Étude du risque d'inondation d'un site industriel par des crues extrêmes : de l'évaluation des valeurs extrêmes aux incertitudes hydrologiques et hydrauliques

Alliau, Damien; Seine, Jacques De Saint; Lang, Michel; Sauquet, Éric; Renard, Benjamin

doi:10.1051/lhb/20150021

Cited by 7 publications

(6 citation statements)

References 3 publications

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“…1. This type of general protocol for GSA has already been applied to 1D hydraulic model [Iooss, 2011;Nguyen et al, 2015;Alliau et al, 2015]. Common aspects arise between 1D and 2D models hydraulic application to implement a GSA approach and are described step by step below: The first step (Step i, in fig.…”

Section: Protocol Applied For Gsa With 2d Hydraulic Modelsmentioning

confidence: 99%

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Global sensitivity analysis with 2d hydraulic codes: applied protocol and practical tool

et al. 2015

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Global Sensitivity Analysis (GSA) methods are useful tools to rank input parameters uncertainties regarding their impact on result variability. In practice, such type of approach is still at an exploratory level for studies relying on 2D Shallow Water Equations (SWE) codes as GSA requires specific tools and deals with important computational capacity. The aim of this paper is to provide both a protocol and a tool to carry out a GSA for 2D hydraulic modelling applications. A coupled tool between Prométhée (a parametric computation environment) and FullSWOF 2D (a code relying on 2D SWE) has been set up: Prométhée-FullSWOF 2D (P-FS). The main steps of our protocol are: i) to identify the 2D hydraulic code input parameters of interest and to assign them a probability density function, ii) to propagate uncertainties within the model, and iii) to rank the effects of each input parameter on the output of interest. For our study case, simulations of a river flood event were run with uncertainties introduced through three parameters using P-FS tool. Tests were performed on regular computational mesh, spatially discretizing an urban area, using up to 17.9 million of computational points. P-FS tool has been installed on a cluster for computation. Method and P-FS tool successfully allow the computation of Sobol indices maps. Keywords Uncertainty, flood hazard modelling, global sensitivity analysis, 2D shallow water equation, Sobol index.

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Section: Protocol Applied For Gsa With 2d Hydraulic Modelsmentioning

confidence: 99%

“…The coupling procedure has taken advantage of previous coupling experience of Promthe with 1D SWE based hydraulic code [Nguyen et al, 2015;Alliau et al, 2015]. The coupled code Prométhée-FullSWOF (P-FS) has been performed on a HPC computation structure.…”

Section: Operational Tool and Setupmentioning

confidence: 99%

Global sensitivity analysis with 2d hydraulic codes: applied protocol and practical tool

et al. 2015

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“…Le projet a montré l'intérêt de la distribution prédictive pour améliorer notamment l'estimation de lois GEV ou GP calées sur un échantillon local. Il n'en reste pas moins que les incertitudes de modélisation restent encore difficiles à appréhender (Alliau et al, 2014).…”

Section: Conclusion Et Pistes De Rechercheunclassified

Résultats du projet ExtraFlo (ANR 2009-2013) sur l'estimation des pluies et crues extrêmes

et al. 2014

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Cette communication présente les principaux résultats du projet ExtraFlo sur l'estimation des pluies et crues extrêmes. A partir d'un jeu de données conséquent de plusieurs milliers de stations, une procédure d'inter-comparaison a permis d'évaluer les performances d'une trentaine d'implémentations différentes issues de différentes combinaisons (modèle probabiliste, méthode d'estimation, cadre local / régional / mixte local et régional). Le projet ExtraFlo a permis de mettre en évidence le manque de robustesse des approches basées sur le traitement statistique d'une série de quelques dizaines d'années d'observation. Des alternatives intéressantes existent, basées sur l'exploitation des records de pluie et de débit à l'échelle d'une région, de la collecte de données historiques quand cela est possible, de méthodes de simulation basées sur le couplage d'un générateur d'averses avec un modèle hydrologique pour la transformation des pluies en débit, ou des traces morphologiques laissées par les crues anciennes. Mots-clés : pluies extrêmes, crues extrêmes, justesse, robustesse, comparaison de méthodes, distribution prédictive Main results of a French project on extreme rainfall and flood assessment ABSTRACT.-This paper presents a comparison of models for extreme rainfall and flood values. Based on a large set of thousands of rainfall and discharge data, the French ExtraFlo project showed that design estimate of extreme values based on the fitting of a distribution on a limited sample of maximum values is very inaccurate when only a few decades of observation are available. Some interesting alternatives are possible, using a regional approach, or historical data when available, or simulation methods, or sedimentological or geochemical signatures of flood deposits.

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“…On the other hand, stochastic models introduce various techniques for flood estimation, ranging from simple regression of discharge to detailed modeling of hydrological processes. However, stochastic models are criticized for being more data-intensive, requiring in-situ observation data to ensure reliable predictions [13,14]. A variety of stochastic models have been proposed for hydrological flow prediction.…”

Section: Introductionmentioning

confidence: 99%

Forecasting Lake Nokoué Water Levels Using Long Short-Term Memory Network

Dabire,

Ezin,

Firmin

2024

Preprint

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The prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of lake Nokoue in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Lake Nokoue, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.

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Étude du risque d'inondation d'un site industriel par des crues extrêmes : de l'évaluation des valeurs extrêmes aux incertitudes hydrologiques et hydrauliques

Cited by 7 publications

References 3 publications

Global sensitivity analysis with 2d hydraulic codes: applied protocol and practical tool

Global sensitivity analysis with 2d hydraulic codes: applied protocol and practical tool

Résultats du projet ExtraFlo (ANR 2009-2013) sur l'estimation des pluies et crues extrêmes

Forecasting Lake Nokoué Water Levels Using Long Short-Term Memory Network

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