Multi-parameterization of Hydrological Processes in a Single-Layer Urban Canopy Model
Yuqi Huang is currently a Ph.D. student in the School of Meteorology at the University of Oklahoma (OU), advised by Prof. Chenghao Wang. Before coming to OU, Yuqi completed his master’s degree in civil engineering at Beijing Normal University, China. His previous research focused on understanding and modeling the physical, hydrological, and ecological processes of inland water bodies and the response of aquatic ecosystems to climate change. His Ph.D. research topic is urban climate and hydrometeorology in which he seeks to understand and improve the predictive capability of urban hydrometeorological and climate simulations across multiple spatial scales.
Abstract
Accurately representing urban hydrological processes is essential for understanding energy and water exchanges in cities, improving weather and climate simulations across scales, and informing effective flood and water resource management. Despite notable advancements in urban land surface models since the last international urban model intercomparison project, several challenges persist. Notably, many models still struggle to achieve a closed water balance, and the representation of hydrological processes often remains oversimplified. These issues primarily stem from the inherent complexity and heterogeneity of the urban hydrologic cycle. In this study, we integrated multiple hydrological parameterization schemes into a single-layer urban canopy model to better capture key processes such as canopy interception by urban grass and trees, surface runoff, soil moisture dynamics, and groundwater runoff. These new schemes complement the model’s existing capabilities of resolving root water uptake and evapotranspiration. We evaluated the performance of these new schemes with observations from different sites across a wide range of background climates and site characteristics. Results demonstrate that employing these new schemes enhances the accuracy of surface energy and water partitioning and improves the characterization of urban hydrological behavior. Additionally, our findings highlight the dependence of model accuracy on specific parameterization schemes in different climate regions. Our approach has important implications for urban planners and policymakers, especially in enhancing urban water management and resilience under extreme weather and climate conditions. Furthermore, these multi-parameterization schemes can be coupled into the urban canopy models in mesoscale and global models such as WRF, MPAS, and CESM to improve the representation of urban hydrological processes, ultimately leading to better predictive capabilities and more informed decision-making.