Optimal and centralized reservoir management for drought and flood protection on the upper Seine-Aube river system using stochastic dual dynamic programming

Autor: David Dorchies, Luciano Raso, M. Chiavico
Přispěvatelé: Delft University of Technology (TU Delft), ENI SAN DONATO MILANESE ITA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Gestion de l'Eau, Acteurs, Usages (UMR G-EAU), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management, American Society of Civil Engineers, 2019, 145 (3), pp.05019002. ⟨10.1061/(ASCE)WR.1943-5452.0001040⟩
ISSN: 0733-9496
Popis: International audience; The basin of the Seine River is an extremely important economic region for France and Europe. Four reservoirs are operated to reduce the natural variability of the Seine River, reducing both flood and drought risk. Presently, reservoir operation is not centrally coordinated, and release rules are based on empirical rule curves. This study presents the setting of an optimal and centralized solution to the problem of reservoir operation on the Upper Seine-Aube river system, found by applying the stochastic dual dynamic programming (SDDP) procedure. The novelty of this study lies on the combination of reservoir and hydraulic models in SDDP for flood and drought protection. Including the hydraulic process in SDDP is required for estimating flood and drought at different locations along the river, and for representing the delay between the release from the reservoirs and their effects downstream. The study case covers the Seine basin until the confluence with the Aube River: this system includes two reservoirs, the city of Troyes, France, and, at the confluence of the two rivers, the nuclear power plant at Nogent-Sur-Seine. Results shows that the SDDP solution can be effectively used to optimize the operation of a water system made of multiple reservoirs and multiple hydraulic transfer components, solving a relatively large stochastic dynamic programming problem in an acceptable time. The management obtained from SDDP rules exploits the centralized operation and, compared to the current operational rules, results in more frequent but shorter, less intense, and less severe flood and drought events at Nogent-Sur-Seine.
Databáze: OpenAIRE