The delta of the Mekong River in Vietnam has been heavily impacted by anthropogenic stresses in recent years, such as upstream dam construction and sand mining within the main and distributary channels, leading to riverbank and coastal erosion. Intensive bathymetric surveys, conducted within the Tien River branch during the dry and wet season 2018, reveal a high magnitude of sand mining activities. For the year 2018, an analysis of bathymetric maps and the local refilling processes leads to an estimated sand extraction volume of 4.64  0.31 Mm/yr in the study area, which covered around 20 km. Reported statistics of sand mining for all of the Mekong’s channels within the delta, which have a cumulative length of several hundred kilometres, are 17.77 Mm/yr for this period. Results from this study highlight that these statistics are likely too conservative. It is also shown that natural sediment supplies from upper reaches of the Mekong are insufficient to compensate for the loss of extracted bed aggregates, illustrating the non-sustainable nature of the local sand mining practices.

The hydro- and morphodynamic processes within the Vietnamese Mekong Delta are heavily impacted by human activity, which in turn affects the livelihood of millions of people. The main drivers that could impact future developments within the delta are local stressors like hydropower development and sand mining, but also global challenges like climate change and relative sea level rise. Within this study, a hydro-morphodynamic model was developed, which focused on a stretch of the Tien River and was nested into a well-calibrated model of the delta’s hydrodynamics. Multiple scenarios were developed in order to assess the projected impacts of the different drivers on the river’s morphodynamics. Simulations were carried out for a baseline scenario (2000–2010) and for a set of plausible scenarios for a future period (2050–2060). The results for the baseline scenario indicate that the Tien River is already subject to substantial erosion under present-day conditions. For the future period, hydropower development has the highest impact on the local erosion and deposition budget, thus amplifying erosional processes, followed by an increase in sand mining activity and climate change-related variations in discharge. The results also indicate that relative sea level rise only has a minimal impact on the local morphodynamics of this river stretch, while erosional tendencies are slowed by a complete prohibition of sand mining activity. In the future, an unfavourable combination of drivers could increase the local imbalance between erosion and deposition by up to 89%, while the bed level could be incised by an additional 146%.

In this study, we demonstrate how freely available satellite images can be used to understand large-scale coastline developments along the coast of Mecklenburg-Western Pomerania (MWP). By validating the resulting dataset with an independent Light Detection and Ranging (LIDAR) dataset, we achieved a high level of accuracy for the calculation of rates of change (ROC) with a root mean square error (RMSE) of up to 0.91 m, highlighting the reliability of Earth observation data for this purpose. The study assessed the coastal system’s natural evolution from 1984 to 1990, prior to significant human interventions, and examined the period from 1996 to 2022, which was characterized by regular sand nourishments amounting to approximately 16 million m³. The results reveal notable changes in the study area, with a significant decline in erosive trends and an increase in the number of stable and accreting transects. However, it is important to note that the regular sand nourishments may be masking the true ROC along the coastline. Furthermore, the future supply of sand raises concerns about the sustainability of coastal developments, particularly in the context of future sea level rise (SLR). The study provides valuable insights for coastal authorities and policymakers, informing decisions on sand resource allocation and highlighting the need for appropriate adaptation strategies to address future SLR and ensure long-term coastal resilience.

Abstract. Hydro-numerical models offer an increasingly important tool to determine the adequacy and evaluate the effectiveness of potential flood protection measures. However, a significant obstacle in setting up hydro-numerical and associated flood damage models is the tedious and oftentimes prohibitively costly process of acquiring reliable input data, which particularly applies to coastal megacities in developing countries and emerging economies. To address this problem, this paper takes the example of Ho Chi Minh City, Vietnam, and proposes a new and comprehensive methodology for acquiring, processing, and applying the necessary open-access data (topography, bathymetry, tidal, river flow, and precipitation time series) to set up an urban surface run-off model. As a key novelty of the paper, a normalized flood severity index (NFSI) that combines flood depth and duration is proposed. The index serves as an indicator that helps uncover urban inundation hotspots with severe damage potential, drawing attention to specific districts or boroughs with special adaptation needs or emergency response measures. The approach is validated by comparison with more than 300 locally reported flood samples, which correspond to NFSI-processed inundation hotspots in over 73 % of all cases. These findings corroborate the robustness of the proposed index, which may significantly enhance the interpretation and trustworthiness of hydro-numerical assessments in the future. The proposed approach and developed indicators are generic and may be replicated and adopted in other coastal megacities.

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Abstract. Hydro-numerical models are increasingly important to determine the adequacy and evaluate the effectiveness of potential flood protection measures. However, a significant obstacle in setting up hydro-numerical and associated flood damage models is the tedious and oftentimes prohibitively costly process of acquiring reliable input data, which particularly applies to coastal megacities in developing countries and emerging economies. To help alleviate this problem, this paper explores the usability and reliability of flood models built on open-access data in regions where highly resolved (geo)data are either unavailable or difficult to access yet where knowledge about elements at risk is crucial for mitigation planning. The example of Ho Chi Minh City, Vietnam, is taken to describe a comprehensive but generic methodology for obtaining, processing and applying the required open-access data. The overarching goal of this study is to produce preliminary flood hazard maps that provide first insights into potential flooding hotspots demanding closer attention in subsequent, more detailed risk analyses. As a key novelty, a normalized flood severity index (INFS), which combines flood depth and duration, is proposed to deliver key information in a preliminary flood hazard assessment. This index serves as an indicator that further narrows down the focus to areas where flood hazard is significant. Our approach is validated by a comparison with more than 300 flood samples locally observed during three heavy-rain events in 2010 and 2012 which correspond to INFS-based inundation hotspots in over 73 % of all cases. These findings corroborate the high potential of open-access data in hydro-numerical modeling and the robustness of the newly introduced flood severity index, which may significantly enhance the interpretation and trustworthiness of risk assessments in the future. The proposed approach and developed indicators are generic and may be replicated and adopted in other coastal megacities around the globe.

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