Science.gov

Sample records for national flood forecasting

  1. Experiences from coordinated national-level landslide and flood forecasting in Norway

    NASA Astrophysics Data System (ADS)

    Krøgli, Ingeborg; Fleig, Anne; Glad, Per; Dahl, Mads-Peter; Devoli, Graziella; Colleuille, Hervé

    2015-04-01

    While flood forecasting at national level is quite well established and operational in many countries worldwide, landslide forecasting at national level is still seldom. Examples of coordinated flood and landslide forecasting are even rarer. Most of the time flood and landslide forecasters work separately (investigating, defining thresholds, and developing models) and most of the time without communication with each other. One example of coordinated operational early warning systems (EWS) for flooding and shallow landslides is found at the Norwegian Water Resources and Energy Directorate (NVE) in Norway. In this presentation we give an introduction to the two separate but tightly collaborative EWSs and to the coordination of these. The two EWSs are being operated from the same office, every day using similar hydro-meteorological prognosis and hydrological models. Prognosis and model outputs on e.g. discharge, snow melt, soil water content and exceeded landslide thresholds are evaluated in a web based decision-making tool (xgeo.no). The experts performing forecasts are hydrologists, geologists and physical geographers. A similar warning scale, based on colors (green, yellow, orange and red) is used for both EWSs, however thresholds for flood and landslide warning levels are defined differently. Also warning areas may not necessary be the same for both hazards and depending on the specific meteorological event, duration of the warning periods can differ. We present how knowledge, models and tools, but also human and economic resources are being shared between the two EWSs. Moreover, we discuss challenges faced in the communication of warning messages using recent flood and landslide events as examples.

  2. Real-time flood forecasting

    USGS Publications Warehouse

    Lai, C.; Tsay, T.-K.; Chien, C.-H.; Wu, I.-L.

    2009-01-01

    Researchers at the Hydroinformatic Research and Development Team (HIRDT) of the National Taiwan University undertook a project to create a real time flood forecasting model, with an aim to predict the current in the Tamsui River Basin. The model was designed based on deterministic approach with mathematic modeling of complex phenomenon, and specific parameter values operated to produce a discrete result. The project also devised a rainfall-stage model that relates the rate of rainfall upland directly to the change of the state of river, and is further related to another typhoon-rainfall model. The geographic information system (GIS) data, based on precise contour model of the terrain, estimate the regions that were perilous to flooding. The HIRDT, in response to the project's progress, also devoted their application of a deterministic model to unsteady flow of thermodynamics to help predict river authorities issue timely warnings and take other emergency measures.

  3. 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting

    E-print Network

    Greenslade, Diana

    SHEET 6 1Bureau of Meteorology | Water Information > INFORMATION SHEET 6 > Flood Forecasting and Warning Services Flood Forecasting and Warning Services The Bureau of Meteorology (the Bureau) is responsible for providing an effective flood forecasting and warning service in each Australian state

  4. Local flood forecasting - From data collection to communicating forecasts

    NASA Astrophysics Data System (ADS)

    Smith, P. J.; Beven, K.

    2013-12-01

    An important aspect of improving resilience to flooding is the provision of timely warnings to flood sensitive locations thus allowing mitigating measures to be implemented. For specific locations such small communities (often in head water catchments) or river side factories the ability of traditional centralised forecasting systems to provide timely & accurate forecasts may be challenged. This is due in part to the finite resources of monitoring agencies which results in courser spatial scales of model and data collection then may be required for the generation of accurate forecasts. One strategy to improve flood resilience at such locations is to develop automated location specific forecasts. In this presentation we outline a methodology to achieve this based on the installation of adequate telemetered monitoring equipment; generally a water level sensor and a rain gauge. This allows the construction of a local flood forecasting model which may be coupled with available precipitation forecasts. The construction of the hydrological forecasting model consists of a guided process which incorporates both data assimilation and the representation of the forecast uncertainty based on post processing. The guided process requires the modeller to make only a few choices thus allowing rapid model deployment and revision. To be of use the derived forecasts must be made available in real time and updated frequently; maybe every five minutes. Traditional practices in issuing warnings dependent on expert interpretation must therefore be altered so that those at the site of interest become their own `experts'. To aid this appropriate presentation of both the predictions and past performance of the model, designed to encourage realistic interpretation of the forecasts and their uncertainties is considered. The resulting forecast chain is demonstrated on UK case studies.

  5. The Flood Forecasting Centre (FFC) in the UK

    NASA Astrophysics Data System (ADS)

    Davies, P.

    2009-09-01

    The Met Office and the Environment Agency in the UK have set up a joint Flood Forecasting Centre (FFC), based at the London offices of the Met Office. This partnership will improve the UK's ability to respond to flooding events by providing an earlier national forecasting and alert service to central and local government departments so as to give them more time to prepare for floods and reduce the risk of loss of life and damage to property. The creation of the centre is in response to a key recommendation of Sir Michael Pitt's Review following the summer 2007 floods over the UK. For the first time, the FFC combines the Environment Agency's expertise in flood risk management and the Met Office's expertise in weather forecasting under one roof. My presentation will describe the benefits it will bring to the emergency responder community. It will also cover the tools available to the centre such as the new generation of high resolution weather models now coming on line. As a result, flood forecasting and warning systems, (which historically have been based on the lack of sufficiently fine scale rainfall information), need to be revisited in the light of the new meteorological modelling capabilities. This is particularly true for surface water flooding, where these new capabilities offer, for the first time, the possibility of providing credible alerts.

  6. Flood Forecasting in River System Using ANFIS

    NASA Astrophysics Data System (ADS)

    Ullah, Nazrin; Choudhury, P.

    2010-10-01

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  7. Flood Forecasting in River System Using ANFIS

    SciTech Connect

    Ullah, Nazrin; Choudhury, P.

    2010-10-26

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  8. National Flood Interoperability Experiment

    NASA Astrophysics Data System (ADS)

    Maidment, D. R.

    2014-12-01

    The National Flood Interoperability Experiment is led by the academic community in collaboration with the National Weather Service through the new National Water Center recently opened on the Tuscaloosa campus of the University of Alabama. The experiment will also involve the partners in IWRSS (Integrated Water Resources Science and Services), which include the USGS, the Corps of Engineers and FEMA. The experiment will address the following questions: (1) How can near-real-time hydrologic forecasting at high spatial resolution, covering the nation, be carried out using the NHDPlus or next generation geofabric (e.g. hillslope, watershed scales)? (2) How can this lead to improved emergency response and community resilience? (3) How can improved an improved interoperability framework support the first two goals and lead to sustained innovation in the research to operations process? The experiment will run from September 2014 through August 2015, in two phases. The mobilization phase from September 2014 until May 2015 will assemble the components of the interoperability framework. A Summer Institute to integrate the components will be held from June to August 2015 at the National Water Center involving faculty and students from the University of Alabama and other institutions coordinated by CUAHSI. It is intended that the insight that arises from this experiment will help lay the foundation for a new national scale, high spatial resolution, near-real-time hydrologic simulation system for the United States.

  9. Flood Forecasting in Wales: Challenges and Solutions

    NASA Astrophysics Data System (ADS)

    How, Andrew; Williams, Christopher

    2015-04-01

    With steep, fast-responding river catchments, exposed coastal reaches with large tidal ranges and large population densities in some of the most at-risk areas; flood forecasting in Wales presents many varied challenges. Utilising advances in computing power and learning from best practice within the United Kingdom and abroad have seen significant improvements in recent years - however, many challenges still remain. Developments in computing and increased processing power comes with a significant price tag; greater numbers of data sources and ensemble feeds brings a better understanding of uncertainty but the wealth of data needs careful management to ensure a clear message of risk is disseminated; new modelling techniques utilise better and faster computation, but lack the history of record and experience gained from the continued use of more established forecasting models. As a flood forecasting team we work to develop coastal and fluvial forecasting models, set them up for operational use and manage the duty role that runs the models in real time. An overview of our current operational flood forecasting system will be presented, along with a discussion on some of the solutions we have in place to address the challenges we face. These include: • real-time updating of fluvial models • rainfall forecasting verification • ensemble forecast data • longer range forecast data • contingency models • offshore to nearshore wave transformation • calculation of wave overtopping

  10. Medium range flood forecasts at global scale

    NASA Astrophysics Data System (ADS)

    Voisin, N.; Wood, A. W.; Lettenmaier, D. P.; Wood, E. F.

    2006-12-01

    While weather and climate forecast methods have advanced greatly over the last two decades, this capability has yet to be evidenced in mitigation of water-related natural hazards (primarily floods and droughts), especially in the developing world. Examples abound of extreme property damage and loss of life due to floods in the underdeveloped world. For instance, more than 4.5 million people were affected by the July 2000 flooding of the Mekong River and its tributaries in Cambodia, Vietnam, Laos and Thailand. The February- March 2000 floods in the Limpopo River of Mozambique caused extreme disruption to that country's fledgling economy. Mitigation of these events through advance warning has typically been modest at best. Despite the above noted improvement in weather and climate forecasts, there is at present no system for forecasting of floods globally, notwithstanding that the potential clearly exists. We describe a methodology that is eventually intended to generate global flood predictions routinely. It draws heavily from the experimental North American Land Data Assimilation System (NLDAS) and the companion Global Land Data Assimilation System (GLDAS) for development of nowcasts, and the University of Washington Experimental Hydrologic Prediction System to develop ensemble hydrologic forecasts based on Numerical Weather Prediction (NWP) models which serve both as nowcasts (and hence reduce the need for in situ precipitation and other observations in parts of the world where surface networks are critically deficient) and provide forecasts for lead times as long as fifteen days. The heart of the hydrologic modeling system is the University of Washington/Princeton University Variable Infiltration Capacity (VIC) macroscale hydrology model. In the prototype (tested using retrospective data), VIC is driven globally up to the time of forecast with daily ERA40 precipitation (rescaled on a monthly basis to a station-based global climatology), ERA40 wind, and ERA40 average surface air temperature (with temperature ranges adjusted to a station-based climatology). In the retrospective forecasting mode, VIC is driven by global NCEP ensemble 15-day reforecasts provided by Tom Hamill (NOAA/ERL), bias corrected with respect to the adjusted ERA40 data and further downscaled spatially using higher spatial resolution Global Precipitation Climatology Project (GPCP) 1dd daily precipitation. Downward solar and longwave radiation, surface relative humidity, and other model forcings are derived from relationships with the daily temperature range during both the retrospective (spinup) and forecast period. The initial system is implemented globally at one-half degree spatial resolution. We evaluate model performance retrospectively for predictions of major floods for the Oder River in 1997, the Mekong River in 2000 and the Limpopo River in 2000.

  11. VERIFICATION OF LONG-RANGE FLOOD FORECASTING PRODUCTS FOR EASTERN IOWA

    NASA Astrophysics Data System (ADS)

    Habib, M. A.; Bradley, A.

    2009-12-01

    After the devastating flood of 2008 in Iowa, communities throughout Iowa are recognizing the need to better anticipate future floods. Flood prediction and usage of reliable forecast systems is essential to better prepare the community for the dangers encountered with floods. One of the currently used forecasting systems for eastern Iowa is the Advanced Hydrological Prediction System (AHPS), developed and implemented for seasonal streamflow forecasting at the National Weather Service (NWS) North Central River Forecast Center (NCRFC). AHPS is a seasonal flood risk assessment, based on an ensemble of up to 50 years of forecast scenarios, extending out to 90 days. Different weather input scenarios are used to generate multiple numerical predictions of streamflow, which take into consideration the initial conditions and recent observations. Verification of streamflow forecasts for a region is a complicated process due to form of the forecasts themselves, the large number of forecast products, and the small size of the available forecast record for each case. The main challenge is to provide an effective way to interpret available forecast data sets for Iowa in a meaningful way to the state-wide community. In this study, the forecast quality of long-range flood predictions is studied for the Eastern half of Iowa. NCRFC has 61 forecast segments from 5 forecast groups within Iowa that have a sufficient record of historical observed streamflow for verification (ranging from 30 to 50 years). To improve the forecasts, diagnostic verification measures and their interpretation for ensemble forecast would be presented. The results show that the quality of long-range flood predictions varies from season-to-season, and that correcting forecast biases can significantly improve their skill.

  12. Recent Operational Innovations and Future Developments at the Flood Forecasting Centre

    NASA Astrophysics Data System (ADS)

    Millard, Jon; Pilling, Charlie

    2015-04-01

    The Flood Forecasting Centre (FFC) was established in 2009 to give an overview of flood risk across England and Wales and is a partnership between the UK Met Office, the Environment Agency and Natural Resources Wales. Primarily serving the emergency response community, the FFC aims to provide trusted guidance to help protect lives and livelihoods from flooding across England and Wales from its base at the Met Office in Exeter. The flood forecasts consist of an assessment of the likelihood as well as the expected level of impacts of flood events during the next five days. The FFC provide forecasts for all natural sources of flooding, namely; fluvial, coastal, surface water and groundwater but liaise closely with meteorologists at the Met Office and local flood forecasters at the Environment Agency and Natural Resources Wales. Key challenges include providing; forecasts with longer lead times especially for fluvial and coastal events, forecasts at shorter timescales and with more spatial focus for rapid response catchments and surface water events, and also clear communications of forecast uncertainties. As well as operational activities, the FFC run a significant development and improvement programme and are linked in with Met Office and Environment Agency science projects in order to bring new science into operations to try and meet these challenges and improve performance. Latest developments which are now being applied operationally to provide an enhanced flood warning service will be presented. Examples include; the use of the national hydrological model Grid to Grid (G2G) for both fluvial and surface water flooding, extended surge ensembles for coastal flooding, enhancements in the surface water forecasting tool, and improvements to products communicating these forecasts. An overview of the current projects under development will also be provided, including; improvements to data within G2G, surface water hazard impact modelling, 7 day wave ensemble forecasts, regime analysis for longer lead time coastal flood forecasting and improving products and communications.

  13. Timetable of an operational flood forecasting system

    NASA Astrophysics Data System (ADS)

    Liechti, Katharina; Jaun, Simon; Zappa, Massimiliano

    2010-05-01

    At present a new underground part of Zurich main station is under construction. For this purpose the runoff capacity of river Sihl, which is passing beneath the main station, is reduced by 40%. If a flood is to occur the construction site is evacuated and gates can be opened for full runoff capacity to prevent bigger damages. However, flooding the construction site, even if it is controlled, is coupled with costs and retardation. The evacuation of the construction site at Zurich main station takes about 2 to 4 hours and opening the gates takes another 1 to 2 hours each. In the upper part of the 336 km2 Sihl catchment the Sihl lake, a reservoir lake, is situated. It belongs and is used by the Swiss Railway Company for hydropower production. This lake can act as a retention basin for about 46% of the Sihl catchment. Lowering the lake level to gain retention capacity, and therewith safety, is coupled with direct loss for the Railway Company. To calculate the needed retention volume and the water to be released facing unfavourable weather conditions, forecasts with a minimum lead time of 2 to 3 days are needed. Since the catchment is rather small, this can only be realised by the use of meteorological forecast data. Thus the management of the construction site depends on accurate forecasts to base their decisions on. Therefore an operational hydrological ensemble prediction system (HEPS) was introduced in September 2008 by the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). It delivers daily discharge forecasts with a time horizon of 5 days. The meteorological forecasts are provided by MeteoSwiss and stem from the operational limited-area COSMO-LEPS which downscales the ECMWF ensemble prediction system to a spatial resolution of 7 km. Additional meteorological data for model calibration and initialisation (air temperature, precipitation, water vapour pressure, global radiation, wind speed and sunshine duration) and radar data are also provided by MeteoSwiss. Additional meteorological and hydrological observations are provided by a hydropower company, the Canton of Zurich and the Federal Office for the Environment (FOEN). The hydrological forecasting is calculated by the semi-distributed hydrological model PREVAH (Precipitation-Runoff-EVapotranspiration-HRU-related Model) and is further processed by the hydraulic model FLORIS. Finally the forecasts and alerts along with additional meteorological and hydrological observations and forecasts from collaborating institution are sent to a webserver accessible for decision makers. We will document the setup of our operational flood forecasting system, evaluate its performance and show how the collaboration and communication between science and practice, including all the different interests, works for this particular example.

  14. Interactive Forecasting with the National Weather Service River Forecast System

    NASA Technical Reports Server (NTRS)

    Smith, George F.; Page, Donna

    1993-01-01

    The National Weather Service River Forecast System (NWSRFS) consists of several major hydrometeorologic subcomponents to model the physics of the flow of water through the hydrologic cycle. The entire NWSRFS currently runs in both mainframe and minicomputer environments, using command oriented text input to control the system computations. As computationally powerful and graphically sophisticated scientific workstations became available, the National Weather Service (NWS) recognized that a graphically based, interactive environment would enhance the accuracy and timeliness of NWS river and flood forecasts. Consequently, the operational forecasting portion of the NWSRFS has been ported to run under a UNIX operating system, with X windows as the display environment on a system of networked scientific workstations. In addition, the NWSRFS Interactive Forecast Program was developed to provide a graphical user interface to allow the forecaster to control NWSRFS program flow and to make adjustments to forecasts as necessary. The potential market for water resources forecasting is immense and largely untapped. Any private company able to market the river forecasting technologies currently developed by the NWS Office of Hydrology could provide benefits to many information users and profit from providing these services.

  15. Operational flash flood forecasting platform based on grid technology

    NASA Astrophysics Data System (ADS)

    Thierion, V.; Ayral, P.-A.; Angelini, V.; Sauvagnargues-Lesage, S.; Nativi, S.; Payrastre, O.

    2009-04-01

    Flash flood events of south of France such as the 8th and 9th September 2002 in the Grand Delta territory caused important economic and human damages. Further to this catastrophic hydrological situation, a reform of flood warning services have been initiated (set in 2006). Thus, this political reform has transformed the 52 existing flood warning services (SAC) in 22 flood forecasting services (SPC), in assigning them territories more hydrological consistent and new effective hydrological forecasting mission. Furthermore, national central service (SCHAPI) has been created to ease this transformation and support local services in their new objectives. New functioning requirements have been identified: - SPC and SCHAPI carry the responsibility to clearly disseminate to public organisms, civil protection actors and population, crucial hydrologic information to better anticipate potential dramatic flood event, - a new effective hydrological forecasting mission to these flood forecasting services seems essential particularly for the flash floods phenomenon. Thus, models improvement and optimization was one of the most critical requirements. Initially dedicated to support forecaster in their monitoring mission, thanks to measuring stations and rainfall radar images analysis, hydrological models have to become more efficient in their capacity to anticipate hydrological situation. Understanding natural phenomenon occuring during flash floods mainly leads present hydrological research. Rather than trying to explain such complex processes, the presented research try to manage the well-known need of computational power and data storage capacities of these services. Since few years, Grid technology appears as a technological revolution in high performance computing (HPC) allowing large-scale resource sharing, computational power using and supporting collaboration across networks. Nowadays, EGEE (Enabling Grids for E-science in Europe) project represents the most important effort in term of grid technology development. This paper presents an operational flash flood forecasting platform which have been developed in the framework of CYCLOPS European project providing one of virtual organizations of EGEE project. This platform has been designed to enable multi-simulations processes to ease forecasting operations of several supervised watersheds on Grand Delta (SPC-GD) territory. Grid technology infrastructure, in providing multiple remote computing elements enables the processing of multiple rainfall scenarios, derived to the original meteorological forecasting transmitted by Meteo-France, and their respective hydrological simulations. First results show that from one forecasting scenario, this new presented approach can permit simulations of more than 200 different scenarios to support forecasters in their aforesaid mission and appears as an efficient hydrological decision-making tool. Although, this system seems operational, model validity has to be confirmed. So, further researches are necessary to improve models core to be more efficient in term of hydrological aspects. Finally, this platform could be an efficient tool for developing others modelling aspects as calibration or data assimilation in real time processing.

  16. Support vector regression for real-time flood stage forecasting

    NASA Astrophysics Data System (ADS)

    Yu, Pao-Shan; Chen, Shien-Tsung; Chang, I.-Fan

    2006-09-01

    SummaryFlood forecasting is an important non-structural approach for flood mitigation. The flood stage is chosen as the variable to be forecasted because it is practically useful in flood forecasting. The support vector machine, a novel artificial intelligence-based method developed from statistical learning theory, is adopted herein to establish a real-time stage forecasting model. The lags associated with the input variables are determined by applying the hydrological concept of the time of response, and a two-step grid search method is applied to find the optimal parameters, and thus overcome the difficulties in constructing the learning machine. Two structures of models used to perform multiple-hour-ahead stage forecasts are developed. Validation results from flood events in Lan-Yang River, Taiwan, revealed that the proposed models can effectively predict the flood stage forecasts one-to-six-hours ahead. Moreover, a sensitivity analysis was conducted on the lags associated with the input variables.

  17. A methodology for forecasting carbon dioxide flooding performance 

    E-print Network

    Marroquin Cabrera, Juan Carlos

    1998-01-01

    A methodology was developed for forecasting carbon dioxide (CO2) flooding performance quickly and reliably. The feasibility of carbon dioxide flooding in the Dollarhide Clearfork "AB" Unit was evaluated using the methodology. This technique is very...

  18. Prospects for Season-ahead Global Flood Forecasts

    NASA Astrophysics Data System (ADS)

    Lee, D.; Block, P. J.; Ward, P.

    2014-12-01

    Flood events rank as one of the most destructive natural hazards, with associated global economic losses increasing starkly over the past half century. This has drawn attention to prospects for flood forecasts to protect life and livelihoods. Typical forecasts emphasize the short-term (hours to days) scale to inform immediate response action. Longer-range forecasts, on the order of months to seasons, however, could compliment short-range forecasts by focusing on disaster preparedness. Initially, we define key flood seasons globally, at grid and basin scales, which are most likely to contain the most severe annual flood using observational (GRDC) and model (PCR-GLOBWB) streamflow data over 1958-2000. Model-defined flood seasons strongly agree (89% of time) with flood seasons defined through observations. Model-defined flood seasons were also qualitatively verified with actual flood records over 1985-2008 from the Dartmouth Flood Observatory records. Subsequently we have begun investigating the effects of inter-annual climate variability on seasonal maximum floods, particularly how ENSO and other large-scale phenomena may modulate discharge and flood severity. Skillful relationship have led to preliminary seasonal global flood forecast models, at the basin scale, providing early (season-ahead) flood probabilities, flood extent, and estimated damages.

  19. Impact of rainfall spatial variability on Flash Flood Forecasting

    NASA Astrophysics Data System (ADS)

    Douinot, Audrey; Roux, Hélène; Garambois, Pierre-André; Larnier, Kevin

    2014-05-01

    According to the United States National Hazard Statistics database, flooding and flash flooding have caused the largest number of deaths of any weather-related phenomenon over the last 30 years (Flash Flood Guidance Improvement Team, 2003). Like the storms that cause them, flash floods are very variable and non-linear phenomena in time and space, with the result that understanding and anticipating flash flood genesis is far from straightforward. In the U.S., the Flash Flood Guidance (FFG) estimates the average number of inches of rainfall for given durations required to produce flash flooding in the indicated county. In Europe, flash flood often occurred on small catchments (approximately 100 km2) and it has been shown that the spatial variability of rainfall has a great impact on the catchment response (Le Lay and Saulnier, 2007). Therefore, in this study, based on the Flash flood Guidance method, rainfall spatial variability information is introduced in the threshold estimation. As for FFG, the threshold is the number of millimeters of rainfall required to produce a discharge higher than the discharge corresponding to the first level (yellow) warning of the French flood warning service (SCHAPI: Service Central d'Hydrométéorologie et d'Appui à la Prévision des Inondations). The indexes ?1 and ?2 of Zoccatelli et al. (2010), based on the spatial moments of catchment rainfall, are used to characterize the rainfall spatial distribution. Rainfall spatial variability impacts on warning threshold and on hydrological processes are then studied. The spatially distributed hydrological model MARINE (Roux et al., 2011), dedicated to flash flood prediction is forced with synthetic rainfall patterns of different spatial distributions. This allows the determination of a warning threshold diagram: knowing the spatial distribution of the rainfall forecast and therefore the 2 indexes ?1 and ?2, the threshold value is read on the diagram. A warning threshold diagram is built for each studied catchment. The proposed methodology is applied on three Mediterranean catchments often submitted to flash floods. The new forecasting method as well as the Flash Flood Guidance method (uniform rainfall threshold) are tested on 25 flash floods events that had occurred on those catchments. Results show a significant impact of rainfall spatial variability. Indeed, it appears that the uniform rainfall threshold (FFG threshold) always overestimates the observed rainfall threshold. The difference between the FFG threshold and the proposed threshold ranges from 8% to 30%. The proposed methodology allows the calculation of a threshold more representative of the observed one. However, results strongly depend on the related event duration and on the catchment properties. For instance, the impact of the rainfall spatial variability seems to be correlated with the catchment size. According to these results, it seems to be interesting to introduce information on the catchment properties in the threshold calculation. Flash Flood Guidance Improvement Team, 2003. River Forecast Center (RFC) Development Management Team. Final Report. Office of Hydrologic Development (OHD), Silver Spring, Mary-land. Le Lay, M. and Saulnier, G.-M., 2007. Exploring the signature of climate and landscape spatial variabilities in flash flood events: Case of the 8-9 September 2002 Cévennes-Vivarais catastrophic event. Geophysical Research Letters, 34(L13401), doi:10.1029/2007GL029746. Roux, H., Labat, D., Garambois, P.-A., Maubourguet, M.-M., Chorda, J. and Dartus, D., 2011. A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments. Nat. Hazards Earth Syst. Sci. J1 - NHESS, 11(9), 2567-2582. Zoccatelli, D., Borga, M., Zanon, F., Antonescu, B. and Stancalie, G., 2010. Which rainfall spatial information for flash flood response modelling? A numerical investigation based on data from the Carpathian range, Romania. Journal of Hydrology, 394(1-2), 148-161.

  20. Fuzzy forecast of flood disaster caused by solar proton flares.

    NASA Astrophysics Data System (ADS)

    Han, Zhengzhong; Tang, Yuhua

    1999-01-01

    The flood disaster caused by solar proton flares is forecasted using the theory of fuzzy mathematics. The index system and standards of fuzzy evaluation, as well as the membership function are proposed. A practical software of computer data processing for forecasting flood disaster is given.

  1. 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.

  2. Operational flood forecasting system of Umbria Region "Functional Centre

    NASA Astrophysics Data System (ADS)

    Berni, N.; Pandolfo, C.; Stelluti, M.; Ponziani, F.; Viterbo, A.

    2009-04-01

    The hydrometeorological alert office (called "Decentrate Functional Centre" - CFD) of Umbria Region, in central Italy, is the office that provides technical tools able to support decisions when significant flood/landslide events occur, furnishing 24h support for the whole duration of the emergency period, according to the national directive DPCM 27 February 2004 concerning the "Operating concepts for functional management of national and regional alert system during flooding and landslide events for civil protection activities purposes" that designs, within the Italian Civil Defence Emergency Management System, a network of 21 regional Functional Centres coordinated by a central office at the National Civil Protection Department in Rome. Due to its "linking" role between Civil Protection "real time" activities and environmental/planning "deferred time" ones, the Centre is in charge to acquire and collect both real time and quasi-static data: quantitative data from monitoring networks (hydrometeorological stations, meteo radar, ...), meteorological forecasting models output, Earth Observation data, hydraulic and hydrological simulation models, cartographic and thematic GIS data (vectorial and raster type), planning studies related to flooding areas mapping, dam managing plans during flood events, non instrumental information from direct control of "territorial presidium". A detailed procedure for the management of critical events was planned, also in order to define the different role of various authorities and institutions involved. Tiber River catchment, of which Umbria region represents the main upper-medium portion, includes also regional trans-boundary issues very important to cope with, especially for what concerns large dam behavior and management during heavy rainfall. The alert system is referred to 6 different warning areas in which the territory has been divided into and based on a threshold system of three different increasing critical levels according to the expected ground effects: ordinary, moderate and high. Particularly, hydrometric and rainfall thresholds for both floods and landslides alarms were assessed. Based on these thresholds, at the Umbria Region Functional Centre an automatic phone-call and SMS alert system is operating. For a real time flood forecasting system, at the CFD several hydrological and hydraulic models were developed. Three rainfall-runoff hydrological models, using different quantitative meteorological forecasts, are available: the event based models X-Nash (based on the Nash theory) and Mike-Drift coupled with the hydraulic model Mike-11 (developed by the Danish Hydraulic Institute - DHI); and the physically-based continuous model Mobidic (MOdello di Bilancio Idrologico DIstribuito e Continuo - Distributed and Continuous Model for the Hydrological Balance, developed by the University of Florence in cooperation with the Functional Centre of Tuscany Region). Other two hydrological models, using observed data of the real time hydrometeorological network, were implemented: the first one is the rainfall-runoff hydrological model Hec-Hms coupled with the hydraulic model Hec-Ras (United States Army Corps of Engineers - USACE). Moreover, Hec-Hms, is coupled also with a continuous soil moisture model for a more precise evaluation of the antecedent moisture condition of the basin, which is a key factor for a correct runoff volume evaluation. The second one is the routing hydrological model Stafom (STage FOrecasting Model, developed by the Italian Research Institute for Geo-Hydrological Protection of the National Research Council - IRPI-CNR). This model is an adaptive model for on-line stage forecasting for river branches where significant lateral inflow contributions occur and, up to now, it is implemented for the main Tiber River branch and it allows a forecasting lead time up to 10 hours for the downstream river section. Recently, during the period between December the 4th and the 16th 2008, Umbria region territory was interested

  3. 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.

  4. Flash flood warnings using the ensemble precipitation forecasting technique: A case study on forecasting floods in Taiwan caused by typhoons

    NASA Astrophysics Data System (ADS)

    Yang, Tsun-Hua; Yang, Sheng-Chi; Ho, Jui-Yi; Lin, Gwo-Fong; Hwang, Gong-Do; Lee, Cheng-Shang

    2015-01-01

    A flash flood is an event that develops rapidly. Given early warnings with sufficient lead time, flood forecasting can help people prepare disaster prevention measures. To provide this early warning, a statistics-based flood forecasting model was developed to evaluate the flooding potential in urban areas using ensemble quantitative precipitation forecasts (the Taiwan Cooperative Precipitation Ensemble Forecast Experiment, TAPEX). The proposed model uses different sources of information, such as (i) the designed capacity of storm sewer systems, (ii) a flood inundation potential database, and (iii) historical flooding observations, to evaluate the potential for flash flooding situations to occur. Using 24-, 48- and 72-h ahead precipitation forecasts from the TAPEX, the proposed model can assess the flooding potential with two levels of risk and at the township scale with a 3-day lead time. The proposed model is applied to Pingtung County, which includes 33 townships and is located in southern Taiwan. A dataset of typhoon storms from 2010 to 2014 was used to evaluate the model performance. The accuracy and threat score for testing events are 0.68 and 0.30, respectively, with a lead time of 24 h. The accuracy and threat score for training events are 0.82 and 0.31, respectively, with a lead time of 24 h. The model performance decreases when the lead time is extended. However, the model demonstrates its potential as a valuable reference to improve emergency responses to alleviate the loss of lives and property due to flooding.

  5. Towards operational flood forecasting using Data Assimilation

    NASA Astrophysics Data System (ADS)

    Piacentini, A.; Ricci, S. M.; Le Pape, E.; Habert, J.; Jonville, G.; Goutal, N.; Barthélémy, S.; Morel, T.; Duchaine, F.; Thual, O.

    2012-12-01

    Over the last few years, a collaborative work between CERFACS, LNHE (EDF R&D), SCHAPI and CETMEF resulted in the implementation of a Data Assimilation (DA) method on top of MASCARET, in the framework of real-time forecasting. This prototype named DAMP (Data Assimilation with MASCARET Prototype) showed promising results on the Adour and Marne catchments as it improves the forecast skills of the hydraulic model using water level and discharge in-situ observations (Ricci et al, 2011) as show in Figure 1. In the existing prototype, data assimilation was implemented with the OpenPalm coupler following two different and sequentially applied approaches based on the Kalman Filter algorithm: the correction of the upstream and lateral inflow to the model and the direct correction of the water level and discharge. As of today both technical and research developments on DAMP are on going. The implementation of DAMP for operational use at SCHAPI is on going within the modeling plateform POM (Plateforme Opérationnelle pour la Modélisation) that will provide integrated numerical models for the major French catchments. The DAMP will also benefits from numerical developments by LNHE on MASCARET that was recently instrumented with interface commands (API) and formulated as an IRF module (Initialize-Run-Finalize). These solutions allow to minimize the interlocking of the DA algorithm and MASCARET sources codes. In addition, the Palm-Parasol functionality in Open-Palm is now used to efficiently spawn an ensemble of MASCARET integrations used to formulate the DA algorithm. Along with these technical aspects, the DA algorithm is also being improved. Sensitivity study carried out: the control vector should be extended, especially to include the Strickler coefficients. An ensemble based DA algorithm (EnKF) is also currently being implemented to improve the modelling of the background error covariance matrix used to distribute the correction to the water level and discharge states when observations are assimilated from observation points to the entire state. Building on the existing prototype and by methodological and theoretical advances, the operational use of the DAMP offers great perspective for the use of DA for flood forecasting with direct application at the French SPC (Service de Prévision des Crues).

  6. NOAA Graphical Flood Severity Inundation Mapping: Enhancing River Forecasts with Geographic Information Systems (GIS)

    NASA Astrophysics Data System (ADS)

    Marcy, D.; Donaldson, T.

    2006-12-01

    The National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) provides flood forecast information in a variety of formats, including graphical hydrographs and text products. Beginning in 2002, the NOAA Coastal Services Center (CSC) and NWS have worked in partnership to develop geographic information systems (GIS) based graphical flood severity inundation products. GIS techniques are used along with the best available topographic data and flood surface profiles generated from hydraulic models to develop inundation maps of the areal extent of NWS flood categories (minor, moderate, major), along with a range of water surface elevations at selected vertical intervals. The resulting inundation map products are called NWS flood severity inundation map libraries and will become a part of the suite of new products being disseminated via the Advanced Hydrologic Prediction Service (AHPS) program. In 2006, the CSC through the contractor, Watershed Concepts, developed a methodologies and standards document and map template for new graphical flood severity products. This report, titled "Methods and Standards for National Weather Service Flood Severity Inundation Maps" will serve as the basis and guide for creating new flood severity inundation map libraries at specific NWS river forecast points. This paper will describe 1.) the history and components of these inundation maps products, 2.) the process for developing flood severity inundation maps using these methods and standards, 3.) the connection of these products to the FEMA map modernization program, 4.) and delivery of these products via the web.

  7. Study of Beijiang catchment flash-flood forecasting model

    NASA Astrophysics Data System (ADS)

    Chen, Y.; Li, J.; Huang, S.; Dong, Y.

    2015-05-01

    Beijiang catchment is a small catchment in southern China locating in the centre of the storm areas of the Pearl River Basin. Flash flooding in Beijiang catchment is a frequently observed disaster that caused direct damages to human beings and their properties. Flood forecasting is the most effective method for mitigating flash floods, the goal of this paper is to develop the flash flood forecasting model for Beijiang catchment. The catchment property data, including DEM, land cover types and soil types, which will be used for model construction and parameter determination, are downloaded from the website freely. Based on the Liuxihe Model, a physically based distributed hydrological model, a model for flash flood forecasting of Beijiang catchment is set up. The model derives the model parameters from the terrain properties, and further optimized with the observed flooding process, which improves the model performance. The model is validated with a few observed floods occurred in recent years, and the results show that the model is reliable and is promising for flash flood forecasting.

  8. SOM-based Hybrid Neural Network Model for Flood Inundation Extent Forecasting

    NASA Astrophysics Data System (ADS)

    Chang, Li-Chiu; Shen, Hung-Yu; Chang, Fi-John

    2014-05-01

    In recent years, the increasing frequency and severity of floods caused by climate change and/or land overuse has been reported both nationally and globally. Therefore, estimation of flood depths and extents may provide disaster information for alleviating risk and loss of life and property. The conventional inundation models commonly need a huge amount of computational time to carry out a high resolution spatial inundation map. Moreover, for implementing appropriate mitigation strategies of various flood conditions, different flood scenarios and the corresponding mitigation alternatives are required. Consequently, it is difficult to reach real-time forecast of the inundation extent by conventional inundation models. This study proposed a SOM-RNARX model, for on-line forecasting regional flood inundation depths and extents. The SOM-RNARX model is composed of SOM (Self-Organizing Map) and RNARX (recurrent configuration of nonlinear autoregressive with exogenous inputs). The SOM network categorizes various flood inundation maps of the study area to produce a meaningful regional flood topological map. The RNARX model is built to forecast the total flooded volume of the study area. To find the neuron with the closest total inundated volume to the forecasted total inundated volumes, the forecasted value is used to adjust the weights (inundated depths) of the closest neuron and obtain a regional flood inundation map. The proposed methodology was trained and tested based on a large number of inundation data generated by a well validated two-dimensional simulation model in Yilan County, Taiwan. For comparison, the CHIM (clustering-based hybrid inundation model) model which was issued by Chang et al. (2010) was performed. The major difference between these two models is that CHIM classify flooding characteristics, and SOM-RNARX extracts the relationship between rainfall pattern and flooding spatial distribution. The results show that (1)two models can adequately provide on-line forecasts of 3-h-ahead flood inundation depths in the study area; and (2)SOM-RNARX consistently outperform CHIM in online multistep-ahead inundation forecasts, while SOM-RNARX needs more storage for model parameters than CHIM and increases the loading of database as well.

  9. Integrated Flood Forecast and Virtual Dam Operation System for Water Resources and Flood Risk Management

    NASA Astrophysics Data System (ADS)

    Shibuo, Yoshihiro; Ikoma, Eiji; Lawford, Peter; Oyanagi, Misa; Kanauchi, Shizu; Koudelova, Petra; Kitsuregawa, Masaru; Koike, Toshio

    2014-05-01

    While availability of hydrological- and hydrometeorological data shows growing tendency and advanced modeling techniques are emerging, such newly available data and advanced models may not always be applied in the field of decision-making. In this study we present an integrated system of ensemble streamflow forecast (ESP) and virtual dam simulator, which is designed to support river and dam manager's decision making. The system consists of three main functions: real time hydrological model, ESP model, and dam simulator model. In the real time model, the system simulates current condition of river basins, such as soil moisture and river discharges, using LSM coupled distributed hydrological model. The ESP model takes initial condition from the real time model's output and generates ESP, based on numerical weather prediction. The dam simulator model provides virtual dam operation and users can experience impact of dam control on remaining reservoir volume and downstream flood under the anticipated flood forecast. Thus the river and dam managers shall be able to evaluate benefit of priori dam release and flood risk reduction at the same time, on real time basis. Furthermore the system has been developed under the concept of data and models integration, and it is coupled with Data Integration and Analysis System (DIAS) - a Japanese national project for integrating and analyzing massive amount of observational and model data. Therefore it has advantage in direct use of miscellaneous data from point/radar-derived observation, numerical weather prediction output, to satellite imagery stored in data archive. Output of the system is accessible over the web interface, making information available with relative ease, e.g. from ordinary PC to mobile devices. We have been applying the system to the Upper Tone region, located northwest from Tokyo metropolitan area, and we show application example of the system in recent flood events caused by typhoons.

  10. High resolution distributed hydrological modeling for river flood forecasting

    NASA Astrophysics Data System (ADS)

    Chen, Y.

    2014-12-01

    High resolution distributed hydrological model can finely describe the river basin hydrological processes, thus having the potential to improve the flood forecasting capabilities, and is regarded as the next generation flood forecast model. But there are great challenges in deploying it in real-time river flood forecasting, such as the awesome computation resources requirement, parameter determination, high resolution precipitation assimilation and uncertainty controls. Liuxihe Model is a physically-based distributed hydrological model proposed mainly for catchment flood forecasting, which is a process-based hydrological model. In this study, based on Liuxihe Model, a parallel computation algorithm for Liuxihe model flood forecasting is proposed, and a cloudy computation system is developed on a high performance computer, this largely improves the applicability of Liuxihe Model in large river. Without the parallel computation, the Liuxihe Model is computationally incapable in application to rivers with drainage area bigger than 10,000km2 at the grid size of 100m. With the parallel computation, the Liuxihe Model is used in a river with a drainage area of 60,000km2, and could be expended indefinitely. Based on this achievement, a model parameter calibration method by using Particle Swale Optimization is proposed and tested in several rivers in southern China with drainage areas ranging from several hundreds to tens thousands km2, and with the model parameter optimization, the model performance has been approved largely. The modeling approach is also tested for coupling radar-based precipitation estimation/prediction for small catchment flash forecasting and for coupling quantitative precipitation estimation/prediction from meteorological model for large river flood forecasting.

  11. Dynamic Critical Rainfall-Based Flash Flood Early Warning and Forecasting for Medium-Small Rivers

    NASA Astrophysics Data System (ADS)

    Liu, Z.; Yang, D.; Hu, J.

    2012-04-01

    China is extremely frequent food disasters hit countries, annual flood season flash floods triggered by rainfall, mudslides, landslides have caused heavy casualties and property losses, not only serious threaten the lives of the masses, but the majority of seriously restricting the mountain hill areas of economic and social development and the people become rich, of building a moderately prosperous society goals. In the next few years, China will focus on prevention and control area in the flash flood disasters initially built "for the surveillance, communications, forecasting, early warning and other non-engineering measure based, non-engineering measures and the combinations of engineering measures," the mitigation system. The latest progresses on global torrential flood early warning and forecasting techniques are reviewed in this paper, and then an early warning and forecasting approach is proposed on the basis of a distributed hydrological model according to dynamic critical rainfall index. This approach has been applied in Suichuanjiang River basin in Jiangxi province, which is expected to provide valuable reference for building a national flash flood early warning and forecasting system as well as control of such flooding.

  12. Looking at the big scale - Global Flood Forecasting

    NASA Astrophysics Data System (ADS)

    Burek, P.; Alfieri, L.; Thielen-del Pozo, J.; Muraro, D.; Pappenberger, F.; Krzeminsk, B.

    2012-04-01

    Reacting to the increasing need for better preparedness to worldwide hydrological extremes, the Joint Research Centre has joined forces with the European Centre for Medium-Range Weather Forecast (ECMWF), to couple state-of-the art weather forecasts with a hydrological model on global scale. On a pre-operationally basis a fully hydro-meteorological flood forecasting model is running since July 2011 and producing daily probabilistic discharge forecast with worldwide coverage and forecast horizon of about 1 month. An important aspect of this global system is that it is set-up on continental scale and therefore independent of administrative and political boundaries - providing downstream countries with information on upstream river conditions as well as continental and global overviews. The prototype of a Global Flood Alert System consists of HTESSEL land surface scheme coupled with LISFLOOD hydrodynamic model for the flow routing in the river network. Both hydrological models are set up on global coverage with horizontal grid resolution of 0.1° and daily time step for input and output data. To estimate corresponding discharge warning thresholds for selected return periods, the coupled HTESSEL-LISFLOOD hydrological model is driven with ERA-Interim input meteorological data for a 21 year period from 1989 onward. For daily forecasts the ensemble stream flow predictions are run by feeding Variable Resolution Ensemble Prediction System (VarEPS) weather forecasts into the coupled model. VarEPS consist of 51-member ensemble global forecasts for 15 days. The hydrological simulations are computed for a 45-day time horizon, to account the routing of flood waves through large river basins with time of concentration of the order of one month. Both results, the discharge thresholds from the long term run and the multiple hydrographs of the daily ensemble stream flow prediction are joined together to produce probabilistic information of critical threshold exceedance. Probabilistic discharge forecasts are compared with three warning threshold maps. Results are displayed through a password protected web-portal where the members can browse in an easy and intuitive way different aspects of the most recent or past forecasts as spatially distributed information. Critical points in the river channels showing an increased probability of flooding over various forecasts are linked to time series of flood threshold exceedances in order to provide more detailed information. Although the system is still in its infancy and requires further research and development, rigorous testing and adaptations, it has already demonstrated its potential in recent catastrophic floods. The severe floods in Pakistan in July-August 2010 were clearly detected by the system as a major flood event. Recent examples are the floods in the South-Eastern Asia (mainly Thailand, Cambodia and Vietnam) in September-October 2011. For the lower Mekong River, probabilistic forecasts from the global simulations on 18th September 2011 showed a probability higher than 40% of exceeding the high alert level from 2nd to 4th October, hence 14 days in advance. Regarding the devastating monsoon flooding in Thailand, the peak flow of the Chao Phraya River was forecast since mid of September 2011, about 10-15 days before the actual peak occurred and the major losses took place.

  13. A first large-scale flood inundation forecasting model

    NASA Astrophysics Data System (ADS)

    Schumann, G. J.-P.; Neal, J. C.; Voisin, N.; Andreadis, K. M.; Pappenberger, F.; Phanthuwongpakdee, N.; Hall, A. C.; Bates, P. D.

    2013-10-01

    At present continental to global scale flood forecasting predicts at a point discharge, with little attention to detail and accuracy of local scale inundation predictions. Yet, inundation variables are of interest and all flood impacts are inherently local in nature. This paper proposes a large-scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas. The model was built for the Lower Zambezi River to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. ECMWF ensemble forecast (ENS) data were used to force the VIC (Variable Infiltration Capacity) hydrologic model, which simulated and routed daily flows to the input boundary locations of a 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of channels that play a key role in flood wave propagation. We therefore employed a novel subgrid channel scheme to describe the river network in detail while representing the floodplain at an appropriate scale. The modeling system was calibrated using channel water levels from satellite laser altimetry and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of between one and two model resolutions compared to an observed flood edge and inundation area agreement was on average 86%. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2.

  14. Impact of precipitation forecast uncertainties and initial soil moisture conditions on a probabilistic flood forecasting chain

    NASA Astrophysics Data System (ADS)

    Silvestro, Francesco; Rebora, Nicola

    2014-11-01

    One of the main difficulties that flood forecasters are faced with is evaluating how errors and uncertainties in forecasted precipitation propagate into streamflow forecast. These errors, must be combined with the effects of different initial soil moisture conditions that generally have a significant impact on the final results of a flood forecast. This is further complicated by the fact that a probabilistic approach is needed, especially when small and medium size basins are considered (the variability of the streamflow scenarios is in fact strongly influenced by the aforementioned factors). Moreover, the ensemble size is a degree of freedom when a precipitation downscaling algorithm is part of the forecast chain. In fact, a change of ensemble size could lead to different final results once the other inputs and parameters are fixed. In this work, a series of synthetic experiments have been designed and implemented to test an operational probabilistic flood forecast system in order to augment the knowledge of how streamflow forecasts can be affected by errors and uncertainties associated with the three aforementioned elements: forecasted rainfall, soil moisture initial conditions, and ensemble size.

  15. An Operational Flood Forecast System for the Indus Valley

    NASA Astrophysics Data System (ADS)

    Shrestha, K.; Webster, P. J.

    2012-12-01

    The Indus River is central to agriculture, hydroelectric power, and the potable water supply in Pakistan. The ever-present risk of drought - leading to poor soil conditions, conservative dam practices, and higher flood risk - amplifies the consequences of abnormally large precipitation events during the monsoon season. Preparation for the 2010 and 2011 floods could have been improved by coupling quantitative precipitation forecasts to a distributed hydrological model. The nature of slow-rise discharge on the Indus and overtopping of riverbanks in this basin indicate that medium-range (1-10 day) probabilistic weather forecasts can be used to assess flood risk at critical points in the basin. We describe a process for transforming these probabilities into an alert system for supporting flood mitigation and response decisions on a daily basis. We present a fully automated two-dimensional flood forecast methodology based on meteorological variables from the European Centre for Medium-Range Weather Forecasts (ECMWF) Variable Ensemble Prediction System (VarEPS). Energy and water fluxes are calculated in 25km grid cells using macroscale hydrologic parameterizations from the UW Variable Infiltration Capacity (VIC) model. A linear routing model transports grid cell surface runoff and baseflow within each grid cell to the outlet and into the stream network. The overflow points are estimated using flow directions, flow velocities, and maximum discharge thresholds from each grid cell. Flood waves are then deconvolved from the in-channel discharge time series and propagated into adjacent cells until a storage criterion based on average grid cell elevation is met. Floodwaters are drained back into channels as a continuous process, thus simulating spatial extent, depth, and persistence on the plains as the ensemble forecast evolves with time.

  16. 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.

  17. Hydrologic Ensemble Forecasts for Flash Flood Warnings at Ungauged Locations

    NASA Astrophysics Data System (ADS)

    Demargne, Julie; Javelle, Pierre; Organde, Didier; Ramos, Maria-Helena

    2013-04-01

    Development of operational flash flood warning systems is one of the challenges in operational hydrology: flash floods are devastating but difficult to monitor and predict due to their nature. To provide flash flood warnings for ungauged basins, Météo-France and Irstea (formally Cemagref) have developed a discharge-threshold flood warning system called AIGA, which combines radar-gauge rainfall grids with a simplified distributed rainfall-runoff model run every 15 minutes at a 1-km² resolution. Operational since 2005 in the Southern part of France, the AIGA system produces, every 15 minutes, a map of the river network with a color chart indicating the range of the estimated return period of the ongoing flood event. To increase forecast lead time and quantify the forcing input uncertainty, the rainfall-runoff distributed model ingests the 11 precipitation ensemble members from the PEARP ensemble prediction system of Météo-France. Performance of the experimental probabilistic precipitation and flow forecasts is evaluated from a variety of ensemble verification metrics (e.g., Continuous Ranked Probability Skill Score, Relative Operating Characteristic score) for different French basins. We also discuss planned enhancements and challenges to assess other sources of hydrologic uncertainty and effectively communicate the uncertainty information to forecasters for better risk-based decision making.

  18. 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.

  19. California climate change, hydrologic response, and flood forecasting

    SciTech Connect

    Miller, Norman L.

    2003-11-11

    There is strong evidence that the lower atmosphere has been warming at an unprecedented rate during the last 50 years, and it is expected to further increase at least for the next 100 years. Warmer air mass implies a higher capacity to hold water vapor and an increased likelihood of an acceleration of the global water cycle. This acceleration is not validated and considerable new research has gone into understanding aspects of the water cycle (e.g. Miller et al. 2003). Several significant findings on the hydrologic response to climate change can be reported. It is well understood that the observed and expected warming is related to sea level rise. In a recent seminar at Lawrence Berkeley National Laboratory, James Hansen (Director of the Institute for Space Studies, National Aeronautics and Space Administration) stressed that a 1.25 Wm{sup -2} increase in radiative forcing will lead to an increase in the near surface air temperature by 1 C. This small increase in temperature from 2000 levels is enough to cause very significant impacts to coasts. Maury Roos (Chief Hydrologist, California Department of Water Resources) has shown that a 0.3 m rise in sea level shifts the San Francisco Bay 100-year storm surge flood event to a 10-year event. Related coastal protection costs for California based on sea level rise are shown. In addition to rising sea level, snowmelt-related streamflow represents a particular problem in California. Model studies have indicated that there will be approximately a 50% decrease in snow pack by 2100. This potential deficit must be fully recognized and plans need to be put in place well in advance. In addition, the warmer atmosphere can hold more water vapor and result in more intense warm winter-time precipitation events that result in flooding. During anticipated high flow, reservoirs need to release water to maintain their structural integrity. California is at risk of water shortages, floods, and related ecosystem stresses. More research needs to be done to further improve our ability to forecast weather events at longer time scales. Seasonal predictions have been statistical and only recently have studies begun to use ensemble simulations and historical observations to constrain such predictions. Understanding the mechanisms of large-scale atmospheric dynamics and its local impacts remain topics of intensive research. The ability to predict extreme events and provide policy makers with this information, along with climate change and hydrologic response information, will help to guide planning to form a more resilient infrastructure in the future.

  20. Model Combination and Weighting Methods in Operational Flood Forecasting

    NASA Astrophysics Data System (ADS)

    Bogner, Konrad; Pappenberger, Florian; Cloke, Hannah L.

    2013-04-01

    In order to get maximum benefits from operational forecast systems based on different model approaches, it is necessary to find an optimal way to combine the forecasts in real-time and to derive the predictive probability distribution by assigning different weights to the different actual forecasts according to the forecast performance of the previous days. In the European Flood Alert System (EFAS) a Bayesian Forecast System has been implemented in order to derive the overall predictive probability distribution. The EFAS is driven by different numerical weather prediction systems like the deterministic forecasts from the German Weather Service and from the ECMWF, as well as Ensemble Prediction Systems from the ECMWS and COSMO-LEPS. In this study the effect of combining these different forecast systems in respect of the total predictive uncertainty are investigated by applying different weighting methods like the Non-homogenous Gaussian Regression (NGR) model, the Bayesian Model Averaging (BMA) and an empirical method. Besides that different methods of bias removal are applied, namely additive and regression based ones, and the applicability in operational forecast is tested. One of the problems identified is the difficulty in optimizing the weight parameters for each lead-time separately resulting in highly inconsistent forecasts, especially for regression based bias removal methods. Therefore in operational use methods with only sub-optimal skill score results, could be preferable showing more realistic shapes of uncertainty bands for the predicted future stream-flow values. Another possible approach could be the optimization of the weighting parameters not for each lead-time separately, but to look at different levels of aggregations over expanding windows of time ranges. First results indicate the importance of the proper choice of the model combination method in view of reliability and sharpness of the forecast system.

  1. A first large-scale flood inundation forecasting model

    SciTech Connect

    Schumann, Guy J-P; Neal, Jeffrey C.; Voisin, Nathalie; Andreadis, Konstantinos M.; Pappenberger, Florian; Phanthuwongpakdee, Kay; Hall, Amanda C.; Bates, Paul D.

    2013-11-04

    At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domain has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode revealed that it is crucial to account for basin-wide hydrological response time when assessing lead time performances notwithstanding structural limitations in the hydrological model and possibly large inaccuracies in precipitation data.

  2. Discharge assimilation in a distributed flood forecasting model

    NASA Astrophysics Data System (ADS)

    Rabuffetti, D.

    2006-07-01

    In the field of operational flood forecasting, uncertainties linked to hydrological forecast are often crucial. In this work, data assimilation techniques are employed to improve hydrological variable estimates coming from numerical simulations using all the available real-time water level measurements. The proposed assimilation scheme, a classical Kalman filter extension to non-linear systems, is applied in a rainfall-runoff distributed model based on the SCS-CN approach. The complex hydrological system of the Toce river basin is studied, a mountainous catchment of about 1500 km2 in the Italian alps, through the development of a prototype available for operational use. For the considered flood event, the assimilation scheme is stable, even when available observations show gaps or outliers. It allows significant improvements in the simulation results, in particular when the focus is addressed to the peak.

  3. Flood forecasting model based on geographical information system

    NASA Astrophysics Data System (ADS)

    Dong, A.; Zhi-Jia, L.; Yong-Tuo, W.; Cheng, Y.; Yi-Heng, D.

    2015-05-01

    In this paper, the Antecedent Precipitation Index Model (API) combined with Nash's Instantaneous Unit Curve Method is adopted for flood forecasting. The parameters n and k of Nash's Method is obtained by setting up the mathematic relation between these two parameters and topographic characteristics. Based on the DEM information, ArcGIS software is used to get the topographic characteristics and the topographic parameters. The Tunxi basin in the humid region was taken as an example for analysis. Through comparison with the simulation results of the Xinanjiang model, the detailed analysis of our simulation results is carried out giving a Nash-Sutcliffe efficiency 0.80 for the combined model and 0.94 for the Xinanjiang model. This indicates that the combined model as well as the Xinanjiang Model has a good performance in the simulation process. The combined model has great potential as a new efficient approach for flood forecasting in similar basins.

  4. National Severe Storms Forecast Center

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The principal mission of the National Severe Storms Forecast Center (NSSFC) is to maintain a continuous watch of weather developments that are capable of producing severe local storms, including tornadoes, and to prepare and issue messages designated as either Weather Outlooks or Tornado or Severe Thunderstorm Watches for dissemination to the public and aviation services. In addition to its assigned responsibility at the national level, the NSSFC is involved in a number of programs at the regional and local levels. Subsequent subsections and paragraphs describe the NSSFC, its users, inputs, outputs, interfaces, capabilities, workload, problem areas, and future plans in more detail.

  5. Real-time Flood Forecasting in China Using TOPKAPI

    NASA Astrophysics Data System (ADS)

    Todini, E.; Mazzetti, C.

