Home Integrated geophysical approach for detection and size-geometry characterization of a multiscale karst system in carbonate units, semiarid Brazil
Article Open Access

Integrated geophysical approach for detection and size-geometry characterization of a multiscale karst system in carbonate units, semiarid Brazil

  • David L. de Castro EMAIL logo , Francisco H. R. Bezerra and Josibel G. Oliveira Jr
Published/Copyright: February 29, 2024
Become an author with De Gruyter Brill

Abstract

The karstification of carbonate rocks creates 3D maze voids that are normally controlled by fracture networks and sedimentary bedding. The spatial distribution and density of karst systems are usually complex and difficult to predict, demanding multidisciplinary studies at different scales of investigation to determine the spatial distribution and density of karst features and their possible links with cave systems controlled by the regional structural setting. The present study integrates geophysical datasets (gravity, electrical resistivity tomography - ERT, and ground penetrating radar - GPR) with a digital elevation model to investigate a karst system in the Irecê basin, a semiarid region of Brazil. Morphostructural lineaments reveal a NNW-SSE- and E-W-oriented structural setting of the crystalline basement, which is imprinted on the internal basin architecture, and surface drainage network. Negative gravity anomalies and high-gradient gravity zones indicate the main karstic zone, where karst landforms are concentrated. In addition, 2.5D gravity modeling provides the internal basin geometry, demonstrating that the karst system has evolved in the thickest sector of the basin. ERT profiles delineate the underground passages that connect dolines at depth. Finally, GPR data image shallow subsurface ghost-rock karstification that spread out from the surface to depth and that took advantage of vertical fractures and slightly arched bedding planes. Our results point out the role of the fracture corridors in channelizing hydrodynamic energy at a sufficiently high level to create caves by the total removal of dissolved material, whereas in the surrounding areas under low hydrodynamic conditions, overall shallow ghost-rock karstification took place, creating residual weathered rocks (alterites).

1 Introduction

The study of karst systems is of great interest in hydrogeology, hydrocarbon exploration, and geological engineering. Karstification generates secondary porosity and permeability mainly in carbonate rocks, thereby determining the hydrodynamics and storage capacities of aquifers and petroleum reservoirs and representing a potential source of environmental, industrial, and urban hazards [16]. A karst system develops by chemical dissolution when acidified waters come into contact with carbonate rocks, mostly limestone and dolostone. Karstification depends on the local hydrodynamic regime controlling the seeping water to remove the dissolved carbonate constituents. Therefore, the process with low hydrodynamic energy removes only dissolved species while leaving undissolved particles in place. This process is known as ghost-rock karstification, which produces a residual material called alterite [7,8].

In contrast, the karstification process by the total removal of the dissolved species, mechanical erosion of the undissolved particles, and creation of open voids requires high hydrodynamic energy and occurs along permeable zones within the bedrock. The type and intensity of karstification depend on permeable pathways, such as bedding planes, fractures, faults, and the amount of interstitial fluids percolating within the bedrock [9]. Indeed, karst systems evolve from small fractures to fracture corridors, promoting interconnectivity between carbonate aquifers and reservoirs and spreading out karst zones [10,11].

Karst systems have complex 3D structures that hamper their geometric characterization. Multiple factors control the development of karst features and networks and are difficult to predict. These factors include processes from light to total removal of weathered carbonate rock, which creates open voids and preferential groundwater or hydrocarbon flow paths [12,13]. Karstification is a multiscale process that ranges from mineral dissolution at the microscale (10−5–10−3 m) to the formation of giga-scale (102–104 m) cave networks (Figure 1). At the oil reservoir mega- to giga-scales (100–101 to 102–104 m), seismic reflection data constrained by cores and well logging are the typical geophysical approach to perform karstified reservoir investigations [14]. At the aquifer/outcrop macro- to mega-scales (10−2–10−1 to 100–101 m), ground-based geophysical methods such as gravity [5,15], electrical resistivity tomography (ERT) [6,8,11], ground penetrating radar (GPR) [13,16,17], near-surface reflection/refraction seismic [6,18,19], and magnetic [3,20] methods have been used for characterizing of karst systems at depth. Geological and structural fieldwork, supported by satellite, light detection and ranging (LiDAR), and unmanned aerial vehicle imagery interpretation, have been used to map karst landforms, surface drainage, and fracture networks associated with karst systems [10,21]. In addition, airborne magnetic data are promising for detection at regional to semiregional scales of bedrock structural settings that influence karst development [22]. However, there is still a gap in the detection and quantification of karst porosity and the best near-surface geophysical methods to identify karst systems, especially in semiarid regions with a predominance of low hydrodynamic conditions. Consequently, multiscale investigation techniques require multidisciplinary studies to assess the karst location, size, and internal geometry.

Figure 1 
               Scales of karst porosity and their detection using different geophysical methods. (a) intercrystalline carbonate dissolution (yellow arrow); (b) intercrystalline pores between matrix carbonate grains; (c) karst breccia and its corresponding pores and fractures; (d) fractured and karstified carbonate rock; (e) orthogonal fracture corridor system (unmanned airborne vehicle image); and (f) cave system entrance. ERT – electrical resistivity tomography; GPR – ground penetrating radar.
Figure 1

Scales of karst porosity and their detection using different geophysical methods. (a) intercrystalline carbonate dissolution (yellow arrow); (b) intercrystalline pores between matrix carbonate grains; (c) karst breccia and its corresponding pores and fractures; (d) fractured and karstified carbonate rock; (e) orthogonal fracture corridor system (unmanned airborne vehicle image); and (f) cave system entrance. ERT – electrical resistivity tomography; GPR – ground penetrating radar.

The contribution of geophysical methods to exploring karst systems was comprehensively described by Chalikakis et al. [12], who correlated geophysical measurements with one or more physical properties of the subsurface and their spatial distribution. The choice of the geophysical method depends on the contrast in physical properties between the karst features and the host rock and the relationship between resolution and investigation depth. These authors recognized five main issues related to karst systems that are addressed by geophysical surveys and often combine two or more different methods. The karst-related issues are as follows: (a) Karst system limits and extent: Potential field (magnetics and gravity), electromagnetic (EM), electrical (self-potential and resistivity), and refraction and reflection seismic techniques provide greater depth of investigation and, therefore, important information concerning the internal geometry and the volume of outcropping and buried karst reservoirs, as demonstrated in several studies [3,6,2325]. (b) Structural discontinuities are karst-related issues: Karst systems are largely controlled by fracture networks due to their presence, orientation, and intensity [12]. Imaging geophysical methods such as frequency-domain EM, ERT, reflection/refraction seismic, and GPR can distinguish more fractured zones of a karst system in the massive part of the same formation [18,19,26]. Karst near-surface heterogeneities are well mapped with these techniques, especially in the epikarst zone, where fracture density is important for the karst development. Otherwise, the potential field methods provide limited resolution for this scale of survey and are successful only when combined with other more accurate methods [15,27]. (c) Preferential pathways and concentrated infiltration: Karst landforms, such as dolines, uvalas, and karst valleys, are near-surface expressions of underground active karst networks whose preferential pathways can be mapped using ERT and GPR surveys, which are sometimes integrated with microgravity and EM methods [3,17]. GPR provides an optimal ratio between resolution and investigation depth to detect complex systems of near-surface cavities, collapsed caves, buried dolines, and even humanmade buried channel systems such as qanats [28,29,30]. (d) Cavities are karst-related issues: The total removal of the dissolved material creates cavities, which are detectable by geophysical methods using their size, depth, and filling (air, water, soil, or mixing thereof) [5,31]. The contrast in physical properties (density, magnetic susceptibility, seismic velocity, electrical conductivity, and dielectric permittivity) between the cavity and the surrounding rock produces recognizable anomalies in the natural or artificial fields measured by geophysical sensors on the surface. (e) Finally, overburden is also a karst-related issue. Sedimentary cover generated by carbonate rock weathering or deposited by alluvial processes can significantly change the geophysical response of the karst system. Mapping the near-surface weathered/karstified carbonate rock demands high-resolution GPR data ([17,27,31], and this study), while the detection of karst-related targets buried by sedimentary cover requires geophysical methods with greater investigation depth, such as ERT, reflection/refraction seismic, EM, and microgravity methods [6,24,26]. In addition, Martínez-Moreno et al. [5] show extensive studies using combinations of geophysical techniques for mapping karst systems and detecting caves.

The Iraquara karst system, located on the southern edge of the Irecê Basin, northeastern Brazil (Figure 2), offers an opportunity to investigate the karst porosity location, size, and geometry at different scales. Giant caves that are hundreds of kilometers long occur mainly along the hinge zones of anticlines where fracturing is intense [33]. In the Iraquara area, various stages of epigenetic karstification coexist, from slightly altered carbonates to prominent karst landforms. Karstification has developed under certain structural constraints, which control surface drainage and underground flow throughout underground connectivity, determining the intensity of host rock dissolution. However, geophysical studies have not yet assessed the dimensions and internal geometry of karst systems.

Figure 2 
               Tectonic and stratigraphic setting of the Iraquara karst system. (a) The South American continent and location of the study area as part of the São Francisco Craton and the Irecê basin. (b) Synthetic geological map of the southernmost sector of the Neoproterozoic basin (modified from the study by Dalton de Souza et al. [32]). The black rectangle limits the Iraquara karst system shown in Figure 5. (c) Geological cross-section AA′ of the Irecê basin. The locations of the gravity stations are marked (dots).
Figure 2

Tectonic and stratigraphic setting of the Iraquara karst system. (a) The South American continent and location of the study area as part of the São Francisco Craton and the Irecê basin. (b) Synthetic geological map of the southernmost sector of the Neoproterozoic basin (modified from the study by Dalton de Souza et al. [32]). The black rectangle limits the Iraquara karst system shown in Figure 5. (c) Geological cross-section AA′ of the Irecê basin. The locations of the gravity stations are marked (dots).

The present study aims to identify and characterize the size, density, and internal architecture of the Iraquara karst system by combining gravity, ERT, and GPR data. This multitechnique approach also aims to assess the different sensitivities of geophysical methods to investigate multiscale karst features and bedrock structures in terms of the investigation depth and spatial resolution (Figure 1). The magnetic and gravity data allow us to map karst structures and internal basin geometry and detect karst zones. In addition, ERT and GPR surveys allow detailed imaging of karst features at depths from 60 to 6.0 m, respectively. In addition, we map morphostructural lineaments and karst landforms based on a high-resolution global elevation model to identify the karst network and its structural constraints. These results indicate that considerable fluid flow along fracture corridors promoted intense karstification with the total removal of dissolved carbonate rocks. At the same time, ghost-rock karstification has spread throughout the karst system, where fracturing and hydrodynamic conditions are less intense.

2 Geological and geomorphological settings

The Iraquara karst system comprises a Precambrian shallow epicontinental carbonate platform in the Irecê Basin, which is in the northern part of the São Francisco craton, Brazil [34], and references therein (Figure 2). This vast cratonic landmass encompasses Mesoproterozoic to Neoproterozoic sedimentary sequences overlying deformed Archean to paleoproterozoic geological domains [35] (Figure 2). The Irecê syncline (profile AA′ in Figure 2) formed during an extensional event before contractional tectonics during the Brasiliano orogeny (∼600 Ma), when fold belts surrounding the craton caused shortening across NNE-SSW and E-W fold-thrust systems [36,37]. The Irecê syncline is confined between the surrounding quartzite anticlines (Chapada Diamantina Group), especially on its southern edge, where the Iraquara karst system was established (Figure 2).

