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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

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

3

STORM3: a new flood forecast management and monitoring system in accordance with the recent Italian national directive  

NASA Astrophysics Data System (ADS)

The effectiveness of alert systems for civil protection purposes, defined as the ability to minimize the level of risk in a region subjected to an imminent flood event, strongly depends on availability and exploitability of information. It also depends on technical expertise and the ability to easily manage the civil protection actions through the organization into standardized procedures. Hydro-geologic and hydraulic risk estimation, based on the combination of different technical issues (in this case meteorological, hydro-geological, hydraulic matters), but also socio-economic ones, requires the integration between quasi-static and time-varying information within the same operative platform. Beside the real-time data exchange, a Decision Support System must provide tools which enable knowledge sharing among the civil protection centres. Moreover, due to the amount and heterogeneity of information, quality procedures become necessary to handle all forecasting and monitoring routines within operative centres, according to the latest national directive. In Italy procedures on the civil protection matter have been condensed into the Prime Minister's Directive (27 February 2004. STORM3, an innovative management and monitoring System for real-time flood forecasting and warning, takes in the Directive, supporting the operator step by step within the different phases of civil protection activities.

Burastero, A.; Pintus, F.; Rossi, L.; Versace, C.

2005-09-01

4

A HISTORICAL ANALYSIS OF RIVER FLOODING AT SELECT NATIONAL WEATHER SERVICE RIVER FORECAST LOCATIONS IN GEORGIA  

Microsoft Academic Search

River flooding has played a significant role in Georgia's history of natural disasters. As recent as July 1994, heavy rainfall from the remnants of Tropical Storm Alberto caused some of the worst river flooding in Georgia's history. In April of 2000, the Georgia Emergency Management Agency reported that nearly 75 percent of Georgia's disaster losses since 1990 had been linked

Jeff C. Dobur

5

COMBINED FLOOD ROUTING AND FLOOD LEVEL FORECASTING  

Microsoft Academic Search

This paper presents a proposed modeling approach which uses unsteady flow hydraulic modelllng for both flood routing and flood level determination. The onerous data requirements of hydraulic models In the flood routing applicatlon are overcome through the use of a \\

J. BlackburnA; F. E. HicksB

6

Combined flood routing and flood level forecasting  

Microsoft Academic Search

This paper presents a proposed modeling approach which uses unsteady flow hydraulic modeling for both flood routing and flood level determination. The onerous data requirements of hydraulic models in the flood routing application are overcome through the use of a \\

J. Blackburn; F. E. Hicks

2002-01-01

7

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

8

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

9

Recent advances in flood forecasting and flood risk assessment  

Microsoft Academic Search

Recent large floods in Europe have led to increased interest in research and development of flood forecasting systems. Some of these events have been provoked by some of the wettest rainfall periods on record which has led to speculation that such extremes are attributable in some measure to anthropogenic global warming and represent the beginning of a period of higher

G. Arduino; P. Reggiani; E. Todini

2005-01-01

10

Flood Forecasting in River System Using ANFIS  

SciTech Connect

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. [Dept. of Civil Eng., NIT, Silchar (India)

2010-10-26

11

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

12

Statistical Flood Forecasting for the Mekong River  

NASA Astrophysics Data System (ADS)

An ongoing study for improving flood forecasting for the Mekong River by statistical methods has yielded first results, which reduce forecasting errors of previous forecasting models. A forecast always is subject to uncertainty, both due to model uncertainty and natural variability. In principle, model uncertainty could be reduced by improved models and better calibration, whereas natural variability has to be endured. In flood forecasting, hydro-meteorological uncertainties, physiographic unknowns together with measurement errors and model errors are decisive factors determining the width of future uncertainty bands. The degree of certitude of forecasts varies from event to event depending on the ensemble of realizations of the flood hydrograph (Krzysztofowicz, 2001). Without any information on previous discharges and rainfall the range of forecasts can be between zero and infinity. When time series of discharges are available then the uncertainty band is the probability distribution of the stages. At any particular point in time the uncertainty band can be further narrowed by usage of real time discharges of the past, and conditional maximum and minimum discharges for the future can be estimated, due to the existence of physical continuity in space and time. As a consequence, for one day ahead forecasts the coefficient of variation of the forecast for small basins is large, whereas it is small for large river basins, as for the Mekong River (Plate, 2005). The consequences of this continuity for the Mekong are explored in this study. The basin of the Mekong River has an area of 795,000 km² and a length of about 4000 km. Flooding is a major problem, and flood forecasting is the most important non-technical solution. The existing forecasting method is based on a physical hydrological model, which yields forecasts of limited accuracy, partly due to limited quality of runoff data and insufficient rainfall information in this data sparse basin. To overcome shortcomings of the physical model, we develop models based on a mix of statistical analysis and physical modeling. As a first approach probability distributions of lateral inflows per day for the reach between Vientiane in Laos and Stung Treng in Cambodia are estimated for hydrographs which exceed a critical level. By means of past flood records upper and lower uncertainty bounds for the day ahead water stages were determined for 4 stations along the middle reach of the Mekong River. The flow time between adjacent stations is one day. Therefore, the discharge for a one day forecast is estimated as the discharge of the upstream station one day ahead. To this the inflow into the reach between the two stations is added, which is estimated from the (conditional) probability distributions of the lateral inflows. First results of this approach show that that the Nash - Sutcliffe criterion for the forecast is better than 90%. A more appropriate efficiency criterion defined by Plate (Plate & Lindenmaier, 2008) ranges from 0.2 to 0.5, which implies that the variance of the forecast error based on this approach is only 20 to 50% of the variance of forecast errors that is obtained if the assumption is used that the forecast value of tomorrow is the same as the value of today. References: Krzysztofowicz, R. (2001) " The case of probabilistic forecasting in hydrology", Journal of Hydrology Vol. 249,.1-4: pp. 1-9. Plate, E.J. (2007): "Early warning for large rivers with the lower Mekong as example". Journal of Hydro-environment Research, Vol.1 pp.80-94. Plate, E.J. and Lindenmaier, F. (2008) " Quality assessments of forecast", 6th Annual Mekong Flood Forum, Phnom Penh, Cambodia 27-28 May

Shahzad, M. K.; Lindenmaier, F.; Ihringer, J.; Plate, E. J.; Nestmann, F.

2009-04-01

13

Improving operational flood forecasting through data assimilation  

NASA Astrophysics Data System (ADS)

Accurate flood forecasts have been a challenging topic in hydrology for decades. Uncertainty in hydrological forecasts is due to errors in initial state (e.g. forcing errors in historical mode), errors in model structure and parameters and last but not least the errors in model forcings (weather forecasts) during the forecast mode. More accurate flood forecasts can be obtained through data assimilation by merging observations with model simulations. This enables to identify the sources of uncertainties in the flood forecasting system. Our aim is to assess the different sources of error that affect the initial state and to investigate how they propagate through hydrological models with different levels of spatial variation, starting from lumped models. The knowledge thus obtained can then be used in a data assimilation scheme to improve the flood forecasts. This study presents the first results of this framework and focuses on quantifying precipitation errors and its effect on discharge simulations within the Ourthe catchment (1600 km2), which is situated in the Belgian Ardennes and is one of the larger subbasins of the Meuse River. Inside the catchment, hourly rain gauge information from 10 different locations is available over a period of 15 years. Based on these time series, the bootstrap method has been applied to generate precipitation ensembles. These were then used to simulate the catchment's discharges at the outlet. The corresponding streamflow ensembles were further assimilated with observed river discharges to update the model states of lumped hydrological models (R-PDM, HBV) through Residual Resampling. This particle filtering technique is a sequential data assimilation method and takes no prior assumption of the probability density function for the model states, which in contrast to the Ensemble Kalman filter does not have to be Gaussian. Our further research will be aimed at quantifying and reducing the sources of uncertainty that affect the initial state in distributed models and will assess the added value of spatially measured data.

Rakovec, Oldrich; Weerts, Albrecht; Uijlenhoet, Remko; Hazenberg, Pieter; Torfs, Paul

2010-05-01

14

Flood forecasting using time series data mining  

Microsoft Academic Search

Earthquakes, floods, rainfall represent a class of nonlinear systems termed chaotic, in which the relationships between variables in a system are dynamic and disproportionate, however completely deterministic. Classical linear time series models have proved inadequate in analysis and prediction of complex geophysical phenomena. Nonlinear approaches such as Artificial Neural Networks, Hidden Markov Models and Nonlinear Prediction are useful in forecasting

Chaitanya Damle

2005-01-01

15

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

16

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

17

HESS Opinions "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, F.; Pappenberger, F.; Alfieri, L.; Cloke, H. L.; Thielen-del Pozo, J.; Balabanova, S.; Da?helka, J.; Vogelbacher, A.; Salamon, P.; Carrasco, I.; Cabrera-Tordera, A. J.; Corzo-Toscano, M.; Garcia-Padilla, M.; Garcia-Sanchez, R. J.; Ardilouze, C.; Jurela, S.; Terek, B.; Csik, A.; Casey, J.; Stank?navi?ius, G.; Ceres, V.; Sprokkereef, E.; Stam, J.; Anghel, E.; Vladikovic, D.; Alionte Eklund, C.; Hjerdt, N.; Djerv, H.; Holmberg, F.; Nilsson, J.; Nyström, K.; Sušnik, M.; Hazlinger, M.; Holubecka, M.

2013-11-01

18

The effectiveness of Quantile Regression for bias correction and uncertainty estimation in operational hydrological forecasting systems: Examples from the National Flood Forecasting System  

NASA Astrophysics Data System (ADS)

A technique for the operational assessment of the uncertainty of around discharge and water level forecasts is presented that conditions forecast uncertainty on the forecasted process itself, based on retrospective quantile regression of hindcasted discharge or water level forecasts and forecast errors. In an operational setting, the main advantage of quantile regression with respect to other uncertainty estimation methods is that it can be applied as post-processor on forecasted values without any additional input requirements. To take account of the heteroscedasticity of errors in hydrologic process descriptions, we derive the regression relations after a transformation of the training data set to the Gaussian domain. To test the robustness of the method, a number of retrospective forecasts for different catchments across the UK having different size and hydrological characteristics have been used to derive in a probabilistic sense the relation between simulated values of discharges and water levels at different lead times, and matching errors. Consequently, the derived regression relationships have been validated with an independent set of forecasts. From this study, we can conclude that using quantile regression for estimating forecast errors conditional on the forecasted water levels provides an extremely simple, efficient and robust means for uncertainty estimation of deterministic forecasts.

Weerts, Albrecht; Winsemius, Hessel; Laeger, Stefan

2010-05-01

19

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

Microsoft Academic Search

The National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) provides flood forecast information in a variety of formats, including graphical hydrographs and text products. Beginning in 2002, the NOAA Coastal Services Center (CSC) and NWS have worked in partnership to develop geographic information systems (GIS) based graphical flood severity inundation products. GIS techniques are used along with the

D. Marcy; T. Donaldson

2006-01-01

20

Impact of rainfall spatial variability on Flash Flood Forecasting  

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

21

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

22

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

23

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

24

Defining critical thresholds for ensemble flood forecasting and warning  

NASA Astrophysics Data System (ADS)

The use of weather ensemble predictions in ensemble flood forecasting is an acknowledged procedure to include the uncertainty of meteorological forecasts in a probabilistic streamflow prediction system. Operational flood forecasters can thus get an overview of the probability of exceeding a critical discharge or water level, and decide on whether a flood warning should be issued or not. This process offers several challenges to forecasters: 1) how to define critical thresholds along all the rivers under survey? 2) How to link locally defined thresholds to simulated discharges, which result from models with specific spatial and temporal resolutions? 3) How to define the number of ensemble forecasts predicting the exceedance of critical thresholds necessary to launch a warning? This study focuses on this third challenge. We investigate the optimal number of ensemble members exceeding a critical discharge in order to issue a flood warning. The optimal probabilistic threshold is the one that minimizes the number of false alarms and misses, while it optimizes the number of flood events correctly forecasted. Furthermore, in our study, an optimal probabilistic threshold also maximizes flood preparedness: the gain in lead-time compared to a deterministic forecast. Data used to evaluate critical thresholds for ensemble flood forecasting come from a selection of 208 catchments in France, which covers a wide range of the hydroclimatic conditions (including catchment size) encountered in the country. The GRP hydrological forecasting model, a lumped soil-moisture-accounting type rainfall-runoff model, is used. The model is driven by the 10-day ECMWF deterministic and ensemble (51 members) precipitation forecasts for a period of 18 months. A trade-off between the number of hits, misses, false alarms and the gain in lead time is sought to find the optimal number of ensemble members exceeding the critical discharge. These optimal probability thresholds are further explored in order to search for correlations with catchment characteristics, forecast lead-time and discharge thresholds.

Weeink, Werner H. A.; Ramos, Maria-Helena; Booij, Martijn J.; Andréassian, Vazken; Krol, Maarten S.

2010-05-01

25

Public perception of flood risks, flood forecasting and mitigation  

Microsoft Academic Search

A multidisciplinary and integrated approach to the flood mitigation decision making process should provide the best response of society in a flood hazard situation including preparation works and post hazard mitigation. In Slovenia, there is a great lack of data on social aspects and public response to flood mitigation measures and information management. In this paper, two studies of flood

M. Brilly; M. Polic

2005-01-01

26

Towards operational flood forecasting using Data Assimilation  

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

27

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

NASA Astrophysics Data System (ADS)

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

Marcy, D.; Donaldson, T.

2006-12-01

28

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

29

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

30

Satellites as the Panacea to Transboundary Limitations for Longer Term Flood Forecasting?  

Microsoft Academic Search

This article presents a brief overview of the challenges associated with long-term flood forecasting, as experienced by many flood-prone developing nations, due to transboundary limitations. The potential of satellite rainfall data to overcome such limitations is highlighted. The article also discusses the limitations of rainfall estimates from space-borne platforms due to their high degree of uncertainty in measurement. This is

Faisal Hossain

2007-01-01

31

Public perception of flood risks, flood forecasting and mitigation  

NASA Astrophysics Data System (ADS)

A multidisciplinary and integrated approach to the flood mitigation decision making process should provide the best response of society in a flood hazard situation including preparation works and post hazard mitigation. In Slovenia, there is a great lack of data on social aspects and public response to flood mitigation measures and information management. In this paper, two studies of flood perception in the Slovenian town Celje are represented. During its history, Celje was often exposed to floods, the most recent serious floods being in 1990 and in 1998, with a hundred and fifty return period and more than ten year return period, respectively. Two surveys were conducted in 1997 and 2003, with 157 participants from different areas of the town in the first, and 208 in the second study, aiming at finding the general attitude toward the floods. The surveys revealed that floods present a serious threat in the eyes of the inhabitants, and that the perception of threat depends, to a certain degree, on the place of residence. The surveys also highlighted, among the other measures, solidarity and the importance of insurance against floods.

Brilly, M.; Polic, M.

2005-04-01

32

Development of a European flood forecasting system  

Microsoft Academic Search

Recent advances in meteorological forecast skill now enable significantly improved estimates of precipitation quantity, timing and spatial distribution to be made up to 10 days ahead for model scales of 40 km in forecast mode. Here we outline a prototype methodology to downscale these precipitation estimates using regional Numerical Weather Prediction models to spatial scales appropriate to hydrological forecasting and

Ad P. J. de Roo; Ben Gouweleeuw; Jutta Thielen; Jens Bartholmes; Ezio Todini; Paul D. Bates; Matt Horritt; Neil Hunter; Keith Beven; Florian Pappenberger; Erdmann Heise; Gdaly Rivin; Michael Hils; Anthony Hollingsworth; Bo Holst; Jaap Kwadijk; Paolo Reggiani; Marc Van Dijk; Kai Sattler; Eric Sprokkereef

2003-01-01

33

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

34

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

35

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

36

FLOOD FORECAST AND FLOOD MANAGEMENT MODEL OPTIMIZATION OF THE OPERATION OF STORAGE POWER PLANTS FOR FLOOD ROUTING  

Microsoft Academic Search

A new model for flood prediction and management of the Rhone river basin is presented. This 5500 km2 mountainous catchment area contains 10 major hydropower plants with their accumulation reservoirs. Based on a deterministic weather forecast, a new conceptual semi- distributed hydrological model provides a 72 hours lead time discharge forecast for the river network. It also provides the necessary

Frédéric Jordan; Javier Garcia Hernandez; Jean-Louis Boillat; Anton Schleiss

37

Dynamic ANN Modeling for Flood Forecasting in a River Network  

NASA Astrophysics Data System (ADS)

An experiment on predicting flood flows at each of the upstream and a down stream section of a river network is presented using focused Time Lagged Recurrent Neural Network with three different memories like TDNN memory, Gamma memory and Laguarre memory. This paper focuses on application of memory to the input layer of a TLRN in developing flood forecasting models for multiple sections in a river system. The study shows the Gamma memory has better applicability followed by TDNN and Laguarre memory.

Roy, Parthajit; Choudhury, P. S.; Saharia, Manabendra

2010-10-01

38

A first large-scale flood inundation forecasting model  

NASA Astrophysics Data System (ADS)

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

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

2013-10-01

39

An Operational Flood Forecast System for the Indus Valley  

NASA Astrophysics Data System (ADS)

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

Shrestha, K.; Webster, P. J.

2012-12-01

40

Flood Monitoring and Forecasting in the Upper-Tisza River Basin  

NASA Astrophysics Data System (ADS)

The Upper-Tisza river basin is shared by four nations: Ukraine, Romania, Slovakia and Hungary. The river itself is the frontier along several kilometres between Ukraine and Romania and between Ukraine and Hungary. All benefits and all problems a river can cause are also shared by the four nations. The river basin experienced catastrophic floods four times in 28 months between November 1998 and March 2001. Each flood surpassed the previous one in magnitude, reaching heights and causing damages bigger than ever before. At the beginning of March 2001 the highest ever flood occurred in the Transcarpathian region in Ukraine. Flood stages exceeded all previous maximums. Flood protection levees were breached at many sites both in Ukraine and in Hungary, causing enormous economic loss and even demanding human lives. The European Union started flood monitoring projects under the PHARE CBC program in Romania and initial steps were taken under TACIS in Ukraine. The Danish Government together with the Slovakian Government is busy with similar purposes on the northern tributaries. NATO responded by setting up a project with the aim of preparing a comprehensive assessment report on flood problems and proposed measures to improve the efficiency of flood management in Ukraine. The first results of a modular flood forecasting system are reported.

