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    Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin

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    Authors
    Xueliang Cai
    Sharma, Bharat R.
    Date Issued
    2009-11
    Date Online
    2009-12
    Language
    en
    Type
    Journal Article
    Accessibility
    Limited Access
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    Citation
    Cai, Xueliang; Sharma, Bharat R. 2009. Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin. Science in China Series E: Technological Sciences, 52(11):3300-3308. doi: http://dx.doi.org/10.1007/s11431-009-0346-3
    Permanent link to cite or share this item: https://hdl.handle.net/10568/40586
    DOI: https://doi.org/10.1007/s11431-009-0346-3
    Abstract/Description
    Understanding of crop water productivity (WP) over large scale, e.g., river basin, has significant impli-cations for sustainable basin development planning. This paper presents a simplified approach to combine remote sensing, census and weather data to analyze basin rice and wheat WP in In-do-Gangetic River Basin, South Asia. A crop dominance map is synthesized from ground truth data and three existing LULC maps. National statistics on crop area and production information are collected and the yield is interpolated to pixel level using moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI). Crop evapotranspiration is mapped using simplified surface energy balance (SSEB) model with MODIS land surface temperature products and meteorological data collected from 56 weather stations. The average ET by rice and wheat is 368 mm and 210 mm respectively, accounting for only 69% and 65% of potential ET, and 67% and 338% of rain-fall of the crop growth period measured from Tropical Rainfall Measurement Mission (TRMM). Average WP for rice and wheat is 0.84 and 1.36 kg/m3 respectively. WP variability generally follows the same trend as shown by crop yield disregarding climate and topography changes. Sum of rice-wheat water productivity, however, exhibits different variability leading to better understanding of irrigation water management as wheat heavily relies on irrigation. Causes for variations and scope for improvement are also analyzed.
    AGROVOC Keywords
    remote sensing; water productivity; cropping systems; rice; wheat; evapotranspiration; models; mapping; river basins
    Countries
    India; Pakistan; Bangladesh; Nepal; China; Afghanistan
    Regions
    Southern Asia; Eastern Asia
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    • IWMI Journal Articles [2546]

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