Effect of initial plant density on modeling accuracy of the revised sparse Gash model: a case study of Pinus tabuliformis plantations in northern China

• Main Authors: Yiran Li, Xiaohua Liu, Chuanjie Zhang, Zedong Li, Ye Zhao, Yong Niu
• Format: Article
• Language: English
• Published: IWA Publishing 2020-10-01
• Series: Hydrology Research
• Subjects: initial plant density; interception loss; revised sparse gash model; sensitivity analysis; simulation accuracy
• Online Access: http://hr.iwaponline.com/content/51/5/1170

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. HIGHLIGHTS Application of the revised sparse Gash model (RSGM) in six Chinese pine plantations of different initial densities.; RSGM still does not perform well at the sparse initial densities.; Changes in initial plant density can affect the simulation accuracy of RSGM.; Discuss the possibility of perfecting RSGM to improve its accuracy.; Explore the changes in sensitivity of the parameters in RSGM under different initial densities.;