A Past Discharges Assimilation System for Ensemble Streamflow Forecasts over France - Part 1: Description and Validation of the Assimilation System

Two Ensemble Streamflow Prediction Systems (ESPSs) have been set up at Météo-France. They are based on the French SIM distributed hydrometeorological model. A deterministic analysis run of SIM is used to initialize the two ESPSs. In order to obtain a better initial state, a past discharges assimilation system has been implemented into this analysis SIM run, using the Best Linear Unbiased Estimator (BLUE). Its role is to improve the model soil moisture by using streamflow observations in order to better simulate streamflow. The skills of the assimilation system were assessed for a 569-day period on six different configurations, including two different physics schemes of the model (the use of an exponential profile of hydraulic conductivity or not) and, for each one, three different ways of considering the model soil moisture in the BLUE state variables. Respect of the linearity hypothesis of the BLUE was verified by assessing of the impact of iterations of the BLUE. The configuration including the use of the exponential profile of hydraulic conductivity and the combination of the moisture of the two soil layers in the state variable showed a significant improvement of streamflow simulations. It led to a significantly better simulation than the reference one, and the lowest soil moisture corrections. These results were confirmed by the study of the impacts of the past discharge assimilation system on a set of 49 independent stations.JRC.H.7-Climate Risk Managemen

A past discharges assimilation system for ensemble streamflow forecasts over France – Part 1: Description and validation of the assimilation system

International audienceTwo Ensemble Streamflow Prediction Systems (ESPSs) have been set up at M´et´eo-France. They are based on the French SIM distributed hydrometeorological model. A deterministic analysis run of SIM is used to initialize the two ESPSs. In order to obtain a better initial state, a past discharges assimilation system has been implemented into this analysis SIM run, using the Best Linear Unbiased Estimator (BLUE). Its role is to improve the model soil moisture by using streamflow observations in order to better simulate streamflow. The skills of the assimilation system were assessed for a 569-day period on six different configurations, including two different physics schemes of the model (the use of an exponential profile of hydraulic conductivity or not) and, for each one, three different ways of considering the model soil moisture in the BLUE state variables. Respect of the linearity hypothesis of the BLUE was verified by assessing of the impact of iterations of the BLUE. The configuration including the use of the exponential profile of hydraulic conductivity and the combination of the moisture of the two soil layers in the state variable showed a significant improvement of streamflow simulations. It led to a significantly better simulation than the reference one, and the lowest soil moisture corrections. These results were confirmed by the study of the impacts of the past discharge assimilation system on a set of 49 independent stations

A Past Discharge Assimilation System for Ensemble Streamflow Forecasts over France - Part 2: Impact on the Ensemble Streamflow Forecasts

The use of ensemble streamflow forecasts is developing in the international flood forecasting services. Ensemble streamflow forecast systems can provide more accurate forecasts and useful information about the uncertainty of the forecasts, thus improving the assessment of risks. Nevertheless, these systems, like all hydrological forecasts, suffer from errors on initialization or on meteorological data, which lead to hydrological prediction errors. This article, which is the second part of a 2-part article, concerns the impacts of initial states, improved by a streamflow assimilation system, on an ensemble streamflow prediction system over France. An assimilation system was implemented to improve the streamflow analysis of the SAFRAN-ISBA-MODCOU (SIM) hydro-meteorological suite, which initializes the ensemble streamflow forecasts at Météo-France. This assimilation system, using the Best Linear Unbiased Estimator (BLUE) and modifying the initial soil moisture states, showed an improvement of the streamflow analysis with low soil moisture increments. The final states of this suite were used to initialize the ensemble streamflow forecasts of Météo-France, which are based on the SIM model and use the European Centre for Medium-range Weather Forecasts (ECMWF) 10-day Ensemble Prediction System (EPS). Two different configurations of the assimilation system were used in this study: the first with the classical SIM model and the second using improved soil physics in ISBA. The effects of the assimilation system on the ensemble streamflow forecasts were assessed for these two configurations, and a comparison was made with the original (i.e. without data assimilation and without the improved physics) ensemble streamflow forecasts. It is shown that the assimilation system improved most of the statistical scores usually computed for the validation of ensemble predictions (RMSE, Brier Skill Score and its decomposition, Ranked Probability Skill Score, False Alarm Rate, etc.), especially for the first few days of the time range. The assimilation was slightly more efficient for small basins than for large ones.JRC.H.7-Climate Risk Managemen

