scholarly journals The benefit of high-resolution operational weather forecasts for flash flood warning

2008 ◽  
Vol 12 (4) ◽  
pp. 1039-1051 ◽  
Author(s):  
J. Younis ◽  
S. Anquetin ◽  
J. Thielen

Abstract. In Mediterranean Europe, flash flooding is one of the most devastating hazards in terms of loss of human life and infrastructures. Over the last two decades, flash floods have caused damage costing a billion Euros in France alone. One of the problems of flash floods is that warning times are very short, leaving typically only a few hours for civil protection services to act. This study investigates if operationally available short-range numerical weather forecasts together with a rainfall-runoff model can be used for early indication of the occurrence of flash floods. One of the challenges in flash flood forecasting is that the watersheds are typically small, and good observational networks of both rainfall and discharge are rare. Therefore, hydrological models are difficult to calibrate and the simulated river discharges cannot always be compared with ground measurements. The lack of observations in most flash flood prone basins, therefore, necessitates the development of a method where the excess of the simulated discharge above a critical threshold can provide the forecaster with an indication of potential flood hazard in the area, with lead times of the order of weather forecasts. This study is focused on the Cévennes-Vivarais region in the Southeast of the Massif Central in France, a region known for devastating flash floods. This paper describes the main aspects of using numerical weather forecasting for flash flood forecasting, together with a threshold – exceedance. As a case study the severe flash flood event which took place on 8–9 September 2002 has been chosen. Short-range weather forecasts, from the Lokalmodell of the German national weather service, are used as input for the LISFLOOD model, a hybrid between a conceptual and physically based rainfall-runoff model. Results of the study indicate that high resolution operational weather forecasting combined with a rainfall-runoff model could be useful to determine flash floods more than 24 h in advance.

2008 ◽  
Vol 5 (1) ◽  
pp. 345-377 ◽  
Author(s):  
J. Younis ◽  
S. Anquetin ◽  
J. Thielen

Abstract. In Mediterranean Europe, flash flooding is one of the most devastating hazards in terms of human life loss and infrastructures. Over the last two decades, flash floods brought losses of a billion Euros of damage in France alone. One of the problems of flash floods is that warning times are very short, leaving typically only a few hours for civil protection services to act. This study investigates if operationally available shortrange numerical weather forecasts together with a rainfall-runoff model can be used as early indication for the occurrence of flash floods. One of the challenges in flash flood forecasting is that the watersheds are typically small and good observational networks of both rainfall and discharge are rare. Therefore, hydrological models are difficult to calibrate and the simulated river discharges cannot always be compared with ground "truth". The lack of observations in most flash flood prone basins, therefore, lead to develop a method where the excess of the simulated discharge above a critical threshold can provide the forecaster with an indication of potential flood hazard in the area with leadtimes of the order of the weather forecasts. This study is focused on the Cévennes-Vivarais region in the Southeast of the Massif Central in France, a region known for devastating flash floods. The critical aspects of using numerical weather forecasting for flash flood forecasting are being described together with a threshold – exceedance. As case study the severe flash flood event which took place on 8–9 September 2002 has been chosen. The short-range weather forecasts, from the Lokalmodell of the German national weather service, are driving the LISFLOOD model, a hybrid between conceptual and physically based rainfall-runoff model. Results of the study indicate that high resolution operational weather forecasting combined with a rainfall-runoff model could be useful to determine flash floods more than 24 hours in advance.


2020 ◽  
Author(s):  
Takahiro Sayama ◽  
Masafumi Yamada ◽  
Yoshito Sugawara ◽  
Dai Yamazaki

