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Advances in Meteorology
Volume 2017, Article ID 1086456, 15 pages
https://doi.org/10.1155/2017/1086456
Research Article

Hydrological Evaluation of Satellite Soil Moisture Data in Two Basins of Different Climate and Vegetation Density Conditions

WEMRC, Department of Civil Engineering, University of Bristol, Bristol, UK

Correspondence should be addressed to Lu Zhuo; ku.ca.lotsirb@ouhz.ul

Received 27 July 2016; Revised 15 November 2016; Accepted 6 December 2016; Published 29 January 2017

Academic Editor: Minha Choi

Copyright © 2017 Lu Zhuo and Dawei Han. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. D. Aubert, C. Loumagne, and L. Oudin, “Sequential assimilation of soil moisture and streamflow data in a conceptual rainfall—runoff model,” Journal of Hydrology, vol. 280, no. 1–4, pp. 145–161, 2003. View at Publisher · View at Google Scholar · View at Scopus
  2. J. C. Refsgaard, “Validation and intercomparison of different updating procedures for real-time forecasting,” Nordic Hydrology, vol. 28, no. 2, pp. 65–84, 1997. View at Google Scholar · View at Scopus
  3. C. Ottlé and D. Vidal-Madjar, “Assimilation of soil moisture inferred from infrared remote sensing in a hydrological model over the HAPEX-MOBILHY region,” Journal of Hydrology, vol. 158, no. 3-4, pp. 241–264, 1994. View at Publisher · View at Google Scholar · View at Scopus
  4. M.-E. Ridler, H. Madsen, S. Stisen, S. Bircher, and R. Fensholt, “Assimilation of SMOS-derived soil moisture in a fully integrated hydrological and soil-vegetation-atmosphere transfer model in Western Denmark,” Water Resources Research, vol. 50, no. 11, pp. 8962–8981, 2014. View at Publisher · View at Google Scholar · View at Scopus
  5. P. K. Srivastava, D. Han, M. A. Rico-Ramirez, P. O'Neill, T. Islam, and M. Gupta, “Assessment of SMOS soil moisture retrieval parameters using tau-omega algorithms for soil moisture deficit estimation,” Journal of Hydrology, vol. 519, pp. 574–587, 2014. View at Publisher · View at Google Scholar · View at Scopus
  6. P. K. Srivastava, D. Han, M. A. Rico-Ramirez, D. Al-Shrafany, and T. Islam, “Data Fusion techniques for improving soil moisture deficit using SMOS satellite and WRF-NOAH land surface model,” Water Resources Management, vol. 27, no. 15, pp. 5069–5087, 2013. View at Publisher · View at Google Scholar · View at Scopus
  7. P. K. Srivastava, D. Han, M. A. Rico Ramirez, and T. Islam, “Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate,” Journal of Hydrology, vol. 498, pp. 292–304, 2013. View at Publisher · View at Google Scholar · View at Scopus
  8. W. Wagner, V. Naeimi, K. Scipal, R. Jeu, and J. Martínez-Fernández, “Soil moisture from operational meteorological satellites,” Hydrogeology Journal, vol. 15, no. 1, pp. 121–131, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. N. Wanders, D. Karssenberg, A. De Roo, S. M. De Jong, and M. F. P. Bierkens, “The suitability of remotely sensed soil moisture for improving operational flood forecasting,” Hydrology and Earth System Sciences, vol. 18, no. 6, pp. 2343–2357, 2014. View at Publisher · View at Google Scholar · View at Scopus
  10. N. Wanders, D. Karssenberg, M. Bierkens et al., “Observation uncertainty of satellite soil moisture products determined with physically-based modeling,” Remote Sensing of Environment, vol. 127, pp. 341–356, 2012. View at Publisher · View at Google Scholar · View at Scopus
  11. D. Al-Shrafany, M. A. Rico-Ramirez, D. Han, and M. Bray, “Comparative assessment of soil moisture estimation from land surface model and satellite remote sensing based on catchment water balance,” Meteorological Applications, vol. 21, no. 3, pp. 521–534, 2014. View at Publisher · View at Google Scholar · View at Scopus
