3.4 Error Considerations for Time-Lapse Measurements

In the case of time-lapse imaging, collecting multiple background datasets can be useful for determining systematic errors and is generally well worth the time, as the most time-consuming part of ER data collection usually is deploying the electrodes and cables, and understanding the background conditions is important to interpreting changes. In systems where a hydrogeologic change is being introduced (infiltration or a tracer test, for instance), collecting multiple background datasets provides some measure of natural variability before the introduction of that change. In cases where fast time-lapse data are needed, collecting a subset of reciprocals—or collecting repeat measurements to get errors between two complete data sequences, one collected right after the other—may be a valuable way to get another measure of error beyond stacks. An example of time-lapse monitoring is provided in Section 5.2.