The Spectral Induced Polarization (SIP) method has emerged as a well-suited laboratory technique to characterize hydrogeological and biogeochemical parameters in soil samples. However, field applications of the SIP imaging method are still rare, which can be attributed to the particular care required to minimize the contamination of the data by electromagnetic coupling. To date, field procedures rely on the use of two different cables separating the current and potential dipoles to improve the quality of the SIP readings, although this increases the efforts in the field and might reduce the depth of investigation or the spatial resolution of the data. To overcome these limitations, we investigate here the use of a single coaxial cable, as an alternative to improve data quality and simplify field procedures. We present a thoughtful evaluation of SIP imaging data collected with the same measuring device using a coaxial cable and a combination of multicore cables of different length and manufacturers. Data sets collected with a single coaxial cable reveal a significantly lower number of outliers and high spatial consistency between the phase-lag readings, even for measurements collected with a coaxial cable five times longer than the length of the profile. Furthermore, the data collected with coaxial cables reveal an improved quality for deeper measurements (with lower signal-to-noise ratio) in comparison to data sets collected with separated cables. Our results demonstrate that the use of coaxial cables might permit the collection of SIP readings with high quality and similar field procedures to those used in resistivity surveys.

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In recent years, the time-domain induced polarization (TDIP) imaging technique has emerged as a suitable method for the characterization and the monitoring of hydrogeologic and biogeochemical processes. However, one of the major challenges refers to the resolution of the electrical images. Hence, various studies have stressed the importance of data processing, error characterization, and the deployment of adequate inversion schemes. A widely accepted method to assess data error in electrical imaging relies on the analysis of the discrepancy between normal and reciprocal measurements. Nevertheless, the collection of reciprocals doubles the acquisition time and is only viable for a limited subset of commonly used electrode configurations (e.g., dipole-dipole [DD]). To overcome these limitations, we have developed a new methodology to quantify the data error in TDIP imaging, which is entirely based on the analysis of the recorded IP decay curve and does not require recollection of data (e.g., reciprocals). The first two steps of the methodology assess the general characteristics of the decay curves and the spatial consistency of the measurements for the detection and removal of outliers. In the third and fourth steps, we quantify the deviation of the measured decay curves from a smooth model for the estimation of random error of the total chargeability and transfer resistance measurement. The error models and imaging results obtained from this methodology — in the following referred to as “decay curve analysis” — are compared with those obtained following a conventional normal-reciprocal analysis revealing consistent results. We determine the applicability of our methodology with real field data collected at the floodplain scale (approximately 12 ha) using multiple gradient and DD configurations.

Abstract. Karst water resources play an important role in drinking water supply but are highly vulnerable to even slight changes in climate. Thus, solid and spatially dense geological information is needed to model the response of karst hydrological systems to such changes. Additionally, environmental information archived in lake sediments can be used to understand past climate effects on karst water systems. In the present study, we carry out a multi-methodological geophysical survey to investigate the geological situation and sedimentary infill of two karst lakes (Metzabok and Tzibaná) of the Lacandon Forest in Chiapas, southern Mexico. Both lakes present large seasonal lake-level fluctuations and experienced an unusually sudden and strong lake-level decline in the first half of 2019, leaving Lake Metzabok (maximum depth ∼25 m) completely dry and Lake Tzibaná (depth ∼70 m) with a water level decreased by approx. 15 m. Before this event, during a lake-level high stand in March 2018, we collected water-borne seismic data with a sub-bottom profiler (SBP) and transient electromagnetic (TEM) data with a newly developed floating single-loop configuration. In October 2019, after the sudden drainage event, we took advantage of this unique situation and carried out complementary measurements directly on the exposed lake floor of Lakes Metzabok and Tzibaná. During this second campaign, we collected time-domain induced polarization (TDIP) and seismic refraction tomography (SRT) data. By integrating the multi-methodological data set, we (1) identify 5–6 m thick, likely undisturbed sediment sequences on the bottom of both lakes, which are suitable for future paleoenvironmental drilling campaigns, (2) develop a comprehensive geological model implying a strong interconnectivity between surface water and karst aquifer, and (3) evaluate the potential of the applied geophysical approach for the reconnaissance of the geological situation of karst lakes. This methodological evaluation reveals that under the given circumstances, (i) SBP and TDIP phase images consistently resolve the thickness of the fine-grained lacustrine sediments covering the lake floor, (ii) TEM and TDIP resistivity images consistently detect the upper limit of the limestone bedrock and the geometry of fluvial deposits of a river delta, and (iii) TDIP and SRT images suggest the existence of a layer that separates the lacustrine sediments from the limestone bedrock and consists of collapse debris mixed with lacustrine sediments. Our results show that the combination of seismic methods, which are most widely used for lake-bottom reconnaissance, with resistivity-based methods such as TEM and TDIP can significantly improve the interpretation by resolving geological units or bedrock heterogeneities, which are not visible from seismic data. Only the use of complementary methods provides sufficient information to develop comprehensive geological models of such complex karst environments

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