  12. E. T. Engman and R. J. Gurney, Remote Sensing in Hydrology, Chapman and Hall, 1991.
  13. J. P. Walker, G. R. Willgoose, and J. D. Kalma, “In situ measurement of soil moisture: a comparison of techniques,” Journal of Hydrology, vol. 293, no. 1–4, pp. 85–99, 2004. View at Publisher · View at Google Scholar · View at Scopus
  14. L. Wang and J. J. Qu, “Satellite remote sensing applications for surface soil moisture monitoring: a review,” Frontiers of Earth Science in China, vol. 3, no. 2, pp. 237–247, 2009. View at Publisher · View at Google Scholar · View at Scopus
  15. E. T. Engman and N. Chauhan, “Status of microwave soil moisture measurements with remote sensing,” Remote Sensing of Environment, vol. 51, no. 1, pp. 189–198, 1995. View at Publisher · View at Google Scholar · View at Scopus
  16. T. N. Carlson, K. Dodd Joseph, G. Benjamin Stanley, and N. Cooper James, “Satellite estimation of the surface energy balance, moisture availability and thermal inertia,” Journal of Applied Meteorology, vol. 20, no. 1, pp. 67–87, 1981. View at Publisher · View at Google Scholar
  17. T. N. Carlson, R. R. Gillies, and E. M. Perry, “A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover,” Remote Sensing Reviews, vol. 9, no. 1-2, pp. 161–173, 1994. View at Publisher · View at Google Scholar · View at Scopus
  18. P. J. Curran, “A photographic method for the recording of polarised visible light for soil surface moisture indications,” Remote Sensing of Environment, vol. 7, no. 4, pp. 305–322, 1978. View at Publisher · View at Google Scholar · View at Scopus
  19. D. Entekhabi, E. G. Njoku, P. E. O'Neill et al., “The soil moisture active passive (SMAP) mission,” Proceedings of the IEEE, vol. 98, no. 5, pp. 704–716, 2010. View at Publisher · View at Google Scholar · View at Scopus
  20. Y. H. Kerr, P. Waldteufel, J.-P. Wigneron, J. Martinuzzi, J. Font, and M. Berger, “Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission,” IEEE Transactions on Geoscience and Remote Sensing, vol. 39, no. 8, pp. 1729–1735, 2001. View at Publisher · View at Google Scholar · View at Scopus
  21. R. H. Reichle, R. D. Koster, P. Liu, S. P. P. Mahanama, E. G. Njoku, and M. Owe, “Comparison and assimilation of global soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E) and the Scanning Multichannel Microwave Radiometer (SMMR),” Journal of Geophysical Research: Atmospheres (1984–2012), vol. 112, no. 9, 2007. View at Publisher · View at Google Scholar
  22. E. G. Njoku, T. J. Jackson, V. Lakshmi, T. K. Chan, and S. V. Nghiem, “Soil moisture retrieval from AMSR-E,” IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 2, pp. 215–229, 2003. View at Publisher · View at Google Scholar · View at Scopus
  23. E. G. Njoku and S. K. Chan, “Vegetation and surface roughness effects on AMSR-E land observations,” Remote Sensing of Environment, vol. 100, no. 2, pp. 190–199, 2006. View at Publisher · View at Google Scholar · View at Scopus
  24. T. Lacava, P. Matgen, L. Brocca et al., “A first assessment of the SMOS soil moisture product with in situ and modeled data in Italy and Luxembourg,” IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 5, pp. 1612–1622, 2012. View at Publisher · View at Google Scholar · View at Scopus
