Geo-spatially integrated soil quality evaluation: A case of Toba Tek Singh, Pakistan

Abstract

Agricultural development and rapid human population growth are among the key prevalent factors that have caused soil degradation in several terrestrial ecosystems. Soil quality is being increasingly affected by water and wind-related erosion, aridity, salinity due to misuse, and erroneous agrarian practices. Evaluating soil quality is an essential tool for crop management and soil sustainability; this is exclusively unique in semi-arid and dry regions where the observation of soil quality offers a prospect to gauge land management systems. Here, we evaluated the soil quality in the agricultural district Toba Tek Singh, Punjab, Pakistan. For this purpose, the Integrated Quality Index (IQI) model was executed through Total Dataset (TDS) and Minimum Dataset (MDS) methods of data selection. TDS shows the soil quality results of all the selected indicators (i.e., EC, pH, CaCO3, OM, P, K, SP). To select the MDS, the Principal Component Analysis was used and three indicators were selected including pH, EC, and OM. Among the two indices (IQITDS and IQIMDS), moderate and low soil quality were recognized as a leading grade for soil quality of the study area. The reason for low-quality soil was a considerably low percentage of OM, a lower amount of CaCO3 in soil, a high rate of pH and EC, and a lesser amount of Phosphorous and K in the soil of the study area. The results for TDS and MDS were found to be appropriate to each other as confirmed by the Geographically Weighted Regression (GWR) model (Adjusted R2 0.81). Thus, this approach might be used as a helpful tool for the development of quantitative techniques to estimate soil quality. This is helpful to identify areas where soil quality is low and can be improved with better management practices and maintain a suitable amount of fertilizers in the soil.