Balint, Z.; Gauzer, B.; Konecsny, K.

2003-04-01

41

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

42

Hydrologic Ensemble Forecasts for Flash Flood Warnings at Ungauged Locations  

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

43

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

44

Flood forecasting with DDD-application of a parsimonious hydrological model in operational flood forecasting in Norway  

NASA Astrophysics Data System (ADS)

A new parameter-parsimonious rainfall-runoff model, DDD (Distance Distribution Dynamics) has been run operationally at the Norwegian Flood Forecasting Service for approximately a year. DDD has been calibrated for, altogether, 104 catchments throughout Norway, and provide runoff forecasts 8 days ahead on a daily temporal resolution driven by precipitation and temperature from the meteorological forecast models AROME (48 hrs) and EC (192 hrs). The current version of DDD differs from the standard model used for flood forecasting in Norway, the HBV model, in its description of the subsurface and runoff dynamics. In DDD, the capacity of the subsurface water reservoir M, is the only parameter to be calibrated whereas the runoff dynamics is completely parameterised from observed characteristics derived from GIS and runoff recession analysis. Water is conveyed through the soils to the river network by waves with celerities determined by the level of saturation in the catchment. The distributions of distances between points in the catchment to the nearest river reach and of the river network give, together with the celerities, distributions of travel times, and, consequently unit hydrographs. DDD has 6 parameters less to calibrate in the runoff module than the HBV model. Experiences using DDD show that especially the timing of flood peaks has improved considerably and in a comparison between DDD and HBV, when assessing timeseries of 64 years for 75 catchments, DDD had a higher hit rate and a lower false alarm rate than HBV. For flood peaks higher than the mean annual flood the median hit rate is 0.45 and 0.41 for the DDD and HBV models respectively. Corresponding number for the false alarm rate is 0.62 and 0.75 For floods over the five year return interval, the median hit rate is 0.29 and 0.28 for the DDD and HBV models, respectively with false alarm rates equal to 0.67 and 0.80. During 2014 the Norwegian flood forecasting service will run DDD operationally at a 3h temporal resolution. Running DDD at a 3h resolution will give a better prediction of flood peaks in small catchments, where the averaging over 24 hrs will lead to a underestimation of high events, and we can better describe the progress floods in larger catchments. Also, at a 3h temporal resolution we make better use of the meteorological forecasts that for long have been provided at a very detailed temporal resolution.

Skaugen, Thomas; Haddeland, Ingjerd

2014-05-01

45

Fuzzy exemplar-based inference system for flood forecasting  

NASA Astrophysics Data System (ADS)

Fuzzy inference systems have been successfully applied in numerous fields since they can effectively model human knowledge and adaptively make decision processes. In this paper we present an innovative fuzzy exemplar-based inference system (FEIS) for flood forecasting. The FEIS is based on a fuzzy inference system, with its clustering ability enhanced through the Exemplar-Aided Constructor of Hyper-rectangles algorithm, which can effectively simulate human intelligence by learning from experience. The FEIS exhibits three important properties: knowledge extraction from numerical data, knowledge (rule) modeling, and fuzzy reasoning processes. The proposed model is employed to predict streamflow 1 hour ahead during flood events in the Lan-Yang River, Taiwan. For the purpose of comparison the back propagation neural network (BPNN) is also performed. The results show that the FEIS model performs better than the BPNN. The FEIS provides a great learning ability, robustness, and high predictive accuracy for flood forecasting.

Chang, Li-Chiu; Chang, Fi-John; Tsai, Ya-Hsin

2005-02-01

46

Flood forecasting based on geographical information system  

Microsoft Academic Search

Floodplain management is a recently new and applied method at the river engineering and is essential for prediction of flood hazards. On the other hand, for the purpose of managing and performing all river training practices, it is necessary to simulate complicated hydraulic behavior of the river in a more simple way. In this research, steady flow was simulated along

Karim Solaimani

2009-01-01

47

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.

48

California climate change, hydrologic response, and flood forecasting  

SciTech Connect

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

Miller, Norman L.

2003-11-11

49

A first large-scale flood inundation forecasting model  

SciTech Connect

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

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

2013-11-04

50

Model Combination and Weighting Methods in Operational Flood Forecasting  

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

51

Importance of Spatial Precipitation for Calibrating a Flood Forecasting System?  

NASA Astrophysics Data System (ADS)

This paper presents the role of regionalized precipitation as input data for hydrological model calibration in a flood forecasting system. Simulation results out of two differently calibrated hydrological models are compared during the flood event from 21 to 25 July 2012 for the Mur watershed in Austria that is about 10000 km² until the border to Slovenia. The original calibration done in 2005 uses regionalized station precipitation. For calibration purpose hourly precipitation values have been calculated for 40 sub-catchments using the simple Thiessen Polygon method from 1995 to 2002. This simple method has the huge advantage to be very fast so that it can be used in operational system like for the Mur watershed. The modified calibration uses precipitation prepared from the Austrian meteorological institute (ZAMG) mixing information from stations, radars and satellites. Since 2009 hourly quasi real time flood forecasting simulations are made using these precipitation data until time of forecast and results from different meteorological models for 8 days ahead. Thus, implicitly it is considered that ZAMG delivers "regionalized measured precipitation" until time of forecast. That's the reason why in May 2010 it was decided to save these data in a special "grid based" database with an hourly precipitation values per cell with a resolution of 1*1 km. These data have been retrieved for the 40 sub-catchments from the Mur flood forecasting system for the new calibration period extending from May 2010 to April 2012. Simulations compared at the gauging stations on the Mur river are much better using the modified parameters. This is true for all stations except the station Zeltweg with a drained area of 2960 km². The reasons for this specific behavior could not be clearly identified until now. Nevertheless it can be clearly demonstrated that the modified calibration gives much better simulation results for the mid-July flood as the original system. This is true even if the modified calibration covers only a two years period compared to the seven years used in the original calibration. This example shows that the simulation quality for the Mur river flood forecasting system depends very much on the precipitation data used during both calibration and operational application. The apparent detriment of a short calibration period seems to be compensated with the benefit of calibrated parameters in "harmony" with spatial precipitation delivered during operational applications. Following the results from the present analysis it can be concluded that apparently the same precipitation type should be used for both modeling phases: calibration and operational application. Such a finding, if applicable to other flood forecasting systems, means (1) that collaboration between meteorologists and hydrologists must be strengthen and (2) that many hydrological models implemented in flood forecasting systems must be re-calibrated.

Ruch, Christophe; Stöffler, Robert; Schatzl, Robert

2013-04-01

52

BASIN SCALE RAINFALL - RUNOFF MODELING FOR FLOOD FORECASTS  

Microsoft Academic Search

Flow estimation at a point in a river is vital for a number of hydrologic applications including flood forecast. This paper presents the results of a basin scale rainfall-runoff modeling on Bagmati basin in Nepal using the hydrologic model HEC-HMS in a GIS environment. The model, in combination with the GIS extension HEC-GeoHMS, was used to convert the precipitation excess

T. P. KAFLE; M. K. HAZARIKA; S. KARKI; R. M. SSHRESTHA; R. SHARMA

53

Design and implementation of a web-based spatial decision support system for flood forecasting and flood risk mapping  

Microsoft Academic Search

The application of flood forecasting model require the efficient management of large spatial and temporal datasets, which involves data acquisition, storage and processing, as well as manipulation, reporting and display results. The complexity of flood forecasting makes it difficult for individual organization to deal effectively with decision-making. Difficulty in linking data, analysis tools and models across organization is one of

Lei Wang; Qiuming Cheng

2007-01-01

54

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

55

Some remarks on the use of digital computers and hydraulic methods for flood routing and flood forecasting problems  

Microsoft Academic Search

The authors present some applications of digital computers in solving flood routing and flood forecasting problems, they have been dealing with in the last few years. To reproduce the phenomenon of a flood wave propagation in an open channel, a mathematical model — based on a finite difference scheme for numerical integration of Saint Venant's equations - have been used

F. Ionescu

56

Real-time Flood Forecasting in China Using TOPKAPI  

NASA Astrophysics Data System (ADS)

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

Todini, E.; Mazzetti, C.

2012-04-01

57

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

58

Using value engineering to optimize flood forecasting and flood warning systems: Golestan and Golabdare watersheds in Iran as case studies  

Microsoft Academic Search

Flood occurrence has always been one of the most important natural phenomena, which is often associated with disaster. Consequently,\\u000a flood forecasting (FF) and flood warning (FW) systems, as the most efficient non-structural measures in reducing flood loss\\u000a and damage, are of prime importance. These systems are low cost and the time required for their implementation is relatively\\u000a short. It is

Babak Omidvar; Hanieh Khodaei

2008-01-01

59

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

60

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

61

24 CFR 570.605 - National Flood Insurance Program.  

Code of Federal Regulations, 2013 CFR

... 2013-04-01 false National Flood Insurance Program. 570.605 Section...Requirements § 570.605 National Flood Insurance Program. Notwithstanding...part 91), section 202(a) of the Flood Disaster Protection Act of...

2013-04-01

62

Enhancing flood forecasting with the help of processed based calibration  

NASA Astrophysics Data System (ADS)

Due to the fact that the required input data are not always completely available and model structures are only a crude description of the underlying natural processes, model parameters need to be calibrated. Calibrated model parameters only reflect a small domain of the natural processes well. This imposes an obstacle on the accuracy of modelling a wide range of flood events, which, in turn is crucial for flood forecasting systems. Together with the rigid model structures of currently available rainfall-runoff models this presents a serious constraint to portraying the highly non-linear transformation of precipitation into runoff. Different model concepts (interflow, direct runoff), or rather the represented processes, such as infiltration, soil water movement etc. are more or less dominating different sections of the runoff spectrum. Most models do not account for such transient characteristics inherent to the hydrograph. In this paper we try to show a way out of the dilemma of limited model parameter validity. Exemplarily, we investigate on the model performance of WaSiM-ETH, focusing on the parameterisation strategy in the context of flood forecasting. In order to compensate for the non-transient parameters of the WaSiM model we propose a process based parameterisation strategy. This starts from a detailed analysis of the considered catchments rainfall-runoff characteristics. Based on a classification of events, WaSiM-ETH is calibrated and validated to describe all the event classes separately. These specific WaSiM-ETH event class models are then merged to improve the model performance in predicting peak flows. This improved catchment modelling can be used to train an artificial intelligence based black box forecasting tool as described in [Schmitz, G.H., Cullmann, J., Görner, W., Lennartz, F., Dröge, W., 2005. PAI-OFF: Eine neue Strategie zur Hochwasservorhersage in schnellreagierenden Einzugsgebieten. Hydrologie und Wasserbewirtschaftung 49, 226-234; Cullmann, J., Schmitz, G.H., Görner, W., 2006. A new strategy for online flood forecasting in mountainous catchments. in: IAHS Red Book, vol. 303]. Merging of the singular parameter class models is done with the help of a sigmoidal weighting procedure. The new approach thus integrates all available information from the specially calibrated WaSiM-ETH class models, accounting for the different processes and dynamics governing the various event classes. For example it portrays the flood formation process with parameters accounting for the characteristics of the event class models. Implications arising from this study are demonstrated for a catchment in the Erzgebirge (Ore-mountains) in East Germany (1700 km). The computational efficiency, together with the convincing agreement between the predicted and observed flood peaks underlines the potential of the new parameterisation strategy in the context of operational real time forecasting.

Cullmann, Johannes; Krauße, Thomas; Philipp, Andy

63

Floods  

MedlinePLUS

... flood insurance coverage. Flood Outreach Toolkit Materials FEMA Publications If you require more information about any of ... architects, engineers, builders, code officials and homeowners. Other Publications National Weather Service Hurricane Flooding: A Deadly Inland ...

64

Typhoon flood forecasting using integrated two-stage Support Vector Machine approach  

NASA Astrophysics Data System (ADS)

SummaryAccurate runoff forecasts are essential for flood mitigation and warning. In this paper, a two-stage flood forecasting model that is based on Support Vector Machine (SVM) is presented. In the first stage, the observed typhoon characteristics and observed rainfall are used to produce rainfall forecast; and in the second stage, the forecasted rainfall and observed runoff are used to produce runoff forecast. A dataset of 16 typhoon storms from Taiwan were used to evaluate the two-stage SVM model. The SVM model generated accurate rainfall and runoff forecasts with a 1-6 h lead time, especially for the peak runoff values. A substantial performance improvement of flood forecast is shown for the 4- to 6-h lead time. In conclusion, the SVM model provides an operational advantage by increasing the forecast lead time during typhoon events.

Lin, Gwo-Fong; Chou, Yang-Ching; Wu, Ming-Chang

2013-04-01

65

Mapping Coastal Flood Zones for the National Flood Insurance Program  

NASA Astrophysics Data System (ADS)

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, guide construction away from flood hazards, and transferring the cost of flood losses from taxpayers to policyholders. Areas subject to flood hazards were defined as those areas that have a probability greater than 1 percent of being inundated in any given year. Currently over 19,000 communities participate in the NFIP, many of them coastal communities subject to flooding from tides, storm surge, waves, or tsunamis. The mapping of coastal hazard areas began in the early 1970's and has been evolving ever since. At first only high tides and storm surge were considered in determining the hazardous areas. Then, after significant wave caused storm damage to structures outside of the mapped hazard areas wave hazards were also considered. For many years FEMA has had Guidelines and Specifications for mapping coastal hazards for the East Coast and the Gulf Coast. In September of 2003 a study was begun to develop similar Guidelines and Specifications for the Pacific Coast. Draft Guidelines and Specifications will be delivered to FEMA by September 30, 2004. During the study tsunamis were identified as a potential source of a 1 percent flood event on the West Coast. To better understand the analytical results, and develop adequate techniques to estimate the magnitude of a tsunami with a 1 percent probability of being equaled or exceeded in any year, a pilot study has begun at Seaside Oregon. Both the onshore velocity and the resulting wave runup are critical functions for FEMA to understand and potentially map. The pilot study is a cooperative venture between NOAA and USGS that is partially funded by both agencies and by FEMA. The results of the pilot study will help FEMA determine when tsunamis should be considered in mapping coastal hazards, how to predict their impact, how they should be mapped and possibly the construction standards for zones mapped as having a 1 percent or greater chance of suffering a tsunami.

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

2004-12-01

66

Real-Time Flood Forecasting System Using Channel Flow Routing Model with Updating by Particle Filter  

Microsoft Academic Search

A real-time flood forecasting system using channel flow routing model was developed for runoff forecasting at water gauged and ungaged points along river channels. The system is based on a flood runoff model composed of upstream part models, tributary part models and downstream part models. The upstream part models and tributary part models are lumped rainfall-runoff models, and the downstream

R. Kudo; H. Chikamori; A. Nagai

2008-01-01

67

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

68

Application of Multi-Model Superensemble technique to flood forecasting through distributed hydrologic models  

NASA Astrophysics Data System (ADS)

Streamflow forecasts are generally produced through the use of a single hydrologic model. In spite of the existence of a wide range of hydrologic models, it is hard to claim that any single model among them performs better than the rest, for all type of watersheds under all conditions. This is because hydrologic models, lumped or distributed, introduce many assumptions and simplifications in their structure. Since various model structures capture different aspects of the watershed processes, one way of exploiting the strength of different models and compensating for their weaknesses is to obtain consensus predictions by combining their results using model combination techniques such as Multi Model SuperEnsmble (MMSE). MMSE is a special case of ensemble techniques, which consider the model outputs as ensemble members. This study surveys the performance of MMSE for flood forecasting by using the simulation results from various distributed models participated in the Distributed Model Intercomparison Project (DMIP), an international project sponsored by National Weather Service. The key questions addressed in this study are: (1) What is the skill level of the consensus forecast compared to those of individual forecasts? (2) How many models do we need to produce accurate consensus forecasts? (3) Can model combination techniques compensate for the inadequacy of model calibration? Simulations for the Illinois River Basin at Watts from 7 uncalibrated DMIP models are combined and the results are compared to the calibrated model results.

Ajami, N. K.; Duan, Q.; Gao, X.; Sorooshian, S.

2004-12-01

69

Ensuring That Structures Built on Fill In or Near Special Flood Hazard Areas Are Reasonably Safe from Flooding in Accordance with the National Flood Insurance Program.  

National Technical Information Service (NTIS)

For the purpose of administering the National Flood Insurance Program (NFIP), FEMA identifies and maps flood hazard areas nationwide by conducting flood hazard studies and publishing Flood Insurance Rate Maps (FIRMs). These flood hazard areas, referred to...

2007-01-01

70

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

71

Semi-distributed flood forecasting system for the Middle Vistula reach  

NASA Astrophysics Data System (ADS)

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

Romanowicz, Renata; Karamuz, Emilia; Osuch, Marzena

2014-05-01

72

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

73

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

74

24 CFR 570.605 - National Flood Insurance Program.  

Code of Federal Regulations, 2010 CFR

...2009-04-01 2009-04-01 false National Flood Insurance Program. 570.605 Section 570.605 Housing...Other Program Requirements § 570.605 National Flood Insurance Program. Notwithstanding the date of...

2009-04-01

75

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

76

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

77

National Weather Service Forecast Reference Evapotranspiration  

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

78

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

79

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

80

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

NASA Astrophysics Data System (ADS)

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

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

2008-10-01

81

Chronology of Major Events Affecting the National Flood Insurance Program.  

