资源环境科技发展态势分析平台

Accurately predicting bare-soil evaporation requires the proper characterization of the near-surface atmospheric conditions. These conditions, dependent on factors such as surface microtopography and wind velocity, vary greatly and therefore require high-resolution datasets to be fully incorporated into evaporation models. These factors are oftentimes parameterized in models through the aerodynamic resistance (r_a), in which the vapor roughness length (z_0v) and the momentum roughness length (z_0m) are two crucial parameters that describe the transport near the soil-atmosphere interface. Typically, when evaluating bare-soil evaporation, these two characteristic lengths are assumed equal, although differences are likely to occur especially in turbulent flows over undulating surfaces. Thus, this study aims to investigate the relationship between z_0v and z_0m above undulating surfaces to ultimately improve accuracy in estimating evaporation rate. To achieve this goal, four uniquely-designed wind tunnel – soil tank experiments were conducted considering different wind speeds and undulation spacings. Particle Image Velocimetry (PIV) was used to measure the velocity field above the undulating surface in high resolution. Using the high-fidelity dataset, the logarithmic ratio of z_0v to z_0m is determined and used to estimate r_a. Results confirm that these lengths differ significantly, with the logarithmic ratio roughly ranging from -15 to -5 under the conditions tested. PIV-measured results demonstrate this ratio is closely tied to the mass and momentum transport behaviors influenced by surface undulations. Using the data-integrated formulation of r_a, predictions of evaporation rate were prepared for both the laboratory and lysimeter experiments, demonstrating the efficacy of the proposed approach in this study.

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