植物生态学报 ›› 2022, Vol. 46 ›› Issue (3): 300-310.DOI: 10.17521/cjpe.2021.0292
所属专题: 生态学研究的方法和技术; 生态系统碳水能量通量
黄樱, 陈挚, 石喆, 熊博文, 鄢春华*(), 邱国玉*()
收稿日期:
2021-08-12
接受日期:
2021-10-30
出版日期:
2022-03-20
发布日期:
2022-01-05
通讯作者:
鄢春华,邱国玉
作者简介:
Qiu GY, qiugy@pkusz.edu.cn)基金资助:
HUANG Ying, CHEN Zhi, SHI Zhe, XIONG Bo-Wen, YAN Chun-Hua*(), QIU Guo-Yu*()
Received:
2021-08-12
Accepted:
2021-10-30
Online:
2022-03-20
Published:
2022-01-05
Contact:
YAN Chun-Hua,QIU Guo-Yu
Supported by:
摘要:
蒸散发广义互补原理是实测数据稀少条件下估算蒸散发的重要方法, 其中准确估算参数αe是应用该方法的关键。该研究利用中国不同气候和生态类型的8个通量站数据, 首先基于实测数据校准得到αe年值及月值, 探究αe的时空变异性并对比使用不同时间尺度的αe对广义互补原理模型计算精度的影响。考虑到实际情况下蒸散发实测数据缺乏而无法校准得到αe, 进一步探究两个基于干旱系数(AI)的αe年值统计模型(下称Liu法和Brutsaert法)在站点尺度的适用性, 明确αe是否可以利用AI确定, 最后探讨各计算方法的误差来源。主要结论如下: 1)季节变化影响αe, 不同通量站αe月值变化规律有所差异; 在空间变化上, 湿润站点αe年值总体大于干旱站点。Liu法和Brutsaert法计算的αe接近年校准值。2)在应用广义互补原理模型时, 使用校准αe年值能取得较好的模拟精度, 使用各月份αe时精度进一步提升。两种基于AI的免校准方法取得较好的模拟效果, 当缺少实测数据而无法校准αe时, 基于AI计算αe具有较大的潜力。3)使用校准αe年值时广义互补原理模型能模拟出蒸散发的年内变化趋势, 但在部分月份估算值出现偏差。Liu法和Brutsaert法计算的蒸散发在干旱站点的夏季月份呈现低估现象, 原因可能在于高估了降雨集中的夏季月份的AI。结果也进一步验证了广义互补原理在估算广泛不同的自然环境下的蒸散发的潜力。
黄樱, 陈挚, 石喆, 熊博文, 鄢春华, 邱国玉. 蒸散发广义互补原理中关键参数αe的时空变化特征及计算方法分析. 植物生态学报, 2022, 46(3): 300-310. DOI: 10.17521/cjpe.2021.0292
HUANG Ying, CHEN Zhi, SHI Zhe, XIONG Bo-Wen, YAN Chun-Hua, QIU Guo-Yu. Temporal and spatial variation characteristics and different calculation methods for the key parameter αe in the generalized complementary principle of evapotranspiration. Chinese Journal of Plant Ecology, 2022, 46(3): 300-310. DOI: 10.17521/cjpe.2021.0292
生态系统类型 Ecosystem type | 通量站 Flux station | 下垫面类型 Underlying surface type | 气候类型 Climate type | 海拔 Altitude (m) | 经纬度 Longitude and latitude | 干旱系数 Aridity index | 研究年限 Research time |
---|---|---|---|---|---|---|---|
森林 Forest | 鼎湖山 Dinghushan | 常绿阔叶林 Evergreen broadleaf forest | 亚热带季风湿润气候 Subtropical monsoon humid climate | 300 | 112.32° E 23.10° N | 0.85 | 2003-01-2010-12 |
西双版纳 Xishuangbanna | 热带雨林 Tropical rainforest | 热带季风气候 Tropical monsoon climate | 756 | 101.15° E 21.55° N | 0.73 | 2003-01-2010-12 | |
千烟洲 Qianyanzhou | 人工林 Artificial forest | 亚热带季风气候 Subtropical monsoon climate | 100 | 115.03° E 26.44° N | 1.02 | 2003-01- 2010-12 | |
长白山 Changbaishan | 针阔混交林 Mixed needleleaf and broadleaf forest | 温带大陆性气候 Temperate continental climate | 738 | 128.05° E 42.24° N | 1.92 | 2003-01-2010-12 | |
九寨沟 Jiuzhaigou | 针叶林 Coniferous forest | 高原温带季风气候 Plateau temperate monsoon climate | 2 478 | 103.87° E 33.15° N | 1.00 | 2013-08-2015-12 | |
草地 Grassland | 内蒙古 Nei Mongol | 温带典型草原 Typical temperate grassland | 温带半干旱草原气候 Temperate semi-arid steppe climate | 1 200 | 116.24° E 43.19° N | 3.96 | 2004-01-2010-12 |
