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. Seasonal Flood Forecasts and Dynamic Flood Risk Management

    NASA Astrophysics Data System (ADS)

    Arumugam, S.; Lall, U.

    2004-05-01

    Recent developments in predicting seasonal flood peaks/volumes conditioned on ocean, atmospheric and land surface conditions offer the scope for dynamic flood risk management. We address a deficiency of the traditional assumption that flood series are stationary, independent and identically distributed (iid). In this study, we evaluate a semi-parametric methodology based on local likelihood estimation for estimating the flood quantiles based on climatic indices for a seasonal storage reservoir. The utility of this methodology for estimating long-term slow variation of flood potential and for reconstructing past flood series using a small set of climate and other predictors is also explored. Conditioned on the seasonal flood forecasts and streamflow forecasts, the flood rule curve and the operating rules of the reservoir are modified to evaluate the additional benefits the seasonal flood forecasts offer in improving the reservoir operation over the currently pursued approach of constant/static flood rule curve. The benefits of seasonal flood forecasts in relation to the seasonal streamflow forecasts are quantified and their potential utility in flood premium and insurance setting is also discussed.

  4. Advances in Global Flood Forecasting Systems

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    A trend of increasing number of heavy precipitation events over many regions in the world during the past century has been observed (IPCC, 2007), but conclusive results on a changing frequency or intensity of floods have not yet been established. However, the socio-economic impact particularly of floods is increasing at an alarming trend. Thus anticipation of severe events is becoming a key element of society to react timely to effectively reduce socio-economic damage. Anticipation is essential on local as well as on national or trans-national level since management of response and aid for major disasters requires a substantial amount of planning and information on different levels. Continental and trans-national flood forecasting systems already exist. The European Flood Awareness System (EFAS) has been developed in close collaboration with the National services and is going operational in 2012, enhancing the national forecasting centres with medium-range probabilistic added value information while at the same time providing the European Civil Protection with harmonised information on ongoing and upcoming floods for improved aid management. Building on experiences and methodologies from EFAS, a Global Flood Awareness System (GloFAS) has now been developed jointly between researchers from the European Commission Joint Research Centre (JRC) and the European Centre for Medium-Range Weather Forecast (ECWMF). The prototype couples HTESSEL, the land-surface scheme of the ECMWF NWP model with the LISFLOOD hydrodynamic model for the flow routing in the river network. GloFAS is set-up on global scale with horizontal grid spacing of 0.1 degree. The system is driven with 51 ensemble members from VAREPS with a time horizon of 15 days. In order to allow for the routing in the large rivers, the coupled model is run for 45 days assuming zero rainfall after day 15. Comparison with observations have shown that in some rivers the system performs quite well while in others the hydro-meteorological processes are not fully captured and calibration is necessary. Critical thresholds are computed from long-term simulations where the coupled HTESSEL/LISFLOOD model is driven with ERA-Interim data for a period of 21 years.From the longterm runs return periods are estimated against which each flood forecasts are compared. Results are displayed as maps and time series on a web-interface providing global overviews as well as local quantitative information. Major floods such as the ones in South East Asia in September-October 2010 in Thailand, Cambodia and Vietnam were well captured by the system: for the lower Mekong River, probabilistic forecasts from the global simulations on the 18th September 2011 showed a probability higher than 40% of exceeding the high alert level from 2nd-4th October, hence 14 days in advance. Collaborations exist between the EU and Brazil to further the system for Brazilian rivers. Next steps include further research and development, rigorous testing and adaptations. calibration of the system with available data, and work on selected case studies for quantitative improvements.

  5. Evaluation of Flood Forecast and Warning in Elbe river basin - Impact of Forecaster's Strategy

    NASA Astrophysics Data System (ADS)

    Danhelka, Jan; Vlasak, Tomas

    2010-05-01

    Czech Hydrometeorological Institute (CHMI) is responsible for flood forecasting and warning in the Czech Republic. To meet that issue CHMI operates hydrological forecasting systems and publish flow forecast in selected profiles. Flood forecast and warning is an output of system that links observation (flow and atmosphere), data processing, weather forecast (especially NWP's QPF), hydrological modeling and modeled outputs evaluation and interpretation by forecaster. Forecast users are interested in final output without separating uncertainties of separate steps of described process. Therefore an evaluation of final operational forecasts was done for profiles within Elbe river basin produced by AquaLog forecasting system during period 2002 to 2008. Effects of uncertainties of observation, data processing and especially meteorological forecasts were not accounted separately. Forecast of flood levels exceedance (peak over the threshold) during forecasting period was the main criterion as flow increase forecast is of the highest importance. Other evaluation criteria included peak flow and volume difference. In addition Nash-Sutcliffe was computed separately for each time step (1 to 48 h) of forecasting period to identify its change with the lead time. Textual flood warnings are issued for administrative regions to initiate flood protection actions in danger of flood. Flood warning hit rate was evaluated at regions level and national level. Evaluation found significant differences of model forecast skill between forecasting profiles, particularly less skill was evaluated at small headwater basins due to domination of QPF uncertainty in these basins. The average hit rate was 0.34 (miss rate = 0.33, false alarm rate = 0.32). However its explored spatial difference is likely to be influenced also by different fit of parameters sets (due to different basin characteristics) and importantly by different impact of human factor. Results suggest that the practice of interactive model operation, experience and forecasting strategy differs between responsible forecasting offices. Warning is based on model outputs interpretation by hydrologists-forecaster. Warning hit rate reached 0.60 for threshold set to lowest flood stage of which 0.11 was underestimation of flood degree (miss 0.22, false alarm 0.28). Critical success index of model forecast was 0.34, while the same criteria for warning reached 0.55. We assume that the increase accounts not only to change of scale from single forecasting point to region for warning, but partly also to forecaster's added value. There is no official warning strategy preferred in the Czech Republic (f.e. tolerance towards higher false alarm rate). Therefore forecaster decision and personal strategy is of great importance. Results show quite successful warning for 1st flood level exceedance, over-warning for 2nd flood level, but under-warning for 3rd (highest) flood level. That suggests general forecaster's preference of medium level warning (2nd flood level is legally determined to be the start of the flood and flood protection activities). In conclusion human forecaster's experience and analysis skill increases flood warning performance notably. However society preference should be specifically addressed in the warning strategy definition to support forecaster's decision making.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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

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

    NASA Astrophysics Data System (ADS)

    Bao, Hongjun; Zhao, Linna

    2012-02-01

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

  13. 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.

  14. Probabilistic Flash Flood Forecasting using Stormscale Ensembles

    NASA Astrophysics Data System (ADS)

    Hardy, J.; Gourley, J. J.; Kain, J. S.; Clark, A.; Novak, D.; Hong, Y.

    2013-12-01

    Flash flooding is one of the most costly and deadly natural hazards in the US and across the globe. The loss of life and property from flash floods could be mitigated with better guidance from hydrological models, but these models have limitations. For example, they are commonly initialized using rainfall estimates derived from weather radars, but the time interval between observations of heavy rainfall and a flash flood can be on the order of minutes, particularly for small basins in urban settings. Increasing the lead time for these events is critical for protecting life and property. Therefore, this study advances the use of quantitative precipitation forecasts (QPFs) from a stormscale NWP ensemble system into a distributed hydrological model setting to yield basin-specific, probabilistic flash flood forecasts (PFFFs). Rainfall error characteristics of the individual members are first diagnosed and quantified in terms of structure, amplitude, and location (SAL; Wernli et al., 2008). Amplitude and structure errors are readily correctable due to their diurnal nature, and the fine scales represented by the CAPS QPF members are consistent with radar-observed rainfall, mainly showing larger errors with afternoon convection. To account for the spatial uncertainty of the QPFs, we use an elliptic smoother, as in Marsh et al. (2012), to produce probabilistic QPFs (PQPFs). The elliptic smoother takes into consideration underdispersion, which is notoriously associated with stormscale ensembles, and thus, is good for targeting the approximate regions that may receive heavy rainfall. However, stormscale details contained in individual members are still needed to yield reasonable flash flood simulations. Therefore, on a case study basis, QPFs from individual members are then run through the hydrological model with their predicted structure and corrected amplitudes, but the locations of individual rainfall elements are perturbed within the PQPF elliptical regions using Monte Carlo sampling. This yields an ensemble of flash flood simulations. These simulated flows are compared to historically-based flow thresholds at each grid point to identify basin scales most susceptible to flash flooding, therefore, deriving PFFF products. This new approach is shown to: 1) identify the specific basin scales within the broader regions that are forecast to be impacted by flash flooding based on cell movement, rainfall intensity, duration, and the basin's susceptibility factors such as initial soil moisture conditions; 2) yield probabilistic information about on the forecast hydrologic response; and 3) improve lead time by using stormscale NWP ensemble forecasts.

  15. Ensemble flood forecasting on the Tocantins River - Brazil

    NASA Astrophysics Data System (ADS)

    Fan, Fernando; Collischonn, Walter; Jiménez, Karena; Sorribas, Mino; Buarque, Diogo; Siqueira, Vinicius

    2014-05-01

    The Tocantins River basin is located in the northern region of Brazil and has about 300.000 km2 of drainage area upstream of its confluence with river Araguaia, its major tributary. The Tocantins River is intensely used for hydropower production, with seven major dams, including Tucuruí, world's fourth largest in terms of installed capacity. In this context, the use of hydrological streamflow forecasts at this basin is very useful to support the decision making process for reservoir operation, and can produce benefits by reducing damages from floods, increasing dam safety and upgrading efficiency in power generation. The occurrence of floods along the Tocantins River is a relatively frequent event, where one recent example is the year of 2012, when a large flood occurred in the Tocantins River with discharge peaks exceeding 16.000m³/s, and causing damages to cities located along the river. After this flooding event, a hydrological forecasting system was developed and is operationally in use since mid-2012 in order to assist the decision making of dam operation along the river basin. The forecasting system is based on the MGB-IPH model, a large scale distributed hydrological model, and initially used only telemetric data as observed information and deterministic rainfall forecasts from the Brazilian Meteorological Forecasting Centre (CPTEC) with 7-days lead time as input. Since August-2013 the system has been updated and now works with two new features: (i) a technique for merging satellite TRMM real-time precipitation estimative with gauged information is applied to reduce the uncertainty due to the lack of observed information over a portion of the basin, since the total number of rain gages available is scarce compared to the total basin area; (ii) rainfall ensemble forecasts with 16-days lead time provided by the Global Ensemble Forecasting System (GEFs), from the 2nd Generation of NOAA Global Ensemble Reforecast Data Set, maintained by the National Center for Environmental Prediction (NCEP-NOAA) of the United States, are added in the system as additional inputs. This system is one of the first operational ensemble forecasting systems in Brazil, and it is also one of the first based on mixed satellite-telemetric data. This work presents the Tocantins forecasting system and some hindcasting analysis of how recent floods could have been predicted with the use of the ensemble forecasts.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Real-time application of meteorological ensembles for Danube flood forecasting

    NASA Astrophysics Data System (ADS)

    Csk, A.; Gauzer, B.; Gnandt, B.; Balint, G.

    2009-04-01

    Flood forecasting schemes may have the most diverse structure depending on catchment size, response or concentration time and the availability of real time input data. The centre of weight of the hydrological forecasting system is often shifted from hydrological tools to the meteorological observation and forecasting systems. At lowland river sections simple flood routing techniques prevail where accuracy of discharge estimation might depend mostly on the accuracy of upstream discharge estimation. In large river basin systems both elements are present. Attempts are made enabling the use of ensemble of short and medium term meteorological forecast results for real-time flood forecasting by coupling meteorological and hydrological modelling tools. The system is designed in three parts covering the upper and central Danube. The large number of nodes (41) makes the system in fact semi distributed in basin scale. All of the nodes are prepared for forecast purposes. Real time mode runs are carried out in 6 hourly time steps. The available meteorological analysis and forecasting tools are linked to the flood forecasting system. Meteorological forecasts include 6 days and 12 days out of the ECMWF 10-14-day ahead EPS and VarEPS. The hydrological side of the system includes the data ingestion part producing semi distributed catchment wise input from gridded fields and rainfall-runoff, flood routing modules. Operational application of the of the ensemble system has been studied by the comparison of real time deterministic forecast and the experimental real time ensemble forecast results since the summer of 2008 on the river Danube. The period of June-October 2008 included mostly low water period interrupted by smaller floods. The real time ensemble hydrological forecasting experiment proved that the use of meteorological ensembles to produce sets of hydrological predictions increased the capability to issue forecasts with describing current uncertainties. As the result of the demonstration experiment was that the NHFS (VITUKI National Hydrological Forecasting Service of Hungary) system can be used for such a purpose like real-time usage. The relative large number of model runs could be performed within reasonable time. Suggestions are given to adjust appropriate decision support rules to utilise the array of flood forecasts for flood management and warning purposes. The proper estimation of the contribution to forecast error by different modules of the system may help to better understand expected current uncertainty of the forecast. The given research has been partly supported by EC under INTEGRATED PROJECT PREVIEW PREVention, Information and Early Warning Proposal/Contract: 516172. Keywords: real time flood forecast, hydrological ensembles, meteorological ensembles, River Danube, quantitative precipitation forecast, gridded fields, semi-distributed.

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  2. 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.

  3. 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.

  4. 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.; Barthlmy, 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 Oprationnelle pour la Modlisation) 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 Prvision des Crues).

  5. 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 by a severe rainfall event causing many floods and landslides. During the mainly critical phases the CFD furnished an immediate, significant 24h support for the decision support activities. The official web site (www.cfumbria.it), entirely developed with open source tools, represented a very useful device furnishing good performances for the monitoring and data dissemination to all the subjects involved, especially to the National/Regional Civil Protection offices and territorial presidium. Thresholds presented good accordance with non instrumental observations and automatic alert system was very effective. At last, during the flooding event a continuous link with the National Department, regional Civil Protection offices, territorial presidium and local public services, together with real time instrumental monitoring and now-casting hydrological activities performed by available models, represented a suitable junction between practice and science in CFD operational forecasting system at local, regional and national scale.

  6. 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.

  7. 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.

  8. Short-term Ensemble Flood Forecasting Experiments in Brazil

    NASA Astrophysics Data System (ADS)

    Collischonn, Walter; Meller, Adalberto; Fan, Fernando; Moreira, Demerval; Dias, Pedro; Buarque, Diogo; Bravo, Juan

    2013-04-01

    Flood Forecasting and issuing early warnings to communities under risk can help reduce the impacts of those events. However, to be effective, warnings should be given several hours in advance. The best solution to extend the lead time is possibly the use of rainfall-runoff models with input given by rainfall and streamflow observations and by forecasts of future precipitation derived from numerical weather prediction (NWP) models. Recent studies showed that probabilistic or ensemble flood forecasts produced using ensemble precipitation forecasts as input data outperform deterministic flood forecasts in several cases in Europe and the United States, and ensemble flood forecasting systems are increasingly becoming operational in these regions. In Brazil, on the other hand, operational flood warning systems are rare, and often based on simplified river routing or linear transfer function models. However, a large number of global and regional meteorological models is operationally run covering most of the country, and forecasts of those models are available for recent years. We used this available data to conduct experiments of short term ensemble flood forecasting in the Paraopeba River basin (12 thousand km2), located in Southeastern Brazil. Streamflow forecasts were produced using the MGB-IPH hydrological model, using a simple empirical state updating method and using an ensemble of precipitation forecasts generated by several models, with different initial conditions and parameterizations, from several weather forecasting centers. A single deterministic streamflow forecast, based on a quantitative precipitation forecast derived from the optimal combination of several outputs of NWP models was used as a reference to assess the performance of the ensemble streamflow forecasts. Flood forecasts experiments were performed for three rainy seasons (austral summer) between 2008-2011. The results for predictions of dichotomous events, which mean exceeding or not flood warning thresholds, showed that the upper quantiles of the ensemble (e.g. 80th and 90th quantiles) over performed the deterministic forecast and even the ensemble mean. In most cases we observed an increase in the proportion of correctly forecasted events while keeping false alarm rates at low levels. This benefit was generally higher for higher flow thresholds and for longer lead times, which are the most important situations for flood impact mitigation. In parallel with the ensemble forecasts studies, a forecasting system platform fully coupled to a GIS tool (Mapwindow GIS) is being developed, which facilitates the system operation and interpretation of results. Currently, this system is being tested, however using only deterministic precipitation forecasts, in two large scale river basins in Brazil: the So Francisco River upstream of Pirapora (60 thousand km2) and the Tocantins River (300 thousand km2). Results obtained in the Paraopeba River are now motivating the incorporation of NWP ensemble outputs in these systems to make probabilistic predictions.

  9. 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.

  10. 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.

  11. Flood forecasting for River Mekong with data-based models

    NASA Astrophysics Data System (ADS)

    Shahzad, Khurram M.; Plate, Erich J.

    2014-09-01

    In many regions of the world, the task of flood forecasting is made difficult because only a limited database is available for generating a suitable forecast model. This paper demonstrates that in such cases parsimonious data-based hydrological models for flood forecasting can be developed if the special conditions of climate and topography are used to advantage. As an example, the middle reach of River Mekong in South East Asia is considered, where a database of discharges from seven gaging stations on the river and 31 rainfall stations on the subcatchments between gaging stations is available for model calibration. Special conditions existing for River Mekong are identified and used in developing first a network connecting all discharge gages and then models for forecasting discharge increments between gaging stations. Our final forecast model (Model 3) is a linear combination of two structurally different basic models: a model (Model 1) using linear regressions for forecasting discharge increments, and a model (Model 2) using rainfall-runoff models. Although the model based on linear regressions works reasonably well for short times, better results are obtained with rainfall-runoff modeling. However, forecast accuracy of Model 2 is limited by the quality of rainfall forecasts. For best results, both models are combined by taking weighted averages to form Model 3. Model quality is assessed by means of both persistence index PI and standard deviation of forecast error.

  12. Real-time error correction method combined with combination flood forecasting technique for improving the accuracy of flood forecasting

    NASA Astrophysics Data System (ADS)

    Chen, Lu; Zhang, Yongchuan; Zhou, Jianzhong; Singh, Vijay P.; Guo, Shenglian; Zhang, Junhong

    2015-02-01

    Flood forecasting has been recognized as one of the most important and reliable ways for flood management. It is therefore necessary to improve the reliability and accuracy of the flood forecasting model. Flood error correction (FEC) and multi-model composition (MC) methods are two effective ways to enhance the model performance. The current focus seems to be on either of these two methods. In this study, we combine these two methods and propose three combined methods, namely flood error correction together with multi-model composition method (FEC-MC), multi-model composition method together with flood error correction (MC-FEC), and global real-time combination method (GRCM). The Three Gorge Reservoir (TGR) and Jinsha River are selected as case studies. First, the flood error correction method and multi-model composition techniques are used separately. Then, the three combined methods are employed. The performances of the five models are compared using the root-mean-square error (RMSE), Nash-Sutcliffe efficiency R2, and qualified rate ?. Results show that the combined methods perform better than the single FEC and MC methods. The proposed GRCM method is found to be the most effective method for improving the accuracy of discharge predicted by the flood forecasting model.

  13. 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.

  14. Discriminant Flash-Flood Forecasting in an Urban Environment

    NASA Astrophysics Data System (ADS)

    Yates, D.; Sharif, H.; Rindahl, B.

    2003-12-01

    This study demonstrates the application of high-resolution weather radar data, quantitative precipitation nowcasting, combined with simple hydrologic modeling to forecast flood potential for multiple, discriminate urban watersheds. The approach defines meta-data models based on the Extensive Markup Language (XML) to disseminate severe storm attributes (their size, orientation, history, and forecast position) and 5-minute, 2-hour rainfall accumulations for the watersheds to an Automated Location Evaluation in Real Time (ALERT) urban flood warning system- the Urban Drainage and Flood Control District (UDFCD), in Denver Colorado, USA. In addition, a simple graphical display system based on the World Wide Web Consortium's (W3C) Scalable Vector Graphics (SVG) format, requires only the simple exchange of small XML data files from the Nowcasting server to the UDFCD client for monitoring storm position and streamflow by the UDFCD in realtime. Example of severe storms that produce local flooding in the UDFCD domain will be shown.

  15. 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.

  16. Improving real time flood forecasting using fuzzy inference system

    NASA Astrophysics Data System (ADS)

    Lohani, Anil Kumar; Goel, N. K.; Bhatia, K. K. S.

    2014-02-01

    In order to improve the real time forecasting of foods, this paper proposes a modified Takagi Sugeno (T-S) fuzzy inference system termed as threshold subtractive clustering based Takagi Sugeno (TSC-T-S) fuzzy inference system by introducing the concept of rare and frequent hydrological situations in fuzzy modeling system. The proposed modified fuzzy inference systems provide an option of analyzing and computing cluster centers and membership functions for two different hydrological situations, i.e. low to medium flows (frequent events) as well as high to very high flows (rare events) generally encountered in real time flood forecasting. The methodology has been applied for flood forecasting using the hourly rainfall and river flow data of upper Narmada basin, Central India. The available rainfall-runoff data has been classified in frequent and rare events and suitable TSC-T-S fuzzy model structures have been suggested for better forecasting of river flows. The performance of the model during calibration and validation is evaluated by performance indices such as root mean square error (RMSE), model efficiency and coefficient of correlation (R). In flood forecasting, it is very important to know the performance of flow forecasting model in predicting higher magnitude flows. The above described performance criteria do not express the prediction ability of the model precisely from higher to low flow region. Therefore, a new model performance criterion termed as peak percent threshold statistics (PPTS) is proposed to evaluate the performance of a flood forecasting model. The developed model has been tested for different lead periods using hourly rainfall and discharge data. Further, the proposed fuzzy model results have been compared with artificial neural networks (ANN), ANN models for different classes identified by Self Organizing Map (SOM) and subtractive clustering based Takagi Sugeno fuzzy model (SC-T-S fuzzy model). It has been concluded from the study that the TSC-T-S fuzzy model provide reasonably accurate forecast with sufficient lead-time.

  17. 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.

  18. Evaluation of flash-flood discharge forecasts in complex terrain using precipitation

    USGS Publications Warehouse

    Yates, D.; Warner, T.T.; Brandes, E.A.; Leavesley, G.H.; Sun, Jielun; Mueller, C.K.

    2001-01-01

    Operational prediction of flash floods produced by thunderstorm (convective) precipitation in mountainous areas requires accurate estimates or predictions of the precipitation distribution in space and time. The details of the spatial distribution are especially critical in complex terrain because the watersheds are generally small in size, and small position errors in the forecast or observed placement of the precipitation can distribute the rain over the wrong watershed. In addition to the need for good precipitation estimates and predictions, accurate flood prediction requires a surface-hydrologic model that is capable of predicting stream or river discharge based on the precipitation-rate input data. Different techniques for the estimation and prediction of convective precipitation will be applied to the Buffalo Creek, Colorado flash flood of July 1996, where over 75 mm of rain from a thunderstorm fell on the watershed in less than 1 h. The hydrologic impact of the precipitation was exacerbated by the fact that a significant fraction of the watershed experienced a wildfire approximately two months prior to the rain event. Precipitation estimates from the National Weather Service's operational Weather Surveillance Radar-Doppler 1988 and the National Center for Atmospheric Research S-band, research, dual-polarization radar, colocated to the east of Denver, are compared. In addition, very short range forecasts from a convection-resolving dynamic model, which is initialized variationally using the radar reflectivity and Doppler winds, are compared with forecasts from an automated-algorithmic forecast system that also employs the radar data. The radar estimates of rain rate, and the two forecasting systems that employ the radar data, have degraded accuracy by virtue of the fact that they are applied in complex terrain. Nevertheless, the radar data and forecasts from the dynamic model and the automated algorithm could be operationally useful for input to surface-hydrologic models employed for flood warning. Precipitation data provided by these various techniques at short time scales and at fine spatial resolutions are employed as detailed input to a distributed-parameter hydrologic model for flash-flood prediction and analysis. With the radar-based precipitation estimates employed as input, the simulated flood discharge was similar to that observed. The dynamic-model precipitation forecast showed the most promise in providing a significant discharge-forecast lead time. The algorithmic system's precipitation forecast did not demonstrate as much skill, but the associated discharge forecast would still have been sufficient to have provided an alert of impending flood danger.

  19. Flood Forecasting via Time Lag Forward Network; Kelantan, Malaysia

    NASA Astrophysics Data System (ADS)

    Jajarmizadeh, Milad; Mohd Sidek, Lariyah; Bte Basri, Hidayah; Shakira Jaffar, Aminah

    2016-03-01

    Forecasting water level is one of the critical issues in Malaysia for Kelantan region. Based on the flood events in 2014, this study investigates the hourly-forecasting of water level in one station namely Kg Jenob in Kelantan. For this issue, Time Lag Forward Network (TLFN) is evaluated for forecasting the water level as dynamic model. Heuristic method in stepwise forward methodology is performed. Rainfall and water level are the input and output of the modelling respectively. For selected flood period 15/12/2014 to 30/12/2014, 8 scenarios are developed to obtain a minimum error in water level forecasting. By monitoring the error, it will show that the optimum configuration of network has 2 processors in hidden layer and 7 lags have enough contribution on the result of hourly forecasting. Transfer functions in hidden and output layers are is Tangent hyperbolic and bias. Observed and simulated data are compared with usual error criteria called Mean Square Error (MSE) and Root Mean Square Error (RMSE) which obtained 0.005 and 0.07 respectively. In conclusion, this study will be as a baseline for Kelantan to show that TLFN has promising result to forecast the flood events.

  20. Flood monitoring for ungauged rivers: the power of combining space-based monitoring and global forecasting models

    NASA Astrophysics Data System (ADS)

    Revilla-Romero, Beatriz; Netgeka, Victor; Raynaud, Damien; Thielen, Jutta

    2013-04-01

    Flood warning systems typically rely on forecasts from national meteorological services and in-situ observations from hydrological gauging stations. This capacity is not equally developed in flood-prone developing countries. Low-cost satellite monitoring systems and global flood forecasting systems can be an alternative source of information for national flood authorities. The Global Flood Awareness System (GloFAS) has been develop jointly with the European Centre for Medium-Range Weather Forecast (ECMWF) and the Joint Research Centre, and it is running quasi operational now since June 2011. The system couples state-of-the art weather forecasts with a hydrological model driven at a continental scale. The system provides downstream countries with information on upstream river conditions as well as continental and global overviews. In its test phase, this global forecast system provides probabilities for large transnational river flooding at the global scale up to 30 days in advance. It has shown its real-life potential for the first time during the flood in Southeast Asia in 2011, and more recently during the floods in Australia in March 2012, India (Assam, September-October 2012) and Chad Floods (August-October 2012).The Joint Research Centre is working on further research and development, rigorous testing and adaptations of the system to create an operational tool for decision makers, including national and regional water authorities, water resource managers, hydropower companies, civil protection and first line responders, and international humanitarian aid organizations. Currently efforts are being made to link GloFAS to the Global Flood Detection System (GFDS). GFDS is a Space-based river gauging and flood monitoring system using passive microwave remote sensing which was developed by a collaboration between the JRC and Dartmouth Flood Observatory. GFDS provides flood alerts based on daily water surface change measurements from space. Alerts are shown on a world map, with detailed reports for individual gauging sites. A comparison of discharge estimates from the Global Flood Detection System (GFDS) and the Global Flood Awareness System (GloFAS) with observations for representative climatic zones is presented. Both systems have demonstrated strong potential in forecasting and detecting recent catastrophic floods. The usefulness of their combined information on global scale for decision makers at different levels is discussed. Combining space-based monitoring and global forecasting models is an innovative approach and has significant benefits for international river commissions as well as international aid organisations. This is in line with the objectives of the Hyogo and the Post-2015 Framework that aim at the development of systems which involve trans-boundary collaboration, space-based earth observation, flood forecasting and early warning.

  1. A data based mechanistic approach to nonlinear flood routing and adaptive flood level forecasting

    NASA Astrophysics Data System (ADS)

    Romanowicz, Renata J.; Young, Peter C.; Beven, Keith J.; Pappenberger, Florian

    2008-08-01

    Operational flood forecasting requires accurate forecasts with a suitable lead time, in order to be able to issue appropriate warnings and take appropriate emergency actions. Recent improvements in both flood plain characterization and computational capabilities have made the use of distributed flood inundation models more common. However, problems remain with the application of such models. There are still uncertainties associated with the identifiability of parameters; with the computational burden of calculating distributed estimates of predictive uncertainty; and with the adaptive use of such models for operational, real-time flood inundation forecasting. Moreover, the application of distributed models is complex, costly and requires high degrees of skill. This paper presents an alternative to distributed inundation models for real-time flood forecasting that provides fast and accurate, medium to short-term forecasts. The Data Based Mechanistic (DBM) methodology exploits a State Dependent Parameter (SDP) modelling approach to derive a nonlinear dependence between the water levels measured at gauging stations along the river. The transformation of water levels depends on the relative geometry of the channel cross-sections, without the need to apply rating curve transformations to the discharge. The relationship obtained is used to transform water levels as an input to a linear, on-line, real-time and adaptive stochastic DBM model. The approach provides an estimate of the prediction uncertainties, including allowing for heterescadasticity of the multi-step-ahead forecasting errors. The approach is illustrated using an 80 km reach of the River Severn, in the UK.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Probabilistic flood forecast: Exact and approximate predictive distributions

    NASA Astrophysics Data System (ADS)

    Krzysztofowicz, Roman

    2014-09-01

    For quantification of predictive uncertainty at the forecast time t0, the future hydrograph is viewed as a discrete-time continuous-state stochastic process {Hn: n=1,…,N}, where Hn is the river stage at time instance tn>t0. The probabilistic flood forecast (PFF) should specify a sequence of exceedance functions {F‾n: n=1,…,N} such that F‾n(h)=P(Zn>h), where P stands for probability, and Zn is the maximum river stage within time interval (t0,tn], practically Zn=max{H1,…,Hn}. This article presents a method for deriving the exact PFF from a probabilistic stage transition forecast (PSTF) produced by the Bayesian forecasting system (BFS). It then recalls (i) the bounds on F‾n, which can be derived cheaply from a probabilistic river stage forecast (PRSF) produced by a simpler version of the BFS, and (ii) an approximation to F‾n, which can be constructed from the bounds via a recursive linear interpolator (RLI) without information about the stochastic dependence in the process {H1,…,Hn}, as this information is not provided by the PRSF. The RLI is substantiated by comparing the approximate PFF against the exact PFF. Being reasonably accurate and very simple, the RLI may be attractive for real-time flood forecasting in systems of lesser complexity. All methods are illustrated with a case study for a 1430 km headwater basin wherein the PFF is produced for a 72-h interval discretized into 6-h steps.

  10. Application of WRF model forecasts and PERSIANN satellite rainfalls for real-time flood forecasting

    NASA Astrophysics Data System (ADS)

    Kuo, C.; Chen, J.; Yang, T.; Lin, Y.; Wang, Y.; Hsu, K.; Sorooshian, S.; Lee, C.; Yu, P.

