Dr. Xichao Gao | Hydrology | Best Researcher Award
Dr. Xichao Gao | Hydrology | Senior Engineer at China Institute of Water Resources and Hydropower Research | China
Gr. Xichao Gao is an eminent researcher specializing in hydrology, water resources, and climate-driven environmental modeling, with a strong focus on urban waterlogging, drought recovery, and real-time rainfall estimation using advanced computational and deep learning methods. He obtained his Ph.D. in Hydrology and Water Resources from a leading Chinese research university, which provided a solid foundation for his extensive contributions to the China Institute of Water Resources and Hydropower Research in Beijing, China, where he currently serves as a leading researcher. Over his career, Gr. Gao has published 30 high-impact documents, which have collectively received 403 citations from 356 documents, reflecting his scholarly influence and an h-index of 12. His professional experience encompasses leading and participating in multinational research projects addressing climate resilience, hydrological risk management, and sustainable urban water systems. Gr. Gao’s research interests include hydrological process modeling, environmental monitoring using video-based and remote-sensing techniques, AI-driven water resource management, and climate adaptation strategies. He possesses advanced research skills in machine learning applications in hydrology, statistical modeling, image-based waterlogging analysis, and integrated assessment of drought recovery processes, which have enabled him to produce innovative methodologies recognized internationally. His work has appeared in reputed journals such as Hydrological Processes, Environmental Modelling and Software, and Measurement: Journal of the International Measurement Confederation, highlighting his commitment to advancing high-quality scientific knowledge. In addition to his research output, Gr. Gao has demonstrated leadership through mentoring early-career researchers, contributing to community-based water resilience initiatives, and serving on professional committees within hydrology and environmental engineering societies. He has received multiple research honors and recognitions for his contributions to climate-adaptive hydrology and computational water modeling, reflecting his growing reputation as a leading scholar in his field.
Academic Profile: Scopus
Featured Publications:
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Gao, X. (2026). Measuring urban waterlogging depth from video images using human body models. Measurement: Journal of the International Measurement Confederation. 0 citations.
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Gao, X., et al. (2025). A framework to quantify drought recovery time accounting for the lagged effect. Hydrological Processes. 1 citation.
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Gao, X., et al. (2025). Real-time rainfall estimation using deep learning: Influence of background and rainfall intensity. Environmental Modelling and Software. 1 citation.