ZHU Mingcheng ZHAN Chesheng WANG Huixiao. Regional evapotranspiration estimation by a two layer model based on remote sensing in Baojixia irrigation area[J]. Journal of Beijing Normal University(Natural Science), 2017, 53(2): 194-200. DOI: 10.16360/j.cnki.jbnuns.2017.02.014
Citation: ZHU Mingcheng ZHAN Chesheng WANG Huixiao. Regional evapotranspiration estimation by a two layer model based on remote sensing in Baojixia irrigation area[J]. Journal of Beijing Normal University(Natural Science), 2017, 53(2): 194-200. DOI: 10.16360/j.cnki.jbnuns.2017.02.014

Regional evapotranspiration estimation by a two layer model based on remote sensing in Baojixia irrigation area

  • TM data and relevant meteorological data for typical days in different seasons from 2000—2011
    in Baojixia irrigation area was used to develop land-surface evapotranspiration (ET)remote sensing retrieval
     system, and to estimate daily ET in Baojixia irrigation area.Tendencies in temporal and spatial distribution of
     ET and ET changes of different land use in representative seasonal days were analyzed. The average daily ET
     on typical days was found to be about5 .06 mm in spring,5.36mm in summer,4.24mm in autumn, and1.03
    mm in winter.A unimodal distribution seemed to dominate.Seasonal variation was found to be significant.
    Spatial distribution in different seasonal representative days showed large discrepancies. The seasonal variation
     indaily evapotranspiration characteristics wasfoundto besimilarin differentland usetypes. Actual
     evapotranspiration of the study area was calculated from Penman-Monteithe quation to compare with remote
    sensing retrieval system estimates. The correlation coefficient R2 was found to be greater than 0.9 in farmland
     and forests. Therefor ethe current system could be used for accurate estimation of evapotranspiration in
    Baojixia irrigation area.
  • loading

Catalog

    Turn off MathJax
    Article Contents

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return
    Baidu
    map