Rapid Extreme Tropical Precipitation and Flood Inundation Mapping Framework (Retrace)

Initial Testing for the 2021–2022 Malaysia Flood

Bibliographic Data

ID22032693
AuthorsYi Lin Tew (0000-0002-3334-0955, Universiti Sains Malaysia), Mou Leong Tan (0000-0003-3939-0336, Universiti Sains Malaysia, corresponding author), Liew Juneng (0000-0001-8839-5198, National University of Malaysia), Kwok Pan Chun (0000-0001-9873-6240, University of the West of England), Mohamad Hafiz bin Hassan (National Flood Forecasting and Warning Centre, Department of Irrigation and Drainage, Kuala Lumpur 68000, Malaysia), Sazali Osman (0009-0003-3835-1308), Sazali bin Osman (National Flood Forecasting and Warning Centre, Department of Irrigation and Drainage, Kuala Lumpur 68000, Malaysia), Narimah Samat (0000-0002-7540-0717, Universiti Sains Malaysia), Chun Kiat Chang (0000-0002-5900-5020, Universiti Sains Malaysia), Muhammad Humayun Kabir (0000-0002-9682-3591, Sher-e-Bangla Agricultural University)
Year2022
Volume11
Issue7
Pages378
Publication date2022-07-07
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi11070378
OpenAlexW4284885591
LanguageEN
References cited49

The 2021–2022 flood is one of the most serious flood events in Malaysian history, with approximately 70,000 victims evacuated daily, 54 killed and total losses up to MYR 6.1 billion. From this devastating event, we realized the lack of extreme precipitation and flood inundation information, which is a common problem in tropical regions. Therefore, we developed a Rapid Extreme TRopicAl preCipitation and flood inundation mapping framEwork (RETRACE) by utilizing: (1) a cloud computing platform, the Google Earth Engine (GEE); (2) open-source satellite images from missions such as Global Precipitation Measurement (GPM), Sentinel-1 SAR and Sentinel-2 optical satellites; and (3) flood victim information. The framework was demonstrated with the 2021–2022 Malaysia flood. The preliminary results were satisfactory with an optimal threshold of five for flood inundation mapping using the Sentinel-1 SAR data, as the accuracy of inundated floods was up to 70%. Extreme daily precipitation of up to 230 mm/day was observed and resulted in an inundated area of 77.43 km2 in Peninsular Malaysia. This framework can act as a useful tool for local authorities and scientists to retrace the extreme precipitation and flood information in a relatively short period for flood management and mitigation strategy development

Climatology · Flood forecasting · Flood myth · Geography · Global Precipitation Measurement · Meteorology · Precipitation · Tropical cyclone · Environmental Science · Flood Risk Assessment and Management · Precipitation Measurement and Analysis · Tropical and Extratropical Cyclones Research · Geology

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