非参数化蒸散发估算方法在华北灌溉农田的适用性评价

张晓龙; 张玉翠; 石嘉丽; 王妍; 沈彦军

doi:10.12357/cjea.20210415

非参数化蒸散发估算方法在华北灌溉农田的适用性评价

doi: 10.12357/cjea.20210415

张晓龙^1,,
张玉翠¹,
石嘉丽^{1, 2},
王妍^{1, 2, 3},
沈彦军^{1, 2, ,}

1.
中国科学院遗传与发育生物学研究所农业资源研究中心/中国科学院农业水资源重点实验室/河北省节水农业重点实验室　石家庄　050022
2.
中国科学院大学　北京　100049
3.
河北师范大学资源与环境科学学院/河北省环境演变与生态建设实验室　石家庄　050024

基金项目: 国家自然科学基金项目(42001037, 41807157)及中国水利水电科学研究院流域水循环模拟与调控国家重点实验室开放研究基金(IWHR-SKL-KF202015)资助

详细信息

作者简介:
张晓龙, 主要从事生态水文学、蒸散量理论研究。E-mail: xlzhang@sjziam.ac.cn

通讯作者:
沈彦军, 主要从事流域生态水文模拟与水环境管理方向研究。E-mail: shenyanjun@sjziam.ac.cn

中图分类号: S162.1; K903
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出版历程
- 收稿日期: 2021-06-30
- 录用日期: 2021-08-05
- 网络出版日期: 2021-11-10
- 刊出日期: 2022-02-08

Applicability evaluation of the nonparametric approach for estimating evapotranspiration on irrigated farmland in the North China Plain

ZHANG Xiaolong^1
,,
ZHANG Yucui¹,
SHI Jiali^{1, 2},
WANG Yan^{1, 2, 3},
SHEN Yanjun^{1, 2
, ,}

1.
Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences / Key Laboratory of Agricultural Water Resources, Chinese Academy of Sciences / Hebei Laboratory of Agricultural Water-Saving, Shijiazhuang 050022, China
2.
University of Chinese Academy of Sciences, Beijing 100049, China
3.
College of Resources and Environmental Sciences, Hebei Normal University / Hebei Key Laboratory of Environmental Change and Ecological Construction, Shijiazhuang 050024, China

Funds: This research was supported by the National Natural Science Foundation of China (42001037, 41807157) and the Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin (China Institute of Water Resources and Hydropower Research) (IWHR-SKL-KF202015).

