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1

Application of data-based mechanistic modelling for flood forecasting at multiple locations in the Eden catchment in the National Flood Forecasting System (England and Wales)  

NASA Astrophysics Data System (ADS)

The Delft Flood Early Warning System provides a versatile framework for real-time flood forecasting. The UK Environment Agency has adopted the Delft framework to deliver its National Flood Forecasting System. The Delft system incorporates new flood forecasting models very easily using an "open shell" framework. This paper describes how we added the data-based mechanistic modelling approach to the model inventory and presents a case study for the Eden catchment (Cumbria, UK).

Leedal, D.; Weerts, A. H.; Smith, P. J.; Beven, K. J.

2013-01-01

2

OPERATIONAL FLOOD FORECAST IN BAVARIA  

Microsoft Academic Search

The structure and organisation of the Bavarian flood information service is introduced with focus on the operational flood forecast. Five flood forecast centres corresponding to the main river basins (Main, Danube, Inn) and tributary basins where large reservoirs have to be operated (Iller-Lech, Isar) are responsible for the operational flood forecast. They closely co-operate with the co-ordinating main flood information

Christine Hangen-Brodersen; Alfons Vogelbacher; Franz-Klemens Holle

3

Improving Flood Forecasting in International River Basins  

Microsoft Academic Search

In flood-prone international river basins (IRBs), many riparian nations that are located close to a basin's outlet face a major problem in effectively forecasting flooding because they are unable to assimilate in situ rainfall data in real time across geopolitical boundaries. NASA's proposed Global Precipitation Measurement (GPM) mission, which is expected to begin in 2010, will comprise high-resolution passive microwave

Faisal Hossain; Nitin Katiyar

2006-01-01

4

Flood Forecasting Case Study: International Edition  

NSDL National Science Digital Library

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

COMET

2011-05-17

5

Forecasting Flash Floods with an Operational Model  

Microsoft Academic Search

The flash flood forecasting model ALHTAÏR (“Alarme Hydrologique Territoriale Automatisée par Indicateur de Risque”) has been\\u000a developed during the last five years by the flood-warning service of the Gard Region (SAC-30), in the South-East of France.\\u000a A spatial version for the flash flood forecasting model is described in this paper. This flash flood forecasting model is\\u000a divided in three separate

P. A. Ayral; S. Sauvagnargues-Lesage; S. Gay; F. Bressand

6

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

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

Local flood forecasting - From data collection to communicating forecasts  

NASA Astrophysics Data System (ADS)

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

Smith, P. J.; Beven, K.

2013-12-01

10

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

NASA Astrophysics Data System (ADS)

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

Bao, Hongjun; Zhao, Linna

2012-02-01

11

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

12

A comparison of nonlinear flood forecasting methods  

NASA Astrophysics Data System (ADS)

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

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

2003-05-01

13

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

Microsoft Academic Search

Czech Hydrometeorological Institute (CHMI) is responsible for flood forecasting and warning in the Czech Republic. To meet that issue CHMI operates hydrological forecasting systems and publish flow forecast in selected profiles. Flood forecast and warning is an output of system that links observation (flow and atmosphere), data processing, weather forecast (especially NWP's QPF), hydrological modeling and modeled outputs evaluation and

Jan Danhelka; Tomas Vlasak

2010-01-01

14

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

E-print Network

of flood warnings and forecasts through the introduction of new technology, specialist training and more and alarms. More than one hundred shared data systems are now operating and the technology has recently been useful because it allows local emergency authorities and people in the flood threatened zone to determine the a

Greenslade, Diana

15

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

16

Interactive Forecasting with the National Weather Service River Forecast System  

NASA Technical Reports Server (NTRS)

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

Smith, George F.; Page, Donna

1993-01-01

17

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

18

Real-time application of meteorological ensembles for Danube flood forecasting  

NASA Astrophysics Data System (ADS)

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

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

2009-04-01

19

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

Microsoft Academic Search

Operational flood forecasting requires accurate forecasts with a suitable lead time, in order to be able to issue appropriate warnings and take appropriate emergency actions. Recent improvements in both flood plain characterization and computational capabilities have made the use of distributed flood inundation models more common. However, problems remain with the application of such models. There are still uncertainties associated

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

2008-01-01

20

Application and improvement of BFS in Flood forecasting  

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

21

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

Microsoft Academic Search

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

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

2005-01-01

22

The National Collegiate Forecasting Contest  

NSDL National Science Digital Library

This undergraduate meteorology tutorial from Texas A&M University explains the basic rules of the National Collegiate Weather Forecasting Contest, the procedure for entering a forecast, and a technique for converting from Greenwich Time to local time.

John Nielsen-Gammon

1996-01-01

23

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

NASA Astrophysics Data System (ADS)

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

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

2010-09-01

24

Accounting for uncertainty in distributed flood forecasting models  

Microsoft Academic Search

Recent research investigating the uncertainty of distributed hydrological flood forecasting models will be presented. These findings utilise the latest advances in rainfall estimation, ensemble nowcasting and Numerical Weather Prediction (NWP). The hydrological flood model that forms the central focus of the study is the Grid-to-Grid Model or G2G: this is a distributed grid-based model that produces area-wide flood forecasts across

Steven J. Cole; Alice J. Robson; Victoria A. Bell; Robert J. Moore; Clive E. Pierce; Nigel Roberts

2010-01-01

25

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

26

A reservoir flood forecasting and control system for China  

Microsoft Academic Search

Reservoirs play a vital role in flood prevention and disaster relief in China. The objectives of the project described in this study were to establish a reservoir flood forecasting and control system and to design and develop corresponding application software. This paper introduces the current reservoir flood control and operation practice with this system in China. Using modern integration technologies,

SHENGLIAN GUO; HONGGANG ZHANG; HUA CHEN; DINGZHI PENG; PAN LIU; BO PANG

27

Operational flood forecasting system of Umbria Region "Functional Centre  

NASA Astrophysics Data System (ADS)

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

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

2009-04-01

28

Guest column: Improve flood forecasting Des Moines Register, June 22, 2008  

E-print Network

conditions and what happened during past flood events. In the longer term, flood forecasts for a day or soGuest column: Improve flood forecasting Des Moines Register, June 22, 2008 by Kristie Franz The recent flooding in Iowa may have some people wondering: How are flood forecasts made, are they any good

Debinski, Diane M.

29

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

NASA Astrophysics Data System (ADS)

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

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

2015-01-01

30

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

31

Semiempirical mixed statistical flood forecasting for the Mekong River  

Microsoft Academic Search

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

Muhammad Khurram Shahzad; Jürgen Ihringer; Erich J. Plate

2010-01-01

32

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

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

Forecasting Severe Floods for the Meghna River Basin  

NASA Astrophysics Data System (ADS)

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

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

2010-12-01

35

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

NASA Astrophysics Data System (ADS)

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

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

2010-05-01

36

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

NASA Astrophysics Data System (ADS)

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

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

2015-02-01

37

Flood forecasting for River Mekong with data-based models  

NASA Astrophysics Data System (ADS)

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

Shahzad, Khurram M.; Plate, Erich J.

2014-09-01

38

An Open-Book Modular Watershed Modeling Framework for Rapid Prototyping of GPM- based Flood Forecasting in International River Basins  

Microsoft Academic Search

Floods have always been disastrous for human life. It accounts for about 15 % of the total death related to natural disasters. There are around 263 transboundary river basins listed by UNESCO, wherein at least 30 countries have more than 95% of their territory locked in one or more such transboundary basins. For flood forecasting in the lower riparian nations

N. Katiyar; F. Hossain

2006-01-01

39

Discriminant Flash-Flood Forecasting in an Urban Environment  

NASA Astrophysics Data System (ADS)

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

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

2003-12-01

40

The european flood alert system EFAS - Part 2: Statistical skill assessment of probabilistic and deterministic operational forecasts  

NASA Astrophysics Data System (ADS)

Since 2005 the European Flood Alert System (EFAS) has been producing probabilistic hydrological forecasts in pre-operational mode at the Joint Research Centre (JRC) of the European Commission. EFAS aims at increasing preparedness for floods in trans-national European river basins by providing medium-range deterministic and probabilistic flood forecasting information, from 3 to 10 days in advance, to national hydro-meteorological services. This paper is Part 2 of a study presenting the development and skill assessment of EFAS. In Part 1, the scientific approach adopted in the development of the system has been presented, as well as its basic principles and forecast products. In the present article, two years of existing operational EFAS forecasts are statistically assessed and the skill of EFAS forecasts is analysed with several skill scores. The analysis is based on the comparison of threshold exceedances between proxy-observed and forecasted discharges. Skill is assessed both with and without taking into account the persistence of the forecasted signal during consecutive forecasts. Skill assessment approaches are mostly adopted from meteorology and the analysis also compares probabilistic and deterministic aspects of EFAS. Furthermore, the utility of different skill scores is discussed and their strengths and shortcomings illustrated. The analysis shows the benefit of incorporating past forecasts in the probability analysis, for medium-range forecasts, which effectively increases the skill of the forecasts.

Bartholmes, J. C.; Thielen, J.; Ramos, M. H.; Gentilini, S.

2009-02-01

41

Improving real time flood forecasting using fuzzy inference system  

NASA Astrophysics Data System (ADS)

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

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

2014-02-01

42

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

43

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

NASA Astrophysics Data System (ADS)

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

Silvestro, Francesco; Rebora, Nicola

2014-11-01

44

PROBABILISTIC FLOOD FORECASTING USING A DISTRIBUTED RAINFALL-RUNOFF MODEL  

E-print Network

PROBABILISTIC FLOOD FORECASTING USING A DISTRIBUTED RAINFALL-RUNOFF MODEL PAUL JAMES SMITH 2005 #12., for their assistance regarding rainfall- runoff modeling, and to Yoshiyuki Zushi of the Foundation of River and Basin...................................................................................................... 1 2. DISTRIBUTED RAINFALL-RUNOFF MODELING.............................................. 3 2

Fernandez, Thomas

45

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

46

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

47

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

48

Probabilistic flood forecast: Exact and approximate predictive distributions  

NASA Astrophysics Data System (ADS)

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

Krzysztofowicz, Roman

2014-09-01

49

Efficiency of raster-based real time flood forecasting models  

NASA Astrophysics Data System (ADS)

In 1990, the state of Baden-Wuerttemberg (Germany) established a flood forecast centre in order to be able to forecast floods on the river Rhine and other large rivers within the state boundaries. Since this time, the necessary flood forecast models have been developed and continuously improved by Ludwig Consultant Engineers. In the meantime, we also support the flood forecast centres of the states of Rhineland-Palatinate and Bavaria. The conceptual, physically based LARSIM model, created by our office, is used for a large variety of tasks associated with flood forecasting within these three states. Therefore, required adjustments and further developments of the model can be achieved in direct contact with state officials and the administration. In addition, we developed programs for pre- and postprocessing of the data as well as visualisation tools necessary for the operational use. The required input data of the model (beside the measured discharge and precipitation data) is the 48 h precipitation forecast of the German Weather Service (spatial resolution: 7 km x 7 km grid). Snow accumulation and snow melt can also be considered as well as artificial influences (e.g. storage basins, diversions or water transfer between different basins). A raster based model structure with a spatial resolution of 1 km x 1 km was chosen for the discretisation of the catchments. Length and gradients of the rivers and the river network were determined with the help of GIS tools. For each 1 km2 raster cell the runoff generation within the area as well as the flood routing in the river channels can be calculated. Up to now, these high resolution models were established covering an area of approx. 85.000 km2 (including the catchments of the Moselle (approx. 30.000 km2), the Danube (up to gauge Schwabelwies, approx. 25.000 km 2), the Neckar (approx. 14.000 km 2) and other catchments in Baden-Wuerttemberg). The use of 1 km2 raster cells offers several advantages like e.g. flexible discretisation of the catchment according to the available gauges or inclusion of high resolution radar precipitation data. In addition, LARSIM can also be applied as a water balance model for the continuous simulation of the water cycle which requires a high spatial resolution. The experiences of the operational application of the raster based 1 km2 models will be presented in terms of their practical use and in terms of their performances meeting the users' requirements.

