Integrating remote sensing, census and weather data for an assessment of rice yield, water consumption and water productivity in the Indo-Gangetic river basin
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Cai, Xueliang; Sharma, Bharat R. 2010. Integrating remote sensing, census and weather data for an assessment of rice yield, water consumption and water productivity in the Indo-Gangetic river basin. Agricultural Water Management, 97(2):309-316. doi: http://dx.doi.org/10.1016/j.agwat.2009.09.021
Permanent link to this item: http://hdl.handle.net/10568/40487
Crop consumptive water use and productivity are key elements to understand basin watermanagement performance. This article presents a simplified approach tomap rice (Oryza sativa L.) water consumption, yield, and water productivity (WP) in the Indo-Gangetic Basin (IGB) by combining remotely sensed imagery, national census and meteorological data. The statistical rice cropped area and production data were synthesized to calculate district-level land productivity, which is then further extrapolated to pixel-level values using MODIS NDVI product based on a crop dominance map. The water consumption by actual evapotranspiration is estimated with Simplified Surface Energy Balance (SSEB) model taking meteorological data and MODIS land surface temperature products as inputs. WP maps are then generated by dividing the rice productivity map with the seasonal actual evapotranspiration (ET) map. The average rice yields for Pakistan, India, Nepal and Bangladesh in the basin are 2.60, 2.53, 3.54 and 2.75 tons/ha, respectively. The average rice ET is 416 mm, accounting for only 68.2% of potential ET. The average WP of rice is 0.74 kg/m3. The WP generally varies with the trends of yield variation. A comparative analysis of ET, yield, rainfall and WP maps indicates greater scope for improvement of the downstream areas of the Ganges basin. The method proposed is simple, with satisfactory accuracy, and can be easily applied elsewhere.
SubjectsRICE; CROP YIELD; MAPPING; EVAPOTRANSPIRATION; WATER PRODUCTIVITY; WATER USE; MODELS; REMOTE SENSING; RIVER BASINS;
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