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Special Issue on

Applications of Machine Learning and Artificial Intelligence Methods for Sustainable Water Resource Management




The ability to deal with big data and solve complex hydrological problems has improved due to the advances in modern computation facilities and machine-learning approaches. This progress has simplified the handling of complicated problems in areas of water resource management, including issues in hydrological simulation, fluid flow in different mediums (especially porous), and surface and sub-surface detailed characterizations. With this in mind, machine-learning methods have been widely developed to utilize available big data from sources including sensors, drones, satellite images, geographical data, etc., and also to explore the relationship between affecting parameters.  

In this Special Issue, authors are invited to submit their recent and novel papers on the applications of machine-learning methods using big data being to tackle the serious global concerns of water resources and related issues. Papers that present innovative machine-learning solutions for issues that have not yet been addressed or those that utilize conventional solutions for huge computational power are welcomed. We will also accept papers on physics-based simulations combined with machine learning models in the areas of water resources and subsurface systems.

We are pleased to invite you to submit a manuscript to Water Science and Technology for peer review and possible publication in a Special Issue entitled 'Applications of Machine Learning and Artificial intelligence methods for Sustainable Water Resources Management'.


Relevant topics include:

  • Hydrologic forecasting (modelling stream flow, sediment, groundwater, lake levels, evaporation, evapotranspiration etc.) with advanced MLM,
  • Implementation of MLM with new metaheuristic algorithms in WR,
  • Reservoir operation using Mas,
  • Ensemble modeling procedure with MLM in WR,
  • Application of conjunction MLM such as wavelet or EEMD based MLM,
  • Ways to address scale dependencies between punctual and areal measurements of the water cycle.


Key dates:

Deadline for manuscript submission: 25 May 2023.

Expected publication: Accepted papers will be published online as soon as possible.


Guest Editors:

  • Prof. Mohammad Hossein Ahmadi, Shahrood University of Technology, Iran
  • Prof. Giulio Lorenzini, University of Parma, Italy
  • Prof. Süheyla Yerel Kandemir, Bilecik Şeyh Edebali University, Turkey
  • Prof. Hafiz Muhammad Ali, King Fahd University of Petroleum and Minerals, Saudi Arabia


How to submit:

Please make sure that your paper follows the Instructions to Authors of the journal, before submitting your paper directly to Water Science and Technology’s peer review system. Then choose the article type ‘Special Issue Article OA’ and the submission category ‘Special Issue: Machine Learning and Artificial Intelligence’. This will send your paper to one of the Guest Editors.

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