Gerlinger, K.

2003-04-01

50

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

51

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

52

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

53

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

54

Application of a Bayesian Processor for Predictive Uncertainty Assessment in Real Time Flood Forecasting  

Microsoft Academic Search

The work aims at presenting and discussing the results of a Bayesian method, the Model Conditional Processor (MCP), for assessing predictive uncertainty in real time flood forecasting. Real time flood forecasting requires taking into account predictive uncertainty due to a number of reasons. Deterministic hydrological\\/hydraulic forecasts give useful information about real future events, but they can't be taken and used

Gabriele Coccia; Felix Francés; Juan Camilo Múnera; Ezio Todini

2010-01-01

55

Consensus Seasonal Flood Forecasts and Warning Response System (FFWRS): an alternate for nonstructural flood management in Bangladesh.  

PubMed

Despite advances in short-range flood forecasting and information dissemination systems in Bangladesh, the present system is less than satisfactory. This is because of short lead-time products, outdated dissemination networks, and lack of direct feedback from the end-user. One viable solution is to produce long-lead seasonal forecasts--the demand for which is significantly increasing in Bangladesh--and disseminate these products through the appropriate channels. As observed in other regions, the success of seasonal forecasts, in contrast to short-term forecast, depends on consensus among the participating institutions. The Flood Forecasting and Warning Response System (henceforth, FFWRS) has been found to be an important component in a comprehensive and participatory approach to seasonal flood management. A general consensus in producing seasonal forecasts can thus be achieved by enhancing the existing FFWRS. Therefore, the primary objective of this paper is to revisit and modify the framework of an ideal warning response system for issuance of consensus seasonal flood forecasts in Bangladesh. The five-stage FFWRS-i) Flood forecasting, ii) Forecast interpretation and message formulation, iii) Warning preparation and dissemination, iv) Responses, and v) Review and analysis-has been modified. To apply the concept of consensus forecast, a framework similar to that of the Southern African Regional Climate Outlook Forum (SARCOF) has been discussed. Finally, the need for a climate Outlook Fora has been emphasized for a comprehensive and participatory approach to seasonal flood hazard management in Bangladesh. PMID:15940404

Chowdhury, Rashed

2005-06-01

56

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.

57

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

58

Flood forecasting using medium-range probabilistic weather prediction Hydrology and Earth System Sciences, 9(4), 365380 (2005) EGU  

E-print Network

Flood forecasting using medium-range probabilistic weather prediction 365 Hydrology and Earth System Sciences, 9(4), 365380 (2005) © EGU Flood forecasting using medium-range probabilistic weather the developments in short- and medium-range weather forecasting over the last decade, operational flood forecasting

Paris-Sud XI, Université de

59

Artificial neural network approach to flood forecasting in the River Arno  

Microsoft Academic Search

The basin of the River Arno is a flood-prone area where flooding events have caused damage valued at more than 100 billion euro in the last 40 years. At present, the occurrence of an event similar to the 1966 flood of Firenze (Florence) would result in damage costing over 15.5 billion euro. Therefore, the use of flood forecasting and early

MARINA CAMPOLO; ALFREDO SOLDATI; PAOLO ANDREUSSI

2003-01-01

60

Karst flash-flood forecasting in the city of Nmes1 (southern France)2  

E-print Network

conditions prior to the flood event are the main factors involved in karst39 flood generation. Considering1 Karst flash-flood forecasting in the city of Nîmes1 (southern France)2 Fleury, P., Maréchal, J ABSTRACT5 In southern France, karst flash-floods may be the result of two, potentially cumulative,6

Paris-Sud XI, Université de

61

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

62

A soil moisture sensorweb for use in flood forecasting applications  

NASA Astrophysics Data System (ADS)

This paper describes work towards building an integrated Earth sensing capability and focuses on the demonstration of a prototype in-situ sensorweb in remote operation in support of flood forecasting. A five-node sensorweb was deployed in the Roseau River Sub-Basin of the Red River Watershed in Manitoba, Canada in September 2002 and remained there throughout the flood season until the end of June 2003. The sensorweb operated autonomously, with soil moisture measurements and standard meteorological parameters accessed remotely via land line and/or satellite from the Integrated Earth Sensing Workstation (IESW) at the Canada Centre for Remote Sensing (CCRS) in Ottawa. Independent soil moisture data were acquired from actual grab samples and field-portable sensors on the days of RADARSAT and Envisat Synthetic Aperture Radar (SAR) data acquisitions. The in-situ data were used to help generate spatial soil moisture estimates from the remotely sensed SAR data for use in a hydrological model for flood forecasting.

Teillet, Philippe M.; Gauthier, Robert P.; Pultz, Terry J.; Deschamps, A.; Fedosejevs, Gunar; Maloley, Matthew; Ainsley, Gino; Chichagov, Alexander

2004-02-01

63

Developing a Web-based flood forecasting system for reservoirs with J2EE  

Microsoft Academic Search

A flood forecasting system is a crucial component in flood mitigation. For certain important large-scale reservoirs, cooperation and communication among federal, state, and local stakeholders are required when heavy flood events are en- countered. The Web-based environment is emerging as a very important development and delivery platform for real-time flood forecasting systems. In this paper, the findings of a case

CHUN-TIAN CHENG; K. W. CHAU; XIANG-YANG LI

2005-01-01

64

Assessing uncertainties in flood forecasts for decision making: prototype of an operational flood management system integrating ensemble predictions  

Microsoft Academic Search

Ensemble forecasts aim at framing the uncertainties of the potential future development of the hydro-meteorological situation. A probabilistic evaluation can be used to communicate forecast uncertainty to decision makers. Here an operational system for ensemble based flood forecasting is presented, which combines forecasts from the European COSMO-LEPS, SRNWP-PEPS and COSMO-DE prediction systems. A multi-model lagged average super-ensemble is generated by

J. Dietrich; A. H. Schumann; M. Redetzky; J. Walther; M. Denhard; Y. Wang; B. Pfützner; U. Büttner

2009-01-01

65

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

NASA Astrophysics Data System (ADS)

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

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

2013-02-01

66

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

67

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

68

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

69

National Air Quality Forecast Capability Ivanka Stajner  

E-print Network

) · These meteorological predictions are used for all air quality predictions (October 2011) Ozone - Substantial emissionNational Air Quality Forecast Capability Ivanka Stajner NOAA NWS/OST with contributions from AQAST meeting, College Park, MD June 5, 2013 #12;National Air Quality Forecast Capability Capabilities

Jacob, Daniel J.

70

Thirty Years of Flood Forecasting with John Schaake: Latest Advances in Distributed Modeling  

Microsoft Academic Search

John Schaake must be one of the most versatile hydrologists anywhere. Over his long career John has dealt with everything from urban hydrology to climate change. Throughout that trajectory he has always maintained an avid interest in the very real and pragmatic problem of flood forecasting. This paper briefly discusses modern distributed models for flood forecasting in the context of

R. L. Bras; E. R. Vivoni; V. Y. Ivanov

2001-01-01

71

Web-based hydrological modeling system for flood forecasting and risk mapping  

Microsoft Academic Search

Mechanism of flood forecasting is a complex system, which involves precipitation, drainage characterizes, land use\\/cover types, ground water and runoff discharge. The application of flood forecasting model require the efficient management of large spatial and temporal datasets, which involves data acquisition, storage, pre-processing and manipulation, analysis and display of model results. The extensive datasets usually involve multiple organizations, but no

Lei Wang; Qiuming Cheng

2008-01-01

72

Forecasting of Storm Surge Floods Using ADCIRC and Optimized DEMs  

NASA Technical Reports Server (NTRS)

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

Valenti, Elizabeth; Fitzpatrick, Patrick

2005-01-01

73

A Simple Flood Forecasting Scheme Using Wireless Sensor Networks  

E-print Network

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

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

2012-01-01

74

Flood Hazards - A National Threat  

USGS Publications Warehouse

In the late summer of 2005, the remarkable flooding brought by Hurricane Katrina, which caused more than $200 billion in losses, constituted the costliest natural disaster in U.S. history. However, even in typical years, flooding causes billions of dollars in damage and threatens lives and property in every State. Natural processes, such as hurricanes, weather systems, and snowmelt, can cause floods. Failure of levees and dams and inadequate drainage in urban areas can also result in flooding. On average, floods kill about 140 people each year and cause $6 billion in property damage. Although loss of life to floods during the past half-century has declined, mostly because of improved warning systems, economic losses have continued to rise due to increased urbanization and coastal development.

U.S. Geological Survey

2006-01-01

75

A Modeling Approach for Flash Flood Forecasting for Small Watersheds in Iowa  

NASA Astrophysics Data System (ADS)

Current flood predictions are limited by often out-dated statistical guidance and a rigid modeling system that seldom accounts for basin-specific hydrologic response times. The National Weather Service (NWS) SACramento Soil Moisture Accounting Model (SACSMA), which is used to generate short-range (1-7 days) streamflow forecasts, is most commonly run at a 6-hour timestep. The 6-hour timestep can be inadequate for capturing flood crests in small watersheds (<1500 km2) with 6-12 hour response times. Flood warnings and watches are issued according to Flash Flood Guidance (FFG). FFG is based on statistical relationships between historical streamflow observations, antecedent precipitation and rain rates, and is seldom updated. Modern hydrologic modeling techniques may improve flood forecasting accuracy and lead time in small watersheds. In this study, we apply the US Army Corps Hydrologic Engineering Center-Hydrological Modeling System (HEC-HMS) to small forecast basins in central Iowa to test the feasibility of using the HEC-HMS in real-time at the Des Moines Weather Forecast Office (DMX). The watershed is configured in a semi- distributed, event-based manner, using the Green and Ampt infiltration model and Muskingum routing. Basin specific soil parameters are estimated from historical simulations from the Water Erosion Prediction Project (WEPP) model, which is run by Iowa State University's Daily Erosion Project. Additional model parameters are found via GIS and automatic and manual calibration methods. The model is driven by basin-average precipitation estimates obtained from the University of Iowa Hydro-NEXRAD system (based on a 1.0km CAPPI height and simple bias correction). Initial soil moisture estimates are derived from the WEPP product. Input uncertainties, based on radar data analysis, are carried through the operational modeling process to find lower and upper uncertainty bounds for every forecast. Preliminary analysis of the parameters derived from the WEPP product and initial model runs indicate that adjustment of soil surface parameters require continual adjustment throughout the spring and summer season in this highly managed landscape. Future work will include expansion of the current analysis to additional watersheds, and evaluation by NWS personnel at the DMX for operational potential.

Lincoln, W. S.; Franz, K. J.

2008-12-01

76

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

Microsoft Academic Search

Weather radar, in combination with a distributed rainfall-runoff model, promises to significantly improve real-time flood forecasting. This paper investigates the value of radar-derived precipitation in forecasting streamflow in the Sieve River basin, near Florence, Italy. The basin is modeled with a distributed rainfall-runoff model that exploits topographic information available from digital elevation maps. The sensitivity of the flood forecast to

Marcos L. Pessoa; Rafael L. Bras; Earle R. Williams

1993-01-01

77

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

E-print Network

forecasting problem poses unique challenges because of the frequent life-threatening flooding of the country initialized by NASA and NOAA precipitation products, whose states and fluxes are forecasted forward using information for water re- source management, agriculture practice optimization, and disaster mitigation

Webster, Peter J.

