[1] Brubaker K L, Entekhabi D, 1996. Analysis of feedback mechan-isms in land-atmosphere interaction. Water Resources Research, 32(5): 1343-1357. doi:  10.1029/96WR00005
[2] Burgers G, Leeuwen P J, Evensen G, 1998. Analysis scheme in the ensemble Kalman filter. Monthly Weather Review, 126(6): 1719-1724. doi:  10.1175/1520-0493(1998)126
[3] Crow W T, Berg M J, 2010. An improved approach for estimating observation and model error parameters in soil moisture data assimilation. Water Resources Research, 46(12): 12-51. doi:  10.1029/2010WR009402.
[4] Delworth T, Manabe S, 1988. The influence of potential evapora-tion on the variabilities of the simulated soil wetness and climate. Journal of Climate, 1(5): 523-547. doi:  10.1175/1520-0442(1988)001
[5] Dobson M C, Ulaby F T, 1986. Active microwave soil moisture research. IEEE Transactions on Geoscience and Remote Sensing, 24(1): 23-36. doi:  10.1109/TGRS.1986.289585
[6] Dobson M C, Ulaby F T, Hallikainen M T, 1985. Microwave dielectric behavior of wet soil-Part II: Dielectric mixing models. IEEE Transactions on Geoscience and Remote Sensing, 23(1): 35-46. doi:  10.1109/TGRS.1985.289498
[7] England A W, Galantowicz J F, Schretter M S, 1992. The radio-brightness thermal inertia measure of soil moisture. IEEE Transactions on Geoscience and Remote Sensing, 30(1): 132-139. doi:  10.1109/36.124223
[8] Entekhabi D, Galantowicz J F, Njoku E G, 1994. Solving the in-verse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed ob-servations. IEEE Transactions on Geoscience and Remote Sensing, 32(2): 438-448. doi:  10.1109/36.295058
[9] Etienne H, Dombrowsky E, 2003. Estimation of the optimal in-terpolation parameters in a quasi-geostrophic model of the Northeast Atlantic using ensemble methods. Journal of Marine System, 40(4): 317-339. doi.org/10.1016/S0924-7963 (03)00023-X
[10] Evensen G, 1994. Sequential data assimilation with a non-linear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. Journal of Geophysical Research, 99(C5): 10143-10162. doi:  10.1029/94JC00572
[11] Fung A K, Lee Z, Chen K S, 1992. Backscattering from a ran-domly rough dielectric surface. IEEE Transactions on Geos-cience and Remote Sensing, 30(2): 356-369. doi: 10.1109/36. 134085
[12] Galantowicz J F, Entekhabi D, Njoku E G, 1999. Tests of sequen-tial data assimilation for retrieving profile soil moisture and temperature from observed L-band radiobrightness. IEEE Transactions on Geoscience and Remote Sensing, 37(4): 1860-1870. doi:  10.1109/36.774699
[13] Haugen E J, Evensen G, 2002. Assimilation of SLA and SST data into an OGCM for the Indian Ocean. Ocean Dynamics, 52(3): 133-151. doi:  10.1007/s10236-002-0014-7
[14] Heathman G C, Starks P J, Ahuja L R et al., 2003. ASsimilation of surface soil moisture to estimate profile soil water content. Journal of Hydrology, 27(1): 1-17. doi: 10.1016/S0022-1694 (03)00088-X
[15] Houser P R, Shuttleworth W J, Gupta H V, 1998. Integration of soil moisture remote sensing and hydrologic modeling using data assimilation. Water Resource Research, 34(12): 3405- 3420. doi:  10.1029/1998WR900001
[16] Huang C H, Li X, Lu L et al., 2008. Experiments of one-dimen-sional soil moisture assimilation system based on ensemble Kalman filter. Remote Sensing of Environment, 112(3): 888-900. doi:  10.1016/j.rse.2007.06.026
[17] Kogan F, l990. Remote sensing of weather impacts on vegetation in non-homogeneous areas. International Journal of Remote Sensing, 11(8): 1405-1419. doi:  10.1080/01431169008955102
[18] Lee S J, Jurkevich L, Dewaele P et al., 1994. Speckle filtering of synthetic aperture radar images: A review. Remote Sens-ing Reviews, 8(4): 313-340. doi:  10.1080/02757259409532206
[19] Li F Q, Wade T, William P et al., 2010. Towards the estimation root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals. Advances in Water Resources, 33(2): 201-214. doi: 10.1016/j.advwatres. 2009.11.007
[20] Li X, Koike T, Mahadevan P, 2004. A very fast simulated re-annealing (VFSA) approach for land data assimilation. Computer & Geosciences, 30(3): 239-248. doi: 10.1016/j. ca-geo.2003.11.002
[21] Li X, Lu L, Cheng G D et al., 2001. Quantifying landscape structure of the Heihe River Basin, north-west China using FRAGSTATS. Journal of Arid Environments, 48(4): 521-535. doi:  org/10.1006/jare.2000.0715
