Water productivity mapping (WPM) using Landsat ETM+ data for the irrigated croplands of the Syrdarya River Basin in Central Asia

The overarching goal of this paper was to espouse methods and protocols for water productivity mapping (WPM) using high spatial resolution Landsat remote sensing data. In a world where land and water for agriculture are becoming increasingly scarce, growing "more crop per drop? (increasing water pro...

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Autores principales: Platonov, Alexander, Thenkabail, Prasad S., Biradar, Chandrashekhar M., Xueliang Cai, Gumma, Murali K., Dheeravath, Venkateswarlu, Cohen, Y., Alchanatis, V., Goldshlager, N., Ben-Dor, E., Vithanage, Jagath, Manthrithilake, Herath, Kendjabaev, S., Isaev, S.
Formato: Journal Article
Lenguaje:Inglés
Publicado: 2008
Materias:
Acceso en línea:https://hdl.handle.net/10568/40765
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author Platonov, Alexander
Thenkabail, Prasad S.
Biradar, Chandrashekhar M.
Xueliang Cai
Gumma, Murali K.
Dheeravath, Venkateswarlu
Cohen, Y.
Alchanatis, V.
Goldshlager, N.
Ben-Dor, E.
Vithanage, Jagath
Manthrithilake, Herath
Kendjabaev, S.
Isaev, S.
author_browse Alchanatis, V.
Ben-Dor, E.
Biradar, Chandrashekhar M.
Cohen, Y.
Dheeravath, Venkateswarlu
Goldshlager, N.
Gumma, Murali K.
Isaev, S.
Kendjabaev, S.
Manthrithilake, Herath
Platonov, Alexander
Thenkabail, Prasad S.
Vithanage, Jagath
Xueliang Cai
author_facet Platonov, Alexander
Thenkabail, Prasad S.
Biradar, Chandrashekhar M.
Xueliang Cai
Gumma, Murali K.
Dheeravath, Venkateswarlu
Cohen, Y.
Alchanatis, V.
Goldshlager, N.
Ben-Dor, E.
Vithanage, Jagath
Manthrithilake, Herath
Kendjabaev, S.
Isaev, S.
author_sort Platonov, Alexander
collection Repository of Agricultural Research Outputs (CGSpace)
description The overarching goal of this paper was to espouse methods and protocols for water productivity mapping (WPM) using high spatial resolution Landsat remote sensing data. In a world where land and water for agriculture are becoming increasingly scarce, growing "more crop per drop? (increasing water productivity) becomes crucial for food security of future generations. The study used time-series Landsat ETM+ data to produce WPMs of irrigated crops, with emphasis on cotton in the Galaba study area in the Syrdarya river basin of Central Asia. The WPM methods and protocols using remote sensing data consisted of: (1) crop productivity (ton/ha) maps (CPMs) involving crop type classification, crop yield and biophysical modeling, and extrapolating yield models to larger areas using remotely sensed data; (2) crop water use (m3/ha) maps (WUMs) (or actual seasonal evapotranspiration or actual ET) developed through Simplified Surface Energy Balance (SSEB) model; and (3) water productivity (kg/m3) maps (WPMs) produced by dividing raster layers of CPMs by WUMs. The SSEB model calculated WUMs (actual ET) by multiplying the ET fraction by reference ET. The ET fraction was determined using Landsat thermal imagery by selecting the "hot? pixels (zero ET) and "cold? pixels (maximum ET). The grass reference ET was calculated by FAO Penman-Monteith method using meteorological data. The WPMs for the Galaba study area demonstrated a wide variations (0-0.54 kg/m3) in water productivity of cotton fields with overwhelming proportion (87%) of the area having WP less than 0.30 kg/m3, 11% of the area having WP in range of 0.30-0.36 kg/m3, and only 2% of the area with WP greater than 0.36 kg/m3. These results clearly imply that there are opportunities for significant WP increases in overwhelming proportion of the existing croplands. The areas of low WP are spatially pin-pointed and can be used as focus for WP improvements through better land and water management practices.