78

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

79

Coupling ensemble weather predictions based on TIGGE database with Grid-Xinanjiang model for flood forecast  

NASA Astrophysics Data System (ADS)

The incorporation of numerical weather predictions (NWP) into a flood forecasting system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and lead to a high number of false alarms. The availability of global ensemble numerical weather prediction systems through the THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for flood forecast. The Grid-Xinanjiang distributed hydrological model, which is based on the Xinanjiang model theory and the topographical information of each grid cell extracted from the Digital Elevation Model (DEM), is coupled with ensemble weather predictions based on the TIGGE database (CMC, CMA, ECWMF, UKMO, NCEP) for flood forecast. This paper presents a case study using the coupled flood forecasting model on the Xixian catchment (a drainage area of 8826 km2) located in Henan province, China. A probabilistic discharge is provided as the end product of flood forecast. Results show that the association of the Grid-Xinanjiang model and the TIGGE database gives a promising tool for an early warning of flood events several days ahead.

Bao, H.-J.; Zhao, L.-N.; He, Y.; Li, Z.-J.; Wetterhall, F.; Cloke, H. L.; Pappenberger, F.; Manful, D.

2011-02-01

80

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

81

National Flood Risk Management Planning Center of Expertise  

E-print Network

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

US Army Corps of Engineers

82

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

NASA Astrophysics Data System (ADS)

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

Liu, Jia; Bray, Michaela; Han, Dawei

2014-05-01

83

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

84

Accounting for Uncertainties in Generating Reliable Probabilistic Flood Forecasts for Bangladesh  

NASA Astrophysics Data System (ADS)

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

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

2007-12-01

85

Understanding uncertainty in distributed flash flood forecasting for semiarid regions 1909  

Technology Transfer Automated Retrieval System (TEKTRAN)

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

86

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

E-print Network

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

Ding, Wei

87

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

88

Real-time flood forecasting by employing artificial neural network based model with zoning matching approach  

NASA Astrophysics Data System (ADS)

Flood forecasting models are a necessity, as they help in planning for flood events, and thus help prevent loss of lives and minimize damage. At present, artificial neural networks (ANN) have been successfully applied in river flow and water level forecasting studies. ANN requires historical data to develop a forecasting model. However, long-term historical water level data, such as hourly data, poses two crucial problems in data training. First is that the high volume of data slows the computation process. Second is that data training reaches its optimal performance within a few cycles of data training, due to there being a high volume of normal water level data in the data training, while the forecasting performance for high water level events is still poor. In this study, the zoning matching approach (ZMA) is used in ANN to accurately monitor flood events in real time by focusing the development of the forecasting model on high water level zones. ZMA is a trial and error approach, where several training datasets using high water level data are tested to find the best training dataset for forecasting high water level events. The advantage of ZMA is that relevant knowledge of water level patterns in historical records is used. Importantly, the forecasting model developed based on ZMA successfully achieves high accuracy forecasting results at 1 to 3 h ahead and satisfactory performance results at 6 h. Seven performance measures are adopted in this study to describe the accuracy and reliability of the forecasting model developed.

Sulaiman, M.; El-Shafie, A.; Karim, O.; Basri, H.

2011-10-01

89

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

NASA Astrophysics Data System (ADS)

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

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

2014-06-01

90

Assessing uncertainties in flood forecasts for decision making: prototype of an operational flood management system integrating ensemble predictions  

NASA Astrophysics Data System (ADS)

Ensemble forecasts aim at framing the uncertainties of the potential future development of the hydro-meteorological situation. A probabilistic evaluation can be used to communicate forecast uncertainty to decision makers. Here an operational system for ensemble based flood forecasting is presented, which combines forecasts from the European COSMO-LEPS, SRNWP-PEPS and COSMO-DE prediction systems. A multi-model lagged average super-ensemble is generated by recombining members from different runs of these meteorological forecast systems. A subset of the super-ensemble is selected based on a priori model weights, which are obtained from ensemble calibration. Flood forecasts are simulated by the conceptual rainfall-runoff-model ArcEGMO. Parameter uncertainty of the model is represented by a parameter ensemble, which is a priori generated from a comprehensive uncertainty analysis during model calibration. The use of a computationally efficient hydrological model within a flood management system allows us to compute the hydro-meteorological model chain for all members of the sub-ensemble. The model chain is not re-computed before new ensemble forecasts are available, but the probabilistic assessment of the output is updated when new information from deterministic short range forecasts or from assimilation of measured data becomes available. For hydraulic modelling, with the desired result of a probabilistic inundation map with high spatial resolution, a replacement model can help to overcome computational limitations. A prototype of the developed framework has been applied for a case study in the Mulde river basin. However these techniques, in particular the probabilistic assessment and the derivation of decision rules are still in their infancy. Further research is necessary and promising.

Dietrich, J.; Schumann, A. H.; Redetzky, M.; Walther, J.; Denhard, M.; Wang, Y.; Pfützner, B.; Büttner, U.

2009-08-01

91

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

92

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

93

The potential of remotely sensed soil moisture for operational flood forecasting  

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

94

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

NASA Astrophysics Data System (ADS)

In South Africa, five flood events during the period 1994-1996 resulted in the loss of 173 lives, more than 7000 people requiring evacuation and/or emergency shelter and damages to the value of R680 million (White paper on Disaster Management 1998). The South African Disaster management bill provides for "...preventing or reducing the risk of disasters, mitigating the severity of disasters ...". To this end a pilot study funded by the Water Research Commission aims at providing flood forecasts for the Mgeni and Mlazi catchments near the city of Durban in South Africa. The importance and usefulness of flood forecasting is particularly evident in an urban context where the density of population and infrastructure provide great potential for disaster. A reliable flood warning or forecasting system cannot prevent the occurrence of floods, but provides a key tool that can allow decision makers to be proactive rather than reactive in their response to a flooding event. Taking preventative measures before the fact can significantly reduce the social and economic impacts associated with a disaster. The flood forecasting system described here makes use of a "best estimate" spatial rainfield (obtained by combining radar and telemetered rain gauge rainfall estimates) as input to a linear catchment model. The catchment model parameters are dynamically updated in response to measured streamflows using Kalman filtering techniques, allowing improved forecasts of streamflow as the catchment conditions change. Precomputed flood lines and a graphical representation of the spatial rainfield are dynamically displayed on a GIS in the Durban disaster management control center enabling Disaster Managers to be proactive in times of impending floods.

Sinclair, Scott; Pegram, Geoff

2003-04-01

95

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

NASA Technical Reports Server (NTRS)

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

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

2004-01-01

96

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

NASA Astrophysics Data System (ADS)

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

Pagano, T. C.

2013-11-01

97

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

NASA Astrophysics Data System (ADS)

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

Pagano, T. C.

2014-07-01

98

Usefulness of satellite water vapour imagery in forecasting strong convection: A flash-flood case study  

NASA Astrophysics Data System (ADS)

Using a case study of a severe convective event as an example, a framework for interpreting 6.2 µm channel satellite imagery that enables to indicate upper-level conditioning of the convective environment is presented and discussed. In order to illustrate the approach, all convective cells during the summer of 2007 that produced precipitations over Bulgaria are considered. They are classified regarding the observed moisture pattern in mid-upper levels as well as the low-level conditions of air humidity and convergence of the flow. Water vapour (WV) images are used to study the evolution of the upper-level moist and dry structures. The proposed interpretation is that the role of the upper-level dry boundaries identified in the WV imagery as favoured areas for the initiation of deep moist convection cannot be understood (and hence cannot be forecasted accurately) by considering them in isolation from the dynamic rate at which they are maintained. The paper examines the 23 June 2006 flash flood in Sofia city as a case, in which the operational forecast of the National Institute of Meteorology and Hydrology of Bulgaria based on the mesoscale NWP model ALADIN underestimated the severity of the convective process. A comparison between the satellite water vapour imagery and the corresponding geopotential field of the dynamical tropopause, expressed in terms of potential vorticity (PV), shows an error in the performance of the ARPEGE operational numerical model. There is an obvious mismatch between the PV anomaly structure and the dry zone of the imagery. The forecast field shows underestimation of the tropopause height gradient and displacement of the PV anomaly to the southwest of the real position seen in the satellite image. It is concluded that the observed poor forecast is a result of the ARPEGE failure to treat correctly the interaction between the PV anomaly and the low-level warm anomaly.

Georgiev, Christo G.; Kozinarova, Gergana

99

Soil moisture updating by Ensemble Kalman Filtering in real-time flood forecasting  

NASA Astrophysics Data System (ADS)

SummaryThe aim of this paper is to examine the benefits of updating soil moisture of a distributed rainfall runoff model in forecasting large floods. The updating method uses Ensemble Kalman Filter concepts and involves an iterative similarity approach that avoids calculation of the Jacobian that relates the states and the observations. The soil moisture is updated based on observed runoff in a real-time mode, and is then used as an initial condition for the flood forecasts. The case study is set in the 622 km 2 Kamp catchment, Austria. The results indicate that the updating procedure indeed improves the forecasts substantially. The mean absolute normalised error of the peak flows of six large floods decreases from 25% to 12% (3 h lead time), and from 25% to 19% (48 h lead time). The Nash-Sutcliffe efficiency of forecasting runoff for these flood events increases from 0.79 to 0.92 (3 h lead time), and from 0.79 to 0.88 (48 h lead time). The flood forecasting system has been in operational use since early 2006.

Komma, Jürgen; Blöschl, Günter; Reszler, Christian

2008-08-01

100

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

NASA Astrophysics Data System (ADS)

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

Manukalo, V.

2012-12-01

101

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

102

Liuxihe Model and its application in flood forecasting in Southern China: results and challenges  

NASA Astrophysics Data System (ADS)

Liuxihe Model is a physically-based distributed hydrological model mainly proposed for watershed flood forecasting. This paper first discusses the results of Liuxihe Model's applications in several river basins' flood forecast modeling in southern China with the basin areas ranging from several hundred to ten thousand square kilometers. The results are satisfactory and suggest its maturity for real-time flood forecasting. Then several issues related to the model application to real-time operation, such as the parameter sensitivity, parameter adjusting methods and results, data assimilation for modeling in data-spare basins with remotely sensed data, spatial and temporal scaling, soil moisture estimation and its effect to model performance, model coupling with radar-estimated precipitation, and parallel computing code for lager river basin modeling. Future works to be done is to build a test bed in southern China for model validation, parallel high performance computer system for model developing and simulation that will be open to public worldwide.

Chen, Y.

2011-12-01

103

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

Federal Register 2010, 2011, 2012, 2013, 2014

...SECURITY Federal Emergency Management Agency 44 CFR Part 61...1660-AA70 National Flood Insurance Program...Federal Emergency Management Agency, DHS. ACTION...the Federal Emergency Management Agency (FEMA) provides...insurance protection against flood damage to...