[22] Liu Qian, Wang Mingyu, Zhao Yingshi, 2010. A weighted average soil moisture assimilation experiment based on ensemble Kalman filter. Geography and Geo-Information Science, 26(1): 94-97. (in Chinese)
[23] Mancini M R, Hoeben R, Troch P, 1999. Multifrequency radar observations of bare surface soil moisture content: A laboratory experiment. Water Resources Research, 35(6): 1827-1838. doi:  10.1029/1999WR900033
[24] Miller R N, Ghil M, Ghautiez F, 1994. Advanced data assimilation in strongly nonlinear dynamical system. Journal of the Atmospheric Sciences, 51(8): 1037-1055. doi:  10.1175/1520-0469(1994)051<1037:ADAISN>2.0.CO;2
[25] Reichle R H, Crow W T, Christian L et al., 2008. An adaptive ensemble Kalman filter for soil moisture data assimilation. Water Resources Research, 44(3): 23-34. doi: 10.1029/2007 WR006357
[26] Reichle R H, McLaughlin D B, Entekhabi D, 2002a. Hydrologic data assimilation with the ensemble Kalman filter. Monthly Weather Review, 130(1): 103-114. doi: 10.1175/1520-0493 (2002)130
[27] Reichle R H, Walker J P, Koster R D, 2002b. Extended versus ensemble filtering for land data assimilation. Journal of Hy-drometeorology, 3(2): 728-740. doi: 10.1175/1525-7541 (2002)003
[28] Roo R D, Duetal Y, 2001. A semi-empirical backscattering model at L-band and C-band for a soybean canopy with soil moisture inversion. IEEE Transactions on Geoscience and Remote Sensing, 39(4): 864-872. doi:  10.1109/36.917912
[29] Sandholt I, Rasmussen K, Andersen J, 2002. A simple interpreta-tion of the surface temperature/vegetation index space for as-sessment of surface moisture status. Remote Sensing of Envi-ronment, 79(2): 213-224. doi: 10.1016/S0034-4257(01) 00274-7
[30] Sellers P J, Schimel D S, 1993. Remote sensing of the land bios-phere and biogeochemistry in the EOS era: Science priorities, methods and implementation. Global and Planetary Change, 7(4): 279-297. doi:  10.1016/0921-8181(93)90002-6
[31] Ulaby F T, Allen C T, Eger G, 1984. Relating microwave back-scattering coefficient to leaf area index. Remote Sensing of Environment, 14: 113-133.
[32] Ulaby F T, Batlivala P P, Dobson M C, 1978. Microwave back-scatter dependence on surface roughness, soil moisture, and soil texture. IEEE Transactions on Geoscience and Remote Sensing, 16(4): 286-295. doi:  10.1109/TGE.1978.294586
[33] Ulaby F T, Sarahandi K, Donald M K, 1990. Michigan microwave canopy scattering model. International Journal of Remote Sensing, 11(7): 1223-1253. doi: 10.1080/0143116900 8955090
[34] Verlaan M, Heemink A W, 2001, Nonlinearity in data assimilation applications: A practical method for analysis. Monthly Weather Review, 129(6): 1578-1589. doi: 10.1175/1520-0493 (2001)129
[35] Walker J P, Willgoose G R, 2001. One-dimensional soil moisture profile retrieval by assimilation of near-surface observations: A comparison of retrieval algorithms. Advances in Water Re-sources, 24(6): 631-650. doi:  10.1016/S0309-1708(00)00043-9
[36] Wang S G, Li X, Han X J et al., 2011. Estimation of surface soil moisture and roughness from multi-angular ASAR imagery in the Watershed Allied Telemetry Experimental Research (WATER). Hydrology and Earth System Sciences, 15(5): 1415-1426. doi:  10.5194/hess-15-1415-2011
[37] Wigmosta M S, Nijssen P S, Lettenmaier D P, 2002. The distri-buted hydrology soil vegetation model. In: Singh V P (eds.). Mathematical Models of Small Watershed Hydrology and Ap-plications. Highlands Ranch: Water Resources Press, 7-42.
[38] Wigmosta M S, Vail L, Lettenmaier D P, 1994. A distributed hy-drology-vegetation model for complex terrain. Water Resource Research, 30(6): 1665-1679. doi:  10.1029/94WR00436
[39] Wu T D, Chen K S, Shi J C, 2008. A study of an AIEM model for bistatic scattering from randomly rough surfaces. IEEE Transactions on Geoscience and Remote Sensing, 46(9): 2584-2598. doi:  10.1109/TGRS.2008.919822
[40] Yang Shenbing, Shen Shuanghe, 2009. Mapping rice yield based on assimilation of ASAR data with rice growth model. Journal of Remote Sensing, 13(2): 282-290. (in Chinese)
[41] Zhang S W, Li H R, Zhang W D et al., 2006. Estimating the soil moisture profile by assimilating near-surface observations with the ensemble Kalman filter (EnKF). Advances in Atmosphereic Sciences, 22(6): 936-945. doi:  10.1007/BF02918692