Abstract The heavy rain event of July 2018 and Typhoon Hagibis in October 2019 caused severe flash flood disasters in numerous parts of western and eastern Japan. Flash floods need to be predicted over a wide range with long forecasting lead time for effective evacuation. The predictability of flash floods caused by the two extreme events are investigated by using a high-resolution (~150 m) nationwide distributed rainfall-runoff model forced by ensemble precipitation forecasts with 39-h lead time. Results of the deterministic simulation at nowcasting mode with radar and gauge composite rainfall could reasonably simulate the storm runoff hydrographs at many dam reservoirs over western Japan for the case of heavy rainfall in 2018 (F18) with the default parameter setting. For the case of Typhoon Hagibis in 2019 (T19), a similar performance was obtained by incorporating unsaturated flow effect in the model applied to Kanto region. The performance of the ensemble forecast was evaluated based on the bias ratios and the relative operating characteristic curves, which suggested the higher predictability in peak runoff for T19. For the F18, the uncertainty arises due to the difficulty in accurately forecasting the storm positions by the frontal zone; as a result, the actual distribution of the peak runoff could not be well forecasted. Overall, this study showed that the predictability of flash floods was different between the two extreme events. The ensemble spreads contain quantitative information of predictive uncertainty, which can be utilized for the decision making of emergency responses against flash floods.


2020 ◽  
Author(s):  
Takahiro Sayama ◽  
Masafumi Yamada ◽  
Yoshito Sugawara ◽  
Dai Yamazaki

Abstract The heavy rain event of July 2018 and Typhoon Hagibis in October 2019 caused severe flash flood disasters in numerous parts of western and eastern Japan. Flash floods need to be predicted over a wide range with long forecasting lead time for effective evacuation. The predictability of flash floods caused by the two extreme events are investigated by using a high-resolution (~ 150 m) nationwide distributed rainfall-runoff model forced by ensemble precipitation forecasts with 39-h lead time. Results of the deterministic simulation at nowcasting mode with radar and gauge composite rainfall could reasonably simulate the storm runoff hydrographs at many dam reservoirs over western Japan for the case of heavy rainfall in 2018 (F18) with the default parameter setting. For the case of Typhoon Hagibis in 2019 (T19), a similar performance was obtained by incorporating unsaturated flow effect in the model applied to Kanto region. The performance of the ensemble forecast was evaluated based on the bias scores and the relative operating characteristic curves, which suggested the higher predictability in peak runoff for T19. For the F18, the uncertainty arises due to the difficulty in accurately forecasting the storm positions by the frontal zone; as a result, the actual distribution of the peak runoff could not be well forecasted. Overall, this study showed that the predictability of flash floods was different between the two extreme events. The ensemble spreads contain quantitative information of predictive uncertainty, which can be utilized for the decision making of emergency responses against flash floods.


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Takahiro Sayama ◽  
Masafumi Yamada ◽  
Yoshito Sugawara ◽  
Dai Yamazaki

AbstractThe heavy rain event of July 2018 and Typhoon Hagibis in October 2019 caused severe flash flood disasters in numerous parts of western and eastern Japan. Flash floods need to be predicted over a wide range with long forecasting lead time for effective evacuation. The predictability of flash floods caused by the two extreme events is investigated by using a high-resolution (~ 150 m) nationwide distributed rainfall-runoff model forced by ensemble precipitation forecasts with 39 h lead time. Results of the deterministic simulation at nowcasting mode with radar and gauge composite rainfall could reasonably simulate the storm runoff hydrographs at many dam reservoirs over western Japan for the case of heavy rainfall in 2018 (F18) with the default parameter setting. For the case of Typhoon Hagibis in 2019 (T19), a similar performance was obtained by incorporating unsaturated flow effect in the model applied to Kanto Region. The performance of the ensemble forecast was evaluated based on the bias ratios and the relative operating characteristic curves, which suggested the higher predictability in peak runoff for T19. For the F18, the uncertainty arises due to the difficulty in accurately forecasting the storm positions by the frontal zone; as a result, the actual distribution of the peak runoff could not be well forecasted. Overall, this study showed that the predictability of flash floods was different between the two extreme events. The ensemble spreads contain quantitative information of predictive uncertainty, which can be utilized for the decision making of emergency responses against flash floods.


