Evaluation of Spatio-Temporal Evapotranspiration Using Satellite-Based Approach and Lysimeter in the Agriculture Dominated Catchment

Crop coefficient (K-c) represents the actual crop growth of the crop. It plays an important role in estimating water requirements at the different growth stages of the crop. However, FAO 56 Penman-Monteith K-c method does not account for spatial heterogeneity and uncertainty for regional climatic conditions significantly. Therefore, this study aims to develop the relation between K-c and normalized difference vegetation index (NDVI) using a linear regression and back calculations. These relationships were adjusted to local conditions using information from survey data obtained during Rabi season (2014-2015). The NDVI-K-c model (r(2) = 0.86) has developed using NDVI-K-c from a fine resolution Landsat 8 remote sensing data. NDVI-K-c regression equation was utilized for generating crop coefficient for different month of season. The Vegetation Index-based AET estimated was evaluated with lysimeter data for different crop growth stage across the season. The results have shown that NDVI-K-c estimated AET has been better correlated with NDVI-K-c remote sensing model. Thus, the output of this research can help to calculate actual water demand in a command area and be helpful in allocating water from less demand area toward more demand area.

Automated summary

This study developed a relationship between crop coefficient (Kc) and normalized difference vegetation index (NDVI) using linear regression and back calculations, aiming to estimate water requirements at different growth stages of crops. The results showed that NDVI-Kc estimated actual evapotranspiration (AET) was better correlated with the NDVI-Kc remote sensing model, which could assist in calculating water demand and allocating water resources effectively.