## 3 Results: Discussion and Comparison  
The discussion of the results first follows a qualitative approach, comparing the obtained inverse models with each other and with the synthetic model, and subsequently a quantitative approach, calculating the inversion reliability parameters previously described. All the electrical resistivity sections are presented with the same logarithmic scale of colors to facilitate comparison. This is highlight, with a rainbow scale, only the resistivity values greater than the background resistivity (100 \(\Omega\cdot\)m). The smaller values instead were rendered with shades of gray. Figure 4 summarizes the inverse models obtained starting from the cube model (see Figure 1). The 2D ERT surveys are related to electrode lines arranged at different values of the orthogonal distance \(d\) between the survey line and the projection on the surface of the center of the cube (Figure 4b-j). The results can be compared with the central section (\(d/l=0\)) extracted from the 3D ERT inverse model (Figure 4a) in which the number of iterations \(N_{it}=4\) and the normalized data misfit \(L_{1N}=1.12\%\). In 2D inversions, a greater number of iterations than for 3D inversions is necessary for the process to stop (\(N_{it}\) ranging from 6 to 9), obtaining very low data misfit values (0.15% \(\leq L_{1N}\leq\) 0.19%). However, a low data misfit value does not indicate good results. In fact, the 2D ERT results showed strong variations in the shape of the anomaly compared with the true one. When the 2D survey was centered upon the cube, the height of the anomaly was strongly underestimated, resulting in about half of the real height of the cube. On the other hand, the width was determined with good precision (Figure 4b). When the 2D survey was performed lateral to the cube, the height of the anomaly increased, but its width increased compared with the real one as \(d\) increased (Figure 4c-j). As expected, the displayed resistivity value of the anomaly was always less than that of the cube. However, while in the case of the central section of the 3D ERT the maximum resistivity value was quite high (about 1000 \(\Omega\cdot\)m, Figure 4a), in the 2D ERT, it was much lower, varying from about 320 \(\Omega\cdot\)m when \(d/l=0\) (Figure 4b) down to 106 \(\Omega\cdot\)m when \(d/l=2\) (Figure 4j). Anyway, the effects of the resistive cube were still quite evident even if the 2D survey no longer passed over the cube, or at least for non-excessive distances (0.5 \(<\)\(d/l<\) 1.5, Figure 4e-h). This generates a misleading anomaly that can lead to errors in interpretation. The effectiveness parameters \(\mathbf{P}_{1}\), \(\mathbf{P}_{2}\) and \(\mathbf{P}_{3}\), previously defined to quantify the effectiveness of 2D inversions with respect to the real section, were calculated for each simulated 2D ERT. The results are shown graphically in Figure 5 for the cube-shaped resistive block model. The value of \(\mathbf{P}_{1}\) was always very low (\(\mathbf{P}_{1}<0.15\)) and decreased as \(d/l\) increased, confirming the strong underestimation of the 3D anomaly when this was interpreted as 2D. The parameter \(\mathbf{P}_{2}\), which quantifies the effect of the non-centrality of the 2D ERT with respect to the resistive block, decreased from 1 to about 0.5 when \(d/l\) increased from 0 to 2.5. The parameter \(\mathbf{P}_{3}\) is related to the amount of anomalous area detected with respect to the real one. This parameter surprisingly indicated that the extension of the anomalous structure was underestimated when the distance \(d\) was less than half the dimension \(l\) of the cube. It increased as \(d/l\) increased until \(d/l\) reached 1.25 and then decreased, tending toward zero for \(d/l>2\). In short, the simulations relating to the model in Figure 1 show how the influence on the inversion of a resistive block depends on its position with respect to the survey line.