海北 Haibei | 高寒草甸 Alpine meadow | 高原大陆性气候 Plateau continental climate | 3 190 | 101.19° E 37.39° N | 1.58 | 2003-01-2010-12 | |
农田 Farmland | 禹城 Yucheng | 旱作农田 Dry farmland | 温带季风半湿润气候 Temperate monsoon semi-humid climate | 28 | 116.34° E 36.49° N | 2.28 | 2003-01-2010-12 |
表1 中国通量站基本信息表
Table 1 Basic information table of the China flux sites
生态系统类型 Ecosystem type | 通量站 Flux station | 下垫面类型 Underlying surface type | 气候类型 Climate type | 海拔 Altitude (m) | 经纬度 Longitude and latitude | 干旱系数 Aridity index | 研究年限 Research time |
---|---|---|---|---|---|---|---|
森林 Forest | 鼎湖山 Dinghushan | 常绿阔叶林 Evergreen broadleaf forest | 亚热带季风湿润气候 Subtropical monsoon humid climate | 300 | 112.32° E 23.10° N | 0.85 | 2003-01-2010-12 |
西双版纳 Xishuangbanna | 热带雨林 Tropical rainforest | 热带季风气候 Tropical monsoon climate | 756 | 101.15° E 21.55° N | 0.73 | 2003-01-2010-12 | |
千烟洲 Qianyanzhou | 人工林 Artificial forest | 亚热带季风气候 Subtropical monsoon climate | 100 | 115.03° E 26.44° N | 1.02 | 2003-01- 2010-12 | |
长白山 Changbaishan | 针阔混交林 Mixed needleleaf and broadleaf forest | 温带大陆性气候 Temperate continental climate | 738 | 128.05° E 42.24° N | 1.92 | 2003-01-2010-12 | |
九寨沟 Jiuzhaigou | 针叶林 Coniferous forest | 高原温带季风气候 Plateau temperate monsoon climate | 2 478 | 103.87° E 33.15° N | 1.00 | 2013-08-2015-12 | |
草地 Grassland | 内蒙古 Nei Mongol | 温带典型草原 Typical temperate grassland | 温带半干旱草原气候 Temperate semi-arid steppe climate | 1 200 | 116.24° E 43.19° N | 3.96 | 2004-01-2010-12 |
海北 Haibei | 高寒草甸 Alpine meadow | 高原大陆性气候 Plateau continental climate | 3 190 | 101.19° E 37.39° N | 1.58 | 2003-01-2010-12 | |
农田 Farmland | 禹城 Yucheng | 旱作农田 Dry farmland | 温带季风半湿润气候 Temperate monsoon semi-humid climate | 28 | 116.34° E 36.49° N | 2.28 | 2003-01-2010-12 |
方法 Method | 月份 Month | 鼎湖山 Dinghushan | 西双版纳 Xishuangbanna | 千烟洲 Qianyanzhou | 长白山 Changbaishan | 九寨沟 Jiuzhaigou | 海北 Haibei | 内蒙古 Nei Mongol | 禹城 Yucheng | |
---|---|---|---|---|---|---|---|---|---|---|
校准法(年值) Calibration method (annual αe) | 1.03 | 1.16 | 1.07 | 1.11 | 1.11 | 1.04 | 0.92 | 1.42 | ||
Liu法 Liu method | 1.18 | 1.20 | 1.15 | 1.05 | 1.15 | 1.08 | 0.95 | 1.02 | ||
Brutsaert法 Brutsaert method | 1.07 | 1.10 | 1.03 | 0.89 | 1.04 | 0.94 | 0.71 | 0.85 | ||
校准法(月值) Calibration method (monthly αe) | 1 | 1.02 | 1.24 | 1.06 | - | 1.10 | 0.93 | - | - | |
2 | 0.96 | 1.29 | 1.07 | - | 1.06 | 0.86 | - | - | ||
3 | 0.96 | 1.16 | 1.06 | - | 1.00 | 0.85 | - | - | ||
4 | 1.04 | 1.06 | 1.08 | - | 1.00 | 0.92 | - | - | ||
5 | 1.04 | 1.06 | 1.09 | - | 1.15 | 0.92 | - | - | ||
