1. 中国环境科学研究院 环境基准与风险评估国家重点实验室 国家环境保护区域生态过程 与功能评估重点实验室,北京,100010
2. 福建师范大学 地理科学学院,福建,福州,350007
3. 井冈山生态环境综合观测研究站, 江西 井冈山,343699
4. 江西井冈山国家级自然保护区管理局, 江西 井冈山,343699
纸质出版:2016
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白雲, 李新通, 苏德, 等. 井冈山国家级自然保护区杉木林冠层的截留模型[J]. 水土保持通报, 2016,36(2):216-221.
BAI Yun, LI Xintong, SU De, et al. Model Refinement of Canopy Interception of Rainfall by Chinese Fir Forests at Jinggangshan National Nature Reserve[J]. Bulletin of Soiland Water Conservation, 2016, 36(2): 216-221.
白雲, 李新通, 苏德, 等. 井冈山国家级自然保护区杉木林冠层的截留模型[J]. 水土保持通报, 2016,36(2):216-221. DOI: 10.13961/j.cnki.stbctb.2016.02.041.
BAI Yun, LI Xintong, SU De, et al. Model Refinement of Canopy Interception of Rainfall by Chinese Fir Forests at Jinggangshan National Nature Reserve[J]. Bulletin of Soiland Water Conservation, 2016, 36(2): 216-221. DOI: 10.13961/j.cnki.stbctb.2016.02.041.
[目的] 研究和改进井冈山国家级然保护区杉木林冠层截留模型
为研究区森林资源生态价值评价、水资源保护和管理、生态环境保护等相关研究提供理论基础。[方法] 以仪垂祥等提出的冠层截留模型为基础
对其进行改进
并以实测杉木林截留数据对模型进行率定和验证。[结果] 经实测数据率定
降雨过程中的附加截留量与"截留剩余雨量"(降雨量与叶面截留量的差值)呈幂函数关系。率定之后的模型在次降雨截留模拟的自检验分析中模型有效系数为0.90
比经验模型模拟的精度更高
在其他样地的累计截留模拟中的相对偏差平均为6.49%
模拟精度与同类研究中Gash模型的模拟精度相当。[结论] 经率定的改进模型可以应用于研究区杉木林的冠层截留模拟。
[Objective] Rainfall interception by forest canopy is an important eco-hydrological process of forest. We aimed to model the canopy interception process by chinese fir forest in Jinggangshan nature reserve in order to provide some bases for relevant researches with respect to eco-value evaluation of forest
protection and management of water resources
and environment protection of this region
et al. [Methods] A model developed by Yi Chuixiang et al was refined. And it was calibrated and validated by observed interception data in a chinese fir forest. [Results] The model calibration showed that extra interception as a dependent variable is a power function of remained-rainfall
defined as the result of atmosphere rainfall minus the value intercepted by plant leaves. The calibrated model performed better than those empirical models and is comparable to Gash model in similar researches. The effective coefficient and relative bias in predicting single rainfall event were 0.9 and 6.49%
respectively. [Conclusion] After calibration
the improved model in our study can be used for simulating canopy interception by chinese fir forest in the research region.
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