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spelling CGSpace407652025-03-11T09:50:20Z Water productivity mapping (WPM) using Landsat ETM+ data for the irrigated croplands of the Syrdarya River Basin in Central Asia Platonov, Alexander Thenkabail, Prasad S. Biradar, Chandrashekhar M. Xueliang Cai Gumma, Murali K. Dheeravath, Venkateswarlu Cohen, Y. Alchanatis, V. Goldshlager, N. Ben-Dor, E. Vithanage, Jagath Manthrithilake, Herath Kendjabaev, S. Isaev, S. water productivity mapping remote sensing water use crops productivity crop yield models evapotranspiration irrigated farming river basins The overarching goal of this paper was to espouse methods and protocols for water productivity mapping (WPM) using high spatial resolution Landsat remote sensing data. In a world where land and water for agriculture are becoming increasingly scarce, growing "more crop per drop? (increasing water productivity) becomes crucial for food security of future generations. The study used time-series Landsat ETM+ data to produce WPMs of irrigated crops, with emphasis on cotton in the Galaba study area in the Syrdarya river basin of Central Asia. The WPM methods and protocols using remote sensing data consisted of: (1) crop productivity (ton/ha) maps (CPMs) involving crop type classification, crop yield and biophysical modeling, and extrapolating yield models to larger areas using remotely sensed data; (2) crop water use (m3/ha) maps (WUMs) (or actual seasonal evapotranspiration or actual ET) developed through Simplified Surface Energy Balance (SSEB) model; and (3) water productivity (kg/m3) maps (WPMs) produced by dividing raster layers of CPMs by WUMs. The SSEB model calculated WUMs (actual ET) by multiplying the ET fraction by reference ET. The ET fraction was determined using Landsat thermal imagery by selecting the "hot? pixels (zero ET) and "cold? pixels (maximum ET). The grass reference ET was calculated by FAO Penman-Monteith method using meteorological data. The WPMs for the Galaba study area demonstrated a wide variations (0-0.54 kg/m3) in water productivity of cotton fields with overwhelming proportion (87%) of the area having WP less than 0.30 kg/m3, 11% of the area having WP in range of 0.30-0.36 kg/m3, and only 2% of the area with WP greater than 0.36 kg/m3. These results clearly imply that there are opportunities for significant WP increases in overwhelming proportion of the existing croplands. The areas of low WP are spatially pin-pointed and can be used as focus for WP improvements through better land and water management practices. 2008 2014-06-13T14:48:23Z 2014-06-13T14:48:23Z Journal Article https://hdl.handle.net/10568/40765 en Limited Access Platonov, Alexander; Thenkabail, Prasad; Biradar, Chandrashekhar M.; Cai, Xueliang; Gumma, Murali Krishna; Dheeravath, Venkateswarlu; Cohen, Y.; Alchanatis, V.; Goldshlager, N.; Ben-Dor, E.; Vithanage, Jagath; Manthrithilake, Herath; Kendjabaev, S.; Isaev, S. 2008. Water productivity mapping (WPM) using Landsat ETM+ data for the irrigated croplands of the Syrdarya River Basin in Central Asia. Sensors, 8:8156-8180.
spellingShingle water productivity
mapping
remote sensing
water use
crops
productivity
crop yield
models
evapotranspiration
irrigated farming
river basins
Platonov, Alexander
Thenkabail, Prasad S.
Biradar, Chandrashekhar M.
Xueliang Cai
Gumma, Murali K.
Dheeravath, Venkateswarlu
Cohen, Y.
Alchanatis, V.
Goldshlager, N.
Ben-Dor, E.
Vithanage, Jagath
Manthrithilake, Herath
Kendjabaev, S.
Isaev, S.
Water productivity mapping (WPM) using Landsat ETM+ data for the irrigated croplands of the Syrdarya River Basin in Central Asia
title Water productivity mapping (WPM) using Landsat ETM+ data for the irrigated croplands of the Syrdarya River Basin in Central Asia
title_full Water productivity mapping (WPM) using Landsat ETM+ data for the irrigated croplands of the Syrdarya River Basin in Central Asia
title_fullStr Water productivity mapping (WPM) using Landsat ETM+ data for the irrigated croplands of the Syrdarya River Basin in Central Asia
title_full_unstemmed Water productivity mapping (WPM) using Landsat ETM+ data for the irrigated croplands of the Syrdarya River Basin in Central Asia
title_short Water productivity mapping (WPM) using Landsat ETM+ data for the irrigated croplands of the Syrdarya River Basin in Central Asia
title_sort water productivity mapping wpm using landsat etm data for the irrigated croplands of the syrdarya river basin in central asia
topic water productivity
mapping
remote sensing
water use
crops
productivity
crop yield
models
evapotranspiration
irrigated farming
river basins
url https://hdl.handle.net/10568/40765
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