Mapping of Soil Nutrient Variability and Delineating Site-Specific Management Zones Using Fuzzy Clustering Analysis in Eastern Coastal Region, India

Coastal agriculture occupies significant farmlands providing livelihood to the rural community. Delineation of soil management zones in the coastal region is essential to get more economic return through reducing environmental risk, crop inputs. The present study aims to delineate the soil management zones in part of the coastal agriculture system in Ganjam block, Odisha part of Eastern India. Assessment of spatial variability of soil nutrients and satellite-derived vegetation indices, i.e. , normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and soil-adjusted vegetation index (SAVI) were used for better crop management decisions. A total of 85 geo-referenced representative surface soil samples at 0–25 cm depth were collected randomly from different landuse and landforms. Soil samples were analyzed for pH, EC, organic carbon (OC), available nitrogen (AN), available phosphorus (AP), available potassium (AK), and micronutrients (Fe, Mn, Cu, and Zn), and spatial distribution maps were developed using geostatistical techniques. The soil electrical conductivity (EC), iron (Fe), and available potassium (AK) show a high coefficient of variation (CV) of 139.95%, 84.37%, and 78.34%, respectively. The site-specific soil management zones were delineated by principal component analysis (PCA) and fuzzy c means clustering algorithm. Four principal components were selected in the present study, representing a total variance of 69.29% with eigenvalues > 1 using the soil and vegetation attributes. Fuzzy c means clustering was performed for the scores of the selected principal components (PCs) along with the Fuzzy Performance Index (FPI) and Modified Partition Entropy (MPE) was used for determining the optimum number of management zones. Five soil management zones were delineated in the study area and the significant difference between the management zones was identified by analysis of variance. The delineated MZs significantly differ concerning soil and vegetation parameters, thus knowledge of soil variability and site-specific management zones helps for sustainable utilization of resources and reducing soil degradation, and maximizing crop yield.