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      Water Productivity Mapping (WPM) Using Landsat ETM+ Data for the Irrigated Croplands of the Syrdarya River Basin in Central Asia

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          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 (m 3/ha) maps (WUMs) (or actual seasonal evapotranspiration or actual ET) developed through Simplified Surface Energy Balance (SSEB) model; and (3) water productivity (kg/m 3) 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/m 3) in water productivity of cotton fields with overwhelming proportion (87%) of the area having WP less than 0.30 kg/m 3, 11% of the area having WP in range of 0.30-0.36 kg/m 3, and only 2% of the area with WP greater than 0.36 kg/m 3. 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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              Increasing crop productivity when water is scarce—from breeding to field management


                Author and article information

                Sensors (Basel)
                Sensors (Basel)
                Sensors (Basel, Switzerland)
                Molecular Diversity Preservation International (MDPI)
                December 2008
                10 December 2008
                : 8
                : 12
                : 8156-8180
                [1 ] International Water Management Institute (IWMI), 127, Sunil Mawatha, Colombo, Sri Lanka
                [2 ] U.S. Geological Survey, 2255 N. Gemini Drive, Flagstaff, AZ 86001, USA
                [3 ] University of Oklahoma, 101 David L. Boren Blvd, Norman, Oklahoma 73019, USA
                [4 ] United Nations Joint Logistics Center, Juba, Sudan
                [5 ] Institute of Agricultural Engineering, ARO
                [6 ] University of Soil Sciences, ARO, Volcani center, Bet Dagan 50250, Israel
                [7 ] Department of Geography, P.O. B. 39040, Tel-Aviv University 69989, Israel
                [8 ] Central Asian Scientific Research Institute of Irrigation, Block 11, Karasu-4, Tashkent, 700187, Uzbekistan
                [9 ] Scientific Research Institute for Growing Cotton, Uzbekistan, Tashkent
                [10 ] International Water Management Institute (IWMI), Apt. 123, House 6, Murtazaeva Street, Tashkent 700000, Uzbekistan
                Author notes
                [* ] Authors to whom correspondence should be addressed; E-mails: a.platonov@ 123456cgiar.org ; pthenkabail@ 123456usgs.gov ; Tel.: +998-71-2370445 (Uzbekistan) or +1-928-556-7221 (USA).
                © 2008 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).



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