2011-02-10

104

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

105

A comparison of different approaches for forecasting spring floods in Sweden  

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

106

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

107

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

108

Hurricane Analysis and Forecasting at the National Hurricane Center  

E-print Network

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

109

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

NASA Astrophysics Data System (ADS)

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

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

2014-06-01

110

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

NASA Astrophysics Data System (ADS)

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

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

2013-11-01

111

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

NASA Astrophysics Data System (ADS)

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

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

2014-05-01

112

Rainfall forecasting using an artificial neural network model to prevent flash floods  

Microsoft Academic Search

Flash floods are a dangerous natural disaster as they have killed more people than any other natural disaster and caused millions of ringgit in property damage. This paper presents a new approach for modeling rainfall forecasting using the artificial neural network technique (ANN). Daily actual data from the years 2007 to 2010, collected from 3 main stations in Selangor, were

Izyan'Izzati Abdul Rahman; Nik Mohd Asrol Alias

2011-01-01

113

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

NASA Astrophysics Data System (ADS)

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

Andreadis, Konstantinos; Schumann, Guy

2014-05-01

114

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

115

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

116

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

NASA Astrophysics Data System (ADS)

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

Trinh, B.; Pappenberger, F.

2009-04-01

117

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

118

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

119

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

120

Verification of National Weather Service spot forecasts using surface observations  

NASA Astrophysics Data System (ADS)

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

Lammers, Matthew Robert

121

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

122

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

NASA Astrophysics Data System (ADS)

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

van der Zwan, Rene

2013-04-01

123

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

Federal Register 2010, 2011, 2012, 2013, 2014

...issued through the National Flood Insurance Program (NFIP...Information Title: National Flood Insurance Program Claim Forms...Coverage, Subject to Terms and Conditions of this Policy; 086-0-13; National Flood Insurance Program...

2013-07-30

124

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

E-print Network

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

Bowles, David S.

125

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

126

Flood forecast in complex orography coupling distributed hydro-meteorological models and in-situ and remote sensing data  

Microsoft Academic Search

Summary  A flood forecast chain, developed at the Centre of Excellence for Remote Sensing and Hydro-Meteorology (CETEMPS) and based\\u000a on coupled mesoscale atmospheric and a newly developed distributed hydrological model with in-situ and remote sensing data\\u000a integration, is illustrated. The focus is on small-catchment flood forecast in complex topography in Central Italy, but the\\u000a developed modelling and processing integrated tools may

M. Verdecchia; E. Coppola; C. Faccani; R. Ferretti; A. Memmo; M. Montopoli; G. Rivolta; T. Paolucci; E. Picciotti; A. Santacasa; B. Tomassetti; G. Visconti; F. S. Marzano

2008-01-01

127

Assessment of sewer flooding model based on ensemble quantitative precipitation forecast  

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

128

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

129

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

130

Coupling meteorological and hydrological models for flood forecasting Hydrology and Earth System Sciences, 9(4), 333346 (2005) EGU  

E-print Network

Coupling meteorological and hydrological models for flood forecasting 333 Hydrology and Earth System Sciences, 9(4), 333346 (2005) © EGU Coupling meteorological and hydrological models for flood.bartholmes@jrc.it Abstract This paper deals with the problem of analysing the coupling of meteorological meso

Paris-Sud XI, Université de

131

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.

Drew Patrick

132

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

133

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

NASA Astrophysics Data System (ADS)

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

Van Steenbergen, N.; Willems, P.

2012-04-01

134

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

NASA Astrophysics Data System (ADS)

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

Tao, Jing; Barros, Ana P.

2013-12-01

135

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

E-print Network

Biggert-Waters Flood Insurance Program Act of 2012: Preliminary Fact Sheet Background Established in 1968, the National Flood Insurance Program (NFIP) is the sole provider of flood insurance in the United States. Its overall goal is "to reduce the impact of flooding on private and public structures

136

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

137

National Streamflow Information Program Implementation Plan and Progress Report  

E-print Network

- Real-time stage and streamflow data are required to support flood forecasting by the National Weathe of many users. For example, streamflow information is needed for: Flood forecasting and flood-prone area stations in the past decade, while the need for streamflow data for flood forecasting and long- term water

Fleskes, Joe

138

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

139

NWS tools to forecast river stages in the coastal zones  

Microsoft Academic Search

The National Weather Service (NWS) is the federal agency with the mandate to provide river and flood forecasts to save lives and property and support the Nation's economy. To accomplish this mission, the NWS provides forecasted river levels five days in the future at over 4,000 locations. The NWS Lower Mississippi River Forecast Center (LMRFC) is responsible for providing forecasts

David B. Reed; Jeffrey S. Graschel; David M. Welch; David A. Ramirez

2009-01-01

140

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

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

141

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

142

Mapping Statewide Flash Flood Potential Index (FFPI) in Indiana  

Microsoft Academic Search

National Weather Service (NWS) employees must make forecasting decisions on a daily basis. These forecasts are important to save people’s lives and property. One area where the NWS has very little guidance is flash flood prediction. A GIS project was undertaken to create a preliminary flash flood potential index map for the state of Indiana to help weather forecasters issue

Evan Bentley

2011-01-01

143

Skill in Precipitation Forecasting in the National Weather Service.  

NASA Astrophysics Data System (ADS)

All known long-term records of forecasting performance for different types of precipitation forecasts in the National Weather Service were examined for relative skill and secular trends in skill. The largest upward trends were achieved by local probability of precipitation (PoP) forecasts for the periods 24-36 h and 36-48 h after 0000 and 1200 GMT. Over the last 13 years, the skill of these forecasts has improved at an average rate of 7.2% per 10-year interval. Over the same period, improvement has been smaller in local PoP skill in the 12-24 h range (2.0% per 10 years) and in the accuracy of "Yea/No" forecasts of measurable precipitation. The overall trend in accuracy of centralized quantitative precipitation forecasts of 0.5 in and 1.0 in has been slightly upward at the 0-24 h range and strongly upward at the 24-48 h range. Most of the improvement in these forecasts has been achieved from the early 1970s to the present. Strong upward accuracy trends in all types of precipitation forecasts within the past eight years are attributed primarily to improvements in numerical and statistical centralized guidance forecasts.The skill and accuracy of both measurable and quantitative precipitation forecasts is 35-55% greater during the cool season than during the warm season. Also, the secular rate of improvement of the cool season precipitation forecasts is 50-110% greater than that of the warm season. This seasonal difference in performance reflects the relative difficulty of forecasting predominantly stratiform precipitation of the cool season and convective precipitation of the warm season.

Charba, Jerome P.; Klein, William H.

1980-12-01

144

Time Series Models Adoptable for Forecasting Nile Floods and Ethiopian Rainfalls.  

NASA Astrophysics Data System (ADS)

Long-term rainfall forecasting is used in making economic and agricultural decisions in many countries. It may also be a tool in minimizing the devastation resulting from recurrent droughts. To be able to forecast the total annual rainfall or the levels of seasonal floods, a class of models has first been chosen. The model parameters have then been estimated with an appropriate parameter estimation algorithm. Finally, diagnostic tests have been performed to verify the adequacy of the model. These are the general principles of system identification, which is the most crucial part of the forecasting procedure. In this paper several sets of data have been studied using different statistical procedures. The examined data include a historical 835-year record representing the levels of the seasonal Nile floods in Cairo, Egypt, during the period A.D. 622-1457. These readings were originally carried out by the Arabsto a great degree of accuracy in order to be used in estimating yearly taxes or Zacat (islamic duties). The observations also comprise recent total annual rainfall data over Addis Ababa (Ethiopia) (1907-1984), the total annual discharges of Ethiopian rivers (including the river Sobat discharges at Hillet Doleib, Blue Nile discharge at Roseris, river Dinder, river Rahar, and river Atbara), equatorial lake plateau supply as contributed at Aswan during the period 1912-1982, and the total annual discharges at Aswan during the period 1871-1982. Periodograms have been used to uncover possible peridodicities. Trends of rainfall and discharges of some rivers of east and central Africa have been also estimated.Using the first half of the available record, two autoregressive integrated moving average (ARIMA) time series models have been identified, one for the levels of the seasonal Nile floods in Cairo, the second to model the annual rainfall over Ethiopia. The time series models have been applied in 1-year-ahead forecasting to the other hall of the available record and give fairly promising results, thus indicating the adequacy of the fitted models.

El-Fandy, M. G.; Taiel, S. M. M.; Ashour, Z. H.

1994-01-01

145

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

NASA Astrophysics Data System (ADS)

We investigate the effects of noise specification on the quality of hydrological forecasts via an advanced data assimilation (DA) procedure using a distributed hydrological model driven by numerical weather predictions. The sequential DA procedure is based on (1) a multivariate rainfall ensemble generator, which provides spatial and temporal correlation error structures of input forcing, and (2) lagged particle filtering to update past and current state variables simultaneously in a lag-time window to consider the response times of internal hydrologic processes. The procedure is evaluated for streamflow forecasting of three flood events in two fast-responding catchments in Japan (Maruyama and Katsura). The rainfall ensembles are derived from ground-based rain gauge observations for the analysis step and numerical weather predictions for the forecast step. The ensemble simulation performs multi-site updating using information from the streamflow gauging network and considers the artificial effects of reservoir release. Sensitivity analysis is performed to assess the impacts of noise specification in DA, comparing a different setup of random state noise and input forcing with/without multivariate conditional simulation (MCS) of rainfall ensembles. The results show that lagged particle filtering (LPF) forced with MCS provides good performance with small and consistent random state noise, whereas LPF forced with Thiessen rainfall interpolation requires larger random state noise to yield performance comparable to that of LPF + MCS for short lead times.

Noh, Seong Jin; Rakovec, Old?ich; Weerts, Albrecht H.; Tachikawa, Yasuto

2014-11-01

146

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

147

A reservoir flood forecasting and control system for China \\/ Un système chinois de prévision et de contrôle de crue en barrage  

Microsoft Academic Search

Reservoirs play a vital role in flood prevention and disaster relief in China. The objectives of the project described in this study were to establish a reservoir flood forecasting and control system and to design and develop corresponding application software. This paper introduces the current reservoir flood control and operation practice with this system in China. Using modern integration technologies,

Shenglian Guo; Honggang Zhang; Hua Chen; Dingzhi Peng; Pan Liu; Bo Pang

2004-01-01

148

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

149

Forecasting of Storm-Surge Floods Using ADCIRC and Optimized DEMs  

NASA Technical Reports Server (NTRS)

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

Valenti, Elizabeth; Fitzpatrick, Patrick

2006-01-01

150

An integrated error parameter estimation and lag-aware data assimilation scheme for real-time flood forecasting  

NASA Astrophysics Data System (ADS)

For operational flood forecasting, discharge observations may be assimilated into a hydrologic model to improve forecasts. However, the performance of conventional filtering schemes can be degraded by ignoring the time lag between soil moisture and discharge responses. This has led to ongoing development of more appropriate ways to implement sequential data assimilation. In this paper, an ensemble Kalman smoother (EnKS) with fixed time window is implemented for the GR4H hydrologic model (modèle du Génie Rural à 4 paramètres Horaire) to update current and antecedent model states. Model and observation error parameters are estimated through the maximum a posteriori method constrained by prior information drawn from flow gauging data. When evaluated in a hypothetical forecasting mode using observed rainfall, the EnKS is found to be more stable and produce more accurate discharge forecasts than a standard ensemble Kalman filter (EnKF) by reducing the mean of the ensemble root mean squared error (MRMSE) by 13-17%. The latter tends to over-correct current model states and leads to spurious peaks and oscillations in discharge forecasts. When evaluated in a real-time forecasting mode using rainfall forecasts from a numerical weather prediction model, the benefit of the EnKS is reduced as uncertainty in rainfall forecasts becomes dominant, especially at large forecast lead time.

Li, Yuan; Ryu, Dongryeol; Western, Andrew W.; Wang, Q. J.; Robertson, David E.; Crow, Wade T.