Neoproterozoic compressional tectonics and subsequent Cretaceous rifting, which folded and fractured the Irecê basin and its basement units, were responsible for the rise of hydrothermal fluids upward through the basal unit and intense hypogenic karstification of the entire carbonate platform [38]. The Iraquara karst system is one of the most representative hypogenic cave networks of the Irecê Basin [39]. Major caves occur in the hinge zones of open folds, where karst features concentrate along subvertical fractures and horizontal bedding [33,34,38,40]. The carbonate units consist mostly of subhorizontal limestones and dolomites, which can locally dip up to 30° and exceed thicknesses of 150 m in the central portion of the area [41]. Surface ghost karstification processes overwhelm the hypogenic cave network, weathering the carbonate bedrock, and enlarging cavities, causing their collapse and formation of dolines and uvalas [39].

The area of the Iraquara karst system comprises a 30-km-wide carbonate syncline with a NNW-SSE-oriented axis. The syncline narrows to the south, bounded by quartzite anticlines (Figure 2). Glaciogenic siliciclastic units underlay the carbonates and outcrop at the carbonate basin edges (profile AA′ in Figure 2). A thick reddish soil sequence covers most of the carbonate platform and the caves. Rock exposures occur mostly in oval-shaped dolines with vertical cliff faces and scarped margins of karst valleys [39]. The Iraquara area occupies a 12.5 km × 23 km karst plateau with slopes <12% and wavy ramps [42]. Landform karst features correspond to dolines, uvalas, and karstic valleys, concentrated along NNW-SSE- and E-W-oriented zones and roughly parallel to the main streams. Cruz Jr. [41] identified collapse dolines with steep profiles and suffusion dolines, represented by smooth depressions associated with slow subsidence caused by the removal and infiltration of detrital overburden. The Bambuí Speleological Group (Grupo Bambuí de Pesquisas Espeleológicas, https://bambuiespeleo.wordpress.com/) mapped 101 cave entrances in the Iraquara area. This group also mapped the internal geometry of the caves. Their maps of the major cave systems reveal 3D mazes of orthogonally oriented conduits. These cave systems extended to 6.5 km2, with conduits >2.5 km long. The preferred conduit directions are NNW-SSE and E-W, which coincide with the spatial distribution of the karst landforms. Dolines and karst valleys expose cave entrances.

3 Digital elevation model (DEM) and geophysical datasets

We investigated the Iraquara karst system using a high-resolution DEM and gravity, ERT, and GPR geophysical methods. This multiscale investigation approach aimed to characterize the karst system at three different scales: (a) the macro-scale (10−2–10−1 m), related to small cavities and fractures enhanced by karstification; (b) mega-scale (100–101 m), related to fractured and karstified host rocks; and (c) giga-scale (102–104 m), related to fracture corridors, cave systems, and karst landform structures (Figure 1). Starting at the mega- to giga-scale – aquifer/outcrop to oil reservoir scales (Figure 1d–f, respectively), we comprehensively mapped karst landforms and superficial drainage in the study area (Figure 2) using the Shuttle Radar Topography Mission (SRTM) global elevation grid with a spatial sampling interval of 3 arcsec (∼90 m) (Figure 3a). We applied a Gaussian regional-residual filter to enhance residual topographic features, attenuating the lowest wavenumber signal content (<0.28 km−1). The central cutoff wavelength of 3.5 km satisfactorily attenuated the regional content of the DEM (Figure 3b), highlighting the karst landforms and main streams (Figure 3c). In addition, the analytic signal amplitude (ASA) of the DEM was calculated for the residual elevation grid to highlight topographic gradients related to cliffs, dolines, uvalas, and karst valleys. The ASA is the square root of the sum of the squares of the partial derivatives of a function in the three Cartesian directions.

Figure 3 
               (a) Original elevation map of the Iraquara karst system, installed in a regional flat plain (dashed black line). (b) Radially averaged log-power spectra (original – black and filtered – red) of the study area elevation grid and the Gaussian regional/residual filter (blue). (c) Filtered elevation map highlighting residual topographic features.
Figure 3

(a) Original elevation map of the Iraquara karst system, installed in a regional flat plain (dashed black line). (b) Radially averaged log-power spectra (original – black and filtered – red) of the study area elevation grid and the Gaussian regional/residual filter (blue). (c) Filtered elevation map highlighting residual topographic features.

Dolines and uvalas were mapped on DEM maps for further analysis of the spatial distribution and density of the karst landforms, considering them all to be dolines for simplification. As dolines display a wide variety of dimensions in the study area, we estimated doline density by considering the area effectively occupied by dolines instead of the “one dot – one doline” principle. In this way, we obtained a doline density map using a simple kernel method [43], which determines the percentage of a 1.0 km2 area occupied by dolines within a circle with a radius of 500 m and a center located by 31.6 m cells of a regular raster grid set. For example, 50 doline/km2 means dolines dominate 50% of a 1.0 km2 area. The doline density map was compared with the gravity anomaly map to establish any probable correlation between the spatial distribution of surface (dolines) and deep (caves) karst features in the study area.

Gravity anomalies make it possible to detect near-surface density changes caused by the presence of dolines and caves with respect to the host rock [5]. The scale of the investigation varies from macro- (small shallow cavities) to giga-scale (crust-mantle interface), depending on the space between gravity stations. As a rule of thumb, a denser concentration of measurement points improves the spatial resolution of the gravity survey. In this study, we used gravity data to identify areas with high surface and deep karst feature concentrations at a more regional mega- to giga-scale. We also used gravity data to model the internal architecture of the Irecê basin, which hosts the Iraquara karst system.

New 594 gravity stations were acquired using an Autograv Scintrex CG-5 gravity meter with an accuracy of 0.001 mGal to study the Iraquara karst system (Figure 2). The stations were spaced ∼500 m across the study area, 250 m in the area with the highest doline concentration, and 20 m along ERT surveys. A differential GPS provided proper accurate coordinates and the altitude of each station. The nongeological gravity effects were removed from the measurements using standard reductions: tidal and instrumental, latitude, free air, Bouguer, and terrain corrections. The resulting complete Bouguer anomaly was interpolated in a 200 m regular grid using the minimum curvature method. Furthermore, the residual gravity anomaly was calculated by regional trend removal using a matched filter with central cutoff wavelengths of 11,010 and 887 m. In addition, the ASA of the gravity field was calculated to the residual gravity grid to highlight gravity gradients related to lateral density changes. In general, high-amplitude ASA values should indicate areas with high concentrations of surface and deep karst features.

Finally, we performed forward gravity modeling along two orthogonal regional profiles crossing the center of the karst system. The residual gravity anomalies were modeled using the GM-SYS profile modeling extension of Oasis Montaj software [44]. The 2.5D gravity modeling process tries to reduce the root-mean-square (RMS) misfit between observed and calculated anomalies after each interaction to find a better model. Forward gravity modeling is rather limited if the geometry of the modeled object is not partially known beforehand. Therefore, geological field information, karst landform mapping, and internal cave geometry defined in the 2D resistivity inversion models were considered during gravity modeling, constraining its results. The final gravity models provide the internal geometry of the basin and cave system, with an estimated accuracy of a few tens of meters (mega-scale).

Six ERT profiles were performed to detect caves that interconnect dolines under the ground and determine their internal geometry more accurately than a gravity survey. We used a Syscal Pro multimode resistivity meter imaging system for collecting data from 16 levels by using Wenner, Schlumberger, and dipole–dipole arrays. The multichannel cables were used along ERT profiles with lengths of 150–740 m and electrode separation of 10 m. The ERT datasets from the three electrode arrays were processed using Prosys II software (IRIS Instrument) and then inverted using RES2DINV software v. 3.54 to obtain 2D geoelectric cross sections of the caves, which constrained the gravity modeling along these profiles. The inversion algorithm discretizes the subsurface in rectangular prisms. It calculates the resistivity value of each prism to minimize the difference between the calculated and observed apparent resistivity using the least-square method (RMS) [45]. The final inverse model is given at the iteration, after which the RMS error does not change significantly. In our study, the final RMS was <4% after five iterations. The maximum depth of investigation was achieved at 65 m. After comparing the inverted profiles with the three different electrode arrays, the Werner array was chosen due to its high lateral and vertical resolution and effectiveness in better imaging caves in the study area. The karst features imaged along the ERT profiles range from a few meters to tens of meters (mega-scale) at depths of up to 65 m.

A large volume of 2D and 3D GPR data was also acquired in the study area to image the karst features at the macro- to mega-scale properly – fractured/karstified rock to aquifer/outcrop scales (Figure 1c and d, respectively). On the basis of typical GPR patterns, we selected the best examples to identify macro- to mega-scale karst features related to ghost karstification or karstification by total removal. Furthermore, the advanced process of carbonate weathering and soil formation causes intense attenuation of the GPR signal, restricting the investigation depth to less than 10 m. The cave tops are below 15–30 m, so these structures were not targeted in the present GPR survey.

The GPR survey was carried out with a SIR-3000 system (GSSI Inc.) using 80, 200, and 400 MHz antennas. Each GPR trace was acquired with 1,024 samples for time windows of 200 and 150 ns, a vertical stack of 64 traces at each location, and a distance between traces of 0.02 m. The data processing comprised time-zero correction, low-frequency content (wow) removal, background removal, bandpass filtering, gain application based on energy decay, and migration based on hyperbola adjustment (EM velocities between 0.075 and 0.11 m/ns). In addition, the texture attribute, which delineates spatial relations and patterns of amplitude variation, was applied in the processed GPR data to enhance subvertical, high-amplitude zones and cavities. We used REFLEXW software to process the GPR data.

4 Results

4.1. Surface analysis of karst features using satellite elevation data (mega- to giga-scale porosity)

From a geomorphological point of view, the southernmost edge of the Irecê basin represents a moderately flat carbonate plain surrounded by quartzite scarps on the E, W, and S sides (Figures 2, 3, 4a, and 5). The surface drainage runs mainly from north to south and from west to east within the basin (yellow lines and colored arrows in Figure 5). Major streams are sinking underground in the central sector of the Iraquara karst system, where karst landforms and cave entrances are concentrated (Figures 4a and 5). The discontinuity of the surface drainage in the area where karst landforms and caves are concentrated (Figure 5a and b) indicates that groundwater (yellow arrows in Figure 5a) flows eastward through a cave system to a large river on the eastern border of the carbonate plain (Figure 3a). On the eastern boundary of the carbonate basin, a wide E-W-oriented canyon cuts across the eastern cliff, allowing surface water to escape from the valley (red arrows in Figure 5a).

Figure 4 
                  (a) Residual DEM of the southern edge of the Irecê basin, showing the Iraquara karst system (white rectangle), cave entrances (white dots) and the location of gravity profiles (BB′ and CC′) (Figure 8) and ERT profiles (Figures 9 and 10); and (b) the morphostructural map. (c) Rose diagrams display the strike of relief lineaments within the quartzite basement (black lines) and the Irecê carbonate basin (blue lines) and LD and TR cave systems. The Bambuí Speleological Group (https://bambuiespeleo.wordpress.com/) mapped the cave locations and internal geometries.
Figure 4

(a) Residual DEM of the southern edge of the Irecê basin, showing the Iraquara karst system (white rectangle), cave entrances (white dots) and the location of gravity profiles (BB′ and CC′) (Figure 8) and ERT profiles (Figures 9 and 10); and (b) the morphostructural map. (c) Rose diagrams display the strike of relief lineaments within the quartzite basement (black lines) and the Irecê carbonate basin (blue lines) and LD and TR cave systems. The Bambuí Speleological Group (https://bambuiespeleo.wordpress.com/) mapped the cave locations and internal geometries.

