Assessing soil quality in semiarid tropical region of southern India using GIS and remote sensing

Soil quality assessment has been recognized as an important step towards understanding the long term effects of land management practices within a landscape. This case study addressed the spatial variability of soil properties and their quality at the watershed and district level using geostatistical methods. Soils samples were collected from different land use systems of Nalgonda and Warnagal District of Andhra Pradesh in Southern India. An assessment framework that included a minimum data set, linear scoring technique, and additive indices was used to evaluate the Soil Quality Index (SQI). The minimum data sets were chosen using principal component analysis and based on contribution of soil parameters to soil function through expert opinion. The order of calculated SQIs for different land use system was castor < intercrop < redgram < sorghum < cotton < maize < fallow < rice. Among the different soil orders, Vertic Inceptisol and Vertisol had the highest SQI followed by Inceptisols and Alfisols. A krigged map of SQI for the watershed as well as Nalgonda and Warangal districts was prepared. The results indicated that soil having higher soil quality indices were more productive and less erosion prone.