Unlocking the potential of soil potassium: Geostatistical approaches for understanding spatial variations in Northwestern Himalayas

This study delves into the heterogeneity of total soil potassium (TSK) in the Northwestern Himalayas (NWH) region by employing standard and geostatistical methods on surface soils (0–20 cm) randomly collected from various land use systems. This research aims to unveil the spatial dynamics of TSK in the challenging context of the NWH region, by unravelling connections between TSK levels, land use practices, and soil properties. The findings of this study are instrumental for sustainable agriculture and ecological resilience in the region. The results of this work reveal that soil TSK levels in different land use types were significantly different in the order: horticulture (13.76 g/kg) > agricultural (11.25 g/kg) > forest (7.38 g/kg) > fallow (4.72 g/kg), which is clearly associated with different K application rates. The stepwise multiple regression analysis provides a significant correlation between TSK levels and soil organic matter, clay, and other fine-grained particles. Spatially, the nugget ratios of TSK exhibit an apparent decrease correlated to land use types, in the order: agriculture > horticulture > forest > mixed. Among the Gaussian, exponential, linear, and spherical geostatistical models considered, the linear model yields the best fit. The isotropy models of TSK optimization vary based on land use type. The role of land use types is very important for modelling and predicting the TSK status at the scientific and industrial scale, ensuring the relevance and applicability of such insights for global scientific audiences and policymakers. This work provides a novel contribution to soil science, with direct implications for sustainable land management practices in fragile agroecological regions beyond geographical boundaries.