    2012-04-01

    The early development of real time flood forecasting in China can be dated at the beginning of the '80s of last century. It was at that time that a group of researchers, lead by Prof. Wang Juemou, set up a quasi real-time system at the Ministry of Water Resources, based on a 6 hour collection of data dispatched to Bei Jing via telegraph from all parts of China. Forecasts were then available for the major rivers, such as the Yellow River, the Yangtze River, the Huai He River and the Pearl River. Models were based on the Xinan Jiang model developed by Prof. Zhao and on the S-CLS, namely the combination of the Xinan Jiang model with the CLS, developed by Todini. Later on, other models were also introduced, such as the Sacramento model on the Yellow River on behalf of the Yellow River Conservancy Commission, the Arno model on the Fuchun River, within the frame of a EU funded project and the Mike 11 model on the Yangtze. More recently the distributed hydrological model TOPKAPI, developed at the University of Bologna, was introduced in China as part of the renewal and upgrade of the real time flood forecasting systems in the of Sanmenxia to Huayuankou reach of the Yellow River as well as on the Fuchun River from the outlet of the Xinan Jiang reservoir to Hangzhou. The paper will describe the new real-time flood forecasting systems and their extended performances in the light of the historical development that has taken place during more than 30 years in China,

  6. Flash flood forecasting using simplified hydrological models, radar rainfall forecasts and data assimilation

    NASA Astrophysics Data System (ADS)

    Smith, P. J.; Beven, K.; Panziera, L.

    2012-04-01

    The issuing of timely flood alerts may be dependant upon the ability to predict future values of water level or discharge at locations where observations are available. Catchments at risk of flash flooding often have a rapid natural response time, typically less then the forecast lead time desired for issuing alerts. This work focuses on the provision of short-range (up to 6 hours lead time) predictions of discharge in small catchments based on utilising radar forecasts to drive a hydrological model. An example analysis based upon the Verzasca catchment (Ticino, Switzerland) is presented. Parsimonious time series models with a mechanistic interpretation (so called Data-Based Mechanistic model) have been shown to provide reliable accurate forecasts in many hydrological situations. In this study such a model is developed to predict the discharge at an observed location from observed precipitation data. The model is shown to capture the snow melt response at this site. Observed discharge data is assimilated to improve the forecasts, of up to two hours lead time, that can be generated from observed precipitation. To generate forecasts with greater lead time ensemble precipitation forecasts are utilised. In this study the Nowcasting ORographic precipitation in the Alps (NORA) product outlined in more detail elsewhere (Panziera et al. Q. J. R. Meteorol. Soc. 2011; DOI:10.1002/qj.878) is utilised. NORA precipitation forecasts are derived from historical analogues based on the radar field and upper atmospheric conditions. As such, they avoid the need to explicitly model the evolution of the rainfall field through for example Lagrangian diffusion. The uncertainty in the forecasts is represented by characterisation of the joint distribution of the observed discharge, the discharge forecast using the (in operational conditions unknown) future observed precipitation and that forecast utilising the NORA ensembles. Constructing the joint distribution in this way allows the full historic record of data at the site to inform the predictive distribution. It is shown that, in part due to the limited availability of forecasts, the uncertainty in the relationship between the NORA based forecasts and other variates dominated the resulting predictive uncertainty.

  7. Performance assessment of a Bayesian Forecasting System (BFS) for real-time flood forecasting

    NASA Astrophysics Data System (ADS)

    Biondi, D.; De Luca, D. L.

    2013-02-01

    SummaryThe paper evaluates, for a number of flood events, the performance of a Bayesian Forecasting System (BFS), with the aim of evaluating total uncertainty in real-time flood forecasting. The predictive uncertainty of future streamflow is estimated through the Bayesian integration of two separate processors. The former evaluates the propagation of input uncertainty on simulated river discharge, the latter computes the hydrological uncertainty of actual river discharge associated with all other possible sources of error. A stochastic model and a distributed rainfall-runoff model were assumed, respectively, for rainfall and hydrological response simulations. A case study was carried out for a small basin in the Calabria region (southern Italy). The performance assessment of the BFS was performed with adequate verification tools suited for probabilistic forecasts of continuous variables such as streamflow. Graphical tools and scalar metrics were used to evaluate several attributes of the forecast quality of the entire time-varying predictive distributions: calibration, sharpness, accuracy, and continuous ranked probability score (CRPS). Besides the overall system, which incorporates both sources of uncertainty, other hypotheses resulting from the BFS properties were examined, corresponding to (i) a perfect hydrological model; (ii) a non-informative rainfall forecast for predicting streamflow; and (iii) a perfect input forecast. The results emphasize the importance of using different diagnostic approaches to perform comprehensive analyses of predictive distributions, to arrive at a multifaceted view of the attributes of the prediction. For the case study, the selected criteria revealed the interaction of the different sources of error, in particular the crucial role of the hydrological uncertainty processor when compensating, at the cost of wider forecast intervals, for the unreliable and biased predictive distribution resulting from the Precipitation Uncertainty Processor.

  8. Application of hydrological models for flood forecasting and flood control in India and Bangladesh

    NASA Astrophysics Data System (ADS)

    Refsgaard, J. C.; Havnø, K.; Ammentorp, H. C.; Verwey, A.

    A general mathematical modelling system for real-time flood forecasting and flood control planning is described. The system comprises a lumped conceptual rainfall-runoff model, a hydrodynamic model for river routing, reservoir and flood plain simulation, an updating procedure for real-time operation and a comprehensive data management system. The system is presently applied for real-time forecasting of the two 20 000 km 2 (Yamuna and Damodar) catchments in India as well as for flood control modelling at the same two catchments in India. In another project the system is being established for the entire Bangladesh with a coarse discretization and for the South East Region of Bangladesh with a fine model discretization. The objectives of the modelling application in Bangladesh are to enable predictions of the effects of alternative river regulation structures in terms of changes in water levels, inundations, siltration and salinity. The modelling system has been transferred to the Central Water Commission of India and the Master Plan Organization of Bangladesh in connection with comprehensive training programmes. The models are presently being operated by Indian and Bangladeshi engineers in the two countries.

  9. Forecasting of Storm Surge Floods Using ADCIRC and Optimized DEMs

    NASA Technical Reports Server (NTRS)

    Valenti, Elizabeth; Fitzpatrick, Patrick

    2005-01-01

    Increasing the accuracy of storm surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite element based codes. It affords a capability for simulating tidal circulation and storm surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate.

  10. The strategy of building a flood forecast model by neuro-fuzzy network

    NASA Astrophysics Data System (ADS)

    Chen, Shen-Hsien; Lin, Yong-Huang; Chang, Li-Chiu; Chang, Fi-John

    2006-04-01

    A methodology is proposed for constructing a flood forecast model using the adaptive neuro-fuzzy inference system (ANFIS). This is based on a self-organizing rule-base generator, a feedforward network, and fuzzy control arithmetic. Given the rainfall-runoff patterns, ANFIS could systematically and effectively construct flood forecast models. The precipitation and flow data sets of the Choshui River in central Taiwan are analysed to identify the useful input variables and then the forecasting model can be self-constructed through ANFIS. The analysis results suggest that the persistent effect and upstream flow information are the key effects for modelling the flood forecast, and the watershed's average rainfall provides further information and enhances the accuracy of the model performance. For the purpose of comparison, the commonly used back-propagation neural network (BPNN) is also examined. The forecast results demonstrate that ANFIS is superior to the BPNN, and ANFIS can effectively and reliably construct an accurate flood forecast model.

  11. A Simple Flood Forecasting Scheme Using Wireless Sensor Networks

    E-print Network

    Seal, Victor; Maity, Shovan; Mitra, Souvik Kr; Mukherjee, Amitava; Naskar, Mrinal Kanti

    2012-01-01

    This paper presents a forecasting model designed using WSNs (Wireless Sensor Networks) to predict flood in rivers using simple and fast calculations to provide real-time results and save the lives of people who may be affected by the flood. Our prediction model uses multiple variable robust linear regression which is easy to understand and simple and cost effective in implementation, is speed efficient, but has low resource utilization and yet provides real time predictions with reliable accuracy, thus having features which are desirable in any real world algorithm. Our prediction model is independent of the number of parameters, i.e. any number of parameters may be added or removed based on the on-site requirements. When the water level rises, we represent it using a polynomial whose nature is used to determine if the water level may exceed the flood line in the near future. We compare our work with a contemporary algorithm to demonstrate our improvements over it. Then we present our simulation results for t...

  12. Flood quantiles in a changing climate: Seasonal forecasts and causal relations

    E-print Network

    Arumugam, Sankar

    Flood quantiles in a changing climate: Seasonal forecasts and causal relations A maximum floods at a given location may change over time in response to interannual and longer climate fluctuations, we compare two approaches for the estimation of flood quantiles conditional on selected ``climate

  13. An analytical framework for flood water conservation considering forecast uncertainty and acceptable risk

    NASA Astrophysics Data System (ADS)

    Ding, Wei; Zhang, Chi; Peng, Yong; Zeng, Ruijie; Zhou, Huicheng; Cai, Ximing

    2015-06-01

    This paper addresses how much flood water can be conserved for use after the flood season through the operation of reservoir by taking into account the residual flood control capacity (the difference between flood conveyance capacity and the expected inflow in a lead time). A two-stage model for dynamic control of the flood-limited water level (the maximum allowed water level during the flood season, DC-FLWL) is established considering forecast uncertainty and acceptable flood risk. It is found that DC-FLWL is applicable when the reservoir inflow ranges from small to medium levels of the historical records, while both forecast uncertainty and acceptable risk in the downstream affect the feasible space of DC-FLWL. As forecast uncertainty increases (under a given risk level) or as acceptable risk level decreases (under a given forecast uncertainty level), the minimum required safety margin for flood control increases, and the chance for DC-FLWL decreases. The derived hedging rules from the modeling framework illustrate either the dominant role of water conservation or flood control or the trade-off between the two objectives under different levels of forecast uncertainty and acceptable risk. These rules may provide useful guidelines for conserving water from flood, especially in the area with heavy water stress. The analysis is illustrated via a case study with a real-world reservoir in northeastern China.

  14. 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.

  15. Semi-distributed flood forecasting system for the Middle Vistula reach

    NASA Astrophysics Data System (ADS)

    Romanowicz, Renata; Karamuz, Emilia; Osuch, Marzena

    2014-05-01

    The aim of this study is the development of an integrated forecasting system for the middle reach of the River Vistula. The system consists of combined in series lumped parameter Stochastic Transfer Function models. In order to prolong the forecast lead-time, the system was extended to include gauging stations situated upstream of Zawichost. There is a number of tributaries located along the studied reach. The largest are Kamienna, Pilica and Wieprz. Therefore apart from Single- Input -Single-Output models (SISO), multiple input models were also developed (MISO). The system is based on water levels instead of flows, in order to avoid errors related to rating curve transformation. The problem of the nonlinear transformation of system inputs in order to separate the nonlinearity of the flow process to obtain the linear model dynamics is equally important for the accuracy of forecasts. The possibility of linearizing the flow routing process was investigated using a State Dependent Parameter approach. The nonparametric relationship was parameterised using a power function. This procedure allowed the application of a model with a nonlinear transformation of input in the forecasting mode. It is important to note that the applied methods are stochastic in nature and the structure of the models and their parameters are estimated from available observations, taking into account inherent observation and model approximation errors. As a result, forecasts are estimated together with uncertainty bands. We apply a Kalman filter updating of model predictions as a data assimilation procedure. The procedure involves formulating the forecasting problem in a state space form. Validation of the developed forecasting system shows that the quality of forecasts obtained using a semi-distributed lumped parameter model is comparable with the forecasts obtained using a distributed model with the advantage of obtaining forecast uncertainty by the former. This work was supported by the project "Stochastic flood forecasting system (The River Vistula reach from Zawichost to Warsaw)" carried by the Institute of Geophysics, Polish Academy of Sciences on the order of the National Science Centre (contract No. 2011/01/B/ST10/06866). The water level data were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

  16. 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.

  17. A Distributed Hydrologic Model, HL-RDHM, for Flash Flood Forecasting in Hawaiian Watersheds

    NASA Astrophysics Data System (ADS)

    Fares, A.; Awal, R.; Michaud, J.; Chu, P.; Fares, S.; Kevin, K.; Rosener, M.

    2012-12-01

    Hawai'i's watersheds are flash flood prone due to their small contributing areas, and frequent intense spatially variable precipitation. Accurate simulation of the hydrology of these watersheds should incorporate spatial variability of at least the major input data, e.g., precipitation. The goal of this study is to evaluate the performance of the U.S. National Weather Service Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM) in flash flood forecasting at Hanalei watershed, Kauai, Hawai'i. Some of the major limitations of using HL-RDHM in Hawaii are: i) Hawaii lies outside the Hydrologic Rainfall Analysis Project (HRAP) coordinate system of the continental US (CONUS), unavailability of a priori SAC-SMA parameter grids, and absence of hourly multi-sensor NEXRAD based precipitation grids. The specific objectives of this study were to i) run HL-RDHM outside CONUS domain, and ii) evaluate the performance of HL-RDHM for flash flood forecasting in the flood prone Hanalei watershed, Kauai, Hawai'i. We i) modified HRAP coordinate system; ii) generated input data of precipitation grids at different resolutions using data from 20 precipitation gauges five of which were within Hanalei watershed; iii) and generated SAC-SMA and routing parameter grids for the modified HRAP coordinate system. The one HRAP resolution grid (4 km x 4 km) was not accurate; thus, the basin averaged annual hourly precipitation of 1 HRAP grid is comparatively lower than that of ½ and ¼ HRAP grids. The performance of HL-RDHM using basin averaged a priori grids and distributed a priori grids was reasonable even using non-optimized a priori parameter values for 2008 data. HL-RDHM reasonably matched the observed streamflow magnitudes of peaks and time to peak during the calibration and validation periods. Overall, HL-RDHM performance is "good" to "very good" if we use input data of finer resolution grids (½ HRAP or ¼ HRAP) and precipitation grids interpolated from sufficient data of rain gauges. Results of this study show the potential of using HL-RDHM for flood forecasting in Hawaii; however, there are still some necessary modifications of HL-RDHM that should be implemented to make it more user friendly. There is also a need to produce HRAP quantitative precipitation estimates (QPEs) grids for Hawaii. The size and coordinate system of quantitative precipitation forecasts (QPFs) grids for Hawaii are different from those for the CONUS; hence, further work should focus on generating QPE grids and incorporating QPF grids in HL-RDHM model.

  18. 24 CFR 570.605 - National Flood Insurance Program.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ...2013-04-01 true National Flood Insurance Program. ...570.605 National Flood Insurance Program. ...grantee's consolidated plan, in accordance with 24...section 202(a) of the Flood Disaster Protection Act of...

  19. 24 CFR 570.605 - National Flood Insurance Program.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ...2010-04-01 false National Flood Insurance Program. ...570.605 National Flood Insurance Program. ...grantee's consolidated plan, in accordance with 24...section 202(a) of the Flood Disaster Protection Act of...

  20. 24 CFR 570.605 - National Flood Insurance Program.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ...2013-04-01 false National Flood Insurance Program. ...570.605 National Flood Insurance Program. ...grantee's consolidated plan, in accordance with 24...section 202(a) of the Flood Disaster Protection Act of...

  1. 24 CFR 570.605 - National Flood Insurance Program.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ...2012-04-01 false National Flood Insurance Program. ...570.605 National Flood Insurance Program. ...grantee's consolidated plan, in accordance with 24...section 202(a) of the Flood Disaster Protection Act of...

  2. 24 CFR 570.605 - National Flood Insurance Program.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ...2010-04-01 true National Flood Insurance Program. ...570.605 National Flood Insurance Program. ...grantee's consolidated plan, in accordance with 24...section 202(a) of the Flood Disaster Protection Act of...

  3. 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.

  4. Application Study of Empirical Model and Xiaohuajian Flood Forecasting Model in the Middle Yellow River

    NASA Astrophysics Data System (ADS)

    Hu, Caihong

    2013-04-01

    Xiaolandi-Huayuankou region is an important rainstorm centre in the middle Yellow river, which drainage area of 35883km2. A set of forecasting methods applied in this region was formed throughout years of practice. The Xiaohuajian flood forecasting model and empirical model were introduced in this paper. The simulated processes of the Xiaohuajian flood forecasting model include evapotranspiration, infiltration, runoff, river flow. Infiltration and surface runoff are calculated utilizing the Horton model for infiltration into multilayered soil profiles. Overland flow is routed by Nash instantaneous unit hydrograph and Section Muskingum method. The empirical model are simulated using P~Pa~R and empirical relation approach for runoff generation and concentration. The structures of these two models were analyzed and compared in detail. Yihe river basin located in Xiaolandi-Huayuankou region was selected for the purpose of the study. The results show that the accuracy of the two methods are similar, however, the accuracy of Xiaohuajian flood forecasting model for flood forecasting is relatively higher, especially the process of the flood; the accuracy of the empirical methods is much worse, but it can also be accept. The two models are both practicable, so the two models can be combined to apply. The result of the Xiaohuajian flood forecasting model can be used to guide the reservoir for flood control, and the result of empirical methods can be as a reference.

  5. Accounting for Uncertainties in Generating Reliable Probabilistic Flood Forecasts for Bangladesh

    NASA Astrophysics Data System (ADS)

    Hopson, T. M.; Webster, P. J.

    2007-12-01

    The country of Bangladesh experiences life-threatening floods in the basins of the Ganges and Brahmaputra rivers flowing through the country with tragic regularity. These floods result in loss of life on a scale that often greatly eclipses the deaths due to natural disasters in developed countries. Flooding in these basins can occur on weekly time scales (as occurred during the severe Brahmaputra floods of 2004 and of this year) to seasonal time scales (as occurred during the disastrous floods of 1998). Beginning in 2003, the Climate Forecasting Applications for Bangladesh (CFAB) project began issuing operational probabilistic flood forecasts to the country of Bangladesh over a wide-range of time scales to provide advanced warning of severe flood-stage discharges in the catchments of the Ganges and Brahmaputra basins. In this paper we discuss the uncertainty estimator module to our 1- to 10-day in-advance automated real-time operational multi-model flood forecast scheme for the upper basins of the Ganges and Brahmaputra rivers. These forecasts are based on an application of the European Centre for Medium-Range Weather Forecasts (ECMWF) 51-member ensemble weather forecasts, near-real-time GPCP and CMORPH satellite and NOAA CPC rain gauge precipitation estimates, and near-real- time discharge estimates from the Bangladesh Flood Forecasting and Warning Centre. The uncertainty estimator module estimates multi-model hydrologic error utilizing daily-updated hindcasts, which are separate from the forecasted weather variable uncertainty. Such a separation of error sources is done to maximize the sharpness of the final forecast probability distribution function (PDF), as well as to enhance the utility of the ensemble spread as an indicator of ensemble skill; for this latter feature of ensemble forecasts, we also present a new measure to test the spread-skill utility. In the final step of the uncertainty module, we merge these two sources of uncertainty together while at the same time providing an additional forecast error correction. This last step utilizes a relatively- unused statistical tool that ensures reliability in the PDF while ensuring skill no worse than a climatological forecast or persistence.

  6. Understanding uncertainty in distributed flash flood forecasting for semiarid regions 1909

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Semi-arid flash floods pose a significant danger for life and property in the US. One effective way to mitigate flood risk is by implementing a rainfall-runoff model in a real-time forecast and warning system. This study used a physically based, distributed semi-arid rainfall-runoff model driven by ...

  7. Implementing the national AIGA flash flood warning system in France

    NASA Astrophysics Data System (ADS)

    Organde, Didier; Javelle, Pierre; Demargne, Julie; Arnaud, Patrick; Caseri, Angelica; Fine, Jean-Alain; de Saint Aubin, Céline

    2015-04-01

    The French national hydro-meteorological and flood forecasting centre (SCHAPI) aims to implement a national flash flood warning system to improve flood alerts for small-to-medium (up to 1000 km2) ungauged basins. This system is based on the AIGA method, co-developed by IRSTEA these last 10 years. The method, initially set up for the Mediterranean area, is based on a simple event-based hourly hydrologic distributed model run every 15 minutes (Javelle et al. 2014). The hydrologic model ingests operational radar-gauge rainfall grids from Météo-France at a 1-km² resolution to produce discharges for successive outlets along the river network. Discharges are then compared to regionalized flood quantiles of given return periods and warnings (expressed as the range of the return period estimated in real-time) are provided on a river network map. The main interest of the method is to provide forecasters and emergency services with a synthetic view in real time of the ongoing flood situation, information that is especially critical in ungauged flood prone areas. In its enhanced national version, the hourly event-based distributed model is coupled to a continuous daily rainfall-runoff model which provides baseflow and a soil moisture index (for each 1-km² pixel) at the beginning of the hourly simulation. The rainfall-runoff models were calibrated on a selection of 700 French hydrometric stations with Météo-France radar-gauge reanalysis dataset for the 2002-2006 period. To estimate model parameters for ungauged basins, the 2 hydrologic models were regionalised by testing both regressions (using different catchment attributes, such as catchment area, soil type, and climate characteristic) and spatial proximity techniques (transposing parameters from neighbouring donor catchments), as well as different homogeneous hydrological areas. The most valuable regionalisation method was determined for each model through jack-knife cross-validation. The system performance was then evaluated with contingency criteria (e.g., Critical Success Index, Probability Of Detection, Success Ratio) using operational rainfall radar-gauge products from Météo-France for the 2009-2012 period. The regionalised parameters of the distributed model were finally adjusted for each homogeneous hydrological area to optimize the Heidke skill score (HSS) calculated with three levels of warnings (2-, 10- and 50-year flood quantiles). This work is currently being implemented by the SCHAPI to set up an automated national flash flood warning system by 2016. Planned improvements include developing a unique continuous model to be run at a sub-hourly timestep, discharge assimilation, as well as integrating precipitation forecasts while accounting for the main sources of forecast uncertainty. Javelle, P., Demargne, J., Defrance, D., and Arnaud, P. 2014. Evaluating flash flood warnings at ungauged locations using post-event surveys: a case study with the AIGA warning system. Hydrological Sciences Journal, DOI: 10.1080/02626667.2014.923970

  8. Using subseasonal-to-seasonal (S2S) extreme rainfall forecasts for extended-range flood prediction in Australia

    NASA Astrophysics Data System (ADS)

    White, C. J.; Franks, S. W.; McEvoy, D.

    2015-06-01

    Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S) forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR) activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

  9. 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.

  10. 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.

  11. National Weather Service Forecast Reference Evapotranspiration

    NASA Astrophysics Data System (ADS)

    Osborne, H. D.; Palmer, C. K.; Krone-Davis, P.; Melton, F. S.; Hobbins, M.

    2013-12-01

    The National Weather Service (NWS), Weather Forecasting Offices (WFOs) are producing daily reference evapotranspiration (ETrc) forecasts or FRET across the Western Region and in other selected locations since 2009, using the Penman - Monteith Reference Evapotranspiration equation for a short canopy (12 cm grasses), adopted by the Environmental Water Resources Institute of the American Society of Civil Engineers (ASCE-EWRI, 2004). The sensitivity of these daily calculations to fluctuations in temperatures, humidity, winds, and sky cover allows forecasters with knowledge of local terrain and weather patterns to better forecast in the ETrc inputs. The daily FRET product then evolved into a suite of products, including a weekly ETrc forecast for better water planning and a tabular point forecast for easy ingest into local water management-models. The ETrc forecast product suite allows water managers, the agricultural community, and the public to make more informed water-use decisions. These products permit operational planning, especially with the impending drought across much of the West. For example, the California Department of Water Resources not only ingests the FRET into their soil moisture models, but uses the FRET calculations when determining the reservoir releases in the Sacramento and American Rivers. We will also focus on the expansion of FRET verification, which compares the daily FRET to the observations of ETo from the California Irrigation Management Information System (CIMIS) across California's Central Valley for the 2012 water year.

  12. National Flood Risk Management Planning Center of Expertise

    E-print Network

    US Army Corps of Engineers

    National Flood Risk Management Planning Center of Expertise The Flood Risk Management Planning Center of Expertise (FRM-PCX) was established and Reallocation, Hydropower, and Flood Risk Management. The FRM-PCX is a virtual

  13. Evaluation of radar-based precipitation estimates for flash flood forecasting in the Three Gorges Region

    NASA Astrophysics Data System (ADS)

    Li, Z.; Yang, D.; Hong, Y.; Qi, Y.; Cao, Q.

    2015-05-01

    Spatial rainfall pattern plays a critical role in determining hydrological responses in mountainous areas, especially for natural disasters such as flash floods. In this study, to improve the skills of flood forecasting in the mountainous Three Gorges Region (TGR) of the Yangtze River, we developed a first version of a high-resolution (1 km) radar-based quantitative precipitation estimation (QPE) consideration of many critical procedures, such as beam blockage analysis, ground-clutter filter, rain type identification and adaptive Z-R relations. A physically-based distributed hydrological model (GBHM) was established and further applied to evaluate the performance of radar-based QPE for regional flood forecasting, relative to the gauge-driven simulations. With two sets of input data (gauge and radar) collected during summer 2010, the applicability of the current radar-based QPE to rainstorm monitoring and flash flood forecasting in the TGR is quantitatively analysed and discussed.

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

  15. An operational real-time flood forecasting system in Southern Italy

    NASA Astrophysics Data System (ADS)

    Ortiz, Enrique; Coccia, Gabriele; Todini, Ezio

    2015-04-01

    A real-time flood forecasting system has been operating since year 2012 as a non-structural measure for mitigating the flood risk in Campania Region (Southern Italy), within the Sele river basin (3.240 km2). The Sele Flood Forecasting System (SFFS) has been built within the FEWS (Flood Early Warning System) platform developed by Deltares and it assimilates the numerical weather predictions of the COSMO LAM family: the deterministic COSMO-LAMI I2, the deterministic COSMO-LAMI I7 and the ensemble numerical weather predictions COSMO-LEPS (16 members). Sele FFS is composed by a cascade of three main models. The first model is a fully continuous physically based distributed hydrological model, named TOPKAPI-eXtended (Idrologia&Ambiente s.r.l., Naples, Italy), simulating the dominant processes controlling the soil water dynamics, runoff generation and discharge with a spatial resolution of 250 m. The second module is a set of Neural-Networks (ANN) built for forecasting the river stages at a set of monitored cross-sections. The third component is a Model Conditional Processor (MCP), which provides the predictive uncertainty (i.e., the probability of occurrence of a future flood event) within the framework of a multi-temporal forecast, according to the most recent advancements on this topic (Coccia and Todini, HESS, 2011). The MCP provides information about the probability of exceedance of a maximum river stage within the forecast lead time, by means of a discrete time function representing the variation of cumulative probability of exceeding a river stage during the forecast lead time and the distribution of the time occurrence of the flood peak, starting from one or more model forecasts. This work shows the Sele FFS performance after two years of operation, evidencing the added-values that can provide to a flood early warning and emergency management system.

  16. Forecasting skills of the ensemble hydro-meteorological system for the Po river floods

    NASA Astrophysics Data System (ADS)

    Ricciardi, Giuseppe; Montani, Andrea; Paccagnella, Tiziana; Pecora, Silvano; Tonelli, Fabrizio

    2013-04-01

    The Po basin is the largest and most economically important river-basin in Italy. Extreme hydrological events, including floods, flash floods and droughts, are expected to become more severe in the next future due to climate change, and related ground effects are linked both with environmental and social resilience. A Warning Operational Center (WOC) for hydrological event management was created in Emilia Romagna region. In the last years, the WOC faced challenges in legislation, organization, technology and economics, achieving improvements in forecasting skill and information dissemination. Since 2005, an operational forecasting and modelling system for flood modelling and forecasting has been implemented, aimed at supporting and coordinating flood control and emergency management on the whole Po basin. This system, referred to as FEWSPo, has also taken care of environmental aspects of flood forecast. The FEWSPo system has reached a very high level of complexity, due to the combination of three different hydrological-hydraulic chains (HEC-HMS/RAS - MIKE11 NAM/HD, Topkapi/Sobek), with several meteorological inputs (forecasted - COSMOI2, COSMOI7, COSMO-LEPS among others - and observed). In this hydrological and meteorological ensemble the management of the relative predictive uncertainties, which have to be established and communicated to decision makers, is a debated scientific and social challenge. Real time activities face professional, modelling and technological aspects but are also strongly interrelated with organization and human aspects. The authors will report a case study using the operational flood forecast hydro-meteorological ensemble, provided by the MIKE11 chain fed by COSMO_LEPS EQPF. The basic aim of the proposed approach is to analyse limits and opportunities of the long term forecast (with a lead time ranging from 3 to 5 days), for the implementation of low cost actions, also looking for a well informed decision making and the improvement of flood preparedness and crisis management for basins greater than 1.000 km2.

  17. General characteristics of causes of urban flood damage and flood forecasting/warning system in Seoul, Korea Young-Il Moon1, 2, Jong-Suk Kim1, 2 1 Department of Civil Engineering, University of Seoul, Seoul 130-743, South Korea 2 Urban Flood Research Inst

    NASA Astrophysics Data System (ADS)

    Moon, Young-Il; Kim, Jong-Suk

    2015-04-01

    Due to rapid urbanization and climate change, the frequency of concentrated heavy rainfall has increased, causing urban floods that result in casualties and property damage. As a consequence of natural disasters that occur annually, the cost of damage in Korea is estimated to be over two billion US dollars per year. As interest in natural disasters increase, demands for a safe national territory and efficient emergency plans are on the rise. In addition to this, as a part of the measures to cope with the increase of inland flood damage, it is necessary to build a systematic city flood prevention system that uses technology to quantify flood risk as well as flood forecast based on both rivers and inland water bodies. Despite the investment and efforts to prevent landside flood damage, research and studies of landside-river combined hydro-system is at its initial stage in Korea. Therefore, the purpose of this research introduces the causes of flood damage in Seoul and shows a flood forecasting and warning system in urban streams of Seoul. This urban flood forecasting and warning system conducts prediction on flash rain or short-term rainfall by using radar and satellite information and performs prompt and accurate prediction on the inland flooded area and also supports synthetic decision-making for prevention through real-time monitoring. Although we cannot prevent damage from typhoons or localized heavy rain, we can minimize that damage with accurate and timely forecast and a prevention system. To this end, we developed a flood forecasting and warning system, so in case of an emergency there is enough time for evacuation and disaster control. Keywords: urban flooding, flood risk, inland-river system, Korea Acknowledgments This research was supported by a grant (13AWMP-B066744-01) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport of Korean government.

  18. Computer technology forecasting at the National Laboratories

    SciTech Connect

    Peskin, A M

    1980-01-01

    The DOE Office of ADP Management organized a group of scientists and computer professionals, mostly from their own national laboratories, to prepare an annually updated technology forecast to accompany the Department's five-year ADP Plan. The activities of the task force were originally reported in an informal presentation made at the ACM Conference in 1978. This presentation represents an update of that report. It also deals with the process of applying the results obtained at a particular computing center, Brookhaven National Laboratory. Computer technology forecasting is a difficult and hazardous endeavor, but it can reap considerable advantage. The forecast performed on an industry-wide basis can be applied to the particular needs of a given installation, and thus give installation managers considerable guidance in planning. A beneficial side effect of this process is that it forces installation managers, who might otherwise tend to preoccupy themselves with immediate problems, to focus on longer term goals and means to their ends. (RWR)

  19. The Hurricane-Flood-Landslide Continuum: Forecasting Hurricane Effects at Landfall

    NASA Technical Reports Server (NTRS)

    Negri, A.; Golden, J. H.; Updike, R.

    2004-01-01

    Hurricanes, typhoons, and cyclones strike Central American, Caribbean, Southeast Asian and Pacific Island nations even more frequently than the U.S. The global losses of life and property from the floods, landslides and debris flows caused by cyclonic storms are staggering. One of the keys to reducing these losses, both in the U.S. and internationally, is to have better forecasts of what is about to happen from several hours to days before the event. Particularly in developing nations where science, technology and communication are limited, advance-warning systems can have great impact. In developing countries, warnings of even a few hours or days can mitigate or reduce catastrophic losses of life. With the foregoing needs in mind, we propose an initial project of three years total duration that will aim to develop and transfer a warning system for a prototype region in the Central Caribbean, specifically the islands of Puerto Rico and Hispanola. The Hurricane-Flood-Landslide Continuum will include satellite observations to track and nowcast dangerous levels of precipitation, atmospheric and hydrological models to predict near-future runoff, and streamflow changes in affected regions, and landslide models to warn when and where landslides and debris flows are imminent. Since surface communications are likely to be interrupted during these crises, the project also includes the capability to communicate disaster information via satellite to vital government officials in Puerto Rico, Haiti, and Dominican Republic.

  20. Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization

    NASA Astrophysics Data System (ADS)

    Chen, Y.; Li, J.; Xu, H.

    2015-10-01

    Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for Liuxihe model parameter optimization effectively, and could improve the model capability largely in catchment flood forecasting, thus proven that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for Liuxihe model catchment flood forcasting is 20 and 30, respectively.

  1. 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.

  2. Initial assessment of a multi-model approach to spring flood forecasting in Sweden

    NASA Astrophysics Data System (ADS)

    Olsson, J.; Uvo, C. B.; Foster, K.; Yang, W.

    2015-06-01

    Hydropower is a major energy source in Sweden and proper reservoir management prior to the spring flood onset is crucial for optimal production. This requires useful forecasts of the accumulated discharge in the spring flood period (i.e. the spring-flood volume, SFV). Today's SFV forecasts are generated using a model-based climatological ensemble approach, where time series of precipitation and temperature from historical years are used to force a calibrated and initialised set-up of the HBV model. In this study, a number of new approaches to spring flood forecasting, that reflect the latest developments with respect to analysis and modelling on seasonal time scales, are presented and evaluated. Three main approaches, represented by specific methods, are evaluated in SFV hindcasts for three main Swedish rivers over a 10-year period with lead times between 0 and 4 months. In the first approach, historically analogue years with respect to the climate in the period preceding the spring flood are identified and used to compose a reduced ensemble. In the second, seasonal meteorological ensemble forecasts are used to drive the HBV model over the spring flood period. In the third approach, statistical relationships between SFV and the large-sale atmospheric circulation are used to build forecast models. None of the new approaches consistently outperform the climatological ensemble approach, but for specific locations and lead times improvements of 20-30 % are found. When combining all forecasts in a weighted multi-model approach, a mean improvement over all locations and lead times of nearly 10 % was indicated. This demonstrates the potential of the approach and further development and optimisation into an operational system is ongoing.

  3. USGS Measures Historic Flooding Across the Nation

    USGS Multimedia Gallery

    USGS scientists Chris Rowden, Larry Buschmann and Bob Holmes were on the Mississippi River at St. Louis taking streamflow measurements on New Years Eve. This information is critical to the National Weather Service, the U.S. Army Corps of Engineers and emergency managers in making flood predictions a...

  4. USGS Measures Historic Flooding Across the Nation

    USGS Multimedia Gallery

    USGS scientists Chris Rowden, Larry Buschmann and Bob Holmes were on the Mississippi River at St. Louis taking streamflow measurements on New Years Eve. This information is critical to the National Weather Service, the U.S. Army Corps of Engineers and emergency managers in making flood predictio...

  5. Decision-relevant early-warning thresholds for ensemble flood forecasting systems

    NASA Astrophysics Data System (ADS)

    Stephens, Liz; Pappenberger, Florian; Cloke, Hannah; Alfieri, Lorenzo

    2014-05-01

    Over and under warning of potential future floods is problematic for decision-making, and could ultimately lead to trust being lost in the forecasts. The use of ensemble flood forecasting systems for early warning therefore requires a consideration of how to determine and implement decision-relevant thresholds for flood magnitude and probability. This study uses a year's worth of hindcasts from the Global Flood Awareness System (GloFAS) to explore the sensitivity of the warning system to the choice of threshold. We use a number of different methods for choosing these thresholds, building on current approaches that use model climatologies to determine the critical flow magnitudes, to those that can provide 'first guesses' of potential impacts (through integration with global-scale inundation mapping), as well as methods that could incorporate resource limitations.

  6. Use of Precipitation Data Derived from Satellite Data for Hydrologic Modeling: Flood Forecasting and Snowpack Monitoring

    NASA Astrophysics Data System (ADS)

    Artan, G. A.; Shrestha, M.; Tokar, S.; Rowland, J.; Verdin, J. P.; Amer, S.

    2012-12-01

    Floods are the most common and widespread climate-related hazards throughout the globe. Most human losses due to floods occur in the tropical regions of Africa, Asia, and Central America. The use of flood forecasting can reduce the death toll associated with floods. Recent research suggests that the frequency and severity of extreme rainfall events will increase; therefore, there is an urgent need for timely flood forecasting. In those tropical regions, a paucity of the ground-based precipitation data collection networks and the lack of data sharing across international borders for trans-boundary basins have made it impractical to use traditional flood forecasting that relies on station-measured precipitation data. Precipitation estimated from satellite data offers an effective means for calculating areal precipitation estimates in sparsely gauged regions. Because of the apparent uncertainty associated with satellite-based precipitation estimates, the use of such data in hydrologic modeling has been limited in the past. We will present results from our research on the utility of precipitation estimates from satellite data for flood forecasting and snowpack monitoring purposes. We found that remotely sensed precipitation data in combination with distributed hydrologic models can play an important role in early warning and monitoring of floods. For large basins the results of hydrologic models forced with satellite-based precipitation were comparable those the stream flow simulated stream using precipitation measured with ground-based networks. Snowpack simulated with precipitation estimates from satellite data underestimated the snow water content compared with snow water recorded by the SNOTEL network or simulated by SNODAS system; nevertheless, the estimates were found to be useful in mapping the snowpack.

  7. A channel dynamics model for real-time flood forecasting

    USGS Publications Warehouse

    Hoos, A.B.; Koussis, A.D.; Beale, G.O.

    1989-01-01

    A new channel dynamics scheme ASPIRE (alternative system predictor in real time), designed specifically for real-time river flow forecasting, is introduced to reduce uncertainty in the forecast. ASPIRE is a storage routing model that limits the influence of catchment model forecast errors to the downstream station closest to the catchment. Comparisons with the Muskingum routing scheme in field tests suggest that the ASPIRE scheme can provide more accurate forecasts, probably because discharge observations are used to a maximum advantage and routing reaches (and model errors in each reach) are uncoupled. Using ASPIRE in conjunction with the Kalman filter did not improve forecast accuracy relative to a deterministic updating procedure. Theoretical analysis suggests that this is due to a large process noise to measurement noise ratio. -Authors

  8. Hourly runoff forecasting for flood risk management: Application of various computational intelligence models

    NASA Astrophysics Data System (ADS)

    Badrzadeh, Honey; Sarukkalige, Ranjan; Jayawardena, A. W.

    2015-10-01

    Reliable river flow forecasts play a key role in flood risk mitigation. Among different approaches of river flow forecasting, data driven approaches have become increasingly popular in recent years due to their minimum information requirements and ability to simulate nonlinear and non-stationary characteristics of hydrological processes. In this study, attempts are made to apply four different types of data driven approaches, namely traditional artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), wavelet neural networks (WNN), and, hybrid ANFIS with multi resolution analysis using wavelets (WNF). Developed models applied for real time flood forecasting at Casino station on Richmond River, Australia which is highly prone to flooding. Hourly rainfall and runoff data were used to drive the models which have been used for forecasting with 1, 6, 12, 24, 36 and 48 h lead-time. The performance of models further improved by adding an upstream river flow data (Wiangaree station), as another effective input. All models perform satisfactorily up to 12 h lead-time. However, the hybrid wavelet-based models significantly outperforming the ANFIS and ANN models in the longer lead-time forecasting. The results confirm the robustness of the proposed structure of the hybrid models for real time runoff forecasting in the study area.

  9. Serbian Torrent Flood Defense Practice - Modeling, observation, forecasting and impact

    NASA Astrophysics Data System (ADS)

    Gavrilovic, Zoran; Stefnovic, Milutin

    2010-05-01

    Many areas in Europe have been affected by an increasing number of severe flood events in the past few years. Because of these floods numerous measures to improve the organization of disaster management have been taken. This includes the preparation of specific alarm plans for flood disaster events. Serbian Torrent Flood Defense methodology, combines observation by radar meteorology, torrential hydrology and new GIS techniques to enable quick determination and assessment of the detected situation in order to provide a sufficient time for the flood defense system to be put in operation. Alarm plans can be seen as one corner stone of disaster management but their practical use can still be optimized. For this end aims to support the risk analysis and risk communication process by improving the availability, reliability and communicability of hazard maps and alarm plans. The main focus will be on levels of population protection and critical infrastructure protection in respect to natural hazards. Paper presents Obtained results in the field of torrent defense in Serbia. Key words: Hydrology, Torrent Flood Analysis, Meteorology, Flood Defense

  10. Satellite-supported flood forecasting in river networks: A real case study

    NASA Astrophysics Data System (ADS)

    García-Pintado, Javier; Mason, David C.; Dance, Sarah L.; Cloke, Hannah L.; Neal, Jeff C.; Freer, Jim; Bates, Paul D.

    2015-04-01

    Satellite-based (e.g., Synthetic Aperture Radar [SAR]) water level observations (WLOs) of the floodplain can be sequentially assimilated into a hydrodynamic model to decrease forecast uncertainty. This has the potential to keep the forecast on track, so providing an Earth Observation (EO) based flood forecast system. However, the operational applicability of such a system for floods developed over river networks requires further testing. One of the promising techniques for assimilation in this field is the family of ensemble Kalman (EnKF) filters. These filters use a limited-size ensemble representation of the forecast error covariance matrix. This representation tends to develop spurious correlations as the forecast-assimilation cycle proceeds, which is a further complication for dealing with floods in either urban areas or river junctions in rural environments. Here we evaluate the assimilation of WLOs obtained from a sequence of real SAR overpasses (the X-band COSMO-Skymed constellation) in a case study. We show that a direct application of a global Ensemble Transform Kalman Filter (ETKF) suffers from filter divergence caused by spurious correlations. However, a spatially-based filter localization provides a substantial moderation in the development of the forecast error covariance matrix, directly improving the forecast and also making it possible to further benefit from a simultaneous online inflow error estimation and correction. Additionally, we propose and evaluate a novel along-network metric for filter localization, which is physically-meaningful for the flood over a network problem. Using this metric, we further evaluate the simultaneous estimation of channel friction and spatially-variable channel bathymetry, for which the filter seems able to converge simultaneously to sensible values. Results also indicate that friction is a second order effect in flood inundation models applied to gradually varied flow in large rivers. The study is not conclusive regarding whether in an operational situation the simultaneous estimation of friction and bathymetry helps the current forecast. Overall, the results indicate the feasibility of stand-alone EO-based operational flood forecasting.

  11. Clustering-based hybrid inundation model for forecasting flood inundation depths

    NASA Astrophysics Data System (ADS)

    Chang, Li-Chiu; Shen, Hung-Yu; Wang, Yi-Fung; Huang, Jing-Yu; Lin, Yen-Tso

    2010-05-01

    SummaryEstimation of flood depths and extents may provide disaster information for dealing with contingency and alleviating risk and loss of life and property. We present a two-stage procedure underlying CHIM (clustering-based hybrid inundation model), which is composed of linear regression models and ANNs (artificial neural networks) to build the regional flood inundation forecasting model. The two-stage procedure mainly includes data preprocessing and model building stages. In the data preprocessing stage, K-means clustering is used to categorize the data points of the different flooding characteristics in the study area and to identify the control point(s) from individual flooding cluster(s). In the model building stage, three classes of flood depth forecasting models are built in each cluster: the back-propagation neural network (BPNN) for each control point, the linear regression models for the grids that have highly linear correlation with the control point, and a multi-grid BPNN for the grids that do not have highly linear correlation with the control point. The practicability and effectiveness of the proposed approach is tested in the Dacun Township, Changhua County in Central Taiwan. The results show that the proposed CHIM can continuously and adequately provide 1-h-ahead flood inundation maps that well match the simulation flood inundation results and very effectively reduce 99% CPU time.

  12. Fuzzy modelling of basin saturation state and neural networks for flood forecasting

    E-print Network

    Corani, Giorgio

    and rainfalls, without providing a description of the saturation state of the basin, which in contrast plays. A different neural predictor is specialized to mimick the rainfall-runoff relationship which pertains to each networks. Keywords: feedforward neural networks, fuzzy sets, flood forecasting 1 INTRODUCTION An efficient

  13. On noise specification in data assimilation schemes for improved flood forecasting using distributed hydrological models

    NASA Astrophysics Data System (ADS)

    Noh, S.; Rakovec, O.; Weerts, A.; Tachikawa, Y.

    2013-12-01

    While important advances have been achieved in flood forecasting, due to various uncertainties that originate from simulation models, observations, and forcing data, they are still insufficient to obtain accurate prediction results with the required lead times. To increase the certainty of the hydrological forecast, data assimilation (DA) may be utilized to consider or propagate all of these sources of uncertainty through the hydrological modelling chain embedded in a flood forecasting system. Although numerous sophisticated DA algorithms have been proposed to mitigate uncertainty, DA methods dealing with the correction of model inputs, states, and initial conditions are conducted in a rather empirical and subjective way, which may reduce credibility and transparency to operational forecasts. In this study, we investigate the effect of noise specification on the quality of hydrological forecasts via an advanced DA procedure using a distributed hydrological model driven by numerical weather predictions. The sequential DA procedure is based on (1) a multivariate rainfall ensemble generator, which provides spatial and temporal correlation error structures of input forcing and (2) lagged particle filtering to update past and current state variables simultaneously in a lag-time window to consider the response times of internal hydrologic processes. The strength of the proposed procedure is that it requires less subjectivity to implement DA compared to conventional methods using consistent and objectively-induced error models. The procedure is evaluated for streamflow forecasting of three flood events in two Japanese medium-sized catchments. The rainfall ensembles are derived from ground based rain gauge observations for the analysis step and numerical weather predictions for the forecast step. Sensitivity analysis is performed to assess the impacts of uncertainties coming from DA such as random walk state noise and different DA methods with/without objectively-induced rainfall uncertainty conditions. The results show that multivariate rainfall ensembles provide sound input perturbations and model states updated by lagged particle filtering produce improved streamflow forecasts in conjunction with fine-resolution numerical weather predictions.

  14. High-resolution simulation and forecasting of Jeddah floods using WRF version 3.5

    NASA Astrophysics Data System (ADS)

    Deng, L.; McCabe, M. F.; Stenchikov, G. L.; Evans, J. P.; Kucera, P. A.

    2013-12-01

    Modeling flash flood events in arid environments is a difficult but important task that has impacts on both water resource related issues and also emergency management and response. The challenge is often related to adequately describing the precursor intense rainfall events that cause these flood responses, as they are generally poorly simulated and forecast. Jeddah, the second largest city in the Kingdom of Saudi Arabia, has suffered from a number of flash floods over the last decade, following short-intense rainfall events. The research presented here focuses on examining four historic Jeddah flash floods (Nov. 25-26 2009, Dec. 29-30 2010, Jan. 14-15 2011 and Jan. 25-26 2011) and investigates the feasibility of using numerical weather prediction models to achieve a more realistic simulation of these flood-producing rainfall events. The Weather Research and Forecasting (WRF) model (version 3.5) is used to simulate precipitation and meteorological conditions via a high-resolution inner domain (1-km) around Jeddah. A range of different convective closure and microphysics parameterization, together with high-resolution (4-km) sea surface temperature data are employed. Through examining comparisons between the WRF model output and in-situ, radar and satellite data, the characteristics and mechanism producing the extreme rainfall events are discussed and the capacity of the WRF model to accurately forecast these rainstorms is evaluated.

  15. 18 CFR 801.8 - Flood plain management and protection.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ...standards for flood plain management. (4) Promote the use of flood insurance by helping localities qualify for the national program. (5) Assist in the development of a modern flood forecasting and warning...

  16. The flood event of 10-12 November 2013 on the Tiber River basin (central Italy): real-time flood forecasting with uncertainty supporting risk management and decision-making

    NASA Astrophysics Data System (ADS)

    Berni, Nicola; Brocca, Luca; Barbetta, Silvia; Pandolfo, Claudia; Stelluti, Marco; Moramarco, Tommaso

    2014-05-01

    The Italian national hydro-meteorological early warning system is composed by 21 regional offices (Functional Centres, CF). Umbria Region (central Italy) CF provides early warning for floods and landslides, real-time monitoring and decision support systems (DSS) for the Civil Defence Authorities when significant events occur. The alert system is based on hydrometric and rainfall thresholds with detailed procedures for the management of critical events in which different roles of authorities and institutions involved are defined. The real-time flood forecasting system is based also on different hydrological and hydraulic forecasting models. Among these, the MISDc rainfall-runoff model ("Modello Idrologico SemiDistribuito in continuo"; Brocca et al., 2011) and the flood routing model named STAFOM-RCM (STAge Forecasting Model-Rating Curve Model; Barbetta et al., 2014) are continuously operative in real-time providing discharge and stage forecasts, respectively, with lead-times up to 24 hours (when quantitative precipitation forecasts are used) in several gauged river sections in the Upper-Middle Tiber River basin. Models results are published in real-time in the open source CF web platform: www.cfumbria.it. MISDc provides discharge and soil moisture forecasts for different sub-basins while STAFOM-RCM provides stage forecasts at hydrometric sections. Moreover, through STAFOM-RCM the uncertainty of the forecast stage hydrograph is provided in terms of 95% Confidence Interval (CI) assessed by analyzing the statistical properties of model output in terms of lateral. In the period 10th-12th November 2013, a severe flood event occurred in Umbria mainly affecting the north-eastern area and causing significant economic damages, but fortunately no casualties. The territory was interested by intense and persistent rainfall; the hydro-meteorological monitoring network recorded locally rainfall depth over 400 mm in 72 hours. In the most affected area, the recorded rainfall depths correspond approximately to a return period of 200 years. Most rivers in Umbria have been involved, exceeding hydrometric thresholds and causing flooding (e.g. Chiascio river). The flood event was continuously monitored at the Umbria Region CF and the possible evolution predicted and assessed on the basis of the model forecasts. The predictions provided by MISDc and STAFOM-RCM were found useful to support real-time decision-making addressed to flood risk management. Moreover, the quantification of the uncertainty affecting the deterministic forecast stages was found consistent with the level of confidence selected and had practical utility corroborating the need of coupling deterministic forecast and 'uncertainty' when the model output is used to support decisions about flood management. REFERENCES Barbetta, S., Moramarco, T., Brocca, L., Franchini, M., 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. Brocca, L., Melone, F., Moramarco, T. (2011). Distributed rainfall-runoff modelling for flood frequency estimation and flood forecasting. Hydrological Processes, 25 (18), 2801-2813

  17. Natural Uncertainty Measure for Forecasting Floods in Ungauged Basins

    NASA Astrophysics Data System (ADS)

    Mantilla, Ricardo; Krajewski, Witold F.; Gupta, Vijay K.; Ayalew, Tibebu B.

    2015-04-01

    Recent data analysis have shown that peak flows for individual Rainfall-Runoff (RF-RO) events exhibit power law scaling with respect to drainage area, but the scaling slopes and intercepts change from one event to the next. We test this feature in the 32,400 km2 Iowa River basin, and give supporting evidence for our hypothesis that scaling slope and intercept incorporates all the pertinent physical processes that produce floods. These developments serve as the foundations for the key question that is addressed here: How to define uncertainty bounds for flood prediction for each event? We theoretically introduce the concept of Natural Uncertainty Measure for peak discharge (NUMPD) and test it using data from the Iowa River basin. We conjecture that NUMPD puts a limit to predictive uncertainty using measurements and modeling. In other words, the best any amount of data collection combined with any model can do is to come close to predicting NUMPD, but it cannot match or reduce it any further. For the applications of flood predictions, the concepts of Type-I and Type-II uncertainties in flood prediction are explained. We demonstrate Type-I uncertainty using the concept of NUMPD. Our results offer a context for Type-II uncertainty. Our results make a unique contribution to International Association of Hydrologic Sciences (IAHS) decade-long initiative on Predictions in Unaguged Basins (PUB) (2003-2012).

  18. Remodeling and Flood Forecasting due to Climate Change and Land Used:

    NASA Astrophysics Data System (ADS)

    Mohammad, Munira; Bárdossy, András.

    2010-05-01

    This study is to review the impact of climate change and land used on flooding through the SMART Project. It also simulate the Flood Forecasting in Klang River Basin in order to compare the changes in the existing river system in Klang River Basin with the Storm water Management and Road Tunnel (SMART) which is now already operating in the city center of Kuala Lumpur.The catchment area of the Klang River basin is 1,288 square kilometers (km2), and it is the most urbanized region in Malaysia, encompassing the Federal Territory of Kuala Lumpur and part of the state of Selangor. The basin spreads over nine local government authorities and faces serious environmental degradation and flooding problems from urbanization, industrialization, and population growth. More than half of the basin has been urbanized, and much of this continuing urban development has taken place on land that is prone to flooding. Flooding problem in Klang River Basin is still exist even measures and numerous flood mitigation projects and programs has been carried out by many parties. Even though that the new drainage guideline has been proposed since year 2000, flood reduction for Klang River basins is not successful enough. This problem contributed to the needs of this research to enhance the existing flood forecasting and mitigation project. This study analyzed and quantified the spatial patterns and time-variability of daily, monthly and yearly rainfall in Kuala Lumpur. An overview of rainfall patterns will be obtained through the analysis of 12 point data sources. Statistical properties of annual, monthly, and daily rainfall were derived. Spatial correlation fields for the annual and monthly rainfalls were studied.

  19. A Rolling Flood Forecast Method for River Basins with Newly-Built Meteorological and Hydrological Station Network

    NASA Astrophysics Data System (ADS)

    Shi, H.

    2014-12-01

    Destructive flash floods occurred more frequently in the small and medium river basins in China recently. However, meteorological and hydrological station networks in such river basins were usually poor. Some of them were newly-built only several years ago so that long-series observations are unavailable; and therefore, it is impossible to gain the most suitable parameters for flood forecast from the historical data directly. This paper developed a rolling flood forecast method for such regions, taking the Leli River basin in Guangxi Province, China, as the study area. The Digital Yellow River Integrated Model (DYRIM) was adopted to simulate the streamflows of the Tianlin hydrological station for each flood during the study period, and the model parameters were rolling optimized in real time as follows. First, the parameters were calibrated with the observed rainfall and streamflow data of the first flood, and they were used to forecast the flood caused by the next rain. Second, when the rain came true, the parameters were modified with the newly-observed rainfall and streamflow data if the simulation result obtained with the parameters of the last flood was not satisfied; and the new parameters would be used to forecast the next flood. Through repeating the above two steps for each flood, the parameters may be optimized constantly; and finally, the value ranges of the parameters could be obtained. From a sample demonstration, it can be concluded that this flood forecast method was feasible; it would be valuable for the flood forecast of river basins with newly-built meteorological and hydrological station network.

  20. The potential of satellite radar altimetry in flood forecasting: concept and implementation for the Niger-Benue river basin

    NASA Astrophysics Data System (ADS)

    Pandey, R.; Amarnath, G.

    2015-06-01

    Flood forecasting in the downstream part of any hydrological basin is extremely difficult due to the lack of basin-wide hydrological information in near real-time and the absence of a data-sharing treaty among the transboundary nations. The accuracy of forecasts emerging from a hydrological model could be compromised without prior knowledge of the day-to-day flow regulation at different locations upstream of the Niger and Benue rivers. Only satellite altimeter monitoring allows us to identify the actual river levels upstream that reflect the human intervention at that location. This is critical for making accurate downstream forecasts. This present study aims to demonstrate the capability of altimeter-based flood forecasting along the Niger-Benue River in Nigeria. The study includes the comparison of decadal (at every 10 days from Jason-2) or monthly (at every 35 days from Envisat/AltiKa) observations from 2002 to 2014, with historical in situ measurements from 1990 to 2012. The water level obtained from these sources shows a good correlation (0.7-0.9). After validation of hydrological parameters obtained from two sources, a quantitative relation (rating curve) of upstream water level and downstream discharge is derived. This relation is then adopted for calculation of discharge at observation points, which is used to propagate the flow downstream at a desired location using a hydraulic river model. Results from this study from Jason-2 shows a promising correlation (R2 ? 90% with a Nash-Sutcliffe coefficient of more than 0.70) with 5~days ahead of downstream flow prediction over the Benue stream.

  1. Assimilation of Satellite Based Soil Moisture Data in the National Weather Service's Flash Flood Guidance System

    NASA Astrophysics Data System (ADS)

    Seo, D.; Lakhankar, T.; Cosgrove, B.; Khanbilvardi, R.

