Next Generation Technologies toward Smarter/Intelligent Water Management and Disaster Risks Forecasting and Assessment Systems
A special issue of Climate (ISSN 2225-1154).
Deadline for manuscript submissions: closed (31 January 2023) | Viewed by 534
Special Issue Editors
Interests: urban sustainability; nature-based solutions; air pollution, greenhouse gases emission and energy management; sustainable use of energy
Special Issues, Collections and Topics in MDPI journals
2. Laboratório de Inteligência Artificial e Ciência de Computadores (LIACC), University of Porto, 4200-465 Porto, Portugal
Interests: artificial intelligence; computer vision; machine learning; algorithms; ubicomp and IoT systems
Special Issues, Collections and Topics in MDPI journals
Interests: water resources management; semiarid regions hydrology; hydrologic processes; climate change; hydrologic modeling; water quality
Special Issues, Collections and Topics in MDPI journals
2. Laboratório de Inteligência Artificial e Ciência de Computadores (LIACC), University of Porto, 4200-465 Porto, Portugal
Interests: applying machine learning together with reflective middleware and software architectures for building and managing intelligent and sensing dynamically adaptable distributed, ubiquitous and IoT systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Climate change and the expected increasing pressure on water resources pose new and ever-demanding challenges to the development of public policies and systems towards more resilient urban environments. Next-generation solutions for smarter water management systems need to cope with the protection of people in vulnerable situations and those affected by the economic losses caused by water-related disasters. Climate disaster risk assessment and intelligent mitigation countermeasures need to be integrated into the priorities for clean water and sanitation policies at the local level to make cities and human settlements more inclusive, safe, resilient and sustainable. Artificial intelligence, and, in particular, machine learning-based tools and solutions will contribute to a broader and faster assessment of the risks and impacts of water-related hazards. The collection of open-source datasets and the provision of new machine learning pipeline tools will promote active citizen and researcher participation, fostering capacity building for sustainable urban planning and disaster preparedness, and support better informed urban management plans and policies.
We invite contributions to this Special Issue exploring and combining the complexity of existing and new effective tools and methods, sharing critical thinking approaches and applying knowledge towards the protection and mitigation of impacts from water-related disasters.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Water-related hazard risk assessment and mitigation;
- Machine learning pipelines applied to water-related disaster risk assessment;
- Low-impact development solutions;
- Artificial intelligence-based tools and solutions for water-related applications;
- Internet of Things (IoT) architectures for monitoring and managing water flows and public sewage systems;
- Deep learning exploitation for parameterizing hydrologic–hydraulic models;
- Decision support systems for water resources management;
- Active citizen participation for water-related disaster preparedness;
- Capacity building for sustainable urban planning.
We look forward to receiving your contributions.
Dr. Gisela Marta Oliveira
Dr. José Manuel Manuel Torres
Dr. Maria Simas Guerreiro
Dr. Rui S. Moreira
Guest Editors
Manuscript Submission Information
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Keywords
- water-related hazards
- risks assessment
- machine learning pipelines
- artificial intelligence
- Internet of Things (IoT) architectures
- deep learning exploitation
- hydrologic-hydraulic models
- decision support systems
- water resources management
- sustainable urban planning
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