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1

Real-time flood forecasting  

USGS Publications Warehouse

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.

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

2009-01-01

2

Flood Forecasting Case Study: International Edition  

NSDL National Science Digital Library

This module allows users to explore the flood forecasting process by assuming the role of a visiting hydrologist intern at the National Hydrologic Service in Main Country. Fictional senior hydrologists guide the intern through an idealized flooding event that takes place over Main Country's Mainstem river basin and its tributary basins, each with varying landscapes and observation systems. Users will examine how these variations impact the quality and type of forecast that can be achieved. Users will also learn about common problems encountered in flood forecasting, and how to adjust forecasts accordingly. This module is intended for a diverse audience that uses a variety of observing and computing technologies, and builds upon material covered in the foundation topics of the International Basic Hydrologic Sciences Course. These core foundation topics are recommended as a prerequisite since this module assumes some pre-existing knowledge of hydrologic principles.

Comet

2011-05-17

3

Forecaster priorities for improving probabilistic flood forecasts  

NASA Astrophysics Data System (ADS)

Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by European hydrometeorological agencies. The most obvious advantage of HEPS is that more of the uncertainty in the modelling system can be assessed. In addition, ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the physical and technical aspects of the model systems, such as increased resolution in time and space and better description of physical processes. Developments like these are certainly needed; however, in this paper we argue that there are other areas of HEPS that need urgent attention. This was also the result from a group exercise and a survey conducted to operational forecasters within the European Flood Awareness System (EFAS) to identify the top priorities of improvement regarding their own system. They turned out to span a range of areas, the most popular being to include verification of an assessment of past forecast performance, a multi-model approach for hydrological modelling, to increase the forecast skill on the medium range (>3 days) and more focus on education and training on the interpretation of forecasts. In light of limited resources, we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them. This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement of EFAS in particular and to spur the development of operational HEPS in general.

Wetterhall, Fredrik; Pappenberger, Florian; Alfieri, Lorenzo; Cloke, Hannah; Thielen, Jutta

2014-05-01

4

Advances in Global Flood Forecasting Systems  

NASA Astrophysics Data System (ADS)

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.

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

2012-12-01

5

FLOODRELIEF - INTERNET-BASED FLOOD FORECASTING DECISION SUPPORT  

Microsoft Academic Search

Flood forecasting specialists and operational water managers require ready access to a wide range of information including both current and forecasted meteorological conditions, and current and forecasted hydrological conditions to make decisions to initiate flood response measures or to issue flood warnings. Effective flood forecasting systems must provide reliable, accurate and timely forecasts for a range of catchments; from small

M. B. Butts; A. Klinting; M. Ivan; J. K. Larsen; J. Hartnack; J. Brandt

6

A pan-African Flood Forecasting System  

NASA Astrophysics Data System (ADS)

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 paper the predictive capability is investigated in a hindcast mode, by reproducing hydrological predictions for the year 2003 where important floods were observed. Results were verified with ground measurements of 36 subcatchments as well as with reports of various flood archives. 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. The case study for "Save flooding" 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 large potential as an operational pan-African flood forecasting system, although issues related to the practical implication will still need to be investigated.

Thiemig, V.; Bisselink, B.; Pappenberger, F.; Thielen, J.

2014-05-01

7

Flood forecasting for Tucurui Hydroelectrical Plant, Brazil  

SciTech Connect

The construction of the Tucurui Hydroelectric Plant on the Tocantins River basin in Brazil requires flood forecasting to ensure the safety of the cofferdam. The latter has been initially designed for a flood with a return frequency of one in 25 years. Lack of adequate forecasting facilities during the earlier stages of construction has resulted in significant damages and construction delays. Statistical forecasting models were developed by Projeto de Hidrologia y Climatologie da Amazonia (PHCA) for the purpose of preventing further damage at the site. The application of these models during the 1980 flood season, when the highest flood on record occurred at the Tucurui site, proved of great assistance in preventing the flooding of the cofferdam. In conjunction with the development of these models a number of data collection platforms using data transmission through the GOES system were installed to provide the data required for forecasting.

Solomon, S.I.; Basso, E.; Osorio, C.; Melo de Moraes, H.; Serrano, A.

1986-04-01

8

Forecasting Extreme Flooding in South Asia (Invited)  

NASA Astrophysics Data System (ADS)

In most years there is extensive flooding across India, Pakistan and Bangladesh. On average, 40 million people are displaced by floods in India and half that many again in Bangladesh. Occasionally, even more extensive and severe flooding occurs across South Asia. In 2007 and 2008 the Brahmaputra flooded three times causing severe disruption of commerce, agriculture and life in general. Systems set up by an international collaboration predicted these Bangladesh floods with an operational system at the 10 and 15-day horizon. These forecasts determined the risk of flooding and allowed the Bangladeshis in peril to prepare, harvesting crops and storing of household and agricultural assets. Savings in increments of annual income resulted form the forecasts. In July and August 2010, severe flooding occurred in Pakistan causing horrendous damage and loss of life. But these floods were also predictable at the 10-day time scale if the same forecasting system developed for Bangladesh had been implemented. Similar systems could be implemented in India but would require local cooperation. We describe the manner in which quantified probabilistic precipitation forecasts, coupled with hydrological models can provide useful and timely extended warnings of flooding.

Webster, P. J.

2010-12-01

9

Flood Forecasting in River System Using ANFIS  

NASA Astrophysics Data System (ADS)

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.

Ullah, Nazrin; Choudhury, P.

2010-10-01

10

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

NASA Astrophysics Data System (ADS)

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.

Bao, Hongjun; Zhao, Linna

2012-02-01

11

A comparison of nonlinear flood forecasting methods  

NASA Astrophysics Data System (ADS)

Two nonlinear models, nonlinear prediction (NLP) and artificial neural networks (ANN), are compared for multivariate flood forecasting. For NLP the calibration of the locally linear model is quite simple, while for ANN the validation and identification of the model can be cumbersome, mainly because of overfitting. Very good results are obtained with the two methods: NLP performs slightly better at short forecast times while the situation is reversed for longer times.

Laio, F.; Porporato, A.; Revelli, R.; Ridolfi, L.

2003-05-01

12

Probabilistic Flash Flood Forecasting using Stormscale Ensembles  

NASA Astrophysics Data System (ADS)

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.

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

2013-12-01

13

Ensemble flood forecasting on the Tocantins River - Brazil  

NASA Astrophysics Data System (ADS)

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.

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

2014-05-01

14

Timetable of an operational flood forecasting system  

NASA Astrophysics Data System (ADS)

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

Liechti, Katharina; Jaun, Simon; Zappa, Massimiliano

2010-05-01

15

Real-time application of meteorological ensembles for Danube flood forecasting  

NASA Astrophysics Data System (ADS)

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.

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

2009-04-01

16

Application and improvement of BFS in Flood forecasting  

NASA Astrophysics Data System (ADS)

Application and improvement of BFS in Flood forecasting Since the existence of flood forecasting uncertainties have been widely accepted gradually recently, how to quantitatively describe these uncertainties and achieve probabilistic forecasting becomes a hot topic. To realize probabilistic flood forecasting, the hydrologic uncertainty processor (HUP) within Bayesian forecasting system (BFS) was employed to investigate the hydrologic forecasting uncertainties in the article, and then probabilistic flood forecasting was realized. As a determinate hydrological model, Xin'anjiang model which is widespreadly applied in humid region was used to yield initial discharge forecasting series, meanwhile, the posterior distribution of discharge could be solved with selected prior distribution and likelihood function based on Bayesian theory, then, the probabilistic flood forecasting results at any time during the duration of flood hydrograph could be obtained according to the posterior distribution of discharge. It needs to point out that the method can not only achieve a good precision but also provide rich uncertainty information such as average, variance, quantile of different confidence interval and so on. In research or practice, the mean value of posterior distribution of discharge is always adopted as the final forecasting result. Analyzing the statistical characteristic of the ultimate forecasting results, a law that the forecasting precision is higher when the discharge magnitude is large was discovered. To overcome the disadvantage that forecasting accuracy is lower in the case of small discharge magnitude, according to the magnitude of the forecasting results, an improvement method of which kernel is selected two kinds of likelihood functions for different magnitudes discharge series to deduce posterior distribution was proposed. As an example, finally, BFS was applied to the probabilistic flood forecasting for MiSai basin in south of China, It indicates that BFS can improve forecasting accuracy appropriately and the improvement method of BFS is effective. Furthermore, the improved BFS can achieve a better precision when the discharge magnitude is small.

Wang, J.; Liang, Z.; Hu, Y.

2012-04-01

17

Flood Hazards - A National Threat  

NSDL National Science Digital Library

This USGS Fact Sheet (2006-3026) illustrates the national scope of the risk of flooding events in the US. The vast majority of counties have experienced at least one presidential disaster declaration related to flooding since 1965. The fact sheet examines the risks and how USGS scientists are studying floods in order to reduce future risks to the US population, property, and infrastructure.

Usgs

18

Operational flood forecasting system of Umbria Region "Functional Centre  

NASA Astrophysics Data System (ADS)

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

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

2009-04-01

19

Mapping Coastal Flood Zones for the National Flood Insurance Program  

Microsoft Academic Search

The National Flood Insurance Program (NFIP) was created by Congress in 1968, and significantly amended in 1973 to reduce loss of life and property caused by flooding, reduce disaster relief costs caused by flooding and make Federally backed flood insurance available to property owners. These goals were to be achieved by requiring building to be built to resist flood damages,

D. Carlton; C. L. Cook; J. Weber

2004-01-01

20

Seasonal Flood Forecasts and Dynamic Flood Risk Management  

Microsoft Academic Search

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

S. Arumugam; U. Lall

2004-01-01

21

A Stochastic-Dynamic Model for Real Time Flood Forecasting  

NASA Astrophysics Data System (ADS)

A stochastic-dynamic model for real time flood forecasting was developed using Box-Jenkins modelling techniques. The purpose of the forecasting system is to forecast flood levels of the Saint John River at Fredericton, New Brunswick. The model consists of two submodels: an upstream model used to forecast the headpond level at the Mactaquac Dam and a downstream model to forecast the water level at Fredericton. Inputs to the system are recorded values of the water level at East Florenceville, the headpond level and gate position at Mactaquac, and the water level at Fredericton. The model was calibrated for the spring floods of 1973, 1974, 1977, and 1978, and its usefulness was verified for the 1979 flood. The forecasting results indicated that the stochastic-dynamic model produces reasonably accurate forecasts for lead times up to two days. These forecasts were then compared to those from the existing forecasting system and were found to be as reliable as those from the existing system.

Chow, K. C. A.; Watt, W. E.; Watts, D. G.

1983-06-01

22

Short-term Ensemble Flood Forecasting Experiments in Brazil  

NASA Astrophysics Data System (ADS)

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 simpli?ed 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 São 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.

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

2013-04-01

23

Forecasting Severe Floods for the Meghna River Basin  

NASA Astrophysics Data System (ADS)

Accurate prediction of extreme floods in Bangladesh is vital for the agricultural practices and planning in the region, and to provide warnings for evacuation in case of flooding. Hopson and Webster (2010) developed and implemented a short-term flood forecasting scheme in Bangladesh for the Ganges and Brahmaputra basins that performs significantly better than the climatological and persistence forecasts at all lead times. Probabilistic forecast of river discharge at two entry points into Bangladesh of the Ganges and Brahmaputra rivers was developed using a hydrologic multimodel initialized by NASA and NOAA rainfall products, whose fluxes were forecasted forward using calibrated ECMWF ensemble prediction system products. We investigate whether extreme floods in the Bangladesh for the Meghna river basin are equally predictable on a 1-15 day time scale. The Hopson and Webster meteorological-hydrological forecast model developed for the Ganges and Brahmaputra basins is calibrated and adapted for the Meghna basin at Bhairab Bazar. It is found that, on 1-15 day time scales, the floods for the summers of 2007-2010 are well predicted.

Toma, V. E.; Jian, J.; Hopson, T. M.; Webster, P. J.

2010-12-01

24

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

25

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

NASA Astrophysics Data System (ADS)

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.

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

2012-04-01

26

Flood forecasting for River Mekong with data-based models  

NASA Astrophysics Data System (ADS)

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.

Shahzad, Khurram M.; Plate, Erich J.

2014-09-01

27

Application of a developed atmospheric-hydrologic-hydraulic flood forecasting model driven by ensemble weather predictions to Chinese watershed  

NASA Astrophysics Data System (ADS)

A coupled atmospheric-hydrologic-hydraulic ensemble flood forecast model, driven by the ‘THORPEX Interactive Grand Global Ensemble' (TIGGE) ensemble weather predictions, was developed for flood forecast purpose of complex watershed with flood diversion and retention areas. Hydrological model is used to forecast rainfall-runoff hydrograph, and hydraulic model is used for channel flood routing. In the case of precipitation, NWPs' corrected precipitation is the input of hydrological model. The Xinanjiang model was used for the hydrological rainfall-runoff modeling. One-dimension unsteady flow model was applied for main channel flood routing. The nonlinear of the channel without cross-section data was discussed by non-liner Muskingum method. 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 retention area is calculated as a reservoir with the water balance method. Muskingum method was used for flood routing in flood diversion area. The upper reaches of the Huaihe River above Lutaizi station in China was taken as the test case. The test case, which is a humid watershed, drains an area of 8.86×104 km2, and the length of the channel from Wangjiaba to Lutaizi is 155.16 km. There are three flood diversion areas, four flood retention areas and nine large reservoirs in the test case. There are three large tributaries: the Shi River and Pi River to the south of the Huaihe River, and the Shaying River to the north. The coupled ensemble flood forecasting model was applied to flood forecasting of the upper reaches of the Huaihe River above Lutaizi station during the 2007 and 2008 flood seasons. A probabilistic discharge and flood inundation forecast was provided as the end product to study the potential benefits of using the TIGGE NWPs. The results demonstrated satisfactory flood forecasting with clear signals of probability of floods up to 10 days in advance, and showed that ensemble weather predictions is a promising tool to forecast flood inundation, comparable with that driven by raingauge observation. ACKNOWLEDGE:This work was supported by the Research Fund for Commonweal Trades (Meteorology) (Grant number: GYHY200906007, GYHY200706037 and GYHY(QX)2007-6-1), the National Natural Science Foundation of China (Grant No. 50479017 and 40971016), Innovation China UK(ICUK) Foundation, and the Program for Changjiang Scholars and Innovative Research Teams in Universities (Grant No. IRT071) Corresponding author (e-mail: baohongjun@cma.gov.cn)

Bao, Hongjun; Zhao, Linna; Li, Zhijia; He, Yi; Wetterhall, Fredrik; Cloke, Hannah; Pappenberger, Florian; Manful, Desmond; Wang, Lili

2010-05-01

28

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

NASA Astrophysics Data System (ADS)

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.

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

2013-04-01

29

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

USGS Publications Warehouse

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.

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

2001-01-01

30

Understanding uncertainty in distributed flash flood forecasting for semiarid regions  

Microsoft Academic Search

Semiarid flash floods pose a significant danger for life and property in many dry regions around the world. One effective way to mitigate flood risk lies in implementing a real-time forecast and warning system based on a rainfall-runoff model. This study used a semiarid, physics-based, and spatially distributed watershed model driven by high-resolution radar rainfall input to evaluate such a

Soni Yatheendradas; Thorsten Wagener; Hoshin Gupta; Carl Unkrich; David Goodrich; Mike Schaffner; Anne Stewart

2008-01-01

31

Flash Flood Forecasting: An Ingredients-Based Methodology  

Microsoft Academic Search

An approach to forecasting the potential for flash flood - producing storms is developed, using the notion of basic ingredients. Heavy precipitation is the result of sustained high rainfall rates. In turn, high rainfall rates involve the rapid ascent of air containing substantial water vapor and also depend on the precipitation efficiency. The duration of an event is associated with

Charles A. Doswell; Harold E. Brooks; Robert A. Maddox

1996-01-01

32

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

NASA Astrophysics Data System (ADS)

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

Silvestro, Francesco; Rebora, Nicola

2014-11-01

33

Medium Range Ensembles Flood Forecasts for Community Level Applications  

NASA Astrophysics Data System (ADS)

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

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

2013-05-01

34

National Flood Insurance Program: Flood Hazard Mapping  

NSDL National Science Digital Library

The Federal Emergency Management Agency (FEMA) has created this helpful set of resources for policymakers, elected officials, journalists, and members of the general public who would like to know more about the world of flood hazard mapping. On this site, visitors can find a host of resources and over a dozen thematic links, such as Coastal Projects, Change My Flood Zone Designation, and User Groups. Each link is preceded by a brief introduction to the resource, along with a description of the various items within each link. Visitors shouldn't miss the Online Tutorials offered here, as they include several multimedia instructional resources designed to provide in-depth training on different facets on these programs.

35

National Severe Storms Forecast Center  

NASA Technical Reports Server (NTRS)

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.

1977-01-01

36

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

NASA Astrophysics Data System (ADS)

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.

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

2013-12-01

37

An Improved Global Flood Forecasting System Using Satellite Rainfall Information and a Hydrological Model (Invited)  

NASA Astrophysics Data System (ADS)

A real-time experimental system to estimate and forecast floods over the globe, the Global Flood Monitoring System (GFMS), has been significantly improved to provide flood detection, streamflow and inundation mapping information at higher resolution (as fine as 1 km) and nowcasts and forecasts (out to five days). Images and output data are available for use by the community with updates available every three hours (http://flood.umd.edu). The system uses satellite-based rainfall information, currently the TRMM Multi-satellite Precipitation Analysis [TMPA]), other satellite and conventional information and a newly-developed hydrological and routing combination model. The improved combined model, the Dominant river Routing Integrated with VIC Environment (DRIVE) system, is based on the VIC (Variable Infiltration Capacity) land surface model (U. of Washington) and the Dominant River Tracing Routing (DRTR) method. Within the DRIVE system the surface hydrological calculations are carried out at 0.125° latitude-longitude resolution with routing, streamflow and other calculations done at that resolution and at 1km resolution. Flood detection and intensity estimates are based on water depth and streamflow thresholds calculated from a 15-year retrospective run using the satellite rainfall and model. This period is also used for testing and evaluation with results indicating improved streamflow estimation and flood detection statistics. The satellite rainfall data are integrated with global model NASA GEOS-5 Numerical Weather Prediction (NWP) rainfall predictions (adjusted to the satellite data) to extend the flood calculations out to five days. Examples of results for recent flood events are presented along with validation statistics and comparison with other flood observations (e.g., inundation calculations vs. MODIS and/or SAR flood maps). The outlook for further development in this area in terms of increased utility for national and international disaster management/response agencies is described in relation to new data sources (e.g., improved input data from GPM rainfall, SMAP soil moisture information), improved modeling, and further integration and dissemination of remote sensing flood products (e.g., hydrological calculations, MODIS/SAR flood mapping, etc.).

Adler, R. F.; Wu, H.; Tian, Y.

2013-12-01

38

FEWS Vecht, a crossing boundaries flood forecasting system  

NASA Astrophysics Data System (ADS)

The river Vecht is a cross boundary river, starting in Germany and flowing to the Netherlands. The river is completely dependant on rainfall in the catchment. Being one of the smaller big rivers in the Netherlands, there was still no operational forecasting system avaible because of the hugh number of involved organisations (2 in Germany, 5 in the Netherlands) and many other stake holders. In 2011 a first operational forecasting system has been build by using the Delft-FEWS software. It collects the real time fluvial and meteorological observations from all the organisations, in that sense being a portal where all the collected information is available and can be consistantly interpreted as a whole. In 2012 an HBV rainfall runoff model and a Sobek 1D hydraulic model has been build. These models have been integrated into the FEWS system and are operationally running since the 2012 autumn. The system forecasts 5 days ahead using a 5 days ECMWF rainfall ensemble forecast. It enables making scenarios, especially useful for the operation of storage reservoirs. During the 2012 Christmas days a (relatively small) T=2 flood occurred (Q=175-200 m3/s) and proved the system to run succesfully. Dissemination of the forecasts is performed by using the FEWS system in all organisations, connected to the central system through internet. There is also a (password protected) website available that provides the current forecast to all stake holders in the catchment. The challenge of the project was not to make the models and to build the fews, but to connect all data and all operators together into one system, even cross boundary. Also in that sense the FEWS Vecht system has proved to be very succesful.

van Heeringen, Klaas-Jan; Filius, Pieter; Tromp, Gerben; Renner, Tobias

2013-04-01

39

Identifying Effects of Forecast Uncertainty on Flood Control Decision - A Hydro-economic Hedging Framework  

NASA Astrophysics Data System (ADS)

Different from conventional studies developing reservoir operation models and treating forecast as input to obtain operation decisions case by case, this study issues a hydro-economic analysis framework and derives some general relationships between optimal flood control decision and streamflow forecast. By analogy with the hedging rule theory for water supply, we formulate reservoir flood control with a two-stage optimization model, in which the properties of flood damage (i.e., diminishing marginal damage) and the characteristics of forecast uncertainty (i.e., the longer the forecast horizon, the larger the forecast uncertainty) are incorporated to minimize flood risk. We define flood conveying capacity surplus (FCCS) variables to elaborate the trade-offs between the release of current stage (i.e., stage 1) and in the release of future stage (i.e., stage 2). Using Karush-Kuhn-Tucker conditions, the flood risk trade-off between the two stages is theoretically represented and illustrated by three typical situations depending on forecast uncertainty and flood magnitude. The analytical results also show some complicated effects of forecast uncertainty and flood magnitude on real-time flood control decision: 1) When there is a big flood with a small FCCS, the whole FCCS should be allocated to the current stage to hedge against the more certain and urgent flood risk in the current stage; 2) when there is a medium flood with a moderate FCCS, some FCCS should be allocated to the future stage but more FCCS still should be allocated to the current stage; and 3) when there is a small flood with a large FCCS, more FCCS should be allocated to the future stage than the current stage, as a large FCCS in the future stage can still induce some flood risk (distribution of future stage forecast uncertainty is more disperse) while a moderate FCCS in the current stage can induce a small risk. Moreover, this study also presents a hypothetical case study to analyze the flood risk under Pseudo probabilistic streamflow forecast (pPSF, deterministic forecast with variance) and Real probabilistic streamflow forecast (rPSF, ensemble forecast) forecast uncertainties, which shows ensemble forecast techniques are more efficient on mitigating flood risk.

Zhao, T.; Zhao, J.; Cai, X.; Yang, D.

2011-12-01

40

Forecasting of Storm Surge Floods Using ADCIRC and Optimized DEMs  

NASA Technical Reports Server (NTRS)

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.

Valenti, Elizabeth; Fitzpatrick, Patrick

2005-01-01

41

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

NASA Astrophysics Data System (ADS)

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

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

2006-04-01

42

76 FR 7508 - National Flood Insurance Program, Policy Wording Correction  

Federal Register 2010, 2011, 2012, 2013

...FEMA-2010-0021] RIN 1660-AA70 National Flood Insurance Program, Policy Wording Correction...Mitigation Administration, Standard Flood Insurance Policy regulations. In order...the provisions of the Standard Flood Insurance Policy, FEMA is adding two...

2011-02-10

43

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

Federal Register 2010, 2011, 2012, 2013

...FEMA-2010-0021] RIN 1660-AA70 National Flood Insurance Program, Policy Wording Correction...Mitigation Administration, Standard Flood Insurance Policy regulations. In this...the provisions of the Standard Flood Insurance Policy by adding in two...

2010-09-03

44

Drought Monitoring and Forecasting Using the Princeton/U Washington National Hydrologic Forecasting System  

NASA Astrophysics Data System (ADS)

Extreme hydrologic events in the form of droughts or floods are a significant source of social and economic damage in many parts of the world. Having sufficient warning of extreme events allows managers to prepare for and reduce the severity of their impacts. A hydrologic forecast system can give seasonal predictions that can be used by mangers to make better decisions; however there is still much uncertainty associated with such a system. Therefore it is important to understand the forecast skill of the system before transitioning to operational usage. Seasonal reforecasts (1982 - 2010) from the NCEP Climate Forecast System (both version 1 (CFS) and version 2 (CFSv2), Climate Prediction Center (CPC) outlooks and the European Seasonal Interannual Prediction (EUROSIP) system, are assessed for forecasting skill in drought prediction across the U.S., both singularly and as a multi-model system The Princeton/U Washington national hydrologic monitoring and forecast system is being implemented at NCEP/EMC via their Climate Test Bed as the experimental hydrological forecast system to support U.S. operational drought prediction. Using our system, the seasonal forecasts are biased corrected, downscaled and used to drive the Variable Infiltration Capacity (VIC) land surface model to give seasonal forecasts of hydrologic variables with lead times of up to six months. Results are presented for a number of events, with particular focus on the Apalachicola-Chattahoochee-Flint (ACF) River Basin in the South Eastern United States, which has experienced a number of severe droughts in recent years and is a pilot study basin for the National Integrated Drought Information System (NIDIS). The performance of the VIC land surface model is evaluated using observational forcing when compared to observed streamflow. The effectiveness of the forecast system to predict streamflow and soil moisture is evaluated when compared with observed streamflow and modeled soil moisture driven by observed atmospheric forcing. The forecast skills from the dynamical seasonal models (CFSv1, CFSv2, EUROSIP) and CPC are also compared with forecasts based on the Ensemble Streamflow Prediction (ESP) method, which uses initial conditions and historical forcings to generate seasonal forecasts. The skill of the system to predict drought, drought recovery and related hydrological conditions such as low-flows is assessed, along with quantified uncertainty.

