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Evapotranspiration (ET) is vital process in land surface atmosphere research.In the present study, Surface Energy Balance Algorithm for Land,(SEBAL)for assessment of ET (for ) from LANDSAT7-ETM+ and validation with Lysimeter data set, is illustrated. It is based on the evaporative fraction concept, and it has been applied to LANDSAT7-ETM+ (30 meter resolution) data acquired over the Indian Agricultural Research Institute (IARI) agricultural farm land. The ET from SEBAL comparison with Lysimeter ET by using 4 statistical tests (Root mean square error (RMSE), Relative Root Mean Square Error (R-RMSE), Mean Absolute Error (MAE), and Normalized Root Mean Square Error (NRMSE)) and each test shows good correlation between predicted and observed ET values. Results from present study revealed that the RMSE of crop growing period was 0.51 mm d -1 for ET SEBAL i.e. ET SEBAL having good accuracy with respect to observed ET Lysimeter . Results are also Downloaded by [New York University] at 21:38 31 July 2015 2 validated by using R-RMSE test. Which also proves that ET SEBAL data is having good accuracy with respect to observed ET Lysimeter as R-RMSE of crop growing period is 0.19mm d -1 . MAE (0.19), NRMSE (0.21) and r 2 (0.91) test indicates model prediction is significant and model can be effectively use for estimation of ET from SEBAL as input of remote sensing (RS) data sets. Finally, the SEBAL has been use full to remote agricultural land where ground based data (Lysimeter data) is not available for daily ET (ET 24h ) estimation. The temporal study of the ET 24h values analyzed have revealed that the highest ET 24h values are owing to the higher development (high greenness) of crops, whereas the lower values are related with lower development (low greenness) or null crop.

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In this study an attempt has been made to estimate the actual wheat crop evapotranspiration (ET c ) by Surface Energy Balance Algorithm (SEBAL) and standardized FAO-Penman-Monteith (FAO-PM). Improved knowledge of evapotranspiration (ET) helps in understanding the water balance of any region. The results obtained through measured lysimeter, SEBAL and PM method were evaluated through statistical performance measure tests. ET c estimated from SEBAL was found to correlate significantly as r 2 (0.910) with the measured ET c of lysimeter. ET c estimated by SEBAL was also compared with PM ET c with the help of crop coefficient and was found to correlate significantly as r 2 (0.850). The other statistical parameters (RMSE=0.561, nRMSE=0.090, MAE=0.265, NRMSE=0.2033, R-RMSE=0.268, NSE=1, d=0.870 (≈1)) were also showing a good agreement between SEBAL ET c and PM ET c . The findings of work have suggested that SEBAL model shows a good potential to estimate spatial ET c for the region. Additionally the validation of models results were performed with the analysis of correlation between models ET c and district level wheat production and area under crop of five years. The results of this analysis outline that water availability and good amount of rainfall gives higher wheat yield and resulted into more ET c .

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This study describes the VIs Vegetation Condition Index in term of vegetation health of wheat crop; with help of LANDSAT-7ETM+ data based NDVI and LAI for Bhiwani District of Haryana states (India) and gave the spatial development pattern of wheat crop in year 2005 over the study area of India. NDVI is found to vary from 0.3 to 0.8. In northern and southern parts of study area NDVI varied from 0.6 to 0.7 but in western part of Bhiwani showed NDVI 0.2 to 0.4 due to fertility of soil and well canal destitution. LAI showed variation from 1 to 6 according to the health of crop as the same manner of NDVI because LAI VI is NDVI dependent only change the manner of representation of vegetation health, due to this fact relation curve (r 2 =) between NDVI and LAI of four different growing date of sates are in successively increasing order 0.509, 0.563, 0.577 and 0.719. The study reveals that VIs can be mapped with LANDSAT-7ETM+ through remote sensing, which can be further used for many studies like crop yield or estimating evaptranspiration on regional basis for water management because satellite observations provide better spatial and temporal coverage, the VIs based system will provide efficient tools for monitoring health of crop for improvement of agricultural planning. VIs based monitoring will serve as a prototype in the other parts of the world where ground observations are limited or not available.