Assessing the adequacy of traditional hydrological models for climate change impact studies: a case for long short-term memory (LSTM) neural networks

Keyphrases

• Hydrological Model 100%
• Climate Change Impact Assessment 100%
• Long Short-term Memory Neural Network 100%
• Long Short-term Memory Model 66%
• Streamflow 33%
• Climate Sensitivity 33%
• Climate Change 16%
• Climate Conditions 16%
• Number of Parameters 16%
• Long Short-term Memory 16%
• Memory-based Model 16%
• Climate Scenarios 16%
• Simplified Method 16%
• Temporal Dependence 16%
• Future Climate 16%
• Mean Annual Precipitation 16%
• SSP5-8.5 16%
• Climate Zones 16%
• Streamflow Simulation 16%
• Water Resources 16%
• Coupled Model Intercomparison Project Phase 6 (CMIP6) 16%
• Precipitation Elasticity 16%
• Continental Scale 16%

Earth and Planetary Sciences

• Climate Change Impact 100%
• Long Short-Term Memory Network 100%
• Streamflow 42%
• General Circulation Model 14%
• Climate Condition 14%
• Coupled Model Intercomparison Project Phase 6 14%