    2012-12-01

    Climate change and variability increases the probability of frequency, timing, intensity, and duration of flood events. After rainfall, soil moisture is the most important factor dictating flash flooding, since rainfall infiltration and runoff are based on the saturation of the soil. It is difficult to conduct ground-based measurements of soil moisture consistently and regionally. As such, soil moisture is often derived from models and agencies such as the National Oceanic and Atmospheric Administration's National Weather Service (NOAA/NWS) use proxy estimates of soil moisture at the surface in order support operational flood forecasting. In particular, a daily national map of Flash Flood Guidance (FFG) is produced that is based on surface soil moisture deficit and threshold runoff estimates. Flash flood warnings are issued by Weather Forecast Offices (WFOs) and are underpinned by information from the Flash Flood Guidance (FFG) system operated by the River Forecast Centers (RFCs). This study analyzes the accuracy and limitations of the FFG system using reported flash flood cases in 2010 and 2011. The flash flood reports were obtained from the NWS Storm Event database for the Arkansas-Red Basin RFC (ABRFC). The current FFG system at the ABRFC provides gridded flash flood guidance (GFFG) System using the NWS Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) to translate the upper zone soil moisture to estimates of Soil Conservation Service Curve Numbers. Comparison of the GFFG and real-time Multi-sensor Precipitation Estimator derived Quantitative Precipitation Estimate (QPE) for the same duration and location were used to analyze the success of the system. Improved flash flood forecasting requires accurate and high resolution soil surface information. The remote sensing observations of soil moisture can improve the flood forecasting accuracy. The Soil Moisture Active and Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellites are two potential sources of remotely sensed soil moisture data. SMOS measures the microwave radiation emitted from the Earth's surface operating at L-band (1.20-1.41 GHz) to measure surface soil moisture directly. Microwave radiation at this wavelength offers relatively deeper penetration and has lower sensitivity to vegetation impacts. The main objective of this research is to evaluate the contribution of remote sensing technology to quantifiable improvements in flash flood applications as well as adding a remote sensing component to the NWS FFG Algorithm. The challenge of this study is employing the direct soil moisture data from SMOS to replace the model-calculated soil moisture state which is based on the soil water balance in 4 km x 4 km Hydrologic Rainfall Analysis Project (HRAP) grid cells. In order to determine the value of the satellite data to NWS operations, the streamflow generated by HL-RDHM with and without soil moisture assimilation will be compared to USGS gauge data. Furthermore, we will apply the satellite-based soil moisture data with the FFG algorithm to evaluate how many hits, misses and false alarms are generated. This study will evaluate the value of remote sensing data in constraining the state of the system for main-stem and flash flood forecasting.

  2. RESERVOIR RELEASE FORECAST MODEL FOR FLOOD OPERATION OF THE FOLSOM PROJECT INCLUDING PRE-RELEASES

    E-print Network

    Bowles, David S.

    the operational capabilities created by a modification to increase outlet capacity and by improved weather forecasts based on the Advanced Hydrologic Prediction System (AHPS) of the National Weather Service (NWS

  3. A simple satellite and model based index for forecasting large-scale flood inundation in data-poor regions

    NASA Astrophysics Data System (ADS)

    Schumann, Guy J.-P.; Andreadis, Kostas; Niebuhr, Emily; Rashid, Kashif; Njoku, Eni

    2014-05-01

    Flood inundation poses a major risk to many populated areas around the world. Despite the economic losses and the devastating societal impacts floods have, low frequency, high magnitude events are still poorly monitored, modelled and predicted in many areas across the globe, especially in data-poor regions of the developing world. In these areas, satellite observations and large scale coupled hydrologic-hydrodynamic models are currently the only option to help understand and predict high magnitude flood events. To contribute to these ongoing efforts, this paper presents a simple index for forecasting large-scale flood inundation in data poor regions. Based on a test case in the Lower Zambezi basin (Mozambique), we demonstrate how satellite data, specifically data from the upcoming SMAP mission can be used in conjunction with meteorological forecast data and outputs from a coupled hydrologic-hydrodynamic (VIC-LISFLOOD-FP) model of the region to build up meaningful correlations between rainfall, antecedent soil moisture and simulated flood inundation variables. Along with the data, these correlations can then be used to build up a long term look-up catalogue to develop a simple flood forecast index. Our project illustrates that this index can be applied to forecast flood inundation based on forecast rainfall and observed antecedent soil moisture without the need to run a model.

  4. Performance of National Weather Service Forecasts Compared to Operational, Consensus, and Weighted Model Output Statistics

    E-print Network

    Mass, Clifford F.

    Performance of National Weather Service Forecasts Compared to Operational, Consensus, and Weighted) forecasts of temperature and precipitation to those of the National Weather Service (NWS) subjective of MOS has approached that of National Weather Service (NWS) forecasters, particularly for longer

  5. The potential of radar-based ensemble forecasts for flash-flood early warning in the southern Swiss Alps

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

    This study explores the limits of radar-based forecasting for hydrological runoff prediction. Two novel radar-based ensemble forecasting chains for flash-flood early warning are investigated in three catchments in the southern Swiss Alps and set in relation to deterministic discharge forecasts for the same catchments. The first radar-based ensemble 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 ensemble forecasting system evaluated is REAL-C2, where the numerical weather prediction COSMO-2 is initialised 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. A clear preference was found for the ensemble approach. Discharge forecasts perform better when forced by NORA and REAL-C2 rather then by deterministic weather radar data. Moreover, it was observed that using an ensemble of initial conditions at the forecast initialisation, as in REAL-C2, significantly improved the forecast skill. These forecasts also perform better then forecasts forced by ensemble rainfall forecasts (NORA) initialised form a single initial condition of the hydrological model. Thus the best results were obtained with the REAL-C2 forecasting chain. However, for regions where REAL cannot be produced, NORA might be an option for forecasting events triggered by orographic precipitation.

  6. 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.

  7. A search for model parsimony in a real time flood forecasting system

    NASA Astrophysics Data System (ADS)

    Grossi, G.; Balistrocchi, M.

    2009-04-01

    As regards the hydrological simulation of flood events, a physically based distributed approach is the most appealing one, especially in those areas where the spatial variability of the soil hydraulic properties as well as of the meteorological forcing cannot be left apart, such as in mountainous regions. On the other hand, dealing with real time flood forecasting systems, less detailed models requiring a minor number of parameters may be more convenient, reducing both the computational costs and the calibration uncertainty. In fact in this case a precise quantification of the entire hydrograph pattern is not necessary, while the expected output of a real time flood forecasting system is just an estimate of the peak discharge, the time to peak and in some cases the flood volume. In this perspective a parsimonious model has to be found in order to increase the efficiency of the system. A suitable case study was identified in the northern Apennines: the Taro river is a right tributary to the Po river and drains about 2000 km2 of mountains, hills and floodplain, equally distributed . The hydrometeorological monitoring of this medium sized watershed is managed by ARPA Emilia Romagna through a dense network of uptodate gauges (about 30 rain gauges and 10 hydrometers). Detailed maps of the surface elevation, land use and soil texture characteristics are also available. Five flood events were recorded by the new monitoring network in the years 2003-2007: during these events the peak discharge was higher than 1000 m3/s, which is actually quite a high value when compared to the mean discharge rate of about 30 m3/s. The rainfall spatial patterns of such storms were analyzed in previous works by means of geostatistical tools and a typical semivariogram was defined, with the aim of establishing a typical storm structure leading to flood events in the Taro river. The available information was implemented into a distributed flood event model with a spatial resolution of 90m; then the hydrologic detail was reduced by progressively assuming a uniform rainfall field and constant soil properties. A semi-distributed model, obtained by subdividing the catchment into three sub-catchment, and a lumped model were also applied to simulate the selected flood events. Errors were quantified in terms of the peak discharge ratio, the flood volume and the time to peak by comparing the simulated hydrographs to the observed ones.

  8. Prospects for flash flood forecasting in mountainous regions - An investigation of Tropical Storm Fay in the Southern Appalachians

    NASA Astrophysics Data System (ADS)

    Tao, Jing; Barros, Ana P.

    2013-12-01

    The sensitivity of Quantitative flash-Flood Estimates (QFEs) and Quantitative flash-Flood Forecasts (QFFs) to Quantitative Precipitation Estimates (QPEs) and Quantitative Precipitation Forecasts (QPFs) was investigated in three headwater catchments with different topographic and hydro-geomorphic characteristics during the passage of Tropical Storm Fay, 2008 over the Southern Appalachian Mountains in North Carolina, USA. QFEs and QFFs were generated by a high-resolution hydrologic model (250 × 250 m2) with coupled surface-subsurface physics and rainfall forcing from the Next Generation Multi-sensor QPE (Q2) spatial rainfall (1 × 1 km2) product, and from National Digital Forecast Database (NDFD) operational QPF product (5 × 5 km2). Optimal QPE products (Q2+) were derived by assimilating rainfall observations from a high density raingauge network through adaptive bias correction. Deterministic QFEs simulated by the hydrologic model agree well with streamgauge observations (15-min intervals) regarding total water volume and peak flow with Nash-Sutcliffe (NS) coefficients 0.8-0.9, thus suggesting that the model without calibration captures well the dominant flash-flood physics. The propagation of uncertainty in storm rainfall to rainfall-runoff response was subsequently evaluated through model simulations forced by Monte Carlo replications of the QPEs to generate QFE distributions. Analysis of the joint QPE-QFE distributions shows that flood response at the catchment scale is highly non-linear, and exhibits strong dependence on basin physiography, initial soil moisture conditions (transient basin storage capacity), the space-time organization of runoff generation and conveyance mechanisms, and in particular interflow dynamics, with respect to the space-time structure of rainfall. QFFs for 6- to 1-h lead times using precipitation composites of Q2 QPE and NDFD QPF to drive the hydrology model in operational mode exhibited ubiquitous lack of skill yielding consistently negative NS scores. An experiment consisting of merging satellite-like observations into operational QPE/QPF showed significant improvement in QFF performance (e.g. 5-50% relative NS increases), especially when the timing of satellite overpass is such that it captures transient episodes of heavy rainfall during the event. Future advances in QFF remain principally constrained by progress in QPE and QPF at the spatial resolution necessary to resolve rainfall-interflow dynamics in mountainous regions.

  9. Development of Hydrological Model of Klang River Valley for flood forecasting

    NASA Astrophysics Data System (ADS)

    Mohammad, M.; Andras, B.

    2012-12-01

    This study is to review the impact of climate change and land used on flooding through the Klang River and to compare the changes in the existing river system in Klang River Basin with the Storm water Management and Road Tunnel (SMART) which is now already operating in the city centre of Kuala Lumpur. Klang River Basin is the most urbanized region in Malaysia. More than half of the basin has been urbanized on the land that is prone to flooding. Numerous flood mitigation projects and studies have been carried out to enhance the existing flood forecasting and mitigation project. The objective of this study is to develop a hydrological model for flood forecasting in Klang Basin Malaysia. Hydrological modelling generally requires large set of input data and this is more often a challenge for a developing country. Due to this limitation, the Tropical Rainfall Measuring Mission (TRMM) rainfall measurement, initiated by the US space agency NASA and Japanese space agency JAXA was used in this study. TRMM data was transformed and corrected by quantile to quantile transformation. However, transforming the data based on ground measurement doesn't make any significant improvement and the statistical comparison shows only 10% difference. The conceptual HYMOD model was used in this study and calibrated using ROPE algorithm. But, using the whole time series of the observation period in this area resulted in insufficient performance. The depth function which used in ROPE algorithm are then used to identified and calibrated using only unusual event to observed the improvement and efficiency of the model.

  10. Rapid setup of the high resolution interactive hydrological / hydraulic model for flood forecasting at global scale

    NASA Astrophysics Data System (ADS)

    Donchyts, G.; Haag, A.; Winsemius, H.; Baart, F.; Hut, R.; Drost, N.; Van De Giesen, N.

    2014-12-01

    Rapid predictions of flood using high resolution process-based numerical models applied at global scale is a useful tool for flood forecasting. Usually it requires days or even months to create such a model for a specific area and in most cases the process assumes a lot of manual work. Our goal is to significantly decrease the time required for this process by means of software integration of data processing tools, numerical models and global data sets. The methodology is based on the use of the global hydrological model PCR-GLOBWB to identify the potential flood areas. An automated set of tools will be applied to generate a coupled hydrological / hydraulic model using a high resolution input data based on free global data sets such as SRTM, HydroSHEDS, CORINE, and OpenStreetMaps. This information should be sufficient to generate high resolution input for distributed rainfall-runoff and shallow water flow models. For the detection of potential flood areas, and generation of the unstructured model grid required by the D-Flow FM hydrodynamic model, we will use Height Above the Nearest Drainage (HAND) dataset derived from SRTM. For coupling the distributed hydrological and shallow water models we will use the Basic Model Interface (BMI). BMI is a lightweight API that enables communication with numerical models at runtime. We will validate benefits of the algorithm by applying it to the San Francisco bay area. The models and data processing tools will be integrated into an interactive user interface that will enable data exploration and will allow generation of new models based on user request or automatic rules. Using our approach we expect to make significant steps towards realizing our goal of global availability of flood forecasting models.

  11. Updating real-time flood forecasts via the dynamic system response curve method

    NASA Astrophysics Data System (ADS)

    Si, Wei; Bao, Weimin; Gupta, Hoshin V.

    2015-07-01

    The accuracy of flood forecasts generated using spatially lumped hydrological models can be severely affected by errors in the estimates of areal mean rainfall. The quality of the latter depends both on the size and type of errors in point-based rainfall measurements, and on the density and spatial arrangement of rain gauges in the basin. Here we use error feedback correction, based on the dynamic system response curve (DSRC) method, to compute updated estimates of the rainfall inputs. The method is evaluated via synthetic and real-data cases, showing that the method works as theoretically expected. The ability of the method to improve the accuracy of real-time flood forecasts is then demonstrated using 20 basins of different sizes and having different rain gauge densities. We find that the degree of forecast improvement is more significant for larger basins and for basins with lower rain gauge density. The method is relatively simple to apply and can improve the accuracy and stability of real-time model predictions without increasing either model complexity and/or the number of model parameters.

  12. Flood and Fire Monitoring and Forecasting Within the Chornobyl Exclusion Zone

    NASA Astrophysics Data System (ADS)

    Los, Victor

    2001-03-01

    Taking into consideration that radioactivity from the contaminating elements of the Chernobyl Exclusion Zone (CEZ) amounts to a huge number, one of the most urgent tasks, at present, is the resolution of problems related to secondary radioactive contamination caused by floods and fires. These factors may lead to critical consequences. For instance, if radioactive contaminants migrate into the water system, namely into the Dnipro River, a threat arises to more than 20 million inhabitants of Ukraine. Additionally, fires in the CEZ potentially could cause contaminants to be dispersed into the air and to migrate in the atmosphere for long distances. The elements of information support system for administrative decision-making to respond to the appearances and consequences of forest fires and floods in contaminated areas of the CEZ have been developed. The system proposes: using Earth Remote Sensing (R/S) data for timely detection of forest fires; integration by Geographic Information System (GIS) of mathematical models for radionuclide migration by air in order to forecast radiological consequences of forest fires; forecasting and assessing flood consequences by means of spatial analysis of GIS and R/S; and development of a system for dissemination of information. This project was performed within the framework of USAID Cooperative Agreement #121-A-00-98-00615-00, dedicated to the establishment of the Ukrainian Land and Resource Management Center.

  13. 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.

  14. Building Cyberinfrastructure to Support a Real-time National Flood Model

    NASA Astrophysics Data System (ADS)

    Salas, F. R.; Maidment, D. R.; Tolle, K.; Navarro, C.; David, C. H.; Corby, R.

    2014-12-01

    The National Weather Service (NWS) is divided into 13 regional forecast centers across the country where the Sacramento Soil Moisture Accounting (SAC-SMA) model is run on average over a 10 day period, 5 days in the past and 5 days in the future. Model inputs and outputs such as precipitation and surface runoff are spatially aggregated over approximately 6,600 forecast basins with an average area of 1,200 square kilometers. In contrast, the NHDPlus dataset, which represents the geospatial fabric of the country, defines over 3 million catchments with an average area of 3 square kilometers. Downscaling the NWS land surface model outputs to the NHDPlus catchment scale in real-time requires the development of cyberinfrastructure to manage, share, compute and visualize large quantities of hydrologic data; streamflow computations through time for over 3 million river reaches. Between September 2014 and May 2015, the National Flood Interoperability Experiment (NFIE), coordinated through the Integrated Water Resource Science and Services (IWRSS) partners, will focus on building a national flood model for the country. This experiment will work to seamlessly integrate data and model services available on local and cloud servers (e.g. Azure) through disparate data sources operating at various spatial and temporal scales. As such, this paper will present a scalable information model that leverages the Routing Application for Parallel Computation of Discharge (RAPID) model to produce real-time flow estimates for approximately 67,000 NHDPlus river reaches in the NWS West Gulf River Forecast Center region.

  15. 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.

  16. 24 CFR 570.605 - National Flood Insurance Program.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... accordance with 24 CFR part 91), section 202(a) of the Flood Disaster Protection Act of 1973 (42 U.S.C. 4106) and the regulations in 44 CFR parts 59 through 79 apply to funds provided under this part 570. ... 24 Housing and Urban Development 3 2011-04-01 2010-04-01 true National Flood Insurance...

  17. 24 CFR 570.605 - National Flood Insurance Program.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... accordance with 24 CFR part 91), section 202(a) of the Flood Disaster Protection Act of 1973 (42 U.S.C. 4106) and the regulations in 44 CFR parts 59 through 79 apply to funds provided under this part 570. ... 24 Housing and Urban Development 3 2012-04-01 2012-04-01 false National Flood Insurance...

  18. 24 CFR 570.605 - National Flood Insurance Program.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... accordance with 24 CFR part 91), section 202(a) of the Flood Disaster Protection Act of 1973 (42 U.S.C. 4106) and the regulations in 44 CFR parts 59 through 79 apply to funds provided under this part 570. ... 24 Housing and Urban Development 3 2010-04-01 2010-04-01 false National Flood Insurance...

  19. 24 CFR 570.605 - National Flood Insurance Program.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... accordance with 24 CFR part 91), section 202(a) of the Flood Disaster Protection Act of 1973 (42 U.S.C. 4106) and the regulations in 44 CFR parts 59 through 79 apply to funds provided under this part 570. ... 24 Housing and Urban Development 3 2014-04-01 2013-04-01 true National Flood Insurance...

  20. 24 CFR 570.605 - National Flood Insurance Program.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... accordance with 24 CFR part 91), section 202(a) of the Flood Disaster Protection Act of 1973 (42 U.S.C. 4106) and the regulations in 44 CFR parts 59 through 79 apply to funds provided under this part 570. ... 24 Housing and Urban Development 3 2013-04-01 2013-04-01 false National Flood Insurance...

  1. Observed and forecast flood-inundation mapping application-A pilot study of an eleven-mile reach of the White River, Indianapolis, Indiana

    USGS Publications Warehouse

    Kim, Moon H.; Morlock, Scott E.; Arihood, Leslie D.; Kiesler, James L.

    2011-01-01

    A Service-Oriented Architecture-based dynamic flood-inundation application was developed and was designed to start automatically during a flood, obtain near real-time and forecast data (from the colocated USGS streamgage and NWS flood forecast point within the study reach), run the two-dimensional hydraulic model, and produce flood-inundation maps. The application used local building data and depth-damage curves to estimate flood losses based on the maps, and it served inundation maps and flood-loss estimates through a Web-based graphical user interface.

  2. Plans for national flood frequency by microcomputer

    USGS Publications Warehouse

    Jennings, M.E.; Cookmeyer, E.N.

    1989-01-01

    Work is underway on a planned microcomputer program that will include about 1500 prediction equations for 214 flood regions of the United States and Puerto Rico. The program will include calculation routines for rural and urban flood frequency and hydrograph characteristics and will have links to a detention-pond routing model.

  3. Storm surge forecasting for operating the Venice Flood Barrier with minimal impact on port activities

    NASA Astrophysics Data System (ADS)

    Cecconi, Giovanni

    2015-04-01

    The operation of the Venice storm barrier, due to enter into operation by the end of 2017 , is particularly demanding in terms of the required accuracy of the forecast of the max water level for the time lead of 3-6 hours. With present sea level and safeguard level established at 1.1 m a.s.l. of 1895 the barrier is expected to be operated 10 times a year to cope with an average of 5 storms with around 15 redirections of the navigation through the locks. The 5 extra closures and the 10 extra interferences with navigation are needed for compensating the present forecast uncertainty of 10 cm in the maximum storm high for the required time lead of three hours, the time needed to stop navigation before the closures of the lagoon inlets. A decision support system based on these rules have been tested along the last four year with satisfactory results in term of reliability easy of operations. The forecast is presently based on a statistical model associated with a deterministic local model; the main source of uncertainty is related to the prediction of the local wind. Due to delays in the completion of Venice local protection till 1.1 m it is expected that the population will urge a reduction of the safeguard level from 1.1m to 0.9m with an exponential increase in the number of closures with greater impact on navigation. The present acceleration in sea level rise will also contribute to the increase in the number of closures. To reduce the impact on port activity, better forecast accuracy is required together with experimenting new operational closures : e.g. activating only the northern barriers. The paper evaluate the problem and the possible solutions in terms of improving storm surge forecast and developing new schemes for partial operation of the barriers for predicted limited floods not requiring complete closures.

  4. Assimilation of stream discharge for flood forecasting: Updating a semidistributed model with an integrated data assimilation scheme

    NASA Astrophysics Data System (ADS)

    Li, Yuan; Ryu, Dongryeol; Western, Andrew W.; Wang, Q. J.

    2015-05-01

    Real-time discharge observations can be assimilated into flood models to improve forecast accuracy; however, the presence of time lags in the routing process and a lack of methods to quantitatively represent different sources of uncertainties challenge the implementation of data assimilation techniques for operational flood forecasting. To address these issues, an integrated error parameter estimation and lag-aware data assimilation (IEELA) scheme was recently developed for a lumped model. The scheme combines an ensemble-based maximum a posteriori (MAP) error estimation approach with a lag-aware ensemble Kalman smoother (EnKS). In this study, the IEELA scheme is extended to a semidistributed model to provide for more general application in flood forecasting by including spatial and temporal correlations in model uncertainties between subcatchments. The result reveals that using a semidistributed model leads to more accurate forecasts than a lumped model in an open-loop scenario. The IEELA scheme improves the forecast accuracy significantly in both lumped and semidistributed models, and the superiority of the semidistributed model remains in the data assimilation scenario. However, the improvements resulting from IEELA are confined to the outlet of the catchment where the discharge observations are assimilated. Forecasts at "ungauged" internal locations are not improved, and in some instances, even become less accurate.

  5. Long lead-time flood forecasting using data-driven modeling approaches

    NASA Astrophysics Data System (ADS)

    Bhatia, N.; He, J.; Srivastav, R. K.

    2014-12-01

    In spite of numerous structure measures being taken for floods, accurate flood forecasting is essential to condense the damages in hazardous areas considerably. The need of producing more accurate flow forecasts motivates the researchers to develop advanced innovative methods. In this study, it is proposed to develop a hybrid neural network model to exploit the strengths of artificial neural networks (ANNs). The proposed model has two components: i.) Dual - ANN model developed using river flows; and ii.) Multiple Linear Regression (MLR) model trained on meteorological data (Rainfall and Snow on ground). Potential model inputs that best represent the process of river basin were selected in stepwise manner by identifying input-output relationship using a linear approach, Partial Correlation Input Selection (PCIS) combined with Akaike Information Criterion (AIC) technique. The presented hybrid model was compared with three conventional methods: i) Feed-forward artificial neural network (FF-ANN) using daily river flows; ii) FF-ANN applied on decomposed river flows (low flow, rising limb and falling limb of hydrograph); and iii) Recursive method for daily river flows with lead-time of 7 days. The applicability of the presented model is illustrated through daily river flow data of Bow River, Canada. Data from 1912 to 1976 were used to train the models while data from 1977 to 2006 were used to validate the models. The results of the study indicate that the proposed model is robust enough to capture the non-linear nature of hydrograph and proves to be highly promising to forecast peak flows (extreme values) well in advance (higher lead time).

  6. Assessment of a fuzzy based flood forecasting system optimized by simulated annealing

    NASA Astrophysics Data System (ADS)

    Reyhani Masouleh, Aida; Pakosch, Sabine; Disse, Markus

    2010-05-01

    Flood forecasting is an important tool to mitigate harmful effects of floods. Among the many different approaches for forecasting, Fuzzy Logic (FL) is one that has been increasingly applied over the last decade. This method is principally based on the linguistic description of Rule Systems (RS). A RS is a specific combination of membership functions of input and output variables. Setting up the RS can be implemented either automatically or manually, the choice of which can strongly influence the resulting rule systems. It is therefore the objective of this study to assess the influence that the parameters of an automated rule generation based on Simulated Annealing (SA) have on the resulting RS. The study area is the upper Main River area, located in the northern part of Bavaria, Germany. The data of Mainleus gauge with area of 1165 km2 was investigated in the whole period of 1984 and 2004. The highest observed discharge of 357 m3/s was recorded in 1995. The input arguments of the FL model were daily precipitation, forecasted precipitation, antecedent precipitation index, temperature and melting rate. The FL model of this study has one output variable, daily discharge and was independently set up for three different forecast lead times, namely one-, two- and three-days ahead. In total, each RS comprised 55 rules and all input and output variables were represented by five sets of trapezoidal and triangular fuzzy numbers. Simulated Annealing, which is a converging optimum solution algorithm, was applied for optimizing the RSs in this study. In order to assess the influence of its parameters (number of iterations, temperature decrease rate, initial value for generating random numbers, initial temperature and two other parameters), they were individually varied while keeping the others fixed. With each of the resulting parameter sets, a full-automatic SA was applied to gain optimized fuzzy rule systems for flood forecasting. Evaluation of the performance of the resulting fuzzy rule forecasting systems (with the intention to draw conclusions on the best SA parameters) was carried out in two steps: a) Evaluation of objective functions such as Nash-Sutcliffe and RMSE for all RSs. b) Manual evaluation of the preselected results from the first step. The evaluation was based on visual inspection (scatter plots, time-series and Degree Of Fulfilment (DOF) graphs) as well as logical interpretation of the rule systems. Comparing the results showed that there were SA parameter sets which lead to forecast systems of equally high quality (with respect to objective criteria such as Nash-Sutcliffe), however the underlying rule systems significantly varied from each other. Therefore, manual inspection played a key role in finding the overall best results. In the presentation, the procedure of preparing different sets of SA parameters, the evaluation process of different results and the performance of the optimal RS will be explained and presented by an example.

  7. A flood routing Muskingum type simulation and forecasting model based on level data alone

    NASA Astrophysics Data System (ADS)

    Franchini, Marco; Lamberti, Paolo

    1994-07-01

    While the use of remote hydrometers for measuring the level in water courses is both economical and widespread, the same cannot be said for cross section and channel profile measurements and, even less, for rating curves at the measuring cross sections, all of which are more often than not incomplete, out of date, and unreliable. The mass of data involved in level measurements alone induces a degree of perplexity in those who try to use them, for example, for flood event simulations or the construction of forecasting models which are not purely statistical. This paper proposes a method which uses recorded level data alone to construct a simulation model and a forecasting model, both of them characterized by an extremely simple structure that can be used on any pocket calculator. These models, referring to a river reach bounded by two measuring sections, furnish the downstream levels, where the upstream levels are known, and the downstream level at time t + ?t*, where the upstream and downstream levels are known at time t, respectively. The numerical applications performed show that while the simulation model is somewhat penalized by the simplifications adopted, giving not consistently satisfactory results on validation, the forecasting model generated good results in all the cases examined and seems reliable.

  8. Flash flood forecasting in poorly gauged basins using neural networks: case study of the Gardon de Mialet basin (southern France)

    NASA Astrophysics Data System (ADS)

    Artigue, G.; Johannet, A.; Borrell, V.; Pistre, S.

    2012-11-01

    In southern France, flash flood episodes frequently cause fatalities and severe damage. In order to inform and warn populations, the French flood forecasting service (SCHAPI, Service Central d'Hydrométéorologie et d'Appui à la Prévision des Inondations) initiated the BVNE (Bassin Versant Numérique Expérimental, or Experimental Digital Basin) project in an effort to enhance flash flood predictability. The target area for this study is the Gardon d'Anduze basin, located in the heart of the Cévennes range. In this Mediterranean mountainous setting, rainfall intensity can be very high, resulting in flash flooding. Discharge and rainfall gauges are often exposed to extreme weather conditions, which undermines measurement accuracy and continuity. Moreover, the processes governing rainfall-discharge relations are not well understood for these steeply-sloped and heterogeneous basins. In this context of inadequate information on both the forcing variables and process knowledge, neural networks are investigated due to their universal approximation and parsimony properties. We demonstrate herein that thanks to a rigorous variable and complexity selection, efficient forecasting of up to two-hour durations, without requiring rainfall forecasting as input, can be derived using the measured discharges available from a feedforward model. In the case of discharge gauge malfunction, in degraded mode, forecasting may result using a recurrent neural network model. We also observe that neural network models exhibit low sensitivity to uncertainty in rainfall measurements since producing ensemble forecasting does not significantly affect forecasting quality. In providing good results, this study suggests close consideration of our main purpose: generating forecasting on ungauged basins.

  9. Taking into account hydrological modelling uncertainty in Mediterranean flash-floods forecasting

    NASA Astrophysics Data System (ADS)

    Edouard, Simon; Béatrice, Vincendon; Véronique, Ducrocq

    2015-04-01

    Title : Taking into account hydrological modelling uncertainty in Mediterranean flash-floods forecasting Authors : Simon EDOUARD*, Béatrice VINCENDON*, Véronique Ducrocq* * : GAME/CNRM(Météo-France, CNRS)Toulouse,France Mediterranean intense weather events often lead to devastating flash-floods (FF). Increasing the lead time of FF forecasts would permit to better anticipate their catastrophic consequences. These events are one part of Mediterranean hydrological cycle. HyMeX (HYdrological cycle in the Mediterranean EXperiment) aims at a better understanding and quantification of the hydrological cycle and related processes in the Mediterranean. In order to get a lot of data, measurement campaigns were conducted. The first special observing period (SOP1) of these campaigns, served as a test-bed for a real-time hydrological ensemble prediction system (HEPS) dedicated to FF forecasting. It produced an ensemble of quantitative discharge forecasts (QDF) using the ISBA-TOP system. ISBATOP is a coupling between the surface scheme ISBA and a version of TOPMODEL dedicated to Mediterranean fast responding rivers. ISBA-TOP was driven with several quantitative precipitation forecasts (QPF) ensembles based on AROME atmospheric convection-permitting model. This permitted to take into account the uncertainty that affects QPF and that propagates up to the QDF. This uncertainty is major for discharge forecasting especially in the case of Mediterranean flash-floods. But other sources of uncertainty need to be sampled in HEPS systems. One of them is inherent to the hydrological modelling. The ISBA-TOP coupled system has been improved since the initial version, that was used for instance during Hymex SOP1. The initial ISBA-TOP consisted into coupling a TOPMODEL approach with ISBA-3L, which represented the soil stratification with 3 layers. The new version consists into coupling the same TOPMODEL approach with a version of ISBA where more than ten layers describe the soil vertical stratification, that is ISBA-DF. The use of ISBA-DF into ISBA-TOP coupling permits to get rid of the calibration issues but also to change the pedometer functions used to compute the main hydrological parameters (saturated water content, saturated hydraulic conductivity,...). The first step of this work is thus to assess the impact of these new options on discharge simulations. This was carried out through an academic case to reduce the degrees of freedom of the system. Each parameter is then tested one after another to determine which has the greatest impact on discharge simulations. Finally, the conclusions of the sensitivity analyses are cheeked in realistic configurations. The following step is to vary initial conditions which is another part of modelling uncertainty. The most important parameter tested is soil moisture. The last step will be to slightly vary the ISBA-TOP sensitive parameters so as to produce an QDF ensemble from a given single rainfall forcing field. Later on, this will be applied to ISBA-TOP driven by QPF ensembles. This should improve the HEPS performances.

  10. Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs

    NASA Technical Reports Server (NTRS)

    Valenti, Elizabeth; Fitzpatrick, Patrick

    2006-01-01

    Increasing the accuracy of storm-surge flood forecasts is essential for improving preparedness for hurricanes and other severe storms and, in particular, for optimizing evacuation scenarios. An interactive database, developed by WorldWinds, Inc., contains atlases of storm-surge flood levels for the Louisiana/Mississippi gulf coast region. These atlases were developed to improve forecasting of flooding along the coastline and estuaries and in adjacent inland areas. Storm-surge heights depend on a complex interaction of several factors, including: storm size, central minimum pressure, forward speed of motion, bottom topography near the point of landfall, astronomical tides, and, most importantly, maximum wind speed. The information in the atlases was generated in over 100 computational simulations, partly by use of a parallel-processing version of the ADvanced CIRCulation (ADCIRC) model. ADCIRC is a nonlinear computational model of hydrodynamics, developed by the U.S. Army Corps of Engineers and the US Navy, as a family of two- and three-dimensional finite-element-based codes. It affords a capability for simulating tidal circulation and storm-surge propagation over very large computational domains, while simultaneously providing high-resolution output in areas of complex shoreline and bathymetry. The ADCIRC finite-element grid for this project covered the Gulf of Mexico and contiguous basins, extending into the deep Atlantic Ocean with progressively higher resolution approaching the study area. The advantage of using ADCIRC over other storm-surge models, such as SLOSH, is that input conditions can include all or part of wind stress, tides, wave stress, and river discharge, which serve to make the model output more accurate. To keep the computational load manageable, this work was conducted using only the wind stress, calculated by using historical data from Hurricane Camille, as the input condition for the model. Hurricane storm-surge simulations were performed on an eight-node Linux computer cluster. Each node contained dual 2-GHz processors, 2GB of memory, and a 40GB hard drive. The digital elevation model (DEM) for this region was specified using a combination of Navy data (over water), NOAA data (for the coastline), and optimized Interferometric Synthetic Aperture Radar data (over land). This high-resolution topographical data of the Mississippi coastal region provided the ADCIRC model with improved input with which to calculate improved storm-surge forecasts.

  11. Efficiency of a real time flood forecasting system in the Alps and in the Apennines: deterministic versus ensemble predictions

    NASA Astrophysics Data System (ADS)

    Grossi, G.

    2009-04-01

    Real time hydrological forecasting is still a challenging task for most of the Italian territory, especially in mountain areas where both the topography and the meteorological forcing are affected by a strong spatial variability. Nevertheless there is an increasing request to provide some clues for the development of efficient real time flood forecasting systems, for warning population as well as for water management purposes. In this perspective the efficiency of a real time forecasting system needs to be investigated, with particular care to the uncertainty of the provided prediction and to how this prediction will be handled by water resources managers and land protection services. To this aim a real time flood forecasting system using both deterministic and ensemble meteorological predictions has been implemented at University of Brescia and applied to an Alpine area (the Toce River - Piemonte Region) and to an Apennine area (the Taro River - Emilia Romagna Region). The Map D- Phase experiment (autumn 2007) was a good test for the implemented system: daily rainfall fields provided by high resolution deterministic limited area meteorological models and esemble rainfall predictions provided by coarser resolution meteorological models could be used to force a hydrological model and produce either a single deterministic or an esemble of flood forecats. Namely only minor flood events occurred in the Alpine area in autumn 2007, while one major flood event affected the Taro river at the end of November 2007. Focusing on this major event the potentials of the forecasting system was tested and evaluated with reference also to the geographical and climatic characteristics of the investigated area.

  12. Neural network modeling and geochemical water analyses to understand and forecast karst and non-karst part of flash floods (case study on the Lez river, Southern France)

    NASA Astrophysics Data System (ADS)

    Darras, T.; Raynaud, F.; Borrell Estupina, V.; Kong-A-Siou, L.; Van-Exter, S.; Vayssade, B.; Johannet, A.; Pistre, S.

    2015-06-01

    Flash floods forecasting in the Mediterranean area is a major economic and societal issue. Specifically, considering karst basins, heterogeneous structure and nonlinear behaviour make the flash flood forecasting very difficult. In this context, this work proposes a methodology to estimate the contribution from karst and non-karst components using toolbox including neural networks and various hydrological methods. The chosen case study is the flash flooding of the Lez river, known for his complex behaviour and huge stakes, at the gauge station of Lavallette, upstream of Montpellier (400 000 inhabitants). After application of the proposed methodology, discharge at the station of Lavallette is spited between hydrographs of karst flood and surface runoff, for the two events of 2014. Generalizing the method to future events will allow designing forecasting models specifically for karst and surface flood increasing by this way the reliability of the forecasts.

  13. 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.

  14. Flooding

    MedlinePLUS

    ... flooding Prepare for flooding For communities, companies, or water and wastewater facilities: Suggested activities to help facilities ... con monóxido de carbono. Limit contact with flood water. Flood water may have high levels of raw ...

  15. Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts

    EIA Publications

    2010-01-01

    The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

  16. A Multitemporal Remote Sensing Approach to Streamflow Prediction and Flood Vulnerability Forecasting

    NASA Astrophysics Data System (ADS)

    Weissling, B. P.; Xie, H.

    2006-12-01

    The Guadalupe and San Antonio River basins of south-central Texas have a long history of catastrophic flooding events. Recent events in July 2002 and October 1998 resulted in enormous property losses and dozens of deaths. More than 48,000 homes were damaged or destroyed during the 2002 event, when as much as 35 inches of rain fell in parts of the upper and middle reaches of both river basins over an 8 day period. Eighty Texas counties were affected in some way by this catastrophe, with damage estimates exceeding $1.5 billion. The USGS currently operates and monitors 27 streamflow gaging stations within the Guadalupe and neighboring San Antonio river basins, providing adequate coverage for select reaches of main channels and major tributaries. However, numerous watersheds within both basins remain ungaged. Driven by budget constraints, these ungaged watersheds will likely remain so; thus contributing little hydrologic information toward a better understanding of basin flood hydrology while potentially contributing catastrophic runoff outflows during major precipitation events. A streamflow prediction model for gaged and ungaged watersheds in the Guadalupe and San Antonio river basins is currently under development based on multitemporal remote sensing imagery from the MODIS/Terra satellite platform. Recognizing that antecedent soil moisture plays a vital role in a watershed's hydrologic response to a precipitation event, the characterization of the antecedent moisture state of a watershed from remotely sensed biophysical variables could parameterize a statistical streamflow or runoff prediction model solely utilizing gaged, radar and/or satellite-based precipitation records and these remotely sensed variables. A 1418 km2 rural watershed in the central region of the Guadalupe River basin, a watershed that experienced a 90,000 cfs peak flow rate during the 1998 flood event, was selected for the model training phase of this project. A multiple regression model of gaged precipitation, land surface temperature, and select vegetation indices accounted for 78% (R2adj = 0.78) of the variance of gage station observed streamflow for calendar year 2004. Efforts are underway to calibrate and validate this model for other time periods within the data availability window of MODIS imagery products, and for other watersheds of varying size and similar climatic regime within the Guadalupe River and neighboring basins. The success of this remote sensing approach will have implications for developing near real-time flood risk and vulnerability forecasting models for both gaged and ungaged watersheds, as well as water supply management in regions of the world with limited resources to undertake conventional ground-based hydrologic studies.

  17. Calibration and parameterization of a semi-distributed hydrological model to support sub-daily ensemble flood forecasting; a watershed in southeast Brazil

    NASA Astrophysics Data System (ADS)

    de Almeida Bressiani, D.; Srinivasan, R.; Mendiondo, E. M.

    2013-12-01

    The use of distributed or semi-distributed models to represent the processes and dynamics of a watershed in the last few years has increased. These models are important tools to predict and forecast the hydrological responses of the watersheds, and they can subside disaster risk management and planning. However they usually have a lot of parameters, of which, due to the spatial and temporal variability of the processes, are not known, specially in developing countries; therefore a robust and sensible calibration is very important. This study conduced a sub-daily calibration and parameterization of the Soil & Water Assessment Tool (SWAT) for a 12,600 km2 watershed in southeast Brazil, and uses ensemble forecasts to evaluate if the model can be used as a tool for flood forecasting. The Piracicaba Watershed, in São Paulo State, is mainly rural, but has about 4 million of population in highly relevant urban areas, and three cities in the list of critical cities of the National Center for Natural Disasters Monitoring and Alerts. For calibration: the watershed was divided in areas with similar hydrological characteristics, for each of these areas one gauge station was chosen for calibration; this procedure was performed to evaluate the effectiveness of calibrating in fewer places, since areas with the same group of groundwater, soil, land use and slope characteristics should have similar parameters; making calibration a less time-consuming task. The sensibility analysis and calibration were performed on the software SWAT-CUP with the optimization algorithm: Sequential Uncertainly Fitting Version 2 (SUFI-2), which uses Latin hypercube sampling scheme in an iterative process. The performance of the models to evaluate the calibration and validation was done with: Nash-Sutcliffe efficiency coefficient (NSE), determination coefficient (r2), root mean square error (RMSE), and percent bias (PBIAS), with monthly average values of NSE around 0.70, r2 of 0.9, normalized RMSE of 0.01, and PBIAS of 10. Past events were analysed to evaluate the possibility of using the SWAT developed model for Piracicaba watershed as a tool for ensemble flood forecasting. For the ensemble evaluation members from the numerical model Eta were used. Eta is an atmospheric model used for research and operational purposes, with 5km resolution, and is updated twice a day (00 e 12 UTC) for a ten day horizon, with precipitation and weather estimates for each hour. The parameterized SWAT model performed overall well for ensemble flood forecasting.

  18. Real-time multi-step-ahead water level forecasting by recurrent neural networks for urban flood control

    NASA Astrophysics Data System (ADS)

    Chang, Fi-John; Chen, Pin-An; Lu, Ying-Ray; Huang, Eric; Chang, Kai-Yao

    2014-09-01

    Urban flood control is a crucial task, which commonly faces fast rising peak flows resulting from urbanization. To mitigate future flood damages, it is imperative to construct an on-line accurate model to forecast inundation levels during flood periods. The Yu-Cheng Pumping Station located in Taipei City of Taiwan is selected as the study area. Firstly, historical hydrologic data are fully explored by statistical techniques to identify the time span of rainfall affecting the rise of the water level in the floodwater storage pond (FSP) at the pumping station. Secondly, effective factors (rainfall stations) that significantly affect the FSP water level are extracted by the Gamma test (GT). Thirdly, one static artificial neural network (ANN) (backpropagation neural network-BPNN) and two dynamic ANNs (Elman neural network-Elman NN; nonlinear autoregressive network with exogenous inputs-NARX network) are used to construct multi-step-ahead FSP water level forecast models through two scenarios, in which scenario I adopts rainfall and FSP water level data as model inputs while scenario II adopts only rainfall data as model inputs. The results demonstrate that the GT can efficiently identify the effective rainfall stations as important inputs to the three ANNs; the recurrent connections from the output layer (NARX network) impose more effects on the output than those of the hidden layer (Elman NN) do; and the NARX network performs the best in real-time forecasting. The NARX network produces coefficients of efficiency within 0.9-0.7 (scenario I) and 0.7-0.5 (scenario II) in the testing stages for 10-60-min-ahead forecasts accordingly. This study suggests that the proposed NARX models can be valuable and beneficial to the government authority for urban flood control.

  19. 76 FR 70745 - Agency Information Collection Activities: Proposed Collection; Comment Request; National Flood...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-11-15

    ...; Comment Request; National Flood Insurance Program--Mortgage Portfolio Protection Program AGENCY: Federal... comments concerning the National Flood Insurance Program Mortgage Portfolio Protection program, which is an option that companies participating in the National Flood Insurance Program can use to bring...

  20. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...2010-10-01 2010-10-01 false National Flood Insurance Program B Appendix B to Part...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND...B Appendix B to Part 62—National Flood Insurance Program A Plan to...

  1. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2012-10-01 2011-10-01 true National Flood Insurance Program B Appendix B to Part...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND...B Appendix B to Part 62—National Flood Insurance Program A Plan to...

  2. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 2013-10-01 false National Flood Insurance Program B Appendix B to Part...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND...B Appendix B to Part 62—National Flood Insurance Program A Plan to...

  3. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 2014-10-01 false National Flood Insurance Program B Appendix B to Part...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND...B Appendix B to Part 62—National Flood Insurance Program A Plan to...

  4. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...2011-10-01 2011-10-01 false National Flood Insurance Program B Appendix B to Part...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND...B Appendix B to Part 62—National Flood Insurance Program A Plan to...

  5. Application of Satellite information (JASON-2) in improvement of Flood Forecasting and Early Warning Service in Bangladesh

    NASA Astrophysics Data System (ADS)

    Hossain, M. A.; Anderson, E. R.; Bhuiyan, M. A.; Hossain, F.; Shah-Newaz, S. M.

    2014-12-01

    Bangladesh is the lowest riparian of the huge system of the Ganges, Brahmaputra and Meghna (GBM) basins, second to that of Amazan, with 1.75 million sq-km catchment area, only 7% is inside Bangladesh. High inflow from GBM associated with the intense rainfall is the source of flood in Bangladesh. Flood Forecasting and Early Warning (FFEW) is the mandate and responsibility of Bangladesh Water Development Board (BWDB) and Flood Forecasting and Warning Center (FFWC) under BWDB has been carrying out this responsibility since 1972 and operational on 7-days a week during monsoon (May to October). FFEW system started with few hours lead time has been upgraded up to to 5-days with reasonable accuracy. At FFWC numerical Hydrodynamic model is used for generating water level (WL) forecast upto 5-days at 54 points on 29 rivers based on real-time observed WL of 83 and rainfall of 56 stations with boundary estimationa on daily basis. Main challenge of this system is the boundary estimation is the limited upstream data of the transboundary rivers, obstacle for increasing lead-time for FFEW. The satellite based upper catchment data may overcome this limitation. Recent NASA-French joint Satellite mission JASON-2 records Water Elevation (WE) and it may be used within 24 hours. Using JASON-2 recorded WE data of 4 and 3 virtual stations on the Ganges and Brahmaputra rivers , respectively (upper catchment), a new methodology has been developed for increasing lead time of forecast. Correlation between the JASON-2 recorded WE on the virtual stations at the upper catchment and WL of 2 dominating boundary stations at model boundary on the Ganges and Brahmaputra has been derived for generating WL forecast at those 2 boundary stations, which used as input in model. FFWC has started experimental 8-days lead-time WL forecast at 09 stations (5 in Brahmaputra and 4 in Ganges) using generated boundary data and regularly updating the results in the website. The trend of the forecasted WL using JASON-2 data is similar to those upto 5-days forecast generated in the existing system. This is a new approach in FFEW in Bangladesh where boundary estimation becomes possible using JASON-2 observed WE data of the Transboundary rivers. There is scope of further development of this system along with increase of lead time. Reference: www.ffwc.gov.bd

  6. Development of Open-book Watershed Modeling for Satellite Based Flood Forecasting in International River Basin

    NASA Astrophysics Data System (ADS)

    Katiyar, N.; Hossain, F.

    2006-12-01

    A parsimonious way to understand the surface hydrology across the political boundaries of a river basin is to adopt an open book watershed modeling approach, first formulated by Yen and Chow (1961). The proposed NASA mission, Global Precipitation Measurement (GPM) may now usher a new era of application of the open- book modeling framework to understand the worth of anticipated availability of high resolution satellite rainfall data for predicting transboundary river flow. In our study we developed, verified and implemented our open-book watershed model for rapid prototyping of satellite rainfall based flood monitoring systems for International River Basins (IRBs). The model follows conservation of mass and momentum balance that brings minimum requirement of data. We first demonstrate the physical consistency of our model through sensitivity analysis of some geo physical basin parameters pertinent to rainfall-runoff transformation. Next, we simulate the stream- flow hydrograph for a 4 month long period using basin-wide radar (WSR-88D) rainfall data over Oklahoma assuming an open-book configuration. Finally, using the radar-simulated hydrograph as the benchmark, and assuming a two-nation hypothetical IRB over Oklahoma, we explored the impact of assimilating NASA's real- time satellite rainfall data (IR-3B41RT) over the upstream nation on the flow monitoring accuracy of the downstream nation. We developed a relationship defining the improvement in flow monitoring that can be expected from assimilating IR-3B41RT over transboundary regions as a function of the relative area occupied by the downstream nation. The relative improvement in flow monitoring accuracy for the downstream nation can be a maximum of 45% when more than 90% of the basin is transboundary to the nation. However, flow monitoring accuracy does not appear amenable for tangible improvement when 25% or less of the basin area is transboundary to the downstream nation. For IR-3B41RT to have non-negligible improvement (> 30% reduction in Relative RMSE of streamflow prediction), the downstream nation should not occupy more than 40% of the total IRB area. Finally, we mapped this relationship world-wide on the basis of climate-regime similarity using the Koppen classification. Our climate-based mapping scheme identified 5 specific downstream nations (North Korea, Bangladesh, Senegal, Mozambique and Uruguay) that could potentially benefit significantly from the integrating basin-wide IR-3B41RT data in their flood monitoring systems.

  7. A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts

    NASA Astrophysics Data System (ADS)

    Liu, P.

    2013-12-01

    Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based hydrologic forecasts directly depict the inflows not only the marginal distributions but also their persistence via scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasts as inputs. A method is developed by using the forecast horizon point to divide the future time into two stages, the forecast lead-time and the unpredicted time. The risk within the forecast lead-time is computed based on counting the failure number of forecast scenarios, and the risk in the unpredicted time is estimated using reservoir routing with the design floods and the reservoir water levels of forecast horizon point. As a result, a two-stage risk analysis method is set up to quantify the entire flood risks by defining the ratio of the number of scenarios that excessive the critical value to the total number of scenarios. The China's Three Gorges Reservoir (TGR) is selected as a case study, where the parameter and precipitation uncertainties are implemented to produce ensemble-based hydrologic forecasts. The Bayesian inference, Markov Chain Monte Carlo, is used to account for the parameter uncertainty. Two reservoir operation schemes, the real operated and scenario optimization, are evaluated for the flood risks and hydropower profits analysis. With the 2010 flood, it is found that the improvement of the hydrologic forecast accuracy is unnecessary to decrease the reservoir real-time operation risk, and most risks are from the forecast lead-time. It is therefore valuable to decrease the avarice of ensemble-based hydrologic forecasts with less bias for a reservoir operational purpose.

  8. 77 FR 23270 - Agency Information Collection Activities: Proposed Collection; Comment Request, National Flood...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-04-18

    ...; Comment Request, National Flood Insurance Program Call Center and Agent Referral Enrollment Form AGENCY... comments concerning this information collection that allows the National Flood Insurance Program (NFIP) to facilitate the availability of flood insurance to those who have a need to purchase such. The NFIP...

  9. 76 FR 64361 - Agency Information Collection Activities: Proposed Collection; Comment Request; National Flood...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-18

    ...; Comment Request; National Flood Insurance Program Claims Appeals Process AGENCY: Federal Emergency... revision of the National Flood Insurance Claims Appeals Process. The appeal process establishes a formal..., and loss estimates. Under this process, FEMA sends the NFIP Flood Insurance Claims Handbook to...

  10. 78 FR 45936 - Agency Information Collection Activities: Proposed Collection; Comment Request; National Flood...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-30

    .... Collection of Information Title: National Flood Insurance Program Claim Forms. Type of Information Collection...; Comment Request; National Flood Insurance Program Claim Forms AGENCY: Federal Emergency Management Agency... information related to the flood insurance claims process. DATES: Comments must be submitted on or...

  11. Floods

    MedlinePLUS

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

  12. Cross-institutional Flood Forecasting in Regional Water Systems;Innovative application of Delft-FEWS in The Netherlands

    NASA Astrophysics Data System (ADS)

    van Heeringen, Klaas-Jan; Douben, Klaas-Jan; van de Wouw, Mark; IJpelaar, Ruben; van Loenen, Arnejan

    2015-04-01

    The regional water system in the North-Brabant province in The Netherlands is (operationally) managed by four different Water Authorities: Rijkswaterstaat Southern-Netherlands, and the three Regional Water Authorities (RWA's) Aa & Maas, De Dommel and Brabantse Delta. The water systems basically consist of mid-sized (navigable) canals, semi-natural brook valleys in mildly sloping sandy soils, and man-made watercourses in clayey polder areas. The management areas of the De Dommel and Brabantse Delta RWA's are bordering Belgium over a total length of approx. 185 km, and are prone to transboundary flood flows. The current project 'Dynamic Water Management' intends to improve the mutual cooperation and communication between the RWA's and Rijkswaterstaat during periods of both high and low water stages. The project deals with governance issues such as water agreements and water systems analyses. A powerful product of the project is a DSS for flood forecasting ('DSS Brabant'). One of the main benefits of cooperation between the RWA's and Rijkswaterstaat is to enable assistance during peak flows and flood events and to try to optimise operational water systems management by deploying drainage and storage facilities by using the connecting (navigable) canals. A set of hydraulic structures like pumps, weirs and sluices facilitate the control and routing of the water flows. Especially during peak flow and flood events, these canals allow to deviate excess flow to neighbours who suffer less from flooding. During regular conditions the water systems are fully independent, but during floods connections are made by using the canal system. The heart of DSS Brabant consists of a Delft-FEWS application, containing several RTC (1st) and hydrodynamic Sobek (2nd order) models FEWS is receiving a variety of data on hourly or six-hourly basis, consisting of measured and forecasted meteorological input (radar-precipitation/HIRLAM, evaporation and wind), water levels and discharges at (transboundary) model boundary locations. Three RTC models, which are running continuously, are fed with the output of conceptual rainfall-runoff models to simulate water level, discharge and weir height forecasts. These RTC models simulate a five days period within a few minutes. In addition, an ECWMF ensemble of 50 members runs each 12 hours to estimate the reliability and uncertainties of forecasted water levels and discharges. The FEWS application in DSS Brabant also contains three additional RTC (beta) models that optimise the (penalty based) settings of weirs and gates, and the deployment of water retention areas. Four different hydrodynamic Sobek models are used for routing purposes and more detailed overland flow forecasts on various 'key' locations. These models run standard on a six hourly basis, but can also be used manually to simulate the impacts of the various operational measures. These 2nd order model runs are intended to run within one hour.

  13. Near-real-time simulation and internet-based delivery of forecast-flood inundation maps using two-dimensional hydraulic modeling--A pilot study for the Snoqualmie River, Washington

    USGS Publications Warehouse

    Jones, Joseph L.; Fulford, Janice M.; Voss, Frank D.

    2002-01-01

    A system of numerical hydraulic modeling, geographic information system processing, and Internet map serving, supported by new data sources and application automation, was developed that generates inundation maps for forecast floods in near real time and makes them available through the Internet. Forecasts for flooding are generated by the National Weather Service (NWS) River Forecast Center (RFC); these forecasts are retrieved automatically by the system and prepared for input to a hydraulic model. The model, TrimR2D, is a new, robust, two-dimensional model capable of simulating wide varieties of discharge hydrographs and relatively long stream reaches. TrimR2D was calibrated for a 28-kilometer reach of the Snoqualmie River in Washington State, and is used to estimate flood extent, depth, arrival time, and peak time for the RFC forecast. The results of the model are processed automatically by a Geographic Information System (GIS) into maps of flood extent, depth, and arrival and peak times. These maps subsequently are processed into formats acceptable by an Internet map server (IMS). The IMS application is a user-friendly interface to access the maps over the Internet; it allows users to select what information they wish to see presented and allows the authors to define scale-dependent availability of map layers and their symbology (appearance of map features). For example, the IMS presents a background of a digital USGS 1:100,000-scale quadrangle at smaller scales, and automatically switches to an ortho-rectified aerial photograph (a digital photograph that has camera angle and tilt distortions removed) at larger scales so viewers can see ground features that help them identify their area of interest more effectively. For the user, the option exists to select either background at any scale. Similar options are provided for both the map creator and the viewer for the various flood maps. This combination of a robust model, emerging IMS software, and application interface programming should allow the technology developed in the pilot study to be applied to other river systems where NWS forecasts are provided routinely.

  14. Retrospective analysis of a non-forecasted rain-on-snow flood in the Alps - a matter of model-limitations or unpredictable nature?

    NASA Astrophysics Data System (ADS)

    Rössler, O.; Froidevaux, P.; Börst, U.; Rickli, R.; Martius, O.; Weingartner, R.

    2013-10-01

    On 10 October 2011, a rain-on-snow flood occurred in the Bernese Alps, Switzerland, and caused significant damage. As this flood peak was unpredicted by the flood forecast system, questions were raised concerning what has caused this flood and whether it was predictable at all. In this study, we focused on one valley that was heavily hit by the event, the Loetschen valley (160 km2), and aimed to reconstruct the anatomy of this rain-on-snow flood from the synoptic conditions represented by European Centre for Medium-Range Weather Forecasts ECWMF analysis data, and the local meteorology within the valley recorded by an extensive met-station network. In addition, we applied the hydrological model WaSiM-ETH to improve our hydrological process understanding about this event and to demonstrate the predictability of this rain-on-snow flood. We found an atmospheric river bringing moist and warm air to Switzerland that followed an anomalous cold front with sustained snowfall to be central for this rain-on-snow event. Intensive rainfall (average 100 mm day-1) was accompanied by a drastic temperature increase (+8 K) that shifted the zero degree line from 1500 m a.s.l. to 3200 m a.s.l. in 12 h. The northern flank of the valley received significantly more precipitation than the southern flank, leading to an enormous flood in tributaries along the northern flank, while the tributaries along the southern flank remained nearly unchanged. We hypothesized that the reason for this was a cavity circulation combined with a seeder-feeder-cloud system enhancing both local rainfall and snow melt by condensation of the warm, moist air on the snow. Applying and adjusting the hydrological model, we show that both the latent and the sensible heat fluxes were responsible for the flood and that locally large amounts of precipitation (up to 160 mm rainfall in 12 h) was necessary to produce the estimated flood peak. With considerable adjustments to the model and meteorological input data, we were able to reproduce the flood peak, demonstrating the ability of the model to reproduce the flood. However, driving the optimized model with COSMO-2 forecast data, we still failed to simulate the flood precisely because COSMO-2 forecast data underestimated both the local precipitation peak and the temperature increase. Thus, this rain-on-snow flood was predictable, but requires a special model set up and extensive and locally precise meteorological input data, especially in terms of both precipitation and temperature.

