植物生态学报 ›› 2023, Vol. 47 ›› Issue (7): 912-921.DOI: 10.17521/cjpe.2022.0015
所属专题: 生态遥感及应用; 生态系统碳水能量通量
收稿日期:
2022-01-11
接受日期:
2022-09-28
出版日期:
2023-07-20
发布日期:
2023-07-21
通讯作者:
*陈奇(基金资助:
WANG Xiu-Ying, CHEN Qi(), DU Hua-Li, ZHANG Rui, MA Hong-Lu
Received:
2022-01-11
Accepted:
2022-09-28
Online:
2023-07-20
Published:
2023-07-21
Contact:
*CHEN Qi(Supported by:
摘要:
以青藏高原典型高寒沼泽湿地为观测研究站, 以实际蒸散发为研究对象, 结合气象因子(净辐射、气温、土壤热通量、风速、相对湿度、土壤含水率), 建立基于多元线性回归(MLR)、决策树(CART)、随机森林(RF)、支持向量回归(SVR)、多层感知机(MLP) 7种组合5类算法的预测模型, 找出对于蒸散发具有较高精度的插补方法, 实现实际蒸散发数据集的构建。结果表明: 1)研究区蒸散发与净辐射相关性最大, 而土壤热通量是影响蒸散发过程的关键因子; 2) 7种组合的5类机器学习算法模型的决定系数变化范围为0.58-0.83, 均方根误差变化范围为0.038-0.089 mm·30 min-1; 2)随机森林回归模型决定系数最高, 模型稳定性最佳, 插补效果最优; 3)插补完整的蒸散发与净辐射、土壤热通量、气温日尺度变化趋势相同, 与风速、相对湿度变化趋势相反。日蒸散发主要集中在生长季, 日最大值为8.77 mm·d-1, 出现在7月9日, 日最小值为0.21 mm·d-1, 出现在1月30日。
王秀英, 陈奇, 杜华礼, 张睿, 马红璐. 基于机器学习的青藏高原高寒沼泽湿地蒸散发插补研究. 植物生态学报, 2023, 47(7): 912-921. DOI: 10.17521/cjpe.2022.0015
WANG Xiu-Ying, CHEN Qi, DU Hua-Li, ZHANG Rui, MA Hong-Lu. Evapotranspiration interpolation in alpine marshes wetland on the Qingzang Plateau based on machine learning. Chinese Journal of Plant Ecology, 2023, 47(7): 912-921. DOI: 10.17521/cjpe.2022.0015
月份 Month | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |
有效记录 Active record | 1 206 | 1 206 | 1 382 | 1 309 | 1 110 | 1 057 | 1 152 | 1 282 | 1 075 | 936 |
缺失数据 Missing data | 282 | 138 | 106 | 131 | 378 | 383 | 336 | 206 | 365 | 240 |
缺失率 Absence rate (%) | 19 | 10 | 7 | 9 | 25 | 27 | 23 | 14 | 25 | 20 |
表1 隆宝高寒沼泽湿地蒸散发通量观测数据缺失统计表
Table 1 Statistical table showing the absence of observed evapotranspiration fluxes in Longbao alpine marshes wetland
月份 Month | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | |
有效记录 Active record | 1 206 | 1 206 | 1 382 | 1 309 | 1 110 | 1 057 | 1 152 | 1 282 | 1 075 | 936 |
缺失数据 Missing data | 282 | 138 | 106 | 131 | 378 | 383 | 336 | 206 | 365 | 240 |
缺失率 Absence rate (%) | 19 | 10 | 7 | 9 | 25 | 27 | 23 | 14 | 25 | 20 |
气象因子 Meteorological factor | 月份 Month | 平均 Mean | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ||
净辐射 Net radiation | 0.80 | 0.83 | 0.69 | 0.72 | 0.77 | 0.76 | 0.79 | 0.83 | 0.81 | 0.69 | 0.769 |
土壤热通量 Soil heat flux | 0.74 | 0.43 | 0.54 | 0.86 | 0.84 | 0.87 | 0.84 | 0.84 | 0.84 | 0.85 | 0.765 |
相对湿度 Relative humidity | -0.62 | -0.68 | -0.69 | -0.74 | -0.71 | -0.75 | -0.78 | -0.80 | -0.78 | -0.72 | -0.727 |
气温 Air temperature | 0.63 | 0.64 | 0.56 | 0.75 | 0.73 | 0.69 | 0.77 | 0.78 | 0.66 | 0.69 | 0.690 |
