Clear-sky dekadal relative evapotranspiration (RET) was derived using the surface energy-balance approach applied to 10-day composite NOAA PAL (8 km68 km) datasets over the Indian landmass. This was further used to differentiate between growth characteristics for an irrigated intensive agriculture over a northern India state (e.g. Punjab) and a rainfed ill-posed agriculture over a central India state (e.g. Madhya Pradesh) using time-series data sets for five growing years (. The triangular scatter between RET and normalized difference vegetation index (NDVI) showed that the minimum RET increases linearly with NDVI producing a 'basal line' that represents relative canopy transpiration only. A clear distinction in scatter was found between the two contrasting agroecosystems showing a higher RET or root zone wetness in irrigated than rainfed systems. In rainfed rice-growing regions, an inverse correlation (0.6-0.75) was found between RET and the Keetch-Byram meteorological drought index (KBDI), and a substantial reduction in RET was also found in a sub-normal (2000) compared with a normal (1999) monsoon season. RET estimates were found to be most sensitive to atmospheric transmissivity followed by other landsurface radiation budget inputs, such as NDVI, LST, and albedo. Error propagation due to three surface parameters is the opposite of that for transmissivity. The maximum possible error in clear-sky NOAA PAL RET was estimated to be 12-15%. This test study would be helpful in deriving RET using optical and thermal data from a suite of current and future Indian geostationary satellite sensors for monitoring growing conditions.

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