Figure 5 
                  (a) Residual DEM of the Iraquara karst system, showing major karst landforms and superficial drainage and main fluvial (red arrows) and underground (yellow arrows) water flow. (b) ASA of the DEM, highlighting relief features. The location of the area is provided in Figure 4.
Figure 5

(a) Residual DEM of the Iraquara karst system, showing major karst landforms and superficial drainage and main fluvial (red arrows) and underground (yellow arrows) water flow. (b) ASA of the DEM, highlighting relief features. The location of the area is provided in Figure 4.

A morphostructural analysis depicts a high concentration of NNW-SSE-trending lineaments in both the basement and the basin areas (Figure 4b). In the basement, these lineaments define the lateral limits of the basin. In contrast, a secondary set of WNW-ESE-trending lineaments occurs in the western part of the basin. N-S-trending lineaments are concentrated along the main streams within the basin, whereas relief features are widely distributed in different directions over areas outside river valleys.

The Bambuí Speleological Group (Grupo Bambuí de Pesquisas Espeleológicas, https://bambuiespeleo.wordpress.com/) mapped 101 cave entrances in the Iraquara area. This group also mapped the internal geometry of the caves. Their maps of the two major cave systems (Lapa Doce – LD – and Torrinha – TR) reveal 3D mazes of orthogonally oriented conduits (Figure 4c). These cave systems extend over areas of 4.8 km2 (LD) and 1.17 km2 (TR), with conduits up to 2.3 km long. The preferred conduit directions are NNW-SSE and E-W, which coincide with the spatial distribution of the karst landforms. Dolines and karst valleys expose some cave entrances. The caves connect other dolines, forming a complex karst network. A series of dolines coalesce, forming uvalas and sometimes karst valleys, where a few main streams excavated canyons in the karstic zones. In addition, fluvial-related karst landforms are largely absent in the southern sector of the Irecê basin.

In the study area, dolines have semicircular to oval shapes, preferably oriented along the NNW-SSE and E-W directions, forming sets of dolines along two right-angle axes (Figures 5 and 6). The streams and karst landforms show a similar orthogonal pattern, indicating that the same regional fault and joint systems control the karst system and the surface drainage. A total of 118 dolines were found within the study area of 476.5 km2, resulting in an overall density of 0.24 dolines per km2 (Figure 6). Suppose that the area with no dolines is excluded. In that case, the remaining area of 131.5 km2 has a density of 0.9 dolines per km2, reaching a density of 1.4 dolines per km2 in the area with the highest concentration of dolines. Considering only the areas occupied by dolines, the region with a higher density of dolines (10–77 dolines/km2) is located in the central valley of the basin, bounded by the main streams on both the western and eastern edges (Figure 6a). Two zones of high doline density stand out at the eastern margin of the mainstream along the eastern border of the Irecê basin (Figure 6b). They are not fully covered by the gravity survey and, therefore, are not the subject of the present study.

Figure 6 
                  Doline density map of the Iraquara karst system derived from the digital elevation model, showing dolines (red polygons) and superficial drainage (black lines) (a) and high-gradient gravity zones (gray areas – Figure 7b) and cave entrances (blue dots) (b). The location of the area is provided in Figure 4.
Figure 6

Doline density map of the Iraquara karst system derived from the digital elevation model, showing dolines (red polygons) and superficial drainage (black lines) (a) and high-gradient gravity zones (gray areas – Figure 7b) and cave entrances (blue dots) (b). The location of the area is provided in Figure 4.

4.2. Gravity method (mega- to giga-scale porosity)

The residual gravity anomaly map of the Iraquara karst system (Figure 7a) was derived from 594 new gravity measurement stations (Figure 2) and separated from the regional trend using a matched filter. In the study area, the residual gravity anomalies allow one to investigate the internal basin architecture from hundreds of meters deep (giga-scale) to karstified zones at the near surface (mega-scale). The gravity anomalies vary from −3.6 to 3.9 mGal, which is a range of 7.5 mGal. Gravity lows occur in the central sector of the karst system, where karst landforms and cave entrances are concentrated, especially in the karst valley formed at the southernmost end of the mainstream, oriented N-S (Figures 4 to 6). The gravity minima are separated by positive anomalies that trend approximately NW-SE and E-W, reflecting the structural control in karstification, which is equally revealed by morphological lineaments (Figure 4). Peripheral gravity lows seem to be related to areas with more intense fluvial drainage and sedimentation and karst features with incipient surface expressions.

Figure 7 
                  Residual gravity anomaly (a) and ASA (b) maps of the Iraquara karst system over the DEM (grey scale). Yellow lines – superficial drainage, white lines – dolines. Location of gravity profiles BB′ and CC′ shown in Figure 8.
Figure 7

Residual gravity anomaly (a) and ASA (b) maps of the Iraquara karst system over the DEM (grey scale). Yellow lines – superficial drainage, white lines – dolines. Location of gravity profiles BB′ and CC′ shown in Figure 8.

The presence of gravity lows and highs causes strong gravity gradients, setting up high-amplitude zones (>0.15 mGal/m) in the analytical signal (ASA) map (red zones in Figure 7b). These sectors represent a high susceptibility zone of karst features with a surface area of ∼30 km2. Considering the superficial and deep cavities in the host rock as the main source of gravity anomalies in this geological context, the high amplitude zones should indicate the areas where the karst features are concentrated. In fact, the main high-amplitude zone (Figure 7b) occurs in the central sector of the karst system, where a high doline density occupies an area ca. 7.5 km long and approximately 6.4 km wide (Figure 6). Furthermore, 62% of the cave entrances are located within the zone with a high gravity gradient. This close relationship between the spatial distribution of dolines, cave entrances, and gravity gradient suggests a promising potential for using the gravity method for mapping karst systems at a semiregional (mega- to giga-) scale, which is discussed in Section 5.

The E-W- and N-S-oriented gravity profiles (BB′ and CC′ in Figures 4 and 7, respectively) depict asymmetric intercalation of positive and negative residual anomalies, which are slightly displaced in the central portion of the Iraquara karst system (Figure 8). The main karstic zone, defined by ASA values >0.15 mGal/m, occupies areas that are 6.2 and 4.6 km long in profiles BB′ and CC′, respectively. Gravity maxima reach ∼3.0 and 0.56 mGal, and gravity minima reach −3.2 and −2.2 mGal in BB′ and CC′ profiles, respectively. Variations of ∼6.2 mGal in the residual gravity field reflect the mass deficit due to sinkholes, caves, and density contrasts within the basin and in the underlaid basement. To support this assumption, we calculated 2.5D three-layer gravity models, including the basement, composed of quartzites (density of 2.67 g/cm3) and the Irecê basin, filled by diamictites (2.58 g/cm3) and limestones (2.71 g/cm3). The densities of quartzites and diamictites were extracted from the classic literature [46]. In contrast, the average density of the limestones was based on rock sample measurements carried out by Borges et al. [47] in the Irecê basin. In addition, we included zones with high-density carbonate rocks (HDC of 2.77 g/cm3) in the gravity models to fit the high-amplitude positive anomalies satisfactorily. The presence of dolomites in the study area, with densities ranging from 2.28 to 2.90 g/cm3, according to Telford et al. [46], can justify carbonates with such high densities in the models. We assigned a 0.0 g/cm3 to the karst landforms and caves since most rivers and caves remain dry over the years. DEM and ERT data and the locations of the cave entrances constrained the location and internal geometry of the karst features. The insignificant gravity effect of the thin sediment layers that fill some caves was neglected in the gravity modeling.

Figure 8 
                  2.5D gravity models along profiles BB′ (a) and CC′ (b) of the southernmost edge of the Irecê basin. Numbers in parenthesis are densities in g/cm3. RMS error is annotated in each profile. ASA – analytic signal amplitude. HDC – high-density carbonate rock. Profile locations in Figures 4 and 7.
Figure 8

2.5D gravity models along profiles BB′ (a) and CC′ (b) of the southernmost edge of the Irecê basin. Numbers in parenthesis are densities in g/cm3. RMS error is annotated in each profile. ASA – analytic signal amplitude. HDC – high-density carbonate rock. Profile locations in Figures 4 and 7.

The gravity models resulting from 2.5D modeling show RMS errors close to 0.15%, revealing an up-to-600-m-thick basin with an E-W-oriented synform geometry, thinning to the W, E, and S borders and filled with diamictite and limestone layers (Figure 8a and b). To the north, the basin infill shows a constant thickness of ∼450 m toward the central sector of the Irecê basin. Profile BB′ shows a striking gravity gradient of 6.0 mGal in the main karstic zone, which was modeled as an abrupt thickness variation in the carbonate layer (Figure 8a). This internal basin architecture suggests an ∼5.0 km-wide graben-like structure in the central part of the basin. The abrupt borders of this structure are coincident with the two major N-S-oriented shear zones that are deep seated in the Precambrian basement, whose subvertical boundaries could represent the faulted borders of the Irecê syncline. Otherwise, the top of the carbonate layer is smoother along profile CC′ (Figure 8b) parallel to the main axis of the Irecê syncline.

In the uppermost part of the basin, the gravity-modeled cave system extends for more than 4.5 and 3.2 km in profiles BB′ (E-W – Figure 8a) and CC′ (N-S – Figure 8b), respectively. These caves have developed in limestones and high-density carbonate rocks (dolomites). No caves have been mapped outside the main karstic zone in gravity profiles. Most likely, the low coverage of gravity stations and the limited spatial resolution of the method make it difficult to identify smaller and more isolated caves along the profiles.

4.3. ERT (mega-scale porosity)

Three resistivity models resulting from 2D numerical inversions are shown in Figures 9 and 10. The geoelectric models generally display a relatively low resistive superficial layer (∼70 to 550 Ωm), corresponding to reddish soil and alterite, which is the residual carbonate weathering product. The thickness of the uppermost geoelectric layer varies from a few meters to >25 m, presenting abrupt lateral changes, probably associated with less weathered rock zones. These zones, here called underground karst towers, are relatively more resistive subvertical blocks that are partially controlled by the local fracturing system and properly imaged on GPR profiles (see the next section). The high-density carbonate rocks, modeled in the gravity profiles (HDC in Figure 8), could represent the regional expression of these more resistive subvertical blocks. Furthermore, a high-resistivity layer (650–50,000 Ωm) extends downward from the surface and the base of the upper low-resistivity layer to the final ERT investigation depth (∼65 m). We interpret this resistivity layer as the less weathered and fresh carbonate bedrock, and the very high-resistive zones (>50,000 Ωm) might be associated with caves that interconnect the karst landforms at depth.

Figure 9 
                  Satellite image (a), residual gravity anomaly (b), and inversion model of electrical resistivity tomography (c) of the profile ERT01. RMS error is 8.3% after three iterations. Unit electrode spacing is 10 m. Profile location in Figure 4.
Figure 9

Satellite image (a), residual gravity anomaly (b), and inversion model of electrical resistivity tomography (c) of the profile ERT01. RMS error is 8.3% after three iterations. Unit electrode spacing is 10 m. Profile location in Figure 4.

Figure 10 
                  Satellite image (a), residual gravity anomaly (b) and inversion model of electrical resistivity tomography (c) and (d) of the profiles ERT02 and ERT03. RMS errors are 4.9 and 7.7%, respectively, after three iterations. Unit electrode spacing is 10 m. Profile locations are presented in Figure 4.
Figure 10

Satellite image (a), residual gravity anomaly (b) and inversion model of electrical resistivity tomography (c) and (d) of the profiles ERT02 and ERT03. RMS errors are 4.9 and 7.7%, respectively, after three iterations. Unit electrode spacing is 10 m. Profile locations are presented in Figure 4.