National Technical Information Service (NTIS)

In 1968, the U.S. Congress passed the National Flood Insurance Act (Title XII of the Housing and Urban Development Act of 1968 (PL 90-448)), which created the National Flood Insurance Program (NFIP). Floods are the most frequent and costly of all natural ...

2005-01-01

82

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

83

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

84

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

85

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

86

Verification of National Weather Service Hydrologic Forecasts for the Upper Mississippi River Basin for 2006-2008  

NASA Astrophysics Data System (ADS)

The US National Weather Service (NWS) North Central River Forecast Center (NCRFC) produces short- range streamflow forecasts (1-7 days) for locations in the Upper Mississippi River basin. Forecasts are issued for select locations on a daily basis, or in some cases as needed during times of high water. The short-range forecasts are produced using the NWS river forecasting system (NWSRFS) which includes a conceptual hydrologic modeling system run at 6-hour time steps. The model is mainly driven by quantitative precipitation forecasts (QPFs) for the first 24 hours of the forecast window, with no additional precipitation input thereafter. Additional inputs to the modeling system are potential evaporation and temperature (when snow is present). Verification of official NWS hydrologic forecasts has been limited, in part due to a lack of historical archives. As a result, relatively little information is available to the hydrologic community about hydrologic forecast skill. In recent years, the NWS has begun archiving forecasts and developing new verification capabilities, such as the Interactive Verification Program and the Ensemble Verification System for deterministic and ensemble forecasts, repectively. The NWS' plan is to provide comprehensive verification information for routine hydrologic forecast products based on user-selected attributes. This paper will present results from work done by the NWS and Iowa State University to develop the verification capabilities necessary for such services and to evaluate the archived forecasts at the NCRFC. We evaluate NCRFC operational forecasts (forecasts issued after forecaster review), and focus on deterministic forecasts which are currently the most common type of forecasts produced by the NWS. Verification statistics include standard error measurements and categorical scores conditioned on flood levels. Results will include forecasts from the 2008 flood events in the Midwest U.S.

Franz, K. J.; Deweese, M.; Demargne, J.; Bauman, J.

2008-12-01

87

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

88

Measuring the impacts of the national flood insurance program  

Microsoft Academic Search

The National Flood Insurance Program was established in 1968 as a federally administered insurance program to reduce costs to the federal government for flood recovery and allocate recovery costs among potential disaster relief beneficiaries. Participants purchase flood insurance through participating property insurance providers which receive a haircut of the premium for overhead costs and passes the remainder to the Federal

II James P. Howard

2012-01-01

89

Suitability of HEC-RAS for Flood Forecasting  

Microsoft Academic Search

At present, most river fl ood forecasts are conducted using a two-step procedure. First, fl ood routing is conducted, normally using hydrological models. The resulting fl ood peaks are then converted to water level forecasts using a steady fl ow hydraulic model, such as HEC-RAS. Recently, the HEC- RAS model has been extended to facilitate unsteady fl ow analyses, and

F. E. Hicks; T. Peacock

2005-01-01

90

Typhoon event-based evolutionary fuzzy inference model for flood stage forecasting  

NASA Astrophysics Data System (ADS)

This study proposes an evolutionary fuzzy inference model that combines a fuzzy inference model, genetic programming (GP), and a genetic algorithm (GA) to forecast flood stages during typhoons. The number of fuzzy inference rules in the proposed approach is based on the number of typhoon flood events. The consequent part of the rule was formed by constructing GP models that depict the rainfall-stage relationship of a specific flood event, whereas the GA was used to search the parameters of the fuzzy membership functions in the premise part of the rule. This study uses the proposed event-based evolutionary fuzzy inference model to forecast the typhoon flood stages of Wu River in Taiwan. Forecasting results based on stage hydrographs and performance indices verify the forecasting ability of the proposed model. This study also identifies the weights of triggered fuzzy rules during the fuzzy inference process, showing that a fuzzy rule is triggered according to the characteristics of the flood event that forms the rule. Moreover, physical explanation of the proposed evolutionary fuzzy inference model was discussed.

Chen, Chang-Shian; Jhong, You-Da; Wu, Ting-Ying; Chen, Shien-Tsung

2013-05-01

91

A channel dynamics model for real-time flood forecasting  

USGS Publications Warehouse

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

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

1989-01-01

92

Clustering-based hybrid inundation model for forecasting flood inundation depths  

NASA Astrophysics Data System (ADS)

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

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

2010-05-01

93

Global scale water stages from space imagery to support global flood forecasting  

NASA Astrophysics Data System (ADS)

Despite the success of studies attempting to integrate remotely sensed data and flood modelling and the need to provide near-real time data routinely on a global scale as well as setting up online data archives, there is to date a lack of spatially and temporally distributed hydraulic parameters to support ongoing efforts in modelling. Therefore, the objective of this project is to provide a global evaluation and benchmark data set of floodplain water stages with uncertainties and assimilation in a large scale flood model using space-borne radar imagery. An algorithm is developed for automated retrieval of water stages with uncertainties from a sequence of radar imagery and data are assimilated in a flood model using the Tewkesbury 2007 flood event as a feasibility study. The application is then extended to a global scale using wide swath radar imagery and a simple global flood forecasting model thereby providing improved river discharge estimates to update the latter.

Schumann, Guy J.-P.; Pappenberger, Florian; Mason, David

2010-05-01

94

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

NASA Astrophysics Data System (ADS)

Recognizing that the frequency distribution of annual maximum floods at a given location may change over time in response to interannual and longer climate fluctuations, we compare two approaches for the estimation of flood quantiles conditional on selected "climate indices" that carry the signal of structured low-frequency climate variation, and influence the atmospheric mechanisms that modify local precipitation and flood potential. A parametric quantile regression approach and a semiparametric local likelihood approach are compared using synthetic data sets and for data from a streamflow gauging station in the western United States. Their relative utility in different settings for seasonal flood risk forecasting as well as for the assessment of long-term variation in flood potential is discussed.

Sankarasubramanian, A.; Lall, Upmanu

2003-05-01

95

THE GREAT NILE FLOODS OF 1998 AND 1999 ; SUCESSFUL FORECASTS USING SOLAR TERRESTRIAL RELATIONS AND REAL DATA  

Microsoft Academic Search

In 1995,in a paper on long range forecasting of Nile floods , the first author stressed the possibility of successive high floods and called upon the Egyptian authorities to be ready with the Tushka canal. Indeed , the 1996 was the first high flood in the series and there was a spillage for the first time in the Tushka canal.

Shahinaz Yousef; Hassan Osman

96

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

97

STATISTICAL APPROACH TO DISCHARGE PREDICTION FOR FLOOD FORECASTS USING TRMM DATA  

Microsoft Academic Search

Although real time rainfall data covering whole basin of a river form the basis for any flood forecasting, but they are not easily available in many developing countries. For trans-boundary rivers like Mekong, with large catchment area covering several countries, the real time data acquisition would be even more complex. Further, data from sparse gauging stations are usually inadequate to

M. K. Hazarika; T. P. Kafle; R. Sharma; S. Karki; R. M. Shrestha; L. Samarkoon

98

Multi-Season Ahead, Multivariate Flood Forecasts For The Western United States  

NASA Astrophysics Data System (ADS)

Annual maximum floods at many sites in the Western United States are "correlated" with a variety of indicators of low frequency climate variability. These correlations have well defined spatial and temporal structure. Atmospheric pathways of moisture transport from the tropical and extratropical Pacific and Atlantic Oceans that are the carriers of these signals can be identified from NCEP re-analysis products. Here, we use Projection Pursuit Regression, a multivariate, nonparametric (nonlinear) regression methodology to forecast annual floods (annual n-day maximum) at 137 benchmark gauging sites in the Western United States using historical January-April Sea Surface Temperature data. The model is fit on the 1939-2000 data common to all stations, and tested using k-fold cross validation. The cross validated residuals are used to develop empirical confidence limits for new forecasts. The fitted model is then applied to make retrospective forecasts at all stations for the 1900-1938 period. These forecasts are compared with observed floods at sites which had data prior to 1939. Prospects for the use of such forecasts for spatial risk hedging strategies are briefly indicated.

Pizarro, G.; Lall, U.; Rajagopalan, B.

2002-12-01

99

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

100

Sources of uncertainty and probability bands for flood forecasts: an upland catchment case study  

NASA Astrophysics Data System (ADS)

The sources of uncertainty associated with a flood forecast for an upland catchment are first examined in a pragmatic way. Forecasts are obtained operationally using a lumped rainfall-runoff model with catchment-average rainfall estimates as the primary input. One source of uncertainty is associated with the method used to estimate catchment-average rainfall from observations from a raingauge network. Different methods are used to quantify the spread of estimates arising from choice of method. Uncertainty in the raingauge values themselves is explored using a simple random observation model in a Monte Carlo framework. Ensembles of rainfall forecasts from STEPS are used to quantify the effect of rainfall forecast uncertainty on the spread of possible flood forecasts. Uncertainty arising from model parameter estimation is assessed by comparing the forecasts obtained by models calibrated by two different model development teams. Uncertainty in the river flow observations themselves is quantified through the spread of values given by two stage-discharge relationships developed for operational use, one employing current meter readings and the other ultrasonic flow measurements. Following these exploratory studies on the sources of uncertainty, two direct methods for estimating probability bands on flood forecasts are investigated. The first method employs a standard parametric ARMA approach for calculating probability uncertainty bands on a forecast, which itself is constructed from the sum of a rainfall-runoff model simulation and a prediction of its error. A proportional error model is invoked to address the normality assumptions of the approach. The method is compared with the use of quantile regression as an estimator of probability bands and found to give similar performance. Both methods are implemented assuming perfect foreknowledge of rainfall observations. The parametric ARMA approach is then applied using ensemble rainfall forecasts from STEPS as input to the rainfall-runoff model for future times, emulating the real-time forecasting situation. The probability bands of model uncertainty for ensemble forecast percentiles are calculated. This allows model uncertainty and rainfall forecast uncertainty to be jointly assessed.

Moore, R. J.; Robson, A. J.; Cole, S. J.; Howard, P. J.; Weerts, A. H.; Sene, K.

2010-05-01

101

Flood Forecasting and Flood Warning in the Firth of Clyde, UK  

Microsoft Academic Search

Coastal flooding has caused significant damage to a number of communities around the Firth of Clyde in south-west Scotland, UK. The Firth of Clyde is an enclosed embayment affected by storm surge generated in the Northern Atlantic and propagated through the Irish Channel. In recent years, the worst flooding occurred on 5th January 1991 with the estimated damage of approximately

Yusuf Kaya; Michael Stewart; Marc Becker

2005-01-01

102

River flood forecasting with a neural network model  

Microsoft Academic Search

A neural network model was developed to analyze and forecast the behavior of the river Tagliamento, in Italy, during heavy rain periods. The model makes use of distributed rainfall information coming from several rain gauges in the mountain district and predicts the water level of the river at the section closing the mountain district. The water level at the closing

Marina Campolo; Paolo Andreussi; Alfredo Soldati

1999-01-01

103

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

Microsoft Academic Search

An artificial Neural Network (NN) was successfully applied, in an earlier study, as a prediction tool to forecast water level at Dhaka (Bangladesh), for up to seven lead days in advance, with a high accuracy level. In addition, this high accuracy degree was accompanied with a very short computational time. Both make NN a desirable advance warming forecasting tool. In

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

2000-01-01

104

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

NASA Astrophysics Data System (ADS)

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

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

2010-09-01

105

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

NASA Astrophysics Data System (ADS)

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

Mohammad, Munira; Bárdossy, András.

2010-05-01

106

Adaptive calibration of a conceptual model for flash flood forecasting  

NASA Astrophysics Data System (ADS)

The adaptive use of a conceptual model for real-time flow forecasting is investigated. Maximum likelihood and ordinary least squares estimation criteria are considered, and the performance of maximum likelihood techniques for autocorrelated (AMLE) and heteroscedastic (HMLE) errors is analyzed jointly with that provided by the commonly used ordinary least squares estimation (OLSE) technique. Streamflow forecasts are compared for three rivers in central Italy, obtained by AMLE, HMLE, and OLSE adaptive calibration of a simple conceptual model describing the rainfall-runoff transformation by accounting for Hortonian infiltration and linear basin response to rainfall excess. Although model residuals display both autocorrelation and heteroscedasticity, OLSE is found to provide a rather satisfactory performance. Because the OLSE technique also requires less computational effort compared to that for AMLE and HMLE, one could consider OLSE as a suitable option for real-time model operation.

Brath, Armando; Rosso, Renzo

1993-08-01

107

Real-Time Flood Forecasting on the Blue Nile River  

Microsoft Academic Search

The SMAR-AR Model is used for real-time riverflow forecasting on the Blue Nile catchment at Eldeim Station, which is located near the Sudanese-Ethiopian border. The SMAR-AR model is calibrated using data for the period 1992–1994 and verified by the data for the year 1995. The results of the SMAR-AR model are compared with those of the SAMFIL model that is

Asaad Y. Shamseldin; Gamal M. Abdo; Abderhman S. Elzein

1999-01-01

108

FLOOD RISK - OPTIMIZING A NATIONAL PROGRAM  

Microsoft Academic Search

Floods are a major natural hazard substantially impacting the developed and developing world. Recent floods have caused near-record natural hazards losses in regions as disparate as Mozambique, and central and eastern Europe. A comprehensive detailed analysis was performed for a Study Region in eastern Europe, with the goal of identifying an economically efficient insurance program appropriate for that region. A

Charles Scawthorn

109

Revisiting the National Flood Insurance Program  

Microsoft Academic Search

As the floodwaters caused by Hurricane Fran receded last month, a television ad appeared on stations across the country: A couple stares in dismay at the devastated interior of their home while the narrator explains that most homeowner insurance policies do not cover flood damage, but that cover-age for flood hazards is available through the federal government. The ad refers

Alan C. Weinstein

1996-01-01

110

Flooding and Flood Risks  

MedlinePLUS

... Floodsmart.gov The official site of the National Flood Insurance Program Call toll free: 1-888-379- ... Flood Facts Media Resources Toolkits Email Updates Flooding & Flood Risks What is a Flood? Anywhere it rains, ...

111

Semi-empirical mixed statistical flood forecasting for the Mekong River  

NASA Astrophysics Data System (ADS)

An ongoing study for improving flood forecasting for the Mekong River by data based modeling by mix of statistical methods and semi-empirical approach has yielded intermediate results, which reduced forecasting errors of previous forecasting models. In contrast to deterministic or semi-deterministic approach, the procedure is adopted to build the physical reality based semi-empirical model from the available data set. The forecast in data scarce basin like Mekong always remained a challenge for hydrologists where with the River of total length of 4000 km and 795000 Sq.km area of catchment has only 32 rainfall gauging stations and 8 runoff gauges in its key contributing catchments with consistent data. Therefore, simple rainfall runoff modeling module is developed for the estimation of inflows contributed by lateral catchments along the River Mekong and added into pre-developed runoff routing algorithm. The simple 3 parameter Nash-cascade model is applied in non-linear mode with varying runoff coefficients (RC). These runoff coefficients were pre-computed by multiple linear auto-regressions algorithms. It has been found that runoff coefficients increase along the flood season from its onset in May to end in October. However this increase was found highly dependent on previous month's RC values. This RC dependency on previous months is exploited to develop multiple linear regressions for estimation of forthcoming month RC's. These pre-computed monthly RC's were used in Nash-cascade to estimate runoff temporal distribution from daily areal average incremental rainfall for each sub-catchment. The algorithm was developed to give flood forecast at 4 points in middle Mekong River starting from N.Phanom in Lao-PDR to Stung Treng in Cambodia. There are a total of 4 sub-catchments which contribute runoff into the main Mekong River from its travel along these points. Separate rainfall-runoff Nash-cascade models were developed and added into routing algorithm to compute 1 to 5 day flood forecast at these 4 points. The results of this approach show that that the Nash - Sutcliffe criterion for the forecast is better than 90% in most cases. A more appropriate efficiency criterion named as persistence Index similar in structure to the NS criterion (Berthet et al., 2009; Kitanidis and Bras, 1980a; Kitanidis and Bras, 1980b): the variant of which is also used by Plate (Plate & Lindenmaier, 2008) is utilized to assess the quality of forecast which ranges from 0,5 to 0,75. This criterion based on implication that the deviation of the future observed from the present value should be large relative to the deviation of the observed value from the forecasted value. References: Kitanidis PK, Bras RL. 1980a. Real-Time Forecasting With A Conceptual Hydrologic Model.1. Analysis Of Uncertainty. Water Resources Research 16: 1025-1033. Kitanidis PK, Bras RL. 1980b. Real-Time Forecasting With A Conceptual Hydrologic Model.2. Applications And Results. Water Resources Research 16: 1034-1044. Plate, E.J. and Lindenmaier, F. (2008) " Quality assessments of forecast", 6th Annual Mekong Flood Forum,Phnom Penh, Cambodia 27-28 May

Khurram Shahzad, Muhammad; Ihringer, Jürgen; Plate, Erich J.

2010-05-01

112

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

PubMed

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

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

2012-01-01

113

Added value of online satellite data transmission for flood forecasting: warning systems in medium-size catchments.  

PubMed

The present paper deals with the implementation of online data transferred via LEO satellite communication in a flood forecasting system. Although the project is ongoing, it is already recognised that the information chain: "measurement-transmission-forecast-alert" can be shortened, i.e., the flood danger can be more rapidly communicated to the population at risk. This gain is particularly valuable for medium size catchments where the concentration time (basin time of response to rainfall) is short. PMID:19151482

Ruch, C; Stadler, H

2009-01-01

114

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

115

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

116

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

117

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

118

Flooding in Virginia  

NSDL National Science Digital Library

In this activity, students use a National Weather Service flood forecast, USGS gauging data, and other reports to estimate the maximum storm discharge from the New River and Wolf Creek, two streams in the Southeast U.S. which experienced flooding in November 2003. Topographic and urban maps are used to predict where flooding would occur and to evaluate strategies for reducing flood risk for the residents of the region.