  25. K. Rötzer, C. Montzka, H. Bogena et al., “Catchment scale validation of SMOS and ASCAT soil moisture products using hydrological modeling and temporal stability analysis,” Journal of Hydrology, vol. 519, pp. 934–946, 2014. View at Publisher · View at Google Scholar · View at Scopus
  26. L. Zhuo, Q. Dai, and D. Han, “Evaluation of SMOS soil moisture retrievals over the central United States for hydro-meteorological application,” Physics and Chemistry of the Earth, vol. 83-84, pp. 146–155, 2015. View at Publisher · View at Google Scholar · View at Scopus
  27. L. Zhuo, Q. Dai, T. Islam, and D. Han, “Error distribution modelling of satellite soil moisture measurements for hydrological applications,” Hydrological Processes, vol. 30, no. 13, pp. 2223–2236, 2016. View at Publisher · View at Google Scholar · View at Scopus
  28. L. Zhuo and D. Han, “Could operational hydrological models be made compatible with satellite soil moisture observations?” Hydrological Processes, vol. 30, no. 10, pp. 1637–1648, 2016. View at Publisher · View at Google Scholar · View at Scopus
  29. M. C. Peel, B. L. Finlayson, and T. A. McMahon, “Updated world map of the Köppen-Geiger climate classification,” Hydrology and Earth System Sciences, vol. 11, no. 5, pp. 1633–1644, 2007. View at Publisher · View at Google Scholar · View at Scopus
  30. E. Bartholomé and A. S. Belward, “GLC2000: a new approach to global land cover mapping from earth observation data,” International Journal of Remote Sensing, vol. 26, no. 9, pp. 1959–1977, 2005. View at Publisher · View at Google Scholar · View at Scopus
  31. M. Hansen, R. DeFries, J. R. G. Townshend, and R. Sohlberg, “UMD global land cover classification,” in 1 Kilometer, pp. 1981–1994, Department of Geography, University of Maryland, College Park, Md, USA, 1998. View at Google Scholar
  32. R. W. Webb, C. E. Rosenzweig, and E. R. Levine, Global Soil Texture and Derived Water-Holding Capacities (Webb et al.). Data Set, Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tenn, USA, 2000, http://www.daac.ornl.gov.
  33. Q. Duan, J. Schaake, V. Andréassian et al., “Model Parameter Estimation Experiment (MOPEX): an overview of science strategy and major results from the second and third workshops,” Journal of Hydrology, vol. 320, no. 1-2, pp. 3–17, 2006. View at Publisher · View at Google Scholar · View at Scopus
  34. K. E. Mitchell, D. Lohmann, P. R. Houser et al., “The multi-institution North American Land Data Assimilation System (NLDAS): utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system,” Journal of Geophysical Research D: Atmospheres, vol. 109, no. D7, 2004. View at Google Scholar · View at Scopus
  35. NCDC, NOAA National Climatic Data Center, 2015, http://www.ncdc.noaa.gov/.
  36. Y. H. Kerr, P. Waldteufel, J.-P. Wigneron et al., “The SMOS mission: new tool for monitoring key elements ofthe global water cycle,” Proceedings of the IEEE, vol. 98, no. 5, pp. 666–687, 2010. View at Publisher · View at Google Scholar · View at Scopus
  37. Y. H. Kerr, P. Waldteufel, P. Richaume et al., “The SMOS soil moisture retrieval algorithm,” IEEE Transactions on Geoscience and Remote Sensing, vol. 50, no. 5, pp. 1384–1403, 2012. View at Publisher · View at Google Scholar · View at Scopus
  38. BEC-SMOS, “SMOS-BEC ocean and land products description,” 2016, https://cp34-bec.cmima.csic.es/doc/BEC-SMOS-0001-PD.pdf.