The ∼E-W-trending profile ERT01 crosses semicircular dolines roughly oriented NNW-SSE (Figure 9). A high-resistivity zone (>150,000 Ωm) is located near 330 and 430 m in this profile and between 20 and 45 m deep, revealing a presumable underground passage between these dolines and the large karst valley to the north (yellow star in Figure 4a). The residual gravity anomaly depicts a slight low between distances of 250 and 300 m along the high-resistivity zone (Figure 9a and b), indicating a subtle mass deficit related to the cave. This local gravity low is embedded within a 500-m-wide positive gravity anomaly, suggesting that the cave and/or underground passage formed within denser carbonate rocks, which in turn concealed the local gravity effect of the caves. More expressive gravity lows occur at both profile ends, where dolines with steeper cliffs occur. Likewise, profiles ERT02 and ERT03, located 2.5 km to the east (yellow star in Figure 4a), display similar geophysical patterns (Figure 10). A large doline occupies the SW sector of the area, connected to a smaller doline by an underground passage. A third oval-shaped doline occurs 100 m to the north (Figure 10a). The underground passage can be observed from the surface, with its top at a depth of ∼14 m. Profile ERT03 crosses the area between the two dolines. It shows a high-resistivity zone (>26,000 Ωm) in the first 110 m of the profile and at a depth of 13.5 m (Figure 10d). High-resistivity anomalies (>25,000 Ωm) also occur along profile ERT02 between distances of 0–250 m and 380–490 m (Figure 10c), revealing a buried karst network that spreads northward from the dolines with no evident surface expression (Figure 10a). Residual gravity lows support the presence of caves (Figure 10b), which deepen slightly to the east (Figure 10c).

4.4. GPR (macro to mega-scale porosity)

Figures 11 and 12 show the typical 200 MHz antenna GPR response of the shallowest part of the Iraquara karst system, dominated by weathered carbonate rocks (alterite) and soil, associated with strong signal attenuation. Our interpretation is based on the study by Conti et al. [48], who measured dielectric permittivities and electrical conductivities in unweathered and weathered carbonate rock samples. These authors pointed out that the decrease in the GPR signal amplitude occurs in alterites of the Irecê basin due to an overall reduction in EM impedance contrast and increased GPR attenuation as a result of weathering (ghost-rock karstification) and soil formation. Subhorizontal reflections are attenuated, but their lateral continuity is preserved (Figure 11a and b). Vertical high-amplitude zones are interspersed along the GPR profiles with widths from 0.5 to 2.0 m and 2.0 to 12 m apart, depending on the intensity of the karstification affecting each area. They are associated with non- or less-altered carbonate bedrock, constituting underground karst towers due to differential resistance to weathering. In regions with advanced weathering, the removal of the alterite forms karst pinnacles and towers a few tens of meters high (Figure 12a and b). The larger high-amplitude zones are up to 10 m wide and are normally divided into two columns by a karstification halo around fractures. They form narrow, weathered corridors observed at distances of 12 and 47 m in profile GPR01 (Figure 11) and at distances of 14 and 20 m in profile GPR02 (Figure 12c). This suggests that the abrupt and vertical edges of the high-amplitude zones are caused by the lateral expansion of weathering from vertical fractures and horizontal bedding (Figure 12d).

Figure 11 
                  Typical GPR signal (200 MHz antennas) of the karstified carbonate rocks (alterite) showing vertical high-amplitude zones related to tower-like fresh unweathered (or unaltered) carbonate and stratified residual soil at the profile top (a). GPR closeup on high-amplitude zones: processed GPR signal (b), texture attribute (c), and interpreted section (d).
Figure 11

Typical GPR signal (200 MHz antennas) of the karstified carbonate rocks (alterite) showing vertical high-amplitude zones related to tower-like fresh unweathered (or unaltered) carbonate and stratified residual soil at the profile top (a). GPR closeup on high-amplitude zones: processed GPR signal (b), texture attribute (c), and interpreted section (d).

Figure 12 
                  GPR profile along the doline cliff above the LD cave entrance (a) and (b) 500 m to the north of the profile ERT01 (location in Figure 4). GPR profile (200 MHz antennas) with vertically segmented high-amplitude zones, whose tops are deepening to NW-wards (c). Schematic diagram showing preferential pathways of descending fluid (red arrows) that causes overall ghost-karstification and leads to the formation of tower-like karst features comprising fresh rock blocks (d).
Figure 12

GPR profile along the doline cliff above the LD cave entrance (a) and (b) 500 m to the north of the profile ERT01 (location in Figure 4). GPR profile (200 MHz antennas) with vertically segmented high-amplitude zones, whose tops are deepening to NW-wards (c). Schematic diagram showing preferential pathways of descending fluid (red arrows) that causes overall ghost-karstification and leads to the formation of tower-like karst features comprising fresh rock blocks (d).

Profile GPR02 was measured 500 m north of resistivity profile ERT01 (location in Figure 4) and at the NE border of the doline that marks the entrance of the Lapa Doce (LD) cave (Figure 12a and b), which is the longest known cave of the Iraquara karst system [39]. The top of the cave is ∼15 m deep and, therefore, is not imaged by the GPR data, which penetrates only 7.5 m below the surface. Several high-amplitude zones occur along the entire GPR profile, 2–10 m apart from each other (Figure 12c). The aerial photograph displays steep walls of doline, comprising orthogonal faulted blocks with subtle horizontal bedding planes (Figure 12b). The exposed carbonate rocks exhibit gray or beige colorations, denoting different degrees of ghost-rock karstification. The high-amplitude GPR zones are vertically segmented, whose tops are deepening to the NW and form a set of at least seven arcuated levels. These geometries would result from intense weathering along the preferential underground water pathways, namely, the subvertical fracture network and the bedding planes, in this case, subtle arcuated NW-wards features (Figure 12d).

Some cavities were identified in the GPR profiles based on attenuated to transparent EM signals (yellow areas in Figure 11d). Partially or completely emptied cavities and voids are supposedly present throughout the karstified region; however, they are more easily identified within the high-amplitude zones because the GPR patterns show greater contrast (Figure 11b and c). In the GPR profiles, the mapped main cavities range from 0.5 to 2.5 m in width and from 0.2 m to 1.5 in height (Figure 11d). The strong attenuation of the GPR signal in the alterites prevents the identification of smaller cavities or other karst features.

5 Discussion

Understanding the environmental conditions that influenced karst system formation in the Iraquara region in semiarid Brazil requires considering the spatial distribution, structural framework, and hydrodynamic characteristics. Geophysical methods and detailed topographic data helped detect and characterize superficial karst features, cave systems, and the interconnectivity between surface and subsurface features from macro- to giga-scales. The correlation between the different results for different investigation techniques can be summarized as follows: (a) geomorphological data depict the superficial distribution of karst landforms, their relationships with the surface drainage network, and morphostructural features within the sedimentary basin; (b) gravity data provide the basin internal geometry, location of the main karstic zone, and its correlation with karst landforms and morphostructural features; (c) ERT profiles integrated with gravity anomalies allow for the identification of caves and underground passages connecting karst landforms; and (d) GPR profiles, in turn, provide a high-resolution image of the near-surface karst system, delineating more intensively karstified zones along subvertical fractures and slightly arched bedding planes. The multiscale and multidisciplinary investigation approach in which karst was detected, spatially characterized, and evolved based on the combination of the different results is described in detail in the following sections.

5.1. Karst detection and spatial distribution

Due to the subhumid to semiarid climate, the rivers are ephemeral and carry water only after intense rainfall. They flow SE-wards from the headwaters in the quartzite hills to the south and from higher carbonate plains to the north and sink into the carbonate rocks in the Iraquara karst zone (Figures 36). They are the major water sources for epigenetic karstification, and the preferential pathways were provided by opened fractures, empty voids, and cave systems resulting from previous karstogenesis. The topographic and doline density maps (Figures 36) display a significant concentration of karst landforms (dolines, uvalas, and karst valleys) in a regional, u-shaped valley surrounded by quartzite hills (Figures 3a and 4a). The highest density of karst landforms is located between the main streams (Figures 5a and 6a), which sink underground, feeding a groundwater flow through the cave system and providing strong hydrodynamic conditions for karstification with total removal and cave collapse (zones 1 and 2 in Figure 13). Ghost karstification predominates in the areas further away from the streams (zone 3 in Figure 13), conditioned only by the scarce rainfall regime typical of the semiarid climate.

Figure 13 
                  Schematic diagram of the Iraquara karst system, showing fresh unweathered carbonate (a), weathered/ghost-rock karstified (b), hypogenic cave network (c), dolines (d), uvalas (e), and karst valley (f). The karst system is divided into three domains: (1) underground karstification by total removal (cave network); (2) superficial karstification by total removal (karst landforms); and (3) ghost-rock karstification (alterites and residual soil). Adapted from the thermodynamic concept of karstification described by Dubois et al. [7].
Figure 13

Schematic diagram of the Iraquara karst system, showing fresh unweathered carbonate (a), weathered/ghost-rock karstified (b), hypogenic cave network (c), dolines (d), uvalas (e), and karst valley (f). The karst system is divided into three domains: (1) underground karstification by total removal (cave network); (2) superficial karstification by total removal (karst landforms); and (3) ghost-rock karstification (alterites and residual soil). Adapted from the thermodynamic concept of karstification described by Dubois et al. [7].

The karst landforms are preferentially oriented in the NNW-SSE or WNW-ESE directions, coinciding with the two main trends of the morphostructural lineaments (Figure 4b). Furthermore, the cave entrances are concentrated in the zones with the highest density of dolines (Figures 4a and 6b). In addition, the internal geometries of the main cave systems present orthogonal galleries oriented in the NW-SE and E-W directions (Figure 4c). This spatial distribution of karst features both at the surface and at depth indicates the influence of structural-tectonic conditions on the development of the Iraquara karst system at a regional scale (mega- to giga-scales).

At the outcrop scale (mega-scale), short-wavelength gravity lows indicate mass deficits caused by the removal of karstified material at depth (caves) and on the surface (karst landforms) (Figure 7a). In contrast, gravity highs are related to the dolines and uvalas edges, constituted by denser carbonate rocks (dolomites). Zones with high-amplitude analytical signal (ASA) indicate high concentrations of karst features (Figure 7b) and, consequently, high gradients of gravity anomalies. In these areas, the densities of dolines vary from 10 to 77 dolines/km2, especially in the central valley of the basin, bounded by the main streams on both the western and eastern edges of the karst system (Figure 6b). Zones of high doline density also occur outside the central valley. However, the sparse or lack of gravity coverage does not allow proper investigation of the presence of dolines based on gravity patterns in these areas. Similarly, more than 60% of cave entrances are also located in high-gravity gradients (Figure 6b), confirming that the generation of cave systems and karst landforms must have taken advantage of the same structural conditions. It is worth mentioning that the fact that almost 40% of the cave entrances are distributed outside the high-gravity gradient zones may be due to the low-gravity coverage and the regional character of the cave mapping. Certainly, further studies are necessary to establish precise relations between gravity patterns and karst occurrences. For example, a second high-gradient gravity zone is located on the western edge of the study area, where few dolines are observed. The presence of a cave system is not expected for this region. Therefore, density variations within the sedimentary pile and/or of the underlying basement would be likely causes of the local gravity anomalies.

