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Physical Model-Based Maximization of Historical Precipitation in the Basin with Complex Topography

Author(s): Yusuke Hiraga; Joaquin Meza

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Abstract: In basins where extreme floods have caused significant damages, Probable Maximum Precipitation (PMP) estimate is important for flood risk management. Conventionally, PMP has been estimated using the statistical approach in many regions of the world due to its applicability for sparsely-gauged basins. However, for complex terrain such as Andes Mountain Range, the statistical method may not be appropriate since it cannot deal with non-linear orographic effects and precipitation observations are usually not dense. This study used the model-based PMP estimation approach to maximize the target historical precipitation over the Maipo River Basin, Chile. This study further deals with the recently raised questions on the model-based PMP estimation: (1) How can one estimate PMP with the range (not deterministically)? (2) How can one evaluate the frequency of the estimated PMP? Overall, this study will be useful basis on the next generation model-based PMP estimation, especially for basins with complex topography, dominated by Atmospheric Rivers.

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Year: 2024

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