Study on estimating the evapotranspiration cover coefficient for stream flow simulation through remote sensing techniques

被引:13
|
作者
Wu, Chihda [2 ]
Cheng, Chichuan [1 ]
Lo, Hannchung [2 ]
Chen, Yeongkeung [3 ]
机构
[1] Chinese Culture Univ, Dept Landscape Architecture, Taipei, Taiwan
[2] Natl Taiwan Univ, Sch Forestry & Resource Conservat, Taipei 10764, Taiwan
[3] Ming Chuan Univ, Sch Tourism, Tao Yuan, Taiwan
关键词
Evapotranspiration cover coefficient; Remote sensing; Stream flow simulation; SEBAL model;
D O I
10.1016/j.jag.2010.03.001
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
This study focuses on using remote sensing techniques to estimate the evapotranspiration cover coefficient (CV) which is an important parameter for stream flow. The objective is to derive more accurate stream flow from the estimated CV. The study area is located in the Dan-Shuei watershed in northern Taiwan. The processes include the land-use classification using hybrid classification and four Landsat-5 TM images; the CV estimations based on remote sensing and traditional approaches; comparison of stream flow simulation according to the above two CV values. The result indicated that the study area was classified into seven land-use types with 88.3% classification accuracy. The simulated stream flow using remote sensing approach could represent more accurate hydrological characteristics than a traditional approach. Obviously integrating remote sensing technique and the SEBAL model is a useful approach to estimate the CV. The CV parameter estimated by remote sensing technique did improve the accuracy of the stream flow simulation. Therefore, the results can be extended to further studies such as forest water management. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:225 / 232
页数:8
相关论文
共 50 条
  • [1] Study on estimating the evapotranspiration cover coefficient for stream flow simulation through remote sensing techniques (vol 12, pg 225, 2010)
    Wu, Chihda
    Cheng, Chichuan
    Lo, Hannchung
    Chen, Yeongkuan
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2011, 13 (01): : 163 - 163
  • [2] Estimating land cover effects on evapotranspiration with remote sensing: a case study in Ethiopian Rift Valley
    Billi, Paolo
    Caparrini, Francesca
    HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES, 2006, 51 (04): : 655 - 670
  • [3] Estimating evapotranspiration of orange orchards using surface renewal and remote sensing techniques
    Consoli, S.
    Russo, A.
    Snyder, R.
    EARTH OBSERVATION FOR VEGETATION MONITORING AND WATER MANAGEMENT, 2006, 852 : 185 - +
  • [4] Application of SEBAL and Markov Models for Future Stream Flow Simulation Through Remote Sensing
    Wu, Chih-Da
    Cheng, Chi-Chuan
    Lo, Hann-Chung
    Chen, Yeong-Keung
    WATER RESOURCES MANAGEMENT, 2010, 24 (14) : 3773 - 3797
  • [5] Application of SEBAL and Markov Models for Future Stream Flow Simulation Through Remote Sensing
    Chih-Da Wu
    Chi-Chuan Cheng
    Hann-Chung Lo
    Yeong-Keung Chen
    Water Resources Management, 2010, 24 : 3773 - 3797
  • [6] Estimating Evapotranspiration using Remote Sensing Techniques for the Sustainable Use of Irrigation Water in Agriculture
    Hadjimitsis, Diofantos G.
    Papadavid, Giorgos
    Agapiou, Athos
    IMAGIN [E,G] EUROPE, 2010, : 166 - 173
  • [7] Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing
    Glenn, Edward P.
    Nagler, Pamela L.
    Huete, Alfredo R.
    SURVEYS IN GEOPHYSICS, 2010, 31 (06) : 531 - 555
  • [8] Estimating Evapotranspiration using Remote Sensing in the Haihe Basin
    Xiong, Jun
    Wu, Bingfang
    Zhou, Yuemin
    Li, Jing
    2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8, 2006, : 1044 - 1047
  • [9] Vegetation Index Methods for Estimating Evapotranspiration by Remote Sensing
    Edward P. Glenn
    Pamela L. Nagler
    Alfredo R. Huete
    Surveys in Geophysics, 2010, 31 : 531 - 555
  • [10] Estimating wheat evapotranspiration through remote sensing utilizing GeeSEBAL and comparing with lysimetric data
    Baboli, Neda
    Ghamarnia, Houshang
    Mavaddat, Maryam Hafezparast
    APPLIED WATER SCIENCE, 2024, 14 (09)