Wood, E. F.; Yuan, X.; Roundy, J. K.; Lettenmaier, D. P.; Mo, K. C.; Xia, Y.; Ek, M. B.

2011-12-01

45

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

NASA Astrophysics Data System (ADS)

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.

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

2013-04-01

46

Market Failure in Information: The National Flood Insurance Program  

Microsoft Academic Search

The National Flood Insurance Program (NFIP) was established in 1968 and requires mandatory flood insurance for property owners who have federally backed mortgages. Krutilla (1966) noted that a compulsory national flood insurance program could greatly improve the economic efficiency of flood plain occupancy in the United States. However, in order to realize the efficiency gains suggested by Krutilla, property owners

James Chivers; Nicholas E. Flores

2002-01-01

47

Real-time flood forecasting with high-resolution NWP rainfall and dual data assimilation  

NASA Astrophysics Data System (ADS)

Mesoscale Numerical Weather Prediction (NWP) models are nowadays gaining more and more attention in providing high-resolution rainfall forecasts for real-time flood forecasting. In this study, the newest generation NWP model, Weather Research & Forecasting (WRF) model, is integrated with the rainfall-runoff model in real-time to generate accurate flow forecasts at the catchment scale. The rainfall-runoff model is chosen as the Probability Distribution Model (PDM), which has widely been used for flood forecasting. Dual data assimilation is carried out for real-time updating of the flood forecasting system. The 3-Dimensional Variational (3DVar) data assimilation scheme is incorporated with WRF to assimilate meteorological observations and weather radar reflectivity data in order to improve the WRF rainfall forecasts; meanwhile real-time flow observations are assimilated by the Auto-Regressive Moving Average (ARMA) model to update the forecasted flow transformed by PDM. The Brue catchment located in Southwest England with a drainage area of 135.2 km2 is chosen to be the study area. A dense rain gauge network was set up during a project named HYREX (Hydrological radar experiment), which contains 49 rain gauges and a C-band weather radar, providing with sufficient hydrological and radar data for WRF model verification and data assimilation. Besides the radar reflectivity data, two types of NCAR archived data (SYNOP and SOUND, http://dss.ucar.edu) are also assimilated by 3DVar, which provide real-time surface and upper-level observations of pressure, temperature, humidity and wind from fixed and mobile stations. Four 24 hour storm events are selected from the HYREX project with different characteristics regarding storm formation and rainfall-runoff responses. Real-time flood forecasting is then carried out by the constructed forecasting system for the four storm events with a forecast lead time of 12 hours. The forecasting accuracy of the whole system is found to be largely improved by incorporating the WRF forecasted rainfall when the forecast lead time is beyond the catchment concentration time. The assimilation of real-time meteorological and radar data also show great advantage in improving the performance of the flood forecasting system. Key words: real-time flood forecasting; Weather Research & Forecasting (WRF) model; high-resolution rainfall forecasts; dual data assimilation.

Liu, Jia; Bray, Michaela; Han, Dawei

2014-05-01

48

Operational aspects of asynchronous filtering for improved flood forecasting  

NASA Astrophysics Data System (ADS)

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.

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

2014-05-01

49

24 CFR 570.605 - National Flood Insurance Program.  

Code of Federal Regulations, 2011 CFR

... 2011-04-01 2010-04-01 true National Flood Insurance Program. 570.605 Section 570.605 Housing...Other Program Requirements § 570.605 National Flood Insurance Program. Notwithstanding the date of...

2011-04-01

50

24 CFR 570.605 - National Flood Insurance Program.  

Code of Federal Regulations, 2013 CFR

...2013-04-01 2013-04-01 false National Flood Insurance Program. 570.605 Section 570.605 Housing...Other Program Requirements § 570.605 National Flood Insurance Program. Notwithstanding the date of...

2013-04-01

51

24 CFR 570.605 - National Flood Insurance Program.  

Code of Federal Regulations, 2010 CFR

...2010-04-01 2010-04-01 false National Flood Insurance Program. 570.605 Section 570.605 Housing...Other Program Requirements § 570.605 National Flood Insurance Program. Notwithstanding the date of...

2010-04-01

52

24 CFR 570.605 - National Flood Insurance Program.  

Code of Federal Regulations, 2012 CFR

...2012-04-01 2012-04-01 false National Flood Insurance Program. 570.605 Section 570.605 Housing...Other Program Requirements § 570.605 National Flood Insurance Program. Notwithstanding the date of...

2012-04-01

53

24 CFR 570.605 - National Flood Insurance Program.  

... 2014-04-01 2013-04-01 true National Flood Insurance Program. 570.605 Section 570.605 Housing...Other Program Requirements § 570.605 National Flood Insurance Program. Notwithstanding the date of...

2014-04-01

54

Towards Long-lead Forecasting of Extreme Flood Events: A Data Mining Framework for Precipitation Cluster  

E-print Network

Towards Long-lead Forecasting of Extreme Flood Events: A Data Mining Framework for Precipitation of precipitation events occurring over from several days to several weeks. Though precise short- term forecasting of precipitation clusters can be attempted by identifying persistent atmospheric regimes that are conducive

Ding, Wei

55

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

NASA Astrophysics Data System (ADS)

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.

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

2013-04-01

56

Improving our understanding of flood forecasting using earlier hydro-meteorological intelligence  

NASA Astrophysics Data System (ADS)

In recent decades, Taiwan has suffered from severe bouts of torrential rain, and typhoon induced floods have become the major natural threat to Taiwan. In order to warn the public of potential risks, authorities are considering establishing an early warning system derived from an integrated hydro-meteorological estimation process. This study aims at the development and accuracy of such a warning system. So it is first necessary to understand the distinctive features of flood forecasting in integrated rainfall-runoff simulations. Additionally the adequacies of a warning system that is based on extracting useful intelligence from earlier, possibly faulty numerical simulation results are discussed. In order to precisely model flooding, hydrological simulations based upon spot measured rainfall data have been utilized in prior studies to calibrate model parameters. Here, precipitation inputs from an ensemble of almost 20 different realizations of rainfall fields have been used to derive flood forecasts. The flood warning system therefore integrates rainfall-runoff calculations, field observations and data assimilations. Simulation results indicate that the ensemble precipitation estimates generated by a Weather Research Forecasting (WRF) mesoscale model produce divergent estimates. Considerable flooding is often shown in the simulated hydrographs, but the results as to the peak time and peak stage are not always in agreement with the observations. In brief, such forecasts can be good for warning against potential damaging floods in the near future, but the meteorological inputs are not good enough to forecast the time and magnitude of the peaks. The key for such warning system is not to expect highly accurate rainfall predictions, but to improve our understanding from individual ensemble flood forecasts.

Shih, Dong-Sin; Chen, Cheng-Hsin; Yeh, Gour-Tsyh

2014-05-01

57

Effects of Rainfall Prediction in the Flood Forecasting of the Tiber River in Rome  

NASA Astrophysics Data System (ADS)

In order to protect Rome from extreme floods propagating along the Tiber River, two flood forecasting models were recently proposed by the authors: a conceptual hydrological-hydraulic model (TFF - Tevere Flood Forecasting) and a data driven model based on Artificial Neural Network (ANN). To forecast water levels in Rome, both these models utilize observations of rainfall and discharge in the gauging stations located in the meddle-lower Tiber valley and do not include forecast of rainfall. According to this assumption, the water levels in Rome can be forecasted with a lead time of 12 hours using the TFF model and with a lead time slightly greater (14-16 hours) using the ANN model. This lead time depend on the dynamics of the formation and the propagation of the flood wave in meddle-lower Tiber valley. The catchment area of the Tiber River in Rome is 16,000 km2, approximately. The catchment upstream of the Corbara dam is approximately 6,000 km2; this reservoir, which is located about 150 km north from Rome, has an active storage capacity of 165 hm3 and disconnect the floods coming from the upper Tiber valley from the floods in the meddle-lower valley. Downstream of Corbara dam, the contributions of the main three tributaries are observed in stream gauging stations; the contribution of 37 small tributaries, located in the lower valley and whose catchment area is about 3000 km2 at all, is unknown and, consequently, must be computed by means of rainfall-runoff procedure in the TFF model. However these ungauged tributaries play a relevant role in the flood propagation. The lower Tiber valley is wide, so that the peak the flood wave released from Corbara dam, with the contribution of the main tributaries, can be reduced by the lamination due to the inundation of the floodplains. On the contrary, if the contribution of the ungauged tributaries is relevant, the peak of the flood wave coming from the meddle Tiber valley does not reduce and relevant discharges may reach Rome. The sum of the concentration time and travel time through the river network to Rome for most of the 37 ungauged tributaries is greater than 10 hours and this influences significantly the lead time. This paper deals with the analysis of the effects of the introduction of rainfall prediction for the 37 ungauged tributaries in both the flood forecasting models on the lead time and on the uncertainties on the forecasted water levels in Rome. More specifically the errors in the prediction of both total rainfall and rainfall time distribution are analyzed and discussed. Keywords: real-time forecasting, rainfall prediction, lead time

Napolitano, G.; See, L.; Savi, F.; Calvo, B.

2009-04-01

58

Evaluation of Mekong River commission operational flood forecasts, 2000-2012  

NASA Astrophysics Data System (ADS)

This study created a 13-year historical archive of operational flood forecasts issued by the Regional Flood Management and Mitigation Center (RFMMC) of the Mekong River Commission. The RFMMC issues 1- to 5-day daily deterministic river height forecasts for 22 locations throughout the wet season (June-October). When these forecasts reach near flood level, government agencies and the public are encouraged to take protective action against damages. When measured by standard skill scores, the forecasts perform exceptionally well (e.g., 1 day-ahead Nash-Sutcliffe > 0.99) although much of this apparent skill is due to the strong seasonal cycle and the narrow natural range of variability at certain locations. Five-day forecasts upstream of Phnom Penh typically have 0.8 m error standard deviation, whereas below Phnom Penh the error is typically 0.3 m. The coefficients of persistence for 1-day forecasts are typically 0.4-0.8 and 5-day forecasts are typically 0.1-0.7. RFMMC uses a series of benchmarks to define a metric of percentage satisfactory forecasts. As the benchmarks were derived based on the average error, certain locations and lead times consistently appear less satisfactory than others. Instead, different benchmarks were proposed and derived based on the 70th percentile of absolute error over the 13-year period. There are no obvious trends in the percentage of satisfactory forecasts from 2002 to 2012, regardless of the benchmark chosen. Finally, when evaluated from a categorical "crossing above/not-crossing above flood level" perspective, the forecasts have a moderate probability of detection (48% at 1 day ahead, 31% at 5 days ahead) and false alarm rate (13% at 1 day ahead, 74% at 5 days ahead).

Pagano, T. C.

2014-07-01

59

Computer technology forecasting at the National Laboratories  

SciTech Connect

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

Peskin, A M

1980-01-01

60

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

NASA Astrophysics Data System (ADS)

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.

Manukalo, V.

2012-12-01

61

Real-Time Flood Forecasting Using Automatic Parameter Optimization and Rainfall Projections.  

NASA Astrophysics Data System (ADS)

Scope and method of study. The purpose of this study was to minimize forecasting error and improve lead time on real-time flood forecasts. A real-time flood forecast (RTFF) system has been developed and evaluated on the Stillwater Creek basin of north-central Oklahoma. Exponential smoothing was used to estimate the calibration factor (CF) for real -time calibration of NEXRAD radar to raingauge data. Rainfall forecasting is based on autoregressive and moving average (ARMA) models. The initial estimates of the model parameters were obtained using moment estimators. The Box-Jenkins forecast theory was applied to predict the future rainfall values. Good results for updating parameters and lead time weights were obtained mainly due to the adaptive estimation procedure which used only the more recent calibrated data. An automatic parameter estimation (APE) algorithm was used to optimize and update model parameters during the real -time runs. Findings and conclusions. The exponential smoothing approach was found to significantly improve the CF when the smoothing parameter is 0.3. Parameter estimates updated in the RTFF system can be improved by using the most recent data and a weighting function. The ARMA model with a Box -Jenkins forecast function can forecast rainfall for improving the lead time and accuracy in flood prediction.

Jia, Zhenwen

62

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

NASA Astrophysics Data System (ADS)

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.

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

2012-12-01

63

Wake-up Call in East Tennessee?: Correlating Flood Losses to National Flood Insurance Program Enrollment (1978-2006)  

Microsoft Academic Search

:The National Flood Insurance Program (NFIP) provides federally-backed insurance for properties in Special Flood Hazard Areas, yet many property owners do not enroll in the program. I compared flood losses and flood insurance enrollment for three Tennessee communities: Chattanooga, Elizabethton and Pigeon Forge, to investigate the relationship between flooding and NFIP enrollment. Normalized flood losses and insurance purchases were cross-correlated

Ingrid E. Luffman

2010-01-01

64

Utilizing Climate Based Flood Forecasting for Operational Rule Curve Development  

Microsoft Academic Search

Delaying the date of maximum flood control drawdown at large storage reservoirs will provide benefits to ecosystem health, power generation, and water supply reliability. This project focuses on using climate-based information to extend predictions of spring runoff to lead times greater than 10 days. Current operation within the Columbia River storage system relies on static rule curves for flood management.

D. A. Raff

2005-01-01

65

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

NASA Astrophysics Data System (ADS)

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.

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

2014-05-01

66

Use of a snowmelt model for weekly flood forecast for a major reservoir in Lithuania  

NASA Astrophysics Data System (ADS)

A snowmelt model is used for the weekly forecast of daily discharges in the Kaunas reservoir, Lithuania. The results are used to feed a risk-based decision-making model developed by the first author for dam operation during floods. Physically based calibration of a degree-day model is carried out and coupled with flow routing using Nash's instantaneous unit hydrograph theory. Temperature forecast is used as the driving variable. Due to the relative smoothness of snowmelt over time and the considerable basin size, the model provides acceptable results. Kalman filtering is then used to merge the estimates from the snowmelt model with those from an ARIMA flow model, resulting in better forecasting than that using each method alone. Uncertainty analysis of the snowmelt-model results is then carried out, showing considerable influence of the main parameter degree-day and of soil moisture conditions. Therefore these must be accurately estimated for forecasting purposes during flood events.

Simaityte, Jurgita; Bocchiola, Daniele; Augutis, Juozas; Rosso, Renzo

67

Forecast uncertainty in semi-arid flash flood modeling using radar rain input  

Microsoft Academic Search

Flash floods are extremely dangerous hazards in the semi-arid southwest US at short temporal scales, posing a significant danger to life and property. Attempts to mitigate this flood risk using model-based forecasting are subject to uncertainties in the model and the data. This study reports on such an attempt using the distributed, semi-arid mechanistic rainfall-runoff model KINEROS2 driven by the

C. Unkrich; S. Yatheendradas; H. Gupta; T. Wagener; D. Goodrich; M. Schaffner; A. Stewart

2007-01-01

68

Real-time flood forecasting of the Tiber river in Rome  

Microsoft Academic Search

An adaptive, conceptual model for real-time flood forecasting of the Tiber river in Rome is proposed. This model simulates\\u000a both rainfall-runoff transformations, to reproduce the contributions of 37 ungauged sub-basins that covered about 30% of the\\u000a catchment area, and flood routing processes in the hydrographic network. The adaptive component of the model concerns the\\u000a rainfall-runoff analysis: at any time step

Benedetto Calvo; Fabrizio Savi

2009-01-01

69

A comparison of different approaches for forecasting spring floods in Sweden  

NASA Astrophysics Data System (ADS)

In seasonally snow covered regions, such as Sweden, the winter precipitation often falls as snow which is temporarily stored in the snow pack during the colder months. This storage is later released over a relatively short period of intense flows during in the warmer months. These spring flood events dominate the hydrology of these regions and therefore there is a real interest in reliable hydrological forecasts of these events. In the state-of-the-art forecasting approach for three catchments in Sweden, the HBV model is firstly run using observed temperature and precipitation up until the time of the forecast, that way producing an optimal description of the hydro-meteorological conditions. Then temperature and precipitation data, for the period corresponding with that being forecasted, from all historical years since 1961 is used to create an ensemble of model runs representing possible evolutions in the coming period. Since all historical years are used, the (median) forecast is climatological, i.e. it predicts the spring flood under the assumption that the development of the weather in the forecasting period will be normal. The forecast error will thus be larger the more unusual the weather develops, provided that the initial HBV-condition represents reality well. In this study, three different ensemble forecast approaches to spring flood forecasting were compared to the state-of-the-art operational method. (1) A reduced historical ensemble approach, where analogue years from the historical dataset are selected to run the hydrological model. (2) Using meteorological seasonal forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) to run the hydrological model. (3) Statically downscaling large-scale circulation variables from ECMWF seasonal forecasts to accumulated discharge using the Singular Value Decomposition method. The different approaches were evaluated for forecasts issued on 1/1, 1/3 and 1/5 for the spring floods 2000-2010 in the rivers Vindelälven, Ångermanälven and Ljusnan. The evaluation was mainly performed in terms of the mean absolute error (MAE) of accumulated discharge with the state-of-the-art forecast as a reference. Also the frequency of cases when the new approach outperformed the state-of-the-art forecast was calculated and used. The results indicate that some reduction of the forecast error seems attainable for Vindelälven and Ångermanälven, whereas none of the single approaches generated any clear improvement for Ljusnan. This is probably because the spring floods in the former rivers are more clearly related to snow melt. The largest improvement was found for the 1/1-forecasts using the statistical downscaling approach, while the reduced ensemble approach gave the best improvement when considering all forecast dates. Using ECMWF seasonal forecasts approach did not generate any improvements; an analysis of the ECWMF forecasts indicated clearly overestimated precipitation in Feb-Apr and temperature in Jun-Jul, as compared with catchment observations.

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

2012-04-01

70

Ensemble Flood Forecasting in Africa: A Feasibility Study in the Juba-Shabelle River Basin  

NASA Astrophysics Data System (ADS)

Over the last years the African continent has increasingly experienced severe transnational floods that caused substantial socio-economic losses and put enormous pressure on countries across the continent. The planning, coordination and realization of flood prevention, protection and mitigation measures require time, which can be provided through an early flood prediction. In this paper, the transferability of the European Flood Alert System (EFAS) to equatorial African basins is assessed. EFAS achieves early flood warnings for large to medium-size river basins with lead times of 10 days. This is based on probabilistic weather forecasts, the exceedance of alert thresholds and persistence indicators. These methodologies, having been tested for different events and time scales in mid-latitude basins in Europe, are being applied in this paper to the Juba-Shabella river basin, shared between Ethopia and Somalia. A variety of different meteorological data sources have been used, including ERA-40 and CHARM for the calculation of climatologies. The unique re-forecasts of the current operational ECMWF model provided hindcasts of historic flood events. The results show that for the selected flood events a detection rate of 85% was achieved, with a high accuracy in terms of timing and magnitude.

Thiemig, Vera; Pappenberger, Florian; Thielen, Jutta; Gadain, Hussein; de Roo, Ad; Bodis, Katalin; Del Medico, Mauro; Muthusi, Flavian

2010-05-01

71

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

E-print Network

Fuzzy modelling of basin saturation state and neural networks for flood forecasting G. Corani a , G and rainfalls, without providing a description of the saturation state of the basin, which in contrast plays a description of the basin saturation state; the basin state is classified as belonging with different degrees

Corani, Giorgio

72

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

NASA Astrophysics Data System (ADS)

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.

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

2013-12-01

73

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

74

Estimating the impact of satellite observations on large-scale river flood forecasting  

NASA Astrophysics Data System (ADS)

Floods are one of the costliest natural disasters, posing severe risks to human population. Hydraulic models are able to predict flood characteristics, such as water surface elevations and inundated area, and are being used for forecasting operationally although there are many uncertainties. In this work, the potential value of satellite observations to initialize these hydraulic models (and their forecasts correspondingly) is explored. The Ensemble Sensitivity method is adapted to evaluate the impact of potential satellite observations on the forecasting of flood characteristics. The estimation of the impact is based on the Local Ensemble Transform Kalman Filter, allowing for the forecast error reductions to be computed without additional model runs. The study area was located in the Ohio River basin, and the model used was the LISFLOOD-FP hydrodynamic model. The experimental design consisted of two configurations of the LISFLOOD-FP model. The first (baseline) simulation represents a calibrated 'best effort' model based on a sub-grid channel structure using observations for parameters and boundary conditions, whereas the second (background) simulation consists of estimated parameters and SRTM-based boundary conditions. Results showed that the forecast skill was improved for water heights up to lead times of 11 days, while even partial observations of the river contained information for the entire river's water surface profile and allowed forecasting 5 to 7 days ahead. On the other hand, discharge forecasts were not improved as much when assimilating water height observations although forecast errors were reduced. Finally, the potential for identifying errors in the model structure and parameterizations via the ensemble sensitivity method is discussed.

Andreadis, Konstantinos; Schumann, Guy

2014-05-01

75

Feedbacks of the use of two uncertainty assessment techniques by operational flood forecasters  

NASA Astrophysics Data System (ADS)

In 2013, forecasters working in the French flood forecasting services tested two automatic techniques for forecast uncertainty assessment in their operational context. These techniques were expected to characterize predictive uncertainty, and provide forecasters with confidence intervals (for example, 80% central intervals) associated to their forecasts (forecast intervals) and estimates of the probability of exceeding some warning thresholds. The first technique was the quantile regression method (Weerts et al., 2011), while the second one was a data-based and non-parametric method. These techniques were applied to a forecasting rainfall-runoff model (GRP) and to two hydraulic models (HYDRA and MASCARET). Both techniques are based on the statistical analysis of past forecast errors. In the case of the hydrological model, the past forecast errors were estimated using a 'perfect' rainfall scenario (corresponding to a posteriori observed rainfall). The forecasters pointed out that the approaches are simple enough to be easily understood, which was stressed as a clear advantage over "black-box" tools. The feedbacks showed that many operational forecasters enjoyed the fact that these automatic assessments brought out the qualities and the defaults of the model (e.g., bias) of which they were aware... or not. Therefore these results clearly helped them to better know the limits of their models. The forecast intervals (80%) produced by the methods were often found too large by the forecasters to be very helpful in their decision-making. Moreover, forecasters thought they were able to give narrower intervals (still being reliable) based on their experience. The methods were considered as providing very good starting points by the forecasters, encouraging them to build their own forecast intervals. Forecasters use the probability of exceeeding a threshold as one piece of information (among others) to decide whether to issue a warning or not. It is considered as very informative and valuable by the forecasters, even in the case different future precipitation scenarios would be used. Operational perspectives are the combination of ensemble precipitation forecasts and these techniques.

