beaches, and threaten human life across large geographic areas, hence posing the greatest threat of all the hurricane hazards. The United States Gulf of Mexico has proven vulnerable to hurricanes as it has been hit by some of the most destructive hurricanes on record. With projected rises in sea level and increases in hurricane activity, there is a need to better understand the associated risks for disaster mitigation, preparedness, and response. GIS has become a critical tool in enhancing disaster planning, risk assessment, and emergency response by communicating spatial information through a multi-layer approach. However, there is a need for a near real-time method of identifying areas with a high risk of being impacted by storm surge. Research was conducted alongside Baron, a private industry weather enterprise, to facilitate automated modeling and visualization of storm surge inundation and vulnerability on a near real-time basis. This research successfully automated current flood hazard mapping techniques using a GIS framework written in a Python programming environment, and displayed resulting data through an Application Program Interface (API). Data used for this methodology included high resolution topography, NOAA Probabilistic Surge model outputs parsed from Rich Site Summary (RSS) feeds, and the NOAA Census tract level Social Vulnerability Index (SoVI). The development process required extensive data processing and management to provide high resolution visualizations of potential flooding and population vulnerability in a timely manner. The accuracy of the developed methodology was assessed using Hurricane Isaac as a case study, which through a USGS and NOAA partnership, contained ample data for statistical analysis. This research successfully created a fully automated, near real-time method for mapping high resolution storm surge inundation and vulnerability for the Gulf of Mexico, and improved the accuracy and resolution of the Probabilistic Storm Surge model.

Cognitive Development Effects of Teaching Probabilistic Decision Making to Middle School Students

ERIC Educational Resources Information Center

Mjelde, James W.; Litzenberg, Kerry K.; Lindner, James R.

2011-01-01

This study investigated the comprehension and effectiveness of teaching formal, probabilistic decision-making skills to middle school students. Two specific objectives were to determine (1) if middle school students can comprehend a probabilistic decision-making approach, and (2) if exposure to the modeling approaches improves middle school…

Generative Topic Modeling in Image Data Mining and Bioinformatics Studies

ERIC Educational Resources Information Center

Chen, Xin

2012-01-01

Probabilistic topic models have been developed for applications in various domains such as text mining, information retrieval and computer vision and bioinformatics domain. In this thesis, we focus on developing novel probabilistic topic models for image mining and bioinformatics studies. Specifically, a probabilistic topic-connection (PTC) model…

Probabilistic cost-benefit analysis of disaster risk management in a development context.

PubMed

Kull, Daniel; Mechler, Reinhard; Hochrainer-Stigler, Stefan

2013-07-01

Limited studies have shown that disaster risk management (DRM) can be cost-efficient in a development context. Cost-benefit analysis (CBA) is an evaluation tool to analyse economic efficiency. This research introduces quantitative, stochastic CBA frameworks and applies them in case studies of flood and drought risk reduction in India and Pakistan, while also incorporating projected climate change impacts. DRM interventions are shown to be economically efficient, with integrated approaches more cost-effective and robust than singular interventions. The paper highlights that CBA can be a useful tool if certain issues are considered properly, including: complexities in estimating risk; data dependency of results; negative effects of interventions; and distributional aspects. The design and process of CBA must take into account specific objectives, available information, resources, and the perceptions and needs of stakeholders as transparently as possible. Intervention design and uncertainties should be qualified through dialogue, indicating that process is as important as numerical results. © 2013 The Author(s). Journal compilation © Overseas Development Institute, 2013.

Joint projections of sea level and storm surge using a flood index

NASA Astrophysics Data System (ADS)

Little, C. M.; Lin, N.; Horton, R. M.; Kopp, R. E.; Oppenheimer, M.

2016-02-01

Capturing the joint influence of sea level rise (SLR) and tropical cyclones (TCs) on future coastal flood risk poses significant challenges. To address these difficulties, Little et al. (2015) use a proxy of tropical cyclone activity and a probabilistic flood index that aggregates flood height and duration over a wide area (the US East and Gulf coasts). This technique illuminates the individual impacts of TCs and SLR and their correlation across different coupled climate models. By 2080-2099, changes in the flood index relative to 1986-2005 are substantial and positively skewed: a 10th-90th percentile range of 35-350x higher for a high-end business-as-usual emissions scenario (see figure). This aggregated flood index: 1) is a means to consistently combine TC-driven storm surges and SLR; 2) provides a more robust description of historical surge-climate relationships than is available at any one location; and 3) allows the incorporation of a larger climate model ensemble - which is critical to uncertainty characterization. It does not provide a local view of the complete spectrum of flood severity (i.e. return curves). However, alternate techniques that provide localized return curves (e.g. Lin et al., 2012) are computationally intensive, limiting the set of large-scale climate models that can be incorporated, and require several linked statistical and dynamical models, each with structural uncertainties that are difficult to quantify. Here, we present the results of Little et al. (2015) along with: 1) alternate formulations of the flood index; 2) strategies to localize the flood index; and 3) a comparison of flood index projections to those provided by model-based return curves. We look to this interdisciplinary audience for feedback on the advantages and disadvantages of each tool for coastal planning and decision-making. Lin, N., K. Emanuel, M. Oppenheimer, and E. Vanmarcke, 2012: Physically based assessment of hurricane surge threat under climate change. Nature Clim. Change, 2(6), 462-467. Little, C. M., R. M. Horton, R. E. Kopp, M. Oppenheimer, G. A. Vecchi, and G. Villarini, 2015: Joint projections of us east coast sea level and storm surge. Nature Clim. Change, advance online publication.

Advanced Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Technical Exchange Meeting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Curtis

2013-09-01

During FY13, the INL developed an advanced SMR PRA framework which has been described in the report Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Detailed Technical Framework Specification, INL/EXT-13-28974 (April 2013). In this framework, the various areas are considered: Probabilistic models to provide information specific to advanced SMRs Representation of specific SMR design issues such as having co-located modules and passive safety features Use of modern open-source and readily available analysis methods Internal and external events resulting in impacts to safety All-hazards considerations Methods to support the identification of design vulnerabilities Mechanistic and probabilistic data needs to support modelingmore » and tools In order to describe this framework more fully and obtain feedback on the proposed approaches, the INL hosted a technical exchange meeting during August 2013. This report describes the outcomes of that meeting.« less

floodX: urban flash flood experiments monitored with conventional and alternative sensors

NASA Astrophysics Data System (ADS)

Moy de Vitry, Matthew; Dicht, Simon; Leitão, João P.

2017-09-01

The data sets described in this paper provide a basis for developing and testing new methods for monitoring and modelling urban pluvial flash floods. Pluvial flash floods are a growing hazard to property and inhabitants' well-being in urban areas. However, the lack of appropriate data collection methods is often cited as an impediment for reliable flood modelling, thereby hindering the improvement of flood risk mapping and early warning systems. The potential of surveillance infrastructure and social media is starting to draw attention for this purpose. In the floodX project, 22 controlled urban flash floods were generated in a flood response training facility and monitored with state-of-the-art sensors as well as standard surveillance cameras. With these data, it is possible to explore the use of video data and computer vision for urban flood monitoring and modelling. The floodX project stands out as the largest documented flood experiment of its kind, providing both conventional measurements and video data in parallel and at high temporal resolution. The data set used in this paper is available at https://doi.org/10.5281/zenodo.830513.

Remote Sensing and River Discharge Forecasting for Major Rivers in South Asia (Invited)

NASA Astrophysics Data System (ADS)

Webster, P. J.; Hopson, T. M.; Hirpa, F. A.; Brakenridge, G. R.; De-Groeve, T.; Shrestha, K.; Gebremichael, M.; Restrepo, P. J.

2013-12-01

The South Asia is a flashpoint for natural disasters particularly flooding of the Indus, Ganges, and Brahmaputra has profound societal impacts for the region and globally. The 2007 Brahmaputra floods affecting India and Bangladesh, the 2008 avulsion of the Kosi River in India, the 2010 flooding of the Indus River in Pakistan and the 2013 Uttarakhand exemplify disasters on scales almost inconceivable elsewhere. Their frequent occurrence of floods combined with large and rapidly growing populations, high levels of poverty and low resilience, exacerbate the impact of the hazards. Mitigation of these devastating hazards are compounded by limited flood forecast capability, lack of rain/gauge measuring stations and forecast use within and outside the country, and transboundary data sharing on natural hazards. Here, we demonstrate the utility of remotely-derived hydrologic and weather products in producing skillful flood forecasting information without reliance on vulnerable in situ data sources. Over the last decade a forecast system has been providing operational probabilistic forecasts of severe flooding of the Brahmaputra and Ganges Rivers in Bangldesh was developed (Hopson and Webster 2010). The system utilizes ECMWF weather forecast uncertainty information and ensemble weather forecasts, rain gauge and satellite-derived precipitation estimates, together with the limited near-real-time river stage observations from Bangladesh. This system has been expanded to Pakistan and has successfully forecast the 2010-2012 flooding (Shrestha and Webster 2013). To overcome the in situ hydrological data problem, recent efforts in parallel with the numerical modeling have utilized microwave satellite remote sensing of river widths to generate operational discharge advective-based forecasts for the Ganges and Brahmaputra. More than twenty remotely locations upstream of Bangldesh were used to produce stand-alone river flow nowcasts and forecasts at 1-15 days lead time. showing that satellite-based flow estimates are a useful source of dynamical surface water information in data-scarce regions and that they could be used for model calibration and data assimilation purposes in near-time hydrologic forecast applications (Hirpa et al. 2013). More recent efforts during this year's monsoon season are optimally combining these different independent sources of river forecast information along with archived flood inundation imagery of the Dartmouth Flood Observatory to improve the visualization and overall skill of the ongoing CFAB ensemble weather forecast-based flood forecasting system within the unique context of the ongoing flood forecasting efforts for Bangladesh.

A probabilistic storm surge risk model for the German North Sea and Baltic Sea coast

NASA Astrophysics Data System (ADS)

Grabbert, Jan-Henrik; Reiner, Andreas; Deepen, Jan; Rodda, Harvey; Mai, Stephan; Pfeifer, Dietmar

2010-05-01

The German North Sea coast is highly exposed to storm surges. Due to its concave bay-like shape mainly orientated to the North-West, cyclones from Western, North-Western and Northern directions together with astronomical tide cause storm surges accumulating the water in the German bight. Due to the existence of widespread low-lying areas (below 5m above mean sea level) behind the defenses, large areas including large economic values are exposed to coastal flooding including cities like Hamburg or Bremen. The occurrence of extreme storm surges in the past like e.g. in 1962 taking about 300 lives and causing widespread flooding and 1976 raised the awareness and led to a redesign of the coastal defenses which provide a good level of protection for today's conditions. Never the less the risk of flooding exists. Moreover an amplification of storm surge risk can be expected under the influence of climate change. The Baltic Sea coast is also exposed to storm surges, which are caused by other meteorological patterns. The influence of the astronomical tide is quite low instead high water levels are induced by strong winds only. Since the exceptional extreme event in 1872 storm surge hazard has been more or less forgotten. Although such an event is very unlikely to happen, it is not impossible. Storm surge risk is currently (almost) non-insurable in Germany. The potential risk is difficult to quantify as there are almost no historical losses available. Also premiums are difficult to assess. Therefore a new storm surge risk model is being developed to provide a basis for a probabilistic quantification of potential losses from coastal inundation. The model is funded by the GDV (German Insurance Association) and is planned to be used within the German insurance sector. Results might be used for a discussion of insurance cover for storm surge. The model consists of a probabilistic event driven hazard and a vulnerability module, furthermore an exposure interface and a financial module to account for specific (re-) insurance conditions. This contribution will mainly concentrate on the hazard module. The hazard is covered by an event simulation engine enabling Monte Carlo simulations. The event generation is done on-the-fly. A classification of historical storm surges is used based on observed sea water levels at gauging stations and extended literature research. To characterize the origin of storm events and storm surges caused by those, also meteorological parameters like wind speed and wind direction are being used. If high water levels along the coast are mainly caused by strong wind from particular directions as observed at the North Sea, there is a clear empirical relationship between wind and surge (where surge is defined as the wind-driven component of the sea water level) which can be described by the ATWS (Average Transformed Wind speed). The parameters forming the load at the coastal defense elements are water level and wave parameters like significant wave height, wave period and wave direction. To assess the wave characteristics at the coast the numerical model SWAN (Simulating Waves Near Shore) from TU Delft has been used. To account for different probabilities of failure and inundation the coast is split into segments with similar defense characteristics like type of defense, height, width, orientation and others. The chosen approach covers the most relevant failure mechanisms for coastal dikes induced by wave overtopping and overflow. Dune failure is also considered in the model. Inundation of the hinterland after defense failure is modeled using a simple dynamical 2d-approach resulting in distributed water depths and flood outlines for each segment. Losses can be estimated depending on the input exposure data either coordinate based for single buildings or aggregated on postal code level using a set of depths-damage functions.

Interim Reliability Evaluation Program: analysis of the Browns Ferry, Unit 1, nuclear plant. Main report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mays, S.E.; Poloski, J.P.; Sullivan, W.H.

1982-07-01

A probabilistic risk assessment (PRA) was made of the Browns Ferry, Unit 1, nuclear plant as part of the Nuclear Regulatory Commission's Interim Reliability Evaluation Program (IREP). Specific goals of the study were to identify the dominant contributors to core melt, develop a foundation for more extensive use of PRA methods, expand the cadre of experienced PRA practitioners, and apply procedures for extension of IREP analyses to other domestic light water reactors. Event tree and fault tree analyses were used to estimate the frequency of accident sequences initiated by transients and loss of coolant accidents. External events such as floods,more » fires, earthquakes, and sabotage were beyond the scope of this study and were, therefore, excluded. From these sequences, the dominant contributors to probable core melt frequency were chosen. Uncertainty and sensitivity analyses were performed on these sequences to better understand the limitations associated with the estimated sequence frequencies. Dominant sequences were grouped according to common containment failure modes and corresponding release categories on the basis of comparison with analyses of similar designs rather than on the basis of detailed plant-specific calculations.« less

Derivation of flood frequency curves in poorly gauged Mediterranean catchments using a simple stochastic hydrological rainfall-runoff model

NASA Astrophysics Data System (ADS)

Aronica, G. T.; Candela, A.

2007-12-01

SummaryIn this paper a Monte Carlo procedure for deriving frequency distributions of peak flows using a semi-distributed stochastic rainfall-runoff model is presented. The rainfall-runoff model here used is very simple one, with a limited number of parameters and practically does not require any calibration, resulting in a robust tool for those catchments which are partially or poorly gauged. The procedure is based on three modules: a stochastic rainfall generator module, a hydrologic loss module and a flood routing module. In the rainfall generator module the rainfall storm, i.e. the maximum rainfall depth for a fixed duration, is assumed to follow the two components extreme value (TCEV) distribution whose parameters have been estimated at regional scale for Sicily. The catchment response has been modelled by using the Soil Conservation Service-Curve Number (SCS-CN) method, in a semi-distributed form, for the transformation of total rainfall to effective rainfall and simple form of IUH for the flood routing. Here, SCS-CN method is implemented in probabilistic form with respect to prior-to-storm conditions, allowing to relax the classical iso-frequency assumption between rainfall and peak flow. The procedure is tested on six practical case studies where synthetic FFC (flood frequency curve) were obtained starting from model variables distributions by simulating 5000 flood events combining 5000 values of total rainfall depth for the storm duration and AMC (antecedent moisture conditions) conditions. The application of this procedure showed how Monte Carlo simulation technique can reproduce the observed flood frequency curves with reasonable accuracy over a wide range of return periods using a simple and parsimonious approach, limited data input and without any calibration of the rainfall-runoff model.

Towards flash-flood prediction in the dry Dead Sea region utilizing radar rainfall information

NASA Astrophysics Data System (ADS)

Morin, Efrat; Jacoby, Yael; Navon, Shilo; Bet-Halachmi, Erez

2009-07-01

Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. This paper presents a flash-flood warning model which utilizes radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipitation estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on the 5 years of data for one of the catchments. Validation was performed for a subsequent 5-year period for the same catchment and then for an entire 10-year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood warning model is feasible for catchments in the area studied.

Towards flash flood prediction in the dry Dead Sea region utilizing radar rainfall information

NASA Astrophysics Data System (ADS)

Morin, E.; Jacoby, Y.; Navon, S.; Bet-Halachmi, E.

2009-04-01

Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. This paper presents a flash-flood warning model utilizing radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipitation estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on five years of data for one of the catchments. Validation was performed for a subsequent five-year period for the same catchment and then for an entire ten year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood-warning model is feasible for catchments in the area studied.

A pan-African medium-range ensemble flood forecast system

NASA Astrophysics Data System (ADS)

Thiemig, Vera; Bisselink, Bernard; Pappenberger, Florian; Thielen, Jutta

2015-04-01

The African Flood Forecasting System (AFFS) is a probabilistic flood forecast system for medium- to large-scale African river basins, with lead times of up to 15 days. The key components are the hydrological model LISFLOOD, the African GIS database, the meteorological ensemble predictions of the ECMWF and critical hydrological thresholds. In this study the predictive capability is investigated, to estimate AFFS' potential as an operational flood forecasting system for the whole of Africa. This is done in a hindcast mode, by reproducing pan-African hydrological predictions for the whole year of 2003 where important flood events were observed. Results were analysed in two ways, each with its individual objective. The first part of the analysis is of paramount importance for the assessment of AFFS as a flood forecasting system, as it focuses on the detection and prediction of flood events. Here, results were verified with reports of various flood archives such as Dartmouth Flood Observatory, the Emergency Event Database, the NASA Earth Observatory and Reliefweb. The number of hits, false alerts and missed alerts as well as the Probability of Detection, False Alarm Rate and Critical Success Index were determined for various conditions (different regions, flood durations, average amount of annual precipitations, size of affected areas and mean annual discharge). The second part of the analysis complements the first by giving a basic insight into the prediction skill of the general streamflow. For this, hydrological predictions were compared against observations at 36 key locations across Africa and the Continuous Rank Probability Skill Score (CRPSS), the limit of predictability and reliability were calculated. Results showed that AFFS detected around 70 % of the reported flood events correctly. In particular, the system showed good performance in predicting riverine flood events of long duration (> 1 week) and large affected areas (> 10 000 km2) well in advance, whereas AFFS showed limitations for small-scale and short duration flood events. Also the forecasts showed on average a good reliability, and the CRPSS helped identifying regions to focus on for future improvements. The case study for the flood event in March 2003 in the Sabi Basin (Zimbabwe and Mozambique) illustrated the good performance of AFFS in forecasting timing and severity of the floods, gave an example of the clear and concise output products, and showed that the system is capable of producing flood warnings even in ungauged river basins. Hence, from a technical perspective, AFFS shows a good prospective as an operational system, as it has demonstrated its significant potential to contribute to the reduction of flood-related losses in Africa by providing national and international aid organizations timely with medium-range flood forecast information. However, issues related to the practical implication will still need to be investigated.

Application of probabilistic analysis/design methods in space programs - The approaches, the status, and the needs

NASA Technical Reports Server (NTRS)

Ryan, Robert S.; Townsend, John S.

1993-01-01

The prospective improvement of probabilistic methods for space program analysis/design entails the further development of theories, codes, and tools which match specific areas of application, the drawing of lessons from previous uses of probability and statistics data bases, the enlargement of data bases (especially in the field of structural failures), and the education of engineers and managers on the advantages of these methods. An evaluation is presently made of the current limitations of probabilistic engineering methods. Recommendations are made for specific applications.

The Study on Flood Reduction and Securing Instreamflow by applying Decentralized Rainwater Retention Facilities for Chunggyechun in Seoul of Korea

NASA Astrophysics Data System (ADS)

Park, J. H.; Jun, S. M.; Park, C. G.

2014-12-01

Recently abnormal climate phenomena and urbanization recently causes the changes of the hydrological environment. To restore the hydrological cycle in urban area some fundamental solutions such as decentralized rainwater management system and Low Impact Development (LID) techniques may be choosed. In this study, SWMM 5 was used to analyze the effects of decentralized stormwater retention for preventing the urban flood and securing the instreamflow. The Chunggyechun stream watershed(21.29㎢) which is located in Seoul city(Korea) and fully developed as urban area was selected as the study watershed, and the runoff characteristics of urban stream with various methods of LID techniques (Permeable pavement, small rainwater storage tank, large rainwater storage tank) were analyzed. By the simulation results, the permeability of pavement materials and detention storage at the surface soil layer make high effect to the flood discharge, and the initial rainfall retention at the rainwater storage tank effected to reduce the flood peak. The peak discharge was decreased as 22% for the design precipitation. Moreover the instreamflow was increased as 55% by using adequate LID techniques These kind of data could be used as the basis data for designing urban flood prevention facilities, urban regeneration planning in the view of the integrated watershed management.

Technical evaluation of the susceptibility of safety-related systems to flooding caused by the failure of non-Category I systems for Turkey Point Nuclear Power Plant, Units 3 and 4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collins, E.K.

1979-08-01

Three separate reviews of the Turkey Point Units 3 and 4 were conducted by the FPLCO between 1972 and 1975. Initially, at the request of NBC in 1972, the FPLCO reviewed several water systems as sources of flooding. Subsequently, as a result of an abnormal occurrence, the drainage system was reviewed. Finally, the facilities were again reviewed at NRC's request and both the potential sources of flooding and safety-related equipment which could be damaged by flooding were identified. The sources of flooding and the appropriate safety equipment are discussed. An evaluation is presented of measures that were taken by FPLCOmore » to minimize the danger of flooding and to protect safety-related equipment.« less

Improving the effectiveness of real-time flood forecasting through Predictive Uncertainty estimation: the multi-temporal approach

NASA Astrophysics Data System (ADS)

Barbetta, Silvia; Coccia, Gabriele; Moramarco, Tommaso; Todini, Ezio

2015-04-01

The negative effects of severe flood events are usually contrasted through structural measures that, however, do not fully eliminate flood risk. Non-structural measures, such as real-time flood forecasting and warning, are also required. Accurate stage/discharge future predictions with appropriate forecast lead-time are sought by decision-makers for implementing strategies to mitigate the adverse effects of floods. Traditionally, flood forecasting has been approached by using rainfall-runoff and/or flood routing modelling. Indeed, both types of forecasts, cannot be considered perfectly representing future outcomes because of lacking of a complete knowledge of involved processes (Todini, 2004). Nonetheless, although aware that model forecasts are not perfectly representing future outcomes, decision makers are de facto implicitly assuming the forecast of water level/discharge/volume, etc. as "deterministic" and coinciding with what is going to occur. Recently the concept of Predictive Uncertainty (PU) was introduced in hydrology (Krzysztofowicz, 1999), and several uncertainty processors were developed (Todini, 2008). PU is defined as the probability of occurrence of the future realization of a predictand (water level/discharge/volume) conditional on: i) prior observations and knowledge, ii) the available information obtained on the future value, typically provided by one or more forecast models. Unfortunately, PU has been frequently interpreted as a measure of lack of accuracy rather than the appropriate tool allowing to take the most appropriate decisions, given a model or several models' forecasts. With the aim to shed light on the benefits for appropriately using PU, a multi-temporal approach based on the MCP approach (Todini, 2008; Coccia and Todini, 2011) is here applied to stage forecasts at sites along the Upper Tiber River. Specifically, the STAge Forecasting-Rating Curve Model Muskingum-based (STAFOM-RCM) (Barbetta et al., 2014) along with the Rating-Curve Model in Real Time (RCM-RT) (Barbetta and Moramarco, 2014) are used to this end. Both models without considering rainfall information explicitly considers, at each time of forecast, the estimate of lateral contribution along the river reach for which the stage forecast is performed at downstream end. The analysis is performed for several reaches using different lead times according to the channel length. Barbetta, S., Moramarco, T., Brocca, L., Franchini, M. and Melone, F. 2014. Confidence interval of real-time forecast stages provided by the STAFOM-RCM model: the case study of the Tiber River (Italy). Hydrological Processes, 28(3),729-743. Barbetta, S. and Moramarco, T. 2014. Real-time flood forecasting by relating local stage and remote discharge. Hydrological Sciences Journal, 59(9 ), 1656-1674. Coccia, G. and Todini, E. 2011. Recent developments in predictive uncertainty assessment based on the Model Conditional Processor approach. Hydrology and Earth System Sciences, 15, 3253-3274. doi:10.5194/hess-15-3253-2011. Krzysztofowicz, R. 1999. Bayesian theory of probabilistic forecasting via deterministic hydrologic model, Water Resour. Res., 35, 2739-2750. Todini, E. 2004. Role and treatment of uncertainty in real-time flood forecasting. Hydrological Processes 18(14), 2743_2746. Todini, E. 2008. A model conditional processor to assess predictive uncertainty in flood forecasting. Intl. J. River Basin Management, 6(2): 123-137.

Environmental overview and hydrogeologic conditions at Aniak, Alaska

USGS Publications Warehouse

Dorava, J.M.

1994-01-01

The remote Native village of Aniak, on the flood plain of the Kuskokwim River in southwestern Alaska, has long cold winters and short summers that affect both the hydrology of the area and the lifestyle of the residents. Aniak obtains its drinking water from a shallow aquifer in the thick alluvium underlying the village. Surface spills and disposal of hazardous materials combined with annual flooding of the Kuskokwim River may affect the quality of the ground water. Alternative drinking water sources are available but at significantly greater cost than existing supplies. The Federal Aviation Administration (FAA) owns or operates airport support facilities in Aniak. The subsistence lifestyle of the villagers and the quality of the current environment must be taken into consideration when the FAA evaluates options for remediation of environmental contamination at these facilities. This report describes the ground- and surface-water hydrology, geology, climate, vegetation, soils, and flood potential of the areas surrounding the FAA sites.

76 FR 70768 - Biweekly Notice; Applications and Amendments to Facility Operating Licenses Involving No...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-15

... perform a probabilistic risk evaluation using the guidance contained in NRC approved NEI [Nuclear Energy... Issue Summary 2003-18, Supplement 2, ``Use of Nuclear Energy Institute (NEI) 99-01, Methodology for...

A Probabilistic, Facility-Centric Approach to Lightning Strike Location

NASA Technical Reports Server (NTRS)

Huddleston, Lisa L.; Roeder, William p.; Merceret, Francis J.

2012-01-01

A new probabilistic facility-centric approach to lightning strike location has been developed. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even with the location error ellipse. This technique is adapted from a method of calculating the probability of debris collisionith spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force Station. Future applications could include forensic meteorology.

18 CFR 5.6 - Pre-application document.

Code of Federal Regulations, 2011 CFR

2011-04-01

... project, including any daily or seasonal ramping rates, flushing flows, reservoir operations, and flood... document must describe the existing and proposed (if any) project facilities and operations, provide...)(viii). (2) Project location, facilities, and operations. The potential applicant must include in the...

Modelling multi-hazard hurricane damages on an urbanized coast with a Bayesian Network approach

USGS Publications Warehouse

van Verseveld, H.C.W.; Van Dongeren, A. R.; Plant, Nathaniel G.; Jäger, W.S.; den Heijer, C.

