August 25, 2025WaterOpen Access

Video-Based Deep Learning Approach for Water Level Monitoring in Reservoirs

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This research reveals advanced deep learning methods enhance water level monitoring in reservoirs, indicating potential for flood forecasting.

EfficientNet achieved about 99% accuracy in recognizing water levels, surpassing other models like ResNet and CNN.
The study utilized two years of video data from the Myeonggyeong Reservoir for accurate real-time monitoring.
A semantic segmentation approach with U-Net effectively extracted water surface areas for analysis.
Future improvements focus on integrating multi-sensors and optimizing the model for enhanced performance.

Jung et al. (2025) studied this question.

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This research reveals advanced deep learning methods enhance water level monitoring in reservoirs, indicating potential for flood forecasting.