A past discharge assimilation system for ensemble streamflow forecasts over France – Part 2: Impact on the ensemble streamflow forecasts

International audienceThe use of ensemble streamflow forecasts is developing in the international flood forecasting services. Ensemble streamflow forecast systems can provide more accurate forecasts and useful information about the uncertainty of the forecasts, thus improving the assessment of risks. Nevertheless, these systems, like all hydrological forecasts, suffer from errors on initialization or on meteorological data, which lead to hydrological prediction errors. This article, which is the second part of a 2-part article, concerns the impacts of initial states, improved by a streamflow assimilation system, on an ensemble streamflow prediction system over France. An assimilation system was implemented to improve the streamflow analysis of the SAFRAN-ISBAMODCOU (SIM) hydro-meteorological suite, which initializes the ensemble streamflow forecasts at M´et´eo-France. This assimilation system, using the Best Linear Unbiased Estimator (BLUE) and modifying the initial soil moisture states, showed an improvement of the streamflow analysis with low soil moisture increments. The final states of this suite were used to initialize the ensemble streamflow forecasts of M´et´eo-France, which are based on the SIM model and use the European Centre for Medium-range Weather Forecasts (ECMWF) 10-day Ensemble Prediction System (EPS). Two different configurations of the assimilation system were used in this study: the first with the classical SIM model and the second using improved soil physics in ISBA. The effects of the assimilation system on the ensemble streamflow forecasts were assessed for these two configurations, and a comparison was made with the original (i.e. without data assimilation and without the improved physics) ensemble streamflow forecasts. It is shown that the assimilation system improved most of the statistical scores usually computed for the validation of ensemble predictions (RMSE, Brier Skill Score and its decomposition, Ranked Probability Skill Score, False Alarm Rate, etc.), especially for the first few days of the time range. The assimilation was slightly more efficient for small basins than for large ones

Hydrology modelling R packages: a unified analysis of models and practicalities from a user perspective

Following the rise of R as a scientific programming language, the increasing requirement for more transferable research, and the growth of data availability in hydrology, R packages containing hydrological models are becoming more and more available to hydrologists. Corresponding to the core of the hydrological studies workflow, their value is increasingly meaningful regarding the reliability of methods and results. Despite package and model distinctiveness, no study has ever 5 provided a comparison of R packages for conceptual rainfall-runoff modelling from a user perspective, contrasting their philosophy, model characteristics and ease of use. We have selected eight packages based on our ability to consistently run their models on simple hydrology modelling examples. We have uniformly analysed the exact structure of seven of the hydrological models integrated in these R packages in terms of conceptual storages and fluxes, spatial discretisation, data requirements and output provided. The analysis showed that very different modelling choices are associated with these packages, which emphasises various hydrological concepts. These specificities are not always sufficiently well explained by the package documentation. Therefore a synthesis of the package functionalities was performed from a user perspective. This synthesis helps inform selection of what packages could/should be used depending on the problem at hand. In this regard, technical features, documentation, R implementations and computational times were investigated. Moreover, by providing a framework for package comparison, this study is a step forward towards supporting more transferable and reusable methods and results for hydrological modelling in R

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

Use of expert elicitation to assign weights to climate and hydrological models in climate impact studies

