Solute transport in low-heterogeneity sandboxes: The role of correlation length and permeability variance

This work examines how heterogeneity structure, in particular correlation length, controls flow and solute transport. We used two‐dimensional (2D) sandboxes (21.9 cm × 20.6 cm) and four modeling approaches, including 2D Advection‐Dispersion Equation (ADE) with explicit heterogeneity structure, 1D ADE with average properties, and nonlocal Continuous Time Random Walk (CTRW) and fractional ADE (fADE). The goal is to answer two questions: (1) how and to what extent does correlation length control effective permeability and breakthrough curves (BTC)? (2) Which model can best reproduce data under what conditions? Sandboxes were packed with the same 20% (v/v) fine and 80% (v/v) coarse sands in three patterns that differ in correlation length. The Mixed cases contain uniformly distributed fine and coarse grains. The Four‐zone and One‐zone cases have four and one square fine zones, respectively. A total of seven experiments were carried out with permeability variance of 0.10 (LC), 0.22 (MC), and 0.43 (HC). Experimental data show that the BTC curves depend strongly on correlation length, especially in the HC cases. The HC One‐zone (HCO) case shows distinct breakthrough steps arising from fast advection in the coarse zone, slow advection in the fine zone, and slow diffusion, while the LCO and MCO BTCs do not exhibit such behavior. With explicit representation of heterogeneity structure, 2D ADE reproduces BTCs well in all cases. CTRW reproduces temporal moments with smaller deviation from data than fADE in all cases except HCO, where fADE has the lowest deviation. Key Points Large correlation length leads to distinct stages of solute breakthrough Two‐dimensional ADE reproduces the BTC in HCO with lowest deviation from data Correlation length potentially has stronger control than permeability variance