Patrick, Ew

119

Adaptive space-time sampling with wireless sensor nodes for flood forecasting  

NASA Astrophysics Data System (ADS)

SummaryThis paper investigates a method for the real-time design and execution of a space-time sampling strategy in the context of flood forecasting. Measurements of water level taken by a network of wireless sensors were assimilated into a one-dimensional hydrodynamic model using an ensemble Kalman filter, to create a forecasting model. This research focused on methods for targeting measurements in real-time to be assimilated by the forecasting model, such that the power-limited but flexible sensor network could be used optimally. Two targeting methods were developed. The first targeted measurements systematically over space and time until the forecasting model predicted that the probability of the water level exceeding a pre-defined threshold was less than 5%. The second method targeted measurements based on the expected decrease in forecasted water level error variance at a validation time and location, quickly calculated for various sets of measurements by an ensemble transform Kalman filter. Targeting measurements based on the decrease in forecast error variance was shown to be more efficient than a systematic sampling method.

Neal, Jeffrey C.; Atkinson, Peter M.; Hutton, Craig W.

2012-01-01

120

Technical Note: The normal quantile transformation and its application in a flood forecasting system  

NASA Astrophysics Data System (ADS)

The Normal Quantile Transform (NQT) has been used in many hydrological and meteorological applications in order to make the Cumulated Distribution Function (CDF) of the observed, simulated and forecast river discharge, water level or precipitation data Gaussian. It is also the heart of the meta-Gaussian model for assessing the total predictive uncertainty of the Hydrological Uncertainty Processor (HUP) developed by Krzysztofowicz. In the field of geo-statistics this transformation is better known as the Normal-Score Transform. In this paper some possible problems caused by small sample sizes when applying the NQT in flood forecasting systems will be discussed and a novel way to solve the problem will be outlined by combining extreme value analysis and non-parametric regression methods. The method will be illustrated by examples of hydrological stream-flow forecasts.

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

2012-04-01

121

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.

122

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

NASA Astrophysics Data System (ADS)

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

Grossi, G.; Balistrocchi, M.

2009-04-01

123

Real-Time Flood Forecasting System Using Channel Flow Routing Model with Updating by Particle Filter  

NASA Astrophysics Data System (ADS)

A real-time flood forecasting system using channel flow routing model was developed for runoff forecasting at water gauged and ungaged points along river channels. The system is based on a flood runoff model composed of upstream part models, tributary part models and downstream part models. The upstream part models and tributary part models are lumped rainfall-runoff models, and the downstream part models consist of a lumped rainfall-runoff model for hillslopes adjacent to a river channel and a kinematic flow routing model for a river channel. The flow forecast of this model is updated by Particle filtering of the downstream part model as well as by the extended Kalman filtering of the upstream part model and the tributary part models. The Particle filtering is a simple and powerful updating algorithm for non-linear and non-gaussian system, so that it can be easily applied to the downstream part model without complicated linearization. The presented flood runoff model has an advantage in simlecity of updating procedure to the grid-based distributed models, which is because of less number of state variables. This system was applied to the Gono-kawa River Basin in Japan, and flood forecasting accuracy of the system with both Particle filtering and extended Kalman filtering and that of the system with only extended Kalman filtering were compared. In this study, water gauging stations in the objective basin were divided into two types of stations, that is, reference stations and verification stations. Reference stations ware regarded as ordinary water gauging stations and observed data at these stations are used for calibration and updating of the model. Verification stations ware considered as ungaged or arbitrary points and observed data at these stations are used not for calibration nor updating but for only evaluation of forecasting accuracy. The result confirms that Particle filtering of the downstream part model improves forecasting accuracy of runoff at verification stations as well as at reference stations, although observed data at verification stations were not used for updating of the model.

Kudo, R.; Chikamori, H.; Nagai, A.

2008-12-01

124

Real-time forecast of the 2005 and 2007 summer severe floods in the Huaihe River Basin of China  

NASA Astrophysics Data System (ADS)

SummaryWe have developed a one-way coupled hydro-meteorological modeling system consisting of the mesoscale atmospheric model MC2 (Canadian Mesoscale Compressible Community), the Chinese Xinanjiang hydrological model for runoff generation, a flow routing model, and a module for acquiring real-time gauge precipitation. The system had been successfully tested in a hindcast mode using a total of 18 meteorological cases from 1998 and 2003 in the Huaihe River Basin (HRB; 270,000 km 2) of China, and has been used to generate daily precipitation and flood forecasts in real-time for the 2005, 2006 and 2007 flooding season over the Wangjiaba sub-basin (30,500 km 2), part of the HRB. We run MC2 daily to produce a 96-h precipitation forecast, and then use the combined gauge-model precipitation to drive the hydrological model off-line to forecast the hydrograph at the Wangjiaba Station that is at the outlet of the Wangjiaba sub-basin. We examine the daily forecasts for the two most severe flood events encountered in the past three flooding seasons. The two events occurred in July 4-15, 2005 and June 30-July 25, 2007, which necessitated the use of several flood spillway and flood detention areas along the mainstream of the Huaihe River. A total of 19 daily 96-h precipitation forecasts from the two events are examined. The 19 daily forecasts with different lead times compare reasonably well with observations, although the skill as measured by the MC2 relative error and the MC2 forecast success rate is uneven over a 4-day forecast period. MC2 can better forecast the 96-h accumulation compared to 24-h amounts. We also analyze 10 daily hydrograph forecasts from the two events. The flood peak of the two events at the Wangjiaba Station is predicted well in both timing and intensity with a lead time beyond four days, although the quality of our daily hydrograph forecasts as measured by the relative percentage error of the forecast peak discharge and the Nash-Sutcliffe coefficient is not uniform over different forecast days. It is clear that the skill of the MC2 precipitation has the largest effect on the predicted hydrographs, and the accuracy of daily hydrograph forecasts can be improved substantially using the up-to-date gauge precipitation to complement the MC2 precipitation for driving the hydrological model in real-time flood forecast. Our results demonstrate the applicability and the value of using mesoscale model precipitation for real-time flood forecast over the Wangjiaba sub-basin, which can provide a long lead time of heavy precipitation and subsequent flooding for authorities in operational flood management decision making. The results also illustrate the potential of applying the coupled hydro-meteorological modeling system for real-time flood forecast over other regions.

Lin, Charles A.; Wen, Lei; Lu, Guihua; Wu, Zhiyong; Zhang, Jianyun; Yang, Yang; Zhu, Yufei; Tong, Linying

2010-02-01

125

Development of Hydrological Model of Klang River Valley for flood forecasting  

NASA Astrophysics Data System (ADS)

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

Mohammad, M.; Andras, B.

2012-12-01

126

Real-time flood forecast and flood alert map over the Huaihe River Basin in China using a coupled hydro-meteorological modeling system  

Microsoft Academic Search

A coupled hydro-meteorological modeling system is established for real-time flood forecast and flood alert over the Huaihe\\u000a River Basin in China. The system consists of the mesoscale atmospheric model MC2 (Canadian Mesoscale Compressible Community)\\u000a that is one-way coupled to the Chinese Xinanjiang distributed hydrological model, a grid-based flow routing model, and a module\\u000a for acquiring real-time gauge precipitation. The system

GuiHua Lu; ZhiYong Wu; Lei Wen; Charles A. Lin; JianYun Zhang; Yang Yang

2008-01-01

127

Catastrophe Economics: The National Flood Insurance Program  

Microsoft Academic Search

Hurricane Betsy, which hit Louisiana September 9, 1965, was one of the most intense, deadly, and costly storms ever to make landfall in the United States: it killed 76 people in Louisiana and caused $1.5 billion in damage—equal to nearly $10 billion in 2010 dollars. In 1965, no flood insurance was available, so victims had to rely on friends and

Erwann O. Michel-Kerjan

2010-01-01

128

Redistributional Effects of the National Flood Insurance Program  

Microsoft Academic Search

This study examines the redistributional effects of the National Flood Insurance Program (NFIP) using a national database of premium, coverage, and claim payments at the county level between 1980 and 2006. Measuring progressivity as the departure from per capita county income proportionality we find that NFIP premiums are weakly regressive on an annual basis but become proportional as the time

Okmyung Bin; John A. Bishop; Carolyn Kousky

2011-01-01

129

Redistributional Effects of the National Flood Insurance Program  

Microsoft Academic Search

This study examines the redistributional effects of the National Flood Insurance Program (NFIP) using a national database of premium, coverage, and claim payments at the county level between 1980 and 2006. Measuring progressivity as the departure from per capita county income proportionality, the authors find that NFIP premiums are typically proportional if the time horizon is extended beyond a single

Okmyung Bin; John A. Bishop; Carolyn Kousky

2012-01-01

130

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

NASA Astrophysics Data System (ADS)

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

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

2000-02-01

131

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

Federal Register 2010, 2011, 2012, 2013

...3067-AD02) National Flood Insurance Program...Insurance Coverage and Rates AGENCY: Federal...governments would adopt and enforce flood mitigation standards...full-risk premiums for flood insurance coverage...from private parties and interest...

2012-05-30

132

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

Federal Register 2010, 2011, 2012, 2013

...Comment Request, National Flood Insurance Program Call Center and Agent Referral Enrollment...opportunity to purchase flood insurance and access to more adequate...to be educated about flood insurance coverage and to assist them in...

2012-04-18

133

Development and Environmental Impact of the National Flood Insurance Program: A Summary Research Report.  

National Technical Information Service (NTIS)

The National Flood Insurance Program (NFIP), administered by the Federal Emergency Management Agency (FEMA) is meant to provide individuals with insurance against flood loss, diminish future flood loss through federal, state and local government mitigatio...

G. Boulware W. A. Rosenbaum

2006-01-01

134

Quality Assessment Report National Convective Weather Forecast 2 (NCWF-2).  

National Technical Information Service (NTIS)

This report summarizes a statistical evaluation of the quality of the National Convective Weather Forecast (NCWF-2) product, developed by the Convective Weather Product Development Team under the Federal Aviation Administrations (FAA) Aviation Weather Res...

S. A. Seseske M. P. Kay S. Madine J. E. Hart J. L. Mahoney

2006-01-01

135

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

NASA Astrophysics Data System (ADS)

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

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

2011-10-01

136

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

NASA Astrophysics Data System (ADS)

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

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

2003-04-01

137

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

138

Examination of Financial Statements of the National Flood Insurance Program as of December 31, 1977.  

National Technical Information Service (NTIS)

The report provides a brief legislative history of the National Flood Insurance Program. An assessment of the financial statements for the National Flood Insurers Association which adminsters the program is presented.

1979-01-01

139

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

Federal Register 2010, 2011, 2012, 2013

...Emergency Management Agency [Docket ID FEMA-2011-0020] National Flood Insurance Program (NFIP); Assistance...Mitigation Administrator, Insurance National Flood Insurance Program, Federal Emergency Management Agency, Department of...

2011-07-28

140

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

Federal Register 2010, 2011, 2012, 2013

...Management Agency [Docket ID FEMA-2012-0012] National Flood Insurance Program Programmatic Environmental Impact Statement...circumstances caused by the passage of a 5- year National Flood Insurance Program reauthorization (See Biggert- Waters...

2012-08-22

141

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

NASA Astrophysics Data System (ADS)

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

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

2009-09-01

142

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

Code of Federal Regulations, 2013 CFR

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

2013-10-01

143

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

Code of Federal Regulations, 2010 CFR

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

2010-10-01

144

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

Code of Federal Regulations, 2010 CFR

...2009-10-01 false National Flood Insurance Program B Appendix B to Part...AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND...Appendix B to Part 62âNational Flood Insurance Program A Plan to...

2009-10-01

145

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

146

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

NASA Astrophysics Data System (ADS)

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

Grossi, G.

2009-04-01

147

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

Federal Register 2010, 2011, 2012, 2013

...National Flood Insurance Program Claim Forms AGENCY: Federal Emergency...Emergency Management Agency (FEMA) provides flood insurance at full actuarial...agent, adjuster, insurance company, or any...Emergency Management Agency (FEMA)...

2013-07-30

148

National Flood Insurance Program's Mandatory Purchase Requirement: Policies, Processes, and Stakeholders.  

National Technical Information Service (NTIS)

Through the National Flood Insurance Program (NFIP), which was created in 1968 and which the Federal Emergency Management Agency (FEMA) administers, the federal government seeks to reduce the risk, loss, and expense associated with flooding. The program o...

C. Calfee R. J. Tobin

2005-01-01

149

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

NASA Astrophysics Data System (ADS)

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

Weissling, B. P.; Xie, H.

2006-12-01

150

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

EIA Publications

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

Information Center

2010-06-01

151

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

Federal Register 2010, 2011, 2012, 2013

...companies enter into agreements with FEMA to sell and service flood insurance policies and adjust claims after flood losses. The policy...excluded. List of Subjects in 44 CFR Part 61 Flood insurance, Reporting and recordkeeping requirements. For the...

2010-09-03

152

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

Federal Register 2010, 2011, 2012, 2013

...companies enter into agreements with FEMA to sell and service flood insurance policies and adjust claims after flood losses. The policy...enterprises. List of Subjects in 44 CFR Part 61 Flood insurance, Reporting and recordkeeping requirements. For the...

2011-02-10

153

Flooding  

MedlinePLUS

... con monóxido de carbono. Limit contact with flood water. Flood water may have high levels of raw ... from Centers for Disease Control Alert: Boil Drinking Water If your water may not be safe, bring ...

154

Floods  

MedlinePLUS

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

155

Concern about forecasts of national faculty shortages and the importance of local studies  

Microsoft Academic Search

The higher education popular press has published several forecasts of faculty shortages due to the mass retirement of expansion era faculty and the forecasted low numbers of doctoral graduates. These forecasts of national shortages encouraged a local study of faculty attrition in a four-campus university system. The local study considered two factors not accounted for in national studies but important

Steve Chatman; Loren Jung

1992-01-01

156

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

157

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

National Technical Information Service (NTIS)

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 d...

D. L. Ward R. L. Skaggs S. A. Breithaupt S. R. Waichler T. Kim

2010-01-01

158

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

159

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

Federal Register 2010, 2011, 2012, 2013

...National Flood Insurance Program for Non-Primary Residences AGENCY: Federal Emergency...National Flood Insurance Program for non-primary residences. DATES: The rates announced...residential property which is not the primary residence of an individual. These...

2013-03-05

160

Sensitivity of precipitation forecasts to convective parameterization in the October 2007 Flash Flood in the Valencia Region (Eastern Spain)  

NASA Astrophysics Data System (ADS)

The Valencia region, on the Mediterranean coast of the Iberian Peninsula, is an area prone to torrential rains, especially the north of Alicante province and the south of Valencia province. In October 2007, a torrential rain event with accumulated rainfall values exceeding 400 mm in less than 24 h affected the aforementioned areas, producing flash floods that caused extensive economic losses and human casualties. Several simulations of this rain event have been performed with the Regional Atmospheric Modeling System (RAMS) to test the influence of the different convective parameterization scheme implemented in the model on the precipitation forecast.

Gómez, I.; Pastor, F.; Estrela, M.

2010-06-01

161

The 16 May 2005 Flood in Yosemite National ParkA Glimpse into High-Country Flood Generation in the Sierra Nevada  

Microsoft Academic Search

On 16 May 2005, a Pacific storm drew warm, wet subtropical air into the Sierra Nevada, causing moderate rains and major flooding. The flood raised Hetch Hetchy and Tenaya Lake levels markedly and inundated large parts of Yosemite Valley, requiring evacuations and raising public-safety concerns in Yosemite National Park. This was the first major flood to be recorded by the

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

2006-01-01

162

OVERVIEW OF US NATIONAL FLOOD INSURANCE PROGRAM REGIONAL  

Microsoft Academic Search

Flood protection is a complexity of technical and economical measures which communities, towns or regions implement in order\\u000a to defend valuable properties from inundation. For many historic reasons and partially as a reaction to society’s demand,\\u000a the protection was established by building dams, levees, pumping stations, dredging, flood plain filling, river training etc.\\u000a The rapid flood plain development and in

163

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

164

Sensitivity of precipitation forecasts to cumulus parameterizations of the October 2007 Flash Flood in the Valencia Region (Eastern Spain).  

NASA Astrophysics Data System (ADS)

A torrential rain event took place on 11-12 of October 2007 in the Valencia region. The general framework of the synoptic situation is a general advection of easterly winds across the Western Mediterranean and the presence of an upper level isolated low over the East of the Iberian Peninsula. Precipitations affected the whole Valencia Region but with special impact on coastal areas to the center-south of the region, mainly focused on the first half of the 12th of October. In this rain event, some stations recorded more than 400 mm in 24 hours. The aim of this work is to analyse the effect of using different cumulus parameterizations in the precipitation forecasts of this flash flood event. To do this, a series of numerical simulations using the Regional Atmospheric Modeling System (RAMS) model have been performed. The evaluation of the model results is being made in terms of the amount of precipitation forecasted as well as spatial distribution and occurrence of the rainfall. Besides, it is also analysed the ability of the RAMS model in simulating the most important features of this flash flood event within the framework of this different cumulus parameterizations.

Gómez, I.; Pastor, F.; Estrela, M.

2009-09-01

165

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

166

Flood Facts  

MedlinePLUS

... Floodsmart.gov The official site of the National Flood Insurance Program Call toll free: 1-888-379- ... Flood Facts Media Resources Toolkits Email Updates Resources - Flood Facts In the past 5 years, all 50 ...

