A parsimonious hybrid model: Integrating wavelet neural networks and deep learning for water quality forecasting in Southern Iran

Key Points

• Water quality forecasting accuracy improves significantly using the hybrid model, showing a marked enhancement over traditional methods.
• The hybrid model integrates wavelet neural networks with deep learning, highlighting a novel approach to environmental monitoring.
• Assessment of water quality data from Southern Iran confirms the model's effectiveness through robust predictive capabilities.
• The findings may enable future developments in water management, supporting sustainability efforts in vulnerable regions.