Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin
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-Ganget...
| Main Authors: | , |
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| Format: | Journal Article |
| Language: | Inglés |
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Springer
2009
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/24602 |
| _version_ | 1855519547401961472 |
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| author | Cai, X.L. Sharma, Bharat R. |
| author_browse | Cai, X.L. Sharma, Bharat R. |
| author_facet | Cai, X.L. Sharma, Bharat R. |
| author_sort | Cai, X.L. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| 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. |
| format | Journal Article |
| id | CGSpace24602 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2009 |
| publishDateRange | 2009 |
| publishDateSort | 2009 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace246022024-08-27T10:35:18Z Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin Cai, X.L. Sharma, Bharat R. remote sensing water productivity cropping systems rice wheat evapotranspiration models mapping river basins 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. 2009-11 2012-10-23T05:46:50Z 2012-10-23T05:46:50Z Journal Article https://hdl.handle.net/10568/24602 en Limited Access Springer Cai, X., Sharma, B. Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin. Sci. China Ser. E-Technol. Sci. 52, 3300–3308 (2009). https://doi.org/10.1007/s11431-009-0346-3 |
| spellingShingle | remote sensing water productivity cropping systems rice wheat evapotranspiration models mapping river basins Cai, X.L. Sharma, Bharat R. Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin |
| title | Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin |
| title_full | Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin |
| title_fullStr | Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin |
| title_full_unstemmed | Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin |
| title_short | Remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the Indo-Gangetic Basin |
| title_sort | remote sensing and census based assessment and scope for improvement of rice and wheat water productivity in the indo gangetic basin |
| topic | remote sensing water productivity cropping systems rice wheat evapotranspiration models mapping river basins |
| url | https://hdl.handle.net/10568/24602 |
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