    2013-12-01

    This study aims to propose an approach which applies Weather Research and Forecasting (WRF) model forecasts and satellite rainfalls by Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) to physiographic inundation-drainage model for real-time flood forecasting. The study area is Dianbao River Basin in southern Taiwan, which is a low-relief area easily suffering flood disasters. Since the study area lacks reliable rainfall forecasting and inundation simulation models, the study proposes an approach to refine WRF model forecasts (abbreviated as WRFMFs hereafter) using satellite rainfalls by PERSIANN (abbreviated as PERSIANN rainfalls hereafter) for enhancing the inundation forecasts and prolonging the lead time. Twenty one sets of on-line WRFMFs under different hypothesized boundary conditions are provided by Taiwan Typhoon and Flood Research Institute. The WRFMFs with a spatial resolution of 5 km*5 km cover the extent of Taiwan (120°E~122°E, 22°N~25°N), which are issued for 72 hours ahead for every 6 hours. However, WRFMFs have a 6-hour delay and are quite different due to their different non-isolated boundary conditions. On the other hand, PERSIANN rainfalls provided by CHRS/UCI are based on the real-time satellite images and can provide real-time global rainfall estimation. Therefore, integrating WRFMFs and PERSIANN rainfalls may be a good approach to provide better rainfall forecasts. The main idea of this approach is to give different WRFMFs different weights by comparing to the PERSIANN rainfalls when a typhoon is formed in the open sea and approaching to Taiwan. Based on the 21 sets of WRFMFs, a pattern recognition method is used to compare the PERSIANN rainfalls to each of the 21 sets of WRFMFs during a same time period for every 6 hours. For example, at a present time (18:00) the WRFMFs are issued with a 6-hour delay from 12:00 for 72 hours ahead. The comparison between each of the 21 sets of WRFMFs and the PERSIANN rainfalls during the past 6 hours (12:00~18:00) is made. Based on the comparisons, 21 errors can be calculated for assigning the weights to the 21 sets of WRFMFs for the 66 hours ahead (herein, six hours ahead are adopted). A set of WRFMF with a smaller error is assigned to have a higher weight. Then, the ensemble approach for the 21 sets of WRFMFs with different weights is performed to obtain more reliable rainfall forecasts. Finally, the study uses physiographic inundation-drainage model for flood inundation simulation. This inundation-drainage model is a pseudo 2-D model which can reasonably simulate flood inundation under the condition of complex topography. By inputting the ensemble of WRFMFs, the inundation-drainage model can forecast the flood extent and depth with less computational time in the study area. These forecasted inundation information can be used to plot the flood inundation maps and help decision makers quickly identify the flood prone areas and make emergency preparedness in advance.

  11. PAI-OFF: A new proposal for online flood forecasting in flash flood prone catchments

    NASA Astrophysics Data System (ADS)

    Schmitz, G. H.; Cullmann, J.

    2008-10-01

    SummaryThe Process Modelling and Artificial Intelligence for Online Flood Forecasting (PAI-OFF) methodology combines the reliability of physically based, hydrologic/hydraulic modelling with the operational advantages of artificial intelligence. These operational advantages are extremely low computation times and straightforward operation. The basic principle of the methodology is to portray process models by means of ANN. We propose to train ANN flood forecasting models with synthetic data that reflects the possible range of storm events. To this end, establishing PAI-OFF requires first setting up a physically based hydrologic model of the considered catchment and - optionally, if backwater effects have a significant impact on the flow regime - a hydrodynamic flood routing model of the river reach in question. Both models are subsequently used for simulating all meaningful and flood relevant storm scenarios which are obtained from a catchment specific meteorological data analysis. This provides a database of corresponding input/output vectors which is then completed by generally available hydrological and meteorological data for characterizing the catchment state prior to each storm event. This database subsequently serves for training both a polynomial neural network (PoNN) - portraying the rainfall-runoff process - and a multilayer neural network (MLFN), which mirrors the hydrodynamic flood wave propagation in the river. These two ANN models replace the hydrological and hydrodynamic model in the operational mode. After presenting the theory, we apply PAI-OFF - essentially consisting of the coupled "hydrologic" PoNN and "hydrodynamic" MLFN - to the Freiberger Mulde catchment in the Erzgebirge (Ore-mountains) in East Germany (3000 km 2). Both the demonstrated computational efficiency and the prediction reliability underline the potential of the new PAI-OFF methodology for online flood forecasting.

  12. 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.

  13. 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.

  14. 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.

  15. Flooding and Flood Management

    USGS Publications Warehouse

    Brooks, K.N.; Fallon, J.D.; Lorenz, D.L.; Stark, J.R.; Menard, Jason

    2011-01-01

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

  16. 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.

  17. Sensitivity analysis of surface runoff generation in urban flood forecasting.

    PubMed

    Simões, N E; Leitão, J P; Maksimović, C; Sá Marques, A; Pina, R

    2010-01-01

    Reliable flood forecasting requires hydraulic models capable to estimate pluvial flooding fast enough in order to enable successful operational responses. Increased computational speed can be achieved by using a 1D/1D model, since 2D models are too computationally demanding. Further changes can be made by simplifying 1D network models, removing and by changing some secondary elements. The Urban Water Research Group (UWRG) of Imperial College London developed a tool that automatically analyses, quantifies and generates 1D overland flow network. The overland flow network features (ponds and flow pathways) generated by this methodology are dependent on the number of sewer network manholes and sewer inlets, as some of the overland flow pathways start at manholes (or sewer inlets) locations. Thus, if a simplified version of the sewer network has less manholes (or sewer inlets) than the original one, the overland flow network will be consequently different. This paper compares different overland flow networks generated with different levels of sewer network skeletonisation. Sensitivity analysis is carried out in one catchment area in Coimbra, Portugal, in order to evaluate overland flow network characteristics. PMID:20453333

  18. 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.

  19. 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.

  20. 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.

  1. Spatially distributed flood forecasting in flash flood prone areas: Application to road network supervision in Southern France

    NASA Astrophysics Data System (ADS)

    Naulin, J.-P.; Payrastre, O.; Gaume, E.

    2013-04-01

    SummaryAccurate flood forecasts are critical to an efficient flood event management strategy. Until now, hydro-meteorological forecasts have mainly been used to establish early-warnings in France (meteorological and flood vigilance maps) or over the world (flash-flood guidances). These forecasts are typically limited either to the main streams covered by the flood forecasting services or to watersheds with specific assets like check dams, which in most cases are well gauged river sections, thus leaving aside large parts of the territory. This paper presents a distributed hydro-meteorological forecasting approach, which makes use of the high spatial and temporal resolution rainfall estimates that are now available, to provide information at ungauged sites. The proposed system intended to detect road inundation risks had initially been developed and tested in areas of limited size. This paper presents the extension of such a system to an entire region (i.e. the Gard region in Southern France), including over 2000 crossing points between rivers and roads and its validation with respect to a large data set of actual reported road inundations observed during recent flash flood events. These initial validation results appear to be most promising. The eventual proposed tool would provide the necessary information for flood event management services to identify the areas at risk and adopt appropriate safety and rescue measures: i.e. pre-positioning of rescue equipment, interruption of the traffic on the exposed roads and determination of safe access or evacuation routes. Moreover, beyond the specific application to the supervision of a road network, the research undertaken herein also provides results for the performance of hydro-meteorological forecasts on ungauged headwaters.

  2. 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.

  3. Operational aspects of asynchronous filtering for improved flood forecasting

    NASA Astrophysics Data System (ADS)

    Rakovec, Oldrich; Weerts, Albrecht; Sumihar, Julius; Uijlenhoet, Remko

    2014-05-01

    Hydrological forecasts can be made more reliable and less uncertain by recursively improving initial conditions. A common way of improving the initial conditions is to make use of data assimilation (DA), a feedback mechanism or update methodology which merges model estimates with available real world observations. The traditional implementation of the Ensemble Kalman Filter (EnKF; e.g. Evensen, 2009) is synchronous, commonly named a three dimensional (3-D) assimilation, which means that all assimilated observations correspond to the time of update. Asynchronous DA, also called four dimensional (4-D) assimilation, refers to an updating methodology, in which observations being assimilated into the model originate from times different to the time of update (Evensen, 2009; Sakov 2010). This study investigates how the capabilities of the DA procedure can be improved by applying alternative Kalman-type methods, e.g., the Asynchronous Ensemble Kalman Filter (AEnKF). The AEnKF assimilates observations with smaller computational costs than the original EnKF, which is beneficial for operational purposes. The results of discharge assimilation into a grid-based hydrological model for the Upper Ourthe catchment in Belgian Ardennes show that including past predictions and observations in the AEnKF improves the model forecasts as compared to the traditional EnKF. Additionally we show that elimination of the strongly non-linear relation between the soil moisture storage and assimilated discharge observations from the model update becomes beneficial for an improved operational forecasting, which is evaluated using several validation measures. In the current study we employed the HBV-96 model built within a recently developed open source modelling environment OpenStreams (2013). The advantage of using OpenStreams (2013) is that it enables direct communication with OpenDA (2013), an open source data assimilation toolbox. OpenDA provides a number of algorithms for model calibration and assimilation and is suitable to be connected to any kind of environmental model. This setup is embedded in the Delft Flood Early Warning System (Delft-FEWS, Werner et al., 2013) for making all simulations and forecast runs and handling of all hydrological and meteorological data. References: Evensen, G. (2009), Data Assimilation: The Ensemble Kalman Filter, Springer, doi:10.1007/978-3-642-03711-5. OpenDA (2013), The OpenDA data-assimilation toolbox, www.openda.org, (last access: 1 November 2013). OpenStreams (2013), OpenStreams, www.openstreams.nl, (last access: 1 November 2013). Sakov, P., G. Evensen, and L. Bertino (2010), Asynchronous data assimilation with the EnKF, Tellus, Series A: Dynamic Meteorology and Oceanography, 62(1), 24-29, doi:10.1111/j.1600-0870.2009.00417.x. Werner, M., J. Schellekens, P. Gijsbers, M. van Dijk, O. van den Akker, and K. Heynert (2013), The Delft-FEWS flow forecasting system, Environ. Mod. & Soft., 40(0), 65-77, doi: http://dx.doi.org/10.1016/j.envsoft.2012.07.010.

  4. 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.

  5. 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 ...

  6. How can we deal with ANN in flood forecasting? As a simulation model or updating kernel!

    NASA Astrophysics Data System (ADS)

    Hassan Saddagh, Mohammad; Javad Abedini, Mohammad

    2010-05-01

    Flood forecasting and early warning, as a non-structural measure for flood control, is often considered to be the most effective and suitable alternative to mitigate the damage and human loss caused by flood. Forecast results which are output of hydrologic, hydraulic and/or black box models should secure accuracy of flood values and timing, especially for long lead time. The application of the artificial neural network (ANN) in flood forecasting has received extensive attentions in recent years due to its capability to capture the dynamics inherent in complex processes including flood. However, results obtained from executing plain ANN as simulation model demonstrate dramatic reduction in performance indices as lead time increases. This paper is intended to monitor the performance indices as it relates to flood forecasting and early warning using two different methodologies. While the first method employs a multilayer neural network trained using back-propagation scheme to forecast output hydrograph of a hypothetical river for various forecast lead time up to 6.0 hr, the second method uses 1D hydrodynamic MIKE11 model as forecasting model and multilayer neural network as updating kernel to monitor and assess the performance indices compared to ANN alone in light of increase in lead time. Results presented in both graphical and tabular format indicate superiority of MIKE11 coupled with ANN as updating kernel compared to ANN as simulation model alone. While plain ANN produces more accurate results for short lead time, the errors increase expeditiously for longer lead time. The second methodology provides more accurate and reliable results for longer forecast lead time.

  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. Verification of a probabilistic flood forecasting system for an Alpine Region of northern Italy

    NASA Astrophysics Data System (ADS)

    Laiolo, P.; Gabellani, S.; Rebora, N.; Rudari, R.; Ferraris, L.; Ratto, S.; Stevenin, H.

    2012-04-01

    Probabilistic hydrometeorological forecasting chains are increasingly becoming an operational tool used by civil protection centres for issuing flood alerts. One of the most important requests of decision makers is to have reliable systems, for this reason an accurate verification of their predictive performances become essential. The aim of this work is to validate a probabilistic flood forecasting system: Flood-PROOFS. The system works in real time, since 2008, in an alpine Region of northern Italy, Valle d'Aosta. It is used by the Civil Protection regional service to issue warnings and by the local water company to protect its facilities. Flood-PROOFS uses as input Quantitative Precipitation Forecast (QPF) derived from the Italian limited area model meteorological forecast (COSMO-I7) and forecasts issued by regional expert meteorologists. Furthermore the system manages and uses both real time meteorological and satellite data and real time data on the maneuvers performed by the water company on dams and river devices. The main outputs produced by the computational chain are deterministic and probabilistic discharge forecasts in different cross sections of the considered river network. The validation of the flood prediction system has been conducted on a 25 months period considering different statistical methods such as Brier score, Rank histograms and verification scores. The results highlight good performances of the system as support system for emitting warnings but there is a lack of statistics especially for huge discharge events.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Study on snowmelt flood forecasting based on 3S technologies and DSS

    NASA Astrophysics Data System (ADS)

    Fang, Shifeng; Pei, Huan; Liu, Zhihui; Dai, Wei; Liu, Yongqiang; Zhao, Qiudong; Feng, Lin

    2008-10-01

    Flood disaster is one of the most frequently and the biggest natural disasters in the world, and snowmelt floods which break out in spring often bring enormous social and economic loss, especially in arid and semi-arid areas, such as in Northern Tianshan Mountains in Xinjiang, China. Any effective prevention or mitigation of disasters is built on the basis of forecasting, so the real-time processing, snow information analysis, and weather forecasting, are combined into a system which can provide intelligent reports and prewarning information of snowmelt flood duly and accurately for the government departments or other organizations. So it is of great significance for flood prevention and disaster reduction. Furthermore, effective forecasting and prewarning can generate enormous social, economic and ecological benefits, so the establishment of a real-time, efficient and reliable Flood Forecasting/Prewarning DSS, is an important part of the building of non-engineering measures for flood prevention and disaster reduction. Now the integrated applications of remote sensing(RS), geographic information systems(GIS) and global positioning systems(GPS), named "3S" technologies, have been infiltrated through hydrology and water resource management, and there are rapid developments and extensive applications of Decision Support System (DSS) in recent years in many fields. But there is seldom appearance of mature applications of Snowmelt Flood Forecasting/Prewarning DSS, and a shortage of study on effective Snowmelt Flood Forecasting. In this paper, firstly, a Distributed Snowmelt Runoff Model had been built based on the "3S" technologies, and then a Snowmelt Flood Forecasting DSS based on the B/S (Browser server) and J2EE structure had been established, then introduced the T213 Numerical Forecasting Production from WRF mode and revised it with our synchronous field observation data. Various snow information and other basic geoinformation also had been extracted from RS imagines or other data with RS and GIS tools. At last, snowmelt flood based on "3S" technologies and DSS had been forested in the typical study area, Quergou River Basin, which is located in the middle of the Northern Tianshan Mountains, Xinjiang, China, and is contrasted with the latter measured runoff. Good forecasting results had been achieved, and the average accuracy was up to 0.90.

  15. The potential of remotely sensed soil moisture for operational flood forecasting

    NASA Astrophysics Data System (ADS)

    Wanders, N.; Karssenberg, D.; de Roo, A.; de Jong, S.; Bierkens, M. F.

    2013-12-01

    Nowadays, remotely sensed soil moisture is readily available from multiple space born sensors. The high temporal resolution and global coverage make these products very suitable for large-scale land-surface applications. The potential to use these products in operational flood forecasting has thus far not been extensively studied. In this study, we evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the timing and height of the flood peak and low flows. EFAS is used for operational flood forecasting in Europe and uses a distributed hydrological model for flood predictions for lead times up to 10 days. Satellite-derived soil moisture from ASCAT, AMSR-E and SMOS is assimilated into the EFAS system for the Upper Danube basin and results are compared to assimilation of only discharge observations. Discharge observations are available at the outlet and at six additional locations throughout the catchment. To assimilate soil moisture data into EFAS, an Ensemble Kalman Filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, derived from a detailed model-satellite soil moisture comparison study, is included to ensure optimal performance of the EnKF. For the validation, additional discharge observations not used in the EnKF are used as an independent validation dataset. Our results show that the accuracy of flood forecasts is increased when more discharge observations are used in that the Mean Absolute Error (MAE) of the ensemble mean is reduced by 65%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of base flows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the Continuous Ranked Probability Score (CRPS) shows a performance increase of 10-15% on average, compared to assimilation of discharge only. The rank histograms show that the forecast is not biased. The timing errors in the flood predictions are decreased when soil moisture data is used and imminent floods can be forecasted with skill one day earlier. In conclusion, our study shows that assimilation of satellite soil moisture increases the performance of flood forecasting systems for large catchments, like the Upper Danube. The additional gain is highest when discharge observations from both upstream and downstream areas are used in combination with the soil moisture data. These results show the potential of future soil moisture missions with a higher spatial resolution like SMAP to improve near-real time flood forecasting in large catchments.

  16. Improving flood forecasting capability of physically based distributed hydrological models by parameter optimization

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

    Physically based distributed hydrological models (hereafter referred to as PBDHMs) divide 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. They are regarded to have the potential to improve the catchment hydrological process 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. However, unfortunately the uncertainties associated with this model derivation are 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 particle swarm optimization (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 model capability in catchment 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 the Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improved PSO algorithm is developed for the parameter optimization of the Liuxihe model in catchment flood forecasting. The improvements include adoption of the linearly 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 the Liuxihe model parameter optimization effectively and could improve the model capability largely in catchment flood forecasting, thus proving that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological models. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for the Liuxihe model catchment flood forecasting are 20 and 30 respectively.

  17. Development of Hydrometeorological Monitoring and Forecasting as AN Essential Component of the Early Flood Warning System:

    NASA Astrophysics Data System (ADS)

    Manukalo, V.

    2012-12-01

    Defining issue The river inundations are the most common and destructive natural hazards in Ukraine. Among non-structural flood management and protection measures a creation of the Early Flood Warning System is extremely important to be able to timely recognize dangerous situations in the flood-prone areas. Hydrometeorological information and forecasts are a core importance in this system. The primary factors affecting reliability and a lead - time of forecasts include: accuracy, speed and reliability with which real - time data are collected. The existing individual conception of monitoring and forecasting resulted in a need in reconsideration of the concept of integrated monitoring and forecasting approach - from "sensors to database and forecasters". Result presentation The Project: "Development of Flood Monitoring and Forecasting in the Ukrainian part of the Dniester River Basin" is presented. The project is developed by the Ukrainian Hydrometeorological Service in a conjunction with the Water Management Agency and the Energy Company "Ukrhydroenergo". The implementation of the Project is funded by the Ukrainian Government and the World Bank. The author is nominated as the responsible person for coordination of activity of organizations involved in the Project. The term of the Project implementation: 2012 - 2014. The principal objectives of the Project are: a) designing integrated automatic hydrometeorological measurement network (including using remote sensing technologies); b) hydrometeorological GIS database construction and coupling with electronic maps for flood risk assessment; c) interface-construction classic numerical database -GIS and with satellite images, and radar data collection; d) providing the real-time data dissemination from observation points to forecasting centers; e) developing hydrometeoroogical forecasting methods; f) providing a flood hazards risk assessment for different temporal and spatial scales; g) providing a dissemination of current information, forecasts and warnings to consumers automatically. Besides scientific and technical issues the implementation of these objectives requires solution of a number of organizational issues. Thus, as a result of the increased complexity of types of hydrometeorological data and in order to develop forecasting methods, a reconsideration of meteorological and hydrological measurement networks should be carried out. The "optimal density of measuring networks" is proposed taking into account principal terms: a) minimizing an uncertainty in characterizing the spacial distribution of hydrometeorological parameters; b) minimizing the Total Life Cycle Cost of creation and maintenance of measurement networks. Much attention will be given to training Ukrainian disaster management authorities from the Ministry of Emergencies and the Water Management Agency to identify the flood hazard risk level and to indicate the best protection measures on the basis of continuous monitoring and forecasts of evolution of meteorological and hydrological conditions in the river basin.

  18. 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.

  19. 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.

  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. USGS Measures Historic Flooding Across the Nation

    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...

  2. USGS Measures Historic Flooding Across the Nation

    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...

  3. 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

  4. Model Integration for Real-Time Flood Forecasting Inundation Mapping for Nashville Tributaries

    NASA Astrophysics Data System (ADS)

    Charley, W.; Moran, B.; LaRosa, J.

    2012-12-01

    In May of 2010, between 14 and 19 inches of rain fell on the Nashville metro area in two days, quickly overwhelming tributaries to the Cumberland River and causing wide-spread, serious flooding. Tractor-trailers and houses were seen floating down Mill Creek, a primary tributary in the south eastern area of Nashville. Twenty-six people died and over 2 billion dollars in damage occurred as a result of the flood. Since that time, several other significant rainfall events have occurred in the area. Emergency responders were unable to deliver aid or preventive measures to areas under threat of flooding (or under water) in time to reduce damages because they could not identify those areas far enough in advance of the floods. Nashville Metro Water, the National Weather Service, the US Geological Survey and the US Army Corps of Engineers established a joint venture to seek ways to better forecast short-term flood events in the region. One component of this effort was a pilot project to compute and display real time inundation maps for Mill Creek, a 108 square-mile basin to the south east of Nashville. HEC-RTS (Real-Time Simulation) was used to assimilate and integrate the hydrologic model HEC-HMS with the hydraulics model HEC-RAS and the inundation mapping program HEC-RAS Mapper. The USGS, along with the other agencies, installed additional precipitation and flow/stage gages in the area. Measurements are recorded every 5-30 minutes and are posted on the USGS NWIS database, which are downloaded by HEC-RTS. Using this data in combination with QPFs (Quantitative Precipitation Forecasts) from the NWS, HEC-RTS applies HEC-HMS and HEC-RAS to estimate current and forecast stage hydrographs. The peak stages are read by HEC-RAS Mapper to compute inundation depths for 6 by 6 foot grid cells. HEC-RTS displays the inundation on a high resolution MrSid aerial photo, along with subbasin boundary, street and various other layers. When a user zooms in and "mouses" over a cell, the inundation depth for that cell is displayed as a tool-tip. This procedure for real-time inundation mapping provides a relatively accurate depiction of water depths throughout the basin, as it is computed using the temporal and spatial distribution of rainfall that has actually occurred and will compute depths based on forecasted rainfall. In addition, the HEC-RAS hydraulics model can be modified as the event is occurring to represent changes in the stream channels, such as obstructions at bridges. This paper covers the procedure used and provides results and images from the integrated models for various precipitation scenarios.

  5. 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.

  6. 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.

  7. Predictability of horizontal water vapor transport relative to precipitation: Enhancing situational awareness for forecasting western U.S. extreme precipitation and flooding

    NASA Astrophysics Data System (ADS)

    Lavers, David A.; Waliser, Duane E.; Ralph, F. Martin; Dettinger, Michael D.

    2016-03-01

    The western United States is vulnerable to socioeconomic disruption due to extreme winter precipitation and floods. Traditionally, forecasts of precipitation and river discharge provide the basis for preparations. Herein we show that earlier event awareness may be possible through use of horizontal water vapor transport (integrated vapor transport (IVT)) forecasts. Applying the potential predictability concept to the National Centers for Environmental Prediction global ensemble reforecasts, across 31 winters, IVT is found to be more predictable than precipitation. IVT ensemble forecasts with the smallest spreads (least forecast uncertainty) are associated with initiation states with anomalously high geopotential heights south of Alaska, a setup conducive for anticyclonic conditions and weak IVT into the western United States. IVT ensemble forecasts with the greatest spreads (most forecast uncertainty) have initiation states with anomalously low geopotential heights south of Alaska and correspond to atmospheric rivers. The greater IVT predictability could provide warnings of impending storminess with additional lead times for hydrometeorological applications.

  8. Local flood forecasting using guided model construction, data assimilation and web interfaces

    NASA Astrophysics Data System (ADS)

    Smith, Paul; Beven, Keith

    2013-04-01

    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 install adequate telemetered monitoring equipment; generally a water level sensor and a rain gauge; which allows the construction of a local flood forecast. In this presentation we outline a methodology for providing detailed and location specific forecasts which can be computed either 'on-' or `off-site'. The basis of this is a guided model building process which incorporates both data assimilation and representation of the forecast uncertainty. The process requires the modeller to make only a few choices thus allowing rapid model deployment and revision. To be of use such forecasts require 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 in this a web interface, showing both the predictions and past performance of the model, designed to encourage realistic interpretation of the forecasts and their uncertainties is presented. This tool and the guided model build are outlined using case studies based in the North West of the UK.

  9. 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.

  10. Development of roughness updating based on artificial neural network in a river hydraulic model for flash flood forecasting

    NASA Astrophysics Data System (ADS)

    Fu, J. C.; Hsu, M. H.; Duann, Y.

    2016-02-01

    Flood is the worst weather-related hazard in Taiwan because of steep terrain and storm. The tropical storm often results in disastrous flash flood. To provide reliable forecast of water stages in rivers is indispensable for proper actions in the emergency response during flood. The river hydraulic model based on dynamic wave theory using an implicit finite-difference method is developed with river roughness updating for flash flood forecast. The artificial neural network (ANN) is employed to update the roughness of rivers in accordance with the observed river stages at each time-step of the flood routing process. Several typhoon events at Tamsui River are utilized to evaluate the accuracy of flood forecasting. The results present the adaptive n-values of roughness for river hydraulic model that can provide a better flow state for subsequent forecasting at significant locations and longitudinal profiles along rivers.

  11. 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.

  12. The suitability of remotely sensed soil moisture for improving operational flood forecasting

    NASA Astrophysics Data System (ADS)

    Wanders, N.; Karssenberg, D.; de Roo, A.; de Jong, S. M.; Bierkens, M. F. P.

    2013-11-01

    We evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the prediction of the timing and height of the flood peak and low flows. EFAS is an operational flood forecasting system for Europe and uses a distributed hydrological model for flood predictions with lead times up to 10 days. For this study, satellite-derived soil moisture from ASCAT, AMSR-E and SMOS is assimilated into the EFAS system for the Upper Danube basin and results are compared to assimilation of discharge observations only. To assimilate soil moisture and discharge data into EFAS, an Ensemble Kalman Filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, is included to ensure optimal performance of the EnKF. For the validation, additional discharge observations not used in the EnKF, are used as an independent validation dataset. Our results show that the accuracy of flood forecasts is increased when more discharge observations are assimilated; the Mean Absolute Error (MAE) of the ensemble mean is reduced by 65%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of base flows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the Continuous Ranked Probability Score (CRPS) shows a performance increase of 5-10% on average, compared to assimilation of discharge only. When soil moisture data is used, the timing errors in the flood predictions are decreased especially for shorter lead times and imminent floods can be forecasted with more skill. The number of false flood alerts is reduced when more data is assimilated into the system and the best performance is achieved with the assimilation of both discharge and satellite observations. The additional gain is highest when discharge observations from both upstream and downstream areas are used in combination with the soil moisture data. These results show the potential of remotely sensed soil moisture observations to improve near-real time flood forecasting in large catchments.

  13. The suitability of remotely sensed soil moisture for improving operational flood forecasting

    NASA Astrophysics Data System (ADS)

    Wanders, N.; Karssenberg, D.; de Roo, A.; de Jong, S. M.; Bierkens, M. F. P.

    2014-06-01

    We evaluate the added value of assimilated remotely sensed soil moisture for the European Flood Awareness System (EFAS) and its potential to improve the prediction of the timing and height of the flood peak and low flows. EFAS is an operational flood forecasting system for Europe and uses a distributed hydrological model (LISFLOOD) for flood predictions with lead times of up to 10 days. For this study, satellite-derived soil moisture from ASCAT (Advanced SCATterometer), AMSR-E (Advanced Microwave Scanning Radiometer - Earth Observing System) and SMOS (Soil Moisture and Ocean Salinity) is assimilated into the LISFLOOD model for the Upper Danube Basin and results are compared to assimilation of discharge observations only. To assimilate soil moisture and discharge data into the hydrological model, an ensemble Kalman filter (EnKF) is used. Information on the spatial (cross-) correlation of the errors in the satellite products, is included to ensure increased performance of the EnKF. For the validation, additional discharge observations not used in the EnKF are used as an independent validation data set. Our results show that the accuracy of flood forecasts is increased when more discharge observations are assimilated; the mean absolute error (MAE) of the ensemble mean is reduced by 35%. The additional inclusion of satellite data results in a further increase of the performance: forecasts of baseflows are better and the uncertainty in the overall discharge is reduced, shown by a 10% reduction in the MAE. In addition, floods are predicted with a higher accuracy and the continuous ranked probability score (CRPS) shows a performance increase of 5-10% on average, compared to assimilation of discharge only. When soil moisture data is used, the timing errors in the flood predictions are decreased especially for shorter lead times and imminent floods can be forecasted with more skill. The number of false flood alerts is reduced when more observational data is assimilated into the system. The added values of the satellite data is largest when these observations are assimilated in combination with distributed discharge observations. These results show the potential of remotely sensed soil moisture observations to improve near-real time flood forecasting in large catchments.

  14. Operational aspects of asynchronous filtering for flood forecasting

    NASA Astrophysics Data System (ADS)

    Rakovec, O.; Weerts, A. H.; Sumihar, J.; Uijlenhoet, R.

    2015-06-01

    This study investigates the suitability of the asynchronous ensemble Kalman filter (AEnKF) and a partitioned updating scheme for hydrological forecasting. The AEnKF requires forward integration of the model for the analysis and enables assimilation of current and past observations simultaneously at a single analysis step. The results of discharge assimilation into a grid-based hydrological model (using a soil moisture error model) for the Upper Ourthe catchment in the Belgian Ardennes show that including past predictions and observations in the data assimilation method improves the model forecasts. Additionally, we show that elimination of the strongly non-linear relation between the soil moisture storage and assimilated discharge observations from the model update becomes beneficial for improved operational forecasting, which is evaluated using several validation measures.

  15. Impact of Different Data Assimilation Strategies for SMOS Observations on Flood Forecasting Accuracy

    NASA Astrophysics Data System (ADS)

    Pauwels, V. R. N.; Verhoest, N.; Lievens, H.; Martens, B.; van Den Berg, M. J.; Al-Bitar, A.; Merlin, O.; Kumar Tomer, S.; Cabot, F.; Kerr, Y. H.; Pan, M.; Wood, E. F.; Drusch, M.; Hendricks Franssen, H. J.; Vereecken, H.; De Lannoy, G. J. M.; Dumedah, G.; Walker, J. P.

