Artificial Intelligence and Machine Learning (AI/ML) in Climate Change Impacts Analysis
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Air, Climate Change and Sustainability".
Deadline for manuscript submissions: closed (1 November 2023) | Viewed by 8569
Special Issue Editor
Interests: hydroclimatology; climate change impacts assessment; bias correction; downscaling; analysis of hydroclimatic extremes; analysis of floods and droughts; sea level rise; statistical methods; probabilistic prediction and uncertainty quantification; remote sensing applications in hydrology; AI/ML in hydroclimatology
Special Issue Information
Dear Colleagues,
Artificial intelligence/Machine Learning (AI/ML) approaches are proven to have great potential in understanding many complex phenomena with a wide range of computational challenges. With the availability of a large set of observed and simulated records of hydrological, meteorological and climatological variables, AI/ML approaches have a huge potential scope in climate change impact analysis.
Towards this aim, several AI/ML approaches, such as Artificial Neural Network (ANN), Support Vector Machines (SVMs), Relevance Vector Machines (RVMs), Deep Learning (DL), and Reinforcement Learning (RL), etc., have been found to yield undeniable performances and are now being widely applied by many researchers in many different parts of the globe.
Our interest lies primarily in the data-sparse regions across the world to showcase the potential of AI/ML approaches in climate change impact analysis.
The overall purpose of this Special Issue is to showcase the potential of AI/ML approaches in modelling different hydroclimatic processes all across the world.
We welcome original research articles and reviews for this Special Issue. Research areas may include (but are not limited to) the following:
i) Extreme events in a changing climate
ii) Flood and drought analyses
iii) Streamflow assessment
iv) Reservoir operation
v) Future climate and hydrology
vi) Change in precipitation
vii) Case studies on climate change impact assessment
viii) Mitigation strategies
ix) Policy making
x) Remote sensing applications
xi) Surface and ground water management under climate change
We look forward to receiving your contributions.
Dr. Rajib Maity
Guest Editor
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Keywords
- climate change
- hydrology
- meteorology
- extreme events
- artificial intelligence
- machine learning
- AI/ML
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