Volume 3 Issue 4
Dec.  2010
Turn off MathJax
Article Contents
Huang-he GU, Zhong-bo YU, Chuan-guo YANG, Qin JU, Bao-hong LU, Chuan LIANG. 2010: Study on the large scale hydrologic simulation using multi-satellite precipitation. Water Science and Engineering, 3(4): 418-430. doi: 10.3882/j.issn.1674-2370.2010.04.005
Citation: Huang-he GU, Zhong-bo YU, Chuan-guo YANG, Qin JU, Bao-hong LU, Chuan LIANG. 2010: Study on the large scale hydrologic simulation using multi-satellite precipitation. Water Science and Engineering, 3(4): 418-430. doi: 10.3882/j.issn.1674-2370.2010.04.005

Study on the large scale hydrologic simulation using multi-satellite precipitation

doi: 10.3882/j.issn.1674-2370.2010.04.005
Funds:  Major Science and Technology Program for Water Pollution Control and Treatment in China;Major Science and Technology Program for Water Pollution Control and Treatment in China;Major Science and Technology Program for Water Pollution Control and Treatment in China;Major Science and Technology Program for Water Pollution Control and Treatment in China
  • Received Date: 2010-09-10
  • Rev Recd Date: 2010-10-27
  • High-quality rainfall information is critical for accurate simulation of runoff and the water cycle process on the land surface. In situ monitoring of precipitation has a very limited usefulness on the regional and global scale because of the high spatial and temporal variability of precipitation. It is unlikely to improve rainfall station network and rainfall radar network in short term in all regions. The inaccuracy of rainfall in some areas with sparse rainfall stations is bound to bring great uncertainty into the runoff and water cycle process simulation. On the way to overcome these problems, microwave remote sensing observations are appropriate for retrieving the spatial and temporal precipitation coverage because of the global and frequent availability. With the development of the satellite radar technology, TRMM precipitation data get more and more attention by meteorologists and hydrologists because of its high temporal (3 hours) and spatial (0.25°×0.25°) resolution. For distributed hydrological model, the distributed input data is the basic condition for hydrological simulation. This paper addresses the question of whether remotely sensed precipitation estimates over a catchment can be used to improve distributed hydrological model water balance computations. The TRMM (Tropical Rainfall Measuring Mission) precipitation product was introduced into the hydrological cycle simulation for Yangtze basin, in south China. A tool was developed to interpolate the observations into the same spatial and temporal resolution with TRMM data and then evaluate the precision of TRMM data from 1998 to 2006. It shows that TRMM rainfall in the moderate-intensity with high accuracy, but low-intensity and heavy-intensity rainfall with low fidelity. So the integrated application of TRMM data and ground observations was proposed to the watershed hydrology process simulation and achieved good results.


  • loading
  • Anagnostou, E. N., Krajewski, W. F., and Smith, J. 1999. Uncertainty quantification of mean-areal radar-rainfall estimates. Journal of Atmospheric and Oceanic Technology, 2(16), 206-215. [doi: 10.1175/1520-0426(1999)016<0206:UQOMAR>2.0.CO;2]
    Arkin, P., and Ardanuy, P. 1989. Estimating climatic-scale precipitation from space: A review. Journal of Climate, 2(11), 1229-1238. [doi: 10.1175/1520-0442(1989)002<1229:ECSPFS>2.0.CO;2]
    Boi, P., Marrocu, M., and Giachetti, A. 2004. Rainfall estimation from infrared data using an improved version of the auto-estimator technique. International Journal of Remote Sensing, 25(21), 4657-4673. [doi: 10.1080/0143116042000192312] 
    Brown, J. E. M. 2006. An analysis of the performance of hybrid infrared and microwave satellite precipitation algorithms over India and adjacent regions. Remote Sensing of Environment, 101(1), 63-81. [doi: 10.1016/j.rse.2005.12.005]
    Browning, K. A. 1990. Rain, rainclouds and climate. Quarterly Journal of the Royal Meteorological Society, 116(495), 1025-1051. [doi: 10.1002/qj.49711649502]
    Bussieres, N., and Hogg, W. 1989. The objective analysis of daily rainfall by distance weighting schemes on a mesoscale grid. Atmosphere Ocean, 27(3), 521-541. [doi: 10.1080/07055900.1989.9649350]
    Chang, A. T. C., and Chiu, L. S. 1999. Nonsystematic errors of monthly oceanic rainfall derived from SSM/I. Monthly Weather Review, 127(7), 1630-1638. [doi:10.1175/1520-0493(1999)127<1630:NEOMOR>2.0. CO;2]
    Cho, H. K., and Chun, H. Y. 2008. Impacts on the TRMM data due to orbit boost in the spectral domain. Geophysical Research Letters, 35, L01403. [doi: 10.1029/2007GL032320]
    Collischonn, B., Collischonn, W., and Tucci, C. E. M. 2008. Daily hydrological modeling in the Amazon basin using TRMM rainfall estimates. Journal of Hydrology, 360(1-4), 207-216. [doi:10.1016/j.jhydrol. 2008.07.032]
    Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R. 1984. A statistical exploration of the relationships of soil moisture characteristics to the physical properties of soils. Water Resources Research, 20(6), 682-690. [doi: 10.1029/WR020i006p00682]
    Dingman, S. L. 2002. Physical Hydrology. Englewood Cliffs: Prentice-Hall, Inc.