    2014-12-01

    During the last decade, significant efforts have been directed towards establishing and improving flood forecasting systems for large river basins. Examples include the European Flood Alert System, and the Bureau of Meteorology Flood Warning Systems in Australia. A number of attempts have also been made to increase the accuracy of the forecasted flood volumes from these systems. One attractive way in which this can be achieved is to use remotely sensed surface soil moisture contents to constrain the hydrologic model predictions. Satellite missions such as SMOS can provide very useful information on the wetness conditions of these basins, which in many cases is an important initial condition for discharge generation. Assimilation of these satellite data is thus a logical way to proceed. We will present results from two different assimilation strategies for the Murray-Darling basin in Australia using the Variable Infiltration Capacity (VIC) model. Firstly, the SMOS soil moisture data are assimilated into the hydrologic model at their original spatial resolution. As the spatial resolution of the remote sensing data (25 km) is coarser than the spatial resolution of the model (10 km), a multiscale data assimilation algorithm needs to be implemented. Secondly, the SMOS data are downscaled to the model resolution, prior to their assimilation. In this presentation, the impact of the assimilation of both products on the accuracy of the forecasted flood volumes is assessed.

  16. 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.

  17. Improvement of operational flood forecasting through the assimilation of satellite observations and multiple river flow data

    NASA Astrophysics Data System (ADS)

    Castelli, Fabio; Ercolani, Giulia

    2016-05-01

    Data assimilation has the potential to improve flood forecasting. However, it is rarely employed in distributed hydrologic models for operational predictions. In this study, we present variational assimilation of river flow data at multiple locations and of land surface temperature (LST) from satellite in a distributed hydrologic model that is part of the operational forecasting chain for the Arno river, in central Italy. LST is used to estimate initial condition of soil moisture through a coupled surface energy/water balance scheme. We present here several hindcast experiments to assess the performances of the assimilation system. The results show that assimilation can significantly improve flood forecasting, although in the limit of data error and model structure.

  18. Climate forecasts in disaster management: Red Cross flood operations in West Africa, 2008.

    PubMed

    Braman, Lisette Martine; van Aalst, Maarten Krispijn; Mason, Simon J; Suarez, Pablo; Ait-Chellouche, Youcef; Tall, Arame

    2013-01-01

    In 2008, the International Federation of Red Cross and Red Crescent Societies (IFRC) used a seasonal forecast for West Africa for the first time to implement an Early Warning, Early Action strategy for enhanced flood preparedness and response. Interviews with disaster managers suggest that this approach improved their capacity and response. Relief supplies reached flood victims within days, as opposed to weeks in previous years, thereby preventing further loss of life, illness, and setbacks to livelihoods, as well as augmenting the efficiency of resource use. This case demonstrates the potential benefits to be realised from the use of medium-to-long-range forecasts in disaster management, especially in the context of potential increases in extreme weather and climate-related events due to climate variability and change. However, harnessing the full potential of these forecasts will require continued effort and collaboration among disaster managers, climate service providers, and major humanitarian donors. PMID:23066755

  19. 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).

  20. GloFAS - global ensemble streamflow forecasting and flood early warning

    NASA Astrophysics Data System (ADS)

    Alfieri, L.; Burek, P.; Dutra, E.; Krzeminski, B.; Muraro, D.; Thielen, J.; Pappenberger, F.

    2013-03-01

    Anticipation and preparedness for large-scale flood events have a key role in mitigating their impact and optimizing the strategic planning of water resources. Although several developed countries have well-established systems for river monitoring and flood early warning, figures of populations affected every year by floods in developing countries are unsettling. This paper presents the Global Flood Awareness System (GloFAS), which has been set up to provide an overview on upcoming floods in large world river basins. GloFAS is based on distributed hydrological simulation of numerical ensemble weather predictions with global coverage. Streamflow forecasts are compared statistically to climatological simulations to detect probabilistic exceedance of warning thresholds. In this article, the system setup is described, together with an evaluation of its performance over a two-year test period and a qualitative analysis of a case study for the Pakistan flood, in summer 2010. It is shown that hazardous events in large river basins can be skilfully detected with a forecast horizon of up to 1 month. In addition, results suggest that an accurate simulation of initial model conditions and an improved parameterization of the hydrological model are key components to reproduce accurately the streamflow variability in the many different runoff regimes of the earth.

  1. The Impact Of Calibration and Reforecasts of Ensemble Prediction System of Inputs on a Flood Forecast System

    NASA Astrophysics Data System (ADS)

    Trinh, B.; Pappenberger, F.

    2009-04-01

    The pre-operation European Flood Alerts System (EFAS) relies on reliable and accurate input by ensembles of Numerical Weather Predictions (NWPs). The usage of such inputs for Probabilistic Quantitative Hydrology Forecast is still difficult as a variety of uncertainties arise. For example, forecasts are biased and the ensemble spread of forecasts is often under- or overestimating observational variances. Moreover, anthropogenic effects (land use, urbanization and dykes), climate change, and tectonic/isostatic relief change, which affect return periods, significantly influence the quality of flood forecasts. In order to access to the hazard associated to the hydrological forecast issued by EFAS, we compare two methods to calibrate the ensemble forecast, especially Ensemble Prediction System (EPS) of ECMWF, as the inputs of EFAS: 1. Reforecast for regional meteorological forecast 2. Calibrating EPS for regional meteorological forecast. The results will be evaluated in terms of Talagrand diagram, Continuous Rank Probability Score (CRPS), spread skill relationship and Relative Operating Characteristic (ROC).

  2. A Nested Probabilistic and Deterministic Flood Forecasting Model: Toward an Early Warning System

    NASA Astrophysics Data System (ADS)

    AghaKouchak, A.

    2011-12-01

    Floods are the most life threatening hydrologic extremes and are one of the most widespread natural disasters. A 20-year (1985-2004) record shows that on average 150 flood events occurred each year across the globe resulting in 7500 deaths and approximately $15 billion in property and economic damage. We present a nested hydrologic model for quasi-global flood forecasting using satellite data. The model operates in two steps. Step 1: A 0.25 degree gridded probabilistic quasi-global hydrologic model is used to identify locations with high probability of flooding. The model provides an ensemble of runoff simulations using a set of resampled model parameters. Step 2: A deterministic semi-distributed model, nested within the probabilistic model, is employed for detailed flood analysis in watershed scale. The semi-distributed mode (Step 2) is activated only for areas identified as high risk in the first step. Satellite-based precipitation, snow covered areas, evapotranspiration and soil moisture data, derived from multiple sensors, are used as input data. Other forcings are obtained from NASA Land Information System (LIS). The results indicate that the model can provide reasonable probability of flooding. Efforts are underway to use this model for an early flood warning system that can provide probability of flood events and their uncertainties.

  3. 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

  4. Verification of National Weather Service spot forecasts using surface observations

    NASA Astrophysics Data System (ADS)

    Lammers, Matthew Robert

    Software has been developed to evaluate National Weather Service spot forecasts issued to support prescribed burns and early-stage wildfires. Fire management officials request spot forecasts from National Weather Service Weather Forecast Offices to provide detailed guidance as to atmospheric conditions in the vicinity of planned prescribed burns as well as wildfires that do not have incident meteorologists on site. This open source software with online display capabilities is used to examine an extensive set of spot forecasts of maximum temperature, minimum relative humidity, and maximum wind speed from April 2009 through November 2013 nationwide. The forecast values are compared to the closest available surface observations at stations installed primarily for fire weather and aviation applications. The accuracy of the spot forecasts is compared to those available from the National Digital Forecast Database (NDFD). Spot forecasts for selected prescribed burns and wildfires are used to illustrate issues associated with the verification procedures. Cumulative statistics for National Weather Service County Warning Areas and for the nation are presented. Basic error and accuracy metrics for all available spot forecasts and the entire nation indicate that the skill of the spot forecasts is higher than that available from the NDFD, with the greatest improvement for maximum temperature and the least improvement for maximum wind speed.

  5. Interpolation of observed rainfall fields for flood forecasting in data poor areas

    NASA Astrophysics Data System (ADS)

    Rogelis Prada, M. C.; Werner, M. G. F.

    2010-09-01

    Observed rainfall fields constitute a crucial input for operational flood forecasting, providing boundary conditions to hydrological models for prediction of flows and levels in relevant forecast points. Such observed fields are derived through interpolation from available observed data from rain gauges. The reliability of the derived rainfall field depends on the density of the gauge network within the basin, as well as on the variability of the rainfall itself, and the interpolation method. In this paper interpolation methods to estimate rainfall fields under data- poor environments are researched, with the derived rainfall fields being used in operational flood warnings. Methods are applied in a small catchment in Bogotá, Colombia. This catchment has a complex climatology, which is strongly influenced by the inter-tropical convergence zone and orographic enhancement. As is common in such catchments in developing countries, the rainfall gauging network is sparse, while the need for reliable rainfall in flood forecasting is high. The extensive high flood risk zones in the lower areas of the catchment, where urbanization processes are characterized by unplanned occupation of areas close to rivers, is common in developing countries. Results show the sensitivity of interpolated rainfall fields to the interpolation methods chosen, and the importance of the use of indicator variables for improving the spatial distribution of interpolated rainfall. The value of these methods in establishing optimal new gauging sites for augmenting the sparse gauge network is demonstrated.

  6. Operational water management of Rijnland water system and pilot of ensemble forecasting system for flood control

    NASA Astrophysics Data System (ADS)

    van der Zwan, Rene

    2013-04-01

    The Rijnland water system is situated in the western part of the Netherlands, and is a low-lying area of which 90% is below sea-level. The area covers 1,100 square kilometres, where 1.3 million people live, work, travel and enjoy leisure. The District Water Control Board of Rijnland is responsible for flood defence, water quantity and quality management. This includes design and maintenance of flood defence structures, control of regulating structures for an adequate water level management, and waste water treatment. For water quantity management Rijnland uses, besides an online monitoring network for collecting water level and precipitation data, a real time control decision support system. This decision support system consists of deterministic hydro-meteorological forecasts with a 24-hr forecast horizon, coupled with a control module that provides optimal operation schedules for the storage basin pumping stations. The uncertainty of the rainfall forecast is not forwarded in the hydrological prediction. At this moment 65% of the pumping capacity of the storage basin pumping stations can be automatically controlled by the decision control system. Within 5 years, after renovation of two other pumping stations, the total capacity of 200 m3/s will be automatically controlled. In critical conditions there is a need of both a longer forecast horizon and a probabilistic forecast. Therefore ensemble precipitation forecasts of the ECMWF are already consulted off-line during dry-spells, and Rijnland is running a pilot operational system providing 10-day water level ensemble forecasts. The use of EPS during dry-spells and the findings of the pilot will be presented. Challenges and next steps towards on-line implementation of ensemble forecasts for risk-based operational management of the Rijnland water system will be discussed. An important element in that discussion is the question: will policy and decision makers, operator and citizens adapt this Anticipatory Water management, including temporary lower storage basin levels and a reduction in extra investments for infrastructural measures.

  7. 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.

  8. Parcel-scale urban coastal flood mapping: Leveraging the multi-scale CoSMoS model for coastal flood forecasting

    NASA Astrophysics Data System (ADS)

    Gallien, T.; Barnard, P. L.; Sanders, B. F.

    2011-12-01

    California coastal sea levels are projected to rise 1-1.4 meters in the next century and evidence suggests mean tidal range, and consequently, mean high water (MHW) is increasing along portions of Southern California Bight. Furthermore, emerging research indicates wind stress patterns associated with the Pacific Decadal Oscillation (PDO) have suppressed sea level rise rates along the West Coast since 1980, and a reversal in this pattern would result in the resumption of regional sea level rise rates equivalent to or exceeding global mean sea level rise rates, thereby enhancing coastal flooding. Newport Beach is a highly developed, densely populated lowland along the Southern California coast currently subject to episodic flooding from coincident high tides and waves, and the frequency and intensity of flooding is expected to increase with projected future sea levels. Adaptation to elevated sea levels will require flood mapping and forecasting tools that are sensitive to the dominant factors affecting flooding including extreme high tides, waves and flood control infrastructure. Considerable effort has been focused on the development of nowcast and forecast systems including Scripps Institute of Oceanography's Coastal Data Information Program (CDIP) and the USGS Multi-hazard model, the Southern California Coastal Storm Modeling System (CoSMoS). However, fine scale local embayment dynamics and overtopping flows are needed to map unsteady flooding effects in coastal lowlands protected by dunes, levees and seawalls. Here, a recently developed two dimensional Godunov non-linear shallow water solver is coupled to water level and wave forecasts from the CoSMoS model to investigate the roles of tides, waves, sea level changes and flood control infrastructure in accurate flood mapping and forecasting. The results of this study highlight the important roles of topographic data, embayment hydrodynamics, water level uncertainties and critical flood processes required for meaningful prediction of sea level rise impacts and coastal flood forecasting.

  9. Development of an Operational Typhoon Swell Forecasting and Coastal Flooding Early Warning System

    NASA Astrophysics Data System (ADS)

    Fan, Y. M.; Wu, L. C.; Doong, D. J.; Kao, C. C.; Wang, J. H.

    2012-04-01

    Coastal floods and typhoon swells are a consistent threat to oceanfront countries, causing major human suffering and substantial economic losses, such as wrecks, ship capsized, and marine construction failure, etc. Climate change is exacerbating the problem. An early warning system is essential to mitigate the loss of life and property from coastal flooding and typhoon swells. The purpose of this study is to develop a typhoon swell forecasting and coastal flooding early warning system by integrating existing sea-state monitoring technology, numerical ocean forecasting models, historical database and experiences, as well as computer science. The proposed system has capability offering data for the past, information for the present, and for the future. The system was developed for Taiwanese coast due to its frequent threat by typhoons. An operational system without any manual work is the basic requirement of the system. Integration of various data source is the system kernel. Numerical ocean models play the important role within the system because they provide data for assessment of possible typhoon swell and flooding. The system includes regional wave model (SWAN) which nested with the large domain wave model (NWW III), is operationally set up for coastal waves forecasting, especially typhoon swell forecasting before typhoon coming, and the storm surge predicted by a POM model. Data assimilation technology is incorporated for enhanced accuracy. A warning signal is presented when the storm water level that accumulated from astronomical tide, storm surge, and wave-induced run-up exceeds the alarm sea level. This warning system has been in practical use for coastal flooding damage mitigation in Taiwan for years. Example of the system operation during Typhoon Haitung struck Taiwan in 2005 is illustrated in this study.

  10. 77 FR 28891 - National Flood Insurance Program Programmatic Environmental Impact Statement

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-16

    ... SECURITY Federal Emergency Management Agency National Flood Insurance Program Programmatic Environmental... three components of the NFIP are Flood Insurance, Floodplain Management, and Flood Hazard Mapping. More... providing flood insurance and reducing flood damages through floodplain management regulations, the...

  11. Reduction of the uncertainties in the water level-discharge relation of a 1D hydraulic model in the context of operational flood forecasting

    NASA Astrophysics Data System (ADS)

    Habert, J.; Ricci, S.; Le Pape, E.; Thual, O.; Piacentini, A.; Goutal, N.; Jonville, G.; Rochoux, M.

    2016-01-01

    This paper presents a data-driven hydrodynamic simulator based on the 1-D hydraulic solver dedicated to flood forecasting with lead time of an hour up to 24 h. The goal of the study is to reduce uncertainties in the hydraulic model and thus provide more reliable simulations and forecasts in real time for operational use by the national hydrometeorological flood forecasting center in France. Previous studies have shown that sequential assimilation of water level or discharge data allows to adjust the inflows to the hydraulic network resulting in a significant improvement of the discharge while leaving the water level state imperfect. Two strategies are proposed here to improve the water level-discharge relation in the model. At first, a modeling strategy consists in improving the description of the river bed geometry using topographic and bathymetric measurements. Secondly, an inverse modeling strategy proposes to locally correct friction coefficients in the river bed and the flood plain through the assimilation of in situ water level measurements. This approach is based on an Extended Kalman filter algorithm that sequentially assimilates data to infer the upstream and lateral inflows at first and then the friction coefficients. It provides a time varying correction of the hydrological boundary conditions and hydraulic parameters. The merits of both strategies are demonstrated on the Marne catchment in France for eight validation flood events and the January 2004 flood event is used as an illustrative example throughout the paper. The Nash-Sutcliffe criterion for water level is improved from 0.135 to 0.832 for a 12-h forecast lead time with the data assimilation strategy. These developments have been implemented at the SAMA SPC (local flood forecasting service in the Haute-Marne French department) and used for operational forecast since 2013. They were shown to provide an efficient tool for evaluating flood risk and to improve the flood early warning system. Complementary with the deterministic forecast of the hydraulic state, the estimation of an uncertainty range is given relying on off-line and on-line diagnosis. The possibilities to further extend the control vector while limiting the computational cost and equifinality problem are finally discussed.

  12. Short-Term flood forecasting in developing countries and in non-ordinary conditions

    NASA Astrophysics Data System (ADS)

    Kuzmin, V. A.

    2001-05-01

    Every natural process may be separated on four additions: 1. Deterministic component described by differential equations; 2. Stochastic component having a clear period of fluctuation, a physic reasons of which is unknown; 3. Deterministic component having extremely small inertia; this component is not to be forecasted; 4. Noises. The following principles of the forecasting of catastrophes to be offered: a) Real process may be considered as a combination of known deterministic process, unknown periodic one, and noises; b) This combination must be described correctly by the forecasting model which must be robust; c) Correct forecast of extreme hydro-logical events cannot be deterministic; and finally d) As parameters of model cease to be adequacy reflection of their natural prototypes, the non-parametric methods of determination of latent trends are prefer-able. Offered scheme may be used for both short-term and long-term forecasting as follows: 1. Deterministic differential equation of the first moment; 2. Non-parametric method of accounting of unknown factors; 3. Stochastic differential equation for an analysis of unknown com-ponents of studied process or residuals. As a result, we have the equations for the mode of the forecasted probability distribution, which compose the Unified Stochastic Self-Training Procedure (USSTP). It gave more then 50 successful fore-casts of disastrous floods and droughts. This gives ground to propose the USSTP for its application in the developing countries and in most difficult situations.

  13. 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.

  14. Development of Flood Forecasting Using Statistical Method in Four River Basins in Terengganu, Malaysia

    NASA Astrophysics Data System (ADS)

    Noor, M. S. F. M.; Sidek, L. M.; Basri, H.; Husni, M. M. M.; Jaafar, A. S.; Kamaluddin, M. H.; Majid, W. H. A. W. A.; Mohammad, A. H.; Osman, S.

    2016-03-01

    One of the critical regions in Malaysia is Terengganu which is located at east coast of Peninsular Malaysia. In Terengganu, flood is experienced regularly because of attributed topography and climate including northeast monsoon. Moreover, rainfall is with high intensity during the November to February in Terengganu as forcing factor to produce of flood. In this study, main objectives are water stage forecasting and deriving the related equations based on least squared method. For this study, it is used two methods which called inclusion of residual (Method A) and non-inclusion residual (Method B) respectively. Result depicts that Method B outperformed to forecast the water stage at selected case studies (Besut, Dungun, Kemaman, Terengganu).

  15. A fuzzy inference method based on association rule analysis with application to river flood forecasting.

    PubMed

    Zhang, Chi; Wang, Yilun; Zhang, Lili; Zhou, Huicheng

    2012-01-01

    In this paper, a computationally efficient version of the widely used Takagi-Sugeno (T-S) fuzzy reasoning method is proposed, and applied to river flood forecasting. It is well known that the number of fuzzy rules of traditional fuzzy reasoning methods exponentially increases as the number of input parameters increases, often causing prohibitive computational burden. The proposed method greatly reduces the number of fuzzy rules by making use of the association rule analysis on historical data, and therefore achieves computational efficiency for the cases of a large number of input parameters. In the end, we apply this new method to a case study of river flood forecasting, which demonstrates that the proposed fuzzy reasoning engine can achieve better prediction accuracy than the widely used Muskingum-Cunge scheme. PMID:22949238

  16. 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.

  17. Potential application of wavelet neural network ensemble to forecast streamflow for flood management

    NASA Astrophysics Data System (ADS)

    Kasiviswanathan, K. S.; He, Jianxun; Sudheer, K. P.; Tay, Joo-Hwa

    2016-05-01

    Streamflow forecasting, especially the long lead-time forecasting, is still a very challenging task in hydrologic modeling. This could be due to the fact that the forecast accuracy measured in terms of both the amplitude and phase or temporal errors and the forecast precision/reliability quantified in terms of the uncertainty significantly deteriorate with the increase of the lead-time. In the model performance evaluation, the conventional error metrics, which primarily quantify the amplitude error and do not explicitly account for the phase error, have been commonly adopted. For the long lead-time forecasting, the wavelet based neural network (WNN) among a variety of advanced soft computing methods has been shown to be promising in the literature. This paper presented and compared WNN and artificial neural network (ANN), both of which were combined with the ensemble method using block bootstrap sampling (BB), in terms of the forecast accuracy and precision at various lead-times on the Bow River, Alberta, Canada. Apart from conventional model performance metrics, a new index, called percent volumetric error, was proposed, especially for quantifying the phase error. The uncertainty metrics including percentage of coverage and average width were used to evaluate the precision of the modeling approaches. The results obtained demonstrate that the WNN-BB consistently outperforms the ANN-BB in both the categories of the forecast accuracy and precision, especially in the long lead-time forecasting. The findings strongly suggest that the WNN-BB is a robust modeling approach for streamflow forecasting and thus would aid in flood management.

  18. Use of geostationary meteorological satellite images in convective rain estimation for flash-flood forecasting

    NASA Astrophysics Data System (ADS)

    Wardah, T.; Abu Bakar, S. H.; Bardossy, A.; Maznorizan, M.

    2008-07-01

    SummaryFrequent flash-floods causing immense devastation in the Klang River Basin of Malaysia necessitate an improvement in the real-time forecasting systems being used. The use of meteorological satellite images in estimating rainfall has become an attractive option for improving the performance of flood forecasting-and-warning systems. In this study, a rainfall estimation algorithm using the infrared (IR) information from the Geostationary Meteorological Satellite-5 (GMS-5) is developed for potential input in a flood forecasting system. Data from the records of GMS-5 IR images have been retrieved for selected convective cells to be trained with the radar rain rate in a back-propagation neural network. The selected data as inputs to the neural network, are five parameters having a significant correlation with the radar rain rate: namely, the cloud-top brightness-temperature of the pixel of interest, the mean and the standard deviation of the temperatures of the surrounding five by five pixels, the rate of temperature change, and the sobel operator that indicates the temperature gradient. In addition, three numerical weather prediction (NWP) products, namely the precipitable water content, relative humidity, and vertical wind, are also included as inputs. The algorithm is applied for the areal rainfall estimation in the upper Klang River Basin and compared with another technique that uses power-law regression between the cloud-top brightness-temperature and radar rain rate. Results from both techniques are validated against previously recorded Thiessen areal-averaged rainfall values with coefficient correlation values of 0.77 and 0.91 for the power-law regression and the artificial neural network (ANN) technique, respectively. An extra lead time of around 2 h is gained when the satellite-based ANN rainfall estimation is coupled with a rainfall-runoff model to forecast a flash-flood event in the upper Klang River Basin.

  19. Towards a flash flood early warning system through hydrological simulation of probabilistic ensemble forecasts

    NASA Astrophysics Data System (ADS)

    Alfieri, Lorenzo; Thielen Del Pozo, Jutta

    2010-05-01

    In this work we test a flash flood early warning system based on state-of-the-art probabilistic weather forecasting input data. We make use of the Limited area Ensemble Prediction System (LEPS) provided by the Consortium for Small scale Modeling (COSMO). COSMO-LEPS ensembles are fed into a distributed hydrological model, to obtain discharge estimates. Likewise, discharge climatology is created from a continuous meteorological dataset based on 30-year COSMO-LEPS hindcasts, and used as reference to detect threshold exceedance in the operational ensemble hydrographs. Coherent reference climatology is particularly useful for flash flood events, as they often take place in small watersheds, where no gauge measurements are available. The concept of persistence of meteorological forecasts is also tested as a method to improve the detection of severe events. Starting from the operational 5-km simulation at the European scale, when a signal for possible flash flooding is detected a regional catchment-scale simulation is activated on a finer spatial scale (1 km grid). Two targeted analyses are carried out to investigate: a) an automatic rule to activate the fine-scale analysis, and b) the influence of initial conditions on the estimated hydrographs, and in turn on threshold exceedances. The Gardon d'Anduze catchment, in the south of France, is chosen as a case study. A number of simulations are performed and results are analyzed and discussed. Our findings show that flash floods can sometimes be detected with a considerable lead time, especially if compared to the response time of the catchments where these phenomena take place. However, the amount of uncertainty related to the forecast is considerable, therefore the choice of appropriate thresholds for flash flood detection is of crucial importance and should account for the maximum acceptable number of either false alarms and undetected events.

  20. Simulating and Forecasting Flooding Events in the City of Jeddah, Saudi Arabia

    NASA Astrophysics Data System (ADS)

    Ghostine, Rabih; Viswanadhapalli, Yesubabu; Hoteit, Ibrahim

    2014-05-01

    Metropolitan cities in the Kingdom of Saudi Arabia, as Jeddah and Riyadh, are more frequently experiencing flooding events caused by strong convective storms that produce intense precipitation over a short span of time. The flooding in the city of Jeddah in November 2009 was described by civil defense officials as the worst in 27 years. As of January 2010, 150 people were reported killed and more than 350 were missing. Another flooding event, less damaging but comparably spectacular, occurred one year later (Jan 2011) in Jeddah. Anticipating floods before they occur could minimize human and economic losses through the implementation of appropriate protection, provision and rescue plans. We have developed a coupled hydro-meteorological model for simulating and predicting flooding events in the city of Jeddah. We use the Weather Research Forecasting (WRF) model assimilating all available data in the Jeddah region for simulating the storm events in Jeddah. The resulting rain is then used on 10 minutes intervals to feed up an advanced numerical shallow water model that has been discretized on an unstructured grid using different numerical schemes based on the finite elements or finite volume techniques. The model was integrated on a high-resolution grid size varying between 0.5m within the streets of Jeddah and 500m outside the city. This contribution will present the flooding simulation system and the simulation results, focusing on the comparison of the different numerical schemes on the system performances in terms of accuracy and computational efficiency.

  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. Probabilistic flood forecasting for Rapid Response Catchments using a countrywide distributed hydrological model: experience from the UK

    NASA Astrophysics Data System (ADS)

    Cole, Steven J.; Moore, Robert J.; Robson, Alice J.; Mattingley, Paul S.

    2014-05-01

    Across Britain, floods in rapidly responding catchments are a major concern and regularly cause significant damage (e.g. Boscastle 2004, Morpeth 2008, Cornwall 2010 and Comrie 2012). Typically these catchments have a small area and are characterised by steep slopes and/or significant suburban/urban land-cover. The meteorological drivers can be of convective origin or frontal with locally intense features (e.g. embedded convection or orographic enhancement); saturated catchments can amplify the flood response. Both rainfall and flood forecasting for Rapid Response Catchments (RRCs)are very challenging due to the often small-scale nature of the intense rainfall which is of most concern, the small catchment areas, and the short catchment response times. Over the last 3 to 4 years, new countrywide Flood Forecasting Systems based on the Grid-to-Grid (G2G) distributed hydrological (rainfall-runoff and routing) model have been implemented across Britain for use by the Flood Forecasting Centre and Scottish Flood Forecasting Service. This has achieved a step-change in operational capability with forecasts of flooding several days ahead "everywhere" on a 1 km grid now possible. The modelling and forecasting approach underpins countrywide Flood Guidance Statements out to 5 days which are used by emergency response organisations for planning and preparedness. The initial focus of these systems has been to provide a countrywide overview of flood risk. However, recent research has explored the potential of the G2G approach to support more frequent and detailed alerts relevant to flood warning in RRCs. Integral to this activity is the use of emerging high-resolution (~1.5km) rainfall forecast products, in deterministic and ensemble form. High spatial resolutions are required to capture some of the small-scale processes and intense rainfall features such as orographic enhancement and convective storm evolution. Even though a deterministic high-resolution numerical weather prediction (NWP) model can provide realistic looking rainfall forecasts, significant uncertainties remain in timing, location and whether a particular feature develops or not. Generally the smaller the scale of the rainfall feature, the shorter the lead-time at which these uncertainties become important. Therefore ensembles are needed to provide uncertainty context for longer lead-time G2G flow forecasts, particularly for small-scale RRCs. A systematic assessment framework has been developed for exploring and understanding the utility of G2G flood forecasts for RRCs. Firstly perfect knowledge of rainfall observations is assumed for past and future times, so as not to confound the hydrological model analysis with errors from rainfall forecasts. Secondly an assessment is made of using deterministic rainfall forecasts (from NWP UKV) in a full emulation of real-time G2G forecasts, and using foreknowledge of rainfall observations as a reference baseline. Finally use of rainfall forecast ensembles with G2G to produce probabilistic flood forecasts is considered, empploying a combination of case-study and longer-term analyses. Blended Ensemble rainfall forecasts (combining radar ensemble nowcast and NWP rainfalls) are assessed in two forms: forecasts out to 24 hours updated 4 times a day, and nowcasts out to 7 hours updated every 15 minutes. Results from the assessment will be presented along with candidates for new operational products and tools that can support flood warning for RRCs, taking account of the inherent uncertainty in the forecasts.

  3. Development of web-based services for a novel ensemble flood forecasting and risk assessment system

    NASA Astrophysics Data System (ADS)

    He, Y.; Manful, D. Y.; Cloke, H. L.; Wetterhall, F.; Li, Z.; Bao, H.; Pappenberger, F.; Wesner, S.; Schubert, L.; Yang, L.; Hu, Y.

    2009-12-01

    Flooding is a wide spread and devastating natural disaster worldwide. Floods that took place in the last decade in China were ranked the worst amongst recorded floods worldwide in terms of the number of human fatalities and economic losses (Munich Re-Insurance). Rapid economic development and population expansion into low lying flood plains has worsened the situation. Current conventional flood prediction systems in China are neither suited to the perceptible climate variability nor the rapid pace of urbanization sweeping the country. Flood prediction, from short-term (a few hours) to medium-term (a few days), needs to be revisited and adapted to changing socio-economic and hydro-climatic realities. The latest technology requires implementation of multiple numerical weather prediction systems. The availability of twelve global ensemble weather prediction systems through the ‘THORPEX Interactive Grand Global Ensemble’ (TIGGE) offers a good opportunity for an effective state-of-the-art early forecasting system. A prototype of a Novel Flood Early Warning System (NEWS) using the TIGGE database is tested in the Huai River basin in east-central China. It is the first early flood warning system in China that uses the massive TIGGE database cascaded with river catchment models, the Xinanjiang hydrologic model and a 1-D hydraulic model, to predict river discharge and flood inundation. The NEWS algorithm is also designed to provide web-based services to a broad spectrum of end-users. The latter presents challenges as both databases and proprietary codes reside in different locations and converge at dissimilar times. NEWS will thus make use of a ready-to-run grid system that makes distributed computing and data resources available in a seamless and secure way. An ability to run or function on different operating systems and provide an interface or front that is accessible to broad spectrum of end-users is additional requirement. The aim is to achieve robust interoperability through strong security and workflow capabilities. A physical network diagram and a work flow scheme of all the models, codes and databases used to achieve the NEWS algorithm are presented. They constitute a first step in the development of a platform for providing real time flood forecasting services on the web to mitigate 21st century weather phenomena.

