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    • Keywords


      Scintillometry; sensible heat flux; latent heat flux; Bowen ratio; evapotranspiration.

    • Abstract


      Amount of available net energy and its partitioning into sensible, latent and soil heat fluxes over an agricultural landscape are critical to improve estimation of evapotranspiration and modelling parse (ecosystem modelling, hydrological and meteorological modelling). Scintillometry is a peculiar and robust methodology to provide structure parameter of refractive index and energy balance. Scintillometer has proven for assessment of sensible and latent heat flux, which is based on the principle of Monin–Obukhov similarity theory. Scintillometer has been installed in the agricultural experimental farm of ICAR-Indian Agricultural Research Institute, New Delhi, with a spatial covering path length of 990 m of irrigated and cultivable agricultural landscape. This paper discusses the patterns of energy flux as diurnal and seasonal basis at scintillometer path which was mainly covered by maize in Kharif and wheat in Rabi season during a crop growing seasons of 2014–2015. The biophysical parameters (leaf area, soil moisture, crop height) were recorded at a temporal resolution of fortnight basis along the path length at usual sampling distance. The Bowen ratio value for both Kharif and Rabi season was 0.76 and 0.88, respectively by scintillometer. Leaf area index had a significantly positive correlation with latent heat flux ($R^{2} =0.80$) while a significantly negative correlation with sensible heat flux ($R^{2}{=}-0.79$). Soil moisture had a significant negative correlation with sensible heat flux ($R^{2}{=}-0.68$). The average evapotranspiration from crop land was 1.58 mm d−1 and total evapotranspiration was 543 mm over the 12 months study period. This study defines that large aperture scintillometer is robust instrument which can evaluate energy flux over a large area with a long term series time domain. Moreover, further studied should be conducted to use in crop simulation modelling, developing of new model with calibration and validation of remote sensing energy balance algorithm, etc.

    • Author Affiliations


      Abhishek Danodia1 2 V K Sehgal1 N R Patel2 R Dhakar1 J Mukherjee1 S K Saha2 A Senthil Kumar2

      1. Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India.
      2. Agriculture and Soils Division, Indian Institute of Remote Sensing – ISRO, Dehradun 248 001, India.
    • Dates

  • Journal of Earth System Science | News

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      Posted on July 25, 2019

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