The use of UAV-derived bathymetric data for hydraulic modelling to inform e-flow assessments
Citation
Maharaj, U.; Harvey, T. A.; Pike, T.; Singh, K. R. 2024. The use of UAV-derived bathymetric data for hydraulic modelling to inform e-flow assessments. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Digital Innovation. 24p.
Abstract/Description
Environmental flows (E-flows) are crucial for maintaining healthy river ecosystems as an essential part of water resources management, but traditional E-flow assessments that include modelling of hydraulic habitats, often rely on limited, single cross-section data. This study presents a novel approach integrating Sound Navigation and Ranging (SoNAR) and Light Detection and Ranging (LiDAR) data collected using an Unmanned Aerial Vehicle (UAV) to create a high-resolution Digital Terrain Model (DTM) and was carried out for a section of the Olifants River in Southern Africa. The integrated DTM enabled detailed 2-Dimensional (2D) hydraulic modelling using Hydraulic Engineering Centre River Analysis System (HEC-RAS), with the resulting depth and velocity outputs used to visualise the HABitat FLOw (HABFLO) fish and invertebrate habitat classes across the entire reach that was modelled. Additionally, a habitat distribution calculator was developed to determine habitat distributions based on river flows. The longitudinal analysis of habitat distributions for a section of the river revealed variations in habitat class distributions that a single cross-section-based analysis would not highlight, thus providing a more comprehensive understanding of habitat dynamics under varying flow conditions. The successful merging of SoNAR and LiDAR data demonstrates the power of combining UAV-derived remote sensing techniques for characterisation of riverine features. This workflow has the potential to further enhance E-flow assessments, aiding in the development of ecologically sound water management strategies. However, future work should include in-field validation of modelled habitat distributions and the expansion of the methodology to larger areas.
