<div>Background: Soil texture is one of the important property constitute ultimate size particles. Proportions of these ultimate soil particles depend on the pedogenesis and mineralogical composition of parent material and also decide all other soil properties. Due to the imprudent crop selection and imperfect agricultural methods, the very fertile soil is becoming denser and low productive. Geostatistics is a set of Models and tools developed for statistical analysis of continuous data. A critical aspect of agriculture ecosystem and environment modeling is the accurate prediction for the spatial variability of soil properties.&nbsp;&nbsp; 
 
Methods: In this study, Geostatistical modeling based Kriging techniques has been used to identify the textural variation of soil in the present scenario of Melur Block of Madurai district. Totally, 150 soil samples were collected across Melur block of Madurai district based on grid soil survey and geo coordinates.&nbsp; 
 
Result: Geostatistical soil textural maps have been generated based on Kriging tools and these would be utilized for Land Use Pattern, precision agriculture, conservation practices, as well as land management in the research region. The characterization of the spatial variability and influence of soil texture on hydraulic conductivity is essential to accomplish a better understanding of intricate relations between soil properties and environmental factors.&nbsp;</div>

Spatial Analysis of Soil Texture using GIS based Geostatistics Models and Influence of Soil Texture on Soil Hydraulic Conductivity in Melur Block of Madurai District, Tamil Nadu

Background: Knowledge about the spatial variability of soil field capacity is important to understand the nuances of soil water holding capacity and how to manage it so that the farm does not need to irrigate or suffer from a drought. 
 
Methods: A study was conducted in order to evaluate the spatial variability of filed capacity of Lalgudi block of Tiruchirapalli district located in Tamil Nadu, India. The soil samples were collected from different locations in Lalgudi block and the field capacity of the soil samples was estimated by using pressure plate apparatus for the soil samples. Geostatistics was applied for identifying the best interpolation method to acquire the spatial map of field capacity. Ordinary kriging and Disjunctive kriging fitted with six models via circular, spherical, exponential, Gaussian, pentaspherical and sine-hole effect model were used for spatial prediction of field capacity. 
 
Result: Initial data exploration resulted in non-normal distribution of field capacity and hence log-transformation was done before kriging was used. The semivariograms showed that the field capacity dataset had moderate spatial dependency in case of both kriging methods and with six models except Sine-Hole effect model in disjunctive kriging. A maximum range of 10709 m was observed in Exponential and Sine-Hole Effect model in ordinary kriging. The cross validation statistics indicated that the circular model in disjunctive kriging gave lesser root mean square value. The significant variability of field capacity should be taken into account in soil management practices.

Spatial Analysis of Soil Texture using GIS based Geostatistics Models and Influence of Soil Texture on Soil Hydraulic Conductivity in Melur Block of Madurai District, Tamil Nadu

Spatial Variability Analysis of Soil Field Capacity at Lalgudi Block in Tamil Nadu using Geostatistical Models