The massive destruction and loss caused by the 2004 Sumatra-Andaman tsunami were attributed to the lack of knowledge on tsunami and low regional detection and communication systems for early warning in that region. This study aimed to identify locations at risk of impending tsunami from Andaman Sea for the safety of community and proper development planning at the coastal areas by providing an updated and revised inundation maps. The last study on this area was conducted several years ago which open the possibility to new findings. Generated by tsunami simulation models, the maps illustrate the extent and level of inundation to which the coastal community and infrastructure would be subjected. As a result of coastal changes and availability of better topographic data, the existing inundation maps for the coastal areas of northwest Peninsular Malaysia at risk to impending tsunami from the Andaman Sea are revised. This paper documented the computational setup leading to the generation of the revised inundation maps. The tsunami simulation model TUNA was used to simulate the generation, propagation, and subsequent run-up and inundation of tsunamis triggered by earthquakes of moment magnitudes (Mw) 8.5, 9.0, and 9.25 along the Sunda Trench. From the simulations, it was found that at Mw 9.25, Balik Pulau, Pulau Pinang would be subjected to inundation of as far as 3.47 km with 5.40-m-deep inundation at the highest section.
The power generation sector consumes significant amounts of water. A comprehensive water footprint (WF) assessment helps identify and monitor the processes consuming high amounts of water. This research evaluates the water footprint (WF) of electricity generation at a USC coal power plant, integrating on-site data for enhanced reliability. Based on the Water Footprint Assessment Manual, the electricity WF includes supply chain and operational WF. This study exhibits that the average electricity WF is 2.96 m3/MWh. The supply chain WF accounts for 95% of the total electricity WF, while operational WF contributes 5%. The blue WF accounts for 9.9% of the total electricity WF, while the grey water footprint accounts for 90.1%. The results of this research show a significant difference in the distribution of blue and grey WF in electricity WF. Factors contributing to the differences include the amount of coal consumption, power generation technology and power plant cooling technology. Furthermore, this study shows that grey WF depends on the concentration of pollutants considered. This research also conducted a WF impact assessment on local water resources and found that the blue and grey operational WF contributes to low impact. Monitoring the water footprint associated with electricity generation at a coal power plant would provide a more enhanced understanding of water consumption patterns, which could help influence water resources management.