  15. Performing Multiple Simulations for Multiple Watersheds in Flood Forecasting Using the GSSHA Distributed Hydrologic Models in Large Basins

    NASA Astrophysics Data System (ADS)

    Perez, F.; Jones, N.; Nelson, E. J.; Christensen, S. D.

    2014-12-01

    When massive storm events are imminently expected over a given area, flood forecast centers often need to execute hydrologic model simulations for multiple watersheds some of which may be large in size for distributed models to be able to complete in a relatively short time. And since it is advantageous to subdivide the watersheds for a distributed model like GSSHA to be able to have short run times, the operational solution needs to consider simultaneous simulations runs for the models of the individual sub-basins. The number of simulations in each watershed would increase if there are different scenarios that consider several weather forecasts with storm tracks and direction that produce many rainfall patterns that would differ in the magnitude and spatial distribution of rainfall. The problem is further increased when it is necessary to analyze several possible watershed conditions and several emergency operation alternatives for flood control. Some computer hardware solution is needed to perform the many that would result from the combination of the forecasted scenarios, the operation alternatives, watershed conditions in an already large number of watersheds which might also be subdivided into many sub-basins. The first problem is finding a suitable watershed sub-division that breaks down the size of the areas for the models in a way that saves run-time. This is accomplished in two test-case watersheds using a workflow of basin-model orchestration where arrangements of parallel and cascade simulations are done for the sub-basins of tributary rivers and the main river. The second problem of running all the possible simulations is dealt with using distributed computing options such as HT Condor and Microsoft Azure. The results are compared using operational performance indicators.

  16. A Performance Evaluation of the National Air Quality Forecast Capability for the Summer of 2007

    EPA Science Inventory

    This paper provides a performance evaluation of the real-time, CONUS-scale National Air Quality Forecast Capability (NAQFC), developed collaboratively by the National Oceanic and Atmospheric Administration (NOAA) and Environmental Protection Agency (EPA), that supported, in part,...

  17. Ensemble Statistical Post-Processing of the National Air Quality Forecast Capability: Enhancing Ozone Forecasts in Baltimore, Maryland

    NASA Technical Reports Server (NTRS)

    Garner, Gregory G.; Thompson, Anne M.

    2013-01-01

    An ensemble statistical post-processor (ESP) is developed for the National Air Quality Forecast Capability (NAQFC) to address the unique challenges of forecasting surface ozone in Baltimore, MD. Air quality and meteorological data were collected from the eight monitors that constitute the Baltimore forecast region. These data were used to build the ESP using a moving-block bootstrap, regression tree models, and extreme-value theory. The ESP was evaluated using a 10-fold cross-validation to avoid evaluation with the same data used in the development process. Results indicate that the ESP is conditionally biased, likely due to slight overfitting while training the regression tree models. When viewed from the perspective of a decision-maker, the ESP provides a wealth of additional information previously not available through the NAQFC alone. The user is provided the freedom to tailor the forecast to the decision at hand by using decision-specific probability thresholds that define a forecast for an ozone exceedance. Taking advantage of the ESP, the user not only receives an increase in value over the NAQFC, but also receives value for An ensemble statistical post-processor (ESP) is developed for the National Air Quality Forecast Capability (NAQFC) to address the unique challenges of forecasting surface ozone in Baltimore, MD. Air quality and meteorological data were collected from the eight monitors that constitute the Baltimore forecast region. These data were used to build the ESP using a moving-block bootstrap, regression tree models, and extreme-value theory. The ESP was evaluated using a 10-fold cross-validation to avoid evaluation with the same data used in the development process. Results indicate that the ESP is conditionally biased, likely due to slight overfitting while training the regression tree models. When viewed from the perspective of a decision-maker, the ESP provides a wealth of additional information previously not available through the NAQFC alone. The user is provided the freedom to tailor the forecast to the decision at hand by using decision-specific probability thresholds that define a forecast for an ozone exceedance. Taking advantage of the ESP, the user not only receives an increase in value over the NAQFC, but also receives value for

  18. Idaho National Laboratory Materials and Fuels Complex Natural Phenomena Hazards Flood Assessment

    SciTech Connect

    Gerald Sehlke; Paul Wichlacz

    2010-12-01

    This report presents the results of flood hazards analyses performed for the Materials and Fuels Complex (MFC) and the adjacent Transient Reactor Experiment and Test Facility (TREAT) located at Idaho National Laboratory. The requirements of these analyses are provided in the U.S. Department of Energy Order 420.1B and supporting Department of Energy (DOE) Natural Phenomenon Hazard standards. The flood hazards analyses were performed by Battelle Energy Alliance and Pacific Northwest National Laboratory. The analyses addressed the following: • Determination of the design basis flood (DBFL) • Evaluation of the DBFL versus the Critical Flood Elevations (CFEs) for critical existing structures, systems, and components (SSCs).

  19. Evaluation of the Sacramento Soil Moisture Accounting Model for Flood Forecasting in a Hawaiian Watershed

    NASA Astrophysics Data System (ADS)

    Awal, R.; Fares, A.; Michaud, J.; Chu, P.; Fares, S.; Rosener, M.; Kevin, K.

    2012-12-01

    The focus of this study was to assess the performance of the U.S. National Weather Service Sacramento Soil Moisture Accounting Model (SAC-SMA) on the flash flood prone Hanalei watershed, Kauai, Hawaii, using site specific hydrologic data. The model was calibrated and validated using six-years of observed field hydrological data, e.g., stream flow, and spatially distributed rainfall. The ordinary kriging method was used to calculate mean watershed wide hourly precipitation for the six years using data from twenty rain gauges from north shore Kauai including five rain gauges within the watershed. Ranges of the values of a priori SAC-SMA parameters were also estimated based on the site specific soil hydrological properties; these calculated values were well within those reported in literature for different watersheds SAC-SMA was run for one year runs using the calibration and validation data. The performance of model in predicting streamflow using average watershed wide values of the a priori parameters was very poor. SAC-SMA over predicted streamflow throughout the year as compared to observed streamflow data. The upper limit of the lower layer tension water capacity, LZTWM, parameter was higher than those reported in the literature this might be due to the wetter conditions, higher precipitation, in Hanalei watershed (>6400mm) than the other previously studied watersheds (<1600mm). When the upper bound of LZTWM varied between 2500 and 3000 during calibration, SAC-SMA's performance improved to satisfactory and even to good for almost all years based on PBIAS and Nash-Sutcliffe coefficients of efficiency. When we used optimized parameter of one year to other years for the validation, the performance of optimized parameter of year 2005 was satisfactory for most of the year when upper bound of LZTWM = 2500 and the optimized parameter of year 2004 was satisfactory for most of the year when upper bound of LZTWM = 3000. The annual precipitation of 2004 was the highest however, that of 2005 was the closest to the mean annual precipitation of the study period (2001-2010). The upper bound of LZTWM increased as a function of precipitation, it was equal to 3000 for the 2004 wet year and 2500 for the 2005 which had an average precipitation. Although we increased the upper bound of LZTWM, the performance of SAC-SMA was not satisfactory in all years for both calibration and validation. The main reason for poor performance is due to the high spatial variation of precipitation across the watershed. Furthermore, studies on other tropical basins will help to generalize these findings.

  20. What is the Safest Way to Cross the Valley of Death: Wisdom gained from Making a Satellite based Flood Forecasting System Operational and Owned by Stakeholders

    NASA Astrophysics Data System (ADS)

    Hossain, F.

    2013-12-01

    More than a decade ago, the National Research Council report popularized the term 'Valley of Death' to describe the region where research on Weather Satellites had struggled to survive before reaching maturity for societal applications. For example, the space vantage of earth observing satellites can solve some of the world's otherwise fundamentally intractable operational problems on water resources. However, recent experiences show that many of the potential beneficiaries, who are not as familiar with water cycle remote sensing missions or anthropogenic climate studies, referred here as the ';non-traditional consumers,' may have a more skeptical view based on their current practices. This talk will focus on one such non-traditional consumer group: the water resources managers/staff in developing nations of South Asia. Using real-world examples on applications and hands-on-training to make a satellite based flood forecasting system operational, the talk will dissect the view that is shared by many water managers of Bangladesh on satellite remote sensing for day to day decision making. The talk will share the experience and wisdom generated in the successful capacity building of emerging satellite technology for water management. It will end with an overview of initiatives for more effective promotion of the value of planned water cycle satellite missions for water resources management community in the developing world.

  1. Understanding sources of uncertainty in flash-flood forecasting for semi-arid regions 1913

    Technology Transfer Automated Retrieval System (TEKTRAN)

    About one-third of the earth’s landsurface is located in arid or semi-arid regions, often in areas suffering severely from the negative impacts of desertification and population pressure. Reliable hydrological forecasts across spatial and temporal scales are crucial in order to achieve water securit...

  2. Development of flood profiles and flood-inundation maps for the Village of Killbuck, Ohio

    USGS Publications Warehouse

    Ostheimer, Chad J.

    2013-01-01

    Digital flood-inundation maps for a reach of Killbuck Creek near the Village of Killbuck, Ohio, were created by the U.S. Geological Survey (USGS), in cooperation with Holmes County, Ohio. The inundation maps depict estimates of the areal extent of flooding corresponding to water levels (stages) at the USGS streamgage Killbuck Creek near Killbuck (03139000) and were completed as part of an update to Federal Emergency Management Agency Flood-Insurance Study. The maps were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning system that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. The digital maps also have been submitted for inclusion in the data libraries of the USGS interactive Flood Inundation Mapper. Data from the streamgage can be used by emergency-management personnel, in conjunction with the flood-inundation maps, to help determine a course of action when flooding is imminent. Flood profiles for selected reaches were prepared by calibrating a steady-state step-backwater model to an established streamgage rating curve. The step-backwater model then was used to determine water-surface-elevation profiles for 10 flood stages at the streamgage with corresponding streamflows ranging from approximately the 50- to 0.2-percent annual exceedance probabilities. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas.

  3. National Air Quality Forecast Capability: Status and Research Needs

    NASA Astrophysics Data System (ADS)

    Stajner, I.; McQueen, J.; Lee, P.; Draxler, R. R.; Tong, D.; Pan, L.; Huang, J. P.; Shafran, P.; Dickerson, P.; Upadhayay, S.

    2014-12-01

    Operational air quality predictions for the United States (U. S.) are provided by National Air Quality Forecasting Capability (NAQFC), which is being built by NOAA in partnership with the U.S. EPA. NAQFC provides nationwide operational predictions of ozone, smoke from wildfires, as well as dust from dust storms for the contiguous 48 states. Predictions are produced beyond midnight of the following day at 12 km resolution and 1 hour time intervals and distributed at http://airquality.weather.gov. Ozone predictions and developmental testing of aerosol predictions combine the NOAA National Centers for Environmental Prediction (NCEP) operational North American Mesoscale (NAM) weather predictions with the Community Multiscale Air Quality (CMAQ) model. Predictions of smoke and dust storms use the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Routine verification of ozone and developmental aerosol predictions relies on AIRNow observations, whereas smoke and dust predictions rely on satellite retrievals. Recent updates to operational ozone prediction at NOAA have focused on mobile emissions, which were updated using the projections of mobile sources for 2012. Satellite and ground observations were used to derive NOx trends, which were compared with the emissions data used by NAQFC indicating improved agreement over large metropolitan areas in the US. Updates to the chemical mechanism are being tested for operational implementation. Recent testing of PM2.5 predictions is relying on National Emission Inventory (NEI) inputs augmented by real time sources from wildfires and dust storms. Testing of PM2.5 predictions continues to exhibit seasonal biases - overprediction in the winter and underprediction in the summer. Current efforts are focusing on inclusion of bias correction and development of linkages with global atmospheric composition predictions.

  4. Hydrological modelling for flood forecasting: Calibrating the post-fire initial conditions

    NASA Astrophysics Data System (ADS)

    Papathanasiou, C.; Makropoulos, C.; Mimikou, M.

    2015-10-01

    Floods and forest fires are two of the most devastating natural hazards with severe socioeconomic, environmental as well as aesthetic impacts on the affected areas. Traditionally, these hazards are examined from different perspectives and are thus investigated through different, independent systems, overlooking the fact that they are tightly interrelated phenomena. In fact, the same flood event is more severe, i.e. associated with increased runoff discharge and peak flow and decreased time to peak, if it occurs over a burnt area than that occurring over a land not affected by fire. Mediterranean periurban areas, where forests covered with flammable vegetation coexist with agricultural land and urban zones, are typical areas particularly prone to the combined impact of floods and forest fires. Hence, the accurate assessment and effective management of post-fire flood risk becomes an issue of priority. The research presented in this paper aims to develop a robust methodological framework, using state of art tools and modern technologies to support the estimation of the change in time of five representative hydrological parameters for post-fire conditions. The proposed methodology considers both longer- and short-term initial conditions in order to assess the dynamic evolution of the selected parameters. The research focuses on typical Mediterranean periurban areas that are subjected to both hazards and concludes with a set of equations that associate post-fire and pre-fire conditions for five Fire Severity (FS) classes and three soil moisture states. The methodology has been tested for several flood events on the Rafina catchment, a periurban catchment in Eastern Attica (Greece). In order to validate the methodology, simulated hydrographs were produced and compared against available observed data. Results indicate a close convergence of observed and simulated flows. The proposed methodology is particularly flexible and thus easily adaptable to catchments with similar hydrometeorological and geomorphological features.

  5. Observing and real-time evaluating of snow cover for flood forecasting service in the Czech Republic

    NASA Astrophysics Data System (ADS)

    Bercha, S.; Cekal, R.; Danhelka, J.; Ricicova, P.

    2009-04-01

    Snow cover accumulation and melting is a significant part of the hydrological cycle in the central Europe. Rapid snow melting combined with rainfall in spring caused many historical floods in the Czech Republic like disastrous floods in 1784, 1845, 1940 or most recently 2006. But estimation of water content in snow cover is important also for reservoir operation and planning, because spring melting donates reservoirs for water supply during the rest of the year. Therefore snow cover measurement and real-time evaluation is a significant part of the operational hydrological forecasting service. There are about 400 gauges providing weekly (Monday) measurements of snow depth (SD) and snow water equivalent (SWE) in the Czech Republic. Data are collected by forecasting offices of Czech Hydrometeorological Institute and stored in operational database CLIDATA. Besides that comparative measurements of SD and SWE for open space and forest are made in the network of 20 profiles. Evaluation of snow water amount in important basins (especially those of large reservoirs) is made within CLIDATA-GIS module. Data are interpolated in space using orographical dependent interpolation method. As there is usually no continuous snow cover in the Czech Republic linear interpolation fails to reflect reality if it interpolates between zero and non zero values on the mountain slopes. Therefore the regular (3 km) network of pseudo gauges was design. During interpolation hydrologist manually defines the altitude of actual snow line. Based on that, pseudo gauges below defined threshold are set equal to 0, while gauges above the threshold are not taken into account during the interpolation. Testing of accounting for differences in snow cover in open space and forest is under development to be implemented into computation procedure next winter season. Output 500 m grid is used to compute the total amount of snow and average SWE for the network of more than 90 basins. Data are provided to River Authorities, who operate reservoir, and other users. SWE data are also used for verification of states (computed SWE) in hydrological models used for real-time forecasting in the Czech Republic. Comparison to the original method of computing snow cover amount (using simply averages of station observation in 100 elevation zones average for 14 basins in the Czech Republic) proved applicability of the method.

  6. Real time flood forecasting in the Nan Basin, Thailand, by using a distributed Xin'anjiang Model

    NASA Astrophysics Data System (ADS)

    Chen, Xiaohong; Qiu, Xiaobin

    2015-04-01

    Taking Nan basin in Thailand as a research case, on the basis of DEM, this paper extracts the digital information of Nan basin and divides it into ten sub-basins, considering the land usage and terrain distribution, to construct the distributed Xinanjiang model. Before the model simulation, various digital basin information is established involving elevation matrix, river net matrix, direction matrix and so on. The three-water-source Xinanjiang model is adopted in the grids to calculate the runoff yield under a specific precipitation in grids, and then all the water flows of the grids are convoluted to the sub-basin's outlet to synthesize the runoff process of a subbasin. Eventually the subbasin runoff is routed to the basin outlet to obtain runoff process of the whole basin with real-time correction. The model parameters are calibrated by using the trial and error method. The sensitivity and uncertainty of the parameters are analyzed. The main achievements of this paper are as follows. (1) The basin information is extracted and the digital NAN basin is constructed on the basis of DEM data. As a result, a series of basin information matrix and digital Nan basin are generated. (2) The constant flow in grids and isochrones concept are used to replace the unit hydrograph of sub-basins. The basin discharge process is obtained through calculating the grid runoff yield and subbasin runoff convolution and routing the subbasin runoffs to the basin outlet. (3) The model is calibrated on more than 50 historical flood processes. The sensitivity and uncertainty of model parameters are analyzed by the perturbation analysis method, showing that some parameters, including KC, KKG, KKSS, WUM, KG, WLM, KSS and WDM are more sensitive. At the same time, the model uncertainty is analyed by the GLUE method and the results illustrate that the simulation effect depends on the values of parameter group while the observed runoff is in the uncertainty range. (4) The calculated discharge process is adaptively corrected by Attenuation memory least squares method to obtain final forecasting flood process. Verifications of this real-time flood forecasting model show high precision and the model system has been practically used in Thailand.

  7. IMPROVING NATIONAL AIR QUALITY FORECASTS WITH SATELLITE AEROSOL OBSERVATIONS

    EPA Science Inventory

    Air quality forecasts for major US metropolitan areas have been provided to the public through a partnership between the US Environmental Protection Agency and state and local air agencies since 1997. Recent years have witnessed improvement in forecast skill and expansion of fore...

  8. Seasonal Drought Prediction in East Africa: Can National Multi-Model Ensemble Forecasts Help?

    NASA Technical Reports Server (NTRS)

    Shukla, Shraddhanand; Roberts, J. B.; Funk, Christopher; Robertson, F. R.; Hoell, Andrew

    2014-01-01

    The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. As recently as in 2011 part of this region underwent one of the worst famine events in its history. Timely and skillful drought forecasts at seasonal scale for this region can inform better water and agro-pastoral management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts. However seasonal drought prediction in this region faces several challenges. Lack of skillful seasonal rainfall forecasts; the focus of this presentation, is one of those major challenges. In the past few decades, major strides have been taken towards improvement of seasonal scale dynamical climate forecasts. The National Centers for Environmental Prediction's (NCEP) National Multi-model Ensemble (NMME) is one such state-of-the-art dynamical climate forecast system. The NMME incorporates climate forecasts from 6+ fully coupled dynamical models resulting in 100+ ensemble member forecasts. Recent studies have indicated that in general NMME offers improvement over forecasts from any single model. However thus far the skill of NMME for forecasting rainfall in a vulnerable region like the East Africa has been unexplored. In this presentation we report findings of a comprehensive analysis that examines the strength and weakness of NMME in forecasting rainfall at seasonal scale in East Africa for all three of the prominent seasons for the region. (i.e. March-April-May, July-August-September and October-November- December). Simultaneously we also describe hybrid approaches; that combine statistical approaches with NMME forecasts; to improve rainfall forecast skill in the region when raw NMME forecasts lack in skill.

  9. Seasonal Drought Prediction in East Africa: Can National Multi-Model Ensemble Forecasts Help?

    NASA Technical Reports Server (NTRS)

    Shukla, Shraddhanand; Roberts, J. B.; Funk, Christopher; Robertson, F. R.; Hoell, Andrew

    2015-01-01

    The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. As recently as in 2011 part of this region underwent one of the worst famine events in its history. Timely and skillful drought forecasts at seasonal scale for this region can inform better water and agro-pastoral management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts. However seasonal drought prediction in this region faces several challenges. Lack of skillful seasonal rainfall forecasts; the focus of this presentation, is one of those major challenges. In the past few decades, major strides have been taken towards improvement of seasonal scale dynamical climate forecasts. The National Centers for Environmental Prediction's (NCEP) National Multi-model Ensemble (NMME) is one such state-of-the-art dynamical climate forecast system. The NMME incorporates climate forecasts from 6+ fully coupled dynamical models resulting in 100+ ensemble member forecasts. Recent studies have indicated that in general NMME offers improvement over forecasts from any single model. However thus far the skill of NMME for forecasting rainfall in a vulnerable region like the East Africa has been unexplored. In this presentation we report findings of a comprehensive analysis that examines the strength and weakness of NMME in forecasting rainfall at seasonal scale in East Africa for all three of the prominent seasons for the region. (i.e. March-April-May, July-August-September and October-November- December). Simultaneously we also describe hybrid approaches; that combine statistical approaches with NMME forecasts; to improve rainfall forecast skill in the region when raw NMME forecasts lack in skill.

  10. Coupling Green-Ampt infiltration method and two-dimensional kinematic wave theory for flood forecast in semi-arid catchment

    NASA Astrophysics Data System (ADS)

    Wang, L.-L.; Chen, D.-H.; Li, Z.-J.; Zhao, L.-N.

    2011-08-01

    Due to the specific characteristics of semi-arid catchments, this paper aims to establish a grid-and-Green-Ampt-and-two-dimensional-kinematic-wave-based distributed hydrological physical model (Grid-GA-2D model) coupling Green-Ampt infiltration method and two dimensional overland flow routing model based on kinematic wave theory for flood simulation and forecasting with using GIS technology and digital elevation model (DEM). Taking into consideration the soil moisture redistribution at hillslope, Green-Ampt infiltration physical method is applied for grid-based runoff generation and two-dimensional implicit finite difference kinematic wave model is introduced to solve depressions water storing for grid-based overland flow concentration routing in the Grid-GA-2D model. The Grid-GA-2D model, the Grid-GA model with coupling Green-Ampt infiltration method and one-dimension kinematic wave theory, and Shanbei model were employed to the upper Kongjiapo catchment in Qin River, a tributary of the Yellow River, with an area of 1454 km2 for flood simulation. Results show that two grid-based distributed hydrological models perform better in flood simulation and can be used for flood forecasting in semi-arid catchments. Comparing with the Grid-GA model, the flood peak simulation accuracy of the newly developed model is higher.

  11. Skill Assessment of National Multi-Model Ensemble Forecasts for Seasonal Drought Prediction in East Africa

    NASA Astrophysics Data System (ADS)

    Shukla, S.; Hoell, A.; Roberts, J. B.; Funk, C. C.; Robertson, F. R.

    2014-12-01

    The increasing food and water demands of East Africa's growing population are stressing the region's inconsistent water resources and rain-fed agriculture. As recently as 2011, part of this region underwent one of the worst famine events in its history. Timely and skillful drought forecasts at a seasonal scale for this region can inform better water and agro-pastoral management decisions, support optimal allocation of the region's water resources, and mitigate socio-economic losses incurred by droughts. However, seasonal drought prediction in this region faces several challenges including lack of skillful seasonal rainfall forecasts. The National Multi-model Ensemble (NMME); a state-of-the-art dynamical climate forecast system is potentially a promising tool for drought prediction in this region. The NMME incorporates climate forecasts from 6+ fully coupled dynamical models resulting in 100+ forecasts ensemble members. Recent studies have indicated that in general NMME offers improvement over forecasts from any of the individual model. However, thus far the skill of NMME for forecasting rainfall in a vulnerable region like East Africa has largely been unexplored. In this presentation we report findings of a comprehensive analysis that examines the strength and weakness of NMME in forecasting rainfall at seasonal scale in East Africa for all three of the prominent seasons of the region. (i.e. March-April-May, July-August-September, and October-November-December). Additionally we describe a hybrid approach that combines statistical method with NMME forecasts to improve rainfall forecast skill in the region when raw NMME forecasts skill is lacking. This approach uses constructed analog method to improve NMME's March-April-May rainfall forecast skill in East Africa.

  12. Towards real-time flood forecasting in hydraulics: merits of in situ discharge and water level data assimilation for the modeling of the Marne catchment in France

    NASA Astrophysics Data System (ADS)

    Ricci, S. M.; Habert, J.; Le Pape, E.; Piacentini, A.; Jonville, G.; Thual, O.; Zaoui, F.

    2011-12-01

    The present study describes the assimilation of river flow and water level observations and the resulting improvement in flood forecasting. The Kalman Filter algorithm was built on top of the one-dimensional hydraulic model, MASCARET, [1] which describes the Saint-Venant equations. The assimilation algorithm folds in two steps: the first one was based on the assumption that the upstream flow can be adjusted using a three-parameter correction; the second one consisted of directly correcting the hydraulic state. This procedure was previously applied on the Adour Maritime Catchment using water level observations [2]. On average, it was shown that the data assimilation procedure enables an improvement of 80% in the simulated water level over the reanalysis period, 60 % in the forecast water level at a one-hour lead time, and 25% at a twelve-hour lead time. The procedure was then applied on the Marne Catchment, which includes karstic tributaries, located East of the Paris basin, characterized by long flooding periods and strong sensitivity to local precipitations. The objective was to geographically extend and improve the existing model used by the flood forecasting service located in Chalons-en-Champagne. A hydrological study first enabled the specification of boundary conditions (upstream flow or lateral inflow), then the hydraulic model was calibrated using in situ discharge data (adjustment of Strickler coefficients or cross sectional geometry). The assimilation of water level data enabled the reduction of the uncertainty in the hydrological boundary conditions and led to significant improvement of the simulated water level in re-analysis and forecast modes. Still, because of errors in the Strickler coefficients or cross section geometry, the improvement of the simulated water level sometimes resulted in a degradation of discharge values. This problem was overcome by controlling the correction of the hydrological boundary conditions by directly assimilating discharge observations rather than water level observations. As this approach leads to a satisfying simulation of flood events in the Marne catchment in re-analysis and forecast mode, ongoing work aims at controlling Strickler coefficients through data assimilation procedures in order to simultaneously improve the water level and discharge state. [1] N. Goutal, F. Maurel: A finite volume solver for 1D shallow water equations applied to an actual river, Int. J. Numer. Meth. Fluids, 38(2), 1--19, 2002. [2] S. Ricci, A. Piacentini, O. Thual, E. Le Pape, G. Jonville, 2011: Correction of upstream flow and hydraulic state with data assimilation on the context of flood forecasting. Submitted to Hydrol. Earth Syst. Sci, In review.

  13. Comparison of Agricultural Seed Loss in Flooded and Unflooded Fields on the Tennessee National

    E-print Network

    Gray, Matthew

    National Wildlife Refuge Melissa A. Foster, Matthew J. Gray,* Craig A. Harper, Johnathan G. Walls M agricultural field vs. seed submersed in a flooded field on the Tennessee National Wildlife Refuge from October on the Tennessee National Wildlife Refuge. Journal of Fish and Wildlife Management 1(1):43­46; e1944-687X. doi: 10

  14. Performance and robustness of probabilistic river forecasts computed with quantile regression based on multiple independent variables

    NASA Astrophysics Data System (ADS)

    Hoss, F.; Fischbeck, P. S.

    2015-09-01

    This study applies quantile regression (QR) to predict exceedance probabilities of various water levels, including flood stages, with combinations of deterministic forecasts, past forecast errors and rates of water level rise as independent variables. A computationally cheap technique to estimate forecast uncertainty is valuable, because many national flood forecasting services, such as the National Weather Service (NWS), only publish deterministic single-valued forecasts. The study uses data from the 82 river gauges, for which the NWS' North Central River Forecast Center issues forecasts daily. Archived forecasts for lead times of up to 6 days from 2001 to 2013 were analyzed. Besides the forecast itself, this study uses the rate of rise of the river stage in the last 24 and 48 h and the forecast error 24 and 48 h ago as predictors in QR configurations. When compared to just using the forecast as an independent variable, adding the latter four predictors significantly improved the forecasts, as measured by the Brier skill score and the continuous ranked probability score. Mainly, the resolution increases, as the forecast-only QR configuration already delivered high reliability. Combining the forecast with the other four predictors results in a much less favorable performance. Lastly, the forecast performance does not strongly depend on the size of the training data set but on the year, the river gauge, lead time and event threshold that are being forecast. We find that each event threshold requires a separate configuration or at least calibration.

  15. Avalanche Forecasting for Transportation Corridor and Backcountry in Glacier National Park (BC, Canada)

    E-print Network

    Smith, Dan

    Avalanche Forecasting for Transportation Corridor and Backcountry in Glacier National Park (BC, 2500 University Drive NW Calgary AB T2N 1N4, Canada David Skjonsberg Avalanche Control, Mt. Revelstoke and Glacier National Parks, PO Box 350 Revelstoke BC V0E 2S0, Canada ABSTRACT. The Avalanche Control Section

  16. A real-time flood forecasting and simulation system based on GIS and DEM: Analysis of sensitivity to scale factors

    NASA Astrophysics Data System (ADS)

    Garcia, Sandra G.

    The hydrometeorological telemetric networks in real time interrelated with weather forecasting and rainfall information obtained from remote sensing, constitute real forecasting and protection instruments in the event of flash flooding, so typical of semiarid environments. In this Thesis, spatial analysis approached with functions embedded in a Geographical Information System (GIS) are proposed. The aims are: (a) To combine efficiently information from different sources (telemetric networks and radar-satellite technology). (b) To develop methodology of application of spatially distributed and hybrid hydrologic models, which are topographically based and event-oriented. (c) To extract automatically from Digital Elevation Models (DEM) the relevant parameters of the hydrologic models used. When extracting the drainage networks from a DEM, various questions arise: what is the most suitable drainage density for the hydrographic network? What degree of affection does the selection of DEM cell size have on the hydrologic results, or are they not sensitive to it? Can any invariable property by defined with the scale which characterizes indexes or parameters based on the drainage network hierarchy? A clear inter-relationship can be seen between the geomorphological and hydrologic parameters and the DEM resolution. The morphometric parameters are also affected by threshold area variation. It is proposed a methodology to identify a priori the range of DEM resolutions and threshold areas for in which the parameters present a certain stability for modelling based on drainage networks topology. When working with spatially distributed models, several questions crop up: Are the distributed parameters derived from DEM and the complete hydrologic results affected by cell size? Is it feasible to identify invariable properties with the scale which characterizes the spatial distributions of the parameters? The terrain slope and the flow path length are affected by the DEM cell-size adopted. The spatially distributed flow velocity presents invariance properties with the DEM scale, founded on the behaviour of the cumulative drainage area distribution curve. Thus, the hydrographs simulated by means of distributed UH models, present slight sensitivity to the DEM cell size. Scale exponents, invariable with DEM resolution, of power distributions which characterize the behaviour of certain distributed parameters, have been identified.

  17. Queensland River BasinsQueensland River Basins and Weather Forecast Districtsand Weather Forecast Districts

    E-print Network

    Greenslade, Diana

    Queensland River BasinsQueensland River Basins and Weather Forecast Districtsand Weather Forecast Penninsula (1) Weather forecast district, name and number. #12; Districts Map Produced by Flood Forecasting and Warning Services, Bureau of Meteorology, Brisbane Note

  18. Application of quantitative precipitation forecasting and precipitation ensemble prediction for hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Tao, P.; Tie-Yuan, S.; Zhi-Yuan, Y.; Jun-Chao, W.

    2015-05-01

    The precipitation in the forecast period influences flood forecasting precision, due to the uncertainty of the input to the hydrological model. Taking the ZhangHe basin as the example, the research adopts the precipitation forecast and ensemble precipitation forecast product of the AREM model, uses the Xin Anjiang hydrological model, and tests the flood forecasts. The results show that the flood forecast result can be clearly improved when considering precipitation during the forecast period. Hydrological forecast based on Ensemble Precipitation prediction gives better hydrological forecast information, better satisfying the need for risk information for flood prevention and disaster reduction, and has broad development opportunities.

  19. Concern about Forecasts of National Faculty Shortages and the Importance of Local Studies.

    ERIC Educational Resources Information Center

    Shatman, Steve; Jung, Loren

    1992-01-01

    A local study of faculty attrition in a four-campus university system examined two factors not considered in national studies: discipline and campus location (urban or rural). Lack of forecasted increases in local demand for faculty puts into question whether special action to increase faculty supply is needed. (MSE)

  20. Evaluation of a physics-based distributed hydrologic model for flood forecasting

    NASA Astrophysics Data System (ADS)

    Vieux, Baxter E.; Cui, Zhengtao; Gaur, Anubhav

    2004-10-01

    A fully distributed, physics-based rainfall-runoff model called r.water.fea is applied within the Distributed Model Inter-comparison Project (DMIP) organized by the US National Weather Service. Simulations are performed for two basins, the Illinois River and Blue River in Oklahoma. The r.water.fea model is an event-based model that derives parameters and is calibrated using geospatial data. Longstanding research on the Blue and Illinois River basins resulted in a calibrated model using eight events. In order to draw statistical comparisons, the number of events was augmented for the purposes of DMIP. Model performance is evaluated for the Blue and Illinois for the initial and augmented set of storm events. An important finding related to the stability of calibrated parameters from the original 8 to 18-event storm series was observed. As more events were added to expand the number of storms, parameter values changed only slightly. Beyond the calibration phase, a verification period was also used to test the validity of the calibrated parameters. Consistent results were found between the calibration and verification period. In fact prediction accuracy was better in some cases during the verification period, which adds to the confidence in the calibrated model predictions and the methodology. Interior points are used to identify internal model consistency and achievable accuracy. At the interior points located at Watts and Savoy, predictions were biased at Savoy but had better R2 values than obtained at Tahlequah in terms of volume and peak. Watts had comparable bias and nearly identical prediction accuracy compared to Tahlequah. During the verification period for the Blue and Illinois, volume predictions had an accuracy of RMSE=17 and 19 mm. Peak discharge in the two basins was predicted with an accuracy of RMSE=105 and 292 m 3/s, respectively. Closer agreement in volume than peak or timing was found in both watersheds, which may indicate the need for improved channel characteristics and routing. The peak discharge predictions achieved by this model in the Illinois during the verification period are biased towards over-prediction by 16% with an R2 of 0.716. Peak discharge prediction accuracy in the Blue River during the verification period is biased towards under-prediction by 13% with an R2 of 0.438. The performance demonstrates that geospatial data may be used to parameterize and calibrate a fully distributed physics-based model, and is capable of making reliable predictions at the outlet and at some interior points.

  1. 78 FR 14315 - Notice of Chargeable Rates Under the National Flood Insurance Program for Non-Primary Residences

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-05

    ... SECURITY Federal Emergency Management Agency Notice of Chargeable Rates Under the National Flood Insurance... National Flood Insurance Program for non-primary residences. DATES: The rates announced in this notice are... (202) 6463419. SUPPLEMENTARY INFORMATION: Pursuant to section 100205 of the Biggert- Waters...

  2. Analysis of Flood Hazards for the Materials and Fuels Complex at the Idaho National Laboratory Site

    SciTech Connect

    Skaggs, Richard; Breithaupt, Stephen A.; Waichler, Scott R.; Kim, Taeyun; Ward, Duane L.

    2010-11-01

    Researchers at Pacific Northwest National Laboratory conducted a flood hazard analysis for the Materials and Fuels Complex (MFC) site located at the Idaho National Laboratory (INL) site in southeastern Idaho. The general approach for the analysis was to determine the maximum water elevation levels associated with the design-basis flood (DBFL) and compare them to the floor elevations at critical building locations. Two DBFLs for the MFC site were developed using different precipitation inputs: probable maximum precipitation (PMP) and 10,000 year recurrence interval precipitation. Both precipitation inputs were used to drive a watershed runoff model for the surrounding upland basins and the MFC site. Outflows modeled with the Hydrologic Engineering Centers Hydrologic Modeling System were input to the Hydrologic Engineering Centers River Analysis System hydrodynamic flood routing model.

  3. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... requirements of this Plan. (b) Financial Control Plan. (1) The WYO Companies are subject to audit, examination... Program B Appendix B to Part 62 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY... INSURANCE AND ADJUSTMENT OF CLAIMS Pt. 62, App. B Appendix B to Part 62—National Flood Insurance Program...

  4. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... requirements of this Plan. (b) Financial Control Plan. (1) The WYO Companies are subject to audit, examination... Program B Appendix B to Part 62 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY... INSURANCE AND ADJUSTMENT OF CLAIMS Pt. 62, App. B Appendix B to Part 62—National Flood Insurance Program...

  5. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... requirements of this Plan. (b) Financial Control Plan. (1) The WYO Companies are subject to audit, examination... Program B Appendix B to Part 62 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY... INSURANCE AND ADJUSTMENT OF CLAIMS Pt. 62, App. B Appendix B to Part 62—National Flood Insurance Program...

  6. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... requirements of this Plan. (b) Financial Control Plan. (1) The WYO Companies are subject to audit, examination... Program B Appendix B to Part 62 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY... INSURANCE AND ADJUSTMENT OF CLAIMS Pt. 62, App. B Appendix B to Part 62—National Flood Insurance Program...

  7. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... requirements of this Plan. (b) Financial Control Plan. (1) The WYO Companies are subject to audit, examination... Program B Appendix B to Part 62 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY... INSURANCE AND ADJUSTMENT OF CLAIMS Pt. 62, App. B Appendix B to Part 62—National Flood Insurance Program...

  8. 75 FR 69096 - Public Meetings of National Flood Insurance Program (NFIP) Reform Effort

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-10

    ...) Reform Effort AGENCY: Federal Emergency Management Agency, DHS. ACTION: Announcement of public meetings. SUMMARY: This notice announces two public meetings of the National Flood Insurance Program (NFIP) Reform.... To this end, FEMA has engaged in a comprehensive reform effort to address the concerns of the...

  9. 75 FR 71136 - Public Meetings of National Flood Insurance Program (NFIP) Reform Effort; Correction

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-22

    ... in the Federal Register on November 10, 2010 (75 FR 69096), announcing two public meetings. The...) Reform Effort; Correction AGENCY: Federal Emergency Management Agency, DHS. ACTION: Announcement of... the National Flood Insurance Program (NFIP) Reform Effort. In performing its mission, FEMA believes...

  10. THE NOAA - EPA NATIONAL AIR QUALITY FORECASTING SYSTEM

    EPA Science Inventory

    Building upon decades of collaboration in air pollution meteorology research, in 2003 the National Oceanic and Atmospheric Administration (NOAA) and the United States Environmental Protection Agency (EPA) signed formal partnership agreements to develop and implement an operationa...

  11. Effects of forcing uncertainties in the improvement skills of assimilating satellite soil moisture retrievals into flood forecasting models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Floods have negative impacts on society, causing damages in infrastructures and industry, and in the worst cases, causing loss of human lives. Thus early and accurate warning is crucial to significantly reduce the impacts on public safety and economy. Reliable flood warning can be generated using ...

  12. Aiming towards improved flood forecasting: Identification of an adequate model structure for a semi-arid and data-scarce region

    NASA Astrophysics Data System (ADS)

    Pilz, Tobias; Francke, Till; Bronstert, Axel

    2015-04-01

    A lot of effort has already been put into the development of forecasting systems to warn people of approaching flood events. Such systems, however, are influenced by various sources of uncertainty which constrain the skill of forecasts. The main goal of this study is the identification, quantification and reduction of uncertainties to provide improved early warnings with adequate lead times in a data-scarce region with strong seasonality of the hydrological regime. This includes the setup of hydrological models and post-processing of simulation results by mathematical means such as data assimilation. The focus area is the Jaguaribe watershed in northeastern Brazil. The region is characterized by a seasonal climate with strong inter-annual variation and recurrent droughts. To ensure a secure water supply also during the dry season several thousand small and some large reservoirs have been constructed. On the other hand, floods caused by heavy rain events are an issue as well. This topic, however, so far has hardly been considered by the scientific community and until today no flood forecasting system exists for that region. To identify the most appropriate model structure for the catchment the process-based hydrological model for semi-arid environments WASA was implemented into the eco-hydrological simulation environment ECHSE. The environment consists of a generic part providing data types and simulation methods, and a problem-specific part where the user can implement different model formulations. This provides the possibility to test various process realisations under consistent input and output data structures. The most appropriate model structure can then be determined by statistical means such as Bayesian model averaging. Subsequently, forecast results may be updated by post-processing and/or data assimilation. Furthermore, methods of data fusion can be used to combine measurements of different quality and resolution, such as in-situ and remotely sensed data, and reduce uncertainties in input data and boundary conditions of the model and in the data assimilation procedure. In this contribution the setup of the simulation environment and identification of an appropriate model structure for a meso-scale and data-scarce region in a semi-arid environment is presented.

  13. PROFS to hone local storm forecasts

    NASA Astrophysics Data System (ADS)

    Richman, Barbara T.

    Short-range forecasting of local tornadoes, flash floods, blizzards, and other severe storms is at best a tangle of myriad pieces of weather data, intricate processing of the data, careful interpretation of the results, and effective and rapid dissemination of the appropriate information; and because accuracy matters, the job becomes Herculean. A prototype program within the National Oceanic and Atmospheric Administration (NOAA) has shouldered the task of developing a systematic way to look at weather information and of translating it into operational forecasts for local, severe storms occurring within the proceeding 24 hours.The Prototype Regional Observing and Forecasting Service (PROFS), underway at NOAA's Environmental Research Laboratories in Boulder, Colo., mixes and matches an assortment of techniques used to gather and analyze weather data to see which combination yields the most accurate forecast. PROFS is a cooperative program between the National Weather Service, the National Environmental Satellite Service, and the Environmental Research Laboratories.

  14. Configuring the HYSPLIT Model for National Weather Service Forecast Office and Spaceflight Meteorology Group Applications

    NASA Technical Reports Server (NTRS)

    Dreher, Joseph; Blottman, Peter F.; Sharp, David W.; Hoeth, Brian; Van Speybroeck, Kurt

    2009-01-01

    The National Weather Service Forecast Office in Melbourne, FL (NWS MLB) is responsible for providing meteorological support to state and county emergency management agencies across East Central Florida in the event of incidents involving the significant release of harmful chemicals, radiation, and smoke from fires and/or toxic plumes into the atmosphere. NWS MLB uses the National Oceanic and Atmospheric Administration Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to provide trajectory, concentration, and deposition guidance during such events. Accurate and timely guidance is critical for decision makers charged with protecting the health and well-being of populations at risk. Information that can describe the geographic extent of areas possibly affected by a hazardous release, as well as to indicate locations of primary concern, offer better opportunity for prompt and decisive action. In addition, forecasters at the NWS Spaceflight Meteorology Group (SMG) have expressed interest in using the HYSPLIT model to assist with Weather Flight Rules during Space Shuttle landing operations. In particular, SMG would provide low and mid-level HYSPLIT trajectory forecasts for cumulus clouds associated with smoke plumes, and high-level trajectory forecasts for thunderstorm anvils. Another potential benefit for both NWS MLB and SMG is using the HYSPLIT model concentration and deposition guidance in fog situations.

  15. Long-term trends in flood fatalities in the United State

    NASA Astrophysics Data System (ADS)

    Sharif, Hatim; Chaturvedi, Smita

    2015-04-01

    This presentation reviews flood-related fatalities in the United States between 1959 and 2013. Information on flood fatality victims and the flood-causing events was obtained from the National Climatic Data Center. The data collected included the date, time, location, and weather conditions and the gender and age of the flood victims. Long term trends in the numbers of fatalities and fatality rates were analyzed. For most of the states fatalities were largely caused by single catastrophic events. The analysis indicates that the standardized annual flood fatality rates are decreasing significantly for all states. Vehicle related fatalities represent more than 50% of flood fatalities for most of the states and can be as high as 77%. A combination of improved hydrometeorological forecasting, educational programs aimed at enhancing public awareness of flood risk and the seriousness of flood warnings, and timely and appropriate action by local emergency and safety authorities will help further reduce flood fatalities in Texas.

  16. On the use of wave parameterizations and a storm impact scaling model in National Weather Service Coastal Flood and decision support operations

    USGS Publications Warehouse

    Mignone, Anthony; Stockdon, H.; Willis, M.; Cannon, J.W.; Thompson, R.

    2012-01-01

    National Weather Service (NWS) Weather Forecast Offices (WFO) are responsible for issuing coastal flood watches, warnings, advisories, and local statements to alert decision makers and the general public when rising water levels may lead to coastal impacts such as inundation, erosion, and wave battery. Both extratropical and tropical cyclones can generate the prerequisite rise in water level to set the stage for a coastal impact event. Forecasters use a variety of tools including computer model guidance and local studies to help predict the potential severity of coastal flooding. However, a key missing component has been the incorporation of the effects of waves in the prediction of total water level and the associated coastal impacts. Several recent studies have demonstrated the importance of incorporating wave action into the NWS coastal flood program. To follow up on these studies, this paper looks at the potential of applying recently developed empirical parameterizations of wave setup, swash, and runup to the NWS forecast process. Additionally, the wave parameterizations are incorporated into a storm impact scaling model that compares extreme water levels to beach elevation data to determine the mode of coastal change at predetermined “hotspots” of interest. Specifically, the storm impact model compares the approximate storm-induced still water level, which includes contributions from tides, storm surge, and wave setup, to dune crest elevation to determine inundation potential. The model also compares the combined effects of tides, storm surge, and the 2 % exceedance level for vertical wave runup (including both wave setup and swash) to dune toe and crest elevations to determine if erosion and/or ocean overwash may occur. The wave parameterizations and storm impact model are applied to two cases in 2009 that led to significant coastal impacts and unique forecast challenges in North Carolina: the extratropical “Nor'Ida” event during 11-14 November and the large swell event from distant Hurricane Bill on 22 August. The coastal impacts associated with Nor'Ida were due to the combined effects of surge, tide, and wave processes and led to an estimated 5.8 million dollars in damage. While the impacts from Hurricane Bill were not as severe as Nor'Ida, they were mainly associated with wave processes. Thus, this event exemplifies the importance of incorporating waves into the total water level and coastal impact prediction process. These examples set the stage for potential future applications including adaption to the more complex topography along the New England coast.

  17. Calibration and evaluation of a flood forecasting system: Utility of numerical weather prediction model, data assimilation and satellite-based rainfall

    NASA Astrophysics Data System (ADS)

    Yucel, I.; Onen, A.; Yilmaz, K. K.; Gochis, D. J.

    2015-04-01

    A fully-distributed, multi-physics, multi-scale hydrologic and hydraulic modeling system, WRF-Hydro, is used to assess the potential for skillful flood forecasting based on precipitation inputs derived from the Weather Research and Forecasting (WRF) model and the EUMETSAT Multi-sensor Precipitation Estimates (MPEs). Similar to past studies it was found that WRF model precipitation forecast errors related to model initial conditions are reduced when the three dimensional atmospheric data assimilation (3DVAR) scheme in the WRF model simulations is used. A comparative evaluation of the impact of MPE versus WRF precipitation estimates, both with and without data assimilation, in driving WRF-Hydro simulated streamflow is then made. The ten rainfall-runoff events that occurred in the Black Sea Region were used for testing and evaluation. With the availability of streamflow data across rainfall-runoff events, the calibration is only performed on the Bartin sub-basin using two events and the calibrated parameters are then transferred to other neighboring three ungauged sub-basins in the study area. The rest of the events from all sub-basins are then used to evaluate the performance of the WRF-Hydro system with the calibrated parameters. Following model calibration, the WRF-Hydro system was capable of skillfully reproducing observed flood hydrographs in terms of the volume of the runoff produced and the overall shape of the hydrograph. Streamflow simulation skill was significantly improved for those WRF model simulations where storm precipitation was accurately depicted with respect to timing, location and amount. Accurate streamflow simulations were more evident in WRF model simulations where the 3DVAR scheme was used compared to when it was not used. Because of substantial dry bias feature of MPE, as compared with surface rain gauges, streamflow derived using this precipitation product is in general very poor. Overall, root mean squared errors for runoff were reduced by 22.2% when hydrological model calibration is performed with WRF precipitation. Errors were reduced by 36.9% (above uncalibrated model performance) when both WRF model data assimilation and hydrological model calibration was utilized. Our results also indicated that when assimilated precipitation and model calibration is performed jointly, the calibrated parameters at the gauged sites could be transferred to ungauged neighboring basins where WRF-Hydro reduced mean root mean squared error from 8.31 m3/s to 6.51 m3/s.

  18. Appeared in 1991 National Weather Digest, 16 (No. 1), 2-16. A REVIEW FOR FORECASTERS ON THE APPLICATION OF HODOGRAPHS TO

    E-print Network

    Doswell III, Charles A.

    ON THE APPLICATION OF HODOGRAPHS TO FORECASTING SEVERE THUNDERSTORMS Charles A. Doswell III National Severe Storms that it is a waste of time to study the tools of the severe thunderstorm forecasting trade. I contend of hodographs to apply them to severe thunder- storm forecasting. 1. INTRODUCTION With the development

  19. European Flood Awareness System - now operational

    NASA Astrophysics Data System (ADS)

    Alionte Eklund, Cristina.; Hazlinger, Michal; Sprokkereef, Eric; Garcia Padilla, Mercedes; Garcia, Rafael J.; Thielen, Jutta; Salamon, Peter; Pappenberger, Florian

    2013-04-01

    The European Commission's Communication "Towards a Stronger European Union Disaster Response" adopted and endorsed by the Council in 2010, underpins the importance of strengthening concerted actions for natural disasters including floods, which are amongst the costliest natural disasters in the EU. The European Flood Awareness System (EFAS) contributes in the case of major flood events. to better protection of the European Citizen, the environment, property and cultural heritage. The disastrous floods in Elbe and Danube rivers in 2002 confronted the European Commission with non-coherent flood warning information from different sources and of variable quality, complicating planning and organisation of aid. Thus, the Commission initiated the development of a European Flood Awareness System (EFAS) which is now going operational. EFAS has been developed and tested at the Joint Research Centre, the Commission's in house science service, in close collaboration with the National hydrological and meteorological services, European Civil Protection through the Monitoring and Information Centre (MIC) and other research institutes. EFAS provides Pan-European overview maps of flood probabilities up to 10 days in advance as well as detailed forecasts at stations where the National services are providing real time data. More than 30 hydrological services and civil protection services in Europe are part of the EFAS network. Since 2011, EFAS is part of the COPERNICUS Emergency Management Service, (EMS) and is now an operational service since 2012. The Operational EFAS is being executed by several consortia dealing with different operational aspects: • EFAS Hydrological data collection centre —REDIAM and ELIMCO- will be collecting historic and realtime discharge and water levels data in support to EFAS • EFAS Meteorological data collection centre —outsourced but running onsite of JRC Ispra. Will be collecting historic and realtime meteorological data in support to EFAS • EFAS Computational centre - European Centre for Medium-Range Weather Forecasts - will be running the forecasts, post-processing and operating the EFAS-Information System platform • EFAS Dissemination centre—Swedish Meteorological and Hydrological Institute, Slovak Hydrometeorological Institute and Rijkswaterstaat Waterdienst (the Netherlands)—analyse the results on a daily basis, assess the situation, and disseminate information to the EFAS partners The European Commission is responsible for contract management. The Joint Research Centre further provides support for EFAS through research and development. Aims of EFAS operational • added value early flood forecasting products to hydrological services • unique overview products of ongoing and forecast floods in Europe more than 3 days in advance • create a European network of operational hydrological services

  20. Configuring the HYSPLIT Model for National Weather Service Forecast Office and Spaceflight Meteorology Group Applications

    NASA Technical Reports Server (NTRS)

    Dreher, Joseph G.

    2009-01-01

    For expedience in delivering dispersion guidance in the diversity of operational situations, National Weather Service Melbourne (MLB) and Spaceflight Meteorology Group (SMG) are becoming increasingly reliant on the PC-based version of the HYSPLIT model run through a graphical user interface (GUI). While the GUI offers unique advantages when compared to traditional methods, it is difficult for forecasters to run and manage in an operational environment. To alleviate the difficulty in providing scheduled real-time trajectory and concentration guidance, the Applied Meteorology Unit (AMU) configured a Linux version of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) (HYSPLIT) model that ingests the National Centers for Environmental Prediction (NCEP) guidance, such as the North American Mesoscale (NAM) and the Rapid Update Cycle (RUC) models. The AMU configured the HYSPLIT system to automatically download the NCEP model products, convert the meteorological grids into HYSPLIT binary format, run the model from several pre-selected latitude/longitude sites, and post-process the data to create output graphics. In addition, the AMU configured several software programs to convert local Weather Research and Forecast (WRF) model output into HYSPLIT format.

  1. Department of Energy award DE-SC0004164 Climate and National Security: Securing Better Forecasts

    SciTech Connect

    Reno Harnish

    2011-08-16

    The Climate and National Security: Securing Better Forecasts symposium was attended by senior policy makers and distinguished scientists. The juxtaposition of these communities was creative and fruitful. They acknowledged they were speaking past each other. Scientists were urged to tell policy makers about even improbable outcomes while articulating clearly the uncertainties around the outcomes. As one policy maker put it, we are accustomed to making these types of decisions. These points were captured clearly in an article that appeared on the New York Times website and can be found with other conference materials most easily on our website, www.scripps.ucsd.edu/cens/. The symposium, generously supported by the NOAA/JIMO, benefitted the public by promoting scientifically informed decision making and by the transmission of objective information regarding climate change and national security.

  2. Ensemble stream flow predictions using the ECMWF forecasts

    NASA Astrophysics Data System (ADS)

    Kiczko, Adam; Romanowicz, Renata; Osuch, Marzena; Pappenberger, Florian; Karamuz, Emilia

    2015-04-01

    Floods and low flows in rivers are seasonal phenomena that can cause several problems to society. To anticipate high and low flow events, flow forecasts are crucial. They are of particular importance in mountainous catchments, where the lead time of forecasts is usually short. In order to prolong the forecast lead-time, numerical weather predictions (NWPs) are used as a hydrological model driving force. The forecasted flow is commonly given as one value, even though it is uncertain. There is an increasing interest in accounting for the uncertainty in flood early warning and decision support systems. When NWP are given in the form of ensembles, such as the ECMWF forecasts, the uncertainty of these forecasts can be accounted for. Apart from the forecast uncertainty the uncertainty related to the hydrological model used also plays an important role in the uncertainty of the final flow prediction. The aim of this study is the development of a stream flow prediction system for the Bia?a Tarnowska, a mountainous catchment in the south of Poland. We apply two different hydrological models. One is a conceptual HBV model for rainfall-flow predictions, applied within a Generalised Likelihood Uncertainty Estimation (GLUE) framework, the second is a data-based DBM model, adjusted for Polish conditions by adding the Soil Moisture Accounting (SMA) and snow-melt modules. Both models provide the uncertainty of the predictions, but the DBM approach is much more numerically efficient, therefore more suitable for the real-time forecasting.. The ECMWF forecasts require bias reduction in order to correspond to observations. Therefore we applied Quantile Mapping with and without seasonal adjustment for bias correction. Up to seven-days ahead forecast skills are compared using the Relative Operation Characteristic (ROC) graphs, for the flood warning and flood alarm flow value thresholds. The ECMWF forecasts are obtained from the project TIGGE (http://www.ecmwf.int/en/research/projects/tigge) to prolong the lead time of the forecasts downstream. Both hydrological models show different performances when forced with raw and de-biased ECMWF ensembles. This work was partly supported by the project "Stochastic flood forecasting system (The River Vistula reach from Zawichost to Warsaw)" carried out by the Institute of Geophysics, Polish Academy of Sciences by order of the National Science Centre (contract No. 2011/01/B/ST10/06866). The rainfall and flow data were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

  3. A Novel Hydro-information System for Improving National Weather Service River Forecast System

    NASA Astrophysics Data System (ADS)

    Nan, Z.; Wang, S.; Liang, X.; Adams, T. E.; Teng, W. L.; Liang, Y.

    2009-12-01

    A novel hydro-information system has been developed to improve the forecast accuracy of the NOAA National Weather Service River Forecast System (NWSRFS). An MKF-based (Multiscale Kalman Filter) spatial data assimilation framework, together with the NOAH land surface model, is employed in our system to assimilate satellite surface soil moisture data to yield improved evapotranspiration. The latter are then integrated into the distributed version of the NWSRFS to improve its forecasting skills, especially for droughts, but also for disaster management in general. Our system supports an automated flow into the NWSRFS of daily satellite surface soil moisture data, derived from the TRMM Microwave Imager (TMI) and Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), and the forcing information of the North American Land Data Assimilation System (NLDAS). All data are custom processed, archived, and supported by the NASA Goddard Earth Sciences Data Information and Services Center (GES DISC). An optional data fusing component is available in our system, which fuses NEXRAD Stage III precipitation data with the NLDAS precipitation data, using the MKF-based framework, to provide improved precipitation inputs. Our system employs a plug-in, structured framework and has a user-friendly, graphical interface, which can display, in real-time, the spatial distributions of assimilated state variables and other model-simulated information, as well as their behaviors in time series. The interface can also display watershed maps, as a result of the integration of the QGIS library into our system. Extendibility and flexibility of our system are achieved through the plug-in design and by an extensive use of XML-based configuration files. Furthermore, our system can be extended to support multiple land surface models and multiple data assimilation schemes, which would further increase its capabilities. Testing of the integration of the current system into the NWSRFS is ongoing.