Various methods are available for assessing uncertainties in climate impact studies. Among such methods, model weighting by expert elicitation is a practical way to provide a weighted ensemble of models for specific real-world impacts. The aim is to decrease the influence of improbable models in the results and easing the decision-making process. In this study both climate and hydrological models are analysed, and the result of a research experiment is presented using model weighting with the participation of six climate model experts and six hydrological model experts. For the experiment, seven climate models are a priori selected from a larger EURO-CORDEX (Coordinated Regional Downscaling Experiment - European Domain) ensemble of climate models, and three different hydrological models are chosen for each of the three European river basins. The model weighting is based on qualitative evaluation by the experts for each of the selected models based on a training material that describes the overall model structure and literature about climate models and the performance of hydrological models for the present period. The expert elicitation process follows a three-stage approach, with two individual rounds of elicitation of probabilities and a final group consensus, where the experts are separated into two different community groups: a climate and a hydrological modeller group. The dialogue reveals that under the conditions of the study, most climate modellers prefer the equal weighting of ensemble members, whereas hydrological-impact modellers in general are more open for assigning weights to different models in a multi-model ensemble, based on model performance and model structure. Climate experts are more open to exclude models, if obviously flawed, than to put weights on selected models in a relatively small ensemble. The study shows that expert elicitation can be an efficient way to assign weights to different hydrological models and thereby reduce the uncertainty in climate impact. However, for the climate model ensemble, comprising seven models, the elicitation in the format of this study could only re-establish a uniform weight between climate models.This work was funded by the project AQUA-CLEW, which is part of ERA4CS (European Research Area for Climate Services), an ERANET (European Research Area Net-work) initiated by JPI Climate (Joint Programming Initiative) andfunded by Formas (Sweden); German Aerospace Center (DLR, Germany); Ministry of Education, Science and Research (BMBWF,Austria); Innovation Fund Denmark; Ministry of Economic Affairs and Digital Transformation (MINECO, Spain); and French National Research Agency with co-funding by the European Commission (grant no. 69046). The contribution of Philippe Lucas-Picher was supported by the French National Research Agency (future investment programme no. ANR-18-MPGA-0005). Rafael Pimentel acknowledges funding by the Modality 5.2 of the Programa Propio 2018 of the University of Córdoba and the Juan de la Cierva Incorporación programme of the Ministry of Science and Innovation (grant no. IJC2018-038093-I). Rafael Pimentel and María J. Polo are members of DAUCO (Unit of Excellence reference no. CEX2019-000968-M), with financial support from the Spanish Ministry of Science and Innovation and the Spanish State Research Agency, through the Severo Ochoa Centre of Excellence and María de Maeztu Unit of Excellence in research and development (R&D)

Le partage de la ressource en eau sur la Durance en 2050 : vers une évolution du mode de gestion des grands ouvrages duranciens ?

Congrès SHF: Water Tensions in Europe and in the Mediterranean: water crisis by 2050?, Paris, FRA, 08-/10/2015 - 09/10/2015International audienceUne vision prospective de la gestion de l'eau du bassin de la Durance et des territoires alimentés par ses eaux à l'horizon 2050 a été élaborée, appuyée par une chaine de modèles incluant des représentations du climat, de la ressource naturelle, des demandes en eau et du fonctionnement des grands ouvrages hydrauliques (Serre-Ponçon, Castillon et Sainte-Croix), sous contraintes de respect des débits réservés, de cotes touristiques dans les retenues et de restitution d'eau stockée pour des usages en aval. Cet ensemble, validé en temps présent, a été alimenté par des projections climatiques et paramétré pour intégrer les évolutions du territoire décrites par des scénarios de développement socio-économique avec une hypothèse de conservation des règles de gestion actuelles. Les résultats suggèrent à l'horizon 2050 : une hausse de la température moyenne de l'air impactant l'hydrologie de montagne ; une évolution incertaine des précipitations ; une réduction des stocks de neige et une fonte avancée dans l'année qui induisent une réduction des débits au printemps ; une diminution de la ressource en eau en période estivale ; une diminution de la demande globale en eau à l'échelle du territoire, cette demande étant fortement conditionnée par les scénarios territoriaux élaborés ici ; la satisfaction des demandes en eau en aval des ouvrages considérées comme prioritaires, au détriment de la production d'énergie en hiver (flexibilité moindre en période de pointe) et du maintien de cotes touristiques en été ;une diminution de la production d'énergie due notamment à la réduction des apports en amont des ouvrages hydroélectriques