# Uncertainty of the 2D Resistivity Survey on the Subsurface Cavities
## 4 Conclusions  
This study examined the uncertainties of resistivity imaging and identified the efficient arrays for subsurface cavity studies. Different numerical examples were demonstrated to examine the depth, size, orientation, geometry, and filling material effects on the array's imaging ability. An experimental cavity study was also performed to compare with the numerical model results. In addition, we studied the spatial resolution for different checkerboard sizes and assessed arrays' sensitivities to resistivity perturbations. The conceptual models were simulated to generate apparent resistivity data. The detection abilities of the arrays were statistically analyzed using variances and anomaly effects of the synthetically measured resistivity data. The apparent resistivity data were inverted to recover geoelectric models, and the model accuracies were evaluated. Based on cavity depth modeling, the DD array exhibited the highest anomaly effect (1.46) and variance (24,400 \(\Omega\cdot\)m) in measured resistivity data for the shallowest cavity (T\({}_{1}\)) set at 2.2 m depth. In contrast, the PP array showed the lowest anomaly effect (0.18) and variance (900 \(\Omega\cdot\)m) for the deeper cavity (T\({}_{6}\)) set at 12.2 m depth. The anomaly effect and the variance of resistivity data decreased for increasing cavity depths, limiting the recovery of the cavity information. The DOI threshold depths were delineated, and the inverted models were inspected. As cavity depth increases, the statistical image correlation between the inverted and actual models was significantly decreased. The anomaly sizes were considerably overestimated as cavity depth increases, which can highly restrict the recovery of accurate geometries. The arrays' spatial resolution was significantly reduced as the size of the checkerboard decreased. All the tested arrays accurately resolved the first row of the checkerboard cells, but the second-row cells were considerably smeared, especially in the WS, PD, and PP arrays. Based on sensitivity tests, all the arrays were highly sensitive to the resistivity contrasts at the vicinity to electrode location. The DD and WS arrays showed higher sensitivity to resistivity perturbations than the PD and PP arrays. The PD displayed slightly better sensitivity compared to the PP array. Considerable artefact contaminations occurred for the DD, PD, and PP models, whereas minor contamination was observed on the WS models, which correlates with the signal-to-noise ratios of these arrays. The study identified the ideal subsurface target probing arrays based on model accuracy, resolution, and sensitivity. We infer that the DD array is the most effective for studying subsurface targets (e.g., cavity), the PD and WS arrays are adequate, whereas the PP array is the least suitable for target probing. The sensitivity and resolution were substantially reduced as the depth increased; thus, a single cavity set at varying depth resulted in different solutions. This leads to ambiguity in model interpretations of the resistivity method. Under these circumstances, integrating prior information, performing a joint inversion of different parameters, and jointly interpreting the model outputs of two or more methods can significantly reduce the inherent uncertainties of the resistivity method. [PERSON] was responsible for data analysis, simulations, and writing the draft. [PERSON]-[PERSON] supervised and instructed results analysis and modified the manuscript. [PERSON] provided comments on results discussions with the other two authors. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the Minister of Science and Technology (MOST) of Taiwan under the project number of MOST 108-2638-E-008-001-MY2. This research was also partly supported by Earthquake-Disaster, Risk Evaluation and Management Centre, E-DREaM, from the Featured Areas Research Centre Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.