# Uncertainty of the 2D Resistivity Survey on the Subsurface Cavities
## 3 Results and Discussion
### Model Accuracy, Resolution, and Sensitivity
#### 3.3.1 Model Accuracy
We delineated the more reliable zones of the inverted models since higher credibility is given for the DOI patterns with values below 0.1 [28]. The zone below the threshold depth (DOI \(\leq\) 0.1) is considered a low sensitive zone and assumed to be poorly imaged [63]. Air-filled cavity model simulation showed a small change of DOI index with cavity position, which is slightly shifted up as the cavity depth increases (Figures 7-10). Consistent with our results, other studies [57] depicted the variation of DOI indexes based on the resistivity distribution of the survey domain. In our study, a significant variation of DOI index was also observed for different types of arrays. The inverted models have displayed the average DOI threshold depth of 8 m for DD, 9.8 m for WS, 10.5 m for PD, and 12.7 m for PP models (Figures 7-10). For the same number of electrodes, equal spacing, and profile length, the largest DOI threshold depth shown by the PP array may be due to its greater penetration depth [22,25]. The PP array depicted the largest DOI threshold depth; however, it obtained the lowest model resolution with blurred cavity anomalies (Figure 10). This is likely related to the least sensitivity of the PP array to the subsurface resistivity variations [22,47]. Figure 11: Resistivity anomaly gradient of the arrays for the target cavity T\({}_{2}\). Size of Cavity  
The air-filled cavity size scenarios were used since the cavity size is an important factor in the array-model resolution. We used three cavity sizes as three scenarios: 0.5 \(\times\) 6 m, 1.5 \(\times\) 6 m, and 3 \(\times\) 6 m respectively, all set at 4.2 m depth. The cavity size significantly affects the resolution of the resistivity tomogram. The small cavity size in scenario 1 was not correctly resolved in any tested arrays; however, the DD array showed a relatively better result (Figure 13). The small size cavity can be highly smoothened by the inversion process, in addition to the low-resistivity measurement on the recording instrument that nearly approaches the host resistivity value (Figure 13). We show the results of scenario 2 with the results of the previous section for the similar-sized cavity T\({}_{2}\) for the sake of comparison (Figure 14). Scenario 2 was adequately resolved in the DD, PD, and WS arrays; however, the PD and WS arrays' resolution were slightly lower than the DD array, whereas the PP array poorly recovered the cavity in scenario 2. Moreover, all the tested arrays resolved scenario 3 cavities (Figure 15), but the PP array showed a relatively lower resolution than the other arrays. For increasing cavity size, the model resolution significantly improved, while the inversion artefacts considerably increased. The result showed that the overestimation in anomaly size was less pronounced as cavity size increases. By considering the homogenous host medium, cavity targets larger than the anomaly size in scenario 1 could be recovered effectively by the DD array. The DD and WS arrays could be effective for the cavity targets greater than or equal to the anomaly size in scenario 2. The PP array could be effective for the cavity size having a size greater than or equal to the anomaly in scenario 3. Figure 12: Resistivity anomaly gradient for the air-filled cavity set at different survey depths using the dipole-dipole (DD) array. Figure 14: The inverted resistivity model for scenario 2 with 1.5 \(\times\) 6 m cavity size using: **(a)** DD array, **(b)** PD array, **(c)** WS array, **(d)** PP array. The rectangular box indicates the actual cavity target. Figure 5:0 The inverted resistivity model for scenario 3 with 3 \(\times\) 6 m cavity size using: **(a)** DD array, **(b)** PD array, **(c)** WS array, **(d)** PP array. The rectangular box indicates the actual cavity target.