  39. E. Jacquette, A. Al Bitar, A. Mialon et al., “SMOS CATDS level 3 global products over land,” in Proceedings of the Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, Toulouse, France, September 2010. View at Publisher · View at Google Scholar · View at Scopus
  40. A. Al-Yaari, J.-P. Wigneron, A. Ducharne et al., “Global-scale evaluation of two satellite-based passive microwave soil moisture datasets (SMOS and AMSR-E) with respect to Land Data Assimilation System estimates,” Remote Sensing of Environment, vol. 149, pp. 181–195, 2014. View at Publisher · View at Google Scholar · View at Scopus
  41. T. J. Jackson, “Profile soil moisture from surface measurements,” Journal of the Irrigation and Drainage Division, American Society of Civil Engineers, vol. 106, no. 2, pp. 81–92, 1980. View at Google Scholar · View at Scopus
  42. C. S. Draper, J. P. Walker, P. J. Steinle, R. A. M. de Jeu, and T. R. H. Holmes, “An evaluation of AMSR-E derived soil moisture over Australia,” Remote Sensing of Environment, vol. 113, no. 4, pp. 703–710, 2009. View at Publisher · View at Google Scholar · View at Scopus
  43. E. Cho, M. Choi, and W. Wagner, “An assessment of remotely sensed surface and root zone soil moisture through active and passive sensors in northeast Asia,” Remote Sensing of Environment, vol. 160, pp. 166–179, 2015. View at Publisher · View at Google Scholar · View at Scopus
  44. C. Rüdiger, J.-C. Calvet, C. Gruhier, T. R. H. Holmes, R. A. M. de Jeu, and W. Wagner, “An intercomparison of ERS-Scat and AMSR-E soil moisture observations with model simulations over France,” Journal of Hydrometeorology, vol. 10, no. 2, pp. 431–447, 2009. View at Publisher · View at Google Scholar · View at Scopus
  45. I. R. Calder, R. J. Harding, and P. T. W. Rosier, “An objective assessment of soil-moisture deficit models,” Journal of Hydrology, vol. 60, no. 1-4, pp. 329–355, 1983. View at Publisher · View at Google Scholar · View at Scopus
  46. K. R. Rushton, V. H. M. Eilers, and R. C. Carter, “Improved soil moisture balance methodology for recharge estimation,” Journal of Hydrology, vol. 318, no. 1, pp. 379–399, 2006. View at Publisher · View at Google Scholar · View at Scopus
  47. M. H. Khan, “Xinanjiang model on bird creek catchment in USA,” Pakistan Journal of Agricultural Research, vol. 14, no. 4, pp. 373–382, 1993. View at Google Scholar
  48. Z. Ren-Jun, “The Xinanjiang model applied in China,” Journal of Hydrology, vol. 135, no. 1, pp. 371–381, 1992. View at Publisher · View at Google Scholar · View at Scopus
  49. Q. J. Wang, “The genetic algorithm and its application to calibrating conceptual rainfall‐runoff models,” Water Resources Research, vol. 27, no. 9, pp. 2467–2471, 1991. View at Publisher · View at Google Scholar · View at Scopus
  50. R.-J. Zhao, “The Xinanjiang model applied in China,” Journal of Hydrology, vol. 135, no. 1–4, pp. 371–381, 1992. View at Publisher · View at Google Scholar · View at Scopus
  51. R.-J. Zhao, X. R. Liu, and V. P. Singh, “The Xinanjiang model,” in Computer Models of Watershed Hydrology, pp. 215–232, 1995. View at Google Scholar
  52. X.-M. Song, F.-Z. Kong, C.-S. Zhan, and J.-W. Han, “Hybrid optimization rainfall-runoff simulation based on Xinanjiang model and artificial neural network,” Journal of Hydrologic Engineering, vol. 17, no. 9, pp. 1033–1041, 2012. View at Publisher · View at Google Scholar
  53. C. Yao, Z. Li, Z. Yu, and K. Zhang, “A priori parameter estimates for a distributed, grid-based Xinanjiang model using geographically based information,” Journal of Hydrology, vol. 468-469, pp. 47–62, 2012. View at Publisher · View at Google Scholar · View at Scopus
  54. L. Zhuo and D. Han, “Misrepresentation and amendment of soil moisture in conceptual hydrological modelling,” Journal of Hydrology, vol. 535, pp. 637–651, 2016. View at Publisher · View at Google Scholar · View at Scopus
  55. R.-J. Zhao, “The Xinanjiang model,” in Hydrological Forecasting Proceedings Oxford Symposium, vol. 129, pp. 351–356, IASH, 1980. View at Google Scholar
  56. J. E. Nash and J. V. Sutcliffe, “River flow forecasting through conceptual models part I—a discussion of principles,” Journal of Hydrology, vol. 10, no. 3, pp. 282–290, 1970. View at Publisher · View at Google Scholar · View at Scopus