More Information

Corresponding author: E-mail: shenyanjun@sjziam.ac.cn

摘要

摘要: 蒸散发是水循环和地表能量平衡系统重要的组成部分之一, 是农业、水资源管理和气候变化研究中的基础信息。非参数化蒸散发估算方法避免了复杂的参数化过程, 降低了计算过程的不确定性, 具有广阔的应用前景。本文基于华北灌溉农田中国科学院栾城农业生态系统试验站、中国科学院禹城综合试验站和北京师范大学馆陶试验站3个通量站点的观测数据, 利用非参数化方法估算3个站点30 min和日尺度蒸散发, 利用能量残差闭合修正方法修正后的通量数据为验证参考值, 评价非参数化蒸散发估算方法在华北平原灌溉农田不同季节和不同时间尺度的适用性。结果显示: 1) 非参数化方法在华北灌溉农田不同作物类型、不同时间尺度具有可靠和稳健的表现, 估算结果可以较好地反映季节及日内变化特征, 但总体上低估蒸散发; 对比估算值与参考值, 在日尺度上, 平均偏差为−16.18~−12.88 W∙m⁻², 决定系数为0.80~0.83, 均方根误差为22.45~31.06 W∙m⁻², Nash-Sutcliffe效率系数为0.66~0.75; 在30 min尺度上, 平均偏差为−13.30~−7.68 W∙m⁻², 决定系数均为0.88, 均方根误差为39.22~42.15 W∙m⁻², Nash-Sutcliffe效率系数为0.86~0.87。2)非参数化估算方法在水分供应较充足或作物生长茂盛时较严重低估潜热通量, 而在较干燥或作物稀疏时轻度低估或不低估潜热通量。3)该方法对灌溉活动的响应考虑不足, 可能需要在模型结构上进一步改进以提高灌溉农田模拟精度。4)非参数化估算方法在华北灌溉农田中参数敏感性从高到低依次为地表空气温度、地表温度、地表净辐射和土壤热通量, 其中可忽略土壤热通量的影响。该研究不仅为非参数化蒸散发估算方法改进提供参考, 而且有助于加深对蒸散发理论的认识。
- 非参数化方法 /
- 蒸散发 /
- 华北灌溉农田 /
- 时间尺度 /
- 能量闭合修正方法
Abstract: Evapotranspiration (ET), generated by the evaporation of water from a natural surface into the atmosphere, is an important component of the water cycle and surface energy balance system, which is a fundamental information for agriculture, water resource management, and climate change research. In recent decades, the estimation of ET or latent energy (LE, which is the amount of heat required for ET) has remained one of the most challenging problems for researchers. A nonparametric approach for estimating ET may avoid the complex parameterization process and reduce the calculation uncertainties; therefore, it has broad application prospects. However, a more detailed applicability evaluation of the nonparametric approach in different regions or ecosystems is needed, as most of the current studies on the application of this approach focus on arid basins, with few applicability analysis reports focusing on irrigated farmland in sub-humid areas. In this study, the eddy covariance data modified by the energy residual closed correction method in three irrigated farmland stations (Luancheng Agroecosystem Experimental Station, Chinese Academy of Sciences; Yucheng Comprehensive Experimental Station, Chinese Academy of Sciences; and Guantao Experimental Station, Beijing Normal University) in the North China Plain were used as references, and the applicability of the nonparametric approach for estimating LE on irrigated farmland at different time scales (daily scale and 30 min scale) and seasons in the three stations was evaluated. The results showed that the nonparametric approach had reliable and robust performance for different crop types and time scales on irrigated farmland in the North China Plain. The estimated LE could ideally reflect seasonal and intraday variations, but these values were generally underestimated. Furthermore, the bias, coefficient of determination, root mean square error, and Nash-Sutcliffe coefficient at the daily (and 30 min) scale were −16.18 to −12.88 W∙m⁻² (−13.30 to −7.68 W∙m⁻²), 0.80 to 0.83 (0.88), 22.45 to 31.06 W∙m⁻² (39.22 to 42.15 W∙m⁻²), and 0.66 to 0.75 (0.86 to 0.87), respectively. The nonparametric approach significantly underestimated the latent heat flux when the water supply was sufficient or when crops were growing vigorously; moreover, this approach slightly or not underestimated the latent heat flux when the water supply was insufficient or when crops were sparse. In addition, the response of the nonparametric approach to irrigation activities was not considered sufficiently, and further improvement to the model structure may be required to improve the simulation accuracy of irrigated farmland. Finally, the parameter sensitivity of the nonparametric approach in irrigated farmland in the North China Plain, from high to low, was air temperature, surface temperature, net radiation, and soil heat flux, but the influence of soil heat flux can be ignored. Ultimately, this study not only provides a reference for the improvement of the nonparametric ET estimation approach but also helps further the understanding of ET fundamental theory.
- Nonparametric approach /
- Evapotranspiration /
- Irrigated farmland in the North China Plain /
- Time scale /
- Energy balance closure correction approaches

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图 1 华北平原作物类型空间分布及通量站点位置

作物类型分布经允许修改自文献[30]。The agricultural land-use types are modified from literature [30].

