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Article

Assessing Future Rainfall Intensity–Duration–Frequency Characteristics across Taiwan Using the k-Nearest Neighbor Method

1
Graduate Institute of Hydrologic and Oceanic Science, National Central University, Taoyuan 32001, Taiwan
2
Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei 10617, Taiwan
3
Department of Civil Engineering, National Chung Hsing University, Taichung 40227, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editors: Xing Fang and Theodore Endreny
Water 2021, 13(11), 1521; https://doi.org/10.3390/w13111521
Received: 24 April 2021 / Revised: 24 May 2021 / Accepted: 25 May 2021 / Published: 28 May 2021
(This article belongs to the Special Issue Water Resources Vulnerability and Resilience in a Changing Climate)
This study analyzes the changes in rainfall intensities across Taiwan using the k-Nearest Neighbor method. Biases are corrected according to the identified discrepancy between the probability distribution of the model run and that of the observed data in the historical period. The projections of 21 weather stations in Taiwan under 10 (2RCP × 5GCM) scenarios for the near-(2021–2040) and far-future (2081–2100) are derived. The frequently occurred short-duration storm events in some regions decrease, but they are still vulnerable to flood considering the existing drainage capacities. More specifically, the land-subsidence region in the central, the landslide-sensitive mountainous region in the north and central, the pluvial- and fluvial-flood prone region in the north, and the eastern regions with vulnerable infrastructures should be especially aware of long-duration extreme events. Associations of the rainfall intensity with the different return period as well as the duration are further analyzed. The short-duration extreme events will become stronger, especially for 1-h events in the northern region and 1 or 2-h events in both the southern and eastern regions. In addition, places without experiences of long-lasting events may experience rainfall amounts exceeding 500 mm should be alert. Adaptation measures such as establishing distributed drainage system or renewing hydrological infrastructures in the eastern region are suggested considering the near future projection, and in the central and the southern regions for far future as well. Our findings can assist adaptation-related decision-making for more detailed stormwater/water resource management. View Full-Text
Keywords: rainfall-intensity projection; k-Nearest Neighbors (k-NN) method; temporal downscaling; return periods; durations rainfall-intensity projection; k-Nearest Neighbors (k-NN) method; temporal downscaling; return periods; durations
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MDPI and ACS Style

Chen, P.-Y.; Tung, C.-P.; Tsao, J.-H.; Chen, C.-J. Assessing Future Rainfall Intensity–Duration–Frequency Characteristics across Taiwan Using the k-Nearest Neighbor Method. Water 2021, 13, 1521. https://doi.org/10.3390/w13111521

AMA Style

Chen P-Y, Tung C-P, Tsao J-H, Chen C-J. Assessing Future Rainfall Intensity–Duration–Frequency Characteristics across Taiwan Using the k-Nearest Neighbor Method. Water. 2021; 13(11):1521. https://doi.org/10.3390/w13111521

Chicago/Turabian Style

Chen, Pei-Yuan, Ching-Pin Tung, Jung-Hsuan Tsao, and Chia-Jeng Chen. 2021. "Assessing Future Rainfall Intensity–Duration–Frequency Characteristics across Taiwan Using the k-Nearest Neighbor Method" Water 13, no. 11: 1521. https://doi.org/10.3390/w13111521

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