scholarly journals Enhancing Automated Water Level Control at Navigable Waterways by High-Resolution Weather Predictions

10.29007/tfbm ◽  
2018 ◽  
Author(s):  
Julia Kasper ◽  
Georg Pranner ◽  
Franz Simons ◽  
Michael Denhard ◽  
Carsten Thorenz
Keyword(s):  
High Resolution ◽  
Water Level ◽  
Extreme Weather Events ◽  
Rainfall Runoff ◽  
Level Control ◽  
Weather Events ◽  
Rainfall Runoff Model ◽  
Feed Forward Controller ◽  
Runoff Model ◽  
The Ideal

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.

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
Keyword(s):  
High Resolution ◽  
Short Range ◽  
Weather Forecasting ◽  
Flash Flood ◽  
Flash Floods ◽  
Rainfall Runoff ◽  
Weather Forecasts ◽  
Numerical Weather ◽  
Rainfall Runoff Model ◽  
Runoff Model

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.

scholarly journals Application of Conceptual Rainfall-Runoff Model METQ for Simulation of Daily Runoff and Water Level: The case of the Lake Burtnieks Watershed

2008 ◽  
Vol 62 (1-2) ◽  
pp. 47-54
Author(s):  
Elga Apsīte ◽  
Ansis Zīverts ◽  
Anda Bakute
Keyword(s):  
Water Level ◽  
Correlation Coefficient ◽  
Model Calibration ◽  
Performance Model ◽  
Model Structure ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Parameter Values ◽  
Runoff Model ◽  
Gauging Station

Application of Conceptual Rainfall-Runoff Model METQ for Simulation of Daily Runoff and Water Level: The case of the Lake Burtnieks Watershed In this study a conceptual rainfall-runoff METQ model—the latest version METQ2007BDOPT—was applied to simulate the daily runoff and water level of the Lake Burtnieks watershed from 1990 to 1999. The model structure and parameters were basically the same as in the METQ98, with some additional improvements and semi-automatical calibration performance. Model calibration was done for four rivers and one lake gauging station. The results of calibration showed a good correlation between the measured and simulated daily discharges. The Nash-Sutcliffe efficiency R2 varied from 0.90 to 0.58 and correlation coefficient r from 0.95 to 0.83. The highest values of R2 = 0.90 and r = 0.95 were obtained for the River Salaca and the lowest R2 = 0.53 and r = 0.83 for Lake Burtnieks. We observed some relationships between the model parameter values and physiographic characteristic of the sub-catchments.

Hydrologic-hydraulic coupling for flash flood real-time simulation: Application to the October 2015 French Riviera floods

2020 ◽  
Author(s):  
Maryse Charpentier-Noyer ◽  
François Bourgin ◽  
Geoffroy Kirstetter ◽  
Olivier Delestre ◽  
Pierre Brigode
Keyword(s):  
Water Level ◽  
Real Time ◽  
Flash Floods ◽  
Rainfall Runoff ◽  
Calculation Time ◽  
Time Simulation ◽  
Hydraulic Coupling ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
French Riviera

<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>

A software-based sensor for combined sewer overflows

2012 ◽  
Vol 66 (7) ◽  
pp. 1475-1482 ◽  
Author(s):  
G. Leonhardt ◽  
S. Fach ◽  
C. Engelhard ◽  
H. Kinzel ◽  
W. Rauch
Keyword(s):  
Water Level ◽  
Simulation Models ◽  
Rainfall Runoff ◽  
Combined Sewer Overflows ◽  
Quality Model ◽  
Level Data ◽  
Water Level Data ◽  
Combined Sewer ◽  
Rainfall Runoff Model ◽  
Runoff Model

A new methodology for online estimation of excess flow from combined sewer overflow (CSO) structures based on simulation models is presented. If sufficient flow and water level data from the sewer system is available, no rainfall data are needed to run the model. An inverse rainfall-runoff model was developed to simulate net rainfall based on flow and water level data. Excess flow at all CSO structures in a catchment can then be simulated with a rainfall-runoff model. The method is applied to a case study and results show that the inverse rainfall-runoff model can be used instead of missing rain gauges. Online operation is ensured by software providing an interface to the SCADA-system of the operator and controlling the model. A water quality model could be included to simulate also pollutant concentrations in the excess flow.

scholarly journals Considering rating curve uncertainty in water level predictions

2013 ◽  
Vol 17 (11) ◽  
pp. 4415-4427 ◽  
Author(s):  
A. E. Sikorska ◽  
A. Scheidegger ◽  
K. Banasik ◽  
J. Rieckermann
Keyword(s):  
Water Level ◽  
Bayesian Framework ◽  
Water Levels ◽  
Model Parameters ◽  
Calibration Data ◽  
Rainfall Runoff ◽  
Rating Curve ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

