Modeling Spatial Distribution of Rainfall Interception by Qinghai Spruce Forest Based on Airborne LiDAR Data

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

JOURNAL OF DESERT RESEARCH ›› 2016, Vol. 36 ›› Issue (2): 515-521.DOI: 10.7522/j.issn.1000-694X.2015.00011

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Modeling Spatial Distribution of Rainfall Interception by Qinghai Spruce Forest Based on Airborne LiDAR Data

Gao Chanchan¹, Zhao Chuanyan¹, Li Wenjuan¹, Bie Qiang², Peng Shouzhang¹, Wang Qingtao¹

1. State Key Laboratory of Grassland and Agro-Ecosystem/School of Life Sciencet, Lanzhou University, Lanzhou 730000, China;
2. Colleage of Resources and Enviroment, Lanzhou University, Lanzhou 730000, China

Received:2014-10-03 Revised:2015-01-22 Online:2016-03-20 Published:2016-03-20

Abstract

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

CLC Number:

Q948.112

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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Modeling Spatial Distribution of Rainfall Interception by Qinghai Spruce Forest Based on Airborne LiDAR Data

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