Authors:
Baya Hadid
and
Eric Duviella
Affiliation:
Institut Mines Telecom Lille Douai, Univ. Lille and France
Keyword(s):
Modelling, Water Management, Rainfall/Runoff Model, Optimization, Large Scale Systems, Water System.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Environmental Monitoring and Control
;
Formal Methods
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Planning and Scheduling
;
Signal Processing, Sensors, Systems Modeling and Control
;
Simulation and Modeling
;
Symbolic Systems
Abstract:
Hydrographical networks are large scale systems that are used to answer to the Human uses. They are impacted by extreme events that should be bigger due to climate change. By focusing on extreme rainy events, the amount of water in excess has to be dispatched on all the network to avoid flood, and then rejected to the sea heeding the tides. Pumps can also be used to reject the water to the sea but they lead to big operating cost. To deal with this challenging issue, the modelling tools and the water asset management strategies that have been recently proposed are adapted and improved in this paper. They consist in an integrated model, a flow-based network and a quadratic optimization based on constrains. The efficiency of this water management strategy requires an accurate predictive rainfall/runoff model. It is highlighted by considering a realistic case study that is also used to describe all the methodology step.