论文通过改进遥感蒸散模型的关键参数,结合遥感数据和气象观测数据,对2003—2008年江西千烟洲人工林生态系统蒸散及其组分进行模拟,并利用涡度相关技术获取的蒸散实测数据对模型模拟结果进行验证和评价。结果表明:①年均蒸散总量模拟值比实测值偏低2.4%,决定系数与均方根误差分别为0.83和0.61 mm·d-1。②土壤蒸发、林冠截留蒸发和植被蒸腾分别占总蒸散量的12%、23%和65%。其中,土壤蒸发季节及年际变化相对稳定;林冠截留蒸发季节变化明显且在不同年份差异较大;植被蒸腾季节变化明显,但年际变异较小。③1—3月植被光合作用较弱,植被蒸腾与蒸散比小于30%。随着植被蒸腾的增强,从4月开始植被蒸腾与蒸散比迅速增加,在生长旺季(7月底)可达到约90%。由于该模型所需数据在区域尺度较易获取,从而为开展区域尺度中亚热带人工林生态系统蒸散及其组分模拟提供方法支撑。
In this study, with the verification and improvement to the evapotranspiration(ET)model(PT-Fi model), we simulate the ET and its components of the planted coniferous forest ecosystem at Qianyanzhou during 2003 and 2008 by using remote sensing data from MODIS and meteorological data. The estimated ET is compared with the observation from eddy flux tower sites. The results show that the simulated annual ET is about 2.4% lower than measurement, with a decision coefficient value (R2) of 0.83 and root mean square error of 0.61 mm·d-1. As to the ET components, soil evaporation is 12% of simulated ET with relative stability at seasonal and interannual scale. With obvious seasonal and interannaual variability, interception evaporation contribute 23% of the ET and with the same change tendency as precipitation. Canopy transpiration is about 65% of ET with obvious seasonal variation and interannual stability. During January to March, photosynthesis isn’t to be strong, canopy transpiration and evapotranspiration ration (T/ET) less than 30%, with the enhance of canopy transpiration, T/ET increases rapidly after April, in the end of July up to about 90%. Because of the data is easy to get at regional dimension in this model, which can lay a foundation for the further scaling up of evapotranspiration estimation in subtropical coniferous forest.
[1] Liu J, Chen J M, Cihlar J, et al. Net primary productivity mapped for Canada at 1-km resolution [J]. Global Change Biology, 2002, 11: 115-129.
[2] Field C B, Randerson J T, Malmstrem. Global net primary production: Combining ecology and remote sensing [J]. Remote Sensing of Environment, 1995, 51: 74-88.
[3] 奚歌, 刘绍民, 贾立. 黄河三角洲湿地蒸散量与典型植被的生态需水量[J]. 生态学报, 2008, 28(11): 3546-3569. [XI Ge, LIU Shao-min, JIA Li. Estimation of regional evapotranspiration and ecological water requirement of vegetation by remote sensing in the Yellow River Delta wetland. Acta Ecologica Sinica, 2008, 28(11): 3546-3569. ]
[4] Park S, Feddema J J, Egbert S L. MODIS and surface temperature composite data and their relationships with climatic water budget factors in the Central Great Plains [J]. International Journal of Remote Sensing, 2005, 26(6): 1127-1144.
[5] Tasumi M, Treezza R, Allen R G, et al. Operational aspects of satellite-based energy balance models for irrigated crops in the semi-arid US [J]. Irrigation and Drainage Systems, 2005, 19(3/4): 355-376.
[6] Allen R G, Tasumi M, Morse A, et al. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-applications [J]. Journal of Irrigation and Drainage Engineering, 2007, 1333(4): 395-406.
[7] Hurtado E, Caselles V, Artigao M, et al. Estimating corn evapotranspiration from NOAA-AVHRR data in the Albacete area [J]. International Journal of Remote Sensing, 1995, 10: 2023-2037.
[8] Moran M S, Kustas W P, Vidal A, et al. Use of ground based remotely sensed data for surface energy balance evaluation of a semi-arid range land [J]. Water Resource Research, 1994, 30(5): 1339-1349.
[9] Fisher J B, Kevin P, Tu D D, et al. Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data validated at 16 FLUXNET sites [J]. Remote Sensing of Environment, 2008, 112: 901-919.
[10] MI Na, YU Gui-rui, WEN Xue-fa, et al. use of ecosystem flux data and a simulation model to examine seasonal drought effects on a subtropical coniferous forest [J]. Asia-pacific Journal of Atmospheric Sciences, 2009, 45(2): 207-220.
[11] Vinukollua R K, Wooda E F, Ferguson C R, et al. Global estimates of evapotranspiration for climate studies using multi-sensor remote sensing data: Evaluation of three process-based approaches [J]. Remote Sensing of Environment, 2011, 115: 801-823.
[12] 刘允芬, 于贵瑞, 温学发, 等. 千烟洲中亚热带人工林生态系统CO2通量的季节变异特征[J]. 中国科学D辑: 地球科学, 2006, 36 (增刊Ⅰ): 91-102. [LIU Yun-fen, YU Gui-rui, WEN Xue-fa, et al. Seasonal dynamics of CO2 fluxes from subtropical plantation coniferous ecosystem. Science in China Series D: Earth Sciences, 2006, 36(SuppⅠ): 91-102.]
[13] 李春, 何洪林, 刘敏, 等. ChinaFLUX CO2通量数据处理系统与应用[J]. 地球信息科学, 2008, 10(5): 557 于贵瑞, 孙晓敏. 中国陆地生态系统碳通量观测技术及时空变化特征[M]. 北京: 科学出版社, 2005. [YU Gui-rui, SUN Xiao-min. Flux Measurement and Research of Terrestial Ecosystem in China. Beijing: Science Press, 2005.]
[24] Beer A. Bestimmung der Absorption des rothen Lichts in farbigen Flüssigkeiten [J]. Annalen der Physik, 1852, 86: 78-88.
[25] 李轩然, 刘琪璟, 蔡哲, 等. 千烟洲针叶林的比叶面积及叶面积指数[J]. 植物生态学报, 2007, 31(1): 93-101. [LI Xuan-ran, LIU Qi-jing, CAI Zhe, et al. Specific leaf area and leaf area index of conifer plantations in Qianyanzhou Station of subtropical China. Acta Phytoecologica Sinica, 2007, 31(1): 93-101.]
[26] Gao X, Huete A R, Ni W G, et al. Optical-biophysical relationships of vegetation spectra without background contamination [J]. Remote Sensing of Environment, 2000, 74: 609-620.
[27] Wilson K B, Hansonb P J, Baldocchi D, et al. Controlling evaporation and energy partitioning beneath a deciduous forest over an annual cycle [J]. Agricultural and Forest Meteorology, 2000, 102: 83-103.
[28] 李博, 赵斌, 彭容豪, 等. 陆地生态系统生态学原理[M]. 北京: 高等教育出版社, 2005. [LI Bo, ZHAO Bin, PENG Rong-hao, et al. Principles of Terrestrial Ecosystem Ecology. Beijing: Higher Education Press, 2005.]
[29] Wang L, Caylor K K, Villegas J C, et al. Partitioning evapotranspiration across gradients of woody plant cover: Assessment of a stable isotope technique [J]. Geophysical Research Letters, 2010, 37: 9401-9401.
