Methodologies, instruments and software for reliable estimation of discharges and solid transport in rivers, with special attention to extreme hydrological events

Methodologies, instruments and software for reliable estimation of discharges and solid transport in rivers, with special attention to extreme hydrological events

Rivers are dynamic systems that play a crucial role in the hydrological cycle, supporting ecosystems and providing essential resources for human activities. However, natural processes and human interventions continuously alter river systems, necessitating comprehensive monitoring strategies to manage water resources, mitigate environmental risks, and enhance disaster preparedness. The reliable estimation of flow discharges and sediment transport is essential for understanding and managing river systems, particularly during extreme hydrological events. Advances in methodologies, instruments, and software have significantly enhanced our ability to collect, process, and analyse data, leading to improved predictions and informed decision-making. However, challenges remain, including the need for further validation and calibration of models, integrating uncertainty analysis, and take into consideration climate changes.

This PhD research aims to enhance the accuracy and reliability of river flow and sediment transport predictions, particularly during extreme hydrological events, by advancing monitoring technologies and computational modeling approaches.

Specifically, on one hand the objective is to improve the performance of the ADCP to evaluate flow field and sediment transport. This includes extending ADCP applications to detailed sediment transport studies and integrating ADCP data with image-based techniques to enhance measurement reliability and provide a more comprehensive understanding of river dynamics. On other hand, the research will develop and rigorously evaluate calibration and validation strategies for two widely used computational fluid dynamics (CFD) software packages, OpenFOAM and Ansys Fluent. This involves utilizing both laboratory-generated data and field-collected ADCP data to ensure the models accurately represent real-world river conditions.