REMOTE SENSING INDICES FOR CROP WATER MANAGEMENT

Remote sensing has become a very powerful tool for crop condition assessment and management. The objective of this study was to understand the effectiveness of basal crop coefficient (Kcb) values estimated from remote sensing and their application in real time crop water requirement. During the crop growing season, the value of Kc for most agricultural crops increase from a minimum value at emergence in relation to change in canopy development, until a maximum Kc is reached at full canopy cover. The study was carried out for the Cotton crop in Sirsa district of Haryana. A spectral index such as SAVI (Soil Adjusted Vegetation Index) and Fractional Vegetation Cover (Fc) was used to estimate Kcb value. High spatial resolution Landsat TM 5 images were used to generate a spectral profile of NDVI, SAVI, and Fc for different crop cover. Using, available empirical models from literature, crop coefficient was derived from SAVI values. Reference Crop Evapotranspiration (ET0) was estimated using Blaney - Criddle Method, taking weather data from ICAR Research Station Observatory. The crop coefficients derived from Remote Sensing data were used along with ET0 values to estimate crop evapotranspiration (ETc). The result showed that the spatial distribution of seasonal ETc varied depending upon sowing date and other condition. The estimated crop evapotran spiration (ETc) pattern was compared with fractional vegetation cover. Spatial distribution map of cotton ETc, basal crop coefficient, and fractional vegetation cover showed areas of high and low water demand. This work can help in water management practic es f or better irrigation management .