2015-01-01

Hurricane flood impacts to residential buildings in coastal zones are caused by a number of hazards, such as inundation, overflow currents, erosion, and wave attack. However, traditional hurricane damage models typically make use of stage-damage functions, where the stage is related to flooding depth only. Moreover, these models are deterministic and do not consider the large amount of uncertainty associated with both the processes themselves and with the predictions. This uncertainty becomes increasingly important when multiple hazards (flooding, wave attack, erosion, etc.) are considered simultaneously. This paper focusses on establishing relationships between observed damage and multiple hazard indicators in order to make better probabilistic predictions. The concept consists of (1) determining Local Hazard Indicators (LHIs) from a hindcasted storm with use of a nearshore morphodynamic model, XBeach, and (2) coupling these LHIs and building characteristics to the observed damages. We chose a Bayesian Network approach in order to make this coupling and used the LHIs ‘Inundation depth’, ‘Flow velocity’, ‘Wave attack’, and ‘Scour depth’ to represent flooding, current, wave impacts, and erosion related hazards.The coupled hazard model was tested against four thousand damage observations from a case site at the Rockaway Peninsula, NY, that was impacted by Hurricane Sandy in late October, 2012. The model was able to accurately distinguish ‘Minor damage’ from all other outcomes 95% of the time and could distinguish areas that were affected by the storm, but not severely damaged, 68% of the time. For the most heavily damaged buildings (‘Major Damage’ and ‘Destroyed’), projections of the expected damage underestimated the observed damage. The model demonstrated that including multiple hazards doubled the prediction skill, with Log-Likelihood Ratio test (a measure of improved accuracy and reduction in uncertainty) scores between 0.02 and 0.17 when only one hazard is considered and a score of 0.37 when multiple hazards are considered simultaneously. The LHIs with the most predictive skill were ‘Inundation depth’ and ‘Wave attack’. The Bayesian Network approach has several advantages over the market-standard stage-damage functions: the predictive capacity of multiple indicators can be combined; probabilistic predictions can be obtained, which include uncertainty; and quantitative as well as descriptive information can be used simultaneously.

Assessment of Vulnerability to Extreme Flash Floods in Design Storms

PubMed Central

Kim, Eung Seok; Choi, Hyun Il

2011-01-01

There has been an increase in the occurrence of sudden local flooding of great volume and short duration caused by heavy or excessive rainfall intensity over a small area, which presents the greatest potential danger threat to the natural environment, human life, public health and property, etc. Such flash floods have rapid runoff and debris flow that rises quickly with little or no advance warning to prevent flood damage. This study develops a flash flood index through the average of the same scale relative severity factors quantifying characteristics of hydrographs generated from a rainfall-runoff model for the long-term observed rainfall data in a small ungauged study basin, and presents regression equations between rainfall characteristics and the flash flood index. The aim of this study is to develop flash flood index-duration-frequency relation curves by combining the rainfall intensity-duration-frequency relation and the flash flood index from probability rainfall data in order to evaluate vulnerability to extreme flash floods in design storms. This study is an initial effort to quantify the flash flood severity of design storms for both existing and planned flood control facilities to cope with residual flood risks due to extreme flash floods that have ocurred frequently in recent years. PMID:21845165

Assessment of vulnerability to extreme flash floods in design storms.

PubMed

Kim, Eung Seok; Choi, Hyun Il

2011-07-01

There has been an increase in the occurrence of sudden local flooding of great volume and short duration caused by heavy or excessive rainfall intensity over a small area, which presents the greatest potential danger threat to the natural environment, human life, public health and property, etc. Such flash floods have rapid runoff and debris flow that rises quickly with little or no advance warning to prevent flood damage. This study develops a flash flood index through the average of the same scale relative severity factors quantifying characteristics of hydrographs generated from a rainfall-runoff model for the long-term observed rainfall data in a small ungauged study basin, and presents regression equations between rainfall characteristics and the flash flood index. The aim of this study is to develop flash flood index-duration-frequency relation curves by combining the rainfall intensity-duration-frequency relation and the flash flood index from probability rainfall data in order to evaluate vulnerability to extreme flash floods in design storms. This study is an initial effort to quantify the flash flood severity of design storms for both existing and planned flood control facilities to cope with residual flood risks due to extreme flash floods that have ocurred frequently in recent years.

Probabilistic brain tissue segmentation in neonatal magnetic resonance imaging.

PubMed

Anbeek, Petronella; Vincken, Koen L; Groenendaal, Floris; Koeman, Annemieke; van Osch, Matthias J P; van der Grond, Jeroen

2008-02-01

A fully automated method has been developed for segmentation of four different structures in the neonatal brain: white matter (WM), central gray matter (CEGM), cortical gray matter (COGM), and cerebrospinal fluid (CSF). The segmentation algorithm is based on information from T2-weighted (T2-w) and inversion recovery (IR) scans. The method uses a K nearest neighbor (KNN) classification technique with features derived from spatial information and voxel intensities. Probabilistic segmentations of each tissue type were generated. By applying thresholds on these probability maps, binary segmentations were obtained. These final segmentations were evaluated by comparison with a gold standard. The sensitivity, specificity, and Dice similarity index (SI) were calculated for quantitative validation of the results. High sensitivity and specificity with respect to the gold standard were reached: sensitivity >0.82 and specificity >0.9 for all tissue types. Tissue volumes were calculated from the binary and probabilistic segmentations. The probabilistic segmentation volumes of all tissue types accurately estimated the gold standard volumes. The KNN approach offers valuable ways for neonatal brain segmentation. The probabilistic outcomes provide a useful tool for accurate volume measurements. The described method is based on routine diagnostic magnetic resonance imaging (MRI) and is suitable for large population studies.

Analyzing Future Flooding under Climate Change Scenario using CMIP5 Streamflow Data

NASA Astrophysics Data System (ADS)

Parajuli, Ranjan; Nyaupane, Narayan; Kalra, Ajay

2017-12-01

Flooding is a severe and costlier natural hazard. The effect of climate change has intensified the scenario in recent years. Flood prevention practice along with a proper understanding of flooding event can mitigate the risk of such hazard. The floodplain mapping is one of the technique to quantify the severity of the flooding. Carson City, which is one of the agricultural areas in the desert of Nevada has experienced peak flood in the recent year. The underlying probability distribution for the area, latest Coupled Model Intercomparison Project (CMIP5) streamflow data of Carson River were analyzed for 27 different statistical distributions. The best-fitted distribution underlying was used to forecast the 100yr flood (design flood). The data from 1950-2099 derived from 31 model and total 97 projections were used to predict the future streamflow. Delta change method is adopted to quantify the amount of future (2050-2099) flood. To determine the extent of flooding 3 scenarios (i) historic design flood, (ii) 500yr flood and (iii) future 100yr flood were routed on an HEC-RAS model, prepared using available terrain data. Some of the climate projection shows an extreme increase in future design flood. This study suggests an approach to quantify the future flood and floodplain using climate model projections. The study would provide helpful information to the facility manager, design engineer, and stakeholders.

The impact of flooding on people living with HIV: a case study from the Ohangwena Region, Namibia

PubMed Central

Anthonj, Carmen; Nkongolo, Odon T.; Schmitz, Peter; Hango, Johannes N.; Kistemann, Thomas

2015-01-01

Background Floods are a disaster situation for all affected populations and especially for vulnerable groups within communities such as children, orphans, women, and people with chronic diseases such as HIV and AIDS. They need functioning health care, sanitation and hygiene, safe water, and healthy food supply, and are critically dependent on their social care and support networks. A study carried out in the Ohangwena region, Namibia, where HIV prevalence is high and extensive flooding frequently occurs, aims to provide a deeper understanding of the impact that flooding has on people living with HIV (PLWHIV) as well as on HIV service providers in the region. Design The qualitative research applying grounded theory included semi-structured interviews with PLWHIV, focus group discussions with HIV service providers, and a national feedback meeting. The findings were interpreted using the sustainable livelihoods framework, the natural hazard research approach, and health behaviour theories. Results The study reveals that flooding poses major problems to PLWHIV in terms of their everyday lives, affecting livelihoods, work, income, and living conditions. The factors threatening them under normal conditions – poverty, malnutrition, unsafe water, sanitation and hygiene, limited access to health facilities, a weak health status, and stigma – are intensified by flood-related breakdown of infrastructure, insecurity, malnutrition, and diseases evolving over the course of a flood. A potential dual risk exists for their health: the increased risk both of infection and disease due to the inaccessibility of health services and antiretroviral treatment. A HIV and Flooding Framework was developed to display the results. Conclusions This study demonstrates that vulnerabilities and health risks of PLWHIV will increase in a disaster situation like flooding if access to HIV prevention, treatment, care and support are not addressed and ensured. The findings and the HIV and Flooding Framework are not specific to Ohangwena and can be transferred to any flood-affected region that has a high HIV prevalence and relies mainly on subsistence agriculture. They serve as a model case for analysing vulnerabilities related to health and health service provision under disaster conditions. The impact will vary according to the physical, geographical, climatological, social, and behavioural characteristics of the region and the people affected. In the Ohangwena region, a disaster risk management mechanism is already in place which addresses people with HIV during flooding. However, preparedness could be improved further by applying the HIV and Flooding Framework. PMID:25813771

33 CFR 208.10 - Local flood protection works; maintenance and operation of structures and facilities.

Code of Federal Regulations, 2013 CFR

2013-07-01

... the levee and to repair the damaged section. (c) Flood walls—(1) Maintenance. Periodic inspections... accelerated seepage paths; (iv) The concrete has not undergone cracking, chipping, or breaking to an extent... that no fires are being built near them; (vii) No bank caving conditions exist riverward of the wall...

33 CFR 208.10 - Local flood protection works; maintenance and operation of structures and facilities.

Code of Federal Regulations, 2012 CFR

2012-07-01

... the levee and to repair the damaged section. (c) Flood walls—(1) Maintenance. Periodic inspections... accelerated seepage paths; (iv) The concrete has not undergone cracking, chipping, or breaking to an extent... that no fires are being built near them; (vii) No bank caving conditions exist riverward of the wall...

33 CFR 208.10 - Local flood protection works; maintenance and operation of structures and facilities.

Code of Federal Regulations, 2014 CFR

2014-07-01

... the levee and to repair the damaged section. (c) Flood walls—(1) Maintenance. Periodic inspections... accelerated seepage paths; (iv) The concrete has not undergone cracking, chipping, or breaking to an extent... that no fires are being built near them; (vii) No bank caving conditions exist riverward of the wall...

Saugus River and Tributaries, Lynn Malden, Revere and Saugus, Massachusetts. Flood Damage Reduction. Volume 4. Appendix G. Economics. Appendix H. Socioeconomic.

DTIC Science & Technology

1989-06-01

is not accessible by subway from Boston. Policy guidance for evaluation of recreational facilities for structural flood reduction plans require that...Trapelo Road Waltham, Massachusetts Prepared By: IEP, Inc. P.O. Box 1840 90 Route 6A/Sextant Hill Sandwich , Massachusetts 02563 EPnc. Table of Contents

Towards a detailed knowledge about Mediterranean flash floods and extreme floods in the catchments of Spain, France and Italy

NASA Astrophysics Data System (ADS)

Duband, D.

2009-09-01

It is important to remember that scientific research programs of the European Commission and contributors had implemented a multidisciplinary (geography, history, meteorology, climatology, hydrology, geomorphology, geology, paleohydrology, sociology, economy......) better knowledge and more understanding of the physical risk assessment of disastrous floods (particularly flash floods) with rising factors of vulnerability and perhaps climate change at the end of the XX1 century, in the triangular geographical area Zaragosa (Spain)-Orléans (France)-Firenze (Italy). With reference to historical floods events observed from last two centuries in Spain (Catalonia), France (Languedoc Roussillon - Provence Alpes Cote d’Azur-Corse-Rhone Alpes -Auvergne- Bourgogne) and in Italy (Ligurie - Piemont - Lombardie) we lay particular stress on a detailed understanding of the spatial and temporal scales of the physical dynamic process being at the origin of locals or extensive flash floods. This study requires to be based on the meteorology (atmospheric circulation patterns ,on west Europe- Atlantic and Mediterranean sea) responsible, with relief and sea surface temperature, of high precipitations (amounts, intensities), air temperature, discharges of high floods, observed in the past ,on large and coastal rivers. We will take example of the Rhone river catchments, in connexion with Po-Ebre-Loire-Seine rivers, based on the studies of thirty high historical floods occurred from 1840 to 2005, and characteristics of Oceanic and Mediterranean weather situations, sometime alternated. Since recent years we have the daily mean sea level pressure dataset (EMSLP) reconstructions for European-North Atlantic Region for the period 1850-2006. So it is now possible to allow us the selection in the complete meteorological dataset during 1950- 2009 period by an analog method (like operational daily applications from 1969, at Electricity of France) to select weather situations similar to historical daily situations responsible of extreme floods with larges discharges, with the conditional precipitations associated on catchments with god and up to date observations of precipitations (daily, hourly). This kind of complete studies would be very useful for: -Statistical-physical studies of extreme rainfall-flood events (peak discharge, volume), frequency-probability-uncertainty (GRADEX and SHADEX methodology), -Better forecasting of meteorological (precipitations) and hydrological (floods) events, during crisis situations, -better understanding of the historical variability in the past 2 centuries (atmospheric features, precipitations, discharges high/low), -Better adjustment of modelling simulation, -Better identification and probabilistic approach of uncertainties.

Combining Empirical and Stochastic Models for Extreme Floods Estimation

NASA Astrophysics Data System (ADS)

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.

Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments, making assessments of SLR-induced hazards essential for informed decision making. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30m resolution predictions for more than 38,000 sq km of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Resilient Grid Operational Strategies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pasqualini, Donatella

Extreme weather-related disturbances, such as hurricanes, are a leading cause of grid outages historically. Although physical asset hardening is perhaps the most common way to mitigate the impacts of severe weather, operational strategies may be deployed to limit the extent of societal and economic losses associated with weather-related physical damage.1 The purpose of this study is to examine bulk power-system operational strategies that can be deployed to mitigate the impact of severe weather disruptions caused by hurricanes, thereby increasing grid resilience to maintain continuity of critical infrastructure during extreme weather. To estimate the impacts of resilient grid operational strategies, Losmore » Alamos National Laboratory (LANL) developed a framework for hurricane probabilistic risk analysis (PRA). The probabilistic nature of this framework allows us to estimate the probability distribution of likely impacts, as opposed to the worst-case impacts. The project scope does not include strategies that are not operations related, such as transmission system hardening (e.g., undergrounding, transmission tower reinforcement and substation flood protection) and solutions in the distribution network.« less

Flood risk assessment in a Spanish Mediterranean catchment

NASA Astrophysics Data System (ADS)

Salazar, S.; Francés, F.; García-Bartual, R.; Ortiz, E.; Múnera, J. C.; Vélez, J. J.

2009-04-01

This paper describes a multidisciplinary approach for the risk assessment and its application to analysing the effects of extreme flood events on the Mediterranean catchment called "Rambla del Poyo" in Valencia (Spain). This catchment located in the East coast of Spain has an area of 380 km2 and is clearly open to the Mediterranean Mesoscale Convective Storms. The climate is semiarid, and the flow regime is typically ephemeral, but with highly frequent flash floods, with peak flows in the order of 500 m3/s. Recently, in 2000 and 2002 the area was severe flooded. The flood prone area is located in the lower part of the basin, with an important concentration of different urban centers and industrial and commercial areas (including part of the Valencia International Airport). For this reason, the analysis of damages of residential, industrial and commercial urbanized areas is essential for the prevention of damages with a proper flood risk management. The approach is based on three main steps. The first step entails a detailed hydrological analysis (parameter estimation, calibration-validation and simulations) using a distributed rainfall-runoff model called TETIS. In the case study, on one hand, high temporal resolutions rain gauge data are scarce, because of this, in addition to a small number of historic events, 100 synthetic rainstorms were generated using the multidimensional stochastic model called RAINGEN, which adequately represents the main structural properties typical of intense convective storms, including occurrence of raincells in space and time and the generated intensities. An equivalent daily maximum precipitation Pd was estimated for each synthetic event, thus allowing a return period assignment using the known statistical distribution of Pd in the region. On the other hand, the initial soil moisture condition can have a strong influence in the runoff production, for this reason, long term daily simulation has been done in order to asses the probability distribution of the initial situation before the extreme flood events (dry and wet conditions). For all combinations of precipitation inputs and initial conditions, 200 hydrological simulations has been done in order to obtain the input hydrographs for the hydraulic model. Finally in this step, a frequency analysis to obtain the non-exceedence probability of the peak discharges has been developed using the annual maximum daily precipitation and the initial soil moisture condition with this expression: ž« FX (x) = FX |r (x|r).fR (r).dr -ž where: X= random variable of interest (peak discharge), R= annual maximum daily precipitation, fR(r)= probability density function of R, FX•r(x/r)= conditional density function of X given r obtained from simulations. The main objective of second step is flood hazard estimation, which, the hydraulic modelling has been developed using the coupled computing version of Sobek 1D/2D. In this task, the treatment of DEM calculation can be a key task depending on the scale of work. The introduction of buildings, walls, the opening of drainage works… improving the quality of results in areas with high anthropogenic influence; in our case has been made 6 simulations with 3 different resolutions, after all, the model has been done with a model one-dimensional (1D), logging throughout the stretch to two-dimensional (2D) grid with the parent of 30x30 metres, except for its passage through the urban, commercial and industrial land uses in the flood prone area where it connects with the child grid of 10x10 metres. Unfortunately, for reasons of computer time, the hydraulic model has not been run for the 200 available events. However, 20 events have been carefully select trying to cover the best probabilistic interest spectrum for this study (from two to one thousand years of return period). From the 20 selected flooding maps it has been developed a GIS computational tool for calculating a regression between the independent variable (maximum water depth) and the dependent variable return period transformed into natural logarithm. Using this methodology have been generated the hazard maps for the return periods of interest. Finally, the third step concerns to the flood risk, which was defined as probabilistic integral of the combination of flood hazard and land use vulnerability: ž« R = V (h).fH (h).dh 0 Where: R is the flood risk, V(h) is the land use vulnerability, h is the flood magnitude and fH(h) is its probability density function. The land use vulnerability is expressed in terms of stage-damage functions for urban, commercial and industrial land uses. Both, flood hazard and land use vulnerability are defined in terms of magnitude (water depth). This integral has been solved in discrete form using a GIS tools. The flood risk assessment by a resolution of 10 meters in size cell in the flood prone area of the "Rambla del Poyo" has been done. With this useful methodology, we believe that a complete flood risk analysis is needed in order to objectively compare different future scenarios that can affect either the flood hazard and/or the vulnerability in the flood prone area.

Dynamic Probabilistic Instability of Composite Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2009-01-01

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties in that order.

Maximizing Statistical Power When Verifying Probabilistic Forecasts of Hydrometeorological Events

NASA Astrophysics Data System (ADS)

DeChant, C. M.; Moradkhani, H.

2014-12-01

Hydrometeorological events (i.e. floods, droughts, precipitation) are increasingly being forecasted probabilistically, owing to the uncertainties in the underlying causes of the phenomenon. In these forecasts, the probability of the event, over some lead time, is estimated based on some model simulations or predictive indicators. By issuing probabilistic forecasts, agencies may communicate the uncertainty in the event occurring. Assuming that the assigned probability of the event is correct, which is referred to as a reliable forecast, the end user may perform some risk management based on the potential damages resulting from the event. Alternatively, an unreliable forecast may give false impressions of the actual risk, leading to improper decision making when protecting resources from extreme events. Due to this requisite for reliable forecasts to perform effective risk management, this study takes a renewed look at reliability assessment in event forecasts. Illustrative experiments will be presented, showing deficiencies in the commonly available approaches (Brier Score, Reliability Diagram). Overall, it is shown that the conventional reliability assessment techniques do not maximize the ability to distinguish between a reliable and unreliable forecast. In this regard, a theoretical formulation of the probabilistic event forecast verification framework will be presented. From this analysis, hypothesis testing with the Poisson-Binomial distribution is the most exact model available for the verification framework, and therefore maximizes one's ability to distinguish between a reliable and unreliable forecast. Application of this verification system was also examined within a real forecasting case study, highlighting the additional statistical power provided with the use of the Poisson-Binomial distribution.

Analyzing Future Flooding under Climate Change Scenario using CMIP5 Streamflow Data

NASA Astrophysics Data System (ADS)

Nyaupane, Narayan; Parajuli, Ranjan; Kalra, Ajay

2017-12-01

Flooding is the most severe and costlier natural hazard in US. The effect of climate change has intensified the scenario in recent years. Flood prevention practice along with proper understanding of flooding event can mitigate the risk of such hazard. The flood plain mapping is one of the technique to quantify the severity of the flooding. Carson City, which is one of the agricultural area in the desert of Nevada has experienced peak flood in recent year. The underlying probability distribution for the area, latest Coupled Model Intercomparison Project (CMIP5) streamflow data of Carson River were analyzed for 27 different statistical distributions. The best fitted distribution underlying was used to forecast the 100yr flood (design flood). The data from 1950-2099 derived from 31 model and total 97 projections were used to predict the future streamflow. Delta change method is adopted to quantify the amount of future (2050-2099) flood. To determine the extent of flooding 3 scenarios (i) historic design flood, (ii) 500yr flood and (iii) future 100yr flood were routed on a HEC-RAS model, prepared using available terrain data. Some of the climate projection shows extreme increase in future design flood. The future design flood could be more than the historic 500yr flood. At the same time, the extent of flooding could go beyond the historic flood of 0.2% annual probability. This study suggests an approach to quantify the future flood and floodplain using climate model projections. The study would provide helpful information to the facility manager, design engineer and stake holders.

Probabilistic Evaluation of Anthropogenic Regulations In a Vegetated River Channel Using a Vegetation Dynamics Modeling

NASA Astrophysics Data System (ADS)

Miyamoto, Hitoshi

2015-04-01

Vegetation overgrowth in fluvial floodplains, gravel beds, and sand bars has been a serious engineering problem for riparian management in Japan. From the viewpoints of flood control and ecological conservation, it would be necessary to predict the vegetation dynamics accurately for long-term duration. In this research, we have developed a stochastic model for predicting the vegetation dynamics in fluvial floodplains with emphasis on the interaction with flood impacts. The model consists of the following four components: (i) long-term stochastic behavior of flow discharge, (ii) hydrodynamics in a channel with floodplain vegetation, (iii) variation of riverbed topography, and (iv) vegetation dynamics on floodplains. In the vegetation dynamics model, the flood discharge (i) is stochastically simulated using a filtered Poisson process, one of the conventional approaches in hydrological time-series generation. The component for vegetation dynamics (iv) includes the effects of tree growth, mortality by floods, and infant tree recruitment. Vegetation condition has been observed mainly before and after floods since 2008 at a field site located between 23-24 km from the river mouth in Kako River, Japan. The Kako River has the catchment area of 1,730 km2 and the main channel length of 96 km. This site is one of the vegetation overgrowth sites in the Kako River floodplains. The predominant tree species are willows and bamboos. In the field survey, the position, trunk diameter and height of each tree as well as the riverbed materials were measured after several flood events to investigate their impacts on the floodplain vegetation community. This presentation tries to examine effects of anthropogenic river regulations, i.e., thinning and cutting-down, in the vegetated channel in Kako River by using the vegetation dynamics model. Sensitivity of both the flood water level and the vegetation status in the channel is statistically evaluated in terms of the different cutting-down levels, timings and scales of the thinning, etc., by the Monte Carlo simulation of the model.

Probabilistic drug connectivity mapping

PubMed Central

2014-01-01

Background The aim of connectivity mapping is to match drugs using drug-treatment gene expression profiles from multiple cell lines. This can be viewed as an information retrieval task, with the goal of finding the most relevant profiles for a given query drug. We infer the relevance for retrieval by data-driven probabilistic modeling of the drug responses, resulting in probabilistic connectivity mapping, and further consider the available cell lines as different data sources. We use a special type of probabilistic model to separate what is shared and specific between the sources, in contrast to earlier connectivity mapping methods that have intentionally aggregated all available data, neglecting information about the differences between the cell lines. Results We show that the probabilistic multi-source connectivity mapping method is superior to alternatives in finding functionally and chemically similar drugs from the Connectivity Map data set. We also demonstrate that an extension of the method is capable of retrieving combinations of drugs that match different relevant parts of the query drug response profile. Conclusions The probabilistic modeling-based connectivity mapping method provides a promising alternative to earlier methods. Principled integration of data from different cell lines helps to identify relevant responses for specific drug repositioning applications. PMID:24742351

78 FR 41991 - Pipeline Safety: Potential for Damage to Pipeline Facilities Caused by Flooding

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-12

... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration [Docket No...: Pipeline and Hazardous Materials Safety Administration (PHMSA); DOT. ACTION: Notice; Issuance of Advisory... Gas and Hazardous Liquid Pipeline Systems. Subject: Potential for Damage to Pipeline Facilities Caused...

Transport and fate of radionuclides in aquatic environments--the use of ecosystem modelling for exposure assessments of nuclear facilities.

PubMed

Kumblad, L; Kautsky, U; Naeslund, B

2006-01-01

In safety assessments of nuclear facilities, a wide range of radioactive isotopes and their potential hazard to a large assortment of organisms and ecosystem types over long time scales need to be considered. Models used for these purposes have typically employed approaches based on generic reference organisms, stylised environments and transfer functions for biological uptake exclusively based on bioconcentration factors (BCFs). These models are of non-mechanistic nature and involve no understanding of uptake and transport processes in the environment, which is a severe limitation when assessing real ecosystems. In this paper, ecosystem models are suggested as a method to include site-specific data and to facilitate the modelling of dynamic systems. An aquatic ecosystem model for the environmental transport of radionuclides is presented and discussed. With this model, driven and constrained by site-specific carbon dynamics and three radionuclide specific mechanisms: (i) radionuclide uptake by plants, (ii) excretion by animals, and (iii) adsorption to organic surfaces, it was possible to estimate the radionuclide concentrations in all components of the modelled ecosystem with only two radionuclide specific input parameters (BCF for plants and Kd). The importance of radionuclide specific mechanisms for the exposure to organisms was examined, and probabilistic and sensitivity analyses to assess the uncertainties related to ecosystem input parameters were performed. Verification of the model suggests that this model produces analogous results to empirically derived data for more than 20 different radionuclides.

A Framework and Metric for resilience concept in water infrastructure

NASA Astrophysics Data System (ADS)

Karamouz, M.; Olyaei, M.

2017-12-01

The collaborators of water industries are looking for ways and means to bring resilience into our water infrastructure systems. The key to this conviction is to develop a shared vision among the engineers, builders and decision makers of our water executive branch and policy makers, utilities, community leaders, players, end users and other stakeholders of our urban environment. Among water infrastructures, wastewater treatment plants (WWTP) have a significant role on urban systems' serviceability. These facilities, especially when located in coastal regions, are vulnerable to heavy rain, surface runoff, storm surges and coastal flooding. Flooding can cause overflows from treatment facilities into the natural water bodies and result in environmental predicament of significant proportions. In order to minimize vulnerability to flood, a better understanding of flood risk must be realized. Vulnerability to floods frequency and intensity is increasing by external forcing such as climate change, as well as increased interdependencies in urban systems. Therefore, to quantify the extent of efforts for flood risk management, a unified index is needed for evaluating resiliency of infrastructure. Resiliency is a key concept in understanding vulnerability in dealing with flood. New York City based on its geographic location, its urbanized nature, densely populated area, interconnected water bodies and history of the past flooding events is extremely vulnerable to flood and was selected as the case study. In this study, a framework is developed to evaluate resiliency of WWTPs. An analysis of the current understanding of vulnerability is performed and a new perspective utilizing different components of resiliency including resourcefulness, robustness, rapidity and redundancy is presented. To quantify resiliency and rank the wastewater treatment plants in terms of how resilient they are, an index is developed using Multi Criteria Decision Making (MCDM) technique. Moreover, Improvement of WWTPs' performance is investigated by allocating financial resources to attain a desirable level of resiliency. The result of this study shows the significant value of quantifying and improving flood resiliency of WWTPs that could be used for other water infrastructure and in planning of investment strategies for a region

Probabilistic analysis of the eight-hour-averaged CO impacts of highways.

DOT National Transportation Integrated Search

1980-01-01

This report describes a method for estimating the probability that a highway facility will violate the eight hour National Ambient Air Quality Standard (NAAQS) for carbon monoxide (CO). The method is predicated on the assumption that overlapping eigh...

Development of Real-Time System for Urban Flooding by Surcharge of Storm Drainge and River Inundation

NASA Astrophysics Data System (ADS)

Shim, J. B.; Won, C. Y.; Park, J.; Lee, K.