风速 Wind velocity | 0.74 | 0.74 | 0.71 | 0.61 | 0.59 | 0.43 | 0.39 | 0.29 | 0.46 | 0.63 | 0.559 |
土壤温度 Soil temperature (5 cm) | 0.29 | 0.07 | 0.35 | 0.60 | 0.52 | 0.53 | 0.55 | 0.46 | 0.41 | 0.48 | 0.426 |
土壤温度 Soil temperature (10 cm) | -0.12 | 0.12 | 0.13 | 0.04 | -0.07 | -0.01 | 0 | 0.21 | 0.13 | 0.15 | 0.058 |
土壤温度 Soil temperature (20 cm) | -0.37 | 0 | 0.11 | -0.21 | -0.22 | -0.13 | -0.34 | -0.20 | 0 | 0.03 | -0.133 |
土壤温度 Soil temperature (30 cm) | -0.32 | 0.10 | 0.12 | 0.13 | -0.08 | -0.03 | -0.10 | -0.04 | 0.09 | 0.12 | -0.001 |
土壤温度 Soil temperature (40 cm) | 0 | -0.06 | 0.14 | 0.10 | 0.08 | 0.10 | 0.15 | 0.08 | 0.12 | 0.18 | 0.089 |
土壤含水率 Soil moisture content (5 cm) | 0.26 | 0.08 | 0.11 | -0.08 | 0.30 | 0.22 | 0.04 | 0.36 | 0.40 | 0.33 | 0.202 |
土壤含水率 Soil moisture content (10 cm) | -0.24 | 0 | 0.04 | 0.07 | 0.04 | -0.08 | -0.23 | -0.03 | -0.10 | 0.11 | -0.042 |
土壤含水率 Soil moisture content (20 cm) | -0.24 | 0.10 | 0.07 | 0.12 | 0.05 | -0.01 | -0.14 | -0.08 | -0.11 | 0.10 | -0.014 |
土壤含水率 Soil moisture content (30 cm) | -0.02 | -0.10 | 0.09 | 0.15 | -0.02 | 0.03 | -0.15 | -0.02 | -0.09 | 0.11 | -0.002 |
土壤含水率 Soil moisture content (40 cm) | -0.03 | 0.04 | 0.10 | 0.15 | -0.02 | 0 | 0 | 0 | -0.05 | 0.15 | 0.034 |
表2 隆宝高寒沼泽湿地蒸散发与气象因子间的相关性
Table 2 Correlation between evapotranspiration and meteorological factors in Longbao alpine marshes wetland
气象因子 Meteorological factor | 月份 Month | 平均 Mean | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ||
净辐射 Net radiation | 0.80 | 0.83 | 0.69 | 0.72 | 0.77 | 0.76 | 0.79 | 0.83 | 0.81 | 0.69 | 0.769 |
土壤热通量 Soil heat flux | 0.74 | 0.43 | 0.54 | 0.86 | 0.84 | 0.87 | 0.84 | 0.84 | 0.84 | 0.85 | 0.765 |
相对湿度 Relative humidity | -0.62 | -0.68 | -0.69 | -0.74 | -0.71 | -0.75 | -0.78 | -0.80 | -0.78 | -0.72 | -0.727 |
气温 Air temperature | 0.63 | 0.64 | 0.56 | 0.75 | 0.73 | 0.69 | 0.77 | 0.78 | 0.66 | 0.69 | 0.690 |
风速 Wind velocity | 0.74 | 0.74 | 0.71 | 0.61 | 0.59 | 0.43 | 0.39 | 0.29 | 0.46 | 0.63 | 0.559 |
土壤温度 Soil temperature (5 cm) | 0.29 | 0.07 | 0.35 | 0.60 | 0.52 | 0.53 | 0.55 | 0.46 | 0.41 | 0.48 | 0.426 |
土壤温度 Soil temperature (10 cm) | -0.12 | 0.12 | 0.13 | 0.04 | -0.07 | -0.01 | 0 | 0.21 | 0.13 | 0.15 | 0.058 |
土壤温度 Soil temperature (20 cm) | -0.37 | 0 | 0.11 | -0.21 | -0.22 | -0.13 | -0.34 | -0.20 | 0 | 0.03 | -0.133 |
土壤温度 Soil temperature (30 cm) | -0.32 | 0.10 | 0.12 | 0.13 | -0.08 | -0.03 | -0.10 | -0.04 | 0.09 | 0.12 | -0.001 |
土壤温度 Soil temperature (40 cm) | 0 | -0.06 | 0.14 | 0.10 | 0.08 | 0.10 | 0.15 | 0.08 | 0.12 | 0.18 | 0.089 |
