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Andre D. L. Zanchetta, Paulin Coulibaly and Vincent Fortin
The use of machine learning (ML) for predicting high river flow events is gaining prominence and among its non-trivial design decisions is the definition of the quantitative precipitation estimate (QPE) product included in the input dataset. This study p...
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Andre D. L. Zanchetta and Paulin Coulibaly
Timely generation of accurate and reliable forecasts of flash flood events is of paramount importance for flood early warning systems in urban areas. Although physically based models are able to provide realistic reproductions of fast-developing inundati...
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Dayal Wijayarathne, Paulin Coulibaly, Sudesh Boodoo and David Sills
Demand for radar Quantitative Precipitation Estimates (QPEs) as precipitation forcing to hydrological models in operational flood forecasting has increased in the recent past. It is practically impossible to get error-free QPEs due to the intrinsic limit...
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Ameer Muhammad, Grey R. Evenson, Tricia A. Stadnyk, Alaba Boluwade, Sanjeev Kumar Jha and Paulin Coulibaly
The Prairie Pothole Region (PPR) of Canada contains millions of small isolated wetlands and is unique to North America. The goods and services of these isolated wetlands are highly sensitive to variations in precipitation and temperature. We evaluated th...
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