2017-12-01

Korea experiences frequent flood disasters, which cause considerable economic losses and damages to towns and farms. Especially, a regional torrential storm is about 98.5mm/hr on September 21, 2010 in Seoul. The storm exceeds the capacity of urban drainage system of 75mm/hr, and 9,419 houses. How to monitor and control the urban flood disasters is an important issue in Korea. To mitigate the flood damage, a customizing system was developed to estimate urban floods and inundation using by integrating drainage system data and river information database which are managed by local governments and national agencies. In the case of Korean urban city, there are a lot of detention ponds and drainage pumping stations on end of drainage system and flow is going into river. The drainage pumping station, it is very important hydraulic facility for flood control between river and drainage system. So, it is possible to occur different patterns of flood inundation according to operation rule of drainage pumping station. A flood disaster is different damage as how to operate drainage pumping station and plan operation rule.

Flood tolerance evaluation of bottomland oaks in a multi-channel field laboratory

Treesearch

Mark V. Coggeshall; J. W. Van Sambeek; Scott E. Schlarbaum

2005-01-01

A multi-channel field laboratory was designed and constructed by the University of Missouri Center for Agroforestry at the Horticulture and Agroforestry Research Center to assess the flood tolerance of forages and hardwood seedlings. This facility located in the Missouri River floodplain consists of twelve 6-m wide x 180-m long channels that had minimal disturbance to...

Large-scale boiling experiments of the flooded cavity concept for in-vessel core retention

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chu, T.Y.; Slezak, S.E.; Bentz, J.H.

1994-03-01

This paper presents results of ex-vessel boiling experiments performed in the CYBL (CYlindrical BoiLing) facility. CYBL is a reactor-scale facility for confirmatory research of the flooded cavity concept for accident management. CYBL has a tank-within-a-tank design; the inner tank simulates the reactor vessel and the outer tank simulates the reactor cavity. Experiments with uniform and edge-peaked heat flux distributions up to 20 W/cm{sup 2} across the vessel bottom were performed. Boiling outside the reactor vessel was found to be subcooled nucleate boiling. The subcooling is mainly due to the gravity head which results from flooding the sides of the reactormore » vessel. The boiling process exhibits a cyclic pattern with four distinct phases: direct liquid/solid contact, bubble nucleation and growth, coalescence, and vapor mass dispersion (ejection). The results suggest that under prototypic heat load and heat flux distributions, the flooded cavity in a passive pressurized water reactor like the AP-600 should be capable of cooling the reactor pressure vessel in the central region of the lower head that is addressed by these tests.« less

Ensemble Streamflow Prediction in Korea: Past and Future 5 Years

NASA Astrophysics Data System (ADS)

Jeong, D.; Kim, Y.; Lee, J.

2005-05-01

The Ensemble Streamflow Prediction (ESP) approach was first introduced in 2000 by the Hydrology Research Group (HRG) at Seoul National University as an alternative probabilistic forecasting technique for improving the 'Water Supply Outlook' That is issued every month by the Ministry of Construction and Transportation in Korea. That study motivated the Korea Water Resources Corporation (KOWACO) to establish their seasonal probabilistic forecasting system for the 5 major river basins using the ESP approach. In cooperation with the HRG, the KOWACO developed monthly optimal multi-reservoir operating systems for the Geum river basin in 2004, which coupled the ESP forecasts with an optimization model using sampling stochastic dynamic programming. The user interfaces for both ESP and SSDP have also been designed for the developed computer systems to become more practical. More projects for developing ESP systems to the other 3 major river basins (i.e. the Nakdong, Han and Seomjin river basins) was also completed by the HRG and KOWACO at the end of December 2004. Therefore, the ESP system has become the most important mid- and long-term streamflow forecast technique in Korea. In addition to the practical aspects, resent research experience on ESP has raised some concerns into ways of improving the accuracy of ESP in Korea. Jeong and Kim (2002) performed an error analysis on its resulting probabilistic forecasts and found that the modeling error is dominant in the dry season, while the meteorological error is dominant in the flood season. To address the first issue, Kim et al. (2004) tested various combinations and/or combining techniques and showed that the ESP probabilistic accuracy could be improved considerably during the dry season when the hydrologic models were combined and/or corrected. In addition, an attempt was also made to improve the ESP accuracy for the flood season using climate forecast information. This ongoing project handles three types of climate forecast information: (1) the Monthly Industrial Meteorology Information Magazine (MIMIM) of the Korea Meteorological Administration (2) the Global Data Assimilation Prediction System (GDAPS), and (3) the US National Centers for Environmental Prediction (NCEP). Each of these forecasts is issued in a unique format: (1) MIMIM is a most-probable-event forecast, (2) GDAPS is a single series of deterministic forecasts, and (3) NCEP is an ensemble of deterministic forecasts. Other minor issues include how long the initial conditions influences the ESP accuracy, and how many ESP scenarios are needed to obtain the best accuracy. This presentation also addresses some future research that is needed for ESP in Korea.

Plants are less negatively affected by flooding when growing in species-rich plant communities.

PubMed

Wright, Alexandra J; de Kroon, Hans; Visser, Eric J W; Buchmann, Tina; Ebeling, Anne; Eisenhauer, Nico; Fischer, Christine; Hildebrandt, Anke; Ravenek, Janneke; Roscher, Christiane; Weigelt, Alexandra; Weisser, Wolfgang; Voesenek, Laurentius A C J; Mommer, Liesje

2017-01-01

Flooding is expected to increase in frequency and severity in the future. The ecological consequences of flooding are the combined result of species-specific plant traits and ecological context. However, the majority of past flooding research has focused on individual model species under highly controlled conditions. An early summer flooding event in a grassland biodiversity experiment in Jena, Germany, provided the opportunity to assess flooding responses of 60 grassland species in monocultures and 16-species mixtures. We examined plant biomass, species-specific traits (plant height, specific leaf area (SLA), root aerenchyma, starch content) and soil porosity. We found that, on average, plant species were less negatively affected by the flood when grown in higher-diversity plots in July 2013. By September 2013, grasses were unaffected by the flood regardless of plant diversity, and legumes were severely negatively affected regardless of plant diversity. Plants with greater SLA and more root aerenchyma performed better in September. Soil porosity was higher in higher-diversity plots and had a positive effect on plant performance. As floods become more frequent and severe in the future, growing flood-sensitive plants in higher-diversity communities and in soil with greater soil aeration may attenuate the most negative effects of flooding. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Characterizing climate-change impacts on the 1.5-yr flood flow in selected basins across the United States: a probabilistic approach

USGS Publications Warehouse

Walker, John F.; Hay, Lauren E.; Markstrom, Steven L.; Dettinger, Michael D.

2011-01-01

The U.S. Geological Survey Precipitation-Runoff Modeling System (PRMS) model was applied to basins in 14 different hydroclimatic regions to determine the sensitivity and variability of the freshwater resources of the United States in the face of current climate-change projections. Rather than attempting to choose a most likely scenario from the results of the Intergovernmental Panel on Climate Change, an ensemble of climate simulations from five models under three emissions scenarios each was used to drive the basin models. Climate-change scenarios were generated for PRMS by modifying historical precipitation and temperature inputs; mean monthly climate change was derived by calculating changes in mean climates from current to various future decades in the ensemble of climate projections. Empirical orthogonal functions (EOFs) were fitted to the PRMS model output driven by the ensemble of climate projections and provided a basis for randomly (but representatively) generating realizations of hydrologic response to future climates. For each realization, the 1.5-yr flood was calculated to represent a flow important for sediment transport and channel geomorphology. The empirical probability density function (pdf) of the 1.5-yr flood was estimated using the results across the realizations for each basin. Of the 14 basins studied, 9 showed clear temporal shifts in the pdfs of the 1.5-yr flood projected into the twenty-first century. In the western United States, where the annual peak discharges are heavily influenced by snowmelt, three basins show at least a 10% increase in the 1.5-yr flood in the twenty-first century; the remaining two basins demonstrate increases in the 1.5-yr flood, but the temporal shifts in the pdfs and the percent changes are not as distinct. Four basins in the eastern Rockies/central United States show at least a 10% decrease in the 1.5-yr flood; the remaining two basins demonstrate decreases in the 1.5-yr flood, but the temporal shifts in the pdfs and the percent changes are not as distinct. Two basins in the eastern United States show at least a 10% decrease in the 1.5-yr flood; the remaining basin shows little or no change in the 1.5-yr flood.

18 CFR 5.6 - Pre-application document.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., flushing flows, reservoir operations, and flood control operations. (v) In the case of an existing licensed...) project facilities and operations, provide information on the existing environment, and existing data or... meeting and site visit required by § 5.8(b)(3)(viii). (2) Project location, facilities, and operations...

An Integrated Ensemble-Based Operational Framework to Predict Urban Flooding: A Case Study of Hurricane Sandy in the Passaic and Hackensack River Basins

NASA Astrophysics Data System (ADS)

Saleh, F.; Ramaswamy, V.; Georgas, N.; Blumberg, A. F.; Wang, Y.

2016-12-01

Advances in computational resources and modeling techniques are opening the path to effectively integrate existing complex models. In the context of flood prediction, recent extreme events have demonstrated the importance of integrating components of the hydrosystem to better represent the interactions amongst different physical processes and phenomena. As such, there is a pressing need to develop holistic and cross-disciplinary modeling frameworks that effectively integrate existing models and better represent the operative dynamics. This work presents a novel Hydrologic-Hydraulic-Hydrodynamic Ensemble (H3E) flood prediction framework that operationally integrates existing predictive models representing coastal (New York Harbor Observing and Prediction System, NYHOPS), hydrologic (US Army Corps of Engineers Hydrologic Modeling System, HEC-HMS) and hydraulic (2-dimensional River Analysis System, HEC-RAS) components. The state-of-the-art framework is forced with 125 ensemble meteorological inputs from numerical weather prediction models including the Global Ensemble Forecast System, the European Centre for Medium-Range Weather Forecasts (ECMWF), the Canadian Meteorological Centre (CMC), the Short Range Ensemble Forecast (SREF) and the North American Mesoscale Forecast System (NAM). The framework produces, within a 96-hour forecast horizon, on-the-fly Google Earth flood maps that provide critical information for decision makers and emergency preparedness managers. The utility of the framework was demonstrated by retrospectively forecasting an extreme flood event, hurricane Sandy in the Passaic and Hackensack watersheds (New Jersey, USA). Hurricane Sandy caused significant damage to a number of critical facilities in this area including the New Jersey Transit's main storage and maintenance facility. The results of this work demonstrate that ensemble based frameworks provide improved flood predictions and useful information about associated uncertainties, thus improving the assessment of risks as when compared to a deterministic forecast. The work offers perspectives for short-term flood forecasts, flood mitigation strategies and best management practices for climate change scenarios.

Toward Probabilistic Risk Analyses - Development of a Probabilistic Tsunami Hazard Assessment of Crescent City, CA

NASA Astrophysics Data System (ADS)

González, F. I.; Leveque, R. J.; Hatheway, D.; Metzger, N.

2011-12-01

Risk is defined in many ways, but most are consistent with Crichton's [1999] definition based on the ''risk triangle'' concept and the explicit identification of three risk elements: ''Risk is the probability of a loss, and this depends on three elements: hazard, vulnerability, and exposure. If any of these three elements in risk increases or decreases, then the risk increases or decreases respectively." The World Meteorological Organization, for example, cites Crichton [1999] and then defines risk as [WMO, 2008] Risk = function (Hazard x Vulnerability x Exposure) while the Asian Disaster Reduction Center adopts the more general expression [ADRC, 2005] Risk = function (Hazard, Vulnerability, Exposure) In practice, probabilistic concepts are invariably invoked, and at least one of the three factors are specified as probabilistic in nature. The Vulnerability and Exposure factors are defined in multiple ways in the relevant literature; but the Hazard factor, which is the focus of our presentation, is generally understood to deal only with the physical aspects of the phenomena and, in particular, the ability of the phenomena to inflict harm [Thywissen, 2006]. A Hazard factor can be estimated by a methodology known as Probabilistic Tsunami Hazard Assessment (PTHA) [González, et al., 2009]. We will describe the PTHA methodology and provide an example -- the results of a previous application to Seaside, OR. We will also present preliminary results for a PTHA of Crescent City, CA -- a pilot project and coastal modeling/mapping effort funded by the Federal Emergency Management Agency (FEMA) Region IX office as part of the new California Coastal Analysis and Mapping Project (CCAMP). CCAMP and the PTHA in Crescent City are being conducted under the nationwide FEMA Risk Mapping, Assessment, and Planning (Risk MAP) Program which focuses on providing communities with flood information and tools they can use to enhance their mitigation plans and better protect their citizens.

Hurricane Sandy: Caught in the eye of the storm and a city's adaptation response

NASA Astrophysics Data System (ADS)

Orton, P. M.; Horton, R. M.; Blumberg, A. F.; Rosenzweig, C.; Solecki, W.; Bader, D.

2015-12-01

The NOAA RISA program has funded the seven-institution Consortium for Climate Risk in the Urban Northeast (CCRUN) for the past five years to serve stakeholder needs in assessing and managing risks from climate variability and change. When Hurricane Sandy struck, we were in an ideal position, making flood forecasts and communicating NOAA forecasts to the public with dozens of media placements, translating the poorly understood flood forecasts into human dimensions. In 2013 and 2015, by request of New York City (NYC), we worked through the NYC Panel on Climate Change to deliver updated climate risk assessment reports, to be used in the post-Sandy rebuilding and resiliency efforts. These utilized innovative methodologies for probabilistic local and regional sea level change projections, and contrasted methods of dynamic versus (the more common) static flood mapping. We participated in a federal-academic partnership that developed a Sea Level Tool for Sandy Recovery that integrates CCRUN sea level rise projections with policy-relevant FEMA flood maps, and now several updated flood maps and coastal flood mapping tools (NOAA, FEMA, and USACE) incorporate our projections. For the adaptation response, we helped develop NYC's $20 billion flood adaptation plan, and we were on a winning team under the Housing and Urban Development Rebuild By Design (RBD) competition, a few of the many opportunities that arose with negligible additional funding and which CCRUN funds supported. Our work at times disrupted standard lines of thinking, but NYC showed an openness to altering course. In one case we showed that an NYC plan of wetland restoration in Jamaica Bay would provide no reduction in flooding unless deep-dredged channels circumventing them were shallowed or narrowed. In another, the lead author's RBD team challenged the notion at one location that levees were the solution to accelerating sea level rise, developing a plan to use ecological breakwaters and layered components of physical and social resilience. CCRUN has succeeded in winning another five years of RISA funding, and this will enable us to continue our climate risk and adaptation work for the entire Urban Northeast.

33 CFR 211.6 - Rights which may be granted by the Secretary of the Army in river and harbor and flood control...

Code of Federal Regulations, 2011 CFR

2011-07-01

... recreational facilities in reservoir areas under the control of the Department of the Army and to permit the construction, maintenance, and operation of such facilities. The Secretary of the Army is authorized to grant leases of lands, including structures or facilities thereon, in reservoir areas for such periods and upon...

Probabilistic approach for decay heat uncertainty estimation using URANIE platform and MENDEL depletion code

NASA Astrophysics Data System (ADS)

Tsilanizara, A.; Gilardi, N.; Huynh, T. D.; Jouanne, C.; Lahaye, S.; Martinez, J. M.; Diop, C. M.

2014-06-01

The knowledge of the decay heat quantity and the associated uncertainties are important issues for the safety of nuclear facilities. Many codes are available to estimate the decay heat. ORIGEN, FISPACT, DARWIN/PEPIN2 are part of them. MENDEL is a new depletion code developed at CEA, with new software architecture, devoted to the calculation of physical quantities related to fuel cycle studies, in particular decay heat. The purpose of this paper is to present a probabilistic approach to assess decay heat uncertainty due to the decay data uncertainties from nuclear data evaluation like JEFF-3.1.1 or ENDF/B-VII.1. This probabilistic approach is based both on MENDEL code and URANIE software which is a CEA uncertainty analysis platform. As preliminary applications, single thermal fission of uranium 235, plutonium 239 and PWR UOx spent fuel cell are investigated.

An analytical probabilistic model of the quality efficiency of a sewer tank

NASA Astrophysics Data System (ADS)

Balistrocchi, Matteo; Grossi, Giovanna; Bacchi, Baldassare

2009-12-01

The assessment of the efficiency of a storm water storage facility devoted to the sewer overflow control in urban areas strictly depends on the ability to model the main features of the rainfall-runoff routing process and the related wet weather pollution delivery. In this paper the possibility of applying the analytical probabilistic approach for developing a tank design method, whose potentials are similar to the continuous simulations, is proved. In the model derivation the quality issues of such devices were implemented. The formulation is based on a Weibull probabilistic model of the main characteristics of the rainfall process and on a power law describing the relationship between the dimensionless storm water cumulative runoff volume and the dimensionless cumulative pollutograph. Following this approach, efficiency indexes were established. The proposed model was verified by comparing its results to those obtained by continuous simulations; satisfactory agreement is shown for the proposed efficiency indexes.

Natural phenomena hazards design and evaluation criteria for Department of Energy Facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1994-04-01

This DOE standard gives design and evaluation criteria for natural phenomena hazards (NPH) effects as guidance for implementing the NPH mitigation requirements of DOE 5480.28. Goal of the criteria is to assure that DOE facilities can withstand the effects of earthquakes, extreme winds, tornadoes, flooding, etc. They apply to the design of new facilities and the evaluation of existing facilities; they may also be used for modification and upgrading of the latter.

ENSO impacts on flood risk at the global scale

NASA Astrophysics Data System (ADS)

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 (and by extension insured losses). We carried out the research by simulating daily river discharges using a global hydrological model (PCR-GLOBWB), forced with gridded climate reanalysis time-series (EU-WATCH). 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.

78 FR 20128 - Extension of the Designation of Nicaragua for Temporary Protected Status

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-03

... Nicaragua's roads are paved. Hurricane Mitch damaged potable water, sewage treatment systems, water uptake systems, wells, water pump stations, and pipes in Nicaragua. The storm floods and runoff polluted water... education facilities, water supply and sanitation facilities, and the agricultural sector. Living conditions...

Medium Range Ensembles Flood Forecasts for Community Level Applications

NASA Astrophysics Data System (ADS)

Fakhruddin, S.; Kawasaki, A.; Babel, M. S.; AIT

2013-05-01

Early warning is a key element for disaster risk reduction. In recent decades, there has been a major advancement in medium range and seasonal forecasting. These could provide a great opportunity to improve early warning systems and advisories for early action for strategic and long term planning. This could result in increasing emphasis on proactive rather than reactive management of adverse consequences of flood events. This can be also very helpful for the agricultural sector by providing a diversity of options to farmers (e.g. changing cropping pattern, planting timing, etc.). An experimental medium range (1-10 days) flood forecasting model has been developed for Bangladesh which provides 51 set of discharge ensembles forecasts of one to ten days with significant persistence and high certainty. This could help communities (i.e. farmer) for gain/lost estimation as well as crop savings. This paper describe the application of ensembles probabilistic flood forecast at the community level for differential decision making focused on agriculture. The framework allows users to interactively specify the objectives and criteria that are germane to a particular situation, and obtain the management options that are possible, and the exogenous influences that should be taken into account before planning and decision making. risk and vulnerability assessment was conducted through community consultation. The forecast lead time requirement, users' needs, impact and management options for crops, livestock and fisheries sectors were identified through focus group discussions, informal interviews and questionnaire survey.

Healthcare-associated infections and their prevention after extensive flooding.

PubMed

Apisarnthanarak, Anucha; Warren, David K; Mayhall, Clovus Glen

2013-08-01

This review will focus on the epidemiology of healthcare-associated infections (HAIs) after extensive blackwater flooding as well as preventive measures. There is evidence suggesting an increased incidence of HAIs and pseudo-outbreaks due to molds after extensive flooding in healthcare facilities. However, there is no strong evidence of an increased incidence of typical nosocomial infections (i.e., ventilator-associated pneumonia, healthcare-associated pneumonia, central line-associated bloodstream infection and catheter-associated urinary tract infections). The prevalence of multidrug-resistant organisms may decrease after extensive flooding, due to repeated and thorough environmental cleaning prior to re-opening hospitals. Contamination of hospital water sources by enteric Gram-negative bacteria (e.g., Aeromonas species), Legionella species and nontuberculous Mycobacterium species in flood-affected hospitals has been reported. Surveillance is an important initial step to detect potential outbreaks/pseudo-outbreaks of HAIs. Hospital preparedness policies before extensive flooding, particularly with environmental cleaning and mold remediation, are key to reducing the risk of flood-related HAIs. These policies are still lacking in most hospitals in countries that have experienced or are at risk for extensive flooding, which argues for nationwide policies to strengthen preparedness planning. Additional studies are needed to evaluate the epidemiology of flood-related HAIs and the optimal surveillance and control methods following extensive flooding.

Displaying uncertainty: investigating the effects of display format and specificity.

PubMed

Bisantz, Ann M; Marsiglio, Stephanie Schinzing; Munch, Jessica

2005-01-01

We conducted four studies regarding the representation of probabilistic information. Experiments 1 through 3 compared performance on a simulated stock purchase task, in which information regarding stock profitability was probabilistic. Two variables were manipulated: display format for probabilistic information (blurred and colored icons, linguistic phrases, numeric expressions, and combinations) and specificity level (in which the number and size of discrete steps into which the probabilistic information was mapped differed). Results indicated few performance differences attributable to display format; however, performance did improve with greater specificity. Experiment 4, in which participants generated membership functions corresponding to three display formats, found a high degree of similarity in functions across formats and participants and a strong relationship between the shape of the membership function and the intended meaning of the representation. These results indicate that participants can successfully interpret nonnumeric representations of uncertainty and can use such representations in a manner similar to the way numeric expressions are used in a decision-making task. Actual or potential applications of this research include the use of graphical representations of uncertainty in systems such as command and control and situation displays.

The total probabilities from high-resolution ensemble forecasting of floods

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2015-04-01

Ensemble forecasting has for a long time been used in meteorological modelling, to give an indication of the uncertainty of the forecasts. As meteorological ensemble forecasts often show some bias and dispersion errors, there is a need for calibration and post-processing of the ensembles. Typical methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). To make optimal predictions of floods along the stream network in hydrology, we can easily use the ensemble members as input to the hydrological models. However, some of the post-processing methods will need modifications when regionalizing the forecasts outside the calibration locations, as done by Hemri et al. (2013). We present a method for spatial regionalization of the post-processed forecasts based on EMOS and top-kriging (Skøien et al., 2006). We will also look into different methods for handling the non-normality of runoff and the effect on forecasts skills in general and for floods in particular. Berrocal, V. J., Raftery, A. E. and Gneiting, T.: Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts, Mon. Weather Rev., 135(4), 1386-1402, doi:10.1175/MWR3341.1, 2007. Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T.: Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation, Mon. Weather Rev., 133(5), 1098-1118, doi:10.1175/MWR2904.1, 2005. Hemri, S., Fundel, F. and Zappa, M.: Simultaneous calibration of ensemble river flow predictions over an entire range of lead times, Water Resour. Res., 49(10), 6744-6755, doi:10.1002/wrcr.20542, 2013. Raftery, A. E., Gneiting, T., Balabdaoui, F. and Polakowski, M.: Using Bayesian Model Averaging to Calibrate Forecast Ensembles, Mon. Weather Rev., 133(5), 1155-1174, doi:10.1175/MWR2906.1, 2005. Skøien, J. O., Merz, R. and Blöschl, G.: Top-kriging - Geostatistics on stream networks, Hydrol. Earth Syst. Sci., 10(2), 277-287, 2006.

An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios

NASA Astrophysics Data System (ADS)

Addor, N.; Jaun, S.; Zappa, M.

2011-01-01

The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This models chain relies on limited-area atmospheric forecasts provided by the deterministic model COSMO-7 and the probabilistic model COSMO-LEPS. These atmospheric forecasts are used to force a semi-distributed hydrological model (PREVAH), coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework to compare the potential of deterministic and probabilistic discharge forecasts for flood mitigation. To study the suitability of HEPS for small-scale basins and to quantify the added-value conveyed by the probability information, a reforecast was made for the period June 2007 to December 2009 for the Sihl catchment (336 km2). Several metrics support the conclusion that the performance gain can be of up to 2 days lead time for the catchment considered. Brier skill scores show that COSMO-LEPS-based hydrological forecasts overall outperform their COSMO-7 based counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts, as shown by comparisons with a reference run driven by observed meteorological parameters. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. The two most intense events of the study period are investigated utilising a novel graphical representation of probability forecasts and used to generate high discharge scenarios. They highlight challenges for making decisions on the basis of hydrological predictions, and indicate the need for a tool to be used in addition to forecasts to compare the different mitigation actions possible in the Sihl catchment.

An innovative early warning system for floods and operational risks in harbours

NASA Astrophysics Data System (ADS)

Smets, Steven; Bolle, Annelies; Mollaert, Justine; Buitrago, Saul; Gruwez, Vincent

2016-04-01

Early Warning Systems (EWS) are nowadays becoming fairly standard in river flood forecasting or in large scale hydrometeorological predictions. For complex coastal morphodynamic problems or in the vicinity of complex coastal structures, such as harbours, EWS are much less used because they are both technically and computationally still very challenging. To advance beyond the state-of-the-art, the EU FP7 project Risc-KIT (www.risc-kit.eu) is developing prototype EWS which address specifically these topics. This paper describes the prototype EWS which IMDC has developed for the case study site of the harbour of Zeebrugge. The harbour of Zeebrugge is the largest industrial seaport on the coast of Belgium, extending more than 3 km into the sea. Two long breakwaters provide shelter for the inner quays and docks for regular conditions and frequent storms. Extreme storms surges and waves can however still enter the harbour and create risks for the harbour operations and infrastructure. The prediction of the effects of storm surges and waves inside harbours are typically very complex and challenging, due to the need of different types of numerical models for representing all different physical processes. In general, waves inside harbours are a combination of locally wind generated waves and offshore wave penetration at the port entrance. During extreme conditions, the waves could overtop the quays and breakwaters and flood the port facilities. Outside a prediction environment, the conditions inside the harbour could be assessed by superimposing processes. The assessment can be carried out by using a combination of a spectral wave model (i.e. SWAN) for the wind generated waves and a Boussinesq type wave model (i.e. Mike 21 BW) for the wave penetration from offshore. Finally, a 2D hydrodynamic model (i.e. TELEMAC) can be used to simulate the overland flooding inside the port facilities. To reproduce these processes in an EWS environment, an additional challenge is to cope with the limitations of the calculation engines. This is especially true with the Boussinesq model. A model train is proposed that integrates processed based modelling, for wind generated waves, with an intelligent simplification of the Boussinesq model for the wave penetration effects. These wave conditions together with the extreme water levels (including storm surge) can then be used to simulate the overtopping/overflow behaviour for the quays. Finally, the hydrodynamic model TELEMAC is run for the inundation forecast inside the port facilities. The complete model train was integrated into the Deltares Delft FEWS software to showcase the potential for real time operations.

75 FR 64366 - Advisory Committee on Reactor Safeguards

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-19

... NUREG/CR- 6997, ``Modeling a Digital Feedwater Control System Using Traditional Probabilistic Risk.../reading-rm/adams.html or http://www.nrc.gov/reading-rm/doc-collections/ACRS/ . Video teleconferencing... line charges and for providing the equipment and facilities that they use to establish the video...

Prediction of extreme flood in August 2002 along the Upper-Danube in Hungary

NASA Astrophysics Data System (ADS)

Sütheö, L.; Bálint, G.; Szlávik, L.