6 | 1.01 | 1.17 | 1.12 | - | 1.15 | 1.04 | - | - | ||
7 | 0.98 | 1.19 | 1.09 | - | 1.11 | 1.16 | - | - | ||
8 | 1.00 | 1.19 | 1.03 | - | 1.10 | 1.17 | - | - | ||
9 | 1.04 | 1.13 | 1.02 | - | 1.20 | 1.08 | - | - | ||
10 | 1.11 | 1.14 | 1.05 | - | 1.19 | 0.90 | - | - | ||
11 | 1.18 | 1.16 | 1.07 | - | 1.20 | 0.89 | - | - | ||
12 | 1.18 | 1.18 | 1.08 | - | 1.20 | 0.99 | - | - |
表2 不同计算方法αe值对比
Table 2 Comparison of αe value of different methods
方法 Method | 月份 Month | 鼎湖山 Dinghushan | 西双版纳 Xishuangbanna | 千烟洲 Qianyanzhou | 长白山 Changbaishan | 九寨沟 Jiuzhaigou | 海北 Haibei | 内蒙古 Nei Mongol | 禹城 Yucheng | |
---|---|---|---|---|---|---|---|---|---|---|
校准法(年值) Calibration method (annual αe) | 1.03 | 1.16 | 1.07 | 1.11 | 1.11 | 1.04 | 0.92 | 1.42 | ||
Liu法 Liu method | 1.18 | 1.20 | 1.15 | 1.05 | 1.15 | 1.08 | 0.95 | 1.02 | ||
Brutsaert法 Brutsaert method | 1.07 | 1.10 | 1.03 | 0.89 | 1.04 | 0.94 | 0.71 | 0.85 | ||
校准法(月值) Calibration method (monthly αe) | 1 | 1.02 | 1.24 | 1.06 | - | 1.10 | 0.93 | - | - | |
2 | 0.96 | 1.29 | 1.07 | - | 1.06 | 0.86 | - | - | ||
3 | 0.96 | 1.16 | 1.06 | - | 1.00 | 0.85 | - | - | ||
4 | 1.04 | 1.06 | 1.08 | - | 1.00 | 0.92 | - | - | ||
5 | 1.04 | 1.06 | 1.09 | - | 1.15 | 0.92 | - | - | ||
6 | 1.01 | 1.17 | 1.12 | - | 1.15 | 1.04 | - | - | ||
7 | 0.98 | 1.19 | 1.09 | - | 1.11 | 1.16 | - | - | ||
8 | 1.00 | 1.19 | 1.03 | - | 1.10 | 1.17 | - | - | ||
9 | 1.04 | 1.13 | 1.02 | - | 1.20 | 1.08 | - | - | ||
10 | 1.11 | 1.14 | 1.05 | - | 1.19 | 0.90 | - | - | ||
11 | 1.18 | 1.16 | 1.07 | - | 1.20 | 0.89 | - | - | ||
12 | 1.18 | 1.18 | 1.08 | - | 1.20 | 0.99 | - | - |
生态系统类型 Ecosystem type | 通量站 Flux station | 校准法(年值) Calibration method (annual value) | 校准法(月值) Calibration method (monthly value) | Brutsaert法 Brutsaert method (Brutsaert et al., | Liu法 Liu method (Liu et al., | ||||
---|---|---|---|---|---|---|---|---|---|
R2 | RMSE | R2 | RMSE | R2 | RMSE | R2 | RMSE | ||
森林 Forest | 鼎湖山 Dinghushan | 0.81 | 0.67 | 0.81 | 0.64 | 0.81 | 0.68 | 0.81 | 0.82 |
西双版纳 Xishuangbanna | 0.73 | 0.51 | 0.75 | 0.49 | 0.73 | 0.55 | 0.73 | 0.54 | |
千烟洲 Qianyanzhou | 0.92 | 0.55 | 0.92 | 0.54 | 0.91 | 0.60 | 0.91 | 0.64 | |
长白山 Changbaishan | 0.80 | 0.78 | - | - | 0.81 | 1.02 | 0.81 | 0.79 | |
九寨沟 Jiuzhaigou | 0.85 | 0.59 | 0.87 | 0.53 | 0.85 | 0.63 | 0.85 | 0.61 | |
草地 Grassland | 海北 Haibei | 0.92 | 0.45 | 0.96 | 0.34 | 0.92 | 0.54 | 0.92 | 0.46 |
内蒙古 Nei Mongol | 0.67 | 0.75 | - | - | 0.64 | 0.93 | 0.63 | 0.75 | |
农田 Farmland | 禹城 Yucheng | 0.78 | 0.97 | - | - | 0.76 | 1.82 | 0.77 | 1.45 |
表3 不同计算方法的均方根误差(RMSE)和决定系数(R2)
