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Water Supply Special Issue on


Theoretical Analysis and Applications of Artificial Intelligence in Hydrology and Water Resource Management




In the past decades, a variety of advanced artificial intelligence methods have been successfully developed to help understand or simulate the real-world physical features of the complicated hydrodynamic process in nature, like artificial neural network, support vector machine, deep learning machine, Bayesian network, Markov model, Kalman Filter, chaos theory, and Gaussian process regression. Generally, the artificial intelligence methods can effectively simulate the nonlinear relationship between the input variables and output variables by learning the valuable knowledge from a large amount of data samples. In recent years, due to the comprehensive influences of human activities and climate variation, the traditional methods may fail to produce satisfying performances for the practical engineering problems (like regression or classification) in the hydrology and water resources fields under the changing environments. Then, more attention has been paid to the emerging artificial intelligence methods in hydrology and water resource management, producing an increasing number of research results around the world. Under this realistic background, the Special Issue (SI) is organized to provide a platform for knowledge sharing and scientific communication about the state-of-the-art theoretical analysis and applications of artificial intelligence in hydrology and water resource management.


Topics of interest for the special issue include but are not limited to the following areas:

  • Hydrology-based artificial intelligence theories
  • Emerging artificial intelligence methods in hydrology and water resource management
  • Swarm intelligence in hydrology and water resource management
  • Parallel computing in hydrology and water resource management
  • Big data and machine learning in hydrology and water resource management
  • Hydrological forecasting via artificial intelligence


Key dates

  • Deadline for paper submission: December 31, 2021
  • Expected Publication: July 2022


How to submit:

Please make sure that your paper follows the Instructions to Authors, before submitting your paper directly to Water Supply’s peer review system:

You should then select the article type – ‘Special Issue Article OA’ and the submission category – ‘Special Issue: Hydrology and Water Resource Management’. This will send your paper to one of the Guest Editors.


Guest Editors

Shiping Wen, University of Technology Sydney, Australia

Zhong-kai Feng, Hohai University, China
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