基于机载雷达数据的青海云杉(Picea crassifolia)林降雨截留空间模拟

doi:10.7522/j.issn.1000-694X.2015.00011

摘要/Abstract

摘要： 以祁连山天老池流域青海云杉(Picea crassifolia)林为对象,以2013年降雨截留观测数据和机载雷达数据,结合GIS技术对青海云杉林进行流域尺度上的截留模拟。先以样方尺度上观测的数据建立截留量统计模型,然后利用机载雷达数据计算冠层激光穿透指数(LPI),根据LPI与叶面积指数(LAI)的关系实现对青海云杉LAI的反演,最后利用青海云杉林区降雨量和LAI空间分布数据,在GIS的空间分析中,模拟研究区青海云杉林截留的空间分布。结果表明:2013年生长季研究区青海云杉林林冠截留量0~331.0 mm,平均161.9 mm,林冠截留率在0~67.97%,平均33.89%;整个生长季,流域青海云杉林冠截留量约5.26×10⁵ m³,占整个流域生长季总降雨量的7.38%。

关键词: 林冠截留, 机载雷达, 叶面积指数, 青海云杉(Picea crassifolia)

Abstract: Rainfall interception from plant canopy is an important component in water cycle, especial in the arid and semi-arid region. In this study, Tianlaochi catchment in the upper reaches of Heihe river was selected as a research site, and the Picea crassifolia as a study object. We focused on the canopy rainfall interception at regional scale based on measuring in situ and combining with airborne LiDAR data and GIS technology. First, precipitation, interception by the forest canopy and leaf area index (LAI) of P. crassifolia forest were measured at stand scale, which were used to build a model for the canopy interception of P. crassifolia. Then, laser penetration index (LPI) was estimated by LiDAR data, and a relationship between LPI estimated and LAI measured was built based on Beer-Lambert law. We used the relationship to spatialize the LAI in the study area. Finally, the spatial distribution of canopy interception of Qinghai spruce forest during the growth season was estimated by the canopy interception model with the spatial distribution data of precipitation and LAI in 2013. The results showed that LAI value was between 0 and 4.93, with the mean value 1.24, compared with optical remote sensing, airborne LiDAR has an advantage in the inversion of LAI, the amount of canopy interception was between 0 and 331.0 mm, with the mean amount 161.9 mm, the interception percentage was between 0 and 67.97%, with the mean value 33.89%, the total interception amount was 5.26×10⁵ m³, accounting for 7.38% of the total precipitation during the growth season in 2013. So we can draw some conclusions from the study that the canopy interception model M3 is the best, and the way to obtain spatial distribution of LAI based on LiDAR data is better than on passive remote sensing. In addition, rainfall interception by Qinghai spruce plays an important role in water balance of the forest ecosystem in the catchment. This study lays the foundation for further predicting runoff in the research area.

Key words: canopy interception, airborne LiDAR, LAI, Picea crassifolia

中图分类号:

Q948.112

高婵婵, 赵传燕, 李文娟, 别强, 彭守璋, 王清涛. 基于机载雷达数据的青海云杉(Picea crassifolia)林降雨截留空间模拟[J]. 中国沙漠, 2016, 36(2): 515-521.

Gao Chanchan, Zhao Chuanyan, Li Wenjuan, Bie Qiang, Peng Shouzhang, Wang Qingtao. Modeling Spatial Distribution of Rainfall Interception by Qinghai Spruce Forest Based on Airborne LiDAR Data[J]. JOURNAL OF DESERT RESEARCH, 2016, 36(2): 515-521.

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