近30年来中国陆地蒸散量和土壤水分变化特征分析

doi:10.3724/SP.J.1047.2012.00001

地球信息科学学报 ›› 2012, Vol. 14 ›› Issue (1): 1-13.doi: 10.3724/SP.J.1047.2012.00001

• 陆地表层系统模拟 • 下一篇

近30年来中国陆地蒸散量和土壤水分变化特征分析

邴龙飞^1,2, 苏红波¹, 邵全琴^1*, 刘纪远¹

1. 中国科学院地理科学与资源研究所, 北京 100101;
2. 中国科学院研究生院, 北京 100049

收稿日期:2011-11-04 修回日期:2012-02-01 出版日期:2012-02-25 发布日期:2012-02-24
通讯作者: 邵全琴(1965-), 女, 博士, 研究员, 研究方向为GIS应用与生态信息。E-mail: shaoqq@lreis.ac.cn E-mail:shaoqq@lreis.ac.cn
作者简介:邴龙飞(1979-), 男, 山东青岛人, 博士研究生, 研究方向为区域水热平衡。E-mail: binglf@lreis.ac.cn
基金资助:
国家重点基础研究发展规划"973"项目(2010CB950902);国家重点基础研究发展规划"973"项目(2009CB421105)。

Changing Characteristic of Land Surface Evapotranspiration and Soil Moisture in China during the Past 30 Years

BING Longfei^1,2, SU Hongbo¹, SHAO Quanqin^1*, LIU Jiyuan¹

1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China

Received:2011-11-04 Revised:2012-02-01 Online:2012-02-25 Published:2012-02-24

摘要/Abstract

摘要： 对NOAH陆面模式模拟的近30年中国陆地蒸散量和土壤含水量,按照6大片区和5种生态系统类型进行了统计分析。讨论全国以及各大区不同生态系统类型蒸散和土壤含水量的变化,研究不同类型蒸散和土壤含水量的关系。中国陆地蒸散量总体呈增加的趋势,年内蒸散量最大的月份是7月,年末和年初蒸散量较小。而我国中南、西南、华东、东北和西北蒸散量变化趋势和全国的总趋势一致,呈增加的趋势。华北地区蒸散量近30年来总体趋势是下降的,华北蒸散量最大的年份是上世纪90年代。在所有生态系统类型中,林地蒸散最大的有东北、华东、西南和中南4区;而华北和西北草地在各类型中蒸散量所占比例最高。6大片区对比,林地蒸散水量最大的地区是西南和中南,最小的西北;草地蒸散水量最大的地区是西南,最小的是东北区;农田蒸散水量最高的是华东,最低的是西北;荒漠蒸散量最大的片区是西北;湿地蒸散最大的是东北。80年代以来,全国土壤含水量总体呈下降的趋势。从各片区的情况看,仅西北地区稍有增加,其余5区土壤含水量皆是下降的。植被覆盖度和土壤水分是影响蒸散量最重要的因子,在植被覆盖较差时,土壤水分和蒸散量相关性较好。

关键词: 蒸散, 土壤含水量, 植被覆盖度, NOAH, 陆面模式, LUCC

Abstract: The land surface evapotranspiration (ET) and soil moisture used in this paper were retrieved from land surface model (LSM) of NOAH. The variation of land surface ET and soil moisture was analyzed by statistics in six large regions and by four ecosystem types in China. Then the relationship between ET and soil moisture was discussed. The long term trend of land surface ET was increasing in China. The maximum ET occurred in July, while the minimum one was usually at the beginning/end of a year. The trend of ET in South-Central China, Southwest China, East China, Northeast China and Northwestern China was also increasing, agreed with the whole China. The long term variation trend of ET was decreasing in North China, where the maximum ET was 43.091 Billion Cubic Meters (BCM) in 1990. The relative ratio of evapotranspiration of forest was the highest among all the ecosystem types in Northeast, East, Southwest and South-Central China, while the highest one was grassland in North and Northwest China. To compare the amount of water used by evapotranspiration, the biggest forest ET was in Southwest and South Central China, the smallest was in Northwest China; the biggest grassland ET was in Southwest China, the smallest was in Northeast China; the biggest farmland ET was in East China, the smallest was in Northwest China; the biggest ET for desert and wet land was in Northwest and Northeast China respectively. The soil moisture was decreasing in most China regions except for that in Northwest China ever since 1980s, agreed with the whole China. The main impact factors of ET were vegetation fraction and soil moisture. There existed a good relationship between soil water content and evapotranspiration in rare vegetation covered regions.

Key words: soil moisture, vegetation fraction, NOAH, land surface model, evapotranspiration, LUCC

邴龙飞, 苏红波, 邵全琴, 刘纪远. 近30年来中国陆地蒸散量和土壤水分变化特征分析[J]. 地球信息科学学报, 2012, 14(1): 1-13.DOI:10.3724/SP.J.1047.2012.00001

BING Longfei, SU Hongbo, SHAO Quanqin, LIU Jiyuan. Changing Characteristic of Land Surface Evapotranspiration and Soil Moisture in China during the Past 30 Years[J]. , 2012, 14(1): 1-13.DOI:10.3724/SP.J.1047.2012.00001

参考文献

[1] Li Z, Tang R, Wan Z, et al. A review of current methodologies for regional evapotranspiration estimation from remotely sensed data[J]. Sensors, 2009, 9(5): 3801-3853.

