Coasts in peril?! – How to assess flood hazards and relative sea-level rise impact in data-sparse coastal lowlands using open data

Coastal lowlands in the world are facing huge challenges due to their increasing exposure to coastal, pluvial and fluvial flooding as well as relative sea-level rise, underscoring the need of comprehensive hazard and impact assessments. However, due to data scarcity for many coasts and river deltas worldwide, the generation of accurate and thorough information on these hazards as well as area, population and assets at risk is problematic and demanding. Especially as both relative sea-level rise impact and flood inundation are closely linked to land elevation, the reliability of such assessments heavily depends on the vertical accuracy and proper datum referencing of the coastal elevation data.

In this context, we present a concept designed for enhancing the quality of coastal exposure analysis in the world using publicly available coastal elevation data. By performing a globally consistent vertical datum conversion of elevation data to continuous local mean sea level, we account for uncertainties that have not or only inadequately been addressed in previous studies. This strengthens the reliability of coastal flood hazard and relative sea-level rise impact assessments. We demonstrate the improvements in the performance of recent global digital elevation models (DEMs) for impact assessments in data-sparse coastal regions by validating the DEMs for several key coastal lowlands such as large river deltas.

We also highlight a workflow for conducting a first-order assessment of single and multiple flood-type hazards in inaccessible and data-sparse coastal lowlands, showcasing the Ayeyarwady Delta in Myanmar. Our approach employs only freely available datasets such as satellite imagery, global precipitation estimates, satellite-based river discharge measurements, elevation data, land use information, and population data. The highly flexible workflow allows to integrate and combine various further datasets while keeping computational demands low.

Our approaches provide valuable strategies for assessing flood-prone areas on both regional and local scales in data-sparse coastal lowlands worldwide. They allow to attribute different flood hazards and enhance the quality of flood hazard assessments through the use of improved elevation data. Our work further provides a foundation for integrating vertical land motion dynamics to gain a better understanding of the interplay and implications of relative sea-level rise, changes in elevation, and changes in flood exposure. Ultimately, this contributes to a holistic perspective to grasp the complexity of these interconnected processes, which is essential for developing effective coastal risk adaptation and mitigation strategies.