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Rainfall interception of typical ecosystems in the Heihe River Basin: Based on high temporal resolution soil moisture data

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Abstract

Rainfall interception is of great significance to the fully utilization of rainfall in water limited areas. Until now, studies on rainfall partitioning process of typical ecosystems in Heihe River Basin, one of the most important inland river basins in China, is still insufficient. In this study, six typical ecosystems were selected, namely alpine meadow, coniferous forest, mountain steppe, desert, cultivated crop, and riparian forest, in Heihe River Basin for investigation of the rainfall interception characteristics and their influencing factors, including rainfall amount, duration, and intensity, based on the gross rainfall and high temporal resolution soil moisture data obtained from 12 automatic observation sites. The results show that the average interception amount and average interception rate of the six ecosystems are significantly different: alpine meadow 6.2 mm and 45.9%, coniferous forest 7.4 mm and 69.1%, mountain steppe 3.5 mm and 37.3%, desert 3.5 mm and 57.2%, cultivated crop 4.5 mm and 69.1%, and riparian forest 2.6 mm and 66.7%, respectively. The rainfall amount, duration, and intensity all had impact on the process of rainfall interception. Among these three factors, the impact of rainfall amount was most significant. The responses of these ecosystems to the rainfall characteristics were also different. Analyzing rainfall interception with high temporal resolution soil moisture data is proved to be a feasible method and need further development in the future.

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Correspondence to Yongmei Huang.

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National Natural Science Foundation of China, No.91425301, No.91725000; State Key Laboratory of Land Surface Processes and Resource Ecology, No.2017-ZY-04

Author: Author: Yang Chongyao (1994-), Master, specialized in vegetation ecology and ecohydrology.

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Yang, C., Huang, Y., Li, E. et al. Rainfall interception of typical ecosystems in the Heihe River Basin: Based on high temporal resolution soil moisture data. J. Geogr. Sci. 29, 1527–1547 (2019). https://doi.org/10.1007/s11442-019-1675-1

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  • DOI: https://doi.org/10.1007/s11442-019-1675-1

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