    Dirks, K. N., Hay, J. E., Stow, C. D., and Harris, D. 1998. High-resolution studies of rainfall on Norfolk Island, Part II: Interpolation of rainfall data. Journal of Hydrology, 208 (3-4), 187-193. [doi:10.1016/S0022- 1694(98)00155-3]
    Dorman, J. L., and Sellers, P. J. 1989. A global climatology of albedo, roughness length, and stomatal resistance for atmospheric general circulation models as represented by the simple biosphere model (SiB). Journal of Applied Meteorology, 28(9), 833-855. [doi:10.1175/1520-0450(1989)028<0833:AGCOAR> 2.0.CO;2]
    Higgins, R. W., Janowiak, J. E., and Yao, Y. P. 1996. A Gridded Hourly Precipitation Data Base for the United States (1963-1993), NCEP/Climate Prediction Center Atlas 1. Washington, D.C.: National Centers for Environment Prediction.
    Huffman, G. J., Alder, R. F., Rudolf, B., Schneider, U., and Keehn, P. R. 1995. Global precipitation estimates based on a technique for combining satellite-based estimates, rain gauge analysis, and NWP model information. American Meteorological Society, 8(5), 1284-1295. [doi:10.1175/1520-0442(1995) 008<1284:GPEBOA>2.0.CO;2]
    Hughes, D. A. 2006. Comparison of satellite rainfall data with observations from gauging station networks. Journal of Hydrology, 327(3-4), 339-410. [doi: 10.1016/j.jhydrol.2005.11.041]
    Johnson, D. L., and Miller, A. C. 1997. A spatially distributed hydrologic model utilizing raster data structures. Computers and Geosciences, 23(3), 267-272. [doi: 10.1016/S0098-3004(96)00084-2]
    Kummerow, C. 1998. Beamfilling errors in passive microwave rainfall retrievals. Journal of Applied Meteorology, 37(4), 356-371. [doi: 10.1175/1520-0450(1998)037<0356:BEIPMR>2.0.CO;2]
    Kummerow, C., Barnes, W., Kozu, T., Shiue, J., and Simpson, J. 1998. The Tropical Rainfall Measuring Mission (TRMM) sensor package. Journal of Atmospheric and Oceanic Technology, 15(3), 809-817. [doi: 10.1175/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2]
    Monteith, J. L. 1981. Presidential address: Evaporation and surface temperature. Quarterly Journal of the Royal Meteorological Society, 107(451), 1-27. [doi: 10.1002/qj.49710745102]
    Nicholson, S. 2005. On the question of the “recovery” of the rains in the West African Sahel. Journal of Arid Environment, 63(3), 615-641. [doi: 10.1016/j.jaridenv.2005.03.004]
    Petty, G. W. 1995. The status of satellite-based rainfall estimation over land. Remote Sensing and Environment, 51, 125-137. [doi: 10.1016/0034-4257(94)00070-4]
    Pollard, D., and Thompson, S. L. 1995. Use of a land-surface-transfer scheme (LSX) in a global climate model: The response to doubling stomatal resistance. Global and Planetary Change, 10(1-4), 129-161. [doi: 10.1016/0921-8181(94)00023-7]
    Simpson, J., Adler, R. F., and North, G. R. 1988. A proposed Tropical Rainfall Measuring Mission (TRMM) satellite. Bulletin of the American Meteorological Society, 69(3), 278-295. [doi:10.1175/1520-0477 (1988)069<0278:APTRMM>2.0.CO;2]
    Smith, E., Asrar, G., Furuhama, Y., Ginati, A., Kummerow, C., Levizzani, V., Mugnai, A., Nakamura, K., Adler, R. F., Chou, M. D., Casse, V., Cleave, M., Debois, M., and Durning, J. F., et al. 2007. International global precipitation measurement (GPM) program and mission: An overview. Levizzani, V., Bauer, P., and Turk, F. J., eds., Measuring Precipitation from Space: EURAINSAT and the Future, 611-653. Springer. [doi: 10.1007/978-1-4020-5835-6_48]
    Tabios, G. Q., and Salas, J. D. 1985. A comparative analysis of techniques for spatial interpolation of precipitation. Journal of the American Water Resources Association, 21(3), 365-380. [doi: 10.1111/j.175 2-1688.1985.tb00147.x]
    Thompson, S. L., and Pollard, D. 1997. Greenland and Antarctica mass balances for present and doubled atmospheric CO2 from the GENESIS version 2 global climate model. Journal of Climate, 10(5), 871-900. [doi: 10.1175/1520-0442(1997)010<0871:GAAMBF>2.0.CO;2]
    Todd, M. C., Kidd, C., Kniveton, D., and Bellerby, T. J.2001. A combined satellite infrared and passive microwave techniques for estimation of small-scale rainfall. Journal of Atmospheric and Oceanic Technology,18(5), 742-755. [doi: 10.1175/1520-0469(2001)058<0742:ACSIAP>2.0.CO;2]
    Webb, R. W., Rosenzweig, C. E., and Levine, E. R. 2000. Global Soil Texture and Derived Water-Holding Capacities. Oak Ridge: Oak Ridge National Laboratory Distributed Active Archive Center. [doi: 10.3334/ORNLDAAC/548.]
