Satellite methodologies for rationalising crop water requirements in vulnerable agroecosystems. (2nd August 2019)

• Record Type: Journal Article
• Authors: Dalezios, Nicolas R.; Blanta, Anna; Loukas, Athanasios; Spiliotopoulos, Marios; Faraslis, Ioannis N.; Dercas, Nicholas
• Is Part Of: International journal of sustainable agricultural management and informatics. Volume 5:Number 1(2019)
• Page Start: 37
• Page End: 58
• Publication Date: 2019-08-02
• Subjects: crop evapotranspiration -- remote sensing -- vulnerable agriculture -- crop water needs; Sustainable agriculture -- Management -- Periodicals; Sustainable agriculture -- Data processing -- Periodicals; Agricultural productivity -- Management -- Periodicals; Agricultural productivity -- Data processing -- Periodicals; Agricultural resources -- Data processing -- Periodicals; Agricultural systems -- Management -- Periodicals; Agricultural systems -- Data processing -- Periodicals; 338.1
• Languages: English
• ISSNs: 2054-5819

Abstract

Vulnerability in agriculture is influenced, among others, by extended periods of water shortage in regions exposed to droughts. In order to assess irrigation water requirements, remote sensing (RS) techniques are integrated for the estimation and monitoring of cotton crop evapotranspiration ET c . Cotton fields in a small agricultural sub-catchment in Thessaly, Central Greece, are used as an experimental site. Daily meteorological data and weekly field data are recorded throughout seven (2004-2010) growing seasons for the computation of reference evapotranspiration ET o, crop coefficient K c and cotton crop ET c based on conventional data, which are compared during the corresponding period with the satellite-based method (Landsat TM) for the estimation of cotton crop coefficient K c and cotton crop ET c, which also delineates its spatiotemporal variability. The methodology is applied for monitoring K c and ET c during growing season in the selected sub-catchment. Several error statistics are used showing very good agreement with ground-truth observations.