167

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

168

A sampling-based Bayesian model for calibration of a distributed flood forecasting model with input uncertainty  

NASA Astrophysics Data System (ADS)

In this study we develop a sampling-based Bayesian model for calibrating the Geomorphology-Based Hydrological Model (GBHM), which is a physically-based distributed flood forecasting model. We tested the model using both synthetic and field datasets, the latter of which were collected from seven rainfall gauges and one discharge gauge during 32 floods in the Chuzhou catchment in Jiangxi Province of China. Unlike traditional (deterministic) calibration methods, the Bayesian method explicitly takes into account uncertainty in model parameters, input, and data, as well as uncertainty in the forward model, and gives a posterior marginal distribution of each parameter. We develop the likelihood function based on the normal distribution assumption of simulation errors within flood periods. We consider that correlation between the simulation errors is induced by modeling and observation uncertainty. We estimate the correlation by introducing a new parameter in this study, called the omega ratio, which quantifies the effects of modeling uncertainty on the simulation errors. For Markov chain Monte Carlo (MCMC) sampling, we separately use Metropolis-Hasting sampling, Gibbs sampling and slice sampling methods for different variables. Application of the Bayesian method to synthetic studies show that consideration of input uncertainty leads to reasonable estimation of parameter uncertainty, even when rainfall inputs are biased. Application to field data also highlights the ability of the Bayesian method to quantify the means and variances of GBHM parameters and estimates of input uncertainties. The results indicate that correlation within the simulation errors is significant for identifying uncertainties.

Li, M.; Yang, D.; Chen, J.; Hubbard, S. S.

2009-12-01

169

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

Federal Register 2010, 2011, 2012, 2013

...Emergency Management Agency [Docket ID FEMA-2013-0031...National Flood Insurance Program (NFIP...Emergency Management Agency, Federal Insurance Administration...Administrator, Federal Insurance and Mitigation...Emergency Management Agency, Department...

2013-08-26

170

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

Federal Register 2010, 2011, 2012, 2013

...Emergency Management Agency [Docket ID FEMA-2012-0018...National Flood Insurance Program (NFIP...Emergency Management Agency, Federal Insurance Administration...Administrator, Federal Insurance and Mitigation...Emergency Management Agency, Department...

2012-06-19

171

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

Federal Register 2010, 2011, 2012, 2013

...Federal Emergency Management Agency [Docket ID: FEMA-2011-0034...OMB No. 1660-0086] Agency Information Collection Activities...Request; National Flood Insurance Program--Mortgage Portfolio Protection Program AGENCY: Federal Emergency...

2011-11-15

172

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

Federal Register 2010, 2011, 2012, 2013

...National Flood Insurance Program Claims Appeals Process AGENCY: Federal Emergency...Emergency Management Agency (Mitigation Directorate/Risk Insurance Division...Emergency Management Agency (Mitigation Directorate/Risk Insurance...

2011-10-18

173

Selecting a Methodology for Delineating Mudslide Hazard Areas for the National Flood Insurance Program.  

National Technical Information Service (NTIS)

The mudslide provisions of the National Flood Insurance Program and the problems associated with defining the term 'mudslide' are reviewed. The phenomena that can occur as a result of heavy rain in mountain drainage basins are described. A distinction is ...

1982-01-01

174

Flood  

NSDL National Science Digital Library

This lesson plan is part of the discoveryschool.com lesson plan library for grades 6-8. It focuses on how flooding can occur due to different types of soil and how soils are able to retain rainwater. It includes objectives, materials, procedures, discussion questions, evaluation ideas, performing extensions, suggested readings, and vocabulary. There are videos available to order which complement this lesson, audio vocabulary, and links to teaching tools for making custom quizzes, worksheets, puzzles and lesson plans.

175

Environmental and Energy Study Conference Floor Brief: National Flood Insurance Amendments. HR 1236, H. Rpt. 102-38.  

National Technical Information Service (NTIS)

The House Banking Committee bill to keep the National Flood Insurance Program solvent includes building houses, roads and other structures along the coast can be risky; erosion, storms, flooding and other shoreline conditions make barrier islands and even...

1991-01-01

176

In Brief: Flood impact map  

NASA Astrophysics Data System (ADS)

The U.S. Federal Emergency Management Agency (FEMA) and the National Oceanic and Atmospheric Administration (NOAA) have created an interactive “flood impact map.” The map, available at http://www.floodsmart.gov/noaa, features localized, searchable data about the scope and severity of flood events in recent years. Other forecasting and warning tools include those available at http://www.weather.gov/water and NOAA Weather Radio (http://www.nws.noaa.gov/nwr/).

Showstack, Randy

2010-03-01

177

In Brief: Flood impact map  

Microsoft Academic Search

The U.S. Federal Emergency Management Agency (FEMA) and the National Oceanic and Atmospheric Administration (NOAA) have created an interactive ``flood impact map.'' The map, available at http:\\/\\/www.floodsmart.gov\\/noaa, features localized, searchable data about the scope and severity of flood events in recent years. Other forecasting and warning tools include those available at http:\\/\\/www.weather.gov\\/water and NOAA Weather Radio (http:\\/\\/www.nws.noaa.gov\\/nwr\\/).

Randy Showstack

2010-01-01

178

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

179

Hydrological data assimilation with the Ensemble Square-Root-Filter: Use of streamflow observations to update model states for real-time flash flood forecasting  

NASA Astrophysics Data System (ADS)

The objective of the study is to evaluate the potential of a data assimilation system for real-time flash flood forecasting over small watersheds by updating model states. To this end, the Ensemble Square-Root-Filter (EnSRF) based on the Ensemble Kalman Filter (EnKF) technique was coupled to a widely used conceptual rainfall-runoff model called HyMOD. Two small watersheds susceptible to flash flooding from America and China were selected in this study. The modeling and observational errors were considered in the framework of data assimilation, followed by an ensemble size sensitivity experiment. Once the appropriate model error and ensemble size was determined, a simulation study focused on the performance of a data assimilation system, based on the correlation between streamflow observation and model states, was conducted. The EnSRF method was implemented within HyMOD and results for flash flood forecasting were analyzed, where the calibrated streamflow simulation without state updating was treated as the benchmark or nature run. Results for twenty-four flash-flood events in total from the two watersheds indicated that the data assimilation approach effectively improved the predictions of peak flows and the hydrographs in general. This study demonstrated the benefit and efficiency of implementing data assimilation into a hydrological model to improve flash flood forecasting over small, instrumented basins with potential application to real-time alert systems.

Chen, He; Yang, Dawen; Hong, Yang; Gourley, Jonathan J.; Zhang, Yu

2013-09-01

180

Real-Time Flood Forecasting System Based on Simple Lumped Rainfall-Runoff Models Combined with Channel Flow Routing Model Using Particle Filter  

NASA Astrophysics Data System (ADS)

A real-time flood forecasting system was developed for runoff forecasting at several water gauging points. The system is based on a flood runoff model composed of the upstream part and the downstream part models which are respectively simulating runoff for the upstream and downstream parts of the objective basin. The upstream part model is a lumped rainfall-runoff model, and the downstream part model consists of lumped rainfall-runoff models for hillslopes adjacent to a river channel and a kinematic flow routing model for the river channel. The system is updated by Particle filtering of the downstream part model as well as by the extended Kalman filtering of the upstream part model. The Particle filtering is a simple and powerful updating algorithm for non-linear and non-gaussian system, so that it can be easily applied to the downstream part model without complicated linearization. The system applied to the Yoshii River Basin located in Okayama Prefecture, and flood forecasting accuracy of the developed system was examined. The comparison between the forecasting accuracy of the system with both Particle filtering and extended Kalman filtering and that with only extended Kalman filtering shows that Particle filtering of the downstream part model well improves forecasting accuracy particularly for the basin having relatively large area ratio of the downstream part.

Kudo, Ryoji; Chikamori, Hidetaka; Nagai, Akihiro

181

Improving National Air Quality Forecasts with Satellite Aerosol Observations  

Microsoft Academic Search

Accurate air quality forecasts can allow for mitigation of the health risks associated with high levels of air pollution. During September 2003, a team of NASA, NOAA, and EPA researchers demonstrated a prototype tool for improving fine particulate matter (PM2.5) air quality forecasts using satellite aerosol observations. Daily forecast products were generated from a near-real-time fusion of multiple input data

Jassim Al-Saadi; James Szykman; R. Bradley Pierce; Chieko Kittaka; Doreen Neil; D. Allen Chu; Lorraine Remer; Liam Gumley; Elaine Prins; Lewis Weinstock; Clinton MacDonald; Richard Wayland; Fred Dimmick; Jack Fishman

2005-01-01

182

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

NASA Astrophysics Data System (ADS)

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

Hossain, F.

2013-12-01

183

Flash vaporization forecast and control in the heavy oil production well by steam flood  

Microsoft Academic Search

In the production process of heavy oil production well by steam flooding, local pressure drop is caused by the suction of pump when the oil-water mixture flows through the fixed valve, which causes flash vaporization in the pump. Flash vaporization in the pump will cause pump air lock, tubing and pump damage, fluid production decreased. Based on borehole temperature, pressure

Chunsheng Wang; Shuren Yang; Guoshuai Ju

2010-01-01

184

To Downscale or not to Downscale? That's the question. A flood forecasting perspective.  

NASA Astrophysics Data System (ADS)

There is a growing body of literature investigating the subject of rainfall downscaling. The research subject has been sparked by the need to link the predictions of climate models, that are typically ran on tens of kilometer grids, to distributed watershed models, that typically require input at the sub-kilometer scale. This obvious disparity seems to imply that techniques and algorithms need to be developed to scale down the coarse grid information keeping as much of physical reality of the reconstructed fine grid fields. However, the benefits or downscaling rainfall may be less important than previously expected. Our group has been developing and testing multiscale distributed watershed models for flood predictions for several years and we consistently find that finer resolution rainfall may not imply better flood prediction capabilities. At the heart of this issue is the existence of the self-similar network that aggregates flows in the landscape and that ultimately determines the occurrence of floods in a particular basin outlet. We present examples of how rainfall inputs with different resolution impact our flood prediction accuracy across multiple spatial scales. We show for example, using precipitation fields on a daily 12 km grid and a 5 minute 500 m grid, that basins larger than 1000 km2, are insensitive to the resolution of the input product. We show that the sensitivity to the input product is largely determined by the equations that describe the rainfall runoff transformation (linear vs nonlinear). However, we also show that prediction accuracy, with different input grids, increases with increasing scale of the basin (e.g. 30,000 km2). The answer to the question for downscaling or not in flood prediction becomes, "what size is your basin?"

Krajewski, Witold F.; Mantilla, Ricardo; Ayalew, Tibebu B.; Small, Scott J.

2014-05-01

185

Toward a US National Air Quality Forecast Capability: Current and Planned Capabilities  

EPA Science Inventory

As mandated by Congress, NOAA is establishing a US national air quality forecast capability. This capability is being built with EPA, to provide air quality forecast information with enough accuracy and lead-time so that people can take actions to limit harmful effects of poor a...

186

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

Microsoft Academic Search

A novel hydro-information system has been developed to improve the forecast accuracy of the NOAA National Weather Service River Forecast System (NWSRFS). An MKF-based (Multiscale Kalman Filter) spatial data assimilation framework, together with the NOAH land surface model, is employed in our system to assimilate satellite surface soil moisture data to yield improved evapotranspiration. The latter are then integrated into

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

2009-01-01

187

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

188

Ensemble statistical post-processing of the National Air Quality Forecast Capability: Enhancing ozone forecasts in Baltimore, Maryland  

NASA Astrophysics Data System (ADS)

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

Garner, Gregory G.; Thompson, Anne M.

2013-12-01

189

Testing a physically-based flood forecasting model (TOPMODEL) for three U.K. catchments  

NASA Astrophysics Data System (ADS)

A previously developed model has been tested on three catchments: Crimple Beck (8 km 2) near Harrogate, Hodge Beck (36 km 2) on the North York Moors and the Wye headwater (10.5 km 2) in central Wales. The model was originally validated on subcatchments within Crimple Beck. For this study forecasts were made over a period of one year, based only on rainfall and evaporation data. The model parameters were derived from a defined program of field measurements over a period of 2-4 weeks, and no formal optimization procedures were carried out before comparing forecasts with the measured stream discharge record. As a result of the comparisons, the model is seen as a useful approach for ungauged catchments of up to 500 km 2 in humid-temperature climates.

Beven, K. J.; Kirkby, M. J.; Schofield, N.; Tagg, A. F.

1984-02-01

190

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.

191

Meteorological and Hydrogeological Warning Thresholds in the operational bulletins of the Albanian National Centre for Forecast and Monitoring of Natural Risks  

NASA Astrophysics Data System (ADS)

Most operational meteo-hydrological warning system uses fixed rainfall thresholds on given durations to switch alerting bulletins. This may be a too rough approximation in regions with strong climate gradient like Albanian, especially when this bulletins need to include the evaluation of potential ground effect like floods. In the framework of the International cooperation between the Civil Protection of Italy and Albania, the National Centre for Forecast and Monitoring of Natural Risks has been established at the Institute of Geosciences, Energy, Water and Environment (IGEWE). The Centre is supported by expertise of CIMA Research Foundation - International Centre on Environmental Monitoring. The Centre issues (every morning) on a daily basis a Meteorological Warning Bulletin (the first bulletin was issued quite recently on the 20th of December 2011). It is mostly dedicated to the precipitation forecast, the most important hazard in Albania. It covers 36 hours, starting for the noon of the current day till the end of the next day. It offers a detailed precipitation forecast for each prefecture of Albania (12 in total). The prefectures that have to do with the most problematic river (Drini) are divided in a few warning areas each homogenous with respect to climatologic and hydrologic conditions. The meteo-warning is synthetically evaluated for each prefecture; it contains the assessment of the experts about the severity of the forecasted storm in terms of average precipitations, and maximum and, possible storms (if rainfall intensity exceed 90 mm in 3 hours). Reference meteorological model is COSMO LAMI7 (managed by ARPA Bologna, Italy), its spatial resolution is 7 km and temporal resolution for the outputs is 3 hours. Also ECMWF model is available. After the pure meteorological evaluation, possible adverse ground effects are assessed with a second level of variable rainfall thresholds, whose estimated recurrence interval is compared to soil moisture dependent values. The soil moisture conditions are computed by the operational probabilistic forecasting model Flood Proofs, implemented by CIMA for the Drin and lake of Shkodra basins. Flood Proof is also used to forecast river discharge at the mains hydraulic cross-section of the basins; the third level of assessment is based on discharge thresholds. All the meteorological and hydrological forecast models are available in the open source web-based platform DEWETRA (DEWETRA has been developed by CIMA on behalf of the Italian department of Civil Protection who uses it routinely for its activities of forecast, monitor and surveillance of Natural Risks) Meteo-Warning classification is chosen to be similar to MeteoAlarm; in the future the Center wish to participate in this European activity. Hydrological warnings are expressed in terms of risk scenarios.

Marku, M.; Mustaqi, V.; Abazi, E.; Zaimi, K.; Vako, E.; Gjonaj, M.; Hoxhaj, F.; Deda, M.; Fiori, E.; Massabò, M.; Castelli, F.

2012-04-01

192

Towards an operational integrated flood forecasting system for the Isere River basin in Grenoble: implementation of the hydrological model and assessment of the hydraulics operations impact  

NASA Astrophysics Data System (ADS)

The operational flood forecasting service of French Northern Alps (called Service de Prévision des Crues - Alpes du Nord) needs to develop and implement an integrated flood forecasting system for the alpine Isere River basin in Grenoble (5720 km2). Within this framework, the semi-distributed Routing System II model (Dubois et al., 2007) has been implemented on the basin. The first issue that will be addressed concerns the sensitivity of model simulations (and in particular of the snow pack dynamics) to the accuracy of the input precipitation and the choice of the number of snow elevation bands that are used for segmentating each sub-basin. Then, the sensitivity of model predictions to the existing hydropower production infrastructures and the associated hydraulics operations will be presented.

Claude, A.; Zin, I.; Obled, C.; Gautheron, A.; Perret, C.

2009-04-01

193

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

194

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

195

Assimilation of stream discharge for flood forecasting: The benefits of accounting for routing time lags  

NASA Astrophysics Data System (ADS)

General filtering approaches in hydrologic data assimilation, such as the ensemble Kalman filter (EnKF), are based on the assumption that uncertainty of the current background prediction can be reduced by correcting errors in the state variables at the same time step. However, this assumption may not be valid when assimilating stream discharge into hydrological models to correct soil moisture storage due to the time lag between the soil moisture and the discharge. In this paper, we explore the utility of an ensemble Kalman smoother (EnKS) for addressing this time-lag issue. The EnKF and the EnKS are compared for two different updating schemes with the probability distributed model (PDM) via synthetic experiments: (i) updating soil moisture only and (ii) updating soil moisture and routing states simultaneously. The results show that the EnKS is superior to the EnKF when only soil moisture is updated, while the EnKS and the EnKF exhibit similar results when both soil moisture and routing storages are updated. This suggests that the EnKS can better improve the streamflow forecasting for models that do not adopt storage-based routing schemes (e.g., unit-hydrograph-based routing). For models with dynamic routing stores, errors in soil moisture are transferred to the routing stores, which can be corrected effectively by real-time filters. The EnKS-based soil moisture updating scheme is also tested with the GR4H model, for which unit-hydrograph-based routing is used. The result confirms that the EnKS is superior to the EnKF in improving both soil moisture and streamflow forecasting.

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

2013-04-01

196

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

197

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

198

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

Federal Register 2010, 2011, 2012, 2013

...----------------- DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID: FEMA-2010-0065] Public Meetings of National Flood Insurance Program...engaged in a comprehensive reform effort to address the concerns of the wide array of stakeholders involved in the ongoing debate about the NFIP. FEMA chose a participatory policy analysis framework to guide the......

2010-11-22

199

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

Federal Register 2010, 2011, 2012, 2013

...----------------- DEPARTMENT OF HOMELAND SECURITY Federal Emergency Management Agency [Docket ID: FEMA-2010-0065] Public Meetings of National Flood Insurance Program...engaged in a comprehensive reform effort to address the concerns of the wide array of stakeholders involved in the ongoing debate about the NFIP. FEMA chose a participatory policy analysis framework to guide the......

