Prediction of nitrate and phosphorus concentrations using machine learning algorithms in watersheds with different landuse

Keyphrases

• Nitrate Concentration 100%
• Land Use 100%
• Phosphorus Concentration 100%
• Machine Learning Algorithms 100%
• Agricultural Watershed 75%
• Machine Learning Models 75%
• Nitrate 50%
• Water Quality 50%
• Urban Watershed 50%
• Forested Watershed 50%
• Phosphate 25%
• Model Performance 25%
• Total Phosphorus 25%
• Politicians 25%
• Water System 25%
• Aquatic Ecosystems 25%
• Adverse Effects 25%
• Water Pollution 25%
• Population Growth 25%
• Land Use Practices 25%
• Wastewater Treatment Plant 25%
• One-class Support Vector Machine (OCSVM) 25%
• Rapid Industrialization 25%
• Model Predictability 25%
• Land Use Distribution 25%

Agricultural and Biological Sciences

• Watersheds 100%
• Agricultural Watersheds 50%
• Land Use 33%
• Forested Watersheds 33%
• Wastewater Treatment 16%
• Population Growth 16%
• Water Pollution 16%
• Adverse Effects 16%
• Aquatic Ecosystem 16%

Earth and Planetary Sciences

• Machine Learning 100%
• Land Use 33%
• Artificial Neural Network 33%
• Aquatic Ecosystem 16%
• Water Pollution 16%
• Population Growth 16%
• Ground Penetrating Radar 16%
• Waste Water Treatment Plant 16%