• DocumentCode
    2705660
  • Title

    Analysis of space-time pattern in evapotranspiration and meteorological driving factors over the source region of the Yellow River

  • Author

    Deng, Shizan ; Zhang, Youjing ; Zheng, Shuqian ; Ming Cao ; Fang, Yingying

  • Author_Institution
    Dept. of Earth Sci. & Eng., Hohai Univ., Naijing, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    To analyze the space-time distribution characteristic of evapotranspiration (ET) in the source region of the Yellow River, 16-day synthetic MODIS remote sensing products data, hydrological and meteorological data from 2000 to 2009 were used to build an ET dataset with long time series by SEBAL model, and then study the correlation between ET and meteorological factors in space. The quantitative estimation of the regression model has been established on different time scales and the model and its error was tested and analysed respectively. The results demonstrate that the prediction model built for the study area can pass the significance test at 0.01 confidence level is suit for the prediction of ET in different regions and seasons.
  • Keywords
    atmospheric boundary layer; evaporation; hydrological techniques; meteorology; radiometry; regression analysis; remote sensing; rivers; transpiration; AD 2000 to 2009; China; SEBAL model; Yellow river source region; evapotranspiration space-time distribution characteristics; hydrological data; meteorological data; meteorological driving factors; prediction model; quantitative estimation; regression model; space-time pattern analysis; synthetic MODIS data products; Correlation; Meteorological factors; Meteorology; Rivers; Springs; Temperature; Time series analysis; SEBAL model; correlation analysis; driver model; evapotranspiration(ET); genetic programming; time series harmonic; time-lag effect;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2011 19th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-61284-849-5
  • Type

    conf

  • DOI
    10.1109/GeoInformatics.2011.5980684
  • Filename
    5980684