2003-04-01

Specific for summer conditions weather situation caused the flood. A cyclone reached the region of Alps, humid air and great instability of stratification produced high precipitation throughout the region in two vawes. The flood has reached historical maxima on the reach between Bratislava Budapest. This is the first flood of this magnitude, which has passed this section of the Danube without breaching the dikes, flood embankments. The peak flow rate attenuated along this section from 10 000 m3s-1 to 8600 m3s-1. Specifics of flood routing conditions are discussed. Barrages and training has changed flood routing patterns along the Austrian and joined Slovak Hungarian sections of the Danube. Increased velocity of wave propagation decreases the impact of superposition of consequent flood waves, but attenuation of flood waves is also less expressed. The most significant impact on the present flood was, that this was the first flood of this magnitude, which has passed this section of the Danube without breaching the flood embankments. Earlier extreme floods including the 1954 and 1965 floods resulted failure of the dikes and spill over of 1.5- 2 million m3 of water to the protected floodplain. This time the flood was contained within the floodberm.

Active and Passive Remote Sensing Data Time Series for Flood Detection and Surface Water Mapping

NASA Astrophysics Data System (ADS)

Bioresita, Filsa; Puissant, Anne; Stumpf, André; Malet, Jean-Philippe

2017-04-01

As a consequence of environmental changes surface waters are undergoing changes in time and space. A better knowledge of the spatial and temporal distribution of surface waters resources becomes essential to support sustainable policies and development activities. Especially because surface waters, are not only a vital sweet water resource, but can also pose hazards to human settlements and infrastructures through flooding. Floods are a highly frequent disaster in the world and can caused huge material losses. Detecting and mapping their spatial distribution is fundamental to ascertain damages and for relief efforts. Spaceborne Synthetic Aperture Radar (SAR) is an effective way to monitor surface waters bodies over large areas since it provides excellent temporal coverage and, all-weather day-and-night imaging capabilities. However, emergent vegetation, trees, wind or flow turbulence can increase radar back-scatter returns and pose problems for the delineation of inundated areas. In such areas, passive remote sensing data can be used to identify vegetated areas and support the interpretation of SAR data. The availability of new Earth Observation products, for example Sentinel-1 (active) and Sentinel-2 (passive) imageries, with both high spatial and temporal resolution, have the potential to facilitate flood detection and monitoring of surface waters changes which are very dynamic in space and time. In this context, the research consists of two parts. In the first part, the objective is to propose generic and reproducible methodologies for the analysis of Sentinel-1 time series data for floods detection and surface waters mapping. The processing chain comprises a series of pre-processing steps and the statistical modeling of the pixel value distribution to produce probabilistic maps for the presence of surface waters. Images pre-processing for all Sentinel-1 images comprise the reduction SAR effect like orbit errors, speckle noise, and geometric effects. A modified Split Based Approach (MSBA) is used in order to focus on surface water areas automatically and facilitate the estimation of class models for water and non-water areas. A Finite Mixture Model is employed as the underlying statistical model to produce probabilistic maps. Subsequently, bilateral filtering is applied to take into account spatial neighborhood relationships in the generation of final map. The elimination of shadows effect is performed in a post-processing step. The processing chain is tested on three case studies. The first case is a flood event in central Ireland, the second case is located in Yorkshire county / Great Britain, and the third test case covers a recent flood event in northern Italy. The tests showed that the modified SBA step and the Finite Mixture Models can be applied for the automatic surface water detection in a variety of test cases. An evaluation again Copernicus products derived from very-high resolution imagery was performed, and showed a high overall accuracy and F-measure of the obtained maps. This evaluation also showed that the use of probability maps and bilateral filtering improved the accuracy of classification results significantly. Based on this quantitative evaluation, it is concluded that the processing chain can be applied for flood mapping from Sentinel-1 data. To estimate robust statistical distributions the method requires sufficient surface waters areas in the observed zone and sufficient contrast between surface waters and other land use classes. Ongoing research addresses the fusion of Sentinel-1 and passive remote sensing data (e.g. Sentinel-2) in order to reduce the current shortcomings in the developed processing chain. In this work, fusion is performed at the feature level to better account for the difference image properties of SAR and optical sensors. Further, the processing chain is currently being optimized in terms of calculation time for a further integration as a flood mapping service on the A2S (Alsace Aval Sentinel) high-performance computing infrastructure of University of Strasbourg.

A mediation model to explain decision making under conditions of risk among adolescents: the role of fluid intelligence and probabilistic reasoning.

PubMed

Donati, Maria Anna; Panno, Angelo; Chiesi, Francesca; Primi, Caterina

2014-01-01

This study tested the mediating role of probabilistic reasoning ability in the relationship between fluid intelligence and advantageous decision making among adolescents in explicit situations of risk--that is, in contexts in which information on the choice options (gains, losses, and probabilities) were explicitly presented at the beginning of the task. Participants were 282 adolescents attending high school (77% males, mean age = 17.3 years). We first measured fluid intelligence and probabilistic reasoning ability. Then, to measure decision making under explicit conditions of risk, participants performed the Game of Dice Task, in which they have to decide among different alternatives that are explicitly linked to a specific amount of gain or loss and have obvious winning probabilities that are stable over time. Analyses showed a significant positive indirect effect of fluid intelligence on advantageous decision making through probabilistic reasoning ability that acted as a mediator. Specifically, fluid intelligence may enhance ability to reason in probabilistic terms, which in turn increases the likelihood of advantageous choices when adolescents are confronted with an explicit decisional context. Findings show that in experimental paradigm settings, adolescents are able to make advantageous decisions using cognitive abilities when faced with decisions under explicit risky conditions. This study suggests that interventions designed to promote probabilistic reasoning, for example by incrementing the mathematical prerequisites necessary to reason in probabilistic terms, may have a positive effect on adolescents' decision-making abilities.

Recommendations for the user-specific enhancement of flood maps

NASA Astrophysics Data System (ADS)

Meyer, V.; Kuhlicke, C.; Luther, J.; Fuchs, S.; Priest, S.; Dorner, W.; Serrhini, K.; Pardoe, J.; McCarthy, S.; Seidel, J.; Palka, G.; Unnerstall, H.; Viavattene, C.; Scheuer, S.

2012-05-01

The European Union Floods Directive requires the establishment of flood maps for high risk areas in all European member states by 2013. However, the current practice of flood mapping in Europe still shows some deficits. Firstly, flood maps are frequently seen as an information tool rather than a communication tool. This means that, for example, local stocks of knowledge are not incorporated. Secondly, the contents of flood maps often do not match the requirements of the end-users. Finally, flood maps are often designed and visualised in a way that cannot be easily understood by residents at risk and/or that is not suitable for the respective needs of public authorities in risk and event management. The RISK MAP project examined how end-user participation in the mapping process may be used to overcome these barriers and enhance the communicative power of flood maps, fundamentally increasing their effectiveness. Based on empirical findings from a participatory approach that incorporated interviews, workshops and eye-tracking tests, conducted in five European case studies, this paper outlines recommendations for user-specific enhancements of flood maps. More specific, recommendations are given with regard to (1) appropriate stakeholder participation processes, which allow incorporating local knowledge and preferences, (2) the improvement of the contents of flood maps by considering user-specific needs and (3) the improvement of the visualisation of risk maps in order to produce user-friendly and understandable risk maps for the user groups concerned. Furthermore, "idealised" maps for different user groups are presented: for strategic planning, emergency management and the public.

A probabilistic analysis of the crystal oscillator behavior at low drive levels

NASA Astrophysics Data System (ADS)

Shmaliy, Yuriy S.; Brendel, Rémi

2008-03-01

The paper discusses a probabilistic model of a crystal oscillator at low drive levels where the noise intensity is comparable with the oscillation amplitude. The stationary probability density of the oscillations envelope is derived and investigated for the nonlinear resonator loses. A stochastic explanation is given for the well-known phenomenon termed sleeping sickness associated with losing a facility of self-excitation by a crystal oscillator after a long storage without a power supply. It is shown that, with low drive levels leading to an insufficient feedback, a crystal oscillator generates the noise-induced oscillations rather than it absolutely "falls in sleep".

Flash floods warning technique based on wireless communication networks data

NASA Astrophysics Data System (ADS)

David, Noam; Alpert, Pinhas; Messer, Hagit

2010-05-01

Flash floods can occur throughout or subsequent to rainfall events, particularly in cases where the precipitation is of high-intensity. Unfortunately, each year these floods cause severe property damage and heavy casualties. At present, there are no sufficient real time flash flood warning facilities found to cope with this phenomenon. Here we show the tremendous potential of flash floods advanced warning based on precipitation measurements of commercial microwave links. As was recently shown, wireless communication networks supply high resolution precipitation measurements at ground level while often being situated in flood prone areas, covering large parts of these hazardous regions. We present the flash flood warning potential of the wireless communication system for two different cases when floods occurred at the Judean desert and at the northern Negev in Israel. In both cases, an advanced warning regarding the hazard could have been announced based on this system. • This research was supported by THE ISRAEL SCIENCE FOUNDATION (grant No. 173/08). This work was also supported by a grant from the Yeshaya Horowitz Association, Jerusalem. Additional support was given by the PROCEMA-BMBF project and by the GLOWA-JR BMBF project.

Improving precipitation estimates over the western United States using GOES-R precipitation data

NASA Astrophysics Data System (ADS)

Karbalaee, N.; Kirstetter, P. E.; Gourley, J. J.

2017-12-01

Satellite remote sensing data with fine spatial and temporal resolution are widely used for precipitation estimation for different applications such as hydrological modeling, storm prediction, and flash flood monitoring. The Geostationary Operational Environmental Satellites-R series (GOES-R) is the next generation of environmental satellites that provides hydrologic, atmospheric, and climatic information every 30 seconds over the western hemisphere. The high-resolution and low-latency of GOES-R observations is essential for the monitoring and prediction of floods, specifically in the Western United States where the vantage point of space can complement the degraded weather radar coverage of the NEXRAD network. The GOES-R rainfall rate algorithm will yield deterministic quantitative precipitation estimates (QPE). Accounting for inherent uncertainties will further advance the GOES-R QPEs since with quantifiable error bars, the rainfall estimates can be more readily fused with ground radar products. On the ground, the high-resolution NEXRAD-based precipitation estimation from the Multi-Radar/Multi-Sensor (MRMS) system, which is now operational in the National Weather Service (NWS), is challenged due to a lack of suitable coverage of operational weather radars over complex terrain. Distribution of QPE uncertainties associated with the GOES-R deterministic retrievals are derived and analyzed using MRMS over regions with good radar coverage. They will be merged with MRMS-based probabilistic QPEs developed to advance multisensor QPE integration. This research aims at improving precipitation estimation over the CONUS by combining the observations from GOES-R and MRMS to provide consistent, accurate and fine resolution precipitation rates with uncertainties over the CONUS.

46 CFR 62.35-10 - Flooding safety.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 2 2014-10-01 2014-10-01 false Flooding safety. 62.35-10 Section 62.35-10 Shipping... Requirements for Specific Types of Automated Vital Systems § 62.35-10 Flooding safety. (a) Automatic bilge.... (b) Remote controls for flooding safety equipment must remain functional under flooding conditions to...

46 CFR 62.35-10 - Flooding safety.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 2 2013-10-01 2013-10-01 false Flooding safety. 62.35-10 Section 62.35-10 Shipping... Requirements for Specific Types of Automated Vital Systems § 62.35-10 Flooding safety. (a) Automatic bilge.... (b) Remote controls for flooding safety equipment must remain functional under flooding conditions to...

46 CFR 62.35-10 - Flooding safety.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 2 2012-10-01 2012-10-01 false Flooding safety. 62.35-10 Section 62.35-10 Shipping... Requirements for Specific Types of Automated Vital Systems § 62.35-10 Flooding safety. (a) Automatic bilge.... (b) Remote controls for flooding safety equipment must remain functional under flooding conditions to...

46 CFR 62.35-10 - Flooding safety.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 2 2011-10-01 2011-10-01 false Flooding safety. 62.35-10 Section 62.35-10 Shipping... Requirements for Specific Types of Automated Vital Systems § 62.35-10 Flooding safety. (a) Automatic bilge.... (b) Remote controls for flooding safety equipment must remain functional under flooding conditions to...

46 CFR 62.35-10 - Flooding safety.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Flooding safety. 62.35-10 Section 62.35-10 Shipping... Requirements for Specific Types of Automated Vital Systems § 62.35-10 Flooding safety. (a) Automatic bilge.... (b) Remote controls for flooding safety equipment must remain functional under flooding conditions to...

Review of Selected Documents Related to Flooding at City of Salisbury Facilities on the Yadkin River Upstream from High Rock Dam, North Carolina, September 2007

USGS Publications Warehouse

Bales, Jerad D.

2007-01-01

This report documents a review of the hydraulic and sediment-transport models developed by the City of Salisbury, Alcoa Power Generating, Inc., and the Federal Energy Regulatory Commission to address issues of flooding and sedimentation in the vicinity of Salisbury's water-supply intake 19.4 miles upstream from High Rock Dam. The objective of the review was to determine if the modeling results submitted by Salisbury clearly demonstrate that the presence of High Rock Dam has led to an increase in water levels at Salisbury facilities or, conversely, if the documents of Alcoa Power Generating, Inc., demonstrate that High Rock Dam has not had an effect on water levels at Salisbury facilities. No new data were collected as a part of the review, and the models developed by involved parties were not tested during the review. Some historical discharge-measurement notes and previously published reports were checked as part of the review. The one-dimensional hydraulic modeling results submitted by Alcoa Power Generating, Inc., did not assess the effects of changes in bathymetry on changes in flood levels at Salisbury's facilities because pre-impoundment conditions were not simulated. Hydraulic modeling performed by consultants for the City of Salisbury seems to indicate that both the presence of the dam in the absence of any post-impoundment sedimentation and changes in bathymetry between pre-impoundment and 1997 conditions have resulted in increased water levels relative to pre-impoundment conditions at Salisbury facilities on the Yadkin River for a fairly wide range of flows. The degree to which the dam and the changes in bathymetry have affected flood levels at the Salisbury facilities relative to pre-impoundment conditions is open to discussion because of uncertainty in topographic/bathymetric data and the absence of calibration and sensitivity testing of the hydraulic models. None of the three hydraulic models appears to have been calibrated to or tested against measurements, and no sensitivity testing was reported. Sediment-transport modeling results submitted by the City of Salisbury were calibrated, well documented, and provide a good understanding of the expected growth of the sediment delta in the upper end of High Rock Lake. Simulations made using this model seem to have demonstrated that the presence of the dam and the growth of the delta have resulted in increases in water-surface elevations at Salisbury's facilities over a range of flows and that these increases are expected to increase through time if current conditions remain unchanged.

Integration of social vulnerability into emergency management plans: designing of evacuation routes against flood disasters

NASA Astrophysics Data System (ADS)

Aroca-Jimenez, Estefanía; Bodoque, Jose Maria; Garcia, Juan Antonio; Diez-Herrero, Andres

2017-04-01

Flash floods are highly spatio-temporal localized flood events characterized by reaching a high peak flow in a very short period of time, i.e., generally with times of concentration lower than six hours. Its short duration, which limits or even voids any warning time, means that flash floods are considered to be one of the most destructive natural hazards with the greatest capacity to generate risk, either in terms of the number of people affected globally or the proportion of individual fatalities. The above highlights the importance of a realistic and appropriate design of evacuation strategies in order to reduce flood-related losses, being evacuation planning considered of critical importance for disaster management. Traditionally, evacuation maps have been based on flood-prone areas, shelters or emergency residences location and evacuation routes information. However, evacuation plans rarely consider the spatial distribution of vulnerable population (i.e., people with special needs, mobility constraints or economic difficulties), which usually require assistance from emergency responders. The goal of this research is to elaborate an evacuation map against the occurrence of flash floods by combining geographic information (e.g. roads, health facilities location, sanitary helicopters) and social vulnerability patterns, which are previously obtained from socioeconomic variables (e.g. population, unemployment, dwelling characteristics). To do this, ArcGis Network Analyst tool is used, which allows to calculate the optimal evacuation routes. The methodology proposed here is implemented in the region of Castilla y León (94,230 km2). Urban areas prone to flash flooding are identified taking into account the following requirements: i) city centers are crossed by rivers or streams with a longitudinal slope higher than 0.01 m m-1; ii) city centers are potentially affected by flash floods; and iii) city centers are affected by an area with low or exceptional probability of flooding (i.e., 500-year flood). A total of 3 evacuation routes were designed and automatically traced for each of the 39 urban areas identified as interest, considering the nearest: i) health facility, ii) hospital; and iii) evacuation area (i.e. sports halls or any other). The suitable elaboration of evacuation plans is really important in small mountainous areas prone to flash flooding as they are managed by local organisms where available economic resources are often limited. Furthermore, the short response time obliges emergency responders to act efficiently, which requires the design of evacuation plans taking into account certain social characteristics for evacuation routes designing.

24 CFR 55.12 - Inapplicability of 24 CFR part 55 to certain categories of proposed actions.

Code of Federal Regulations, 2011 CFR

2011-04-01

... communities that are in the Regular Program of the National Flood Insurance Program (NFIP) and in good... facilities, and intermediate care facilities) in communities that are in good standing under the NFIP. (3) HUD mortgage insurance actions for the repair, rehabilitation, modernization or improvement of...

18 CFR 1304.406 - Removal of unauthorized, unsafe, and derelict structures or facilities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 2 2010-04-01 2010-04-01 false Removal of unauthorized, unsafe, and derelict structures or facilities. 1304.406 Section 1304.406 Conservation of Power and Water... flood control) is anchored, installed, constructed, or moored in a manner inconsistent with this part...

Assessing the Congregate Disaster Shelter: Using Shelter Facility Assessment Data for Evaluating Potential Hazards to Occupants During Disasters.

PubMed

Cruz, Miguel A; Garcia, Stephanie; Chowdhury, Muhammad A B; Malilay, Josephine; Perea, Nancy; Williams, O Dale

Disaster shelter assessments are environmental health assessments conducted during disaster situations to evaluate the living environment of shelters for hygiene, sanitation, and safety conditions. We conducted a secondary data analysis of shelter assessment records available (n = 108) on ice storms, floods, and tornado events from 1 state jurisdiction. Descriptive statistics were used to analyze results of environmental health deficiencies found in the facilities. The greater numbers of environmental health deficiencies were associated with sanitation (26%), facility physical issues (19%), and food areas (17%). Most deficiencies were reported following ice storms, tornadoes, and flood events. This report describes the first analysis of environmental health deficiencies found in disaster shelters across a spectrum of disaster events. Although the number of records analyzed for this project was small and results may not be generalizable, this new insight into the living environment in shelter facilities offers the first analysis of deficiencies of the shelter operation and living environment that have great potential to affect the safety and health of shelter occupants.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing.

PubMed

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

PubMed Central

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. PMID:29062288

77 FR 21595 - Applications and Amendments to Facility Operating Licenses and Combined Licenses Involving...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-10

... must be one which, if proven, would entitle the requestor/petitioner to relief. A requestor/ petitioner..., and fire modeling calculations, have been performed to demonstrate that the performance-based... may include engineering evaluations, probabilistic safety assessments, and fire modeling calculations...

Extending the flood record on the Middle Gila River with Holocene stratigraphy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huckleberry, G.

1993-04-01

Historical changes in flood frequency and magnitude are correlated to changes in channel geometry for the Middle Gila River (MGR) in south-central Arizona. The author has attempted to reconstruct the frequency of large floods on the MGR for the last 1,000 years by looking at the stratigraphic record with the purpose of modeling channel changes during a period of significant local cultural change, i.e., the Hohokam-Pima cultural transition. After distinguishing and mapping geological surfaces in the eastern part of the Gila River Indian Community. The author placed a series of backhoe trenches on late Holocene MGR terraces. He interprets lithologicalmore » discontinuities within overbank deposits as boundaries separating temporally discrete floods. Detrital charcoal from within the stratigraphy was submitted to the National Science Foundation-University of Arizona AMS facility for radiocarbon analysis. The stratigraphic record indicates that a minimum of four large floods have occurred on the MGR since A.D. 1300. Three of these floods may correspond to large historical floods in 1833, 1868, and 1905. If so, then it appears that MGR flood frequency increased after A.D. 1800. There is no evidence for increased flood frequency and channel transformations during the cultural decline of the Hohokam in the 15th century.« less

Risk factors of diarrhoea among flood victims: a controlled epidemiological study.

PubMed

Mondal, N C; Biswas, R; Manna, A

2001-01-01

The concept and practice of 'disaster preparedness and response', instead of traditional casualty relief, is relatively new. Vulnerability analysis and health risks assessment of disaster prone communities are important prerequisites of meaningful preparedness and effective response against any calamity. In this community based study, the risk of diarrhoeal disease and its related epidemiological factors were analysed by collecting data from two selected flood prone block of Midnapur district of West Bengal. The information was compared with that of another population living in two non-flood prone blocks of the same district. The study showed that diarrhoeal disease was the commonest morbidity in flood prone population. Some behaviours, like use of pond water for utensil wash and kitchen purpose, hand washing after defecation without soap, improper hand washing before eating, open field defecation, storage of drinking water in wide mouth vessels etc. were found to be associated with high attack rate of diarrhoea, in both study and control population during flood season compared to pre-flood season. Attack rates were also significantly higher in flood prone population than that of population in non-flood prone area during the same season. Necessity of both community education for proper water use behaviour and personal hygiene along with ensuring safe water and sanitation facilities of flood affected communities were emphasized.

30 CFR 762.5 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... dunes, severe wind or soil erosion, frequent flooding, avalanches and areas of unstable geology...-handling, preparation, extraction or storage facilities, and other capital-intensive activities. Costs of...

30 CFR 762.5 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... dunes, severe wind or soil erosion, frequent flooding, avalanches and areas of unstable geology...-handling, preparation, extraction or storage facilities, and other capital-intensive activities. Costs of...

30 CFR 762.5 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... dunes, severe wind or soil erosion, frequent flooding, avalanches and areas of unstable geology...-handling, preparation, extraction or storage facilities, and other capital-intensive activities. Costs of...

Overview of environmental and hydrogeologic conditions at Tanana, Alaska

USGS Publications Warehouse

Nakanishi, Allan S.; Dorava, Joseph M.

1994-01-01

The remote Native village of Tanana along the Yukon River in west-central Alaska has long cold winters and short summers. The Federal Aviation Administration owns or operates airway support facilities near Tanana and wishes to consider the subsistence lifestyle of the residents and the quality of the current environment when evaluating the severity of environmental contamination at these facilities. Tanana is located on the flood plain of the Yukon River and obtains its drinking water from a shallow aquifer located in thick alluvium underlying the village. Surface spills and disposal of hazardous materials combined with annual flooding of the Yukon River may affect the quality of the ground water. Alternative drinking-water sources are available, but may cost more than existing supplies.

Overview of environmental and hydrogeologic conditions at Saint Marys, Alaska

USGS Publications Warehouse

Nakanishi, Allan S.; Dorava, Joseph M.

1994-01-01

The Federal Aviation Administration (FAA) owns or operates airway support facilities near Saint Marys along the Yukon River in west-central Alaska. The FAA is evaluating the severity of environmental contamination and options for remediation of environmental contamination at their facilities. Saint Marys is on a flood plain near the continence of the Yukon and Andreafsky Rivers and has long cold winters and short summers. Residents obtain their drinking water from an infiltration gallery fed by a creek near the village. Surface spills and disposal of hazardous materials combined with potential flooding may affect the quality of the surface and ground water. Alternative drinking-water sources are available, but would likely cost more than existing supplies to develop.

Feedback from uncertainties propagation research projects conducted in different hydraulic fields: outcomes for engineering projects and nuclear safety assessment.

NASA Astrophysics Data System (ADS)

Bacchi, Vito; Duluc, Claire-Marie; Bertrand, Nathalie; Bardet, Lise

2017-04-01

In recent years, in the context of hydraulic risk assessment, much effort has been put into the development of sophisticated numerical model systems able reproducing surface flow field. These numerical models are based on a deterministic approach and the results are presented in terms of measurable quantities (water depths, flow velocities, etc…). However, the modelling of surface flows involves numerous uncertainties associated both to the numerical structure of the model, to the knowledge of the physical parameters which force the system and to the randomness inherent to natural phenomena. As a consequence, dealing with uncertainties can be a difficult task for both modelers and decision-makers [Ioss, 2011]. In the context of nuclear safety, IRSN assesses studies conducted by operators for different reference flood situations (local rain, small or large watershed flooding, sea levels, etc…), that are defined in the guide ASN N°13 [ASN, 2013]. The guide provides some recommendations to deal with uncertainties, by proposing a specific conservative approach to cover hydraulic modelling uncertainties. Depending of the situation, the influencing parameter might be the Strickler coefficient, levee behavior, simplified topographic assumptions, etc. Obviously, identifying the most influencing parameter and giving it a penalizing value is challenging and usually questionable. In this context, IRSN conducted cooperative (Compagnie Nationale du Rhone, I-CiTy laboratory of Polytech'Nice, Atomic Energy Commission, Bureau de Recherches Géologiques et Minières) research activities since 2011 in order to investigate feasibility and benefits of Uncertainties Analysis (UA) and Global Sensitivity Analysis (GSA) when applied to hydraulic modelling. A specific methodology was tested by using the computational environment Promethee, developed by IRSN, which allows carrying out uncertainties propagation study. This methodology was applied with various numerical models and in different contexts, as river flooding on the Rhône River (Nguyen et al., 2015) and on the Garonne River, for the studying of local rainfall (Abily et al., 2016) or for tsunami generation, in the framework of the ANR-research project TANDEM. The feedback issued from these previous studies is analyzed (technical problems, limitations, interesting results, etc…) and the perspectives and a discussion on how a probabilistic approach of uncertainties should improve the actual deterministic methodology for risk assessment (also for other engineering applications) will be finally given.

76 FR 46715 - Proposed Flood Elevation Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-03

... table provided here represents the flooding sources, location of referenced elevations, effective and.... Specifically, it addresses the following flooding sources: Cabin Branch, Franklin Branch, Hall Creek, Little... Incorporated Areas'' addressed the following flooding sources: Cabin Branch, Franklin Branch, Little Patuxent...

SSHAC Level 1 Probabilistic Seismic Hazard Analysis for the Idaho National Laboratory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Payne, Suzette Jackson; Coppersmith, Ryan; Coppersmith, Kevin

A Probabilistic Seismic Hazard Analysis (PSHA) was completed for the Materials and Fuels Complex (MFC), Advanced Test Reactor (ATR), and Naval Reactors Facility (NRF) at the Idaho National Laboratory (INL). The PSHA followed the approaches and procedures for Senior Seismic Hazard Analysis Committee (SSHAC) Level 1 study and included a Participatory Peer Review Panel (PPRP) to provide the confident technical basis and mean-centered estimates of the ground motions. A new risk-informed methodology for evaluating the need for an update of an existing PSHA was developed as part of the Seismic Risk Assessment (SRA) project. To develop and implement the newmore » methodology, the SRA project elected to perform two SSHAC Level 1 PSHAs. The first was for the Fuel Manufacturing Facility (FMF), which is classified as a Seismic Design Category (SDC) 3 nuclear facility. The second was for the ATR Complex, which has facilities classified as SDC-4. The new methodology requires defensible estimates of ground motion levels (mean and full distribution of uncertainty) for its criteria and evaluation process. The INL SSHAC Level 1 PSHA demonstrates the use of the PPRP, evaluation and integration through utilization of a small team with multiple roles and responsibilities (four team members and one specialty contractor), and the feasibility of a short duration schedule (10 months). Additionally, a SSHAC Level 1 PSHA was conducted for NRF to provide guidance on the potential use of a design margin above rock hazard levels for the Spent Fuel Handling Recapitalization Project (SFHP) process facility.« less

PoliRisposta: Overcoming present limits of flood damage data

NASA Astrophysics Data System (ADS)

Molinari, Daniela; Mazuran, Mirjana; Arias, Carolina; Minucci, Guido; Atun, Funda; Ardagna, Danilo

2014-05-01

Already in the Fifties, US researchers identified the main weakness of flood records in the inadequacy of flood damage data. The recent seminar "Flood damage survey and assessment: which priorities for future research and practice?", held at Politecnico di Milano on 24-25 January 2012, highlighted that poor and insufficient flood loss data is still a matter of concern. In detail, participants concluded that the lack of damage data and of innovative approaches for their analysis (e.g. multivariate approaches, data mining) is one of the main causes of the shortcomings of present risk assessment tools; among them: the uncertainty of flood risk predictions and the limited capacity of estimating damages apart from the direct ones to residential sector (i.e. indirect/intangible damages). On the other hand, flood damage data collected in the aftermath of a disastrous event can support a variety of actions besides the validation/definition of damage models: the identification of priorities for intervention during emergencies, the creation of complete event scenarios on the bases of which understating the fragilities of the flooded areas as well as defining compensation schemes. However, few efforts have been addressed so far on the improvement of the way in which data are presently collected and stored. The aim of this presentation is to discuss first results of Poli-RISPOSTA (stRumentI per la protezione civile a Supporto delle POpolazioni nel poST Alluvione), a research project founded by Politecnico di Milano which is just intended to develop tools and procedures for the collection and storage of high quality, consistent and reliable flood damage data. In detail, specific objectives of Poli-RISPOSTA are: - Develop an operational procedure for collecting, storing and analyzing all damage data, in the aftermath of flood event, including: damage to infrastructures and public facilities, damage suffered by citizens and their dwellings and goods, and to economic activities; - Develop educational material and modules for training practitioners in the use of the procedure; - Develop enhanced IT tools (both hardware and software) to support the procedure, easing as much as possible the collection of field data, the creation of databases and the connection between the latter and different regional and municipal databases that already exist for different purposes (from cadastral data, to satellite images, etc.). Results will be discussed with respect to first applications in the Umbria Region (Central Italy). Emphasis will be put on the utility of results for damage modelling, risk mitigation and emergency management.