  4. Development of web-based services for an ensemble flood forecasting and risk assessment system

    NASA Astrophysics Data System (ADS)

    Yaw Manful, Desmond; He, Yi; Cloke, Hannah; Pappenberger, Florian; Li, Zhijia; Wetterhall, Fredrik; Huang, Yingchun; Hu, Yuzhong

    2010-05-01

    Flooding is a wide spread and devastating natural disaster worldwide. Floods that took place in the last decade in China were ranked the worst amongst recorded floods worldwide in terms of the number of human fatalities and economic losses (Munich Re-Insurance). Rapid economic development and population expansion into low lying flood plains has worsened the situation. Current conventional flood prediction systems in China are neither suited to the perceptible climate variability nor the rapid pace of urbanization sweeping the country. Flood prediction, from short-term (a few hours) to medium-term (a few days), needs to be revisited and adapted to changing socio-economic and hydro-climatic realities. The latest technology requires implementation of multiple numerical weather prediction systems. The availability of twelve global ensemble weather prediction systems through the ‘THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a good opportunity for an effective state-of-the-art early forecasting system. A prototype of a Novel Flood Early Warning System (NEWS) using the TIGGE database is tested in the Huai River basin in east-central China. It is the first early flood warning system in China that uses the massive TIGGE database cascaded with river catchment models, the Xinanjiang hydrologic model and a 1-D hydraulic model, to predict river discharge and flood inundation. The NEWS algorithm is also designed to provide web-based services to a broad spectrum of end-users. The latter presents challenges as both databases and proprietary codes reside in different locations and converge at dissimilar times. NEWS will thus make use of a ready-to-run grid system that makes distributed computing and data resources available in a seamless and secure way. An ability to run or function on different operating systems and provide an interface or front that is accessible to broad spectrum of end-users is additional requirement. The aim is to achieve robust interoperability through strong security and workflow capabilities. A physical network diagram and a work flow scheme of all the models, codes and databases used to achieve the NEWS algorithm are presented. They constitute a first step in the development of a platform for providing real time flood forecasting services on the web to mitigate 21st century weather phenomena.

  5. 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.

  6. Correction of upstream flow and hydraulic state with data assimilation in the context of flood forecasting

    NASA Astrophysics Data System (ADS)

    Ricci, S.; Piacentini, A.; Thual, O.; Le Pape, E.; Jonville, G.

    2011-11-01

    The present study describes the assimilation of river water level observations and the resulting improvement in flood forecasting. The Kalman Filter algorithm was built on top of a one-dimensional hydraulic model 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 applied using a four-day sliding window over the flood event. The background error covariances for water level and discharge were represented with anisotropic correlation functions where the correlation length upstream of the observation points is larger than the correlation length downstream of the observation points. This approach was motivated by the implementation of a Kalman Filter algorithm on top of a diffusive flood wave propagation model. The study was carried out on the Adour and the Marne Vallage (France) catchments. The correction of the upstream flow as well as the control of the hydraulic state during the flood event leads to a significant improvement in the water level and discharge in both analysis and forecast modes.

  7. 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.

  8. Towards spatially distributed flood forecasts in flash flood prone areas: application to the supervision of a road network in the South of France

    NASA Astrophysics Data System (ADS)

    Naulin, Jean-Philippe; Payrastre, Olivier; Gaume, Eric; Delrieu, Guy

    2013-04-01

    Accurate flood forecasts are crucial for an efficient flood event management. Until now, hydro-meteorological forecasts have been mainly used for early-warnings in France (Meteorological and flood vigilance maps) or over the world (Flash-flood guidances). These forecasts are generally limited to the main streams covered by the flood forecasting services or to specific watersheds with particular assets like check dams which are in most cases well gauged river sections, leaving aside large parts of the territory. A distributed hydro-meteorological forecasting approach will be presented, able to take advantage of the high spatial and temporal resolution rainfall estimates that are now available to provide information at ungauged sites. The proposed system aiming at detecting road inundation risks had been initially developed and tested in areas of limited size. Its extension to a whole region (the Gard region in the South of France) will be presented, including over 2000 crossing points between rivers and roads and its validation against a large data set of actually reported road inundations observed during recent flash-flood events. These first validation results appear promising. Such a tool would provide the necessary information for flood event management services to identify the areas at risk and to take the appropriate safety and rescue measures: pre-positioning of rescue means, stopping of the traffic on exposed roads, determination of safe accesses or evacuation routes. Moreover, beyond the specific application to the supervision of a road network, this work provides also results concerning the performances of hydro-meteorological forecasts for ungauged headwaters.

  9. 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.

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

    NASA Astrophysics Data System (ADS)

    Van Steenbergen, N.; Willems, P.

    2012-04-01

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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Correction of upstream flow and hydraulic state with data assimilation in the context of flood forecasting

    NASA Astrophysics Data System (ADS)

    Ricci, S.; Piacentini, A.; Thual, O.; Le Pape, E.; Jonville, G.

    2010-11-01

    The present study describes the assimilation of river water level observations and the resulting improvement of the river flood forecast. The BLUE algorithm was built on top of the one-dimensional hydraulics model MASCARET. The assimilation algorithm folds in two steps: the first one is based on the assumption that the upstream flow can be adjusted using a three-parameter correction, the second one consists in directly correcting the hydraulic state. This procedure is applied on a four-day sliding window over the whole flood event. The background error covariances for water level and discharge are represented with asymmetric correlation functions where the upstream correlation length is bigger than the downstream correlation length. This approach is motivated by the implementation of a Kalman Filter algorithm on top of an advection-diffusion toy model. The assimilation study with MASCARET is carried out on the Adour and the Marne Vallage (France) catchments. The correction of the upstream flow as well as the control of the hydraulic state along the flood event leads to a significant improvement of the water level and discharge in analysis and forecast modes.

  16. Advance flood forecasting for flood stricken Bangladesh with a fuzzy reasoning method

    NASA Astrophysics Data System (ADS)

    Liong, Shie-Yui; Lim, Wee-Han; Kojiri, Toshiharu; Hori, Tomoharu

    2000-02-01

    An artificial Neural Network (NN) was successfully applied, in an earlier study, as a prediction tool to forecast water level at Dhaka (Bangladesh), for up to seven lead days in advance, with a high accuracy level. In addition, this high accuracy degree was accompanied with a very short computational time. Both make NN a desirable advance warming forecasting tool. In a later study, a sensitivity analysis was also performed to retain only the most sensitive gauging stations for the Dhaka station. The resulting reduction of gauging stations insignificantly affects the prediction accuracy level.The work concerning the possibility of measurement failure in any of the gauging stations during the critical flow level at Dhaka requires prediction tools which can interpret linguistic assessment of flow levels. A fuzzy logic approach is introduced with two or three membership functions, depending on necessity, for the input stations with five membership functions for the output station. Membership functions for each station are derived from their respective water level frequency distributions, after the Kohonen neural network is used to group the data into clusters. The proposed approach in deriving membership function shows a number of advances over the approach commonly used. When prediction results are compared with measured data, the prediction accuracy level is comparable with that of the data driven neural network approach.

  17. Flood forecasting for the Ukrainian part of the Tisza Basin: linking with the numerical weather forecasts, comparative testing of distributed and lumped models

    NASA Astrophysics Data System (ADS)

    Belov, S.; Donchytz, G.; Kivva, S.; Kuschan, A.; Zheleznyak, M.

    2003-04-01

    The implementation of new flood forecasting systems for the Ukrainian part of the Tisza basin has started last years by the customisation of Mike-11 model for the Uzh River and Latoritsa River (part of the Bodrog Catchment) in the frame of the joint project with the 'DHI Water&Environment'. The calibration and testing of the lumped parameter model NAM was provided in collaboration with the Ukrainian Hydrometcenter and the Uzhgorod Hydrometcenter for the period 1998-2000, which includes two hazardous floods of years 1998 and 2000. The tuning of hydrodynamical module of Mike-11 is provided in collaboration with the Transcarpathian Branch of State Committee of Water Management (SCWM), Uzhgorod. The information about existing and designed hydraulic structures in the river channels, -bridges, polders, dikes, pump stations is used for the model tuning. The flood forecasting system for Uzh River and Latoritsa River based on Mike -11 is in pre-operational use in Uzhgorod Hydromet and SCUWM offices. The advance time of the flood forecasts can be increased by the real-time assimilation of the precipitation forecasts of a Numerical Weather Predictions (NWP) model. The Penn State University /UCAR NWP model MM5 was customized for the Ukrainian territory in resolution 30*30 km on the basis of the rare gridded forecasting data from the German meteorological center Offenbach, assimilating the data from the Ukrainian meteorological stations, processed by the Ukrainian Hydrometcenter. The region of the Uzh and Latoritsa watersheds was simulated by MM5 in the resolution 10*10 km for the linking with the Mike -11 (NAM). The preliminary results of flood forecasting on the basis of the meteorological forecasts are analyzed. For further improvement of the flood forecasting systems the implementations of GIS based distributed models are planned. Two types of distributed models based upon physically meaningful parameters are comparatively studied- 2-D finite- difference model RUNTOX (Kivva, Zheleznyak, 2001) based on Saint Venant equations and TOPographic Kinematic Approximation and Integration - TOPKAPI model (Todini, 1995,2000). The new computer code was developed, based on the TOPKAPI equations. Both models was initially tested for the small watersheds ( from 0.085 km2 to 0.40 km2 ) of the Boguslav Field Experimental Laboratory of the Ukrainian Hydrometeorological Institute. The comparison with the experimental data shows that TOPKAPI produces the reasonable results for the different floods without special tuning of the model parameters. The study of the applicability of TOPKAPI for the sub-watersheds of Uzh and Latoritsa rivers is going on.

  18. Technical Note: The Normal Quantile Transformation and its application in a flood forecasting system

    NASA Astrophysics Data System (ADS)

    Bogner, K.; Pappenberger, F.; Cloke, H. L.

    2011-10-01

    The Normal Quantile Transform (NQT) has been used in many hydrological and meteorological applications in order to make the Cumulated Density Function (CDF) of the observed, simulated and forecast river discharge, water level or precipitation data Gaussian. It is also the heart of the meta-Gaussian model for assessing the total predictive uncertainty of the Hydrological Uncertainty Processor (HUP) developed by Krzysztofowicz. In the field of geo-statistics this transformation is better known as Normal-Score Transform. In this paper some possible problems caused by small sample sizes for the applicability in flood forecasting systems will be discussed and illustrated by examples. For the practical implementation commands and examples from the freely available and widely used statistical computing language R (R Development Core Team, 2011) will be given (represented in Courier font) and possible solutions are suggested by combining extreme value analysis and non-parametric regression methods.

  19. Flood forecasting; An alternate response for PMF at the Saluda Dam

    SciTech Connect

    Colon, R.; Wallace, J.R.; Olson, R.W. ); Massey, K.L. )

    1989-01-01

    This paper reports on the Saluda hydroelectric project, a peaking power project located bout 11 miles upstream from Columbia, South Carolina on the Saluda River. The Saluda Dam creates Lake Murray reservoir with a drainage area of about 2,420 square miles and a surface area of approximately 48,000 acres at maximum pool elevation. Storage for this reservoir is about 1.3 million acre-feet between elevations 330 and 360 ft-NGVD. Flood forecasting at the dam is discussed in this paper.

  20. Technical Note: Initial assessment of a multi-method approach to spring-flood forecasting in Sweden

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    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 accurate 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 initialized 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 timescales are presented and evaluated. Three main approaches, represented by specific methods, are evaluated in SFV hindcasts for the Swedish river Vindelälven 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 early forecasts improvements of up to 25 % are found. This potential is reasonably well realized in a multi-method system, which over all forecast dates reduced the error in SFV by ˜ 4 %. This improvement is limited but potentially significant for e.g. energy trading.

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    Garca, Daro; Baquerizo, Asuncin; Ortega, Miguel; Herrero, Javier; ngel 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 Almera (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 Jtico creek, that are normally dry, became raging torrents. The massive flooding of occupied areas resulted in eleven deaths and two missing in Andaluca, 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 Almera 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 Almera 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.

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. Uncertainty of high-resolution forecasting of a flood event near Venice

    NASA Astrophysics Data System (ADS)

    Davolio, S.; Drofa, O.; Buzzi, A.

    2009-04-01

    Heavy precipitation due to the development of a mesoscale convective system (MCS) affected the area of the Venice Lagoon during the early morning of 26 September 2007. As a consequence of the impressive amount of rainfall (more than 300 mm in less than 12 hours), flooding was reported. The quantitative precipitation forecasts (QPF) provided by the high-resolution, convection-resolving model MOLOCH, operated daily at ISAC-CNR, allowed a suitable warning at least 36 hours in advance. However, remarkable sensitivity in terms of QPF to the specification of the initial and boundary conditions, as well as to different model configurations, was detected. Although in principle precipitation events characterized by deep convective activity are expected to have low predictability, the large scale flow in which the MCS development was embedded favoured a relatively small growth of the forecast error. Moreover, the analysis of the precipitation patterns and of other meteorological fields provided by several additional simulations allowed to identify the relevant mechanisms responsible for the flood and to capture the main characteristics of the MCS

  12. Flash Flood Risks and Warning Decisions: A Mental Models Study of Forecasters, Public Officials, and Media Broadcasters in Boulder, Colorado.

    PubMed

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

    2015-11-01

    Timely warning communication and decision making are critical for reducing harm from flash flooding. To help understand and improve extreme weather risk communication and management, this study uses a mental models research approach to investigate the flash flood warning system and its risk decision context. Data were collected in the Boulder, Colorado area from mental models interviews with forecasters, public officials, and media broadcasters, who each make important interacting decisions in the warning system, and from a group modeling session with forecasters. Analysis of the data informed development of a decision-focused model of the flash flood warning system that integrates the professionals' perspectives. Comparative analysis of individual and group data with this model characterizes how these professionals conceptualize flash flood risks and associated uncertainty; create and disseminate flash flood warning information; and perceive how warning information is (and should be) used in their own and others' decisions. The analysis indicates that warning system functioning would benefit from professionals developing a clearer, shared understanding of flash flood risks and the warning system, across their areas of expertise and job roles. Given the challenges in risk communication and decision making for complex, rapidly evolving hazards such as flash floods, another priority is development of improved warning content to help members of the public protect themselves when needed. Also important is professional communication with members of the public about allocation of responsibilities for managing flash flood risks, as well as improved system-wide management of uncertainty in decisions. PMID:25988286

  13. 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).

  14. 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.

  15. 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 + Δt*, 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Sub-Optimal Ensemble Filters and distributed hydrologic modeling: a new challenge in flood forecasting

    NASA Astrophysics Data System (ADS)

    Baroncini, F.; Castelli, F.

    2009-09-01

    Data assimilation techniques based on Ensemble Filtering are widely regarded as the best approach in solving forecast and calibration problems in geophysics models. Often the implementation of statistical optimal techniques, like the Ensemble Kalman Filter, is unfeasible because of the large amount of replicas used in each time step of the model for updating the error covariance matrix. Therefore the sub optimal approach seems to be a more suitable choice. Various sub-optimal techniques were tested in atmospheric and oceanographic models, some of them are based on the detection of a "null space". Distributed Hydrologic Models differ from the other geo-fluid-dynamics models in some fundamental aspects that make complex to understanding the relative efficiency of the different suboptimal techniques. Those aspects include threshold processes , preferential trajectories for convection and diffusion, low observability of the main state variables and high parametric uncertainty. This research study is focused on such topics and explore them through some numerical experiments on an continuous hydrologic model, MOBIDIC. This model include both water mass balance and surface energy balance, so it's able to assimilate a wide variety of datasets like traditional hydrometric "on ground" measurements or land surface temperature retrieval from satellite. The experiments that we present concern to a basin of 700 kmq in center Italy, with hourly dataset on a 8 months period that includes both drought and flood events, in this first set of experiment we worked on a low spatial resolution version of the hydrologic model (3.2 km). A new Kalman Filter based algorithm is presented : this filter try to address the main challenges of hydrological modeling uncertainty. The proposed filter use in Forecast step a COFFEE (Complementary Orthogonal Filter For Efficient Ensembles) approach with a propagation of both deterministic and stochastic ensembles to improve robustness and convergence proprieties. After, through a P.O.D. Reduction from control theory, we compute a Reduced Order Forecast Covariance matrix . In analysis step the filter uses a LE (Local Ensemble) Kalman Filter approach. We modify the LE Kalman Filter assimilation scheme and we adapt its formulation to the P.O.D. Reduced sub-space propagated in forecast step. Through this, assimilation of observations is made only in the maximum covariance directions of the model error. Then the efficiency of this technique is weighed in term of hydrometric forecast accuracy in a preliminary convergence test of a synthetic rainfall event toward a real rain fall event.

  1. 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.

  2. A Research on Development of The Multi-mode Flood Forecasting System Version Management

    NASA Astrophysics Data System (ADS)

    Shen, J.-C.; Chang, C. H.; Lien, H. C.; Wu, S. J.; Horng, M. J.

    2009-04-01

    With the global economy and technological development, the degree of urbanization and population density relative to raise. At the same time, a natural buffer space and resources year after year, the situation has been weakened, not only lead to potential environmental disasters, more and more serious, disaster caused by the economy, loss of natural environment at all levels has been expanded. In view of this, the active participation of all countries in the world cross-sectoral integration of disaster prevention technology research and development, in addition, the specialized field of disaster prevention technology, science and technology development, network integration technology, high-speed data transmission and information to support the establishment of mechanisms for disaster management The decision-making and cross-border global disaster information network building and other related technologies, has become the international anti-disaster science and technology development trends, this trend. Naturally a few years in Taiwan, people's lives and property losses caused by many problems related to natural disaster prevention and disaster prevention and the establishment of applications has become a very important. For FEWS_Taiwan, flood warning system developed by the Delft Hydraulics and introduced the Water Resources Agency (WRA), it provides those functionalities for users to modify contents to add the basins, regions, data sources, models and etc. Despite this advantage, version differences due to different users or different teams yet bring about the difficulties on synchronization and integration.At the same time in different research teams will also add different modes of meteorological and hydrological data. From the government perspective of WRA, the need to plan standard operation procedures for system integration demands that the effort for version control due to version differences must be cost down or yet canceled out. As for FEWS_Taiwan, this paper proposed the feasible avenues and solutions to smoothly integrate different configurations from different teams. In the current system has been completed by 20 of Taiwan's main rivers in the building of the basic structure of the flood forecasting. And regular updating of the relevant parameters, using the new survey results, in order to have a better flood forecasting results.

  3. 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.

  4. 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.

  5. 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 ...

  6. 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.

  7. Towards a better knowledge of flash flood forecasting at the Three Gorges Region: Progress over the past decade and challenges ahead

    NASA Astrophysics Data System (ADS)

    Li, Zhe; Yang, Dawen; Yang, Hanbo; Wu, Tianjiao; Xu, Jijun; Gao, Bing; Xu, Tao

    2015-04-01

    The study area, the Three Gorges Region (TGR), plays a critical role in predicting the floods drained into the Three Gorges Reservoir, as reported local floods often exceed 10000m3/s during rainstorm events and trigger fast as well as significant impacts on the Three Gorges Reservoir's regulation. Meanwhile, it is one of typical mountainous areas in China, which is located in the transition zone between two monsoon systems: the East Asian monsoon and the South Asian (Indian) monsoon. This climatic feature, combined with local irregular terrains, has shaped complicated rainfall-runoff regimes in this focal region. However, due to the lack of high-resolution hydrometeorological data and physically-based hydrologic modeling framework, there was little knowledge about rainfall variability and flood pattern in this historically ungauged region, which posed great uncertainties to flash flood forecasting in the past. The present study summarize latest progresses of regional flash floods monitoring and prediction, including installation of a ground-based Hydrometeorological Observation Network (TGR-HMON), application of a regional geomorphology-based hydrological model (TGR-GBHM), development of an integrated forecasting and modeling system (TGR-INFORMS), and evaluation of quantitative precipitation estimations (QPE) and quantitative precipitation forecasting (QPF) products in TGR flash flood forecasting. With these continuing efforts to improve the forecasting performance of flash floods in TGR, we have addressed several critical issues: (1) Current observation network is still insufficient to capture localized rainstorms, and weather radar provides valuable information to forecast flash floods induced by localized rainstorms, although current radar QPE products can be improved substantially in future; (2) Long-term evaluation shows that the geomorphology-based distributed hydrologic model (GBHM) is able to simulate flash flooding processes reasonably, while model performance will decline at hourly scale with larger uncertainties. However, model comparison suggests that this physically-based distributed model (GBHM), compared with a traditional lumped model (Xin'anjiang model), shows more robust performance and larger transferability for prediction in those ungauged basins in TGR; (3) Operational test of our integrated forecasting system (TRG-INFORMS) shows that it works reasonably to simulate the flood routing in Three Gorges reservoir, indicating the accuracy of simulation of total floods generated at region scale; (4) Current operational QPF is too coarse to provide valuable information even for flood forecasting of whole TGR, thus, downscaling and high-resolution QPF are necessary to unravel the potentials of weather forecasting. Finally, according to these results, we also discuss about some possible solutions with high priority for future advanced forecasting scheme of local flash floods in TGR.

  8. 75 FR 54076 - National Flood Insurance Program, Policy Wording Correction

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-03

    ... SECURITY Federal Emergency Management Agency 44 CFR Part 61 RIN 1660-AA70 National Flood Insurance Program... notice published in the Federal Register on March 24, 2005 (70 FR 15086). B. Submission of Sensitive... source: * * * III. Discussion of Rule On May 31, 2000, FEMA published an NPRM at 65 FR 34823...

  9. The potential of flood forecasting using a variable-resolution global Digital Terrain Model and flood extents from Synthetic Aperture Radar images.

    NASA Astrophysics Data System (ADS)

    Mason, David; Garcia-Pintado, Javier; Cloke, Hannah; Dance, Sarah

    2015-08-01

    A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.

  10. Forecasts, warnings and social response to flash floods: Is temporality a major problem? The case of the September 2005 flash flood in the Gard region (France)

    NASA Astrophysics Data System (ADS)

    Lutoff, C.; Anquetin, S.; Ruin, I.; Chassande, M.

    2009-09-01

    Flash floods are complex phenomena. The atmospheric and hydrological generating mechanisms of the phenomenon are not completely understood, leading to highly uncertain forecasts of and warnings for these events. On the other hand warning and crisis response to such violent and fast events is not a straightforward process. In both the social and physical aspect of the problem, space and time scales involved either in hydrometeorology, human behavior and social organizations sciences are of crucial importance. Forecasters, emergency managers, mayors, school superintendents, school transportation managers, first responders and road users, all have different time and space frameworks that they use to take emergency decision for themselves, their group or community. The integration of space and time scales of both the phenomenon and human activities is therefore a necessity to better deal with questions as forecasting lead-time and warning efficiency. The aim of this oral presentation is to focus on the spatio-temporal aspects of flash floods to improve our understanding of the event dynamic compared to the different scales of the social response. The authors propose a framework of analysis to compare the temporality of: i) the forecasts (from Méteo-France and from EFAS (Thielen et al., 2008)), ii) the meteorological and hydrological parameters, iii) the social response at different scales. The September 2005 event is particularly interesting for such analysis. The rainfall episode lasted nearly a week with two distinct phases separated by low intensity precipitations. Therefore the Méteo-France vigilance bulletin where somehow disconnected from the local flood’s impacts. Our analysis focuses on the timings of different types of local response, including the delicate issue of school transportation, in regard to the forecasts and the actual dynamic of the event.

  11. 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.

  12. 75 FR 69096 - Public Meetings of National Flood Insurance Program (NFIP) Reform Effort

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-10

    ... SECURITY Federal Emergency Management Agency Public Meetings of National Flood Insurance Program (NFIP) 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)...

  13. 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.

  14. Forecasting Austrian national elections: The Grand Coalition model

    PubMed Central

    Aichholzer, Julian; Willmann, Johanna

    2014-01-01

    Forecasting the outcomes of national elections has become established practice in several democracies. In the present paper, we develop an economic voting model for forecasting the future success of the Austrian ‘grand coalition’, i.e., the joint electoral success of the two mainstream parties SPOE and OEVP, at the 2013 Austrian Parliamentary Elections. Our main argument is that the success of both parties is strongly tied to the accomplishments of the Austrian system of corporatism, that is, the Social Partnership (Sozialpartnerschaft), in providing economic prosperity. Using data from Austrian national elections between 1953 and 2008 (n=18), we rely on the following predictors in our forecasting model: (1) unemployment rates, (2) previous incumbency of the two parties, and (3) dealignment over time. We conclude that, in general, the two mainstream parties benefit considerably from low unemployment rates, and are weakened whenever they have previously formed a coalition government. Further, we show that they have gradually been losing a good share of their voter basis over recent decades. PMID:26339109

  15. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 44 Emergency Management and Assistance 1 2012-10-01 2011-10-01 true National Flood Insurance..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND ADJUSTMENT OF CLAIMS Pt. 62, App. B Appendix B to Part 62—National Flood Insurance Program...

  16. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 44 Emergency Management and Assistance 1 2013-10-01 2013-10-01 false National Flood Insurance..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND ADJUSTMENT OF CLAIMS Pt. 62, App. B Appendix B to Part 62—National Flood Insurance Program...

  17. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 44 Emergency Management and Assistance 1 2011-10-01 2011-10-01 false National Flood Insurance..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND ADJUSTMENT OF CLAIMS Pt. 62, App. B Appendix B to Part 62—National Flood Insurance Program...

  18. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 44 Emergency Management and Assistance 1 2014-10-01 2014-10-01 false National Flood Insurance..., DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND ADJUSTMENT OF CLAIMS Pt. 62, App. B Appendix B to Part 62—National Flood Insurance Program...

  19. Uncertainty propagation for flood forecasting in the Alps: different views and impacts from MAP D-PHASE

    NASA Astrophysics Data System (ADS)

    Rotach, M. W.; Arpagaus, M.; Dorninger, M.; Hegg, C.; Montani, A.; Ranzi, R.

    2012-08-01

    D-PHASE was a Forecast Demonstration Project of the World Weather Research Programme (WWRP) related to the Mesoscale Alpine Programme (MAP). Its goal was to demonstrate the reliability and quality of operational forecasting of orographically influenced (determined) precipitation in the Alps and its consequences on the distribution of run-off characteristics. A special focus was, of course, on heavy-precipitation events. The D-PHASE Operations Period (DOP) ran from June to November~2007, during which an end-to-end forecasting system was operated covering many individual catchments in the Alps, with their water authorities, civil protection organizations or other end users. The forecasting system's core piece was a Visualization Platform where precipitation and flood warnings from some 30 atmospheric and 7 hydrological models (both deterministic and probabilistic) and corresponding model fields were displayed in uniform and comparable formats. Also, meteograms, nowcasting information and end user communication was made available to all the forecasters, users and end users. D-PHASE information was assessed and used by some 50 different groups ranging from atmospheric forecasters to civil protection authorities or water management bodies. In the present contribution, D-PHASE is briefly presented along with its outstanding scientific results and, in particular, the lessons learnt with respect to uncertainty propagation. A focus is thereby on the transfer of ensemble prediction information into the hydrological community and its use with respect to other aspects of societal impact. Objective verification of forecast quality is contrasted to subjective quality assessments during the project (end user workshops, questionnaires) and some general conclusions concerning forecast demonstration projects are drawn.

  20. Comparison between genetic programming and an ensemble Kalman filter as data assimilation techniques for probabilistic flood forecasting

    NASA Astrophysics Data System (ADS)

    Mediero, L.; Garrote, L.; Requena, A.; Chávez, A.

    2012-04-01

    Flood events are among the natural disasters that cause most economic and social damages in Europe. Information and Communication Technology (ICT) developments in last years have enabled hydrometeorological observations available in real-time. High performance computing promises the improvement of real-time flood forecasting systems and makes the use of post processing techniques easier. This is the case of data assimilation techniques, which are used to develop an adaptive forecast model. In this paper, a real-time framework for probabilistic flood forecasting is presented and two data assimilation techniques are compared. The first data assimilation technique uses genetic programming to adapt the model to the observations as new information is available, updating the estimation of the probability distribution of the model parameters. The second data assimilation technique uses an ensemble Kalman filter to quantify errors in both hydrologic model and observations, updating estimates of system states. Both forecast models take the result of the hydrologic model calibration as a starting point and adapts the individuals of this first population to the new observations in each operation time step. Data assimilation techniques have great potential when are used in hydrological distributed models. The distributed RIBS (Real-time Interactive Basin Simulator) rainfall-runoff model was selected to simulate the hydrological process in the basin. The RIBS model is deterministic, but it is run in a probabilistic way through Monte Carlo simulations over the probability distribution functions that best characterise the most relevant model parameters, which were identified by a probabilistic multi-objective calibration developed in a previous work. The Manzanares River basin was selected as a case study. Data assimilation processes are computationally intensive. Therefore, they are well suited to test the applicability of the potential of the Grid technology to hydrometeorological research.

  1. 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.

  2. 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 ...

  3. Improvement of rainfall and flood forecasts by blending ensemble NWP rainfall with radar prediction considering orographic rainfall

    NASA Astrophysics Data System (ADS)

    Yu, Wansik; Nakakita, Eiichi; Kim, Sunmin; Yamaguchi, Kosei

    2015-12-01

    Many basins in Japan are characterized by steep mountainous regions, generating orographic rainfall events. Orographic rainfall may cause localized heavy rainfall to induce flash floods and sediment disasters. However, the accuracy of radar-based rainfall prediction was not enough because of the complex geographical pattern of the mountainous areas. In order to reduce damage due to localized heavy rainfall, characteristics of orographic rainfall must be identified into a short-term rainfall prediction procedure. The accuracy of radar-based rainfall prediction performs best for very short lead time, however the accuracy of radar prediction rapidly decreases with increasing lead times. At longer lead times, higher accuracy QPFs are produced by Numerical Weather Prediction (NWP) models, which solve the dynamics and physics of the atmosphere. This study proposes hybrid blending system of ensemble information from radar-based prediction and numerical weather prediction (NWP) to improve the accuracy of rainfall and flood forecasting. First, an improved radar image extrapolation method, which is comprised of the orographic rainfall identification and the error ensemble scheme, is introduced. Then, ensemble NWP outputs are updated based on mean bias of the error fields considering error structure. Finally, the improved radar-based prediction and updated NWP rainfall considering bias correction are blended dynamically with changing weight functions, which are computed from the expected skill of each radar prediction and updated NWP rainfall. The proposed method is verified temporally and spatially through a target event and is applied to the hybrid flood forecasting for updating with 1 h intervals. The newly proposed method shows sufficient reproducibility in peak discharge value, and could reduce the width of ensemble spread, which is expressed as the uncertainty, in the flood forecasting. Our study is carried out and verified using the largest flood event by typhoon 'Talas' of 2011 over the two catchments, which are Futatsuno (356.1 km2) and Nanairo (182.1 km2) dam catchments of Shingu river basin (2360 km2), which is located in the Kii peninsula, Japan.

