An enhanced rainfall–runoff model with coupled canopy interception

Wanghai Tao, Quanjiu Wang, Li Guo, Henry Lin, Xiaopeng Chen, Yan Sun, Songrui Ning

Research output: Contribution to journalArticle

Abstract

The translation of rainfall to runoff is significantly affected by canopy interception. Therefore, a realistic representation of the role played by vegetation cover when modelling the rainfall–runoff system is essential for predicting water, sediment, and nutrient transport on hillslopes. Here, we developed a new mathematical model to describe the dynamics of interception, infiltration, and overland flow on canopy-covered sloping land. Based on the relationship between rainfall intensity and the maximum interception rate, the interception process was modelled under two simplified scenarios (i.e., re ≤ Intm and re > Intm). Parameterization of the model was based on consideration of both vegetation condition and soil properties. By analysing the given examples, we found that Intm reflects the capacity of the canopy to store the precipitation, k reveals the ability of the canopy to retain the intercepted water, and the processes of infiltration and runoff generation are impacted dramatically by Intm and k. To evaluate the model, simulated rainfall experiments were conducted in 2 years (2016 and 2017) across six cultivation plots at Changwu State Key Agro-Ecological Experimental Station of the Chinese Loess Plateau. The parameters were obtained by fitting the unit discharge (simulated rainfall experiments in 2016) using the least squares method, and estimation formulas for parameters pertaining to vegetation/soil factors (measured in 2016) were constructed via multiple nonlinear regressions. By matching the simulated results and unit discharge (simulated rainfall experiments in 2017), the validity of the model was verified, and a reasonable precision (average R2 =.86 and average root mean square error = 6.45) was obtained. The model developed in this research creatively incorporates the canopy interception process to complement the modelling of rainfall infiltration and runoff generation during vegetation growth and offers an improved hydrological basis to analyse matter transport during rainfall events.

Original languageEnglish (US)
Pages (from-to)1837-1853
Number of pages17
JournalHydrological Processes
Volume34
Issue number8
DOIs
StatePublished - Apr 15 2020

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

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