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Simulation of rainfall interception of Qinghai spruce (Picea crassifolia) forest in the eastern part of Qilian Mountains by Gash model.

GAO Chan-chan1, PENG Huan-hua2, ZHAO Chuan-yan1**, LIU Xing-ming3   

  1. (1State Key Laboratory of Grassland and AgroEcosystem, Lanzhou University, Lanzhou 730000, China; 2Wuhan Botanical Garden, Key Laboratory of
    Aquatic Botany and Watershed Ecology, Chinese Academy of Sciences, Wuhan 430000, China; 3Administrate Bureau of Gansu Qilianshan Nature Reserve, Zhangye 734000, Gansu, China)
  • Online:2015-01-10 Published:2015-01-10

Abstract:

The improved Gash model (1995) was used to simulate the rainfall interception by Qinghai spruce forest in the eastern part of Qilian Mountains. Firstly, precipitation, rainfall interception and canopy coverage were measured from the end of May to September in 2009. Secondly, canopy evaporation was calculated by PenmanMonteith method. Thirdly, interception was simulated by Gash model at three time scales (i.e., the observed period, 15 days, and rainfall events during the observed period). Finally, sensitive analysis of parameters in Gash model was made. The results showed that the estimated interception value by Gash model at the whole observed period scale was 8.70% lower than the observed value. The estimated values were 18.92% and 14.23% lower than the observed values respectively, at 15 days scale and rainfall event scale. The interception amount by canopy evaporation accounted for 74.94% of total interception, and the adsorption interception amount by canopy accounted for 25.06% of total interception. The ratio of average evaporation capacity to rainfall intensity is an important parameter of Gash model. The paper suggested that canopy evaporation during a precipitation event should play a key role in improving the accuracy of Gash model, and independent rainfall events should be defined for better estimation of rainfall interception by Gash model.
 

Key words: net primary productivity, Inner Mongolia grassland, CENTURY modeling, climate change scenario