Estimation of Wheat Crop Coefficient Using GIS and Remote Sensing- A Case Study of Akola District of Maharashtra, India

Abstract

Efficient water use in agriculture is crucial for sustainability, requiring precise irrigation practices to maximize every drop of water. This study addresses the challenge of accurately estimating wheat crop coefficients, which are vital for effective water management. Using Sentinel-2A satellite data, the research examines the relationship between vegetation indices (EVI, NDVI, NDWI, and SAVI) and wheat crop coefficients in Akola District, Maharashtra. Ground truth data was collected to validate the satellite observations. Profiles of all the four vegetation indices of wheat were studied in detail and compared with profiles of crop coefficients of wheat recommended by Mahatma Phule Krishi Vidyapeeth (MPKV) Rahuri. Among the indices, NDWI (Normalized Difference Water Index) demonstrated the strongest correlation with wheat crop coefficients, expressed by the linear equation Kc=3.8078 NDWI+0.5396 with highest value of R2. This finding underscores the potential of NDWI as a robust tool for estimating crop coefficients, thus enhancing water use efficiency in irrigation practices. It is recommended that NDWI be utilized in local irrigation management to optimize water resources effectively.