Quantitative accuracy assessment of the revised sparse Gash model using distinct time-step climatic parameters

Abstract

Abstract Rainfall interception (I) can considerably influence the transport process of water. The revised sparse Gash model (RSGM) is a tool for determining the I, which assumes that the two climate parameters in the model are equal for all storms. However, few studies have provided additional cases to reexamine the correctness of this assumption and investigated the response of I of single storms to the time-step variability in climatic parameters. Hence, rainfall partitioning was measured during the growing season in 2017 for Pinus tabuliformis, Platycladus orientalis, and Acer truncatum in Northern China, and we ran RSGM on an event basis using different time-step climatic parameters (storm-based, monthly, and fixed) to estimate I. In summary, the modeling accuracy of both cumulative I and individual I was enhanced by increasing the time step of the climatic parameters in this study. These positively support the assumption in the RSGM. These results suggest that it is more appropriate to run the RSGM using fixed climate parameters to estimate I for these tree species during the growing season in northern China. Additionally, the assumption in the RSGM should be appealed to be further confirmed across the widest possible range of species, regions, and time scales.