Machine learning for hydrologic sciences: An introductory overview

Earth & Environmental Sciences

• machine learning 84%
• rainfall-runoff modeling 23%
• hardware 16%
• repository 16%
• accessibility 15%
• land use change 15%
• parameterization 14%
• modeling 14%
• learning 13%
• software 10%
• detection 9%
• water 5%

Agriculture & Biology

• artificial intelligence 100%
• hydrologic data 32%
• hydrologic factors 29%
• land use change 20%
• runoff 19%
• learning 15%
• water 6%
• sampling 5%

Engineering & Materials Science

• Machine learning 61%
• Runoff 24%
• Rain 18%
• Parameterization 17%
• Deep learning 14%
• Computer hardware 9%
• Water 9%