Spatial variability and simulation of soil organic carbon under different land use systems: geostatistical approach

The knowledge of spatial variability of soil properties is useful for agricultural management decision making. This study was aimed at examining the spatial variability patterns of soil organic carbon (SOC) in a representative watershed in submontane Punjab, at field, landscape and watershed scales using geostatistical tools. Six land use systems from the Hoshiarpur district of Punjab, India lying in the Satluj Lower Sub basin watershed (code A01SUL11) were selected. Highest SOC content (0.26%) was found in the poplar agroforestry system and the least (0.16%) in the maize land uses system. The brick-kiln system showed a higher variability in SOC content (52%), followed by sesame (32.5%) and mango system (31.3%). Microbial biomass carbon (MBC) and dehydrogenase activity (DHA) did not show a consistently positive relation with SOC. Sensitivity analysis conducted to ascertain sample size for detecting a critical change in SOC content showed that about 5000 samples were required for detecting a 0.01% critical change in SOC in the maize land use compared to fewer samples in other systems. Kriged surface was generated by using ordinary kriging for soil organic carbon in all land use types and all variables (physical, chemical and biological) showed variable degree of spatial dependence. The study revealed the potential effects of management practices on the spatial distribution of measured parameters. Geostatistical simulation showed better performance than kriging in general. Agro-forestry systems especially poplar-based showed considerable promise in carbon sequestration. Several variables especially SOC and texture varied with change in longitude and latitude, thus signifying the need for further examination of spatial variability at watershed scale.