  4. 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.

  5. All-season flash flood forecasting system for real-time operations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Flash floods can cause extensive damage to both life and property, especially because they are difficult to predict. Flash flood prediction requires high-resolution meteorologic observations and predictions, as well as calibrated hydrologic models in addition to extensive data handling. We have de...

  6. Hydrologic Ensemble Forecast Service for Operational Short-to-Long Range Hydrometeorological and Hydrologic Ensembles in the U.S. National Weather Service

    NASA Astrophysics Data System (ADS)

    Demargne, Julie; Brown, James; Wu, Limin; Regonda, Satish; He, Minxue; Fresch, Mark

    2013-04-01

    In order to quantify the main sources of uncertainty in hydrologic forecasts for a wide range of practical applications (e.g. flood risk management, water supply management, streamflow regulation, and recreation planning), the NOAA's National Weather Service (NWS) is implementing a short- to long-range Hydrologic Ensemble Forecast Service (HEFS). The HEFS extends the existing hydrologic ensemble services to include short-range forecasts and incorporate additional weather and climate information. It provides, at forecast horizons ranging from 6-hr to about a year, hydrometeorological and hydrologic ensemble forecasts that are reasonably unbiased and skillful over a wide range of spatio-temporal scales. Based on separate modeling of the input and hydrologic uncertainties, the HEFS includes: 1) the Meteorological Ensemble Forecast Processor (MEFP), which ingests weather and climate forecasts from multiple numerical weather prediction models to produce bias-corrected forcing ensembles at the hydrologic basin scales; 2) the hydrologic Ensemble Post-processor (EnsPost), which models the collective hydrologic uncertainty and corrects for systematic biases in streamflow; 3) the Ensemble Verification Service, which verifies the forcing and streamflow ensembles to help identify the main sources of skill and error in the forecasts and provides forecast quality information for forecasters and users; and 4) the Graphics Generator, which enables forecasters to create configurable plots for analysis and delivery to the public. The implementation started in 2011 and now five NWS River Forecast Centers are testing the HEFS in real-time over a large number of basins. The New York City Department of Environmental Protection is currently transitioning its water supply system for New York City to make use of the HEFS ensembles for more efficient and effective water management. This presentation describes recent verification results from multi-year hindcasting based on precipitation and temperature forecasts from the NWS Global Forecast System and Global Ensemble Forecast System for a 14-day forecast horizon. Various verification metrics (e.g., Relative Mean Error, Continuous Rank Probability Skill Score) show the relative contribution of the MEFP (along with the raw forcing forecasts) and the EnsPost to the quality of the streamflow ensembles.

  7. 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.

  8. 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.

  9. 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,...

  10. Flood warning level forecasting for ungauged catchments by means of a combined API storage concept

    NASA Astrophysics Data System (ADS)

    Lehmann, T.; Holzmann, H.

    2008-11-01

    The knowledge of the expected dimension of the flood peak is of major importance for security and warning services to take preventive measures. In this paper the authors want to introduce the concept of the Antecedent Precipitation Index (API) as a possible variable to estimate runoff warning classes. The aim was (a) to define API warning classes which correspond to runoff warning classes at a certain runoff gauge and (b) apply the method to ungauged basins. To consider time and state dependant rainfall losses a spatially distributed linear storage concept was applied to intercept the actual rainfall. The 3-parameter API function was fitted to several flood events at observed gauges within the district of lower Austria and lead to a set of optimized parameters. Through extreme value statistics the 1, 5 and 30 years API extremes were derived and set into correlation to the corresponding flood events. These API extremes together with the optimized API parameters were spatially interpolated and thus transferred to ungauged basins. The calculated flood events had the tendency to underestimate the smaller flood frequencies whereas the extreme flood classes could be reliably performed.

  11. 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

  12. The Hurricane-Flood-Landslide Continuum: An Integrated, End-to-end Forecast and Warning System for Mountainous Islands in the Tropics

    NASA Astrophysics Data System (ADS)

    Golden, J.; Updike, R. G.; Verdin, J. P.; Larsen, M. C.; Negri, A. J.; McGinley, J. A.

    2004-12-01

    In the 10 days of 21-30 September 1998, Hurricane Georges left a trail of destruction in the Caribbean region and U.S. Gulf Coast. Subsequently, in the same year, Hurricane Mitch caused widespread destruction and loss of life in four Central American nations, and in December,1999 a tropical disturbance impacted the north coast of Venezuela causing hundreds of deaths and several million dollars of property loss. More recently, an off-season disturbance in the Central Caribbean dumped nearly 250 mm rainfall over Hispaniola during the 24-hr period on May 23, 2004. Resultant flash floods and debris flows in the Dominican Republic and Haiti killed at least 1400 people. In each instance, the tropical system served as the catalyst for major flooding and landslides at landfall. Our goal is to develop and transfer an end-to-end warning system for a prototype region in the Central Caribbean, specifically the islands of Puerto Rico and Hispaniola, which experience frequent tropical cyclones and other disturbances. The envisioned system would include satellite and surface-based observations to track and nowcast dangerous levels of precipitation, atmospheric and hydrological models to predict short-term runoff and streamflow changes, geological models to warn when and where landslides and debris flows are imminent, and the capability to communicate forecast guidance products via satellite to vital government offices in Puerto Rico, Haiti, and the Dominican Republic. In this paper, we shall present a preliminary proof-of-concept study for the May 21-24, 2004 floods and debris-flows over Hispaniola to show that the envisaged flow of data, models and graphical products can produce the desired warning outputs. The multidisciplinary research and technology transfer effort will require blending the talents of hydrometeorologists, geologists, remote sensing and GIS experts, and social scientists to ensure timely delivery of tailored graphical products to both weather offices and local emergency managers.

  13. 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.

  14. Uncertainty analysis of neural network based flood forecasting models: An ensemble based approach for constructing prediction interval

    NASA Astrophysics Data System (ADS)

    Kasiviswanathan, K.; Sudheer, K.

    2013-05-01

    Artificial neural network (ANN) based hydrologic models have gained lot of attention among water resources engineers and scientists, owing to their potential for accurate prediction of flood flows as compared to conceptual or physics based hydrologic models. The ANN approximates the non-linear functional relationship between the complex hydrologic variables in arriving at the river flow forecast values. Despite a large number of applications, there is still some criticism that ANN's point prediction lacks in reliability since the uncertainty of predictions are not quantified, and it limits its use in practical applications. A major concern in application of traditional uncertainty analysis techniques on neural network framework is its parallel computing architecture with large degrees of freedom, which makes the uncertainty assessment a challenging task. Very limited studies have considered assessment of predictive uncertainty of ANN based hydrologic models. In this study, a novel method is proposed that help construct the prediction interval of ANN flood forecasting model during calibration itself. The method is designed to have two stages of optimization during calibration: at stage 1, the ANN model is trained with genetic algorithm (GA) to obtain optimal set of weights and biases vector, and during stage 2, the optimal variability of ANN parameters (obtained in stage 1) is identified so as to create an ensemble of predictions. During the 2nd stage, the optimization is performed with multiple objectives, (i) minimum residual variance for the ensemble mean, (ii) maximum measured data points to fall within the estimated prediction interval and (iii) minimum width of prediction interval. The method is illustrated using a real world case study of an Indian basin. The method was able to produce an ensemble that has an average prediction interval width of 23.03 m3/s, with 97.17% of the total validation data points (measured) lying within the interval. The derived prediction interval for a selected hydrograph in the validation data set is presented in Fig 1. It is noted that most of the observed flows lie within the constructed prediction interval, and therefore provides information about the uncertainty of the prediction. One specific advantage of the method is that when ensemble mean value is considered as a forecast, the peak flows are predicted with improved accuracy by this method compared to traditional single point forecasted ANNs. Fig. 1 Prediction Interval for selected hydrograph

  15. 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...

  16. 44 CFR Appendix B to Part 62 - National Flood Insurance Program

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false National Flood Insurance Program B Appendix B to Part 62 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND ADJUSTMENT OF CLAIMS Pt....

  17. 78 FR 45936 - Agency Information Collection Activities: Proposed Collection; Comment Request; National Flood...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-30

    ...; Comment Request; National Flood Insurance Program Claim Forms AGENCY: Federal Emergency Management Agency... (1973). The National Flood Insurance Act of 1968 requires that the Federal Emergency Management Agency... decisions of any insurance agent, adjuster, insurance company, or any Federal Emergency Management...

  18. 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.

  19. Improvement of watershed flood forecasting by typhoon rainfall climate model with an ANN-based southwest monsoon rainfall enhancement

    NASA Astrophysics Data System (ADS)

    Pan, Tsung-Yi; Yang, Yi-Ting; Kuo, Hung-Chi; Tan, Yih-Chi; Lai, Jihn-Sung; Chang, Tsang-Jung; Lee, Cheng-Shang; Hsu, Kathryn Hua

    2013-12-01

    This paper improves the typhoon flood forecasting over a watershed in a mountainous island of Taiwan. In the presence of the stiff topography in Taiwan, the typhoon rainfall is often phased-locked with terrain and the typhoon rainfall in general is best predicted by the typhoon rainfall climate model (TRCM) (Lee et al., 2006). However, the TRCM often underestimates the rainfall amount in cases of slowing moving storms with strong southwest monsoon supply of water vapor flux. We apply an artificial neural network (ANN) based southwest monsoon rainfall enhancement (AME) to improve TRCM rainfall forecasting for the Tsengwen Reservoir watershed in the southwestern Taiwan where maximum typhoon rainfall frequently occurred. Six typhoon cases with significant southwest monsoon water vapor flux are used for the test cases. The precipitations of seven rain gauge stations in the watershed and the southwest monsoon water vapor flux are analyzed to get the spatial distribution of the effective water vapor flux threshold, and the threshold is further used to build the AME model. The results indicate that the flux threshold is related to the topographic lifting of the moist air, with lower threshold in the upstream high altitude stations in the watershed. The lower flux threshold allows a larger rainfall amount with AME. We also incorporated the rainfall prediction with a state space neural network (SSNN) to simulate rainfall-runoff processes. Our improved method is robust and produces better flood predictions of total rainfall and multiple rainfall peaks. The runoff processes in the watershed are improved in terms of coefficient of efficiency, peak discharge, and total volume.

  20. Flooding

    MedlinePlus

    ... health problems. The key to mold control is moisture control. After the flood, remove standing water and ... based paint hazards Asbestos: Anyone working on demolition, removal, and cleanup of building debris needs be aware ...

  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. 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.

  3. 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).

  4. The impact of satellite temperature soundings on the forecasts of a small national meteorological service

    NASA Technical Reports Server (NTRS)

    Wolfson, N.; Thomasell, A.; Alperson, Z.; Brodrick, H.; Chang, J. T.; Gruber, A.; Ohring, G.

    1984-01-01

    The impact of introducing satellite temperature sounding data on a numerical weather prediction model of a national weather service is evaluated. A dry five level, primitive equation model which covers most of the Northern Hemisphere, is used for these experiments. Series of parallel forecast runs out to 48 hours are made with three different sets of initial conditions: (1) NOSAT runs, only conventional surface and upper air observations are used; (2) SAT runs, satellite soundings are added to the conventional data over oceanic regions and North Africa; and (3) ALLSAT runs, the conventional upper air observations are replaced by satellite soundings over the entire model domain. The impact on the forecasts is evaluated by three verification methods: the RMS errors in sea level pressure forecasts, systematic errors in sea level pressure forecasts, and errors in subjective forecasts of significant weather elements for a selected portion of the model domain. For the relatively short range of the present forecasts, the major beneficial impacts on the sea level pressure forecasts are found precisely in those areas where the satellite sounding are inserted and where conventional upper air observations are sparse. The RMS and systematic errors are reduced in these regions. The subjective forecasts of significant weather elements are improved with the use of the satellite data. It is found that the ALLSAT forecasts are of a quality comparable to the SAR forecasts.

  5. 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.

  6. 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.

  7. The elasticity of hydrological forecast skill with respect to initial conditions and meteorological forcing for two major flood events in Germany

    NASA Astrophysics Data System (ADS)

    Thober, Stephan; Wood, Andy; Samaniego, Luis; Clark, Martyn; Kumar, Rohini; Zink, Matthias

    2014-05-01

    Major flood events are causing severe socio-economic damages. In Germany alone, the havoc wreaked by the 2002 and 2013 floods along the Elbe and Danube river amounted to more than 11 bn EUR. Highly skilled hydrological forecasts can help to mitigate such damages. Among several factors, these hydrological forecasts are strongly dependent on the initial conditions of the land surface at the beginning of the forecast period and the forecast skill of the meteorological forcing. Prior research has investigated how uncertainties of the initial conditions and meteorological forcing impact hydrological forecasts. In these studies, uncertainty is investigated by coupling an ensemble of basin initial conditions (e.g., snow, soil moisture) with an ensemble of meteorological forecasts (e.g., precipitation). However, most previous hydrological predictability studies focus on seasonal forecasts (e.g., forecasts of June-July-August flow volume, initialized on April 1st), and neglect the errors in meteorological forecasts at lead times from 1-14 days. In this study, an error growth model is proposed to investigate hydrological predictability at lead times of 1-14 days. This error growth model calculates a time-dependent weighted average between the perfect forecast and a stochastic perturbation of this. The time-dependent weights are derived from a logistic function. This error growth model thus attributes high weights to the perfect forecast for short lead times (e.g., less than five days) and low weights for longer lead times (e.g., more than five days). For longer lead times, more weight is given to the stochastic perturbation of the forecast and, hence, the ensemble spread is larger for these lead times resembling a higher uncertainty. Analogous to the error growth model, the initial conditions are calculated as a weighted average between the perfect condition and a historic condition of the land surface. The proposed framework is tested in Germany for the 2002 and 2013 flood events along the Elbe and Danube river. The mesoscale Hydrologic Model - mHM is used to evaluate the impact of varying initial conditions and meteorological forcing. The original meteorological data used to generate ensemble forcing is provided by the German Weather Service (DWD). Common metrics such as mean absolute error (MAE) and continuous ranked probability skill scores (CRPSS) are employed to evaluate the forecast skill. Moreover, the elasticity is quantified which is defined as the change in runoff skill per unit change either in forcing or initial condition skill. The analysis helps to understand the relative importance of basin initial conditions and meteorological forecasts for extreme floods in Germany. Results indicate that initial land surface conditions have great impact in hydrological forecast skill for short lead times (e.g., 16.9% chance of reaching actual peak discharge with historic land surface condition). For longer lead times, however, the hydrological forecast skill becomes more dependent on the forecast skill in the meteorological forcing.

  8. 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.

  9. 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.

  10. 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.

  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. Numerical Study of the Port of Miami (Importance of Dodge Island) in Storm Surge and Flooding Forecasting in North Biscayne Bay

    NASA Astrophysics Data System (ADS)

    Liu, H.; Zhang, K.; Li, Y.

    2011-12-01

    The importance of Port of Miami (Dodge Island) in storm surge and flooding forecasting in North Biscayne Bay was investigated by using the numerical model Coastal and Estuarine Storm Tide (CEST). Firstly, CEST was applied to Hurricane Andrew of 1992 in the Biscayne Bay basin and validated by in situ measurements, which indicated the model results had good agreement with measured data. Secondly, two sets of experiments using Hurricane Miami of 1926 were conducted to study the role of Dodge Island in storm surge and flooding forecasting in North Biscayne Bay: one set of experiments were run in today's Biscayne Bay basin and another set of experiments were run in Biscayne Bay basin of 1926 in which Dodge Island was not created yet. Results indicated that storm surge and flooding areas were reduced a little bit in Miami River areas when Dodge Island was not there. Meanwhile, storm surge and flooding areas in North Miami and Miami Beach regions were largely increased. Results further indicated that as long as the hurricane made landfall in south of Dodge Island, it can provide a good protection for Miami Beach area to reduce storm surge and flooding impacts.

  13. 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.

  14. Assimilation of brightness temperature observations into a process-based hydrological model for flood forecasting applications

    NASA Astrophysics Data System (ADS)

    Weerts, A.; Reggiani, P.; Kwadijk, J.; de Jeu, R.

    2006-12-01

    The aim of this project, sponsored by the Dutch agency for aerospace programmes, is to demonstrate that assimilation of soil moisture data obtained from AMSR-E remotely sensed brightness temperature measurements leads to a reduction of the uncertainty in the stream flow predictions. The method is applied to the 60000 km2 Mosel sub-basin of the river Rhine. Data streams are provided from ground-based telemetric observation networks and from AMSR-E remotely sensed brightness temperature measurements. The satellite soil moisture observations are assimilated into the physcially based representative elementary watershed (REW) model of the Mosel by means of an Ensemble Kalman Filter (EnKF) over a historical simulation time window. The model is then driven in forecast mode with deterministic medium-range weather prediction products. The aim is to demonstrate that the predictive uncertainty on streamflow forecasts due to model deficiencies and errors in the observations can be effectively limited through exploitation of additional information about the system. Remotely sensed brightness temperature observations will be compared with the results of a process-based hydrological modeling platform in which spatial distribution of surface soil moisture and its effect on hydrological response signals can be adequately taken into consideration.

  15. Performance of an Advanced MOS System in the 1996-97 National Collegiate Weather Forecasting Contest.

    NASA Astrophysics Data System (ADS)

    Vislocky, Robert L.; Fritsch, J. Michael

    1997-12-01

    A prototype advanced model output statistics (MOS) forecast system that was entered in the 1996-97 National Collegiate Weather Forecast Contest is described and its performance compared to that of widely available objective guidance and to contest participants. The prototype system uses an optimal blend of aviation (AVN) and nested grid model (NGM) MOS forecasts, explicit output from the NGM and Eta guidance, and the latest surface weather observations from the forecast site. The forecasts are totally objective and can be generated quickly on a personal computer. Other "objective" forms of guidance tracked in the contest are 1) the consensus forecast (i.e., the average of the forecasts from all of the human participants), 2) the combination of NGM raw output (for precipitation forecasts) and NGM MOS guidance (for temperature forecasts), and 3) the combination of Eta Model raw output (for precipitation forecasts) and AVN MOS guidance (for temperature forecasts).Results show that the advanced MOS system finished in 20th place out of 737 original entrants, or better than approximately 97% of the human forecasters who entered the contest. Moreover, the advanced MOS system was slightly better than consensus (23d place). The fact that an objective forecast system finished ahead of consensus is a significant accomplishment since consensus is traditionally a very formidable "opponent" in forecast competitions. Equally significant is that the advanced MOS system was superior to the traditional guidance products available from the National Centers for Environmental Prediction (NCEP). Specifically, the combination of NGM raw output and NGM MOS guidance finished in 175th place, and the combination of Eta Model raw output and AVN MOS guidance finished in 266th place. The latter result is most intriguing since the proposed elimination of all NGM products would likely result in a serious degradation of objective products disseminated by NCEP, unless they are replaced with equal or better substitutes. On the other hand, the positive performance of the prototype advanced MOS system shows that it is possible to create a single objective product that is not only superior to currently available objective guidance products, but is also on par with some of the better human forecasters.

  16. Mortality from flash floods: a review of national weather service reports, 1969-81.

    PubMed Central

    French, J; Ing, R; Von Allmen, S; Wood, R

    1983-01-01

    Of all weather-related disasters that occur in the United States, floods are the main cause of death, and most flood-related deaths are attributed to flash floods. Whenever a weather-related disaster involves 30 or more deaths or more than $100 million in property damage, the National Weather Service (NWS) forms a survey team to investigate the disaster and write a report of findings. All NWS survey reports on flash floods issued during 1969-81 were reviewed to determine the mortality resulting from such floods, the effect of warnings on mortality, and the circumstances contributing to death. A total of 1,185 deaths were associated with 32 flash floods, an average of 37 deaths per flash flood. The highest average number of deaths per event was associated with the four flash floods in which dams broke after heavy rains. Although there were 18 flash floods in 1977-81 and only 14 in 1969-76, the number of deaths was 2 1/2 times greater during the earlier period. More than twice as many deaths were associated with flash floods for which the survey team considered the warnings inadequate than with those with warnings considered adequate. Ninety-three percent of the deaths were due to drowning and 42 percent of these drownings were car related. The other drownings occurred in homes, at campsites, or when persons were crossing bridges and streams. The need for monitoring dams during periods of heavy rainfall is highlighted. PMID:6419273

  17. Policy tenure under the U.S. National Flood Insurance Program (NFIP).

    PubMed

    Michel-Kerjan, Erwann; Lemoyne de Forges, Sabine; Kunreuther, Howard

    2012-04-01

    In the United States, insurance against flood hazard (inland flooding or storm surge from hurricanes) has been provided mainly through the National Flood Insurance Program (NFIP) since 1968. The NFIP covers $1.23 trillion of assets today. This article provides the first analysis of flood insurance tenure ever undertaken: that is, the number of years that people keep their flood insurance policy before letting it lapse. Our analysis of the entire portfolio of the NFIP over the period 2001-2009 reveals that the median tenure of new policies during that time is between two and four years; it is also relatively stable over time and levels of flood hazard. Prior flood experience can affect tenure: people who have experienced small flood claims tend to hold onto their insurance longer; people who have experienced large flood claims tend to let their insurance lapse sooner. To overcome the policy and governance challenges posed by homeowners' inadequate insurance coverage, we discuss policy recommendations that include for banks and government-sponsored enterprises (GSEs) strengthening their requirements and the introduction of multiyear flood insurance contracts attached to the property, both of which are likely to provide more coverage stability and encourage investments in risk-reduction measures. PMID:21919928

  18. Using ensemble NWP wind power forecasts to improve national power system management

    NASA Astrophysics Data System (ADS)

    Cannon, D.; Brayshaw, D.; Methven, J.; Coker, P.; Lenaghan, D.

    2014-12-01

    National power systems are becoming increasingly sensitive to atmospheric variability as generation from wind (and other renewables) increases. As such, the days-ahead predictability of wind power has significant implications for power system management. At this time horizon, power system operators plan transmission line outages for maintenance. In addition, forecast users begin to form backup strategies to account for the uncertainty in wind power predictions. Under-estimating this uncertainty could result in a failure to meet system security standards, or in the worst instance, a shortfall in total electricity supply. On the other hand, overly conservative assumptions about the forecast uncertainty incur costs associated with the unnecessary holding of reserve power. Using the power system of Great Britain (GB) as an example, we construct time series of GB-total wind power output using wind speeds from either reanalyses or global weather forecasts. To validate the accuracy of these data sets, wind power reconstructions using reanalyses and forecast analyses over a recent period are compared to measured GB-total power output. The results are found to be highly correlated on time scales greater than around 6 hours. Results are presented using ensemble wind power forecasts from several national and international forecast centres (obtained through TIGGE). Firstly, the skill with which global ensemble forecasts can represent the uncertainty in the GB-total power output at up to 10 days ahead is quantified. Following this, novel ensemble forecast metrics are developed to improve estimates of forecast uncertainty within the context of power system operations, thus enabling the development of more cost effective strategies. Finally, the predictability of extreme events such as prolonged low wind periods or rapid changes in wind power output are examined in detail. These events, if poorly forecast, induce high stress scenarios that could threaten the security of the power system.

  19. 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.

  20. A statistical forecast model for Tropical Cyclone Rainfall and flood events for the Hudson River

    NASA Astrophysics Data System (ADS)

    Cioffi, Francesco; Conticello, Federico; Hall, Thimoty; Lall, Upmanu; Orton, Philip

    2014-05-01

    Tropical Cyclones (TCs) lead to potentially severe coastal flooding through wind surge and also through rainfall-runoff processes. There is growing interest in modeling these processes simultaneously. Here, a statistical approach that can facilitate this process is presented with an application to the Hudson River Basin that is associated with the New York City metropolitan area. Three submodels are used in sequence. The first submodel is a stochastic model of the complete life cycle of North Atlantic (NA) tropical cyclones developed by Hall and Yonekura (2011). It uses archived data of TCs throughout the North Atlantic to estimate landfall rates at high geographic resolution as a function of the ENSO state and of sea surface temperature (SST). The second submodel translates the attributes of a tropical cyclone simulated by the first model to rainfall intensity at selected stations within the watershed of Hudson River. Two different approaches are used and compared: artificial neural network (ANN) and k-nearest neighbor (KNN). Finally, the third submodel transforms, once again, by using an ANN approach and KNN, the rainfall intensities, calculated for the ensemble of the stations, to the streamflows at specific points of the tributaries of the Hudson River. These streamflows are to be used as inputs in a hydrodynamic model that includes storm surge surge dynamics for the simulation of coastal flooding along the Hudson River. Calibration and validation of the model is carried out by using, selected tropical cyclone data since 1950, and hourly station rainfall and streamflow recorded for such extreme events. Four stream gauges (Troy dam, Mohawk River at Cohoes, Mohawk River diversion at Crescent Dam, Hudson River above lock one nr Waterford), a gauge from a tributary in the lower Hudson River, and over 20 rain gauges are used. The performance of the proposed model as tool for storm events is then analyzed and discussed.

  1. 76 FR 45281 - National Flood Insurance Program (NFIP); Assistance to Private Sector Property Insurers...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-28

    ... private insurance companies (Companies) and to make available to the Companies the terms for subscription... private insurance companies participating under the current FY2011 Arrangement. Any private insurance... SECURITY Federal Emergency Management Agency National Flood Insurance Program (NFIP); Assistance to...

  2. 77 FR 50706 - National Flood Insurance Program Programmatic Environmental Impact Statement

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-22

    ... SECURITY Federal Emergency Management Agency National Flood Insurance Program Programmatic Environmental Impact Statement AGENCY: Federal Emergency Management Agency, DHS. ACTION: Notice. SUMMARY: The Federal... 77 FR 28891, and requested public comments no later than July 16, 2012. Due to the...

  3. 76 FR 64361 - Agency Information Collection Activities: Proposed Collection; Comment Request; National Flood...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-18

    ... SECURITY Federal Emergency Management Agency Agency Information Collection Activities: Proposed Collection; Comment Request; National Flood Insurance Program Claims Appeals Process AGENCY: Federal Emergency Management Agency, DHS. ACTION: Notice. SUMMARY: The Federal Emergency Management Agency, as part of...

  4. 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.

  5. Sensitivity of quantitative precipitation forecasts to boundary layer parameterization: a flash flood case study in the Western Mediterranean

    NASA Astrophysics Data System (ADS)

    Zampieri, M.; Malguzzi, P.; Buzzi, A.

    2005-08-01

    The "Montserrat-2000" severe flash flood event which occurred over Catalonia on 9 and 10 June 2000 is analyzed. Strong precipitation was generated by a mesoscale convective system associated with the development of a cyclone. The location of heavy precipitation depends on the position of the cyclone, which, in turn, is found to be very sensitive to various model characteristics and initial conditions. Numerical simulations of this case study using the hydrostatic BOLAM and the non-hydrostatic MOLOCH models are performed in order to test the effects of different formulations of the boundary layer parameterization: a modified version of the Louis (order 1) model and a custom version of the E-ℓ (order 1.5) model. Both of them require a diagnostic formulation of the mixing length, but the use of the turbulent kinetic energy equation in the E-ℓ model allows to represent turbulence history and non-locality effects and to formulate a more physically based mixing length. The impact of the two schemes is different in the two models. The hydrostatic model, run at 1/5 degree resolution, is less sensitive, but the quantitative precipitation forecast is in any case unsatisfactory in terms of localization and amount. Conversely, the non-hydrostatic model, run at 1/50 degree resolution, is capable of realistically simulate timing, position and amount of precipitation, with the apparently superior results obtained with the E-ℓ parameterization model.

  6. Improvement of hydrological flood forecasting through an event based output correction method

    NASA Astrophysics Data System (ADS)

    Klotz, Daniel; Nachtnebel, Hans Peter

    2014-05-01

    This contribution presents an output correction method for hydrological models. A conceptualisation of the method is presented and tested in an alpine basin in Salzburg, Austria. The aim is to develop a method which is not prone to the drawbacks of autoregressive models. Output correction methods are an attractive option for improving hydrological predictions. They are complementary to the main modelling process and do not interfere with the modelling process itself. In general, output correction models estimate the future error of a prediction and use the estimation to improve the given prediction. Different estimation techniques are available dependent on the utilized information and the estimation procedure itself. Autoregressive error models are widely used for such corrections. Autoregressive models with exogenous inputs (ARX) allow the use of additional information for the error modelling, e.g. measurements from upper basins or predicted input-signals. Autoregressive models do however exhibit deficiencies, since the errors of hydrological models do generally not behave in an autoregressive manner. The decay of the error is usually different from an autoregressive function and furthermore the residuals exhibit different patterns under different circumstances. As for an example, one might consider different error-propagation behaviours under high- and low-flow situations or snow melt driven conditions. This contribution presents a conceptualisation of an event-based correction model and focuses on flood events only. The correction model uses information about the history of the residuals and exogenous variables to give an error-estimation. The structure and parameters of the correction models can be adapted to given event classes. An event-class is a set of flood events that exhibit a similar pattern for the residuals or the hydrological conditions. In total, four different event-classes have been identified in this study. Each of them represents a different hydrological state, which is associated with different error sources and behaviours. Within each event-class, a set of ARX models are applied to simulate the behaviour of the error. This approach makes the correction model highly adaptable and allows for the representation of different behavioural patterns of the error. The procedure is tested and compared with an auto regressive model of first order. It is shown that the event-based correction method can improve the prediction significantly, given that an event is classified correctly.

  7. Forecasting Flooding in the Brahmaputra and Ganges Delta of Bangladesh on Short (1-10 days), Medium (20-30 days) and Seasonal Time Scales (1-6 months)

    NASA Astrophysics Data System (ADS)

    Webster, P. J.; Hoyos, C. D.; Hopson, T. M.; Chang, H.; Jian, J.