土壤含水率 Soil moisture content (5 cm) | 0.26 | 0.08 | 0.11 | -0.08 | 0.30 | 0.22 | 0.04 | 0.36 | 0.40 | 0.33 | 0.202 |
土壤含水率 Soil moisture content (10 cm) | -0.24 | 0 | 0.04 | 0.07 | 0.04 | -0.08 | -0.23 | -0.03 | -0.10 | 0.11 | -0.042 |
土壤含水率 Soil moisture content (20 cm) | -0.24 | 0.10 | 0.07 | 0.12 | 0.05 | -0.01 | -0.14 | -0.08 | -0.11 | 0.10 | -0.014 |
土壤含水率 Soil moisture content (30 cm) | -0.02 | -0.10 | 0.09 | 0.15 | -0.02 | 0.03 | -0.15 | -0.02 | -0.09 | 0.11 | -0.002 |
土壤含水率 Soil moisture content (40 cm) | -0.03 | 0.04 | 0.10 | 0.15 | -0.02 | 0 | 0 | 0 | -0.05 | 0.15 | 0.034 |
模型特征组合 Model feature combination | 输入特征 Input characteristic | 特征个数 Feature number |
---|---|---|
组合1 Combination 1 | Rn、Sg、RH、T、WS | 5 |
组合2 Combination 2 | Rn、Sg、RH、T、WS、ST_5 cm | 6 |
组合3 Combination 3 | Rn、Sg、RH、T、WS、SV_5 cm | 6 |
组合4 Combination 4 | Rn、Sg、RH、T、WS、ST_5 cm、SV_5 cm | 7 |
组合5 Combination 5 | Rn、Sg、RH、T、WS、ST_5 cm、ST_10 cm、ST_20 cm、ST_30 cm、ST_40 cm | 10 |
组合6 Combination 6 | Rn、Sg、RH、T、WS、SV_5 cm、SV_10 cm、SV_20 cm、SV_30 cm、SV_40 cm | 10 |
组合7 Combination 7 | Rn、Sg、RH、T、WS、ST_5 cm-ST_40 cm、SV_5 cm-SV_40 cm | 15 |
表3 隆宝高寒沼泽湿地不同气象因子的模型参数组合
Table 3 Combination of model parameters for different meteorological factors in Longbao alpine marshes wetland
模型特征组合 Model feature combination | 输入特征 Input characteristic | 特征个数 Feature number |
---|---|---|
组合1 Combination 1 | Rn、Sg、RH、T、WS | 5 |
组合2 Combination 2 | Rn、Sg、RH、T、WS、ST_5 cm | 6 |
组合3 Combination 3 | Rn、Sg、RH、T、WS、SV_5 cm | 6 |
组合4 Combination 4 | Rn、Sg、RH、T、WS、ST_5 cm、SV_5 cm | 7 |
组合5 Combination 5 | Rn、Sg、RH、T、WS、ST_5 cm、ST_10 cm、ST_20 cm、ST_30 cm、ST_40 cm | 10 |
组合6 Combination 6 | Rn、Sg、RH、T、WS、SV_5 cm、SV_10 cm、SV_20 cm、SV_30 cm、SV_40 cm | 10 |
组合7 Combination 7 | Rn、Sg、RH、T、WS、ST_5 cm-ST_40 cm、SV_5 cm-SV_40 cm | 15 |
模型特征组合 Model feature combination | MLR | CART | RF | SVR | MLP | R2平均 Mean of R2 | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
R2 | RMSE | R2 | RMSE | R2 | RMSE | R2 | RMSE | R2 | RMSE | ||
组合1 Combination 1 | 0.81 | 0.041 | 0.72 | 0.051 | 0.85 | 0.039 | 0.77 | 0.056 | 0.80 | 0.053 | 0.79 |
组合2 Combination 2 | 0.80 | 0.043 | 0.72 | 0.052 | 0.82 | 0.041 | 0.68 | 0.063 | 0.69 | 0.062 | 0.74 |
组合3 Combination 3 | 0.82 | 0.041 | 0.72 | 0.052 | 0.83 | 0.040 | 0.72 | 0.073 | 0.58 | 0.063 | 0.73 |
组合4 Combination 4 | 0.80 | 0.042 | 0.72 | 0.052 | 0.83 | 0.041 | 0.69 | 0.079 | 0.66 | 0.066 | 0.74 |
组合5 Combination 5 | 0.77 | 0.063 | 0.68 | 0.057 | 0.82 | 0.042 | 0.78 | 0.072 | 0.55 | 0.129 | 0.72 |