The 2.5D gravity modeling indicates that the main karstic zone occurs over a graben-like structure in the central portion of the synclinal basin, where the sedimentary pile reaches up to 600 m thick (Figure 8). The subvertical boundaries of the graben-like structure in the central part of profile BB′ (Figure 8a) could indicate the NNW-SSE-striking faults related to regional dextral transtensional tectonics responsible for the onset of the Irecê syncline [37]. This structural control in the distinct stages of the Iraquara karst system evolution is corroborated by morphostructural lineaments (Figure 4b). The main NNW-SSE- and, secondarily, E-W-trending structures accommodated tectonic events that deformed the Archean/Proterozoic basement, forming the internal basin architecture. This structural framework imprinted on the sedimentary pile was reactivated by compressional events, which led to hydrothermal fluid uprising and intense hypogenic karstification [22,38]. Our results indicate that the same structural setting controlled the bedrock fracturing and surface drainage, which determined the hydrodynamic conditions and pathways for both ghost-rock karstification and karstification by total removal that was overlaid on the hypogenic cave system.

The interconnection between karst landforms and cave systems is also well established at the mega-scale, as observed in some doline cliffs and by ERT and gravity data (Figures 912). High-resistivity zones (>50,000 Ωm) are located between 20 and 45 m deep, revealing underground passages that connect karst landforms at depth by cave conduits (Figures 9 and 10). Some underground passages can be observed from the surface (Profile ERT03 – Figures 10a and d), while most caves show no surface evidence (profiles ERT01 – Figure 9 and ERT02 – Figure 10a and c). Residual gravity lows associated with high-resistivity zones support the presence of caves along the ERT profiles. Exceptionally, caves and underground passages can grow in denser carbonate rocks. In these cases, the expected gravity response will be a local minimum inserted in a longer wavelength positive anomaly, as occurs in profile ERT01 (Figure 9). In fact, interferences from other causative sources of gravity anomalies can make it difficult to detect karst features, which represents an important limitation of the simple use of the gravity method.

The GPR data provide high-resolution imaging of the uppermost portion of the Iraquara karst system, where ghost-karstification prevails. This geophysical method did not investigate the interconnections between caves and dolines, as caves occur at depths greater than 10 m. In macro- to mega-scale characterization of ghost karstification using GPR, it is possible to individualize shadow zones (low-amplitude reflections), interpreted as alterites and residual soil, from high-amplitude zones related to slightly weathered to unweathered carbonate rocks (Figures 11 and 12). According to Conti et al. [48], the loss of GPR energy is due to a decrease in the dielectric permittivity and an increase in the electric conductivity of the karstified bedrock, reducing the EM impedance and intensifying the attenuation of the GPR signal. The high-amplitude zones are subvertical and separated by a few to dozens of meters. They are segmented at depth, forming arcuated levels of high-amplitude reflections (Figure 12c). This peculiar GPR pattern can be associated with non- or less-altered carbonate bedrock comprising underground karst towers due to differential resistance to weathering. Karst towers are exposed on the doline cliffs with more prominent relief and gray coloration (Figure 12b).

Pueyo-Anchuela et al. [3] proposed a three-step integrated geophysical routine for detecting doline areas for applied and engineering geology. The whole study area is examined in the first step to determine anomalous subsoil behaviors. We analyzed gravity data associated with a high-resolution DEM to identify karst landforms and their spatial distribution in the regional approach. Our processing and modeling of gravity data are coincident with residual gravity lows interpreted as buried caves and dolines by Martínez-Moreno et al. [5] and Argentieri et al. [15]. Both studies show 2D/2.5D models constructed from gravity anomalies, revealing caves at depths similar to our models in Figure 8. The second Pueyo-Anchuela et al. [3] survey step concerns imaging subsoil karst structures using ERT and GPR. Our ERT profiles display high-resistivity zones consistent with the ERT response of air-filled caves (Figures 9 and 10). Resistivities increase (500 to > 10,000 Ωm) if the karst features are filled with air [11,12,49]. In the Iraquara area, the cave roofs are deeper than 15 m, which is beyond the investigation depth of our GPR survey using 200 and 400 MHz antennas. Even GPR data acquired with 80 MHz antennas, which allow greater penetration depth, display no clear response of the cave roofs in the study area. For this reason, we used only GPR data in the third stage of the survey routine, characterizing more karstified and weathered levels of the near-surface karst system from shadow zones in the GPR profiles (Figures 11 and 12), as described by Fernandes et al. [16] and Conti et al. [48]. Certainly, lower-frequency antennas (20–40 MHz) should be able to image the top of the cave system under the local geoelectrical setting.

5.2. Karst characterization

In terms of karstification processes, the Iraquara karst system is divided into three domains (Figure 13): (1) underground karstification by total removal (cave network); (2) superficial karstification by total removal (karst landforms); and (3) ghost-rock karstification (alterites and residual soil). The superficial ghost-rock karstification evolved at the southern border of the Irecê basin along the N-S main axis of the central valley surrounded by quartzite hills that channeled surface drainage from N and W to SE throughout the Iraquara karst system (Figure 4). This topographic setting associated with an orthogonal fracture network (NNW-SSE and E-W directions) created higher hydrodynamic potential across the central valley, where sets of dolines, uvalas, and karst valleys developed (Figures 4, 5, and 13). In the areas surrounding the fracture corridors, low hydrodynamic energy leads to ghost-rock features filled with residual alterite, decreasing the karstification intensity toward the basin edges. The weathering is represented by a maze of unweathered strips controlled by the bedding and the vertical fracture sets (Figures 11 and 12).

In the central valley, ghost-rock karstification overlapped the ancient hypogenic cave system, where sufficient hydrodynamic conditions gathered to cause mechanical erosion of the alterite and collapse of cave roofs. Dolines coalesced, forming uvalas and karst valleys, whereas main streams connected the karst landforms (Figure 5). The cliffs around the doline are formed by rectangular pinnacles and karst towers of less weathered rocks (Figure 12b), whose GPR signal is represented by vertical high-amplitude zones (Figures 11 and 12c). As revealed by the ERT profiles, one of the doline faces commonly marks a cave entrance connecting other sinkholes in an intricate underground karst network (Figures 9 and 10). The area that concentrates the cave system interconnected with karst landforms extends over >30 km2, as revealed by the zones with high doline and cave entrance concentrations and high-gradient gravity values (Figures 6b and 7b, respectively).

5.3. Karst evolution

Carbonate rocks can form low-porosity and impermeable sedimentary rocks, whose weathering product is thin, clayey soil in semiarid settings [7,39,50]. However, fracturing and other discontinuities, such as bedding and structural features, create preferential pathways for acidified fluid percolation within the bedrock, triggering chemical dissolution and mechanical erosion [7]. Discontinuities and hydrodynamic energy are key parameters that dictate the type and intensity of karstification, which can cause only in situ weathering of the carbonate with the removal of soluble materials (ghost-rock karstification) or promote the total removal of minerals and create open voids (karstification by total removal) [8,9]. The voids may develop into karst networks and eventually expand to large cave systems. Both types of karstification can occur synchronously in the same region or during karstification episodes that are distinct in time, as seems to be the case in the Iraquara karst system [38,39].

On the basis of GPR data and field observations, we proposed a five-stage model for carbonate rock formation and karst evolution in the Iraquara region (Figure 14). The Neoproterozoic carbonate sequence of the Irecê basin was deposited in a shallow epicontinental marine system and subjected to diagenetic processes, such as recrystallization, dolomitization, and stratification [34, and references therein] (Figure 14a). Continental-scale tectonic events caused intense fracturing and gentle folding in the carbonate layers, which served as preferential pathways to ascending hydrothermal fluids under confined conditions [38,40] (Figure 14b). Upwelling acidic groundwater from deep hydrothermal sources dissolved carbonate minerals in a confined environment of high chemical and hydrodynamic energies (Figure 14c). Karstification by total removal of dissolved material resulted in enlarged fractures and cavities (Figure 14d), culminating in the development of the longest cave system in South America [51]. Klimchouk et al. [38] identified at least three speleo-stratigraphic stories in the caves of the northern sector of the Irecê basin, whose mechanical and fracture stratigraphy controlled the rising fluid recharge, lateral distribution and outflow components [52]. This process spread out to the whole carbonate platform of the Neoproterozoic basin, including the Iraquara cave system.

Figure 14 
                  Schematic cartoon showing the evolution of the Iraquara karst system: Depositional and diagenetic stage (a); tectonic events caused fractures and gentle folding of the carbonate layers (b); upwelling hydrothermal fluids from deep sources under confined conditions along preferential pathways (red arrows) (c); hypogenic karstification by total removal of the dissolved bedrock (d); and superficial ghost-karstification nucleated along the fractures and beddings and formation of residual soil (e).
Figure 14

Schematic cartoon showing the evolution of the Iraquara karst system: Depositional and diagenetic stage (a); tectonic events caused fractures and gentle folding of the carbonate layers (b); upwelling hydrothermal fluids from deep sources under confined conditions along preferential pathways (red arrows) (c); hypogenic karstification by total removal of the dissolved bedrock (d); and superficial ghost-karstification nucleated along the fractures and beddings and formation of residual soil (e).

On the basis of the topographic and geophysical data and field observations, we verified that a posterior epigenic ghost-rock karstification used the same fracture and bedding networks to control meteoric water infiltration and dissolve the carbonate rocks. This process formed from alterites and residual soil under low-hydrodynamic conditions (Figure 14e), to karst landforms, where fracture corridors are present, channeling and potentiating hydrodynamic energy. In the macro- to mega-scales, structural control is evidenced by vertical high-amplitude GPR zones related to unweathered carbonate rocks. In contrast, low-amplitude GPR signals (shadow zones) characterize alterites and residual soil (Figures 11 and 12). At the mega- to giga-scales, the spatial distribution of karst landforms and cave entrances are concentrated in the central valley, as unveiled by topographic and magnetic lineaments [22] and high-gradient gravity zones. A synthesis of the different types of karst features found in the Iraquara karst system is shown in Figure 13.

6 Conclusions

This contribution combined shallow subsurface GPR, ERT, and gravity data with a digital elevation model. By integrating these multidisciplinary and multiscale datasets, we detected and spatially characterized the Iraquara karst system in carbonate units in the Brazilian semiarid region. The karst system comprises a long network of caves overlain by an epigenic ghost-rock karstification covering a much wider region. The karstification processes caused by chemical dissolution and mechanical removal were controlled by orthogonal fracture corridors and gentle folding, which channelized acidic underground fluids and provided hydrodynamic energy conditions for the total removal of dissolved material, causing the collapse of cave roofs and forming karst landforms.

Cave entrances, karst landforms, and surface drainage preferentially occur along topographic lineaments associated with the Irecê basin structural framework. This indicates the importance of structural-tectonic conditions in developing the Iraquara karst system. An ∼30 km2 area delimits the central portion of the main karstic zone with a high gravity gradient, which concentrates the cave system and karst landform network as indicated in the doline density map. The 2.5D gravity modeling also reveals an up-to-600-m-thick sedimentary pile underlying the Iraquara karst system, with an E-W-oriented synform geometry. The subvertical boundaries of the graben-like structure within the basin coincide with the NNW-SSE direction of the regional dextral transtensional tectonics, which concentrated fracture corridors and overprinted karst networks along the hinge zones. In the same way, the surface drainage is also controlled by this structural setting, as indicated by the detailed digital elevation model. This structural control probably remained active during the different karstification episodes throughout the long-term karstogenetic evolution of the Neoproterozoic carbonate platform.

At the macro- to mega-scales, ERT and GPR data constrained by field observations allowed us to detect and characterize the near-surface karstification and the interconnectivity between karst landforms and the cave network. We also demonstrated a clear link between vertical high-amplitude GPR zones and underground fresh rock towers within the residual alterite, whose GPR signal is strongly attenuated. The tower-like structures are segmented into blocks since the weathering spreads preferentially from the stratified bedding and fracture corridors. In the ERT profiles, we could identify high-resistivity zones associated with cave passages between 20 and 45 m deep, connecting the karst landform network. These underground passages are revealed at the doline cliffs, where the remotion of the residual alterite formed rectangular towers and pinnacles around the collapsed features.