Figure 1. Spatial distribution of agricultural land-use types and location of flux stations in the North China Plain

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图 2 日尺度和30 min尺度上3个站点通量站点的能量平衡特征

LE、H、R_n和G_s分布为潜热通量、感热通量、净辐射和土壤热通量; LE+H表示热通量之和; R_n−G_s表示可利用能量。LE, H, R_n and G_s are latent heat flux, sensible heat flux, net radiation and soil heat flux, respectively. LE+H represents the sum of heat fluxes; R_n−G_s represents the available energy.

Figure 2. Energy balance characteristics of flux stations at daily scale and 30 min scale in the three stations

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图 3 日尺度上3个站点的潜热通量(LE)年内变化过程及估算结果对比

DOY为年积日。LE_ER和LE_NP分别代表利用能量残差法修正后的潜热通量和NP估算得到的潜热通量。箱体图右侧数据从上到下依次为3个站点的LE_ER和LE_NP的平均值和中位数。DOY is days of year. LE_ER and LE_NP represent the latent heat flux corrected by energy residual method and estimated by the nonparametric approach, respectively. The data on the right side of the box plot from top to bottom are the mean and median of LE_ER and LE_NP in the three stations, respectively.

Figure 3. Comparison of latent heat flux (LE) between estimation and observation at daily scale in the three stations

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图 4 30 min尺度上3个站点的潜热通量日内变化过程及估算结果对比(9月1—15日)

DOY为年积日。Bias、RE、R²、RMSE和NSE分别为平均偏差、相对误差、决定系数、均方根误差和Nash-Sutcliffe效率系数。DOY is days of year. Bias, RE, R², RMSE and NSE are mean deviation, relative error, determination coefficient, root mean square error and Nash-Sutcliffe efficiency coefficient, respectively.

Figure 4. Comparison of latent heat flux between estimation and observation at 30 min scale (from September 1^st to 15^th) in the three stations

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图 5 日尺度和30 min尺度3个站点的蒸散发估算精度在各季节上的评价

Bias、RE、R²、RMSE和NSE分别为平均偏差、相对误差、决定系数、均方根误差和Nash-Sutcliffe效率系数。Bias, RE, R², RMSE and NSE are mean deviation, relative error, determination coefficient, root mean square error and Nash-Sutcliffe efficiency coefficient, respectively.

Figure 5. Accuracy evaluation of evapotranspiration estimates at daily scale and 30 min scale in the three stations

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图 6 非参数化方法在3个站点的参数敏感性分析

T_a: 地表空气温度; T_s: 地表温度; R_n: 地表净辐射; G_s: 土壤热通量。T_a: air temperature; T_s: surface temperature; R_n: net radiation; G_s: soil heat flux.

Figure 6. Sensitivity analysis of the parameters of the nonparametric approach in the three stations

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图 7 日尺度上3个站点的潜热通量(LE)估算结果与观测结果的比较

LE_ER和LE_NP分别代表利用能量残差法修正后的潜热通量和NP估算得到的潜热通量。黑色实线为1∶1线; 红色实线为线性拟合线; 红色带为95%预测带。LE_ER and LE_NP represent the latent heat flux corrected by energy residual method and estimated by the nonparametric approach, respectively. The solid black line is 1∶1 line; the solid red line is the linear fitting line; the red band is the 95% prediction band.

Figure 7. Comparison of latent heat flux (LE) between estimation and observation at daily scale in the three stations

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图 8 30 min尺度上3个站点的潜热通量(LE)估算结果与观测结果的比较

Figure 8. Comparison of latent heat flux (LE) between estimation and observation at 30 min scale in the three stations

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表 1 3个通量站点能量通量和环境参数平均值

Table 1. Average of energy fluxes and environment parameters at the three stations

