Wan Zurina Wan Jaafar

Integration of Geographic Information System (GIS) and hydraulic modelling to simulate floodplain inundation level for Bandar Segamat

Flooding is an unavoidable disaster. However, the impact and the risk to be affected by flooding can be reduced. Recently, floodplain modeling known as new method applied in river engineering modeling and has been used by many researchers in determining flood prone area, The objective of this research is to explore the integration of Geographic Information System (GIS) and hydraulic simulation model, Hydrologic Engineering Centers River Analysis System (HEC RAS) in determining the steady flow simulation model and possibility flooding areas for Bandar Segamat Johor. The methodology of this research is divided into 5 stages, include study area identification, data acquisition, data processing (spatial data generation), data processing (simulation), result and analysis. In this research, steady flow for Segamat River and Kapeh River was simulated. Flood map was produced by integrating both GIS and HEC RAS analysis. The results suggest that the integration of HEC RAS and GIS analysis can lead to a better visualization for flood mapping to be used by the society and considered to be helpful for future development.

Soil Moisture Deficit Estimation Through SMOS Soil Moisture and MODIS Land Surface Temperature

Abstract Soil moisture acts as a key variable in the exchanges of water and energy from land surface to atmosphere. The work presented here showed the first-time comprehensive evaluation of land surface temperature (LST) derived from moderate resolution imaging spectroradiometer (MODIS) and soil moisture from soil moisture and ocean salinity (SMOS) for prediction hydrological soil moisture deficit (SMD). The main focus of the work relies on the application of adaptive neuro fuzzy inference system (ANFIS) for evaluating its capabilities towards SMD estimation. The performances between estimated and ANFIS simulated SMD are assessed in terms of Nash-Sutcliffe Efficiency, root mean square error, and the percentage of bias. The performance statistics revealed a good agreement between benchmark and ANFIS estimated SMD from MODIS as compared to the SMOS. This present study has strong supportive evidence that there are SMOS soil moisture and MODIS LST products for different hydrometeorological studies. The assessment of the product with respect to this peculiar evidence is an important step for successful development of hydrometeorological model and forecasting system.

Soil erosion assessment on hillslope of GCE using RUSLE model

A new method for obtaining the C factor (i.e., vegetation cover and management factor) of the RUSLE model is proposed. The method focuses on the derivation of the C factor based on the vegetation density to obtain a more reliable erosion prediction. Soil erosion that occurs on the hillslope along the highway is one of the major problems in Malaysia, which is exposed to a relatively high amount of annual rainfall due to the two different monsoon seasons. As vegetation cover is one of the important factors in the RUSLE model, a new method that accounts for a vegetation density is proposed in this study. A hillslope near the Guthrie Corridor Expressway (GCE), Malaysia, is chosen as an experimental site whereby eight square plots with the size of

Calibration Catchment Selection for Flood Regionalization Modeling

8\times 8

Analysis of rainfall events over Peninsular Malaysia

8×8 and

Uncertainty in Index Flood Modelling due to Calibration Data Sizes

5\times 5