research

Welcome to our research lab, where we are dedicated to advancing hydrologic science and water resources system analysis through cutting-edge research. Our focus lies in predictive science, uncertainty analysis, data analytics, and high-performance computing, with a primary emphasis on addressing the challenges posed by climate change. At the heart of our research is a multidisciplinary approach that integrates engineering, statistics, and data science to deepen our understanding of the interactions between climate, hydrology, and water resources. Leveraging state-of-the-art methodologies such as machine learning, remote sensing, and advanced data assimilation techniques, we develop predictive models capable of simulating complex hydrologic processes with unprecedented accuracy and reliability. Through innovative techniques such as Bayesian inference, ensemble simulation, and multi-modeling approaches, we enhance the reliability of our predictive models and decision-making processes in the face of uncertain future climate conditions. In our research group, we study surface and subsurface hydrologic processes and their interactions to improve the predictability of extreme hydroclimate events under climate change. Furthermore, our lab is committed to developing novel methodologies for post-processing and analyzing large-scale hydrologic datasets. By extracting actionable insights from these datasets, we aim to inform more effective water resource management practices and policy decisions. Through our collaborative and interdisciplinary approach, we strive to contribute to the development of sustainable and resilient water resource systems that can withstand the challenges posed by a changing climate.