Rate My Professor Valentijn Pauwels

Pauwels' research expertise encompasses water management, hydrology, optimization, system analysis, modeling of land-surface processes, hydrologic model development, data assimilation, model parameter estimation, hydraulic groundwater theory, and measurement of hydrologic variables across scales. He is proficient in land-atmosphere modeling, hydrological modeling, remote sensing, and scientific computing across various programming languages. A member of the American Geophysical Union and European Geosciences Union, he has led projects including improving flood forecast skill using remote sensing data, numerical simulation of damage mitigation for flash floods, assimilating remote sensing data into hydrogeological models, forecasting drought impacts with satellite data, and quantitative spatio-temporal flood risk modeling. Key publications include 'The evolution of process-based hydrologic models: Historical challenges and the collective quest for physical realism' (Clark et al., 2017, Hydrology and Earth System Sciences), 'Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil moisture retrievals' (Tian et al., 2017, Water Resources Research), 'Advantages of analytically computing the ground heat flux in land surface models' (Pauwels and Daly, 2016, Hydrology and Earth System Sciences), and 'Estimating Rainfall Intensity Using an Image-Based Convolutional Neural Network Inversion Technique for Potential Crowdsourcing Applications in Urban Areas' (Shalaby et al., 2024, Big Data and Cognitive Computing). His work has garnered over 8,000 citations on Google Scholar. Pauwels has secured grants such as from CSIRO for novel hydrologic forecasting methods and data assimilation projects. He accepts PhD students and contributes to UN Sustainable Development Goals including clean water, sustainable cities, and climate action.