Mapping of soil macronutrients under major land use systems in district Rajouri of Jammu and Kashmir using GIS

Assessment of land use induced changes in soil properties is essential for addressing issues of agroecosystem transformation and sustainable land productivity. With a view to assess and map major soil nutrients of Rajouri district of J&K, present investigation was undertaken using GIS technique. In this study, a total of 250 random soil samples (0-15 cm depth) on the basis of different land use systems were collected from seven tehsils namely Rajouri, Thanamandi, Nowshera, Sunderbani, Kalakote, Budhal and Darhal. Collection of soil samples was based on stratified random sampling method. Five land use systems, namely agriculture, horticulture, forest, pastures and wastelands were selected for the study. The soil fertility maps showed that soil pH of district was moderately acidic to moderately alkaline (4.9 to 9.0) in reaction, EC was safe from the salinity hazards and organic carbon (OC) ranged from low to high ranging from 1.20 to 23.0 g kg-1 under different land use systems. However, OC was found to be higher in forest soils than agriculture soils and other land use systems. Sand content was higher in wastelands whereas clay content was higher in agriculture land use system. Cation exchange capacity was found to be higher under horticulture and forest systems than other land use systems with mean values of 18.18 and 17.58 c mol(p+)kg-1, respectively. All the primary macronutrients viz., available nitrogen (N), phosphorus (P) and potassium (K) content of agriculture lands, pasture lands and wastelands were lower than the forest lands although the mean value was higher in agriculture soils. The mean exchangeable Ca content was higher under horticulture land use system whereas exchangeable Mg content was higher under wastelands and available sulphur content was higher under forest soils than other land use systems. All major nutrients showed negative correlation with sand and silt content whereas they showed positive and significant relationship with clay content, organic carbon content, electrical conductivity and cation exchange capacity. The maps generated will be helpful to the farmers for the location specific correction of nutrient deficiencies.