Abstract
Afforestation in the transitional zone between the loess hilly area and the Mu Us Sandy Land of China has reshaped the landscape and greatly affected eco-hydrological processes. Plantations are crucial for regulating local net rainfall inputs, thus making it necessary to quantify the closure loss of plantation species in drought and semi-arid areas. To quantify and model the canopy interception of these plantations, we conducted rainfall redistribution measurement experiments. Based on this, we used the modified Gash model to simulate their interception losses, and the model applicability across varying rainfall types was further compared and verified. Herein, Caragana korshinskii, Salix psammophila, and Pinus sylvestris plantations in the Kuye River mountain tract were chosen to measure the precipitation distribution from May to October (growing season). The applicability of a modified Gash model for different stands was then evaluated using the assessed data. The results showed that the canopy interception characteristics of each typical plantation were throughfall, interception, and stemflow. The relative error of canopy interception of C. korshinskii simulated by the modified Gash model was 8.79%. The relative error of simulated canopy interception of S. psammophila was 4.19%. The relative error of canopy interception simulation of P. sylvestris was 13.28%, and the modified Gash model had good applicability in the Kuye River Basin. The modified Gash model has the greatest sensitivity to rainfall intensity among the parameters of the C. korshinskii and S. psammophila forest. The sensitivity of P. sylvestris in the modified Gash model is that the canopy cover has the greatest influence, followed by the mean rainfall intensity. Our results provide a scientific basis for the rational use of water resources and vegetation restoration in the transitional zone between the loess hilly region and the Mu Us Sandy Land. This study is of import for the restoration and sustainability of fragile ecosystems in the region.
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