组合6 Combination 6 | 0.71 | 0.045 | 0.71 | 0.043 | 0.82 | 0.031 | 0.69 | 0.093 | 0.36 | 0.136 | 0.66 |
组合7 Combination 7 | 0.57 | 0.223 | 0.71 | 0.044 | 0.83 | 0.033 | 0.35 | 0.118 | 0.41 | 0.117 | 0.57 |
平均 Mean | 0.75 | 0.071 | 0.71 | 0.050 | 0.83 | 0.038 | 0.67 | 0.079 | 0.58 | 0.089 | 0.71 |
表4 隆宝高寒沼泽湿地不同气象因子组合下的模型精度
Table 4 Model accuracy under the combination of different meteorological factors in Longbao alpine marshes wetland
模型特征组合 Model feature combination | MLR | CART | RF | SVR | MLP | R2平均 Mean of R2 | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
R2 | RMSE | R2 | RMSE | R2 | RMSE | R2 | RMSE | R2 | RMSE | ||
组合1 Combination 1 | 0.81 | 0.041 | 0.72 | 0.051 | 0.85 | 0.039 | 0.77 | 0.056 | 0.80 | 0.053 | 0.79 |
组合2 Combination 2 | 0.80 | 0.043 | 0.72 | 0.052 | 0.82 | 0.041 | 0.68 | 0.063 | 0.69 | 0.062 | 0.74 |
组合3 Combination 3 | 0.82 | 0.041 | 0.72 | 0.052 | 0.83 | 0.040 | 0.72 | 0.073 | 0.58 | 0.063 | 0.73 |
组合4 Combination 4 | 0.80 | 0.042 | 0.72 | 0.052 | 0.83 | 0.041 | 0.69 | 0.079 | 0.66 | 0.066 | 0.74 |
组合5 Combination 5 | 0.77 | 0.063 | 0.68 | 0.057 | 0.82 | 0.042 | 0.78 | 0.072 | 0.55 | 0.129 | 0.72 |
组合6 Combination 6 | 0.71 | 0.045 | 0.71 | 0.043 | 0.82 | 0.031 | 0.69 | 0.093 | 0.36 | 0.136 | 0.66 |
组合7 Combination 7 | 0.57 | 0.223 | 0.71 | 0.044 | 0.83 | 0.033 | 0.35 | 0.118 | 0.41 | 0.117 | 0.57 |
平均 Mean | 0.75 | 0.071 | 0.71 | 0.050 | 0.83 | 0.038 | 0.67 | 0.079 | 0.58 | 0.089 | 0.71 |
月份 Month | 总计 Sum | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ||
插补前 Before interpolation | 23.69 | 30.66 | 60.86 | 122.21 | 128.86 | 131.13 | 141.09 | 160.42 | 104.60 | 62.36 | 965.88 |
插补后 After interpolation | 24.57 | 31.21 | 62.48 | 127.17 | 145.49 | 157.33 | 162.69 | 168.41 | 119.45 | 70.97 | 1 069.77 |
表5 隆宝高寒沼泽湿地月蒸散发(mm)插补前后统计表
Table 5 Statistical tables of monthly evapotranspiration (mm) before and after interpolation in Longbao alpine marshes wetland
月份 Month | 总计 Sum | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | ||
插补前 Before interpolation | 23.69 | 30.66 | 60.86 | 122.21 | 128.86 | 131.13 | 141.09 | 160.42 | 104.60 | 62.36 | 965.88 |
插补后 After interpolation | 24.57 | 31.21 | 62.48 | 127.17 | 145.49 | 157.33 | 162.69 | 168.41 | 119.45 | 70.97 | 1 069.77 |
图6 隆宝高寒沼泽湿地插补完整蒸散发(ET)与气象因子日变化趋势图。
Fig. 6 Daily variation trend of evaportranspiration (ET) and meteorological factors in Longbao alpine marshes wetland.
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