  4. Methodology for national wheat yield forecast using wheat growth model, WTGROWS, and remote sensing inputs

    NASA Astrophysics Data System (ADS)

    Kalra, Naveen; Aggarwal, P. K.; Singh, A. K.; Dadhwal, V. K.; Sehgal, V. K.; Harith, R. C.; Sharma, S. K.

    2006-12-01

    Wheat is an important food crop of the country. Its productivity lies in a very wide range due to diverse bio-physical and socio-economic conditions in the growing regions. Crop cutting and sample surveys are time consuming as well tedious, and procedure of forecast is delayed. CAPE methodology, which uses remote sensing, ground truth and prevailing weather, has been very successful, but empirical in nature. In a joint IARI-SAC Research Programme, possibility of linking the dynamic wheat growth model with the remote sensing input and other relational database layers was tried. Use of WTGROWS, a wheat growth model developed at IARI, with the remote sensing and relational databases is dynamic and can be updated whenever weather, acreage and fertilizer and other inputs are received. National wheat yield forecast was done for three seasons on meteorological sub-division scale by using WTGROWS, relational database layers and satellite image. WTGROWS was run for historic weather dataset (last 25 years), with the relational database inputs through their associated growth rates and compared with the productivity trends of the met-subdivision. Calibration factor, for each met-subdivision, were obtained to capture the other biotic and abiotic stresses and subsequently used to bring down the yields at each sub-division to realistic scale. The satellite image was used to compute the acreage with wheat in each sub-division. Meteorological data for each-subdivision was obtained from IMD (weekly basis). WTGROWS was run with actual weather data obtained upto a given time, and weather normals use for subsequent period, and the forecast was prepared. This was updated on weekly basis, and the methodology could forecast the wheat yield well in advance with a great accuracy. This procedure shows the pathway for Crop Growth Monitoring System (CGMS) for the country, to be used for land use planning and agri-production estimates, which although looks difficult for diverse agro-ecologies and wide range of bio-physical and socio-economic characters contributing to differential productivity trends.

  5. A successful forecast of an El Nino winter

    SciTech Connect

    Kerr, R.A.

    1992-01-24

    This year, for the first time, weather forecasters used signs of a warming in the tropical Pacific as the basis for a long-range prediction of winter weather patterns across the United States. Now forecasters are talking about the next step: stretching the lead time for such forecasts by a year or more. That seems feasible because although this Pacific warming was unmistakable by the time forecasters at the National Weather Service's Climate Analysis Center (CAC) in Camp Springs, Maryland, issued their winter forecast, the El Nino itself had been predicted almost 2 years in advance by a computer model. Next time around, the CAC may well be listening to the modelers and predicting El Nino-related patterns of warmth and flooding seasons in advance.

  6. Flood Watch A new service for the Queensland community

    E-print Network

    Greenslade, Diana

    Flood Watch A new service for the Queensland community What is a FloodWatch? Flood Watch there is an increased risk of riverine flooding. It joins the best of our rainfall and flood forecasting capabilities into a single product. Flood Watches will be available from 15 October 2014, allowing Queenslanders to make

  7. National plans for aircraft icing and improved aircraft icing forecasts and associated warning services

    NASA Technical Reports Server (NTRS)

    Pass, Ralph P.

    1988-01-01

    Recently, the United States has increased its activities related to aircraft icing in numerous fields: ice phobics, revised characterization of icing conditions, instrument development/evaluation, de-ice/anti-ice devices, simulated supercooled clouds, computer simulation and flight tests. The Federal Coordinator for Meteorology is involved in two efforts, one a National Plan on Aircraft Icing and the other a plan for Improved Aircraft Icing Forecasts and Associated Warning Services. These two plans will provide an approved structure for future U.S. activities related to aircraft icing. The recommended activities will significantly improve the position of government agencies to perform mandated activities and to enable U.S. manufacturers to be competitive in the world market.

  8. Flooding and Schools

    ERIC Educational Resources Information Center

    National Clearinghouse for Educational Facilities, 2011

    2011-01-01

    According to the Federal Emergency Management Agency, flooding is the nation's most common natural disaster. Some floods develop slowly during an extended period of rain or in a warming trend following a heavy snow. Flash floods can occur quickly, without any visible sign of rain. Catastrophic floods are associated with burst dams and levees,…

  9. Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

    NASA Technical Reports Server (NTRS)

    Zavodsky, Bradley; Case, Jonathan L.; Gotway, John H.; White, Kristopher; Medlin, Jeffrey; Wood, Lance; Radell, Dave

    2014-01-01

    Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use cases.

  10. Development of flood index by characterisation of flood hydrographs

    NASA Astrophysics Data System (ADS)

    Bhattacharya, Biswa; Suman, Asadusjjaman

    2015-04-01

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

  11. Flood Frequency Analysis using different flood descriptors - the Warsaw reach of the river Vistula case study

    NASA Astrophysics Data System (ADS)

    Karamuz, Emilia; Kochanek, Krzysztof; Romanowicz, Renata

    2014-05-01

    Flood frequency analysis (FFA) is customarily performed using annual maximum flows. However, there is a number of different flood descriptors that could be used. Among them are water levels, peaks over the threshold, flood-wave duration, flood volume, etc. In this study we compare different approaches to FFA for their suitability for flood risk assessment. The main goal is to obtain the FFA curve with the smallest possible uncertainty limits, in particular for the distribution tail. The extrapolation of FFA curves is crucial in future flood risk assessment in a changing climate. We compare the FFA curves together with their uncertainty limits obtained using flows, water levels, flood inundation area and volumes for the Warsaw reach of the river Vistula. Moreover, we derive the FFA curves obtained using simulated flows. The results are used to derive the error distribution for the maximum simulated and observed values under different modelling techniques and assess its influence on flood risk predictions for ungauged catchments. MIKE11, HEC-RAS and transfer function model are applied in average and extreme conditions to model flow propagation in the Warsaw Vistula reach. The additional questions we want to answer are what is the range of application of different modelling tools under various flow conditions and how can the uncertainty of flood risk assessment be decreased. This work was partly supported by the projects "Stochastic flood forecasting system (The River Vistula reach from Zawichost to Warsaw)" and "Modern statistical models for analysis of flood frequency and features of flood waves", carried by the Institute of Geophysics, Polish Academy of Sciences on the order of the National Science Centre (contracts Nos. 2011/01/B/ST10/06866 and 2012/05/B/ST10/00482, respectively). The water level and flow data were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

  12. Verification of precipitation forecasts from two numerical weather prediction models in the Middle Atlantic Region of the USA: A precursory analysis to hydrologic forecasting

    NASA Astrophysics Data System (ADS)

    Siddique, Ridwan; Mejia, Alfonso; Brown, James; Reed, Seann; Ahnert, Peter

    2015-10-01

    Accurate precipitation forecasts are required for accurate flood forecasting. The structures of different precipitation forecasting systems are constantly evolving, with improvements in forecasting techniques, increases in spatial and temporal resolution, improvements in model physics and numerical techniques, and better understanding of, and accounting for, predictive uncertainty. Hence, routine verification is necessary to understand the quality of forecasts as inputs to hydrologic modeling. In this study, we verify precipitation forecasts from the National Centers for Environmental Prediction (NCEP) 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2), as well as the 21-member Short Range Ensemble Forecast (SREF) system. Specifically, basin averaged precipitation forecasts are verified for different basin sizes (spatial scales) in the operating domain of the Middle Atlantic River Forecast Center (MARFC), using multi-sensor precipitation estimates (MPEs) as the observed data. The quality of the ensemble forecasts is evaluated conditionally upon precipitation amounts, forecast lead times, accumulation periods, and seasonality using different verification metrics. Overall, both GEFSRv2 and SREF tend to overforecast light to moderate precipitation and underforecast heavy precipitation. In addition, precipitation forecasts from both systems become increasingly reliable with increasing basin size and decreasing precipitation threshold, and the 24-hourly forecasts show slightly better skill than the 6-hourly forecasts. Both systems show a strong seasonal trend, characterized by better skill during the cool season than the warm season. Ultimately, the verification results lead to guidance on the expected quality of the precipitation forecasts, together with an assessment of their relative quality and unique information content, which is useful and necessary for their application in hydrologic forecasting.

  13. On the identification of flood prone areas from national scale territorial information: the case study of Italy

    NASA Astrophysics Data System (ADS)

    Taramasso, A. C.; Roth, G.; Rudari, R.; Lomazzi, M.; Ghizzoni, T.

    2009-12-01

    The magnitude of recent flood events (e.g., Mississippi, 1993; Elba and Danube, 2002; Iowa and Midwest US, 2008) in terms of their spatial extent and economic impact calls for enhanced descriptions of flood risk scenarios. An evaluation of flood risk can be obtained through a lasting effort aimed at the collection of all the elements that contribute to risk definition: identification of flood prone areas, associated hazard levels, exposed values and vulnerabilities. This framework would benefit from a preliminary ranking able to identify those areas in which the hazard, the exposed values, or both are significant. This first risk evaluation has the indubitable advantage of using widely available information and could guide the risk evaluation process by defining a prioritization of river segments to be analyzed. In the present work a risk-ranking model, originally intended for insurance purposes, is presented. The model is based on the combination of information extracted from multiple catalogues, representing either physical aspects related to the flooding processes or economic and trading information, mainly related to exposed values and vulnerabilities. In this framework, digital terrain elevation and drainage network models are used to derive flood susceptibility, while data on the geographic location of population, industries, public services, infrastructures and land use are used as proxies of exposed values and vulnerability. To enhance the information content of the data, the model operates at both the national and the local scale of analysis. An application to the Italian territory shows that is possible to identify areas that, in resource-limited conditions, should be first selected for detailed studies. Results are finally compared against detailed studies provided by Basin Authorities, where available, and against the historical flood events catalogue "Aree Vulnerate Italiane" (AVI, http://avi.gndci.cnr.it/), produced by the Italian National Research Council.

  14. Weather: National | Victoria | NSW | ACT | Queensland | South Aus | Western Aus | Nthn. Territory | Tasmania FLOOD WARNING SYSTEM

    E-print Network

    Greenslade, Diana

    | Tasmania FLOOD WARNING SYSTEM for the UPPER BRISBANE RIVER ABOVE WIVENHOE DAM This brochure describes the flood warning system operated by the Bureau of Meteorology for the upper Brisbane River above Wivenhoe Dam. It includes reference information which will be useful for understanding Flood Warnings and River

  15. Necessity of Flood Early Warning Systems in India

    NASA Astrophysics Data System (ADS)

    Kurian, C.; Natesan, U.; Durga Rao, K. H. V.

    2014-12-01

    India is one of the highly flood prone countries in the world. National flood commission has reported that 400,000 km² of geographical area is prone to floods, constituting to twelve percent of the country's geographical area. Despite the reoccurrences of floods, India still does not have a proper flood warning system. Probably this can be attributed to the lack of trained personnel in using advanced techniques. Frequent flood hazards results in damage to livelihood, infrastructure and public utilities. India has a potential to develop an early warning system since it is one of the few countries where satellite based inputs are regularly used for monitoring and mitigating floods. However, modeling of flood extent is difficult due to the complexity of hydraulic and hydrologic processes during flood events. It has been reported that numerical methods of simulations can be effectively used to simulate the processes correctly. Progress in computational resources, data collection and development of several numerical codes has enhanced the use of hydrodynamic modeling approaches to simulate the flood extent in the floodplains. In this study an attempt is made to simulate the flood in one of the sub basins of Godavari River in India using hydrodynamic modeling techniques. The modeling environment includes MIKE software, which simulates the water depth at every grid cell of the study area. The runoff contribution from the catchment was calculated using Nebdor Afstromnings model. With the hydrodynamic modeling approach, accuracy in discharge and water level computations are improved compared to the conventional methods. The results of the study are proming to develop effective flood management plans in the basin. Similar studies could be taken up in other flood prone areas of the country for continuous modernisation of flood forecasting techniques, early warning systems and strengthening decision support systems, which will help the policy makers in developing management plans and policies.

  16. Social Media: Flood #FloodSafety #FallSafety

    E-print Network

    Social Media: Flood #FloodSafety #FallSafety Please help the NWS spread these important safety build a WeatherReady Nation. Turn Around Don't Drown Video Cars Carried off by Flood Waters People Carried off by Flood Waters Difference Between Flood Watch and Warning Putting Yours and Your

  17. Social Media: Flood #FloodSafety #WinterSafety

    E-print Network

    Social Media: Flood #FloodSafety #WinterSafety Please help the NWS spread these important the NWS build a WeatherReady Nation. Turn Around Don't Drown Video Cars Carried off by Flood Waters People Carried off by Flood Waters Difference Between Flood Watch and Warning Putting Yours

  18. A coupled modelling system for the Irish Sea and Liverpool Bay with application to coastal flood forecasting and beyond

    NASA Astrophysics Data System (ADS)

    Wolf, J.; Bricheno, L. R.; Brown, J. E.; Bolaños, R.

    2012-04-01

    The POLCOMS-WAM coupled wave and hydrodynamic model has been implemented at 1.8km resolution for the Irish Sea and 180m in a nested model of Liverpool Bay. It can be forced with output from the UK Met Office Unified Model. This allows the use of Smith and Banke (1975) and Charnock (1955) formulations for the wind-stress. The former gives an underestimate of the wind-stress, requiring enhanced winds for accurate surge hindcasts. While the latter gives good results for the Irish Sea and Liverpool Bay, with different values of the Charnock coefficient, it also allows the inclusion of a coupled wave stress into the wind-stress (Brown and Wolf, 2009). New results have been obtained by using wind and pressures from the WRF atmospheric model, allowing further development of air-sea coupling. The coupled model also includes bottom friction and the Doppler shift of the waves by the depth-averaged current), as well as advanced coupling procedures: use of the 3D current in the wave physics and calculation of radiation stress and Stokes' drift (Brown et al., 2011). During storm conditions it is found that the radiation stress is the most important term in this shallow water application. However, WAM runs in near real time, making this model only practical for research purposes. The model system has been used to hindcast tides, surges and waves in Liverpool Bay. Data are readily available from the Liverpool Bay Coastal Observatory to quantify the importance of each coupled term with the aim of producing the most accurate model setup for coastal forecasting. A storm event, 18th January 2007, has been hindcast to investigate extreme tide-surge-wave condition both offshore and inshore. During storm events, wave setup in shallow regions can contribute significantly to the total water elevation. The application of a 2D method to calculate radiation stress in a 3D hydrodynamic model is thoroughly examined by comparison with observations and a 3D model (Mellor, 2003). The results show that the 2D method is not only more computationally efficient, so more relevant for operational use, than the 3D solution, but also provides a more plausible solution, especially when coupled to a circulation model to allow proper distribution of wave setup. Radiation stress is demonstrated to be of major importance at an estuary mouth and along the coast, while having lesser impact within an estuary and further offshore. Further development of the coupled system includes modelling of SPM and water quality, both important and complex in this region of freshwater influence. Brown, J.M., Bolaños, R., Wolf, J., 2011. Impact assessment of advanced coupling features in a tide-surge-wave model, POLCOMS-WAM, in a shallow water application. Journal of Marine Systems, 87(1), 13-24. Brown, J. and Wolf, J. 2009 Coupled wave and surge modelling for the eastern Irish Sea and implications for model wind-stress. Continental Shelf Research 29 (10), 1329-1342. Charnock, H., 1955: Wind stress over a water surface. Quarterly Journal of the Royal Meteorological Society, 81, 639-640. Mellor, G., 2003. The three-dimensional current and surface wave equations. Journal of Physical Oceanography, 33(9), 1978-1989. Smith, S. D., Banke, E. G., 1975. Variation of the surface drag coefficient with wind speed. Quarterly Journal of the Royal Meteorological Society, 429, 665-673.

  19. Evaluating National Weather Service Seasonal Forecast Products in Reservoir Operation Case Studies

    NASA Astrophysics Data System (ADS)

    Nielson, A.; Guihan, R.; Polebistki, A.; Palmer, R. N.; Werner, K.; Wood, A. W.

    2014-12-01

    Forecasts of future weather and streamflow can provide valuable information for reservoir operations and water management. A challenge confronting reservoir operators today is how to incorporate both climate and streamflow products into their operations and which of these forecast products are most informative and useful for optimized water management. This study incorporates several reforecast products provided by the Colorado Basin River Forecast Center (CBRFC) which allows a complete retrospective analysis of climate forecasts, resulting in an evaluation of each product's skill in the context of water resources management. The accuracy and value of forecasts generated from the Climate Forecast System version 2 (CFSv2) are compared to the accuracy and value of using an Ensemble Streamflow Predictions (ESP) approach. Using the CFSv2 may offer more insight when responding to climate driven extremes than the ESP approach because the CFSv2 incorporates a fully coupled climate model into its forecasts rather than using all of the historic climate record as being equally probable. The role of forecast updating frequency will also be explored. Decision support systems (DSS) for both Salt Lake City Parley's System and the Snohomish County Public Utility Department's (SnoPUD) Jackson project will be used to illustrate the utility of forecasts. Both DSS include a coupled simulation and optimization model that will incorporate system constraints, operating policies, and environmental flow requirements. To determine the value of the reforecast products, performance metrics meaningful to the managers of each system are to be identified and quantified. Without such metrics and awareness of seasonal operational nuances, it is difficult to identify forecast improvements in meaningful ways. These metrics of system performance are compared using the different forecast products to evaluate the potential benefits of using CFSv2 seasonal forecasts in systems decision making.

  20. The August 2002 flood in Salzburg / Austria experience gained and lessons learned from the ``Flood of the century''?

    NASA Astrophysics Data System (ADS)

    Wiesenegger, H.

    2003-04-01

    On the {12th} of August 2002 a low pressure system moved slowly from northern Italy towards Slovakia. It continuously carried moist air from the Mediterranean towards the northern rim of the Alps with the effect of wide-spread heavy rainfall in Salzburg and other parts of Austria. Daily precipitation amounts of 100 - 160 mm, in some parts even more, as well as rainfall intensities of 5 - 10 mm/h , combined with well saturated soils lead to a rare flood with a return period of 100 years and more. This rare hydrological event not only caused a national catastrophe with damages of several Billion Euro, but also endangered more than 200,000 people, and even killed some. As floods are dangerous, life-threatening, destructive, and certainly amongst the most frequent and costly natural disasters in terms of human hardship as well as economic loss, a great effort, therefore, has to be made to protect people against negative impacts of floods. In order to achieve this objective, various regulations in land use planning (flood maps), constructive measurements (river regulations and technical constructions) as well as flood warning systems, which are not suitable to prevent big floods, but offer in-time-warnings to minimize the loss of human lives, are used in Austria. HYDRIS (Hydrological Information System for flood forecasting in Salzburg), a modular river basin model, developed at Technical University Vienna and operated by the Hydrological Service of Salzburg, was used during the August 2002 flood providing accurate 3 to 4 hour forecasts within 3 % of the real peak discharge of the fast flowing River Salzach. The August {12^th}} flood was in many ways an exceptional, very fast happening event which took many people by surprise. At the gauging station Salzburg / Salzach (catchment area 4425 {km^2}) it took only eighteen hours from mean annual discharge (178 {m3/s}) to the hundred years flood (2300 {m3/s}). The August flood made clear, that there is a strong need for longer lead times in Salzburg's flood forecasts. Methods to incorporate precipitation forecasts, provided by the Met Office, as well as observations of actual soil conditions, therefore, have to be developed and should enable hydrologists to predict possible scenarios and impacts of floods, forecasted for the next 24 hours. As a further consequence of the August 2002 flood, building regulations, e.g. the use of oil tanks in flood prone areas, have to be checked and were necessary adapted. It is also necessary to make people, who already live in flood prone areas, aware of the dangers of floods. They also need to know about the limits of flood protection measurements and about what happens, if flood protection design values are exceeded. Alarm plans, dissemination of information by using modern communication systems (Internet) as well as communication failure in peak times and co-ordination of rescue units are also a subject to be looked at carefully. The above mentioned measurements are amongst others of a 10 point program, developed by the Government of the Province of Salzburg and at present checked with regards to feasibility. As it is to be expected, that the August 2002 flood was not the last rare one of this century, experience gained should be valuably for the next event.

  1. The proposal about constructing the National Disaster Monitoring, Forecast and Control System

    NASA Astrophysics Data System (ADS)

    Chen, Fang-yun; Tong, Kai; Yang, Jia-chi

    It is known that different kinds of natural disaster cause big loss in people's lives and damage in properties every year in many countries, and the monitoring, forecast and control to prevent as mitigate the harm is very important indeed. Some kinds of disasters might be foreseen and the developing trend may be understood from the observation facilities under management of professional department. Here we suggest that the existing domestic and foreign monitoring systems, especially the space systems already in use, should be utilized for disaster mitigation purpose before some new system being developed specially for it. The information collection part of the Disaster Monitoring, Forecast and Control System (DMFCS) may be composed of three layers of sensing implements, the earth observing satellites, the remote sensing airplanes and the local ground sensing instruments whose data could be sent to the centers concerned through the data collcetion system (DCS) of various kinds of satellits. In coordination with the monitoring systems, the position fixing satellite system, the Global Positioning System (GPS/GLONASS) or the Radiodetermination Satellite Service (RDSS) which in China was named the Bisatellite Position Determination System (BPDS) under developing is also indispensable. In DMFCS the nucleus is the Control Center (DMFCC). It is connected with the centers of the existing professional organizations and the Regional Disaster Control Centers (RDCC). In this paper we pay more attention to the construction of DMFCC. The center should be led by the department particularly concerned with disaster prevention, preparedness and relief (as it has been announced by the United Nations). The Centers will fully utilize the real time information from the monitoring means and the information stored in the data base to display the state of the disasters, to help the decision of the department leader to issue instructions to the Regional Centers to take measures for controlling, rescue and salvation. It is also pointed out that the fundamental research works are necessary for the study of the cause, prediction and the social effect of natural disasters and the accumulation of data is important for further use too.

  2. The FASTER Approach: A New Tool for Calculating Real-Time Tsunami Flood Hazards

    NASA Astrophysics Data System (ADS)

    Wilson, R. I.; Cross, A.; Johnson, L.; Miller, K.; Nicolini, T.; Whitmore, P.

    2014-12-01

    In the aftermath of the 2010 Chile and 2011 Japan tsunamis that struck the California coastline, emergency managers requested that the state tsunami program provide more detailed information about the flood potential of distant-source tsunamis well ahead of their arrival time. The main issue is that existing tsunami evacuation plans call for evacuation of the predetermined "worst-case" tsunami evacuation zone (typically at a 30- to 50-foot elevation) during any "Warning" level event; the alternative is to not call an evacuation at all. A solution to provide more detailed information for secondary evacuation zones has been the development of tsunami evacuation "playbooks" to plan for tsunami scenarios of various sizes and source locations. To determine a recommended level of evacuation during a distant-source tsunami, an analytical tool has been developed called the "FASTER" approach, an acronym for factors that influence the tsunami flood hazard for a community: Forecast Amplitude, Storm, Tides, Error in forecast, and the Run-up potential. Within the first couple hours after a tsunami is generated, the National Tsunami Warning Center provides tsunami forecast amplitudes and arrival times for approximately 60 coastal locations in California. At the same time, the regional NOAA Weather Forecast Offices in the state calculate the forecasted coastal storm and tidal conditions that will influence tsunami flooding. Providing added conservatism in calculating tsunami flood potential, we include an error factor of 30% for the forecast amplitude, which is based on observed forecast errors during recent events, and a site specific run-up factor which is calculated from the existing state tsunami modeling database. The factors are added together into a cumulative FASTER flood potential value for the first five hours of tsunami activity and used to select the appropriate tsunami phase evacuation "playbook" which is provided to each coastal community shortly after the forecast is provided.

  3. Forecasting for natural avalanches during spring opening of Going-to-the-Sun Road, Glacier National Park, Montana, USA

    USGS Publications Warehouse

    Reardon, Blase; Lundy, Chris

    2004-01-01

    The annual spring opening of the Going-to-the-Sun Road in Glacier National Park presents a unique avalanche forecasting challenge. The highway traverses dozens of avalanche paths mid-track in a 23-kilometer section that crosses the Continental Divide. Workers removing seasonal snow and avalanche debris are exposed to paths that can produce avalanches of destructive class 4. The starting zones for most slide paths are within proposed Wilderness, and explosive testing or control are not currently used. Spring weather along the Divide is highly variable; rain-on-snow events are common, storms can bring several feet of new snow as late as June, and temperature swings can be dramatic. Natural avalanches - dry and wet slab, dry and wet loose, and glide avalanches - present a wide range of hazards and forecasting issues. This paper summarizes the forecasting program instituted in 2002 for the annual snow removal operations. It focuses on tools and techniques for forecasting natural wet snow avalanches by incorporating two case studies, including a widespread climax wet slab cycle in 2003. We examine weather and snowpack conditions conducive to wet snow avalanches, indicators for instability, and suggest a conceptual model for wet snow stability in a northern intermountain snow climate.

  4. NOAA's National Weather Service Your gateway to web resources provided through NOAA's

    E-print Network

    or stream gauge is not operating. Observations are not current. River or stream level below flood stage locations where observations are color- coded according to their current flood status. NWS river forecasts Administration National Weather Service September 2015 #12;Click this button to bookmark or share your current

  5. A comparison of the causes, effects and aftermaths of the coastal flooding of England in 1953 and France in 2010

    NASA Astrophysics Data System (ADS)

    Lumbroso, D. M.; Vinet, F.

    2011-08-01

    This paper provides a comparison of the causes, effects and aftermaths of the coastal flooding that occurred on the east coast of England in 1953 and the west coast of France in 2010 that resulted in 307 and 47 deaths respectively. The causes of both events are strikingly similar. Both were caused by a combination of high tides, low atmospheric pressure, high winds and the failure of poorly maintained flood defences. In both cases the number of deaths was related to the vulnerability of the buildings and people. Buildings in the flood zones were often single storey bungalows and the people who died were mostly over 60 yr of age. Both tragedies were national disasters. The 1953 flood in England acted as a catalyst for an acceleration in flood risk management policy and practice. It resulted in: the development of a Storm Tide Warning System for the east coast of England; the setting of new design standards for coastal flood defences; increased investment in improving coastal defences; and a substantial new research effort into coastal processes, protection and forecasting. In France there has also been an episodic shift in flood risk management policy with the focus falling on: control of urban developments in areas at risk of flooding; improved coastal forecasting and warning; strengthening of flood defences; and developing a "culture of risk awareness". This paper outlines the lessons that can be learnt from the two events and provides recommendations concerning how future loss of life as a result of coastal flooding can be reduced.

  6. Using constructed analogs to improve the skill of National Multi-Model Ensemble March–April–May precipitation forecasts in equatorial East Africa

    USGS Publications Warehouse

    Shukla, Shraddhanand; Funk, Christopher C.; Hoell, Andrew

    2014-01-01

    In this study we implement and evaluate a simple 'hybrid' forecast approach that uses constructed analogs (CA) to improve the National Multi-Model Ensemble's (NMME) March–April–May (MAM) precipitation forecasts over equatorial eastern Africa (hereafter referred to as EA, 2°S to 8°N and 36°E to 46°E). Due to recent declines in MAM rainfall, increases in population, land degradation, and limited technological advances, this region has become a recent epicenter of food insecurity. Timely and skillful precipitation forecasts for EA could help decision makers better manage their limited resources, mitigate socio-economic losses, and potentially save human lives. The 'hybrid approach' described in this study uses the CA method to translate dynamical precipitation and sea surface temperature (SST) forecasts over the Indian and Pacific Oceans (specifically 30°S to 30°N and 30°E to 270°E) into terrestrial MAM precipitation forecasts over the EA region. In doing so, this approach benefits from the post-1999 teleconnection that exists between precipitation and SSTs over the Indian and tropical Pacific Oceans (Indo-Pacific) and EA MAM rainfall. The coupled atmosphere-ocean dynamical forecasts used in this study were drawn from the NMME. We demonstrate that while the MAM precipitation forecasts (initialized in February) skill of the NMME models over the EA region itself is negligible, the ranked probability skill score of hybrid CA forecasts based on Indo-Pacific NMME precipitation and SST forecasts reach up to 0.45.

  7. Natural glide slab avalanches, Glacier National Park, USA: A unique hazard and forecasting challenge

    USGS Publications Warehouse

    Reardon, Blase; Fagre, Daniel B.; Dundas, Mark; Lundy, Chris

    2006-01-01

    In a museum of avalanche phenomena, glide cracks and glide avalanches might be housed in the “strange but true” section. These oddities are uncommon in most snow climates and tend to be isolated to specific terrain features such as bedrock slabs. Many glide cracks never result in avalanches, and when they do, the wide range of time between crack formation and slab failure makes them highly unpredictable. Despite their relative rarity, glide cracks and glide avalanches pose a regular threat and complex forecasting challenge during the annual spring opening of the Going-to-the-Sun Road in Glacier National Park, U.S.A. During the 2006 season, a series of unusual glide cracks delayed snow removal operations by over a week and provided a unique opportunity to record detailed observations of glide avalanches and characterize their occurrence and associated weather conditions. Field observations were from snowpits, crown profiles and where possible, measurements of slab thickness, bed surface slope angle, substrate and other physical characteristics. Weather data were recorded at one SNOTEL site and two automated stations located from 0.6-10 km of observed glide slab avalanches. Nearly half (43%) of the 35 glide slab avalanches recorded were Class D2-2.5, with 15% Class D3-D3.5. The time between glide crack opening and failure ranged from 2 days to over six weeks, and the avalanches occurred in cycles associated with loss of snow water equivalent and spikes in temperature and radiation. We conclude with suggest ions for further study.

  8. The predictability of Iowa's hydroclimate through analog forecasts

    NASA Astrophysics Data System (ADS)

    Rowe, Scott Thomas

    Iowa has long been affected by periods characterized by extreme drought and flood. In 2008, Cedar Rapids, Iowa was devastated by a record flood with damages around 3 billion. Several years later, Iowa was affected by severe drought in 2012, causing upwards of 30 billion in damages and losses across the United States. These climatic regimes can quickly transition from one regime to another, as was observed in the June 2013 major floods to the late summer 2013 severe drought across eastern Iowa. Though it is not possible to prevent a natural disaster from occurring, we explore how predictable these events are by using forecast models and analogs. Iowa's climate records are analyzed from 1950 to 2012 to determine if there are specific surface and upper-air pressure patterns linked to climate regimes (i.e., cold/hot and dry/wet conditions for a given month). We found that opposing climate regimes in Iowa have reversed anomalies in certain geographical regions of the northern hemisphere. These defined patterns and waves suggested to us that it could be possible to forecast extreme temperature and precipitation periods over Iowa if given a skillful forecast system. We examined the CMC, COLA, and GFDL models within the National Multi-Model Ensemble suite to create analog forecasts based on either surface or upper-air pressure forecasts. The verification results show that some analogs have predictability skill at the 0.5-month lead time exceeding random chance, but our overall confidence in the analog forecasts is not high enough to allow us to issue statewide categorical temperature and precipitation climate forecasts.

  9. Iowa Flood Information System

    NASA Astrophysics Data System (ADS)

    Demir, I.; Krajewski, W. F.; Goska, R.; Mantilla, R.; Weber, L. J.; Young, N.

    2011-12-01

    The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to flood inundation maps, real-time flood conditions, flood forecasts both short-term and seasonal, flood-related data, information and interactive visualizations for communities in Iowa. The key element of the system's architecture is the notion of community. Locations of the communities, those near streams and rivers, define basin boundaries. The IFIS provides community-centric watershed and river characteristics, weather (rainfall) conditions, and streamflow data and visualization tools. Interactive interfaces allow access to inundation maps for different stage and return period values, and flooding scenarios with contributions from multiple rivers. Real-time and historical data of water levels, gauge heights, and rainfall conditions are available in the IFIS by streaming data from automated IFC bridge sensors, USGS stream gauges, NEXRAD radars, and NWS forecasts. Simple 2D and 3D interactive visualizations in the IFIS make the data more understandable to general public. Users are able to filter data sources for their communities and selected rivers. The data and information on IFIS is also accessible through web services and mobile applications. The IFIS is optimized for various browsers and screen sizes to provide access through multiple platforms including tablets and mobile devices. The IFIS includes a rainfall-runoff forecast model to provide a five-day flood risk estimate for around 500 communities in Iowa. Multiple view modes in the IFIS accommodate different user types from general public to researchers and decision makers by providing different level of tools and details. River view mode allows users to visualize data from multiple IFC bridge sensors and USGS stream gauges to follow flooding condition along a river. The IFIS will help communities make better-informed decisions on the occurrence of floods, and will alert communities in advance to help minimize damage of floods. This presentation provides an overview of the tools and interfaces in the IFIS developed to date to provide a platform for one-stop access to flood related data, visualizations, flood conditions, and forecast.

  10. 77 FR 31814 - National Flood Insurance Program (NFIP); Insurance Coverage and Rates

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-30

    ...AGENCY: Federal Emergency Management Agency, DHS. ACTION: Proposed...SUMMARY: The Federal Emergency Management Agency (FEMA) is withdrawing...from flood damages through no fault of their own. III. Reason...Administrator, Federal Emergency Management Agency. [FR Doc....

  11. Short-term Inundation Forecast of Tsunami

    E-print Network

    SIFT Short-term Inundation Forecast of Tsunami Operational tsunami forecast system; combining real-time tsunami observations with numerical models to produce forecasts of tsunami wave arrival, amplitudes, and flooding Background and Overview The SIFT (Short-term Inunda:on for Forecas:ng Tsunamis

  12. Development of a flood-warning system and flood-inundation mapping in Licking County, Ohio

    USGS Publications Warehouse

    Ostheimer, Chad J.

    2012-01-01

    Digital flood-inundation maps for selected reaches of South Fork Licking River, Raccoon Creek, North Fork Licking River, and the Licking River in Licking County, Ohio, were created by the U.S. Geological Survey (USGS), in cooperation with the Ohio Department of Transportation; U.S. Department of Transportation, Federal Highway Administration; Muskingum Watershed Conservancy District; U.S. Department of Agriculture, Natural Resources Conservation Service; and the City of Newark and Village of Granville, Ohio. The inundation maps depict estimates of the areal extent of flooding corresponding to water levels (stages) at the following USGS streamgages: South Fork Licking River at Heath, Ohio (03145173); Raccoon Creek below Wilson Street at Newark, Ohio (03145534); North Fork Licking River at East Main Street at Newark, Ohio (03146402); and Licking River near Newark, Ohio (03146500). The maps were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning system that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. As part of the flood-warning streamflow network, the USGS re-installed one streamgage on North Fork Licking River, and added three new streamgages, one each on North Fork Licking River, South Fork Licking River, and Raccoon Creek. Additionally, the USGS upgraded a lake-level gage on Buckeye Lake. Data from the streamgages and lake-level gage can be used by emergency-management personnel, in conjunction with the flood-inundation maps, to help determine a course of action when flooding is imminent. Flood profiles for selected reaches were prepared by calibrating steady-state step-backwater models to selected, established streamgage rating curves. The step-backwater models then were used to determine water-surface-elevation profiles for up to 10 flood stages at a streamgage with corresponding streamflows ranging from approximately the 50 to 0.2-percent chance annual-exceedance probabilities for each of the 4 streamgages that correspond to the flood-inundation maps. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas. Maps of Licking County showing flood-inundation areas overlain on digital orthophotographs are presented for the selected floods. The USGS also developed an unsteady-flow model for a reach of South Fork Licking River for use by the NWS to enhance their ability to provide advanced flood warning in the region north of Buckeye Lake, Ohio. The unsteady-flow model was calibrated based on data from four flooding events that occurred from June 2008 to December 2011. Model calibration was approximate due to the fact that there were unmeasured inflows to the river that were not able to be considered during the calibration. Information on unmeasured inflow derived from NWS hydrologic models and additional flood-event data could enable the NWS to further refine the unsteady-flow model.

  13. Sediment capture in flood plains of the Mississippi River: A case study in Cat Island National Wildlife Refuge, Louisiana

    NASA Astrophysics Data System (ADS)

    Smith, M.; Bentley, S. J., Sr.

    2015-03-01

    To plan restoration of the Mississippi River Delta, it is imperative to know how much sediment the Mississippi River currently provides. Recent research has demonstrated that between Tarbert Landing and St Francisville on the Mississippi, as much as 67 million metric tons (Mt) per year is lost from river transport, of which ~16 Mt is muddy suspended sediment. So where does this sediment go? Two pathways for loss have been proposed: riverbed storage, and overbank deposition in regions that lack manmade levées. Cat Island National Wildlife Refuge, on the unleveed Mississippi River east bank near St Francisville, Louisiana, consists of undisturbed bottomland forest that is inundated most years by river flooding. To determine fluvial sediment accumulation rates (SAR) from flooding, pushcores 40-50 cm long were collected then dated by Pb-210 and Cs-137 geochronology. Preliminary data suggests that muddy sediment accumulation is 10-13% of muddy suspended sediment lost from river transport along this river reach.

  14. Flow ensemble prediction for flash flood warnings at ungauged basins

    NASA Astrophysics Data System (ADS)

    Demargne, Julie; Javelle, Pierre; Organde, Didier; Caseri, Angelica; Ramos, Maria-Helena; de Saint Aubin, Céline; Jurdy, Nicolas

    2015-04-01

    Flash floods, which are typically triggered by severe rainfall events, are difficult to monitor and predict at the spatial and temporal scales of interest due to large meteorological and hydrologic uncertainties. In particular, uncertainties in quantitative precipitation forecasts (QPF) and quantitative precipitation estimates (QPE) need to be taken into account to provide skillful flash flood warnings with increased warning lead time. In France, the AIGA discharge-threshold flood warning system is currently being enhanced to ingest high-resolution ensemble QPFs from convection-permitting numerical weather prediction (NWP) models, as well as probabilistic QPEs, to improve flash flood warnings for small-to-medium (from 10 to 1000 km²) ungauged basins. The current deterministic AIGA system is operational in the South of France since 2005. It ingests the operational radar-gauge QPE grids from Météo-France to run a simplified hourly distributed hydrologic model at a 1-km² resolution every 15 minutes (Javelle et al. 2014). This produces real-time peak discharge estimates along the river network, which are subsequently compared to regionalized flood frequency estimates of given return periods. Warnings are then provided to the French national hydro-meteorological and flood forecasting centre (SCHAPI) and regional flood forecasting offices, based on the estimated severity of ongoing events. The calibration and regionalization of the hydrologic model has been recently enhanced to implement an operational flash flood warning system for the entire French territory. To quantify the QPF uncertainty, the COSMO-DE-EPS rainfall ensembles from the Deutscher Wetterdienst (20 members at a 2.8-km resolution for a lead time of 21 hours), which are available on the North-eastern part of France, were ingested in the hydrologic model of the AIGA system. Streamflow ensembles were produced and probabilistic flash flood warnings were derived for the Meuse and Moselle river basins and for significant events of the 2010-2013 period. The evaluation showed significant improvements in terms of flash flood event detection and effective warning lead-time, compared to warnings from the current AIGA setup (without any future precipitation). Various verification metrics (e.g., Relative Mean Error, Continuous Rank Probability Skill Score) show the skill of ensemble precipitation and flow forecasts compared to single-valued persistency benchmarks. In addition to propagating the QPF uncertainty to streamflow forecasts, we discuss how to account for other sources of forecast uncertainty, including precipitation observational uncertainty (Caseri et al. 2014) and hydrologic uncertainties. Planned enhancements include ingesting other probabilistic nowcast and NWP products from Météo-France's convection-permitting AROME model, as well as developing comprehensive observational and post-event damage database to determine decision-relevant thresholds for flood magnitude and probability. Caseri, A., Javelle, P., Ramos, M.H., Leblois, E., 2014. Generating precipitation ensembles for flood alert and risk management. Journal of Flood Risk Management (submitted). Javelle, P., Demargne, J., Defrance, D., Arnaud, P., 2014. Evaluating flash flood warnings at ungauged locations using post-event surveys: a case study with the AIGA warning system. Hydrological Sciences Journal. doi: 10.1080/02626667.2014.923970

  15. Forecasting distributional responses of limber pine to climate change at management-relevant scales in Rocky Mountain National Park.

    PubMed

    Monahan, William B; Cook, Tammy; Melton, Forrest; Connor, Jeff; Bobowski, Ben

    2013-01-01

    Resource managers at parks and other protected areas are increasingly expected to factor climate change explicitly into their decision making frameworks. However, most protected areas are small relative to the geographic ranges of species being managed, so forecasts need to consider local adaptation and community dynamics that are correlated with climate and affect distributions inside protected area boundaries. Additionally, niche theory suggests that species' physiological capacities to respond to climate change may be underestimated when forecasts fail to consider the full breadth of climates occupied by the species rangewide. Here, using correlative species distribution models that contrast estimates of climatic sensitivity inferred from the two spatial extents, we quantify the response of limber pine (Pinus flexilis) to climate change in Rocky Mountain National Park (Colorado, USA). Models are trained locally within the park where limber pine is the community dominant tree species, a distinct structural-compositional vegetation class of interest to managers, and also rangewide, as suggested by niche theory. Model forecasts through 2100 under two representative concentration pathways (RCP 4.5 and 8.5 W/m(2)) show that the distribution of limber pine in the park is expected to move upslope in elevation, but changes in total and core patch area remain highly uncertain. Most of this uncertainty is biological, as magnitudes of projected change are considerably more variable between the two spatial extents used in model training than they are between RCPs, and novel future climates only affect local model predictions associated with RCP 8.5 after 2091. Combined, these results illustrate the importance of accounting for unknowns in species' climatic sensitivities when forecasting distributional scenarios that are used to inform management decisions. We discuss how our results for limber pine may be interpreted in the context of climate change vulnerability and used to help guide adaptive management. PMID:24391742

  16. Urban flood risk warning under rapid urbanization.

    PubMed

    Chen, Yangbo; Zhou, Haolan; Zhang, Hui; Du, Guoming; Zhou, Jinhui

    2015-05-01

    In the past decades, China has observed rapid urbanization, the nation's urban population reached 50% in 2000, and is still in steady increase. Rapid urbanization in China has an adverse impact on urban hydrological processes, particularly in increasing the urban flood risks and causing serious urban flooding losses. Urban flooding also increases health risks such as causing epidemic disease break out, polluting drinking water and damaging the living environment. In the highly urbanized area, non-engineering measurement is the main way for managing urban flood risk, such as flood risk warning. There is no mature method and pilot study for urban flood risk warning, the purpose of this study is to propose the urban flood risk warning method for the rapidly urbanized Chinese cities. This paper first presented an urban flood forecasting model, which produces urban flood inundation index for urban flood risk warning. The model has 5 modules. The drainage system and grid dividing module divides the whole city terrain into drainage systems according to its first-order river system, and delineates the drainage system into grids based on the spatial structure with irregular gridding technique; the precipitation assimilation module assimilates precipitation for every grids which is used as the model input, which could either be the radar based precipitation estimation or interpolated one from rain gauges; runoff production module classifies the surface into pervious and impervious surface, and employs different methods to calculate the runoff respectively; surface runoff routing module routes the surface runoff and determines the inundation index. The routing on surface grid is calculated according to the two dimensional shallow water unsteady flow algorithm, the routing on land channel and special channel is calculated according to the one dimensional unsteady flow algorithm. This paper then proposed the urban flood risk warning method that is called DPSIR model based multiple index fuzzy evaluation warning method, and referred to as DMFEW method. DMFEW first selects 5 evaluation indexes based on the DPSIR model for flood risk warning evaluation, including driving force index, pressure index, state index, impact index and response index. Based on the values of all evaluation indexes, one evaluation index for the whole system evaluation result is determined by using the fuzzy comprehensive evaluation method. The flood risk level is divided into 4 levels, having Level 1 the most serious. Every evaluation index is also categorized as 4 levels, and a linear fuzzy subjection function is proposed to do the fuzzy comprehensive evaluation. Dongguan City is used as the study case to validate the proposed method. The urban flood forecasting model is set up with the topographic data, the city map, the underground pipelines and land cover types, and two flood events are simulated with observed precipitation, one is interpolated from the rain gauges data, and another is estimated by digital weather radar. The simulated results are compared with the investigated water depth, and the results show the model has very good performances. The results are further used for the flood risk warning simulation, and are very reasonable. PMID:25769509

  17. Flood Inundation Mapping

    E-print Network

    Pearson, Wendy

    2009-11-18

    2009 November 18, 2009 Wendy L. Pearson NOAA’s National Weather Service Central Region Headquarters Kansas City, Missouri Flood Inundation Mapping “Water Predictions for Life Decisions” Page 2 Flood Inundation Mapping Objectives: Overview... of the technical aspects of the map development process Web demonstration “Water Predictions for Life Decisions”3 NOAA National Weather Service • Flood Mapping depends on partnerships, diligence, dedication, and commitment to ensure consistency. “Water...

  18. 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

  19. Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy

    SciTech Connect

    Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

    2011-10-01

    The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.

  20. Weather forecast needs from the viewpoint of hydrology

    USGS Publications Warehouse

    Thomas, Donald M.; Buchanan, Thomas J.

    1980-01-01

    Hydrologists now depend on directly observed data in their forecasting and only infrequently use meteorological forecasts. Case studies show how reliable meteorological forecasts could be beneficial in flood and drought situations. Hydrologists need meteorological forecasts that recognize spatial variability, that are unbiased, and that have a specified degree of uncertainty. (USGS)

  1. Flood characteristics for the Nisqually River and susceptibility of Sunshine Point and Longmire facilities to flooding in Mount Rainier National Park, Washington

    USGS Publications Warehouse

    Nelson, L.M.

    1987-01-01

    Inundation from 25-, 50-, 100-, and 500-year floods at Sunshine Point and Longmire facilities and the Longmire visitors ' center and ranger station generally is not a serious hazard as long as the existing dikes and banks of the Nisqually River and Tahoma Creek remain intact and flood capacities of the channels are maintained. However, average water velocities during floods are high (as much as 23 ft/sec) and the channel, banks, and some dikes are composed of unstable materials. Sunshine Point campground is particularly susceptible to flooding and damage from Tahoma Creek, and to a lesser extent from the Nisqually River, if large amounts of debris or rock material accumulate in the channels and change the flood elevation or courses of either stream. At Longmire flood inundation or damage from the Nisqually River is much less, but flooding is still possible. There, high ridges upstream protect the several park facilities from the river, but accumulations of debris or rock in the channel could cause flooding from overtopping of dikes or riverbanks. Glacial outburst floods are a matter of serious concern at both Sunshine Point campground and Longmire. Glacial outbursts can and have produced very large flood discharges and transported large quantities of debris and rock materials. Although none have been known to transport these materials from Tahoma Glacier as far as Sunshine Point campground, one in 1955 from Nisqually Glacier (estimated at 70,000 cu ft/sec near the glacier) did appreciably increase the magnitude of the water discharge at Longmire. For safety, campers and visitors need to be advised about the potential flood hazards at both facilities. (Author 's abstract)

  2. Transition of Suomi National Polar-Orbiting Partnership (S-NPP) Data Products for Operational Weather Forecasting Applications

    NASA Astrophysics Data System (ADS)

    Smith, M. R.; Fuell, K.; Molthan, A.; Jedlovec, G.

    2012-12-01

    The launch of the Suomi National Polar-Orbiting Partnership (S-NPP) satellite provides new and exciting opportunities for the application of remotely sensed data products in operational weather forecasting environments. The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, Alabama is a NASA and NOAA-funded project to assist with the transition of experimental and research products to the operational weather community through partnership with NOAA/National Weather Service Weather Forecast Offices (NWS WFOs) throughout the United States. This presentation will provide the S-NPP community with an update on current and future SPoRT projects related to the dissemination of S-NPP derived data to NWS WFOs and highlight unique applications and value of data from the Visible Infrared Imaging Radiometer Suite (VIIRS), specifically applications of high resolution visible and infrared data, uses of the day-night (or near constant contrast) band, and multispectral composites. Other applications are envisioned through use of selected channels of the Cross-track Infrared Sounder (CrIS), the Advanced Technology Microwave Sounder (ATMS), and the Ozone Mapper Profiler Suite (OMPS). This presentation will also highlight opportunities for future collaboration with SPoRT and activities planned for participation in the NOAA Joint Polar Satellite Program (JPSS) Proving Ground.

  3. Improving flash flood forecasting through coupling of a distributed hydrologic rainfall-runoff model (HL-RDHM) with a hydraulic model (BreZo)

    NASA Astrophysics Data System (ADS)

    Nguyen, P.; Sorooshian, S.; Hsu, K.; AghaKouchak, A.; Sanders, B. F.; Smith, M. B.; Koren, V.

    2012-12-01

    Flash floods can be the most devastating events causing heavy life and economic losses. Improving flash flood warning in regions prone to hydrologic extremes is one highest priority of watershed managers. In this study, a distributed flash flood modeling system is presented. This system consists of advantages of a distributed hydrologic model (HL-RDHM) and the appropriate level of physical representation of channel flow through a high-resolution hydraulic model (BreZo). HL-RDHM is employed as a rainfall-runoff generator for runoff flow simulation, while the output from HL-RDHM is then used as input for the BreZo model, which simulates fine resolution flow in the river/channel system. The surface runoff generated from HL-RDHM is zoned to sub-catchment outlets and each outlet is considered as a point source to the channels. Multiple point sources are then simulated within BreZo to produce flash flood simulations in spatial and temporal distribution for the particular river/channel system and/or floodplain. A case study was carried out for ELDO2 catchment in Oklahoma. ArcGIS Terrain Processing tools were used to divide ELDO2 (10m resolution) into sub-catchments with outlets. The surface flow from HL-RDHM was re-gridded to 10m resolution, then zoned to the 57 sub-catchments. The results obtained are very promising not only for better simulating the total discharge at the watershed outlet, but also for capturing the spatial distribution of flooded area in the floodplains. Flooded map of ELDO2 (in meters) during the extreme event starting at 06/21/2000 10:00:00

  4. USGS Crews Measure Historic Flooding in Fargo, ND

    USGS Multimedia Gallery

    USGS scientists Chris Laveau and Joel Galloway measure streamflow during historical flooding in Fargo, ND. This information is critical for developing flood forecasts to help protect lives and property....

  5. National forecast for geothermal resource exploration and development with techniques for policy analysis and resource assessment

    SciTech Connect

    Cassel, T.A.V.; Shimamoto, G.T.; Amundsen, C.B.; Blair, P.D.; Finan, W.F.; Smith, M.R.; Edeistein, R.H.

    1982-03-31

    The backgrund, structure and use of modern forecasting methods for estimating the future development of geothermal energy in the United States are documented. The forecasting instrument may be divided into two sequential submodels. The first predicts the timing and quality of future geothermal resource discoveries from an underlying resource base. This resource base represents an expansion of the widely-publicized USGS Circular 790. The second submodel forecasts the rate and extent of utilization of geothermal resource discoveries. It is based on the joint investment behavior of resource developers and potential users as statistically determined from extensive industry interviews. It is concluded that geothermal resource development, especially for electric power development, will play an increasingly significant role in meeting US energy demands over the next 2 decades. Depending on the extent of R and D achievements in related areas of geosciences and technology, expected geothermal power development will reach between 7700 and 17300 Mwe by the year 2000. This represents between 8 and 18% of the expected electric energy demand (GWh) in western and northwestern states.

  6. Flood Protection Structure Accreditation Task Force: Interim Report

    E-print Network

    US Army Corps of Engineers

    Flood Protection Structure Accreditation Task Force: Interim Report January 2, 2013 #12;FLOOD States Army Corps of Engineers (USACE) are pleased to present this report, titled "Flood Protection inspections and assessments and the National Flood Insurance Program levee accreditation requirements

  7. 44 CFR 78.6 - Flood Mitigation Plan approval process.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...Assistance 1 2014-10-01 2014-10-01 false Flood Mitigation Plan approval process. 78.6 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood...

  8. 44 CFR 78.6 - Flood Mitigation Plan approval process.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...Assistance 1 2011-10-01 2011-10-01 false Flood Mitigation Plan approval process. 78.6 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood...

  9. 44 CFR 78.6 - Flood Mitigation Plan approval process.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...Assistance 1 2013-10-01 2013-10-01 false Flood Mitigation Plan approval process. 78.6 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood...

  10. 44 CFR 78.6 - Flood Mitigation Plan approval process.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...Assistance 1 2012-10-01 2011-10-01 true Flood Mitigation Plan approval process. 78.6 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood...

  11. 44 CFR 78.5 - Flood Mitigation Plan development.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...Assistance 1 2012-10-01 2011-10-01 true Flood Mitigation Plan development. 78.5 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood...

  12. 44 CFR 78.5 - Flood Mitigation Plan development.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...Assistance 1 2014-10-01 2014-10-01 false Flood Mitigation Plan development. 78.5 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood...

  13. 44 CFR 78.5 - Flood Mitigation Plan development.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...Assistance 1 2011-10-01 2011-10-01 false Flood Mitigation Plan development. 78.5 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood...

  14. 44 CFR 78.5 - Flood Mitigation Plan development.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...Assistance 1 2013-10-01 2013-10-01 false Flood Mitigation Plan development. 78.5 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood...

  15. 44 CFR 78.6 - Flood Mitigation Plan approval process.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...Assistance 1 2010-10-01 2010-10-01 false Flood Mitigation Plan approval process. 78.6 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood...

  16. 44 CFR 78.5 - Flood Mitigation Plan development.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...Assistance 1 2010-10-01 2010-10-01 false Flood Mitigation Plan development. 78.5 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood...

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

    USGS Publications Warehouse

    Storm, John B.

    2014-01-01

    Digital flood-inundation maps for a 6.8-mile reach of the Leaf River at Hattiesburg, Mississippi (Miss.), were created by the U.S. Geological Survey (USGS) in cooperation with the City of Hattiesburg, City of Petal, Forrest County, Mississippi Emergency Management Agency, Mississippi Department of Homeland Security, and the Emergency Management District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Leaf River at Hattiesburg, Miss. (station no. 02473000). Current conditions for estimating near-real-time areas of inundation by use of USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relations at the Leaf River at Hattiesburg, Miss. streamgage (02473000) and documented high-water marks from recent and historical floods. The hydraulic model was then used to determine 13 water-surface profiles for flood stages at 1.0-foot intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from light detection and ranging (lidar) data having a 0.6-foot vertical and 9.84-foot horizontal resolution) in order to delineate the area flooded at each water level. Development of the estimated flood inundation maps as described in this report update previously published inundation estimates by including reaches of the Bouie and Leaf Rivers above their confluence. The availability of these maps along with Internet information regarding current stage from USGS streamgages and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post flood recovery efforts.

  18. Severe Flooding in India

    NASA Technical Reports Server (NTRS)

    2002-01-01

    Floods devestated parts of eastern India along the Brahmaputra River in June 2000. In some tributaries of the Brahmaputra, the water reached more than 5 meters (16.5 feet) above flood stage. At least 40 residents died, and the flood waters destroyed a bridge linking the region to the rest of India. High water also threatened endangered Rhinos in Kaziranga National Park. Flooded areas are shown in red in the above image. The map was derived from Advanced Very High Resolution Radiometer (AVHRR) data taken on June 15, 2000. For more information on observing floods with satellites, see: Using Satellites to Keep our Head above Water and the Dartmouth Flood Observatory Image by the Dartmouth Flood Observatory

  19. Namibian Flood Early Warning SensorWeb Pilot

    NASA Technical Reports Server (NTRS)

    Mandl, Daniel; Policelli, Fritz; Frye, Stuart; Cappelare, Pat; Langenhove, Guido Van; Szarzynski, Joerg; Sohlberg, Rob

    2010-01-01

    The major goal of the Namibia SensorWeb Pilot Project is a scientifically sound, operational trans-boundary flood management decision support system for Southern African region to provide useful flood and waterborne disease forecasting tools for local decision makers. The Pilot Project established under the auspices of: Namibian Ministry of Agriculture Water and Forestry (MAWF), Department of Water Affairs; Committee on Earth Observing Satellites (CEOS), Working Group on Information Systems and Services (WGISS); and moderated by the United Nations Platform for Space-based Information for Disaster Management and Emergency Response (UN-SPIDER). The effort consists of identifying and prototyping technology which enables the rapid gathering and dissemination of both space-based and ground sensor data and data products for the purpose of flood disaster management and water-borne disease management.

