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.

Monitoring surface water provides vital information in water management; however, limited data is a fundamental challenge for most developing countries, such as Vietnam. Based on advanced remote sensing technologies, the authors proposed a methodology to process satellite images and use their outcomes to extract surface water in water resource management of Quang Nam province. Results of the proposed study show good agreement with in situ measurement data when the obtained Overall Accuracy and Kappa Coefficient were greater than 90% and 0.99, respectively. Three potential applications based on the surface water results are selected to discuss sustainable water management in Quang Nam province. Firstly, reservoir operating processes can be examined, enhanced, and even developed through long-term extracted water levels, which are the interpolation results between the extracted surface water area and the water level–area–volume curve. Secondly, the long-term morphological change for the Truong Giang river case between 1990 and 2019 can also be detected from the Water Frequency Index performance and provided additional information regarding permanent and seasonal water changes. Lastly, the flood inundation extent was extracted and separated from permanent water to assess the damage of the Mirinae typhoon on 2 November 2009 in terms of population and crop aspects.

Consistent monitoring of surface water dynamics is essential for water resources, flood risk management, and addressing the challenges posed by climate change, urbanization. Nhat Le River Basin witnesses significant and noticeable dynamics in surface water on a yearly basis due to water-related disasters like floods and droughts. This article presents the first comprehensive study to systematically map and analyse the long-term (2016–2022) spatiotemporal dynamics of surface water in the Nhat Le River Basin of Vietnam, utilizing Sentinel-1 data. The results reveal that the optimal threshold for separating water from non-water pixels is −19 dB, with an overall accuracy of 0.93–0.94 and a Kappa coefficient of 0.77–0.82. Through quantitative analysis, the study characterizes seasonal and interannual variations in the surface water extent, contributing to an enhanced understanding of flood patterns and associated risks in a data-scarce region. Our analysis reveals the Kien Giang river delta as the most flooding-vulnerable sub-region, underscoring the importance of targeted risk management and adaptation planning in this area. A Google Earth Engine Tool is developed for automatic detecting, monitoring, and accessing the spatiotemporal dynamics of surface water in Nhat Le River Basin over the period 2016–2022 and is available on GitHub (https://github.com/MinhVu25/Surface_Water_Dynamics_2023).

Coastal erosion and accretion along the Quang Nam coast in Vietnam have been increasing in recent years, causing negative impacts on the inhabitants and local ecology. The Cua Lo estuary in Nui Thanh district has a complex hydrodynamic regime owing to its connection with two estuaries and three different tributaries. Therefore, a detailed study of the mechanisms and processes of these phenomena is crucial to understand the potential impact of a proposed 50,000-ton cargo port. In this study, the Delft3D model is employed to evaluate the morpho-dynamic changes in the area of Cua Lo under monsoon wave climate, storm, and flood conditions both before and after port and navigation channel construction. Results indicate that in the absence of the port, tidal currents and waves during monsoon storms cause significant erosion on the south bank and accretion on the north bank. Furthermore, the GenCade model is utilized to predict the future shoreline changes after the construction of two jetties. The model reveals that after 50 years of operation, the shoreline modifications will extend 449 m towards the sea, in comparison to natural conditions. However, the design of the northern jetty will ensure safe and proper operation without impacting the navigation channel. This study offers valuable insights into the morphological changes in the Cua Lo area and their potential implications, which can aid in the development of sustainable coastal management strategies for the region.

The shoreline of Quang Nam province in Central Vietnam has been experiencing persistent erosion, posing a significant threat to coastal communities and their livelihoods. This study analyzes eight years of Landsat-7/8/9 and Sentinel-2 images to examine shoreline changes along Tam Tien Beach in Quang Nam during the period 2015–2022, identifying patterns of erosion and deposition. The analysis of 75 transects over an 11 km stretch of sandy shoreline revealed that approximately 84% of the transects exhibited erosion, with transects 44 to 60 showing significant retreat of shoreline averaging around 2.5 m/year. The results also demonstrated a significant seasonal variability related to monsoon regimes. The translational and rotational shift of the shoreline was examined, and the influence of wave energy flux and wave direction were clarified. The study also applied Empirical Orthogonal Eigenfunction analysis to explore the relationship between shoreline translation, rotation, and rate of change. Under the expected future climate change, the study also underlines the vulnerability of Central Vietnam to severe erosion events. These findings are the key to predicting coastal impacts, designing effective protection structures, mitigating erosion, and managing coastal resources.

Coastal zones worldwide are densely populated and, as a result, among the areas most affected by urbanization. However, coastlines are very dynamic and always changing due to a variety of human and natural factors. One of today’s most concerning coastal risks is erosion, which can seriously harm buildings and infrastructure along the coast. The Cua Dai estuary in Vietnam, which serves as an outlet of the Thu Bon River, has been experiencing coastal erosion in recent decades. Following human activity in the upstream region, the erosion got severe, such as dam development and sand mining activity. As a result, a comprehensive evaluation of hydro-morphodynamics, sediment transport, and coastal interventions is necessary. We conduct campaigns to understand better the grain-size distribution along the cross-shore profile and the variation of median grain-size diameter (d50), which will help define a representative d50 to characterize the beaches. In addition, images from satellite observations depict coastal erosion patterns. The findings can improve our understanding of the budget from the mountain to the sea. They can be used to recommend specific measures for mitigating or intervening in hotspot areas.