Short Term Reservoirs Operation On The Seine River: Performance Analysis Of Tree-Based Model Predictive Control

The Seine River, in France, flows through territories of large economic value, among which the metropolitan area of Paris. A system of four reservoirs operates upstream to regulate the river flows in order to protect the area against extreme events, such as floods and droughts. Current reservoirs management is based on reactive filling curves, designed from an analysis of historical hydrological regimes. The efficiency of this management strategy is jeopardized when inflows are significantly different from their seasonal average. To improve the current management strategy, we investigated the use of Tree-Based Model Predictive Control (TB-MPC). TB-MPC is a proactive and centralized method that uses information available in real-time, as ensemble weather forecasts. Reservoir management is tested under past hydro-climatic conditions using time series of ensemble weather forecasts produced by ECMWF (European Centre for Medium-Range Weather Forecasts) and weather observations. The performance of TB-MPC is compared to that of deterministic Model Predictive Control (MPC), showing the benefits of considering forecasts uncertainty by using ensemble forecasts

Variationnal parameters estimation of a distributed hydrological model

Le but de ces travaux est d'expérimenter une méthode d'estimation variationnelle pour calibrer les paramètres d'un modèle hydrologique distribué et conceptuel conçu pour la modélisation des crues éclairs. Cette étape est difficile. Des incertitudes quant à la modélisation des processus hydrologiques existent, le nombre de paramètres à déterminer est très grand et les méthodes de calage classiques ne sont pas adaptées. Le modèle est défini sur une grille rectangulaire de résolution 1km2 sur laquelle trois paramètres sont associés à chaque cellule. 23 bassins-versants "aval" contenant 118 sous-bassins emboîtés "amont" ont été étudiés. Pour chaque bassin-versant, des données de débits au niveau des stations de jaugeage, des observations de pluies issues des radars météorologiques et l'estimation de l'évapotranspiration sont disponibles au pas de temps horaire. Le calage variationnel minimise une fonction objectif qui pénalise l'écart entre les variables observées et simulées. Les bénéfices d'un calage distribué par rapport à un calage uniforme des paramètres sont évalués en terme de performances prédictives en validation temporelle et spatiale. Le calage distribué des paramètres sur les bassins "aval" permet d'améliorer les prédictions des débits aux exutoires "amont" utilisés pour la validation. La variabilité spatiale des paramètres optimisés semble représenter certaines caractéristiques hydrologiques des bassins-versants étudiés. Les résultats sont positifs et les perspectives sont encourageantes pour développer des approches permettant de régionaliser les valeurs des paramètres ou bien d'assimiler des observations en temps réel pour faire de la prévisionCalibration of a conceptual hydrological and distributed model is challenging due to a number of reasons, which include fundamental (model adequacy, identifiability) and algorithmic (e.g. local-search versus global-search) issues. The aim of this research work is to investigate the potential of the variational approach for calibrating a simple continuous hydrological model involved in several flash-flood modelling applications. This model is defined on a rectangular 1km2 resolution grid, with three parameters being associated to each cell. 23 watersheds are chosen as the study benchmark. For these watersheds, the discharge observations at several gauging stations, gridded rainfall and potential evapotranspiration estimates are continuously available at an hourly time step. In the variational approach one looks for the optimal solution by minimizing the standard quadratic cost-function which penalizes the misfit between the observed and predicted values. In numerical experiments, the benefits of using the distributed against the uniform calibration are measured in terms of the model predictive performance, in temporal, spatial and spatio-temporel validation. Overall, distributed calibration shows encouraging results, providing better model predictions and relevant spatial distribution of some parameters. Future perspectives are identified, such as the development of a regionalisation approach for the model parameters or real-time assimilation of observations in order to produce forecast

Does Flash Flood Model Performance Increase with Complexity? Signature and Sensitivity-Based Comparison of Conceptual and Process-Oriented Models on French Mediterranean Cases

