Salinity intrusion through the estuaries in low-lying tide-dominated deltas is a serious threat that is expected to worsen in changing climatic conditions. This research makes a comparative analysis on the impact of salinity intrusion due to a reduced upstream discharge, a sea level rise, and cyclonic conditions to find which one of these event dominates the salinity intrusion. A calibrated and validated salinity model (Delft3D) and storm surge model (Delft Dashboard) are used to simulate the surface water salinity for different climatic conditions. Results show that the effects of the reduced upstream discharge, a sea level rise, and cyclones cause different levels of impacts in the Ganges-Brahmaputra-Meghna (GBM) delta along the Bangladesh coast. Reduced upstream discharge causes an increased saltwater intrusion in the entire region. A rising sea level causes increased salinity in the shallower coast. The cyclonic impact on saltwater intrusion is confined within the landfall zone. These outcomes suggest that, for a tide dominated delta, if a sea level rise (SLR) or cyclone occurred, the impact would be conditional and local. However, if the upstream discharge reduces, the impact would be gradual and along the entire coast.

Impact of storm surge largely varies depending on the tidal phase during the landfall of a tropical cyclone. This study investigates comparative variance in inundation condition and thrust force for an identical cyclone during low tide and high tide by applying a numerical model (Delft3D) and a semi-analytical model (DFM). A moderate strength cyclone, Mora, which made landfall on Bangladesh coast in May 2017 is selected to study its impact on land during low tide and high tide. Actual landfall time of Mora was during low tide. To study the impact of storm surge during high tide, a synthetic cyclone is created which has similar strength and track to that of Mora but makes landfall during high tide. The results show that inundation depth, inundation extent, and thrust force increase when a cyclone makes landfall during high tide compared to the condition when the cyclone makes landfall during low tide. But the relation between storm surge impact and tidal phase is not linear. It depends on the land topography of the location, direction of cyclone movement, direction and magnitude of water velocity and wind velocity, gradients of water surface and wind velocity, and proximity and position of the location with respect to cyclone track.

Risk assessment of climatic events and climate change is a globally challenging issue. For risk as well as vulnerability assessment, there can be a large number of socioeconomic indicators, from which it is difficult to identify the most sensitive ones. Many researchers have studied risk and vulnerability assessment through specific set of indicators. The set of selected indicators varies from expert to expert, which inherently results in a biased output. To avoid biased results in this study, the most sensitive indicators are selected through sensitivity analysis performed by applying a non-linear programming system, which is solved by Karush-Kuhn-Tucker conditions. Here, risk is assessed as a function of exposure, hazard, and vulnerability, which is defined in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), where, exposure and vulnerability are described via socioeconomic indicators. The Kolmogorov-Smirnov statistical test is applied to select the set of indicators that are the most sensitive for the system to assess risk. The method is applied to the Bangladesh coast to determine the most sensitive socioeconomic indicators in addition to assessing different climatic and climate change hazard risks. The methodology developed in this study can be a useful tool for risk-based planning.

Selection of relative weights for different indicators is a critical step during assessment of composite hazards, vulnerability, and risk. While assigning weight to an indicator, it is important to consider the influence of an individual indicator on a particular composite index. In general, the larger the weight of the indicator, the higher the importance of that indicator compared to other indicators. In this study, a new matrix based statistical framework (MSF) for weight assignment is developed that can be considered as the simplest and most accurate method for assigning weights for a large number of indicators. This method (MSF) is based on the valuation of the correlation matrix and Eigenvector associated with Eigenvalue. Relying on the inter build up methodology, MSF can fulfill some built-in gaps among other weightage methods. It can also directly give the ‘decision’ to select the relative weights that are found from the Eigenvector corresponding to the largest Eigenvalue. The new method is applied by assigning weights to 15 socio-economic indicators and assessed vulnerability and risk in the Bangladesh coast. While comparing with other weight methods, it is found that MSF gives the most acceptable physical explanation about the relative values of weights of indicators. In terms of accuracy, MSF is found to be most accurate compared to other weight methods. When large numbers of indicators are involved in an application, MSF is found to be relatively simple and easy to apply compared to other methods.

A moving water mass generates force which is exerted on its moving path. Cyclone generated storm surge or earthquake generated tsunami are specific examples of moving water mass the generates force along the coasts. In addition to human lives, these moving water masses cause severe damages to the coastal infrastructure due to tremendous force exerted on these structures. To assess the damage on these infrastructures, an essential parameter is the resultant force exerted on these structures. To evaluate the damages, there is hardly any quantitative method available to compute this force. In this paper we have developed a semi-analytical model, named as Dynamic Force Model (DFM), by using Variational Iteration Method to compute this force. As governing equations, we have used the Saint Venant equations which are basically 1D shallow water equations derived from the Navier-Stokes equations. The verified, calibrated and validated DFM is applied in Bangladesh coastal zone to compute dynamic thrust force due to tropical cyclone SIDR.