    2007-12-01

    Following the devastating flood years of 1998 during which 60% of Bangladesh was under water for a period of 3 months, the Climate Forecast Applications in Bangladesh (CFAB) project was formed with funding by USAID and NSF which eventually resulted in a joint project with the European Centre for Medium Range Weather Forecasting (ECMWF), the Asian Disaster Preparedness Centre (ADPC) and the Bangladesh Flood Forecasting and Warning Centre. The project was organized and developed through the Georgia Institute of Technology. The aim of CFAB was to develop innovative methods of extending the warning of flooding in Bangladesh noting that there was a unique problem: India provided no upstream discharge data to Bangladesh so that before CFAB the maximum lead time of a forecast was that given by measuring river discharge at the India-Bangladesh border: no lead-time at the border and 2 days in the southern parts of the country. Given that the Brahmaputra and Ganges catchment areas had to be regarded as essentially unguaged, it was clear that innovative techniques had to be developed. On of the basic criterion was that the system should provide probabilistic forecasts in order for the Bangladeshis to assess risk. A three-tier system was developed to allow strategic and tactical decisions to be made for agricultural purposes and disaster mitigation: seasonal (1-6 months: strategic), medium range (20-30 days: strategic/tactical) and short range (1-10 days: tactical). The system that has been developed brings together for the first time operational meteorological forecasts (ensemble forecasts from ECMWF), with satellite and discharge data and a suite of hydrological models. In addition, with ADPC and FFWC we have developed an in-country forecast dispersion system that allows a rapid dissemination. The system has proven to be rather successful, especially in the short range. The flooding events of 2004 were forecast with all forecasting tiers at the respective lead time. In particular, the short-term forecasts picked 10 days ahead of time the double flooding peak. In 2007, the system forecast the commencement and retreat of the July- August floods allowing for the first time for the Bangladesh Disaster Management Committee to act proactively rather than reactively. As a result, many thousands of villagers were evacuated out of harms way. The forecasting system will be discussed in some detail together with examples of forecasts made during the last 5 years. Most importantly, we see the method we have developed as a template for flood forecasting in the developing world where modern technology from the United States and Europe interfaces, interacts and supports local infrastructure.

  8. Evaluation of Monthly Precipitation Forecasting Skill of the National Multi-Model Ensemble

    NASA Astrophysics Data System (ADS)

    Wang, H.

    2012-12-01

    National Multi-Model Ensemble (NMME) comprises of seven climate models from different sources, including NOAA, NASA, NCAR and the International Research Institute for Climate and Society (IRI). It provides 89 ensemble members for precipitation forecasts at different lead time. Precipitation forecasting from climate models have been applied to streamflow forecasts and its utility in water resources system operation has been demonstrated in the literature. In this study, one-month-ahead precipitation forecasts from NMME is evaluated for 180 grids of 2.5 degree by 2.5 degree over the continental United States using Mean square error (MSE) and Rank probability score (RPS). The forecasting skill over different months and its spatial variability are discussed. Preliminary results show that the variability of the forecasting skill reveals the correlation between precipitation observation and large scale oceanic-atmospheric indexes, e.g., NINO 3.4. Such analyses have implications for monthly/seasonal streamflow forecasts and water resources management at the watershed scale.

  9. A one-way coupled atmospheric-hydrological modeling system with combination of high-resolution and ensemble precipitation forecasting

    NASA Astrophysics Data System (ADS)

    Wu, Zhiyong; Wu, Juan; Lu, Guihua

    2015-11-01

    Coupled hydrological and atmospheric modeling is an effective tool for providing advanced flood forecasting. However, the uncertainties in precipitation forecasts are still considerable. To address uncertainties, a one-way coupled atmospheric-hydrological modeling system, with a combination of high-resolution and ensemble precipitation forecasting, has been developed. It consists of three high-resolution single models and four sets of ensemble forecasts from the THORPEX Interactive Grande Global Ensemble database. The former provides higher forecasting accuracy, while the latter provides the range of forecasts. The combined precipitation forecasting was then implemented to drive the Chinese National Flood Forecasting System in the 2007 and 2008 Huai River flood hindcast analysis. The encouraging results demonstrated that the system can clearly give a set of forecasting hydrographs for a flood event and has a promising relative stability in discharge peaks and timing for warning purposes. It not only gives a deterministic prediction, but also generates probability forecasts. Even though the signal was not persistent until four days before the peak discharge was observed in the 2007 flood event, the visualization based on threshold exceedance provided clear and concise essential warning information at an early stage. Forecasters could better prepare for the possibility of a flood at an early stage, and then issue an actual warning if the signal strengthened. This process may provide decision support for civil protection authorities. In future studies, different weather forecasts will be assigned various weight coefficients to represent the covariance of predictors and the extremes of distributions.

  10. Error discrimination of an operational hydrological forecasting system at a national scale

    NASA Astrophysics Data System (ADS)

    Jordan, F.; Brauchli, T.

    2010-09-01

    The use of operational hydrological forecasting systems is recommended for hydropower production as well as flood management. However, the forecast uncertainties can be important and lead to bad decisions such as false alarms and inappropriate reservoir management of hydropower plants. In order to improve the forecasting systems, it is important to discriminate the different sources of uncertainties. To achieve this task, reanalysis of past predictions can be realized and provide information about the structure of the global uncertainty. In order to discriminate between uncertainty due to the weather numerical model and uncertainty due to the rainfall-runoff model, simulations assuming perfect weather forecast must be realized. This contribution presents the spatial analysis of the weather uncertainties and their influence on the river discharge prediction of a few different river basins where an operational forecasting system exists. The forecast is based on the RS 3.0 system [1], [2], which is also running the open Internet platform www.swissrivers.ch [3]. The uncertainty related to the hydrological model is compared to the uncertainty related to the weather prediction. A comparison between numerous weather prediction models [4] at different lead times is also presented. The results highlight an important improving potential of both forecasting components: the hydrological rainfall-runoff model and the numerical weather prediction models. The hydrological processes must be accurately represented during the model calibration procedure, while weather prediction models suffer from a systematic spatial bias. REFERENCES [1] Garcia, J., Jordan, F., Dubois, J. & Boillat, J.-L. 2007. "Routing System II, Modélisation d'écoulements dans des systèmes hydrauliques", Communication LCH n° 32, Ed. Prof. A. Schleiss, Lausanne [2] Jordan, F. 2007. Modèle de prévision et de gestion des crues - optimisation des opérations des aménagements hydroélectriques à accumulation pour la réduction des débits de crue, thèse de doctorat n° 3711, Ecole Polytechnique Fédérale, Lausanne [3] Keller, R. 2009. "Le débit des rivières au peigne fin", Revue Technique Suisse, N°7/8 2009, Swiss engineering RTS, UTS SA, Lausanne, p. 11 [4] Kaufmann, P., Schubiger, F. & Binder, P. 2003. Precipitation forecasting by a mesoscale numerical weather prediction (NWP) model : eight years of experience, Hydrology and Earth System

  11. Use of radar rainfall estimates and forecasts to prevent flash flood in real time by using a road inundation warning system

    NASA Astrophysics Data System (ADS)

    Versini, Pierre-Antoine

    2012-01-01

    SummaryImportant damages occur in small headwater catchments when they are hit by severe storms with complex spatio-temporal structure, sometimes resulting in flash floods. As these catchments are mostly not covered by sensor networks, it is difficult to forecast these floods. This is particularly true for road submersions, representing major concerns for flood event managers. The use of Quantitative Precipitation Estimates and Forecasts (QPE/QPF) especially based on radar measurements could particularly be adequate to evaluate rainfall-induced risks. Although their characteristic time and space scales would make them suitable for flash flood modelling, the impact of their uncertainties remain uncertain and have to be evaluated. The Gard region (France) has been chosen as case study. This area is frequently affected by severe flash floods, and an application devoted to the road network has also been recently developed for the North part of this region. This warning system combines distributed hydro-meteorological modelling and susceptibility analysis to provide warnings of road inundations. The warning system has been tested on the specific storm of the 29-30 September 2007. During this event, around 200 mm dropped on the South part of the Gard and many roads were submerged. Radar-based QPE and QPF have been used to forecast the exact location of road submersions and the results have been compared to the effective road submersions actually occurred during the event as listed by the emergency services. Used on an area it has not been calibrated, the results confirm that the road submersion warning system represents a promising tool for anticipating and quantifying the consequences of storm events at ground. It rates the submersion risk with an acceptable level of accuracy and demonstrates also the quality of high spatial and temporal resolution radar rainfall data in real time, and the possibility to use them despite their uncertainties. However because of the quality of rainfall forecasts falls drastically with time, it is not often sufficient to provide valuable information for lead times exceeding 1 h.

  12. Application of a rule-based system for flash flood forecasting taking into account climate change in the Llobregat basin

    NASA Astrophysics Data System (ADS)

    Velasco, M.; Cabello, A.; Barrera-Escoda, A.; Versini, P. A.; Zappa, M.

    2012-04-01

    IMPRINTS, an EC 7th Framework Programme project, has the main objective of contributing to the reduction of loss of lives and economic damage through the improvement of preparedness and operational risk management of flash floods (FF) and debris flow (DF) events. Global change is expected to put more stress on the entire water cycle and extreme events are likely to increase due to climate change. Thus, in the context of this project, impacts of future changes are analysed. The results of the project have been tested in the Llobregat river basin, in the Northeastern part of Spain. Its source is in the Pyrenees, and due to the rough orography of the region and the reduced size of most of the sub-basins, the hydrologic response times of these watersheds are around a few hours. The basin presents the typical Mediterranean climate where one third of the average annual precipitation can fall in less than 48h. Hence, flash floods occur during convective storms in many of the sub-basins. For this study, the Alt Llobregat, Anoia and Gaverresa sub-basins have been studied. One of the tasks of the IMPRINTS Project dealt with the development of different rule-based FF and DF forecasting systems, with the final goal of providing early warnings to the river basin authorities, improving the operation and management of extreme events. Nevertheless, in this work future climate change scenarios were implemented in the FF rule-based system for the mentioned Llobregat sub-basins. Despite losing the operational function, this could also be an issue of high interest, so the ability to represent the future with this system can be tested, and the possible future impacts can be assessed. The rule-based system used, based on daily precipitation data and developed by WSL, allows to determine future peak flows in some of the existing gauges, being able to approximate the increase of future extreme events. This was done using the future climate scenarios (2011 - 2100) developed by SMC and corrected by CRAHI to better represent the spatial variability. Using the previously described information, the future discharge time series for the A2 and B1 SRES scenarios were obtained and a Peak Over Threshold (POT) analysis was undertaken. By comparing the control period to the future ones, the expected changes of flash flood events in terms of occurrence and intensity were assessed. Despite the uncertainties that appear in the process (and which will be further studied in a next phase), the results obtained can shed some light on how future FF events may be. For the three sub-basins of the Llobregat river studied, the results coincide: an increase of both the occurrence and intensity of the peak discharge values will occur.

  13. 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.

  14. 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...

  15. The 16 May 2005 Flood in Yosemite National Park--A Glimpse into High-Country Flood Generation in the Sierra Nevada

    NASA Astrophysics Data System (ADS)

    Dettinger, M.; Lundquist, J.; Cayan, D.; Meyer, J.

    2006-12-01

    On 16 May 2005, a Pacific storm drew warm, wet subtropical air into the Sierra Nevada, causing moderate rains and major flooding. The flood raised Hetch Hetchy and Tenaya Lake levels markedly and inundated large parts of Yosemite Valley, requiring evacuations and raising public-safety concerns in Yosemite National Park. This was the first major flood to be recorded by the high-country hydroclimatic network in the Park. Since 2001, scientists from US Geological Survey, Scripps Institution of Oceanography, California Department of Water Resources, National Park Service, and other institutions have developed the network of over 30 streamflow and 50 air-temperature loggers at altitudes ranging from <1500 m to >3000 m above sea level, and 8 snow-instrumentation sites measuring snow-water contents, snow depths, radiation, soil moisture, and temperatures in air, snow, and soil. The network documented flooding that derived its runoff mostly from high-altitude rainfall on soils already wet due to the onset of snowmelt a few days earlier. Air temperatures during the storm were above freezing up to altitudes of nearly 3000 m, so that rain fell to as high as 3000 m, compared with normal winter snowlines nearer 1500 m. Streams flooded below 3000 m, and above that altitude did not flood or contribute much to the flooding below. Meanwhile, no significant snow-water content changes were measured. Thus this flood resulted from rain-through-snow runoff rather than rain-on-snow melting. In the Park as a whole, about five times more catchment area received rain, rather than snow, during this storm than during typical cool winter storms. Because the flood was more a result of the large area that received rainfall than of melting snow, snowpack reductions that are expected if recent warming trends continue would not have reduced the flood. Instead, the opportunity for warm storms may increase if warming continues, in which case the potential for this kind of flooding will increase.

  16. 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.

  17. 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 ...

  18. 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.

  19. National scale high-resolution quantification of fluvial flood risk in Great Britain

    NASA Astrophysics Data System (ADS)

    Thornton, James; Thomson, Tina; Liu, Ye; Chaney, Sarah; Dunning, Paul; Hutchings, Stephen; Taylor, Peter; Pickering, Cathy

    2014-05-01

    Britain has experienced repeated episodes of widespread river flooding in recent years, with considerable implications for insurance companies. Probabilistic models enable these companies to robustly quantify flood risk. Because flood events are often very localised, the models would ideally incorporate high-resolution flood data, but although such data are increasingly available at a national scale their inclusion has, to date, been a daunting 'big data' challenge. Here, we discuss some of the scientific and technological advancements we have made to develop a detailed probabilistic model which is underpinned by high-resolution flood data. Return period river flows were first estimated at a large number of locations along the national river network using the Flood Estimation Handbook approach. These flows were then routed across a high-resolution Digital Terrain Model using our 2D hydraulic model, JFlow, to produce 5m resolution river flood hazard maps for the entire county. Our probabilistic model integrates these 'design' hazard data, a state-of-the-art stochastic event set containing tens of thousands of synthetic extreme flow events, a 'built environment' database and 'vulnerability functions' (which relate water depth and damage) to determine the probability distribution of annual river flood losses to insured properties. Stochastic events were carefully assigned to 'years' in the simulation period, with each year being a plausible version of 'next year'. The flood footprint associated with each simulated event was defined, and event-by-event total damage and insured loss calculated. Precise property locations could be provided as an input, and all calculations were carried out on an extremely fine grid to minimise uncertainties due to data aggregation. Being comprised of large data tables, models of this nature are computationally demanding; to enable full analyses on reasonable timescales, our model was re-coded to run on IBM's PureData for Analytics appliance. The model will also be made available in the Oasis Loss Modelling Framework. Uncertainty in the results stems from numerous sources. Two are particularly important: i) uncertainty in the magnitude of long return period river flows, and ii) uncertainty in the damage expected given flooding of a known depth. Whilst the former could not be reduced without access to longer records, the latter could be reduced somewhat by further empirical studies.

  20. 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.

  1. Urban flood simulation based on the SWMM model

    NASA Astrophysics Data System (ADS)

    Jiang, L.; Chen, Y.; Wang, H.

    2015-05-01

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

  2. Development of a screening method to assess flood risk on danish national roads and highway systems.

    PubMed

    Nielsen, N H; Larsen, M R A; Rasmussen, S F

    2011-01-01

    A method to assess flood risk on Danish national roads in a large area in the middle and southern part of Jutland, Denmark, was developed for the Danish Road Directorate. Flood risk has gained renewed focus due to the climate changes in recent years and extreme rain events are expected to become more frequent in the future. The assessment was primarily based on a digital terrain model (DTM) covering 7,500 km2 in a 1.6 x 1.6 m grid. The high-resolution terrain model was chosen in order to get an accurate estimation of the potential flooding in the road area and in the immediate vicinity, but also put a high requirement on the methods, hardware and software applied. The outcome of the analysis was detailed maps (as GIS layers) illustrating the location of depressions with depths, surface area and volume data for each depression. Furthermore, preferential flow paths, catchment boundaries and ranking of each depression were calculated. The ranking was based on volume of depressions compared with upstream catchment and a sensitivity analysis of the runoff coefficient. Finally, a method for assessing flood risk at a more advanced level (hydrodynamic simulation of surface and drainage) was developed and used on a specific blue spot as an example. The case study shows that upstream catchment, depressions, drainage system, and use of hydrodynamic calculations have a great influence on the result. Upstream catchments can contribute greatly to the flooding. PMID:22049725

  3. New smoke predictions for Alaska in NOAA’s National Air Quality Forecast Capability

    NASA Astrophysics Data System (ADS)

    Davidson, P. M.; Ruminski, M.; Draxler, R.; Kondragunta, S.; Zeng, J.; Rolph, G.; Stajner, I.; Manikin, G.

    2009-12-01

    Smoke from wildfire is an important component of fine particle pollution, which is responsible for tens of thousands of premature deaths each year in the US. In Alaska, wildfire smoke is the leading cause of poor air quality in summer. Smoke forecast guidance helps air quality forecasters and the public take steps to limit exposure to airborne particulate matter. A new smoke forecast guidance tool, built by a cross-NOAA team, leverages efforts of NOAA’s partners at the USFS on wildfire emissions information, and with EPA, in coordinating with state/local air quality forecasters. Required operational deployment criteria, in categories of objective verification, subjective feedback, and production readiness, have been demonstrated in experimental testing during 2008-2009, for addition to the operational products in NOAA's National Air Quality Forecast Capability. The Alaska smoke forecast tool is an adaptation of NOAA’s smoke predictions implemented operationally for the lower 48 states (CONUS) in 2007. The tool integrates satellite information on location of wildfires with weather (North American mesoscale model) and smoke dispersion (HYSPLIT) models to produce daily predictions of smoke transport for Alaska, in binary and graphical formats. Hour-by hour predictions at 12km grid resolution of smoke at the surface and in the column are provided each day by 13 UTC, extending through midnight next day. Forecast accuracy and reliability are monitored against benchmark criteria for accuracy and reliability. While wildfire activity in the CONUS is year-round, the intense wildfire activity in AK is limited to the summer. Initial experimental testing during summer 2008 was hindered by unusually limited wildfire activity and very cloudy conditions. In contrast, heavier than average wildfire activity during summer 2009 provided a representative basis (more than 60 days of wildfire smoke) for demonstrating required prediction accuracy. A new satellite observation product was developed for routine near-real time verification of these predictions. The footprint of the predicted smoke from identified fires is verified with satellite observations of the spatial extent of smoke aerosols (5km resolution). Based on geostationary aerosol optical depth measurements that provide good time resolution of the horizontal spatial extent of the plumes, these observations do not yield quantitative concentrations of smoke particles at the surface. Predicted surface smoke concentrations are consistent with the limited number of in situ observations of total fine particle mass from all sources; however they are much higher than predicted for most CONUS fires. To assess uncertainty associated with fire emissions estimates, sensitivity analyses are in progress.

  4. Development of a flood-warning network and flood-inundation mapping for the Blanchard River in Ottawa, Ohio

    USGS Publications Warehouse

    Whitehead, Matthew T.

    2011-01-01

    Digital flood-inundation maps of the Blanchard River in Ottawa, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service and the Village of Ottawa, Ohio. The maps, which correspond to water levels (stages) at the USGS streamgage at Ottawa (USGS streamgage site number 04189260), were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning Network that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. Flood profiles were computed by means of a step-backwater model calibrated to recent field measurements of streamflow. The step-backwater model was then used to determine water-surface-elevation profiles for 12 flood stages with corresponding streamflows ranging from less than the 2-year and up to nearly the 500-year recurrence-interval flood. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas. Maps of the Village of Ottawa showing flood-inundation areas overlain on digital orthophotographs are presented for the selected floods. As part of this flood-warning network, the USGS upgraded one streamgage and added two new streamgages, one on the Blanchard River and one on Riley Creek, which is tributary to the Blanchard River. The streamgage sites were equipped with both satellite and telephone telemetry. The telephone telemetry provides dual functionality, allowing village officials and the public to monitor current stage conditions and enabling the streamgage to call village officials with automated warnings regarding flood stage and/or predetermined rates of stage increase. Data from the streamgages serve as a flood warning that emergency management personnel can use in conjunction with the flood-inundation maps by to determine a course of action when flooding is imminent.

  5. Use of flooded timber by waterfowl at the Montezuma National Wildlife Refuge

    USGS Publications Warehouse

    Cowardin, L.M.

    1969-01-01

    Waterfowl use of bottomland hardwood timber stands which were flooded and killed was studied at the Montezuma National Wildlife Refuge, Seneca Falls, New York, from 1962 to 1964. Comparisons of use were made among six habitat types containing dead timber, stumps, and no timber, and with and without emergent vegetation. An index to waterfowl use was derived by direct counts and by counts made with automatic cameras which photographed randomly selected plots in each habitat type. Movement between types was studied by observation of both marked and unmarked birds. The camera index of use showed that cut timber with emergent vegetation received the greatest overall use. Use was positively correlated with the proximity of the plot to emergent vegetation and nearest vegetative type boundary. A stand flooded for 7 years was used primarily by black ducks (Anas rubripes) and mallards (A. platyrhynchos). Use of stands flooded for 20 years was dominated by American widgeon (Mareca americana). Waterfowl spent more time resting than feeding in timbered areas, and more time feeding than resting in marsh areas. Young-of-the-year did not move between pools after they had reached an age of IIc (Gollop and Marshall 1954). Use by broods was greatest in areas near emergent vegetation. Flying birds used timbered areas during the daytime and non-timbered areas at night during fall. Flooded dead timber appeared to be attractive to waterfowl because it furnished abundant loafing sites.

  6. Flood Risk and Flood hazard maps - Visualisation of hydrological risks

    NASA Astrophysics Data System (ADS)

    Spachinger, Karl; Dorner, Wolfgang; Metzka, Rudolf; Serrhini, Kamal; Fuchs, Sven

    2008-11-01

    Hydrological models are an important basis of flood forecasting and early warning systems. They provide significant data on hydrological risks. In combination with other modelling techniques, such as hydrodynamic models, they can be used to assess the extent and impact of hydrological events. The new European Flood Directive forces all member states to evaluate flood risk on a catchment scale, to compile maps of flood hazard and flood risk for prone areas, and to inform on a local level about these risks. Flood hazard and flood risk maps are important tools to communicate flood risk to different target groups. They provide compiled information to relevant public bodies such as water management authorities, municipalities, or civil protection agencies, but also to the broader public. For almost each section of a river basin, run-off and water levels can be defined based on the likelihood of annual recurrence, using a combination of hydrological and hydrodynamic models, supplemented by an analysis of historical records and mappings. In combination with data related to the vulnerability of a region risk maps can be derived. The project RISKCATCH addressed these issues of hydrological risk and vulnerability assessment focusing on the flood risk management process. Flood hazard maps and flood risk maps were compiled for Austrian and German test sites taking into account existing national and international guidelines. These maps were evaluated by eye-tracking using experimental graphic semiology. Sets of small-scale as well as large-scale risk maps were presented to test persons in order to (1) study reading behaviour as well as understanding and (2) deduce the most attractive components that are essential for target-oriented risk communication. A cognitive survey asking for negative and positive aspects and complexity of each single map complemented the experimental graphic semiology. The results indicate how risk maps can be improved to fit the needs of different user groups. Recommendations were developed of how to provide stakeholder-oriented information on hydrological risks.

  7. 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 Program for Non-Primary Residences AGENCY: Federal Emergency Management Agency, DHS. ACTION: Notice... Federal Insurance, Federal Emergency Management Agency. BILLING CODE 9110-11-P...

  8. Ensemble flood forecasting to support dam water release operation using 10 and 2 km-resolution JMA Nonhydrostatic Model ensemble rainfalls

    NASA Astrophysics Data System (ADS)

    Kobayashi, K.; Otsuka, S.; Apip; Saito, K.

    2015-12-01

    This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency Nonhydrostatic Model are used as the input data to a rainfall-runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolution. A distributed rainfall-runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km-resolution JMA-NHM ensemble simulation are more appropriate than the 10 km-resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s-1; a threshold value for flood control. The inflows with the 10 km-resolution ensemble rainfall are all considerably smaller than the observations, while, at least one simulated discharge out of 11 ensemble members with the 2 km-resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls show much better results than the original ensemble discharge simulations.

  9. 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.

  10. Potential hazards from flood in part of the Chalone Creek and Bear Valley drainage basins, Pinnacles National Monument, California

    USGS Publications Warehouse

    Meyer, Robert W.

    1995-01-01

    Areas of Chalone Creek and Bear Valley drainage basins in Pinnacles National Monument, California, are subject to frontal storms that can cause major flooding from November to April in areas designated for public use. To enhance visitor safety and to protect cultural and natural resources, the U.S. Geological Survey in cooperation with the National Park Service studied flood-hazard potentials within the boundaries of the Pinnacles National Monument. This study area extends from about a quarter of a mile north of Chalone Creek Campground to the mouth of Bear Valley and from the east monument entrance to Chalone Creek. Historical data of precipitation and floodflow within the monument area are sparse to nonexistent, therefore, U.S. Soil Conservation Service unit-hydrograph procedures were used to determine the magnitude of a 100-year flood. Because of a lack of specific storm-rainfall data, a simulated storm was applied to the basins using a digital-computer model developed by the Soil Conservation Service. A graphical relation was used to define the regionally based maximum flood for Chalone Creek and Bear Valley. Water-surface elevations and inundation areas were determined using a conventional step-backwater program. Flood-zone boundaries were derived from the computed water-surface elevations. The 100-year flood plain for both streams would be inundated at all points by the regional maximum flood. Most of the buildings and proposed building sites in the monument area are above the elevation of the 100-year flood, except the proposed building sites near the horse corral and the east monument entrance. The 100-year flood may cause reverse flow through a 12-inch culvert embedded in the embankment of Old Pinnacles Campground Road in the center of Chalone Creek Campground. The likelihood of this occurring is dependant upon the amount of aggradation that occurs upstream; therefore, the campground area also is considered to be within the 100-year flood zone.

  11. The Impact of Corps Flood Control Reservoirs in the June 2008 Upper Mississippi Flood

    NASA Astrophysics Data System (ADS)

    Charley, W. J.; Stiman, J. A.

    2008-12-01

    The US Army Corps of Engineers is responsible for a multitude of flood control project on the Mississippi River and its tributaries, including levees that protect land from flooding, and dams to help regulate river flows. The first six months of 2008 were the wettest on record in the upper Mississippi Basin. During the first 2 weeks of June, rainfall over the Midwest ranged from 6 to as much as 16 inches, overwhelming the flood protection system, causing massive flooding and damage. Most severely impacted were the States of Iowa, Illinois, Indiana, Missouri, and Wisconsin. In Iowa, flooding occurred on almost every river in the state. On the Iowa River, record flooding occurred from Marshalltown, Iowa, downstream to its confluence with the Mississippi River. At several locations, flooding exceeded the 500-year event. The flooding affected agriculture, transportation, and infrastructure, including homes, businesses, levees, and other water-control structures. It has been estimated that there was at least 7 billion dollars in damages. While the flooding in Iowa was extraordinary, Corps of Engineers flood control reservoirs helped limit damage and prevent loss of life, even though some reservoirs were filled beyond their design capacity. Coralville Reservoir on the Iowa River, for example, filled to 135% of its design flood storage capacity, with stage a record five feet over the crest of the spillway. In spite of this, the maximum reservoir release was limited to 39,500 cfs, while a peak inflow of 57,000 cfs was observed. CWMS, the Corps Water Management System, is used to help regulate Corps reservoirs, as well as track and evaluate flooding and flooding potential. CWMS is a comprehensive data acquisition and hydrologic modeling system for short-term decision support of water control operations in real time. It encompasses data collection, validation and transformation, data storage, visualization, real time model simulation for decision-making support, and data dissemination. The system uses precipitation and flow data, collected in real-time, along with forecasted flow from the National Weather Service to model and optimize reservoir operations and forecast downstream flows and stages, providing communities accurate and timely information to aid their flood-fighting. This involves integrating several simulation modeling programs, including HEC-HMS to forecast flows, HEC-ResSim to model reservoir operations and HEC-RAS to compute forecasted stage hydrographs. An inundation boundary and depth map of water in the flood plain can be calculated from the HEC-RAS results using ArcInfo. By varying future precipitation and releases, engineers can evaluate different "What if?" scenarios. The effectiveness of this tool and Corps reservoirs are examined.

  12. Accuracy of the Operational NOAA-EPA National Air Quality Forecasting System during Summer 2005 and 2006 in Philadelphia

    NASA Astrophysics Data System (ADS)

    Huff, A. K.; Ryan, W. F.; Bahrmann, C. P.

    2007-12-01

    The NOAA-EPA National Air Quality Forecasting System (NAQFS) is a numerical ozone forecast model that consists of a coupled version of NOAA's North American Mesoscale (NAM)-12 model and EPA's Community Multiscale Air Quality model (CMAQ). NAQFS runs twice daily at 0600 UTC and 1200 UTC and predicts hourly ozone abundances as mixing ratios in units of parts per billion (ppb). Model output is typically processed to provide 1-hour and 8-hour average ozone forecasts that correspond to the national ambient air quality standards (NAAQS) for ozone. Now in its third season as an operational model, NAQFS is designed to assist air quality meteorologists by providing accurate and dependable forecast guidance. Before air quality meteorologists are willing to rely upon a new tool like NAQFS to assist them in preparing forecasts for the public, however, the model must be evaluated in the typical operational setting for air quality forecasting - the metropolitan scale. To address this need, results will be presented from a pilot statistical study of Summer 2005 and 2006 NAQFS performance in the Philadelphia forecast area. The accuracy, bias, and skill of the model has been determined by comparing 8-hour average ozone forecasts from the 1200 UTC run of NAQFS to corresponding observed ozone values. Overall, the model shows the best skill in suburban areas, where ozone levels tend to peak across the metropolitan region. NAQFS was not reliable in 2005 during Code Orange and Red events, when ozone levels were greater than 84 ppb. In 2006, NAQFS accuracy increased during these cases, which was most likely a result of the NAM's changeover from the Eta model to the Weather and Forecasting (WRF) model. The most probable sources of error that impacted NAQFS performance in 2005 and 2006 will be discussed, including shortcomings in emissions databases and poorly characterized atmospheric chemistry. Preliminary results from the 2007 summer ozone season will also be provided.

  13. 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.

  14. 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.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

    Serinaldi, F.; Kilsby, C. G.

