Joao Paulo Leitao

Dr. Joao Paulo Leitao

Senior scientist (Group Leader)

Department Urban Water Management

About Me

Research scientist

Systems Engineering and Intelligent Network Operations, Department of Urban Water Management

ResearcherID: F-5292-2012

Scopus author ID: 34870089600

ORCID: 0000-0002-7371-0543

Google Scholar

Research interests

My research involves the development of new methods to improve urban hydrology/ hydraulic modelling accuracy, taking advantage of newly available data resources: (i) identify urban water systems features (e.g. sewer inlets and manholes) from aerial imagery obtained using Unmanned Aerial Vehicles (UAVs), and (ii) estimate flow velocity and surface water depth from videos acquired from urban surveillance cameras and social media images, respectively.

I am also interested in the development of urban flood models to more realistically assess urban flood risk. This focus on the improvement and development of Cellular Automata urban drainage/ flood models and one-dimensional (1D) overland flow models. The ultimate goal is to investigate fast but accurate models targeted to be used in real-time flood forecasting applications.

More recently, I am also investigating Infrastructure Asset Management methods aiming at improving the industry’s perennial need for more efficient infrastructure, geared to reducing costs and risks while increasing its performance and flexibility.

Recent publications

Leitão, J.P., Peña-Haro, S., Lüthi, B., Scheidegger, A., Moy de Vitry, M. (2018). Urban overland runoff velocity measurement with consumer-grade surveillance cameras and surface structure image velocimetry. Journal of Hydrology, 565, 791-804. doi: 10.1016/j.jhydrol.2018.09.001

Moy de Vitry, M., Schindler, K., Rieckermann, J., Leitão, J.P. (2018). Sewer Inlet Localization in UAV Image Clouds: Improving Performance with Multiview Detection. Remote Sensing, 10(5). doi: 10.3390/rs10050706

Leitão, J.P., de Sousa, L.M. (2018). Towards optimal fusion of Digital Elevation Models for detailed flood assessment in urban areas. Journal of Hydrology, 561, 651-661. doi: 10.1016/j.jhydrol.2018.04.043

de Sousa L. M., Leitão J.P. (2018). HexASCII: a file format for cartographical hexagonal grids. Transactions in GIS, 22(1), 217-232. doi: 10.1111/tgis.12304

Carvalho, G., Amado, C., Brito, R.S., Coelho, S.T., Leitão, J.P. (2018). Analysing the importance of variables for sewer failure prediction. Urban Water Journal. doi: 10.1080/1573062X.2018.1459748

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Cost Effective Neural Technique to Alleviate Urban flood Risk
Hexagonal Grids for urban flood modelling
Alternative data collection and assimilation methods for urban flood modelling

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Phone: +41 58 765 6714
Fax: +41 58 765 5802
Address: Eawag
Überlandstrasse 133
8600 Dübendorf
Office: BU C15

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Research Focus

Urban flood modelling and assessment

Image-based data sources for flood measurement

Urban water infrastructure planning 

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