SWAT and ANN model hydrological assessment using Malaysia soil data / Khairi Khalid - Khalid, Khairi (Institute of Graduate Studies, UiTM, 2017)
Flood is a primary hazard affecting Malaysia, often responsible for loss of lives and a severe threat to infrastructure and environment. Activities in flood plain and catchment such as land clearing for other developments effort may increase the magnitude of a flood. The problem of flood management cannot be solved simply by providing more construction of dams and reservoirs. The adoption of a strategic approach is needed for planning and managing that flood management in any watershed. The evolution of distributed watershed models has been established for more accurate representation of the hydrological system by considering the spatial variability of model parameters and inputs. The research aims to evaluate the performance and hydrological response of the Soil Water Assessment Tool (SWAT) process-based model in tropical river basin using Malaysia soil data. This study was specific to the upper part of Langat River Basin (UPLRB) in the context of Greater Kuala Lumpur Plan in the southern region. The research also provides a streamflow prediction using the Artificial Neural Network (ANN) method as another tool for assessment. ArcSWAT2009.93.b, which is embedded in ArcGIS10, has been selected for this study, and the model requires comprehensive data on topography, soils, land use and daily weather data within a watershed. SWAT-CUP, which links SUFI-2 algorithm to SWAT models, has been utilized in the study for the calibration of SWAT models.