    2012-04-01

    While extensive research has been devoted to rainfall-runoff modelling for risk assessment in small and medium size watersheds, less attention has been paid, so far, to large scale trans-national basins, where flood events have severe societal and economic impacts with magnitudes quantified in billions of Euros. As an example, in the April 2006 flood events along the Danube basin at least 10 people lost their lives and up to 30 000 people were displaced, with overall damages estimated at more than half a billion Euros. In this context, refined analytical methods are fundamental to improve the risk assessment and, then, the design of structural and non structural measures of protection, such as hydraulic works and insurance/reinsurance policies. Since flood events are mainly driven by exceptional rainfall events, suitable characterization and modelling of space-time properties of rainfall fields is a key issue to perform a reliable flood risk analysis based on alternative precipitation scenarios to be fed in a new generation of large scale rainfall-runoff models. Ultimately, this approach should be extended to a global flood risk model. However, as the need of rainfall models able to account for and simulate spatio-temporal properties of rainfall fields over large areas is rather new, the development of new rainfall simulation frameworks is a challenging task involving that faces with the problem of overcoming the drawbacks of the existing modelling schemes (devised for smaller spatial scales), but keeping the desirable properties. In this study, we critically summarize the most widely used approaches for rainfall simulation. Focusing on stochastic approaches, we stress the importance of introducing suitable climate forcings in these simulation schemes in order to account for the physical coherence of rainfall fields over wide areas. Based on preliminary considerations, we suggest a modelling framework relying on the Generalized Additive Models for Location, Scale and Shape (GAMLSS). This approach allows exploiting climate variables to improve the simulation of the spatio-temporal rainfall structure through dynamically varying marginal and joint distributions. The preliminary results of the spatio-temporal analysis and modelling of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe are shown. Finally, indications are given of how the model outputs will be used with rainfall runoff models for estimating collective flood risk across the Danube basin.

  17. 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.

  18. Probabilistic forecasts for Decision Support at the North Central River Forecast Center

    NASA Astrophysics Data System (ADS)

    Restrepo, Pedro; Buan, Steven; Connelly, Brian; DeWeese, Michael; Diamond, Laura; Ellis, Larry; Goering, Dustin; Holz, Andrea; Husaby, James; Merrigan, Douglas; Palmer, Justin; Pokorny, Daniel; Reckel, Holly; Sites, William; Stockhaus, Scott; Thornburg, Jonathon; Wavrin, Robert.; Ziemer, Mark

    2013-04-01

    The North Central River Forecast Center (NCRFC) of the US National Weather Service has the responsibility for issuing river forecasts at 426 points over an area of nearly 890,000 km2, covering the Upper Mississippi river basin, the US watersheds flowing to lakes Superior, Huron and Michigan, and rivers flowing from the US to the Hudson Bay in Canada. The NCRFC issues probabilistic outlook forecasts at all its forecast points starting on December. While focused primarily on the risks associated with flooding during the spring snow melt down, the RFC frequently issues probabilistic forecasts to deal with water resources operations during drought times. This presentation will focus on probabilistic forecasts issued to assess flooding risk at Red River of the North , to support navigation operations on the Mississippi river during drought conditions, and on support of reservoir operations for hydropower generation and recreation. The presentation will discuss the improvements over the current practice that will be possible to achieve once the NWS Hydrologic Ensemble Forecasting System is put into operations later this year.

  19. Extreme Rainfall and Flood Events for the Hudson River Induced by Tropical Cyclones: a Statistical Forecast Model

    NASA Astrophysics Data System (ADS)

    Conticello, F.; Hall, T. M.; Lall, U.; Orton, P. M.; Cioffi, F.; Georgas, N.

    2014-12-01

    Tropical Cyclones (TCs) lead to potentially severe coastal flooding through wind surge and also through rainfall-runoff processes. There is growing interest in modeling these processes simultaneously. Here, a statistical approach that can facilitate this process is presented with an application to the Hudson River Basin that is associated with the New York City metropolitan area. Three submodels are used in sequence. The first submodel is a stochastic model of the complete life cycle of North Atlantic (NA) tropical cyclones developed by Hall and Yonekura (2011). It uses archived data of TCs throughout the North Atlantic to estimate landfall rates at high geographic resolution as a function of the ENSO state and of sea surface temperature (SST). The second submodel translates the attributes of a tropical cyclone simulated by the first model to the streamflows at specific points of the tributaries of the Hudson River. That points are the closure sections of five different watersheds. Two different approaches are used and compared: 1) an ANN-cyclone/rainfall clustering model which calculates the rainfall intensity at selected stations within the watershed, that are then used as inputs of an ANN rainfall/runoff model; 2) an ANN/ Bayesian multivariate approach that translates the TC attributes ( track, SST, Velocities,..) directly in streamflows in the tributaries. Finally, the streamflows of the tributaries of the Hudson River are to be used as inputs in a hydrodynamic model that includes storm surge dynamics for the simulation of coastal flooding along the Hudson River. Calibration and validation of the model is carried out by using, selected tropical cyclone data since 1950, and hourly and daily station rainfall and streamflow recorded for such extreme events. Seven stream gauges (Croton River, Rondout Creek, Wappinger Creek, Troy dam, Mohawk River at Cohoes, Mohawk River diversion at Crescent Dam, Hudson River above lock one nr Waterford) and over 20 rain gauges are used. The performance of the proposed model as tool for storm events is then analyzed and discussed.

  20. 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.

  1. 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

  2. The flood retention analysis of ?asica canal valley situated in the Kampinos National Park in Poland.

    NASA Astrophysics Data System (ADS)

    Grniak, Anna; Kubrak, Janusz; Okruszko, Tomasz; Chorma?ski, Jaros?aw

    2010-05-01

    The ?asica canal is situated in second largest national park in Poland, in the Kampinos National Park localized near to Warsaw. The ?asica canal valley has 100 square kilometers surface. One of the most unique and valuable wetland areas in Poland are threatened by environmental degradation. Drainage land reclamation done in the past and regulation of watercourses leads to negative changes in water conditions and permanent, advanced changes in flora and fauna in consequences. There is an urgent need to improve water conditions in the endangered wetland area of the Kampinos National Park. The flood retention of area situated along ?asica canal in the Kampinos National Park has been analysed. The analysis was based on calculations done at one dimension model in steady and unsteady water flow conditions in ?asica canal with existing water structures. The Digital Elevation Model has been also used to define flood extent and retention capacity of the ?asica valley. The Digital Elevation Model of the valley was elaborated and validated by universal kriging method with help of ArcGIS Geostatistical Analyst as a raster representation of the floodplain morphology. The basis data source for constructing of DEM was set of point data directly measured by GPS RTK on open space or by classical leveling in forest. The morphology forms like oxbows and old meanders were extract by photogrammetric methods and include in post-interpolation processing of the DEM. The changes of retention caused by damming up the water and flow growth in ?asica canal has been analysed, described and presented on poster.

  3. 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.

  4. 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 Biała 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.

  5. Progress and challenges with Warn-on-Forecast

    NASA Astrophysics Data System (ADS)

    Stensrud, David J.; Wicker, Louis J.; Xue, Ming; Dawson, Daniel T.; Yussouf, Nusrat; Wheatley, Dustan M.; Thompson, Therese E.; Snook, Nathan A.; Smith, Travis M.; Schenkman, Alexander D.; Potvin, Corey K.; Mansell, Edward R.; Lei, Ting; Kuhlman, Kristin M.; Jung, Youngsun; Jones, Thomas A.; Gao, Jidong; Coniglio, Michael C.; Brooks, Harold E.; Brewster, Keith A.

    2013-04-01

    The current status and challenges associated with two aspects of Warn-on-Forecast-a National Oceanic and Atmospheric Administration research project exploring the use of a convective-scale ensemble analysis and forecast system to support hazardous weather warning operations-are outlined. These two project aspects are the production of a rapidly-updating assimilation system to incorporate data from multiple radars into a single analysis, and the ability of short-range ensemble forecasts of hazardous convective weather events to provide guidance that could be used to extend warning lead times for tornadoes, hailstorms, damaging windstorms and flash floods. Results indicate that a three-dimensional variational assimilation system, that blends observations from multiple radars into a single analysis, shows utility when evaluated by forecasters in the Hazardous Weather Testbed and may help increase confidence in a warning decision. The ability of short-range convective-scale ensemble forecasts to provide guidance that could be used in warning operations is explored for five events: two tornadic supercell thunderstorms, a macroburst, a damaging windstorm and a flash flood. Results show that the ensemble forecasts of the three individual severe thunderstorm events are very good, while the forecasts from the damaging windstorm and flash flood events, associated with mesoscale convective systems, are mixed. Important interactions between mesoscale and convective-scale features occur for the mesoscale convective system events that strongly influence the quality of the convective-scale forecasts. The development of a successful Warn-on-Forecast system will take many years and require the collaborative efforts of researchers and operational forecasters to succeed.

  6. 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.

  7. Estimated flood-inundation maps for Cowskin Creek in western Wichita, Kansas

    USGS Publications Warehouse

    Studley, Seth E.

    2003-01-01

    The October 31, 1998, flood on Cowskin Creek in western Wichita, Kansas, caused millions of dollars in damages. Emergency management personnel and flood mitigation teams had difficulty in efficiently identifying areas affected by the flooding, and no warning was given to residents because flood-inundation information was not available. To provide detailed information about future flooding on Cowskin Creek, high-resolution estimated flood-inundation maps were developed using geographic information system technology and advanced hydraulic analysis. Two-foot-interval land-surface elevation data from a 1996 flood insurance study were used to create a three-dimensional topographic representation of the study area for hydraulic analysis. The data computed from the hydraulic analyses were converted into geographic information system format with software from the U.S. Army Corps of Engineers' Hydrologic Engineering Center. The results were overlaid on the three-dimensional topographic representation of the study area to produce maps of estimated flood-inundation areas and estimated depths of water in the inundated areas for 1-foot increments on the basis of stream stage at an index streamflow-gaging station. A Web site (http://ks.water.usgs.gov/Kansas/cowskin.floodwatch) was developed to provide the public with information pertaining to flooding in the study area. The Web site shows graphs of the real-time streamflow data for U.S. Geological Survey gaging stations in the area and monitors the National Weather Service Arkansas-Red Basin River Forecast Center for Cowskin Creek flood-forecast information. When a flood is forecast for the Cowskin Creek Basin, an estimated flood-inundation map is displayed for the stream stage closest to the National Weather Service's forecasted peak stage. Users of the Web site are able to view the estimated flood-inundation maps for selected stages at any time and to access information about this report and about flooding in general. Flood recovery teams also have the ability to view the estimated flood-inundation map pertaining to the most recent flood. The availability of these maps and the ability to monitor the real-time stream stage through the U.S. Geological Survey Web site provide emergency management personnel and residents with information that is critical for evacuation and rescue efforts in the event of a flood as well as for post-flood recovery efforts.

  8. Floods and Flash Flooding

    MedlinePlus

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

  9. Revisions Recommended to Bulletin 17B - US National Flood Frequency Guidelines

    NASA Astrophysics Data System (ADS)

    England, J. F.; Cohn, T. A.; Faber, B. A.; Stedinger, J. R.; Thomas, W. O.; Mason, R. R.

    2013-12-01

    The Hydrologic Frequency Analysis Work Group (HFAWG) has synthesized recent research and completed its own studies to support proposed revisions to the current the US national flood frequency guidelines (Bulletin 17B). Bulletin 17 was originally issued in 1976; Bulletin 17B, the last revision, was published in 1982, over 30 years ago. To reflect advances that have occurred since 1982, the HFAWG has proposed revisions in four main areas: (1) use of historical information; (2) the motivation for low outlier identification and their statistical definition and treatment; (3) procedures for estimating generalized/regional skew; and (4) procedures for estimating confidence intervals for estimated quantiles. We present overviews of the HFAWG process and technical studies that led us to these revisions. The focus is on the use of the Expected Moments Algorithm (EMA) with the log-Pearson Type III distribution. A new Multiple Grubbs-Beck low outlier test and improved EMA confidence intervals are important parts of the revision.

  10. Flash Flood Nowcasting in an Urban Watershed

    NASA Astrophysics Data System (ADS)

    Sharif, H.; Yates, D.; Roberts, R.; Brandes, E.

    2003-04-01

    Flash floods occur when particular meteorological events are combined with certain hydrologic conditions. Several approaches to nowcast flash floods are being developed,> However, predictions of the magnitude and timing of flash flood events is a major challenge. Nowcasts of convective storm events need to be linked with robust hydrologic modeling and analysis in order to produce useful flash flood predictions in terms of timing, and the spatial and temporal distribution of the runoff. Advances in radar-rainfall estimation and two-dimensional physically based runoff modeling offer tools to improve flash flooding forecasting and to reduce the potential for loss of life and property damage in urban catchments. The ability to model extreme hydrologic events in detail was demonstrated using the physically based distributed-parameter hydrologic model GSSHA (Downer and Ogden, 2002) on an urban watershed in Denver, Colorado (Sharif et al., 2002). The study addressed the necessary detail in urban topography and drainage characteristics needed for accurate simulations of urban flood events. With this kind of detailed hydrologic model, accurate short-range meteorological nowcasts (30 60 minutes) would prove useful. Such a nowcast is available from the National Center for Atmospheric Research’s (NCAR) Autonowcaster, a data fusion system that combines several predictor fields with membership functions and weighting schemes to produce automated time and place specific nowcasts of convective rainfall. Predictor fields are derived from characteristics of boundary layer convergence regions, storm characteristics, and dynamic and kinematic attributes of the boundary layer. Simple extrapolations are also used as benchmark nowcasts. The GSSHA model was coupled with the Autonowcaster to produce distributed, physics-based hydrologic predictions in the urban setting. Flash flood predictions of the coupled system are compared to predictions computed using traditional approaches and lumped hydrologic models. This study highlights both the meteorological and hydrologic aspects of the flash flood problem in an effort to develop a real-time flash flood forecasting system.

  11. 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.

  12. 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.

  13. Coastal ocean forecasting systems in Europe

    NASA Astrophysics Data System (ADS)

    Dugan, John

    During my tour as the liaison oceanographer at the Office of Naval Research's European branch, I conducted a focused study of coastal ocean forecasting systems. This study is of direct interest to ONR because of an increased interest in the coastal zone and to the civilian U.S. oceanographic community because of numerous problems in the coastal zone that could be alleviated with an operational forecasting system. The Europeans have a long history of excellent research and developmental work in this area. The Europeans' distinguished history in coastal ocean forecasting is due in part to their strong dependence on the sea. However, the original motivation for these systems was the recognition early in this century that weather conditions were responsible for damaging storm surges around the periphery of the North Sea and that science could predict these catastrophic floods. Forecasting systems called tide-surge prediction systems, which provide warnings of impending flood conditions, were designed and constructed and are operational in the various meteorological centers of the nations surrounding the North Sea. Over time, the services have been extended to provide forecasts of ocean waves, water depth for navigation, and currents for a large customer base. These systems now are being extended further into the three-dimensional domain that is required for management of problems associated with water quality, pollution, and aquaculture and fisheries interests.

  14. 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,…

  15. 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

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

    NASA Astrophysics Data System (ADS)

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

    1982-03-01

    The background, structure and use of modern forecasting methods for estimating the development of geothermal energy are documented. The forecasting instrument may be divided into two sequential submodels. The first predicts the timing and quality of geothermal resource discoveries from an underlying resource base. 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 energy demands.

  17. 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.

  18. 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.

  19. Verification of Precipitation Forecasts from Two Numerical Weather Prediction Models for the Middle- and North-Eastern Region of the USA

    NASA Astrophysics Data System (ADS)

    Siddique, R.; Brown, J.; Reed, S. M.; Mejia, A.

    2014-12-01

    Accurate precipitation and temperature forecasts are the pre-requisites to produce skillful flood forecasts. The structures of different precipitation forecasting systems are constantly evolving, for example, with improvements in the forecasting techniques, increases in spatial and temporal resolution, improvements in model physics and numerical techniques, and better understanding of uncertainty. Hence, routine verification is necessary to understand the quality of forecasts at particular times and locations, and as inputs to hydrologic modeling. Hydrologic forecasters in the National Weather Service are evaluating precipitation and temperature forecasts from a wide range of numerical prediction models to improve the streamflow forecasts. To assist in this effort, our goal here is to verify the operational precipitation forecasts from the National Centers for Environmental Prediction 21-member Short Range Ensemble Forecast (SREF) system, together with precipitation reforecasts from the 11-member Global Ensemble Forecast System (GEFS). The verification is done for the middle- and north-eastern region of the United States and for mean areal precipitation forecasts conditioned on precipitation amounts, lead times, seasonality, and accumulation periods. Multi-sensor precipitation estimates are used as observed data. The effect of different basin sizes on forecast quality is also studied by simply choosing areal extents of varying sizes. Although flood forecasting is the main context of this study, separate analyses are presented for moderate and large precipitation events with a view towards providing additional information to forecasters. The summary of verification statistics indicates similar forecasting performance for both SREF and GEFS reforecasts even though GEFS reforecasts are valid for much longer lead times and coarser grid resolution. Precipitation forecasts from both of these models show greater skill in large basins than in relatively smaller ones. Lastly, we identify and highlight the potential of the verified precipitation forecasts as forcing inputs to hydrologic modeling.

  20. 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.

  1. 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.

  2. 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 km 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.

  3. 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.

  4. Flood-inundation maps for the Suncook River in Epsom, Pembroke, Allenstown, and Chichester, New Hampshire

    USGS Publications Warehouse

    Flynn, Robert H.; Johnston, Craig M.; Hays, Laura

    2012-01-01

    Digital flood-inundation maps for a 16.5-mile reach of the Suncook River in Epsom, Pembroke, Allenstown, and Chichester, N.H., from the confluence with the Merrimack River to U.S. Geological Survey (USGS) Suncook River streamgage 01089500 at Depot Road in North Chichester, N.H., were created by the USGS in cooperation with the New Hampshire Department of Homeland Security and Emergency Management. The inundation maps presented in this report depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Suncook River at North Chichester, N.H. (station 01089500). The current conditions at the USGS streamgage may be obtained on the Internet (http://waterdata.usgs.gov/nh/nwis/uv/?site_no=01089500&PARAmeter_cd=00065,00060). The National Weather Service forecasts flood hydrographs at many places that are often collocated with USGS streamgages. Forecasted peak-stage information is available on the Internet at the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) flood-warning system 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. These maps along with real-time stream stage data from the USGS Suncook River streamgage (station 01089500) and forecasted stream stage from the NWS will provide emergency management personnel and residents with information that is critical for flood-response activities, such as evacuations, road closures, disaster declarations, and post-flood recovery. The maps, along with current stream-stage data from the USGS Suncook River streamgage and forecasted stream-stage data from the NWS, can be accessed at the USGS Flood Inundation Mapping Science Web site http://water.usgs.gov/osw/flood_inundation/.

  5. Forecasting Distributional Responses of Limber Pine to Climate Change at Management-Relevant Scales in Rocky Mountain National Park

    PubMed Central

    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/m2) 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

  6. 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.

  7. 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.

  8. 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.

  9. Forecasting forecast skill

    NASA Technical Reports Server (NTRS)

    Kalnay, Eugenia; Dalcher, Amnon

    1987-01-01

    It is shown that it is possible to predict the skill of numerical weather forecasts - a quantity which is variable from day to day and region to region. This has been accomplished using as predictor the dispersion (measured by the average correlation) between members of an ensemble of forecasts started from five different analyses. The analyses had been previously derived for satellite-data-impact studies and included, in the Northern Hemisphere, moderate perturbations associated with the use of different observing systems. When the Northern Hemisphere was used as a verification region, the prediction of skill was rather poor. This is due to the fact that such a large area usually contains regions with excellent forecasts as well as regions with poor forecasts, and does not allow for discrimination between them. However, when regional verifications were used, the ensemble forecast dispersion provided a very good prediction of the quality of the individual forecasts.

  10. 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.

  11. 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.

  12. Flood analysis along the Little Missouri River within and adjacent to Theodore Roosevelt National Park, North Dakota

    USGS Publications Warehouse

    Emerson, D.G.; Macek-Rowland, Kathleen

    1986-01-01

    The Little Missouri River flows through Theodore Roosevelt National Park, which consists of three separate units: South Unit, Elkhorn Ranch Site, and North Unit. The park is located in the Little Missouri badlands. Discharges and water surface elevations for 100 yr or 500 yr floods or both were computed for selected reaches along the Little Missouri River and three of its tributaries (Knutson Creek, Paddock Creek, and Squaw Creek) within and adjacent to Theodore Roosevelt National Park. The 100-yr flood discharge determined for the Little Missouri River South Unit reach was 65,300 cu ft/sec; the discharge determined for the Little Missouri River Elkhorn Ranch Site reach was 69 ,000 cu ft/sec; and the discharge determined for the Little Missouri River North Unit reach was 78,800 cu ft/sec. A multiple regression equation based on drainage area and infiltration index was used in the flood flow frequency analysis for the creeks. The 100 yr flood discharge determined for Knutson Creek reach was 31,800 cu ft/sec; the discharge determined for Paddock Creek reach was 18,500 cu ft/sec; and the discharge determined for Squaw Creek reach was 24,600 cu ft/sec. Cross-sectional data were obtained by field surveys. Water surface elevations were computed using step-backwater methods. Streamflow records for two stations on the Little Missouri River were used to develop maximum observed backwater envelope curves and elevation frequency curves. The maximum observed backwater envelope curves show a trend in which the backwater decreases as the discharge increases. The backwater due to ice approaches zero before reaching the computed elevations for the 100 yr discharges. (Lantz-PTT)

  13. The integrated local flood warning system: A look at the flood response system

    SciTech Connect

    Neal, D.M.; Lee, R.

    1988-01-01

    Local Flood Warning Systems are instituted and maintained at a local level. They consist of two parts: (1) the flood forecast system, and (2) the flood response system. The flood forecast system is primarily built around the technology used to predict flooding. In this paper, we stress two points about local flood warning systems. First, the system must be integrated. Specifically, collecting data, transmitting data, forecasting the flood, informing local officials, warning local residents, and taking protective action (including evacuation of residents) must all occur in an integrated fashion if the whole system is to succeed. Second, we outline some important organizational characteristics that should be improved when developing a local flood response system. Key organizational characteristics include experience, networks, communications, decision making, everyday disaster task overlap. By focusing upon experience (including learning from the past flood or disaster experience or participating in drills and exercises) and by improving preparedness can be inexpensively improved. 6 refs.,

  14. Battle of Inches: The Spring 2011 Flood along the Ohio River and Upper Mississippi

    NASA Astrophysics Data System (ADS)

    Hanbali, F.; Brunner, G. W.; Hanbali, F. U.; Astifan, B. M.

    2011-12-01

    Sustained rainfall over the Ohio River Basin in Spring 2011, with records that yielded the wettest April in over a hundred years, led to one of the largest flood events in that region in the last century. Simultaneous heavy rains and runoff within the upper Mississippi River Basin further challenged the flood mitigation efforts by the US Army Corps of Engineers (USACE) and its partner agencies. In coordination with the National Weather Service (NWS) and relying on daily flow forecasts by the regional NWS River Forecast Centers, the USACE used its river hydraulics analysis computer program (HEC-RAS) to predict flood stages along the entire Ohio River and a significant section of the Mississippi River around the Ohio River confluence. Informed by the hydrologic and hydraulic analysis tools, the flood mitigation efforts entailed significant curbing of releases from flood control dams and navigation projects, as well as crucial decisions to activate major floodway bypasses, prevent levee failures, and protect urban centers. This presentation will review the Spring 2011 Flood and the use of the National Weather Service forecast products along with the USACE river hydraulics analysis models as real-time decision support tools in an event that was deemed to be a "Battle of Inches".

  15. 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.

  16. 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.

  17. Assessment of NOx and O3 forecasting performances in the U.S. National Air Quality Forecasting Capability before and after the 2012 major emissions updates

    NASA Astrophysics Data System (ADS)

    Pan, Li; Tong, Daniel; Lee, Pius; Kim, H.-C.; Chai, Tianfeng

    2014-10-01

    In this study, we address outdated emissions inventory problems in air quality forecasting systems. The National Emissions Inventory for NOx from area and mobile sources is projected from 2005 to 2012 and NOx from point sources is projected from 2010 to 2012, in which we find that NOx emissions from area, mobile and point sources reduce by 8.1%, 37.8% and 4.1%, respectively. The majority of the NOx emissions reduction occurs in megacities over the CONtiguous U.S. (CONUS), in which the spatial distribution pattern is generally supported by the NO2 column result retrieved from the GOME-2 satellite data. The CMAQ-predicted NOx and O3 concentrations using updated NOx emissions were then compared to Air Quality System (AQS) ground observations in order to evaluate the updated NOx emissions inventory. The comparison showed an improvement in NOx and O3 predictions over the CONUS. The NOx bias, in July 2011, for urban, suburban and rural land-use types was reduced by 2.34 ppb, 2.09 ppb and 0.57 ppb, respectively. Meanwhile, the O3 bias is reduced by 0.92 ppb, 1.26 ppb and 1.87 ppb, respectively. However, problems remain in CMAQ for NOx and O3 simulations despite undertaking this emissions adjustment. For example, the O3 overestimation in CMAQ during the daytime over the CONUS decreases when the NOx underestimation increases, suggesting that in addition to the NOx emissions inventory, further study of VOC emissions, NOx chemical and physical mechanisms as well as meteorology parameters in the NAQFC is necessary.

  18. 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)

  19. 77 FR 31814 - National Flood Insurance Program (NFIP); Insurance Coverage and Rates

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-30

    ... Flood Insurance Program (NFIP); Insurance Coverage and Rates AGENCY: Federal Emergency Management Agency... on August 5, 1999 (64 FR 42632), is withdrawn as of May 30, 2012. ADDRESSES: The Notice of Proposed... CFR part 79 on September 16, 2009 (74 FR 47471). Therefore, this NPRM is no longer necessary....

  20. 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

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    Shukla, Shraddhanand; Funk, Christopher; Hoell, Andrew

    2014-09-01

    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.

  3. 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.

  4. Ohio River backwater flood-inundation maps for the Saline and Wabash Rivers in southern Illinois

    USGS Publications Warehouse

    Murphy, Elizabeth A.; Sharpe, Jennifer B.; Soong, David T.

    2012-01-01

    Digital flood-inundation maps for the Saline and Wabash Rivers referenced to elevations on the Ohio River in southern Illinois were created by the U.S. Geological Survey (USGS). The inundation maps, accessible 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 (gage heights) at the USGS streamgage at Ohio River at Old Shawneetown, Illinois-Kentucky (station number 03381700). Current gage height and flow conditions at this USGS streamgage may be obtained on the Internet at http://waterdata.usgs.gov/usa/nwis/uv?03381700. In addition, this streamgage is incorporated into the Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/) by the National Weather Service (NWS). The NWS forecasts flood hydrographs at many places that are often co-located at USGS streamgages. That NWS forecasted peak-stage information, also shown on the Ohio River at Old Shawneetown inundation Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, eight water-surface elevations were mapped at 5-foot (ft) intervals referenced to the streamgage datum ranging from just above the NWS Action Stage (31 ft) to above the maximum historical gage height (66 ft). The elevations of the water surfaces were compared to a Digital Elevation Model (DEM) by using a Geographic Information System (GIS) in order to delineate the area flooded at each water level. These maps, along with information on the Internet regarding current gage heights 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.

  5. 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

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

    PubMed

    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

  7. 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

  8. 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)

  9. 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

  10. Development of flood-inundation maps for the Mississippi River in Saint Paul, Minnesota

    USGS Publications Warehouse

    Czuba, Christiana R.; Fallon, James D.; Lewis, Corby R.; Cooper, Diane F.

    2014-01-01

    Digital flood-inundation maps for a 6.3-mile reach of the Mississippi River in Saint Paul, Minnesota, were developed through a multi-agency effort by the U.S. Geological Survey in cooperation with the U.S. Army Corps of Engineers and in collaboration with the National Weather Service. The inundation maps, which can be accessed through the U.S. Geological Survey Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ and the National Weather Service Advanced Hydrologic Prediction Service site at http://water.weather.gov/ahps/inundation.php, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey streamgage at the Mississippi River at Saint Paul (05331000). The National Weather Service forecasted peak-stage information at the streamgage 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 Mississippi River by means of a one-dimensional step-backwater model. The hydraulic model was calibrated using the most recent stage-discharge relation at the Robert Street location (rating curve number 38.0) of the Mississippi River at Saint Paul (streamgage 05331000), as well as an approximate water-surface elevation-discharge relation at the Mississippi River at South Saint Paul (U.S. Army Corps of Engineers streamgage SSPM5). The model also was verified against observed high-water marks from the recent 2011 flood event and the water-surface profile from existing flood insurance studies. The hydraulic model was then used to determine 25 water-surface profiles for flood stages at 1-foot intervals ranging from approximately bankfull stage to greater than the highest recorded stage at streamgage 05331000. The simulated water-surface profiles were then combined with a geographic information system digital elevation model, derived from high-resolution topography data, to delineate potential areas flooded and to determine the water depths within the inundated areas for each stage at streamgage 05331000. The availability of these maps along with information regarding current stage at the U.S. Geological Survey streamgage and forecasted stages from the National Weather Service provides enhanced flood warning and visualization of the potential effects of a forecasted flood for the city of Saint Paul and its residents. The maps also can aid in emergency management planning and response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

  11. 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.

  12. 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.

  13. 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.

  14. USGS Crews Measure Historic Flooding in Fargo, ND

    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. ...

  15. USGS Crews Measure Historic Flooding in Fargo, ND

    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....

  16. Hydrometeorological and climatological conditions associated with flash flooding in the Catskill Mountains, NY

    NASA Astrophysics Data System (ADS)

    Teale, N. G.; Quiring, S. M.

    2014-12-01

    Flash flooding is a concern in watersheds of the New York City Water Supply System, as the turbidity associated with rapid flooding is unacceptable in an unfiltered water supply. Previous studies suggest that flash flooding will occur more frequently in this region in a changing climate. Therefore, a thorough understanding of the conditions associated with flash flooding are important for effective watershed management. Seven flash floods were identified in the hydrologic record for the Neversink River near Claryville, NY from 1 April 1987 through 15 July 2014. Case studies using Weather Prediction Center forecast maps, National Centers for Environmental Prediction/ National Center for Atmospheric Research (NCEP/NCAR) reanalysis daily composites, and co-operative station data were used to characterize each event. Forecast maps indicate synoptic-scale frontal activity concurrent with all flash flood events. The four winter flash flood peaks are associated with rain on existing snowpack, with anomalously warm 1000 mb temperatures and anomalously high precipitation rates. The three summer flash flood peaks are associated with convective activity, high precipitation rates, anomalously warm 1000 mb temperatures, and southerly winds. NCEP/NCAR climate composites for winter and summer flash flood events are consistent with the case studies presented. The frequency of these broad-scale conditions suggest that localized effects of the basin conditions separate flash flood events from other high discharge events. Recognizing these conditions in the context of climate predictions is useful for effective and proactive water management in the region to maintain an unfiltered water supply for the greater New York City area.

  17. 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.

  18. Lessons learned from four years of actively using River Forecast Center Ensemble Streamflow Predictions to inform reservoir management

    NASA Astrophysics Data System (ADS)

    Polebitski, A.; Palmer, R.; Meaker, B.