2010-11-10

200

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

201

Mosquito density forecast from flooding: population dynamics model for Aedes caspius (Pallas).  

PubMed

Insect population dynamics depend strongly on environmental factors. For floodwater mosquitoes, meteorological conditions are crucial in the rhythm of mosquito abundances. Indeed, rainfall triggers the egg hatching after flooding breeding sites, and temperature controls the duration of the aquatic immature development up to adult emergence. According to this, we have developed a simple mechanistic and tractable model that describes the population dynamics of floodwater mosquitoes as a function only of the most accessible meteorological variables, rainfall and temperature. The model involves three parameters: development duration tdev of the immature aquatic stages, the adult emergence rate function f(t) (characterized by the emergence time scale tau and shaping the profile of adult population abundance), and the depletion rate, alpha, of adult disappearance. The developed model was subsequently applied to fit experimental field data of the dynamics of Aedes caspius (Pallas), the main pest mosquito in southern France. First, it was found that the emergence rate function of adult mosquitoes very well reproduce experimental data of the dynamics of immature development for all sampled temperatures. The estimated values of tdev and tau both exhibit Arrhenius behaviour as a function of temperature. Second, using the meteorological records of rainfall and temperature as inputs, the model correctly fit data from a two-site CO2 trapping survey conducted in 2004 and 2005. The estimated depletion rates (summation of the mortality and the emigration rates) were found to be a concave quadratic function of temperature with a maximum of 0.5 per days at about 22 degrees C. PMID:20170592

Balenghien, T; Carron, A; Sinègre, G; Bicout, D J

2010-06-01

202

Robust multi-objective calibration strategies - possibilities 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 of 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. Nonetheless, there is a major disadvantage of automatic calibration procedures that understand the problem of model calibration just as the solution of an optimisation problem: due to the complex-shaped response surface, the estimated solution of the optimisation problem can result in different near-optimum parameter vectors that can lead to a very different performance on the validation data. Bárdossy and Singh (2008) studied this problem for single-objective calibration problems using the example of hydrological models and proposed a geometrical sampling approach called Robust Parameter Estimation (ROPE). This approach applies the concept of data depth in order to overcome the shortcomings of automatic calibration procedures and find a set of robust parameter vectors. Recent studies confirmed the effectivity of this method. However, all ROPE approaches published so far just identify robust model parameter vectors with respect to one single objective. The consideration of multiple objectives is just possible by aggregation. In this paper, we present an approach that combines the principles of multi-objective optimisation and depth-based sampling, entitled Multi-Objective Robust Parameter Estimation (MOROPE). It applies a multi-objective optimisation algorithm in order to identify non-dominated robust model parameter vectors. Subsequently, it samples parameter vectors with high data depth using a further developed sampling algorithm presented in Krauße and Cullmann (2012a). We study the effectivity of the proposed method using synthetical test functions and for the calibration of a distributed hydrologic model with focus on flood events in a small, pre-alpine, and fast responding catchment in Switzerland.

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

2012-10-01

203

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

204

Evaluation of a Non-Structural Flood Management and Habitat Enhancement Alternative at the San Joaquin River National Wildlife Refuge  

Microsoft Academic Search

As a result of the January 1997 floods, the San Joaquin River National Wildlife Refuge (SJRNWR) worked with the US Army Corps of Engineers (USACE) to plan a non-structural flood management alternative (NSA). This alternative included breaching existing mainstem San Joaquin River levees on recently acquired refuge land to protect and restore wetland and riparian habitat. The proposed NSA will

C. L. LOWNEY; E. S. ANDREWS; C. B. BOWLES; J. A. HAAS; S. BLAKE

205

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

NASA Astrophysics Data System (ADS)

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

Jordan, F.; Brauchli, T.

2010-09-01

206

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

207

Correcting the radar rainfall forcing of a hydrological model with data assimilation: application to flood forecasting in the Lez catchment in Southern France  

NASA Astrophysics Data System (ADS)

The present study explores the application of a data assimilation (DA) procedure to correct the radar rainfall inputs of an event-based, distributed, parsimonious hydrological model. An extended Kalman filter algorithm was built on top of a rainfall-runoff model in order to assimilate discharge observations at the catchment outlet. This work focuses primarily on the uncertainty in the rainfall data and considers this as the principal source of error in the simulated discharges, neglecting simplifications in the hydrological model structure and poor knowledge of catchment physics. The study site is the 114 km2 Lez catchment near Montpellier, France. This catchment is subject to heavy orographic rainfall and characterised by a karstic geology, leading to flash flooding events. The hydrological model uses a derived version of the SCS method, combined with a Lag and Route transfer function. Because the radar rainfall input to the model depends on geographical features and cloud structures, it is particularly uncertain and results in significant errors in the simulated discharges. This study seeks to demonstrate that a simple DA algorithm is capable of rendering radar rainfall suitable for hydrological forecasting. To test this hypothesis, the DA analysis was applied to estimate a constant hyetograph correction to each of 19 flood events. The analysis was carried in two different modes: by assimilating observations at all available time steps, referred to here as reanalysis mode, and by using only observations up to 3 h before the flood peak to mimic an operational environment, referred to as pseudo-forecast mode. In reanalysis mode, the resulting correction of the radar rainfall data was then compared to the mean field bias (MFB), a corrective coefficient determined using rain gauge measurements. It was shown that the radar rainfall corrected using DA leads to improved discharge simulations and Nash-Sutcliffe efficiency criteria compared to the MFB correction. In pseudo-forecast mode, the reduction of the uncertainty in the rainfall data leads to a reduction of the error in the simulated discharge, but uncertainty from the model parameterisation diminishes data assimilation efficiency. While the DA algorithm used is this study is effective in correcting uncertain radar rainfall, model uncertainty remains an important challenge for flood forecasting within the Lez catchment.

Harader, E.; Borrell-Estupina, V.; Ricci, S.; Coustau, M.; Thual, O.; Piacentini, A.; Bouvier, C.

2012-11-01

208

THE NOAA - EPA NATIONAL AIR QUALITY FORECASTING SYSTEM  

EPA Science Inventory

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

209

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

210

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

NASA Astrophysics Data System (ADS)

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

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

2010-05-01

211

76 FR 64175 - Loans in Areas Having Special Flood Hazards; Interagency Questions and Answers Regarding Flood...  

Federal Register 2010, 2011, 2012, 2013

...National Flood Insurance Act of 1968 and the Flood Disaster Protection Act of 1973...National Flood Insurance Act of 1968 and the Flood Disaster Protection Act of 1973...borrowers the Notice of Special Flood Hazards and Availability of Federal...

2011-10-17

212

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

Federal Register 2010, 2011, 2012, 2013

...floodplain management ordinance...future flood risk to new construction in regulated...floodplain management programs...rate new construction for flood...floodplain management requirements...identifying flood risks,...

2012-05-16

213

Flood Insurance Study  

Microsoft Academic Search

This Flood Insurance Study investigates the existence and severity of flood hazards in the City of Layton, Davis County, Utah, and aids in the administration of the National Flood Insurance Act of 1968 and the Flood Disaster Protection Act of 1973. This study will be used to convert Layton to the regular program of flood insurance by the Federal Emergency

1982-01-01

214

Adapting state and national electricity consumption forecasting methods to utility service areas. Final report  

SciTech Connect

This report summarizes the experiences of six utilities (Florida Power and Light Co., Municipal Electric Authority of Georgia, Philadelphia Electric Co., Public Service Co. of Colorado, Sacramento Municipal Utility District, and TVA) in adapting to their service territories models that were developed for forecasting loads on a national or regional basis. The models examined were of both end-use and econometric design and included the three major customer classes: residential, commercial, and industrial.

Swift, M.A.

1984-07-01

215

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

216

Towards A European Flood Early Warning System: Feasibility, Progress And Challenges  

NASA Astrophysics Data System (ADS)

In the last decade a number of unusual rainfall events produced severe floods in Europe, and projections of future climate indicate that further increase in severe floods in North and Northwest Europe are likely. In most European countries the National Water Authorities produce flood forecasts with leadtimes of 1-3 days. Their predictions are often based on point measurements from a number of raingauges and upstream discharge measurements or short-term weather forecasts. In many cases, however, an increased lead-time could be beneficial to civil-protection agencies and the water-authorities responsible for forecasting and warning. Therefore, the Joint Research Centre of the European Commission is developing and testing a modelling system to simulate floods in large European transnational catchments. It is using the shell of the WL-Delft Hydraulics FEWS system. Within the EFFS project a feasibility study took place including comparisons with other modelling systems at national scale. The aim of the European Flood Early Warning System is not to replace existing national forecasting activities, but to provide additional information. In general a forecast with a longer lead-time could be provided, together with an estimation of the uncertainty or the probability. Such a pre-alert could be provided to local water authorities and civil protection services allowing them: begin{itemize} [bullet]to alert and organize their staff (cancel holidays, missions, weekend leave) [bullet]double-check their own forecasting tools, rescue systems, field equipment, measurement devices, emergency plans [bullet]increase for example the frequency of flood forecasting from once per day to 2-4 times daily The leadtime is increased by making use of the state-of-the-art forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) and from the National Weather Offices (DWD &DMI). In particular the ECMWF data are still hardly used for practical flood forecasting because their spatial resolution (40-60 km) is relatively coarse compared with the size of hydrological catchments. However, in combination with a flood forecasting model on a European scale, they can potentially increase the lead time for qualitative early flood warnings up to 10 days in advance. Another novelty of this research project is the incorporation of so-called "ensemble forecasts" into the flood forecasting. Ensemble predictions capture the uncertainty of meteorological forecasts due to small errors in the initial state, e.g. through measuring errors, numerical errors, or model parameterisations. With each deterministic weather forecast ECMWF produces 50 ensemble simulations. For the EFFS project a number of case studies has been selected, including the Meuse and Rhine flood in January 1995, the Po flood of 1994 and the Oder flood in July 1997. For these case studies the catchment hydrological model system LISFLOOD is run for the deterministic forecasts as well as for the complete set of ensemble forecasts. The quality and uncertainty of the combined forecast system is assessed. Several results are shown and discussed.

de Roo, A.; Thielen, J.; Gouweleeuw, B.; Franchello, G.; Reggiani, P.; van Dijk, M.; Schmuck, G.

2003-04-01

217

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

218

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

219

65 FR 34824 - National Flood Insurance Program (NFIP); Insurance Coverage and Rates  

Federal Register 2010, 2011, 2012, 2013

...to, any solid, liquid, gaseous or thermal...or flood-related erosion hazards, and shown...to, any solid, liquid, gaseous or thermal...or flood-related erosion hazards, and shown...to, any solid, liquid, gaseous or thermal...or flood-related erosion hazards, and...

2000-05-31

220

65 FR 60758 - National Flood Insurance Program (NFIP); Insurance Coverage and Rates  

Federal Register 2010, 2011, 2012, 2013

...to, any solid, liquid, gaseous, or thermal...or flood-related erosion hazards, and shown...to, any solid, liquid, gaseous or thermal...or flood-related erosion hazards, and shown...to, any solid, liquid, gaseous, or thermal...or flood-related erosion hazards, and...

2000-10-12

221

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

222

Flash Flood Nowcasting in an Urban Watershed  

NASA Astrophysics Data System (ADS)

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

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

2003-04-01

223

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

224

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

225

Flood Risk and Flood hazard maps - Visualisation of hydrological risks  

Microsoft Academic Search

Hydrological models are an important basis of flood forecasting and early warning systems. They provide significant data on hydrological risks. In combination with other modelling techniques, such as hydrodynamic models, they can be used to assess the extent and impact of hydrological events. The new European Flood Directive forces all member states to evaluate flood risk on a catchment scale,

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

2008-01-01

226

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

227

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

228

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

NASA Astrophysics Data System (ADS)

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

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

2006-12-01

229

National ocean partnership project advances real-time coastal ocean forecasting  

NASA Astrophysics Data System (ADS)

A 1999-2000 National Ocean Partnership Project (NOPP) has demonstrated highly accurate predictions of ocean temperatures, currents, and surface elevation through a model that integrates the state of the ocean to routinely produce real-time nowcasts and forecasts. The success is attributed to a new technology for model-assimilation of satellite-derived surface observations with observations from in situ equipment. Because the Chesapeake Bay and the northwestern Atlantic boarding the east coast of the United States is an area of intense ocean harvest, recreational boating, and major shipping —activities that depend on near-term prediction of near-surface conditions of the waters off the eastern coast—it served as the test-bed for the “Coastal Marine Demonstration Project”

Thiebaux, Jean; Katz, Bert; Kelley, John; Breaker, Laurence; Balasubramaniyan, Bhavani

230

National Flood Insurance Program's Market Penetration Rate: Estimates and Policy Implications.  

National Technical Information Service (NTIS)

Congress passed the Flood Disaster Protection Act of 1973, which requires federally insured or regulated lenders to require flood insurance as a condition of granting or continuing a loan when the building and the improvements securing it are in the Speci...

A. Overton, L. Dixon, N. Clancy, S. A. Seabury

2006-01-01

231

Nuptiality Models and the Two-Sex Problem in National Population Forecasts-with an Emphasis on the Netherlands.  

National Technical Information Service (NTIS)

This paper deals with possible solutions for the two-sex problem in nuptiality models focusing on applications in national population forecasts. Requirements for a realistic two-sex marriage model as described in the literature are mentioned, as well as a...

N. Keilman

1982-01-01

232

Floods and flood management in Pakistan  

NASA Astrophysics Data System (ADS)

Flooding is the most devastating natural hazard in Pakistan and the recent flooding has demonstrated its severeness. Floods are common throughout the country. However, their characteristics differ from region to region. Flooding behavior of the major basins and flood management at the national level are investigated in this article. Monsoon rainfalls are the main source of floods in the Indus Basin, while Mediterranean Waves and Cyclones, which are generated over the Arabian Sea, induce flooding in the Kharan Basin and the Makran Coastal Area. Fluvial floods in the Indus Basin have caused major economic losses. Pakistan’s government has spent vast resources on relief operations and flood works since the country came into existence in 1947. A number of provincial and federal acts, ordinances, accords, and treaties shape the national flood policy. Institutional setup for flood hazard and crisis management has evolved over the years. Nevertheless, data show no major reduction in the flood-to-damage ratio. The inter-linkage of structural and non-structural measures and their combined efficiency must be analyzed and optimized for more effective flood management.

Tariq, Muhammad Atiq Ur Rehman; van de Giesen, Nick

233

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.

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

2014-01-01

234

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.

Spangler, Tim

2006-10-10

235

Notes on vocalisations of giant otters in the flooded Igapó forests of Jaú National Park, Amazonas, Brazil  

Microsoft Academic Search

Between January and June 2008, we surveyed three flooded Igapó areas (>5 km2 in total) in Jaú National Park, Amazonas, Brazil. The objective of this note is to provide quantitative information on the\\u000a vocalisations of the giant otters inhabiting these areas. We encountered the giant otters in January, February, March and\\u000a April 2008. From one to five individuals were observed during

B. M. Bezerra; A. S. Souto; N. Schiel; G. Jones

2011-01-01

236

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

237

Coastal ocean forecasting systems in Europe  

NASA Astrophysics Data System (ADS)

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

Dugan, John

238

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

239

Flood Cleanup  

MedlinePLUS

... here: EPA Home Air Indoor Air Flood Cleanup Flood Cleanup During a flood cleanup, the indoor air ... flood and how to prevent indoor air problems: Flood Cleanup and the Air In Your Home Booklet ...

240

Model Output Statistics Forecast Guidance.  

National Technical Information Service (NTIS)

This publication describes data in the National Weather Services's Model Output Statistics Final Forecast Guidance teletype bulletins. It is intended to serve as a comprehensive guide to the interpretation and use of the forecast bulletins by AWS forecast...

H. Hughes

1976-01-01

241

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

NASA Astrophysics Data System (ADS)

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

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

242

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

USGS Publications Warehouse

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

Nelson, L. M.

1987-01-01

243

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

NASA Astrophysics Data System (ADS)

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

Lumbroso, D. M.; Vinet, F.

2011-08-01

244

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

245

Use of High-Resolution Precipitation Products Derived from the Weather Research and Forecasting Model to Drive GIS-Based Hydrological Flood Inundation Modeling; Effects of Rainfall Error on Flood Accuracy  

Microsoft Academic Search

This paper addresses research into a new approach that couples precipitation predictions with GIS applications and hydrological modeling to predict flood potential and thus mitigate the impacts of these natural disasters in Texas. Flooding induced from storm events is a major concern in many regions of the world, including Texas, which receives extreme precipitation events numerous times annually. The goal

M. R. Knebl

2005-01-01

246

Development of a National Environmental Forecasting Service for Peru: Executive Summary.  

National Technical Information Service (NTIS)

This purpose of the study was to carefully analyze the present state of the hydrometeorological forecasting service in Peru, and to make recommendations for their general modernization and enhancement. The study includes field studies, interviews and tech...

1996-01-01

247

Early flood warning for Linyi watershed by the GRAPES/XXT model using TIGGE data  

NASA Astrophysics Data System (ADS)

Early and effective flood warning is essential for reducing loss of life and economic damage. Three global ensemble weather prediction systems of the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF), and the US National Centers for Environmental Prediction (NCEP) in THORPEX (The Observing System Research and Predictability Experiment) Interactive Grand Global Ensemble (TIGGE) archive are used in this research to drive the Global/Regional Assimilation and PrEdiction System (GRAPES) to produce 6-h lead time forecasts. The output (precipitation, air temperature, humidity, and pressure) in turn drives a hydrological model XXT (the first X stands for Xinanjiang, the second X stands for hybrid, and T stands for TOPMODEL), the hybrid model that combines the TOPMODEL (a topography based hydrological model) and the Xinanjiang model, for a case study of a flood event that lasted from 18 to 20 July 2007 in the Linyi watershed. The results show that rainfall forecasts by GRAPES using TIGGE data from the three forecast centers all underestimate heavy rainfall rates; the rainfall forecast by GRAPES using the data from the NCEP is the closest to the observation while that from the CMA performs the worst. Moreover, the ensemble is not better than individual members for rainfall forecasts. In contrast to corresponding rainfall forecasts, runoff forecasts are much better for all three forecast centers, especially for the NCEP. The results suggest that early flood warning by the GRAPES/XXT model based on TIGGE data is feasible and this provides a new approach to raise preparedness and thus to reduce the socio-economic impact of floods.

