Assessment and validation of evapotranspiration using SEBAL algorithm and Lysimeter data of IARI agricultural farm, India

Abstract

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.

Estimation and Validation of Actual Evapotranspiration for Wheat Crop Using SEBAL Model over Hisar District, Haryana, India

“…Such issues may be resolved by developing various validation methods, which may include comparison of ET derived from RS and groundbased measurements over the same location. Thus the present study was carried out with the objective of spatial ET estimation using the SEBAL model, which was already validated/tested in the same agro-climatic zone 7 using Landsat7 ETM+ data for Hisar district. Another objective was to validate the SEBAL model by ground truthing of the study area using PM model according to FAO 56 guidelines 8 and using locally developed crop coefficients.…”

“…After acquiring satellite images using reflectance from visible, infrared and thermal bands, normalized difference vegetation index (NDVI), leaf area index (LAI), surface temperature and albedo maps were generated and then all the fluxes mentioned in eq. (1) were estimated 6,7 . By summing up long-and shortwave radiations, the net radiation was estimated.…”

“…After validation of SEBAL ET with ground-observed lysimeter data with high coefficient of correlation (R 2 = 0.91) 7 and with PM ET c having coefficient of correlation (R 2 = 0.835), the SEBAL model was applied over 15 different dates'/years' Landsat7 ETM+ images for ET mapping of the study area during wheat cropping seasons. The SEBAL ET estimation involves calculation of different vegetation indices, viz.…”

“…All vorticities were limited to the inner core zone and the outer zone was free of vorticity. During the last few decades, different studies experimentally modelled flow field in the presence of vortices to understand the behaviour of this phenomenon 3,[5][6][7][8][9][10][11][12][13][14][15][16][17][18] . Besides experimental studies, researchers also tried to numerically simulate vortex formation in the reservoirs [19][20][21][22][23][24][25][26][27] .…”

Vegetation indices mapping for Bhiwani district of Haryana (India) through LANDSAT-7ETM+ and remote sensing techniques

“…It is also considered ISSN : 0974-9411 (Print), 2231-5209 (Online) All Rights Reserved © Applied and Natural Science Foundation www.ansfoundation.org as the representative of LAI and is able to estimate the LAI in different ecosystems. As a result, NDVI−LAI can be applied to study the state of crop vegetation cover.Several studies indicate that NDVI and LAI are used for estimation and prediction of crop yield because both parameters are dependent on the state of vegetation cover (Curran, 1994;Bala et al, 2015). The relationship between NDVI and vegetation cover can be established based on the distribution of vegetation cover which is weak and sparse or dense.…”