Sunghyuk Jang on Muck Rack

Sunghyuk Jang

Seoul
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ConvLSTM-Based Surrogate Modeling for Flood Inflow Prediction at Namgang Dam

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By Jiyoung Sung, Taehyeong Kim, Boosik Kang, Sunghyuk Jang
| ascelibrary.org
Conclusions and Future Work This study demonstrated the effectiveness of LSTM-based surrogate modeling—specifically the ConvLSTM—for predicting flood inflows at the Namgang multipurpose dam. Compared with the traditional HEC-HMS physical model, ConvLSTM showed significantly higher computational efficiency and prediction accuracy, particularly in peak flow magnitude and timing, while drastically reducing runtime (under 0.05 s per event) and memory use.
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