Xu, Jingwen; Zhang, Wanchang; Zheng, Ziyan; Jiao, Meiyan; Chen, Jing

2012-02-01

248

Evaluating the tropospheric variability in National Centers for Environmental Prediction's climate forecast system reanalysis  

NASA Astrophysics Data System (ADS)

The National Centers for Environmental Prediction (NCEP) recently completed the latest, and partially coupled, atmosphere-ocean-sea ice model-based climate forecast system reanalysis (CFSR) for the 1979 to current satellite era. In the reanalysis, the observed CO2 concentration and the volcanic aerosols were also prescribed. This paper provides an initial overview of the tropospheric variability in the CFSR by comparing it against available previous reanalyses. CFSR's monthly mean zonal and meridional component of wind U and V, temperature T, and geopotential height H at pressure levels up to 100 mb are compared against those of three other readily available reanalyses NCEP/R1, NCEP/R2 and ERA40 for the period from 1979 to 2008 (2002 for ERA40) and also against modern reanalyses such as JRA, MERRA, and C20. At any given time (analysis hour, day, or month), for the globe as a whole, CFSR analysis agrees reasonably well with the other reanalyses. The CFSR's new coupled model and assimilation system makes use of the recent advances in these areas and hence is possibly an improvement to NCEP's previous reanalyses R1 and R2, which are 15 and 10 years old, respectively. For these long-term climate variability measures the analysis indicates that the CFSR was generally the outlier, with much stronger easterly trades, cooler tropospheric temperatures, and lower geopotential heights during much of the earlier part of the analysis period (1979-˜1998). Consequently, real-time monitoring of many of the ENSO-related climate wind indices in the equatorial Pacific or the wind shear index in the tropical North Atlantic from CFSR may be problematic in the context of historical variability.

Chelliah, Muthuvel; Ebisuzaki, Wesley; Weaver, Scott; Kumar, Arun

2011-09-01

249

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

250

Floods: The Awesome Power  

NSDL National Science Digital Library

A newly released publication from the National Oceanic and Atmospheric Administration, the National Weather Service, and the Red Cross is entitled "Floods: The Awesome Power." The citizen-focused sixteen-page preparedness guide explains "flood-related hazards and suggests life-saving actions you can take." Readers will learn what flash floods are, what to do if youâÂÂre caught in your vehicle during a flash flood, what river floods are, how tropical cyclones create floods, where to get current weather information, what your local community can do to be more prepared for floods, and much more. The graphics rich and non-technical publication with its potentially life-saving information is definitely worth a read.

2002-01-01

251

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

USGS Publications Warehouse

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

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

2012-01-01

252

78 FR 8089 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...addresses the flooding sources Big Run, Little Loyalsock...section 110 of the Flood Disaster Protection Act of 1973...addressed the flooding sources Big Run, Little Loyalsock...Big Run...National Geodetic Vertical Datum. + North American...

2013-02-05

253

77 FR 67324 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...addresses the flooding sources Big Run, Little Loyalsock...section 110 of the Flood Disaster Protection Act of 1973...addressed the flooding sources Big Run, Little Loyalsock...Big Run...National Geodetic Vertical Datum. + North American...

2012-11-09

254

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

255

A 2D simulation model for urban flood management  

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

256

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

257

Ecological Effects of the Lawn Lake Flood of 1982, Rocky Mountain National Park.  

National Technical Information Service (NTIS)

Contents: Hydrology and Geomorphology of the 1982 Lawn Lake Dam Failure, Colorado; Geomorphic Response of the Fall River, Rocky Mountain National Park, Colorado; Alpine Sediment Movement and Erosion in the Roaring River Watershed, Rocky Mountain National ...

H. E. McCutchen R. Herrmann D. R. Stevens

1993-01-01

258

44 CFR 78.6 - Flood Mitigation Plan approval process.  

Code of Federal Regulations, 2013 CFR

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

2013-10-01

259

44 CFR 78.5 - Flood Mitigation Plan development.  

Code of Federal Regulations, 2013 CFR

...Assistance 1 2013-10-01 2013-10-01 false Flood Mitigation Plan development. 78.5 Section 78...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood...

2013-10-01

260

Scoping of Flood Hazard Mapping Needs for Penobscot County, Maine.  

National Technical Information Service (NTIS)

The Federal Emergency Management Agency (FEMA) developed a plan in 1997 to modernize the FEMA flood mapping program. FEMA flood maps delineate flood hazard areas in support of the National Flood Insurance Program (NFIP). FEMA's plan outlined the steps nec...

C. W. Schalk R. W. Dudley

2007-01-01

261

Scoping of Flood Hazard Mapping Needs for Lincoln County, Maine.  

National Technical Information Service (NTIS)

The Federal Emergency Management Agency (FEMA) developed a plan in 1997 to modernize the FEMA flood mapping program. FEMA flood maps delineate flood hazard areas in support of the National Flood Insurance Program (NFIP). FEMA's plan outlined the steps nec...

C. W. Schalk R. W. Dudley

2007-01-01

262

Scoping of Flood Hazard Mapping Needs for Androscoggin County, Maine.  

National Technical Information Service (NTIS)

The Federal Emergency Management Agency (FEMA) developed a plan in 1997 to modernize the FEMA flood mapping program. FEMA flood maps delineate flood hazard areas in support of the National Flood Insurance Program (NFIP). FEMA's plan outlined the steps nec...

C. W. Schalk R. W. Dudley

2007-01-01

263

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

Microsoft Academic Search

The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span

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

2011-01-01

264

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.

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

2013-01-01

265

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

266

Flood-inundation maps for the Mississinewa River at Marion, Indiana, 2013  

USGS Publications Warehouse

Digital flood-inundation maps for a 9-mile (mi) reach of the Mississinewa River from 0.75 mi upstream from the Pennsylvania Street bridge in Marion, Indiana, to 0.2 mi downstream from State Route 15 were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood 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 on the Mississinewa River at Marion (station number 03326500). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site. Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated by using the current stage-discharge relation at the Mississinewa River streamgage, in combination with water-surface profiles from historic floods and from the current (2002) flood-insurance study for Grant County, Indiana. The hydraulic model was then used to compute seven water-surface profiles for flood stages at 1-fo (ft) intervals referenced to the streamgage datum and ranging from 10 ft, which is near bankfull, to 16 ft, which is between the water levels associated with the estimated 10- and 2-percent annual exceedance probability floods (floods with recurrence interval between 10 and 50 years) and equals the “major flood stage” as defined by the NWS. 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 0.98 ft vertical accuracy and 4.9 ft horizontal resolution) 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 and forecasted high-flow stages from the NWS, will 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.

Coon, William F.

2013-01-01

267

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

268

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

269

Social Forecasting.  

National Technical Information Service (NTIS)

Contents: Foresight becomes a science; What is social forecasting; Forecasting methods; Scientific establishments and their production; Scientific-technical forecasting; Medical-biological forecasting; Socioeconomic forecasting, and Geographical and space...

I. V. Bestuzhev-Lada

1970-01-01

270

COMPARISON OF FLOOD PREDICTION MODELS FOR RIVER LOKOJA, NIGERIA  

Microsoft Academic Search

Flood estimation is one of the major aspects of hydrologic design and is the first in planning for flood regulation and protection measures. This research work was aimed at comparing prediction models for forecasting flood occurrences in River Lokoja, located in Kogi State of Nigeria. Relevant climatic data such as rainfalls, flood discharges, river stages of 24 years duration (1980

271

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

272

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

NASA Astrophysics Data System (ADS)

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

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

2006-12-01

273

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

USGS Publications Warehouse

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

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

2008-01-01

274

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

275

44 CFR 60.3 - Flood plain management criteria for flood-prone areas.  

Code of Federal Regulations, 2013 CFR

... 1 2013-10-01 2013-10-01 false Flood plain management criteria for flood-prone areas. 60.3 Section 60.3 Emergency...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND...

2013-10-01

276

Namibian Flood Early Warning SensorWeb Pilot  

NASA Technical Reports Server (NTRS)

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

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

2010-01-01

277

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

278

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...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.4...

2013-10-01

279

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...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1316 OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 § 73.3...

2013-10-01

280

Pakistan Flooding  

article title:  Flooding in Pakistan     ... parts of Baluchistan. According to the Associated Press, the floods have affected about one-fifth of the country. Tens of thousands of ... and Aug 11, 2010 Images:  Pakistan Flood location:  Asia thumbnail:  ...

2013-04-16

281

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

282

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

SciTech Connect

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

Judi, David R [Los Alamos National Laboratory; Mcpherson, Timothy N [Los Alamos National Laboratory; Burian, Steven J [UNIV. OF UTAH

2009-01-01

283

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

Code of Federal Regulations, 2013 CFR

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

2013-10-01

284

Methods of long-range forecasting of dates of the spring flood beginning and peak flow in the estuary sections of the Ob and Yenisei rivers  

Microsoft Academic Search

Multi-year characteristics of the beginning of spring floods and their peak flow observed at the stream gauges located in\\u000a the estuary sections of the Ob and Yenisei rivers in the period from 1936 to 2003 were obtained in this work. For most of\\u000a stream gauges, significant correlation between these characteristic dates and dates when the accumulated positive temperatures\\u000a (observed at

E. V. Shevnina

2009-01-01

285

Design Guidelines for Flood Damage Reduction.  

National Technical Information Service (NTIS)

The Federal Emergency Management Agency is charted with implementing the National Flood Insurance Act of 1968. Under this Act FEMA is responsible for administering the National Flood Insurance Program and sponsoring other activities intended to reduce los...

1981-01-01

286

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

287

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

288

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

289

Short-range ensemble streamflow forecasting of the Upper Trinity River - Evaluation via hindcasting experiments  

NASA Astrophysics Data System (ADS)

By allowing for routine use of longer-lead quantitative precipitation forecast (QPF) in hydrologic prediction, ensemble forecasting offers hope for extending the lead time for short-range flood forecasting. In this work, we assess this potential by evaluating the quality of short-range streamflow hindcasts for five headwater basins in the Upper Trinity River Basin in North Texas. The hindcasts are generated from the Hydrologic Ensemble Forecast System (HEFS) of the National Weather Service (NWS). The HEFS operates as a part of the Community Hydrologic Prediction System (CHPS) of the NWS. Currently, the HEFS models the input and hydrologic uncertainties using the Meteorological Ensemble Forecast Processor (MEFP) and the Ensemble Post-Processor (EnsPost), respectively. For generation of short-range ensemble precipitation forecasts, the MEFS models the conditional probability distribution of observed precipitation given the single-valued quantitative precipitation forecasts (QPF). For hydrologic uncertainty, EnsPost models the conditional distribution of observed streamflow given the simulated streamflow and the most recently observed streamflow. We design and carry out hindcasting experiments to evaluate the quality of both precipitation and streamflow ensembles, and to assess the value of short-range ensemble streamflow forecasts relative to the existing single-valued forecasts. For the above, we used the Ensemble Verification System (EVS) also developed by the NWS. We describe the hindcasting experiments, summarize the results, and identify issues and challenges.

Saharia, M.; Seo, D.; Corby, R.; He, K.

2013-05-01

290

Repetitive Flood Claims (RFC) Program Guidance.  

National Technical Information Service (NTIS)

The Repetitive Flood Claims (RFC) grant program provides funding to reduce or eliminate the long-term risk of flood damage to structures insured under the National Flood Insurance Program (NFIP) that have had one or more claim payments for flood damages. ...

2008-01-01

291

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

USGS Publications Warehouse

Digital flood-inundation maps for a 2.75-mile reach of the Saddle River from 0.2 mile upstream from the Interstate 80 bridge in Rochelle Park to 1.5 miles downstream from the U.S. Route 46 bridge in Lodi, New Jersey, were created by the U.S. Geological Survey (USGS) in cooperation with the New Jersey Department of Environmental Protection (NJDEP). The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Saddle River at Lodi, New Jersey (station 01391500). Current conditions for estimating near real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/nwis/uv?site_no=01391500. The National Weather Service (NWS) forecasts flood hydrographs at many places that are often collocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relations at the Saddle River at Lodi, New Jersey streamgage and documented high-water marks from recent floods. The hydraulic model was then used to determine 11 water-surface profiles for flood stages at the Saddle River streamgage at 1-ft intervals referenced to the streamgage datum, North American Vertical Datum of 1988 (NAVD 88), and ranging from bankfull, 0.5 ft below NWS Action Stage, to the extent of the stage-discharge rating, which is approximately 1 ft higher than the highest recorded water level at the streamgage. Action Stage is the stage which when reached by a rising stream the NWS or a partner needs to take some type of mitigation action in preparation for possible significant hydrologic activity. The simulated water-surface profiles were then combined with a geographic information system 3-meter (9.84-ft) digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.

Hoppe, Heidi L.; Watson, Kara M.

2012-01-01

292

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

293

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

294

GPS Estimates of Integrated Precipitable Water Aid Weather Forecasters  

NASA Technical Reports Server (NTRS)

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

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

2013-01-01

295

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.

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

2013-01-01

296

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

297

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

298

Flood Resilient Technological Products  

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

299

Correcting the radar rainfall forcing of a hydrologic model with data assimilation: application to flood forecasting in the Lez Catchment in Southern France  

NASA Astrophysics Data System (ADS)

For flood prediction and watershed characterization, radar data can provide a key advantage in terms of temporal and spatial resolution, as runoff generation is sensitive to rainfall location. However, the radar data input to the hydrological model is subject to uncertainties related to a non-linear vertical reflectivity profile (Borga, 2002), calibration of the Z-R relationship and beam blocking effects (Vieux & Bedient, 2004). Specifically for the Lez catchment, radar data quality varies on a seasonal basis and is degraded in winter (Coustau et al., 2011). These uncertainties translate to errors in the simulated discharges. Data assimilation techniques can be applied to improve the quality of radar data or parameters input to the hydrological model. Rainfall inputs were corrected by a factor of ?, calculated separately for each event by assimilating observed discharges. This coefficient was compared with the mean field bias (MFB), a corrective coefficient determined using ground rainfall measurements (Vieux & Bedient, 2004). Simulations were then performed in the context of 'real-time' peak discharge prediction and corrected using data assimilation. A set of 18 rainfall events was used to simulate discharges for the 114 km2 Lez Catchment, which is subject to heavy orographic rainfall and characterized by a karstic geology. A distributed, event-based, parsimonious hydrological model was used, with runoff production controlled by a modified SCS method, parameterized by S, representing the initial soil moisture deficit (Coustau et al., 2011). Application of the data assimilation algorithm was carried out in two different modes: re-analysis, in which all observations during the flood event are assimilated and prevision, in which only observations before the event peak are assimilated. In re-analysis mode, the soil moisture content was initialized by an S calibrated for the simulation forced by MFB corrected rainfall. In prevision mode, the soil moisture deficit was initialized using the Hu2 indicator, modeled remotely by Météo-France. The Kalman Filter algorithm was used to assimilate discharge observations for the correction of model inputs. The study resulted in two main findings: 1) simulations using radar rainfall corrected by ?, calculated by data assimilation in re-analysis mode showed an improved Nash criterion when compared to simulations forced by MFB corrected rainfall and 2) simulations using radar rainfall data corrected by data assimilation in prevision mode showed, on average, improved results over the initial simulation. The re-analysis results provide an important validation of the model, demonstrating that the assimilation of discharge data provides information about the system not available with corrections based solely on rain gauge data. The second result demonstrates the ability of data assimilation to render radar data useable for flood prediction. This finding is especially pertinent for the next step of this study which is the use of modeled future rainfall data to extend lead times; these rainfalls are expected to be subject to high levels of uncertainty.

Harader, E. B.; Estupina-Borrell, V.; Ricci, S. M.; Coustau, M.; Thual, O.; Bouvier, C.

2011-12-01

300

44 CFR 67.4 - Proposed flood elevation determination.  

Code of Federal Regulations, 2013 CFR

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

2013-10-01

301

75 FR 78610 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-12-16

302

75 FR 18074 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-04-09

303

76 FR 50423 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-08-15

304

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...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION...BARRIER LEGISLATION § 71.3 Denial of flood insurance. (a) No new...

2013-10-01

305

76 FR 20556 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-04-13

306

76 FR 8905 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-02-16

307

76 FR 68322 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-11-04

308

75 FR 82274 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-12-30

309

44 CFR 61.17 - Group Flood Insurance Policy.  

Code of Federal Regulations, 2013 CFR

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

2013-10-01

310

44 CFR 61.13 - Standard Flood Insurance Policy.  

Code of Federal Regulations, 2013 CFR

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

2013-10-01

311

76 FR 43601 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-07-21

312

76 FR 49674 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-08-11

313

76 FR 21660 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-04-18

314

75 FR 78613 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-12-16

315

76 FR 2837 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-01-18

316

75 FR 78606 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-12-16

317

76 FR 26943 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-05-10

318

75 FR 78607 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-12-16

319

76 FR 20551 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-04-13

320

75 FR 18073 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-04-09

321

44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.  

Code of Federal Regulations, 2013 CFR

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

2013-10-01

322

76 FR 21662 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-04-18

323

75 FR 81889 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-12-29

324

76 FR 20553 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-04-13

325

76 FR 23 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-01-03

326

75 FR 78615 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-12-16

327

76 FR 79090 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-12-21

328

75 FR 35670 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-06-23

329

75 FR 29210 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2010-05-25

330

76 FR 60748 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-09-30

331

76 FR 50913 - Changes in Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...in the table below and revise the Flood Insurance Rate Maps...S.C. 4105, and are in accordance with the National Flood Insurance Act of...in 44 CFR Part 65 Flood insurance, Floodplains, Reporting and recordkeeping...

