Study of Energy Balance of Sugarcane (Saccharum Officinarum L.) using Remote Sensing and Crop Simulation model in Tarai region of Uttarakhand
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Date
2019-09
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G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand)
Abstract
The present study was conducted at the Norman E. Borlaug Crop Research Centre of G.B. Pant University of Agriculture and Technology, Pantnagar to Study the energy balance of sugarcane using surface energy balance algorithm and CANEGRO model
during 2015 and 2016. The sugarcane variety selected for the study was Co-Pant 5224. The performance of the CANEGRO model was reasonably well when compared with the observed crop parameters like Leaf Area Index, fresh cane yield (t/ha), Dry weight Yield of Cane (t/ha) etc. during the period of study. Predicted values through CANEGRO model were very close to the observed values in the experimental year. The model performance was tested on statistical ground on the basis of Index of agreement (d) and RMSE (%). The d value for the analysis was 0.86 and RMSE (%) was 17.28 %, which shows that there was limited error in the predicted values as compared to the observed values. The model was found to be more sensitive to the effect of temperature either decreasing or increasing it than mean temperature, CO2 concentration and Irrigation amount (mm) and Radiation (MJ/m2/day). Calibrated CANEGRO simulation model was also used to analyze the impact of climate change on growth and development parameters of Sugarcane. Leaf Area Index, dry weight yield of cane (kg/ha) and time taken for emergence were found to decrease in the future climatic scenarios (2030-2090). SEBAL is a surface energy balance algorithm predicting evapotranspiration
using remote sensing technique. It calculates ET through a series of procedures that generates residual energy flux as precursor of ET. In this study, LANDSAT-8 (OLI+TIRS) satellite images for the crop period (2015-16 and 2016-17) have been utilized for extraction of various components of SEBAL in sugarcane crop. The parameters required for SEBAL procedure includes surface albedo, emmissivity, land surface temperature (LST), NDVI, LAI, Vegetative Fraction, momentum roughness
length, canopy height, and elevation represented by SRTM-1 arc sec (DEM). The Daily ET computed through SEBAL was later validated by DSSAT computed ET. The results revealed the mean bias error (MBE) of 0.62 mm/day for SEBAL, and R2 of 0.702,
represents a higher similarity between the remotely sensed and model estimated evapotranspiration values.