    2012-12-01

    The National Weather Service's River Forecast Centers (RFCs), located throughout the US, produce operational streamflow forecasts for short term application and long-term lead forecasts at selected locations. These forecasts are targeted for a variety of users, including water supply management, flood control, hydropower production, navigation, and recreation. This presentation highlights the challenges and successes associated with the use of RFC produced ensemble streamflow predictions (ESP) in generating system operations forecasts over the past four years for Snohomish County Public Utility District #1's (SnoPUD) Henry Jackson hydropower system. This research documents a multiyear collaboration between SnoPUD and academic researchers. The collaboration began with a proof of concept study in 2007 and evolved into a weekly decision support activity that has been ongoing since 2008 ( documented in Alemu et al. 2010). The Alemu et al. paper demonstrates the usefulness of ESP forecasts in hydropower operations decision making. This paper focuses on the value of forecasts and a decision support system (DSS) in improving skills in operating reservoir systems. During the application period, the model provided weekly guidance on meeting operational objectives and a probabilistic approach to quantifying system vulnerability during critical periods such as floods and drought. The ESP forecasts and the DSS were heavily used during periods of uncertainty and less so during periods of high system constraint or low system risk.

  19. 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

  20. 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)

  1. Communicating uncertainty in hydrological forecasts: mission impossible?

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  2. 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.

  3. Thirty Years Later: Reflections of the Big Thompson Flood, Colorado, 1976 to 2006

    NASA Astrophysics Data System (ADS)

    Jarrett, R. D.; Costa, J. E.; Brunstein, F. C.; Quesenberry, C. A.; Vandas, S. J.; Capesius, J. P.; O'Neill, G. B.

    2006-12-01

    Thirty years ago, over 300 mm of rain fell in about 4 to 6 hours in the middle reaches of the Big Thompson River Basin during the devastating flash flood on July 31, 1976. The rainstorm produced flood discharges that exceeded 40 m3/s/km2. A peak discharge of 883 m3/s was estimated at the Big Thompson River near Drake streamflow-gaging station. The raging waters left 144 people dead, 250 injured, and over 800 people were evacuated by helicopter. Four-hundred eighteen homes and businesses were destroyed, as well as 438 automobiles, and damage to infrastructure left the canyon reachable only via helicopter. Total damage was estimated in excess of $116 million (2006 dollars). Natural hazards similar to the Big Thompson flood are rare, but the probability of a similar event hitting the Front Range, other parts of Colorado, or other parts of the Nation is real. Although much smaller in scale than the Big Thompson flood, several flash floods have happened during the monsoon in early July 2006 in the Colorado foothills that reemphasized the hazards associated with flash flooding. The U.S. Geological Survey (USGS) conducts flood research to help understand and predict the magnitude and likelihood of large streamflow events such as the Big Thompson flood. A summary of hydrologic conditions of the 1976 flood, what the 1976 flood can teach us about flash floods, a description of some of the advances in USGS flood science as a consequence of this disaster, and lessons that we learned to help reduce loss of life from this extraordinary flash flood are discussed. In the 30 years since the Big Thompson flood, there have been important advances in streamflow monitoring and flood warning. The National Weather Service (NWS) NEXRAD radar allows real-time monitoring of precipitation in most places in the United States. The USGS currently (2006) operates about 7,250 real-time streamflow-gaging stations in the United States that are monitored by the USGS, the NWS, and emergency managers. When substantial flooding occurs, the USGS mobilizes personnel to collect streamflow data in affected areas. Streamflow data improve flood forecasting and provide data for flood-frequency analysis for floodplain management, design of structures located in floodplains, and related water studies. An important lesson learned is that nature provides environmental signs before and during floods that can help people avoid hazard areas. Important contributions to flood science as a result of the 1976 flood include development of paleoflood methods to interpret the preserved flood-plain stratigraphy to document the number, magnitude, and age of floods that occurred prior to streamflow monitoring. These methods and data on large floods can be used in many mountain-river systems to help us better understand flood hazards and plan for the future. For example, according to conventional flood-frequency analysis, the 1976 Big Thompson flood had a flood recurrence interval of about 100 years. However, paleoflood research indicated the 1976 flood was the largest in about the last 10,000 years in the basin and had a flood recurrence interval in excess of 1,000 years.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. Post Processing Numerical Weather Prediction Model Rainfall Forecasts for Use in Ensemble Streamflow Forecasting in Australia

    NASA Astrophysics Data System (ADS)

    Shrestha, D. L.; Robertson, D.; Bennett, J.; Ward, P.; Wang, Q. J.

    2012-12-01

    Through the water information research and development alliance (WIRADA) project, CSIRO is conducting research to improve flood and short-term streamflow forecasting services delivered by the Australian Bureau of Meteorology. WIRADA aims to build and test systems to generate ensemble flood and short-term streamflow forecasts with lead times of up to 10 days by integrating rainfall forecasts from Numerical Weather Prediction (NWP) models and hydrological modelling. Here we present an overview of the latest progress towards developing this system. Rainfall during the forecast period is a major source of uncertainty in streamflow forecasting. Ensemble rainfall forecasts are used in streamflow forecasting to characterise the rainfall uncertainty. In Australia, NWP models provide forecasts of rainfall and other weather conditions for lead times of up to 10 days. However, rainfall forecasts from Australian NWP models are deterministic and often contain systematic errors. We use a simplified Bayesian joint probability (BJP) method to post-process rainfall forecasts from the latest generation of Australian NWP models. The BJP method generates reliable and skilful ensemble rainfall forecasts. The post-processed rainfall ensembles are then used to force a semi-distributed conceptual rainfall runoff model to produce ensemble streamflow forecasts. The performance of the ensemble streamflow forecasts is evaluated on a number of Australian catchments and the benefits of using post processed rainfall forecasts are demonstrated.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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).

  14. A methodology for urban flood resilience assessment

    NASA Astrophysics Data System (ADS)

    Lhomme, Serge; Serre, Damien; Diab, Youssef; Laganier, Richard

    2010-05-01

    In Europe, river floods have been increasing in frequency and severity [Szöllösi-Nagy and Zevenbergen, 2005]. Moreover, climate change is expected to exacerbate the frequency and intensity of hydro meteorological disaster [IPCC, 2007]. Despite efforts made to maintain the flood defense assets, we often observe levee failures leading to finally increase flood risk in protected area. Furthermore, flood forecasting models, although benefiting continuous improvements, remain partly inaccurate due to uncertainties arising all along data calculation processes. In the same time, the year 2007 marks a turning point in history: half of the world population now lives in cities (UN-Habitat, 2007). Moreover, the total urban population is expected to double from two to four billion over the next 30 to 35 years (United Nations, 2006). This growing rate is equivalent to the creation of a new city of one million inhabitants every week, and this during the next four decades [Flood resilience Group]. So, this quick urban development coupled with technical failures and climate change have increased flood risk and corresponding challenges to urban flood risk management [Ashley et al., 2007], [Nie et al., 2009]. These circumstances oblige to manage flood risk by integrating new concepts like urban resilience. In recent years, resilience has become a central concept for risk management. This concept has emerged because a more resilient system is less vulnerable to risk and, therefore, more sustainable [Serre et al., 2010]. But urban flood resilience is a concept that has not yet been directly assessed. Therefore, when decision makers decide to use the resilience concept to manage urban flood, they have no tool to help them. That is why this paper proposes a methodology to assess urban flood resilience in order to make this concept operational. Networks affect the well-being of the people and the smooth functioning of services and, more generally, of economical activities. Yet, multiple networks that innervate the city are particularly sensitive to flooding, through their structures and geographic constraints. Because societal functions are highly dependent on networked systems and the operability of these systems can be vulnerable to disasters, there is a need to understand how networked systems are resilient. That is why, considering that networks can be regarded as the "flood gateway" [Lhomme et al., 2009], we will focus on the resilience assessment of these critical networks before urban resilience assessment. The first part of this paper introduce resilience concept to well understand the importance of this concept to manage flood risk and of assessing this resilience. In a second part, this paper presents the use of safety methods to model network system dysfunctions during flood and then to produce resilience indicators. Finally it presents use of graph theory to assess adaptive capacity of these networks. These researches are the first steps toward the development of a GIS tool to optimize preparedness and recovery after a flood event.

  15. 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.

  16. Some Thoughts about the Flood and First Nations Education in the Yukon.

    ERIC Educational Resources Information Center

    McDonald, Linda

    1994-01-01

    Examines the complexities of postsecondary education for First Nations people in the Yukon. Discusses the importance of maintaining a balance between mainstream and traditional educational goals and values, the role of northern colleges in overcoming the deficiencies of public schooling, and the development of culturally relevant programming at…

  17. 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.

  18. Cyber surveillance for flood disasters.

    PubMed

    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

  19. 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

  20. Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

    NASA Astrophysics Data System (ADS)

    Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

    2013-12-01

    Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail end of high flow periods. These improvements allowed DEP to more effectively manage water quality control and spill mitigation operations immediately after storm events. Later on, post-processed hydrologic forecasts from the National Weather Service (NWS) including the Advanced Hydrologic Prediction Service (AHPS) and the Hydrologic Ensemble Forecast Service (HEFS) were implemented into OST. These forecasts further increased the predictive skill over the initial statistical models as current basin conditions (e.g. soil moisture, snowpack) and meteorological forecasts (with HEFS) are now explicitly represented. With the post-processed HEFS forecasts, DEP may now truly quantify impacts associated with wet weather events on the horizon, rather than relying on statistical representations of current hydrologic trends. This presentation will highlight the benefits of the improved forecasts using examples from actual system operations.

  1. 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.

  2. 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.

  3. 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)

  4. 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.

  5. 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.

  6. 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.

  7. Flood-inundation maps for the Saddle River from Rochelle Park to Lodi, New Jersey, 2012

    USGS Publications Warehouse

    Hoppe, Heidi L.; Watson, Kara M.

    2012-01-01

    Digital flood-inundation maps for a 2.75-mile reach of the Saddle River from 0.2 mile upstream from the Interstate 80 bridge in Rochelle Park to 1.5 miles downstream from the U.S. Route 46 bridge in Lodi, New Jersey, were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection (NJDEP). 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 Saddle River at Lodi, New Jersey (station 01391500). 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/nwis/uv?site_no=01391500. The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated 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 using the most current stage-discharge relations at the Saddle River at Lodi, New Jersey streamgage and documented high-water marks from recent floods. The hydraulic model was then used to determine 11 water-surface profiles for flood stages at the Saddle River streamgage at 1-ft intervals referenced to the streamgage datum, North American Vertical Datum of 1988 (NAVD 88), and ranging from bankfull, 0.5 ft below NWS Action Stage, to the extent of the stage-discharge rating, which is approximately 1 ft higher than the highest recorded water level at the streamgage. Action Stage is the stage which when reached by a rising stream the NWS or a partner needs to take some type of mitigation action in preparation for possible significant hydrologic activity. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84-ft) 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 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.

  8. 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.

  9. 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.

  10. 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.

  11. Real-time flash flood prediction system in the United States

    NASA Astrophysics Data System (ADS)

    Gourley, Jonathan; Flamig, Zachary; Vergara, Humberto; Clark, Robert; Kirstetter, Pierre; Terti, Galatia; Hong, Yang; Howard, Kenneth

    2015-04-01

    This study describes the Flooded Locations and Simulated Hydrographs (FLASH) project in the U.S. that has been designed to develop, evaluate, and transition the latest rainfall-driven flash flood prediction tools to the National Weather Service (NWS). The FLASH system is based on radar-based rainfall estimates from the Multi-Radar Multi-Sensor (MRMS) system, providing mosaicked rainfall rates at 1-km/2-min resolution across the conterminous U.S. Products include rainfall average recurrence intervals (ARIs), ratios of rainfall to flash flood guidance (FFG) values, and simulated streamflow ARIs from a distributed hydrologic modeling framework. NWS forecasters evaluated each of these experimental tools during the inaugural Hazardous Weather Testbed Hydrology experiment (HWT-Hydro) in the summer of 2014. In additional to a subjective evaluation from HWT-Hydro, we present findings from an objective evaluation of the distributed hydrologic modeling approaches that incorporate recent developments in a-priori parameter estimation, improvements in channel routing and model physics, model reanalysis leveraging datasets from the Multi-Year Reanalysis Of Remotely-Sensed Storms (MYRORSS) project, and error models developed for output products. FLASH skill is assessed using a very large dataset of observed flooding as measured by US Geologic Survey (USGS) stream gauges. In addition to the evaluation, this presentation will provide an overview of the latest advances in the FLASH project including forthcoming impact-specific products, probabilistic forecasts, and forcing from short-term precipitation forecasts.

  12. Multi-scale model analysis and hindcast of the 2013 Colorado Flood

    NASA Astrophysics Data System (ADS)

    Gochis, David; Yu, Wei; Sampson, Kevin; Dugger, Aubrey; McCreight, James; Zhang, Yongxin; Ikeda, Kyoko

    2015-04-01

    While the generation of most flood and flash flood events is fundamentally linked to the occurrence of heavy rainfall, the physical mechanisms responsible for translating rainfall into floods are complex and manifold. These runoff generation processes evolve over many spatial and temporal scales during the course of flooding events. As such robust flood and flash flood prediction systems need to account for multitude of terrestrial processes occurring over a wide range of space and time scales. One such extreme multiscale flood event was the 2013 Colorado Flood in which over 400 mm of rainfall fell along the Rock Mountain mountain front region over the course of a few days. The flooding impacts from this heavy rainfall event included not only high, fast flows in steep mountain streams but also included large areas of inundation on the adjacent plains and numerous soil saturation excess impacts such as hillslope failures and groundwater intrusions into domestic structures. A multi-scale and multi-process evaluation of this flood event is performed using the community WRF-Hydro modeling system. We incorporate several operational quantitative precipitation estimate and quantitative precipitation forecast products in the analysis and document the skill of multiple configurations of WRF-Hydro physics options across a range of contributing area length scales. Emphasis is placed on assessing how well the different model configurations capture the multi-scale streamflow response from small headwater catchments out to the entire South Platte River basin whose total contributing area exceeds 25,000 sq km. In addition to streamflow we also present evaluations of event simulations and hindcasts of soil saturation fraction, groundwater levels and inundated areas as a means of assessing different runoff generation mechanisms. Finally, results from a U.S. national-scale, fully-coupled hydrometeorological hindcast of the 2013 Colorado flood event using the combined WRF atmospheric model and WRF-Hydro system will be shown.

  13. 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.

  14. Flood-inundation maps for the DuPage River from Plainfield to Shorewood, Illinois, 2013

    USGS Publications Warehouse

    Murphy, Elizabeth A.; Sharpe, Jennifer B.

    2013-01-01

    Digital flood-inundation maps for a 15.5-mi reach of the DuPage River from Plainfield to Shorewood, Illinois, were created by the U.S. Geological Survey (USGS) in cooperation with the Will County Stormwater Management Planning Committee. 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 (gage heights or stages) at the USGS streamgage at DuPage River at Shorewood, Illinois (sta. no. 05540500). Current conditions at the USGS streamgage may be obtained on the Internet at http://waterdata.usgs.gov/usa/nwis/uv?05540500. 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. The NWS-forecasted peak-stage information, also shown on the DuPage River at Shorewood inundation Web site, 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 hydraulic model was then used to determine nine water-surface profiles for flood stages at 1-ft intervals referenced to the streamgage datum and ranging from NWS Action stage of 6 ft to the historic crest of 14.0 ft. The simulated water-surface profiles were then combined with a Digital Elevation Model (DEM) (derived from Light Detection And Ranging (LiDAR) data) by using a Geographic Information System (GIS) in order to delineate the area flooded at each water level. These maps, along with information on the Internet regarding current gage height 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 postflood recovery efforts.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. How much are you prepared to PAY for a forecast?

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  2. Verification of Advances in a Coupled Snow-runoff Modeling Framework for Operational Streamflow Forecasts

    NASA Astrophysics Data System (ADS)

    Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

    2011-12-01

    The National Oceanic and Atmospheric Administration's (NOAA's) River Forecast Centers (RFCs) issue hydrologic forecasts related to flood events, reservoir operations for water supply, streamflow regulation, and recreation on the nation's streams and rivers. The RFCs use the National Weather Service River Forecast System (NWSRFS) for streamflow forecasting which relies on a coupled snow model (i.e. SNOW17) and rainfall-runoff model (i.e. SAC-SMA) in snow-dominated regions of the US. Errors arise in various steps of the forecasting system from input data, model structure, model parameters, and initial states. The goal of the current study is to undertake verification of potential improvements in the SNOW17-SAC-SMA modeling framework developed for operational streamflow forecasts. We undertake verification for a range of parameters sets (i.e. RFC, DREAM (Differential Evolution Adaptive Metropolis)) as well as a data assimilation (DA) framework developed for the coupled models. Verification is also undertaken for various initial conditions to observe the influence of variability in initial conditions on the forecast. The study basin is the North Fork America River Basin (NFARB) located on the western side of the Sierra Nevada Mountains in northern California. Hindcasts are verified using both deterministic (i.e. Nash Sutcliffe efficiency, root mean square error, and joint distribution) and probabilistic (i.e. reliability diagram, discrimination diagram, containing ratio, and Quantile plots) statistics. Our presentation includes comparison of the performance of different optimized parameters and the DA framework as well as assessment of the impact associated with the initial conditions used for streamflow forecasts for the NFARB.

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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

  9. 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.

  10. Flood-inundation maps for a nine-mile reach of the Des Plaines River from Riverwoods to Mettawa, Illinois

    USGS Publications Warehouse

    Murphy, Elizabeth A.; Soong, David T.; Sharpe, Jennifer B.

    2012-01-01

    Digital flood-inundation maps for a 9-mile reach of the Des Plaines River from Riverwoods to Mettawa, Illinois, were created by the U.S. Geological Survey (USGS) in cooperation with the Lake County Stormwater Management Commission and the Villages of Lincolnshire and Riverwoods. 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 (gage heights) at the USGS streamgage at Des Plaines River at Lincolnshire, Illinois (station no. 05528100). Current conditions at the USGS streamgage may be obtained on the Internet at http://waterdata.usgs.gov/usa/nwis/uv?05528100. In addition, this streamgage is incorporated into the Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/) by the National Weather Service (NWS). The NWS forecasts flood hydrographs at many places that are often co-located at USGS streamgages. The NWS forecasted peak-stage information, also shown on the Des Plaines River at Lincolnshire inundation Web site, 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 hydraulic model was then used to determine seven water-surface profiles for flood stages at roughly 1-ft intervals referenced to the streamgage datum and ranging from the 50- to 0.2-percent annual exceedance probability flows. 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) in order to delineate the area flooded at each water level. These maps, along with information on the Internet regarding current gage height 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.

  11. 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.

  12. Comparing Postprocessing Approaches to Calibrating Operational River Discharge Forecasts

    NASA Astrophysics Data System (ADS)

    Hopson, T. M.; Webster, P. J.; Wood, A. W.

    2010-12-01

    With rare exceptions, current operational ensemble weather and hydrologic forecast systems require a final post-processing step to steer the forecast products towards satisfying the twin constraints of greater reliability while retaining (or enhancing) forecast sharpness. Such post-processing of model output can be viewed as an extension of the modeling effort itself, such as in the case of under-dispersive ensemble forecasts, where post-processing of the ensemble dispersion can implicitly account for missing scales of variability or mis-representation of physical processes. Over the last decade a number of different approaches have emerged that show consistent utility in calibrating ensembles derived from a variety of forecasting systems. In this work we compare and contrast four such approaches under differing operational constraints (e.g. data size limitations): logistic regression, an analogue approach, Bayesian model averaging, and quantile regression. The setting for this study is the Climate Forecasting Applications for Bangladesh (CFAB) forecast system, which over the last decade has been providing operational probabilistic forecasts of severe flooding of the Brahmaputra and Ganges Rivers as part of a humanitarian effort to mitigate the impacts of these events on the country of Bangladesh. The flood forecasting system developed utilizes weather forecast uncertainty information provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble weather forecasts, rain gauge and satellite-derived precipitation estimates from NASA and NOAA, along with near-real-time river stage observations provided by the Flood Forecasting and Warning Centre of Bangladesh. This paper will discuss both the results of the post-processing comparison study more generally, and also within the unique context of this ongoing flood forecasting effort for Bangladesh.

  13. Operational data flow between hydrological forecasting systems

    NASA Astrophysics Data System (ADS)

    Davids, Femke; de Kleermaeker, Simone; van Loenen, Arnejan; Gijsbers, Peter; Bogaard, Tom; Twigt, Daniel; Heynert, Karel

    2014-05-01

    One of the major challenges in operational forecasting is organizing and controlling the flow of data. In the Water Management Centre for the Netherlands several FEWS (Flood Early Warning Systems) have been set up for operational use. The six systems specialize in different areas, namely i) fluvial flooding, ii) water distribution during droughts, iii) real time control of canal water levels and gauges, iv) coastal flooding, v) lake management and flooding and vi) water management in the delta area. These systems obtain data partly from the same but also from different data sources. Each individual system uses (different) models and pre and post processing steps that have been optimized for the most important parameters. It is crucial to exchange data and forecasts in an efficient way between the systems, for example to use as boundaries in model runs. This paper will describe the methods and challenges that we face in organizing the data flow between these systems.

  14. Downscaling Extended Weather Forecasts for Hydrologic Prediction

    SciTech Connect

    Leung, Lai-Yung R.; Qian, Yun

    2005-03-01

    Weather and climate forecasts are critical inputs to hydrologic forecasting systems. The National Center for Environmental Prediction (NCEP) issues 8-15 days outlook daily for the U.S. based on the Medium Range Forecast (MRF) model, which is a global model applied at about 2? spatial resolution. Because of the relatively coarse spatial resolution, weather forecasts produced by the MRF model cannot be applied directly to hydrologic forecasting models that require high spatial resolution to represent land surface hydrology. A mesoscale atmospheric model was used to dynamically downscale the 1-8 day extended global weather forecasts to test the feasibility of hydrologic forecasting through this model nesting approach. Atmospheric conditions of each 8-day forecast during the period 1990-2000 were used to provide initial and boundary conditions for the mesoscale model to produce an 8-day atmospheric forecast for the western U.S. at 30 km spatial resolution. To examine the impact of initialization of the land surface state on forecast skill, two sets of simulations were performed with the land surface state initialized based on the global forecasts versus land surface conditions from a continuous mesoscale simulation driven by the NCEP reanalysis. Comparison of the skill of the global and downscaled precipitation forecasts in the western U.S. showed higher skill for the downscaled forecasts at all precipitation thresholds and increasingly larger differences at the larger thresholds. Analyses of the surface temperature forecasts show that the mesoscale forecasts generally reduced the root-mean-square error by about 1.5 C compared to the global forecasts, because of the much better resolved topography at 30 km spatial resolution. In addition, initialization of the land surface states has large impacts on the temperature forecasts, but not the precipitation forecasts. The improvements in forecast skill using downscaling could be potentially significant for improving hydrologic forecasts for managing river basins.

  15. Is It Going to Rain Today? Understanding the Weather Forecast.

    ERIC Educational Resources Information Center

    Allsopp, Jim; And Others

    1996-01-01

    Presents a resource for science teachers to develop a better understanding of weather forecasts, including outlooks, watches, warnings, advisories, severe local storms, winter storms, floods, hurricanes, nonprecipitation hazards, precipitation probabilities, sky condition, and UV index. (MKR)

  16. Examining Atmospheric and Ecological Drivers of Wildfires, Modeling Wildfire Occurrence in the Southwest United States, and Using Atmospheric Sounding Observations to Verify National Weather Service Spot Forecasts

    NASA Astrophysics Data System (ADS)

    Nauslar, Nicholas J.

    This dissertation is comprised of three different papers that all pertain to wildland fire applications. The first paper performs a verification analysis on mixing height, transport winds, and Haines Index from National Weather Service spot forecasts across the United States. The final two papers, which are closely related, examine atmospheric and ecological drivers of wildfire for the Southwest Area (SWA) (Arizona, New Mexico, west Texas, and Oklahoma panhandle) to better equip operational fire meteorologists and managers to make informed decisions on wildfire potential in this region. The verification analysis here utilizes NWS spot forecasts of mixing height, transport winds and Haines Index from 2009-2013 issued for a location within 50 km of an upper sounding location and valid for the day of the fire event. Mixing height was calculated from the 0000 UTC sounding via the Stull, Holzworth, and Richardson methods. Transport wind speeds were determined by averaging the wind speed through the boundary layer as determined by the three mixing height methods from the 0000 UTC sounding. Haines Index was calculated at low, mid, and high elevation based on the elevation of the sounding and spot forecast locations. Mixing height forecasts exhibited large mean absolute errors and biased towards over forecasting. Forecasts of transport wind speeds and Haines Index outperformed mixing height forecasts with smaller errors relative to their respective means. The rainfall and lightning associated with the North American Monsoon (NAM) can vary greatly intra- and inter-annually and has a large impact on wildfire activity across the SWA by igniting or suppressing wildfires. NAM onset thresholds and subsequent dates are determined for the SWA and each Predictive Service Area (PSA), which are sub-regions used by operational fire meteorologists to predict wildfire potential within the SWA, April through September from 1995-2013. Various wildfire activity thresholds using the number of wildfires and large wildfires identified days or time periods with increased wildfire activity for each PSA and the SWA. Self-organizing maps utilizing 500 and 700 hPa geopotential heights and precipitable water were implemented to identify atmospheric patterns contributing to the NAM onset and busy days/periods for each PSA and the SWA. Resulting SOM map types also showed the transition to, during, and from the NAM. Northward and eastward displacements of the subtropical ridge (i.e., four-corners high) over the SWA were associated with NAM onset, and a suppressed subtropical ridge and breakdown of the subtropical ridge map types over the SWA were associated with increased wildfire activity. We implemented boosted regression trees (BRT) to model wildfire occurrence for all and large wildfires for different wildfire types (i.e., lightning, human) across the SWA by PSA. BRT models for all wildfires demonstrated relatively small mean and mean absolute errors and showed better predictability on days with wildfires. Cross-validated accuracy assessments for large wildfires demonstrated the ability to discriminate between large wildfire and non-large wildfire days across all wildfire types. Measurements describing fuel conditions (i.e., 100 and 1000-hour dead fuel moisture, energy release component) were the most important predictors when considering all wildfire types and sizes. However, a combination of fuels and atmospheric predictors (i.e., lightning, temperature) proved most predictive for large wildfire occurrence, and the number of relevant predictors increases for large wildfires indicating more conditions need to align to support large wildfires.

  17. 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.

  18. 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.

  19. Flood risk and flood management

    NASA Astrophysics Data System (ADS)

    Plate, Erich J.

    2002-10-01

    Risk management has been established as a well defined procedure for handling risks due to natural, environmental or man made hazards, of which floods are representative. Risk management has been discussed in many previous papers giving different meanings to the term—a result of the fact that risk management actually takes place on three different levels of actions: the operational level, which is associated with operating an existing system, a project planning level, which is used when a new, or a revision of an existing project is planned, and a project design level, which is embedded into the second level and describes the process of reaching an optimal solution for the project. The first two levels will be briefly described in the paper. It will be emphasized that the transition from the first to the second level is a dynamic process. As the value system of a nation changes, and as the natural boundary conditions are modified by human actions or global changes, an existing system will be found not meeting the demands of the present society, and actions on the second level are initiated. The decisions for change depend on the changes in options available for handling a flood situation, as well as on the changes in risk perception and attitudes towards risk. On the third level, the actual cost of a design are evaluated and compared with the benefits obtained from the planned project. In particular, on this level the residual risk is considered, i.e. the risk which remains even after a project is completed and fully operational.

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. Utility of flood warning systems for emergency management

    NASA Astrophysics Data System (ADS)

    Molinari, Daniela; Ballio, Francesco; Menoni, Scira

    2010-05-01

    The presentation is focused on a simple and crucial question for warning systems: are flood and hydrological modelling and forecasting helpful to manage flood events? Indeed, it is well known that a warning process can be invalidated by inadequate forecasts so that the accuracy and robustness of the previsional model is a key issue for any flood warning procedure. However, one problem still arises at this perspective: when forecasts can be considered to be adequate? According to Murphy (1993, Wea. Forecasting 8, 281-293), forecasts hold no intrinsic value but they acquire it through their ability to influence the decisions made by their users. Moreover, we can add that forecasts value depends on the particular problem at stake showing, this way, a multifaceted nature. As a result, forecasts verification should not be seen as a universal process, instead it should be tailored to the particular context in which forecasts are implemented. This presentation focuses on warning problems in mountain regions, whereas the short time which is distinctive of flood events makes the provision of adequate forecasts particularly significant. In this context, the quality of a forecast is linked to its capability to reduce the impact of a flood by improving the correctness of the decision about issuing (or not) a warning as well as of the implementation of a proper set of actions aimed at lowering potential flood damages. The present study evaluates the performance of a real flood forecasting system from this perspective. In detail, a back analysis of past flood events and available verification tools have been implemented. The final objective was to evaluate the system ability to support appropriate decisions with respect not only to the flood characteristics but also to the peculiarities of the area at risk as well as to the uncertainty of forecasts. This meant to consider also flood damages and forecasting uncertainty among the decision variables. Last but not least, the presentation explains how the procedure implemented in the case study could support the definition of a proper warning rule.

  9. 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.

  10. Hydrologic Forecasting and Hydropower Production

    NASA Astrophysics Data System (ADS)

    Wigmosta, M. S.; Voisin, N.; Lettenmaier, D. P.; Coleman, A.; Mishra, V.; Schaner, N. A.

    2011-12-01

    Hydroelectric power production is one of many competing demands for available water along with other priority uses such as irrigation, thermoelectric cooling, municipal, recreation, and environmental performance. Increasingly, hydroelectric generation is being used to offset the intermittent nature of some renewable energy sources such as wind-generated power. An accurate forecast of the magnitude and timing of water supply assists managers in integrated planning and operations to balance competing water uses against current and future supply while protecting against the possibility of water or energy shortages and excesses with real-time actions. We present a medium-range to seasonal ensemble streamflow forecasting system where uncertainty in forecasts is addressed explicitly. The integrated forecast system makes use of remotely-sensed data and automated spatial and temporal data assimilation. Remotely-sensed snow cover, observed snow water equivalent, and observed streamflow data are used to update the hydrologic model state prior to the forecast. In forecast mode, the hydrology model is forced by calibrated ensemble weather/climate forecasts. This system will be fully integrated into a water optimization toolset to inform reservoir and power operations, and guide environmental performance decision making. This flow forecast system development is carried out in agreement with the National Weather Service so that the system can later be incorporated into the NOAA eXperimental Ensemble Forecast Service (XEFS).

  11. 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.

  12. Forecast Impact Simulation Studies

    NASA Technical Reports Server (NTRS)

    Atlas, R.; Kalnay, E.; Baker, W. E.; Susskind, J.; Reuter, D.; Halem, M.

    1985-01-01