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

USGS Publications Warehouse

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Hydraulic and hydrologic aspects of flood-plain planning

USGS Publications Warehouse

Wiitala, S.W.; Jetter, K.R.; Sommerville, Alan J.

1961-01-01

The valid incentives compelling occupation of the flood plain, up to and eve n into the stream channel, undoubtedly have contributed greatly to the development of the country. But the result has been a heritage of flood disaster, suffering, and enormous costs. Flood destruction awakened a consciousness toward reduction and elimination of flood hazards, originally manifested in the protection of existing developments. More recently, increased knowledge of the problem has shown the impracticability of permitting development that requires costly flood protect/on. The idea of flood zoning, or flood-plain planning, has received greater impetus as a result of this realization. This study shows how hydraulic and hydrologic data concerning the flood regimen of a stream can be used in appraising its flood potential and the risk inherent in occupation of its flood plain. The approach involves the study of flood magnitudes as recorded or computed; flood frequencies based1 on experience shown by many years of gaging-station record; use of existing or computed stagedischarge relations and flood profiles; and, where required, the preparation of flood-zone maps to show the areas inundated by floods of several magnitudes and frequencies. The planner can delineate areas subject to inundation by floods o* specific recurrence intervals for three conditions: (a) for the immediate vicinity of a gaging station; (b) for a gaged stream at a considerable distance from a gaging station; and (c) for an ungaged stream. The average depth for a flood of specific frequency can be estimated on the basis of simple measurements of area of drainage basin, width of channel, and slope of streambed. This simplified approach should be useful in the initial stages of flood-plain planning. Brief discussions are included on various types of flood hazards, the effects of urbanization on flood runoff, and zoning considerations.

76 FR 43965 - Proposed Flood Elevation Determinations; Correction

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-22

... FR 70944. The table provided here represents the flooding sources, location of referenced elevations... Areas. Specifically, it addresses the flooding sources Cumberland River (Lake Barkley) and Tennessee... County, Kentucky, and Incorporated Areas'' addressed the flooding sources Cumberland River (Lake Barkley...

77 FR 15664 - Proposed Flood Elevation Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-16

... table provided here represents the flooding sources, location of referenced elevations, and effective and modified elevations for the City of Cadiz, Kentucky. Specifically, it addresses the flooding... Cadiz, Kentucky'' addressed the flooding sources Little River (backwater effects from Lake Barkley) and...

Floods of 1971 and 1972 on Glover Creek and Little River in southeastern Oklahoma

USGS Publications Warehouse

Thomas, Wilbert O.; Corley, Robert K.

1973-01-01

Heavy rains of December 9-10, 1971, and Oct. 30-31, 1972, caused outstanding floods on Glover Creek and Little River in McCurtain County in southeastern Oklahoma. This report presents hydrologic data that document the extent of flooding, flood profiles, and frequency of flooding on reaches of both streams. The data presented provide a technical basis for formulating effective flood-plain zoning that will minimize existing and future flood problems. The report also can be useful for locating waste-disposal and water-treatment facilities, and for the development of recreational areas. The area studied includes the reach of Little River on the Garvin and Idabel 7 1/2-minute quadrangles (sheet 1) and the reach of Glover Creek on the southwest quarter of the Golden 15-minute quadrangle (sheet 2). The flood boundaries delineated on the maps are the limits of flooding during the December 1971 and October 1972 floods. Any attempt to delineate the flood boundaries on streams in the study area other than Glover Creek and Little River was considered to be beyond the scope of this report. The general procedure used in defining the flood boundaries was to construct the flood profiles from high-water marks obtained by field surveys and by records at three stream-gaging stations (two on Little River and one on Glover Creek.). The extent of flooding was delineated on the topographic maps by using the flood profiles to define the flood elevations at various points along the channel and locating the elevations on the map by interpolating between contours (lines of equal ground elevation). In addition, flood boundaries were defined in places by field survey, aerial photographs, and information from local residents. The accuracy of the flood boundaries is consistent with the scale and contour interval of the maps (1 inch = 2,000 feet; contour interval 10 and 20 feet), which means the flood boundaries are drawn as accurately as possible on maps having 10- and 20-foot contour intervals.

Flooding and Implosive Therapy with Situation Specific and Non-Situation Specific Anxiety.

ERIC Educational Resources Information Center

Boudewyns, Patrick A.

Two inpatients, one with a circumscribed phobia for dentists and dental offices and another who had been diagnosed as suffering from an anxiety neurosis, were treated with a flooding procedure. A simple flooding technique which dealt with only the symptom contingent cues was sufficient to change behavior in the former case, but for the relatively…

Research on the effect of rainfall flood regulation and control of wetland park based on SWMM model—a case study of wetland park in Yuanjia village, Qishan county, Shaanxi province

NASA Astrophysics Data System (ADS)

Xu, Da; Liu, Yijie

2018-02-01

Taking the wetland park of Yuan Village in Qishan County of Shaanxi Province as the research object, this paper makes a reasonable generalization of the study area, and establishes two models of low impact development (LID) and traditional development in the park. Meantime, rainwater in the surrounding built up area is introduced to into the park for digestion. SWMM model is used to simulate the variation of the total runoff, peak flow and peak time of two development models in Wetland Park under one-hour rainfall at different recurrence periods.The runoff control effect in each single LID facility in the one-hour rainfall once during five years in the built-up area is simulated. The simulation results show that the SWMM model can not only quantify the runoff reduction effect of different LID facilities, but also provide theoretical basis and data support for the urban rainfall flood problem. LID facilities have effects on runoff reduction and peak delay. However, the combined LID facility has obvious advantages for the peak time delay and peak flow control. A single LID facility is more efficient in a single runoff volume control. The order of runoff reduction by various LID facilities is as follows: Rain garden>combined LID facility> vegetative swale> bio-retention cell > permeable pavement. The order of peak time delay effect by the LID facilities is as follows: combined LID facility> Rain garden> vegetative swale> bio-retention cell > permeable pavement. The order of peak flow reduction efficiency by various LID facilities is: combined LID facility> Rain garden> bio-retention cell > vegetative swale> permeable pavement.

Experimental modelling of outburst flood - bed interactions

NASA Astrophysics Data System (ADS)

Carrivick, J. L.; Xie, Z.; Sleigh, A.; Hubbard, M.

2009-04-01

Outburst floods are a sudden release and advancing wave of water and sediment, with a peak discharge that is often several orders of magnitude greater than perennial flows. Common outburst floods from natural sources include those from glacial and moraine-impounded lakes, freshwater dyke and levee bursts, volcanic debris dams, landslides, avalanches, coastal bay-bars, and those from tree or vegetation dams. Outburst flood hazards are regularly incorporated into risk assessments for urban, coastal and mountainous areas, for example. Outburst flood hazards are primarily due to direct impacts, caused by a frontal surge wave, from debris within a flow body, and from the mass and consistency of the flows. A number of secondary impacts also pose hazards, including widespread deposition of sediment and blocked tributary streams. It is rapid landscape change, which is achieved the mobilization and redistribution of sediment that causes one of the greatest hazards due to outburst floods. The aim of this project is therefore to parameterise hydrodynamic - sedimentary interactions in experimental outburst floods. Specifically, this project applies laboratory flume modelling, which offers a hitherto untapped opportunity for examining complex interactions between water and sediment within outburst floods. The experimental set-up is of a tradition lock-gate design with a straight 4 m long tank. Hydraulics are scaled at 1:20 froude scale and the following controls on frontal wave flow-bed interactions and hence on rapid landscape change are being investigated: 1. Pre-existing mobile sediment effects, fixed bed roughness effects, sediment concentration effects, mobile bed effects. An emphasis is being maintained on examining the downstream temporal and spatial change in physical character of the water / sediment frontal wave. Facilities are state-of-the-art with a fully-automated laser bed-profiler to measure bed elevation after a run, Seatek arrays to measure transient flow depths, 0.5 Hz Ultrasonic Velocimeter Profiling to measure within-flow velocities, and Ultrasonic High-Concentration Meter (UHCM) to measure sediment concentrations, for example, all at increments of space and time. These instruments can only be used without a mobile sediment bed and some could be rendered as a source of error because they are intrusive to the flow. Digital video and automated still photography is therefore also important for recording hydraulic and bedform changes through time in flows with freely-moving sediment. This paper will report initial results.

76 FR 28102 - Notice of Issuance of Regulatory Guide

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-13

..., Probabilistic Risk Assessment Branch, Division of Risk Analysis, Office of Nuclear Regulatory Research, U.S... approaches and methods (whether quantitative or qualitative, deterministic or probabilistic), data, and... uses in evaluating specific problems or postulated accidents, and data that the staff needs in its...

Data analysis using scale-space filtering and Bayesian probabilistic reasoning

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Kutulakos, Kiriakos; Robinson, Peter

1991-01-01

This paper describes a program for analysis of output curves from Differential Thermal Analyzer (DTA). The program first extracts probabilistic qualitative features from a DTA curve of a soil sample, and then uses Bayesian probabilistic reasoning to infer the mineral in the soil. The qualifier module employs a simple and efficient extension of scale-space filtering suitable for handling DTA data. We have observed that points can vanish from contours in the scale-space image when filtering operations are not highly accurate. To handle the problem of vanishing points, perceptual organizations heuristics are used to group the points into lines. Next, these lines are grouped into contours by using additional heuristics. Probabilities are associated with these contours using domain-specific correlations. A Bayes tree classifier processes probabilistic features to infer the presence of different minerals in the soil. Experiments show that the algorithm that uses domain-specific correlation to infer qualitative features outperforms a domain-independent algorithm that does not.

Non-Deterministic Dynamic Instability of Composite Shells

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2004-01-01

A computationally effective method is described to evaluate the non-deterministic dynamic instability (probabilistic dynamic buckling) of thin composite shells. The method is a judicious combination of available computer codes for finite element, composite mechanics, and probabilistic structural analysis. The solution method is incrementally updated Lagrangian. It is illustrated by applying it to thin composite cylindrical shell subjected to dynamic loads. Both deterministic and probabilistic buckling loads are evaluated to demonstrate the effectiveness of the method. A universal plot is obtained for the specific shell that can be used to approximate buckling loads for different load rates and different probability levels. Results from this plot show that the faster the rate, the higher the buckling load and the shorter the time. The lower the probability, the lower is the buckling load for a specific time. Probabilistic sensitivity results show that the ply thickness, the fiber volume ratio and the fiber longitudinal modulus, dynamic load and loading rate are the dominant uncertainties, in that order.

76 FR 26981 - Proposed Flood Elevation Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-10

... table provided here represents the flooding sources, location of referenced elevations, effective and.... Specifically, it addresses the following flooding sources: Cache Creek, Cache Creek Left Bank Overflow, and... ``Unincorporated Areas of Yolo County, California'' addressed the flooding source Cache Creek Settling Basin. That...

76 FR 13570 - Proposed Flood Elevation Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-14

.... The table provided here represents the flooding sources, location of referenced elevations, effective.... Specifically, it addresses the flooding source South Creek. DATES: Comments are to be submitted on or before... table, entitled ``Sanpete County, Utah, and Incorporated Areas'' addressed the flooding source South...

77 FR 50667 - Proposed Flood Elevation Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-22

... table provided here represents the flooding sources, location of referenced elevations, effective and...). Specifically, it addresses the flooding sources Fourmile Creek and Lake Erie. DATES: Comments are to be... Jurisdictions)'' addressed the flooding sources Fourmile Creek and Lake Erie. That table contained inaccurate...

Flood hazard assessment of the Hoh River at Olympic National Park ranger station, Washington

USGS Publications Warehouse

Kresch, D.L.; Pierson, T.C.

1987-01-01

Federal regulations require buildings and public facilities on Federal land to be located beyond or protected from inundation by a 100-year flood. Flood elevations, velocities and boundaries were determined for the occurrence of a 100-year flood through a reach, approximately 1-mi-long, of the Hoh River at the ranger station complex in Olympic National Park. Flood elevations, estimated by step-backwater analysis of the 100-year flood discharge through 14 channel and flood-plain cross sections of the Hoh River, indicate that the extent of flooding in the vicinity of buildings or public facilities at the ranger station complex is likely to be limited mostly to two historic meander channels that lie partly within loop A of the public campground and that average flood depths of about 2 feet or less would be anticipated in these channels. Mean flow velocities at the cross sections, corresponding to the passage of a 100-year flood, ranged from about 5 to over 11 ft/sec. Flooding in the vicinity of either the visitors center or the residential and maintenance areas is unlikely unless the small earthen dam at the upstream end of Taft Creek were to fail. Debris flows with volumes on the order of 100 to 1,000 cu yards could be expected to occur in the small creeks that drain the steep valley wall north of the ranger station complex. Historic debris flows in these creeks have generally traveled no more than about 100 yards out onto the valley floor. The potential risk that future debris flows in these creeks might reach developed areas within the ranger station complex is considered to be small because most of the developed areas within the complex are situated more than 100 yards from the base of the valley wall. Landslides or rock avalanches originating from the north valley wall with volumes potentially much larger than those for debris flows could have a significant impact on the ranger station complex. The probability that such landslides or avalanches may occur is unknown. Inspection of aerial photographs of the Hoh River valley revealed the apparent presence, along the ridge crest of the north valley wall, of ridge-top depressions--geologic features that are sometimes associated with the onset of deep-seated slope failures. However, evaluation of the potential landslide hazard associated with these depressions would require an onsite examination of the area by trained personnel. Such an effort was outside the scope of this study. (Author 's abstract)

Process-informed extreme value statistics- Why and how?

NASA Astrophysics Data System (ADS)

Schumann, Andreas; Fischer, Svenja

2017-04-01

In many parts of the world, annual maximum series (AMS) of runoff consist of flood peaks, which differ in their genesis. There are several aspects why these differences should be considered: Often multivariate flood characteristics (volumes, shapes) are of interest. These characteristics depend on the flood types. For regionalization, the main impacts on the flood regime has to be specified. If this regime depends on different flood types, type-specific hydro-meteorological and/or watershed characteristics are relevant. The ratios between event types often change over the range of observations. If a majority of events, which belongs to certain flood type, dominates the extrapolation of a probability distribution function (pdf), it is a problem if this more frequent type would not be typical for extraordinary large extremes, determining the right tail of the pdf. To consider differences in flood origin, several problems has to be solved. The events have to be separated into different groups according to their genesis. This can be a problem for long past events where e.g. precipitation data are not available. Another problem consists in the flood type-specific statistics. If block maxima are used, the sample of floods belong to a certain type is often incomplete as other events are overlaying smaller events. Some practical useable statistical tools to solve this and other problems are presented in a case study. Seasonal models were developed which differ between winter and summer floods but also between events with long and short timescales. The pdfs of the two groups of summer floods are combined via a new mixing model. The application to German watersheds demonstrates the advantages of the new model, giving specific influence to flood types.

HEPS4Power - Extended-range Hydrometeorological Ensemble Predictions for Improved Hydropower Operations and Revenues

NASA Astrophysics Data System (ADS)

Bogner, Konrad; Monhart, Samuel; Liniger, Mark; Spririg, Christoph; Jordan, Fred; Zappa, Massimiliano

2015-04-01

In recent years large progresses have been achieved in the operational prediction of floods and hydrological drought with up to ten days lead time. Both the public and the private sectors are currently using probabilistic runoff forecast in order to monitoring water resources and take actions when critical conditions are to be expected. The use of extended-range predictions with lead times exceeding 10 days is not yet established. The hydropower sector in particular might have large benefits from using hydro meteorological forecasts for the next 15 to 60 days in order to optimize the operations and the revenues from their watersheds, dams, captions, turbines and pumps. The new Swiss Competence Centers in Energy Research (SCCER) targets at boosting research related to energy issues in Switzerland. The objective of HEPS4POWER is to demonstrate that operational extended-range hydro meteorological forecasts have the potential to become very valuable tools for fine tuning the production of energy from hydropower systems. The project team covers a specific system-oriented value chain starting from the collection and forecast of meteorological data (MeteoSwiss), leading to the operational application of state-of-the-art hydrological models (WSL) and terminating with the experience in data presentation and power production forecasts for end-users (e-dric.ch). The first task of the HEPS4POWER will be the downscaling and post-processing of ensemble extended-range meteorological forecasts (EPS). The goal is to provide well-tailored forecasts of probabilistic nature that should be reliable in statistical and localized at catchment or even station level. The hydrology related task will consist in feeding the post-processed meteorological forecasts into a HEPS using a multi-model approach by implementing models with different complexity. Also in the case of the hydrological ensemble predictions, post-processing techniques need to be tested in order to improve the quality of the forecasts against observed discharge. Analysis should be specifically oriented to the maximisation of hydroelectricity production. Thus, verification metrics should include economic measures like cost loss approaches. The final step will include the transfer of the HEPS system to several hydropower systems, the connection with the energy market prices and the development of probabilistic multi-reservoir production and management optimizations guidelines. The baseline model chain yielding three-days forecasts established for a hydropower system in southern-Switzerland will be presented alongside with the work-plan to achieve seasonal ensemble predictions.

Characterizing Macro Scale Patterns Of Uncertainty For Improved Operational Flood Forecasting Over The Conterminous United States

NASA Astrophysics Data System (ADS)

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

2015-12-01

The macro scale patterns of simulated streamflow errors are studied in order to characterize uncertainty in a hydrologic modeling system forced with the Multi-Radar/Multi-Sensor (MRMS; http://mrms.ou.edu) quantitative precipitation estimates for flood forecasting over the Conterminous United States (CONUS). The hydrologic model is centerpiece of the Flooded Locations And Simulated Hydrograph (FLASH; http://flash.ou.edu) real-time system. The hydrologic model is implemented at 1-km/5-min resolution to generate estimates of streamflow. Data from the CONUS-wide stream gauge network of the United States' Geological Survey (USGS) were used as a reference to evaluate the discrepancies with the hydrological model predictions. Streamflow errors were studied at the event scale with particular focus on the peak flow magnitude and timing. A total of 2,680 catchments over CONUS and 75,496 events from a 10-year period are used for the simulation diagnostic analysis. Associations between streamflow errors and geophysical factors were explored and modeled. It is found that hydro-climatic factors and radar coverage could explain significant underestimation of peak flow in regions of complex terrain. Furthermore, the statistical modeling of peak flow errors shows that other geophysical factors such as basin geomorphometry, pedology, and land cover/use could also provide explanatory information. Results from this research demonstrate the utility of uncertainty characterization in providing guidance to improve model adequacy, parameter estimates, and input quality control. Likewise, the characterization of uncertainty enables probabilistic flood forecasting that can be extended to ungauged locations.

Remote collection and analysis of witness reports on flash floods

NASA Astrophysics Data System (ADS)

Gourley, Jonathan; Erlingis, Jessica; Smith, Travis; Ortega, Kiel; Hong, Yang

2010-05-01

Typically, flash floods are studied ex post facto in response to a major impact event. A complement to field investigations is developing a detailed database of flash flood events, including minor events and null reports (i.e., where heavy rain occurred but there was no flash flooding), based on public survey questions conducted in near-real time. The Severe Hazards Analysis and Verification Experiment (SHAVE) has been in operation at the National Severe Storms Laboratory (NSSL) in Norman, OK, USA during the summers since 2006. The experiment employs undergraduate students to analyse real-time products from weather radars, target specific regions within the conterminous US, and poll public residences and businesses regarding the occurrence and severity of hail, wind, tornadoes, and now flash floods. In addition to providing a rich learning experience for students, SHAVE has been successful in creating high-resolution datasets of severe hazards used for algorithm and model verification. This talk describes the criteria used to initiate the flash flood survey, the specific questions asked and information entered to the database, and then provides an analysis of results for flash flood data collected during the summer of 2008. It is envisioned that specific details provided by the SHAVE flash flood observation database will complement databases collected by operational agencies and thus lead to better tools to predict the likelihood of flash floods and ultimately reduce their impacts on society.

Probabilistic flood inundation prediction within a coupled hydrodynamic, distributed hydrologic modeling framework

NASA Astrophysics Data System (ADS)

Adams, T. E.

2016-12-01

Accurate and timely predictions of the lateral exent of floodwaters and water level depth in floodplain areas are critical globally. This paper demonstrates the coupling of hydrologic ensembles, derived from the use of numerical weather prediction (NWP) model forcings as input to a fully distributed hydrologic model. Resulting ensemble output from the distributed hydrologic model are used as upstream flow boundaries and lateral inflows to a 1-D hydrodynamic model. An example is presented for the Potomac River in the vicinity of Washington, DC (USA). The approach taken falls within the broader goals of the Hydrologic Ensemble Prediction EXperiment (HEPEX).

Site-wide seismic risk model for Savannah River Site nuclear facilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eide, S.A.; Shay, R.S.; Durant, W.S.

1993-09-01

The 200,000 acre Savannah River Site (SRS) has nearly 30 nuclear facilities spread throughout the site. The safety of each facility has been established in facility-specific safety analysis reports (SARs). Each SAR contains an analysis of risk from seismic events to both on-site workers and the off-site population. Both radiological and chemical releases are considered, and air and water pathways are modeled. Risks to the general public are generally characterized by evaluating exposure to the maximally exposed individual located at the SRS boundary and to the off-site population located within 50 miles. Although the SARs are appropriate methods for studyingmore » individual facility risks, there is a class of accident initiators that can simultaneously affect several of all of the facilities, Examples include seismic events, strong winds or tornados, floods, and loss of off-site electrical power. Overall risk to the off-site population from such initiators is not covered by the individual SARs. In such cases multiple facility radionuclide or chemical releases could occur, and off-site exposure would be greater than that indicated in a single facility SAR. As a step towards an overall site-wide risk model that adequately addresses multiple facility releases, a site-wide seismic model for determining off-site risk has been developed for nuclear facilities at the SRS. Risk from seismic events up to the design basis earthquake (DBE) of 0.2 g (frequency of 2.0E-4/yr) is covered by the model. Present plans include expanding the scope of the model to include other types of initiators that can simultaneously affect multiple facilities.« less

78 FR 22221 - Proposed Flood Elevation Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-15

... table provided here represents the flooding sources, location of referenced elevations, effective and.... Specifically, it addresses the following flooding sources: Pea Branch and Reedy Branch. DATES: Comments are to... Areas'' did not address the flooding sources Pea Branch and Reedy Branch. That table omitted information...

77 FR 51745 - Proposed Flood Elevation Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-27

.... Specifically, it addresses the following flooding sources: Back Creek, Big Elk Creek, Bohemia River, Chesapeake... Areas'' addressed the following flooding sources: Back Creek, Big Elk Creek, Bohemia River, Chesapeake... modified elevation in feet, and/or communities affected for the following flooding sources: Big Elk Creek...

A PROBABILISTIC POPULATION EXPOSURE MODEL FOR PM10 AND PM 2.5

EPA Science Inventory

A first generation probabilistic population exposure model for Particulate Matter (PM), specifically for predicting PM10, and PM2.5, exposures of an urban, population has been developed. This model is intended to be used to predict exposure (magnitude, frequency, and duration) ...

Flood and Landslide Applications of Near Real-time Satellite Rainfall Products

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Negri, Andrew; Huffman, George J.

2007-01-01

Floods and associated landslides are one of the most widespread natural hazards on Earth, responsible for tens of thousands of deaths and billions of dollars in property damage every year. During 1993-2002, over 1000 of the more than 2,900 natural disasters reported were due to floods. These floods and associated landslides claimed over 90,000 lives, affected over 1.4 billion people and cost about $210 billion. The impact of these disasters is often felt most acutely in less developed regions. In many countries around the world, satellite-based precipitation estimation may be the best source of rainfall data due to lack of surface observing networks. Satellite observations can be of essential value in improving our understanding of the occurrence of hazardous events and possibly in lessening their impact on local economies and in reducing injuries, if they can be used to create reliable warning systems in cost-effective ways. This article addressed these opportunities and challenges by describing a combination of satellite-based real-time precipitation estimation with land surface characteristics as input, with empirical and numerical models to map potential of landslides and floods. In this article, a framework to detect floods and landslides related to heavy rain events in near-real-time is proposed. Key components of the framework are: a fine resolution precipitation acquisition system; a comprehensive land surface database; a hydrological modeling component; and landslide and debris flow model components. A key precipitation input dataset for the integrated applications is the NASA TRMM-based multi-satellite precipitation estimates. This dataset provides near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg. By careful integration of remote sensing and in-situ observations, and assimilation of these observations into hydrological and landslide/debris flow models with surface topographic information, prediction of useful probabilistic maps of landslide and floods for emergency management in a timely manner is possible. Early results shows that the potential exists for successful application of satellite precipitation data in improving/developing global monitoring systems for flood/landslide disaster preparedness and management. The scientific and technological prototype can be first applied in a representative test-bed and then the information deliverables for the region can be tailored to the societal and economic needs of the represented affected countries.

Epic Flooding in Georgia, 2009

USGS Publications Warehouse

Gotvald, Anthony J.; McCallum, Brian E.

2010-01-01

Metropolitan Atlanta-September 2009 Floods The epic floods experienced in the Atlanta area in September 2009 were extremely rare. Eighteen streamgages in the Metropolitan Atlanta area had flood magnitudes much greater than the estimated 0.2-percent (500-year) annual exceedance probability. The Federal Emergency Management Agency (FEMA) reported that 23 counties in Georgia were declared disaster areas due to this flood and that 16,981 homes and 3,482 businesses were affected by floodwaters. Ten lives were lost in the flood. The total estimated damages exceed $193 million (H.E. Longenecker, Federal Emergency Management Agency, written commun., November 2009). On Sweetwater Creek near Austell, Ga., just north of Interstate 20, the peak stage was more than 6 feet higher than the estimated peak stage of the 0.2-percent (500-year) flood. Flood magnitudes in Cobb County on Sweetwater, Butler, and Powder Springs Creeks greatly exceeded the estimated 0.2-percent (500-year) floods for these streams. In Douglas County, the Dog River at Ga. Highway 5 near Fairplay had a peak stage nearly 20 feet higher than the estimated peak stage of the 0.2-percent (500-year) flood. On the Chattahoochee River, the U.S. Geological Survey (USGS) gage at Vinings reached the highest level recorded in the past 81 years. Gwinnett, De Kalb, Fulton, and Rockdale Counties also had record flooding.South Georgia March and April 2009 FloodsThe March and April 2009 floods in South Georgia were smaller in magnitude than the September floods but still caused significant damage. No lives were lost in this flood. Approximately $60 million in public infrastructure damage occurred to roads, culverts, bridges and a water treatment facility (Joseph T. McKinney, Federal Emergency Management Agency, written commun., July 2009). Flow at the Satilla River near Waycross, exceeded the 0.5-percent (200-year) flood. Flows at seven other stations in South Georgia exceeded the 1-percent (100-year) flood.

