Abstract

Irrigation water is limited and scarce in many areas of the world, including the Panchmahal region, Gujarat, India. Panchmahal is located in between 22° 30′ N to 23° 30′ N latitudes and 73° 15′ E to 74° 30′ E covering an area of 3314.56 km². Thus, better estimations of irrigation water requirements are essential to conserve water. The overall objective of the present study was to estimate crop acreage and crop water requirement (ETC) of dominant maize crop at various scales using a satellite remote sensing-based vegetation index. The resulted acreage estimation will helpful in understanding the cropping patterns and their interaction with spatial and temporal variability for present and future estimation of crop water requirements and proper resource availability in this selected region. Twelve clear sky Sentinel-2 satellite images from November 2020 to April 2021 were acquired for the study area for the analysis. For the Rabi season chosen for the current study, 34 images, each with two scenes and a five-day sensing interval, with a total of 68 images were downloaded and applied. The coefficient of maize crop for the entire growing season was generated using average NDVI based values, which were evaluated using remote sensing and GIS techniques. For maize crop, the NDVI and crop coefficient KC (FAO) showed a higher correlation with R2 = 0.8. As a result, the correlations of crop coefficient (KC) with the NDVI were used to create the KC map. Crop water demand based on actual crop evapotranspiration is a product of the average ETC value and the corresponding area. The total crop water demand for maize crop seasons was found to be 171.50 MCM. ETC maps helped to explain the variability of crop water use during the growing season. According to the findings, ETC maps created using remotely sensed multispectral vegetation indices are a helpful tool for assessing crop water usage at regional and field scales. The findings in this study will be helpful to the irrigation planners and farmers for applying appropriate amounts of irrigation water corresponding to each growth stage using ETC maps at the field scale, leading to water conservation, and better irrigation water management.

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