Berthet, Lionel; Bourgin, François; Perrin, Charles; Andréassian, Vazken

2014-05-01

76

Integration of Remote Sensing Data In Operational Flood Forecast In Southwest Germany  

NASA Astrophysics Data System (ADS)

Methods to accurately assess and forecast flood discharge are mandatory to minimise the impact of hydrological hazards. However, existing rainfall-runoff models rarely accurately consider the spatial characteristics of the watershed, which is essential for a suitable and physics-based description of processes relevant for runoff formation. Spatial information with low temporal variability like elevation, slopes and land use can be mapped or extracted from remote sensing data. However, land surface param- eters of high temporal variability, like soil moisture and snow properties are hardly available and used in operational forecasts. Remote sensing methods can improve flood forecast by providing information on the actual water retention capacities in the watershed and facilitate the regionalisation of hydrological models. To prove and demonstrate this, the project 'InFerno' (Integration of remote sensing data in opera- tional water balance and flood forecast modelling) has been set up, funded by DLR (50EE0053). Within InFerno remote sensing data (optical and microwave) are thor- oughly processed to deliver spatially distributed parameters of snow properties and soil moisture. Especially during the onset of a flood this information is essential to estimate the initial conditions of the model. At the flood forecast centres of 'Baden- Württemberg' and 'Rheinland-Pfalz' (Southwest Germany) the remote sensing based maps on soil moisture and snow properties will be integrated in the continuously op- erated water balance and flood forecast model LARSIM. The concept is to transfer the developed methodology from the Neckar to the Mosel basin. The major challenges lie on the one hand in the implementation of algorithms developed for a multisensoral synergy and the creation of robust, operationally applicable remote sensing products. On the other hand, the operational flood forecast must be adapted to make full use of the new data sources. In the operational phase of the project ESA's ENVISAT satellite, which will be launched in 2002, will serve as remote sensing data source. Until EN- VISAT data is available, algorithm retrieval, software development and product gener- ation is performed using existing sensors with ENVISAT-like specifications. Based on these data sets test cases and demonstration runs are conducted and will be presented to prove the advantages of the approach.

Bach, H.; Appel, F.; Schulz, W.; Merkel, U.; Ludwig, R.; Mauser, W.

77

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)

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

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

2014-05-01

78

Short-term flood forecasting with a neurofuzzy model  

NASA Astrophysics Data System (ADS)

This study explores the potential of the neurofuzzy computing paradigm to model the rainfall-runoff process for forecasting the river flow of Kolar basin in India. The neurofuzzy computing technique is a combination of a fuzzy computing approach and an artificial neural network technique. Parameter optimization in the model was performed by a combination of backpropagation and least squares error methods. Performance of the neurofuzzy model was comprehensively evaluated with that of independent fuzzy and neural network models developed for the same basin. The values of three performance evaluation criteria, namely, the coefficient of efficiency, the root-mean-square error, and the coefficient of correlation, were found to be very good and consistent for flows forecasted 1 hour in advance by the neurofuzzy model. The value of the relative error in peak flow prediction was within reasonable limits for the neurofuzzy model. The neurofuzzy model forecasted 47.95% of the total number of flow values 1 hour in advance with less than 1% relative error, while for the neural network and fuzzy models the corresponding values were 36.96 and 18.89%, respectively. The forecasts by the neurofuzzy model at higher lead times (up to 6 hours) are found to be better than those from the neural network model or the fuzzy model, implying that the neurofuzzy model seems to be well suited to exploit the information to model the nonlinear dynamics of the rainfall-runoff process.

Nayak, P. C.; Sudheer, K. P.; Rangan, D. M.; Ramasastri, K. S.

2005-04-01

79

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

NASA Astrophysics Data System (ADS)

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.

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

2011-12-01

80

Hurricane Analysis and Forecasting at the National Hurricane Center  

E-print Network

Hurricane Analysis and Forecasting at the National Hurricane Center Hurricane Analysis and Forecasting at the National Hurricane Center National Hurricane Center, MiamiNational Hurricane Center, Miami WEATHER THREATS." #12;Before Katrina... David & Kimberly King Waveland, MS #12;...After Katrina David

81

Application of stochastic differential equation to reservoir routing with probabilistic inflow forecasting and flood control risk analysis  

NASA Astrophysics Data System (ADS)

Real-time flood control of a reservoir system involves various uncertainties including the prediction uncertainty of inflow flood events, uncertainties in boundary conditions such as the reservoir storage curve, release capacity curve, and the uncertainty within the reservoir flood routing model itself. In this study, the hydrologic uncertainty processor (PUB) under the framework of Bayesian forecasting system (BFS) is adopted to quantify the uncertainty of flood prediction, providing with the probabilistic forecasting for real-time flood events. A Gaussian form of distribution is used to describe uncertainty of reservoir storage or release capacity; parameters of the distribution are estimated by historical measurements. In order to route the flood hydrograph with probability feature, i.e. a probabilistic forecasting flood event, stochastic differential equation (SDE) is introduced to build the reservoir flood routing model. By introducing a Gaussian white noise term, the traditional reservoir's water balance equation is altered to a kind of Ito stochastic differential equation. The solutions of Ito equation provide a probabilistic form of forecasting for reservoir stage process and outflow hydrograph. Both the analytical and numerical approaches are applied to solve the Ito stochastic differential equation, and their applicability for reservoir stochastic flood routing is testified. By assigning a specific flood limit level or reservoir beginning water level on which a real-time flood event is started to route through using the SDE, a corresponding probabilistic reservoir stage processes can be forecasted. For a designed control water level (DCWL), the risk rate or the largest probability that the forecasted reservoir stage excesses DCWL can be computed. Setting a series of flood limit levels, for a forecasted probabilistic inflow hydrograph, there obtains the corresponding reservoir stage processes, and in turn the risk rate of flood protection. By checking if the risk rate is less than a preassigned acceptable risk or flood control standard, a reasonable flood limit water level is determined to raise the utilization ratio of flood resources. As an example, the approach is applied to Dahuofang reservoir, which is located on Hun river in Northeast China. A typical flood event occurred in the flooding season of 2005 is analyzed to demonstrate the application of proposed procedure.

Liang, Z.; Hu, Y.; Wang, J.

2012-04-01

82

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

Code of Federal Regulations, 2011 CFR

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

2011-10-01

83

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

NASA Astrophysics Data System (ADS)

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.

van der Zwan, Rene

2013-04-01

84

Long-Lead Quantitative Flood Forecasts in Ungauged Basins Using Bayesian Neural Networks  

NASA Astrophysics Data System (ADS)

Previously, Kim and Barros (2001) demonstrated the use of a hierarchy of neural network models to forecast flood peaks in four small and medium size ungauged basins (750 to about 9,000 km-sq) in the Northern Appalachian Mountains in Pennsylvania. Using regional rainfall, radiosonde and mesoscale infrared (IR) satellite imagery, their approach consisted of identifying the presence and type of convective activity from the IR imagery, information which was subsequently used to characterize the dominant synoptic scale weather patters and predict storm path and evolution using rainfall and radiosonde data far away from the forecast location. In this regard, the organizational skeleton of the inputs is built to mimic our understanding of physical processes associated with rainstorms. The approach was very successful with skill scores on the order of 80-90 per cent for 18-hour lead-time forecasts of winter and spring floods in response to heavy rainfall (i.e. not associated with snowmelt alone). One weakness of this work was however the lack of a measure of forecast uncertainty, or alternatively a measure of forecast reliability that could be used in hydrometeorological operations. To address this question, we have modified and adapted the existing neural network models according to the principles of Bayesian statistics. In this context, forecasts are issued along with an error bar and are associated with a known probability distribution. One additional advantage of this methodology is that it provides an objective basis for selecting the best model during learning based on the posterior distribution of the parameters. In this context, forecasts are issued along with an error bar and are associated with a known probability distribution. An intercomparison study against Kim and Barros (2001) shows that the 18- and 24-hour lead time BNN forecasts are statistically more robust than those generated by the standard backward-learning NNs. We submit that given the consistently superior skill and forecast range of these models as compared to those relying in NWP output, and given the increasing availability of remote-sensing data around the world, the time has come to make full use of these technologies for early warning and disaster response activities anywhere, anytime. Kim, G., and Barros, A.P., 2001: Quantitative Flood Forecasting Using Multisensor Data and Neural Networks. J. Hydrology, 246, 45-62.

Barros, A. P.; Yoo, J.

2004-05-01

85

A conceptual and neural network model for real-time flood forecasting of the Tiber River in Rome  

Microsoft Academic Search

Rome is at risk from flooding when extreme events with a return period of about 200years occur. For this reason, an accurate real-time flood forecasting system may be a useful non-structural countermeasure. Two different approaches are considered to develop a real-time forecasting system capable of predicting hourly water levels at Ripetta stream gauging station in Rome. The first is an

G. Napolitano; L. See; B. Calvo; F. Savi; A. Heppenstall

2010-01-01

86

Assessment of sewer flooding model based on ensemble quantitative precipitation forecast  

NASA Astrophysics Data System (ADS)

Short duration rainfall intensity in Taiwan has increased in recent years, which results in street runoff exceeding the design capacity of storm sewer systems and causing inundation in urban areas. If potential inundation areas could be forecasted in advance and warnings message disseminated in time, additional reaction time for local disaster mitigation units and residents should be able to reduce inundation damage. In general, meteorological-hydrological ensemble forecast systems require moderately long lead times. The time-consuming modeling process is usually less amenable to the needs of real-time flood warnings. Therefore, the main goal of this study is to establish an inundation evaluation system suitable for all metropolitan areas in Taiwan in conjunction with the quantitative precipitation forecast technology developed by the Taiwan Typhoon and Flood Research Institute, which can be used for inundation forecast 24 h before the arrival of typhoons. In this study, information for the design capacity of storm sewer throughout Taiwan was collected. Two methods are proposed to evaluate the inundations: (a) evaluation based on the criterion of sewer capacity (CSC), and (b) evaluation based on the percentage of ensemble members (PEM). In addition, the probability of inundation is classified into four levels (high, medium, low, and no inundation). To verify the accuracy of the proposed system, Typhoon Megi and Typhoon Nanmadol were used as test cases. Four verification indices were adopted to evaluate the probability of inundation for metropolitan areas during typhoons. The inundation evaluation results basically match the observed data on flooding, which demonstrate that this flood evaluation system has an effective grasp on the probability of inundation for storm sewer systems.

Lee, Cheng-Shang; Ho, Hsin-Ya; Lee, Kwan Tun; Wang, Yu-Chi; Guo, Wen-Dar; Chen, Delia Yen-Chu; Hsiao, Ling-Feng; Chen, Cheng-Hsin; Chiang, Chou-Chun; Yang, Ming-Jen; Kuo, Hung-Chi

2013-12-01

87

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

NASA Astrophysics Data System (ADS)

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.

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

2008-07-01

88

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

NASA Astrophysics Data System (ADS)

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.

Ghostine, Rabih; Viswanadhapalli, Yesubabu; Hoteit, Ibrahim

2014-05-01

89

Use of weather radar for flood forecasting in the Sieve River Basin: A sensitivity analysis  

SciTech Connect

Weather radar, in combination with a distributed rainfall-runoff model, promises to significantly improve real-time flood forecasting. This paper investigates the value of radar-derived precipitation in forecasting streamflow in the Sieve River basin, near Florence, Italy. The basin is modeled with a distributed rainfall-runoff model that exploits topographic information available from digital elevation maps. The sensitivity of the flood forecast to various properties of the radar-derived rainfall is studied. It is found that use of the proper radar reflectivity-rainfall intensity (Z-R) relationship is the most crucial factor in obtaining correct flood hydrographs. Errors resulting from spatially averaging radar rainfall are acceptable, but the use of discrete point information (i.e. raingage) can lead to serious problems. Reducing the resolution of the 5-min radar signal by temporally averaging over 15 and 30 min does not lead to major errors. Using 3-bit radar data (rather than the usual 8-bit data) to represent intensities results in significant operational savings without serious problems in hydrograph accuracy. 24 refs., 28 figs., 2 tabs.

Pessoa, M.L.; Bras, R.L.; Williams, E.R. (Massachusetts Inst. of Technology, Cambridge (United States))

1993-03-01

90

Enforced self-organizing map neural networks for river flood forecasting  

NASA Astrophysics Data System (ADS)

Self-organizing maps (SOMs) have been successfully accepted widely in science and engineering problems; not only are their results unbiased, but they can also be visualized. In this study, we propose an enforced SOM (ESOM) coupled with a linear regression output layer for flood forecasting. The ESOM re-executes a few extra training patterns, e.g. the peak flow, as recycling input data increases the mapping space of peak flow in the topological structure of SOM, and the weighted sum of the extended output layer of the network improves the accuracy of forecasting peak flow. We have investigated an ESOM neural network by using the flood data of the Da-Chia River, Taiwan, and evaluated its performance based on the results obtained from a commonly used back-propagation neural network. The results demonstrate that the ESOM neural network has great efficiency for clustering, especially for the peak flow, and super capability of modelling the flood forecast. The topology maps created from the ESOM are interesting and informative. Copyright

Chang, Fi-John; Chang, Li-Chiu; Wang, Yan-Shiang

2007-03-01

91

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

NASA Astrophysics Data System (ADS)

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.

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

2014-05-01

92

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)

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.

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

2013-04-01

93

Biggert-Waters Flood Insurance Program Act of 2012: Preliminary Fact Sheet Established in 1968, the National Flood Insurance Program (NFIP) is the sole provider of flood  

E-print Network

Biggert-Waters Flood Insurance Program Act of 2012: Preliminary Fact Sheet Background Established in 1968, the National Flood Insurance Program (NFIP) is the sole provider of flood insurance in the United of disaster relief. The NFIP constructs Flood Insurance Rate Maps (FIRM) designating every location

94

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

Federal Register 2010, 2011, 2012, 2013

...Comment Request; National Flood Insurance Program Claim Forms AGENCY...of information related to the flood insurance claims process. DATES: Comments...SUPPLEMENTARY INFORMATION: The National Flood Insurance Program (NFIP) is...

2013-07-30

95

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

Federal Register 2010, 2011, 2012, 2013

...Comment Request; National Flood Insurance Program Claims Appeals Process...concerning revision of the National Flood Insurance Claims Appeals Process. The...process, FEMA sends the NFIP Flood Insurance Claims Handbook to the...

2011-10-18

96

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

Federal Register 2010, 2011, 2012, 2013

...Formerly 3067-AD02) National Flood Insurance Program (NFIP); Insurance...NPRM) concerning National Flood Insurance Program (NFIP) insurance premium...structures to pay a higher premium for flood insurance if they declined an offer...

2012-05-30

97

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

NASA Astrophysics Data System (ADS)

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.

Van Steenbergen, N.; Willems, P.

2012-04-01

98

Historical Floods in the Northeast  

NSDL National Science Digital Library

This site reviews major flooding in the Northeastern United States, as reported by the Northeast River Forecast Center (NERFC), a division of the National Weather Service. It includes photos, rainfall maps, and descriptions of record-breaking floods that occured between the years 1927 and 1996. Descriptions include specific causes of flooding, weather patterns leading up to flooding, as well as results and actions taken due to flooding in the regions discussed.

99

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

NASA Astrophysics Data System (ADS)

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

Tao, Jing; Barros, Ana P.

2013-12-01

100

Flood and Fire Monitoring and Forecasting Within the Chornobyl Exclusion Zone  

NASA Astrophysics Data System (ADS)

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.

Los, Victor

2001-03-01

101

Integrating Neural Networks and Conceptual Modelling for Flood Forecasting on the Tiber River  

NASA Astrophysics Data System (ADS)

The Tiber River has a catchment area of approximately 17,000 km2. The river crosses 6 regions and is about 300 km in length. This study is focused on the bottom part of the catchment, between Rome and the Corbara dam, which is located approximately 150 km north of Rome, with a reservoir active storage of 165 hm3. The area from Corbara dam (11,000 km2) can be subdivided into 37 ungauged and 3 gauged sub-basins. At the bottom of the basin is the city of Rome, which is at risk from flooding when extreme events with a return period of about 200 years occur. Both conceptual modeling and Artificial Neural Networks (ANNS) have already been applied individually to forecasting historical floods for the city of Rome. The results of both models are promising but each one has different strengths. This study considers how hybrid techniques can be applied to the integration of both conceptual and ANN models to improve their performance further. Integration of the individual models using different techniques from the field of data fusion is investigated. Models are developed to predict hourly water levels at Ripetta gauging station in Rome for a lead time of 12 and 18 hours. Model performance is assessed using a series of absolute and relative performance measures as well as a visual inspection of the hydrograph. Keywords: real-time forecasting, flooding, rainfall-runoff modelling, Artificial Neural Networks.

Napolitano, G.; See, L.; Savi, F.

2009-04-01

102

Short period forecasting of catchment-scale precipitation. Part II: a water-balance storm model for short-term rainfall and flood forecasting  

Microsoft Academic Search

A simple two-dimensional rainfall model, based on advection and conservation of mass in a vertical cloud column, is investigated for use in short-term rainfall and flood forecasting at the catchment scale under UK conditions. The model is capable of assimilating weather radar, satellite infra-red and surface weather observations, together with forecasts from a mesoscale numerical weather prediction model, to obtain

V. A. Bell; R. J. Moore

2000-01-01

103

Data assimilation method for real-time flash flood forecasting using a physically based distributed model  

NASA Astrophysics Data System (ADS)

The MARINE model (Roux et al, 2011) is a physically based distributed model dedicated to real time flash flood forecasting on small to medium catchments. The infiltration capacity is evaluated by the Green and Ampt equation and the surface runoff calculation is divided into two parts: the land surface flow and the flow in the drainage network both based on kinematic wave hypothesis. In order to take into account rainfall spatial-temporal variability as well as the various behaviours of soil types among the catchment, the model is spatially distributed, which can also help to understand the flood driving processes. The model integrates remote sensing data such as the land coverage map with spatial resolution adapted to hydrological scales. Minimal data requirements for the model are: the Digital Elevation Model describing catchment topography and the location and description of the drainage network. Moreover some parameters are not directly measurable and need to be calibrated. Most of the sources of uncertainties can be propagated thanks to variational method (Castaings et al, 2009) and finally help to determine time dependent uncertainty intervals. This study also investigates the methodology developed for real-time flash flood forecasting using the MARINE model and data assimilation techniques. According to prior sensitivity analyses and calibrations, parameters values were determined as constants or initial guess. Then a data assimilation method called the adjoint state method is used to update some of the most sensitive parameters to improve accuracy of discharges predictions. The forecast errors are evaluated as a function of lead time and discussed from an operational point of view. Multiple strategies in term of updatable parameters set, length of time window, parameters bounds and observation threshold used to trigger the assimilation method are discussed regarding accuracy, robustness and real-time feasibility.

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

2012-04-01

104

78 FR 52780 - National Flood Insurance Program (NFIP); Assistance to Private Sector Property Insurers...  

Federal Register 2010, 2011, 2012, 2013

...Docket ID FEMA-2013-0031] National Flood Insurance Program (NFIP); Assistance to Private...2013) private sector property insurers sell flood insurance policies and adjust flood insurance claims under their own names based on...

2013-08-26

105

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

Federal Register 2010, 2011, 2012, 2013

...Docket ID FEMA-2011-0020] National Flood Insurance Program (NFIP); Assistance to Private...private sector property insurers issue flood insurance policies and adjust flood insurance claims under their own names based on...

2011-07-28

106

77 FR 36566 - National Flood Insurance Program (NFIP); Assistance to Private Sector Property Insurers...  

Federal Register 2010, 2011, 2012, 2013

...Docket ID FEMA-2012-0018] National Flood Insurance Program (NFIP); Assistance to Private...2012) private sector property insurers sell flood insurance policies and adjust flood insurance claims under their own names based on...

2012-06-19

107

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

USGS Publications Warehouse

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.

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

2011-01-01

108

FUNDAMENTAL STUDY ON REAL-TIME FLOOD FORECASTING METHOD FOR LOCALLY HEAVY RAINFALL IN URBAN DRAINAGE AREAS  

NASA Astrophysics Data System (ADS)

Recently, locally heavy rainfall occurs frequently at highly urbanized area, and causes serious personal accidents, so importance of flood forecasting system is growing in order to reduce damage of inundation. However, flood forecasting that secured lead-time for evacuation is extremely difficult, because the rainfall flows out rapidly. In this study, the numerical simulation model that can finely express inundation mechanism of urban drainage areas was applied with the most recent available data and analysis tool. The influence of the factor (i.e. sewer system, overland and rainfall information) which affected inundation mechanism was evaluated through the sensibility analysis with this model, and evaluation results show some requirements of model condition and information on time and space resolution of real-time flood forecasting.

Kimura, Makoto; Kido, Yoshinobu; Nakakita, Eiichi

109

Integrating lightening information into real-time flash flood forecasting and warning procedures  

NASA Astrophysics Data System (ADS)

This work will combine the algorithm systems developed by the projects HYDRATE and FLASH to provide an assessment of the possibility of integrating lightening information into real-time flash flood forecasting and warning procedures. Realtime lightning and radar rainfall data will be used to extrapolate storm motion forward in time, based on their history over the last hour. This will afford advection of the lightning activity, convective cells and rainfall maxima, tracking the convective cells continuously. The system will provide a stream of information about cell history, i.e. the direction of motion, the velocity of the cells, and whether the cells are intensifying or decaying. This information will be supplied to fully distributed hydrological models, in order to evaluate the gaining in short-term forecasting (lead time and reduction of uncertainty) permitted by the inclusion of lightening information. This work will be carried out based on data made available for a flash flood event, occurred in in Piemonte on 14-15 September 2006.

Borga, Marco; Lagouvardos, Kostas; Llasat, Maria Carmen; Mugnai, Alberto; Price, Colin; Tarolli, Paolo

2010-05-01

110

Development of a short-term river flood forecasting method for snowmelt driven floods based on wavelet and cross-wavelet analysis  

NASA Astrophysics Data System (ADS)

SummaryIn this study, a new method of stand-alone short-term spring snowmelt river flood forecasting was developed based on wavelet and cross-wavelet analysis. Wavelet and cross-wavelet analysis were used to decompose flow and meteorological time series data and to develop wavelet based constituent components which were then used to forecast floods 1, 2, and 6 days ahead. The newly developed wavelet forecasting method (WT) was compared to multiple linear regression analysis (MLR), autoregressive integrated moving average analysis (ARIMA), and artificial neural network analysis (ANN) for forecasting daily stream flows with lead-times equal to 1, 2, and 6 days. This comparison was done using data from the Rideau River watershed in Ontario, Canada. Numerical analysis was performed on daily maximum stream flow data from the Rideau River station and on meteorological data (rainfall, snowfall, and snow on ground) from the Ottawa Airport weather station. Data from 1970 to 1997 were used to train the models while data from 1998 to 2001 were used to test the models. The most significant finding of this research was that it was demonstrated that the proposed wavelet based forecasting method can be used with great accuracy as a stand-alone forecasting method for 1 and 2 days lead-time river flood forecasting, assuming that there are no significant trends in the amplitude for the same Julian day year-to-year, and that there is a relatively stable phase shift between the flow and meteorological time series. The best forecasting model for 1 day lead-time was a wavelet analysis model. In testing, it had the lowest RMSE value (13.8229), the highest R2 value (0.9753), and the highest EI value (0.9744). The best forecasting model for 2 days lead-time was also a wavelet analysis model. In testing, it had the lowest RMSE value (31.7985), the highest R2 value (0.8461), and the second highest EI value (0.8410). It was also shown that the proposed wavelet based forecasting method is not particularly accurate for longer lead-time forecasting such as 6 days, with the ANN method providing more accurate results. The best forecasting model for 6 days lead-time was an ANN model, with the wavelet model not performing as well. In testing, the wavelet model had an RMSE of 57.6917, an R2 of 0.4835, and an EI of 0.4366.

Adamowski, Jan F.

2008-05-01

111

Distributed precipitation corrections in Alpine areas for a real-time flood forecasting system  

NASA Astrophysics Data System (ADS)

This contribution presents a method for estimating spatial and temporal distributed precipitation correction factors. The approach is applied for a flood forecasting model in the Upper Enns and Upper Mur catchments in the Central Austrian Alps. Precipitation exhibits a large spatio-temporal variability in Alpine areas. Additionally the density of the monitoring network is low and measurements are subjected to major errors. This can lead to significant deficits in stream flow simulations, e.g. for flood forecasting models. Therefore precipitation correction factors are frequently applied. These correction factors are however mostly applied for whole catchments in a lumped manor, neglecting, that the magnitude of precipitation errors are spatially distributed. For the presented study a multiplicative linear correction model is therefore implemented, which enables a distribution of the correction factors as a function of elevation. The applied rainfall-runoff model COSERO is set up with a spatial resolution of 1x1km2. The correction of the rainfall pattern is thereby applied for every grid cell. To account for the local meteorological conditions, the correction model is derived for two elevation zones: (1) Valley floors to 2000 m a.s.l. and (2) above 2000 m a.s.l. to mountain peaks. Measurement errors also depend on the precipitation type, with higher magnitudes in winter months during snow fall. Therefore additionally separate correction factors for winter and summer months are estimated. The parameters for the correction model are estimated for every catchment based on independent station observations and observed and simulated runoff of the conceptual rainfall-runoff model. As driving input the INCA-precipitation fields of the Austrian Central Institute for Meteorology and Geodynamics (ZAMG) are used. Due to the mentioned errors, these precipitation fields are corrected according to the described method. The results show a significant improvement of the simulated runoff, not only concerning the long-term water balance and snow melt, but also the simulation of flood peaks.