Overview of environmental and hydrogeologic conditions at Galena, Alaska

USGS Publications Warehouse

Nakanishi, Allan S.; Dorava, Joseph M.

1994-01-01

The remote Native village of Galena along the Yukon River in west-central Alaska has long cold winters and short summers that affects the hydrology of the area. The Federal Aviation Administration owns or operates airport support facilities in Galena and wishes to consider the subsistence lifestyle of the residents and the quality of the current environment when evaluating options for remediation of environmental contamination at these facilities. Galena is located on the flood plain of the Yukon River and obtains its drinking water from a shallow aquifer located in the thick alluvium underlying the village. Surface spills and disposal of hazardous materials combined with annual flooding of the Yukon River may affect the quality of the ground water. Alternative drinking-water sources are available but at significantly greater cost than existing supplies.

The Study of the Relationship between Probabilistic Design and Axiomatic Design Methodology. Volume 1

NASA Technical Reports Server (NTRS)

Onwubiko, Chinyere; Onyebueke, Landon

1996-01-01

This program report is the final report covering all the work done on this project. The goal of this project is technology transfer of methodologies to improve design process. The specific objectives are: 1. To learn and understand the Probabilistic design analysis using NESSUS. 2. To assign Design Projects to either undergraduate or graduate students on the application of NESSUS. 3. To integrate the application of NESSUS into some selected senior level courses in Civil and Mechanical Engineering curricula. 4. To develop courseware in Probabilistic Design methodology to be included in a graduate level Design Methodology course. 5. To study the relationship between the Probabilistic design methodology and Axiomatic design methodology.

Managing flood risks in the Mekong Delta: How to address emerging challenges under climate change and socioeconomic developments.

PubMed

Hoang, Long Phi; Biesbroek, Robbert; Tri, Van Pham Dang; Kummu, Matti; van Vliet, Michelle T H; Leemans, Rik; Kabat, Pavel; Ludwig, Fulco

2018-02-24

Climate change and accelerating socioeconomic developments increasingly challenge flood-risk management in the Vietnamese Mekong River Delta-a typical large, economically dynamic and highly vulnerable delta. This study identifies and addresses the emerging challenges for flood-risk management. Furthermore, we identify and analyse response solutions, focusing on meaningful configurations of the individual solutions and how they can be tailored to specific challenges using expert surveys, content analysis techniques and statistical inferences. Our findings show that the challenges for flood-risk management are diverse, but critical challenges predominantly arise from the current governance and institutional settings. The top-three challenges include weak collaboration, conflicting management objectives and low responsiveness to new issues. We identified 114 reported solutions and developed six flood management strategies that are tailored to specific challenges. We conclude that the current technology-centric flood management approach is insufficient given the rapid socioecological changes. This approach therefore should be adapted towards a more balanced management configuration where technical and infrastructural measures are combined with institutional and governance resolutions. Insights from this study contribute to the emerging repertoire of contemporary flood management solutions, especially through their configurations and tailoring to specific challenges.

Historic Flooding in South Georgia, March 27-April 3, 2009

USGS Publications Warehouse

McCallum, Brian E.; Gotvald, Anthony J.; Landers, Mark N.

2009-01-01

A primary mission of the U.S. Geological Survey (USGS) is the measurement and documentation of the magnitude and extent of hydrologic hazards, such as floods, droughts, and hurricane storm surge. USGS personnel were deployed for historic widespread flooding that occurred throughout South Georgia from a storm event beginning in the late evening of March 27 and continuing through April 3, 2009. Data collected by USGS personnel and a network of automated real-time streamgages are critical to emergency management officials so that informed decisions can be made before, during, and after an event to assist in the protection of life and property. According to the Federal Emergency Management Agency (FEMA), 46 counties in Georgia were declared disaster areas due to flooding. FEMA reported that 1,875 homes and 29 businesses were affected by floodwaters. No lives were lost in this flood. Approximately $60 million in public infrastructure damage occurred to roads, culverts, bridges and a water treatment facility (Joseph T. McKinney, Federal Emergency Management Agency, written commun., July 2009).

Wind/Tornado Guidelines Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, D.S.; Holman, G.S.

1991-10-01

This report documents the strategy employed to develop recommended wind/tornado hazard design guidelines for a New Production Reactor (NRP) currently planned for either the Idaho National Engineering Laboratory (INEL) or the Savannah River (SR) site. The Wind/Tornado Working Group (WTWG), comprising six nationally recognized experts in structural engineering, wind engineering, and meteorology, formulated an independent set of guidelines based on site-specific wind/tornado hazard curves and state-of-the-art tornado missile technology. The basic philosophy was to select realistic wind and missile load specifications, and to meet performance goals by applying conservative structural response evaluation and acceptance criteria. Simplified probabilistic risk analyses (PRAs)more » for wind speeds and missile impact were performed to estimate annual damage risk frequencies for both the INEL and SR sites. These PRAs indicate that the guidelines will lead to facilities that meet the US Department of Energy (DOE) design requirements and that the Nuclear Regulatory Commission guidelines adopted by the DOE for design are adequate to meet the NPR safety goals.« less

Towards the development of a multimodel hydrological ensemble prediction system for La Mojana, Colombia

NASA Astrophysics Data System (ADS)

Brochero, D.; Peña, J.; Anctil, F.; Boucher, M. A.; Nogales, J.; Reyes, N.

2016-12-01

The impacts of floods in Colombia during 2010 and 2011 as a result of ENSO in its cold phase (La Niña) marked a milestone in Colombian politics. In La Mojana region the balance was around 100,000 homeless and 3 km2 of flooded crops. We model the upstream basin of La Mojana (3600 km2 and a mean annual precipitation from 1000mm in valleys to 4500 mm in mountains). A forecasting system of at least three days in advance was judged prudent. This basin receives an streamflow highly regulated by multiple reservoirs that we model with a recurrent neural networks from 1 to 3-days ahead. For hydrological modeling purposes we use the GR4J, HBV, and SIMHYD models, records of daily precipitation, temperature, and streamflows, and 110 prediction scenarios of precipitation and temperature from Canada, USA, Brazil, and Europe extracted from the TIGGE database (MEPS). Calibration period is between January 2004 and August 2011. Validation from September to December 2011, taking as meteorological input the MEPS. We analised four alternative for the 3-day Hydrological Ensemble Prediction System (HEPS) Calibration: 1) only the GR4J model and observed values, 2). as 1 but HBV and SIMHYD are included, 3). Simultaneous optimization of the three hydrological models based on the reliability maximisation and the CRPS minimisation using the multiobjective calibration, observed and forecasted temperature and precipitation from the MEPS and, 4). as 3 but adding the daily streamflow data assimilation. Results show that the use of multiple hydrological models is clearly advantageous but even more performing the simultaneous optimization of hydrological models in the probabilistic context directly. The results evolution of the MAE on the reliability diagram (MAE-RD) are 43%, 27%, 17% and 15% respectively for the four alternatives. Regarding CRPS, MAE results show that the probabilistic prediction improves the deterministic estimate based on the daily mean HEPS scenario, despite the improvement in reliability is not necessarily reflected in the CRPS for the four alternatives: 4.3, 3.06 , 9.98, and 3.94, values that also accompany the mean scenario Nash-Sutcliffe of 0.93, 0.96, 0.51, and 0.93 respectively. In conclusion it shows that alternative 4 reached a good compromise between the deterministic and probabilistic performance (NS=0.93 and MAERD = 15%).

Flood Control Structures Research Program. Annotated Bibliography on Grade Control Structures

DTIC Science & Technology

1991-09-01

evaluating the effects of geology, geomorphology, soils, land use, and climate on runoff and sediment production from major source areas; (4...Otto, and ,t:iji, Ahmed. 1987. "Theoret- ical Flow Model for Drop Structures," -’. aulic ’ngineering, Proceed- ings of the 1987 National Confere’,ce on...Facilities for Unique Flood Problems," Journal of the-Waterways and Harbors Division, ASCE, Vol 97, No. WWI, pp 185-203. The unusual climatic

24 CFR 55.12 - Inapplicability of 24 CFR part 55 to certain categories of proposed actions.

Code of Federal Regulations, 2013 CFR

2013-04-01

... communities that are in the Regular Program of the National Flood Insurance Program (NFIP) and in good... facilities, and intermediate care facilities) in communities that are in good standing under the NFIP. (3... Program of the NFIP and are in good standing, provided that the number of units is not increased more than...

24 CFR 55.12 - Inapplicability of 24 CFR part 55 to certain categories of proposed actions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... communities that are in the Regular Program of the National Flood Insurance Program (NFIP) and in good... facilities, and intermediate care facilities) in communities that are in good standing under the NFIP. (3... Program of the NFIP and are in good standing, provided that the number of units is not increased more than...

Multi-Hazard Advanced Seismic Probabilistic Risk Assessment Tools and Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coleman, Justin L.; Bolisetti, Chandu; Veeraraghavan, Swetha

Design of nuclear power plant (NPP) facilities to resist natural hazards has been a part of the regulatory process from the beginning of the NPP industry in the United States (US), but has evolved substantially over time. The original set of approaches and methods was entirely deterministic in nature and focused on a traditional engineering margins-based approach. However, over time probabilistic and risk-informed approaches were also developed and implemented in US Nuclear Regulatory Commission (NRC) guidance and regulation. A defense-in-depth framework has also been incorporated into US regulatory guidance over time. As a result, today, the US regulatory framework incorporatesmore » deterministic and probabilistic approaches for a range of different applications and for a range of natural hazard considerations. This framework will continue to evolve as a result of improved knowledge and newly identified regulatory needs and objectives, most notably in response to the NRC activities developed in response to the 2011 Fukushima accident in Japan. Although the US regulatory framework has continued to evolve over time, the tools, methods and data available to the US nuclear industry to meet the changing requirements have not kept pace. Notably, there is significant room for improvement in the tools and methods available for external event probabilistic risk assessment (PRA), which is the principal assessment approach used in risk-informed regulations and risk-informed decision-making applied to natural hazard assessment and design. This is particularly true if PRA is applied to natural hazards other than seismic loading. Development of a new set of tools and methods that incorporate current knowledge, modern best practice, and state-of-the-art computational resources would lead to more reliable assessment of facility risk and risk insights (e.g., the SSCs and accident sequences that are most risk-significant), with less uncertainty and reduced conservatisms.« less

Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

NASA Astrophysics Data System (ADS)

Shafiee-Jood, M.; Cai, X.

2017-12-01

Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

From cyclone tracks to the costs of European winter storms: A probabilistic loss assessment model

NASA Astrophysics Data System (ADS)

Renggli, Dominik; Corti, Thierry; Reese, Stefan; Wueest, Marc; Viktor, Elisabeth; Zimmerli, Peter

2014-05-01

The quantitative assessment of the potential losses of European winter storms is essential for the economic viability of a global reinsurance company. For this purpose, reinsurance companies generally use probabilistic loss assessment models. This work presents an innovative approach to develop physically meaningful probabilistic events for Swiss Re's new European winter storm loss model. The meteorological hazard component of the new model is based on cyclone and windstorm tracks identified in the 20th Century Reanalysis data. The knowledge of the evolution of winter storms both in time and space allows the physically meaningful perturbation of properties of historical events (e.g. track, intensity). The perturbation includes a random element but also takes the local climatology and the evolution of the historical event into account. The low-resolution wind footprints taken from 20th Century Reanalysis are processed by a statistical-dynamical downscaling to generate high-resolution footprints of the historical and probabilistic winter storm events. Downscaling transfer functions are generated using ENSEMBLES regional climate model data. The result is a set of reliable probabilistic events representing thousands of years. The event set is then combined with country- and risk-specific vulnerability functions and detailed market- or client-specific exposure information to compute (re-)insurance risk premiums.

Remote collection and analysis of witness reports on flash floods

NASA Astrophysics Data System (ADS)

Gourley, J. J.; Erlingis, J. M.; Smith, T. M.; Ortega, K. L.; Hong, Y.

2010-11-01

SummaryTypically, flash floods are studied ex post facto in response to a major impact event. A complement to field investigations is developing a detailed database of flash flood events, including minor events and null reports (i.e., where heavy rain occurred but there was no flash flooding), based on public survey questions conducted in near-real time. The Severe hazards analysis and verification experiment (SHAVE) has been in operation at the National Severe Storms Laboratory (NSSL) in Norman, OK, USA during the summers since 2006. The experiment employs undergraduate students to analyse real-time products from weather radars, target specific regions within the conterminous US, and poll public residences and businesses regarding the occurrence and severity of hail, wind, tornadoes, and now flash floods. In addition to providing a rich learning experience for students, SHAVE has also been successful in creating high-resolution datasets of severe hazards used for algorithm and model verification. This paper describes the criteria used to initiate the flash flood survey, the specific questions asked and information entered to the database, and then provides an analysis of results for flash flood data collected during the summer of 2008. It is envisioned that specific details provided by the SHAVE flash flood observation database will complement databases collected by operational agencies (i.e., US National Weather Service Storm Data reports) and thus lead to better tools to predict the likelihood of flash floods and ultimately reduce their impacts on society.

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

PubMed

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.

Climate Adaptation and Storms & Flooding

EPA Pesticide Factsheets

EPA works with drinking water, wastewater and stormwater utilities, as well as local, state and tribal governments to help critical water infrastructure facilities prepare for and recover from the impacts of climate change.

The construction technology of Chinese ancient city drainage facilities

NASA Astrophysics Data System (ADS)

Hequn, Li; Yufengyun

2018-03-01

In ancient china, according to the local natural environment, a variety of drainage facilities were built in order to excrete rainwater, domestic sewage, production wastewater and so on. These drainage facilities were mainly made of pottery, bricks, wood, stone, etc. For example, ceramic water pipelines, buried in the ground, connect together one by one, and there was a slight drop from one end to the other in favor of drainage. These measures can also be used for reference in today’s urban drainage and flood control.

Evaluating the Benefits of Adaptation of Critical Infrastructures to Hydrometeorological Risks.

PubMed

Thacker, Scott; Kelly, Scott; Pant, Raghav; Hall, Jim W

2018-01-01

Infrastructure adaptation measures provide a practical way to reduce the risk from extreme hydrometeorological hazards, such as floods and windstorms. The benefit of adapting infrastructure assets is evaluated as the reduction in risk relative to the "do nothing" case. However, evaluating the full benefits of risk reduction is challenging because of the complexity of the systems, the scarcity of data, and the uncertainty of future climatic changes. We address this challenge by integrating methods from the study of climate adaptation, infrastructure systems, and complex networks. In doing so, we outline an infrastructure risk assessment that incorporates interdependence, user demands, and potential failure-related economic losses. Individual infrastructure assets are intersected with probabilistic hazard maps to calculate expected annual damages. Protection measure costs are integrated to calculate risk reduction and associated discounted benefits, which are used to explore the business case for investment in adaptation. A demonstration of the methodology is provided for flood protection of major electricity substations in England and Wales. We conclude that the ongoing adaptation program for major electricity assets is highly cost beneficial. © 2017 Society for Risk Analysis.

Popular myths about flooding in Western Washington

USGS Publications Warehouse

Jones, Joseph L.

2011-01-01

Floods are the most destructive natural hazard in the Nation, causing more deaths and financial loss in the 20th century than any other natural disaster. The most significant 20 riverine floods of the 20th century for which data are available have killed more than 1,843 people and caused more than $50 billion (uninflated) in damages (Perry, 2000). One of the most common means of describing the severity of a flood is a comparison to the "100-year flood." In the last decade, increasing attention has been paid to the fact that some regions, notably the Pacific Northwest, have experienced numerous so-called "100-year" floods in the span of a few years. Part of the confusion stems from the statistical nature of the "100-year flood" (Greene, 1996); however, another part of the confusion is the fact that the statistics are calculated for specific sites (streamgages) on specific rivers, rather than for a region as a whole. Scientists with the U.S. Geological Survey have begun to investigate how the likelihood of flooding may be determined on a regional basis (Troutman and Karlinger, 2003).

Implementation of the SSHAC Guidelines for Level 3 and 4 PSHAs - Experience Gained from Actual Applications

USGS Publications Warehouse

Hanks, Thomas C.; Abrahamson, Norm A.; Boore, David M.; Coppersmith, Kevin J.; Knepprath, Nichole E.

2009-01-01

In April 1997, after four years of deliberations, the Senior Seismic Hazard Analysis Committee released its report 'Recommendations for Probabilistic Seismic Hazard Analysis: Guidance on Uncertainty and Use of Experts' through the U.S. Nuclear Regulatory Commission as NUREG/CR-6372, hereafter SSHAC (1997). Known informally ever since as the 'SSHAC Guidelines', SSHAC (1997) addresses why and how multiple expert opinions - and the intrinsic uncertainties that attend them - should be used in Probabilistic Seismic Hazard Analyses (PSHA) for critical facilities such as commercial nuclear power plants. Ten years later, in September 2007, the U.S. Geological Survey (USGS) entered into a 13-month agreement with the U.S. Nuclear Regulatory Commission (NRC) titled 'Practical Procedures for Implementation of the SSHAC Guidelines and for Updating PSHAs'. The NRC was interested in understanding and documenting lessons learned from recent PSHAs conducted at the higher SSHAC Levels (3 and 4) and in gaining input from the seismic community for updating PSHAs as new information became available. This study increased in importance in anticipation of new applications for nuclear power facilities at both existing and new sites. The intent of this project was not to replace the SSHAC Guidelines but to supplement them with the experience gained from putting the SSHAC Guidelines to work in practical applications. During the course of this project, we also learned that updating PSHAs for existing nuclear power facilities involves very different issues from the implementation of the SSHAC Guidelines for new facilities. As such, we report our findings and recommendations from this study in two separate documents, this being the first. The SSHAC Guidelines were written without regard to whether the PSHAs to which they would be applied were site-specific or regional in scope. Most of the experience gained to date from high-level SSHAC studies has been for site-specific cases, although three ongoing (as of this writing) studies are regional in scope. Updating existing PSHAs will depend more critically on the differences between site-specific and regional studies, and we will also address these differences in more detail in the companion report. Most of what we report here and in the second report on updating PSHAs emanates from three workshops held by the USGS at their Menlo Park facility: 'Lessons Learned from SSHAC Level 3 and 4 PSHAs' on January 30-31, 2008; 'Updates to Existing PSHAs' on May 6-7, 2008; and 'Draft Recommendations, SSHAC Implementation Guidance' on June 4-5, 2009. These workshops were attended by approximately 40 scientists and engineers familiar with hazard studies for nuclear facilities. This company included four of the authors of SSHAC (1997) and four other experts whose contributions to this document are mentioned in the Acknowledgments section; numerous scientists and engineers who in one role or another have participated in one or more high-level SSHAC PSHAs summarized later in this report; and representatives of the nuclear industry, the consulting world, the regulatory community, and academia with a keen interest and expertise in hazard analysis. This report is a community-based set of recommendations to NRC for improved practical procedures for implementation of the SSHAC Guidelines. In an early publication specifically addressing the SSHAC Guidelines, Hanks (1997) noted that the SSHAC Guidelines were likely to evolve for some time to come, and this remains true today. While the broad philosophical and theoretical dimensions of the SSHAC Guidelines will not change, much has been learned during the past decade from various applications of the SSHAC Guidelines to real PSHAs in terms of how they are implemented. We anticipate that, in their practical applications, the SSHAC Guidelines will continue to evolve as more experience is gained from future SSHAC applications. Indeed, to the extent that every PSHA has its

The application of probabilistic fracture analysis to residual life evaluation of embrittled reactor vessels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dickson, T.L.; Simonen, F.A.

1992-05-01

Probabilistic fracture mechanics analysis is a major element of comprehensive probabilistic methodology on which current NRC regulatory requirements for pressurized water reactor vessel integrity evaluation are based. Computer codes such as OCA-P and VISA-II perform probabilistic fracture analyses to estimate the increase in vessel failure probability that occurs as the vessel material accumulates radiation damage over the operating life of the vessel. The results of such analyses, when compared with limits of acceptable failure probabilities, provide an estimation of the residual life of a vessel. Such codes can be applied to evaluate the potential benefits of plant-specific mitigating actions designedmore » to reduce the probability of failure of a reactor vessel. 10 refs.« less

The application of probabilistic fracture analysis to residual life evaluation of embrittled reactor vessels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dickson, T.L.; Simonen, F.A.

1992-01-01

Probabilistic fracture mechanics analysis is a major element of comprehensive probabilistic methodology on which current NRC regulatory requirements for pressurized water reactor vessel integrity evaluation are based. Computer codes such as OCA-P and VISA-II perform probabilistic fracture analyses to estimate the increase in vessel failure probability that occurs as the vessel material accumulates radiation damage over the operating life of the vessel. The results of such analyses, when compared with limits of acceptable failure probabilities, provide an estimation of the residual life of a vessel. Such codes can be applied to evaluate the potential benefits of plant-specific mitigating actions designedmore » to reduce the probability of failure of a reactor vessel. 10 refs.« less

Reconstructing Constructivism: Causal Models, Bayesian Learning Mechanisms, and the Theory Theory

ERIC Educational Resources Information Center

Gopnik, Alison; Wellman, Henry M.

2012-01-01

We propose a new version of the "theory theory" grounded in the computational framework of probabilistic causal models and Bayesian learning. Probabilistic models allow a constructivist but rigorous and detailed approach to cognitive development. They also explain the learning of both more specific causal hypotheses and more abstract framework…

Life Span Differences in Electrophysiological Correlates of Monitoring Gains and Losses during Probabilistic Reinforcement Learning

ERIC Educational Resources Information Center

Hammerer, Dorothea; Li, Shu-Chen; Muller, Viktor; Lindenberger, Ulman

2011-01-01

By recording the feedback-related negativity (FRN) in response to gains and losses, we investigated the contribution of outcome monitoring mechanisms to age-associated differences in probabilistic reinforcement learning. Specifically, we assessed the difference of the monitoring reactions to gains and losses to investigate the monitoring of…

Floods of January-February 1963 in California and Nevada

USGS Publications Warehouse

Rantz, S.E.; Harris, E.E.

1963-01-01

Widespread flooding occurred in central California and northwestern Nevada during January 31 - February 1, 1963, as a result of intense precipitation of about 72 hours duration. The flood-producing storm was of the warm type, with precipitation falling as rain at altitudes as high as 8,000 feet. The heavy precipitation, totaling as much as 20 inches or more in the Sierra Nevada, fell on frozen ground or on the sparse snowpack that existed in the higher altitudes. The response of runoff to rainfall was dramatic, as streams throughout the area rose rapidly. Hardest hit were the basins of the American, Yuba, and Truckee Rivers, where flood peaks either reached record-breaking heights or rivalled the discharges attained in the memorable floods of November 1950 and December 1955. Because of the relatively short duration of the storm, the volume of flood flow in 1963 was not outstanding. Ten deaths were attributed to the storm or flood. Preliminary estimates indicate damage in excess of $16 million in foothill and valley areas, but no attempt has yet been made to assess the heavy damage to highways and drainage structures in the mountain areas. The U. S. Army, Corps of Engineirs estimates that its operation of flood-control facilities prevented additional damage of $236 million. Other reservoirs, operated primarily for water conservation or power production, were also instrumental in preventing damage.

Coupled Land-Atmosphere Dynamics Govern Long Duration Floods: A Pilot Study in Missouri River Basin Using a Bayesian Hierarchical Model

NASA Astrophysics Data System (ADS)

Najibi, N.; Lu, M.; Devineni, N.

2017-12-01

Long duration floods cause substantial damages and prolonged interruptions to water resource facilities and critical infrastructure. We present a novel generalized statistical and physical based model for flood duration with a deeper understanding of dynamically coupled nexus of the land surface wetness, effective atmospheric circulation and moisture transport/release. We applied the model on large reservoirs in the Missouri River Basin. The results indicate that the flood duration is not only a function of available moisture in the air, but also the antecedent condition of the blocking system of atmospheric pressure, resulting in enhanced moisture convergence, as well as the effectiveness of moisture condensation process leading to release. Quantifying these dynamics with a two-layer climate informed Bayesian multilevel model, we explain more than 80% variations in flood duration. The model considers the complex interaction between moisture transport, synoptic-to-large-scale atmospheric circulation pattern, and the antecedent wetness condition in the basin. Our findings suggest that synergy between a large low-pressure blocking system and a higher rate of divergent wind often triggers a long duration flood, and the prerequisite for moisture supply to trigger such event is moderate, which is more associated with magnitude than duration. In turn, this condition causes an extremely long duration flood if the surface wetness rate advancing to the flood event was already increased.

A Study on Regional Rainfall Frequency Analysis for Flood Simulation Scenarios

NASA Astrophysics Data System (ADS)

Jung, Younghun; Ahn, Hyunjun; Joo, Kyungwon; Heo, Jun-Haeng

2014-05-01

Recently, climate change has been observed in Korea as well as in the entire world. The rainstorm has been gradually increased and then the damage has been grown. It is very important to manage the flood control facilities because of increasing the frequency and magnitude of severe rain storm. For managing flood control facilities in risky regions, data sets such as elevation, gradient, channel, land use and soil data should be filed up. Using this information, the disaster situations can be simulated to secure evacuation routes for various rainfall scenarios. The aim of this study is to investigate and determine extreme rainfall quantile estimates in Uijeongbu City using index flood method with L-moments parameter estimation. Regional frequency analysis trades space for time by using annual maximum rainfall data from nearby or similar sites to derive estimates for any given site in a homogeneous region. Regional frequency analysis based on pooled data is recommended for estimation of rainfall quantiles at sites with record lengths less than 5T, where T is return period of interest. Many variables relevant to precipitation can be used for grouping a region in regional frequency analysis. For regionalization of Han River basin, the k-means method is applied for grouping regions by variables of meteorology and geomorphology. The results from the k-means method are compared for each region using various probability distributions. In the final step of the regionalization analysis, goodness-of-fit measure is used to evaluate the accuracy of a set of candidate distributions. And rainfall quantiles by index flood method are obtained based on the appropriate distribution. And then, rainfall quantiles based on various scenarios are used as input data for disaster simulations. Keywords: Regional Frequency Analysis; Scenarios of Rainfall Quantile Acknowledgements This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures by using 3D BIM Technique' [NEMA-12-NH-57] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

Flood-plain study of the Upper Iowa River in the vicinity of Decorah, Iowa

USGS Publications Warehouse

Christiansen, Daniel E.; Eash, David A.

2008-01-01

The city of Decorah, Iowa, has experienced severe flooding from the Upper Iowa River resulting in property damage to homes and businesses. Streamflow data from two U.S. Geological Survey (USGS) streamflow-gaging stations, the Upper Iowa River at Decorah, Iowa (station number 05387500), located upstream from the College Drive bridge; and the Upper Iowa River near Decorah, Iowa (station number 05388000), at the Clay Hill Road bridge (locally known as the Freeport bridge) were used in the study. The three largest floods on the Upper Iowa River at Decorah occurred in 1941, 1961, and 1993, for which the estimated peak discharges were 27,200 cubic feet per second (ft3/s), 20,200 ft3/s, and 20,500 ft3/s, respectively. Flood-discharge information can be obtained from the World Wide Web at URL (uniform resource locator) http://waterdata.usgs.gov/nwis/. In response to the need to provide the City of Decorah and other flood-plain managers with an assessment of the risks of flooding to properties and facilities along an 8.5-mile (mi) reach of the Upper Iowa River, the USGS, in cooperation with the City of Decorah, initiated a study to map 100- and 500-year flood-prone areas.

Wind/tornado design criteria, development to achieve required probabilistic performance goals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, D.S.

