Estimation of relative evapotranspiration from NOAA PAL to derive growth characteristics in India.

Autor: Sarkar, Chaitali, Bhattacharya, BimalK., Gadgil, Alaka, Mallick, Kanishka, Patel, N. K., Parihar, J. S.
Předmět:
Zdroj: International Journal of Remote Sensing; Jun2008, Vol. 29 Issue 11, p3271-3293, 23p, 1 Diagram, 4 Charts, 7 Graphs
Abstrakt: Clear-sky dekadal relative evapotranspiration (RET) was derived using the surface energy-balance approach applied to 10-day composite NOAA PAL (8 km×8 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 (June-April): 1996-1997, 1997-1998, 1998-1999, 1999-2000, and 2000-2001. 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 agro-ecosystems 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 land-surface 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. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index