Professor at Zhengzhou University, China
Professor Caihong Hu is a leading expert in hydrology and water resource engineering, with over three decades of academic and research experience in China. She is currently serving as a professor at the School of Water Conservancy and Environment, Zhengzhou University. Her work has focused on hydrological modeling, flood forecasting, and the impacts of climate change on water systems, particularly in the Yellow River Basin. Over the years, Prof. Hu has developed and applied a variety of innovative hydrological models and forecasting tools to support water management strategies under complex environmental conditions. Through her collaborative and interdisciplinary approach, she has contributed significantly to advancing sustainable water resource practices in China and beyond.
Profile
Scopus
Education
Prof. Hu’s academic foundation is rooted in her education at Wuhan University, a prestigious institution for water science in China. She earned her bachelor’s degree in River Sediment and River Regulation Engineering in 1991, followed by a master’s degree in Hydrology and Water Resources in 1998 under the supervision of Prof. Luo Wensheng. She then pursued her PhD in the same field at Wuhan University and completed it in 2004 under the guidance of Prof. Guo Shenglian. Her doctoral thesis, titled Analytical and Comparative Study on the Hydrological Models in the Yellow River Basin, laid the groundwork for her future research into watershed modeling and climate impact assessments.
Experience
Prof. Hu began her academic career in 1991 as an assistant lecturer at Taiyuan Normal University, where she served until 2004. She then transitioned to Zhengzhou University, where she steadily rose through the ranks from lecturer to associate professor and eventually full professor by 2011. During her tenure, she has taught a wide range of undergraduate, graduate, and doctoral-level courses, including Engineering Hydrology, Hydrological Forecasting, and Watershed Runoff Modeling. In 2012, she also completed a visiting research fellowship at the University of Hong Kong, further expanding her academic exposure and international collaboration.
Research Interest
Prof. Hu’s research focuses on hydrological modeling and forecasting under changing environmental conditions. Her primary interests lie in understanding how climate change and extreme weather events affect runoff and water availability. She is particularly skilled in integrating machine learning and statistical methods, such as support vector machines and neural networks, into hydrological systems for predictive analytics. Her work also extends to water resource utilization and eco-hydrological assessments, enabling better flood risk management and sustainable planning.
Awards
Throughout her career, Prof. Hu has received multiple accolades in recognition of her contributions to water science and education. She has been honored with the Science and Technology Advancement Prize from Henan Province multiple times (2007, 2011, 2016, and 2022), along with distinctions from the Henan Water Conservancy and Meteorological Administration. In 2010, she was named a “Three Education People” advanced individual and earned top recognition in a teaching competition among middle and young faculty at Zhengzhou University. These awards highlight her dual excellence in research and pedagogy.
Publications
Prof. Hu has authored numerous impactful publications in top-tier journals. Selected key works include:
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A modified Xinanjiang model and its application in Northern China, Nordic Hydrology (2005), cited by 200+ articles, explores model adaptation for semi-arid regions.
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Simulating spring flows from karst aquifer with an artificial neural network, Hydrological Process (2008), cited by 300+ articles, demonstrates AI integration in groundwater modeling.
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Precipitation-Runoff modeling Using Support Vector Regression in northern China, ISWREP Proceedings (2011), bridges traditional hydrology with AI techniques.
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Real-time Flood Classification Forecasting Based on K-means Plus Plus Clustering and Neural Network, Water Resources Management (2021), introduces novel clustering methods for flood prediction.
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Mapping flood extent and its impact on land use/land cover, Acta Geophysica (2021), employs remote sensing for flood impact analysis.
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Research on particle swarm optimization in LSTM neural networks for rainfall-runoff simulation, Journal of Hydrology (2022), explores optimization techniques in deep learning applications.
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Study on fractional vegetation cover dynamic in the Yellow River basin from 1901 to 2100, Frontiers in Forests and Global Change (2023), offers climate-driven vegetation trend forecasts.
These publications underscore her interdisciplinary reach and technical innovation, particularly in applying AI and machine learning to hydrological studies.
Conclusion
Prof. Caihong Hu exemplifies excellence in hydrology, blending traditional water science with cutting-edge data techniques to address some of the most pressing environmental challenges. Her consistent contributions through teaching, research, and project leadership have made a profound impact on water resource planning and disaster mitigation. Her visionary approach, supported by national-level research projects and globally cited publications, positions her as a vital contributor to scientific advancement in the era of climate uncertainty. As such, she is a fitting candidate for recognition in the Excellence in Research Award category.