    Xie, P. P., and Arkin, P. A. 1996. Analysis of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions. Journal of Climate, 9(4), 840-858. [doi:10.1175/ 1520-0442(1996)009<0840:AOGMPU>2.0.CO.2]
    Yang, C. G., Yu, Z. B., Lin, Z. H., and Hao, Z. C. 2007. Method study of constructing digital watershed for large-scale distributed hydrological model. Progress of Geography, 26(1), 68-76. (in Chinese)
    Yang, C. G., Yu, Z. B., Lin, Z. H., Hao, Z. C., Wang, Z. L., and Li, M. 2009. Study on watershed hydrologic processes using TRMM satellite precipitation radar products. Advances in Water Science, 20(4), 461-466. (in Chinese). [doi: 10.3321/j.issn:1001-6791.2009.04001]
    Yilmaz, K. K., Gupta, H., Hogue, T. S., Hsu, K., Wagener, T., and Sorooshian, S. 2005. Evaluating the utility of satellite-based precipitation estimates for runoff prediction in ungauged basins. International Symposium on Regional Hydrological Impacts of Climatic Variability and Change with an Emphasis on Less Developed Countries, Regional Hydrological Impacts of Climate Change: Impact Assessment and Decision Making (Vol. 295), 273-282. Wallingford: International Association of Hydrological Sciences.
    Yu, Z., and Schwartz, F. W. 1995. A blueprint for a basin-scale hydrologic model. Cleveland, T. G., ed., Advances in the Development and Use of Models in Water Resources. Herndon: American Water Resources Association.
    Yu, Z., and Schwartz, F. W. 1998. Application of integrated basin-scale hydrologic model to simulate surface water and ground-water interactions in Big Darby Creek Watershed, Ohio. Journal of the American Water Resources Association,34(2), 409-425. [doi: 10.1111/j.1752-1688.1998.tb04145.x]
    Yu, Z., Lakhtakia, M. N., and Barron, E. J. 1999a. Modeling the river-basin response to single-storm events simulated by a mesoscale meteorological model at various resolutions. Journal of Geophysical Research, 104(D16), 19675-19690. [doi: 10.1029/1999JD900339]
    Yu, Z., Lakhtakia, M. N., Yarnal, B., White, R. A., Miller, D. A., Frakes, B., Barron, E. J., Duffy, C., and Schwartz, F. W. 1999b. Simulating the river-basin response to atmospheric forcing by linking a mesoscale meteorological model and a hydrological model system. Journal of Hydrology, 218(1-2), 72-91. [doi:10.1016 /S0022-1694(99)00022-0]
    Yu, Z., and Schwartz, F. W. 1999. Automated calibration applied to watershed-scale flow simulations. Hydrological Processes, 13(2), 191-209. [doi:10.1002/(SICI)1099-1085(19990215)13:2<191::AID- HYP706>3.0.CO;2-N]
    Yu, Z., White, R. A., Guo, Y., Voortman, J., Kolb, P. J., Miller, D. A., and Miller, A. 2001. Stormflow simulation using a geographical information system with a distributed approach. Journal of American Water Resources Association, 37(4), 957-971. [doi: 10.1111/j.1752-1688.2001.tb05525.x]
    Yu, Z., Barron, E. J., Yarnal, B., Lakhtakia, M. N., White, R. A., Pollard, D., and Miller, D. A. 2002. Evaluation of basin-scale hydrologic response to a multi-storm simulation. Journal of Hydrology, 257(1-4), 212-225. [doi: 10.1016/S0022-1694(01)00538-8]
    Yu, Z., Pollard, D., and Cheng, L. 2006. On continental-scale hydrologic simulations with a coupled hydrologic model. Journal of Hydrology, 331(1-2), 110-124. [doi: 10.1016/j.jhydrol.2006.05.021]
    Yu, Z. 2008. The Principle and Application of Distributed Hydrological Model. Beijing: Science Press. (in Chinese)
  • 加载中


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (3995) PDF downloads(4358) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint