Extrapolation of rating curves by hydraulic modelling, with application to flood frequency analysis

Lang, Michel; Pobanz, Karine; Renard, Benjamin; Renouf, Elodie; Sauquet, Éric

doi:10.1080/02626667.2010.504186

Cited by 89 publications

(86 citation statements)

References 46 publications

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“…These measurements and the representativeness of sampling could partly explain why some water seems to be missing at the end of the simulated floods. Another good example of observation problems is given by Lang et al (2010), who raise the issue of uncertainty associated with the extrapolation of the rating curve and its impact on the estimation of high discharge values. They show how the uncertainty of the estimation of flood quantiles can be limited with a mixed approach, using hydraulic modelling and a proper statistical description of hydrological data to better define the rating curve.…”

Section: How Bizarre Is Bizarre In Fact?mentioning

confidence: 99%

The Court of Miracles of Hydrology: can failure stories contribute to hydrological science?

Andréassian¹,

Perrin²,

Parent

et al. 2010

Hydrological Sciences Journal

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Section: How Bizarre Is Bizarre In Fact?mentioning

confidence: 99%

The Court of Miracles of Hydrology: can failure stories contribute to hydrological science?

Andréassian¹,

Perrin²,

Parent

et al. 2010

Hydrological Sciences Journal

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“…Further, stream flows that were estimated using the conventional rating curve (from Water Resources Agency, Taiwan) are demonstrated in Figure 12. By comparison with the discharges from ADCP, flood estimations based on extrapolated part of the rating curve show significant credibility gaps [4], with a large statistical error of NRMSE = 42.2%. The ADIS indirect flow measurement can be utilized to improve stage-discharge relationships and reduce uncertainties associated with flood discharges [31].…”

Section: Discharge Estimationmentioning

confidence: 97%

“…In this study, a velocity-index relationship for ADIS was established based on the depth-averaged velocity derived from the ADCP cross-sectional measurement results. Once the correction factor is obtained, river discharges can be readily estimated from the surface velocities using Equations (3) and (4). Note that velocity fields from concurrent surveys with a standard velocity-area method [26] were also employed to calculate total river discharge (sum of products of depth-averaged velocity and area in divided subsections) for further comparison (or validation).…”

Section: (Ii) Image Mappingmentioning

confidence: 99%

“…Besides, recourse will be made to maintain the reliable rating curve for a natural river (which often presents changing characteristics due to channel encroachment, dredging, weed growth, or other reasons). However, these intrusive approaches would hinder direct measurements under extreme weather, posing the concern of great uncertainties and questionable accuracy in extrapolated high flow rates [4].…”

Section: Introductionmentioning

confidence: 99%

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Application of an Automated Discharge Imaging System and LSPIV during Typhoon Events in Taiwan

Huang

Young

Liu

2018

Water

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An automated discharge imaging system (ADIS), which is a non-intrusive and safe approach, was developed for measuring river flows during flash flood events. ADIS consists of dual cameras to capture complete surface images in the near and far fields. Surface velocities are accurately measured using the Large Scale Particle Image Velocimetry (LSPIV) technique. The stream discharges are then obtained from the depth-averaged velocity (based upon an empirical velocity-index relationship) and cross-section area. The ADIS was deployed at the Yu-Feng gauging station in Shimen Reservoir upper catchment, northern Taiwan. For a rigorous validation, surface velocity measurements were conducted using ADIS/LSPIV and other instruments. In terms of the averaged surface velocity, all of the measured results were in good agreement with small differences, i.e., 0.004 to 0.39 m/s and 0.023 to 0.345 m/s when compared to those from acoustic Doppler current profiler (ADCP) and surface velocity radar (SVR), respectively. The ADIS/LSPIV was further applied to measure surface velocities and discharges during typhoon events (i.e., Chan-Hom, Soudelor, Goni, and Dujuan) in 2015. The measured water level and surface velocity both showed rapid increases due to flash floods. The estimated discharges from ADIS/LSPIV and ADCP were compared, presenting good consistency with correlation coefficient R = 0.996 and normalized root mean square error NRMSE = 7.96%. The results of sensitivity analysis indicate that the components till (τ) and roll (θ) of the camera are most sensitive parameters to affect the surface velocity using ADIS/LSPIV. Overall, the ADIS based upon LSPIV technique effectively measures surface velocities for reliable estimations of river discharges during typhoon events.

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“…Hydrological and hydraulic modelling uncertainty (including parameter uncertainty) is far from being negligible either. Modelling improvement but also model updating and post-processing are still active research fields [e. g. @ 6RPH PRUH µRSHUDWLRQDO ¶ XQFHUWDLQW\ sources should not be forgotten, such as real-time observation uncertainty or rating curve uncertainty which can become very significant when it comes to large floods [8].…”

Section: Operational Forecasts Uncertainty Sourcesmentioning

confidence: 99%

Operational forecast uncertainty assessment for better information to stakeholders and crisis managers

Berthet

Piotte²,

Gaumé³

et al. 2016

E3S Web Conf.

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Abstract. Flood forecasting uncertainty is crucial information for decision makers. However, deterministic only forecasts have been communicated in France until now, like in many other countries. The French Flood Forecast Centres (FFCs) recently set up a new service which aims at publishing quantitative forecasts along with their associated uncertainty. Two surveys (one of the greater audience and identified end-users, another of FFCs worldwide) were conducted to design it. The forecasters' toolbox was then supplemented with two new tools. The first one provides automatic forecasting uncertainty estimations calibrated on past forecasting error series. The second one allows the forecasters to incorporate their own expertise to adjust the automatically calculated uncertainty estimation. The evaluation of the forecast uncertainty estimations issued in real time in 2014 suggests that even if these assessments are perfectible, they are already informative and useful for end-users. The first feedbacks from forecasters and crisis managers also show that if the assessment of probabilistic forecasts remains a technical challenge, their use is foremost a human challenge. This move is a paradigm change for both forecasters and decision makers. Therefore, they have to be accompanied in order to achieve this deep shift in their professional practice.

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Extrapolation of rating curves by hydraulic modelling, with application to flood frequency analysis

Cited by 89 publications

References 46 publications

The Court of Miracles of Hydrology: can failure stories contribute to hydrological science?

The Court of Miracles of Hydrology: can failure stories contribute to hydrological science?

Application of an Automated Discharge Imaging System and LSPIV during Typhoon Events in Taiwan

Operational forecast uncertainty assessment for better information to stakeholders and crisis managers

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