Remote Sensing for Development of Rainfall Intensity–Duration–Frequency Curves at Ungauged Locations of Yangon, Myanmar
1
Department of Water and Environmental Engineering, School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Skudai 81310, Malaysia
2
State Key Laboratory of Hydrology—Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China
3
Research Center for Climate Change, Ministry of Water Resources, Nanjing 210029, China
*
Author to whom correspondence should be addressed.
Academic Editor: Marco Franchini
Water 2022, 14(11), 1699; https://doi.org/10.3390/w14111699
Received: 27 April 2022
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Revised: 23 May 2022
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Accepted: 24 May 2022
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Published: 25 May 2022
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
This study aims to develop the intensity–duration–frequency (IDF) curves for Yangon, the economic center of Myanmar, using four satellite precipitation datasets, namely GPM IMERG, TRMM, GSMaP_NRT, and GSMaP_GC. Different probability distribution functions were used to fit the annual rainfall maximum series to determine the best-fit distribution. The estimated parameters of the best-fit distribution were used to fit the rainfall intensities of 2, 5, 10, 25, 50, and 100-year return periods for generating IDF curves using the Sherman equation. The IDF curves were bias-corrected based on the daily rainfall data available only at a location in Yangon. The bias correction factors were then used to estimate IDF curves from satellite rainfall at ungauged locations of Yangon. The results showed that the Generalized Extreme Value Distribution best fit the hourly rainfall distribution of satellite data. Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) is the most suitable for constructing Yangon’s IDF curves. The bias-corrected IDF curve generated at four locations of greater Yangon indicates higher rainfall intensity at the coastal stations than the inland stations. The methodology presented in this study can be used to derive IDF curves for any location in Myanmar.
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MDPI and ACS Style
Kyaw, A.K.; Shahid, S.; Wang, X. Remote Sensing for Development of Rainfall Intensity–Duration–Frequency Curves at Ungauged Locations of Yangon, Myanmar. Water 2022, 14, 1699. https://doi.org/10.3390/w14111699
AMA Style
Kyaw AK, Shahid S, Wang X. Remote Sensing for Development of Rainfall Intensity–Duration–Frequency Curves at Ungauged Locations of Yangon, Myanmar. Water. 2022; 14(11):1699. https://doi.org/10.3390/w14111699
Chicago/Turabian StyleKyaw, Aung Kyaw, Shamsuddin Shahid, and Xiaojun Wang. 2022. "Remote Sensing for Development of Rainfall Intensity–Duration–Frequency Curves at Ungauged Locations of Yangon, Myanmar" Water 14, no. 11: 1699. https://doi.org/10.3390/w14111699
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