  20. Forecasting the Effects of Fertility Control on Overabundant Ungulates: White-Tailed Deer in the National Capital Region

    PubMed Central

    Raiho, Ann M.; Hooten, Mevin B.; Bates, Scott; Hobbs, N. Thompson

    2015-01-01

    Overabundant populations of ungulates have caused environmental degradation and loss of biological diversity in ecosystems throughout the world. Culling or regulated harvest is often used to control overabundant species. These methods are difficult to implement in national parks, other types of conservation reserves, or in residential areas where public hunting may be forbidden by policy. As a result, fertility control has been recommended as a non-lethal alternative for regulating ungulate populations. We evaluate this alternative using white-tailed deer in national parks in the vicinity of Washington, D.C., USA as a model system. Managers seek to reduce densities of white-tailed deer from the current average (50 deer per km2) to decrease harm to native plant communities caused by deer. We present a Bayesian hierarchical model using 13 years of population estimates from 8 national parks in the National Capital Region Network. We offer a novel way to evaluate management actions relative to goals using short term forecasts. Our approach confirms past analyses that fertility control is incapable of rapidly reducing deer abundance. Fertility control can be combined with culling to maintain a population below carrying capacity with a high probability of success. This gives managers confronted with problematic overabundance a framework for implementing management actions with a realistic assessment of uncertainty. PMID:26650739

  1. ANN modeling for flood prediction in the upstream Eure's catchment (France)

    NASA Astrophysics Data System (ADS)

    Kharroubi, Ouissem; masson, Eric; Blanpain, Olivier; Lallahem, Sami

    2013-04-01

    Rainfall-Runoff relationship at basin scale is strongly depending on the catchment complexity including multi-scale interactions. In extreme events cases (i.e. floods and droughts) this relationship is even more complex and differs from average hydrological conditions making extreme runoff prediction very difficult to achieve. However, flood warning, flood prevention and flood mitigation rely on the possibility to predict both flood peak runoff and lag time. This point is crucial for decision making and flood warning to prevent populations and economical stakes to be damaged by extreme hydrological events. Since 2003 in France, a dedicated state service is in charge of producing flood warning from national level (i.e. SCHAPI) to regional level (i.e. SPC). This flood warning service is combining national weather forecast agency (i.e. Meteo France) together with a fully automated realtime hydrological network (i.e. Rainfall-Runoff) in order to produce a flood warning national map online and provide a set of hydro-meteorological data to the SPC in charge of flood prediction from regional to local scale. The SPC is in fact the flood service delivering hydrological prediction at operational level for decision making about flood alert for municipalities and first help services. Our research in collaboration with the SPC SACN (i.e. "Seine Aval et fleuves Côtiers Normands") is focused on the implementation of an Artificial Neural Network model (ANN) for flood prediction in deferent key points of the Eure's catchment and main subcatchment. Our contribution will focus on the ANN model developed for Saint-Luperce gauging station in the upstream part of the Eure's catchment. Prediction of extreme runoff at Saint-Luperce station is of high importance for flood warning in the Eure's catchment because it gives a good indicator on the extreme status and the downstream propagation of a potential flood event. Despite a good runoff monitoring since 27 years Saint Luperce flood prediction remains a challenge for modeling tools used by the SPC SACN. Calibration phases (i.e. learning, test and validation) of Saint Luperce ANN model will be presented and the efficiency assessment will be discussed by mean of RMSE and Cp indicators for different lag time predictions (i.e. +6h, +12h, +24h, +48h). Our conclusions will address the overall added value of using ANN modeling for flood prediction in the Eure's catchment regarding to the SPC SACN objectives.

  2. Warm Season Storms, Floods, and Tributary Sand Inputs below Glen Canyon Dam: Investigating Salience to Adaptive Management in the Context of a 10-Year Long Controlled Flooding Experiment in Grand Canyon National Park, AZ, USA

    NASA Astrophysics Data System (ADS)

    Jain, S.; Melis, T. S.; Topping, D. J.; Pulwarty, R. S.; Eischeid, J.

    2013-12-01

    The planning and decision processes in the Glen Canyon Dam Adaptive Management Program (GCDAMP) strive to balance numerous, often competing, objectives, such as, water supply, hydropower generation, low flow maintenance, maximizing conservation of downstream tributary sand supply, endangered native fish, and other sociocultural resources of Glen Canyon National Recreation Area and Grand Canyon National Park. In this context, use of monitored and predictive information on the warm season floods (at point-to-regional scales) has been identified as lead-information for a new 10-year long controlled flooding experiment (termed the High-Flow Experiment Protocol) intended to determine management options for rebuilding and maintaining sandbars in Grand Canyon; an adaptive strategy that can potentially facilitate improved planning and dam operations. In this work, we focus on a key concern identified by the GCDAMP, related to the timing and volume of tributary sand input from the Paria and Little Colorado Rivers (located 26 and 124 km below the dam, respectively) into the Colorado River in Grand Canyon National Park. Episodic and intraseasonal variations (with links to equatorial and sub-tropical Pacific sea surface temperature variability) in the southwest hydroclimatology are investigated to understand the magnitude, timing and spatial scales of warm season floods from this relatively small, but prolific sand producing drainage of the semi-arid Colorado Plateau. The coupled variations of the flood-driven sediment input (magnitude and timing) from these two drainages into the Colorado River are also investigated. The physical processes, including diagnosis of storms and moisture sources, are mapped alongside the planning and decision processes for the ongoing experimental flood releases from the Glen Canyon Dam which are aimed at achieving restoration and maintenance of sandbars and instream ecology. The GCDAMP represents one of the most visible and widely recognized adaptive management efforts in the world to manage resources under growing environmental uncertainty as climate change and global warming continues.

  3. Utilization of Precipitation and Moisture Products Derived from Satellites to Support NOAA Operational Precipitation Forecasts

    NASA Astrophysics Data System (ADS)

    Ferraro, R.; Zhao, L.; Kuligowski, R. J.; Kusselson, S.; Ma, L.; Kidder, S. Q.; Forsythe, J. M.; Jones, A. S.; Ebert, E. E.; Valenti, E.

    2012-12-01

    NOAA/NESDIS operates a constellation of polar and geostationary orbiting satellites to support weather forecasts and to monitor the climate. Additionally, NOAA utilizes satellite assets from other U.S. agencies like NASA and the Department of Defense, as well as those from other nations with similar weather and climate responsibilities (i.e., EUMETSAT and JMA). Over the past two decades, through joint efforts between U.S. and international government researchers, academic partners, and private sector corporations, a series of "value added" products have been developed to better serve the needs of weather forecasters and to exploit the full potential of precipitation and moisture products generated from these satellites. In this presentation, we will focus on two of these products - Ensemble Tropical Rainfall Potential (eTRaP) and Blended Total Precipitable Water (bTPW) - and provide examples on how they contribute to hydrometeorological forecasts. In terms of passive microwave satellite products, TPW perhaps is most widely used to support real-time forecasting applications, as it accurately depicts tropospheric water vapor and its movement. In particular, it has proven to be extremely useful in determining the location, timing, and duration of "atmospheric rivers" which contribute to and sustain flooding events. A multi-sensor approach has been developed and implemented at NESDIS in which passive microwave estimates from multiple satellites and sensors are merged to create a seamless, bTPW product that is more efficient for forecasters to use. Additionally, this product is being enhanced for utilization for television weather forecasters. Examples will be shown to illustrate the roll of atmospheric rivers and contribution to flooding events, and how the bTPW product was used to improve the forecast of these events. Heavy rains associated with land falling tropical cyclones (TC) frequently trigger floods that cause millions of dollars of damage and tremendous loss of lives. To provide observations-based forecast guidance for TC heavy rain, the Tropical Rainfall Potential (TRaP), an extrapolation forecast generated by accumulating rainfall estimates from satellites with microwave sensors as the storm is translated along the forecast track, was originally developed to predict the maximum rainfall at landfall, as well as the spatial pattern of precipitation. More recently, an enhancement has been made to combine the TRaP forecasts from multiple sensors and various start times into an ensemble (eTRaP). The ensemble approach provides not only more accurate quantitative precipitation forecasts, including more skillful maximum rainfall amount and location, it also produces probabilistic forecasts of rainfall exceeding various thresholds that decision makers can use to make critical risk assessments. Examples of the utilization and performance of eTRaP will be given in the presentation.

  4. Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew; Fuell, Kevin; Knaff, John; Lee, Thomas

    2012-01-01

    What is an RGB Composite Image? (1) Current and future satellite instruments provide remote sensing at a variety of wavelengths. (2) RGB composite imagery assign individual wavelengths or channel differences to the intensities of the red, green, and blue components of a pixel color. (3) Each red, green, and blue color intensity is related to physical properties within the final composite image. (4) Final color assignments are therefore related to the characteristics of image pixels. (5) Products may simplify the interpretation of data from multiple bands by displaying information in a single image. Current Products and Usage: Collaborations between SPoRT, CIRA, and NRL have facilitated the use and evaluation of RGB products at a variety of NWS forecast offices and National Centers. These products are listed in table.

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

    SciTech Connect

    Judi, David R; Mcpherson, Timothy N; Burian, Steven J

    2009-01-01

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

  6. GPS Estimates of Integrated Precipitable Water Aid Weather Forecasters

    NASA Technical Reports Server (NTRS)

    Moore, Angelyn W.; Gutman, Seth I.; Holub, Kirk; Bock, Yehuda; Danielson, David; Laber, Jayme; Small, Ivory

    2013-01-01

    Global Positioning System (GPS) meteorology provides enhanced density, low-latency (30-min resolution), integrated precipitable water (IPW) estimates to NOAA NWS (National Oceanic and Atmospheric Adminis tration Nat ional Weather Service) Weather Forecast Offices (WFOs) to provide improved model and satellite data verification capability and more accurate forecasts of extreme weather such as flooding. An early activity of this project was to increase the number of stations contributing to the NOAA Earth System Research Laboratory (ESRL) GPS meteorology observing network in Southern California by about 27 stations. Following this, the Los Angeles/Oxnard and San Diego WFOs began using the enhanced GPS-based IPW measurements provided by ESRL in the 2012 and 2013 monsoon seasons. Forecasters found GPS IPW to be an effective tool in evaluating model performance, and in monitoring monsoon development between weather model runs for improved flood forecasting. GPS stations are multi-purpose, and routine processing for position solutions also yields estimates of tropospheric zenith delays, which can be converted into mm-accuracy PWV (precipitable water vapor) using in situ pressure and temperature measurements, the basis for GPS meteorology. NOAA ESRL has implemented this concept with a nationwide distribution of more than 300 "GPSMet" stations providing IPW estimates at sub-hourly resolution currently used in operational weather models in the U.S.

  7. Current Usage and Future Prospects of Multispectral (RGB) Satellite Imagery in Support of NWS Forecast Offices and National Centers

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew L.; Fuell, Kevin K.; Knaff, John; Lee, Thomas

    2012-01-01

    Current and future satellite sensors provide remotely sensed quantities from a variety of wavelengths ranging from the visible to the passive microwave, from both geostationary and low-Earth orbits. The NASA Short-term Prediction Research and Transition (SPoRT) Center has a long history of providing multispectral imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA s Terra and Aqua satellites in support of NWS forecast office activities. Products from MODIS have recently been extended to include a broader suite of multispectral imagery similar to those developed by EUMETSAT, based upon the spectral channel s available from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) aboard METEOSAT-9. This broader suite includes products that discriminate between air mass types associated with synoptic-scale features, assists in the identification of dust, and improves upon paired channel difference detection of fog and low cloud events. Similarly, researchers at NOAA/NESDIS and CIRA have developed air mass discrimination capabilities using channels available from the current GOES Sounders. Other applications of multispectral composites include combinations of high and low frequency, horizontal and vertically polarized passive microwave brightness temperatures to discriminate tropical cyclone structures and other synoptic-scale features. Many of these capabilities have been transitioned for evaluation and operational use at NWS Weather Forecast Offices and National Centers through collaborations with SPoRT and CIRA. Future instruments will continue the availability of these products and also expand upon current capabilities. The Advanced Baseline Imager (ABI) on GOES-R will improve the spectral, spatial, and temporal resolution of our current geostationary capabilities, and the recent launch of the Suomi National Polar-Orbiting Partnership (S-NPP) carries instruments such as the Visible Infrared Imager Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrIS), and the Advanced Technology Microwave Sounder (ATMS), which have unrivaled spectral and spatial resolution, as precursors to the JPSS era (i.e., the next generation of polar orbiting satellites). At the same time, new image manipulation and display capabilities are available within AWIPS II, the next generation of the NWS forecaster decision support system. This presentation will present a review of SPoRT, CIRA, and NRL collaborations regarding multispectral satellite imagery and articulate an integrated and collaborative path forward with Raytheon AWIPS II development staff for integrating current and future capabilities that support new satellite instrumentation and the AWIPS II decision support system.

  8. Flood-inundation maps for the St. Marys River at Fort Wayne, Indiana

    USGS Publications Warehouse

    Menke, Chad D.; Kim, Moon H.; Fowler, Kathleen K.

    2012-01-01

    Digital flood-inundation maps for a 9-mile reach of the St. Marys River that extends from South Anthony Boulevard to Main Street at Fort Wayne, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Fort Wayne. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at the USGS streamgage 04182000 St. Marys River near Fort Wayne, Ind. Current conditions at the USGS streamgages in Indiana may be obtained from the National Water Information System: Web Interface. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system. The NWS forecasts flood hydrographs at many places that are often collocated at USGS streamgages. That forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, water-surface profiles were simulated for the stream reach by means of a hydraulic one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relation at the USGS streamgage 04182000 St. Marys River near Fort Wayne, Ind. The hydraulic model was then used to simulate 11 water-surface profiles for flood stages at 1-ft intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. A flood inundation map was generated for each water-surface profile stage (11 maps in all) so that for any given flood stage users will be able to view the estimated area of inundation. The availability of these maps along with current stage from USGS streamgages and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post flood recovery efforts.

  9. Navigating a Path Toward Operational, Short-term, Ensemble Based, Probablistic Streamflow Forecasts

    NASA Astrophysics Data System (ADS)

    Hartman, R. K.; Schaake, J.

    2004-12-01

    The National Weather Service (NWS) has federal responsibility for issuing public flood warnings in the United States. Additionally, the NWS has been engaged in longer range water resources forecasts for many years, particularly in the Western U.S. In the past twenty years, longer range forecasts have increasingly incorporated ensemble techniques. Ensemble techniques are attractive because they allow a great deal of flexibility, both temporally and in content. This technique also provides for the influence of additional forcings (i.e. ENSO), through either pre or post processing techniques. More recently, attention has turned to the use of ensemble techniques in the short-term streamflow forecasting process. While considerably more difficult, the development of reliable short-term probabilistic streamflow forecasts has clear application and value for many NWS customers and partners. During flood episodes, expensive mitigation actions are initialed or withheld and critical reservoir management decisions are made in the absence of uncertainty and risk information. Limited emergency services resources and the optimal use of water resources facilities necessitates the development of a risk-based decision making process. The development of reliable short-term probabilistic streamflow forecasts are an essential ingredient in the decision making process. This paper addresses the utility of short-term ensemble streamflow forecasts and the considerations that must be addressed as techniques and operational capabilities are developed. Verification and validation information are discussed from both a scientific and customer perspective. Education and training related to the interpretation and use of ensemble products are also addressed.

  10. Flood-inundation maps for the North Branch Elkhart River at Cosperville, Indiana

    USGS Publications Warehouse

    Kim, Moon H.; Johnson, Esther M.

    2014-01-01

    Digital flood-inundation maps for a reach of the North Branch Elkhart River at Cosperville, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Army Corps of Engineers, Detroit District. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/in/nwis/uv?site_no=04100222. In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http:/water.weather.gov/ahps/). The NWS AHPS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the North Branch Elkhart River at Cosperville, Ind. NWS AHPS-forecast peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the North Branch Elkhart River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind., and preliminary high-water marks from the flood of March 1982. The calibrated hydraulic model was then used to determine four water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging [LiDAR]) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage 04100222, North Branch Elkhart River at Cosperville, Ind., and forecast stream stages from the NWS AHPS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

  11. Flood-inundation maps for the Tippecanoe River near Delphi, Indiana

    USGS Publications Warehouse

    Menke, Chad D.; Bunch, Aubrey R.; Kim, Moon H.

    2013-01-01

    Digital flood-inundation maps for an 11-mile reach of the Tippecanoe River that extends from County Road W725N to State Road 18 below Oakdale Dam, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at USGS streamgage 03333050, Tippecanoe River near Delphi, Ind. Current conditions at the USGS streamgages in Indiana may be obtained online at http://waterdata.usgs.gov/in/nwis/current/?type=flow. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often co-located at USGS streamgages. That forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, water-surface profiles were simulated for the stream reach by means of a hydraulic one-dimensional step-backwater model. The model was calibrated by using the most current stage-discharge relation at USGS streamgage 03333050, Tippecanoe River near Delphi, Ind., and USGS streamgage 03332605, Tippecanoe River below Oakdale Dam, Ind. The hydraulic model was then used to simulate 13 water-surface profiles for flood stages at 1-foot intervals reference to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. A flood inundation map was generated for each water-surface profile stage (13 maps in all) so that, for any given flood stage, users will be able to view the estimated area of inundation. The availability of these maps, along with current stage from USGS streamgages and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

  12. Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use with the National Digital Forecast Database

    E-print Network

    Douches, David S.

    Point-trained models in a grid environment: Transforming a potato late blight risk forecast for use have come to expect. Potato late blight risk models were some of the earliest weather-based models. This analysis compares two types of potato late blight risk models that were originally trained on location

  13. 44 CFR 73.4 - Restoration of flood insurance coverage.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...2011-10-01 false Restoration of flood insurance coverage. 73.4 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4...

  14. 44 CFR 73.4 - Restoration of flood insurance coverage.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2011-10-01 true Restoration of flood insurance coverage. 73.4 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4...

  15. 44 CFR 73.4 - Restoration of flood insurance coverage.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 false Restoration of flood insurance coverage. 73.4 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4...

  16. 44 CFR 73.4 - Restoration of flood insurance coverage.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 false Restoration of flood insurance coverage. 73.4 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4...

  17. 44 CFR 73.4 - Restoration of flood insurance coverage.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...2010-10-01 false Restoration of flood insurance coverage. 73.4 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4...

  18. Scientific developments within the Global Flood Partnership

    NASA Astrophysics Data System (ADS)

    de Groeve, Tom; Alfieri, Lorenzo; Thielen, Jutta

    2015-04-01

    More than 90 scientists, end users, and decision makers in the field of flood forecasting, remote sensing, hazard and risk assessment and emergency management collaborate in the Global Flood Partnership (GFP). The Partnership, launched in 2014, aims at the development of flood observational and modelling infrastructure, leveraging on existing initiatives for better predicting and managing flood disaster impacts and flood risk globally. Scientists collaborate in the GFP in different pillars, respectively focused on (1) development of tools and systems for global flood monitoring (Flood Toolbox), (2) applying the tools for publishing near real-time impact-based flood awareness information (Flood Observatory), and (3) collecting flood maps and impact information in a distributed database (Flood Record). The talk will focus on concrete collaboration results in 2014 and 2015, showing the added value of collaborating under a partnership. These include an overview of 10 services, 5 tools (algorithms or software) and 4 datasets related to global flood forecasting and observation. Through the various results (on interoperability, standards, visualization, integration and system design of integrated systems), it will be shown that a user-centric approach can lead to effective uptake of research results, rapid prototype development and experimental services that fill a gap in global flood response.

  19. 44 CFR 67.3 - Establishment and maintenance of a flood elevation determination docket (FEDD).

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... false Establishment and maintenance of a flood elevation determination docket (FEDD). ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD ELEVATION DETERMINATIONS § 67.3...

  20. 44 CFR 67.3 - Establishment and maintenance of a flood elevation determination docket (FEDD).

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... false Establishment and maintenance of a flood elevation determination docket (FEDD). ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD ELEVATION DETERMINATIONS § 67.3...

  1. 44 CFR 67.3 - Establishment and maintenance of a flood elevation determination docket (FEDD).

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... true Establishment and maintenance of a flood elevation determination docket (FEDD). ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD ELEVATION DETERMINATIONS § 67.3...

  2. Flood estimates for ungaged streams in Glacier and Yellowstone National Parks, Montana

    USGS Publications Warehouse

    Omang, R.J.; Parrett, Charles; Hull, J.A.

    1983-01-01

    Estimates of 100-year discharges were made at 59 sites in Glacier National Park and 21 sites in Yellowstone National Park to assist the National Park Services in quantifying stream inflow and outflow in the Parks. The estimates were made using regression equations previously developed for Montana. The resulting 100-year discharges are listed in tables; the discharges ranged from 260 to 53,200 cu ft/s in Glacier National Park and from 110 to 27,900 cu ft/s in Yellowstone National Park. (USGS)

  3. Developing and Evaluating RGB Composite MODIS Imagery for Applications in National Weather Service Forecast Offices

    NASA Technical Reports Server (NTRS)

    Oswald, Hayden; Molthan, Andrew L.

    2011-01-01

    Satellite remote sensing has gained widespread use in the field of operational meteorology. Although raw satellite imagery is useful, several techniques exist which can convey multiple types of data in a more efficient way. One of these techniques is multispectral compositing. The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed two multispectral satellite imagery products which utilize data from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites, based upon products currently generated and used by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The nighttime microphysics product allows users to identify clouds occurring at different altitudes, but emphasizes fog and low cloud detection. This product improves upon current spectral difference and single channel infrared techniques. Each of the current products has its own set of advantages for nocturnal fog detection, but each also has limiting drawbacks which can hamper the analysis process. The multispectral product combines each current product with a third channel difference. Since the final image is enhanced with color, it simplifies the fog identification process. Analysis has shown that the nighttime microphysics imagery product represents a substantial improvement to conventional fog detection techniques, as well as provides a preview of future satellite capabilities to forecasters.

  4. Estimating monetary damages from flooding under a changing climate

    NASA Astrophysics Data System (ADS)

    Wobus, C. W.; Lawson, M.; Smith, J. B.; Jones, R.; Morlando, S.

    2011-12-01

    Extreme precipitation events will very likely become both more frequent and more extreme under a changing climate. It follows that monetary damages from flooding are also likely to increase; yet translating forecast changes in precipitation to changes in flood damages becomes increasingly difficult as the spatial scale of analysis increases. Our goal was to develop a method for estimating changes in monetary damages from flooding under a changing climate at the national scale. To do this, we compiled precipitation and flood damage data from the 99 ASRs in the continental U.S. (a spatial scale intermediate between 4-digit and 2-digit HUCs), and used statistical modeling to quantify relationships between these variables at the scale of the 18 water resource regions (WRRs) in the U.S. Data on flood damages were obtained from the National climatic Data Center (NCDC) storms database, for the years 1993-2008. Each entry in the database includes the date on which the flood occurred; the county in which it occurred; and the crop damage, property damage, and total damage in dollars associated with the flood event. All dollar values were updated to 2007 dollars using annual Consumer Price Index (CPI) values. Counties were matched to corresponding ASRs, from which all available precipitation station data were downloaded for the same period. A logistic regression model was then used to model the probability of a flood exceeding a specified magnitude of monetary damages, by WRR. Independent variables in the model included the median precipitation across the ASR on that day, the standard deviation of precipitation in the ASR on that day, the total 1-day, 3-day, and 5-day precipitation in the ASR (measured as the sum of precipitation at all stations on the previous days), the season, and the interaction of season with median, standard deviation, and total 1-, 3-, and 5-day precipitation. Separate models were estimated for each WRR under baseline conditions, and flood damages under future climates were then modeled using a range of future precipitation scenarios. The models generally show a positive relationship between median and total precipitation and the probability of a damaging flood occurring. Seasonality also plays a very significant role, although this varies substantially across WRRs. Preliminary results indicate that monetary damages from floods are likely to increase in nearly all regions of the United States, but that changes in damages are not uniformly distributed across the nation.

  5. The Effects of the Saluda Dam on the Surface-Water and Ground-Water Hydrology of the Congaree National Park Flood Plain, South Carolina

    USGS Publications Warehouse

    Conrads, Paul A.; Feaster, Toby D.; Harrelson, Larry G.

    2008-01-01

    The Congaree National Park was established '... to preserve and protect for the education, inspiration, and enjoyment of present and future generations an outstanding example of a near-virgin, southern hardwood forest situated in the Congaree River flood plain in Richland County, South Carolina' (Public Law 94-545). The resource managers at Congaree National Park are concerned about the timing, frequency, magnitude, and duration of flood-plain inundation of the Congaree River. The dynamics of the Congaree River directly affect ground-water levels in the flood plain, and the delivery of sediments and nutrients is constrained by the duration, extent, and frequency of flooding from the Congaree River. The Congaree River is the southern boundary of the Congaree National Park and is formed by the convergence of the Saluda and Broad Rivers 24 river miles upstream from the park. The streamflow of the Saluda River has been regulated since 1929 by the operation of the Saluda Dam at Lake Murray. The U.S. Geological Survey, in cooperation with the National Park Service, Congaree National Park, studied the interaction between surface water in the Congaree River and ground water in the flood plain to determine the effect Saluda Dam operations have on water levels in the Congaree National Park flood plain. Analysis of peak flows showed the reduction in peak flows after the construction of Lake Murray was more a result of climate variability and the absence of large floods after 1930 than the operation of the Lake Murray dam. Dam operations reduced the recurrence interval of the 2-year to 100-year peak flows by 6.1 to 17.6 percent, respectively. Analysis of the daily gage height of the Congaree River showed that the dam has had the effect of lowering high gage heights (95th percentile) in the first half of the year (December to May) and raising low gage heights (5th percentile) in the second half of the year (June to November). The dam has also had the effect of increasing the 1-, 3-, 7-, 30-, and 90-day minimum gage heights by as much as 23.9 percent and decreasing the 1-, 3-, 7-, 30-, and 90-day maximum gage heights by as much as 7.2 percent. Analysis of the ground-water elevations in the Congaree National Park flood plain shows similar results as the gage-height analysis--the dam has had the effect of lowering high ground-water elevations and increasing low ground-water elevations. Overall, the operation of the dam has had a greater effect on the gage heights within the river banks than gage heights in the flood plain. This result may have a greater effect on the subsurface water levels of the surficial flood-plain aquifer than the frequency and magnitude of inundation of the flood plain.

  6. Hydrologic Simulation in Mediterranean flood prone Watersheds using high-resolution quality data

    NASA Astrophysics Data System (ADS)

    Eirini Vozinaki, Anthi; Alexakis, Dimitrios; Pappa, Polixeni; Tsanis, Ioannis

    2015-04-01

    Flooding is a significant threat causing lots of inconveniencies in several societies, worldwide. The fact that the climatic change is already happening, increases the flooding risk, which is no longer a substantial menace to several societies and their economies. The improvement of spatial-resolution and accuracy of the topography and land use data due to remote sensing techniques could provide integrated flood inundation simulations. In this work hydrological analysis of several historic flood events in Mediterranean flood prone watersheds (island of Crete/Greece) takes place. Satellite images of high resolution are elaborated. A very high resolution (VHR) digital elevation model (DEM) is produced from a GeoEye-1 0.5-m-resolution satellite stereo pair and is used for floodplain management and mapping applications such as watershed delineation and river cross-section extraction. Sophisticated classification algorithms are implemented for improving Land Use/ Land Cover maps accuracy. In addition, soil maps are updated with means of Radar satellite images. The above high-resolution data are innovatively used to simulate and validate several historical flood events in Mediterranean watersheds, which have experienced severe flooding in the past. The hydrologic/hydraulic models used for flood inundation simulation in this work are HEC-HMS and HEC-RAS. The Natural Resource Conservation Service (NRCS) curve number (CN) approach is implemented to account for the effect of LULC and soil on the hydrologic response of the catchment. The use of high resolution data provides detailed validation results and results of high precision, accordingly. Furthermore, the meteorological forecasting data, which are also combined to the simulation model results, manage the development of an integrated flood forecasting and early warning system tool, which is capable of confronting or even preventing this imminent risk. The research reported in this paper was fully supported by the "ARISTEIA II" Action ("REINFORCE" program) of the "Operational Education and Life Long Learning programme" and is co-funded by the European Social Fund (ESF) and National Resources.

  7. Feasibility of large-scale water monitoring and forecasting in the Asia-Pacific region

    NASA Astrophysics Data System (ADS)

    van Dijk, A. I. J. M.; Peña-Arancibia, J. L.; Sardella, C. S. E.

    2012-04-01

    The Asian-Pacific region (including China, India and Pakistan) is home to 51% of the global population. It accounts for 53% of agricultural and 32% of domestic water use world wide. Due to the influence of Pacific Ocean and Indian Ocean circulation patterns, the region experiences strong inter-annual variations in water availability and occurrence of drought, flood and severe weather. Some of the countries in the region have national water monitoring or forecasting systems, but they are typically of fairly narrow scope. We investigated the feasibility and utility of an integrated regional water monitoring and forecasting system for water resources, floods and drought. In particular, we assessed the quality of information that can be achieved by relying on internationally available data sources, including numerical weather prediction (NWP) and satellite observations of precipitation, soil moisture and vegetation. Combining these data sources with a large scale hydrological model, we produced monitoring and forecast information for selected retrospective case studies. The information was compared to that from national systems, both in terms of information content and system characteristics (e.g. scope, data sources, and information latency). While national systems typically have better access to national observation systems, they do not always make effective use of the available data, science and technology. The relatively slow changing nature of important Pacific and Indian Ocean circulation patterns adds meaningful seasonal forecast skill for some regions. Satellite and NWP precipitation estimates can add considerable value to the national gauge networks: as forecasts, as near-real time observations and as historic reference data. Satellite observations of soil moisture and vegetation are valuable for drought monitoring and underutilised. Overall, we identify several important opportunities for better water monitoring and forecasting in the Asia-Pacific region.

  8. Flood-inundation maps for the Driftwood River and Sugar Creek near Edinburgh, Indiana

    USGS Publications Warehouse

    Fowler, Kathleen K.; Kim, Moon H.; Menke, Chad D.

    2012-01-01

    Digital flood-inundation maps for an 11.2 mile reach of the Driftwood River and a 5.2 mile reach of Sugar Creek, both near Edinburgh, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Camp Atterbury Joint Maneuver Training Center, Edinburgh, Indiana. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at the USGS streamgage 03363000 Driftwood River near Edinburgh, Ind. Current conditions at the USGS streamgage in Indiana may be obtained on the Internet at http://waterdata.usgs.gov/in/nwis/current/?type=flow. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system at http://water.weather.gov/ahps/. The NWS forecasts flood hydrographs at many places that are often collocated at USGS streamgages. That forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the stream reaches by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relations at the USGS streamgage 03363000 Driftwood River near Edinburgh, Ind. The hydraulic model was then used to determine elevations throughout the study reaches for nine water-surface profiles for flood stages at 1-ft intervals referenced to the streamgage datum and ranging from bankfull to nearly the highest recorded water level at the USGS streamgage 03363000 Driftwood River near Edinburgh, Ind. The simulated water-surface profiles were then combined with a geospatial digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps along with real-time information available online regarding current stage from USGS streamgages and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post flood recovery efforts.

  9. Flood-inundation maps for the White River at Newberry, Indiana

    USGS Publications Warehouse

    Fowler, Kathleen K.; Kim, Moon H.; Menke, Chad D.

    2012-01-01

    Digital flood-inundation maps for a 4.9-mile reach of the White River at Newberry, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at USGS streamgage 03360500, White River at Newberry, Ind. Current conditions at the USGS streamgage may be obtained on the Internet (http://waterdata.usgs.gov/in/nwis/uv?site_no=03360500). The National Weather Service (NWS) forecasts flood hydrographs at the Newberry streamgage. That forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the White River reach by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current stage-discharge relation at USGS streamgage 03360500, White River at Newberry, Ind., and high-water marks from a flood in June 2008.The calibrated hydraulic model was then used to determine 22 water-surface profiles for flood stages a1-foot intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage at Newberry, Ind., and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post-flood recovery efforts.

  10. Cyber Surveillance for Flood Disasters

    PubMed Central

    Lo, Shi-Wei; Wu, Jyh-Horng; Lin, Fang-Pang; Hsu, Ching-Han

    2015-01-01

    Regional heavy rainfall is usually caused by the influence of extreme weather conditions. Instant heavy rainfall often results in the flooding of rivers and the neighboring low-lying areas, which is responsible for a large number of casualties and considerable property loss. The existing precipitation forecast systems mostly focus on the analysis and forecast of large-scale areas but do not provide precise instant automatic monitoring and alert feedback for individual river areas and sections. Therefore, in this paper, we propose an easy method to automatically monitor the flood object of a specific area, based on the currently widely used remote cyber surveillance systems and image processing methods, in order to obtain instant flooding and waterlogging event feedback. The intrusion detection mode of these surveillance systems is used in this study, wherein a flood is considered a possible invasion object. Through the detection and verification of flood objects, automatic flood risk-level monitoring of specific individual river segments, as well as the automatic urban inundation detection, has become possible. The proposed method can better meet the practical needs of disaster prevention than the method of large-area forecasting. It also has several other advantages, such as flexibility in location selection, no requirement of a standard water-level ruler, and a relatively large field of view, when compared with the traditional water-level measurements using video screens. The results can offer prompt reference for appropriate disaster warning actions in small areas, making them more accurate and effective. PMID:25621609

  11. Prediction of a Flash Flood in Complex Terrain. Part II: A Comparison of Flood Discharge Simulations Using Rainfall Input from Radar, a Dynamic Model, and an Automated Algorithmic System.

    NASA Astrophysics Data System (ADS)

    Yates, David N.; Warner, Thomas T.; Leavesley, George H.

    2000-06-01

    Three techniques were employed for the estimation and prediction of precipitation from a thunderstorm that produced a flash flood in the Buffalo Creek watershed located in the mountainous Front Range near Denver, Colorado, on 12 July 1996. The techniques included 1) quantitative precipitation estimation using the National Weather Service's Weather Surveillance Radar-1988 Doppler and the National Center for Atmospheric Research's S-band, dual-polarization radars, 2) quantitative precipitation forecasting utilizing a dynamic model, and 3) quantitative precipitation forecasting using an automated algorithmic system for tracking thunderstorms. Rainfall data provided by these various techniques at short timescales (6 min) and at fine spatial resolutions (150 m to 2 km) served as input to a distributed-parameter hydrologic model for analysis of the flash flood. The quantitative precipitation estimates from the weather radar demonstrated their ability to aid in simulating a watershed's response to precipitation forcing from small-scale, convective weather in complex terrain. That is, with the radar-based quantitative precipitation estimates employed as input, the simulated peak discharge was similar to that estimated. The dynamic model showed the most promise in providing a significant forecast lead time for this flash-flood event. The algorithmic system did not show as much skill in comparison with the dynamic model in providing precipitation forcing to the hydrologic model. The discharge forecasts based on the dynamic-model and algorithmic-system inputs point to the need to improve the ability to forecast convective storms, especially if models such as these eventually are to be used in operational flood forecasting.

  12. Concern about Forecasts of National Faculty Shortages and the Importance of Local Studies. AIR 1991 Annual Forum Paper.

    ERIC Educational Resources Information Center

    Chatman, Steve; Jung, Loren

    This paper questions whether there is sufficient evidence, as presented in the popular press, to support special action to increase the supply of college and university faculty. The higher education popular press has published several forecasts of faculty shortages due to the mass retirement of expansion era faculty and the forecasted low numbers…

  13. Interannual Fluctuations in Atmospheric Angular Momentum Simulated by the National Centers for Environmental Prediction Medium Range Forecast Model

    NASA Technical Reports Server (NTRS)

    Mo, Kingtse C.; Dickey, Jean O.; Marcus, Steven L.

    1997-01-01

    An earlier study established the existence of globally coherent interannual fluctuations in atmospheric angular momentum (AAM), associated with the El Nino-Southern Oscillation (ENSO) cycle. In this paper, we pursue the origin and the structure of these fluctuations using an ensemble of experiments generated by the National Centers for Environmental Prediction, medium range forecast model version 9. In the control experiments, where the observed sea surface temperatures (SSTs) were used as the lower boundary conditions, the model captures the characteristic V-like structure in time-latitude plots of zonally averaged AAM, while experiments with climatological SSTs and those with either perpetual warm or cold ENSO conditions superimposed on the climatological SSTs failed to reproduce this structure. The numerical results indicate that these AAM structures are related to SST variations associated with transitions between different phases of the ENSO cycle and have both propagating and standing components. The largest zonal wind contribution from the levels studied (850, 500, and 200 hPa) is at 200 hPa, where the tropical convective outflow is the strongest. Composites of zonal wind and geopotential height show a clear relationship between the stages of the global AAM oscillation and the ENSO cycle. The strong similarity between the simulated and observed AAM series attests to the model's ability to realistically simulate the interannual response of the atmosphere to ENSO SST anomalies.

  14. Analysis of institutional mechanisms that support community response to impacts of floods in the middle-zambezi river basin, Zimbabwe

    NASA Astrophysics Data System (ADS)

    Muhonda, P.; Mabiza, C.; Makurira, H.; Kujinga, K.; Nhapi, I.; Goldin, J.; Mashauri, D. A.

    In recent years, the frequency of occurrence of floods has increased in Southern Africa. An increase in the frequency of extreme events is partly attributed to climate change. Floods negatively impact on livelihoods, especially those classified as poor, mainly by reducing livelihood options and also contributing to reduced crop yields. In response to these climatic events, governments within Southern Africa have formulated policies which try to mitigate the impacts of floods. Floods can be deadly, often occurring at short notice, lasting for short periods, and causing widespread damage to infrastructure. This study analysed institutional mechanisms in Mbire District of Zimbabwe which aim at mitigating the impact of floods. The study used both quantitative (i.e. questionnaires) and qualitative (i.e. key informant interviews, focus group discussions and observations) data collection methods. Secondary data such as policy and legislation documents and operational manuals of organisations that support communities affected by disasters were reviewed. Qualitative data was analysed using the thematic approach and social network analysis using UCINET 6. Quantitative data were analysed using SPSS 19.0. The study found out that there exists institutional framework that has been developed at the national and local level to support communities in the study area in response to the impacts of floods. This is supported by various pieces of legislation that are housed in different government departments. However, the existing institutional framework does not effectively strengthen disaster management mechanisms at the local level. Lack of financial resources and appropriate training and skills to undertake flood management activities reduce the capacity of communities and disaster management organisations to effectively mitigate the impacts of floods. The study also found that there are inadequate hydro-meteorological stations to enable accurate forecasts. Even in those cases where forecasts predicting extreme weather events have been made, communities have difficulties accessing and interpreting such forecasts due to inadequate communication systems. Such factors reduce the preparedness of communities to deal with extreme weather events.

  15. Inland and coastal flooding: developments in prediction and prevention

    E-print Network

    Hunt, Julian

    of various types of inland and coastal flooding by considering the different causes and dynamic processes forecasting; climate change; natural disasters 1. Introduction Floods are the most serious type of naturalInland and coastal flooding: developments in prediction and prevention BY J. C. R. HUNT 1,2 1

  16. Predictive performance of flood frequency analysis approaches: a national comparison based on an extensive French dataset.

    NASA Astrophysics Data System (ADS)

    Renard, Benjamin; Kochanek, Krzysztof; Lang, Michel; Arnaud, Patrick; Aubert, Yoann; Cipriani, Thomas; Sauquet, Eric

    2013-04-01

    An abundance of methods have been developed over the years to implement flood frequency analysis (FFA). This poster describes a data-based framework aiming at comparing the predictive performance of FFA implementations, and shows the results of its application to an extensive dataset of French gauging stations. The comparison framework is based on the following general principles: (i) emphasis is put on the predictive ability of competing FFA implementations, rather than their sole descriptive ability measured by some goodness-of-fit criterion; (ii) predictive ability is quantified by means of reliability indices, describing the consistency between validation data (not used for calibration) and FFA predictions; (iii) stability is also quantified, i.e. the ability of a FFA implementation to yield similar estimates when calibration data change; (iv) the necessity to subject uncertainty estimates to the same scrutiny as point-estimates is recognized, and a practical approach based on the use of the predictive distribution is proposed for this purpose. This framework is then applied to a case study involving more than one thousand gauging stations in France, where several FA implementations are compared. These implementations correspond to the local, regional and local-regional estimation of Gumbel and Generalized Extreme Value (GEV) distributions. In addition, a "derived distribution" approach based on a rainfall simulator coupled with a rainfall-runoff model is also considered. Results suggest that the local-regional estimation of a GEV distribution and the derived distribution approach are the two most reliable implementations in terms of predictive performance. Moreover, the results also illustrate the feasibility of a data-based comparison of FFA implementations : reliability and stability indices are able to reveal marked difference between FFA implementations, and using the predictive distribution enables an indirect assessment of the reliability of uncertainty estimates.

  17. The WMO Coastal Inundation Forecasting Demonstration Project (CIFDP)

    NASA Astrophysics Data System (ADS)

    Lee, Boram; Resio, Don; Swail, Val; Fakhruddin, Shm; Horsburgh, Kevin

    2014-05-01

    Coastal inundations are an increasing threat to the lives and livelihoods of people living in low-lying, highly-populated coastal areas. According to the World Bank Report 2005, at least 2.6 million people have drowned in coastal inundation, particularly caused by storm surges, over the last 200 years. The purpose of the WMO Coastal Inundation Forecasting Demonstration Project (CIFDP) is to meet the challenges of coastal communities' safety and to support sustainable development through enhancing coastal inundation forecasting and warning systems at the regional scale. Upon completion of national sub-projects of CIFDP, countries will implement an operational system for integrated coastal inundation forecasting and warning, providing an objective basis for coastal disaster (flooding) management; contributing to saving lives, reducing loss of livelihood and property, and enhancing resilience and sustainability in coastal communities. Operation and maintenance of the CIF system would be the responsibility of national operational agencies with a mandate for coastal inundation warnings. The main focus of the CIFDP will be to facilitate the development of efficient forecasting and warning systems for coastal inundation based on robust science and observations: The presentation will describe the scope and the technical framework for CIFDP and describe its implementation in the various sub-projects presently underway.

  18. Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs

    E-print Network

    Ganguly, Auroop Ratan

    2002-01-01

    Applications of distributed Quantitative Precipitation Forecasts (QPF) range from flood forecasting to transportation. Obtaining QPF is acknowledged to be one of the most challenging areas in hydrology and meteorology. ...

  19. Precipitation forecasts for rainfall runoff predictions. A case study in poorly gauged Ribb and Gumara catchments, upper Blue Nile, Ethiopia

    NASA Astrophysics Data System (ADS)

    Seyoum, Mesgana; van Andel, Schalk Jan; Xuan, Yunqing; Amare, Kibreab

    Flow forecasting in poorly gauged, flood-prone Ribb and Gumara sub-catchments of the Blue Nile was studied with the aim of testing the performance of Quantitative Precipitation Forecasts (QPFs). Four types of QPFs namely MM5 forecasts with a spatial resolution of 2 km; the Maximum, Mean and Minimum members (MaxEPS, MeanEPS and MinEPS where EPS stands for Ensemble Prediction System) of the fixed, low resolution (2.5 by 2.5 degrees) National Oceanic and Atmospheric Administration Global Forecast System (NOAA GFS) ensemble forecasts were used. Both the MM5 and the EPS were not calibrated (bias correction, downscaling (for EPS), etc.). In addition, zero forecasts assuming no rainfall in the coming days, and monthly average forecasts assuming average monthly rainfall in the coming days, were used. These rainfall forecasts were then used to drive the Hydrologic Engineering Center’s-Hydrologic Modeling System, HEC-HMS, hydrologic model for flow predictions. The results show that flow predictions using MaxEPS and MM5 precipitation forecasts over-predicted the peak flow for most of the seven events analyzed, whereas under-predicted peak flow was found using zero- and monthly average rainfall. The comparison of observed and predicted flow hydrographs shows that MM5, MaxEPS and MeanEPS precipitation forecasts were able to capture the rainfall signal that caused peak flows. Flow predictions based on MaxEPS and MeanEPS gave results that were quantitatively close to the observed flow for most events, whereas flow predictions based on MM5 resulted in large overestimations for some events. In follow-up research for this particular case study, calibration of the MM5 model will be performed. The overall analysis shows that freely available atmospheric forecasting products can provide additional information on upcoming rainfall and peak flow events in areas where only base-line forecasts such as no-rainfall or climatology are available.

  20. Two-dimensional simulation of the June 11, 2010, flood of the Little Missouri River at Albert Pike Recreational Area, Ouachita National Forest, Arkansas

    USGS Publications Warehouse

    Wagner, Daniel M.

    2013-01-01

    In the early morning hours of June 11, 2010, substantial flooding occurred at Albert Pike Recreation Area in the Ouachita National Forest of west-central Arkansas, killing 20 campers. The U.S. Forest Service needed information concerning the extent and depth of flood inundation, the water velocity, and flow paths throughout Albert Pike Recreation Area for the flood and for streamflows corresponding to annual exceedence probabilities of 1 and 2 percent. The two-dimensional flow model Fst2DH, part of the Federal Highway Administration’s Finite Element Surface-water Modeling System, and the graphical user interface Surface-water Modeling System (SMS) were used to perform a steady-state simulation of the flood in a 1.5-mile reach of the Little Missouri River at Albert Pike Recreation Area. Peak streamflows of the Little Missouri River and tributary Brier Creek served as inputs to the simulation, which was calibrated to the surveyed elevations of high-water marks left by the flood and then used to predict flooding that would result from streamflows corresponding to annual exceedence probabilities of 1 and 2 percent. The simulated extent of the June 11, 2010, flood matched the observed extent of flooding at Albert Pike Recreation Area. The mean depth of inundation in the camp areas was 8.5 feet in Area D, 7.4 feet in Area C, 3.8 feet in Areas A, B, and the Day Use Area, and 12.5 feet in Lowry’s Camp Albert Pike. The mean water velocity was 7.2 feet per second in Area D, 7.6 feet per second in Area C, 7.2 feet per second in Areas A, B, and the Day Use Area, and 7.6 feet per second in Lowry’s Camp Albert Pike. A sensitivity analysis indicated that varying the streamflow of the Little Missouri River had the greatest effect on simulated water-surface elevation, while varying the streamflow of tributary Brier Creek had the least effect. Simulated water-surface elevations were lower than those modeled by the U.S. Forest Service using the standard-step method, but the comparison between the two was favorable with a mean absolute difference of 0.58 feet in Area C and 0.32 feet in Area D. Results of a HEC-RAS model of the Little Missouri River watershed upstream from the U.S. Geological Survey streamflow-gaging station near Langley showed no difference in mean depth in the areas in common between the models, and a difference in mean velocity of only 0.5 foot per second. Predictions of flooding that would result from streamflows corresponding to annual exceedence probabilities of 1 and 2 percent indicated that the extent of inundation of the June 11, 2010, flood exceeded that of the 1 percent flood, and that for both the 1 and 2 percent floods, all of Areas C and D, and parts of Areas A, B, and the Day Use Area were inundated. Predicted water-surface elevations for the 1 and 2 percent floods were approximately 1 foot lower than those predicted by the U.S. Forest Service using a standard-step model.

  1. Forecasting the impact of demographic change: the case of the British National Health Service.

    PubMed

    Gray, A M; Bosanquet, N

    1992-01-01

    By projecting trends over the period 1971-85 in discharge rates and lengths of stay in acute and geriatric National Health Service hospitals in England, it is estimated that by 1995 the discharge rate will have risen by 13% and average lengths of stay will have fallen by 26%. Combining these projections with current population projections for England, it is estimated that 13% fewer beds will be in daily use. These changes are shown to vary widely across specialties. The projections reveal that demographic change per se is a less important source of change than are changing activity rates. The 'trend' projections suggest that purchasers and providers within internal markets will have to take account of very different degrees of pressure between specialties. They can provide information which is essential for negotiations about local needs and local contracts. PMID:10118011

  2. Potential flood and debris hazards at Katherine Landing and Telephone Cove, Lake Mead National Recreation Area, Mohave County, Arizona

    USGS Publications Warehouse

    Moosburner, Otto

    1988-01-01

    Katherine Landing is a recreation site on the east shore of Lake Mohave, an impoundment on the Colorado River southeast of Las Vegas, Nevada. With proper inspection and maintenance, the present (1979) channel and diking system at Katherine Landing is judged adequate to confine and restrain floods up to and including the 100-yr flood. In contrast, the 500-yr flood probably would not be confined by some parts of the diking system. The Telephone Cove area, traversed by North and South Telephone Cove Washes, is hazardous for all floods, especially for the 100-yr and more severe floods. Determinations of peak discharge are based on streamflow regression analyses, and channel capacities are based on field surveys of channel-flow capacities. The extreme flood - a flood meteorologically and hydrologically possible but so rare as to preclude a frequency estimate - could cause great damage and possible loss of life at both the Katherine Landing and the Telephone Cove sites. The present dikes would be topped or breached by extreme flooding. (USGS)

  3. Verification of Ensemble Forecasts for the New York City Operations Support Tool

    NASA Astrophysics Data System (ADS)

    Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

    2012-12-01

    The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble forecasts is needed to verify that the post-processed forecasts are unbiased, statistically reliable, and preserve the skill inherent in the "raw" NWS ensemble forecasts. A verification procedure and set of metrics will be presented that provide an objective assessment of ensemble forecasts. The procedure will be applied to both raw ensemble hindcasts and to post-processed ensemble hindcasts. The verification metrics will be used to validate proper functioning of the post-processor and to provide a benchmark for comparison of different types of forecasts. For example, current NWS ensemble forecasts are based on climatology, using each historical year to generate a forecast trace. The NWS Hydrologic Ensemble Forecast System (HEFS) under development will utilize output from both the National Oceanic Atmospheric Administration (NOAA) Global Ensemble Forecast System (GEFS) and the Climate Forecast System (CFS). Incorporating short-term meteorological forecasts and longer-term climate forecast information should provide sharper, more accurate forecasts. Hindcasts from HEFS will enable New York City to generate verification results to validate the new forecasts and further fine-tune system operating rules. Project verification results will be presented for different watersheds across a range of seasons, lead times, and flow levels to assess the quality of the current ensemble forecasts.

  4. 44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...2011-10-01 2011-10-01 false Standard Flood Insurance Policy Interpretations. ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.14 Standard Flood Insurance Policy Interpretations....

  5. 44 CFR 61.17 - Group Flood Insurance Policy.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2012-10-01 2011-10-01 true Group Flood Insurance Policy. 61.17 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A...

  6. 44 CFR 61.13 - Standard Flood Insurance Policy.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...2010-10-01 2010-10-01 false Standard Flood Insurance Policy. 61.13 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.13 Standard Flood Insurance Policy. (a)...

  7. 44 CFR 67.4 - Proposed flood elevation determination.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 2013-10-01 false Proposed flood elevation determination. 67.4 Section... INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD ELEVATION DETERMINATIONS § 67.4...

  8. 44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 2013-10-01 false Standard Flood Insurance Policy Interpretations. ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.14 Standard Flood Insurance Policy Interpretations....

  9. 44 CFR 67.4 - Proposed flood elevation determination.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 2014-10-01 false Proposed flood elevation determination. 67.4 Section... INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD ELEVATION DETERMINATIONS § 67.4...

  10. 44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 2014-10-01 false Standard Flood Insurance Policy Interpretations. ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.14 Standard Flood Insurance Policy Interpretations....

  11. 44 CFR 61.13 - Standard Flood Insurance Policy.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 2013-10-01 false Standard Flood Insurance Policy. 61.13 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.13 Standard Flood Insurance Policy. (a)...

  12. 44 CFR 61.17 - Group Flood Insurance Policy.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 2014-10-01 false Group Flood Insurance Policy. 61.17 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A...

  13. 44 CFR 61.13 - Standard Flood Insurance Policy.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2012-10-01 2011-10-01 true Standard Flood Insurance Policy. 61.13 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.13 Standard Flood Insurance Policy. (a)...

  14. 44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...2010-10-01 2010-10-01 false Standard Flood Insurance Policy Interpretations. ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.14 Standard Flood Insurance Policy Interpretations....

  15. 44 CFR 61.17 - Group Flood Insurance Policy.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 2013-10-01 false Group Flood Insurance Policy. 61.17 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A...

  16. 44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2012-10-01 2011-10-01 true Standard Flood Insurance Policy Interpretations. ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.14 Standard Flood Insurance Policy Interpretations....

  17. 44 CFR 67.4 - Proposed flood elevation determination.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2012-10-01 2011-10-01 true Proposed flood elevation determination. 67.4 Section... INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD ELEVATION DETERMINATIONS § 67.4...

  18. 44 CFR 61.17 - Group Flood Insurance Policy.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...2011-10-01 2011-10-01 false Group Flood Insurance Policy. 61.17 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A...

  19. 44 CFR 61.17 - Group Flood Insurance Policy.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...2010-10-01 2010-10-01 false Group Flood Insurance Policy. 61.17 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A...

  20. 44 CFR 61.13 - Standard Flood Insurance Policy.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 2014-10-01 false Standard Flood Insurance Policy. 61.13 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.13 Standard Flood Insurance Policy. (a)...

  1. 44 CFR 61.13 - Standard Flood Insurance Policy.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...2011-10-01 2011-10-01 false Standard Flood Insurance Policy. 61.13 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.13 Standard Flood Insurance Policy. (a)...

  2. Flood Resilient Technological Products

    NASA Astrophysics Data System (ADS)

    Diez Gonzalez, J. J.; Monnot, J. V.; Marquez Paniagua, P.; Pámpanas, P.; Paz Abuín, S.; Prendes, P.; Videra, O.; U. P. M. Smartest Team

    2012-04-01

    As a consequence of the paradigm shift of the EU water policy (Directive 2007/60/EC, EC 2003) from defense to living with flood, floods shall be faced in the future through resilient solutions, seeking to improve the permanence of flood protection, and getting thus beyond traditional temporary and human-relying solutions. But the fact is that nowadays "Flood Resilient (FRe) Building Technological Products" is an undefined concept, and concerned FRe solutions cannot be even easily identified. "FRe Building Technological materials" is a wide term involving a wide and heterogeneous range of solutions. There is an interest in offering an identification and classification of the referred products, since it will be useful for stakeholders and populations at flood risk for adopting the most adequate protections when facing floods. Thus, a previous schematic classification would enable us at least to identify most of them and to figure out autonomous FRe Technological Products categories subject all of them to intense industrial innovative processes. The flood resilience enhancement of a given element requires providing it enough water-repelling capacity, and different flood resilient solutions can be sorted out: barriers, waterproofing and anticorrosive. Barriers are palliative solutions that can be obtained either from traditional materials, or from technological ones, offering their very low weight and high maneuverability. Belonging barriers and waterproofing systems to industrial branches clearly different, from a conceptual point of view, waterproofing material may complement barriers, and even be considered as autonomous barriers in some cases. Actually, they do not only complement barriers by their application to barriers' singular weak points, like anchors, joints, but on the other hand, waterproofing systems can be applied to enhance the flood resilience of new building, as preventive measure. Anticorrosive systems do belong to a clearly different category because their function do not consist in repelling water, but in preventing damages caused by the watery contact. Finally, others preventive flood resilient technologies could also be considered, since forecasting, near-casting and warning alert are solutions getting more and more involved in flood resilience strategies.

  3. A global approach to defining flood seasons

    NASA Astrophysics Data System (ADS)

    Lee, D.; Ward, P.; Block, P.

    2015-04-01

    Globally, flood catastrophes lead all natural hazards in terms of impacts on society, causing billions of dollars of damages annually. While short-term flood warning systems are improving in number and sophistication, forecasting systems on the order of months to seasons are a rarity, yet may lead to further disaster preparedness. To lay the groundwork for prediction, dominant flood seasons must be adequately defined. A global approach is adopted here, using the PCR-GLOBWB model to define spatial and temporal characteristics of major flood seasons globally. The main flood season is identified using a volume-based threshold technique. In comparison with observations, 40% (50%) of locations at a station (sub-basin) scale have identical peak months and 81% (89%) are within 1 month, indicating strong agreement between model and observed flood seasons. Model defined flood seasons are additionally found to well represent actual flood records from the Dartmouth Flood Observatory, further substantiating the models ability to reproduce the appropriate flood season. Minor flood seasons are also defined for regions with bi-modal streamflow climatology. Properly defining flood seasons can lead to prediction through association of streamflow with local and large-scale hydroclimatic indicators, and eventual integration into early warning systems for informed advanced planning and management. This is especially attractive for regions with limited observations and/or little capacity to develop early warning flood systems.

  4. 44 CFR 65.12 - Revision of flood insurance rate maps to reflect base flood elevations caused by proposed...

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...2011-10-01 2011-10-01 false Revision of flood insurance rate maps to reflect base flood elevations caused by proposed encroachments... INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...

  5. 44 CFR 65.12 - Revision of flood insurance rate maps to reflect base flood elevations caused by proposed...

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 2013-10-01 false Revision of flood insurance rate maps to reflect base flood elevations caused by proposed encroachments... INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...

  6. 44 CFR 65.14 - Remapping of areas for which local flood protection systems no longer provide base flood protection.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... true Remapping of areas for which local flood protection systems no longer provide base flood protection. 65.14 Section 65.14 ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...

  7. 44 CFR 65.12 - Revision of flood insurance rate maps to reflect base flood elevations caused by proposed...

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 2014-10-01 false Revision of flood insurance rate maps to reflect base flood elevations caused by proposed encroachments... INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...

