Smart Water Management and Flood Mitigation
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Resources Management, Policy and Governance".
Deadline for manuscript submissions: closed (9 June 2022) | Viewed by 24885
Special Issue Editors
Interests: large-scale systems – hydrographical systems; reactive control strategies; supervision and prognosis; identification
Interests: large-scale systems management; real-time control of water networks; optimization-based control and state estimation; fault detection and localization
Special Issue Information
Dear Colleagues,
This Special Issue of Water will focus on flood mitigation strategies for open-channel systems based on water flow forecasting, simulation, and control. Several approaches based on artificial intelligence (AI), operations research (OR), and automatic control (AC) are sufficiently mature to develop intelligent management systems to address flood mitigation challenges. An accurate forecast of water entries caused by rain events, based on predictive models, could be helpful to optimize water distribution among the hydraulic network and the available storage areas. Moreover, this should limit the degree of uncertainty that must be compensated using robust, stochastic, and/or learning-based control techniques to fulfill the operational goals. Accurate simulations based on digital twins (DT) of hydrographical networks aim to improve decision tools for managers, allowing to i) analyze past events and guarantee the return of experience, ii) design and test advanced control and optimization approaches, iii) determine the robustness to uncertainties, and iv) anticipate extreme events that might lead to floods. Although this Special Issue may appear to be broad in scope, contributions in all these specific fields are required to design complete flood mitigation strategies.
The Guest Editors are seeking papers that tackle the issue of flood mitigation in open-channel systems, and which deal with runoff forecasts, use of DT as simulation tools, and optimal and predictive control strategies (possibly dealing with uncertainty) for sustainable water resource management. Submissions addressing any of these topics or connecting different approaches using a conceptual framework are encouraged.
Prof. Dr. Eric Duviella
Dr. Pablo Segovia
Guest Editors
Manuscript Submission Information
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Keywords
- large-scale complex systems – open-channel systems
- water management – flood mitigation
- predictive modeling – rainfall/runoff models, identification, bayesian models
- model predictive and optimization-based control – decentralized and distributed control, data-based control, intelligent decision support systems
- computational intelligence in control – reinforcement learning, stochastic
- digital implementation – digital twin, simulation
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