Growing Environment Characterization of Rice and Yield Prediction Using Time Composited Noaa Avhrr Optical and Thermal Data
نویسندگان
چکیده
Relative (actual / potential) evapotranspiration (RET) was derived using ten-day composite NOAA PAL datasets (8km x 8km spatial resolution) over Indian landmass and an operational energy balance algorithm for five agricultural years (June-May) between 1996 to 2001. This was used to characterize ‘Kharif’ (June-October) rice growing environment and its yield prediction in rainfed conditions. Inverse correlation (r = 0.6 to 0.75) was found between RET and Keech-Byram meteorological drought index (KBDI) only in rainfed rice growing regions but least correlation (r = 0.4) was found in irrigated rice growing region. Substantial reduction in RET was also found in a sub-normal (2000) than normal (1999) monsoon season for rainfed rice growing regions only. RET based crop response factor (Ky), averaged from three intermediate years (1997, 1998, 1999) for five different durations within growing period, varied between 0.9 to 1.4. The RET based yield prediction at district level for Kharif 1996 and 2000 in Madhya Pradesh state produced root mean square (RMS) error in the order of 34.4 to 47.5 percent of observed mean. The sources of errors suggest the use of diurnal observations from geostationary sensors at relatively finer spatial resolution and crop simulation model at potential level for better yield prediction.
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