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Babak Mohammadi

Doctoral student

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Application of Machine Learning and Remote Sensing in Hydrology

Author

  • Babak Mohammadi

Summary, in English

Water is vital to all life on earth, but its management is becoming more difficult owing to the behavior of water in nature such as water dynamics, water movements, and different forms of water in nature. In addition, population growth, the impact of climate change, and the inappropriate use of water resources add more complexity to water resource management. The integration of natural sciences necessitates creative methods in decision sciences, data processing, and modeling methodologies. The prediction of such occurrences is a highly nonlinear problem that requires the use of modern capable techniques. For handling the abovementioned items, we need to use tools capable of solving water-based issues. Machine learning and remote sensing technologies as recently developed technologies have been considered as tools for these solving water-based issues. Additionally, the “Topic” sought to obtain a collection ofrecent studies on the application of machine learning and remote sensing in hydrology.

Department/s

  • Dept of Physical Geography and Ecosystem Science

Publishing year

2022-06-22

Language

English

Publication/Series

Sustainability (Switzerland)

Volume

14

Issue

13

Document type

Journal article (comment)

Publisher

MDPI AG

Topic

  • Physical Geography
  • Water Engineering

Keywords

  • hydrological modeling
  • machine learning
  • Remote sensing

Status

Published

ISBN/ISSN/Other

  • ISSN: 2071-1050