The National Capital Integrated Coastal Development (NCICD) is a construction megaproject around Jakarta Bay targeted environmental revitalization and flood mitigation. One of the main projects of NCICD is to develop the Jakarta's outer sea dike to prevent future disasters triggered by the increase of the sea level around Jakarta Bay. In this paper, we aim to assess and optimize the design of Jakarta's outer sea dike by investigating the wave run-up phenomenon, which is measured as the maximum vertical extent of wave uprush on a structure above the still water level. We used the Non-linear Shallow Water Equations (NSWE) as our mathematical model to simulate this phenomenon. The NSWE model was solved numerically using the finite volume method on a staggered grid with a wet-dry procedure to obtain accurate wave run-up height. To validate our numerical scheme, we conducted benchmark tests against a publicized experimental dataset, resulting in a good agreement between the numerical and experimental data, which confirms the robustness and accuracy of our model. We then simulate the wave run-up over three different sea dike profiles: single slope, single berm, and single berm with rocks. Our study shows that among the cases we investigated, the single berm with rocks is the most effective design of the sea dike as even small-sized rock units can significantly reduce the wave run-up height.

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Tsunamis are destructive natural disasters that can cause severe damage to property and the loss of many lives. To mitigate the damage and casualties, tsunami warning systems are implemented in coastal areas, especially in locations with high seismic activity. This study presents a method to identify the placement of near-shore detection sensors by minimizing the tsunami detection time, obtained by solving the two-dimensional shallow water equations (SWE). Several benchmark tests were done to establish the robustness of the SWE model, which is solved using a staggered finite volume method. The optimization problem is solved using particle swarm optimization (PSO). The proposed method is applied to different test problems. As an application, the method is used to find the optimal location of a detection sensor using data from the 2018 Palu tsunami. Our findings show that detection time can be significantly reduced through the strategic placement of tsunami sensors.