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Paul Andrés Muñoz Pauta |
Acerca de:
Paul Muñoz received the civil engineering degree from the University of Cuenca, Cuenca, Ecuador, in 2015, and the M.Sc. degree in water resources engineering from the Katholieke Universiteit Leuven, Leuven, Belgium and Vrije Universiteit Brussel, Brussels, Belgium, in 2018. He is currently working toward the Ph.D. degree in water resources in the University of Cuenca. His research interests include the use of artificial intelligence for real-time hydrological applications such as flood and drought forecasting, the use of remote sensing products for retrieving reliable precipitation information, and the evaluation of high-resolution technologies for punctual estimation of precipitation. Paul is a selected member of the young scientists programme from Integrated Research on Disaster Risk (IRDR), China. He has been awarded with several scholarships including the VLIR-UOS Award Scholarship to study in Belgium, and recently, a 2-year research grant from the German Academic Exchange Service to complement his doctoral studies at the Philipps-University Marburg in Germany.
Líneas de Investigación
Pronóstico de inundaciones; Inteligencia Artificial, Remote Sensing; Hidroinformática; Hidrometeorología.
Investigación maestría:
Flash-flood forecast modeling in a mountain catchment based on the Random Forest algorithm.
Investigación doctorado:
Flash-Flood Forecast Modeling with Machine Learning techniques. Use of information retrieved from ground and Remote Sensing products.
Publicaciones:
- Muñoz, P., Orellana-Alvear, J., Bendix, J., Feyen, J., & Célleri, R. (2021). Flood Early Warning Systems Using Machine Learning Techniques: The Case of the Tomebamba Catchment at the Southern Andes of Ecuador. Hydrology, 8(4), 183.
- Muñoz, D. F., Muñoz, P., Moftakhari, H., & Moradkhani, H. (2021). From local to regional compound flood mapping with deep learning and data fusion techniques. Science of The Total Environment, 782, 146927.
- Muñoz, P., Orellana-Alvear, J., & Célleri, R. (2021). Application of a Machine Learning Technique for Developing Short-Term Flood and Drought Forecasting Models in Tropical Mountainous Catchments. In Integrated Research on Disaster Risks (pp. 11-35). Springer, Cham.
- Muñoz, D. F., Muñoz, P., Alipour, A., Moftakhari, H., Moradkhani, H., & Mortazavi, B. (2021). Fusing multi-source data to estimate the effects of urbanization, sea level rise and hurricane impacts on long-term wetland change dynamics. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
- Contreras P, Orellana-Alvear J, Muñoz P, Bendix J, Célleri R. (2021). Influence of Random Forest Hyperparameterization on Short-Term Runoff Forecasting in an Andean Mountain Catchment. Atmosphere 12(2):238.
- Orellana-Alvear, J., Célleri, R., Rollenbeck, R., Muñoz, P., Contreras, P., & Bendix, J. (2020). Assessment of Native Radar Reflectivity and Radar Rainfall Estimates for Discharge Forecasting in Mountain Catchments with a Random Forest Model. Remote Sensing, 12(12), 1986.
- Muñoz, P.; Orellana-Alvear, J.; Willems, P.; Célleri, R. (2018). Flash-Flood Forecasting in an Andean Mountain Catchment—Development of a Step-Wise Methodology Based on the Random Forest Algorithm. Water, 10, 1519.
- Muñoz, P.; Célleri, R.; Feyen, J. (2016). Effect of the Resolution of Tipping-Bucket Rain Gauge and Calculation Method on Rainfall Intensities in an Andean Mountain Gradient. Water, 8, 534.
Más detalles se los encuentra en el CV Adjunto.