Zeng, W.; Zhao, T.; Shi, C.; Yang, J.; Qian, Y.; Ma, S.; Huang, Q. Spatiotemporal Variation Characteristics and Driving Factors of Vegetation Canopy Interception in Beijing. Preprints2024, 2024101027. https://doi.org/10.20944/preprints202410.1027.v1
APA Style
Zeng, W., Zhao, T., Shi, C., Yang, J., Qian, Y., Ma, S., & Huang, Q. (2024). Spatiotemporal Variation Characteristics and Driving Factors of Vegetation Canopy Interception in Beijing. Preprints. https://doi.org/10.20944/preprints202410.1027.v1
Chicago/Turabian Style
Zeng, W., Shuai Ma and Qingli Huang. 2024 "Spatiotemporal Variation Characteristics and Driving Factors of Vegetation Canopy Interception in Beijing" Preprints. https://doi.org/10.20944/preprints202410.1027.v1
Abstract
In order to better understand the temporal and spatial variation of canopy rainfall interception with watershed, In this study, the remote sensing observation data at the regional scale were coupled with the vegetation canopy rainfall interception model constructed by A.P.J. DEROO for validation, and the spatial variation trend of rainfall interception was analyzed through linear and nonlinear trends, and the rainfall interception was quantified and the influencing factors were analyzed at different altitudes and regions at time scales. The results show that: (1) Compared with the PML_V2 and measured values, the root mean square errors of the simulated rainfall inter-ception values are 5.69 and 3.37, and the effective factor are 0.66 and 0.64, respectively, which confirms the reliability of the A.P.J.DE ROO model in estimating rainfall interception in Beijing. (2) From 2005 to 2020, the annual interception volume and interception rate showed an upward trend, with the largest increase trend in 2005 at 3.8%/a, and the interception volume reversed in 2015, changing from an increase (6.5 mm/a) to a decrease (-5.8 mm/a). (3) The Theil-Sen Median trend was used to test the spatial variation trend of rainfall interception in the canopy in Beijing, with an increasing trend of 89.5%, a decreasing trend of 8.7%, and a basically unchanged area of 1.8%. Through the BFAST01 mutation test, 4.4% of the canopy rainfall interception in the whole region had mutations, and the southern mutation detection type accounted for the largest proportion. (4) Leaf area index, rainfall, canopy height and slope had the strongest explanatory power for canopy interception in the monthly scale analysis, while wind speed and temperature were weaker. The results of this study provide new insights into the analysis of spatial and temporal changes in canopy interception in Beijing, which can help to accurately assess the impact of forest ecosystems on regional water cycles and provide scientific and practical insights for water resource man-agement.
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