2014-11-01

151

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

Code of Federal Regulations, 2012 CFR

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

2012-10-01

152

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 62 Emergency...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND...

2010-10-01

153

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 Part 62 Emergency...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND...

2013-10-01

154

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

Code of Federal Regulations, 2014 CFR

... 2014-10-01 false National Flood Insurance Program B Appendix B to Part 62 Emergency...AGENCY, DEPARTMENT OF HOMELAND SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program SALE OF INSURANCE AND...

2014-10-01

155

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

Federal Register 2010, 2011, 2012, 2013, 2014

...Docket ID FEMA-2012-0012] National Flood Insurance Program Programmatic Environmental...and requested public comments no later than July 16, 2012. FEMA has reopened...the passage of a 5- year National Flood Insurance Program...

2012-08-22

156

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

Code of Federal Regulations, 2011 CFR

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

2011-10-01

157

GEO-SPATIAL TECHNOLOGY USE TO MODEL FLOODING POTENTIAL IN CHESTATEE RIVER WATERSHED  

Microsoft Academic Search

Since 2002, the National Weather Service uses Flash Flood Monitoring Program (FFMP) and Flash Flood Guidance (FFG) to predict flash flood events. However, these programs contain several deficiencies for several forecast areas in the nation. Developing a GIS based model that incorporates basin physiographic characteristics will allow the hydrologist to better predict flash flood events. In this study, we have

Sarah Skelton; Sudhanshu S Panda

2009-01-01

158

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

Microsoft Academic Search

Flooding is a wide spread and devastating natural disaster worldwide. Floods that took place in the last decade in China were ranked the worst amongst recorded floods worldwide in terms of the number of human fatalities and economic losses (Munich Re-Insurance). Rapid economic development and population expansion into low lying flood plains has worsened the situation. Current conventional flood prediction

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

2010-01-01

159

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

Microsoft Academic Search

Flooding is a wide spread and devastating natural disaster worldwide. Floods that took place in the last decade in China were ranked the worst amongst recorded floods worldwide in terms of the number of human fatalities and economic losses (Munich Re-Insurance). Rapid economic development and population expansion into low lying flood plains has worsened the situation. Current conventional flood prediction

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

2009-01-01

160

Floods  

MedlinePLUS

... Matters What's New A - Z Index Disasters & Severe Weather Earthquakes Extreme Heat Floods Hurricanes Landslides Tornadoes Tsunamis ... Septic Systems After a Flood [EPA] Disasters & Severe Weather Earthquakes Extreme Heat Floods Hurricanes Landslides Tornadoes Tsunamis ...

161

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

E-print Network

National flood modelling for insurance purposes:using IFSAR for flood risk estimation in Europe 449 Hydrology and Earth System Sciences, 9(4), 449456 (2005) © EGU National flood modelling for insurance purposes: using IFSAR for flood risk estimation in Europe R. Sanders1 , F. Shaw1 , H. MacKay2 , H. Galy1

Paris-Sud XI, Université de

162

Flooding and Flood Risks  

MedlinePLUS

... Risk Scenarios The Cost of Flooding The Levee Simulator About The National Insurance Program Residential Coverage Commercial ... flash floods and tropical storms. Learn More Levee Simulator The FloodSmart Levee Simulator shows different ways a ...

163

Flash Flood Early Warning System Reference Guide  

NSDL National Science Digital Library

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

COMET

2011-10-18

164

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

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

165

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

NASA Astrophysics Data System (ADS)

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

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

2014-09-01

166

NatioNal aNd Global Forecasts West VirGiNia ProFiles aNd Forecasts  

E-print Network

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

Mohaghegh, Shahab

167

Discussion of "Development and Verification of an Analytical Solution for Fore-casting Nonlinear Kinematic Flood Waves" by Sergio E. Serrano  

E-print Network

Kinematic Flood Waves" by Sergio E. Serrano Journal of Hydrologic Engineering, July/August 2006, Vol. 11, No presents an interesting method to forecast nonlinear kinematic flood waves (Serrano, 2006). As a first given by Eqs. (2­3) of this discussion is exact, explicit and does not require any approximate solution

Paris-Sud XI, Université de

168

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

E-print Network

Operational hydro-meteorological warning and real-time flood forecasting:the Piemonte region case study 457 Hydrology and Earth System Sciences, 9(4), 457466 (2005) © EGU Operational hydro-meteorological forecasting system in the context of the Piemonte Regions hydro-meteorological operational alert procedure

Paris-Sud XI, Université de

169

Floods  

MedlinePLUS

... neighborhood or community, or very large, affecting entire river basins and multiple states. Flash floods can occur ... flooding event typically occurs when waterways such as rivers or streams overflow their banks as a result ...

170

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 ...

171

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

172

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

E-print Network

Local Flood Proofing Programs June 199" #12;This report was prepared for the U.S. Army Corps of Engineers' National Flood Proofing Committee by French & Associates, Ltd., 153 Nanti, Park Forest, Illinois who have designed or implemented flood proofing financial assistance programs. The cost data

US Army Corps of Engineers

173

Developing a Web-based flood forecasting system for reservoirs with J2EE \\/ Développement sur Internet avec J2EE d’un système de prévision de crue pour barrages  

Microsoft Academic Search

A flood forecasting system is a crucial component in flood mitigation. For certain important large-scale reservoirs, cooperation and communication among federal, state, and local stakeholders are required when heavy flood events are encountered. The Web-based environment is emerging as a very important development and delivery platform for real-time flood forecasting systems. In this paper, the findings of a case study

Chun-Tian Cheng; K. W. Chau; Xiang-Yang Li; Gang Li

2004-01-01

174

Forcing a distributed hydrological model with ensemble precipitation forecasts to support dam operation during floods  

Microsoft Academic Search

This study attempts to generate ensemble precipitation considering the accuracy of the quantitative precipitation forecast (QPF) within previous time steps. The combination of the forecasts with real time in situ measurements is used to determine the forecast error. A penalty weighting approach is suggested to account the spatial variability of the error. Underestimated or overestimated intensities of the QPF might

O. C. Saavedra; T. Koike; K. Yang; T. Graf; X. Li; L. Wang; X. Han

2010-01-01

175

Flood  

NSDL National Science Digital Library

The Flood site is an experiment with a stream table to see what happens during a flood. It was originally a joint project between a 6th grade class and the Bureau of Economic Geography. There are explanations and photographs of the experimental set up and of students and their observation of rivers forming and the creation of a flood. There is also a worksheet for experimental notes and a sheet containing the experimental method and instructions.

176

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

E-print Network

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

177

Flood forecasting for medium-sized river basins using probabilistic weather prediction  

Microsoft Academic Search

The latest version of the Ensemble Prediction System (EPS) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) consists of 50 perturbed and one unperturbed 10-day weather forecasts at a spatial resolution of an approximate grid spacing of 80 km at mid-latitudes. The deterministic weather forecast is provided with a grid spacing of approximately 40 km. At present the

B. Gouweleeuw; J. Thielen; G. Franchello; A. de Roo; R. Buizza

2003-01-01

178

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

179

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

180

APPLICATION OF EO DATA IN FLOOD FORECASTING FOR THE CRISURI BASIN, ROMANIA  

Microsoft Academic Search

The risk of flooding due to runoff is a major concern in many areas around the globe and especially in Romania. In the latest\\u000a years river flooding and accompanying landslides, occurred quit frequently in Romania, some of which isolated, others-affecting\\u000a wide areas of the country's territory.

GHEORGHE STANCALIE; ANDREI DIAMANDI; CIPRIAN CORBUS; SIMONA CATANA

181

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

Technology Transfer Automated Retrieval System (TEKTRAN)

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

182

Limits to Flood Forecasting in the Colorado Front Range for Two Summer Convection Periods Using Radar Nowcasting and a Distributed Hydrologic Model  

Microsoft Academic Search

Flood forecasting in mountain basins remains a challenge given the\\u000a difficulty in accurately predicting rainfall and in representing\\u000a hydrologic processes in complex terrain. This study identifies flood\\u000a predictability patterns in mountain areas using quantitative\\u000a precipitation forecasts for two summer events from radar nowcasting and\\u000a a distributed hydrologic model. The authors focus on 11 mountain\\u000a watersheds in the Colorado Front Range

Hernan A. Moreno; Enrique R. Vivoni; David J. Gochis

2013-01-01

183

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

EPA Science Inventory

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

184

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

185

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

NASA Astrophysics Data System (ADS)

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

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

2004-12-01

186

Comparison of short-term rainfall prediction models for real-time flood forecasting  

Microsoft Academic Search

This study compares the accuracy of the short-term rainfall forecasts obtained with time-series analysis techniques, using past rainfall depths as the only input information. The techniques proposed here are linear stochastic auto-regressive moving-average (ARMA) models, artificial neural networks (ANN) and the non-parametric nearest-neighbours method. The rainfall forecasts obtained using the considered methods are then routed through a lumped, conceptual, rainfall–runoff

E. Toth; A. Brath; A. Montanari

2000-01-01

187

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

NASA Technical Reports Server (NTRS)

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

Garner, Gregory G.; Thompson, Anne M.

2013-01-01

188

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

USGS Publications Warehouse

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

Ostheimer, Chad J.

2013-01-01

189

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

190

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

191

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

192

Flood and Fire Monitoring and Forecasting Within the Chornobyl Exclusion Zone  

Microsoft Academic Search

Taking into consideration that radioactivity from the contaminating elements of the Chernobyl Exclusion Zone (CEZ) amounts to a huge number, one of the most urgent tasks, at present, is the resolution of problems related to secondary radioactive contamination caused by floods and fires. These factors may lead to critical consequences. For instance, if radioactive contaminants migrate into the water system,

Victor Los

2001-01-01

193

Forecasting the spatial extent of the annual flood in the Okavango delta, Botswana  

Microsoft Academic Search

The pristine Okavango Delta wetland of northern Botswana is potentially under threat due to water abstraction from its tributaries. We have developed a statistical model which makes it possible to predict the extent of wetland loss which will arise from water abstraction. The model also permits prediction of the maximum area of flooding, and its spatial distribution, three months in

T. Gumbricht; P. Wolski; P. Frost; T. S McCarthy

2004-01-01

194

A GIS GRASS-embedded decision support framework for flood forecasting  

Microsoft Academic Search

1 Abstract In this study spatial analysis tools are presented which allow the simulation and prediction of flash floods in semiarid basins to be carried out. Different applications are analysed of the Shyska operational system in real basins, developed with functions embedded in a Geographical Information System (GIS), which combines information from latest generation data acquisition technologies in real time.

Sandra G. García

2002-01-01

195

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

Technology Transfer Automated Retrieval System (TEKTRAN)

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

196

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

Microsoft Academic Search

About one-third of the Earth's land surface is located in arid or semi-arid regions, often in areas suffering severely from the negative impacts of desertification and population pressure. Reliable hydrological forecasts across spatial and temporal scales are crucial in order to achieve water security - protection from excess and lack of water - for people and ecosystems in these areas.

THORSTEN WAGENER; HOSHIN GUPTA; SONI YATHEENDRADAS; DAVID GOODRICH; CARL UNKRICH; MIKE SCHAFFNER

197

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

198

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

199

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

200

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

E-print Network

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

Arora, Siddharth

201

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

NASA Technical Reports Server (NTRS)

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

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

2015-01-01

202

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

NASA Technical Reports Server (NTRS)

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

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

2014-01-01

203

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.

