A Quang Nam coastline, located in the central of Vietnam, has been strongly affected by severe erosion and accretion due to climate change and human activities. Thus, understanding the causes and mechanisms of coastal morphology changes is essential to offer optimal coastal management and protection solutions. In this research, the Digital Shoreline Analysis System (DSAS) technique developed by the United States Geological Survey was adopted to calculate rate-of-change statistics from multiple historical coastline positions of Quang Nam province extracted from satellite images, i.e., Landsat and Sentinel images from 1990 to 2019. The coastal dynamic was digitized, visualized, and compared by two statistical parameters provided in DSAS, namely End Point Rate (EPR) and Linear Regression Rate (LRR). The final results reveal that the Quang Nam coast experienced remarkable phenomena of erosion and accumulation over the past three decades. The total number of erosional and accretional transects obtained from the EPR results are 401 and 414, with annual change rates of −1.7 and 0.77 m/year, respectively. The LRR parameter was also considered and illustrated a significant correlation with the EPR, as the obtained R² value of 0.96. The lowest value of EPR over the period 1990–2019 is −42.4 m/year, highlighting the most significant erosion at the north of Cua Dai estuary, whereas coastline advance is recorded in the south segment. As a result, this study’s outcomes provide helpful information for better and sustainable coastal management in Quang Nam province of Vietnam.

Nha Trang Coast is located in the South Central Vietnam and the coastal erosion has occurred rapidly in recent years. Hence it is crucial to accurately monitor the shoreline changes for better coastal management and reduction of risks for communities. In this paper, we explored a statistical forecasting model, Seasonal Auto-regressive Integrated Moving Average (SARIMA), and two Machine Learning (ML) models, Neural Network Auto-Regression (NNAR) and Long Short-Term Memory (LSTM), to predict the shoreline variations from surveillance camera images. Compared to the Empirical Orthogonal Function (EOF), the most common method used for predicting shoreline changes from cameras, we demonstrate that the SARIMA, NNAR and LSTM models outperform the EOF model significantly in terms of prediction accuracy. The forecasting performance of the SARIMA model, NNAR model and LSTM model is comparable in both long and short-term predictions. The results suggest that these models are highly effective in detecting shoreline changes from video cameras under extreme weather conditions.

Tidal inlets along the central coast of Vietnam are located in a microtidal, wave-dominated coastal environment. In addition, the Vietnam coast is highly influenced by the seasonal monsoon regime, which is characterized by large northeast waves from October to March and calm southeast waves from April to September every year. Consequently, the tidal inlet entrance morphologies often suffer from a dynamic seasonal evolution due to distinct differences in the direction of wave-induced longshore sediment transport (LST) between the two monsoon seasons. The migration or closure of tidal inlets causes a lot of problems for socio-economic development in the region since these are the main reasons leading to an increase in the risk of coastal flooding and the obstruction of navigation. This paper presents a comprehensive study of the morphological evolutions of natural tidal inlets on the central coast of Vietnam using long-term remote sensing data sets and by the Delft3D numerical model. Surprisingly, the estimated LST rates from the former method are in an order of magnitude agreement with the results from the latter one for all of the areas in this study. Based on the conservation equation for sand and comprehensive data collection, a new simple empirical formula for predicting the sand spit elongation rate as a function of the sand spit width is developed. Although the breaching of sand spit might happen during an extreme flood event at some tidal inlets, the growth rate of the spit before and after the breaching is almost unchanged. These findings are very useful information for supporting the local coastal authorities to find better management solutions in terms of sustainable development.

This paper presents a detailed investigation on unsteady effects in bottom boundary layer beneath a tsunami. In numerical simulation of tsunami, bottom shear stress has commonly been evaluated by using steady flow friction laws such as Manning equation, simply assuming that long-period wave motion satisfies quasi-steady flow conditions. However, the present study found that the behavior of tsunami-induced bottom boundary layer has an unsteady characteristics and acts similar to that induced by wind-generated waves even under long-period wave motion. As a result, bottom shear stress under tsunami is much larger than the estimation using steady friction coefficient due to a steep velocity gradient in the bottom boundary layer. Surprisingly, the steady flow friction law is not valid in almost the entire computational domain, from the source area to shallow region. This result highly coincides with the field measurement data obtained by Lacy group during the 2010 Chilean Tsunami at the Monterey Bay mouth in U.S. A correction coefficient is proposed to take into account unsteady effects in the conventional estimation method using a steady friction factor; this approach is validated by comparing with numerical simulation results using k-ω turbulence model.

It is well known that estuarine systems are significantly affected by hydrodynamic conditions such as river discharge, storm surges, waves and tidal conditions. In addition to this, human interferences through developmental projects have the capability of disrupting the natural morphological processes occurring at estuaries. In West Africa, the goal to improve standards of living through large-scale dam construction, offshore ports and coastal erosion countermeasures has triggered alarming changes in the morphodynamics of estuarine systems. The estuaries at the Volta River mouth (Ghana) and “Bouche du Roi” inlet (Benin), located along the Bight of Benin coast, West Africa, were selected as two case study sites to examine their long-term morphodynamics and sandspit evolution. In this study, we primarily analyzed estuarine morphology using remotely sensed images acquired from 1984 to 2020. We further estimated the longshore sediment transport for this region using results from the image analysis and the depth of active sediment motion. Our results reveal that the longshore sediment transport rates for this region are in the magnitude of 10⁵–10⁶ m³/year. Comparative analysis with other estuaries and sandy coasts suggests that the longshore sediment transport along this coast has one of the largest rates estimated in the world.