不同时间尺度农田蒸散影响因子的通径分析

doi:10.3969/j.issn.1000-6362.2017.04.001

中国农业气象 ›› 2017, Vol. 38 ›› Issue (04): 201-210.doi: 10.3969/j.issn.1000-6362.2017.04.001

不同时间尺度农田蒸散影响因子的通径分析

张雪松，闫艺兰，胡正华

1.南京信息工程大学气象灾害教育部重点实验室/江苏省农业气象重点实验室/气象灾害预报预警与评估协同创新中心，南京 210044；2.中国科学院大学，北京 100049；3.中国科学院地理科学与资源研究所生态系统网络观测与建模重点实验室，北京 100101

收稿日期:2016-08-19 出版日期:2017-04-20 发布日期:2017-04-18
作者简介:张雪松（1975-），博士，讲师，主要研究方向为应用气象。E-mail：lntlzxs@163.com
基金资助:
公益性行业（气象）科研专项（GYHY201506001；GYHY201306046）；气象灾害教育部重点实验室（南京信息工程大学）开放课题（KLME1415）；江苏省农业气象重点实验室项目（KYQ1404）

Using Path Analysis to Identify Impacting Factors of Evapotranspiration at Different Time Scales in Farmland

ZHANG Xue-song, YAN Yi-lan, HU Zheng-hua

1. Key Laboratory of Meteorological Disaster of Ministry of Education/Jiangsu Key Laboratory of Agricultural Meteorology/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China; 2.University of Chinese Academy of Science, Beijing 100049; 3.Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101

Received:2016-08-19 Online:2017-04-20 Published:2017-04-18

摘要/Abstract

摘要：

基于2011-2015年冬小麦农田实测大型称重式蒸渗仪数据及农业气象观测数据，分析不同时间尺度农田蒸散量的分布特征，并利用通径分析方法对各时间尺度农田蒸散的影响因子进行辨识。结果表明：（1）冬小麦开花-乳熟期典型晴天小时尺度蒸散呈单峰变化，最大值为0.9～1.1mm·h-1，日累计蒸散量7.0～9.1mm·d-1；冬小麦全生育期多年平均蒸散总量为385.4mm，日平均蒸散量为2.6mm·d-1，最大日蒸散量11.0mm·d-1，变化趋势为前期较低、后期较高；在生育期尺度，播种-返青期的蒸散速率较小，多年平均值为1.1mm·d-1，返青后，农田蒸散速率加快，多年平均值为4.2mm·d-1。（2）不同时间尺度蒸散变化的影响因子主要包括净辐射（Rn）、饱和水汽压差（VPD）、0cm地温（Tg0）、20cm土壤水分（SW20）。在小时尺度，VPD对典型晴天蒸散变化的直接作用最大，其次为Rn，Tg0通过Rn路径对EThourly变化产生间接影响，对蒸散的综合决定能力排序依次为VPD＞Tg0＞Rn；在日尺度，Rn作为最关键的影响因子，对蒸散的直接影响最大，VPD对蒸散的间接影响最大，VPD、Tg0主要通过Rn路径间接影响蒸散，SW20再通过Tg0路径间接影响蒸散且为负效应，各因子决策系数排序依次为Rn＞VPD＞Tg0＞SW20；在生育期尺度，Tg0和Rn是驱动蒸散变化的最主要因子并起直接影响作用，决策系数表明Tg0对蒸散变化的促进作用比Rn明显。

关键词: 通径分析, 决策系数, 净辐射, 饱和水汽压差, 农田蒸散

Abstract:

Based on the data measured by large-scale weighing lysimeter and agricultural meteorological observation from 2011 to 2015, the distributing characteristics of evapotranspiration at different time scales in winter wheat farmland were analyzed, and the impacting factors were identified by path analysis. The results showed that the change of evapotranspiration displayed a downward-parabola pattern with a single peak at hourly scale, and the maximum evapotranspiration was from 0.9mm·h-1 to 1.1 mm·h-1 and the cumulative value throughout the day was from 7.0mm to 9.1mm on the typical sunny day during flowering-milky stage within 4 years. The mean annual evapotranspiration was 385.4mm, the mean diurnal evapotranspiration was 2.6mm·d-1 and the maximum value was 11.0mm·d-1 during the whole winter wheat growing period. The daily scale variation of evapotranspiration at early growing stage was greater than that at later stage. During the growing season, the evapotranspiration rate was lower during the sowing to turning-green period with an average of 1.1mm·d-1 than that of 4.2mm·d-1 after turning-green period. (2) The impacting factors of evapotranspiration at different time scales mainly included net radiation (Rn), saturated vapor pressure deficit (VPD), ground temperature (Tg0) and soil water content at 20cm (SW20). At hourly scale, VPD had the largest direct effect on evapotranspiration variation on the typical sunny day. Rn and Tg0 affected evapotranspiration indirectly via Rn. The ranking of the decision coefficient of every factor was VPD＞Tg0＞Rn. At daily scale, Rn, as the most critical factor, had the largest direct impact on evapotranspiration, while VPD had the largest indirect influence. VPD and Tg0 affected evapotranspiration indirectly via Rn and the indirect negative influence of SW20 was imposed by Tg0 path. The ranking of the decision coefficient of impacting factors was Rn＞VPD＞Tg0＞SW20.At the whole growing season scale, Tg0 and Rn were the only two most important factors with direct influence and could drive evapotranspiration change. The decision coefficient indicated that Tg0 could significantly increase the variation of evapotranspiration more than Rn.

Key words: Path analysis, Decision coefficient, Net radiation, Vapor pressure deficit, Crop evapotranspiration

张雪松，闫艺兰，胡正华. 不同时间尺度农田蒸散影响因子的通径分析[J]. 中国农业气象, 2017, 38(04): 201-210.

ZHANG Xue-song, YAN Yi-lan, HU Zheng-hua. Using Path Analysis to Identify Impacting Factors of Evapotranspiration at Different Time Scales in Farmland[J]. Chinese Journal of Agrometeorology, 2017, 38(04): 201-210.

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不同时间尺度农田蒸散影响因子的通径分析

Using Path Analysis to Identify Impacting Factors of Evapotranspiration at Different Time Scales in Farmland

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