Effective environmental planning and management to address climate change could be achieved through extensive environmental modeling with machine learning and conventional physical models.
The study provides a comprehensive review of state-of-the-art deep learning approaches used in the water industry for generation, prediction, enhancement, and classification tasks, and serves as a guide for how to utilize available deep learning methods for future water resources challenges.
LIDAR (light detection and ranging) is an optical remote-sensing technique that measures the distance between sensor and object, and the reflected energy from the object.
In this paper, we demonstrated a practical application of realistic river image generation using deep learning.
Predicting flood for any location at times of extreme storms is a longstanding problem that has utmost importance in emergency management.