Author(s): Wan Zurina Wan Jaafar, Eugene Zhen Xiang Soo, Sai Hin Lai, Tanvir Islam, Prashant K. Srivastava
Linked Author(s): Wan Zurina Wan Jaafar
Keywords: Satellite precipitation, extreme flood events, precipitation, rain gauge, climate change.
Abstract: Climate change is one of the most serious environmental threats in the world. In the past, many researchers had used different ways of collecting climatic information to identify the trends of historical stream flow and other hydro climatic variables. Rain gauge is often used but it is limited by its near-point observation or small spatial coverage. Also, it may fail in providing continuous record of precipitation and give out inaccurate readings due to wind effects and mechanical errors. In this study, three advanced satellite precipitation products (SPPs), CMORPH, TRMM 3B42 Version 7 and PERSIANN are utilized in conjunction with the ground observation to investigate their performance in detecting rain, capturing storms and rainfall pattern during extreme flood events. Also, this study evaluated the spatial distribution of the SPPs using various rainfall interpolation methods. The 2014/2015 extreme flood events in Kelantan, Johor and Langat River Basin are examined. Kelantan and Johor River Basins are chosen due to its largest affected areas by the flood whereas Langat River Basin is included as of the study areas due to its geographic location, i. e. west coast of Peninsular Malaysia. This study eventually investigates performance of those three satellite products during the extreme events with regards to the most affected area and geographic location. Precipitation data for the December 2014 and January 2015 are obtained from the related satellite websites. As for observation data, the data are obtained from the Drainage and Irrigation Department (DID) Malaysia. Generally, all three satellite products can estimate well the actual rainfall in Kelantan river basin compared to the other two river basins during the extreme flood events, regardless of the SPPs used or spatial interpolation methods. The analyses suggest that extensive efforts are necessary to improve the satellite algorithms that can capture the rainfall more effectively
Year: 2017