Gaoyuan qixiang (Aug 2024)
A Comprehensive Review of the Application Research of the WRF- Hydro Fully Coupled Atmosphere-Land-Hydrology Model
Abstract
Numerical models have risen to prominence as indispensable tools for the in-depth study of the water cycle and these extreme hydrological phenomena, gaining widespread application across the globe.To delve into the spatiotemporal evolution patterns of global terrestrial water circulation against the backdrop of climate change and to decipher the intricate feedback mechanisms among atmospheric, land, and hydrological systems, the exploration of coupled atmospheric-land-hydrological models has emerged as a pivotal area of focus in the international research landscape dedicated to atmospheric and hydrological studies.This paper embarks on its journey by meticulously reviewing and delineating the evolution of coupled models, shedding light on the distinct advantages of the Weather Research and Forecasting Model Hydrological (WRF-Hydro) modeling system.It methodically dissects the primary sensitivity parameters of the WRF-Hydro model, while extensively covering its applications in analyzing surface runoff, soil moisture, the energy-water cycle, and the intertwined atmospheric and hydrological processes.The discourse culminates in a forward-looking exploration of the future directions in the development of the WRF-Hydro coupled model.Emphasizing strategic advancements, the paper advocates for a concerted effort towards the creation of robust scale conversion schemes, the refinement of parameterization methods, and the execution of high-resolution simulations.These simulations are crucial for accurately mapping the spatial and temporal dynamics of atmospheric and hydrological variables within basins, thereby significantly enhancing the model's capacity to intricately depict the interactions among atmospheric conditions, land surface phenomena, and hydrological processes.This comprehensive approach underlines the imperative to deepen our understanding and improve our modeling capabilities, aiming at a more effective prediction and management of the impacts arising from climate change and extreme hydrometeorological events.
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