Geo-statistical assessment of spatial variability of soil water-holding capacity for optimal irrigation under semi-arid vertisols in South India

Based on a field survey conducted in Lalgudi block, Tiruchirapalli district, Tamil Nadu, India, details about the crops grown, cropping pattern, land utilization and soil samples were collected from 20 locations under seven different soil textures of semi-arid vertisols. Using the data, efficient geostatistical models have been explored to study the spatial variation of irrigation water requirement of paddy, sugarcane and banana grown in the study area. Geostatistics was applied to identify the best interpolation method to acquire the spatial map of the available water holding capacity. Ordinary kriging and Disjunctive kriging were explored with six models viz., Circular, Spherical, Exponential, Gaussian, Penta-spherical and Sine-Hole effect models and were used for spatial prediction. The cross-validation statistics indicated that the Sine-Hole effect model with disjunctive kriging of available water holding capacity was superior for interpolation with a minimum value of RMSE and moderate spatial dependency. With the available water holding capacity map of Lalgudi block, total available water, readily available water and irrigation interval of paddy, sugarcane and banana were estimated. The irrigation interval of paddy, sugarcane and banana were found to vary between 1-2, 3-5 and 2-4 days respectively within Lalgudi block. The adoption of spatial algorithms for estimating crop water requirements would greatly help irrigation planners and water policymakers create efficient regional plans for precision irrigation under semi-arid vertisols.