An accurate quantitative description of interception is necessary to understand regional water circulation. The revised sparse Gash model (RSGM) is currently used to estimate interception loss. Previous studies have proven that changes in initial plant density, which are caused by thinning, affect the accuracy of RSGM; however, the direct effect of initial density on modeling accuracy remains poorly understood because few studies have collected field data of the same species with various initial densities under similar site conditions. Therefore, six Pinus tabuliformis Carr. plantations with various initial densities were assessed from May to October 2016 in northern China. In summary, RSGM performs better with higher initial densities, and it cannot be suitably applied for plantations with lower initial densities, with the relative error ranging from 18.38 to 53.03%. Sensitivity analysis indicated that the predicted interception is highest sensitive to canopy structure, irrespective of initial density. The influence of climate parameters on simulated results decreased, as initial density increased. These support the notion that amending the representation of the canopy structure in the model and improving the estimation methods for determining the evaporation rate in open canopies can improve accuracy, and that the use of RSGM must first involve the consideration of initial density.
The revised sparse Gash model still performs not well at the sparse initial densities.
Changes in initial plant density can affect the simulation accuracy of the revised sparse Gash model.
The predicted interception is highly sensitive to the canopy structure, irrespective of initial density.
Canopy cover is the most sensitive parameter at lower densities, and canopy storage capacity is the most sensitive at higher densities.
Amending the representation of the canopy structure in the model probably can improve estimated accuracy.
Y.R. Li and X.H. Liu should be considered co-first authors.