Abstract. Streamflow cannot be measured directly and is typically derived with a rating curve model. Unfortunately, this causes uncertainties in the streamflow data and also influences the calibration of rainfall-runoff models if they are conditioned on such data. However, it is currently unknown to what extent these uncertainties propagate to rainfall-runoff predictions. This study therefore presents a quantitative approach to rigorously consider the impact of the rating curve on the prediction uncertainty of water levels. The uncertainty analysis is performed within a formal Bayesian framework and the contributions of rating curve versus rainfall-runoff model parameters to the total predictive uncertainty are addressed. A major benefit of the approach is its independence from the applied rainfall-runoff model and rating curve. In addition, it only requires already existing hydrometric data. The approach was successfully demonstrated on a small catchment in Poland, where a dedicated monitoring campaign was performed in 2011. The results of our case study indicate that the uncertainty in calibration data derived by the rating curve method may be of the same relevance as rainfall-runoff model parameters themselves. A conceptual limitation of the approach presented is that it is limited to water level predictions. Nevertheless, regarding flood level predictions, the Bayesian framework seems very promising because it (i) enables the modeler to incorporate informal knowledge from easily accessible information and (ii) better assesses the individual error contributions. Especially the latter is important to improve the predictive capability of hydrological models.

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

2008 ◽  
Vol 5 (1) ◽  
pp. 345-377 ◽  
Author(s):  
J. Younis ◽  
S. Anquetin ◽  
J. Thielen
Keyword(s):  
High Resolution ◽  
Weather Forecasting ◽  
Flash Flood ◽  
Flood Forecasting ◽  
Flash Floods ◽  
Rainfall Runoff ◽  
Weather Forecasts ◽  
Numerical Weather ◽  
Rainfall Runoff Model ◽  
Runoff Model

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.

scholarly journals Flood Simulations in Mid-Latitude Agricultural Land Using Regional Current and Future Extreme Weathers

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2421
Author(s):  
Nobuaki Kimura ◽  
Hirohide Kiri ◽  
Sachie Kanada ◽  
Iwao Kitagawa ◽  
Ikuo Yoshinaga ◽  
...  
Keyword(s):  
Agricultural Land ◽  
Climate Model ◽  
Flood Disaster ◽  
Rainfall Data ◽  
Extreme Weather Events ◽  
Rainfall Runoff ◽  
The Future ◽  
Flood Simulations ◽  
Rainfall Runoff Model ◽  
Runoff Model

Recent extreme weather events like the August 2016 flood disaster have significantly affected farmland in mid-latitude regions like the Tokachi River (TR) watershed, the most productive farmland in Japan. The August 2016 flood disaster was caused by multiple typhoons that occurred in the span of two weeks and dealt catastrophic damage to agricultural land. This disaster was the focus of our flood model simulations. For the hydrological model input, the rainfall data with 0.04° grid space and an hourly interval were provided by a regional climate model (RCM) during the period of multiple typhoon occurrences. The high-resolution data can take account of the geographic effects, hardly reproduced by ordinary RCMs. The rainfall data drove a conceptual, distributed rainfall–runoff model, embedded in the integrated flood analysis system. The rainfall–runoff model provided discharges along rivers over the TR watershed. The RCM also provided future rainfall data with pseudo-global warming climate, assuming that the August 2016 disaster could reoccur again in the late 21st century. The future rainfall data were used to conduct a future flood simulation. With bias corrections, current and future flood simulations showed the potential inundated areas along riverbanks based on flood risk levels. The crop field-based agricultural losses in both simulations were estimated. The future cost may be two to three times higher as indicated by slightly higher simulated future discharge peaks in tributaries.

scholarly journals Considering rating curve uncertainty in water level predictions

2013 ◽  
Vol 10 (3) ◽  
pp. 2955-2986 ◽  
Author(s):  
A. E. Sikorska ◽  
A. Scheidegger ◽  
K. Banasik ◽  
J. Rieckermann
Keyword(s):  
Water Level ◽  
Bayesian Framework ◽  
Water Levels ◽  
Model Parameters ◽  
Calibration Data ◽  
Rainfall Runoff ◽  
Rating Curve ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

Abstract. Streamflow cannot be measured directly and is typically derived with a rating curve model. Unfortunately, this causes uncertainties in the streamflow data and also influences the calibration of rainfall-runoff models if they are conditioned on such data. However, it is currently unknown to what extent these uncertainties propagate to rainfall-runoff predictions. This study therefore presents a quantitative approach to rigorously consider the impact of the rating curve on the prediction uncertainty of water levels. The uncertainty analysis is performed within a formal Bayesian framework and the contributions of rating curve versus rainfall-runoff model parameters to the total predictive uncertainty are addressed. A major benefit of the approach is its independence from the applied rainfall-runoff model and rating curve. In addition, it only requires already existing hydrometric data. The approach was successfully tested on a small urbanized basin in Poland, where a dedicated monitoring campaign was performed in 2011. The results of our case study indicate that the uncertainty in calibration data derived by the rating curve method may be of the same relevance as rainfall-runoff model parameters themselves. A conceptual limitation of the approach presented is that it is limited to water level predictions. Nevertheless, regarding flood level predictions, the Bayesian framework seems very promising because it (i) enables the modeler to incorporate informal knowledge from easily accessible information and (ii) better assesses the individual error contributions. Especially the latter is important to improve the predictive capability of hydrological models.

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