Integrating X‐Ray Computed Tomography and Hydraulic Properties for Soil Quality Assessment Under Soil Compaction

Soil compaction poses a significant threat to soil quality and sustainability, necessitating advanced assessment methods. We hypothesized that incorporating x‐ray computed tomography (XCT)‐derived pore characteristics with hydraulic properties would significantly enhance the development of a soil quality index (SQI) under soil compaction. Ninety soil samples were collected from the surface layer (0–20 cm) of five sites representing varying soil types, and land uses—cultivated and uncultivated—across the Loess Plateau in China. Samples were experimentally compacted at five bulk density levels to simulate different levels of compaction. Data included basic soil properties, direct measurements of hydraulic properties, and quantitative pore metrics from XCT image analysis. The multiple linear regression (MLR) models were developed to predict hydraulic and pore characteristics. A comprehensive SQI using principal component analysis was applied to measure soil quality based on 14 soil properties. The results found that XCT analysis revealed a profound degradation of pore network characteristics, including reduced porosity and connectivity with increasing bulk density. The MLR model, incorporating both basic soil properties and XCT‐derived total porosity (MLR‐MODEL3), provided the highly accurate predictions ( R 2 : 0.864–0.999). The SQI, based on seven key parameters, decreased markedly from 0.82 to 0.17 with increasing compaction, providing a clear quantitative measure of soil degradation. The integration of XCT with hydraulic properties and basic soil properties provides a powerful approach for soil quality assessment and offers invaluable tools for monitoring compaction effects on the Loess Plateau.