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Sumatra-Andaman tsunami was categorized as the third worst tsunami by the United State Geology Survey (USGS). The tsunami was triggered at 00:58:53 UTC by a massive earthquake with recorded moment magnitude of 9.1 at the west coast of North Sumatera. Malaysia is one of the countries affected by the 26th December 2004 tsunami. Others countries also affected by this event include Indonesia, Sri Lanka, Thailand, India, Maldives, Myanmar, Bangladesh, Somalia, Tanzania, Kenya and Yemen. The earthquake epicenter is located where the Indian Plate subducted under the Burma Plate. This tsunami event has raised the awareness of many people. Today, several tsunami numerical models have been developed to model and forecast tsunami events in the future. This paper reviews five tsunami numerical models namely TUNA, TUNAMI, COMCOT, MOST and ANN Tsunami Forecast. Most of these models have been used by other researchers to perform tsunami simulation based on Sumatera-Andaman tsunami event. Each model have their own similarities, differences and limitations. A non-mathematically intensive approach is employed to choose a suitable tsunami numerical model for the case study in Malaysian offshore areas. Future studies will be conducted using one of the tsunami numerical models.

Accurate forecasting of streamflow is desired in many water resources planning and management, flood prevention and design development. In this study, the accuracy of two hybrid model, support vector machine - particle swarm optimization (SVM-PSO) and bat algorithm – backpropagation neural network (BA-BPNN) for monthly streamflow forecasting at Kuantan River located in Peninsular Malaysia are investigated and compared to regular SVM and BPNN model. Heuristic optimization namely PSO and BA are introduced to find the optimum SVM and BPNN parameters. The input parameters to the forecasting models are antecedent streamflow, historical rainfall and meteorological parameters namely evaporation, temperature, relative humidity and mean wind speed. Two performance evaluation measure, root mean square error (RMSE) and coefficient of determination (R2) were employed to evaluate the performance of developed forecasting model. It is found that, RMSE and R2 for hybrid SVM-PSO are 24.8267 m3/s and 0.9651 respectively while general SVM model yields RMSE of 27.5086 m3/s and 0.9305 of R2 for testing phase. Besides that, hybrid BA-BPNN produces RMSE, 17.7579 m3/s and R2, 0.7740 while BPNN model produces lower RMSE and R2 of 28.1396 m3/s and 0.5015 respectively. Therefore, the results indicate that hybrid model, SVM-PSO and Bat-BPNN yield better performance as compared to general SVM and BPNN, respectively in streamflow forecasting.

Modern technology and life-style advancements have increased the demand for clean water. Based on this trend it is expected that our water resources will be under stress leading to a high probability of scarcity. This study aims to evaluate the environmental impacts of selected traditional food manufacturing products namely: tempe, lemang, noodle laksam, fish crackers and salted fish in Malaysia. The cradle-to-gate approach on water footprint assessment (WFA) of these selected traditional food products was carried out using Water Footprint Network (WFN) and Life Cycle Assessment (LCA). Freshwater eutrophication (FEP), marine eutrophication (MEP), freshwater ecotoxicity (FETP), marine ecotoxicity (METP) and water consumption (WCP), LCA were investigated using ReCiPe 2016 methodology. Water footprint accounting of blue water footprint (WFblue), green water footprint (WFgreen) and grey water footprint (WFgrey) were established in this study. It was found that total water footprint for lemang production was highest at 3862.13 m3/ton. The lowest total water footprint was found to be fish cracker production at 135.88 m3/ton. Blue water scarcity (WSblue) and water pollution level (WPL) of these selected food products were also determined to identify the environmental hotspots. Results in this study showed that the WSblue and WPL of these selected food products did not exceed 1%, which is considered sustainable. Based on midpoint approach adopted in this study, the characterization factors for FEP, MEP, FETP, METP and WCP on these selected food products were evaluated. It is recommended that alternative ingredients or product processes be designed in order to produce more sustainable lemang.