2009 ◽  
Vol 4 (4) ◽  
pp. 600-605 ◽  
Author(s):  
Hadi Kardhana ◽  
◽  
Akira Mano ◽  

Numerical weather prediction (NWP) is useful in flood prediction using a rainfall-runoff model. Uncertainty occurring in the forecast, however, adversely affects flood prediction accuracy, in addition to uncertainty inherent in the rainfall-runoff model. Clarifying this uncertainty and its magnitude is expected to lead to wider forecast applications. Taking the case of Japan’s Shichikashuku Dam, 6 flood events between 2002 and 2007 were analyzed. NWP was based on short-range forecasts by the Japan Meteorological Agency (JMA). The rainfall-runoff model is based on a distributed tank model. This research calculates uncertainty by identifying and quantifying the relative error of forecasts by a) NWP and b) the runoff model. Results showed that NAP is the main cause of flood forecast uncertainty. They also showed the correlation between forecast lead time and uncertainty. Uncertainty rises with longer lead time, corresponding to the magnitude of observed discharge and precipitation.


10.29007/tfbm ◽  
2018 ◽  
Author(s):  
Julia Kasper ◽  
Georg Pranner ◽  
Franz Simons ◽  
Michael Denhard ◽  
Carsten Thorenz

Heavy rainfall can cause large variations in the water level of navigable waterways when a lot of urban runoff is generated on sealed surfaces and discharged into the river. Due to climate change, extreme weather events will increase in intensity and frequency demanding a better automated water level control at impounded waterways. High- resolution forecasts of catchment rainfall are intended to serve as input to a rainfall- runoff model. Based on the resulting discharge forecasts, a model predictive feed forward controller calculates the ideal water level and discharge across the barrage. The control system is completed by a PI control loop. In this way water level deviations and discharge peaks resulting from stormwater overflow events can be reduced, which enhances the safety of shipping. Regarding the uncertainties of weather predictions, the consequences of an underestimated or overestimated overflow discharge are investigated.


2017 ◽  
Author(s):  
Guillaume Le Bihan ◽  
Olivier Payrastre ◽  
Eric Gaume ◽  
David Moncoulon ◽  
Frederic Pons

Abstract. Up to now, flash flood monitoring and forecasting systems, based on rainfall radar measurements and distributed rainfall-runoff models, generally aimed at estimating flood magnitudes - typically discharges or return periods – at selected river cross-sections. The approach presented here goes one step ahead by proposing an integrated forecasting chain for the direct assessment of flash flood possible impacts on inhabited areas (number of buildings at risk in the presented case studies). The proposed approach includes, in addition to a distributed rainfall-runoff model, an automatic hydraulic method suited for the computation of flood extent maps on a dense river network and over large territories. The resulting catalogue of flood extent maps is then combined with land use data to build a flood impact curve for each considered river reach: i.e. number of inundated buildings versus discharge. Theses curves are finally used to compute estimated impacts based on forecasted discharges. The approach has been extensively tested in the regions of Alès and Draguignan, located in the South of France, where well documented major flash floods recently occurred. The article presents two types of validation results. First, the automatically computed flood extent maps and corresponding water levels are tested against rating curves at available river gauging stations as well as against local reference or observed flood extent maps. Second, a rich and comprehensive insurance claim database is used to evaluate the relevance of the estimated impacts for some recent major floods.


2020 ◽  
Author(s):  
Maryse Charpentier-Noyer ◽  
François Bourgin ◽  
Geoffroy Kirstetter ◽  
Olivier Delestre ◽  
Pierre Brigode