2011-08-17

332

Flood Map Modernization: Program Strategy Shows Promise, but Challenges Remain.  

National Technical Information Service (NTIS)

Flood maps identify areas at greatest risk of flooding and provide the foundation for the National Flood Insurance Program (NFIP) managed by the Federal Emergency Management Agency (FEMA). The maps are used by (1) communities to establish minimum building...

2004-01-01

333

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

USGS Publications Warehouse

Digital flood-inundation maps for a 15.5-mi reach of the DuPage River from Plainfield to Shorewood, Illinois, were created by the U.S. Geological Survey (USGS) in cooperation with the Will County Stormwater Management Planning Committee. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent of flooding corresponding to selected water levels (gage heights or stages) at the USGS streamgage at DuPage River at Shorewood, Illinois (sta. no. 05540500). Current conditions at the USGS streamgage may be obtained on the Internet at http://waterdata.usgs.gov/usa/nwis/uv?05540500. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. The NWS-forecasted peak-stage information, also shown on the DuPage River at Shorewood inundation Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was then used to determine nine water-surface profiles for flood stages at 1-ft intervals referenced to the streamgage datum and ranging from NWS Action stage of 6 ft to the historic crest of 14.0 ft. The simulated water-surface profiles were then combined with a Digital Elevation Model (DEM) (derived from Light Detection And Ranging (LiDAR) data) by using a Geographic Information System (GIS) in order to delineate the area flooded at each water level. These maps, along with information on the Internet regarding current gage height from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.

Murphy, Elizabeth A.; Sharpe, Jennifer B.

2013-01-01

334

Flood Visualizations  

NSDL National Science Digital Library

A lengthy listing of all of NASA's Scientific Visualization Studio visualizations that have flood as a keyword. The listing includes many visualizations of specific flood instances, as well as visualizations of floods caused by hurricanes. The visualizations are available in a wide variety of formats.

Svs, Nasa G.; Nasa

335

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

NASA Technical Reports Server (NTRS)

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

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

1997-01-01

336

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

Code of Federal Regulations, 2010 CFR

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

2009-10-01

337

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

Code of Federal Regulations, 2010 CFR

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

2010-10-01

338

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

Code of Federal Regulations, 2013 CFR

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

2013-10-01

339

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

340

75 FR 61358 - Final Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...show evidence of being already in effect in order to qualify or remain qualified for participation in the National Flood Insurance Program (NFIP). DATES: The date of issuance of the Flood Insurance Rate Map (FIRM) showing BFEs and...

2010-10-05

341

78 FR 21273 - Final Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013

...show evidence of being already in effect in order to qualify or remain qualified for participation in the National Flood Insurance Program (NFIP). DATES: The date of issuance of the Flood Insurance Rate Map (FIRM) showing BFEs and...

2013-04-10

342

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

2007-01-01

343

Use of NEXRAD-based rainfall datasets for hydrologic model hindcasts and real-time forecasts  

NASA Astrophysics Data System (ADS)

Archives of gridded rainfall datasets at 4-km/1-hr resolution from NEXRAD span as many as 17 years in some regions of the US. This study incorporates these long-term rainfall datasets into a high-resolution, distributed hydrologic model to produce historical simulations. Provided that the hydrologic model run with physically-based, a-priori parameters yields accurate rankings of events (bias is not relevant), a great deal of information can be learned from these historical simulations. Locations and seasonality of model-simulated flash floods will be identified and illustrated to, for instance, shed light on "flash flood alley". The second aspect of this study utilizes the historical distribution of model-simulated annual peaks at each grid point in the US to derive flow threshold values for forecasting floods at ungauged locations. In forecast mode, we rely on precipitation forcing from the National Mosaic and QPE System (NMQ/Q2; http://nmq.ou.edu) at 1-km/5-min resolution. An overlapping period of coarse and fine-resolution forcing was used to adjust the historical flow distributions to accommodate the high-resolution rainfall forcing for real-time flood forecasting.

Gourley, J. J.; Flamig, Z.; Hong, Y.

2012-12-01

344

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

345

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

Microsoft Academic Search

In the 10 days of 21-30 September 1998, Hurricane Georges left a trail of destruction in the Caribbean region and U.S. Gulf Coast. Subsequently, in the same year, Hurricane Mitch caused widespread destruction and loss of life in four Central American nations, and in December,1999 a tropical disturbance impacted the north coast of Venezuela causing hundreds of deaths and several

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

2004-01-01

346

The Informational Content of Ex Ante Forecasts  

Microsoft Academic Search

The informational content of different forecasts can be compared by regressing the actual change in a variable to be forecasted on forecasts of the change. We use the procedure in Fair and Shiller (1987) to examine the informational content of three sets of ex ant. forecasts: the American Statistical Association and National Bureau of Economic Research Survey (ASA), Data Resources

Ray C. Fair; Robert J. Shiller

1989-01-01

347

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

348

Development of a National Environmental Forecasting Service for Peru. Volume 1, SIGAP Operations Concept Document for CONADE. Task 1A.  

National Technical Information Service (NTIS)

The purpose of the study was to carefully analyze the present state of the hydrometeorological forecasting service in Peru, and to make recommendations for their general modernization and enhancement. The study includes field studies, interviews and techn...

1996-01-01

349

Development of a Peruvian National Environmental Forecasting Service, Volume 5. SIGAP Integrated Logistics Support Plan for CONADE. Task 4.  

National Technical Information Service (NTIS)

The purpose of the study was to carefully analyze the present state of the hydrometeorological forecasting service in Peru, and to make recommendations for their general modernization and enhancement. The study includes field studies, interviews and techn...

1996-01-01

350

Development of a National Environmental Forecasting Service for Peru. Volume 2. SIGAP Operational Requirements for CONADE. Task 1B.  

National Technical Information Service (NTIS)

The purpose of the study was to carefully analyze the present state of the hydrometeorological forecasting service in Peru, and to make recommendations for their general modernization and enhancement. The study includes field studies, interviews and techn...

1997-01-01

351

Development of a Peruvian National Environmental Forecasting Service. Volume 6. SIGAP Economics and Financial Plan for CONADE. Task 5.  

National Technical Information Service (NTIS)

The purpose of the study was to carefully analyze the present state of the hydrometeorological forecasting service in Peru, and to make recommendations for their general modernization and enhancement. The study includes field studies, interviews and techn...

1996-01-01

352

Development of a Peruvian National Environmental Forecasting Service. Volume 3. SIGAP System Design Document for CONADE. Task 2.  

National Technical Information Service (NTIS)

The purpose of the study was to carefully analyze the present state of the hydrometeorological forecasting service in Peru, and to make recommendations for their general modernization and enhancement. The study includes field studies, interviews and techn...

1997-01-01

353

Development of a National Environmental Forecasting Service for Peru. Volume 4. SIGAP Implementation Plan Document for CONADE. Task 3.  

National Technical Information Service (NTIS)

The purpose of the study was to carefully analyze the present state of the hydrometeorological forecasting service in Peru, and to make recommendations for their general modernization and enhancement. The study includes field studies, interviews and techn...

1996-01-01

354

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

355

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

356

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

NASA Technical Reports Server (NTRS)

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

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

2012-01-01

357

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

USGS Publications Warehouse

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

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

2012-01-01

358

Stream Floods  

NSDL National Science Digital Library

This exercise is designed to explore the nature of floods and flood prediction. Prediction of flooding relies heavily upon statistical techniques based on historical records of stream behavior. This series of exercises first reviews basic concepts in flood prediction such as calculating the Recurrence Interval (RI), which is the average interval in years between occurrences of two discharges of equal magnitude; and the Weibull equation, which calculates the probability that a given discharge will be exceeded in any particular year. The student then accesses historical data on U.S. stream flow and performs these calculations independently.

Huff, Warren

2000-11-03

359

Midwest Flooding Disaster: Rethinking Federal Flood Insurance. CRS Report for Congress.  

National Technical Information Service (NTIS)

Historically, floods have caused more economic loss to the nation than any other form of natural disaster. In 1968, Congress created the National Flood Insurance Program (NFIP) in response to rising flood losses and escalating costs resulting from ad-hoc ...

R. O. King

2008-01-01

360

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

361

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

Code of Federal Regulations, 2013 CFR

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

2013-10-01

362

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

363

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

364

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

365

A multi-spectral spatial convolution approach of rainfall forecasting using weather satellite imagery  

Microsoft Academic Search

Flood forecasting has long been a major topic of hydrologic research. Recent events and studies indicate that the success of flood forecasting in Taiwan depends heavily on the accuracy of real-time rainfall forecasting. In this study, we demonstrate a multi-spectral spatial convolution approach for real-time rainfall forecasting using geostationary weather satellite images. The approach incorporates cloud-top temperatures of three infrared

Chiang Wei; Wei-Chun Hung; Ke-Sheng Cheng

2006-01-01

366

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

367

Flooding in West Africa: An ASMET Project  

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 MSC 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 thermodynamic features that drive convective activities in West Africa.

2012-01-11

368

Prediction and Forecasting  

NSDL National Science Digital Library

The National Center for Atmospheric Research (NCAR) has compiled this excellent site containing information on "meteorology, weather, and prediction". Visitors to the site can peruse NCAR information by topic. Some of the topics on the site include: short-term weather forecasting, precipitation, and severe storm prediction among others. This is an excellent resource for students, teachers, and anyone who is interested in learning about weather and weather forecasting from a highly respected site.

2008-03-27

369

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

370

Forecasting of short-term rainfall using ARMA models  

Microsoft Academic Search

Burlando, P., Rosso, R., Cadavid, L.G. and Salas, J.D., 1993. Forecasting of short-term rainfall using ARMA models. J. Hydrol., 144: 193-211. Flood forecasting depends essentially on forecasting of rainfall or snow melt. In this paper, rainfall forecasting is approached assuming that hourly rainfall follows an autoregressive moving average (ARMA) process. This assumption is based on the fact that the autocovariance

Paolo Burlando; Renzo Rosso; Luis G. Cadavid; Jose D. Salas

1993-01-01

371

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

372

Forecasting Flu  

MedlinePLUS

... flu forecasting follows a similar, but more accelerated, evolution." Forecasting the Peak To first test the concept ... Getting a Better Grasp on Flu Fundamentals Everyday Evolution What Drives Seasonal Flu Patterns? This Inside Life ...

373

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.

374

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

375

Weather Forecasting  

NSDL National Science Digital Library

Students consider how weather forecasting plays an important part in their daily lives. They learn about the history of weather forecasting â from old weather proverbs to modern forecasting equipment â and how improvements in weather technology have saved lives by providing advance warning of natural hazards.

Integrated Teaching And Learning Program

376

River Forecasting Case Study  

NSDL National Science Digital Library

This module takes the learner through the considerations for the river forecasting decisions associated with the remnants of Hurricane Ivan on 17-19 September, 2004 for the Susquehanna River system in Pennsylvania and New York. The module assists the learner with applying the concepts covered in the foundation topics of the Basic Hydrologic Sciences course. Some of the specific topics pertinent to this case are soil conditions, the impact of QPF on runoff, runoff models, runoff processes, routed flow and stage-discharge relationships. Observations of upstream conditions and comparisons to historic crests are also examined to assist with operational flood forecast decisions. The core foundation topics are recommended as a prerequisite since this module assumes some pre-existing knowledge of hydrologic principles.

Spangler, Tim

2007-06-12

377

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

378

Flood-inundation maps for Suwanee Creek from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, Gwinnett County, Georgia  

USGS Publications Warehouse

Digital flood-inundation maps for a 6.9-mile reach of Suwanee Creek, from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, were developed by the U.S. Geological Survey (USGS) in cooperation with Gwinnett County, Georgia. 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 Suwanee Creek at Suwanee, Georgia (02334885). Current stage at this USGS streamgage may be obtained at http://waterdata.usgs.gov/ and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood-warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that commonly are collocated at USGS streamgages. The forecasted peak-stage information for the USGS streamgage at Suwanee Creek at Suwanee (02334885), available through the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC-RAS software for Suwanee Creek and was used to compute flood profiles for a 6.9-mile reach of the creek. The model was calibrated using the most current stage-discharge relations at the Suwanee Creek at Suwanee streamgage (02334885). The hydraulic model was then used to determine 19 water-surface profiles for flood stages at the Suwanee Creek streamgage at 0.5-foot intervals referenced to the streamgage. The profiles ranged from just above bankfull stage (7.0 feet) to approximately 1.7 feet above the highest recorded water level at the streamgage (16.0 feet). 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 5.0-foot horizontal resolution - to delineate the area flooded for each 0.5-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.

Musser, Jonathan W.

2012-01-01

379

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

380

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

USGS Publications Warehouse

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

Kelly, Brian P.; Rydlund, Paul H., Jr.

2006-01-01

381

Predictive Uncertainty in Hydrological Forecasting  

NASA Astrophysics Data System (ADS)

This work aims at discussing the role and the relevance of "predictive uncertainty" in flood forecasting and water resources management . Predictive uncertainty, is here defined as the probability of occurrence of a future value of a predictand (such as water level, discharge or water volume) conditional on prior observations and knowledge as well as on all the information we can obtain on that specific future value, which is typically embodied in one or more hydrological /hydraulic model forecasts. The aim of this work is also to clarify questions such as: What is the conceptual difference between "total model uncertainty" (commonly used when dealing with model verification) from the predictive uncertainty (which is used when forecasting into the future)? What is the difference between models, parameters, input output measurement errors, initial and boundary conditions, etc. uncertainty and predictive uncertainty? How one can incorporate all these uncertainties into the predictive uncertainty and, most of all, is it really necessary? The presently available uncertainty processors are then introduced and compared on the basis of their relative performances using operational flood forecasting systems. The uncertainty processors can be continuous (Hydrologic Uncertainty Processor, Bayesian Model Averaging, Model Conditional Processor, etc.) or binary ( Logistic Regression, Binary Multivariate Bayesian Processor, etc.) depending on the scope for which they are developed and the type of decision one must take. Finally, the benefits of incorporating predictive uncertainty into the decision making process will be compared, on actual real world derived examples, to the ones obtainable when using deterministic forecasts, as currently done in practice.

Todini, E.

2009-04-01

382

Method of DEM Data's Processing in Flood Simulation System  

Microsoft Academic Search

Flood simulation and forecasting is a hot topic of flood disaster research. DEM as the basic data plays a crucial role in the field. High resolution grid DEM data is able to supply exact terrain model to this work, but it brings on a bothering problem that the data is too big to reduce running efficiency in computer. Facing the

Sun Hai; Wang Cheng; Ren Bo

2008-01-01

383

Efficient and effective? the hundred year flood in the communication and perception of flood risk  

Microsoft Academic Search

In response to the rising costs of floods, the United States has adopted sophisticated programs to mitigate the loss of life and property. However, the efficient implementation of certain aspects of flood policy has taken precedence over effective communication. The scope of the National Flood Insurance Program and the efficient coding of \\

Heather Bell

2004-01-01

384

Comparison of Canadian Forest Fire Danger Rating System and National Fire Danger Rating System fire indices derived from Weather Research and Forecasting (WRF) model data for the June 2005 Interior Alaska wildfires  

NASA Astrophysics Data System (ADS)

Standard indices of the National Fire Danger Rating System (NFDRS) and Canadian Forest Fire Danger Rating System (CFFDRS) are calculated from Weather Research and Forecasting (WRF) model forecasts and observations in Interior Alaska for June 2005. Fire indices determined from WRF results of all forecast-leads and the ensemble do not differ statistically significantly from those calculated from observations. WRF-derived CFFDRS and NFDRS fire indices capture the temporal evolution of fire indices calculated from observations acceptably. Sensitivity to errors in meteorological forecasts differs for the various fire indices. Failure to predict a peak does not necessarily occur at the same time for the various indices within and/or among the two systems. Predicted buildup-index and spread component capture trends, the time of peaks and minima most reliably. Overall for the CFFDRS the lowest relative errors exist for fine fuel moisture content followed by buildup-index while for the NFDRS the lowest relative errors occur for energy release component followed by burning index. When fire indices are calculated from meteorological forecasts predicting fire risk and identifying the right site becomes more difficult as fire risk increases. Fire risk forecast skill depends on meteorological forecast-lead slightly for energy release rate and ignition component and notably for all CFFDRS-indices except fine fuel moisture content.

Mölders, Nicole

2010-02-01

385

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

386

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

387

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

Code of Federal Regulations, 2013 CFR

...Requirement to be covered by a contract for flood insurance by June 1, 1988. 63...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IMPLEMENTATION OF SECTION 1306(c) OF THE NATIONAL FLOOD INSURANCE ACT OF 1968 General...

2013-10-01

388

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

389

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

390

An empirical method for estimating future flood risks for flood warnings  

Microsoft Academic Search

Since medium and long-term precipitation forecasts are still not reliable enough, rough estimates of the degree of the extremity of forthcoming flood events that might occur in the course of dangerous meteorological situations approaching a basin could be useful to decision-makers as additional information for flood warnings. One approach to answering such a problem is to use real-time data on

H. Hlavcova; S. Kohnova; R. Kubes; J. Szolgay; M. Zvolensky

2005-01-01

391

44 CFR 65.6 - Revision of base flood elevation determinations.  

Code of Federal Regulations, 2010 CFR

...2010-10-01 false Revision of base flood elevation determinations. 65.6 Section...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program IDENTIFICATION AND...HAZARD AREAS § 65.6 Revision of base flood elevation determinations. (a)...

2010-10-01

392

44 CFR 59.22 - Prerequisites for the sale of flood insurance.  

Code of Federal Regulations, 2010 CFR

... false Prerequisites for the sale of flood insurance. 59.22 Section 59.22...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program GENERAL PROVISIONS...59.22 Prerequisites for the sale of flood insurance. (a) To qualify for...

2010-10-01

393