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[黄土高原丘陵沟壑区刺槐液流的动态变化]

[Dynamic changes of Robinia pseudoacacia sap flow in hilly-gully region of Loess Plateau].

作者信息

Hu Wei, Du Feng, Xu Xue-Xuan, Zhang Liang-De

机构信息

Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, Shaanxi, China.

出版信息

Ying Yong Sheng Tai Xue Bao. 2010 Jun;21(6):1367-73.

PMID:20873607
Abstract

From April 14 to October 10, 2009, the dynamic changes of Robinia pseudoacacia sap flow in the hilly-gully region of Loess Plateau were measured with thermal dissipation probe. Meantime, the photosynthetic active radiation (PAR), air temperature, relative air humidity, water vapor pressure deficit (VPD), wind speed, and rainfall were monitored. The diurnal variation of the sap flow velocity (SFV) displayed a single-peak curve, but the pattern varied among different months. In April, the sap flow started to increase at about 12:00, and reached the peak at about 18:00. From May to August, the sap flow started to increase at 5:30-7:30, and reached the peak at about 15:00. In September and October, the sap flow started to increase at about 8:00, and reached the peak at 11:30-13:00. The monthly average SFV was the highest in August and the lowest in April, with the value being 0.002610 cm x s(-1) and 0.000549 cm x s(-1), respectively. During the monitoring period, the sap flow velocity was significantly correlated with PAR, air temperature, VPD, wind speed, and air relative humidity, and the correlation coefficients declined in the order of air temperature > VPD > PAR > relative humidity > wind speed. The sap flow velocity could be estimated by the linear equation with variables PAR and VPD, and the regression coefficients were highly significant.

摘要

2009年4月14日至10月10日,利用热消散探针测定了黄土高原丘陵沟壑区刺槐液流的动态变化。同时,监测了光合有效辐射(PAR)、气温、相对空气湿度、水汽压亏缺(VPD)、风速和降雨量。液流速度(SFV)的日变化呈单峰曲线,但不同月份的模式有所不同。4月,液流在约12:00开始增加,并在约18:00达到峰值。5月至8月,液流在5:30 - 7:30开始增加,并在约15:00达到峰值。9月和10月,液流在约8:00开始增加,并在11:30 - 13:00达到峰值。月平均SFV在8月最高,4月最低,其值分别为0.002610 cm·s⁻¹和0.000549 cm·s⁻¹。在监测期间,液流速度与PAR、气温、VPD、风速和空气相对湿度显著相关,相关系数按气温>VPD>PAR>相对湿度>风速的顺序递减。液流速度可以通过包含变量PAR和VPD的线性方程来估计,回归系数高度显著。

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