Herrnegger, Mathew; Senoner, Tobias; Nachtnebel, Hans-Peter

2014-05-01

112

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

NASA Astrophysics Data System (ADS)

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.

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

2010-05-01

113

A conceptual and neural network model for real-time flood forecasting of the Tiber River in Rome  

NASA Astrophysics Data System (ADS)

Rome is at risk from flooding when extreme events with a return period of about 200 years occur. For this reason, an accurate real-time flood forecasting system may be a useful non-structural countermeasure. Two different approaches are considered to develop a real-time forecasting system capable of predicting hourly water levels at Ripetta stream gauging station in Rome. The first is an adaptive, conceptual model (TFF model), which consists of a rainfall-runoff model that simulates the contribution of 41 ungauged sub-basins (covering approximately 30% of the catchment area) of the Tiber River and a hydraulic model to route the flood through the hydrographic network. The rainfall-runoff model is calibrated online during each flood event at every time step via an adaptive procedure while the flood routing model parameters were calibrated offline and held constant during the forecast. The second approach used is a data-driven one through the application of an artificial neural network (TNN model). Feedforward networks trained with backpropagation and Bayesian regularization were developed using a continuous historical dataset. Both models were used to forecast the most recent significant floods that occurred in Rome (November 2005 and December 2008) with lead times of 12 and 18 h. The results show good performance using both models when compared with observations for a series of absolute and relative performance measures as well as a visual inspection of the hydrographs. At present both models are suitable for real-time forecasting and the power of an integrated approach is still to be investigated.

Napolitano, G.; See, L.; Calvo, B.; Savi, F.; Heppenstall, A.

114

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs  

NASA Technical Reports Server (NTRS)

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.

Valenti, Elizabeth; Fitzpatrick, Patrick

2006-01-01

115

Assimilation of soil moisture observations from remote sensing in operational flood forecasting  

NASA Astrophysics Data System (ADS)

Flooding and the resulting damages occurred in Europe in recent decades showed that the need of a preparation to critical events can be considered as a key factor in reducing their impact on society. It has been shown that early warning systems may reduce significantly the direct and indirect damages and costs of a flood impact. In order to improve the forecasting systems, data assimilation methods were proposed in the last years to integrate real-time observations into hydrological and hydrodynamic models. The aim of this work is to assimilate observations of soil moisture into an operational flood forecasting system in Italy in order to evaluate the effect on the water level along the main river channel. The methodology is applied in the Bacchiglione catchment, located in the North of Italy, having a drainage area of about 1400 km2, length of main reach of 118km and average discharge of 30m3/s at Padova. In order to represent this system, the Bacchiglione basin was considered as a set of different sub-basins characterized by its own hydrologic response and connected each other mainly by propagation phenomena. A 1D hydrodynamic model was then used to estimate water level along the main channel. The assimilation of the soil moisture observations was carried out using a variant of the Kalman filter-based technique. The main idea of this study was to update the model state (the soil water capacity) as response of the distributed information of soil moisture, and then estimate the flow hydrograph at the basin outlet. As a basis we used the approach by Brocca et al.(2012), using a different model structure and with adaption allowing for real-time use. The results of this work show how the added value of soil moisture into the hydrological model can improve the forecast of the flow hydrograph and the consequent water level in the main channel. This study is part of the FP7 European Project WeSenseIt. [1] Brocca, L., Moramarco, T., Melone, F., Wagner, W., Hasenauer, S., and Hahn, S. (2012) Assimilation of Surface- and Root-Zone ASCAT Soil Moisture Products Into Rainfall-Runoff Modeling, IEEE Transactions on Geoscience and Remote Sensing, 50(7), 2542-2555

Mazzoleni, Maurizio; Alfonso, Leonardo; Ferri, Michele; Monego, Martina; Norbiato, Daniele; Solomatine, Dimitri P.

2014-05-01

116

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

Code of Federal Regulations, 2012 CFR

... 2011-10-01 true National Flood Insurance Program B Appendix B to Part 62 Emergency...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND...

2012-10-01

117

National flood modelling for insurance purposes:using IFSAR for flood risk estimation in Europe Hydrology and Earth System Sciences, 9(4), 449456 (2005) EGU  

E-print Network

National flood modelling for insurance purposes:using IFSAR for flood risk estimation in Europe 449 Hydrology and Earth System Sciences, 9(4), 449456 (2005) © EGU National flood modelling for insurance@willis.com Abstract Flood risk poses a major problem for insurers and governments who ultimately pay the financial

Paris-Sud XI, Université de

118

A 110-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe Floods of 200307*  

E-print Network

A 1­10-Day Ensemble Forecasting Scheme for the Major River Basins of Bangladesh: Forecasting Severe of the Brahmaputra and Ganges Rivers as they flow into Bangladesh; it has been operational since 2003. The Bangladesh points of the Ganges and Brahmaputra into Bangladesh. Forecasts with 1­10-day horizons are presented

Webster, Peter J.

119

FORECASTING FLOOD HYDROGRAPHS at TIBER RIVER BASIN in ITALY by ARTIFICIAL NEURAL NETWORKS  

Microsoft Academic Search

Tracing the flood waves in natural rivers in order to mitigate flood damages is a challenging problem for engineers. To this end, engineers have strived to develop hydrologic and hydraulic methods to predict flood hydrographs. Hydraulic methods are based on solving flood wave equations that require complex numerical tech- niques while the hydrologic methods route flood wave using only the

G. TAYFUR; T. MORAMARCO

120

National flood modelling for insurance purposes: using IFSAR for flood risk estimation in Europe  

Microsoft Academic Search

Flood risk poses a major problem for insurers and governments who ultimately pay the financial costs of losses resulting from flood events. Insurers therefore face the problem of how to assess their exposure to floods and how best to price the flood element of their insurance products. This paper looks at the insurance implications of recent flood events in Europe

R. Sanders; F. Shaw; H. Mackay; H. Galy; M. Foote

2005-01-01

121

The HBV spatially distributed flash flood forecasting model - The Slovenia case study  

NASA Astrophysics Data System (ADS)

The HBV distributed flash flood forecasting model which is in operational use in northern Austria is applied to a watershed in northwest Slovenia, a case study for the FP6 project HYDRATE. The selected watershed consists of 6 sub-basins with a total area of 646 Km2. Model setup and calibration was performed in this watershed and three long duration rainfall - runoff periods were simulated in order to examine the efficiency of the model. The selected periods included rainfall events that produced high outflows on the exit of the watershed, such as the September 2007 event that caused a flash flooding and severe damages to the towns of Zali Log and Zelezniki. The model uses 1km grid rainfall and temperature data of fifteen minute time intervals in order to simulate the rainfall - runoff process. Inverse distance weighting interpolation is used in order to generate the spatially distributed rainfall and temperature while the hydrological parameters are defined for each 1km grid cell that correspond to one hydrological response units (HRU - areas with analogous hydrogeological characteristics). The basic calibration of the HBV model is based on hydrological parameters of each HRU, parameters that control the rainfall - runoff process within the basin and non HRU parameters that control the river routing between the basins. The model performance is based on seven efficiency criteria that were selected as appropriate for long simulation periods, e.g. coefficient of determination R2 and Nash Sutcliffe efficiency E. The HBV model produced satisfactory results for the three rainfall periods and could be used as an operational model in Slovenia as well.

Tsanis, I. K.; Grillakis, M. G.; Blöschl, G.; Poga?nik, N.

2009-04-01

122

Floods  

MedlinePLUS

... rainfall , topography, flood-control measures, river-flow and tidal-surge data, and changes due to new construction ... may be electrically charged from underground or downed power lines. Flooding may have caused familiar places to ...

123

Flash Flood Early Warning System Reference Guide  

NSDL National Science Digital Library

The Flash Flood Warning System Reference Guide is intended to promote the implementation of flash flood early warning systems based upon proven and effective methods already in use in flash-flood prone nations around the world. Both governmental and non-governmental decision makers can use it to better understand flash floods and the elements that constitute a robust, end-to-end flash flood early warning system. The guide includes chapters on Flash Flood Science, Flash Flood Forecasting Methods, Monitoring Networks, Technology Infrastructure, Warning Dissemination and Notification, and Community-based Disaster Management, and offers several examples of warning systems.

Comet

2011-10-18

124

Can end-users' flood management decision making be improved by information about forecast uncertainty?  

NASA Astrophysics Data System (ADS)

In the course of the D-PHASE project, a visualisation platform was created, which provided a large amount of meteorological and hydrological information that was used not only by scientists, but also by scientifically aware laypeople in the field of flood prevention. This paper investigates the benefits of the platform for its end-users' situation analysis and decision making, and in particular, its usefulness in providing an ensemble of models instead of already interpreted forecasts. To evaluate the platform's impact on users in Switzerland, a panel approach was used. Twenty-four semi-standardized questionnaires were completed at the beginning of the demonstration phase and 27 questionnaires were completed five months later. The results suggest that the platform was perceived as adding value to both situation analysis and decision making, and helped users to feel more confident about both. Interestingly, users' preference for receiving complex, primary information and forming their own impressions over receiving interpreted information and recommendations increased during the demonstration phase. However, no actual improvement in the quality of decisions was reported.

Frick, J.; Hegg, C.

2011-05-01

125

Kalman filtering correction in real-time forecasting with hydrodynamic model * * Project supported by the National Science and Technology Planning (Grant No. 2006BAC05B02)  

Microsoft Academic Search

Accurate and reliable flood forecast is crucial for efficient real-time river management, including flood control, flood warning, reservoir operation and river regulation. In order to improve the estimate of the initial state of the forecasting system and to reduce the errors in the forecast period a data assimilation procedure was often need. The Kalman filter was proven to be an

Xiao-ling WU; Chuan-hai WANG; Xi CHEN; Xiao-hua XIANG; Quan ZHOU

2008-01-01

126

Reanalysis of U.S. National Weather Service Flood Loss Database  

E-print Network

Reanalysis of U.S. National Weather Service Flood Loss Database Mary W. Downton1 ; J. Zoe Barnard by floods" [42 U.S.C. §4102(c)(3)]. Researchers evaluat- ing the program would like to isolate the effect Miller2 ; and Roger A. Pielke Jr.3 Abstract: To understand the nature of increasing flood damage

Colorado at Boulder, University of

127

A Multiseason Climate Forecast System at the National Meteorological Center  

Microsoft Academic Search

The Coupled Model Project was established at the National Meteorological Center(NMC)in January l991 to develop a multiseason forecast system based on coupled ocean atmosphere general circulation models. This provided a focus to combine expertise in near real-time ocean modeling and analyses situated in the Climate Analysis Center (CAC) with expertise in atmospheric modeling and data assimilation in the Development Division.

Ming Ji; Arun Kumar; Ants Leetmaa

1994-01-01

128

NatioNal aNd Global Forecasts West VirGiNia ProFiles aNd Forecasts  

E-print Network

· NatioNal aNd Global Forecasts · West VirGiNia ProFiles aNd Forecasts · eNerGy · Healt Department of Revenue Jeff Herholdt Director, West Virginia Division of Energy Tom Jones President & CEO 17 Employment 17 Income 17 Population 17 Energy 17 Healthcare 20 Wholesale and Retail Trade 20

Mohaghegh, Shahab

129

Identification of hydrological model parameters for flood forecasting using data depth measures  

NASA Astrophysics Data System (ADS)

The development of methods for estimating the parameters of hydrological models considering uncertainties has been of high interest in hydrological research over the last years. Besides the very popular Markov Chain Monte Carlo (MCMC) methods which estimate the uncertainty of model parameters in the settings of a Bayesian framework, the development of depth based sampling methods, also entitled robust parameter estimation (ROPE), have attracted an increasing research interest. These methods understand the estimation of model parameters as a geometric search of a set of robust performing parameter vectors by application of the concept of data depth. Recent studies showed that the parameter vectors estimated by depth based sampling perform more robust in validation. One major advantage of this kind of approach over the MCMC methods is that the formulation of a likelihood function within a Bayesian uncertainty framework gets obsolete and arbitrary purpose-oriented performance criteria defined by the user can be integrated without any further complications. In this paper we present an advanced ROPE method entitled the Advanced Robust Parameter Estimation by Monte Carlo algorithm (AROPEMC). The AROPEMC algorithm is a modified version of the original robust parameter estimation algorithm ROPEMC developed by Bárdossy and Singh (2008). AROPEMC performs by merging iterative Monte Carlo simulations, identifying well performing parameter vectors, the sampling of robust parameter vectors according to the principle of data depth and the application of a well-founded stopping criterion applied in supervised machine learning. The principals of the algorithm are illustrated by means of the Rosenbrock's and Rastrigin's function, two well known performance benchmarks for optimisation algorithms. Two case studies demonstrate the advantage of AROPEMC compared to state of the art global optimisation algorithms. A distributed process-oriented hydrological model is calibrated and validated for flood forecasting in a small catchment characterised by extreme process dynamics.

Krauße, T.; Cullmann, J.

2011-03-01

130

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

NASA Astrophysics Data System (ADS)

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.

Liu, P.

2013-12-01

131

Flood insurance--why have it? Where can I buy it? NOAA/National Weather Service Des Moines, Iowa  

E-print Network

Flood insurance--why have it? Where can I buy it? NOAA/National Weather Service ­ Des Moines, Iowa June 2010 Thank you for your interest in flood insurance. Below are frequently asked questions and answers regarding flood insurance and the related National Flood Insurance Program (NFIP

132

Floods  

MedlinePLUS

... quickly, often have a dangerous wall of roaring water. The wall carries rocks, mud, and rubble and can sweep away most things in its path. Be aware of flood hazards no matter where you live, but especially if you live ...

133

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

SciTech Connect

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).

Gerald Sehlke; Paul Wichlacz

2010-12-01

134

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

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.

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

2002-01-01

135

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

NASA Astrophysics Data System (ADS)

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

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

2013-10-01

136

Use of ASCAT derived soil moisture product for real-time flood forecasting in the Upper Tiber River  

NASA Astrophysics Data System (ADS)

The role and the importance of soil moisture for meteorological, agricultural and hydrological applications is widely acknowledged. In particular, for a given storm event, different values of initial soil moisture conditions can discriminate between minor or catastrophic effects. Therefore, a real time flood forecasting system founded on a rainfall-runoff model strictly requires an accurate estimation of the initial state of the catchment wetness to obtain a reliable estimation of the flood hydrograph. It has to be pointed out that, in flood-prone areas, a Flood Monitoring and Warning System operating in real time represents the main non-structural measure to be actuated to dampen the risk. At the catchment scale, soil moisture monitoring can be addressed by using sensors operating on remote sensing platforms. Among them, the coarse resolution scatterometers have been employed in different studies due to their high temporal resolution suitable for hydrological applications. Specifically, the Advanced Scatterometer (ASCAT) on-board of the Meteorological Operational satellite provides an operative surface soil moisture product available at global scale since March 2007. This sensor is characterized by a spatial resolution of 25/50 km and a nearly daily time step. To get profile soil moisture estimates, an exponential filter is applied to the time series of the ASCAT surface soil moisture obtaining the so-called Soil Wetness Index (SWI). The reliability of the SWI was recently evaluated through the comparison both with in-situ and modelled soil moisture data in the Upper Tiber River basin. In this study, the effects of assimilating satellite-derived soil moisture estimates into a continuous and distributed rainfall-runoff model, named MISDc, were assessed. This topic is relevant not only for scientific purposes but also for operational applications. In fact, the MISDc model is actually operative at the Umbria Region Functional Centre for real time flood forecasting in the Upper Tiber River (~5300 km2). The model is based on the coupling of a simple soil water balance and an event-based rainfall-runoff model through an experimentally derived relationship. Therefore, MISDc is characterized by a parsimonious structure and parameterization and, at the same time, a high computational speed that is crucial for real time operational purposes. By using simple data assimilation techniques, the SWI derived by ASCAT was assimilated into MISDc and the model performance on flood estimation, with and without assimilation, was compared. In particular, two significant flood events occurred on December 2008 and January 2010 that produced flooding and damages were carefully investigated. Moreover, three synthetic experiments considering errors on rainfall, model parameters and initial soil wetness conditions were carried out in order to further ascertain the SWI potential when uncertain conditions take place. Results reveal that the ASCAT soil moisture estimates can be conveniently used to improve runoff prediction in the study area. These products become essential when the soil wetness conditions before a storm event are highly uncertain or unknown.

Brocca, Luca; Melone, Florisa; Moramarco, Tommaso; Wagner, Wolfgang; Hasenauer, Stefan; Berni, Nicola

2010-05-01

137

EXPANDING THE NATIONAL FLOOD INSURANCE PROGRAM TO COVER COASTAL EROSION DAMAGE  

Microsoft Academic Search

The National Flood Insurance Program does not currently cover damage strictly attributable to coastal erosion. This paper uses the results of a nationwide survey of coastal property owners to estimate the demand for such insurance. We find that there is significant demand at prices in the range of current flood insurance premiums. Demand is influenced in the hypothesized way by

Andrew G. Keeler; Warren Kriesel; Craig E. Landry

2000-01-01

138

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,...

139

Operational hydro-meteorological warning and real-time flood forecasting:the Piemonte region case study Hydrology and Earth System Sciences, 9(4), 457466 (2005) EGU  

E-print Network

data, available since the year 1800, the Piedmont Region is hit by calamitous meteorological eventsOperational hydro-meteorological warning and real-time flood forecasting:the Piemonte region case study 457 Hydrology and Earth System Sciences, 9(4), 457466 (2005) © EGU Operational hydro-meteorological

Paris-Sud XI, Université de

140

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

NASA Astrophysics Data System (ADS)

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

Kasiviswanathan, K.; Sudheer, K.

2013-05-01

141

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

Federal Register 2010, 2011, 2012, 2013

...intends to prepare an Environmental Impact Statement evaluating the impacts on the quality of the human environment of the National Flood...actions that would have significant impacts to the quality of the human environment. FEMA is...

2012-05-16

142

A distributed model for real-time flood forecasting using digital elevation models  

Microsoft Academic Search

A distributed model for real-time rainfall-runoff simulation during floods is presented. The model, called Distributed Basin Simulator (DBSIM) is based on the detailed topographical information provided by Digital Elevation Models (DEM). Basin representation uses the rectangular grid of the DEM. Soil properties, input data and state variables are also represented as data layers using the same scheme. Distributed rainfall input

Luis Garrote; Rafael L. Bras

1995-01-01

143

The Design and Implementation of a Real-Time Flood Forecasting System in Durban, South Africa  

Microsoft Academic Search

In South Africa, five flood events during the period 1994-1996 resulted in the loss of 173 lives, more than 7000 people requiring evacuation and\\/or emergency shelter and damages to the value of R680 million (White paper on Disaster Management 1998). The South African Disaster management bill provides for \\

Scott Sinclair; Geoff Pegram

2003-01-01

144

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

E-print Network

and Environmental Engineering, Institute for Dam Safety Risk Management, Utah Water Research Laboratory, Utah State-line Planning Mode, the Reservoir Release Forecast Model (RRFM) is being used to test alternatives operating in addition to developing and testing operating rule changes, including possible pre-release strategies

Bowles, David S.

145

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)

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.

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

2014-05-01

146

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

NASA Astrophysics Data System (ADS)

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.

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

2011-08-01

147

USGS Surface Water Information: Flood Information  

NSDL National Science Digital Library

This site from the USGS Office of Surface Water provides access to many resources and data sets about current and past flooding events in the United States. There are links to maps showing current water conditions, 28 day National Weather Service forecasts, Water Science Centers in the various states, as well as national and local flooding resources. There are also links to other parts of the USGS Surface Water Information site which host a variety of data and information resources.

Water, Usgs O.

148

Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product  

E-print Network

Numerous time series models are available for forecasting economic output. Autoregressive models were initially applied to US gross national product (GNP), and have been extended to nonlinear structures, such as the ...

Arora, Siddharth

149

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

NASA Astrophysics Data System (ADS)

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.

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

2014-05-01

150

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)

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.

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

2011-12-01

151

Flood forecasting by the filter separation AR method and comparison with modeling efficiencies by some rainfall-runoff models  

NASA Astrophysics Data System (ADS)

In this paper, the authors firstly propose a flood forecasting system with and without rainfall data, applying the filter separation AR method. The runoff time series are separated sequentially into two runoff components. Since each hydrologic subsystem is expressible by linear input-output relationships, the rainfall components are inversely estimated from the ARX model or from the response function type model. Future runoff is computed by the ARX or the response function type model utilizing the inversely estimated effective past rainfalls and the extrapolated future rainfalls as input, and, as for the shorter-period runoff, using also the past rainfall data. Secondly, we calculate and compare modeling efficiencies for four rainfall-runoff models. The four models are (1) the filter separation AR model, (2) and (3) two l inds of the generalized storage function model (Prasad model and Hoshi model) to which Karman filtering theory is applied, and (4) the tank model. The generalized storage function method contains the nonlinearity in the runoff equation itself and the single component nonlinear model. The filter separation AR method is composed of linear subsystems, and the nonlinearity of the total system is explained by the nonlinearity of the rainfall separation process into subsystems and the multicomponent model.

Hasebe, Masahiko; Hino, Mikio; Hoshi, Kiyoshi

1989-09-01

152

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)

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.

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

2007-12-01

153

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

NASA Astrophysics Data System (ADS)

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.

Klotz, Daniel; Nachtnebel, Hans Peter

2014-05-01

154

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

SciTech Connect

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.

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

2010-11-01

155

High-resolution flash flood forecasting for large urban areas - Sensitivity to scale of precipitation input and model resolution  

NASA Astrophysics Data System (ADS)

Urban flash flooding is a serious problem in large, highly populated areas such as the Dallas-Fort Worth Metroplex (DFW). Being able to monitor and predict flash flooding at a high spatiotemporal resolution is critical to mitigating its threat and cost-effective emergency management. The higher the resolution of the model and the precipitation input is, the better the spatiotemporal specificity of the model output is. Due to errors in the precipitation input, the model parameters and the model itself, however, there are practical limits to the scale of modeling. In this work, we assess this scale dependence using the National Weather Service (NWS) Hydrology Laboratory's Distributed Hydrologic Model (HL-RDHM) at different spatiotemporal resolutions ranging from ~250 m to ~4 km and from 1min to 1 hour for a large part of DFW. The high-resolution precipitation input is from the DFW Demonstration Network of CASA radars. The model simulation results are evaluated using the water level data obtained from the Cities of Fort Worth, Arlington and Grand Prairie in DFW.

rafieei nasab, A.; Norouzi, A.; Seo, D.; Kim, S.; Chen, H.; Chandrasekar, C. V.; Cosgrove, B.; Cannon, A.

2013-12-01

156

Robust multi-objective calibration strategies - chances for improving flood forecasting  

NASA Astrophysics Data System (ADS)

Process-oriented rainfall-runoff models are designed to approximate the complex hydrologic processes within a specific catchment and in particular to simulate the discharge at the catchment outlet. Most of these models exhibit a high degree of complexity and require the determination of various parameters by calibration. Recently automatic calibration methods became popular in order to identify parameter vectors with high corresponding model performance. The model performance is often assessed by a purpose-oriented objective function. Practical experience suggests that in many situations one single objective function cannot adequately describe the model's ability to represent any aspect of the catchment's behaviour. This is regardless whether the objective is aggregated of several criteria that measure different (possibly opposite) aspects of the system behaviour. One strategy to circumvent this problem is to define multiple objective functions and to apply a multi-objective optimisation algorithm to identify the set of Pareto optimal or non-dominated solutions. One possible approach to estimate the Pareto set effectively and efficiently is the particle swarm optimisation (PSO). It has already been successfully applied in various other fields and has been reported to show effective and efficient performance. Krauße and Cullmann (2011b) presented a method entitled ROPEPSO which merges the strengths of PSO and data depth measures in order to identify robust parameter vectors for hydrological models. In this paper we present a multi-objective parameter estimation algorithm, entitled the Multi-Objective Robust Particle Swarm Parameter Estimation (MO-ROPE). The algorithm is a further development of the previously mentioned single-objective ROPEPSO approach. It applies a newly developed multi-objective particle swarm optimisation algorithm in order to identify non-dominated robust model parameter vectors. Subsequently it samples robust parameter vectors by the application of data depth metrics. In a preliminary assessment MO-PSO-GA is compared with other multi-objective optimisation algorithms. In the frame of a real world case study MO-ROPE is applied identifying robust parameter vectors of a distributed hydrological model with focus on flood events in a small, pre-alpine, and fast responding catchment in Switzerland. The method is compared with existing robust parameter estimation methods.

