地球科学进展 ›› 2006, Vol. 21 ›› Issue (12): 1350 -1362. doi: 10.11867/j.issn.1001-8166.2006.12.1350

研究论文 上一篇    下一篇

基于土壤水模型及站点资料的土壤湿度同化方法
张生雷 1,2,谢正辉 1,田向军 1,师春香 1,陈锋 1   
  1. 1.中国科学院大气物理研究所,北京 100029;2.中国科学院研究生院,北京 100049
  • 收稿日期:2006-10-11 修回日期:2006-11-15 出版日期:2006-12-15
  • 通讯作者: 谢正辉(1963-),男,湖南长沙人,博士,研究员,博士生导师,主要从事陆面过程模式的发展、陆气相互作用中地下水位的动态表示、气候与水文耦合模式研制等方面的研究. E-mail:zxie@lasg.iap.ac.cn
  • 基金资助:

    国家自然科学基金项目“地表地下水文机制集成与区域气候模式的双向耦合”(编号:90411007);国家重点基础研究专项经费项目“复杂流动问题的高性能算法研究”(编号:2005CB321703);中国科学院创新团队国际合作伙伴计划项目“气候系统模式研发及应用研究”资助.

A Soil Moisture Assimilation Scheme With an Unsaturated Soil Water Flow Model and In-Site Observation

Zhang Shenglei 1,2,Xie Zhenghui 1,Tian Xiangjun 1,Shi Chunxiang 1,Chen Feng 1   

  1. 1.Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,China;2.Graduate School of the Chinese Academy of Science,Beijing 100049,China
  • Received:2006-10-11 Revised:2006-11-15 Online:2006-12-15 Published:2006-12-15

基于非饱和土壤水模型和扩展卡尔曼滤波(Extended Kalman Filter)同化算法并结合陆面过程模型VIC发展了一个土壤湿度同化方案,并进行了理想试验及同化站点资料的同化试验。理想试验结果表明:扩展卡尔曼滤波方法能完整反演土壤湿度廓线,对土壤湿度的估计有较大改善;观测深度、观测层数和观测资料引入频率对同化结果有一定影响;加大观测频率,可以进一步改善同化效果。利用气象强迫驱动陆面模型VIC算出地表入渗条件而进行的同化站点资料的试验所得土壤湿度分布与观测资料基本吻合,反映了站点土壤湿度的月、季变化,表明该方案是合理的。

A soil moisture assimilation scheme based on the extended Kalman filter(EKF)and an unsaturated soil water flow model is developed and numerical experiments using synthetic data and numerical simulation with in-site observations are presented. The numerical experiments show that the assimilation scheme improve estimation of soil moisture, the frequency of observation, the depth and the layers at which observation is introduced have the influence on assimilation. The assimilation experiments with in-site observations and infiltration derived from meteorologic forcing condition and the land surface model VIC show the monthly and seasonal variation of soil moisture, which show that the assimilation scheme is reasonable.

中图分类号: 

[1] Jackson T J. Measuring surface soil moisture using passive microwave remote sensing[J]. Hydrological Processes, 1993,7:139-152.

[2] Jackson T J, Schmugge T J, Engman E T. Remote sensing applications to hydrology:Soil moisture [J]. Hydrological Sciences Journal,1996, 41(4):517-530.

[3] Koster R D, Suarez M J, Heiser M. Variance and predictability of precipitation at seasonal to interannual timescales [J]. Journal of Hydrometeorology,2000,1:26-46.

[4] Yeh T C, Wetherald R I, Manabe S. The effect of soil moisture on the short term climate and hydrology change—A numerical experiment [J]. Monthly Weather Review,1984,112:474-490.

[5] Schmugge T. Chapter 5:Remote sensing of soil moisture[C]Anderson M G, Burt T P, eds. Hydrological Forecasting. New York:Wiley ,1985:101-124.

[6] Zhang S W,Qiu C J,Xu Q. Estimating soil water contents from soil temperature measurements by using adaptive Kalman filter[J]. Journal of Applied Meteorology,2004,43:379-389.

[7] Lin D S, Wood E F, Troch P A, et al. Comparisons of remotely sensed and model-simulated soil moisture over a heterogeneous watershed[J] . Remote Sensing of Environment,1994,48:159-171.

[8] Entin J K,Robock A,Vinnikov K Y,et al. Evaluation of global soil wetness project soil moisture simulation[J]. Journal of the Meteorological Society of Japan,1999,77(1B):183-198.

[9] Njoku E G, Entekhabi D. Passive microwave remote sensing of soil moisture[J]. Journal of the Meteorological Society of Japan,1995,184:101-130.

[10] Crow W T, Wood E F. The assimilation of remotely sensed soil brightness temperature imagery into a land surface model using Ensemble Kalman filtering:A case study based on ESTAR measurements during SGP97[J]. Advances in Water Resources,2003,26:137-149.