International audienceWe compare three hydrological models of different complexities, GR4H (lumped, continuous), SMASH (distributed, continuous), and MARINE (distributed, event-based), for Mediterranean flash flood modeling. The objective was to understand how differently they simulate the catchment’s behavior, in terms of outlet discharge and internal dynamics, and how these can help to improve the relevance of the models. The methodology involved global sensitivity analysis, calibration/validation, and signature comparison at the event scale with good performances. For all models, we found transfer parameters to be sensitive in the case of Gardon and production parameters in the case of Ardeche. The non-conservative flow component of GR4H was found to be sensitive and could benefit the distributed models. At the event scale, the process-based MARINE model at finer resolution outperformed the two continuous hourly models at flood peak and its timing. SMASH, followed by GR4H, performed better in the volume of water exported. Using the operational surface model SIM2 to benchmark the soil moisture simulated by the three models, MARINE (initialized with SIM1) emerged as the most accurate. GR4H followed closely, while SMASH was the least accurate. Flexible modeling and regionalization should be developed based on multi-source signatures and worldwide physiographic databases

SMASH -SPATIALLY DISTRIBUTED MODELLING AND ASSIMILATION FOR HYDROLOGY: PYTHON WRAPPING TOWARDS ENHANCED RESEARCH-TO-OPERATIONS TRANSFER

International audienceThe distributed SMASH platform is based on a gridded mesh and on a modular design. On each cell, the model features different hydrological components. Each component offers different modeling options such as snow modules, surface interception, production, transfer and percolation functions. At the grid scale, different routing models are implemented via a cell-to-cell numerical routing scheme. S MASH comes with its numerical adjoint model which is obtained by automatic differentiation with Tapenade. A variational data assimilation algorithm is implemented and helps to calibrate the distributed parameters or evaluate the model states. This algorithm uses the quasi-Newton lbfgs-b descent algorithm and the gradient of the cost function relative to the model parameters and states. This gradient is computed by a run of the adjoint model. T he numerical SMASH platform is a Fortran code. To gain in modularity and facilitate the use of SMASH in the research and engineering communities, a Python interface has been created with the new F90Wrap software. The original Fortran code has been revamped. The new structure enables to 1) control any inputs and outputs with Python, 2) keep an automatically differentiable and computationally efficient numerical Fortran model, 3) call a binary from the shell to preserve a backward compatibility with old practices. T he key to achieve this Python interface is to use Fortran modules and derived types to store all inputs and outputs variables. These Fortran structures are stored in different modules. F 90Wrap automatically generates the fortran functions and wrappers to give access to every component of each derived type. A Python class is generated to facilitate the use of these wrappers inside a Python code. T he Python object "model" aggregates all inputs/outputs variables required by SMASH. The "model" object comes with built-in methods to allow end users to perform simulations, calibrations, plotting and hdf5 export. The Python binding facilitates all post-processing since it does not requires I/O into text files anymore

Climate change impact on the management of water resources in the Seine River Basin

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On the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchment

International audienceCalibration of a conceptual distributed model is challenging due to a number of reasons, which include fundamental (model adequacy and identifiability) and algorithmic (e.g., local search vs. global search) issues. The aim of the presented study is to investigate the potential of the variational approach for calibrating a simple continuous hydrological model (GRD; Genie Rural distributed involved in several flash flood modeling applications. This model is defined on a rectangular 1 km(2) resolution grid, with three parameters being associated with each cell. The Gardon d'Anduze watershed (543 km( )(2)) is chosen as the study benchmark. For this watershed, the discharge observations at five gauging stations, gridded rainfall and potential-evapotranspiration estimates are continuously available for the 2007-2018 period at an hourly time step.In the variational approach one looks for the optimal solution by minimizing the standard quadratic cost function, which penalizes the misfit between the observed and predicted values, under some additional a priori constraints. The cost function gradient is efficiently computed using the adjoint model. In numerical experiments, the benefits of using the distributed against the uniform calibration are measured in terms of the model predictive performance, in temporal, spatial and spatiotemporal validation, both globally and for particular flood events. Overall, distributed calibration shows encouraging results, providing better model predictions and relevant spatial distribution of some parameters. The numerical stability analysis has been performed to understand the impact of different factors on the calibration quality. This analysis indicates the possible directions for future developments, which may include considering a non-Gaussian likelihood and upgrading the model structure

CRUES, PARTIE II : Genèse, propagation et prévision des crues à Montpellier.

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Two recent hydrological post event campaigns in France: the Cèze and Ardèche august 2018 and Aude october 2018 floods

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Two recent hydrological post event campaigns in France: the Cèze and Ardèche august 2018 and Aude october 2018 floods

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