Krauße, T.; Cullmann, J.; Saile, P.; Schmitz, G. H.

2011-04-01

157

Effects of Floods on Brook Trout Populations in the Monongahela National Forest, West Virginia  

Microsoft Academic Search

The objectives of this study were to describe the effects of the January and May 1996 floods on the stream habitat features, redds of brook trout Salvelinus fontinalis, and brook trout density in 14 headwater streams in the Monongahela National Forest, West Virginia. We measured stream habitat features, estimated wild brook trout density, and mapped brook trout redds in summer

Robert F. Carline; Brian J. McCullough

2003-01-01

158

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

NASA Astrophysics Data System (ADS)

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.

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

2014-05-01

159

Beach erosion rates and the National Flood Insurance Program  

Microsoft Academic Search

Thirty of the nation's 50 states have coastlines on the Atlantic and Pacific oceans, the Gulf of Mexico, and the Great Lakes. These 30 states contain approximately 85% of the nation's population, and about half of this population resides in the coastal zone. Continued population growth is projected in the future, with a greatly increasing demand for beachfront development. At

Stephen P. Leatherman; Robert G. Dean

1991-01-01

160

Beach erosion rates and the National Flood Insurance Program  

NASA Astrophysics Data System (ADS)

Thirty of the nation's 50 states have coastlines on the Atlantic and Pacific oceans, the Gulf of Mexico, and the Great Lakes. These 30 states contain approximately 85% of the nation's population, and about half of this population resides in the coastal zone. Continued population growth is projected in the future, with a greatly increasing demand for beachfront development. At present, there is considerable public concern over coastal erosion, erosion control measures, and land use regulations [National Research Council, 1990].Beach erosion is a significant and growing national problem. The National Shoreline Study, conducted by the U.S. Army Corps of Engineers in 1971, was the first national appraisal of shore erosion problems. Significant erosion was found to occur along 43% of the U.S. shoreline if Alaska is excluded. Other large sections of sandy shoreline are also eroding, but the U.S. Army Corps of Engineers categorized it as noncritical erosion largely because of the lack of immediate threat to buildings and infrastructure at that time.

Leatherman, Stephen P.; Dean, Robert G.

161

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

NASA Astrophysics Data System (ADS)

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.

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

2012-04-01

162

Flood hazard assessment of the Hoh River at Olympic National Park ranger station, Washington  

USGS Publications Warehouse

Federal regulations require buildings and public facilities on Federal land to be located beyond or protected from inundation by a 100-year flood. Flood elevations, velocities and boundaries were determined for the occurrence of a 100-year flood through a reach, approximately 1-mi-long, of the Hoh River at the ranger station complex in Olympic National Park. Flood elevations, estimated by step-backwater analysis of the 100-year flood discharge through 14 channel and flood-plain cross sections of the Hoh River, indicate that the extent of flooding in the vicinity of buildings or public facilities at the ranger station complex is likely to be limited mostly to two historic meander channels that lie partly within loop A of the public campground and that average flood depths of about 2 feet or less would be anticipated in these channels. Mean flow velocities at the cross sections, corresponding to the passage of a 100-year flood, ranged from about 5 to over 11 ft/sec. Flooding in the vicinity of either the visitors center or the residential and maintenance areas is unlikely unless the small earthen dam at the upstream end of Taft Creek were to fail. Debris flows with volumes on the order of 100 to 1,000 cu yards could be expected to occur in the small creeks that drain the steep valley wall north of the ranger station complex. Historic debris flows in these creeks have generally traveled no more than about 100 yards out onto the valley floor. The potential risk that future debris flows in these creeks might reach developed areas within the ranger station complex is considered to be small because most of the developed areas within the complex are situated more than 100 yards from the base of the valley wall. Landslides or rock avalanches originating from the north valley wall with volumes potentially much larger than those for debris flows could have a significant impact on the ranger station complex. The probability that such landslides or avalanches may occur is unknown. Inspection of aerial photographs of the Hoh River valley revealed the apparent presence, along the ridge crest of the north valley wall, of ridge-top depressions--geologic features that are sometimes associated with the onset of deep-seated slope failures. However, evaluation of the potential landslide hazard associated with these depressions would require an onsite examination of the area by trained personnel. Such an effort was outside the scope of this study. (Author 's abstract)

Kresch, D.L.; Pierson, T.C.

1987-01-01

163

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

PubMed

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

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

2011-01-01

164

Participation in the National Flood Insurance Program: An Empirical Analysis for Coastal Properties  

Microsoft Academic Search

AbstractA perennial question about the National Flood Insurance Program is: how can participation be increased? An empirical analysis of individual-level data reveals that in a sample of coastal areas the participation rate is 49 percent of eligible properties. Participation responsiveness to price is inelastic, but it has been increased by the mandatory purchase requirements for mortgage borrowers. Easing conditions for

Warren Kriesel; Craig Landry

2004-01-01

165

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

Microsoft Academic Search

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,

Reno Harnish

2011-01-01

166

Flood characteristics for the New River in the New River Gorge National River, West Virginia  

USGS Publications Warehouse

The frequency and magnitude of flooding of the New River in the New River Gorge National River was studied. A steady-state, one-dimensional flow model was applied to the study reach. Rating curves, cross sections, and Manning's roughness coefficients that were used are presented in this report. Manning's roughness coefficients were evaluated by comparing computed elevations (from application of the steady-state, one-dimensional flow model) to rated elevations at U.S. Geological Survey (USGS) streamflow-gaging stations and miscellaneous-rating sites. Manning's roughness coefficients ranged from 0.030 to 0.075 and varied with hydraulic depth. The 2-, 25-, and 100-year flood discharges were esti- mated on the basis of information from flood- insurance studies of Summers County, Fayette County, and the city of Hinton, and flood-frequency analysis of discharge records for the USGS streamflow-gaging stations at Hinton and Thurmond. The 100-year discharge ranged from 107,000 cubic feet per second at Hinton to 150,000 cubic feet per second at Fayette.

Wiley, J.B.; Cunningham, M.K.

1994-01-01

167

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

USGS Publications Warehouse

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

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

2012-01-01

168

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

NASA Technical Reports Server (NTRS)

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.

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

2009-01-01

169

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

NASA Astrophysics Data System (ADS)

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.

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

2008-12-01

170

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

NASA Astrophysics Data System (ADS)

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.

Serinaldi, F.; Kilsby, C. G.

2012-04-01

171

Flooding on the Mighty Mississippi  

NSDL National Science Digital Library

This week, floodwaters of the Mississippi River crested, leading several counties in Iowa, Minnesota, Illinois, and Wisconsin to declare states of emergency. Floodwaters have reached over 22 feet in Davenport Iowa, closing in on the 1993 record water level. Davenport is perhaps particularly hard hit because it is not equipped with concrete levees, as it relies heavily on its riverfront as a tourist attraction, and city residents feel that levees would create an unsightly barrier. Also, many hydrology experts will agree that levees might not be the wisest choice for flood management because they intensify the flooding downriver. This Week's In the News features Websites dealing with Mississippi River flood data, flood management, and general water resources.Readers who wish to catch up on the situation should browse the first few news sites listed above. The first (1), coming straight from the flood frontlines, is from the Minneapolis Star Tribune giving general news about the Mississippi flood. The next two sites cover the situation in Davenport, IA and the controversy over constructing flood walls. The second site (2) is an article from the Los Angeles Times reviewing the controversy over building flood barriers in Davenport. It mentions how other Iowa towns built levees after the disastrous floods of 1965 while Davenport did not. The third site (3) is a special section of Davenport's Quad City Times entitled Flood 2001. Flood 2001 holds a small archive of recent articles about the flood from the Quad City Times along with other regional papers, hosts an online poll about installing levees, and provides video clips (RealPlayer) and still photos of the flood. It also gives shots from a "floodcam" poised along the banks of the Mississippi. The next few resources house hydrologic data. The US Geological Survey (USGS) posts real-time water data online (4). The plain-text data from all states can be accessed via a clickable map or from lists by state or by station. The National Weather Service's Quad Cities division (the "quad cities" of Davenport, Bettendorf, Moline, and Rock Island straddle the Mississippi River on the Illinois-Iowa border) provides graphs of flood stages of rivers and streams (selected using a clickable map) and real-time weather conditions, forecasts, and flood warnings online (5). Readers will probably encounter the term "100 Year Flood" while reading flood news and stage data. If you are unfamiliar with this term, which refers to the estimated probability that a flood event has a one-in-one hundred chance of occurrence in any given year, this site (7) from an environmental consulting firm gives a nice explanation of the term and its uses. Another educational site comes from the International Rivers Network. About Rivers and Dams (8), gives an overview of the function of dams (for flood control, power generation, water collection) and presents the environmental case against damming of rivers. Other sites related to the environmental impacts of flood control include Cadillac Desert (9), a supplement to the award-winning PBS documentary series on water and the control of nature, and the Powell Consortium (10), a network of research institutions dealing with water management in the arid American West. Another neat site from PBS Online is the supplement to the film "American Experience: Fatal Flood" (11), documenting the 1927 flooding of the Mississippi and its impacts on residents of Greenville, MS. The Fatal Flood site features video clips and interviews with survivors of the 1927 flood.

2001-01-01

172

PROFS to hone local storm forecasts  

NASA Astrophysics Data System (ADS)

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

Richman, Barbara T.

173

European Flood Awareness System - now operational  

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

174

Potential flood and debris hazards at Cottonwood Cove, Lake Mead National Recreation Area, Clark County, Nevada  

USGS Publications Warehouse

At Cottonwood Cove, Nevada, most of the existing dikes at the recreation sites are effective in diverting and routing floodflows, up to and including the 100-year flood, away from people and facilities. The dikes across Ranger Residence Wash and Access Road Wash at the mouth divert floods up to the 50-year recurrence interval away from residential areas. Flow and debris damage in protected areas will be relatively minor minor for floods including the 100-year flood, whereas damage caused by sediment deposition at the mouths of the washes near Lake Mohave could be significant for floods equal to or less than the 100-year flood. 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. The present dikes would be topped or breached by such flooding. (USGS)

Moosburner, Otto

1981-01-01

175

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

NASA Astrophysics Data System (ADS)

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.

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

2013-12-01

176

Modeling national flood insurance policy holding at the county scale in Florida, 1999–2005  

Microsoft Academic Search

We analyze household flood insurance purchases in Florida from 1999 to 2005, and the extent to which household insurance purchases correspond with flood mitigation activities by local governments involved in the Federal Emergency Management Agency's (FEMA) Community Rating System (CRS). Regression results indicate that household flood insurance purchases correlate strongly with local government mitigation activities, adjusting for hazard experience, hazard

Sammy Zahran; Stephan Weiler; Samuel D. Brody; Michael K. Lindell; Wesley E. Highfield

2009-01-01

177

National flood insurance and the coastal zone: a case study of hurricane Eloise  

Microsoft Academic Search

A critical assessment of published flood insurance premiums in coastal zones subject to hurricanes is presented. Direct and indirect economic consequences of underpricing coastal flood risk are discussed. Statistics used were collected in Bay County, Fla. Flood losses in this area due to hurricane Eloise are compared with losses that are predicted by the Federal Insurance Administration. The comparison raises

E. W. Shows

1977-01-01

178

Flood Proofing This report was prepared for the U.S. Army Corps of Engineers' National  

E-print Network

Local Flood Proofing Programs June 199" #12;This report was prepared for the U.S. Army Corps to reducing flood damage. As detailed in this report, it involves altering an existing building or its immediate area to prevent or minimize damage during a flood. Alterations nlay range from minor changes

US Army Corps of Engineers

179

Flooding and Schools  

ERIC Educational Resources Information Center

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,…

National Clearinghouse for Educational Facilities, 2011

2011-01-01

180

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

NASA Astrophysics Data System (ADS)

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.

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

2009-12-01

181

Table of Contents Page 2National High Magnetic Field Laboratory and Its Forecasted Impact on the Florida Economy  

E-print Network

Impact on the Florida Economy History and Evaluation of the Economic Impact of the Magnet Lab Forecasted Impact on the Florida Economy The National Science Foundation (NSF) awarded the National High generated by Magnet Lab activities across the broader statewide economy. Since 1990, the Magnet Lab has

Weston, Ken

182

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

NASA Technical Reports Server (NTRS)

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.

Dreher, Joseph G.

2009-01-01

183

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

SciTech Connect

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.

Reno Harnish

2011-08-16

184

Coupling high-resolution hydraulic and hydrologic models for flash flood forecasting and inundation mapping in urban areas - A case study for the City of Fort Worth  

NASA Astrophysics Data System (ADS)

With many diverse features such as channels, pipes, culverts, buildings, etc., hydraulic modeling in urban areas for inundation mapping poses significant challenges. Identifying the practical extent of the details to be modeled in order to obtain sufficiently accurate results in a timely manner for effective emergency management is one of them. In this study we assess the tradeoffs between model complexity vs. information content for decision making in applying high-resolution hydrologic and hydraulic models for real-time flash flood forecasting and inundation mapping in urban areas. In a large urban area such as the Dallas-Fort Worth Metroplex (DFW), there exists very large spatial variability in imperviousness depending on the area of interest. As such, one may expect significant sensitivity of hydraulic model results to the resolution and accuracy of hydrologic models. In this work, we present the initial results from coupling of high-resolution hydrologic and hydraulic models for two 'hot spots' within the City of Fort Worth for real-time inundation mapping.

Nazari, B.; Seo, D.; Cannon, A.

2013-12-01

185

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

NASA Astrophysics Data System (ADS)

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.

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

186

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

NASA Astrophysics Data System (ADS)

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.

Karamuz, Emilia; Kochanek, Krzysztof; Romanowicz, Renata

2014-05-01

187

Flood forecasting using a fully distributed model: application of the TOPKAPI model to the Upper Xixian Catchment  

NASA Astrophysics Data System (ADS)

TOPKAPI is a physically-based, fully distributed hydrological model with a simple and parsimonious parameterisation. The original TOPKAPI is structured around five modules that represent evapotranspiration, snowmelt, soil water, surface water and channel water, respectively. Percolation to deep soil layers was ignored in the old version of the TOPKAPI model since it was not important in the basins to which the model was originally applied. Based on published literature, this study developed a new version of the TOPKAPI model, in which the new modules of interception, infiltration, percolation, groundwater flow and lake/reservoir routing are included. This paper presents an application study that makes a first attempt to derive information from public domains through the internet on the topography, soil and land use types for a case study Chinese catchment - the Upper Xixian catchment in Huaihe River with an area of about 10000 km2, and apply a new version of TOPKAPI to the catchment for flood simulation. A model parameter value adjustment was performed using six months of the 1998 dataset. Calibration did not use a curve fitting process, but was chiefly based upon moderate variations of parameter values from those estimated on physical grounds, as is common in traditional calibration. The hydrometeorological dataset of 2002 was then used to validate the model, both against the outlet discharge as well as at an internal gauging station. Finally, to complete the model performance analysis, parameter uncertainty and its effects on predictive uncertainty were also assessed by estimating a posterior parameter probability density via Bayesian inference.

Liu, Z.; Martina, M. L. V.; Todini, E.

2005-10-01

188

Cost of Flooding  

MedlinePLUS

... Simulator About The National Insurance Program Residential Coverage Commercial Coverage PolicyHolder Resources Preparation & Recovery Agent Site Agent ... devastating testimonials about flooding to our Home Personified commercials. Watch Now Flood Risk Scenarios There are many ...

189

Flood Frequency Analysis  

NSDL National Science Digital Library

The Flood Frequency Analysis module offers an introduction to the use of flood frequency analysis for flood prediction and planning. Through use of rich illustrations, animations, and interactions, this module explains the basic concepts, underlying issues, and methods for analyzing flood data. Common concepts such as the 100-year flood and return periods as well as issues affecting the statistical representation of floods are discussed. Common flood data analysis methods as well as an overview of design events are also covered. As a foundation topic for the Basic Hydrologic Science course, this module may be taken on its own, but it will also be available as a supporting topic providing factual scientific information to support students in completion of the case-based forecasting modules.

Comet

2006-10-10

190

OPERATIONAL AUSTRALIA'S NATIONAL METEOROLOGICAL SERVICE  

E-print Network

resources and its oceans. We build the nation's climate record, stand ready to help protect and secure the nation's people and property, and when required we warn ­ of cyclone, storm, tsunami, fire or flood and forecasts; tidal prediction; sea level monitoring; tsunami warning; and ionospheric (space weather

Greenslade, Diana

191

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

NASA Technical Reports Server (NTRS)

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.

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

2014-01-01

192

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

NASA Astrophysics Data System (ADS)

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.

Wiesenegger, H.

2003-04-01

193

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

USGS Publications Warehouse

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/.

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

2012-01-01

194

Flash Flood Processes  

NSDL National Science Digital Library

According to NOAAâs National Weather Service, a flash flood is a life-threatening flood that begins within 6 hours--and often within 3 hours--of a causative event. That causative event can be intense rainfall, the failure of a dam, levee, or other structure that is impounding water, or the sudden rise of water level associated with river ice jams. The âFlash Flood Processesâ module offers an introduction to the distinguishing features of flash floods, the underlying hydrologic influences and the use of flash flood guidance (FFG) products. Through use of rich illustrations, animations, and interactions, this module explains the differences between flash floods and general floods and examines the hydrologic processes that impact flash flooding risk. In addition, it provides an introduction to the use of flash flood guidance (FFG) products including derivation from ThreshR and rainfall-runoff curves as well as current strengths and limitations.

Comet

2006-11-08

195

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

USGS Publications Warehouse

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)

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

1986-01-01

196

44 CFR 78.5 - Flood Mitigation Plan development.  

Code of Federal Regulations, 2010 CFR

...Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood Mitigation Plan development. A...

2010-10-01

197

44 CFR 78.5 - Flood Mitigation Plan development.  

Code of Federal Regulations, 2011 CFR

...Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood Mitigation Plan development. A...

2011-10-01

198

44 CFR 78.5 - Flood Mitigation Plan development.  

Code of Federal Regulations, 2012 CFR

...Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood Mitigation Plan development. A...

2012-10-01

199

44 CFR 78.5 - Flood Mitigation Plan development.  

Code of Federal Regulations, 2013 CFR

...Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood Mitigation Plan development. A...

2013-10-01

200

Iowa Flood Information System  

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

201

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

NASA Astrophysics Data System (ADS)

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".

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

2011-12-01

202

Weather Forecasting  

NSDL National Science Digital Library

Weather Forecasting is a set of computer-based learning modules that teach students about meteorology from the point of view of learning how to forecast the weather. The modules were designed as the primary teaching resource for a seminar course on weather forecasting at the introductory college level (originally METR 151, later ATMO 151) and can also be used in the laboratory component of an introductory atmospheric science course. The modules assume no prior meteorological knowledge. In addition to text and graphics, the modules include interactive questions and answers designed to reinforce student learning. The module topics are: 1. How to Access Weather Data, 2. How to Read Hourly Weather Observations, 3. The National Collegiate Weather Forecasting Contest, 4. Radiation and the Diurnal Heating Cycle, 5. Factors Affecting Temperature: Clouds and Moisture, 6. Factors Affecting Temperature: Wind and Mixing, 7. Air Masses and Fronts, 8. Forces in the Atmosphere, 9. Air Pressure, Temperature, and Height, 10. Winds and Pressure, 11. The Forecasting Process, 12. Sounding Diagrams, 13. Upper Air Maps, 14. Satellite Imagery, 15. Radar Imagery, 16. Numerical Weather Prediction, 17. NWS Forecast Models, 18. Sources of Model Error, 19. Sea Breezes, Land Breezes, and Coastal Fronts, 20. Soundings, Clouds, and Convection, 21. Snow Forecasting.

Nielsen-Gammon, John

1996-09-01

203

Development of a Semi-Arid, Site-Specific Flash Flood Forecasting System for the Western Region: Results, Insights and Way Forward  

Microsoft Academic Search

An increasingly drier and more variable climate trend has significantly increased the incidence of intense (extreme) precipitation events during the 20th century. This has led to a continuous growth of extreme-flood- event losses, despite the widespread problem of water scarcity. In semi-arid regions, the extremely localized and intense summertime convective storm systems cause 'short-fused' flash floods, often result in significant

S. Yatheendradas; H. Gupta; T. Wagener; C. Unkrich; D. Goodrich; M. Schaffner

2006-01-01

204

75 FR 61373 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...participation in the National Flood Insurance Program (NFIP). In addition...others to calculate appropriate flood insurance premium rates for new buildings...The corresponding preliminary Flood Insurance Rate Map (FIRM) for the...

2010-10-05

205

76 FR 26976 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...participation in the National Flood Insurance Program (NFIP). In addition...others to calculate appropriate flood insurance premium rates for new buildings...The corresponding preliminary Flood Insurance Rate Map (FIRM) for the...

2011-05-10

206

76 FR 26978 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...participation in the National Flood Insurance Program (NFIP). In addition...others to calculate appropriate flood insurance premium rates for new buildings...The corresponding preliminary Flood Insurance Rate Map (FIRM) for the...

2011-05-10

207

75 FR 59188 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...participation in the National Flood Insurance Program (NFIP). In addition...others to calculate appropriate flood insurance premium rates for new buildings...The corresponding preliminary Flood Insurance Rate Map (FIRM) for the...

2010-09-27

208

75 FR 61371 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...participation in the National Flood Insurance Program (NFIP). In addition...others to calculate appropriate flood insurance premium rates for new buildings...The corresponding preliminary Flood Insurance Rate Map (FIRM) for the...

2010-10-05

209

76 FR 39063 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...participation in the National Flood Insurance Program (NFIP). In addition...others to calculate appropriate flood insurance premium rates for new buildings...The corresponding preliminary Flood Insurance Rate Map (FIRM) for the...

2011-07-05

210

75 FR 55527 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...participation in the National Flood Insurance Program (NFIP). In addition...others to calculate appropriate flood insurance premium rates for new buildings...The corresponding preliminary Flood Insurance Rate Map (FIRM) for the...

2010-09-13

211

76 FR 20606 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...participation in the National Flood Insurance Program (NFIP). In addition...others to calculate appropriate flood insurance premium rates for new buildings...The corresponding preliminary Flood Insurance Rate Map (FIRM) for the...

2011-04-13

212

76 FR 73534 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...participation in the National Flood Insurance Program (NFIP). In addition...others to calculate appropriate flood insurance premium rates for new buildings...The corresponding preliminary Flood Insurance Rate Map (FIRM) for the...

2011-11-29

213

76 FR 19005 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...participation in the National Flood Insurance Program (NFIP). In addition...others to calculate appropriate flood insurance premium rates for new buildings...The corresponding preliminary Flood Insurance Rate Map (FIRM) for the...

2011-04-06

214

Integrated Forecast and Reservoir Management for Northern California  

NASA Astrophysics Data System (ADS)

The INFORM (Integrated Forecast and Reservoir Management) Demonstration Project was created to demonstrate the utility of climate, weather and hydrologic predictions for water resources management in Northern California (includes Trinity River, the Sacramento River, the Feather River, the American River, the San Joaquin River, and the Sacramento-San Joaquin Delta). The INFORM system integrates climate-weather-hydrology forecasting and adaptive reservoir management methods, explicitly accounting for system input and model uncertainties. Operational ensemble forecasts from the Global Forecast System (GFS) and the Climate Forecast System (CFS) of the National Centers of Environmental Prediction (NCEP) are used to drive the WRF model and an Intermediate Complexity Regional Model (ICRM) to produce ensemble precipitation and temperature forecasts with a 10km x 10km resolution and from 6 hours to 30 days. These forecasts feed hydrologic models and provide ensemble inflow forecasts for the major reservoirs of Northern California. The ensemble inflow forecasts are input to a multiobjective and multisite adaptive decision support system designed to support the planning and management processes by deriving real time trade-offs among all relevant water management objectives (i.e., water supply and conservation, hydroelectric power production, flood control, and fisheries and environmental management) at user preferred risk levels. Operational tests over an initial three-year demonstration phase showed good operational performance both for wet and dry years. The presentation focuses on (1) modeling aspects of the current forecast and reservoir components and recent tests and (2) use of recent forecasts for the generation of applicable operational tradeoffs. The test results corroborate the operational value of the integrated forecast-management system.

