Comparing Drone and Satellite DEMs for Hydrodynamic Flood Modeling in a Rural Brazilian Catchment

Abstract

The rural region of the municipality of Bananal (SP, Brazil) experiences recurrent flooding events associated with rising water levels in tributaries of the Bananal River, especially during periods of intense rainfall. This study aimed to compare the performance of different Digital Elevation Models (DEMs), one derived from NASA orbital data and another generated from drone-based aerophotogrammetric surveys, in identifying and mapping flood-prone areas. The objective was to assess whether drone field campaigns are essential for this type of analysis or whether orbital DEMs are sufficient for the hydrodynamic characterization of the area. Hydrodynamic models were developed using the software QGIS, HidroFlu—for watershed parametrization and inflow estimation, and MODCEL—for hydrodynamic simulation, with spatial resolutions of 10 m, 30 m, and 50 m, in order to analyze the impact of topographic detail on simulation results. Two approaches were tested for defining boundary conditions: one based on precipitation data with a 25-year return period, and another based on the Bananal River discharge estimated from the watershed. The results indicated that the model based on the drone-derived DEM, with 10 m resolution and boundary conditions defined by river discharge, showed the best performance in representing floodable areas. However, the findings also highlight that high-resolution DEMs entail higher operational costs, due to the need for field activities and greater computational capacity to run the simulations.

Keywords

Hydrodynamic modeling / Digital elevation models / Drone

CRediT authorship contribution statement Author Contributions

Conceptualization, A.R.L.D.; Methodology, A.R.L.D.; Software, A.R.L.D.; Validation, A.R.L.D., J.T.A.J. and A.K.B.d.O.; Formal analysis, A.R.L.D.; Investigation, A.R.L.D.; Data curation, A.R.L.D.; Writing—original draft preparation, A.R.L.D.; Writing—review and editing, J.T.A.J. and A.K.B.d.O.; Visualization, A.R.L.D.; Supervision, J.T.A.J. and A.K.B.d.O.; Project administration, J.T.A.J.; Funding acquisition, J.T.A.J.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Funding

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -Finance Code 001. The authors also acknowledge the financial support of the Human Resources Program of the Agência Nacional do Petróleo, Gás Natural e Biocombustíveis (PRH-ANP), through a scholarship granted during the MSc program.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors would like to express their sincere gratitude to the laboratory technicians at the Pontifical Catholic University of Rio de Janeiro for their valuable technical support. The authors also wish to thank Solonovo Soluções Sustentáveis, especially Julio Prezotti, José Márcio Ferreira and Lucas Bridi, for providing the drone used in this study and for their technical guidance on its operation. Special thanks are extended to Gabriel Nogueira Brum for his kindness in allowing this research to be conducted on his property, generously granting access to the study area, which was essential for the development of this work. The authors are also grateful to Roberto Newton Carneiro, from IBIOS, for his continuous support and for closely following all stages of this research. Finally, the authors would like to thank all those who contributed, directly or indirectly, to the completion of this study.

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