Alternative approach for determining streamflow discharge using SWAT model and remote sensing databases in Poorly Gauged basin

Flood issues have always been major disaster in many countries especially the tropical regions where extreme precipitations occurred during the monsoon seasons. Hence, well-established hydrological modelling framework is required to estimate the peak discharge in the river network as part of flood mitigation measures. Unfortunately, in poorly gauged river basin, observations data required for performing hydrological modelling such as landuse changes, climatology data, hydrological data, and soil information are often insufficient and difficult to obtained. The objectives of this study are to utilize readily accessible remote sensing data to generate the topography, land use characteristics, and climate data, and to establish the hydrological model framework for determining the peak streamflow discharge in poorly gauged basin. For this study, hydrological modelling was performed using ArcSWAT, an integrated extension in ArcGIS. Two types of data are used for the simulation, remote sensing climate data (RSCD) and observe climate data (OCD). There were 20 subbasins delineated for Kuantan River Basin with a total number of 87 Hydrological Response Unit (HRU) defined through ArcGIS. The periods used for calibration and validation of the hydrological model selected were from January 2010 to December 2011 and January 2017 to December 2018 based on the availability of the climate data to run the simulation. Both data will be the compared using observed streamflow data (OSD) at Station Bukit Kenau. Overall result obtained from the simulation, the observed climate data give better prediction than remote sensing climate data by comparing the performance rating using Ration of Standard deviation to RSME (RSR) and Percentage bias (PBIAS).