Table 3 Root mean square error (RMSE) and determinate coefficient (R2) of different calculation methods
生态系统类型 Ecosystem type | 通量站 Flux station | 校准法(年值) Calibration method (annual value) | 校准法(月值) Calibration method (monthly value) | Brutsaert法 Brutsaert method (Brutsaert et al., | Liu法 Liu method (Liu et al., | ||||
---|---|---|---|---|---|---|---|---|---|
R2 | RMSE | R2 | RMSE | R2 | RMSE | R2 | RMSE | ||
森林 Forest | 鼎湖山 Dinghushan | 0.81 | 0.67 | 0.81 | 0.64 | 0.81 | 0.68 | 0.81 | 0.82 |
西双版纳 Xishuangbanna | 0.73 | 0.51 | 0.75 | 0.49 | 0.73 | 0.55 | 0.73 | 0.54 | |
千烟洲 Qianyanzhou | 0.92 | 0.55 | 0.92 | 0.54 | 0.91 | 0.60 | 0.91 | 0.64 | |
长白山 Changbaishan | 0.80 | 0.78 | - | - | 0.81 | 1.02 | 0.81 | 0.79 | |
九寨沟 Jiuzhaigou | 0.85 | 0.59 | 0.87 | 0.53 | 0.85 | 0.63 | 0.85 | 0.61 | |
草地 Grassland | 海北 Haibei | 0.92 | 0.45 | 0.96 | 0.34 | 0.92 | 0.54 | 0.92 | 0.46 |
内蒙古 Nei Mongol | 0.67 | 0.75 | - | - | 0.64 | 0.93 | 0.63 | 0.75 | |
农田 Farmland | 禹城 Yucheng | 0.78 | 0.97 | - | - | 0.76 | 1.82 | 0.77 | 1.45 |
图1 互补原理日蒸散发估算值与观测值的比较结果。Liu法见文献Liu等(2016), Brutsaert法见文献Brutsaert等(2020)。RMSE, 均方根误差。
Fig. 1 Comparison of estimated daily evapotranspiration (E) calculated by the nonlinear complementary principle and observed E. Liu method refers to Liu et al. (2016), Brutsaert method refers to Brutsaert et al. (2020). RMSE, root mean square error.
图2 不同计算方法的蒸散发估算值和观测值之间的均方根误差(RMSE)和决定系数(R2)箱线图。Liu法见文献Liu等(2016), Brutsaert法见文献Brutsaert等(2020)。
Fig. 2 Root mean square error (RMSE) and determinate coefficient (R2) boxplot between the estimated evapotranspiration (E) with different calculation methods and observed E at all stations. Liu method refers to Liu et al. (2016), Brutsaert method refers to Brutsaert et al. (2020).
图3 由校准法确定αe年值, 广义互补原理估算的蒸散发月值与月蒸散发观测值结果对比。
Fig. 3 Comparison of monthly estimated evapotranspiration (E) calculated by calibration annual αe and observed E.
图4 由校准法确定各月αe, 广义互补原理估算的蒸散发月值与月蒸散发观测值结果对比。
Fig. 4 Comparison of monthly estimated evapotranspiration (E) calculated by calibration monthly αe and observed E.
图5 由Liu法确定参数αe, 广义互补原理估算的蒸散发月值与月蒸散发观测值结果对比。Liu法见文献Liu等(2016)。
Fig. 5 Comparison of monthly estimated evapotranspiration (E) calculated by Liu method and observed E. Liu method refers to Liu et al. (2016).
图6 由Brutsaert法确定参数αe, 广义互补原理估算的蒸散发月值与月蒸散发观测值结果对比。Brutsaert法见文献Brutsaert等(2020)。
Fig. 6 Comparison of monthly estimated evapotranspiration (E) calculated by Brutsaert method and observed E. Brutsaert method refers to Brutsaert et al. (2020)
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