Remote-sensing estimation of the water stress coefficient and comparison with drought evidence

被引:6
|
作者
Abid, Nesrine [1 ]
Bargaoui, Zoubeida [1 ]
Mannaerts, Chris M. [2 ]
机构
[1] ENIT Univ Tunis El Manar, Ecole Natl Ingenieurs Tunis, Tunis, Tunisia
[2] Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, Enschede, Netherlands
关键词
Drought; stress coefficient (K-s) actual evapotranspiration (AET); NDVI; FVC; satellite application facility (LSA SAF); crop coefficient (K-c); VEGETATION; EVAPOTRANSPIRATION; FAO-56; MODEL; SOIL; WHEAT;
D O I
10.1080/01431161.2018.1430917
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Drought assessment of croplands and sylvo-pastoral areas is crucial in semi-arid regions. Satellite remote sensing offers an opportunity for such assessment. This study presents a method of spatial and temporal estimation of drought index in Medjerda basin (23,700km(2)) using satellite data and its validation with in situ investigation of areas with crop damage realized by the ministry of agriculture. To estimate drought index, potential evapotranspiration (PET) is calculated using Penman-Monteith equation and modified FAO-56 crop coefficient (K-c) approach combined with remote-sensing data and actual evapotranspiration is derived from the Meteosat Second Generation platforms. The period of study is the 2010 water year. PET estimations show good accuracy with corrected pan evaporation observations up to 0.9. In comparison, the water stress coefficient (K-s) aggregated by land-cover type shows the coefficient of determination with the fraction of drought damage areas of 0.5 for the third decade of March and first decade of April in croplands areas and 0.8 for the second and third decades of May in croplands and sylvo-pastoral areas. This study showed that satellite data approaches could successfully be used to monitor drought in river basins in the Northern Africa and Mediterranean region.
引用
收藏
页码:4616 / 4639
页数:24
相关论文
共 50 条
  • [1] REMOTE-SENSING OF LEAF WATER-STRESS
    HUNT, ER
    COHEN, WB
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 1991, 57 (11): : 1474 - 1474
  • [2] REMOTE-SENSING HIGHLIGHTS AFRICAN DROUGHT
    MACKENZIE, D
    NEW SCIENTIST, 1984, 103 (1416) : 26 - 26
  • [3] SATELLITE REMOTE-SENSING OF DROUGHT CONDITIONS
    TUCKER, CJ
    CHOUDHURY, BJ
    REMOTE SENSING OF ENVIRONMENT, 1987, 23 (02) : 243 - 251
  • [4] MICROWAVE REMOTE-SENSING OF PLANT WATER-STRESS
    PALOSCIA, S
    PAMPALONI, P
    REMOTE SENSING OF ENVIRONMENT, 1984, 16 (03) : 249 - 255
  • [5] Remote-sensing technique for determination of the volume absorption coefficient of turbid water
    Sydor, M
    Arnone, RA
    Gould, RW
    Terrie, GE
    Ladner, SD
    Wood, CG
    APPLIED OPTICS, 1998, 37 (21): : 4944 - 4950
  • [6] CROP AREA ESTIMATION - A COMPARISON OF REMOTE-SENSING AND CENSUS METHODS
    SHUEB, S
    ATKINS, P
    GEOGRAPHY, 1991, 76 (332) : 235 - 239
  • [7] Phenotyping Peanut Drought Stress with Aerial Remote-Sensing and Crop Index Data
    Balota, Maria
    Sarkar, Sayantan
    Bennett, Rebecca S.
    Burow, Mark D.
    AGRICULTURE-BASEL, 2024, 14 (04):
  • [8] REMOTE-SENSING OF PLANT STRESS AND WATER-USE - INTRODUCTION
    HEILMAN, JL
    AGRICULTURAL WATER MANAGEMENT, 1983, 7 (1-3) : 301 - 301
  • [9] REMOTE-SENSING IN ESTIMATION OF CULTIVATED AREA
    GERMAIN, MF
    JULIEN, C
    CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 1988, 16 : 9 - 23
  • [10] Water stress coefficient determined by orbital remote sensing techniques
    Alves, Elvis da S.
    Filgueiras, Roberto
    Rodrigues, Lineu N.
    da Cunha, Fernando F.
    Aleman, Catariny C.
    REVISTA BRASILEIRA DE ENGENHARIA AGRICOLA E AMBIENTAL, 2020, 24 (12): : 847 - 853