<p>The vulnerability of the French Riviera to hydro meteorological hazards has been dramatically illustrated by the flash floods of October 3, 2015: 20 people were killed and the cost of the direct damages were higher than 600 million euros. Due to their fast dynamics, flash floods are difficult to predict and leave little time for forecasting. In this context, it is needed to improve real-time simulations to enable a short-range anticipation of the consequences of these phenomena. The main goal of this work was to test a hydrologic-hydraulic coupling in order to assess whether this coupling can be used for real-time forecasting purposes. The coupling is composed for the hydrological part of the event-based spatially distributed rainfall-runoff model Cinecar and for the hydraulic part of the Basilisk software, which is based on 2D hydraulic modelling (finite volume methods for shallow water equations) with adaptive grid refinement. The main interest of this coupling method is the compromise obtained between calculation time and precision. The rainfall-runoff model is run on the upstream part of the domain and feeds the hydraulic model applied in the downstream part. The rainfall-runoff model makes it possible to estimate very quickly the streamflow temporal evolution, while the hydraulic model, although much slower when applied at high spatial resolution (up to 4m), makes it possible to have water level and velocity at any point of the downstream area. The application of this coupling approach is presented for three basins severely affected by the October 2015 flash floods: the Brague (68 km²), the Frayère (22 km²) and the Riou de l’Argentière (48 km²) catchments. The results obtained for the three basins are compared with information gathered from post-event surveys, particularly the high water level marks. A particular attention is also put on computation times in order to evaluate the possibilities of real-time simulation. The results show promising performances both in terms of calculation time but also in terms of accuracy of the simulated flood areas and water levels.</p>


2002 ◽  
Vol 6 (2) ◽  
pp. 267-284 ◽  
Author(s):  
M.C. Rulli ◽  
R. Rosso

Abstract. A stochastic rainfall generator and a deterministic rainfall-runoff model, both distributed in space and time, are combined to provide accurate flood frequency prediction in the Bisagno River basin (Thyrrenian Liguria, N.W. Italy). The inadequacy of streamflow records with respect to the return period of the required flow discharges makes the stochastic simulation methodology a useful operational alternative to a regionalisation procedure for flood frequency analysis and derived distribution techniques. The rainfall generator is the Generalized Neyman-Scott Rectangular Pulses (GNSRP) model. The rainfall-runoff model is the FEST98 model. The GNSRP generator was calibrated using a continuous 7-years' record of hourly precipitation measurements at five raingauges scattered over the Bisagno basin. The calibrated rainfall model was then used to generate a 1000 years' series of continuous rainfall data at the gauging sites and a flood-oriented model validation procedure was developed to evaluate the agreement between observed and simulated extreme values of rainfall at different scales of temporal aggregation. The synthetic precipitation series were input to the FEST98 model to provide flood hydrographs at selected cross-sections across the river network. Flood frequency analysis of the annual flood series (AFS) obtained from these simulations was undertaken using L-moment estimations of Generalized Extreme Value (GEV) distributions. The results are compared with those determined by applying a regional flood analysis in Thyrrhenian Liguria and the derived distribution techniques to the Bisagno river basin. This approach is also useful to assess the effects of changes in land use on flood frequency regime (see Rosso and Rulli, 2002). Keywords: flood frequency, stochastic rainfall generator, distributed rainfall runoff model, derived distribution


2017 ◽  
Vol 21 (11) ◽  
pp. 5911-5928 ◽  
Author(s):  
Guillaume Le Bihan ◽  
Olivier Payrastre ◽  
Eric Gaume ◽  
David Moncoulon ◽  
Frédéric Pons

Abstract. Up to now, flash flood monitoring and forecasting systems, based on rainfall radar measurements and distributed rainfall–runoff models, generally aimed at estimating flood magnitudes – typically discharges or return periods – at selected river cross sections. The approach presented here goes one step further by proposing an integrated forecasting chain for the direct assessment of flash flood possible impacts on inhabited areas (number of buildings at risk in the presented case studies). The proposed approach includes, in addition to a distributed rainfall–runoff model, an automatic hydraulic method suited for the computation of flood extent maps on a dense river network and over large territories. The resulting catalogue of flood extent maps is then combined with land use data to build a flood impact curve for each considered river reach, i.e. the number of inundated buildings versus discharge. These curves are finally used to compute estimated impacts based on forecasted discharges. The approach has been extensively tested in the regions of Alès and Draguignan, located in the south of France, where well-documented major flash floods recently occurred. The article presents two types of validation results. First, the automatically computed flood extent maps and corresponding water levels are tested against rating curves at available river gauging stations as well as against local reference or observed flood extent maps. Second, a rich and comprehensive insurance claim database is used to evaluate the relevance of the estimated impacts for some recent major floods.


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