The Iraquara karst system exhibits three well-defined domains. In the central part of the carbonate valley, intense hydrodynamic flow promoted underground karstification (cave network – Domain 1) and superficial karstification (dolines, uvalas, and karst valleys – Domain 2) by total removal of the dissolved material. In this region, fracture corridors potentiate the hydrodynamic regime, while in areas farther from the fracture zones, ghost-rock karstification (Domain 3) preferentially promotes the development of residual weathered carbonate rocks (alterites) and soil under low hydrodynamic conditions without the formation of cavities and collapsed features. In all karst domains, the main pathways for meteoric water infiltration were vertical joints and slightly arched bedding planes.

Acknowledgments

This research was carried out in association with the ongoing R&D project registered as ANP 20502–1, Processos e Propriedades em Reservartórios Carbonáticos Fraturados e Carstificados – POROCARSTE 3D (UFRN/UNB/UFRJ/UFC/Shell Brasil/ANP) – Porokarst – Processes and Properties in Fractured and Karstified Carbonate Reservoirs, sponsored by Shell Brasil under the ANP R&D levy as “Compromisso de Investimento com Pesquisa e Desenvolvimento.” We acknowledge the Companhia Baiana de Pesquisa Mineral (CBPM), which provided magnetic data used in the present study. DLC and FHB thank the Brazilian National Council for Scientific and Technological Development (CNPq) for their productivity grants. We thank Grupo Bambuí de Pesquisas Espeleológicas for providing the cave entrance locations. We also thank Iuriane M. M. Conti and Francisco Tomaz Bezerra, who helped acquire and process the geophysical data.

  1. Author contributions: D.L. de Castro: Conceptualization, Data curation, Methodology, Investigation, Formal analysis, Validation, Visualization, Writing – Original Draft, Writing – review & editing, Supervision, Project administration, Funding acquisition. F.H.R. Bezerra: Conceptualization, Data curation, Methodology, Investigation, Validation, Writing – review & editing. J.G. Oliveira Jr: Investigation, Validation, Writing – review & editing.

  2. Conflict of interest: Authors state no conflict of interest.

  3. Data availability statement: Data are available upon request to the authors.

References

[1] Ehrenberg SN, Nadeau PH. Sandstone vs carbonate petroleum reservoirs: A global perspective on porosity-depth and porosity-permeability relationships. AAPG Bull. 2005;89(4):435–45.10.1306/11230404071Search in Google Scholar

[2] Parise M, de Waele J, Gutierrez F. Engineering and environmental problems in karst - An introduction. Eng Geol. 2008;99:91–4.10.1016/j.enggeo.2007.11.009Search in Google Scholar

[3] Pueyo-Anchuela Ó, Casas-Sainz AM, Soriano MA, Pocoví-Juan A. A geophysical survey routine for the detection of doline areas in the surroundings of Zaragoza (NE Spain). Eng Geol. 2010;114:382–96.10.1016/j.enggeo.2010.05.015Search in Google Scholar

[4] De Waele J, Gutiérrez F, Parise M, Plan L. Geomorphology and natural hazards in karst areas: a review. Geomorphology. 2011;134:1–8.10.1016/j.geomorph.2011.08.001Search in Google Scholar

[5] Martínez-Moreno FJ, Pedrera A, Ruano P, Galindo-Zaldívar J, Martos-Rosillo S, González-Castillo L, et al. Combined microgravity, electrical resistivity tomography and induced polarization to detect deeply buried caves: Algaidilla cave (southern Spain). Eng Geol. 2013;162:67–78.10.1016/j.enggeo.2013.05.008Search in Google Scholar

[6] Benjumea B, Gabàs A, Macau A, Ledo J, Bellmunt F, Figueras S, et al. Undercover karst imaging using a Fuzzy c-means data clustering approach (Costa Brava, NE Spain). Eng Geol. 2021;293:106327.10.1016/j.enggeo.2021.106327Search in Google Scholar

[7] Dubois C, Quinif Y, Baele JM, Barriquand L, Bini A, Bruxelles L, et al. The process of ghost-rock karstification and its role in the formation of cave systems. Earth Sci Rev. 2014;131:116–48.10.1016/j.earscirev.2014.01.006Search in Google Scholar

[8] Kaufmann O, Deceuster J. Detection and mapping of ghost-rock features in the Tournaisis area through geophysical methods - an overview. Geologica Belgica. 2014;17:17–26.Search in Google Scholar

[9] Quinif Y. Ghost rock structures and the nature of Azé Caves. Quaternaire. 2011;4:7–14 (Special Issue).Search in Google Scholar

[10] Bagni FL, Bezerra FHR, Balsamo F, Maia RP, Dall’Aglio M. Karst dissolution along fracture corridors in an anticline hinge, Jandaíra Formation, Brazil: implications for reservoir quality. Mar Pet Geol. 2020;115:104249.10.1016/j.marpetgeo.2020.104249Search in Google Scholar

[11] Furtado CPQ, Borges SVF, Bezerra FHR, de Castro DL, Maia RP, Teixeira WLE, et al. The fracture-controlled carbonate Brejões Karst System mapped with UAV, LiDAR, and electroresistivity in the Irecê Basin – Brazil. J South Am Earth Sci. 2022;119:103986.10.1016/j.jsames.2022.103986Search in Google Scholar

[12] Chalikakis K, Plagnes V, Guerin R, Valois R, Bosch FP. Contribution of geophysical methods to karst-system exploration: an overview. Hydrogeol J. 2011;19(6):1169–80.10.1007/s10040-011-0746-xSearch in Google Scholar

[13] Martel R, Castellazz P, Gloaguen E, Trépanier L, Garfias J. ERT, GPR, InSAR, and tracer tests to characterize karst aquifer systems under urban areas: the case of Quebec City. Geomorphology. 2018;310:45–56.10.1016/j.geomorph.2018.03.003Search in Google Scholar

[14] Lu X, Wang Y, Tian F, Li X, Yang D, Li T, et al. New insights into the carbonate karstic fault system and reservoir formation in the Southern Tahe area of the Tarim Basin. Mar Pet Geol. 2017;86:587–605.10.1016/j.marpetgeo.2017.06.023Search in Google Scholar

[15] Argentieri A, Carluccio R, Cecchini F, Chiappini M, Ciotoli G, De Ritis R, et al. Early stage sinkhole formation in the Acque Albule basin of Central Italy from geophysical and geochemical observations. Eng Geol. 2015;191:36–47.10.1016/j.enggeo.2015.03.010Search in Google Scholar

[16] Fernandes AL, Medeiros WE, Bezerra FHR, Oliveira JG, Cazarin CL. GPR investigation of karst guided by comparison with outcrop and unmanned aerial vehicle imagery. J Appl Geophys. 2015;112:268–78.10.1016/j.jappgeo.2014.11.017Search in Google Scholar

[17] Reis Jr. JA, de Castro DL, Casas AP, Benomar MH, Lima Filho FP. ERT and GPR survey of collapsed paleocave systems at the western border of the Potiguar Basin in northeast Brazil. Surf Geophys. 2015;13:369–81.10.3997/1873-0604.2015013Search in Google Scholar

[18] Grandjean G, Leparoux D. The potential of seismic methods for detecting cavities and buried objects: Experimentation at a test site. J Appl Geophys. 2004;56:93–106.10.1016/j.jappgeo.2004.04.004Search in Google Scholar

[19] Amanatidou E, Vargemezis G, Tsourlos P. Combined application of seismic and electrical geophysical methods for karst cavities detection: A case study at the campus of the new University of Western Macedonia, Kozani, Greece. J Appl Geophys. 2022;196:104499.10.1016/j.jappgeo.2021.104499Search in Google Scholar

[20] Rybakov M, Rotstein Y, Shirman B, Al-Zoubi A. Cave detection near the Dead Sea - a micromagnetic feasibility study. Lead Edge. 2005;24(6):585–90.10.1190/1.1946210Search in Google Scholar

[21] Silva OL, Bezerra FHR, Maia RP, Cazarin CL. Karst landforms revealed at various scales using LiDAR and UAV in semiarid Brazil: consideration on karstification processes and methodological constraints. Geomorphology. 2017;295:611–30.10.1016/j.geomorph.2017.07.025Search in Google Scholar

[22] Cazarin CL, van der Velde R, Santos RV, Reijmer JJG, Bezerra FHR, Bertotti G, et al. Hydrothermal activity along a strike-slip fault zone and host units in the São Francisco Craton, Brazil – Implications for fluid flow in sedimentary basins. Precambrian Res. 2021;365:106365.10.1016/j.precamres.2021.106365Search in Google Scholar

[23] He L, Feng M, He Z, Wang X. Application of EM methods for the investigation of Qiyueshan tunnel, China. J Environ Eng Geophys. 2006;11:151–6.10.2113/JEEG11.2.151Search in Google Scholar

[24] Mochales T, Casas AM, Pueyo EL, Román MT, Pocoví A, Soriano MA, et al. Detection of underground cavities by combining gravity, magnetic and ground penetrating radar surveys: a case study from the Zaragoza area, NE Spain. Environ Geol. 2008;53:1067–77.10.1007/s00254-007-0733-7Search in Google Scholar

[25] Harun AR, Samsudin AR. Application of gravity survey for geological mapping and cavity detection: Malaysian case studies. Electron J Geotech Eng. 2014;19:8247–59.Search in Google Scholar

[26] Park MK, Park S, Yi MJ, Kim C, Son JS, Kim JH, et al. Application of electrical resistivity tomography (ERT) technique to detect underground cavities in a karst area of South Korea. Environ Earth Sci. 2014;71:2797–2806.10.1007/s12665-013-2658-7Search in Google Scholar

[27] Beres M, Luetscher M, Olivier R. Integration of ground-penetrating radar and microgravimetric methods to map shallow caves. J Appl Geophysics. 2001;46:249–62.10.1016/S0926-9851(01)00042-8Search in Google Scholar

[28] Kruse S, Grasmueck M, Weiss M, Viggiano D. Sinkhole structure imaging in covered karst terrain. Geophys Res Lett. 2006;33:L16405.10.1029/2006GL026975Search in Google Scholar

[29] Hojat A, Zanzi L, Loke MH, Ranjbar H, Karimi-Nasab S. Integration of geoengineering techniques to map hidden qanats at Shahid Bahonar University of Kerman. 24th European Meeting of Environmental and Engineering Geophysics. Porto: 2018.10.3997/2214-4609.201802529Search in Google Scholar

[30] Hojat A, Ranjbar H, Karimi-Nasab S, Zanzi L. Laboratory tests and field surveys to explore the optimum frequency for GPR surveys in detecting qanats. Pure Appl Geophys. 2023;180:2389–405.10.1007/s00024-023-03272-4Search in Google Scholar

[31] Alsharahi G, Faize A, Maftei C, Bayjja M, Louzazni M, Driouach A, et al. Analysis and modeling of GPR signals to detect cavities: case studies in Morocco. J Electromagnetic Eng Sci. 2019;19(3):177–87.10.26866/jees.2019.19.3.177Search in Google Scholar

[32] Dalton de Souza J, Kosin M, Melo RC, Santos RA, Teixeira LR, Sampaio AR, et al. Mapa geológico do Estado da Bahia – Escala 1:1.000.000. Salvador: CPRM, 2003. Versão 1.1. Programas Carta Geológica do Brasil ao Milionésimo e Levantamentos Geológicos Básicos do Brasil (PLGB). Convênio de Cooperação e Apoio Técnico-Científico CBPM/CPRM; 2003.Search in Google Scholar