1991-06-01

This paper describes the strategy for developing new design criteria for a critical facility to withstand loading induced by the wind/tornado hazard. The proposed design requirements for resisting wind/tornado loads are based on probabilistic performance goals. The proposed design criteria were prepared by a Working Group consisting of six experts in wind/tornado engineering and meteorology. Utilizing their best technical knowledge and judgment in the wind/tornado field, they met and discussed the methodologies and reviewed available data. A review of the available wind/tornado hazard model for the site, structural response evaluation methods, and conservative acceptance criteria lead to proposed design criteriamore » that has a high probability of achieving the required performance goals.« less

Wind/tornado design criteria, development to achieve required probabilistic performance goals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, D.S.

This paper describes the strategy for developing new design criteria for a critical facility to withstand loading induced by the wind/tornado hazard. The proposed design requirements for resisting wind/tornado loads are based on probabilistic performance goals. The proposed design criteria were prepared by a Working Group consisting of six experts in wind/tornado engineering and meteorology. Utilizing their best technical knowledge and judgment in the wind/tornado field, they met and discussed the methodologies and reviewed available data. A review of the available wind/tornado hazard model for the site, structural response evaluation methods, and conservative acceptance criteria lead to proposed design criteriamore » that has a high probability of achieving the required performance goals.« less

Compression of Probabilistic XML Documents

NASA Astrophysics Data System (ADS)

Veldman, Irma; de Keijzer, Ander; van Keulen, Maurice

Database techniques to store, query and manipulate data that contains uncertainty receives increasing research interest. Such UDBMSs can be classified according to their underlying data model: relational, XML, or RDF. We focus on uncertain XML DBMS with as representative example the Probabilistic XML model (PXML) of [10,9]. The size of a PXML document is obviously a factor in performance. There are PXML-specific techniques to reduce the size, such as a push down mechanism, that produces equivalent but more compact PXML documents. It can only be applied, however, where possibilities are dependent. For normal XML documents there also exist several techniques for compressing a document. Since Probabilistic XML is (a special form of) normal XML, it might benefit from these methods even more. In this paper, we show that existing compression mechanisms can be combined with PXML-specific compression techniques. We also show that best compression rates are obtained with a combination of PXML-specific technique with a rather simple generic DAG-compression technique.

Highlights of advances in the field of hydrometeorological research brought about by the DRIHM project

NASA Astrophysics Data System (ADS)

Caumont, Olivier; Hally, Alan; Garrote, Luis; Richard, Évelyne; Weerts, Albrecht; Delogu, Fabio; Fiori, Elisabetta; Rebora, Nicola; Parodi, Antonio; Mihalović, Ana; Ivković, Marija; Dekić, Ljiljana; van Verseveld, Willem; Nuissier, Olivier; Ducrocq, Véronique; D'Agostino, Daniele; Galizia, Antonella; Danovaro, Emanuele; Clematis, Andrea

2015-04-01

The FP7 DRIHM (Distributed Research Infrastructure for Hydro-Meteorology, http://www.drihm.eu, 2011-2015) project intends to develop a prototype e-Science environment to facilitate the collaboration between meteorologists, hydrologists, and Earth science experts for accelerated scientific advances in Hydro-Meteorology Research (HMR). As the project comes to its end, this presentation will summarize the HMR results that have been obtained in the framework of DRIHM. The vision shaped and implemented in the framework of the DRIHM project enables the production and interpretation of numerous, complex compositions of hydrometeorological simulations of flood events from rainfall, either simulated or modelled, down to discharge. Each element of a composition is drawn from a set of various state-of-the-art models. Atmospheric simulations providing high-resolution rainfall forecasts involve different global and limited-area convection-resolving models, the former being used as boundary conditions for the latter. Some of these models can be run as ensembles, i.e. with perturbed boundary conditions, initial conditions and/or physics, thus sampling the probability density function of rainfall forecasts. In addition, a stochastic downscaling algorithm can be used to create high-resolution rainfall ensemble forecasts from deterministic lower-resolution forecasts. All these rainfall forecasts may be used as input to various rainfall-discharge hydrological models that compute the resulting stream flows for catchments of interest. In some hydrological simulations, physical parameters are perturbed to take into account model errors. As a result, six different kinds of rainfall data (either deterministic or probabilistic) can currently be compared with each other and combined with three different hydrological model engines running either in deterministic or probabilistic mode. HMR topics which are allowed or facilitated by such unprecedented sets of hydrometerological forecasts include: physical process studies, intercomparison of models and ensembles, sensitivity studies to a particular component of the forecasting chain, and design of flash-flood early-warning systems. These benefits will be illustrated with the different key cases that have been under investigation in the course of the project. These are four catastrophic cases of flooding, namely the case of 4 November 2011 in Genoa, Italy, 6 November 2011 in Catalonia, Spain, 13-16 May 2014 in eastern Europe, and 9 October 2014, again in Genoa, Italy.

Designing an 'expert knowledge' based approach for the quantification of historical floods - the case study of the Kinzig catchment in Southwest Germany

NASA Astrophysics Data System (ADS)

Bösmeier, Annette; Glaser, Rüdiger; Stahl, Kerstin; Himmelsbach, Iso; Schönbein, Johannes

2017-04-01

Future estimations of flood hazard and risk for developing optimal coping and adaption strategies inevitably include considerations of the frequency and magnitude of past events. Methods of historical climatology represent one way of assessing flood occurrences beyond the period of instrumental measurements and can thereby substantially help to extend the view into the past and to improve modern risk analysis. Such historical information can be of additional value and has been used in statistical approaches like Bayesian flood frequency analyses during recent years. However, the derivation of quantitative values from vague descriptive information of historical sources remains a crucial challenge. We explored possibilities of parametrization of descriptive flood related data specifically for the assessment of historical floods in a framework that combines a hermeneutical approach with mathematical and statistical methods. This study forms part of the transnational, Franco-German research project TRANSRISK2 (2014 - 2017), funded by ANR and DFG, with the focus on exploring the floods history of the last 300 years for the regions of Upper and Middle Rhine. A broad data base of flood events had been compiled, dating back to AD 1500. The events had been classified based on hermeneutical methods, depending on intensity, spatial dimension, temporal structure, damages and mitigation measures associated with the specific events. This indexed database allowed the exploration of a link between descriptive data and quantitative information for the overlapping time period of classified floods and instrumental measurements since the end of the 19th century. Thereby, flood peak discharges as a quantitative measure of the severity of a flood were used to assess the discharge intervals for flood classes (upper and lower thresholds) within different time intervals for validating the flood classification, as well as examining the trend in the perception threshold over time. Furthermore, within a suitable time period, flood classes and other quantifiable indicators of flood intensity (number of damaged locations mentioned in historical sources, general availability of reports associated with a specific event) were combined with available peak discharges measurements. We argue that this information can be considered as 'expert knowledge' and used it to develop a fuzzy rule based model for deriving peak discharge estimates of pre-instrumental events that can finally be introduced into a flood frequency analysis.

Japan: Tsunami Flooding

Atmospheric Science Data Center

2013-04-16

... includes the area around the damaged Fukushima Dai-ichi nuclear power facility and extends northward along the coast. The ... of the Abukuma River to south of the Fukushima Dai-ichi nuclear power facility, and covers an area of 41 kilometers (25 miles) by 89 ... 2 kilometers (1.2 miles) inland is visible just north of the nuclear power plant. Further up the coast, to the south of Matsukawa-ura Bay, ...

Basin-Scale Reconstruction of Flood Characteristics in a Small Urban Waterhsed

NASA Astrophysics Data System (ADS)

Miller, A. J.; Smith, J. A.; Baeck, M. L.

2006-05-01

Intense short-duration summer thunderstorms are primarily responsible for the occurrence of extreme floods in small, highly urban watersheds. In these systems hydrologic response is rapid and the role of urban infrastructure (impervious cover, storm drain networks, stormwater retention facilities, engineered channels, road embankments, bridges and culverts, and floodplain fill and regrading) has potentially important consequences for runoff generation and for flood-wave propagation. The occurrence of even a single well- documented extreme event provides an opportunity to improve our understanding of the relationships between temporal and spatial patterns of precipitation, natural and anthropogenic landscape features, and the dynamics of flood behavior. We report on combined field and modeling studies of a record flood (Qpk ~ 250 m3s-1) that occurred on 7 July 2004 in the 14.3 km2 Dead Run watershed in suburban Baltimore, Maryland. Flood peaks were reconstructed for nine locations in the watershed and streamflow hydrographs were derived for four locations where complete or partial stage records were recovered; these were compared with precipitation mass-balance estimates using bias-corrected radar rainfall data in order to examine the spatial pattern of runoff ratios, lag times, and cumulative properties of the flood wave as it advanced downstream. Flood behavior in part reflects the role of capacity constraints in the storm drain network and of ponding and storage of overbank flow by physical barriers such as road embankments and culverts. The results can be used to improve predictions of flood response to other hydrometeorological events and provide insight on sensitivity of flood behavior to patterns of urban development and infrastructure.

Global scale predictability of floods

NASA Astrophysics Data System (ADS)

Weerts, Albrecht; Gijsbers, Peter; Sperna Weiland, Frederiek

2016-04-01

Flood (and storm surge) forecasting at the continental and global scale has only become possible in recent years (Emmerton et al., 2016; Verlaan et al., 2015) due to the availability of meteorological forecast, global scale precipitation products and global scale hydrologic and hydrodynamic models. Deltares has setup GLOFFIS a research-oriented multi model operational flood forecasting system based on Delft-FEWS in an open experimental ICT facility called Id-Lab. In GLOFFIS both the W3RA and PCRGLOB-WB model are run in ensemble mode using GEFS and ECMWF-EPS (latency 2 days). GLOFFIS will be used for experiments into predictability of floods (and droughts) and their dependency on initial state estimation, meteorological forcing and the hydrologic model used. Here we present initial results of verification of the ensemble flood forecasts derived with the GLOFFIS system. Emmerton, R., Stephens, L., Pappenberger, F., Pagano, T., Weerts, A., Wood, A. Salamon, P., Brown, J., Hjerdt, N., Donnelly, C., Cloke, H. Continental and Global Scale Flood Forecasting Systems, WIREs Water (accepted), 2016 Verlaan M, De Kleermaeker S, Buckman L. GLOSSIS: Global storm surge forecasting and information system 2015, Australasian Coasts & Ports Conference, 15-18 September 2015,Auckland, New Zealand.

Evaluation of multiple hydraulic models in generating design/near-real time flood inundation extents under various geophysical settings

NASA Astrophysics Data System (ADS)

Liu, Z.; Rajib, M. A.; Jafarzadegan, K.; Merwade, V.

2015-12-01

Application of land surface/hydrologic models within an operational flood forecasting system can provide probable time of occurrence and magnitude of streamflow at specific locations along a stream. Creating time-varying spatial extent of flood inundation and depth requires the use of a hydraulic or hydrodynamic model. Models differ in representing river geometry and surface roughness which can lead to different output depending on the particular model being used. The result from a single hydraulic model provides just one possible realization of the flood extent without capturing the uncertainty associated with the input or the model parameters. The objective of this study is to compare multiple hydraulic models toward generating ensemble flood inundation extents. Specifically, relative performances of four hydraulic models, including AutoRoute, HEC-RAS, HEC-RAS 2D, and LISFLOOD are evaluated under different geophysical conditions in several locations across the United States. By using streamflow output from the same hydrologic model (SWAT in this case), hydraulic simulations are conducted for three configurations: (i) hindcasting mode by using past observed weather data at daily time scale in which models are being calibrated against USGS streamflow observations, (ii) validation mode using near real-time weather data at sub-daily time scale, and (iii) design mode with extreme streamflow data having specific return periods. Model generated inundation maps for observed flood events both from hindcasting and validation modes are compared with remotely sensed images, whereas the design mode outcomes are compared with corresponding FEMA generated flood hazard maps. The comparisons presented here will give insights on probable model-specific nature of biases and their relative advantages/disadvantages as components of an operational flood forecasting system.

Estimated flood peak discharges on Twin, Brock, and Lightning creeks, Southwest Oklahoma City, Oklahoma, May 8, 1993

USGS Publications Warehouse

Tortorelli, R.L.

1996-01-01

The flash flood in southwestern Oklahoma City, Oklahoma, May 8, 1993, was the result of an intense 3-hour rainfall on saturated ground or impervious surfaces. The total precipitation of 5.28 inches was close to the 3-hour, 100-year frequency and produced extensive flooding. The most serious flooding was on Twin, Brock, and Lightning Creeks. Four people died in this flood. Over 1,900 structures were damaged along the 3 creeks. There were about $3 million in damages to Oklahoma City public facilities, the majority of which were in the three basins. A study was conducted to determine the magnitude of the May 8, 1993, flood peak discharge in these three creeks in southwestern Oklahoma City and compare these peaks with published flood estimates. Flood peak-discharge estimates for these creeks were determined at 11 study sites using a step-backwater analysis to match the flood water-surface profiles defined by high-water marks. The unit discharges during peak runoff ranged from 881 cubic feet per second per square mile for Lightning Creek at SW 44th Street to 3,570 cubic feet per second per square mile for Brock Creek at SW 59th Street. The ratios of the 1993 flood peak discharges to the Federal Emergency Management Agency 100-year flood peak discharges ranged from 1.25 to 3.29. The water-surface elevations ranged from 0.2 foot to 5.9 feet above the Federal Emergency Management Agency 500-year flood water-surface elevations. The very large flood peaks in these 3 small urban basins were the result of very intense rainfall in a short period of time, close to 100 percent runoff due to ground surfaces being essentially impervious, and the city streets acting as efficient conveyances to the main channels. The unit discharges compare in magnitude to other extraordinary Oklahoma urban floods.

Application of Decision Tree to Obtain Optimal Operation Rules for Reservoir Flood Control Considering Sediment Desilting-Case Study of Tseng Wen Reservoir

NASA Astrophysics Data System (ADS)

ShiouWei, L.

2014-12-01

Reservoirs are the most important water resources facilities in Taiwan.However,due to the steep slope and fragile geological conditions in the mountain area,storm events usually cause serious debris flow and flood,and the flood then will flush large amount of sediment into reservoirs.The sedimentation caused by flood has great impact on the reservoirs life.Hence,how to operate a reservoir during flood events to increase the efficiency of sediment desilting without risk the reservoir safety and impact the water supply afterward is a crucial issue in Taiwan. 　Therefore,this study developed a novel optimization planning model for reservoir flood operation considering flood control and sediment desilting,and proposed easy to use operating rules represented by decision trees.The decision trees rules have considered flood mitigation,water supply and sediment desilting.The optimal planning model computes the optimal reservoir release for each flood event that minimum water supply impact and maximum sediment desilting without risk the reservoir safety.Beside the optimal flood operation planning model,this study also proposed decision tree based flood operating rules that were trained by the multiple optimal reservoir releases to synthesis flood scenarios.The synthesis flood scenarios consists of various synthesis storm events,reservoir's initial storage and target storages at the end of flood operating. 　Comparing the results operated by the decision tree operation rules(DTOR) with that by historical operation for Krosa Typhoon in 2007,the DTOR removed sediment 15.4% more than that of historical operation with reservoir storage only8.38×106m3 less than that of historical operation.For Jangmi Typhoon in 2008,the DTOR removed sediment 24.4% more than that of historical operation with reservoir storage only 7.58×106m3 less than that of historical operation.The results show that the proposed DTOR model can increase the sediment desilting efficiency and extend the reservoir life.

Probabilistic hydrological nowcasting using radar based nowcasting techniques and distributed hydrological models: application in the Mediterranean area

NASA Astrophysics Data System (ADS)

Poletti, Maria Laura; Pignone, Flavio; Rebora, Nicola; Silvestro, Francesco

2017-04-01

The exposure of the urban areas to flash-floods is particularly significant to Mediterranean coastal cities, generally densely-inhabited. Severe rainfall events often associated to intense and organized thunderstorms produced, during the last century, flash-floods and landslides causing serious damages to urban areas and in the worst events led to human losses. The temporal scale of these events has been observed strictly linked to the size of the catchments involved: in the Mediterranean area a great number of catchments that pass through coastal cities have a small drainage area (less than 100 km2) and a corresponding hydrologic response timescale in the order of a few hours. A suitable nowcasting chain is essential for the on time forecast of this kind of events. In fact meteorological forecast systems are unable to predict precipitation at the scale of these events, small both at spatial (few km) and temporal (hourly) scales. Nowcasting models, covering the time interval of the following two hours starting from the observation try to extend the predictability limits of the forecasting models in support of real-time flood alert system operations. This work aims to present the use of hydrological models coupled with nowcasting techniques. The nowcasting model PhaSt furnishes an ensemble of equi-probable future precipitation scenarios on time horizons of 1-3 h starting from the most recent radar observations. The coupling of the nowcasting model PhaSt with the hydrological model Continuum allows to forecast the flood with a few hours in advance. In this way it is possible to generate different discharge prediction for the following hours and associated return period maps: these maps can be used as a support in the decisional process for the warning system.

An Evaluation of the Interactive Query Expansion in an Online Library Catalogue with a Graphical User Interface.

ERIC Educational Resources Information Center

Hancock-Beaulieu, Micheline; And Others

1995-01-01

An online library catalog was used to evaluate an interactive query expansion facility based on relevance feedback for the Okapi, probabilistic, term weighting, retrieval system. A graphical user interface allowed searchers to select candidate terms extracted from relevant retrieved items to reformulate queries. Results suggested that the…

NASA Glenn Research Center Overview

NASA Technical Reports Server (NTRS)

Sehra, Arun K.

2002-01-01

This viewgraph presentation provides information on the NASA Glenn Research Center. The presentation is a broad overview, including the chain of command at the center, its aeronautics facilities, and the factors which shape aerospace product line integration at the center. Special attention is given to the future development of high fidelity probabilistic methods, and NPSS (Numerical Propulsion System Simulation).

The European ASAMPSA_E project : towards guidance to model the impact of high amplitude natural hazards in the probabilistic safety assessment of nuclear power plants. Information on the project progress and needs from the geosciences.

NASA Astrophysics Data System (ADS)

Raimond, Emmanuel; Decker, Kurt; Guigueno, Yves; Klug, Joakim; Loeffler, Horst

2015-04-01

The Fukushima nuclear accident in Japan resulted from the combination of two correlated extreme external events (earthquake and tsunami). The consequences, in particular flooding, went beyond what was considered in the initial engineering design design of nuclear power plants (NPPs). Such situations can in theory be identified using probabilistic safety assessment (PSA) methodology. PSA results may then lead industry (system suppliers and utilities) or Safety Authorities to take appropriate decisions to reinforce the defence-in-depth of the NPP for low probability event but high amplitude consequences. In reality, the development of such PSA remains a challenging task. Definitions of the design basis of NPPs, for example, require data on events with occurrence probabilities not higher than 10-4 per year. Today, even lower probabilities, down to 10-8, are expected and typically used for probabilistic safety analyses (PSA) of NPPs and the examination of so-called design extension conditions. Modelling the combinations of natural or man-made hazards that can affect a NPP and affecting some meaningful probability of occurrence seems to be difficult. The European project ASAMPSAE (www.asampsa.eu) gathers more than 30 organizations (industry, research, safety control) from Europe, US and Japan and aims at identifying some meaningful practices to extend the scope and the quality of the existing probabilistic safety analysis developed for nuclear power plants. It offers a framework to discuss, at a technical level, how "extended PSA" can be developed efficiently and be used to verify if the robustness of Nuclear Power Plants (NPPs) in their environment is sufficient. The paper will present the objectives of this project, some first lessons and introduce which type of guidance is being developed. It will explain the need of expertise from geosciences to support the nuclear safety assessment in the different area (seismotectonic, hydrological, meteorological and biological hazards, …).

Probabilistic failure assessment with application to solid rocket motors

NASA Technical Reports Server (NTRS)

Jan, Darrell L.; Davidson, Barry D.; Moore, Nicholas R.

1990-01-01

A quantitative methodology is being developed for assessment of risk of failure of solid rocket motors. This probabilistic methodology employs best available engineering models and available information in a stochastic framework. The framework accounts for incomplete knowledge of governing parameters, intrinsic variability, and failure model specification error. Earlier case studies have been conducted on several failure modes of the Space Shuttle Main Engine. Work in progress on application of this probabilistic approach to large solid rocket boosters such as the Advanced Solid Rocket Motor for the Space Shuttle is described. Failure due to debonding has been selected as the first case study for large solid rocket motors (SRMs) since it accounts for a significant number of historical SRM failures. Impact of incomplete knowledge of governing parameters and failure model specification errors is expected to be important.

Propagation of radar rainfall uncertainty in urban flood simulations

NASA Astrophysics Data System (ADS)

Liguori, Sara; Rico-Ramirez, Miguel

2013-04-01

This work discusses the results of the implementation of a novel probabilistic system designed to improve ensemble sewer flow predictions for the drainage network of a small urban area in the North of England. The probabilistic system has been developed to model the uncertainty associated to radar rainfall estimates and propagate it through radar-based ensemble sewer flow predictions. The assessment of this system aims at outlining the benefits of addressing the uncertainty associated to radar rainfall estimates in a probabilistic framework, to be potentially implemented in the real-time management of the sewer network in the study area. Radar rainfall estimates are affected by uncertainty due to various factors [1-3] and quality control and correction techniques have been developed in order to improve their accuracy. However, the hydrological use of radar rainfall estimates and forecasts remains challenging. A significant effort has been devoted by the international research community to the assessment of the uncertainty propagation through probabilistic hydro-meteorological forecast systems [4-5], and various approaches have been implemented for the purpose of characterizing the uncertainty in radar rainfall estimates and forecasts [6-11]. A radar-based ensemble stochastic approach, similar to the one implemented for use in the Southern-Alps by the REAL system [6], has been developed for the purpose of this work. An ensemble generator has been calibrated on the basis of the spatial-temporal characteristics of the residual error in radar estimates assessed with reference to rainfall records from around 200 rain gauges available for the year 2007, previously post-processed and corrected by the UK Met Office [12-13]. Each ensemble member is determined by summing a perturbation field to the unperturbed radar rainfall field. The perturbations are generated by imposing the radar error spatial and temporal correlation structure to purely stochastic fields. A hydrodynamic sewer network model implemented in the Infoworks software was used to model the rainfall-runoff process in the urban area. The software calculates the flow through the sewer conduits of the urban model using rainfall as the primary input. The sewer network is covered by 25 radar pixels with a spatial resolution of 1 km2. The majority of the sewer system is combined, carrying both urban rainfall runoff as well as domestic and trade waste water [11]. The urban model was configured to receive the probabilistic radar rainfall fields. The results showed that the radar rainfall ensembles provide additional information about the uncertainty in the radar rainfall measurements that can be propagated in urban flood modelling. The peaks of the measured flow hydrographs are often bounded within the uncertainty area produced by using the radar rainfall ensembles. This is in fact one of the benefits of using radar rainfall ensembles in urban flood modelling. More work needs to be done in improving the urban models, but this is out of the scope of this research. The rainfall uncertainty cannot explain the whole uncertainty shown in the flow simulations, and additional sources of uncertainty will come from the structure of the urban models as well as the large number of parameters required by these models. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and the UK Environment Agency for providing the various data sets. We also thank Yorkshire Water Services Ltd for providing the urban model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1. References [1] Browning KA, 1978. Meteorological applications of radar. Reports on Progress in Physics 41 761 Doi: 10.1088/0034-4885/41/5/003 [2] Rico-Ramirez MA, Cluckie ID, Shepherd G, Pallot A, 2007. A high-resolution radar experiment on the island of Jersey. Meteorological Applications 14: 117-129. [3] Villarini G, Krajewski WF, 2010. Review of the different sources of uncertainty in single polarization radar-based estimates of rainfall. Surveys in Geophysics 31: 107-129. [4] Rossa A, Liechti K, Zappa M, Bruen M, Germann U, Haase G, Keil C, Krahe P, 2011. The COST 731 Action: A review on uncertainty propagation in advanced hydrometeorological forecast systems. Atmospheric Research 100, 150-167. [5] Rossa A, Bruen M, Germann U, Haase G, Keil C, Krahe P, Zappa M, 2010. Overview and Main Results on the interdisciplinary effort in flood forecasting COST 731-Propagation of Uncertainty in Advanced Meteo-Hydrological Forecast Systems. Proceedings of Sixth European Conference on Radar in Meteorology and Hydrology ERAD 2010. [6] Germann U, Berenguer M, Sempere-Torres D, Zappa M, 2009. REAL - ensemble radar precipitation estimation for hydrology in a mountainous region. Quarterly Journal of the Royal Meteorological Society 135: 445-456. [8] Bowler NEH, Pierce CE, Seed AW, 2006. STEPS: a probabilistic precipitation forecasting scheme which merges and extrapolation nowcast with downscaled NWP. Quarterly Journal of the Royal Meteorological Society 132: 2127-2155. [9] Zappa M, Rotach MW, Arpagaus M, Dorninger M, Hegg C, Montani A, Ranzi R, Ament F, Germann U, Grossi G et al., 2008. MAP D-PHASE: real-time demonstration of hydrological ensemble prediction systems. Atmospheric Science Letters 9, 80-87. [10] Liguori S, Rico-Ramirez MA. Quantitative assessment of short-term rainfall forecasts from radar nowcasts and MM5 forecasts. Hydrological Processes, accepted article. DOI: 10.1002/hyp.8415 [11] Liguori S, Rico-Ramirez MA, Schellart ANA, Saul AJ, 2012. Using probabilistic radar rainfall nowcasts and NWP forecasts for flow prediction in urban catchments. Atmospheric Research 103: 80-95. [12] Harrison DL, Driscoll SJ, Kitchen M, 2000. Improving precipitation estimates from weather radar using quality control and correction techniques. Meteorological Applications 7: 135-144. [13] Harrison DL, Scovell RW, Kitchen M, 2009. High-resolution precipitation estimates for hydrological uses. Proceedings of the Institution of Civil Engineers - Water Management 162: 125-135.

Simulating storm surge inundation and damage potential within complex port facilities

NASA Astrophysics Data System (ADS)

Mawdsley, Robert; French, Jon; Fujiyama, Taku; Achutan, Kamalasudhan

2017-04-01

Storm surge inundation of port facilities can cause damage to critical elements of infrastructure, significantly disrupt port operations and cause downstream impacts on vital supply chains. A tidal surge in December 2013 in the North Sea partly flooded the Port of Immingham, which handles the largest volume of bulk cargo in the UK including major flows of coal and biomass for power generation. This flooding caused damage to port and rail transport infrastructure and disrupted operations for several weeks. This research aims to improve resilience to storm surges using hydrodynamic modelling coupled to an agent-based model of port operations. Using the December 2013 event to validate flood extent, depth and duration, we ran a high resolution hydrodynamic simulation using the open source Telemac 2D finite element code. The underlying Digital Elevation Model (DEM) was derived from Environment Agency LiDAR data, with ground truthing of the flood defences along the port frontage. Major infrastructure and buildings are explicitly resolved with varying degrees of permeability. Telemac2D simulations are run in parallel and take only minutes on a single 16 cpu compute node. Inundation characteristics predicted using Telemac 2D differ from a simple Geographical Information System 'bath-tub' analysis of the DEM based upon horizontal application of the maximum water level across the port topography. The hydrodynamic simulation predicts less extensive flooding and more closely matches observed flood extent. It also provides more precise depth and duration curves. Detailed spatial flood depth and duration maps were generated for a range of tide and surge scenarios coupled to mean sea-level rise projections. These inundation scenarios can then be integrated with critical asset databases and an agent-based model of port operation (MARS) that is capable of simulating storm surge disruption along wider supply chains. Port operators are able to act on information from a particular flood scenario to perform adaptive responses (e.g. pre-emptive relocation of equipment), as well as estimate the likely duration of any disruption to port and supply chain operation. High resolution numerical inundation modelling, coupled to accurate storm surge forecasting and an agent based port operation model, thus has the potential to significantly reduce damage and disruption costs associated with storm surge impacts on port infrastructure and systems.

