Abstract

Canopy interception plays a crucial role in eco-hydrological processes, and the development of spatiotemporal simulation models of canopy interception is essential for the study of this phenomenon. This study aims to fill the gap in the application of modeling to the study of canopy interception in grassland ecosystems. By using the A.P.J. DE ROO model and the RS-Gash model in conjunction with remote sensing data, we quantitatively simulate and analyze the interception capacity of the grassland vegetation canopy in the study area during the decade. Remote sensing data and measured data are used to assess the simulation accuracy of the models. The model with higher accuracy is used to analyze the spatiotemporal interception of the vegetation canopy in the study area. The results show that the vegetation canopy interception model can be applied not only to forest ecosystems but also to grassland ecosystems; the RS-Gash model has higher simulation accuracy than the A.P.J.DE ROO model; the two models show different simulation accuracy for different grassland types; the vegetation canopy interception rates of different grassland types are different, respectively: alpine meadows is 3.11 %, mountain meadows is 3.82 %, temperate grassland is 2.45 % and temperate desert grassland is 1.13 %; the ratio of vegetation canopy interception area at different levels is roughly low interception area: medium interception area: high interception area = 5:4:1. It can be seen that the application of mechanistic models combined with remote sensing data to simulate canopy interception in grassland ecosystems has great potential. Alpine meadows and mountain meadows are the main contributors to the interception of the grassland vegetation canopy in the study area.

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