USGS Office of Surface Water

204

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

NASA Astrophysics Data System (ADS)

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

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

2011-08-01

205

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

206

Multiple scenario analyses forecasting the confounding impacts of sea level rise and tides from storm induced coastal flooding in the city of Shanghai, China  

Microsoft Academic Search

Shanghai is physically and socio-economically vulnerable to accelerated sea level rise because of its low elevation, flat\\u000a topography, highly developed economy and highly-dense population. In this paper, two scenarios of sea level rise and storm\\u000a surge flooding along the Shanghai coast are presented by forecasting 24 (year 2030) and 44 (year 2050) years into the future\\u000a and are applied to

Jie YinZhan-e; Zhan-e Yin; Xiao-meng Hu; Shi-yuan Xu; Jun Wang; Zhi-hua Li; Hai-dong Zhong; Fu-bin Gan

2011-01-01

207

FLOOD RISK FORECASTING FOR POORLY GAUGED BASINS IN THE MEKONG RIVER BASIN USING A DISTRIBUTED HYDROLOGICAL MODEL AND A SATELLITE DERIVED PRECIPITATION DATASET  

Microsoft Academic Search

In order to achieve effective flood risk forecasting for poorly gauged sub-basins in the Mekong River Basin, the feasibility of using a currently available distributed hydrological model and satellite-based precipitation datasets coupled with a simple statistical approach is discussed in this paper. A physically based distributed hydrological model, the YHyM\\/BTOP model, was used in this paper to simulate at any

JUN MAGOME; KAZUHIKO FUKAMI; HIRONORI INOMATA

208

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

NASA Astrophysics Data System (ADS)

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

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

2007-12-01

209

Hydrologic Forecasting at the US National Weather Service in the 21st Century: Transition from the NWS River Forecast System (NWSRFS) to the Community Hydrologic Prediction System (CHPS)  

Microsoft Academic Search

The US National Weather Service developed the River Forecast System (NWSRFS) since the 1970s as the platform for performing hydrologic forecasts. The system, originally developed for the computers of that era, was optimized for speed of execution and compact and fast data storage and retrieval. However, with modern computers those features became less of a driver, and, instead, the ability

Pedro Restrepo; Jon Roe; Christine Dietz; Micha Werner; Peter Gijsbers; Robert Hartman; Harold Opitz; Billy Olsen; John Halquist; Robert Shedd

2010-01-01

210

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

Federal Register 2010, 2011, 2012, 2013, 2014

...Children From Environmental Health Risks and Safety Risks...create environmental health risks or safety risks...Children From Environmental Health Risks and Safety Risks...Subjects in 44 CFR Part 61 Flood insurance, Reporting...Administrator, Federal Emergency Management Agency. [FR Doc....

2010-09-03

211

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

212

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

E-print Network

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

Smith, Dan

213

Bulletin of Forest Fire risk in Albania- The experience of the Albania National Centre for forecast and Monitoring of Natural Risks  

NASA Astrophysics Data System (ADS)

In the territory of Albania usually every year around 1000 ha are affected by forest fires, from which about 500 ha are completely destroyed. The number of forest fires (nf), with the burning surface (bs) in years has been like this: during the years 1988-1998: nf / bs = 2.19, 1998-2001: nf / bs = 5.66, year 2002 -2005: nf / bs = 8.2, and during the years 2005-2006: nf / bs = 11.9, while economic losses in a year by forest fires is about 2 million of Euro. The increase in years of these figures and the last floods which happened in the last two years in Shkoder, led to an international cooperation, that between the Italian Civil Protection Department and the Albania General Directorate of Civil Emergency. The focus of this cooperation was the building capacity of the Albanian National System of Civil Protection in forecasting, monitoring and prevention forest fires and floods risks. As a result of this collaboration the "National Center for the Forecast and Monitoring of Natural Risks", was set up at the Institute of Geosciences, Energy, Water and Environment. The Center is the first of its kind in Albania. The mission of the Center is the prediction and monitoring of the forest fire and flood risk in the Albanian territory, as a tools for risk reduction and mitigation. The first step to achieve this strategy was the implementation of the forest fires risk forecast model "RISICO". RISICO was adapted for whole Albania territory by CIMA Research Foundation. The Center, in the summer season, issues a daily bulletin. The bulletin reports the potential risk scenarios related with the ignition and propagation of fires in Albania. The bulletin is broadcasted through email or fax within 12.00 AM of each working day. It highlights where and when severe risk conditions may occur within the next 48 hours

Berdufi, I.; Jaupaj, O.; Marku, M.; Deda, M.; Fiori, E.; D'Andrea, M.; Biondi, G.; Fioruci, P.; Massabò, M.; Zorba, P.; Gjonaj, M.

2012-04-01

214

Cost of Flooding  

MedlinePLUS

... Schedule Floodsmart Video Library Flood Risk Scenarios The Cost of Flooding The Levee Simulator About The National ... you what a flood to your home could cost, inch by inch. Launch Cost Of Flooding Now ...

215

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

NASA Astrophysics Data System (ADS)

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

Wang, H.

2012-12-01

216

Flood inundation simulation in Ajoy River using MIKE-FLOOD  

Microsoft Academic Search

Control and risk management of floods using non-structural measures such as flood forecasting and flood warning, flood hazard mapping and flood risk zoning are quite effective. Of these, preparation of flood hazard maps and flood plain zoning require flood inundation simulation, for which various numerical models are available, for example, one-dimensional (1D), two-dimensional (2D) and 1D-2D-coupled models. In the present

Prashant Kadam; Dhrubajyoti Sen

2012-01-01

217

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

218

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

219

Development of a Flood-Warning System and Flood-Inundation Mapping for the Blanchard River in Findlay, Ohio  

USGS Publications Warehouse

Digital flood-inundation maps of the Blanchard River in Findlay, Ohio, were created by the U.S. Geological Survey (USGS) in cooperation with the City of Findlay, Ohio. The maps, which correspond to water levels at the USGS streamgage at Findlay (04189000), were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning system that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. The USGS reestablished one streamgage and added another on the Blanchard River upstream of Findlay. Additionally, the USGS established one streamgage each on Eagle and Lye Creeks, tributaries to the Blanchard River. The stream-gage sites were equipped with rain gages and multiple forms of telemetry. Data from these gages can be used by emergency management personnel to determine a course of action when flooding is imminent. Flood profiles computed by means of a step-backwater model were prepared and calibrated to a recent flood with a return period exceeding 100 years. The hydraulic model was then used to determine water-surface-elevation profiles for 11 flood stages with corresponding streamflows ranging from approximately 2 to 100 years in recurrence interval. The simulated flood profiles were used in combination with digital elevation data to delineate the flood-inundation areas. Maps of Findlay showing flood-inundation areas overlain on digital orthophotographs are presented for the selected floods.

Whitehead, Matthew T.; Ostheimer, Chad J.

2009-01-01

220

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

221

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

222

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

223

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

224

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

PubMed

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

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

2011-01-01

225

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

Technology Transfer Automated Retrieval System (TEKTRAN)

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

226

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

227

Flood Risk and Flood hazard maps - Visualisation of hydrological risks  

NASA Astrophysics Data System (ADS)

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

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

2008-11-01

228

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

USGS Publications Warehouse

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

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

2012-01-01

229

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

230

OPERATIONAL AUSTRALIA'S NATIONAL METEOROLOGICAL SERVICE  

E-print Network

the nation's people and property, and when required we warn ­ of cyclone, storm, tsunami, fire or flood of the equator, from the Indian Ocean to the Pacific. We cover land, sea and air. We employ around 1400 people for other functions in associated scientific fields: flood forecasting and warning; oceanographic analysis

Greenslade, Diana

231

Flood Facts  

MedlinePLUS

... gov The official site of the National Flood Insurance Program Call toll free: 1-888-379-9531 ... you Enter Search Term(s): Home About The National Insurance Program Residential Coverage Commercial Coverage PolicyHolder Resources Preparation & ...

232

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

E-print Network

with the National Digital Forecast Database Kathleen Baker a, , Paul Roehsner a , Thomas Lake b , Douglas Rivet 2014 Accepted 9 April 2014 Keywords: Geographic information systems Artificial neural network NoSQL specific (point) data in Michigan. A unique system using NoSQL was developed to train, validate

Douches, David S.

233

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

USGS Publications Warehouse

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

Meyer, Robert W.

1995-01-01

234

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

NASA Astrophysics Data System (ADS)

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

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

2009-12-01

235

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.

236

Flood management in a complex river basin with a real-time decision support system based on hydrological forecasts  

E-print Network

ENAC/ Flood management in a complex river basin with a real-time decision support system based) of the Ecole Polytechnique Fédérale de Lausanne (EPFL) as well as the Institute of Geomatics and Risk Analysis (IGAR) of the University of Lausanne (UNIL). What after a "water alert" from MeteoSwiss? "Analysis

237

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

238

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

E-print Network

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

Weston, Ken

239

Ensemble stream flow predictions, a way towards better hydrological forecasting  

NASA Astrophysics Data System (ADS)

The hydrological forecasting division at SMHI has been using hydrological EPS and hydrological probabilities forecasts operationally since some years ago. The inputs to the hydrological model HBV are the EPS forecasts from ECMWF. From the ensemble, non-exceedance probabilities are estimated and final correction of the ensemble spread, based on evaluation is done. Ensemble stream flow predictions are done for about 80 indicator basins in Sweden, where there is a real-time discharge gauge. The EPS runs are updated daily against the latest observed discharge. Flood probability maps for exceeding a certain threshold, i.e. a certain warning level, are produced automatically once a day. The flood probabilistic forecasts are based on a HBV- model application, (called HBV-Sv, HBV Sweden) that covers the whole country and consist of 1001 subbasins with an average size between 200 and 700 km2. Probabilities computations for exceeding a certain warning level are made for each one of these 1001 subbasins. Statistical flood levels have been calculated for each river sub-basin. Hydrological probability forecasts should be seen as an early warning product that can give better support in decision making to end-users communities, for instance Civil Protections Offices and County Administrative Boards, within flood risk management. The main limitations with probability forecasts are: on one hand, difficulties to catch small-scale rain (mainly due to resolution of meteorological models); on the other hand, the hydrological model can't be updated against observations in all subbasins. The benefits of working with probabilities consist, first of all, of a new approach when working with flood risk management and scenarios. A probability forecast can give an early indication for Civil Protection that "something is going to happen" and to gain time in preparing aid operations. The ensemble stream flow prediction at SMHI is integrated with the national forecasting system and the products are available to specialized end-users via Internet.

Edlund, C.

2009-04-01

240

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

241

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

242

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

243

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

USGS Publications Warehouse

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

Studley, Seth E.

2003-01-01

244

Going to space: Implementation of spatial input data processing in real-time flood forecasting in the Czech Republic  

NASA Astrophysics Data System (ADS)

Real-time forecasting systems were developed and used in the Czech Republic since late 90's. AquaLog forecasting system is used for forecasting in the Czech part of the Elbe river basin. AquaLog uses SAC-SMA for rainfall-runoff modeling and SNOW17 for modeling of snow cover accumulation and melting. There are about 150 forecasting profiles (computed sub-basins). Data input pre-processing module AquaBase for data quality check and correction. Previous version of AquaBase and AquaLog (ver.5) operated in the scale of basins using time-series of observed precipitation and temperature to compute MAP and MAT based on Thiessen polygons method for basins of typical size of 200-500 km2 (basins were internally divided into 2-4 computation units based on elevation to simulate more precisely the snow cover). New version of AquaBase (ver.6) process data into regular 1 km grid offering to choose between several interpolating techniques: - Inverse distance weighted (IDW) with optional value of power parameter, number of stations and diameter in km to be taken into account - IDW quadrant (IDWq) using only the nearest station from every quadrant of space (optional power parameter and diameter applicable) - IDW and temperature gradient (for temperature only) correcting the interpolated value according to optional vertical temperature gradient and elevation difference among used stations (optional power parameter and diameter applicable) - Krigging with optional parameters - Co-krigging with optional parameters - Use of radar-raingauge dynamically combined field product AquaBase ver.6 enables editing of precipitation and temperature field by implementing pseudo-gauges anywhere in the space and editing its values. AquaLog computation unit were changed to small sub-basins of typical size of 10 to 15 km2 and specific unit hydrographs were derived for every sub-basin. MAP and MAT based on grid analysis in AquaBase environment input every particular sub-basin. Long time runoff simulation proved a better performance of AquaBase&AquaLog ver.6 in comparison to ver.5 as average Nash-Sutcliffe increased from 0.63 (STD=0.22) to 0.70 (0.14). Beneficial was that increase took place in low performance basins especially.

