Digital Evaluation of Land Improvement Needs Using Topographic and Soil Constraints in an Experimental Farm Context

Land improvement interventions, such as drainage enhancement, deep ploughing, and terracing, are essential in maintaining long-term productivity in agricultural systems. This study aims to digitally assess the spatial distribution of soil and topographic constraints that necessitate land improvements within the Cojocna Experimental Farm. Using a high-resolution digital elevation model (DEM), slope, and topographic wetness index (TWI) were calculated. Interpolated soil properties from 40 field samples soil datasets including texture, drainage class, and bulk density were spatially interpolated across the farm area. A multi-criteria analysis was applied to identify zones where land use is restricted by poor water infiltration, excess water stagnation, steep slope, or compacted layers. The results highlight that approximately 21.4% of the evaluated area falls into moderate or severe limitations requiring interventions such as subsurface drainage or scarification. The study proposes a spatially explicit prioritization scheme for land improvement planning, supporting both agricultural productivity and sustainable land use in the context of didactic and research operations. This model-based approach can assist local land managers and farm technicians in decision-making, even in the absence of real-time field data.