Georgakakos, K. P.; Graham, N.; Georgakakos, A. P.; Yao, H.

2011-12-01

215

FLOOD PROOFING How to Evaluate Your Options  

E-print Network

FLOOD PROOFING How to Evaluate Your Options Decision Tree us Army Corps of �nqineer';:. -- - - . � r Flood ~ro~~IJ NATIONAL FLOOD PROOFING COMMITTEE July 1993 #12;PREFACE FLOOD PROOFING - How TO EVALUATE YOUR OPTIONS This document has been prepared to help answer the question, "Should flood proofing

US Army Corps of Engineers

216

Severe Flooding in India  

NASA Technical Reports Server (NTRS)

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

2002-01-01

217

Flash Flood Processes: International Edition  

NSDL National Science Digital Library

Flash floods can occur in nearly any area of the world. A rainfall-induced flash flood is a truly hydrometeorological event: one that depends on both hydrologic and meteorological conditions. Forecasting flash floods involves a detailed understanding of the local hydrologic features and continual monitoring of the current meteorological situation. This module examines both the hydrologic and meteorological processes that often contribute to the development of flash flooding. Common tools and technologies that are used in flash flood monitoring and forecasting, from manual gauging systems to complex radar- and satellite-based runoff models, are explored. This module also examines the strengths and limitations of these technologies, as well as how they are likely to advance in the future.

Comet

2011-02-22

218

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

PubMed Central

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

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

2013-01-01

219

USGS Crews Measure Historic Flooding in Fargo, ND  

USGS Multimedia Gallery

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

2009-03-30

220

USGS Crews Measure Historic Flooding in Fargo, ND  

USGS Multimedia Gallery

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

2009-03-30

221

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

USGS Publications Warehouse

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)

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

1983-01-01

222

River Floods  

NSDL National Science Digital Library

This shockwave tool combines animations, text, and simulations in order to teach about floods. Topics addressed in the module include the shape of drainage basins, discharge rates, deposition, runoff, flood frequency, and related issues. Finally, the module allows the user to generate a flood and test different flood control techniques to see how a variety of conditions affect flooding.

Smoothstone; Mifflin, Houghton

223

24 CFR 3285.102 - Installation of manufactured homes in flood hazard areas.  

Code of Federal Regulations, 2011 CFR

...are as defined in 44 CFR 59.1 of the National Flood Insurance Program (NFIP) regulations. (b) Applicability...special flood hazard area as shown on the LAHJ's Flood Insurance Rate Map, Flood Boundary and Floodway Map, or Flood...

2011-04-01

224

24 CFR 3285.102 - Installation of manufactured homes in flood hazard areas.  

Code of Federal Regulations, 2012 CFR

...are as defined in 44 CFR 59.1 of the National Flood Insurance Program (NFIP) regulations. (b) Applicability...special flood hazard area as shown on the LAHJ's Flood Insurance Rate Map, Flood Boundary and Floodway Map, or Flood...

2012-04-01

225

24 CFR 203.16a - Mortgagor and mortgagee requirement for maintaining flood insurance coverage.  

Code of Federal Regulations, 2013 CFR

...mortgagee requirement for maintaining flood insurance coverage. 203.16a Section...mortgagee requirement for maintaining flood insurance coverage. (a) If the...subject to a flood hazard, and if flood insurance under the National Flood...

2013-04-01

226

24 CFR 203.16a - Mortgagor and mortgagee requirement for maintaining flood insurance coverage.  

Code of Federal Regulations, 2011 CFR

...mortgagee requirement for maintaining flood insurance coverage. 203.16a Section...mortgagee requirement for maintaining flood insurance coverage. (a) If the...subject to a flood hazard, and if flood insurance under the National Flood...

2011-04-01

227

24 CFR 203.16a - Mortgagor and mortgagee requirement for maintaining flood insurance coverage.  

Code of Federal Regulations, 2012 CFR

...mortgagee requirement for maintaining flood insurance coverage. 203.16a Section...mortgagee requirement for maintaining flood insurance coverage. (a) If the...subject to a flood hazard, and if flood insurance under the National Flood...

2012-04-01

228

24 CFR 3285.102 - Installation of manufactured homes in flood hazard areas.  

Code of Federal Regulations, 2013 CFR

...are as defined in 44 CFR 59.1 of the National Flood Insurance Program (NFIP) regulations. (b) Applicability...special flood hazard area as shown on the LAHJ's Flood Insurance Rate Map, Flood Boundary and Floodway Map, or Flood...

2013-04-01

229

24 CFR 203.16a - Mortgagor and mortgagee requirement for maintaining flood insurance coverage.  

Code of Federal Regulations, 2010 CFR

...mortgagee requirement for maintaining flood insurance coverage. 203.16a Section...mortgagee requirement for maintaining flood insurance coverage. (a) If the...subject to a flood hazard, and if flood insurance under the National Flood...

2010-04-01

230

24 CFR 3285.102 - Installation of manufactured homes in flood hazard areas.  

Code of Federal Regulations, 2010 CFR

...are as defined in 44 CFR 59.1 of the National Flood Insurance Program (NFIP) regulations. (b) Applicability...special flood hazard area as shown on the LAHJ's Flood Insurance Rate Map, Flood Boundary and Floodway Map, or Flood...

2010-04-01

231

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

NASA Astrophysics Data System (ADS)

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.

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

2012-12-01

232

Logical design of a decision support system to forecast technology, prices and costs for the national communications system  

NASA Astrophysics Data System (ADS)

Originally envisioned as a means to integrate the many systems found throughout the government, the general mission of the NCS continues to be to ensure the survivability of communications during and subsequent to any national emergency. In order to accomplish this mission the NCS is an arrangement of heterogeneous telecommunications systems which are provided by their sponsor Federal agencies. The physical components of Federal telecommunications systems and networks include telephone and digital data switching facilities and primary common user communications centers; Special purpose local delivery message switching and exchange facilities; Government owned or leased radio systems; Technical control facilities which are under exclusive control of a government agency. This thesis describes the logical design of a proposed decision support system for use by the National Communications System in forecasting technology, prices, and costs. It is general in nature and only includes those forecasting models which are suitable for computer implementation. Because it is a logical design it can be coded and applied in many different hardware and/or software configurations.

Williams, K. A.; Partridge, E. C., III

1984-09-01

233

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

SciTech Connect

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.

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

234

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

USGS Publications Warehouse

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.

Storm, John B.

2014-01-01

235

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

NASA Astrophysics Data System (ADS)

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.

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

2013-04-01

236

Flood Impacts  

NSDL National Science Digital Library

Flooding causes more deaths and damage than any other hydro meteorological phenomena. The Weather Service provides statistics on flood-related impacts: flood fatalities by year from present to 1903; flood damage, including kinds and value of damage, annually from present to l903. Other features include: reports of current flood watches and warnings, outlooks for impending flooding, hydrologic conditions, and links to climate information and Weather Service offices.

2010-08-02

237

DIRECT FLOOD DAMAGE MODELING TOWARDS URBAN FLOOD RISK MANAGEMENT  

Microsoft Academic Search

An estimate of losses from future floods is essential to prepare for a disaster and facilitating good decision making at the local, regional, state, and national levels of government. Flood loss estimates provide public and private sector agencies with a basis for planning, zoning, and development regulations, and policy that would reduce the risk posed by hazards. Flood loss estimates

DUSHMANTA DUTTA; SRIKANTHA HERATH; KATUMI MUSIAKE

238

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)

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.

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

2014-10-01

239

44 CFR 73.4 - Restoration of flood insurance coverage.  

Code of Federal Regulations, 2011 CFR

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

2011-10-01

240

44 CFR 73.4 - Restoration of flood insurance coverage.  

Code of Federal Regulations, 2013 CFR

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

2013-10-01

241

44 CFR 73.4 - Restoration of flood insurance coverage.  

Code of Federal Regulations, 2010 CFR

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

2010-10-01

242

44 CFR 73.3 - Denial of flood insurance coverage.  

Code of Federal Regulations, 2012 CFR

...2011-10-01 true Denial of flood insurance coverage. 73.3 Section...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3...

2012-10-01

243

44 CFR 73.3 - Denial of flood insurance coverage.  

Code of Federal Regulations, 2010 CFR

...2010-10-01 false Denial of flood insurance coverage. 73.3 Section...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3...

2010-10-01

244

44 CFR 73.3 - Denial of flood insurance coverage.  

Code of Federal Regulations, 2013 CFR

...2013-10-01 false Denial of flood insurance coverage. 73.3 Section...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3...

2013-10-01

245

44 CFR 73.4 - Restoration of flood insurance coverage.  

Code of Federal Regulations, 2012 CFR

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

2012-10-01

246

BUILDING STRONG Flood Protection Structure  

E-print Network

Community/sponsor has decision whether to participate in National Flood Insurance Program. Has a key roleBUILDING STRONG® Flood Protection Structure Accreditation Task Force March 2013 #12;BUILDING STRONG® FEMA's Role in Levees Present flood hazard and risk information Establish appropriate risk zone

US Army Corps of Engineers

247

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)

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.

Shukla, Shraddhanand; Funk, Christopher; Hoell, Andrew

2014-09-01

248

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

249

ASMET: Flooding in West Africa  

NSDL National Science Digital Library

The rainy season in Sahelian West Africa extends from June to September and is tied to the position of the intertropical front. During this period, mesoscale convective systems (MCSs) often produce significant rainfall that can lead to flooding. This module examines an extreme flooding event that occurred in Ouagadougou, Burkina Faso from 31 August to 1 September 2009. Learners assume the role of forecaster, assessing meteorological conditions to see if an MCS will develop that can lead to heavy rain and flooding. They follow a forecast process that emphasizes the use of satellite data, standard surface and upper-air charts, and model output. The forecast process is tied to a conceptual model of the key features that drive convective activities in West Africa.

Comet

2012-01-10

250

Costs and Consequences of Flooding Camilo Sarmiento, Ph.D.  

E-print Network

Costs and Consequences of Flooding Camilo Sarmiento, Ph.D. Senior Economist Fannie Mae #12;Background · Annual property flood loss: $2 Billion. · Most flood losses occur in special flood hazard areas (SFHAs). · Homeowner insurance policies do not cover flood loss. · The National Flood Insurance Program

251

Hazards of Extreme Weather: Flood Fatalities in Texas  

Microsoft Academic Search

The Federal Emergency Management Agency (FEMA) considers flooding ``America's Number One Natural Hazard''. Despite flood management efforts in many communities, U.S. flood damages remain high, due, in large part, to increasing population and property development in flood-prone areas. Floods are the leading cause of fatalities related to natural disasters in Texas. Texas leads the nation in flash flood fatalities. There

H. O. Sharif; T. Jackson; S. Bin-Shafique

2009-01-01

252

44 CFR 65.16 - Standard Flood Hazard Determination Form and Instructions.  

Code of Federal Regulations, 2012 CFR

...HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...Section 528 of the National Flood Insurance Reform Act of 1994 (42...special flood hazards and in which flood insurance under this title is...

2012-10-01

253

44 CFR 65.16 - Standard Flood Hazard Determination Form and Instructions.  

Code of Federal Regulations, 2011 CFR

...HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...Section 528 of the National Flood Insurance Reform Act of 1994 (42...special flood hazards and in which flood insurance under this title is...

2011-10-01

254

Assessment of climate change impacts on floods in Finland  

NASA Astrophysics Data System (ADS)

Climate change impacts on floods in Finland by 2010-2039 and 2070-2099 were estimated to gain a general overview on national scale impacts. General assessments of changes of flood magnitudes are needed to incorporate climate change into planning and because of the EU flood directive. Hydrology in Finland is characterised by strong snow-dominated seasonality with snow accumulation in winter and snow melt in spring, but the temperature gradient from north to south is strong especially in winter. Coastal and southern Finland has a more maritime climate with mild winters. Lakes are an important part of Finnish watersheds especially in the lake region in central and eastern Finland. Changes in floods were evaluated at 67 sites in different part of Finland with runoff-areas ranging from 86 to 61 000 km2. The hydrological simulations were performed with a HBV-type conceptual hydrological model Watershed Simulation and Forecasting System (WSFS) developed and operated in the Finnish Environment Institute (Vehviläinen et al. 2005). Altogether 20 climate scenarios from both global and regional climate models and with different emission scenarios were used with the delta change approach. The magnitudes of 100 year floods in the reference period 1971-2000 and in 2010-2039 and 2070-2099 were estimated with frequency analysis using the Gumbel distribution. According to the results, the 100 year floods in Finland decreased on average 8-22 % in 2070-2099 compared to the reference period, but variation between different sites and regions was significant. In areas in northern and central Finland, where snowmelt-floods are the largest floods, the annual floods decreased or remained unchanged due to decreasing snow accumulation. On the other hand, increased precipitation resulted in increasing floods in large central lakes and their outflow rivers in central Finland. Changes in snow accumulation and melt and the importance of this process in flood generation explained much of the changes in floods. A significant shift took place in the seasonal distribution of runoff and flood with increasing autumn and winter floods and decreasing spring floods especially in southern and central Finland. Floods decreased on most sites with most scenarios, but increased in some of the most important flood hazard regions with high potential damages. The results demonstrate that even within a relatively small area like Finland the impacts of climate change on floods can be vary substantially due to regional differences in climatic conditions and watershed properties. Important explanatory variables in the changes of floods were many present day hydrological and climatological characteristics such as timing of floods, importance of snowmelt-floods, snow water equivalent, winter temperature, latitude, lake percentage and watershed size. These variables can explain most of the average changes in different sites and their explanatory power improves when applied separately to different hydrological regions. The uncertainties included in flood and climate change studies are however still considerable and in many sites the range produced by the 20 climate scenarios was large.

Veijalainen, Noora; Vehviläinen, Bertel; Lotsari, Eliisa; Alho, Petteri; Käyhkö, Jukka

2010-05-01

255

Flood-inundation maps for the Susquehanna River near Harrisburg, Pennsylvania, 2013  

USGS Publications Warehouse

A series of 28 digital flood-inundation maps was developed for an approximate 25-mile reach of the Susquehanna River in the vicinity of Harrisburg, Pennsylvania. The study was selected by the U.S. Army Corps of Engineers (USACE) national Silver Jackets program, which supports interagency teams at the state level to coordinate and collaborate on flood-risk management. This study to produce flood-inundation maps was the result of a collaborative effort between the USACE, National Weather Service (NWS), Susquehanna River Basin Commission (SRBC), The Harrisburg Authority, and the U.S. Geological Survey (USGS). These maps are accessible through Web-mapping applications associated with the NWS, SRBC, and USGS. The maps can be used in conjunction with the real-time stage data from the USGS streamgage 01570500, Susquehanna River at Harrisburg, Pa., and NWS flood-stage forecasts to help guide the general public in taking individual safety precautions and will provide local municipal officials with a tool to efficiently manage emergency flood operations and flood mitigation efforts. The maps were developed using the USACE HEC–RAS and HEC–GeoRAS programs to compute water-surface profiles and to delineate estimated flood-inundation areas for selected stream stages. The maps show estimated flood-inundation areas overlaid on high-resolution, georeferenced, aerial photographs of the study area for stream stages at 1-foot intervals between 11 feet and 37 feet (which include NWS flood categories Action, Flood, Moderate, and Major) and the June 24, 1972, peak-of-record flood event at a stage of 33.27 feet at the Susquehanna River at Harrisburg, Pa., streamgage.

Roland, Mark A.; Underwood, Stacey M.; Thomas, Craig M.; Miller, Jason F.; Pratt, Benjamin A.; Hogan, Laurie G.; Wnek, Patricia A.

2014-01-01

256

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

NASA Technical Reports Server (NTRS)

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.

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

2012-01-01

257

Rainfall-River Forecasting Fusion Team Rainfall-River Forecasting Summit  

E-print Network

1 Rainfall-River Forecasting Fusion Team Rainfall-River Forecasting Summit St. Paul, MN Monday, Oct 19, 2009 #12;2 Created as a 2008 Midwest Flood after-action from the Rainfall-River Forecasting Summit (Oct 2008) Main area of focus, Mississippi River Basin Member Agencies - USACE, USGS, NWS USACE

US Army Corps of Engineers

258

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

NASA Technical Reports Server (NTRS)

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.

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

2012-01-01

259

Flood early warning along the East Coast of Scotland and the Storm of December 2012  

NASA Astrophysics Data System (ADS)

Flood warning is at the heart of improved approaches to flood risk management in Scotland. The Scottish Environment Protection Agency (SEPA) is committed to reducing the impact of coastal flooding through the provision of reliable and timely flood warnings. They have specifically set out a programme of enhancing coastal flood forecasting through modelling and improved understanding of coastal flooding processes and improved approaches to wind and wave forecasting in coastal and tidal waters. In 2011, SEPA commissioned a project to develop a flood forecasting and warning system for the Firths of Forth and Tay along Scotland's North East coast. The new approach to flood forecasting has just been implemented into the Flood Early Warning System (FEWS) (Cranston and Tavendale, 2012) to contribute to the real-time flood forecasting and warning service from November 2012. The new system enables the prediction of coastal and tidal flooding and allows SEPA to warn people about potential flooding, using the latest advances in coastal modelling. The approach to the forecasting system includes: the transformation of tidal surge forecasts from Leith to 28 flood warning sites along the coast and inside the Firths of Forth and Tay; the transformation of offshore wave forecasts to inshore locations including the Firths of Forth and Tay; and the transformation of inshore wave forecasts to mean wave overtopping forecasts at six key communities at risk. In December 2012, some communities along the east coast of Scotland experienced their most severe storm damage since the Great 1953 Storm. This paper will discuss how the flood forecasting system was developed and how the system was utilised in real time during the recent storm. References Cranston, M. D. and Tavendale, A. C. W. (2012) Advances in operational flood forecasting in Scotland. Proceedings of the ICE - Water Management, 165, 2, 79-87.

Cranston, Michael; Hu, Keming

2013-04-01

260

Dynamic mapping of flood boundaries: current possibilities offered by Earth Observation System and Cellular Automata  

NASA Astrophysics Data System (ADS)

Flooding is an ongoing and complex problem in Italy. Very large floods caused inundation of the closest areas to the city centre in Rome in 1937, 1976, 1992, 2005 and most recently in 2008. Rome is located at the bottom of the Tiber River catchment, which cover an area of 16 000 km2. Intense precipitations struck the Tyrrhenian Sea side of the peninsula inducing a flood event on the Tiber and Aniene's (Tiber's tributary) basins - which captured the attention of the national and international media. Actually there is no validated model in operation for real-time flood forecasting. This research aims at comparing the Cellular Model CAESAR (Cellular Automation Evolutionary Slope And River) application on a reach of the Aniene River with Earth Observation Systems. The main result expected is the prediction of future channel dynamics on short and medium time scale.

Gerardi, A.; Ioannilli, M.; Del Frate, F.

2014-01-01

261

Flash Flood Case Studies  

NSDL National Science Digital Library

This module takes the learner through seven case studies of flash flood events that occurred in the conterminous U.S. between 2003 and 2006. The cases covered include: * 30-31 August 2003: Chase & Lyon Counties, KS * 16-17 September 2004: Macon County, NC * 31 July 2006: Santa Catalina Mountains near Tucson, AZ * 25 December 2003: Fire burn area near San Bernardino, CA * 30 August 2004: Urban flash flood in Richmond, VA * 19-20 August 2003: Urban flash flood in Las Vegas, NV * 9 October 2005: Cheshire County, NH This module assists the learner in applying the concepts covered in the foundation topics of the Basic Hydrologic Sciences course. Some of the specific topics pertinent to these cases are the physical characteristics that make a basin prone to flash floods, basin response to precipitation, flash flood guidance (FFG), the relationship between wildfire and flash floods, and the relationship between urban development and flash floods. Related topics brought out in the cases include radar quantitative precipitation estimation (QPE), the National Weather Service Flash Flood Monitoring and Prediction (NWS FFMP) products, debris flows, impounded water, and interagency communications. The core foundation topics are recommended prerequisite materials since this module assumes some pre-existing knowledge of hydrologic principles. In particular, the Runoff Processes and Flash Flood Processes modules contain material directly related to these cases.

Comet

2007-06-26

262

Development and validation of a maritime forecasting system for the New Zealand region  

NASA Astrophysics Data System (ADS)

A new maritime forecasting system for the New Zealand region has been developed including global and regional wave models and regional tide and storm surge models. These form part of an integrated "all - hazards" forecasting capability, which also includes an accurate, data assimilating high resolution weather forecasting system and a national-scale flood forecasting system. For wave predictions, Wavewatch III is run on nested global and regional grids. A 144-hour forecast is run daily on the global domain, providing boundary conditions for twice-daily 48-hour forecasts on a New Zealand regional domain at a resolution of approximately 12 km. The regional wave forecasts have been validated against data from six wave buoy deployments. For global forecasts, these are supplemented with data from NDBC buoys in the North Pacific. Predicted variations in sea surface height and depth-average velocity due to tides and storm surge are provided in twice-daily 48-hour regional forecasts. At present tide and storm surge components are computed separately. Storm surge is predicted for the New Zealand region using the RiCOM model on an unstructured grid, in depth-averaged mode using semi-implicit integration in time. The amplitude and phase of the tidal constituents have been pre-calculated using Tide2D, a companion model to RiCOM which works in frequency space on an unstructured spatial grid. These models are validated against data from 16 sea level gauges located around the New Zealand coast.

Gorman, R. M.; Lane, E. M.; Gillibrand, P. A.; Uddstrom, M. J.

2009-04-01

263

The development of an improved human capital index for assessing and forecasting national capacity and development  

E-print Network

of this dissertation is to construct and validate a more comprehensive human capital index. Study research questions include: 1) What are the significant factors that affect national human capital as revealed in the literature? 2) Can an expanded measure of national...

Verkhohlyad, Olha

2009-05-15

264

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

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.

Wagner, Daniel M.

2013-01-01

265

Flood-inundation maps for the Iroquois River at Rensselaer, Indiana  

USGS Publications Warehouse

Digital flood-inundation maps for a 4.0-mile reach of the Iroquois River at Rensselaer, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at USGS streamgage 05522500, Iroquois River at Rensselaer, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at (http://waterdata.usgs.gov/in/nwis/uv?site_no=05522500). In addition, the National Weather Service (NWS) forecasts flood hydrographs at the Rensselaer streamgage. That forecasted peak-stage information, also available on the Internet (http://water.weather.gov/ahps/), 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 Iroquois River reach by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current (June 27, 2012) stage-discharge relations at USGS streamgage 05522500, Iroquois River at Rensselaer, Ind., and high-water marks from the flood of July 2003. The calibrated hydraulic model was then used to determine nine water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage at Rensselaer, Ind., and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.

Fowler, Kathleen K.; Bunch, Aubrey R.

2013-01-01

266

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

USGS Publications Warehouse

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.

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

2012-01-01

267

A Healthy Campus--Forecasting from the 1990 Health Objectives for the Nation.  

ERIC Educational Resources Information Center

This article review results of a survey concerning the United States' national health profile and delineates health promotion goals to improve health and increase healthy behavior of the population, with special emphasis placed on young adult college students. (CB)

McGinnis, J. Michael

1987-01-01

268

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

NASA Technical Reports Server (NTRS)

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.

Oswald, Hayden; Molthan, Andrew L.

2011-01-01

269

Flood monitoring over the Mackenzie River Basin using passive microwave data  

Microsoft Academic Search

Flooding over the Mackenzie River Basin, which is situated in northwestern Canada, is a complex and rapid process. This process is mainly controlled by the occurrence of ice jams. Flood forecasting is of very important in mitigating social and economic damage. This study investigates the potential of a rating curve model for flood forecasting. The proposed approach is based on

Marouane Temimi; Robert Leconte; Francois Brissette; Naira Chaouch

2005-01-01

270

44 CFR 67.4 - Proposed flood elevation determination.  

Code of Federal Regulations, 2011 CFR

...DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED...elevation determination. The Federal Insurance Administrator shall propose flood elevation determinations in...

2011-10-01

271

44 CFR 67.4 - Proposed flood elevation determination.  

Code of Federal Regulations, 2010 CFR

...DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED...elevation determination. The Federal Insurance Administrator shall propose flood elevation determinations in...

2010-10-01

272

44 CFR 67.4 - Proposed flood elevation determination.  

Code of Federal Regulations, 2012 CFR

...DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED...elevation determination. The Federal Insurance Administrator shall propose flood elevation determinations in...

2012-10-01

273

44 CFR 67.4 - Proposed flood elevation determination.  

Code of Federal Regulations, 2013 CFR

...DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED...elevation determination. The Federal Insurance Administrator shall propose flood elevation determinations in...

