Enhancing digital bathymetric models by advanced measurement uncertainty analysis

Accurate Digital Bathymetric Model (DBM)s are essential for ensuring safe navigation on waterways, yet they heavily depend on precise underwater measurements and robust modeling techniques. However, measurements taken in underwater environments are highly susceptible to uncertainties due to challenging environmental conditions and unknown underwater geometries, complicating the evaluation of both measurements and resulting models. This paper explores the impact of measurement uncertainty on DBM quality and presents a systematic pipeline for modeling these uncertainties to improve the reliability of resulting models. The methodology comprises of two primary stages. A detailed measurement uncertainty model is developed in the first stage based on error propagation principles. This model accounts for multiple uncertainty sources ranging from instrument accuracy to environmental influences. In the second stage, we implement a simulation-based approach to evaluate the influence of these uncertainties on the final DBM. To this end, we have developed a survey simulator that simulates a Multi-Beam Echo Sounder (MBES) system and generates realistic measurement uncertainties. The integration of these uncertainties as observation weights during the modeling process enhances model accuracy and reliability. The effectiveness and practicality of the proposed method are confirmed through validation in a controlled simulation environment with known geometry and uncertainties. The results underscore not only the technical benefits of incorporating measurement uncertainty in surface modeling but also highlight its critical importance in ensuring navigational safety through high-quality, reliable DBMs.