Paul Muñoz

👋! I’m a hydrology and AI researcher developing tools and models for hydrological forecasting and climate applications. My work bridges advanced artificial intelligence, remote sensing, and applied science to solve real-world water challenges.

Current and Past Positions

May 2024 - Present: Postdoctoral researcher at the Department of Water and Climate (HYDR) at the Vrije Universiteit Brussel, Belgium.
2023 - 2024: External Consultant at Food and Agriculture Organization-FAO (United Nations). Specialist in the evaluation of drought impacts on agricultural production and food security.
Oct 2018 - April 2024: Post- and doctoral researcher at Department of Water Resources and Environmental Sciences at Universidad de Cuenca.

Education

2019 – 2023: Ph.D. in Water Resources
University of Cuenca, Cuenca, Ecuador
Thesis: Towards the improvement of machine learning peak runoff forecasting by exploiting ground- and satellite-based precipitation data: A feature engineering approach.
2016 – 2018: MSc. in Water Resources Engineering
KU Leuven, Leuven, Belgium
Thesis: Flash-flood forecasting in an Andean mountain catchment—development of a step-wise methodology based on the random forest algorithm.
2009 – 2015: Bachelor’s in Civil Engineering
University of Cuenca, Cuenca, Ecuador
Thesis: Effect of the resolution of tipping-bucket rain gauge and calculation method on rainfall intensities in an Andean mountain gradient.

Highlighted publications

2024: Enhancing runoff forecasting through the integration of satellite precipitation data and hydrological knowledge into machine learning models - Natural Hazards.
2023: Near-real-time satellite precipitation data ingestion into peak runoff forecasting models - Environmental Modelling & Software.
2021: From local to regional compound flood mapping with deep learning and data fusion techniques - Science of the Total Environment.
2018: Flash-Flood Forecasting in an Andean Mountain Catchment—Development of a Step-Wise Methodology Based on the Random Forest Algorithm - Water.

Highlighted research projects

Data fusion of near-real-time satellite products for improving runoff forecasting.

A research network for the resilience of headwater systems and water availability for downstream communities across the Americas.

Development of hydrological forecasting models using weather radar data in Andean basins.

Highlighted applied-science projects

Development of a real-time runoff forecasting system for the Minas-San Francisco hydropower dam.

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Last Updated: October 2024

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