参数 Parameter	栾城 Luancheng	禹城 Yucheng	馆陶 Guantao
地表净辐射 Net radiation (R_n, W∙m⁻²)	72.47	65.04	65.82
土壤热通量 Soil heat flux (G_s, W∙m⁻²)	0.38	2.21	1.82
地表空气温度 Air temperature (T_a, K)	285.45	286.09	286.7
地表温度 Surface temperature (T_s, K)	285.57	286.9	288.79
大气压 Air pressure (kP)	100.65	101.31	101.04
降水量 Precipitation (mm)	330.1	445.4	577.9
LE_ER (W∙m⁻²)	59.16	53.58	47.55
LE_NP (W∙m⁻²)	46.28	37.40	32.53
LE_ER和LE_NP分别代表利用能量残差法修正后的潜热通量和NP估算得到的潜热通量。LE_ER and LE_NP represent the latent heat flux corrected by energy residual method and estimated by the nonparametric approach, respectively.

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表 2 日尺度和30 min尺度3个站点的蒸散发估算精度评价

Table 2. Accuracy evaluation of evapotranspiration estimates at daily scale and 30 min scale in the three stations

评价指标 Evaluation index	栾城 Luancheng		禹城 Yucheng		馆陶 Guantao		全部 Total
评价指标 Evaluation index	日尺度 Daily	30 min	日尺度 Daily	30 min	日尺度 Daily	30 min	日尺度 Daily	30 min
Bias (W∙m⁻²)	−12.88	−7.68	−16.18	−13.30	−15.12	−9.70	−14.73	−10.34
RE (%)	21.8	17.7	30.2	24.8	31.7	20.6	27.5	21.5
R²	0.83	0.88	0.80	0.88	0.83	0.88	0.81	0.88
RMSE (W∙m⁻²)	22.45	39.22	31.06	42.15	29.00	39.52	27.75	40.37
NSE	0.75	0.87	0.66	0.86	0.71	0.87	0.71	0.87
Bias、RE、R²、RMSE和NSE分别为平均偏差、相对误差、决定系数、均方根误差和Nash-Sutcliffe效率系数。Bias, RE, R², RMSE and NSE are mean deviation, relative error, determination coefficient, root mean square error and Nash-Sutcliffe efficiency coefficient, respectively.

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表 3 日尺度上3个站点的不同修正方法的潜热通量对模拟结果的精度评价

Table 3. Accuracy evaluation of simulation results by latent heat flux of different correction methods at daily scale in the three stations

评价指标 Evaluation index	栾城 Luancheng			禹城 Yucheng			馆陶 Guantao			全部 Total
评价指标 Evaluation index	LE₀	LE_BR	LE_ER	LE₀	LE_BR	LE_ER	LE₀	LE_BR	LE_ER	LE₀	LE_BR	LE_ER
Bias (W∙m⁻²)	−9.52	−11.06	−12.88	−20.21	−16.92	−16.18	−11.56	−16.61	−15.12	−13.76	−14.86	−14.73
RE (%)	17.1	19.3	21.8	35.1	31.2	30.2	26.2	33.8	31.7	26.1	28.1	27.9
R²	0.61	0.82	0.83	0.73	0.80	0.80	0.37	0.78	0.83	0.57	0.80	0.82
RMSE (W·m⁻²)	30.17	21.86	22.45	33.21	31.02	31.06	36.84	27.52	29.00	33.41	26.80	27.50
NSE	0.54	0.76	0.75	0.54	0.66	0.66	0.17	0.65	0.71	0.42	0.69	0.71
Bias、RE、 R²、RMSE和NSE分别为平均偏差、相对误差、决定系数、均方根误差和Nash-Sutcliffe效率系数。LE₀为未修正的潜热通量, LE_ER和LE_BR分别代表利用能量残差法和Bowen比闭合修正法修正后的潜热通量。Bias, RE, R², RMSE and NSE are mean deviation, relative error, determination coefficient, root mean square error and Nash-Sutcliffe efficiency coefficient, respectively. LE₀ is uncorrected latent heat flux, LE_ER and LE_BR represent the latent heat flux corrected by energy residual method and Bowen ratio closed correction method, respectively.

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