[33] Pontes CC, Bezerra FH, Bertotti G, La Bruna V, Audra P, De Waele J, et al. Flow pathways in multiple-direction fold hinges: implications for fractured and karstified carbonate reservoirs. J Struct Geol. 2021;146:10432.10.1016/j.jsg.2021.104324Search in Google Scholar

[34] Cazarin CL, Bezerra FHR, Borghi L, Santos RV, Favoreto J, Brod JA, et al. The conduit-seal system of hypogene karst in Neoproterozoic carbonates in northeastern Brazil. Mar Pet Geol. 2019;101:90–107.10.1016/j.marpetgeo.2018.11.046Search in Google Scholar

[35] Trompette R, Uhlein A, Egydio-Silva M, Karmann I. The Brasiliano São Francisco craton revisited (Central Brazil). J South Am Earth Sci. 1992;6(1/2):49–57.10.1016/0895-9811(92)90016-RSearch in Google Scholar

[36] Danderfer Filho A, de Waele B, Pedreira AJ, Nalini HA. New geochronological constraints on the geological evolution of Espinhaço basin within the São Francisco Craton – Brazil. Precambrian Res. 2009;170:116–28.10.1016/j.precamres.2009.01.002Search in Google Scholar

[37] D’Angelo T, Barbosa MSC, Danderfer Filho A. Basement controls on cover deformation in eastern Chapada Diamantina, northern São Francisco Craton, Brazil: Insights from potential field data. Tectonophysics. 2019;772:228231.10.1016/j.tecto.2019.228231Search in Google Scholar

[38] Klimchouk A, Auler AS, Bezerra FHR, Cazarin CL, Balsamo F, Dublyansky Y. Hypogenic origin, geologic controls and functional organization of a giant cave system in Precambrian carbonates, Brazil. Geomorphology. 2016;253:385–405.10.1016/j.geomorph.2015.11.002Search in Google Scholar

[39] Auler AS. Karst evolution and paleoclimate of eastern Brazil. PhD Dissertation. UK: University of Bristol; 1999. p. 268.Search in Google Scholar

[40] Ennes-Silva RA, Bezerra FHR, Nogueira FCC, Balsamo F, Klimchouk A, Cazarin CL, et al. Superposed folding and associated fracturing influence hypogene karst development in Neoproterozoic carbonates, São Francisco Craton, Brazil. Tectonophysics. 2015;666:244–59.10.1016/j.tecto.2015.11.006Search in Google Scholar

[41] Cruz Jr. FW. Aspectos Geomorfológicos e Geoespeleologia do Carste da Região de Iraquara, Centro-Norte da Chapada Diamantina, Estado da Bahia. MSc thesis. 1998;126 Brazil: Universidade de São Paulo.Search in Google Scholar

[42] Salles LQ, Galvão P, Leal LRB. Pereira RGFA, Purificação CGC, Laureano FV. Evaluation of susceptibility for terrain collapse and subsidence in karst areas, municipality of Iraquara, Chapada Diamantina (BA), Brazil. Environ Earth Sci. 2018;77(593):11.10.1007/s12665-018-7769-8Search in Google Scholar

[43] Silverman BW. Density estimation for statistics and data analysis. 1st edn. London: Routledge; 1998. p. 176.Search in Google Scholar

[44] Geosoft. Oasis Montaj 7.5 Mapping and Processing System. Quick Start Tutorials, Geosoft Incorporated. 2013; 258Search in Google Scholar

[45] Loke MH. Rapid 3-D Resistivity & IP inversion using the least-squares method. Manual for Res2dinv ver. 3.54; 2004.Search in Google Scholar

[46] Telford WM, Geldart LP, Sheriff RE. Applied geophysics. 2nd edn. New York: Cambridge University Press; 1990. p. 770.10.1017/CBO9781139167932Search in Google Scholar

[47] Borges SVF, Balsamo F, Vieira MM, Iacumin P, Srivastava NK, Storti F, et al. Pedogenic calcretes within fracture systems and beddings in Neoproterozoic limestones of the Irecê Basin, northeastern Brazil. Sediment Geol. 2016;341:119–33.10.1016/j.sedgeo.2016.05.012Search in Google Scholar

[48] Conti IMM, de Castro DL, Bezerra FHR, Cazarin CL. Porosity estimation and geometric characterization of fractured and karstified carbonate rocks using GPR data in the Salitre Formation, Brazil. Pure Appl Geophys. 2019;176:1673–89.10.1007/s00024-018-2032-5Search in Google Scholar

[49] Mohamed AME, El-Hussain I, Deif A, Araffa SAS, Man-sour K, Al-Rawas G. Integrated ground penetrating radar, electrical resistivity tomography and multichannel analysis of surface waves for detecting near-surface caverns at Duqmarea, Sultanate of Oman. Surf Geophys. 2019;17(4):379–401.10.1002/nsg.12054Search in Google Scholar

[50] Fairchild IJ, Baker A. Speleothem Science: From Process to Past Environments. Wiley-Blackwel; 2012. p. 432.10.1002/9781444361094Search in Google Scholar

[51] Auler AS, Smart PL. The influence of bedrock-derived acidity in the development of surface and underground karst: evidence from the Precambrian carbonates of semiarid northeastern Brazil. Earth Surf Process Landf. 2003;28:157–68.10.1002/esp.443Search in Google Scholar

[52] Balsamo F, Bezerra FHR, Klimchouk AB, Cazarin CL, Auler AS, Nogueira FC, et al. Influence of fracture stratigraphy on hypogene cave development and fluid flow anisotropy in layered carbonates, NE Brazil. Mar Pet Geol. 2020;114:104207.10.1016/j.marpetgeo.2019.104207Search in Google Scholar

Received: 2023-09-14
Revised: 2023-11-14
Accepted: 2024-01-22
Published Online: 2024-02-29