2013-10-01

274

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

NASA Astrophysics Data System (ADS)

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.

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

275

Forecasting inflation  

Microsoft Academic Search

This paper investigates forecasts of US inflation at the 12-month horizon. The starting point is the conventional unemployment rate Phillips curve, which is examined in a simulated out-of-sample forecasting framework. Inflation forecasts produced by the Phillips curve generally have been more accurate than forecasts based on other macroeconomic variables, including interest rates, money and commodity prices. These forecasts can however

James H. Stock; Mark W. Watson

1999-01-01

276

Communicating uncertainty in hydrological forecasts: mission impossible?  

NASA Astrophysics Data System (ADS)

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.

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

2010-05-01

277

An application of hydroinformatic tools for rainfall forecasting  

Microsoft Academic Search

A knowledge of rainfall is an important component of the information needed for effective flood forecasting systems, especially for urban catchments which are characterised by fast hydrologic response. For these urban catchments, it is necessary to forecast likely rainfall so that managers of the catchments have the opportunity to implement relevant action plans for management of flood events. To meet

Kin Choi Luk

1998-01-01

278

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

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

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

2013-01-01

279

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

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 24 m per year to 68.5m per year, with associated increases in ablation zone ice loss. GCM projections indicate that over the 21(st) 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 21(st) 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

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

2013-01-01

280

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

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.

Wiley, J. B.

1994-01-01

281

TRAVEL DEMAND AND RELIABLE FORECASTS  

E-print Network

Council ­ responsible for ensuring high quality, consistent and defensible forecasts for all · Defensible 7 #12;Forecasting Goals ·This takes time and effort · National and local experience suggest include · Network Definition · Zonal Data 11 #12;Forecasting Process · At each refinement · Ridership

Minnesota, University of

282

Flood-inundation maps for the Elkhart River at Goshen, Indiana  

USGS Publications Warehouse

The U.S. Geological Survey (USGS), in cooperation with the Indiana Office of Community and Rural Affairs, created digital flood-inundation maps for an 8.3-mile reach of the Elkhart River at Goshen, Indiana, extending from downstream of the Goshen Dam to downstream from County Road 17. 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 nine selected water levels (stages) at the USGS streamgage at Elkhart River at Goshen (station number 04100500). Current conditions for the USGS streamgages in Indiana may be obtained on the Internet at http://waterdata.usgs.gov/. In addition, stream stage data have 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 using the most current stage-discharge relation at the Elkhart River at Goshen streamgage. The hydraulic model was then used to compute nine water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from approximately bankfull (5 ft) to greater than the highest recorded water level (13 ft). The simulated water-surface profiles were then combined with a geographic information system (GIS) digital-elevation model (DEM), derived from Light Detection and Ranging (LiDAR) data having a 0.37-ft vertical accuracy and 3.9-ft horizontal resolution 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 postflood recovery efforts.

Strauch, Kellan R.

2013-01-01

283

44 CFR 78.6 - Flood Mitigation Plan approval process.  

Code of Federal Regulations, 2010 CFR

...Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood Mitigation Plan approval process. The...

2010-10-01

284

44 CFR 71.3 - Denial of flood insurance.  

Code of Federal Regulations, 2013 CFR

...2013-10-01 false Denial of flood insurance. 71.3 Section 71.3...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF COASTAL...LEGISLATION § 71.3 Denial of flood insurance. (a) No new...

2013-10-01

285

44 CFR 78.6 - Flood Mitigation Plan approval process.  

Code of Federal Regulations, 2013 CFR

...Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood Mitigation Plan approval process. The...

2013-10-01

286

24 CFR 574.640 - Flood insurance protection.  

Code of Federal Regulations, 2011 CFR

...2011-04-01 2010-04-01 true Flood insurance protection. 574.640 Section...Requirements § 574.640 Flood insurance protection. No property...participating in the National Flood Insurance Program and the regulations...

2011-04-01

287

24 CFR 574.640 - Flood insurance protection.  

Code of Federal Regulations, 2012 CFR

...2012-04-01 2012-04-01 false Flood insurance protection. 574.640 Section...Requirements § 574.640 Flood insurance protection. No property...participating in the National Flood Insurance Program and the regulations...

2012-04-01

288

44 CFR 78.6 - Flood Mitigation Plan approval process.  

Code of Federal Regulations, 2012 CFR

...Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood Mitigation Plan approval process. The...

2012-10-01

289

44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.  

Code of Federal Regulations, 2010 CFR

...2010-10-01 false Standard Flood Insurance Policy Interpretations. 61...HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.14 Standard Flood Insurance Policy Interpretations....

2010-10-01

290

44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.  

Code of Federal Regulations, 2013 CFR

...2013-10-01 false Standard Flood Insurance Policy Interpretations. 61...HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.14 Standard Flood Insurance Policy Interpretations....

2013-10-01

291

44 CFR 71.3 - Denial of flood insurance.  

Code of Federal Regulations, 2010 CFR

...2010-10-01 false Denial of flood insurance. 71.3 Section 71.3...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF COASTAL...LEGISLATION § 71.3 Denial of flood insurance. (a) No new...

2010-10-01

292

44 CFR 71.3 - Denial of flood insurance.  

Code of Federal Regulations, 2012 CFR

...2011-10-01 true Denial of flood insurance. 71.3 Section 71.3...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF COASTAL...LEGISLATION § 71.3 Denial of flood insurance. (a) No new...

2012-10-01

293

44 CFR 71.3 - Denial of flood insurance.  

Code of Federal Regulations, 2011 CFR

...2011-10-01 false Denial of flood insurance. 71.3 Section 71.3...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF COASTAL...LEGISLATION § 71.3 Denial of flood insurance. (a) No new...

2011-10-01

294

24 CFR 574.640 - Flood insurance protection.  

Code of Federal Regulations, 2010 CFR

...2010-04-01 2010-04-01 false Flood insurance protection. 574.640 Section...Requirements § 574.640 Flood insurance protection. No property...participating in the National Flood Insurance Program and the regulations...

2010-04-01

295

24 CFR 574.640 - Flood insurance protection.  

Code of Federal Regulations, 2013 CFR

...2013-04-01 2013-04-01 false Flood insurance protection. 574.640 Section...Requirements § 574.640 Flood insurance protection. No property...participating in the National Flood Insurance Program and the regulations...

2013-04-01

296

44 CFR 78.6 - Flood Mitigation Plan approval process.  

Code of Federal Regulations, 2011 CFR

...Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.6 Flood Mitigation Plan approval process. The...

2011-10-01

297

44 CFR 61.17 - Group Flood Insurance Policy.  

Code of Federal Regulations, 2012 CFR

...DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A Group Flood Insurance Policy (GFIP) is a policy...

2012-10-01

298

44 CFR 61.13 - Standard Flood Insurance Policy.  

Code of Federal Regulations, 2013 CFR

...DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.13 Standard Flood Insurance Policy. (a) Incorporation of forms. Each of the Standard Flood...

2013-10-01

299

44 CFR 61.17 - Group Flood Insurance Policy.  

Code of Federal Regulations, 2013 CFR

...DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES § 61.17 Group Flood Insurance Policy. (a) A Group Flood Insurance Policy (GFIP) is a policy...

2013-10-01

300

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

NASA Astrophysics Data System (ADS)

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.

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

2010-12-01

301

Teaching Floods and Flooding Quantitatively  

NSDL National Science Digital Library

This page helps faculty communicate essential ideas that students struggle with in terms of floods and flooding. It takes into account the concepts of probability and recurrence interval and discusses hydrologic terminology, relations between discharge and stage, and the meaning of the '100 year flood.'

Baer, Eric M.

2008-08-18

302

Relationships between Return Period and Flash Flooding in the United States  

NASA Astrophysics Data System (ADS)

Oftentimes, a given return period of streamflow (typically a 2- or 5-year flow) is used as a proxy for the onset of a flash flood, indicating bankfull conditions. This information is useful in the context of ungauged basins, where simulated return periods might be available, but there is no stream gauge to measure the discharge. While a given observation of streamflow does not necessarily indicate a flash flood, existing streamflow records are useful in providing long-term, continuous measurements at a point, which can be used to augment databases of flash flood reports submitted by humans. There are a total of 10,106 USGS stream gauges with records dating from Jul 1927 through Sep 2010. Of these gauges, 3,490 have defined stage heights associated to stream bankfull conditions, warning, minor, moderate, and major flood stages. Local National Weather Service offices define these thresholds based on impacts to lives and/or property in coordination with the local emergency management and stakeholder community. This study uses a recently published database of flash floods in the United States to relate observed return periods to flood stages at the stream gauges with NWS-defined flood stages. The relationship between return period and certain geological and climatological factors is explored. Since bankfull conditions are often linked to rules-of-thumb regarding return period, the results have useful implications for those in the forecasting community.

Erlingis, J. M.; Gourley, J. J.; Hong, Y.

2013-12-01

303

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

NASA Astrophysics Data System (ADS)

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.

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

2012-04-01

304

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

E-print Network

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

Exeter, University of

305

Modeling Flood Perils and Flood Insurance Program in Taiwan  

Microsoft Academic Search

Taiwan had approximately 3,000 buildings damaged by floods with an economic loss of NT$12.8 billion annually, a figure 4.5 times more than economic losses due to fire damages. Many insurers become extremely cautious when underwriting their flood policies for people living in areas that are frequently struck by floods. The rising damages also trigger the demand for a mandatory national

Ching-Cheng Chang; Wenko Hsu; Ming-Daw Su

2008-01-01

306

Weather Forecasting  

NSDL National Science Digital Library

Weather Forecasting is one of several online guides produced by the Weather World 2010 project at the University of Illinois. These guides use multimedia technology and the dynamic capabilities of the web to incorporate text, colorful diagrams, animations, computer simulations, audio, and video to introduce topics and concepts in the atmospheric sciences. This module introduces forecast methods and the numerous factors one must consider when attempting to make an accurate forecast. Sections include forecasting methods for different scenarios, surface features affecting forecasting, forecasting temperatures for day and night, and factors for forecasting precipitation.

2010-01-01

307

Assessing the Potential of the AIRS Retrieved Surface Temperature for 6-Hour Average Temperature Forecast in River Forecast Centers  

NASA Astrophysics Data System (ADS)

Producing timely and accurate water forecast and information is the mission of National Weather Service River Forecast Centers (NWS RFCs) of National Oceanic and Atmospheric Administration (NOAA). The river forecast system in RFCs requires average surface temperature in the fixed 6-hour period 000-0600, 0600-1200, 1200-1800, and 1200-0000 UTC. The current logic of RFC temperature forecast relies on ingest of point values of daytime maximum and nighttime minimum temperature. Meanwhile, the mean temperature for the 6-hour period is estimated from a weighted average of daytime maximum and nighttime minimum temperature. The Atmospheric Infrared Sounder (AIRS) in the first high spectral resolution infrared sounder on board the Aqua satellite which was launched in May 2002 and follows a Sun-synchronous polar orbit. It is aimed to produce high resolution atmospheric profile and surface atmospheric parameters. As Aqua crosses the equator at about 1330 and 0130 local time, the AIRS retrieved surface temperature may represent daytime maximum and nighttime minimum value. Comparing to point observation from surface weather stations which are often sparse over the less-populated area and are unevenly distributed, satellite may obtain better area averaged observation. This test study assesses the potential of using AIRS retrieved surface temperature to forecast 6-hour average temperature for NWS RFCs. The California Nevada RFC is selected due to the poor coverage of surface observation in the mountainous region and spring snow melting. The study focuses on the March to May spring season when water from snowpack melting often plays important role in flood. AIRS retrieved temperature and surface weather station data set will be used to derive statistical weighting coefficient for 6-hour average temperature forecast. The resulting forecast biases and errors will be the main indicators of the potential usage. All study results will be presented in the meeting.

Ding, F.; Theobald, M.; Vollmer, B.; Savtchenko, A. K.; Hearty, T. J.; Esfandiari, A. E.

2012-12-01

308

Uncertainties in Weather Forecast – Reasons and Handling  

Microsoft Academic Search

\\u000a The generation of precipitation forecasts by means of numerical weather prediction (NWP) models is increasingly becoming an\\u000a important input for hydrological models. Over the past decades the quality and spatial resolution of meteorological numerical\\u000a models has been drastically improved, which makes it now possible to incorporate high-resolution NWP output directly into\\u000a flood forecasting systems. The quality of forecasted precipitation, however,

Dirk Schüttemeyer; Clemens Simmer

309

Section "Informatics" MULTICRITERIA ANALYSIS APPLIED TO A FLOOD EVENT ON RIVER  

E-print Network

. The flood disaster management is highly dependent on early information and needs forecasts and data from disaster management is highly dependent on early information and needs forecasts and data from the river

Mustakerov, Ivan

310

Drug Use Analysis Methodologies: Part I. Screening Methodology to Measure and Compare Normative and Criterial Drug Prescribing (An Example Using Schedule 2 Drug Products). Part II. Methodology to Forecast National Normative Drug Prescribing (An Example Using Schedule 2 Drugs).  

National Technical Information Service (NTIS)

A screening methodology for the purpose of measuring and comparing normative and criterial drug prescribing is demonstrated. Another methodology for forecasting national normative drug prescribing is described. Examples using Schedule 2 drugs are given.

D. E. Knapp, D. L. Crosby, T. F. Morgan, C. S. Lao, J. S. Kennedy

1976-01-01

311

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

NASA Astrophysics Data System (ADS)

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

Supharatid, Seree

2006-02-01

312

Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool  

NASA Astrophysics Data System (ADS)

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.

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

2013-12-01

313

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

NASA Astrophysics Data System (ADS)

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.

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

2012-04-01

314

Performance and robustness of probabilistic river forecasts computed with quantile regression based on multiple independent variables in the North Central USA  

NASA Astrophysics Data System (ADS)

This study further develops the method of quantile regression (QR) to predict exceedance probabilities of flood stages by post-processing forecasts. Using data from the 82 river gages, for which the National Weather Service's North Central River Forecast Center issues forecasts daily, this is the first QR application to US American river gages. Archived forecasts for lead times up to six days from 2001-2013 were analyzed. Earlier implementations of QR used the forecast itself as the only independent variable (Weerts et al., 2011; López López et al., 2014). This study adds the rise rate of the river stage in the last 24 and 48 h and the forecast error 24 and 48 h ago to the QR model. Including those four variables significantly improved the forecasts, as measured by the Brier Skill Score (BSS). Mainly, the resolution increases, as the original QR implementation already delivered high reliability. Combining the forecast with the other four variables results in much less favorable BSSs. Lastly, the forecast performance does not depend on the size of the training dataset, but on the year, the river gage, lead time and event threshold that are being forecast. We find that each event threshold requires a separate model configuration or at least calibration.

Hoss, F.; Fischbeck, P. S.

2014-10-01

315

Summary of available waste forecast data for the Environmental Restoration Program at the Oak Ridge National Laboratory, Oak Ridge, Tennessee  

SciTech Connect

This report identifies patterns of Oak Ridge National Laboratory (ORNL) Environmental Restoration (ER) waste generation that are predicted by the current ER Waste Generation Forecast data base. It compares the waste volumes to be generated with the waste management capabilities of current and proposed treatment, storage, or disposal (TSD) facilities. The scope of this report is limited to wastes generated during activities funded by the Office of the Deputy Assistant Secretary for Environmental Restoration (EM-40) and excludes wastes from the decontamination and decommissioning of facilities. Significant quantities of these wastes are expected to be generated during ER activities. This report has been developed as a management tool supporting communication and coordination of waste management activities at ORNL. It summarizes the available data for waste that will be generated as a result of remediation activities under the direction of the U.S. Department of Energy Oak Ridge Operations Office and identifies areas requiring continued waste management planning and coordination. Based on the available data, it is evident that most remedial action wastes leaving the area of contamination can be managed adequately with existing and planned ORR waste management facilities if attention is given to waste generation scheduling and the physical limitations of particular TSD facilities. Limited use of off-site commercial TSD facilities is anticipated, provided the affected waste streams can be shown to satisfy the requirements of the performance objective for certification of non-radioactive hazardous waste and the waste acceptance criteria of the off-site facilities. Ongoing waste characterization will be required to determine the most appropriate TSD facility for each waste stream.

Not Available

1994-08-01

316

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

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.

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

2014-01-01

317

The WMO Coastal Inundation Forecasting Demonstration Project (CIFDP)  

NASA Astrophysics Data System (ADS)

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.

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

2014-05-01

318

Flood Maps  

NSDL National Science Digital Library

This map, created by combining data from Google Maps and NASA, shows which land areas would be flooded by sea level rises between 0 and 14 meters. The NASA data set used is only of limited reliability, but the map provides a fascinating view of the consequences of rising sea levels, and the consequent floods of costal areas.

Tingle, Alex; Nasa; Maps, Google; Self-Published

319

Polymer flooding  

Microsoft Academic Search

This book covers all aspects of polymer flooding, an enhanced oil recovery method using water soluble polymers to increase the viscosity of flood water, for the displacement of crude oil from porous reservoir rocks. Although this method is becoming increasingly important, there is very little literature available for the engineer wishing to embark on such a project. In the past,

Littmann

1988-01-01

320

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

E-print Network

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

Ganguly, Auroop Ratan

2002-01-01

321

Ocean meets River: connecting Bureau of Meteorology ocean forecasts and river height predictions for  

E-print Network

Ocean meets River: connecting Bureau of Meteorology ocean forecasts and river height predictions, flood warning, operational system. #12;Taylor et al., Ocean meets River: connecting Bureau systems; these include routine global models to forecast weather, climate, and now ocean circulation

Taylor, Andy

322

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

Code of Federal Regulations, 2013 CFR

...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General § 63...against subsequently providing flood insurance or assistance under the...

2013-10-01

323

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

Code of Federal Regulations, 2011 CFR

...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General § 63...against subsequently providing flood insurance or assistance under the...

2011-10-01

324

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

Code of Federal Regulations, 2012 CFR

...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General § 63...against subsequently providing flood insurance or assistance under the...

2012-10-01

325

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

Code of Federal Regulations, 2010 CFR

...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General § 63...against subsequently providing flood insurance or assistance under the...

2010-10-01

326

The 20 February 2010 Madeira flash flood  

NASA Astrophysics Data System (ADS)

On February 20, 2010, Madeira Island was struck by a violent rain storm, which led to a major flash flood leading to more than 50 casualties and an estimated property loss above 1G€. The storm was not well forecasted by the Institute of Meteorology, based on the global ECMWF forecast. However, the operational forecasts made by our group at the University of Lisbon, with MM5 and WRF at 2 km resolution, consistently indicated heavy precipitation for that day, starting on the 72h from 18 February at 00 UTC, and including all intermediate forecasts, issued every 12h, until the day of the event. At the same time, many important details of the forecasts, concerning in particular the timing of precipitation in low level stations, have discrepancies with observations. In the present study we analyze not only the quality of the high resolution forecasts of the rain storm, with the two models at different resolutions, but also review the MM5 model performance in all forecasts from 2006 to 2010, where other important orographic precipitation events have occurred, but no flash flood was triggered. The analysis emphasizes the relative importance of the state of the terrain, due to accumulated precipitation in days and weeks before a major rain storm, in the occurrence of flash floods.

Miranda, P. M. A.; Tomé, R.; Azevedo, E. B.; Cardoso, R. M.

2010-09-01

327

From low-flows to floods under global warming  

NASA Astrophysics Data System (ADS)

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

Panagoulia, D.

2009-04-01

328

The Demand for Flood Insurance: Empirical Evidence  

Microsoft Academic Search

Flood damages that occur worldwide remain largely uninsured losses despite the efforts of governmental programs that in many cases make insurance available at below fair market cost. The current study focuses on the financial experience of the United States' National Flood Insurance Program (NFIP) from 1983 through 1993 to examine the hypothetical determinants of the flood insurance purchasing decision. The

Mark J. Browne; Robert E. Hoyt

2000-01-01

329

Utility of flood warning systems for emergency management  

NASA Astrophysics Data System (ADS)

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.

Molinari, Daniela; Ballio, Francesco; Menoni, Scira

2010-05-01

330

Value of the GENS Forecast Ensemble as a Tool for Adaptation of Economic Activity to Climate Change  

NASA Astrophysics Data System (ADS)

In an atmosphere of uncertainty as to the magnitude and direction of climate change in upcoming decades, one adaptation mechanism has emerged with consensus support: the upgrade and dissemination of spatially-resolved, accurate forecasts tailored to the needs of users. Forecasting can facilitate the changeover from dependence on climatology that is increasingly out of date. The best forecasters are local, but local forecasters face great constraints in some countries. Indeed, it is no coincidence that some areas subject to great weather variability and strong processes of climate change are economically vulnerable: mountainous regions, for example, where heavy and erratic flooding can destroy the value built up by households over years. It follows that those best placed to benefit from forecasting upgrades may not be those who have invested in the greatest capacity to date. More-flexible use of the global forecasts may contribute to adaptation. NOAA anticipated several years ago that their forecasts could be used in new ways in the future, and accordingly prepared sockets for easy access to their archives. These could be used to empower various national and regional capacities. Verification to identify practical lead times for the economically important variables is a needed first step. This presentation presents the verification that our team has undertaken, a pilot effort in which we considered variables of interest to economic actors in several lower income countries, cf. shepherds in a remote area of Central Asia, and verified the ensemble forecasts of those variables.

Hancock, L. O.; Alpert, J. C.; Kordzakhia, M.

2009-12-01

331

Aurora Forecast  

NSDL National Science Digital Library

The Aurora Forecast from the Geophysical Institute at the University of Alaska, Fairbanks, provides aurora activity predictions for different locations around the world. Predictions are available as maps or as audio files. Users select a geographical area, and they are presented with a forecast map with the approximate Universal Time of greatest activity for the selected longitude about an hour before local geomagnetic midnight. Also included are links to information about the forecasts, how to interpret the forecasts, geomagnetic activity, and aurora links.

332

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

USGS Publications Warehouse

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

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

2013-01-01

333

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

NASA Astrophysics Data System (ADS)

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.

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

2012-12-01

334

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

NASA Astrophysics Data System (ADS)

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.

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

2011-12-01

335

Urbanization, climate change and flood policy in the United States  

Microsoft Academic Search

The average annual cost of floods in the United States has been estimated at about $2 billion (current US dollars). The federal\\u000a government, through the creation of the National Flood Insurance Program (NFIP), has assumed responsibility for mitigating\\u000a the societal and economic impacts of flooding by establishing a national policy that provides subsidized flood insurance.\\u000a Increased flood costs during the

Alexandros A. Ntelekos; Michael Oppenheimer; James A. Smith; Andrew J. Miller

2010-01-01

336

Evaluating the Performance of a Coupled Distributed Hydrologic - Hydraulic Model for Flash Flood Modeling Using Multiple Precipitation Data Sources  

NASA Astrophysics Data System (ADS)

Flash floods are considered one of the most hazardous natural disasters, which kills thousands of people and causes billions of US dollar economic damages annually world-wide. Forecasting flash floods to provide accurate warnings in a timely manner is still challenging. At the Center for Hydrometeorology and Remote Sensing (CHRS) at the University of California, Irvine, we have been developing a coupled high resolution distributed hydrologic-hydraulic system for flash flood modeling which has been successfully tested for some selected areas in the U.S. and has potential to be implemented in global scale. The system employs the National Weather Service's distributed hydrologic model (HL-RDHM) as a rainfall-runoff generator, and a high-resolution hydraulic model (BreZo) for simulating the channel and flood-plain flows realistically. In this research, we evaluate the system for flash flood warning using multiple precipitation sources (gauge, radar and satellite and forecast). A flash flood event occurring on June 11, 2010 in the Upper Little Missouri River watershed in Arkansas is used as a case study. The catchment was delineated into 123 sub-catchments based on the 10m Digital Elevation Model (DEM) topography data from USGS. From HL-RDHM surface runoff, 123 hydrographs can be derived and connected as inputs to BreZo. The system was calibrated using NEXRAD Stage IV radar-based rainfall by tuning the roughness parameter in BreZo to best match the USGS discharge observation at the catchment outlet. The results show good agreement with the USGS gauge flow measurement (Nash-Sutcliffe coefficient = 0.91) when using Stage IV data. The system is under investigation with satellite-based precipitation data, rain gauge and Global Forecast System (GFS) data and will be reported in the presentation.

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

2013-12-01

337

Urban flooding and Resilience: concepts and needs  

NASA Astrophysics Data System (ADS)

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

Gourbesville, Ph.