[11] Houser P R, Shuttleworth W J, Famiglietti J S, et al. Integration of soil moisture remote sensing and hydrologic modeling using data assimilation[J]. Water Resources Research,1998,34(12):3 405-3 420.

[12] Reichle R H, Entekhabi D, McLaughlin D B. Downscaling of radio brightness measurements for soil moisture estimation:A four-dimensional variational data assimilation approach[J]. Water Resources Research,2001,37:2 353-2 364.

[13] Reichle R H,Walker J P,Randal D K,et al. Extended versus ensemble Kalman filtering for land data assimilation[J]. Journal of Hydrometeorology,2002,3:728-740.

[14] Entekhabi D, Nakamura H, Njoku E G. Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed observations[J]. IEEE Transactions on Geoscience and Remote Sensing,1994,32:438-448.

[15] Walker J P, Willgoose G R, Kalma J D. One-dimensional soil moisture profile retrieval by assimilation of near-surface observations:A comparison of retrieval algorithms[J]. Advances in Water Resources,2001,24:631-650.

[16] Li J, Islam S. Estimation of soil moisture profile and surface fluxes partitioning from sequential assimilation of surface layer soil moisture[J]. Journal of Hydrology,1999,220:86-103

[17] Galantowicz J F, Entekhabi D, Njoku E G .Test of sequential data assimilation for retrieving profile soil moisture and temperature from observed L-band radiobrightness[J]. JEEE Transactions on Geoscience and Remote Sensing, 1999, 37 (4):1 860-1 870.

[18] Hoeben R, Troch P A. Assimilation of active microwave observation data for soil moisture profile estimation[J]. Water Resources Research,2000,36(10):2 805-2 819.

[19] Li Xin, Toshio Koike, Cheng G D. An algorithm for land data assimilation by using simulated annealing method[J]. Advances in Earth Science,2003,18(4):632-636.[李新,小池俊雄,程国栋.一个基于模拟退火法的陆面数据同化算法[J].地球科学进展,2003,18(4):632-636.]

[20] Zhang Shuwen,Li Haorui,Zhang Weidong,et al. Estimating the soil moisture profile by assimilating near-surface observations with the Ensemble Kalman Filter (EnKF) [J]. Advances in Atmospheric Sciences,2006,22(6):936-945.

[21] Bear J. Dynamics of Fluids in Porous Media[M]. New York :Dover Publications Inc.,1972:764.

[22] Lei Zhidong, Yang Shixiu, Xie Senchuan. Soil Water Dynamics [M]. Beijing:TsingHua University Press, 1988:275-280. [雷志栋,杨诗秀,谢森传.土壤水动力学[M].北京:清华大学出版社,1988:275-280.]

[23] Xie Zhenghui,Zeng Qingcun,Dai Yongjiu,et al. Numerical simulation of an unsaturated flow equation[J]. Sciences in China(Series D),1998,28(4):175-180.[谢正辉,曾庆存,戴永久,.非饱和流问题的数值模拟研究[J].中国科学:D,1998,28(4):175-180.]

[24] Xie Zhenghui,Luo Zhendong,Zeng Qingcun,et al. A numerical simulation solving moisture content and flux for an unsaturated soil water flow problem[J]. Progress in Natural Sciences,1999,9(12):1 280-1 286.[谢正辉,罗振东,曾庆存,.非饱和土壤水流问题含水量和通量的数值模拟研究[J].自然科学进展,1999,9(12):1 280-1 286.]

[25] Campbell G S. A simple method for determining unsaturated conductivity from moisture retention data[J]. Soil Science,1974,117:311.

[26] Clapp R R, Honberger G M. Empirical equations for soil hydraulic properties[J]. Water Resources Research,1978, 14:601-604.

[27] Hu Jianwei,Tang Huaiming. Numerical Methods for Differential Equations[M]. Beijing:Science Press,2000:92-93. [胡建伟,汤怀明.微分方程数值方法[M].北京:科学出版社,2000:92-93.]

[28] Liaqng X,Lettenmaier D P,Wood E F,et al. A Simple hydrological model of land surface water and energy fluxes for general circulation models[J]. Journal of Geophysics Research,1994,99(D7):14 415-14 428.

[29] Liang X, Wood E F, Lettenmaier D P. Surface soil moisture parameterization of the VIC-2L model:Evaluation and modifications [J]. Global and Planetary Change,1996,13:195-206.

[30] Liang X, Xie Z.A new surface runoff parameterization with sub-grid scale soil heterogeneity for land surface models [J]. Advances in Water Resources,2001,24:1 173-1 193.

[31] Daley R. Atmospheric Data Analysis[M]. New York:Cambridge University Press,1991.

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