Regional probabilistic risk assessment of heavy metals in different environmental media and land uses: An urbanization-affected drinking water supply area

NASA Astrophysics Data System (ADS)

Peng, Chi; Cai, Yimin; Wang, Tieyu; Xiao, Rongbo; Chen, Weiping

2016-11-01

In this study, we proposed a Regional Probabilistic Risk Assessment (RPRA) to estimate the health risks of exposing residents to heavy metals in different environmental media and land uses. The mean and ranges of heavy metal concentrations were measured in water, sediments, soil profiles and surface soils under four land uses along the Shunde Waterway, a drinking water supply area in China. Hazard quotients (HQs) were estimated for various exposure routes and heavy metal species. Riverbank vegetable plots and private vegetable plots had 95th percentiles of total HQs greater than 3 and 1, respectively, indicating high risks of cultivation on the flooded riverbank. Vegetable uptake and leaching to groundwater were the two transfer routes of soil metals causing high health risks. Exposure risks during outdoor recreation, farming and swimming along the Shunde Waterway are theoretically safe. Arsenic and cadmium were identified as the priority pollutants that contribute the most risk among the heavy metals. Sensitivity analysis showed that the exposure route, variations in exposure parameters, mobility of heavy metals in soil, and metal concentrations all influenced the risk estimates.

Probabilistic Evaluation of Advanced Ceramic Matrix Composite Structures

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2003-01-01

The objective of this report is to summarize the deterministic and probabilistic structural evaluation results of two structures made with advanced ceramic composites (CMC): internally pressurized tube and uniformly loaded flange. The deterministic structural evaluation includes stress, displacement, and buckling analyses. It is carried out using the finite element code MHOST, developed for the 3-D inelastic analysis of structures that are made with advanced materials. The probabilistic evaluation is performed using the integrated probabilistic assessment of composite structures computer code IPACS. The affects of uncertainties in primitive variables related to the material, fabrication process, and loadings on the material property and structural response behavior are quantified. The primitive variables considered are: thermo-mechanical properties of fiber and matrix, fiber and void volume ratios, use temperature, and pressure. The probabilistic structural analysis and probabilistic strength results are used by IPACS to perform reliability and risk evaluation of the two structures. The results will show that the sensitivity information obtained for the two composite structures from the computational simulation can be used to alter the design process to meet desired service requirements. In addition to detailed probabilistic analysis of the two structures, the following were performed specifically on the CMC tube: (1) predicted the failure load and the buckling load, (2) performed coupled non-deterministic multi-disciplinary structural analysis, and (3) demonstrated that probabilistic sensitivities can be used to select a reduced set of design variables for optimization.

Risk in nuclear power plants due to natural hazard phenomena

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, S.C.

1995-12-01

For the safety of nuclear power plants, it is important to identify potential areas of vulnerabilities to internal as well as external events to which nuclear power plants are exposed. This paper summarizes the risk in nuclear power plants due to natural hazard phenomena such as earthquakes, winds and tornadoes, floods, etc. The reported results are based on a limited number of probabilistic risk assessments (PRAS) performed for a few of the operating nuclear power plants within the United States. The summary includes an importance ranking of various natural hazard phenomena based on their contribution to the plant risk alongmore » with insights observed from the PRA studies.« less

Analysis of the light-water flooding of the HFBR thimble tubes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carew, J.F.; Aronson, A.L.; Cokinos, D.M.

The fuel elements surrounding the central vertical thimble tubes in the Brookhaven National Laboratory High-Flux Beam Reactor (HFBR) are highly undermoderated, and light-water flooding of these irradiation thimbles results in a positive core reactivity insertion. The light-water contamination of the D{sub 2}O thimble tube coolant is the result of a postulated double-ended guillotine break of a U tube in the experimental facilities heat exchanger during the HFBR light-water flooding (LWF) event. While this event has a low probability (1.3 x 10{sup {minus}4}/yr), the HFBR protection system must ensure adequate thermal margin during the power transient. This paper summarizes the analysismore » of the HFBR thimble-tube LWF event.« less

Testing of focal plane arrays at the AEDC

NASA Astrophysics Data System (ADS)

Nicholson, Randy A.; Mead, Kimberly D.; Smith, Robert W.

1992-07-01

A facility was developed at the Arnold Engineering Development Center (AEDC) to provide complete radiometric characterization of focal plane arrays (FPAs). The highly versatile facility provides the capability to test single detectors, detector arrays, and hybrid FPAs. The primary component of the AEDC test facility is the Focal Plane Characterization Chamber (FPCC). The FPCC provides a cryogenic, low-background environment for the test focal plane. Focal plane testing in the FPCC includes flood source testing, during which the array is uniformly irradiated with IR radiation, and spot source testing, during which the target radiation is focused onto a single pixel or group of pixels. During flood source testing, performance parameters such as power consumption, responsivity, noise equivalent input, dynamic range, radiometric stability, recovery time, and array uniformity can be assessed. Crosstalk is evaluated during spot source testing. Spectral response testing is performed in a spectral response test station using a three-grating monochromator. Because the chamber can accommodate several types of testing in a single test installation, a high throughput rate and good economy of operation are possible.

Development of cloud-operating platform for detention facility design

NASA Astrophysics Data System (ADS)

Tun Lee, Kwan; Hung, Meng-Chiu; Tseng, Wei-Fan; Chan, Yi-Ping

2017-04-01

In the past 20 years, the population of Taiwan has accumulated in urban areas. The land development has changed the hydrological environment and resulted in the increase of surface runoff and shortened the time to peak discharge. The change of runoff characteristics increases the flood risk and reduces resilient ability of the city during flood. Considering that engineering measures may not be easy to implement in populated cities, detention facilities set on building basements have been proposed to compromise the increase of surface runoff resulting from development activities. In this study, a web-based operational platform has been developed to integrate the GIS technologies, hydrological analyses, as well as relevant regulations for the design of detention facilities. The design procedure embedded in the system includes a prior selection of type and size of the detention facility, integrated hydrological analysis for the developing site, and inspection of relevant regulations. After login the platform, designers can access the system database to retrieve road maps, land use coverages, and storm sewer information. Once the type, size, inlet, and outlet of the detention facility are assigned, the system can acquire the rainfall intensity-duration-frequency information from adjacent rain gauges to perform hydrological analyses for the developing site. The increase of the runoff volume due to the development and the reduction of the outflow peak through the construction of the detention facility can be estimated. The outflow peak at the target site is then checked with relevant regulations to confirm the suitability of the detention facility design. The proposed web-based platform can provide a concise layout of the detention facility and the drainageway of the developing site on a graphical interface. The design information can also be delivered directly through a web link to authorities for inspecting to simplify the complex administrative procedures.

Adequacy assessment of composite generation and transmission systems incorporating wind energy conversion systems

NASA Astrophysics Data System (ADS)

Gao, Yi

The development and utilization of wind energy for satisfying electrical demand has received considerable attention in recent years due to its tremendous environmental, social and economic benefits, together with public support and government incentives. Electric power generation from wind energy behaves quite differently from that of conventional sources. The fundamentally different operating characteristics of wind energy facilities therefore affect power system reliability in a different manner than those of conventional systems. The reliability impact of such a highly variable energy source is an important aspect that must be assessed when the wind power penetration is significant. The focus of the research described in this thesis is on the utilization of state sampling Monte Carlo simulation in wind integrated bulk electric system reliability analysis and the application of these concepts in system planning and decision making. Load forecast uncertainty is an important factor in long range planning and system development. This thesis describes two approximate approaches developed to reduce the number of steps in a load duration curve which includes load forecast uncertainty, and to provide reasonably accurate generating and bulk system reliability index predictions. The developed approaches are illustrated by application to two composite test systems. A method of generating correlated random numbers with uniform distributions and a specified correlation coefficient in the state sampling method is proposed and used to conduct adequacy assessment in generating systems and in bulk electric systems containing correlated wind farms in this thesis. The studies described show that it is possible to use the state sampling Monte Carlo simulation technique to quantitatively assess the reliability implications associated with adding wind power to a composite generation and transmission system including the effects of multiple correlated wind sites. This is an important development as it permits correlated wind farms to be incorporated in large practical system studies without requiring excessive increases in computer solution time. The procedures described in this thesis for creating monthly and seasonal wind farm models should prove useful in situations where time period models are required to incorporate scheduled maintenance of generation and transmission facilities. There is growing interest in combining deterministic considerations with probabilistic assessment in order to evaluate the quantitative system risk and conduct bulk power system planning. A relatively new approach that incorporates deterministic and probabilistic considerations in a single risk assessment framework has been designated as the joint deterministic-probabilistic approach. The research work described in this thesis illustrates that the joint deterministic-probabilistic approach can be effectively used to integrate wind power in bulk electric system planning. The studies described in this thesis show that the application of the joint deterministic-probabilistic method provides more stringent results for a system with wind power than the traditional deterministic N-1 method because the joint deterministic-probabilistic technique is driven by the deterministic N-1 criterion with an added probabilistic perspective which recognizes the power output characteristics of a wind turbine generator.

10 CFR 960.5-2-8 - Surface characteristics.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Closure § 960.5-2-8 Surface characteristics. (a) Qualifying condition. The site shall be located such that... could lead to the flooding of surface or underground facilities by the occupancy and modification of...

40 CFR 141.5 - Siting requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., avoid locating part or all of the new or expanded facility at a site which: (a) Is subject to a significant risk from earthquakes, floods, fires or other disasters which could cause a breakdown of the...

18 CFR 1304.405 - Fuel storage tanks and handling facilities.

Code of Federal Regulations, 2012 CFR

2012-04-01

... State showing how the tank will be anchored so that it does not float during flooding; and (5) Evidence, where applicable, that the applicant has complied with all spill prevention, control and countermeasures...

18 CFR 1304.405 - Fuel storage tanks and handling facilities.

Code of Federal Regulations, 2013 CFR

2013-04-01

... State showing how the tank will be anchored so that it does not float during flooding; and (5) Evidence, where applicable, that the applicant has complied with all spill prevention, control and countermeasures...

18 CFR 1304.405 - Fuel storage tanks and handling facilities.

Code of Federal Regulations, 2014 CFR

2014-04-01

... State showing how the tank will be anchored so that it does not float during flooding; and (5) Evidence, where applicable, that the applicant has complied with all spill prevention, control and countermeasures...

18 CFR 1304.405 - Fuel storage tanks and handling facilities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... State showing how the tank will be anchored so that it does not float during flooding; and (5) Evidence, where applicable, that the applicant has complied with all spill prevention, control and countermeasures...

18 CFR 1304.405 - Fuel storage tanks and handling facilities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... State showing how the tank will be anchored so that it does not float during flooding; and (5) Evidence, where applicable, that the applicant has complied with all spill prevention, control and countermeasures...

The Gain-Loss Model: A Probabilistic Skill Multimap Model for Assessing Learning Processes

ERIC Educational Resources Information Center

Robusto, Egidio; Stefanutti, Luca; Anselmi, Pasquale

2010-01-01

Within the theoretical framework of knowledge space theory, a probabilistic skill multimap model for assessing learning processes is proposed. The learning process of a student is modeled as a function of the student's knowledge and of an educational intervention on the attainment of specific skills required to solve problems in a knowledge…

Probabilistic storm surge inundation maps for Metro Manila based on Philippine public storm warning signals

NASA Astrophysics Data System (ADS)

Tablazon, J.; Caro, C. V.; Lagmay, A. M. F.; Briones, J. B. L.; Dasallas, L.; Lapidez, J. P.; Santiago, J.; Suarez, J. K.; Ladiero, C.; Gonzalo, L. A.; Mungcal, M. T. F.; Malano, V.

2015-03-01

A storm surge is the sudden rise of sea water over the astronomical tides, generated by an approaching storm. This event poses a major threat to the Philippine coastal areas, as manifested by Typhoon Haiyan on 8 November 2013. This hydro-meteorological hazard is one of the main reasons for the high number of casualties due to the typhoon, with 6300 deaths. It became evident that the need to develop a storm surge inundation map is of utmost importance. To develop these maps, the Nationwide Operational Assessment of Hazards under the Department of Science and Technology (DOST-Project NOAH) simulated historical tropical cyclones that entered the Philippine Area of Responsibility. The Japan Meteorological Agency storm surge model was used to simulate storm surge heights. The frequency distribution of the maximum storm surge heights was calculated using simulation results of tropical cyclones under a specific public storm warning signal (PSWS) that passed through a particular coastal area. This determines the storm surge height corresponding to a given probability of occurrence. The storm surge heights from the model were added to the maximum astronomical tide data from WXTide software. The team then created maps of inundation for a specific PSWS using the probability of exceedance derived from the frequency distribution. Buildings and other structures were assigned a probability of exceedance depending on their occupancy category, i.e., 1% probability of exceedance for critical facilities, 10% probability of exceedance for special occupancy structures, and 25% for standard occupancy and miscellaneous structures. The maps produced show the storm-surge-vulnerable areas in Metro Manila, illustrated by the flood depth of up to 4 m and extent of up to 6.5 km from the coastline. This information can help local government units in developing early warning systems, disaster preparedness and mitigation plans, vulnerability assessments, risk-sensitive land use plans, shoreline defense efforts, and coastal protection measures. These maps can also determine the best areas to build critical structures, or at least determine the level of protection of these structures should they be built in hazard areas. Moreover, these will support the local government units' mandate to raise public awareness, disseminate information about storm surge hazards, and implement appropriate countermeasures for a given PSWS.

Flood damage curves for consistent global risk assessments

NASA Astrophysics Data System (ADS)

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-national scale flood damage assessments, and guide assessment in countries where no damage model is currently available.

Notable local floods of 1942-43, Floods of July 18, 1942 in north-central Pennsylvania, with a section on descriptive details of the storm and floods

USGS Publications Warehouse

Eisenlohr, William Stewart; Stewart, J.E.

1952-01-01

During the night of August 4-5, 1943, a violent thunderstorm of unusual intensity occurred in parts of Braxton, Calhoun, Gilmer, Ritchie, and Wirth Counties in the Little Kanawha River Basin in central West Virginia. Precipitation amounted to as much as 15 inches in 2 hours in some sections. As a result, many small streams and a reach of the Little Kanawha River in the vicinity of Burnsville and Gilmer reached the highest stages known. Computations based on special surveys made at suitable sites on representative small streams in the areas of intense flooding indicate that peak discharges closely approach 50 percent of the Jarvis scale. Twenty-three lives were lost on the small tributaries as numerous homes were swept away by the flood, which developed with incredible rapidity during the early morning hours. Damage estimated at $1,300,000 resulted to farm buildings, crops, land, livestock, railroads, highways, and gas- and oil-producing facilities. Considerable permanent land damage resulted from erosion and deposition of sand and gravel.

Flood-plain delineation for Accotink Creek Basin, Fairfax County, Virginia

USGS Publications Warehouse

Soule, Pat L.

1977-01-01

Water-surface profiles of the 25-year and 100-year floods maps on which the 25-, 50-, and 100-year flood limits are delineated for streams in the Accotink Creek basin are presented in this report. Excluded are segments of Accotink Creek within the Fort Belvoir Military Reservation. The techniques used in the computation of the flood profiles and delineation of flood limits are presented, and specific hydraulic problems encountered within the study area are also included.

Identification of Flood Reactivity Regions via the Functional Clustering of Hydrographs

NASA Astrophysics Data System (ADS)

Brunner, Manuela I.; Viviroli, Daniel; Furrer, Reinhard; Seibert, Jan; Favre, Anne-Catherine

2018-03-01

Flood hydrograph shapes contain valuable information on the flood-generation mechanisms of a catchment. To make good use of this information, we express flood hydrograph shapes as continuous functions using a functional data approach. We propose a clustering approach based on functional data for flood hydrograph shapes to identify a set of representative hydrograph shapes on a catchment scale and use these catchment-specific sets of representative hydrographs to establish regions of catchments with similar flood reactivity on a regional scale. We applied this approach to flood samples of 163 medium-size Swiss catchments. The results indicate that three representative hydrograph shapes sufficiently describe the hydrograph shape variability within a catchment and therefore can be used as a proxy for the flood behavior of a catchment. These catchment-specific sets of three hydrographs were used to group the catchments into three reactivity regions of similar flood behavior. These regions were not only characterized by similar hydrograph shapes and reactivity but also by event magnitudes and triggering event conditions. We envision these regions to be useful in regionalization studies, regional flood frequency analyses, and to allow for the construction of synthetic design hydrographs in ungauged catchments. The clustering approach based on functional data which establish these regions is very flexible and has the potential to be extended to other geographical regions or toward the use in climate impact studies.

Development of a Probabilistic Tsunami Hazard Analysis in Japan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Toshiaki Sakai; Tomoyoshi Takeda; Hiroshi Soraoka

2006-07-01

It is meaningful for tsunami assessment to evaluate phenomena beyond the design basis as well as seismic design. Because once we set the design basis tsunami height, we still have possibilities tsunami height may exceeds the determined design tsunami height due to uncertainties regarding the tsunami phenomena. Probabilistic tsunami risk assessment consists of estimating for tsunami hazard and fragility of structures and executing system analysis. In this report, we apply a method for probabilistic tsunami hazard analysis (PTHA). We introduce a logic tree approach to estimate tsunami hazard curves (relationships between tsunami height and probability of excess) and present anmore » example for Japan. Examples of tsunami hazard curves are illustrated, and uncertainty in the tsunami hazard is displayed by 5-, 16-, 50-, 84- and 95-percentile and mean hazard curves. The result of PTHA will be used for quantitative assessment of the tsunami risk for important facilities located on coastal area. Tsunami hazard curves are the reasonable input data for structures and system analysis. However the evaluation method for estimating fragility of structures and the procedure of system analysis is now being developed. (authors)« less

Models, solution, methods and their applicability of dynamic location problems (DLPs) (a gap analysis for further research)

NASA Astrophysics Data System (ADS)

Seyedhosseini, Seyed Mohammad; Makui, Ahmad; Shahanaghi, Kamran; Torkestani, Sara Sadat

2016-09-01

Determining the best location to be profitable for the facility's lifetime is the important decision of public and private firms, so this is why discussion about dynamic location problems (DLPs) is a critical significance. This paper presented a comprehensive review from 1968 up to most recent on published researches about DLPs and classified them into two parts. First, mathematical models developed based on different characteristics: type of parameters (deterministic, probabilistic or stochastic), number and type of objective function, numbers of commodity and modes, relocation time, number of relocation and relocating facilities, time horizon, budget and capacity constraints and their applicability. In second part, It have been also presented solution algorithms, main specification, applications and some real-world case studies of DLPs. At the ends, we concluded that in the current literature of DLPs, distribution systems and production-distribution systems with simple assumption of the tackle to the complexity of these models studied more than any other fields, as well as the concept of variety of services (hierarchical network), reliability, sustainability, relief management, waiting time for services (queuing theory) and risk of facility disruption need for further investigation. All of the available categories based on different criteria, solution methods and applicability of them, gaps and analysis which have been done in this paper suggest the ways for future research.

Preliminary volcanic hazards evaluation for Los Alamos National Laboratory Facilities and Operations : current state of knowledge and proposed path forward

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keating, Gordon N.; Schultz-Fellenz, Emily S.; Miller, Elizabeth D.

2010-09-01

The integration of available information on the volcanic history of the region surrounding Los Alamos National Laboratory indicates that the Laboratory is at risk from volcanic hazards. Volcanism in the vicinity of the Laboratory is unlikely within the lifetime of the facility (ca. 50–100 years) but cannot be ruled out. This evaluation provides a preliminary estimate of recurrence rates for volcanic activity. If further assessment of the hazard is deemed beneficial to reduce risk uncertainty, the next step would be to convene a formal probabilistic volcanic hazards assessment.

Risk management at the stage of design of high-rise construction facilities

NASA Astrophysics Data System (ADS)

Politi, Violetta

2018-03-01

This paper describes the assessment of the probabilistic risk of an accident formed in the process of designing a technically complex facility. It considers values of conditional probabilities of the compliance of load-bearing structures with safety requirements, provides an approximate list of significant errors of the designer and analyzes the relationship between the degree of compliance and the level of danger of errors. It describes and proposes for implementation the regulated procedures related to the assessment of the safety level of constructive solutions and the reliability of the construction process participants.

The effect of flooding on mental health: Lessons learned for building resilience

NASA Astrophysics Data System (ADS)

Foudi, Sébastien; Osés-Eraso, Nuria; Galarraga, Ibon

2017-07-01

Risk management and climate adaptation literature focuses mainly on reducing the impacts of, exposure to, and vulnerability to extreme events such as floods and droughts. Posttraumatic stress disorder is one of the most important impacts related to these events, but also a relatively under-researched topic outside original psychopathological contexts. We conduct a survey to investigate the mental stress caused by floods. We focus on hydrological, individual, and collective drivers of posttraumatic stress. We assess stress with flood-specific health scores and the GHQ-12 General Health Questionnaire. Our findings show that the combination of water depth and flood velocity measured via a Hazard Class Index is an important stressor; and that mental health resilience can be significantly improved by providing the population with adequate information. More specifically, the paper shows that psychological distress can be reduced by (i) coordinating awareness of flood risks and flood protection and prevention behavior; (ii) developing the ability to protect oneself from physical, material and intangible damage; (iii) designing simple insurance procedures and protocols for fast recovery; and (iv) learning from previous experiences.

77 FR 67324 - Proposed Flood Elevation Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-09

...). Specifically, it addresses the flooding sources Big Run, Little Loyalsock Creek, Loyalsock Creek, and Muncy..., Pennsylvania (All Jurisdictions)'' addressed the flooding sources Big Run, Little Loyalsock Creek, Loyalsock... Sullivan County, Pennsylvania (All Jurisdictions) Big Run At the Muncy Creek +968 +965 Township of Davidson...

76 FR 12665 - Proposed Flood Elevation Determinations

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-08

... Areas. Specifically, it addresses the following flooding sources: Hungry Hollow Gulch, Ice House Creek, Ice House Creek Tributary A, Riggs Gulch, Spearfish Creek, and Unnamed Tributary to Higgins Gulch... Incorporated Areas'' addressed the following flooding sources: Hungry Hollow Gulch, Ice House Creek, Ice House...

Karst flash floods: an example from the Dinaric karst (Croatia)

NASA Astrophysics Data System (ADS)

Bonacci, O.; Ljubenkov, I.; Roje-Bonacci, T.

2006-03-01

Flash floods constitute one of the deadliest and costliest natural disasters worldwide. This paper explains the karst flash flood phenomenon, which represents a special kind of flash flood. As the majority of flash floods karst flash floods are caused by intensive short-term precipitation in an area whose surface rarely exceeds a few square kilometres. The characteristics of all flash floods are their short duration, small areal extent, high flood peaks and rapid flows, and heavy loss of life and property. Karst flash floods have specific characteristics due to special conditions for water circulation, which exist in karst terrains. During karst flash floods a sudden rise of groundwater levels occurs, which causes the appearance of numerous, unexpected, abundant and temporary karst springs. This paper presents in detail an example of a karst flash flood in the Marina bay (Dinaric karst region of Croatia), which occurred in December 2004.

Probability misjudgment, cognitive ability, and belief in the paranormal.

PubMed

Musch, Jochen; Ehrenberg, Katja

2002-05-01

According to the probability misjudgment account of paranormal belief (Blackmore & Troscianko, 1985), believers in the paranormal tend to wrongly attribute remarkable coincidences to paranormal causes rather than chance. Previous studies have shown that belief in the paranormal is indeed positively related to error rates in probabilistic reasoning. General cognitive ability could account for a relationship between these two variables without assuming a causal role of probabilistic reasoning in the forming of paranormal beliefs, however. To test this alternative explanation, a belief in the paranormal scale (BPS) and a battery of probabilistic reasoning tasks were administered to 123 university students. Confirming previous findings, a significant correlation between BPS scores and error rates in probabilistic reasoning was observed. This relationship disappeared, however, when cognitive ability as measured by final examination grades was controlled for. Lower cognitive ability correlated substantially with belief in the paranormal. This finding suggests that differences in general cognitive performance rather than specific probabilistic reasoning skills provide the basis for paranormal beliefs.

Discovering temporal patterns in water quality time series, focusing on floods with the LDA method

NASA Astrophysics Data System (ADS)

Hélène Aubert, Alice; Tavenard, Romain; Emonet, Rémi; Malinowski, Simon; Guyet, Thomas; Quiniou, René; Odobez, Jean-Marc; Gascuel-Odoux, Chantal

2013-04-01

Studying floods has been a major issue in hydrological research for years. It is often done in terms of water quantity but it is also of interest in terms of water quality. Stream chemistry is a mix of solutes. They originate from various sources in the catchment, reach the stream by various flow pathways and are transformed by biogeochemical reactions at different locations. Therefore, we hypothesized that reaction of the stream chemistry to a rainfall event is not unique but varies according to the season (1), and the global meteorological conditions of the year (2). Identifying a typology of temporal chemical patterns of reaction to a rainfall event is a way to better understand catchment processes at the flood time scale. To answer this issue, we applied a probabilistic model (Latent Dirichlet Allocation or LDA (3)) mining recurrent sequential patterns to a dataset of floods. The dataset is 12 years long and daily recorded. It gathers a broad range of parameters from which we selected rainfall, discharge, water table depth, temperature as well as nitrate, dissolved organic carbon, sulphate and chloride concentrations. It comes from a long-term hydrological observatory (AgrHys, western France) located at Kervidy-Naizin. A set of 472 floods was automatically extracted (4). From each flood, a document has been generated that is made of a set of "hydrological words". Each hydrological word corresponds to a measurement: it is a triplet made of the considered variable, the time at which the measurement is made (relative to the beginning of the flood), and its magnitude (that can be low, medium or high). The documents are used as input data to the LDA algorithm. LDA relies on spotting co-occurrences (as an alternative to the more traditional study of correlation) between words that appear within the flood documents. It has two nice properties that are its ability to easily deal with missing data and its additive property that allows a document to be seen as a mixture of several flood patterns. The output of LDA is a set of patterns that can easily be represented in graphics. These patterns correspond to typical reactions to rainfall events. The patterns themselves are carefully studied, as well as their repartition along the year and along the 12 years of the dataset. The novelties are fourfold. First, as a methodological point of view, we learn that hydrological data can be analyzed with this LDA model giving a typology of a multivariate chemical signature of floods. Second, we outline that chemistry parameters are sufficient to obtain meaningful patterns. There is no need to include hydro-meteorological parameters to define the patterns. However, hydro-meteorological parameters are useful to understand the processes leading to these patterns. Third, our hypothesis of seasonal specific reaction to rainfall is verified, moreover detailed; so is our hypothesis of different reactions to rainfall for years with different hydro-meteorological conditions. Fourth, this method allows the consideration of overlapping floods that are usually not studied. We would recommend the use of such model to study chemical reactions of stream after rainfall events, or more broadly after any hydrological events. The typology that has been provided by this method is a kind of bar code of water chemistry during floods. It could be well suited to compare different geographical locations by using the same patterns and analysing the resulting different pattern distributions. (1) Aubert, A.H. et al., 2012. The chemical signature of a livestock farming catchment: synthesis from a high-frequency multi-element long term monitoring. HESSD, 9(8): 9715 - 9741. (2) Aubert, A.H., Gascuel-Odoux, C., Merot, P., 2013. Annual hysteresis of water quality: A method to analyse the effect of intra- and inter-annual climatic conditions. Journal of Hydrology, 478(0): 29-39. (3) Blei, D. M.; Ng, A. Y.; Jordan, M. I., 2003. Latent Dirichlet allocation. Journal of Machine Learning Research, 3(4-5): 993-1022. (4) de Lavenne, A., Cudennec, C., Streamflow velocity estimation in GIUH-type approach: what can neighbouring basins tell us? Poster Presentation - EGU General Assembly, 22-27 April 2012, Vienna, Austria.