2012-04-01

338

Global ensemble forecasting  

NASA Astrophysics Data System (ADS)

During the past 10 years ensemble forecasting has established itself as an important component in numerical weather prediction. Global ensemble prediction systems have been operational at the European Centre for Medium-Range Weather Forecasts (ECMWF) and at the National Meteorological Center for Environmental Prediction (NOAA/NWS/NCEP) since December 1992, and at the Meterological Service of Canada (MSC/CMC) since February 1998. In this talk, the similarities and differences among the three operational global ensemble forecast systems are discussed. The performance of the three systems is illustrated and compared over a three month period (May-July) in 2002. Also reviewed are open issues, ongoing research projects, and future directions related to ensemble forecasting efforts at the three centers.

Toth, Z.; Buizza, R.; Houtekamer, P.

2003-04-01

339

Tips for Emergency Managers Potential Storm Surge Flooding  

E-print Network

Tips for Emergency Managers Potential Storm Surge Flooding The Potential Storm Surge Flooding map storm surge flooding associated with tropical cyclones. This fact sheet can help emergency manag- ers's National Hurricane Center (NHC) will experimentally issue the Potential Storm Surge Flooding map to show

340

COME RAIN OR SHINE: EVIDENCE ON FLOOD INSURANCE PURCHASES IN  

E-print Network

COME RAIN OR SHINE: EVIDENCE ON FLOOD INSURANCE PURCHASES IN FLORIDA Erwann MICHEL-KERJAN Carolyn ON FLOOD INSURANCE PURCHASES IN FLORIDA1 Erwann MICHEL-KERJAN2 Carolyn KOUSKY3 Mars 2009 Cahier n° 2009-11 Abstract: In the U.S., flood insurance is provided essentially through the National Flood Insurance Program

Paris-Sud XI, Université de

341

Flood insurance and floodplain management: the US experience  

Microsoft Academic Search

With over six million buildings located within the boundaries of the 100-yr floodplain, flood losses across the United States are widespread (88% of US counties experienced at least one flood disaster during the second half of the twentieth century). To deal with this problem, the federal government provides flood insurance through the National Flood Insurance Program, which was initiated by

Raymond J. Burby

2001-01-01

342

Modeling and classifying variable width riparian zones utilizing digital elevation models, flood height data, digital soil data and National Wetlands Inventory: A new approach for riparian zone delineation  

NASA Astrophysics Data System (ADS)

Riparian zones are dynamic, transitional ecosystems between aquatic and terrestrial ecosystems with well defined vegetation and soil characteristics. Development of an all-encompassing definition for riparian ecotones, because of their high variability, is challenging. However, there are two primary factors that all riparian ecotones are dependent on: the watercourse and its associated floodplain. Previous approaches to riparian boundary delineation have utilized fixed width buffers, but this methodology has proven to be inadequate as it only takes the watercourse into consideration and ignores critical geomorphology, associated vegetation and soil characteristics. Our approach offers advantages over other previously used methods by utilizing: the geospatial modeling capabilities of ArcMap GIS; a better sampling technique along the water course that can distinguish the 50-year flood plain, which is the optimal hydrologic descriptor of riparian ecotones; the Soil Survey Database (SSURGO) and National Wetland Inventory (NWI) databases to distinguish contiguous areas beyond the 50-year plain; and land use/cover characteristics associated with the delineated riparian zones. The model utilizes spatial data readily available from Federal and State agencies and geospatial clearinghouses. An accuracy assessment was performed to assess the impact of varying the 50-year flood height, changing the DEM spatial resolution (1, 3, 5 and 10m), and positional inaccuracies with the National Hydrography Dataset (NHD) streams layer on the boundary placement of the delineated variable width riparian ecotones area. The result of this study is a robust and automated GIS based model attached to ESRI ArcMap software to delineate and classify variable-width riparian ecotones.

Abood, Sinan A.

343

Flood-inundation maps for the Leaf River at Hattiesburg, Mississippi  

USGS Publications Warehouse

Digital flood-inundation maps for a 1.7-mile reach of the Leaf River were developed 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 Leaf River study reach extends from just upstream of the U.S. Highway 11 crossing to just downstream of East Hardy/South Main Street and separates the cities of Hattiesburg and Petal, Mississippi. 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-surface elevations (stages) at the USGS streamgage at Leaf River at Hattiesburg, Mississippi (02473000). Current conditions at the USGS streamgage may be obtained through the National Water Information System Web site at http://waterdata.usgs.gov/ms/nwis/uv/?site_no=02473000&PARAmeter_cd=00065,00060. 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 collocated at USGS streamgages. The forecasted peak-stage information, available on the AHPS 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 model was calibrated using the most current stage-discharge relations at the Leaf River at Hattiesburg, Mississippi, streamgage 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-surface elevation at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model [derived from Light Detection and Ranging (LiDAR) data having a 0.6-foot vertical accuracy and 9.84-foot horizontal resolution] in order to delineate the area flooded at each 1-foot increment of stream stage. The availability of these maps, when combined with real-time stage information from USGS streamgages and forecasted stream stage from the NWS, provides emergency management personnel and residents with critical information during flood-response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

Storm, John B.

2012-01-01

344

Weather Forecasting  

NSDL National Science Digital Library

This website, supplied by Annenberg / CPB, discusses weather satellites, Doppler radar, and additional tools forecasters use to predict the weather. Students can find a wind chill calculator along with a brief discussion of the history of forecasting and weather lore. Once you have a firm grasp on the science of weather forecasting, be sure to check out the other sections of this site, which include: "ice and snow," "our changing climate," "the water cycle," and "powerful storms."

2008-03-27

345

Comparing Postprocessing Approaches to Calibrating Operational River Discharge Forecasts  

NASA Astrophysics Data System (ADS)

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.

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

2010-12-01

346

Flood Analysis  

NSDL National Science Digital Library

Students learn how to use and graph real-world stream gage data to create event and annual hydrographs and calculate flood frequency statistics. Using an Excel spreadsheet of real-world event, annual and peak streamflow data, they manipulate the data (converting units, sorting, ranking, plotting), solve problems using equations, and calculate return periods and probabilities. Prompted by worksheet questions, they analyze the runoff data as engineers would. Students learn how hydrographs help engineers make decisions and recommendations to community stakeholders concerning water resources and flooding.

Integrated Teaching And Learning Program

347

Rivers and Flooding Lab  

NSDL National Science Digital Library

Understand flooding - why it occurs, how to measure the size and frequency of a flood, the relationship between size and flooding, and how human activity can increase the frequency of flooding events.

Senft, Laurel

348

2-D Numerical Simulation of Flooding Effects Caused by South-to-North Water Transfer Project  

Microsoft Academic Search

Since the General Channel designed for the South-to-North Water Transfer Project in China has to cross many rivers and streams flowing from west to east, there are potentially serious effects additional flooding on the western side of the project alignment. Therefore, a 2-D numerical model for forecasting basin flood disasters was established and verified using historical flood data. The model

Dong-po SUN; Hai XUE; Peng-tao WANG; Rui-li LU; Xiao-long LIAO

2008-01-01

349

44 CFR 63.3 - Requirement to be covered by a contract for flood insurance by June 1, 1988.  

Code of Federal Regulations, 2012 CFR

...to be covered by a contract for flood insurance by June 1, 1988. 63.3...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

2012-10-01

350

44 CFR 63.3 - Requirement to be covered by a contract for flood insurance by June 1, 1988.  

Code of Federal Regulations, 2010 CFR

...to be covered by a contract for flood insurance by June 1, 1988. 63.3...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

2010-10-01

351

44 CFR 63.3 - Requirement to be covered by a contract for flood insurance by June 1, 1988.  

Code of Federal Regulations, 2011 CFR

...to be covered by a contract for flood insurance by June 1, 1988. 63.3...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

2011-10-01

352

44 CFR 63.3 - Requirement to be covered by a contract for flood insurance by June 1, 1988.  

Code of Federal Regulations, 2013 CFR

...to be covered by a contract for flood insurance by June 1, 1988. 63.3...HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General §...

2013-10-01

353

Flood Loss Model for Austria  

NASA Astrophysics Data System (ADS)

A new flood model for Austria quantifying fluvial flood losses based on probabilistic event set developed by Impact Forecasting (Aon Benfield's model development centre) was released in June 2011. It was successfully validated with two serious past flood events - August 2002 and August 2005. The model is based on 10 meters cell size digital terrain model with 1cm vertical step and uses daily mean flows from 548 gauge stations of series of average length ~ 60 years. The even set is based on monthly maxima flows correlation, generating 12 stochastic events per year and allows to calculate annual and occurrence exceedance probability loss estimates. The model contains flood extents for more than 24,000 km of modelled river network compatible with HORA project (HOchwasserRisikoflächen Austria) for design flows ranging from 2 to 10,000 years. Model is primarily constructed to work with postal level resolution insurance data reducing positional uncertainty by weighting over more than 2.5 millions address points from Austria Post's ACGeo database. Countrywide flood protections were provided by the Austrian Ministry of Environment. The model was successfully tested with property portfolios of 8 global and local insurance companies and was also successfully validated with August 2002 and August 2005 past events evaluating their return period on the probabilistic simulation basis.

Pun?ochá?, P.; Podlaha, A.

2012-04-01

354

Introduction to Ensembles: Forecasting Hurricane Sandy  

NSDL National Science Digital Library

This module provides an introduction to ensemble forecast systems with an operational case study of Hurricane Sandy. The module concentrates on models from NCEP and FNMOC available to forecasters in the U.S. Navy, including NAEFS (North American Ensemble Forecast System), and NUOPC (National Unified Operational Prediction Capability). Probabilistic forecasts of winds and waves developed from these ensemble forecast systems are applied to a ship transit and coastal resource protection. Lessons integrated in the case study provide information on ensemble statistics, products, bias correction and verification. Additional lessons address multimodel ensembles, extreme events, and automated forecasting.

Comet

2013-03-28

355

Ensemble forecasting  

Microsoft Academic Search

Numerical weather prediction models as well as the atmosphere itself can be viewed as nonlinear dynamical systems in which the evolution depends sensitively on the initial conditions. The fact that estimates of the current state are inaccurate and that numerical models have inadequacies, leads to forecast errors that grow with increasing forecast lead time. The growth of errors depends on

M. Leutbecher; T. N. Palmer

2008-01-01

356

Weather Forecasting  

NSDL National Science Digital Library

This activity (on page 2 of the PDF) is a full inquiry investigation into meteorology and forecasting. Learners will research weather folklore, specifically looking for old-fashioned ways of predicting the weather. Then, they'll record observations of these predictors along with readings from their own homemade barometer, graphing the correct predictions for analysis. Relates to linked video, DragonflyTV: Forecasting.

Twin Cities Public Television, Inc.

2005-01-01

357

A Decision Support System for Monitoring, Reporting, and Forecasting Ecological Conditions of the Appalachian National Scenic Trail  

NSDL National Science Digital Library

This project represents a collaborative multi-agency effort to support decision-making for the A.T. by providing a coherent framework for data integration, monitoring, reporting and forecasting. The A.T.-DSS integrates NASA multi-platform sensor data, NASA Terrestrial Observation and Prediction System (TOPS) models, and in situ measurements from A.T. MEGA-Transect partners to address the management issues of the A.T. environment. The A.T.-DSS focuses on primary vital signs of phenology and climate, forest health and landscape dynamics, among others.

2012-01-01

358

Flooding Exercises  

NSDL National Science Digital Library

This homework exercise, developed for an undergraduate geology course at Tulane University, leads students through the steps involved in determining the probability that a flood of a given discharge will occur in any given year. Students retrieve discharge data from U.S. Geological Services Internet sites for Dry Creek, LA, Rapid Creek, SD and Red River, ND to make their calculations.

Nelson, Stephen

359

Floods in Central Europe in June 2013  

NASA Astrophysics Data System (ADS)

Several days of heavy rain combined with saturated soil at the end of May and beginning of June 2013, led to extreme flooding in vast areas alongside the major rivers of Central Europe. A quasi-stationary low pressure system brought moist, warm air from the east and northeast into Central Europe causing massive amounts of rain in Southern Germany and Western Austria between the end of May and the beginning of June. Orographic enhancement of precipitation along the northern side of the Alps played an important role. This study evaluates how well the extreme event was captured by ECMWF's model system. ECMWF's ensemble forecast gave an early indication of heavy precipitation and the high-resolution forecast captured the spatial distribution very well. Also satellite observations indicated that there were extremely wet soil conditions. The European Flood Awareness System (EFAS) predicted high to extreme flood events, and a total of 14 flood alerts and watches were sent during the flood period. Although a signal of a hazardous event was detected as far a week in advance in the forecast models, the severity of the event was not fully captured. The models predicted the spatial extent and location of the extreme precipitation well, but the magnitude was underestimated. Experiments with higher resolution in the atmospheric models show some improvement in the magnitude, but the amount of precipitation was still underestimated.

Wetterhall, Fredrik; Pappenberger, Florian; Albergel, Clement; Alfieri, Lorenzo; Balsamo, Gianpaolo; Bogner, Konrad; Haiden, Thomas; Hewson, Tim; Magnusson, Linus; de Rosnay, Patricia; Munoz-Sabater, Joaquin; Tsonevsky, Ivan

2014-05-01

360

In Brief: A new flood monitoring system  

NASA Astrophysics Data System (ADS)

A system of `intelligent' sensors linked in a grid could provide rapid, low-cost flood forecasts. The system's designers, scientists from the University of Lancaster (U.K.), recently installed the sensors at 13 locations across a Yorkshire (U.K.) flood plain. At each location, researchers placed a depth sensor and digital camera that can measure the speed of flotsam in the water. Computers incorporated into the sensors link them together wirelessly in a grid that allows the system to adapt as flood waters rise or if some sensors cease working or wash away. In addition, the sensors can adjust their power management so that, for example, they use less power during dry times. Flood forecasting models are run on the computer grid and adjust their predictions as the information from the sensors changes. Keith Beven of Lancaster University said that this type of local system could provide advance warning even in situations of fast rainfall that typically make flood forecasting difficult.

Zielinski, Sarah

2006-11-01

361

METEOROLOGICAL Weather and Forecasting  

E-print Network

AMERICAN METEOROLOGICAL SOCIETY Weather and Forecasting EARLY ONLINE RELEASE This is a preliminary and interpretation of information from National Weather Service watches and warnings by10 decision makers such an outlier to the regional severe weather climatology. An analysis of the synoptic and13 mesoscale

362

Flood information for flood-plain planning  

USGS Publications Warehouse

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

Bue, Conrad D.

1967-01-01

363

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

Code of Federal Regulations, 2010 CFR

...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD...determination; (h) A copy of the flood insurance study for the community; (i) A...

2010-10-01

364

24 CFR 1000.38 - What flood insurance requirements are applicable?  

...2014-04-01 false What flood insurance requirements are applicable... General § 1000.38 What flood insurance requirements are applicable...participating in the National Flood Insurance Program in accord with...

2014-04-01

365

24 CFR 1000.38 - What flood insurance requirements are applicable?  

Code of Federal Regulations, 2011 CFR

...2011-04-01 false What flood insurance requirements are applicable... General § 1000.38 What flood insurance requirements are applicable...participating in the National Flood Insurance Program in accord with...

2011-04-01

366

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

Code of Federal Regulations, 2011 CFR

...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD...determination; (h) A copy of the flood insurance study for the community; (i) A...

2011-10-01

367

24 CFR 1000.38 - What flood insurance requirements are applicable?  

Code of Federal Regulations, 2012 CFR

...2012-04-01 false What flood insurance requirements are applicable... General § 1000.38 What flood insurance requirements are applicable...participating in the National Flood Insurance Program in accord with...

2012-04-01

368

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

Code of Federal Regulations, 2012 CFR

...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD...determination; (h) A copy of the flood insurance study for the community; (i) A...

2012-10-01

369

24 CFR 1000.38 - What flood insurance requirements are applicable?  

Code of Federal Regulations, 2010 CFR

...2010-04-01 false What flood insurance requirements are applicable... General § 1000.38 What flood insurance requirements are applicable...participating in the National Flood Insurance Program in accord with...

2010-04-01

370

24 CFR 1000.38 - What flood insurance requirements are applicable?  

Code of Federal Regulations, 2013 CFR

...2013-04-01 false What flood insurance requirements are applicable... General § 1000.38 What flood insurance requirements are applicable...participating in the National Flood Insurance Program in accord with...

2013-04-01

371

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

Code of Federal Regulations, 2013 CFR

...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD...determination; (h) A copy of the flood insurance study for the community; (i) A...

2013-10-01

372

Flood Protection Structure Accreditation Task Force: Interim Report  

E-print Network

inspections and assessments and the National Flood Insurance Program levee accreditation requirements Flood Insurance Program (NFIP) so that: n Information and data collected for either purpose can be used (ICW) program or National Flood Insurance Program (NFIP) levee accreditation process can be used

US Army Corps of Engineers

373

Towards real-time eruption forecasting in the Auckland Volcanic Field: application of BET_EF during the New Zealand National Disaster Exercise `Ruaumoko'  

NASA Astrophysics Data System (ADS)

The Auckland Volcanic Field (AVF) is a young basaltic field that lies beneath the urban area of Auckland, New Zealand’s largest city. Over the past 250,000 years the AVF has produced at least 49 basaltic centers; the last eruption was only 600 years ago. In recognition of the high risk associated with a possible future eruption in Auckland, the New Zealand government ran Exercise Ruaumoko in March 2008, a test of New Zealand’s nation-wide preparedness for responding to a major disaster resulting from a volcanic eruption in Auckland City. The exercise scenario was developed in secret, and covered the period of precursory activity up until the eruption. During Exercise Ruaumoko we adapted a recently developed statistical code for eruption forecasting, namely BET_EF (Bayesian Event Tree for Eruption Forecasting), to independently track the unrest evolution and to forecast the most likely onset time, location and style of the initial phase of the simulated eruption. The code was set up before the start of the exercise by entering reliable information on the past history of the AVF as well as the monitoring signals expected in the event of magmatic unrest and an impending eruption. The average probabilities calculated by BET_EF during Exercise Ruaumoko corresponded well to the probabilities subjectively (and independently) estimated by the advising scientists (differences of few percentage units), and provided a sound forecast of the timing (before the event, the eruption probability reached 90%) and location of the eruption. This application of BET_EF to a volcanic field that has experienced no historical activity and for which otherwise limited prior information is available shows its versatility and potential usefulness as a tool to aid decision-making for a wide range of volcano types. Our near real-time application of BET_EF during Exercise Ruaumoko highlighted its potential to clarify and possibly optimize decision-making procedures in a future AVF eruption crisis, and as a rational starting point for discussions in a scientific advisory group. It also stimulated valuable scientific discussion around how a future AVF eruption might progress, and highlighted areas of future volcanological research that would reduce epistemic uncertainties through the development of better input models.

Lindsay, Jan; Marzocchi, Warner; Jolly, Gill; Constantinescu, Robert; Selva, Jacopo; Sandri, Laura

2010-03-01

374

Flood Hazards, Insurance Rates, and Amenities: Evidence From the Coastal Housing Market  

Microsoft Academic Search

Abstract This study employs the hedonic property price method to examine the effects of flood hazard on coastal property values. We utilize Geographic Information System data on National Flood Insurance Program flood zones and residential property sales from Carteret County, North Carolina. Our results indicate that location within a flood zone lowers property value. Price differentials for flood risk and

Okmyung Bin; Jamie Brown Kruse; Craig E. Landry

2008-01-01

375

The Effect of NEXRAD Image Looping and National Convective Weather Forecast Product on Pilot Decision Making in the Use of a Cockpit Weather Information Display  

NASA Technical Reports Server (NTRS)

This experiment investigated improvements to cockpit weather displays to better support the hazardous weather avoidance decision-making of general aviation pilots. Forty-eight general aviation pilots were divided into three equal groups and presented with a simulated flight scenario involving embedded convective activity. The control group had access to conventional sources of pre-flight and in-flight weather products. The two treatment groups were provided with a weather display that presented NEXRAD mosaic images, graphic depiction of METARs, and text METARs. One treatment group used a NEXRAD image looping feature and the second group used the National Convective Weather Forecast (NCWF) product overlaid on the NEXRAD display. Both of the treatment displays provided a significant increase in situation awareness but, they provided incomplete information required to deal with hazardous convective weather conditions, and would require substantial pilot training to permit their safe and effective use.

Burgess, Malcolm A.; Thomas, Rickey P.

2004-01-01

376

Olympian weather forecasting  

NASA Astrophysics Data System (ADS)

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

Showstack, Randy

377

24 CFR 241.265 - Insurance of property against flood.  

Code of Federal Regulations, 2012 CFR

...2012-04-01 false Insurance of property against flood. 241.265 Section...DEVELOPMENT MORTGAGE AND LOAN INSURANCE PROGRAMS UNDER NATIONAL...Obligations § 241.265 Insurance of property against flood. The mortgaged...

2012-04-01

378

24 CFR 241.265 - Insurance of property against flood.  

Code of Federal Regulations, 2013 CFR

...2013-04-01 false Insurance of property against flood. 241.265 Section...DEVELOPMENT MORTGAGE AND LOAN INSURANCE PROGRAMS UNDER NATIONAL...Obligations § 241.265 Insurance of property against flood. The mortgaged...

2013-04-01

379

24 CFR 241.265 - Insurance of property against flood.  

Code of Federal Regulations, 2011 CFR

...2011-04-01 false Insurance of property against flood. 241.265 Section...DEVELOPMENT MORTGAGE AND LOAN INSURANCE PROGRAMS UNDER NATIONAL...Obligations § 241.265 Insurance of property against flood. The mortgaged...

2011-04-01

380

24 CFR 241.265 - Insurance of property against flood.  

Code of Federal Regulations, 2010 CFR

...2010-04-01 false Insurance of property against flood. 241.265 Section...DEVELOPMENT MORTGAGE AND LOAN INSURANCE PROGRAMS UNDER NATIONAL...Obligations § 241.265 Insurance of property against flood. The mortgaged...

2010-04-01

381

24 CFR 241.265 - Insurance of property against flood.  

...2014-04-01 false Insurance of property against flood. 241.265 Section...DEVELOPMENT MORTGAGE AND LOAN INSURANCE PROGRAMS UNDER NATIONAL...Obligations § 241.265 Insurance of property against flood. The mortgaged...

2014-04-01

382

44 CFR 61.13 - Standard Flood Insurance Policy.  

Code of Federal Regulations, 2012 CFR

... 2011-10-01 true Standard Flood Insurance Policy. 61.13 Section 61.13 ...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES...

2012-10-01

383

44 CFR 61.13 - Standard Flood Insurance Policy.  

Code of Federal Regulations, 2010 CFR

... 2010-10-01 false Standard Flood Insurance Policy. 61.13 Section 61.13 ...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES...

2010-10-01

384

44 CFR 64.3 - Flood Insurance Maps.  

Code of Federal Regulations, 2010 CFR

...2010-10-01 2010-10-01 false Flood Insurance Maps. 64.3 Section 64.3 Emergency...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program COMMUNITIES ELIGIBLE FOR THE...

2010-10-01

385

44 CFR 61.17 - Group Flood Insurance Policy.  

Code of Federal Regulations, 2010 CFR

...2010-10-01 2010-10-01 false Group Flood Insurance Policy. 61.17 Section 61.17 ...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES...

2010-10-01

386

44 CFR 61.13 - Standard Flood Insurance Policy.  

Code of Federal Regulations, 2011 CFR

... 2011-10-01 false Standard Flood Insurance Policy. 61.13 Section 61.13 ...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program INSURANCE COVERAGE AND RATES...

2011-10-01

387

44 CFR 73.3 - Denial of flood insurance coverage.  

Code of Federal Regulations, 2011 CFR

...2011-10-01 false Denial of flood insurance coverage. 73.3 Section 73.3 ...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION...

2011-10-01

388

44 CFR 64.3 - Flood Insurance Maps.  

Code of Federal Regulations, 2011 CFR

...2011-10-01 2011-10-01 false Flood Insurance Maps. 64.3 Section 64.3 Emergency...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program COMMUNITIES ELIGIBLE FOR THE...

2011-10-01

389

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

390

Business Forecasting  

NSDL National Science Digital Library

Created by Fred Collopy, Weatherhead School of Management, Case Western Reserve University, this site provides access to current research in business forecasting. The most up-to-date information is maintained in the News section, complete with links to up-coming conferences, competitions, and pub