  8. 44 CFR 65.14 - Remapping of areas for which local flood protection systems no longer provide base flood protection.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... false Remapping of areas for which local flood protection systems no longer provide base flood protection. 65.14 Section 65.14 ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...

  9. 44 CFR 65.12 - Revision of flood insurance rate maps to reflect base flood elevations caused by proposed...

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2012-10-01 2011-10-01 true Revision of flood insurance rate maps to reflect base flood elevations caused by proposed encroachments... INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...

  10. 44 CFR 65.14 - Remapping of areas for which local flood protection systems no longer provide base flood protection.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... false Remapping of areas for which local flood protection systems no longer provide base flood protection. 65.14 Section 65.14 ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...

  11. 44 CFR 65.14 - Remapping of areas for which local flood protection systems no longer provide base flood protection.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... false Remapping of areas for which local flood protection systems no longer provide base flood protection. 65.14 Section 65.14 ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...

  12. 44 CFR 65.14 - Remapping of areas for which local flood protection systems no longer provide base flood protection.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... false Remapping of areas for which local flood protection systems no longer provide base flood protection. 65.14 Section 65.14 ...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...

  13. Transition of Suomi National Polar-Orbiting Partnership (S-NPP) Data Products for Operational Weather Forecasting Applications

    NASA Technical Reports Server (NTRS)

    Smith, Matthew R.; Molthan, Andrew L.; Fuell, Kevin K.; Jedlovec, Gary J.

    2012-01-01

    SPoRT is a team of NASA/NOAA scientists focused on demonstrating the utility of NASA and future NOAA data and derived products on improving short-term weather forecasts. Work collaboratively with a suite of unique products and selected WFOs in an end-to-end transition activity. Stable funding from NASA and NOAA. Recognized by the science community as the "go to" place for transitioning experimental and research data to the operational weather community. Endorsed by NWS ESSD/SSD chiefs. Proven paradigm for transitioning satellite observations and modeling capabilities to operations (R2O). SPoRT s transition of NASA satellite instruments provides unique or higher resolution data products to complement the baseline suite of geostationary data available to forecasters. SPoRT s partnership with NWS WFOs provides them with unique imagery to support disaster response and local forecast challenges. SPoRT has years of proven experience in developing and transitioning research products to the operational weather community. SPoRT has begun work with CONUS and OCONUS WFOs to determine the best products for maximum benefit to forecasters. VIIRS has already proven to be another extremely powerful tool, enhancing forecasters ability to handle difficult forecasting situations.

  14. Climate change and plant community composition in national parks of the southwestern US: forecasting regional, long-term effects to meet management needs

    USGS Publications Warehouse

    Munson, Seth M.; Belnap, Jayne; Webb, Robert H.; Hubbard, J. Andrew; Reiser, M. Hildegard; Gallo, Kirsten

    2014-01-01

    The National Park Service (NPS) faces tremendous management challenges in the future as climates alter the abundance and distribution of plant species. These challenges will be especially daunting in the southwestern U.S., where large increases in aridity are forecasted. The expected reduction in water availability will negatively affect plant growth and may result in shifts of plant community composition. Synthesis of climate and plant vital sign data from National Park Service Inventory and Monitoring (I&M) networks is essential to provide park managers with important insights into contemporary climate responses and a sound basis to forecast likely future changes at species, community, and ecosystem scales. We describe a collaboration between the U.S. Geological Survey (USGS) and NPS in which we have conducted regional cross-site assessments across the Sonoran and Chihuahuan Deserts to understand plant species responses to past climate and forecast future plant community composition. We also determined whether a widely-implemented vegetation monitoring protocol in these deserts is suitable to track long-term vegetation changes caused by climate and other factors. Our results from these analyses are intended to help natural resource managers identify and prepare for changes in plant cover and community composition and evaluate the efficacy of current monitoring programs.

  15. Flood producing mechanism identification in Otava river

    NASA Astrophysics Data System (ADS)

    Vlasák, T.

    2009-04-01

    Variability of flood causes is strongly determined by geographic environment of catchment area. Identification of unique flood characteristics such as seasonality, precipitation pattern, or typical interference of flood peaks at river confluences could be very useful for flood forecasting and control. Analysis of historical flood causes is proved method to get this knowledge. Paper describes compilation and analysis of Flood Archive (database of flood events), which was developed for application in the scope of flood protection of Otava river basin (2780 km2). Otava river basin is situated in southwest part of the Czech Republic and includes north-western part of Šumava mountain (Böhmer Wald). Archive consists of detail description of 72 flood events (including meteorological causes and hydrological response) that occurred between 1890 and 2006 with peak flow in closing profile at Písek exceeding threshold given as 10-year return period for 1890-1961 and 1-year return period for 1961-2006). Flood formation mechanism in Otava river basin was described using this Archive. The most important features of flood formation mechanism in Otava river basin were described and explained in relation to geographical environment. Predominance of summer floods was found in Otava river basin, and its increase with increasing return period was observed. On the other hand there were only 4 out of 72 flood events with dominant snowmelt contribution to the runoff. Expected difference was found between weather causes of winter and summer floods. Winter floods are generally the consequence of strong western circulation with crossing frontal systems bringing rain precipitation on snow. While summer floods are caused mostly by cyclonic precipitation of stable low pressure formation in Central European area. Different air circulation type results in different wind ward effect of precipitation and consequently different runoff response. Analysis results were used to create complex categorization of floods. It recognizes 9 categories of floods with typical characteristics of air circulation, precipitation pattern as well as runoff response in the Otava river basin.

  16. Estimated Flood-Inundation Mapping for the Upper Blue River, Indian Creek, and Dyke Branch in Kansas City, Missouri, 2006-08

    USGS Publications Warehouse

    Kelly, Brian P.; Huizinga, Richard J.

    2008-01-01

    In the interest of improved public safety during flooding, the U.S. Geological Survey, in cooperation with the city of Kansas City, Missouri, completed a flood-inundation study of the Blue River in Kansas City, Missouri, from the U.S. Geological Survey streamflow gage at Kenneth Road to 63rd Street, of Indian Creek from the Kansas-Missouri border to its mouth, and of Dyke Branch from the Kansas-Missouri border to its mouth, to determine the estimated extent of flood inundation at selected flood stages on the Blue River, Indian Creek, and Dyke Branch. The results of this study spatially interpolate information provided by U.S. Geological Survey gages, Kansas City Automated Local Evaluation in Real Time gages, and the National Weather Service flood-peak prediction service that comprise the Blue River flood-alert system and are a valuable tool for public officials and residents to minimize flood deaths and damage in Kansas City. To provide public access to the information presented in this report, a World Wide Web site (http://mo.water.usgs.gov/indep/kelly/blueriver) was created that displays the results of two-dimensional modeling between Hickman Mills Drive and 63rd Street, estimated flood-inundation maps for 13 flood stages, the latest gage heights, and National Weather Service stage forecasts for each forecast location within the study area. The results of a previous study of flood inundation on the Blue River from 63rd Street to the mouth also are available. In addition the full text of this report, all tables and maps are available for download (http://pubs.usgs.gov/sir/2008/5068). Thirteen flood-inundation maps were produced at 2-foot intervals for water-surface elevations from 763.8 to 787.8 feet referenced to the Blue River at the 63rd Street Automated Local Evaluation in Real Time stream gage operated by the city of Kansas City, Missouri. Each map is associated with gages at Kenneth Road, Blue Ridge Boulevard, Kansas City (at Bannister Road), U.S. Highway 71, and 63rd Street on the Blue River, and at 103rd Street on Indian Creek. The National Weather Service issues peak stage forecasts for Blue Ridge Boulevard, Kansas City (at Bannister Road), U.S. Highway 71, and 63rd Street during floods. A two-dimensional depth-averaged flow model simulated flooding within a hydraulically complex, 5.6-mile study reach of the Blue River between Hickman Mills Drive and 63rd Street. Hydraulic simulation of the study reach provided information for the estimated flood-inundation maps and water-velocity magnitude and direction maps. Flood profiles of the upper Blue River between the U.S. Geological Survey streamflow gage at Kenneth Road and Hickman Mills Drive were developed from water-surface elevations calculated using Federal Emergency Management Agency flood-frequency discharges and 2006 stage-discharge ratings at U.S. Geological Survey streamflow gages. Flood profiles between Hickman Mills Drive and 63rd Street were developed from two-dimensional hydraulic modeling conducted for this study. Flood profiles of Indian Creek between the Kansas-Missouri border and the mouth were developed from water-surface elevations calculated using current stage-discharge ratings at the U.S. Geological Survey streamflow gage at 103rd Street, and water-surface slopes derived from Federal Emergency Management Agency flood-frequency stage-discharge relations. Mapped flood water-surface elevations at the mouth of Dyke Branch were set equal to the flood water-surface elevations of Indian Creek at the Dyke Branch mouth for all Indian Creek water-surface elevations; water-surface elevation slopes were derived from Federal Emergency Management Agency flood-frequency stage-discharge relations.

  17. 44 CFR 78.5 - Flood Mitigation Plan development.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Flood Mitigation Plan..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood Mitigation Plan development. A Flood Mitigation Plan will articulate...

  18. 44 CFR 78.5 - Flood Mitigation Plan development.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 44 Emergency Management and Assistance 1 2012-10-01 2011-10-01 true Flood Mitigation Plan..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood Mitigation Plan development. A Flood Mitigation Plan will articulate...

  19. 44 CFR 78.5 - Flood Mitigation Plan development.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 44 Emergency Management and Assistance 1 2014-10-01 2014-10-01 false Flood Mitigation Plan..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood Mitigation Plan development. A Flood Mitigation Plan will articulate...

  20. 44 CFR 78.5 - Flood Mitigation Plan development.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 44 Emergency Management and Assistance 1 2011-10-01 2011-10-01 false Flood Mitigation Plan..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood Mitigation Plan development. A Flood Mitigation Plan will articulate...

  1. 44 CFR 78.5 - Flood Mitigation Plan development.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 44 Emergency Management and Assistance 1 2013-10-01 2013-10-01 false Flood Mitigation Plan..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood Mitigation Plan development. A Flood Mitigation Plan will articulate...

  2. Pakistan Flooding

    Atmospheric Science Data Center

    2013-04-16

    ... Tens of thousands of villages have been flooded, more than 1,500 people have been killed, and millions have been left homeless. The ... and Aug 11, 2010 Images:  Pakistan Flood location:  Asia thumbnail:  ...

  3. Seasonally Flooded Grasslands -Grand CaymanSeasonally Flooded Grasslands -Grand Cayman 0 1 2 3 4 50.5

    E-print Network

    Exeter, University of

    Seasonally Flooded Grasslands - Grand CaymanSeasonally Flooded Grasslands - Grand Cayman 0 1 2 3 4 Protected Areas Seasonally Flooded Grasslands V.A.1.N.g. #12;Seasonally Flooded Grasslands - Little CaymanSeasonally Flooded Grasslands - Little Cayman 0 0.5 1 1.5 2 2.50.25 Kilometers Cayman Islands National Biodiversity

  4. 78 FR 8089 - Proposed Flood Elevation Determinations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-05

    ...addresses the flooding sources Big Run, Little Loyalsock Creek...addressed the flooding sources Big Run, Little Loyalsock Creek...Big Run...National Geodetic Vertical Datum. + North American Vertical...

  5. 77 FR 67324 - Proposed Flood Elevation Determinations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-11-09

    ...addresses the flooding sources Big Run, Little Loyalsock Creek...addressed the flooding sources Big Run, Little Loyalsock Creek...Big Run...National Geodetic Vertical Datum. + North American Vertical...

  6. Flood risk awareness during the 2011 floods in the central United States: showcasing the importance of hydrologic data and interagency collaboration

    USGS Publications Warehouse

    Holmes, Jr., Robert R.; Schwein, Noreen O.; Shadie, Charles E.

    2012-01-01

    Floods have long had a major impact on society and the environment, evidenced by the more than 1,500 federal disaster declarations since 1952 that were associated with flooding. Calendar year 2011 was an epic year for floods in the United States, from the flooding on the Red River of the North in late spring to the Ohio, Mississippi, and Missouri River basin floods in the spring and summer to the flooding caused by Hurricane Irene along the eastern seaboard in August. As a society, we continually seek to reduce flood impacts, with these efforts loosely grouped into two categories: mitigation and risk awareness. Mitigation involves such activities as flood assessment, flood control implementation, and regulatory activities such as storm water and floodplain ordinances. Risk awareness ranges from issuance of flood forecasts and warnings to education of lay audiences about the uncertainties inherent in assessing flood probability and risk. This paper concentrates on the issue of flood risk awareness, specifically the importance of hydrologic data and good interagency communication in providing accurate and timely flood forecasts to maximize risk awareness. The 2011 floods in the central United States provide a case study of the importance of hydrologic data and the value of proper, timely, and organized communication and collaboration around the collection and dissemination of that hydrologic data in enhancing the effectiveness of flood forecasting and flood risk awareness.

  7. The Significance of Shifts in Precipitation Patterns: Modelling the Impacts of Climate Change and Glacier Retreat on Extreme Flood Events in Denali National Park, Alaska

    PubMed Central

    Crossman, Jill; Futter, Martyn N.; Whitehead, Paul G.

    2013-01-01

    In glacier-fed systems climate change may have various effects over a range of time scales, including increasing river discharge, flood frequency and magnitude. This study uses a combination of empirical monitoring and modelling to project the impacts of climate change on the glacial-fed Middle Fork Toklat River, Denali National Park, Alaska. We use a regional calibration of the model HBV to account for a paucity of long term observed flow data, validating a local application using glacial mass balance data and summer flow records. Two Global Climate Models (HADCM3 and CGCM2) and two IPCC scenarios (A2 and B2) are used to ascertain potential changes in meteorological conditions, river discharge, flood frequency and flood magnitude. Using remote sensing methods this study refines existing estimates of glacial recession rates, finding that since 2000, rates have increased from 24m per year to 68.5m per year, with associated increases in ablation zone ice loss. GCM projections indicate that over the 21st century these rates will increase still further, most extensively under the CGCM2 model, and A2 scenarios. Due to greater winter precipitation and ice and snow accumulation, glaciers release increasing meltwater quantities throughout the 21st century. Despite increases in glacial melt, results indicate that it is predominantly precipitation that affects river discharge. Three of the four IPCC scenarios project increases in flood frequency and magnitude, events which were primarily associated with changing precipitation patterns, rather than extreme temperature increases or meltwater release. Results suggest that although increasing temperatures will significantly increase glacial melt and winter baseflow, meltwater alone does not pose a significant flood hazard to the Toklat River catchment. Projected changes in precipitation are the primary concern, both through changing snow volumes available for melt, and more directly through increasing catchment runoff. PMID:24023925

  8. Flood discharges and hydraulics near the mouths of Wolf Creek, Craig Branch, Manns Creek, Dunloup Creek, and Mill Creek in the New River Gorge National River, West Virginia

    USGS Publications Warehouse

    Wiley, J.B.

    1994-01-01

    The U.S. Geological Survey, in cooperation with the National Park Service, studied the frequency and magnitude of flooding near the mouths of five tributaries to the New River in the New River Gorge National River. The 100-year peak discharge at each tributary was determined from regional frequency equations. The 100-year discharge at Wolf Creek, Craig Branch, Manns Creek, Dunloup Creek, and Mill Creek was 3,400 cubic feet per second, 640 cubic feet per second, 8,200 cubic feet per second, 7,100 cubic feet per second, and 9,400 cubic feet per second, respectively. Flood elevations for each tributary were determined by application of a steady-state, one-dimensional flow model. Manning's roughness coefficients for the stream channels ranged from 0.040 to 0.100. Bridges that would be unable to contain the 100-year flood within the bridge opening included: the State Highway 82 bridge on Wolf Creek, the second Fayette County Highway 25 bridge upstream from the confluence with New River on Dunloup Creek, and an abandoned log bridge on Mill Creek.

  9. The Hat Yai 2000 flood: the worst flood in Thai history

    NASA Astrophysics Data System (ADS)

    Supharatid, Seree

    2006-02-01

    Hat Yai, the largest commercial and tourist city in southern Thailand, is subjected to regular flood events, primarily during the northeast monsoon period. Flooding in this region is recognized as a serious disaster in terms of frequency, rate of risk, and affected areas. The monsoon of 21-25 November 2000 caused extremely heavy rain in the southern part of Thailand, resulting in a great flood occupying Hat Yai. This caused significant damage. Therefore, the use of both structural and non-structural measures is mandatory to reduce the economic losses and the risk for society. This paper investigates two modelling approaches for flood prevention and mitigation of Hat Yai city. First, a hard computing approach by a physically distributed model was applied to study the flood behaviour in a two-dimensional floodplain flow. Second, a soft computing approach using a neuro-genetic algorithm was used to develop a flood-forecasting tool. It was found that the great flood of 2000 can be simulated well by the FLO-2D model. Computed discharges and flood level in the floodplain are close to the observed data. Countermeasures using diversion canals are guaranteed to accelerate the floodwater drainage to Songkla Lake, significantly reducing the flood impact to the people. In addition, the flood forecasting technique developed in this study can give satisfactory results. This would be very useful as a flood-warning tool for the community

  10. 44 CFR 73.3 - Denial of flood insurance coverage.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Denial of flood insurance..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3 Denial of flood...

  11. 44 CFR 73.4 - Restoration of flood insurance coverage.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Restoration of flood... AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4 Restoration of flood...

  12. 44 CFR 73.4 - Restoration of flood insurance coverage.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 44 Emergency Management and Assistance 1 2014-10-01 2014-10-01 false Restoration of flood... AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4 Restoration of flood...

  13. 44 CFR 73.4 - Restoration of flood insurance coverage.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 44 Emergency Management and Assistance 1 2011-10-01 2011-10-01 false Restoration of flood... AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4 Restoration of flood...

  14. 44 CFR 73.3 - Denial of flood insurance coverage.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 44 Emergency Management and Assistance 1 2014-10-01 2014-10-01 false Denial of flood insurance..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3 Denial of flood...

  15. 44 CFR 73.3 - Denial of flood insurance coverage.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 44 Emergency Management and Assistance 1 2012-10-01 2011-10-01 true Denial of flood insurance..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3 Denial of flood...

  16. 44 CFR 73.4 - Restoration of flood insurance coverage.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 44 Emergency Management and Assistance 1 2012-10-01 2011-10-01 true Restoration of flood insurance..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4 Restoration of flood...

  17. 44 CFR 73.3 - Denial of flood insurance coverage.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 44 Emergency Management and Assistance 1 2011-10-01 2011-10-01 false Denial of flood insurance..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3 Denial of flood...

  18. 44 CFR 73.3 - Denial of flood insurance coverage.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 44 Emergency Management and Assistance 1 2013-10-01 2013-10-01 false Denial of flood insurance..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3 Denial of flood...

  19. 44 CFR 73.4 - Restoration of flood insurance coverage.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 44 Emergency Management and Assistance 1 2013-10-01 2013-10-01 false Restoration of flood... AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4 Restoration of flood...

  20. Progress in Multi-Center Probabilistic Wave Forecasting and Ensemble-Based Data Assimilation using LETKF at the US National Weather Service

    NASA Astrophysics Data System (ADS)

    Alves, Jose-Henrique; Bernier, Natacha; Etala, Paula; Wittmann, Paul

    2015-04-01

    The combination of ensemble predictions of Hs made by the US National Weather Service (NEW) and the US Navy Fleet Numerical Meteorological and Oceanography Center (FNMOC) has established the NFCENS, a probabilistic wave forecast system in operations at NCEP since 2011. Computed from 41 combined wave ensemble members, the new product outperforms deterministic and probabilistic forecasts and nowcasts of Hs issued separately at each forecast center, at all forecast ranges. The successful implementation of the NFCENS has brought new opportunities for collaboration with Environment Canada (EC). EC is in the process of adding new global wave model ensemble products to its existing suite of operational regional products. The planned upgrade to the current NFCENS wave multi-center ensemble includes the addition of 20 members from the Canadian WES. With this upgrade, the NFCENS will be renamed North American Wave Ensemble System (NAWES). As part of the new system implementation, new higher-resolution grids and upgrades to model physics using recent advances in source-term parameterizations are being tested. We provide results of a first validation of NAWES relative to global altimeter data, and buoy measurements of waves, as well as its ability to forecast waves during the 2012 North Atlantic hurricane Sandy. A second line of research involving wave ensembles at the NWS is the implementation of a LETKF-based data assimilation system developed in collaboration with the Argentinian Navy Meteorological Service. The project involves an implementation of the 4D-LETKF in the NWS global wave ensemble forecast system GWES. The 4-D scheme initializes a full 81-member ensemble in a 6-hour cycle. The LETKF determines the analysis ensemble locally in the space spanned by the ensemble, as a linear combination of the background perturbations. Observations from three altimeters and one scatterometer were used. Preliminary results for a prototype system running at the NWS, including significant wave observations from altimeters show stable errors after the spin-up in the significant wave height, when the background fields are compared to the observations. The same can be said when compared to independent observations from off-shore moored buoys. The observational departures from the full 6-hour assimilation window show a much smoother behavior than the errors at the analysis time, at the ending time of the window.

  1. Belford proactive flood solutions: scientific evidence to influence local and national policy by multi-purpose runoff management

    NASA Astrophysics Data System (ADS)

    Wilkinson, M.; Quinn, P. F.; Jonczyk, J.

    2010-12-01

    The increased risk from flooding continues to be of concern to governments all around the world and flood protection is becoming more of a challenge. In the UK, climate change projections indicate more extremes within the weather systems. In addition, there is an increased demand for using land in urban areas beside channels. These developments both put pressure on our flood defences and there is a need for new solutions to managing flood risk. There is currently support within the England and Wales Environment Agency for sustainable flood management solutions such as storage ponds, wetlands, beaver dams and willow riparian features (referred to here as Runoff Attenuation Features, or RAFs). However the effectiveness of RAFs are not known at the catchment scale since they have only really been trailed at the plot scale. These types of mitigation measure can offer benefits to water quality and create ecological habitats. The village of Belford, situated in the Belford Burn catchment (6km2), northern England, has suffered from numerous flood events. In addition, the catchment suffers from water quality issues within the channel and high sediment loads are having an impact on the ecology of the nearby estuary. There was a desire by the Local Environment Agency Flood Levy team to deliver an alternative catchment-based solution to the problem. With funding from the Northumbria Regional Flood Defence Committee, the Environment Agency North East Local Levy team and Newcastle University have created a partnership to address the flood problem trailing soft engineered RAF’s at the catchment scale. The partnership project, “Belford proactive flood solutions” is testing novel techniques in reducing flood risk in small sub-catchments for the Environment Agency. The project provides the information needed to understand whether the multi-functional mitigation measures are working at the sub-catchment scale. Data suggest that the mitigation measures present have delayed the overall travel time of the flood peak in the catchment by 33%. The current maximum flood storage capacity of all the features stands at around 15,000 m3. The evidence also suggests that a dam like in-stream mitigation measure can significantly reduce sediment load. Other benefits of some mitigation features include large increase in the population of water voles over the past two years. The scheme also acts as a demonstration site for interested stakeholders where they can learn about this approach to flood risk management and see the multipurpose benefits. As the project has progressed and lessons have been learnt, it has been possible to develop a runoff management toolkit for implementing these mitigation measures in other catchments of similar size. Already, the local Environment Agency has utilised the tools and recently applied similar mitigation measures to other catchments. On-going modelling exercises in the project are using the data to explore the up-scaling of the features to larger catchments.

  2. Identification of flood-rich and flood-poor periods in flood series

    NASA Astrophysics Data System (ADS)

    Mediero, Luis; Santillán, David; Garrote, Luis

    2015-04-01

    Recently, a general concern about non-stationarity of flood series has arisen, as changes in catchment response can be driven by several factors, such as climatic and land-use changes. Several studies to detect trends in flood series at either national or trans-national scales have been conducted. Trends are usually detected by the Mann-Kendall test. However, the results of this test depend on the starting and ending year of the series, which can lead to different results in terms of the period considered. The results can be conditioned to flood-poor and flood-rich periods located at the beginning or end of the series. A methodology to identify statistically significant flood-rich and flood-poor periods is developed, based on the comparison between the expected sampling variability of floods when stationarity is assumed and the observed variability of floods in a given series. The methodology is applied to a set of long series of annual maximum floods, peaks over threshold and counts of annual occurrences in peaks over threshold series observed in Spain in the period 1942-2009. Mediero et al. (2014) found a general decreasing trend in flood series in some parts of Spain that could be caused by a flood-rich period observed in 1950-1970, placed at the beginning of the flood series. The results of this study support the findings of Mediero et al. (2014), as a flood-rich period in 1950-1970 was identified in most of the selected sites. References: Mediero, L., Santillán, D., Garrote, L., Granados, A. Detection and attribution of trends in magnitude, frequency and timing of floods in Spain, Journal of Hydrology, 517, 1072-1088, 2014.

  3. From flood management systems to flood resilient systems: integration of flood resilient technologies

    NASA Astrophysics Data System (ADS)

    Salagnac, J.-L.; Diez, J.; Tourbier, J.

    2012-04-01

    Flooding has always been a major risk world-wide. Humans chose to live and develop settlements close to water (rivers, seas) due to the resources water brings, i.e. food, energy, capacity to economically transport persons and goods, and recreation. However, the risk from flooding, including pluvial flooding, often offsets these huge advantages. Floods sometimes have terrible consequences from both a human and economic point of view. The permanence and growth of urban areas in flood-prone zones despite these risks is a clear indication of the choices of concerned human groups. The observed growing concentration of population along the sea shore, the increase of urban population worldwide, the exponential growth of the world population and possibly climate change are factors that confirm flood will remain a major issue for the next decades. Flood management systems are designed and implemented to cope with such situations. In spite of frequent events, lessons look to be difficult to draw out and progresses are rather slow. The list of potential triggers to improve flood management systems is nevertheless well established: information, education, awareness raising, alert, prevention, protection, feedback from events, ... Many disciplines are concerned which cover a wide range of soft and hard sciences. A huge amount of both printed and electronic literature is available. Regulations are abundant. In spite of all these potentially favourable elements, similar questions spring up after each new significant event: • Was the event forecast precise enough? • Was the alert system efficient? • Why were buildings built in identified flood prone areas? • Why did the concerned population not follow instructions? • Why did the dike break? • What should we do to avoid it happens again? • What about damages evaluation, wastes and debris evacuation, infrastructures and buildings repair, activity recovery, temporary relocation of inhabitants, health concerns, insurance concerns, water-resistant materials, vulnerability assessment ? Flood resilient system (FReS) concept has been proposed as a new framework to address flood situations. Such systems intend to better approach such situations from a holistic point of view. FReS encompass ecologic, spatial, structural, social, disaster relief and flood risk aspects. FReS design and implementation conditions have been addressed by the FP7 SMARTeST (Smart Resilience Technology, Systems and Tools) project. The focus of this Project on the use of available and innovative communication, forecasting and flood protection technologies leads to an original contribution which highlights both the scope and the limits of this technology driven approach. These reflexions contribute to the elaboration of guidelines for the design of FReS.

  4. Flood-inundation maps for the Saluda River from Old Easley Bridge Road to Saluda Lake Dam near Greenville, South Carolina

    USGS Publications Warehouse

    Benedict, Stephen T.; Caldwell, Andral W.; Clark, Jimmy M.

    2013-01-01

    Digital flood-inundation maps for a 3.95-mile reach of the Saluda River from approximately 815 feet downstream from Old Easley Bridge Road to approximately 150 feet downstream from Saluda Lake Dam near Greenville, South Carolina, were developed by the U.S. Geological Survey (USGS). The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Saluda River near Greenville, South Carolina (station 02162500). Current conditions at the USGS streamgage may be obtained through the National Water Information System Web site at http://waterdata.usgs.gov/sc/nwis/uv/?site_no=02162500&PARAmeter_cd=00065,00060,00062. The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated with USGS streamgages. Forecasted peak-stage information is available on the Internet at the NWS Advanced Hydrologic Prediction Service (AHPS) flood-warning system Web site (http://water.weather.gov/ahps/) and may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-streamflow relations at USGS streamgage station 02162500, Saluda River near Greenville, South Carolina. The hydraulic model was then used to determine water-surface profiles for flood stages at 1.0-foot intervals referenced to the streamgage datum and ranging from approximately bankfull to 2 feet higher than the highest recorded water level at the streamgage. The simulated water-surface profiles were then exported to a geographic information system, ArcGIS, and combined with a digital elevation model (derived from Light Detection and Ranging [LiDAR] data with a 0.6-foot vertical Root Mean Square Error [RMSE] and a 3.0-foot horizontal RMSE), using HEC-GeoRAS tools in order to delineate the area flooded at each water level. The availability of these maps, along with real-time stage data from the USGS streamgage station 02162500 and forecasted stream stages from the NWS, can provide emergency management personnel and residents with information that is critical during flood-response and flood-recovery activities, such as evacuations, road closures, and disaster declarations.

  5. The Hydroclimatology of Flash Flooding in the Urban Corridor of the Northeastern US

    NASA Astrophysics Data System (ADS)

    Yang, Long; Smith, James; Baeck, Mary Lynn; Niyogi, Dev

    2015-04-01

    We examine the hydroclimatology of flash flooding in the urban corridor of the northeastern US, focusing on the densely urbanized region from Philadelphia PA to New York, NY. We examine the hydrometerology of flash flooding in the region through empirical studies using "storm catalogs" of flash flood producing storms in the region and through numerical modeling experiments using the Weather Research and Forecasting (WRF) model. Empirical analyses are based primarily on volume scan reflectivity observations from the WSR-88D radar network and cloud-to-ground lightning observations from the National Lightning Detection Network (NLDN). Empirical and numerical modeling analyses are designed to determine the role of spatial heterogeneities of land surface properties (both natural and man-made) in controlling rainfall properties of flash flood producing storms. We focus on Lagrangian properties of storms in both empirical and numerical modeling studies. Analyses of urban flooding focus on the Pennypack Creek watershed in Philadelphia and the Harry's Brook watershed in Princeton, NJ. We examine the interplay of storm properties and drainage basin properties in determining flood hazards in urban watersheds.

  6. From low-flows to floods under global warming

    NASA Astrophysics Data System (ADS)

    Panagoulia, D.

    2009-04-01

    The low-flows and floods regimes of the Acheloo's river at the Mesochora catchment outfall in Western-Central Greece were analyzed under global warming conditions. The global warming patterns were simulated through a set of hypothetical and monthly GISS (Goddard Institute for Space Studies) downscaled scenarios of temperature increases, coupled with downscaled precipitation changes. The hydrology of the catchment is dominated by spring snowmelt runoff. Thus, the daily outflow of the catchment was simulated via the coupling of the snowmelt and soil moisture accounting models of the US National Weather Service River Forecast System. A low-flow day was defined as a day during which the streamflow did not reach the quarter of the long-term mean daily streamflow. A flood day was defined as a day during which the streamflow was more than two or three times the long-term mean daily streamflow In both hydrological cases (low-flows and floods) the basic components (number of days and episodes, duration, magnitude, frequency, etc) were determined. Both representations of global warming resulted in more numerous and longer low-flow episodes, as well as smaller mean values of minimum streamflows. Also, all climate cases posted larger low-flow deficits as the precipitation increased. On the other hand, both hypothetical and GISS downscaled climate cases predicted more numerous and longer flood episodes, as well as greater mean values of peak streamflows. Also, all climate cases reflected larger flood volumes as the precipitation increased. The low-flows results could possibly further jeopardize the river water quality, the reliability of the storages and dams, as well the water supply from local groundwater sources, while the combination of higher and more frequent floods could lead to greater risk of inundation and possible damage of existing structures.

  7. 44 CFR 63.12 - Setback and community flood plain management requirements.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...2010-10-01 false Setback and community flood plain management requirements. 63...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

  8. 44 CFR 63.12 - Setback and community flood plain management requirements.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 false Setback and community flood plain management requirements. 63...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

  9. 44 CFR 63.12 - Setback and community flood plain management requirements.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2011-10-01 true Setback and community flood plain management requirements. 63...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

  10. 44 CFR 63.12 - Setback and community flood plain management requirements.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 false Setback and community flood plain management requirements. 63...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

  11. 44 CFR 63.12 - Setback and community flood plain management requirements.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...2011-10-01 false Setback and community flood plain management requirements. 63...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

  12. The New Operational Hydro-meteorological Ensemble Prediction System at Meteo-France and its representation interface for the French Service for Flood Prediction (SCHAPI)

    NASA Astrophysics Data System (ADS)

    Rousset-Regimbeau, Fabienne; Coustau, Mathieu; Martin, Eric; Thirel, Guillaume; Habets, Florence; De Saint Aubin, Céline; Ardilouze, Constantin

    2013-04-01

    The coupled physically-based hydro-meteorological model SAFRAN-ISBA-MODCOU (SIM) is developed at Meteo-France for many years. This fully distributed catchment model is used in an operationnal real-time mode since 2005 for producing mid-range ensemble streamflow forecasts based on the 51-member 10-day ECMWF EPS. New improvements have been recently implemented in this forecasting chain. First, the new version of the forecasting chain includes new atmopheric products from the ECWMF (EPS at the resolution of 0,25° over France). Then an improvement of the physics of the ISBA model (a new physical representation of the soil hydraulic conductivity) is now used. And finally, a past discharges assimilation system has been implemented in order to improve the initial states of the ensemble streamflow forecasts. These developpement were first tested in the framework of a Phd thesis, and are now evaluated in real-time conditions. This study aims to assess the improvements obtained by the new version of the forecasting chain. Several experiments were performed ton assess the effects of i) the high resolution atmospheric forcing ii) the new representation of the hydraulic conductivity iii) the data assimilation method and iv) the real-time framework. Tested on a 18-month period of reforecasts, the new chain presents significantly improved ensemble streamflow forecasts compared to the previous version. Finally, this system provides ensemble 10-day streamflow prediction to the French National Service for Flood Prediction (SCHAPI). A collaboration between Meteo-France and SCHAPI led to the development of a new website. This website shows the streamflow predictions for about 200 selected river stations over France (selected regarding their interest for flood warning) , as well as alerts for high flows (two levels of high flows corresponding to the levels of risk of the French flood warning system). It aims at providing to the French hydrological forecaters a real-time tool for mid-range flood awareness.

  13. 78 FR 29760 - Final Flood Hazard Determinations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-05-21

    ... (SFHA) boundaries or zone designations, or regulatory floodways on the Flood Insurance Rate Maps (FIRMs) and where applicable, in the supporting Flood Insurance Study (FIS) reports have been made final for... (FEMA's) National Flood Insurance Program (NFIP). In addition, the FIRM and FIS report are used...

  14. Program for Prediction, Prevention and Mitigation of Forest Fire and Flood risk in Albania

    NASA Astrophysics Data System (ADS)

    Centoducati, C.; D'Angelo, L.; Deda, M.; Ferraris, L.; Fiori, E.; Gjonaj, M.; Kelmendi, S.; Massabò, M.; Olli, A.; Siccardi, F.

    2012-04-01

    The rationale lying behind the program jointly managed by the Albanian and the Italian Civil protections is that of strengthening the Albanian National System for the prediction and prevention of forest fires and flooding. This is an initiative of the Italian government aimed at implementing in Albania the systems currently used by the Italian National "Functional Centers". The "Functional Centers" are the Operations Centers in charge for assessment forecasting, and surveillance of natural and man-made risks and represent a key component of the Italian Civil Protection System. CIMA Foundation is acting in its capacity as Executing Agency of the Italian Department of Civil Protection (DPC) in the framework of the International Cooperation between the two Countries. CIMA Foundation has been founded by DPC and the University of Genoa with the aim of advancing the scientific research and technical development, high profile engineering and environmental science education, whose ultimate goal is to guarantee public health and safety as well as to safeguard land and sea ecosystems. The "Program for Prediction, Prevention and Mitigation of Forest Fire and Flood risk in Albania" addresses four objectives: Object 1- to establish a National Center for Forecasting and Monitoring of Natural Risk/National Functional Center, a National Operations Center and two Regional Operations Centers; Object 2 to design and to implement an intensive training programme for risk assessment and management; Object 3 - to adapt the Italian Early Warning System for forest fires to the whole Albanian territory; Object 4 - to adapt the Italian Early Warning System for flooding to the Buna river and the Shkodra region, the latter recently affected by two disastrous floods.

  15. Assessment of reservoir system variable forecasts

    NASA Astrophysics Data System (ADS)

    Kistenmacher, Martin; Georgakakos, Aris P.

    2015-05-01

    Forecast ensembles are a convenient means to model water resources uncertainties and to inform planning and management processes. For multipurpose reservoir systems, forecast types include (i) forecasts of upcoming inflows and (ii) forecasts of system variables and outputs such as reservoir levels, releases, flood damage risks, hydropower production, water supply withdrawals, water quality conditions, navigation opportunities, and environmental flows, among others. Forecasts of system variables and outputs are conditional on forecasted inflows as well as on specific management policies and can provide useful information for decision-making processes. Unlike inflow forecasts (in ensemble or other forms), which have been the subject of many previous studies, reservoir system variable and output forecasts are not formally assessed in water resources management theory or practice. This article addresses this gap and develops methods to rectify potential reservoir system forecast inconsistencies and improve the quality of management-relevant information provided to stakeholders and managers. The overarching conclusion is that system variable and output forecast consistency is critical for robust reservoir management and needs to be routinely assessed for any management model used to inform planning and management processes. The above are demonstrated through an application from the Sacramento-American-San Joaquin reservoir system in northern California.

  16. Fishing Forecasts

    NASA Technical Reports Server (NTRS)

    1988-01-01

    ROFFS stands for Roffer's Ocean Fishing Forecasting Service, Inc. Roffer combines satellite and computer technology with oceanographic information from several sources to produce frequently updated charts sometimes as often as 30 times a day showing clues to the location of marlin, sailfish, tuna, swordfish and a variety of other types. Also provides customized forecasts for racing boats and the shipping industry along with seasonal forecasts that allow the marine industry to formulate fishing strategies based on foreknowledge of the arrival and departure times of different fish. Roffs service exemplifies the potential for benefits to marine industries from satellite observations. Most notable results are reduced search time and substantial fuel savings.

  17. Olympian weather forecasting

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    A unique public-private partnership will provide detailed weather information at the 2002 Winter Olympics in Utah, 8-24 February About 50 meteorologists with the National Weather Service (NWS) and several private groups will work in the background to provide accurate forecasts.This is the first time that U.S. government and private meteorologists will share forecasting responsibilities for the Olympics, according to the Salt Lake Organizing Committee for the Olympic Games. The partnership includes meteorologists with the University of Utah and KSL-TV in Salt Lake City.

  18. Assessment of flash flood warning procedures

    NASA Astrophysics Data System (ADS)

    Johnson, Lynn E.

    2000-01-01

    Assessment of four alternate flash flood warning procedures was conducted to ascertain their suitability for forecast operations using radar-rainfall imagery. The procedures include (1) areal mean basin effective rainfall, (2) unit hydrograph, (3) time-area, and (4) 2-D numerical modeling. The Buffalo Creek flash flood of July 12, 1996, was used as a case study for application of each of the procedures. A significant feature of the Buffalo Creek event was a forest fire that occurred a few months before the flood and significantly affected watershed runoff characteristics. Objectives were to assess the applicability of the procedures for watersheds having spatial and temporal scale similarities to Buffalo Creek, to compare their technical characteristics, and to consider forecaster usability. Geographic information system techniques for hydrologic database development and flash flood potential computations are illustrated. Generalizations of the case study results are offered relative to their suitability for flash flood forecasting operations. Although all four methods have relative advantages, their application to the Buffalo Creek event resulted in mixed performance. Failure of any method was due primarily to uncertainties of the land surface response (i.e., burn area imperviousness). Results underscore the need for model calibration; a difficult requirement for real-time forecasting.

  19. Retrospective Analysis of Recent Flood Events With Persistent High Surface Runoff From Hydrological Modelling

    NASA Astrophysics Data System (ADS)

    Joshi, S.; Hakeem, K. Abdul; Raju, P. V.; Rao, V. V.; Yadav, A.; Diwakar, P. G.; Dadhwal, V. K.

    2014-11-01

    Floods are one of the most common and widespread disasters in India, with an estimated 40Mha of land prone to this natural disaster (National Flood Commission, India). Significant loss of property, infrastructure, livestock, public utilities resulting in large economic losses due to floods are recurrent every year in many parts of India. Flood forecasting and early warning is widely recognized and adopted as non-structural measure to lower the damages caused by the flood events. Estimating the rainfall excess that results into excessive river flow is preliminary effort in riverine flood estimation. Flood forecasting models are in general, are event based and do not fully account for successive and persistent excessive surface runoff conditions. Successive high rainfall events result in saturated soil moisture conditions, favourable for high surface runoff conditions. The present study is to explore the usefulness of hydrological model derived surface runoff, running on continuous times-step, to relate to the occurrence of flood inundation due to persistent and successive high surface runoff conditions. Variable Infiltration Capacity (VIC), a macro-scale hydrological model, was used to simulate daily runoff at systematic grid level incorporating daily meteorological data and land cover data. VIC is a physically based, semi-distributed macroscale hydrological model that represents surface and subsurface hydrologic process on spatially distributed grid cell. It explicitly represents sub-grid heterogeneity in land cover classes, taking their phenological changes into account. In this study, the model was setup for entire India using geo-spatial data available from multiple sources (NRSC, NBSS&LUP, NOAA, and IMD) and was calibrated with river discharge data from CWC at selected river basins. Using the grid-wise surface runoff estimates from the model, an algorithm was developed through a set of thresholds of successive high runoff values in order to identify grids/locations with probable flooding conditions. These thresholds were refined through iterative process by comparing with satellite data derived flood maps of 2013 and 2014 monsoon season over India. India encountered many cyclonic flood events during Oct-Dec 2013, among which Phailin, Lehar, and Madi were rated to be very severe cyclonic storm. The path and intensity of these cyclonic events was very well captured by the model and areas were marked with persistent coverage of high runoff risk/flooded area. These thresholds were used to monitor floods in Jammu Kashmir during 4-5 Sep and Odisha during 8-9 Aug, 2014. The analysis indicated the need to vary the thresholds across space considering the terrain and geographical conditions. With respect to this a sub-basin wise study was made based on terrain characteristics (slope, elevation) using Aster DEM. It was found that basins with higher elevation represent higher thresholds as compared to basins with lesser elevation. The results show very promising correlation with the satellite derived flood maps. Further refinement and optimization of thresholds, varying them spatially accounting for topographic/terrain conditions, would lead to estimation of high runoff/flood risk areas for both riverine and drainage congested areas. Use of weather forecast data (NCMWRF, (GEFS/R)), etc. would enhance the scope to develop early warning systems.

  20. EXTENDED-RANGE PROBABILISTIC FORECASTS OF GANGES AND

    E-print Network

    Webster, Peter J.

    societies in the Yellow, Yangtze, Mekong, Irrawaddy, Ganges, Brahmaputra, and Indus river basins, each occurs in the fertile flood plains of major rivers, the loss in agricultural inputs (seed, fertilizerEXTENDED-RANGE PROBABILISTIC FORECASTS OF GANGES AND BRAHMAPUTRA FLOODS IN BANGLADESH M any

  1. 2011 Spring Flood

    USGS Multimedia Gallery

    Left to Right: Phil Turnipseed, T Bradley Keith USGS National Wetlands Research Center Director Phil Turnipseed speaks with Congressional staffers about the work the NWRC does in the Atchafalaya Basin. During the 2011 flood, NWRC crews have undertaken ecological studies and sampling runs, as well a...

  2. 2011 Spring Flood

    USGS Multimedia Gallery

    Left to Right: George Arcement, Phil Turnipseed USGS Louisiana Water Science Center Director George Arcement and USGS National Wetlands Research Center Director Phil Turnipseed are coordinating USGS efforts in Louisiana to respond to the record-setting 2011 flood. Although fairly new to their posit...

  3. 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.

  4. Research Spotlight: New method could improve hurricane surge forecasting

    NASA Astrophysics Data System (ADS)

    Tretkoff, Ernie

    2011-03-01

    In recent years, hurricanes in the Gulf of Mexico, including Katrina and Ike, caused some of the highest surges on record and significant flooding, highlighting the need for good surge forecasts that can be used for early warning and evacuation. However, current approaches for surge forecasting use models that take too much computational time or have spatial resolution too low to provide adequate forecast accuracy. Irish et al. propose a new method for determining probabilistic maximum hurricane surge forecasts. Their approach is based on calculations of surge response functions, which are derived from numerical simulations, along with analysis of meteorological forecasts. They applied the method to data from Hurricane Ike and found that they could accurately compute surge forecast probabilities within seconds, given publicly available meteorological forecast data. The method can provide a forecast of how surge would vary along the coast and identify areas most vulnerable to high surges. (Geophysical Research Letters, doi:10.1029/2010GL046347, 2011)

  5. Estimated flood-inundation mapping for the Lower Blue River in Kansas City, Missouri, 2003-2005

    USGS Publications Warehouse

    Kelly, Brian P.; Rydlund, Paul H.

    2006-01-01

    The U.S. Geological Survey, in cooperation with the city of Kansas City, Missouri, began a study in 2003 of the lower Blue River in Kansas City, Missouri, from Gregory Boulevard to the mouth at the Missouri River to determine the estimated extent of flood inundation in the Blue River valley from flooding on the lower Blue River and from Missouri River backwater. Much of the lower Blue River flood plain is covered by industrial development. Rapid development in the upper end of the watershed has increased the volume of runoff, and thus the discharge of flood events for the Blue River. Modifications to the channel of the Blue River began in late 1983 in response to the need for flood control. By 2004, the channel had been widened and straightened from the mouth to immediately downstream from Blue Parkway to convey a 30-year flood. A two-dimensional depth-averaged flow model was used to simulate flooding within a 2-mile study reach of the Blue River between 63rd Street and Blue Parkway. Hydraulic simulation of the study reach provided information for the design and performance of proposed hydraulic structures and channel improvements and for the production of estimated flood-inundation maps and maps representing an areal distribution of water velocity, both magnitude and direction. Flood profiles of the Blue River were developed between Gregory Boulevard and 63rd Street from stage elevations calculated from high water marks from the flood of May 19, 2004; between 63rd Street and Blue Parkway from two-dimensional hydraulic modeling conducted for this study; and between Blue Parkway and the mouth from an existing one-dimensional hydraulic model by the U.S. Army Corps of Engineers. Twelve inundation maps were produced at 2-foot intervals for Blue Parkway stage elevations from 750 to 772 feet. Each map is associated with National Weather Service flood-peak forecast locations at 63rd Street, Blue Parkway, Stadium Drive, U.S. Highway 40, 12th Street, and the Missouri River at the Hannibal railroad bridge in Kansas City. The National Weather Service issues peak-stage forecasts for these locations during times of flooding. Missouri River backwater inundation profiles were developed using interpolated Missouri River stage elevations at the mouth of the Blue River. Twelve backwater-inundation maps were produced at 2-foot intervals for the mouth of the Blue River from 730.9 to 752.9. To provide public access to the information presented in this report, a World Wide Web site (http://mo.water.usgs.gov/indep/kelly/blueriver/index.htm) was created that displays the results of two-dimensional modeling between 63rd Street and Blue Parkway, estimated flood-inundation maps, estimated backwater-inundation maps, and the latest gage heights and National Weather Service stage forecast for each forecast location within the study area. In addition, the full text of this report, all tables, and all plates are available for download at http://pubs.water.usgs.gov/sir2006-5089.

  6. Flood Risk and Global Change: Future Prospects

    NASA Astrophysics Data System (ADS)

    Serra-Llobet, A.

    2014-12-01

    Global flood risk is increasing in response to population growth in flood-prone areas, human encroachment into natural flood paths (exacerbating flooding in areas formerly out of harm's way), and climate change (which alters variables driving floods). How will societies respond to and manage flood risk in coming decades? Analysis of flood policy evolution in the EU and US demonstrates that changes occurred in steps, in direct response to disasters. After the flood produced by the collapse of Tous Dam in 1982, Spain initiated a systematic assessment of areas of greatest flood risk and civil protection response. The devastating floods on the Elbe and elsewhere in central Europe in 2002 motivated adoption of the EU Floods Directive (2007), which requires member states to develop systematic flood risk maps (now due) and flood risk management plans (due in 2015). The flooding of New Orleans by Hurricane Katrina in 2005 resulted in a nationwide levee-safety assessment and improvements in communicating risk, but overall less fundamental change in US flood management than manifest in the EU since 2007. In the developing world, large (and increasing) concentrations of populations in low-lying floodplains, deltas, and coasts are increasingly vulnerable, and governments mostly ill-equipped to implement fundamental changes in land use to prevent future increases in exposure, nor to develop responses to the current threats. Even in the developed world, there is surprisingly little research on how well residents of flood-prone lands understand their true risk, especially when they are 'protected' by '100-year' levees. Looking ahead, researchers and decision makers should prioritize improvements in flood risk perception, river-basin-scale assessment of flood runoff processes (under current and future climate and land-use conditions) and flood management alternatives, and bridging the disconnect between national and international floodplain management policies and local land-use decisions.

  7. Hydroclimate Forecasts in Ethiopia: Benefits, Impediments, and Ways Forward

    NASA Astrophysics Data System (ADS)

    Block, P. J.

    2014-12-01

    Numerous hydroclimate forecast models, tools, and guidance exist for application across Ethiopia and East Africa in the agricultural, water, energy, disasters, and economic sectors. This has resulted from concerted local and international interdisciplinary efforts, yet little evidence exists of rapid forecast uptake and use. We will review projected benefits and gains of seasonal forecast application, impediments, and options for the way forward. Specific case studies regarding floods, agricultural-economic links, and hydropower will be reviewed.

  8. Integrated flood disaster management and spatial information: Case studies of Netherlands and India

    NASA Astrophysics Data System (ADS)

    Zlatanova, S.; Ghawana, T.; Kaur, A.; Neuvel, J. M. M.

    2014-11-01

    Spatial Information is an integral part of flood management practices which include risk management & emergency response processes. Although risk & emergency management activities have their own characteristics, for example, related to the time scales, time pressure, activities & actors involved, it is still possible to identify at least one common challenge that constrains the ability of risk & emergency management to plan for & manage emergencies effectively and efficiently i.e. the need for better information. Considering this aspect, this paper explores flood management in Netherlands& India with an emphasis on spatial information requirements of each system. The paper examines the activities, actors & information needs related to flood management. Changing perspectives on flood management in Netherlands are studied where additional attention is being paid to the organization and preparation of flood emergency management. Role of different key actors involved in risk management is explored. Indian Flood management guidelines, by National Disaster Management Authority, are analyzed in context of their history, institutional framework, achievements and gaps. Flood Forecasting System of Central Water Commission of India is also analyzed in context of spatial dimensions. Further, information overlap between risk & emergency management from the perspectives of spatial planners & emergency responders and role of GIS based modelling / simulation is analyzed. Finally, the need for an integrated spatial information structure is explained & discussed in detail. This examination of flood management practices in the Netherlands and India with an emphasis on the required spatial information in these practices has revealed an increased recognition of the strong interdependence between risk management and emergency response processes. Consequently, the importance of an integrated spatial information infrastructure that facilitates the process of both risk and emergency management is addressed.

  9. Urban flooding and Resilience: concepts and needs

    NASA Astrophysics Data System (ADS)

    Gourbesville, Ph.

    2012-04-01

    During the recent years, a growing interest for resilience has been expressed in the natural disaster mitigation area and especially in the flood related events. The European Union, under the Seventh Framework Programme (FP7), has initiated several research initiatives in order to explore this concept especially for the urban environments. Under urban resilience is underlined the ability of system potentially exposed to hazard to resist, respond, recover and reflect up to stage which is enough to preserve level of functioning and structure. Urban system can be resilient to lot of different hazards. Urban resilience is defined as the degree to which cities are able to tolerate some disturbance before reorganizing around a new set of structures and processes (Holling 1973, De Bruijn 2005). The United Nation's International strategy for Disaster Reductions has defined resilience as "the capacity of a system, community or society potentially exposed to hazards to adapt, by resisting or changing in order to reach and maintain an acceptable level of functioning and structure. This is determined by the degree to which the social system is capable of organizing itself to increase this capacity for learning from past disasters for better future protection and to improve risk reduction measures."(UN/ISDR 2004). According to that, system should be able to accept the hazard and be able to recover up to condition that provides acceptable operational level of city structure and population during and after hazard event. Main elements of urban system are built environment and population. Physical characteristic of built environment and social characteristic of population have to be examined in order to evaluate resilience. Therefore presenting methodology for assessing flood resilience in urban areas has to be one of the focal points for the exposed cities. Strategies under flood management planning related to resilience of urban systems are usually regarding controlling runoff volume, increasing capacity of drainage systems, spatial planning, building regulations, etc. Resilience also considers resilience of population to floods and it's measured with time. Assessment of resilience that is focused on population is following bottom-up approach starting from individual and then assessing community level. Building resilience involves also contribution of social networks, increasing response capacity of communities, self-organization, learning and education and cheering adaptation culture. Measures for improving social side of resilience covers: raising public awareness, implementation of flood forecasting and warning, emergency response planning and training, sharing information, education and communication. Most of these aspects are analyzed with the CORFU FP7 project. Collaborative Research on Flood Resilience in Urban areas (CORFU) is a major project involving 17 European and Asian institutions, funded by a grant from the European Commission under the Seventh Framework Programme. The overall aim of CORFU is to enable European and Asian partners to learn from each other through joint investigation, development, implementation and dissemination of short to medium term strategies that will enable more scientifically sound management of the consequences of urban flooding in the future and to develop resilience strategies according to each situation. The CORFU project looks at advanced and novel strategies and provide adequate measures for improved flood management in cities. The differences in urban flooding problems in Asia and in Europe range from levels of economic development, infrastructure age, social systems and decision making processes, to prevailing drainage methods, seasonality of rainfall patterns and climate change trends. The study cases are, in Europe, the cities of Hamburg, Barcelona and Nice, and in Asia, Beijing, Dhaka, Mumbai, Taipei, Seoul and Incheon.

  10. A Decision Support System for effective use of probability forecasts

    NASA Astrophysics Data System (ADS)

    De Kleermaeker, Simone; Verkade, Jan

    2013-04-01

    Often, water management decisions are based on hydrological forecasts. These forecasts, however, are affected by inherent uncertainties. It is increasingly common for forecasting agencies to make explicit estimates of these uncertainties and thus produce probabilistic forecasts. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a stricter separation of responsibilities between forecasters and decision maker can be made. However, simply having probabilistic forecasts available is not sufficient to realise the associated benefits. Additional effort is required in areas such as forecast visualisation and communication, decision making in uncertainty and forecast verification. Also, revised separation of responsibilities requires a shift in institutional arrangements and responsibilities. A recent study identified a number of additional issues related to the effective use of probability forecasts. When moving from deterministic to probability forecasting, a dimension is added to an already multi-dimensional problem; this makes it increasingly difficult for forecast users to extract relevant information from a forecast. A second issue is that while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be present. For example, in many cases no estimates of flood damage, of costs of management measures and of damage reduction are available. This paper presents the results of the study, including some suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development of the DSS is outlined.

  11. Flood inundation maps for the Wabash and Eel Rivers at Logansport, Indiana

    USGS Publications Warehouse

    Fowler, Kathleen K.

    2014-01-01

    Digital flood-inundation maps for an 8.3-mile reach of the Wabash River and a 7.6-mile reach of the Eel River at Logansport, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage Wabash River at Logansport, Ind. (sta. no. 03329000) and USGS streamgage Eel River near Logansport, Ind. (sta. no. 03328500). Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/. In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system http:/water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the stream reaches by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgages 03329000, Wabash River at Logansport, Ind., and 03328500, Eel River near Logansport, Ind. The calibrated hydraulic model was then used to determine five water-surface profiles for flood stage at 1-foot intervals referenced to the Wabash River streamgage datum, and four water-surface profiles for flood stages at 1-foot intervals referenced to the Eel River streamgage datum. The stages range from bankfull to approximately the highest stages that have occurred since 1967 when three flood control dams were built upstream of Logansport, Ind. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging [lidar] data having a 0.37-foot vertical accuracy and 3.9-foot horizontal resolution) in order to delineate the area flooded at each stage. The availability of these maps, along with information available on the Internet regarding current stages from the USGS streamgages at Logansport, Ind., and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post flood recovery efforts.

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

    NASA Technical Reports Server (NTRS)

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

    2008-01-01

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

  13. 44 CFR 61.17 - Group Flood Insurance Policy.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

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  14. 44 CFR 71.3 - Denial of flood insurance.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Denial of flood insurance. 71... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF COASTAL BARRIER LEGISLATION § 71.3 Denial of flood insurance. (a) No new flood insurance...

  15. 44 CFR 78.6 - Flood Mitigation Plan approval process.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Flood Mitigation Plan..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood Mitigation Plan approval process. The State POC will forward all...

  16. 44 CFR 78.6 - Flood Mitigation Plan approval process.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 44 Emergency Management and Assistance 1 2012-10-01 2011-10-01 true Flood Mitigation Plan approval..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood Mitigation Plan approval process. The State POC will forward all...

