This paper by the Challenge Programme for Water and Food (CPWF) presents a simplified approach to combine remote sensing, census and weather data to analyze basin rice and wheat water productivity (WP) in Indo-Gangetic river basin, South Asia. It presents an innovative approach to combine meteorological data, ground survey, national census with remotely sensed imagery to assess water use, yield, and finally crop water productivity for the Indo-Gangetic rice-wheat cropping system in South Asia.
The methodology adopted in this study involves three steps: crop dominance map to determine major rice-wheat cultivation extent; crop productivity map of rice and wheat yield at pixel scale; ET map to calculate crop consumptive water use. The water productivity is finally produced by dividing crop productivity map by ET map.
The study notes the following -
- Basin water productivity assessment is of huge significance for better regional water and land management. Proper understanding on the magnitude of WP, the variations, and the scope for improvement is essential in achieving sustainable development to ensure food security. The methods and results presented in this paper aimed at addressing this issue.
- The yield, consumptive use and water productivity of the predominant crops, rice and wheat, in IGB are determined in a simplified approach by combining census, remote sensing, weather, and field survey data.
- The interpolation of yield data from district-wise statistical values to pixelwise through NDVI bridges publicly accepted official figures and advanced remote sensing technology.
- An important input to this yield estimation method is crop map. Precise crop type map will make the result more accurate. A map that distinguishes crop varieties will even make it possible to map yield according to each crop variety, which could significantly improve model accuracy.
- The simplified surface energy balance model is another effort to bring simplicity to crop water use studies. It takes ETo calculated from conventional approach, e.g., P-M equation, Hargreaves, using easily accessible data, and multiplies with crop coefficient to calculate potential ET, which is then extrapolated to large area based on land surface temperature distribution.
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