An alternative approach to estimate river cross-sections using LIDAR-based digital elevation model

ABSTRACT

Topographic LIDAR can be used to estimate elevation values for dry areas down to the river water level during the extraction of river cross-sections (XS). However, LIDAR cannot accurately predict the submerged topography, which causes uncertainty in river XS area estimation. This uncertainty affects the channel water level and flood inundation depth estimation in in situ sparse data. Therefore, an alternative approach is presented to estimate unknown submerged topography (UST) using topographic LIDAR. The one dimension/two dimension Hydrologic Engineering Center River Analysis System (1D/2D HEC-RAS) model is used to simulate the estimated river XS with the help of in situ river water level and flow data which is later validated using in situ data. The results show that the proposed approach accurately estimates water level (error >0.5 m), channel flow areas, and floodplain water depths. Notably, the extent of the estimated floodplain overflow by UST models was in 94% agreement with the real XS.

KEYWORDS:

• cross-section shapes
• digital terrain model
• river cross-sections
• cross-sectional river area
• water level
• hydrological modelling

Editor A. CastellarinAssociate editor A. Domeneghetti

Editor A. CastellarinAssociate editor A. Domeneghetti

Acknowledgements

We gratefully acknowledge the Malaysian Meteorological Department, Department of Irrigation and Drainage, School of Physics, School of Industrial Technology, School of Civil Engineering of Universiti Sains Malaysia, and Malaysian Remote Sensing Agency for providing the required research facilities, university fellowship, and data for this work. We express our gratitude for financial support from the Research Supporting Project (RSP- 2022/351), King Saud University, and Riyadh, Saudi Arabia. Furthermore, we acknowledge the University of Malaya and Universiti Sains Malaysia for providing research facilities [via grant number GPF017B-2018 and grant number 1001/PTEKIND/8011021, respectively] to carry out this work.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

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Additional information

Funding

This work was supported by the Institut Pengurusan dan Pemantauan Penyelidikan, Universiti Malaya [GPF017B-2018]; King Saud University [RSP-2021/351]; and Universiti Sains Malaysia [1001/PTEKIND/8011021].