Vlasak, T.; Krejci, J.; Danhelka, J.

2009-04-01

245

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

246

LANDSCAPE STATE CHANGE IN THE SEMI-ARID SABIE RIVER, KRUGER NATIONAL PARK, IN RESPONSE TO FLOOD AND DROUGHT  

Microsoft Academic Search

Semi arid rivers are subject to highly variable flow regimes as a result of strongly seasonal and unpredictable rainfall. Riparian landscape state changes resulting from a prolonged low flow period followed by a high magnitude flood were examined in the semi arid, mixed bedrock\\/alluvial Sabie River in the Kruger National Park, South Africa. Aerial photographs from 1986 and 1996 were

M. W. ROUNTREE; K. H. ROGERS

2000-01-01

247

Progress and challenges with Warn-on-Forecast  

NASA Astrophysics Data System (ADS)

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

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

2013-04-01

248

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

NASA Technical Reports Server (NTRS)

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

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

2014-01-01

249

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

Microsoft Academic Search

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

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

1982-01-01

250

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.

2014-09-14

251

Flood-inundation maps for Indian Creek and Tomahawk Creek, Johnson County, Kansas, 2014  

USGS Publications Warehouse

The availability of these maps, along with Web information regarding current stage from the U.S. Geological Survey streamgage and forecasted high-flow stages from the National Weather Service, 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 postflood recovery efforts.

Studley, Seth E.; Peters, Arin J.

2015-01-01

252

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.

John Nielsen-Gammon

1996-09-01

253

Flood Protection Structure Accreditation Task Force: Interim Report  

E-print Network

inspections and assessments and the National Flood Insurance Program levee accreditation requirements of Completed Works (ICW) Program with the flood protection structure accreditation requirements of the National to satisfy NFIP flood protection structure accreditation requirements. (Task 2) The Flood Protection

US Army Corps of Engineers

254

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

255

Flash Flood Processes  

NSDL National Science Digital Library

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

2014-09-14

256

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

NASA Astrophysics Data System (ADS)

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

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

2015-03-01

257

Probability Forecasting in Meteorology  

Microsoft Academic Search

Efforts to quantify the uncertainty in weather forecasts began more than 75 years ago, and many studies and experiments involving objective and subjective probability forecasting have been conducted in meteorology in the intervening period. Moreover, the U.S. National Weather Service (NWS) initiated a nationwide program in 1965 in which precipitation probability forecasts were formulated on an operational basis and routinely

Allan H. Murphy; Robert L. Winkler

1984-01-01

258

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

NASA Astrophysics Data System (ADS)

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

Shukla, Shraddhanand; Funk, Christopher; Hoell, Andrew

2014-09-01

259

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

260

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 ...

261

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

USGS Publications Warehouse

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

Ostheimer, Chad J.

2012-01-01

262

Development of Multisensor Precipitation Nowcaster in the National Weather Service  

Microsoft Academic Search

To meet the National Oceanic and Atmospheric Administration (NOAA) objective to increase lead-time and accuracy of flash flood forecasts, the NOAA National Weather Service (NWS) Office of Hydrologic Development has developed the Multisensor Precipitation Nowcaster (MPN) algorithm based on its Flash Flood Potential algorithm. In contrast to many existing nowcast algorithms that are single-radar-based, MPN integrates and mosaics data from

S. Guan; R. Fulton; F. Ding; D. Kitzmiller

2006-01-01

263

The predictability of Iowa's hydroclimate through analog forecasts  

NASA Astrophysics Data System (ADS)

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

Rowe, Scott Thomas

264

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

USGS Publications Warehouse

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

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

2014-01-01

265

Flood Inundation Mapping  

E-print Network

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

Pearson, Wendy

2009-11-18

266

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 youâ??re 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

267

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

PubMed Central

Resource managers at parks and other protected areas are increasingly expected to factor climate change explicitly into their decision making frameworks. However, most protected areas are small relative to the geographic ranges of species being managed, so forecasts need to consider local adaptation and community dynamics that are correlated with climate and affect distributions inside protected area boundaries. Additionally, niche theory suggests that species' physiological capacities to respond to climate change may be underestimated when forecasts fail to consider the full breadth of climates occupied by the species rangewide. Here, using correlative species distribution models that contrast estimates of climatic sensitivity inferred from the two spatial extents, we quantify the response of limber pine (Pinus flexilis) to climate change in Rocky Mountain National Park (Colorado, USA). Models are trained locally within the park where limber pine is the community dominant tree species, a distinct structural-compositional vegetation class of interest to managers, and also rangewide, as suggested by niche theory. Model forecasts through 2100 under two representative concentration pathways (RCP 4.5 and 8.5 W/m2) show that the distribution of limber pine in the park is expected to move upslope in elevation, but changes in total and core patch area remain highly uncertain. Most of this uncertainty is biological, as magnitudes of projected change are considerably more variable between the two spatial extents used in model training than they are between RCPs, and novel future climates only affect local model predictions associated with RCP 8.5 after 2091. Combined, these results illustrate the importance of accounting for unknowns in species' climatic sensitivities when forecasting distributional scenarios that are used to inform management decisions. We discuss how our results for limber pine may be interpreted in the context of climate change vulnerability and used to help guide adaptive management. PMID:24391742

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

2013-01-01

268

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

PubMed

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

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

2013-01-01

269

Flood management benefits of USGS streamgaging program  

E-print Network

Flood management benefits of USGS streamgaging program October 19, 2006 National Hydrologic Warning ................................................................................................................. 6 What are the information needs for flood management in the US?........................................ 13 What is the benefit of meeting the information need for flood management project design

Fleskes, Joe

270

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

271

44 CFR 78.5 - Flood Mitigation Plan development.  

Code of Federal Regulations, 2011 CFR

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

2011-10-01

272

44 CFR 78.5 - Flood Mitigation Plan development.  

Code of Federal Regulations, 2010 CFR

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

2010-10-01

273

44 CFR 78.5 - Flood Mitigation Plan development.  

Code of Federal Regulations, 2012 CFR

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

2012-10-01

274

44 CFR 78.5 - Flood Mitigation Plan development.  

Code of Federal Regulations, 2014 CFR

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

2014-10-01

275

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...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program FLOOD MITIGATION ASSISTANCE § 78.5 Flood...

2013-10-01

276

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

277

FLOOD PROOFING How to Evaluate Your Options  

E-print Network

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

US Army Corps of Engineers

278

Regional-scale flood detection using AMSR-E observations  

Technology Transfer Automated Retrieval System (TEKTRAN)

Remote sensing observations provide spatially distributed information that can be exploited to improve flood forecasting and risk mitigation. These observations provide potential tools for improving the detection and monitoring of flooding events - particularly within data poor regions of the world ...

279

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

SciTech Connect

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

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

1982-03-31

280

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

281

Flash Flood Processes: International Edition  

NSDL National Science Digital Library

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

COMET

2011-02-22

282

EXTENDED-RANGE PROBABILISTIC FORECASTS OF GANGES AND  

E-print Network

EXTENDED-RANGE PROBABILISTIC FORECASTS OF GANGES AND BRAHMAPUTRA FLOODS IN BANGLADESH M any of which is subject to periods of widespread and long-lived flooding. Flooding remains the greatest cause the lives of victims of slow-onset flood disasters, such events remain relentlessly impoverishing. In India

Webster, Peter J.

283

Forecasting forecast skill  

NASA Technical Reports Server (NTRS)

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

Kalnay, Eugenia; Dalcher, Amnon

1987-01-01

284

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

USGS Publications Warehouse

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

Storm, John B.

2014-01-01

285

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

286

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

NASA Astrophysics Data System (ADS)

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

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

2012-12-01

287

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

288

Rainfall-River Forecasting Fusion Team Rainfall-River Forecasting Summit  

E-print Network

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

US Army Corps of Engineers

289

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

Code of Federal Regulations, 2014 CFR

... 1 2014-10-01 2014-10-01 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...

2014-10-01

290

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

291

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

Code of Federal Regulations, 2011 CFR

... 1 2011-10-01 2011-10-01 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...

2011-10-01

292

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

Code of Federal Regulations, 2012 CFR

... 1 2012-10-01 2011-10-01 true 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...

2012-10-01

293

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

294

44 CFR 73.4 - Restoration of flood insurance coverage.  

Code of Federal Regulations, 2014 CFR

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

2014-10-01

295

44 CFR 73.4 - Restoration of flood insurance coverage.  

Code of Federal Regulations, 2011 CFR

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

2011-10-01

296

44 CFR 73.4 - Restoration of flood insurance coverage.  

Code of Federal Regulations, 2010 CFR

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

2010-10-01

297

44 CFR 73.4 - Restoration of flood insurance coverage.  

Code of Federal Regulations, 2012 CFR

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

2012-10-01

298

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

299

USDA's national aquaculture production outlook for 2006: Growth and expansion forecasted Still more imports Even with these changes, imports of aqua-  

E-print Network

USDA's national aquaculture production outlook for 2006: Growth and expansion forecasted Still more aquaculture operations were not severely impacted by storms. Factors for growth The overall picture of anticipated growth in the domestic aquaculture and seafood industries during 2006 is based on four major

Florida, University of

300

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

301

A methodology for urban flood resilience assessment  

NASA Astrophysics Data System (ADS)

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

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

2010-05-01

302

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

303

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

304

An Exploratory Study for Neural Network Forecasting of Retail Sales Trends Using Industry and National Economic Indicators  

E-print Network

An Exploratory Study for Neural Network Forecasting of Retail Sales Trends Using Industry networks (feed forward multi-layer perceptron and Elman recurrent networks) in forecasting sales trends and Elman recurrent neural networks show potential in being able to forecast sales trends with reasonable

Serpen, Gursel

305

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

Code of Federal Regulations, 2014 CFR

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

2014-10-01

306

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

Code of Federal Regulations, 2013 CFR

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

2013-10-01

307

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

Code of Federal Regulations, 2010 CFR

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

2010-10-01

308

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

Code of Federal Regulations, 2012 CFR

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

2012-10-01

309

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

Code of Federal Regulations, 2011 CFR

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

2011-10-01

310

ASMET: Flooding in West Africa  

NSDL National Science Digital Library

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

2014-09-14

311

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

312

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

NASA Astrophysics Data System (ADS)

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

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

2014-01-01

313

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

314

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

NASA Astrophysics Data System (ADS)

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

Cranston, Michael; Hu, Keming

2013-04-01

315

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.

316

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

NASA Astrophysics Data System (ADS)

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

Hartman, R. K.; Schaake, J.