  17. 44 CFR 61.17 - Group Flood Insurance Policy.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 44 Emergency Management and Assistance 1 2014-10-01 2014-10-01 false Group Flood Insurance Policy..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A Group Flood Insurance Policy (GFIP) is...

  18. 44 CFR 71.3 - Denial of flood insurance.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 44 Emergency Management and Assistance 1 2012-10-01 2011-10-01 true Denial of flood insurance. 71... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF COASTAL BARRIER LEGISLATION § 71.3 Denial of flood insurance. (a) No new flood insurance...

  19. 44 CFR 71.3 - Denial of flood insurance.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 44 Emergency Management and Assistance 1 2011-10-01 2011-10-01 false Denial of flood insurance. 71... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF COASTAL BARRIER LEGISLATION § 71.3 Denial of flood insurance. (a) No new flood insurance...

  20. 44 CFR 71.3 - Denial of flood insurance.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

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  1. 44 CFR 61.17 - Group Flood Insurance Policy.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 44 Emergency Management and Assistance 1 2011-10-01 2011-10-01 false Group Flood Insurance Policy..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A Group Flood Insurance Policy (GFIP) is...

  2. 44 CFR 78.6 - Flood Mitigation Plan approval process.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 44 Emergency Management and Assistance 1 2014-10-01 2014-10-01 false Flood Mitigation Plan..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood Mitigation Plan approval process. The State POC will forward all...

  3. 44 CFR 61.17 - Group Flood Insurance Policy.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 44 Emergency Management and Assistance 1 2012-10-01 2011-10-01 true Group Flood Insurance Policy..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A Group Flood Insurance Policy (GFIP) is...

  4. 44 CFR 78.6 - Flood Mitigation Plan approval process.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 44 Emergency Management and Assistance 1 2011-10-01 2011-10-01 false Flood Mitigation Plan..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood Mitigation Plan approval process. The State POC will forward all...

  5. 44 CFR 61.17 - Group Flood Insurance Policy.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 44 Emergency Management and Assistance 1 2013-10-01 2013-10-01 false Group Flood Insurance Policy..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A Group Flood Insurance Policy (GFIP) is...

  6. 44 CFR 78.6 - Flood Mitigation Plan approval process.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 44 Emergency Management and Assistance 1 2013-10-01 2013-10-01 false Flood Mitigation Plan..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood Mitigation Plan approval process. The State POC will forward all...

  7. 44 CFR 71.3 - Denial of flood insurance.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 44 Emergency Management and Assistance 1 2013-10-01 2013-10-01 false Denial of flood insurance. 71... OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF COASTAL BARRIER LEGISLATION § 71.3 Denial of flood insurance. (a) No new flood insurance...

  8. Towards real-time eruption forecasting in the Auckland Volcanic Field: application of BET_EF during the New Zealand National Disaster Exercise `Ruaumoko'

    NASA Astrophysics Data System (ADS)

    Lindsay, Jan; Marzocchi, Warner; Jolly, Gill; Constantinescu, Robert; Selva, Jacopo; Sandri, Laura

    2010-03-01

    The Auckland Volcanic Field (AVF) is a young basaltic field that lies beneath the urban area of Auckland, New Zealand’s largest city. Over the past 250,000 years the AVF has produced at least 49 basaltic centers; the last eruption was only 600 years ago. In recognition of the high risk associated with a possible future eruption in Auckland, the New Zealand government ran Exercise Ruaumoko in March 2008, a test of New Zealand’s nation-wide preparedness for responding to a major disaster resulting from a volcanic eruption in Auckland City. The exercise scenario was developed in secret, and covered the period of precursory activity up until the eruption. During Exercise Ruaumoko we adapted a recently developed statistical code for eruption forecasting, namely BET_EF (Bayesian Event Tree for Eruption Forecasting), to independently track the unrest evolution and to forecast the most likely onset time, location and style of the initial phase of the simulated eruption. The code was set up before the start of the exercise by entering reliable information on the past history of the AVF as well as the monitoring signals expected in the event of magmatic unrest and an impending eruption. The average probabilities calculated by BET_EF during Exercise Ruaumoko corresponded well to the probabilities subjectively (and independently) estimated by the advising scientists (differences of few percentage units), and provided a sound forecast of the timing (before the event, the eruption probability reached 90%) and location of the eruption. This application of BET_EF to a volcanic field that has experienced no historical activity and for which otherwise limited prior information is available shows its versatility and potential usefulness as a tool to aid decision-making for a wide range of volcano types. Our near real-time application of BET_EF during Exercise Ruaumoko highlighted its potential to clarify and possibly optimize decision-making procedures in a future AVF eruption crisis, and as a rational starting point for discussions in a scientific advisory group. It also stimulated valuable scientific discussion around how a future AVF eruption might progress, and highlighted areas of future volcanological research that would reduce epistemic uncertainties through the development of better input models.

  9. Section "Informatics" MULTICRITERIA ANALYSIS APPLIED TO A FLOOD EVENT ON RIVER

    E-print Network

    Borissova, Daniela

    Section "Informatics" 1 MULTICRITERIA ANALYSIS APPLIED TO A FLOOD EVENT ON RIVER MARITZA1 1 Institute of Information Technologies ­ Bulgarian Academy of Sciences, Bulgaria ABSTRACT Floods. The flood disaster management is highly dependent on early information and needs forecasts and data from

  10. 44 CFR 60.5 - Flood plain management criteria for flood-related erosion-prone areas.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 44 Emergency Management and Assistance 1 2011-10-01 2011-10-01 false Flood plain management criteria for flood-related erosion-prone areas. 60.5 Section 60.5 Emergency Management and Assistance... National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood...

  11. 44 CFR 60.5 - Flood plain management criteria for flood-related erosion-prone areas.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 44 Emergency Management and Assistance 1 2012-10-01 2011-10-01 true Flood plain management criteria for flood-related erosion-prone areas. 60.5 Section 60.5 Emergency Management and Assistance... National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood...

  12. 44 CFR 60.5 - Flood plain management criteria for flood-related erosion-prone areas.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 44 Emergency Management and Assistance 1 2014-10-01 2014-10-01 false Flood plain management criteria for flood-related erosion-prone areas. 60.5 Section 60.5 Emergency Management and Assistance... National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood...

  13. 44 CFR 60.5 - Flood plain management criteria for flood-related erosion-prone areas.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Flood plain management criteria for flood-related erosion-prone areas. 60.5 Section 60.5 Emergency Management and Assistance... National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood...

  14. 44 CFR 60.5 - Flood plain management criteria for flood-related erosion-prone areas.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 44 Emergency Management and Assistance 1 2013-10-01 2013-10-01 false Flood plain management criteria for flood-related erosion-prone areas. 60.5 Section 60.5 Emergency Management and Assistance... National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood...

  15. The Effect of NEXRAD Image Looping and National Convective Weather Forecast Product on Pilot Decision Making in the Use of a Cockpit Weather Information Display

    NASA Technical Reports Server (NTRS)

    Burgess, Malcolm A.; Thomas, Rickey P.

    2004-01-01

    This experiment investigated improvements to cockpit weather displays to better support the hazardous weather avoidance decision-making of general aviation pilots. Forty-eight general aviation pilots were divided into three equal groups and presented with a simulated flight scenario involving embedded convective activity. The control group had access to conventional sources of pre-flight and in-flight weather products. The two treatment groups were provided with a weather display that presented NEXRAD mosaic images, graphic depiction of METARs, and text METARs. One treatment group used a NEXRAD image looping feature and the second group used the National Convective Weather Forecast (NCWF) product overlaid on the NEXRAD display. Both of the treatment displays provided a significant increase in situation awareness but, they provided incomplete information required to deal with hazardous convective weather conditions, and would require substantial pilot training to permit their safe and effective use.

  16. Development of an Impact-Oriented Quantitative Coastal Inundation forecasting and early warning system with social and economic assessment

    NASA Astrophysics Data System (ADS)

    Fakhruddin, S. H. M.; Babel, Mukand S.; Kawasaki, Akiyuki

    2014-05-01

    Coastal inundations are an increasing threat to the lives and livelihoods of people living in low-lying, highly-populated coastal areas. According to a World Bank Report in 2005, at least 2.6 million people may have drowned due to coastal inundation, particularly caused by storm surges, over the last 200 years. Forecasting and prediction of natural events, such as tropical and extra-tropical cyclones, inland flooding, and severe winter weather, provide critical guidance to emergency managers and decision-makers from the local to the national level, with the goal of minimizing both human and economic losses. This guidance is used to facilitate evacuation route planning, post-disaster response and resource deployment, and critical infrastructure protection and securing, and it must be available within a time window in which decision makers can take appropriate action. Recognizing this extreme vulnerability of coastal areas to inundation/flooding, and with a view to improve safety-related services for the community, research should strongly enhance today's forecasting, prediction and early warning capabilities in order to improve the assessment of coastal vulnerability and risks and develop adequate prevention, mitigation and preparedness measures. This paper tries to develop an impact-oriented quantitative coastal inundation forecasting and early warning system with social and economic assessment to address the challenges faced by coastal communities to enhance their safety and to support sustainable development, through the improvement of coastal inundation forecasting and warning systems.

  17. Recent forecasts from the National Weather Service and other Hurricane watchers predict an active Hurricane Season for the U.S. Connecticut has been severely affected many times by Hurricanes. Individuals, businesses and communities can take some basic st

    E-print Network

    Post, David M.

    Recent forecasts from the National Weather Service and other Hurricane watchers predict an active Hurricane Season for the U.S. Connecticut has been severely affected many times by Hurricanes. Individuals, businesses and communities can take some basic steps to be better informed about and prepared for Hurricanes

  18. 44 CFR 63.3 - Requirement to be covered by a contract for flood insurance by June 1, 1988.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...Requirement to be covered by a contract for flood insurance by June 1, 1988. 63.3...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

  19. 44 CFR 63.3 - Requirement to be covered by a contract for flood insurance by June 1, 1988.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...Requirement to be covered by a contract for flood insurance by June 1, 1988. 63.3...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

  20. 44 CFR 63.3 - Requirement to be covered by a contract for flood insurance by June 1, 1988.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...Requirement to be covered by a contract for flood insurance by June 1, 1988. 63.3...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

  1. 44 CFR 63.3 - Requirement to be covered by a contract for flood insurance by June 1, 1988.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...Requirement to be covered by a contract for flood insurance by June 1, 1988. 63.3...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

  2. 44 CFR 63.3 - Requirement to be covered by a contract for flood insurance by June 1, 1988.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...Requirement to be covered by a contract for flood insurance by June 1, 1988. 63.3...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

  3. Seasonal hydrological ensemble forecasts over Europe

    NASA Astrophysics Data System (ADS)

    Arnal, Louise; Wetterhall, Fredrik; Pappenberger, Florian

    2015-04-01

    Seasonal forecasts have an important socio-economic value in hydro-meteorological forecasting. The applications are for example hydropower management, spring flood prediction and water resources management. The latter includes prediction of low flows, primordial for navigation, water quality assessment, droughts and agricultural water needs. Traditionally, seasonal hydrological forecasts are done using the observed discharge from previous years, so called Ensemble Streamflow Prediction (ESP). With the recent increasing development of seasonal meteorological forecasts, the incentive for developing and improving seasonal hydrological forecasts is great. In this study, a seasonal hydrological forecast, driven by the ECMWF's System 4 (SEA), was compared with an ESP of modelled discharge using observations. The hydrological model used for both forecasts was the LISFLOOD model, run over a European domain with a spatial resolution of 5 km. The forecasts were produced from 1990 until the present time, with a daily time step. They were issued once a month with a lead time of seven months. The SEA forecasts are constituted of 15 ensemble members, extended to 51 members every three months. The ESP forecasts comprise 20 ensembles and served as a benchmark for this comparative study. The forecast systems were compared using a diverse set of verification metrics, such as continuous ranked probability scores, ROC curves, anomaly correlation coefficients and Nash-Sutcliffe efficiency coefficients. These metrics were computed over several time-scales, ranging from a weekly to a six-months basis, for each season. The evaluation enabled the investigation of several aspects of seasonal forecasting, such as limits of predictability, timing of high and low flows, as well as exceedance of percentiles. The analysis aimed at exploring the spatial distribution and timely evolution of the limits of predictability.

  4. Flood Risk Management in Iowa through an Integrated Flood Information System

    NASA Astrophysics Data System (ADS)

    Demir, Ibrahim; Krajewski, Witold

    2013-04-01

    The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to flood inundation maps, real-time flood conditions, flood forecasts both short-term and seasonal, flood-related data, information and interactive visualizations for communities in Iowa. The key element of the system's architecture is the notion of community. Locations of the communities, those near streams and rivers, define basin boundaries. The IFIS provides community-centric watershed and river characteristics, weather (rainfall) conditions, and streamflow data and visualization tools. Interactive interfaces allow access to inundation maps for different stage and return period values, and flooding scenarios with contributions from multiple rivers. Real-time and historical data of water levels, gauge heights, and rainfall conditions are available in the IFIS by streaming data from automated IFC bridge sensors, USGS stream gauges, NEXRAD radars, and NWS forecasts. Simple 2D and 3D interactive visualizations in the IFIS make the data more understandable to general public. Users are able to filter data sources for their communities and selected rivers. The data and information on IFIS is also accessible through web services and mobile applications. The IFIS is optimized for various browsers and screen sizes to provide access through multiple platforms including tablets and mobile devices. The IFIS includes a rainfall-runoff forecast model to provide a five-day flood risk estimate for around 1100 communities in Iowa. Multiple view modes in the IFIS accommodate different user types from general public to researchers and decision makers by providing different level of tools and details. River view mode allows users to visualize data from multiple IFC bridge sensors and USGS stream gauges to follow flooding condition along a river. The IFIS will help communities make better-informed decisions on the occurrence of floods, and will alert communities in advance to help minimize damage of floods. This presentation provides an overview and live demonstration of the tools and interfaces in the IFIS developed to date to provide a platform for one-stop access to flood related data, visualizations, flood conditions, and forecast.

  5. Crowdsourcing detailed flood data

    NASA Astrophysics Data System (ADS)

    Walliman, Nicholas; Ogden, Ray; Amouzad*, Shahrzhad

    2015-04-01

    Over the last decade the average annual loss across the European Union due to flooding has been 4.5bn Euros, but increasingly intense rainfall, as well as population growth, urbanisation and the rising costs of asset replacements, may see this rise to 23bn Euros a year by 2050. Equally disturbing are the profound social costs to individuals, families and communities which in addition to loss of lives include: loss of livelihoods, decreased purchasing and production power, relocation and migration, adverse psychosocial effects, and hindrance of economic growth and development. Flood prediction, management and defence strategies rely on the availability of accurate information and flood modelling. Whilst automated data gathering (by measurement and satellite) of the extent of flooding is already advanced it is least reliable in urban and physically complex geographies where often the need for precise estimation is most acute. Crowdsourced data of actual flood events is a potentially critical component of this allowing improved accuracy in situations and identifying the effects of local landscape and topography where the height of a simple kerb, or discontinuity in a boundary wall can have profound importance. Mobile 'App' based data acquisition using crowdsourcing in critical areas can combine camera records with GPS positional data and time, as well as descriptive data relating to the event. This will automatically produce a dataset, managed in ArcView GIS, with the potential for follow up calls to get more information through structured scripts for each strand. Through this local residents can provide highly detailed information that can be reflected in sophisticated flood protection models and be core to framing urban resilience strategies and optimising the effectiveness of investment. This paper will describe this pioneering approach that will develop flood event data in support of systems that will advance existing approaches such as developed in the in the UK in the more generalised RASP project (DEFRA and the Environment Agency), and in line with the expressed needs of the ABI (Association of British Insurers) and National Flood Forum. The detailed data produced will also support improved flood risk assessment for the provision of affordable insurance.

  6. Reasonable Forecasts

    ERIC Educational Resources Information Center

    Taylor, Kelley R.

    2010-01-01

    This article presents a sample legal battle that illustrates school officials' "reasonable forecasts" of substantial disruption in the school environment. In 2006, two students from a Texas high school came to school carrying purses decorated with images of the Confederate flag. The school district has a zero-tolerance policy for clothing or…

  7. Forecasting Earthquakes

    NASA Technical Reports Server (NTRS)

    1994-01-01

    In this video there are scenes of damage from the Northridge Earthquake and interviews with Dr. Andrea Donnelan, Geophysics at JPL, and Dr. Jim Dolan, earthquake geologist from Cal. Tech. The interviews discuss earthquake forecasting by tracking changes in the earth's crust using antenna receiving signals from a series of satellites called the Global Positioning System (GPS).

  8. Turbulence forecasting

    NASA Technical Reports Server (NTRS)

    Chandler, C. L.

    1987-01-01

    In order to forecast turbulence, one needs to have an understanding of the cause of turbulence. Therefore, an attempt is made to show the atmospheric structure that often results when aircraft encounter moderate or greater turbulence. The analysis is based on thousands of hours of observations of flights over the past 39 years of aviation meteorology.

  9. Predictive Uncertainty and Hydro-meteorological Ensemble Forecasting

    NASA Astrophysics Data System (ADS)

    Todini, E.

    2009-04-01

    This work aims at discussing the use of "predictive uncertainty" in flood forecasting and water resources management , particularly when meteorological ensemble forecasts are available. Using data from actual operational flood forecasting systems, this work shows the improved expected benefits that can be obtained by fully incorporating predictive uncertainty into the decision making process, instead of using deterministic forecasts (as presently done) or by simply delivering to the end user uncertain, and hardly understood, forecasts (as commonly planned to be done). This work also introduces and discusses the presently available continuous (Hydrologic Uncertainty Processor, Bayesian Model Averaging, Model Conditional Processor, etc.) and binary ( Logistic Regression, Binary Multivariate Bayesian Processor, etc.) uncertainty processors, showing their performances on the basis of actual data derived from operational flood forecasting systems. Finally, the problem of incorporating meteorological ensembles into hydrological predictive uncertainty is discussed and a number of possible alternatives is presented setting into evidence the problems that currently limit their use. The main problems for proficiently use meteorological ensembles relate to (1) the lack of long forecasting meteorological runs for which precipitation forecasts have been saved as opposed to the presently available re-analyses; (2) the continuous improvements in the meteorological models that modify in time their performances combined to the lack of willingness of the meteorological centres of re-running the new versions on past data; and (3) the difficulty at tagging the different members of the ensembles .

  10. 44 CFR 61.12 - Rates based on a flood protection system involving Federal funds.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 false Rates based on a flood protection system involving Federal funds...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.12 Rates based on a flood protection system involving Federal...

  11. 24 CFR 3285.102 - Installation of manufactured homes in flood hazard areas.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... Installation of manufactured homes in flood hazard areas. 3285.102 Section 3285... Installation of manufactured homes in flood hazard areas. (a) Definitions. ...defined in 44 CFR 59.1 of the National Flood Insurance Program (NFIP)...

  12. 44 CFR 65.16 - Standard Flood Hazard Determination Form and Instructions.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 2014-10-01 false Standard Flood Hazard Determination Form and Instructions...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...SPECIAL HAZARD AREAS § 65.16 Standard Flood Hazard Determination Form and...

  13. 44 CFR 60.7 - Revisions of criteria for flood plain management regulations.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... false Revisions of criteria for flood plain management regulations. 60...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations §...

  14. 24 CFR 3285.102 - Installation of manufactured homes in flood hazard areas.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... Installation of manufactured homes in flood hazard areas. 3285.102 Section 3285... Installation of manufactured homes in flood hazard areas. (a) Definitions. ...defined in 44 CFR 59.1 of the National Flood Insurance Program (NFIP)...

  15. 44 CFR 66.3 - Establishment of community case file and flood elevation study docket.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...Establishment of community case file and flood elevation study docket. 66.3 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CONSULTATION WITH LOCAL...Establishment of community case file and flood elevation study docket. (a)...

  16. 24 CFR 3285.102 - Installation of manufactured homes in flood hazard areas.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... Installation of manufactured homes in flood hazard areas. 3285.102 Section 3285... Installation of manufactured homes in flood hazard areas. (a) Definitions. ...defined in 44 CFR 59.1 of the National Flood Insurance Program (NFIP)...

  17. 44 CFR 61.12 - Rates based on a flood protection system involving Federal funds.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 false Rates based on a flood protection system involving Federal funds...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.12 Rates based on a flood protection system involving Federal...

  18. 24 CFR 3285.102 - Installation of manufactured homes in flood hazard areas.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... Installation of manufactured homes in flood hazard areas. 3285.102 Section 3285... Installation of manufactured homes in flood hazard areas. (a) Definitions. ...defined in 44 CFR 59.1 of the National Flood Insurance Program (NFIP)...

  19. 44 CFR 65.16 - Standard Flood Hazard Determination Form and Instructions.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2012-10-01 2011-10-01 true Standard Flood Hazard Determination Form and Instructions...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...SPECIAL HAZARD AREAS § 65.16 Standard Flood Hazard Determination Form and...

  20. 44 CFR 61.12 - Rates based on a flood protection system involving Federal funds.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...2010-10-01 false Rates based on a flood protection system involving Federal funds...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.12 Rates based on a flood protection system involving Federal...

  1. 44 CFR 61.12 - Rates based on a flood protection system involving Federal funds.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2011-10-01 true Rates based on a flood protection system involving Federal funds...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.12 Rates based on a flood protection system involving Federal...

  2. 44 CFR 60.7 - Revisions of criteria for flood plain management regulations.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... false Revisions of criteria for flood plain management regulations. 60...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations §...

  3. 24 CFR 3285.102 - Installation of manufactured homes in flood hazard areas.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... Installation of manufactured homes in flood hazard areas. 3285.102 Section 3285... Installation of manufactured homes in flood hazard areas. (a) Definitions. ...defined in 44 CFR 59.1 of the National Flood Insurance Program (NFIP)...

  4. 44 CFR 65.16 - Standard Flood Hazard Determination Form and Instructions.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...2011-10-01 2011-10-01 false Standard Flood Hazard Determination Form and Instructions...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...SPECIAL HAZARD AREAS § 65.16 Standard Flood Hazard Determination Form and...

  5. 44 CFR 60.7 - Revisions of criteria for flood plain management regulations.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... false Revisions of criteria for flood plain management regulations. 60...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations §...

  6. 44 CFR 65.16 - Standard Flood Hazard Determination Form and Instructions.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...2010-10-01 2010-10-01 false Standard Flood Hazard Determination Form and Instructions...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...SPECIAL HAZARD AREAS § 65.16 Standard Flood Hazard Determination Form and...

  7. 44 CFR 61.12 - Rates based on a flood protection system involving Federal funds.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...2011-10-01 false Rates based on a flood protection system involving Federal funds...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.12 Rates based on a flood protection system involving Federal...

  8. 44 CFR 66.3 - Establishment of community case file and flood elevation study docket.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...Establishment of community case file and flood elevation study docket. 66.3 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CONSULTATION WITH LOCAL...Establishment of community case file and flood elevation study docket. (a)...

  9. 44 CFR 65.16 - Standard Flood Hazard Determination Form and Instructions.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 2013-10-01 false Standard Flood Hazard Determination Form and Instructions...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...SPECIAL HAZARD AREAS § 65.16 Standard Flood Hazard Determination Form and...

  10. 44 CFR 60.7 - Revisions of criteria for flood plain management regulations.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2011-10-01 true Revisions of criteria for flood plain management regulations. 60...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND MANAGEMENT AND USE Requirements for Flood Plain Management Regulations §...

  11. 44 CFR 66.3 - Establishment of community case file and flood elevation study docket.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...Establishment of community case file and flood elevation study docket. 66.3 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CONSULTATION WITH LOCAL...Establishment of community case file and flood elevation study docket. (a)...

  12. 44 CFR 66.3 - Establishment of community case file and flood elevation study docket.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...Establishment of community case file and flood elevation study docket. 66.3 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CONSULTATION WITH LOCAL...Establishment of community case file and flood elevation study docket. (a)...

  13. 44 CFR 66.3 - Establishment of community case file and flood elevation study docket.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...Establishment of community case file and flood elevation study docket. 66.3 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CONSULTATION WITH LOCAL...Establishment of community case file and flood elevation study docket. (a)...

  14. BASELINE EMISSIONS FORECASTS FOR INDUSTRIAL NON-BOILER SOURCES

    EPA Science Inventory

    The report gives regional air emission forecasts from three Process Model Projection Technique (PROMPT) runs. These estimates illustrate a range of possible future emissions. PROMPT, one of a number of National Acid Precipitation Assessment Program emission forecasting models, pr...

  15. Evaluating NEXRAD Multisensor Precipitation Estimates for Operational Hydrologic Forecasting

    E-print Network

    Young, Bryan; Bradley, A. Allen; Krajewski, Witold F.; Kruger, Anton

    2000-06-01

    Next-Generation Weather Radar (NEXRAD) multisensor precipitation estimates will be used for a host of applications that include operational streamflow forecasting at the National Weather Service River Forecast Centers ...

  16. The Hydroclimatology of Extreme Flooding in the Lower Mississippi River

    NASA Astrophysics Data System (ADS)

    Smith, James; Baeck, Mary Lynn

    2015-04-01

    The 1927 flood in the lower Mississippi River was the most destructive flood in American history, inundating more than 68,000 square kilometers of land, resulting in approximately 500 fatalities and leaving more than 700,000 people homeless. Despite the prominence of the 1927 flood, hard details on the flood, and the storms that produced the flood, are sparse. We examine the hydrometeorology, hydroclimatolgy and hydrology of the 1927 flood in the lower Mississippi River through empirical analyses of rainfall and streamflow records and through downscaling simulations of the storms that were responsible for cata-strophic flooding. We use 20th Century Reanalysis fields as boundary conditions and initial conditions for downscaling simulations with the Weather Research and Forecasting (WRF) model. We place the hydrometeorological analyses of the 1927 storms in a hydroclimatolog-ical context through analyses of the 20th Century Reanalysis fields. Analyses are designed to assess the physical processes that control the upper tail of flooding in the lower Missis-sippi River. We compare the 1927 flood in the Lower Mississippi River to floods in 2011, 1937 and 1973 that represent the most extreme flooding in the Lower Mississippi River. Our results show that extreme flooding is tied to anomalous water vapor transport linked to strength and position of the North Atlantic Subtropical High. More generally, the results are designed to provide insights to the hydroclimatology of flooding in large rivers.

  17. 44 CFR 73.3 - Denial of flood insurance coverage.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ...2011-10-01 2011-10-01 false Denial of flood insurance coverage. 73.3 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3...

  18. 44 CFR 73.3 - Denial of flood insurance coverage.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ...2013-10-01 2013-10-01 false Denial of flood insurance coverage. 73.3 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3...

  19. 44 CFR 73.3 - Denial of flood insurance coverage.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ...2014-10-01 2014-10-01 false Denial of flood insurance coverage. 73.3 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3...

  20. 44 CFR 73.3 - Denial of flood insurance coverage.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ...2010-10-01 2010-10-01 false Denial of flood insurance coverage. 73.3 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3...

  1. 44 CFR 73.3 - Denial of flood insurance coverage.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ...2012-10-01 2011-10-01 true Denial of flood insurance coverage. 73.3 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3...

  2. TRAVEL FORECASTER

    NASA Technical Reports Server (NTRS)

    Mauldin, L. E.

    1994-01-01

    Business travel planning within an organization is often a time-consuming task. Travel Forecaster is a menu-driven, easy-to-use program which plans, forecasts cost, and tracks actual vs. planned cost for business-related travel of a division or branch of an organization and compiles this information into a database to aid the travel planner. The program's ability to handle multiple trip entries makes it a valuable time-saving device. Travel Forecaster takes full advantage of relational data base properties so that information that remains constant, such as per diem rates and airline fares (which are unique for each city), needs entering only once. A typical entry would include selection with the mouse of the traveler's name and destination city from pop-up lists, and typed entries for number of travel days and purpose of the trip. Multiple persons can be selected from the pop-up lists and multiple trips are accommodated by entering the number of days by each appropriate month on the entry form. An estimated travel cost is not required of the user as it is calculated by a Fourth Dimension formula. With this information, the program can produce output of trips by month with subtotal and total cost for either organization or sub-entity of an organization; or produce outputs of trips by month with subtotal and total cost for international-only travel. It will also provide monthly and cumulative formats of planned vs. actual outputs in data or graph form. Travel Forecaster users can do custom queries to search and sort information in the database, and it can create custom reports with the user-friendly report generator. Travel Forecaster 1.1 is a database program for use with Fourth Dimension Runtime 2.1.1. It requires a Macintosh Plus running System 6.0.3 or later, 2Mb of RAM and a hard disk. The standard distribution medium for this package is one 3.5 inch 800K Macintosh format diskette. Travel Forecaster was developed in 1991. Macintosh is a registered trademark of Apple Computer, Inc. Fourth Dimension is a registered trademark of Acius, Inc.

  3. Ensemble Forecasts with Useful Skill-Spread Relationships for African meningitis and Asia Streamflow Forecasting

    NASA Astrophysics Data System (ADS)

    Hopson, T. M.

    2014-12-01

    One potential benefit of an ensemble prediction system (EPS) is its capacity to forecast its own forecast error through the ensemble spread-error relationship. In practice, an EPS is often quite limited in its ability to represent the variable expectation of forecast error through the variable dispersion of the ensemble, and perhaps more fundamentally, in its ability to provide enough variability in the ensembles dispersion to make the skill-spread relationship even potentially useful (irrespective of whether the EPS is well-calibrated or not). In this paper we examine the ensemble skill-spread relationship of an ensemble constructed from the TIGGE (THORPEX Interactive Grand Global Ensemble) dataset of global forecasts and a combination of multi-model and post-processing approaches. Both of the multi-model and post-processing techniques are based on quantile regression (QR) under a step-wise forward selection framework leading to ensemble forecasts with both good reliability and sharpness. The methodology utilizes the ensemble's ability to self-diagnose forecast instability to produce calibrated forecasts with informative skill-spread relationships. A context for these concepts is provided by assessing the constructed ensemble in forecasting district-level humidity impacting the incidence of meningitis in the meningitis belt of Africa, and in forecasting flooding events in the Brahmaputra and Ganges basins of South Asia.

  4. Forecaster's dilemma: Extreme events and forecast evaluation

    NASA Astrophysics Data System (ADS)

    Lerch, Sebastian; Thorarinsdottir, Thordis; Ravazzolo, Francesco; Gneiting, Tilmann

    2015-04-01

    In discussions of the quality of forecasts in the media and public, attention often focuses on the predictive performance in the case of extreme events. Intuitively, accurate predictions on the subset of extreme events seem to suggest better predictive ability. However, it can be demonstrated that restricting conventional forecast verification methods to subsets of observations might have unexpected and undesired effects and may discredit even the most skillful forecasters. Hand-picking extreme events is incompatible with the theoretical assumptions of established forecast verification methods, thus confronting forecasters with what we refer to as the forecaster's dilemma. For probabilistic forecasts, weighted proper scoring rules provide suitable alternatives for forecast evaluation with an emphasis on extreme events. Using theoretical arguments, simulation experiments and a case study on probabilistic forecasts of wind speed over Germany, we illustrate the forecaster's dilemma and the use of weighted proper scoring rules.

  5. A Wind Forecasting System for Energy Application

    NASA Astrophysics Data System (ADS)

    Courtney, Jennifer; Lynch, Peter; Sweeney, Conor

    2010-05-01

    Accurate forecasting of available energy is crucial for the efficient management and use of wind power in the national power grid. With energy output critically dependent upon wind strength there is a need to reduce the errors associated wind forecasting. The objective of this research is to get the best possible wind forecasts for the wind energy industry. To achieve this goal, three methods are being applied. First, a mesoscale numerical weather prediction (NWP) model called WRF (Weather Research and Forecasting) is being used to predict wind values over Ireland. Currently, a gird resolution of 10km is used and higher model resolutions are being evaluated to establish whether they are economically viable given the forecast skill improvement they produce. Second, the WRF model is being used in conjunction with ECMWF (European Centre for Medium-Range Weather Forecasts) ensemble forecasts to produce a probabilistic weather forecasting product. Due to the chaotic nature of the atmosphere, a single, deterministic weather forecast can only have limited skill. The ECMWF ensemble methods produce an ensemble of 51 global forecasts, twice a day, by perturbing initial conditions of a 'control' forecast which is the best estimate of the initial state of the atmosphere. This method provides an indication of the reliability of the forecast and a quantitative basis for probabilistic forecasting. The limitation of ensemble forecasting lies in the fact that the perturbed model runs behave differently under different weather patterns and each model run is equally likely to be closest to the observed weather situation. Models have biases, and involve assumptions about physical processes and forcing factors such as underlying topography. Third, Bayesian Model Averaging (BMA) is being applied to the output from the ensemble forecasts in order to statistically post-process the results and achieve a better wind forecasting system. BMA is a promising technique that will offer calibrated probabilistic wind forecasts which will be invaluable in wind energy management. In brief, this method turns the ensemble forecasts into a calibrated predictive probability distribution. Each ensemble member is provided with a 'weight' determined by its relative predictive skill over a training period of around 30 days. Verification of data is carried out using observed wind data from operational wind farms. These are then compared to existing forecasts produced by ECMWF and Met Eireann in relation to skill scores. We are developing decision-making models to show the benefits achieved using the data produced by our wind energy forecasting system. An energy trading model will be developed, based on the rules currently used by the Single Electricity Market Operator for energy trading in Ireland. This trading model will illustrate the potential for financial savings by using the forecast data generated by this research.

  6. Modeling Flood Plain Hydrology and Forest Productivity of Congaree Swamp, South Carolina

    USGS Publications Warehouse

    Doyle, Thomas W.

    2009-01-01

    An ecological field and modeling study was conducted to examine the flood relations of backswamp forests and park trails of the flood plain portion of Congaree National Park, S.C. Continuous water level gages were distributed across the length and width of the flood plain portion - referred to as 'Congaree Swamp' - to facilitate understanding of the lag and peak flood coupling with stage of the Congaree River. A severe and prolonged drought at study start in 2001 extended into late 2002 before backswamp zones circulated floodwaters. Water levels were monitored at 10 gaging stations over a 4-year period from 2002 to 2006. Historical water level stage and discharge data from the Congaree River were digitized from published sources and U.S. Geological Survey (USGS) archives to obtain long-term daily averages for an upstream gage at Columbia, S.C., dating back to 1892. Elevation of ground surface was surveyed for all park trails, water level gages, and additional circuits of roads and boundaries. Rectified elevation data were interpolated into a digital elevation model of the park trail system. Regression models were applied to establish time lags and stage relations between gages at Columbia, S.C., and gages in the upper, middle, and lower reaches of the river and backswamp within the park. Flood relations among backswamp gages exhibited different retention and recession behavior between flood plain reaches with greater hydroperiod in the lower reach than those in the upper and middle reaches of the Congaree Swamp. A flood plain inundation model was developed from gage relations to predict critical river stages and potential inundation of hiking trails on a real-time basis and to forecast the 24-hour flood In addition, tree-ring analysis was used to evaluate the effects of flood events and flooding history on forest resources at Congaree National Park. Tree cores were collected from populations of loblolly pine (Pinus taeda), baldcypress (Taxodium distichum), water tupelo (Nyssa aquatica), green ash (Fraxinus pennslyvanica), laurel oak (Quercus laurifolia), swamp chestnut oak (Quercus michauxii), and sycamore (Plantanus occidentalis) within Congaree Swamp in highand low-elevation sites characteristic of shorter and longer flood duration and related to upriver flood controls and dam operation. Ring counts and dating indicated that all loblolly pine trees and nearly all baldcypress collections in this study are postsettlement recruits and old-growth cohorts, dating from 100 to 300 years in age. Most hardwood species and trees cored for age analysis were less than 100 years old, demonstrating robust growth and high site quality. Growth chronologies of loblolly pine and baldcypress exhibited positive and negative inflections over the last century that corresponded with climate history and residual effects of Hurricane Hugo in 1989. Stemwood production on average was less for trees and species on sites with longer flood retention and hydroperiod affected more by groundwater seepage and site elevation than river floods. Water level data provided evidence that stream regulation and operations of the Saluda Dam (post-1934) have actually increased the average daily water stage in the Congaree River. There was no difference in tree growth response by species or hydrogeomorphic setting to predam and postdam flood conditions and river stage. Climate-growth analysis showed that long-term growth variation is controlled more by spring/ summer temperatures in loblolly pine and by spring/summer precipitation in baldcypress than flooding history.

  7. Flow prediction using stochastic emulators of flood wave propagation process: middle Vistula case study

    NASA Astrophysics Data System (ADS)

    Romanowicz, Renata; Karamuz, Emilia; Kochanek, Krzysztof

    2014-05-01

    Flow predictions along the river reach are required for flood protection, flood risk assessment and also for the planning of water infrastructures and water management. Due to uncertainties involved in hydro-meteorological observations and mathematical modelling, the predictions are always uncertain. Their uncertainty increases with an increase of the time horizon of the prediction - e.g. when forecasts of flow are required many days ahead. Apart from the uncertainty, also the speed of forecast acquisition might also be of concern, in particular when fast preventive actions should be taken to issue flood warning to the public, or some water management actions should be performed. In these cases, the stochastic emulators of flood wave propagation might be very useful. The emulators can be based on available data but also be built using the modelled flows along the river in the absence of the required observations. The middle River Vistula reach stretches between Zawichost and Warsaw and is 100 km long. Two distributed flow routing models were built for the reach based on the detailed river channel and floodplain geometry data. These models are used for the temporal and spatial interpolation of the water level observations available at only 5 cross-sections and in the form of daily averages of water levels. The observations span over 50 years, but they are irregular, with long periods missing either flow or level data. The observed and modelled water level data were used to build stochastic emulators in the form of a nonlinear transformation of water levels at cross-sections along the river reach. The validation of the emulators and the comparison of their performance are done using the available observations of water levels at those cross-sections. A discussion is given on the uncertainty of predictions and the application of emulators to on-line forecasting. This work was partly supported by the project "Stochastic flood forecasting system (The River Vistula reach from Zawichost to Warsaw)" carried by the Institute of Geophysics, Polish Academy of Sciences on the order of the National Science Centre (contract No. 2011/01/B/ST10/06866). The water level and flow data were provided by the Institute of Meteorology and Water Management (IMGW), Poland.

  8. Mesoscale model forecast verification during monsoon 2008

    NASA Astrophysics Data System (ADS)

    Ashrit, Raghavendra; Mohandas, Saji

    2010-08-01

    There have been very few mesoscale modelling studies of the Indian monsoon, with focus on the verification and intercomparison of the operational real time forecasts. With the exception of Das et al (2008), most of the studies in the literature are either the case studies of tropical cyclones and thunderstorms or the sensitivity studies involving physical parameterization or climate simulation studies. Almost all the studies are based on either National Center for Environmental Prediction (NCEP), USA, final analysis fields (NCEP FNL) or the reanalysis data used as initial and lateral boundary conditions for driving the mesoscale model. Here we present a mesoscale model forecast verification and intercomparison study over India involving three mesoscale models: (i) the Weather Research and Forecast (WRF) model developed at the National Center for Atmospheric Research (NCAR), USA, (ii) the MM5 model developed by NCAR, and (iii) the Eta model of the NCEP, USA. The analysis is carried out for the monsoon season, June to September 2008. This study is unique since it is based entirely on the real time global model forecasts of the National Centre for Medium Range Weather Forecasting (NCMRWF) T254 global analysis and forecast system. Based on the evaluation and intercomparison of the mesoscale model forecasts, we recommend the best model for operational real-time forecasts over the Indian region. Although the forecast mean 850 hPa circulation shows realistic monsoon flow and the monsoon trough, the systematic errors over the Arabian Sea indicate an easterly bias to the north (of mean flow) and westerly bias to the south (of mean flow). This suggests that the forecasts feature a southward shift in the monsoon current. The systematic error in the 850 hPa temperature indicates that largely the WRF model forecasts feature warm bias and the MM5 model forecasts feature cold bias. Features common to all the three models include warm bias over northwest India and cold bias over southeast peninsula. The 850 hPa specific humidity forecast errors clearly show that the Eta model features dry bias mostly over the sea, while MM5 features moist bias over large part of domain. The RMSE computed at different levels clearly establish that WRF model forecasts feature least errors in the predicted free atmospheric fields. Detailed rainfall forecast verification further establishes that the WRF model forecast rainfall skill remains more or less same in day-2 and day-3 as in day-1, while the forecast skill in the MM5 and Eta models, deteriorates in day-2 and day-3 forecasts.

  9. Evaluation of Integrating the Invasive Species Forecasting System to Support National Park Service Decisions on Fire Management Activities and Invasive Plant Species Control

    NASA Technical Reports Server (NTRS)

    Ma, Peter; Morisette, T.; Rodman, Ann; McClure, Craig; Pedelty, Jeff; Benson, Nate; Paintner, Kara; Most, Neal; Ullah, Asad; Cai, Weijie; Rocca, Monique; Silverman, Joel; Schunase, John L.

    2007-01-01

    The USGS and NASA, in conjunction with Colorado State University, George Mason University and other partners, have developed the Invasive Species Forecasting System (ISFS), a flexible tool that capitalizes on NASA's remote sensing resource to produce dynamic habitat maps of invasive terrestrial plant species across the United States. In 2006 ISFS was adopted to generate predictive invasive habitat maps to benefit noxious plant and fire management teams in three major National Park systems: The Greater Yellowstone Area (Yellowstone / Grand Tetons National Parks), Sequoia and Kings Canyon National Park, and interior Alaskan (between Denali, Gates of The Arctic and Yukon-Charley). One of the objectives of this study is to explore how the ISFS enhances decision support apparatus in use by National Park management teams. The first step with each park system was to work closely with park managers to select top-priority invasive species. Specific species were chosen for each study area based on management priorities, availability of observational data, and their potential for invasion after fire disturbances. Once focal species were selected, sources of presence/absence data were collected from previous surveys for each species in and around the Parks. Using logistic regression to couple presence/absence points with environmental data layers, the first round of ISFS habitat suitability maps were generated for each National Park system and presented during park visits over the summer of 2006. This first engagement provided a demonstration of what the park service can expect from ISFS and initiated the ongoing dialog on how the parks can best utilized the system to enhance their decisions related to invasive species control. During the park visits it was discovered that separate "expert opinion" maps would provide a valuable baseline to compare against the ISFS model output. Opinion maps are a means of spatially representing qualitative knowledge into a quantitative two-dimensional map. Furthermore, our approach combines the qualitative expert opinion habitat maps -- with the quantitative ISFS habitat maps in a difference map that shows where the two maps agree and disagree. The objective of the difference map is to help focus future field sampling and improve model results. This paper presents a demonstration of the habitat, expert opinion, and difference map for Yellowstone National Park.

  10. FLOOD RESPONSE PLAN River Flood Guide

    E-print Network

    Lennard, William N.

    1 FLOOD RESPONSE PLAN River Flood Guide Effective Date: January 2013 Updated: February 2014 #12 Thames River basin have the potential to cause flooding on Western properties. PURPOSE To establish areas) closing of parking lots and clearing of parked vehicles and other Western property in flood

  11. A uniform technique for flood frequency analysis.

    USGS Publications Warehouse

    Thomas, W.O., Jr.

    1985-01-01

    This uniform technique consisted of fitting the logarithms of annual peak discharges to a Pearson Type III distribution using the method of moments. The objective was to adopt a consistent approach for the estimation of floodflow frequencies that could be used in computing average annual flood losses for project evaluation. In addition, a consistent approach was needed for defining equitable flood-hazard zones as part of the National Flood Insurance Program. -from ASCE Publications Information

  12. Spatio-Temporal Asynchronous Co-Occurrence Pattern for Big Climate Data towards Long-Lead Flood Prediction

    E-print Network

    Ding, Wei

    Spatio-Temporal Asynchronous Co-Occurrence Pattern for Big Climate Data towards Long-Lead Flood floods 5 to 15 days in advance. Current simulation models forecasting heavy precipitation, a major factor related with flood occurrences, are computationally ex- pensive and limited by their error amplification

  13. Predictive capability of a gravity-based flood potential indicator

    NASA Astrophysics Data System (ADS)

    Reager, J. T.; Swenson, S. C.; Famiglietti, J. S.

    2012-12-01

    Traditional flood prediction methodologies adopt the perspective of storm forecasting by coupling predictions of precipitation amount and intensity with river level projections. This approach limits flood prediction capabilities worldwide to the time scales of a weather forecast -- typically in the range of three to ten days. Data from NASA's Gravity Recovery And Climate Experiment (GRACE) satellite mission show that increases in regional water storage beyond a finite storage capacity are often correlated with regional flooding. In this study, observational snow and precipitation data and GLDAS model outputs are coupled with new 1-degree global gravity-based terrestrial water storage observations to construct a flood-potential indicator for quantitative assessment of saturation-limited regional flood risk, with a one to six month warning interval. The methodology is applied over several critical study regions during the GRACE record (2011, Mississippi River; 2009, Rio Negro; 2010, Pakistan; and 2011, Australia) to calibrate the method and show the extent of predictive capabilities in a probabilistic flood potential. Despite error in simulation estimates of snow, runoff and soil water storage and data latency issues, GRACE yields definitive saturation and storage capacity information consistent with these flood events. This information could be used to drastically increasing flood warning time and predictability of flood severity when coupled with current prediction methodologies.

  14. A Distributed Hydrologic Model For Wide-Area Flood Risk Monitoring

    NASA Astrophysics Data System (ADS)

    Artan, G.; Restrepo, M.; Asante, K.; Verdin, J.

    2002-05-01

    Large areas of the African continent have experienced widespread flooding in the last four years. Deployment of hydrologic models can reduce the human and economic losses in these regions by providing improved monitoring and forecast information to guide relief activities in the flood-affected areas. Hydrologic models need to be calibrated for the specific region where they will be used to produce reliable results, but most of the countries in the region lack extended historical hydrometeorological data. In this study, we describe a spatially distributed, physically based hydrologic model used for wide-area flood risk monitoring. The model is forced by daily estimates of rainfall and evapotranspiration derived from remotely sensed data and assimilation fields. In most developing countries hydro-meteorological station networks are sparse, if the data are available at all there are significant delays in receiving them. In the model described in this paper the operational rainfall data are produced by the National Oceanic and Atmospheric Administration Climate Prediction Center (NOAA/CPC) from satellite imagery and ground station data. Model input parameters were derived from widely available continental-scale data sets for topography, soils, and land cover. The model performed well in simulating the timing and magnitude of stream flow in the major rivers of Southern African region during the recent episode of flooding in Mozambique. The model will part of the USGS/EDC contribution to the Distributed Models Intercomparison Project (DMIP).

  15. The east coast Big Flood, 31 January-1 February 1953: a summary of the human disaster.

    PubMed

    Baxter, Peter J

    2005-06-15

    The Big Flood was the worst natural disaster to befall Britain during the twentieth century, and the scale of its human impact was due to the lack of adequate disaster preparedness. The 307 deaths on land were caused by drowning or from the effects of exposure. Two-thirds occurred in four clusters along the shoreline and mainly comprised inhabitants of post-war prefabricated buildings, bungalows and chalets, with the highest mortality among the elderly. The emergency response was spontaneous and community led, with the main search and rescue completed before central government became involved. No individuals or agencies were blamed for the neglected state of the flood defences or the absence of warnings, along with the post-war shortage of adequate housing, which were the main causes of vulnerability. The media played a limited role, and television was in its infancy. Mental health impacts were either self-limiting or failed to be articulated in a society recovering from the Second World War. The major mitigating factors included the empathetic response of people, locally and nationally, as well as the availability of armed forces personnel based in East Anglia, whose actions played a decisive part in the battle against the sea. The major legacies of the Big Flood were a coastal flood forecasting system, a more scientific approach to sea defences and the building of the Thames barrier. PMID:16191651

  16. Monitoring and research to describe geomorphic effects of the 2011 controlled flood on the Green River in the Canyon of Lodore, Dinosaur National Monument, Colorado and Utah

    USGS Publications Warehouse

    Mueller, Erich R.; Grams, Paul E.; Schmidt, John C.; Hazel, Joseph E., Jr.; Kaplinski, Matt; Alexander, Jason A.; Kohl, Keith

    2014-01-01

    In 2011, a large magnitude flow release from Flaming Gorge Reservoir, Wyoming and Utah, occurred in response to high snowpack in the middle Rocky Mountains. This was the third highest recorded discharge along the Green River downstream of Flaming Gorge Dam, Utah, since its initial closure in November 1962 and motivated a research effort to document effects of these flows on channel morphology and sedimentology at four long-term monitoring sites within the Canyon of Lodore in Dinosaur National Monument, Colorado and Utah. Data collected in September 2011 included raft-based bathymetric surveys, ground-based surveys of banks, channel cross sections and vegetation-plot locations, sand-bar stratigraphy, and painted rock recovery on gravel bars. As part of this surveying effort, Global Navigation Satellite System (GNSS) data were collected at benchmarks on the canyon rim and along the river corridor to establish a high-resolution survey control network. This survey control network allows for the collection of repeatable spatial and elevation data necessary for high accuracy geomorphic change detection. Nearly 10,000 ground survey points and more than 20,000 bathymetric points (at 1-meter resolution) were collected over a 5-day field campaign, allowing for the construction of reach-scale digital elevation models (DEMs). Additionally, we evaluated long-term geomorphic change at these sites using repeat topographic surveys of eight monumented cross sections at each of the four sites. Analysis of DEMs and channel cross sections show a spatially variable pattern of erosion and deposition, both within and between reaches. As much as 5 meters of scour occurred in pools downstream from flow constrictions, especially in channel segments where gravel bars were absent. By contrast, some channel cross sections were stable during the 2011 floods, and have shown almost no change in over a decade of monitoring. Partial mobility of gravel bars occurred, and although in some locations vegetation such as tamarisk (Tamarix ramosissima) was damaged, wholesale bed motion necessary to fully clear these surfaces was not evident. In flow recirculation zones, eddy sandbars aggraded one meter or more, increasing the area of bars exposed during typical dam operations. Yet overall, the 2011 flood resulted in a decrease in reach-scale sand storage because bed degradation exceeded bar deposition. The 2011 response is consistent with that of a similar event in 1999, which was followed by sand-bar erosion and sediment accumulation on the bed during subsequent years of normal dam operational flows. Although the 1999 and 2011 floods were exceptional in the post-dam system, they did not exceed the pre-dam 2-year flood, isolating their effects to the modern active channel with minor erosion or reworking of pre-dam deposits stabilized through vegetation encroachment.

  17. Deadly forecast.

    PubMed

    Pines, A

    2015-12-01

    Recent epidemiological studies from various countries point at the mounting incidence of cancer. This continuous increase in the number of cancer cases will keep its pace in the future. The lifetime risk of cancer for people born since 1960 is forecast to be more than 50%. Thus cancer becomes the major health problem, and policy-makers should plan ahead how to implement effective prevention programs, on the one hand, and optimize the strategy for better diagnosis, treatment and surveillance of cancer patients on the other hand. PMID:25812628

  18. The Financial Benefit of Early Flood Warnings in Europe

    NASA Astrophysics Data System (ADS)

    Pappenberger, Florian; Cloke, Hannah L.; Wetterhall, Fredrik; Parker, Dennis J.; Richardson, David; Thielen, Jutta

    2015-04-01

    Effective disaster risk management relies on science based solutions to close the gap between prevention and preparedness measures. The outcome of consultations on the UNIDSR post-2015 framework for disaster risk reduction highlight the need for cross-border early warning systems to strengthen the preparedness phases of disaster risk management in order to save people's lives and property and reduce the overall impact of severe events. In particular, continental and global scale flood forecasting systems provide vital information to various decision makers with which early warnings of floods can be made. Here the potential monetary benefits of early flood warnings using the example of the European Flood Awareness System (EFAS) are calculated based on pan-European Flood damage data and calculations of potential flood damage reductions. The benefits are of the order of 400 Euro for every 1 Euro invested. Because of the uncertainties which accompany the calculation, a large sensitivity analysis is performed in order to develop an envelope of possible financial benefits. Current EFAS system skill is compared against perfect forecasts to demonstrate the importance of further improving the skill of the forecasts. Improving the response to warnings is also essential in reaping the benefits of flood early warnings.

  19. Current problems in communication from the weather forecast in the prevention of hydraulic and hydrogeological risk

    NASA Astrophysics Data System (ADS)

    Fazzini, Massimiliano; Vaccaro, Carmela

    2014-05-01

    The Italian territory is one of the most fragile hydraulic and hydro geologic of the world, due to its complexity physiographic, lithological and above meteo-climatic too. Moreover, In recent years, the unhappy urbanization, the abandonment of mountain areas and countryside have fostered hydro geological instability, ever more devastating, in relation to the extremes of meteorological events. After the dramatic floods and landscapes of the last 24 months - in which more than 50 people died - it is actually open a public debate on the issues related to prevention, forecasting and management of hydro-meteorological risk. Aim of the correct weather forecasting at different spatial and temporal scales is to avoid or minimize the potential occurrence of damage or human losses resulting from the increasingly of frequent extreme weather events. In Italy, there are two major complex problems that do not allow for effective dissemination of the correct weather forecasting. First, the absence of a national meteorological service - which can ensure the quality of information. In this regard, it is at an advanced stage the establishment of a unified national weather service - formed by technicians to national and regional civil protection and the Meteorological Service of the Air Force, which will ensure the quality of the prediction, especially through exclusive processing of national and local weather forecasting and hydro geological weather alert. At present, however, this lack favors the increasing diffusion of meteorological sites more or less professional - often totally not "ethical" - which, at different spatial scales, tend to amplify the signals from the weather prediction models, describing them the users of the web such as exceptional or rare phenomena and often causing unjustified alarmism. This behavior is almost always aimed at the desire of give a forecast before other sites and therefore looking for new commercial sponsors, with easy profits. On the other hand, however, the almost complete absence of education to environmental risks - also from as primary school - does not allow the users to know to select the information ethically and technically correct, increasingly favoring the proliferation of most of the "weather-commercial" or private weather websites. It would seem therefore essential to implement the activities of specific information by the universities and public institutions responsible for forecasting and prevention-hydrological forecast.

  20. 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.

  1. Feedback on flood risk management

    NASA Astrophysics Data System (ADS)

    Moreau, K.; Roumagnac, A.

    2009-09-01

    For several years, as floods were increasing in South of France, local communities felt deprive to assume their mission of protection and information of citizens, and were looking for assistance in flood management. In term of flood disaster, the fact is that physical protection is necessary but inevitably limited. Tools and structures of assistance to anticipation remain slightly developed. To manage repeated crisis, local authorities need to be able to base their policy against flood on prevention, warnings, post-crisis analysis and feedback from former experience. In this objective, after 3 years of test and improvement since 2003, the initiative Predict-Services was developed in South of France: it aims at helping communities and companies to face repeated flood crisis. The principle is to prepare emergency plans, to organize crisis management and reduce risks; to help and assist communities and companies during crisis to activate and adapt their emergency plans with enough of anticipation; and to analyse floods effects and improve emergency plans afterwards. With the help of Meteo France datas and experts, Predict services helps local communities and companies in decision making for flood management. In order to reduce risks, and to keep the benefits of such an initiative, local communities and companies have to maintain the awareness of risk of the citizens and employees. They also have to maintain their safety plans to keep them constantly operational. This is a part of the message relayed. Companies, Local communities, local government authorities and basin stakeholders are the decision makers. Companies and local communities have to involve themselves in the elaboration of safety plans. They are also completely involved in their activation that is their own responsability. This applies to other local government authorities, like districts one's and basin stakeholders, which participle in the financing community safety plans and adminitrative district which are responsible of the transmission of meteorological alert and of rescue actions. In the crossing of the géo-information stemming from the space technology, communication, meteorology, hydraulics and hydrology, Predict-services brings help to local communities in their mission of protection and information to the citizens, for flood problems and helps companies to limit and delete operating losses facing floods. The initiative, developped by BRL, EADS Astrium, in association with Meteo France, has been employed and is functioning on cities of south of France, notably on Montpellier, and also on the scale of catchment area ( BRL is a regional development company, a public private partnership controlled by the local gouvernments of the Languedoc-Roussillon Region). The initiative has to be coordinated with state services to secure continuity and coherence of information. This initiative is developped in dialogue with State services as Météo France, the Ministry for the interior, the Ministry for ecology and the durable development, the Regional Direction of the Environment (DIREN), the Central service of Hydrometeorology and Support to the Forecast of the Floods ( SCHAPI) and service of forecast of rising (SPC). It has been successfully functioning for 5 years with 300 southern cities from South West to South East of France and notably Montpellier and Sommières, famous for it's flood problems on the Vidourle river where no human loss was to regret and where the economic impacts were minimized. Actually developed in cities of South of France, this initiative is to be developed nationaly and very soon internationally. Thanks to the efficiency of it's method, this initiative is also developed in partnership with insurance company involved in prevention actions. After more than 100 events observed and analysed in South of France, the experience gained, allowed PREDICT Services to better anticipate phenomena and also to better manage them. The presentation will expose the feedback of this initiative and lessons learned on risk management.