[2] Allen R G, Pereira L S, Howell T A, et al. Evapotranspiration information reporting: II. Recommended documentation[J]. Agricultural Water Management, 2011, 98(6): 921-929.

[3] Allen R G, Pereira L S, Howell T A, et al. Evapotranspiration information reporting: I. Factors governing measurement accuracy[J]. Agricultural Water Management, 2011, 98(6): 899-920.

[4] Dingman S L. Physical hydrology[M]: Upper Saddle River, NJ: Prentice Hall, 1994.

[5] 王书功,康尔泗, 金博文,等. 黑河山区草地蒸散发量估算方法研究[J]. 冰川冻土, 2003, 25(5): 558-565.

[6] Rana G, Katerji N. Measurement and estimation of actual evapotranspiration in the field under Mediterranean climate: Areview[J]. European Journal of Agronomy, 2000, 13(2-3): 125-153.

[7] Courault D, Seguin B, Olioso A. Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches[J]. Irrigation and Drainage Systems, 2005, 19(3-4): 223-249.

[8] Kustas W P, Norman J M. Use of remote sensing for evapotranspiration monitoring over land surfaces[J]. Hydrological Sciences Journal, 1996, 41(4): 495-516.

[9] Allen R, Tasumi M, Morse A, et al. A Landsat-based energy balance and evapotranspiration model in Western US water rights regulation and planning[J]. Irrigation and Drainage Systems, 2005, 19(3): 251-268.

[10] Fisher J B, Tu K P, Baldocchi D D. 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(3): 901-919.

[11] 刘永强,叶笃正,季劲钧. 土壤湿度和植被对气候的影响——Ⅱ.短期气候异常持续性的数值试验[J]. 中国科学(B辑:化学生命科学地学), 1992(5): 554-560.

[12] 刘永强,叶笃正,季劲钧. 土壤湿度和植被对气候的影响——Ⅰ.短期气候异常持续性的理论分析[J]. 中国科学(B辑:化学生命科学地学), 1992(4): 441-448.

[13] Charusombat U, Niyogi D, Kumar A, et al. Evaluating a new deposition velocity module in the Noah land-surface model[J]. Boundary-Layer Meteorology, 2010,137(2): 271-290.

[14] Ek M B, Mitchell K E, Lin Y, et al. Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model[J]. Journal of Geophysical Research-Atmospheres, 2003, 108(D22): 8851.

[15] Hogue T S, Bastidas L, Gupta H, et al. Evaluation and rransferability of the Noah land surface model in semiarid environments[J]. Journal of Hydrometeorology, 2005, 6(1): 68-84.

[16] Lakshmi V, Hong S, Small E E, et al. The influence of the land surface on hydrometeorology and ecology: new advances from modeling and satellite remote sensing[J]. Hydrology Research, 2011, 42(2-3): 95-112.

[17] Rosero E, Gulden L E, Yang Z, et al. Ensemble evaluation of hydrologically enhanced Noah-LSM: Partitioning of the water balance in high-resolution simulations over the Little Washita River experimental watershed[J]. Journal of Hydrometeorology, 2011, 12(1): 45-64.

[18] Sridhar V, Elliott R L, Chen F, et al. Validation of the NOAH-OSU land surface model using surface flux measurements in Oklahoma[J]. Journal of Geophysical Research-Atmospheres, 2002, 107(D20): 4418.

[19] Sridhar V, Elliott R L, Chen F. Scaling effects on modeled surface energy-balance components using the NOAH-OSU land surface model[J]. Journal of Hydrology, 2003, 280(1-4): 105-123.

[20] Chen Y, Yang K, Zhou D, et al. Improving the Noah land surface model in arid regions with an appropriate parameterization of the thermal roughness length[J]. Journal of Hydrometeorology, 2010, 11(4): 995-1006.

[21] Schaake J C, Koren V I, Duan Q, et al. Simple water balance model for estimating runoff at different spatial and temporal scales[J]. Journal of Geophysical Research-Atmospheres, 1996, 101(D3): 7461-7475.

[22] 刘纪远,布和敖斯尔. 中国土地利用变化现代过程时空特征的研究——基于卫星遥感数据[J]. 第四纪研究, 2000, 20(3): 229-239.

[23] 刘纪远,刘明亮,庄大方,等. 中国近期土地利用变化的空间格局分析[J]. 中国科学(D辑:地球科学), 2002, 32(12): 1031-1043.

[24] 刘纪远, 张增祥, 庄大方. 中国土地利用变化的遥感时空信息研究[M]. 北京: 科学出版社, 2005.

[25] 马洁华,刘园, 杨晓光,等. 全球气候变化背景下华北平原气候资源变化趋势[J]. 生态学报, 2010, 30(14): 3818-3827.

[26] 李正泉,于贵瑞,温学发,等. 中国通量观测网络(ChinaFLUX)能量平衡闭合状况的评价[J]. 中国科学(D辑:地球科学), 2004, 34(SII): 46-56.

[27] Wilson K, Goldstein A, Falge E, et al. Energy balance closure at FLUXNET sites[J]. Agricultural and Forest Meteorology, 2002, 113(1-4): 223-243.

近30年来中国陆地蒸散量和土壤水分变化特征分析

Changing Characteristic of Land Surface Evapotranspiration and Soil Moisture in China during the Past 30 Years

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