2004-12-01

317

Estimating monetary damages from flooding under a changing climate  

NASA Astrophysics Data System (ADS)

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

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

2011-12-01

318

Real-time correction of water stage forecast during rainstorm events using combination of forecast errors  

Microsoft Academic Search

This study proposes a real-time error correction method for the forecasted water stage using a combination of forecast errors\\u000a estimated by the time series models, AR(1), AR(2), MA(1) and MA(2), and the average deviation model to update the water stage\\u000a forecast during rainstorm events. During flood forecasting and warning operations, the proposed real-time error correction\\u000a method takes advantage of being

Shiang-Jen Wu; Ho-Cheng Lien; Che-Hao Chang; Jhih-Cyuan Shen

319

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

320

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

USGS Publications Warehouse

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

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

2012-01-01

321

Cyber surveillance for flood disasters.  

PubMed

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

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

2015-01-01

322

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

NASA Astrophysics Data System (ADS)

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

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

2000-06-01

323

Flood monitoring over the Mackenzie River Basin using passive microwave data  

Microsoft Academic Search

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

Marouane Temimi; Robert Leconte; Francois Brissette; Naira Chaouch

2005-01-01

324

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

NASA Astrophysics Data System (ADS)

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

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

2012-04-01

325

Flash Flood Case Studies  

NSDL National Science Digital Library

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

2014-09-14

326

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

327

A case study of excessive rainfall forecasting  

Microsoft Academic Search

Summary Flash floods have been recognized as one of the most significant natural disaster problems in the world. Within the United States, the annual average flood death toll exceeds one hundred and property damage is on the order of a billion dollars. There has been an increased effort of the meteorological community to improve short term quantitative precipitation forecasting, principally

C.-B. Chang

1998-01-01

328

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

329

Tips for Media Professionals Potential Storm Surge Flooding  

E-print Network

Tips for Media Professionals Potential Storm Surge Flooding The Potential Storm Surge Flooding map) will issue the Potential Storm Surge Flooding map for areas where storm surge is possible for a given storm: » Land areas where, based on the latest NHC forecast, storm surge could occur. » How high above ground

330

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

331

Flood-inundation maps for the East Fork White River at Columbus, Indiana  

USGS Publications Warehouse

Digital flood-inundation maps for a 5.4-mile reach of the East Fork White River at Columbus, Indiana, from where the Flatrock and Driftwood Rivers combine to make up East Fork White River to just upstream of the confluence of Clifty Creek with the East Fork White River, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at USGS streamgage 03364000, East Fork White River at Columbus, Indiana. Current conditions at the USGS streamgage may be obtained on the Internet from the USGS National Water Information System (http://waterdata.usgs.gov/in/nwis/uv/?site_no=03364000&agency_cd=USGS&). The National Weather Service (NWS) forecasts flood hydrographs for the East Fork White River at Columbus, Indiana at their Advanced Hydrologic Prediction Service (AHPS) flood warning system Website (http://water.weather.gov/ahps/), that 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 calibrated by using the most current stage-discharge relation at USGS streamgage 03364000, East Fork White River at Columbus, Indiana. The calibrated hydraulic model was then used to determine 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from bankfull to approximately the highest recorded water level at the streamgage. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from Light Detection and Ranging (LiDAR) data), having a 0.37-ft vertical accuracy and a 1.02 ft horizontal accuracy), in order to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage at Columbus, Indiana, and forecasted stream 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.

Lombard, Pamela J.

2013-01-01

332

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

333

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

NASA Astrophysics Data System (ADS)

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

Hoss, F.; Fischbeck, P. S.

2014-10-01

334

Flash flood warning in ungauged basins by use of the flash flood guidance and model-based runoff thresholds  

Microsoft Academic Search

We investigate here the use of the Flash Flood Guidance (FFG) method and a method of model-based threshold runoff computation to improve the accuracy of flash flood forecasts at ungauged locations. The methodology proposed in this paper requires running a lumped hydrological model to derive flood frequencies at the outlet of the ungauged basin under consideration, and then to derive

Daniele Norbiato; Marco Borga; Roberto Dinale

2009-01-01

335

Forecast Technical Document Forecast Types  

E-print Network

ways of running a forecast on a forest component, depending on the source data and current land which details for the programmers how the Forecast System should handle, for each implemented Forecast the forecast are obtained from two sources: the Forestry Commission sub-compartment database (SCDB) for all

336

44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.  

Code of Federal Regulations, 2011 CFR

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

2011-10-01

337

44 CFR 67.4 - Proposed flood elevation determination.  

Code of Federal Regulations, 2011 CFR

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

2011-10-01

338

44 CFR 67.4 - Proposed flood elevation determination.  

Code of Federal Regulations, 2012 CFR

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

2012-10-01

339

44 CFR 64.3 - Flood Insurance Maps.  

Code of Federal Regulations, 2014 CFR

...2014-10-01 2014-10-01 false Flood Insurance Maps. 64.3 Section 64...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program COMMUNITIES ELIGIBLE FOR THE SALE OF INSURANCE § 64.3 Flood Insurance Maps. (a) The...

2014-10-01

340

44 CFR 67.4 - Proposed flood elevation determination.  

Code of Federal Regulations, 2010 CFR

...2010-10-01 2010-10-01 false Proposed flood elevation determination. 67.4 Section... INSURANCE AND HAZARD MITIGATION National Flood Insurance Program APPEALS FROM PROPOSED FLOOD ELEVATION DETERMINATIONS § 67.4...

2010-10-01

341

44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.  

Code of Federal Regulations, 2012 CFR

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

2012-10-01

342

44 CFR 61.17 - Group Flood Insurance Policy.  

Code of Federal Regulations, 2012 CFR

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

2012-10-01

343

44 CFR 61.17 - Group Flood Insurance Policy.  

Code of Federal Regulations, 2011 CFR

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

2011-10-01

344

44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.  

Code of Federal Regulations, 2013 CFR

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

2013-10-01

345

44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.  

Code of Federal Regulations, 2010 CFR

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

2010-10-01

346

44 CFR 64.3 - Flood Insurance Maps.  

Code of Federal Regulations, 2011 CFR

...2011-10-01 2011-10-01 false Flood Insurance Maps. 64.3 Section 64...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program COMMUNITIES ELIGIBLE FOR THE SALE OF INSURANCE § 64.3 Flood Insurance Maps. (a) The...

2011-10-01

347

44 CFR 64.3 - Flood Insurance Maps.  

Code of Federal Regulations, 2012 CFR

...2012-10-01 2011-10-01 true Flood Insurance Maps. 64.3 Section 64...INSURANCE AND HAZARD MITIGATION National Flood Insurance Program COMMUNITIES ELIGIBLE FOR THE SALE OF INSURANCE § 64.3 Flood Insurance Maps. (a) The...

2012-10-01

348

44 CFR 61.14 - Standard Flood Insurance Policy Interpretations.  

Code of Federal Regulations, 2014 CFR

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

2014-10-01

349

44 CFR 67.4 - Proposed flood elevation determination.  

Code of Federal Regulations, 2014 CFR

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

2014-10-01

350

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

351

Relationships between Return Period and Flash Flooding in the United States  

NASA Astrophysics Data System (ADS)

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

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

2013-12-01

352

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

353

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

Code of Federal Regulations, 2013 CFR

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

2013-10-01

354

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

Code of Federal Regulations, 2013 CFR

... 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...

2013-10-01

355

44 CFR 60.5 - Flood plain management criteria for flood-related erosion-prone areas.  

Code of Federal Regulations, 2012 CFR

... 1 2012-10-01 2011-10-01 true Flood plain management criteria for flood-related erosion-prone areas. 60.5 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND...

2012-10-01

356

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

Code of Federal Regulations, 2012 CFR

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

2012-10-01

357

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

Code of Federal Regulations, 2014 CFR

... 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...

2014-10-01

358

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

Code of Federal Regulations, 2012 CFR

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

2012-10-01

359

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

Code of Federal Regulations, 2014 CFR

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

2014-10-01

360

44 CFR 60.5 - Flood plain management criteria for flood-related erosion-prone areas.  

Code of Federal Regulations, 2014 CFR

... 1 2014-10-01 2014-10-01 false Flood plain management criteria for flood-related erosion-prone areas. 60.5 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND...

2014-10-01

361

44 CFR 60.5 - Flood plain management criteria for flood-related erosion-prone areas.  

Code of Federal Regulations, 2013 CFR

... 1 2013-10-01 2013-10-01 false Flood plain management criteria for flood-related erosion-prone areas. 60.5 Section...SECURITY INSURANCE AND HAZARD MITIGATION National Flood Insurance Program CRITERIA FOR LAND...

2013-10-01

362

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

363

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

Code of Federal Regulations, 2011 CFR

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

2011-10-01

364

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

Code of Federal Regulations, 2011 CFR

... 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...

2011-10-01

365

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

366

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

USGS Publications Warehouse

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

Wiley, J.B.

1994-01-01

367

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

PubMed Central

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

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

2013-01-01

368

FLOOD MANAGEMENT IN FINLAND - INTRODUCTION OF A NEW INFORMATION SYSTEM  

Microsoft Academic Search

In the near future, the importance of sound flood management is expected to rise in Finland, partly due to the proposed flood directive of the EU. Flood management requires usable and reliable information about produced scenarios and flood history. A national flood information system, based on GIS and Web technology, has been developed to bring together the essential information on

TANJA DUBROVIN; VILLE KESKISARJA; MIKKO SANE; JARI SILANDER

369

77 FR 67324 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013, 2014

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

2012-11-09

370

78 FR 8089 - Proposed Flood Elevation Determinations  

Federal Register 2010, 2011, 2012, 2013, 2014

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

2013-02-05

371

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

372

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

USGS Publications Warehouse

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

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

2014-01-01

373

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

E-print Network

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

Exeter, University of

374

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

USGS Publications Warehouse

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

Kelly, Brian P.; Huizinga, Richard J.

2008-01-01

375

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

E-print Network

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

Ganguly, Auroop Ratan

2002-01-01

376

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.

NASA Goddard Space Flight Center SVS

377

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

NASA Astrophysics Data System (ADS)

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

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

2009-12-01

378

Weather Forecast Data an Important Input into Building Management Systems  

E-print Network

Lewis Poulin Implementation and Operational Services Section Canadian Meteorological Centre, Dorval, Qc National Prediction Operations Division ICEBO 2013, Montreal, Qc October 10 2013 Version 2013-09-27 Weather Forecast Data An Important... and weather information ? Numerical weather forecast production 101 ? From deterministic to probabilistic forecasts ? Some MSC weather forecast (NWP) datasets ? Finding the appropriate data for the appropriate forecast ? Preparing for probabilistic...

Poulin, L.

2013-01-01

379

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

380

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

381

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

382

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

383

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.

384

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.'

2011-04-21

385

NINE FALLACIES OF FLOODS ROGER A. PIELKE, JR.  

E-print Network

NINE FALLACIES OF FLOODS ROGER A. PIELKE, JR. Environmental and Societal Impacts Group, National of the nation's flood problem. The fallacies are not universal, with many flood experts, decision makers of floods so as to create obstacles to improved utilization of the lessons of experience. This paper uses

Colorado at Boulder, University of

386

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 — from old weather proverbs to modern forecasting equipment — and how improvements in weather technology have saved lives by providing advance warning of natural hazards.

2014-09-18

387

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

388

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.; Schwein, Noreen O.; Shadie, Charles E.

2012-01-01

389

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

NASA Astrophysics Data System (ADS)

Flooding has always been a major risk world-wide. Humans chose to live and develop settlements close to water (rivers, seas) due to the resources water brings, i.e. food, energy, capacity to economically transport persons and goods, and recreation. However, the risk from flooding, including pluvial flooding, often offsets these huge advantages.