  57. G. W. Snedecor and W. G. Cochran, Statistical Methods, Iowa State University Press, Ames, Iowa, USA, 7th edition, 1980. View at MathSciNet
  58. X. Chen, T. Yang, X. Wang, C.-Y. Xu, and Z. Yu, “Uncertainty intercomparison of different hydrological models in simulating extreme flows,” Water Resources Management, vol. 27, no. 5, pp. 1393–1409, 2013. View at Publisher · View at Google Scholar · View at Scopus
  59. L. Zhuo, D. Han, Q. Dai, T. Islam, and P. K. Srivastava, “Appraisal of NLDAS-2 multi-model simulated soil moistures for hydrological modelling,” Water Resources Management, vol. 29, no. 10, pp. 3503–3517, 2015. View at Publisher · View at Google Scholar · View at Scopus
  60. D. J. Leroux, Y. H. Kerr, E. F. Wood, A. K. Sahoo, R. Bindlish, and T. J. Jackson, “An approach to constructing a homogeneous time series of soil moisture using SMOS,” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 1, pp. 393–405, 2014. View at Publisher · View at Google Scholar · View at Scopus
  61. R. Panciera, J. P. Walker, J. D. Kalma, E. J. Kim, K. Saleh, and J.-P. Wigneron, “Evaluation of the SMOS L-MEB passive microwave soil moisture retrieval algorithm,” Remote Sensing of Environment, vol. 113, no. 2, pp. 435–444, 2009. View at Publisher · View at Google Scholar · View at Scopus
  62. W. Wagner, L. Brocca, V. Naeimi et al., “Clarifications on the "Comparison between SMOS, VUA, ASCAT, and ECMWF soil moisture products over four watersheds in US",” IEEE Transactions on Geoscience and Remote Sensing, vol. 52, no. 3, pp. 1901–1906, 2014. View at Publisher · View at Google Scholar · View at Scopus
  63. Y. Chen, K. Yang, J. Qin, L. Zhao, W. Tang, and M. Han, “Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan Plateau,” Journal of Geophysical Research Atmospheres, vol. 118, no. 10, pp. 4466–4475, 2013. View at Publisher · View at Google Scholar · View at Scopus
  64. Y. H. Kerr, “Soil moisture from space: where are we?” Hydrogeology Journal, vol. 15, no. 1, pp. 117–120, 2007. View at Publisher · View at Google Scholar · View at Scopus
  65. T. Schmugge, Soil Moisture Sensing with Microwave Radiometers, LARS Symposia, 1980.
  66. X. Wang, H. Xie, H. Guan, and X. Zhou, “Different responses of MODIS-derived NDVI to root-zone soil moisture in semi-arid and humid regions,” Journal of Hydrology, vol. 340, no. 1-2, pp. 12–24, 2007. View at Publisher · View at Google Scholar · View at Scopus
  67. G. Wahba and J. Wendelberger, “Some new mathematical methods for variational objective analysis using splines and cross validation,” Monthly Weather Review, vol. 108, no. 8, pp. 1122–1143, 1980. View at Publisher · View at Google Scholar
  68. S. Louvet, T. Pellarin, A. Al Bitar et al., “SMOS soil moisture product evaluation over West-Africa from local to regional scale,” Remote Sensing of Environment, vol. 156, pp. 383–394, 2015. View at Publisher · View at Google Scholar · View at Scopus
  69. R. Rahmoune, P. Ferrazzoli, Y. H. Kerr, and P. Richaume, “SMOS level 2 retrieval algorithm over forests: description and generation of global maps,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 3, pp. 1430–1439, 2013. View at Publisher · View at Google Scholar · View at Scopus
  70. M. Pan, A. K. Sahoo, E. F. Wood, A. Al Bitar, D. Leroux, and Y. H. Kerr, “An initial assessment of SMOS derived soil moisture over the continental United States,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, no. 5, pp. 1448–1457, 2012. View at Publisher · View at Google Scholar · View at Scopus
  71. M. Piles, A. Camps, M. Vall-Llossera et al., “Downscaling SMOS-derived soil moisture using MODIS visible/infrared data,” IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 9, pp. 3156–3166, 2011. View at Publisher · View at Google Scholar · View at Scopus
  72. D. Han and W. Z. W. Jaafar, “Model structure exploration for index flood regionalization,” Hydrological Processes, vol. 27, no. 20, pp. 2903–2917, 2013. View at Publisher · View at Google Scholar · View at Scopus
  73. W. Z. W. Jaafar, J. Liu, and D. Han, “Input variable selection for median flood regionalization,” Water Resources Research, vol. 47, no. 7, Article ID W07503, 2011. View at Publisher · View at Google Scholar · View at Scopus