Soil water, salt, and nutrient variability are essential factors that impact crop productivity in agriculture systems. However, effective management of small farms requires access to fine-scale data on soil water, salt, and nutrients. Large-scale assessments of spatial variability using classical statistics and geostatistical methods can help identify nutrient-deficient zones. In Xinjiang, China, inadequate water and nutrient management has resulted in low crop productivity in agriculture systems. To address this issue, this study evaluated the mechanical composition, bulk density, and contents of water, salt, ammonium nitrogen (), nitrate nitrogen (), and available phosphorus (A-P) in soil at the farm level in the Xinjiang region. Results showed low variability in soil bulk density, medium variability in soil water content, mechanical composition, , and A-P, and high variability in soil salt content and . Mechanical composition and A-P showed a small range of variation across different soil depths, while soil water content and in the surface layer varied significantly more than in other soil layers. variability increased with soil depth. Soil properties showed minimal differences over time. Multi-factor deficiencies, particularly in nitrogen, were observed throughout the study area. The generated maps offer a useful tool for farm managers and policymakers. In summary, this study highlights the significance of evaluating the spatial variability of soil properties for identifying zones deficient in water and nutrients, as well as those with salt accumulation. This information can be utilized to develop effective strategies for site-specific nutrient management.