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Brayden Noh

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Probabilistic Modeling for River Erosion

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While probabilistic approaches have proven effective for forecasting flood hazards, predicting future river channel evolution remains an open challenge in the field. Our work addresses this gap by developing a framework to generate comprehensive geomorphic risk maps

We applied the stochastic model to the Ucayali River, one of the most active meandering rivers in the Amazon Basin.

Risk maps using data from 1, 2, 3, and 4 bends are generated, progressively incorporating more spatial information.

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Brayden Noh

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