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

Yiran Li,Chuanjie Zhang,Yong Niu

doi:10.2166/nh.2021.085

Yiran Li, Chuanjie Zhang + Show 1 more

Open Access

https://doi.org/10.2166/nh.2021.085

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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.

Highlights

Rainfall is a major supply of water within forested catchments and is redistributed into throughfall (TF, mm), stemflow (SF, mm), and rainfall interception (I, mm) after reaching the canopy, thereby affecting the local water balance in a forested ecosystem (Mużyło et al 2012; Ringgaard et al 2014; Sun et al 2014)
Larger underestimations were obtained for revised sparse Gash model (RSGM)-E, with 12.9–20.7% for Pinus tabuliformis (Pt), 16.4–16.5% for Platycladus orientalis (Po), and 14.0–14.7% for Acer truncatum (At), whereas better fits were obtained for RSGM-G, in which cumulative I were underestimated by 9.9–16.1% for Pt, 13.6–15.9% for Po, and 15.7–20.2% for At
This study was conducted to examine the reasonableness of the assumption in the RSGM that the meteorological parameters are the same for all storms, and to explore the differences in the estimation results for single storms when the RSGM was driven by three time-step climate parameters, respectively

Summary

Introduction

Rainfall is a major supply of water within forested catchments and is redistributed into throughfall (TF, mm), stemflow (SF, mm), and rainfall interception (I, mm) after reaching the canopy, thereby affecting the local water balance in a forested ecosystem (Mużyło et al 2012; Ringgaard et al 2014; Sun et al 2014). The original Gash analytical model (Gash 1979) was proposed to simplify the Rutter model (Rutter et al 1971) It was subsequently reformulated into a sparse version due to its unsuitability for sparse forest stands (Gash et al 1995). The resulting model is referred to as the revised sparse Gash model (RSGM) in this paper. This version appears to be more rigorous in its conceptual and physical approaches than the classical and sparse Gash model. There have been few applications of this model version in research relative to the sparse Gash model (Price & Carlyle-Moses 2003; Valente et al 2020)

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