Abstract
Abstract. Estimation of evapotranspiration (ET) parameters is essential for understanding crop water requirements and to find out the ground water recharge. In situ data collection procedures are generally adopted to measure the parameters required to find ET. Latest remote sensing technologies accompanied by newly launched satellite datasets can supplement the field data collection and analysis by finding out some of the parameters such as land surface temperature, normalized difference vegetation index (NDVI), albedo, emissivity, etc. The Upper Ganga Canal Command Area (UGC) lying between two rivers Ganga and Yamuna situated between two states, namely Uttarakhand and Uttar Pradesh in North India is selected as the study area for this research work. Operational Simplified Surface Energy Balance (SSEBop) method is used to derive high resolution (10m) ET map for the Upper Ganga Canal Command Area. Sentinel-2 multi spectral images were used to derive land use, land cover (LU/LC) maps, NDVI, albedo, etc. Downscaled Landsat 8 images were used to derive land surface temperature of the command area. Meteorological data retrieved from the Indian Meteorological Department (IMD) was used to calculate reference evapotranspiration. ET map of the study area was generated using the above estimated parameters. Further, validation of the obtained ET values was accomplished by gridded ET data obtained from IMD.
Highlights
Evapotranspiration is the key component of hydrological cycle
Estimation of evapotranspiration by remote sensing became popular in recent years since it is less expensive than using ground measurement e.g. eddy covariance and requires less ground data
LST was estimated with Landsat image due to its High resolution Thermal infrared band (TIR)
Summary
Evapotranspiration is the key component of hydrological cycle. It helps to know about climate change, land use, water budget and irrigation. It transfers large volumes of water and energy, in the form of latent heat) from the soil (evaporation) and vegetation (transpiration) into the atmosphere (Yan et al.,2018). Estimation of evapotranspiration by remote sensing became popular in recent years since it is less expensive than using ground measurement e.g. eddy covariance and requires less ground data. Several methods on surface energy balance models are available to find ET e.g. S-SEBI, SEBS, SEBAL ,METRIC etc. To produce a seamless ET across image-scenes using remotely sensed thermal data and model-assimilated weather fields Senay et al (2013) introduced Operational Simplified Surface Energy Balance (SSEBop) approach. to produce a seamless ET across image-scenes using remotely sensed thermal data and model-assimilated weather fields
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