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Regular Articles
  2. Theoretical magnetotelluric response of stratiform earth consisting of alternative homogeneous and transitional layers
  3. The research of common drought indexes for the application to the drought monitoring in the region of Jin Sha river
  4. Evolutionary game analysis of government, businesses, and consumers in high-standard farmland low-carbon construction
  5. On the use of low-frequency passive seismic as a direct hydrocarbon indicator: A case study at Banyubang oil field, Indonesia
  6. Water transportation planning in connection with extreme weather conditions; case study – Port of Novi Sad, Serbia
  7. Zircon U–Pb ages of the Paleozoic volcaniclastic strata in the Junggar Basin, NW China
  8. Monitoring of mangrove forests vegetation based on optical versus microwave data: A case study western coast of Saudi Arabia
  9. Microfacies analysis of marine shale: A case study of the shales of the Wufeng–Longmaxi formation in the western Chongqing, Sichuan Basin, China
  10. Multisource remote sensing image fusion processing in plateau seismic region feature information extraction and application analysis – An example of the Menyuan Ms6.9 earthquake on January 8, 2022
  11. Identification of magnetic mineralogy and paleo-flow direction of the Miocene-quaternary volcanic products in the north of Lake Van, Eastern Turkey
  12. Impact of fully rotating steel casing bored pile on adjacent tunnels
  13. Adolescents’ consumption intentions toward leisure tourism in high-risk leisure environments in riverine areas
  14. Petrogenesis of Jurassic granitic rocks in South China Block: Implications for events related to subduction of Paleo-Pacific plate
  15. Differences in urban daytime and night block vitality based on mobile phone signaling data: A case study of Kunming’s urban district
  16. Random forest and artificial neural network-based tsunami forests classification using data fusion of Sentinel-2 and Airbus Vision-1 satellites: A case study of Garhi Chandan, Pakistan
  17. Integrated geophysical approach for detection and size-geometry characterization of a multiscale karst system in carbonate units, semiarid Brazil
  18. Spatial and temporal changes in ecosystem services value and analysis of driving factors in the Yangtze River Delta Region
  19. Deep fault sliding rates for Ka-Ping block of Xinjiang based on repeating earthquakes
  20. Improved deep learning segmentation of outdoor point clouds with different sampling strategies and using intensities
  21. Platform margin belt structure and sedimentation characteristics of Changxing Formation reefs on both sides of the Kaijiang-Liangping trough, eastern Sichuan Basin, China
  22. Enhancing attapulgite and cement-modified loess for effective landfill lining: A study on seepage prevention and Cu/Pb ion adsorption
  23. Flood risk assessment, a case study in an arid environment of Southeast Morocco
  24. Lower limits of physical properties and classification evaluation criteria of the tight reservoir in the Ahe Formation in the Dibei Area of the Kuqa depression
  25. Evaluation of Viaducts’ contribution to road network accessibility in the Yunnan–Guizhou area based on the node deletion method
  26. Permian tectonic switch of the southern Central Asian Orogenic Belt: Constraints from magmatism in the southern Alxa region, NW China
  27. Element geochemical differences in lower Cambrian black shales with hydrothermal sedimentation in the Yangtze block, South China
  28. Three-dimensional finite-memory quasi-Newton inversion of the magnetotelluric based on unstructured grids
  29. Obliquity-paced summer monsoon from the Shilou red clay section on the eastern Chinese Loess Plateau
  30. Classification and logging identification of reservoir space near the upper Ordovician pinch-out line in Tahe Oilfield
  31. Ultra-deep channel sand body target recognition method based on improved deep learning under UAV cluster
  32. New formula to determine flyrock distance on sedimentary rocks with low strength
  33. Assessing the ecological security of tourism in Northeast China
  34. Effective reservoir identification and sweet spot prediction in Chang 8 Member tight oil reservoirs in Huanjiang area, Ordos Basin
  35. Detecting heterogeneity of spatial accessibility to sports facilities for adolescents at fine scale: A case study in Changsha, China
  36. Effects of freeze–thaw cycles on soil nutrients by soft rock and sand remodeling
  37. Vibration prediction with a method based on the absorption property of blast-induced seismic waves: A case study
  38. A new look at the geodynamic development of the Ediacaran–early Cambrian forearc basalts of the Tannuola-Khamsara Island Arc (Central Asia, Russia): Conclusions from geological, geochemical, and Nd-isotope data
  39. Spatio-temporal analysis of the driving factors of urban land use expansion in China: A study of the Yangtze River Delta region
  40. Selection of Euler deconvolution solutions using the enhanced horizontal gradient and stable vertical differentiation
  41. Phase change of the Ordovician hydrocarbon in the Tarim Basin: A case study from the Halahatang–Shunbei area
  42. Using interpretative structure model and analytical network process for optimum site selection of airport locations in Delta Egypt
  43. Geochemistry of magnetite from Fe-skarn deposits along the central Loei Fold Belt, Thailand
  44. Functional typology of settlements in the Srem region, Serbia
  45. Hunger Games Search for the elucidation of gravity anomalies with application to geothermal energy investigations and volcanic activity studies
  46. Addressing incomplete tile phenomena in image tiling: Introducing the grid six-intersection model
  47. Evaluation and control model for resilience of water resource building system based on fuzzy comprehensive evaluation method and its application
  48. MIF and AHP methods for delineation of groundwater potential zones using remote sensing and GIS techniques in Tirunelveli, Tenkasi District, India
  49. New database for the estimation of dynamic coefficient of friction of snow
  50. Measuring urban growth dynamics: A study in Hue city, Vietnam
  51. Comparative models of support-vector machine, multilayer perceptron, and decision tree ‎predication approaches for landslide ‎susceptibility analysis
  52. Experimental study on the influence of clay content on the shear strength of silty soil and mechanism analysis
  53. Geosite assessment as a contribution to the sustainable development of Babušnica, Serbia
  54. Using fuzzy analytical hierarchy process for road transportation services management based on remote sensing and GIS technology
  55. Accumulation mechanism of multi-type unconventional oil and gas reservoirs in Northern China: Taking Hari Sag of the Yin’e Basin as an example
  56. TOC prediction of source rocks based on the convolutional neural network and logging curves – A case study of Pinghu Formation in Xihu Sag
  57. A method for fast detection of wind farms from remote sensing images using deep learning and geospatial analysis
  58. Spatial distribution and driving factors of karst rocky desertification in Southwest China based on GIS and geodetector
  59. Physicochemical and mineralogical composition studies of clays from Share and Tshonga areas, Northern Bida Basin, Nigeria: Implications for Geophagia
  60. Geochemical sedimentary records of eutrophication and environmental change in Chaohu Lake, East China
  61. Research progress of freeze–thaw rock using bibliometric analysis
  62. Mixed irrigation affects the composition and diversity of the soil bacterial community
  63. Examining the swelling potential of cohesive soils with high plasticity according to their index properties using GIS
  64. Geological genesis and identification of high-porosity and low-permeability sandstones in the Cretaceous Bashkirchik Formation, northern Tarim Basin
  65. Usability of PPGIS tools exemplified by geodiscussion – a tool for public participation in shaping public space
  66. Efficient development technology of Upper Paleozoic Lower Shihezi tight sandstone gas reservoir in northeastern Ordos Basin
  67. Assessment of soil resources of agricultural landscapes in Turkestan region of the Republic of Kazakhstan based on agrochemical indexes
  68. Evaluating the impact of DEM interpolation algorithms on relief index for soil resource management
  69. Petrogenetic relationship between plutonic and subvolcanic rocks in the Jurassic Shuikoushan complex, South China
  70. A novel workflow for shale lithology identification – A case study in the Gulong Depression, Songliao Basin, China
  71. Characteristics and main controlling factors of dolomite reservoirs in Fei-3 Member of Feixianguan Formation of Lower Triassic, Puguang area
  72. Impact of high-speed railway network on county-level accessibility and economic linkage in Jiangxi Province, China: A spatio-temporal data analysis
  73. Estimation model of wild fractional vegetation cover based on RGB vegetation index and its application
  74. Lithofacies, petrography, and geochemistry of the Lamphun oceanic plate stratigraphy: As a record of the subduction history of Paleo-Tethys in Chiang Mai-Chiang Rai Suture Zone of Thailand
  75. Structural features and tectonic activity of the Weihe Fault, central China
  76. Application of the wavelet transform and Hilbert–Huang transform in stratigraphic sequence division of Jurassic Shaximiao Formation in Southwest Sichuan Basin
  77. Structural detachment influences the shale gas preservation in the Wufeng-Longmaxi Formation, Northern Guizhou Province
  78. Distribution law of Chang 7 Member tight oil in the western Ordos Basin based on geological, logging and numerical simulation techniques
  79. Evaluation of alteration in the geothermal province west of Cappadocia, Türkiye: Mineralogical, petrographical, geochemical, and remote sensing data
  80. Numerical modeling of site response at large strains with simplified nonlinear models: Application to Lotung seismic array
  81. Quantitative characterization of granite failure intensity under dynamic disturbance from energy standpoint
  82. Characteristics of debris flow dynamics and prediction of the hazardous area in Bangou Village, Yanqing District, Beijing, China
  83. Rockfall mapping and susceptibility evaluation based on UAV high-resolution imagery and support vector machine method
  84. Statistical comparison analysis of different real-time kinematic methods for the development of photogrammetric products: CORS-RTK, CORS-RTK + PPK, RTK-DRTK2, and RTK + DRTK2 + GCP
  85. Hydrogeological mapping of fracture networks using earth observation data to improve rainfall–runoff modeling in arid mountains, Saudi Arabia
  86. Petrography and geochemistry of pegmatite and leucogranite of Ntega-Marangara area, Burundi, in relation to rare metal mineralisation
  87. Prediction of formation fracture pressure based on reinforcement learning and XGBoost
  88. Hazard zonation for potential earthquake-induced landslide in the eastern East Kunlun fault zone
  89. Monitoring water infiltration in multiple layers of sandstone coal mining model with cracks using ERT
  90. Study of the patterns of ice lake variation and the factors influencing these changes in the western Nyingchi area
  91. Productive conservation at the landslide prone area under the threat of rapid land cover changes
  92. Sedimentary processes and patterns in deposits corresponding to freshwater lake-facies of hyperpycnal flow – An experimental study based on flume depositional simulations
  93. Study on time-dependent injectability evaluation of mudstone considering the self-healing effect
  94. Detection of objects with diverse geometric shapes in GPR images using deep-learning methods
  95. Behavior of trace metals in sedimentary cores from marine and lacustrine environments in Algeria
  96. Spatiotemporal variation pattern and spatial coupling relationship between NDVI and LST in Mu Us Sandy Land
  97. Formation mechanism and oil-bearing properties of gravity flow sand body of Chang 63 sub-member of Yanchang Formation in Huaqing area, Ordos Basin
  98. Diagenesis of marine-continental transitional shale from the Upper Permian Longtan Formation in southern Sichuan Basin, China
  99. Vertical high-velocity structures and seismic activity in western Shandong Rise, China: Case study inspired by double-difference seismic tomography
  100. Spatial coupling relationship between metamorphic core complex and gold deposits: Constraints from geophysical electromagnetics
  101. Disparities in the geospatial allocation of public facilities from the perspective of living circles
  102. Research on spatial correlation structure of war heritage based on field theory. A case study of Jinzhai County, China
  103. Formation mechanisms of Qiaoba-Zhongdu Danxia landforms in southwestern Sichuan Province, China
  104. Magnetic data interpretation: Implication for structure and hydrocarbon potentiality at Delta Wadi Diit, Southeastern Egypt
  105. Deeply buried clastic rock diagenesis evolution mechanism of Dongdaohaizi sag in the center of Junggar fault basin, Northwest China
  106. Application of LS-RAPID to simulate the motion of two contrasting landslides triggered by earthquakes
  107. The new insight of tectonic setting in Sunda–Banda transition zone using tomography seismic. Case study: 7.1 M deep earthquake 29 August 2023
  108. The critical role of c and φ in ensuring stability: A study on rockfill dams
  109. Evidence of late quaternary activity of the Weining-Shuicheng Fault in Guizhou, China
  110. Extreme hydroclimatic events and response of vegetation in the eastern QTP since 10 ka
  111. Spatial–temporal effect of sea–land gradient on landscape pattern and ecological risk in the coastal zone: A case study of Dalian City
  112. Study on the influence mechanism of land use on carbon storage under multiple scenarios: A case study of Wenzhou
  113. A new method for identifying reservoir fluid properties based on well logging data: A case study from PL block of Bohai Bay Basin, North China
  114. Comparison between thermal models across the Middle Magdalena Valley, Eastern Cordillera, and Eastern Llanos basins in Colombia
  115. Mineralogical and elemental analysis of Kazakh coals from three mines: Preliminary insights from mode of occurrence to environmental impacts
  116. Chlorite-induced porosity evolution in multi-source tight sandstone reservoirs: A case study of the Shaximiao Formation in western Sichuan Basin
  117. Predicting stability factors for rotational failures in earth slopes and embankments using artificial intelligence techniques
  118. Origin of Late Cretaceous A-type granitoids in South China: Response to the rollback and retreat of the Paleo-Pacific plate
  119. Modification of dolomitization on reservoir spaces in reef–shoal complex: A case study of Permian Changxing Formation, Sichuan Basin, SW China
  120. Geological characteristics of the Daduhe gold belt, western Sichuan, China: Implications for exploration
  121. Rock physics model for deep coal-bed methane reservoir based on equivalent medium theory: A case study of Carboniferous-Permian in Eastern Ordos Basin
  122. Enhancing the total-field magnetic anomaly using the normalized source strength
  123. Shear wave velocity profiling of Riyadh City, Saudi Arabia, utilizing the multi-channel analysis of surface waves method
  124. Effect of coal facies on pore structure heterogeneity of coal measures: Quantitative characterization and comparative study
  125. Inversion method of organic matter content of different types of soils in black soil area based on hyperspectral indices
  126. Detection of seepage zones in artificial levees: A case study at the Körös River, Hungary
  127. Tight sandstone fluid detection technology based on multi-wave seismic data
  128. Characteristics and control techniques of soft rock tunnel lining cracks in high geo-stress environments: Case study of Wushaoling tunnel group
  129. Influence of pore structure characteristics on the Permian Shan-1 reservoir in Longdong, Southwest Ordos Basin, China
  130. Study on sedimentary model of Shanxi Formation – Lower Shihezi Formation in Da 17 well area of Daniudi gas field, Ordos Basin
  131. Multi-scenario territorial spatial simulation and dynamic changes: A case study of Jilin Province in China from 1985 to 2030
  132. Review Articles
  133. Major ascidian species with negative impacts on bivalve aquaculture: Current knowledge and future research aims
  134. Prediction and assessment of meteorological drought in southwest China using long short-term memory model
  135. Communication
  136. Essential questions in earth and geosciences according to large language models
  137. Erratum
  138. Erratum to “Random forest and artificial neural network-based tsunami forests classification using data fusion of Sentinel-2 and Airbus Vision-1 satellites: A case study of Garhi Chandan, Pakistan”
  139. Special Issue: Natural Resources and Environmental Risks: Towards a Sustainable Future - Part I
  140. Spatial-temporal and trend analysis of traffic accidents in AP Vojvodina (North Serbia)
  141. Exploring environmental awareness, knowledge, and safety: A comparative study among students in Montenegro and North Macedonia
  142. Determinants influencing tourists’ willingness to visit Türkiye – Impact of earthquake hazards on Serbian visitors’ preferences
  143. Application of remote sensing in monitoring land degradation: A case study of Stanari municipality (Bosnia and Herzegovina)
  144. Optimizing agricultural land use: A GIS-based assessment of suitability in the Sana River Basin, Bosnia and Herzegovina
  145. Assessing risk-prone areas in the Kratovska Reka catchment (North Macedonia) by integrating advanced geospatial analytics and flash flood potential index
  146. Analysis of the intensity of erosive processes and state of vegetation cover in the zone of influence of the Kolubara Mining Basin
  147. GIS-based spatial modeling of landslide susceptibility using BWM-LSI: A case study – city of Smederevo (Serbia)
  148. Geospatial modeling of wildfire susceptibility on a national scale in Montenegro: A comparative evaluation of F-AHP and FR methodologies
  149. Geosite assessment as the first step for the development of canyoning activities in North Montenegro
  150. Urban geoheritage and degradation risk assessment of the Sokograd fortress (Sokobanja, Eastern Serbia)
  151. Multi-hazard modeling of erosion and landslide susceptibility at the national scale in the example of North Macedonia
  152. Understanding seismic hazard resilience in Montenegro: A qualitative analysis of community preparedness and response capabilities
  153. Forest soil CO2 emission in Quercus robur level II monitoring site
  154. Characterization of glomalin proteins in soil: A potential indicator of erosion intensity
  155. Power of Terroir: Case study of Grašac at the Fruška Gora wine region (North Serbia)
  156. Special Issue: Geospatial and Environmental Dynamics - Part I
  157. Qualitative insights into cultural heritage protection in Serbia: Addressing legal and institutional gaps for disaster risk resilience
Downloaded on 16.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/geo-2022-0606/html
Scroll to top button