Journal of Applied Geophysics 192 (2021) 104395

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Journal of Applied Geophysics

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Detecting active faults in intramountain basins using electrical resistivity

tomography: A focus on Kashmir Basin, NW Himalaya
Hamid Sana a, *, 1, Petr Taborik a, Jan Valenta a, Fayaz A. Bhat b, Jan Flašar a,
Petra Štěpančíkova a, Nisar A. Khwaja b
a
Institute of Rock Structure and Mechanics, Czech Academy of Sciences, V Holesovickach 41, Prague 18209, Czech Republic
b
Deparment of Geology and Mining, Srinagar, 190018, Jammu and Kashmir, India

A R T I C L E I N F O A B S T R A C T

Keywords: Kashmir basin in the NW Himalaya is surrounded by the main Himalayan boundary faults, has very well
Active tectonics documented historical earthquakes and a good instrumental earthquake record. However, the causative faults of
Electrical resistivity tomography these earthquakes except the 8 October 2005 Kashmir earthquake (M7.6) are not known. One of many historical
Kashmir basin
earthquakes that have struck and caused damage and destruction in the Kashmir basin is the 30 May 1885
NW Himalaya
Kashmir earthquake (~M6.3). The extensive damage due to this earthquake was reported in the NW part of the
basin and as usual the causative fault is not known and mapped. As the earthquake related geomorphic features
are not preserved due to the high erosion rates in the Kashmir Himalaya, we mapped certain active fault strands
using high resolution digital elevation models (DEM) and the Google Earth imagery, later complemented by the
field investigation in the NW Kashmir. The Electrical Resistivity Tomography (ERT) was carried out at certain
identified sites in the macroseismic epicentral area of the 1885 Kashmir earthquake. The results show a local
active normal fault which was named as the NW Kashmir fault. The ERT results were confirmed by excavating a
trench and an already existing road cut at the ERT sites. The results show that ERT is a very useful shallow
geophysical method to detect faults in the Karewas. Karewas are the Plio-Pleistocene and Holocene (reworked by
rivers), fluvio-lacustrine, soft and unconsolidated, sand-clay-conglomerate sediments, deposited as distinct table-
land geomorphic features in the Kashmir basin and are significantly water saturated.

1. Introduction in the NW Himalaya, where the peripheral Paleozoic and Mesozoic

formations are overlain by about 1300 m thick alluvium. The deposition
Kashmir basin is one the most significant tectonic features of the of this alluvium started about ~4 million years ago. This alluvium
northwestern Himalaya (Fig. 1). The seismic hazard is high along the consists of two distinct classes: the Plio-Pleistocene Karewas and the
entire Himalayan arc (Stevens and Avouac, 2015; Dal Zilio et al., 2020) Late Pleistocene-Holocene fluvial sediments. Sedimentologically, Kar­
and Kashmir basin is no exception to it (Sana, 2019). As per GPS mea­ ewas are soft, unconsolidated sand-clay-conglomerate deposits while as
surements, the ongoing convergence between India and Eurasia is 40 the fluvial deposits show loose compaction (e.g., Burbank and Johnson,
mm/year and almost half of this convergence, 14–21 mm/year 1982; Sana and Nath, 2016b). The lithology map of the Kashmir basin is
depending on the location, is accommodated along the Himalayan arc shown as Fig. 1b.
(e.g., Jouanne et al., 2004). The geodetic measurements in the Kashmir There is an ongoing debate, to determine the compressional or
Himalaya show a convergence of 13.6 (±1) mm/year (Schiffman et al., extensional tectonic evolution of the Kashmir basin based on the geo­
2013; Kundu et al., 2014) but the tectonic complexity of this part of morphology of the basin, for e.g., see Shah (2013) and Alam et al.
Himalaya as compared to the central Himalaya makes it difficult to (2015). Kashmir basin is surrounded by the Main Himalayan boundary
assign the convergence rates to specific faults in the region (Sana and faults like the Main Mantle Thrust (MMT), Panjal Thrust (PT) and the
Nath, 2017). Main Boundary Thrust (MBT), and out-of-sequence faults like the
Kashmir basin is a Neogene-Quaternary intermountain tectonic basin Balakot-Bagh Fault (B-BF) and the Reasi Thrust (RT). But only one

* Corresponding author.
E-mail addresses: sana@irsm.cas.cz, hamid.sana@jpl.nasa.gov (H. Sana).
1
Pressent address: Jet Propulsion Laboratory (NASA), California Institute of Technology, 4800 Oak Grove Drive, Pasadena, California 91109, United States

https://doi.org/10.1016/j.jappgeo.2021.104395
Received 31 December 2020; Received in revised form 22 May 2021; Accepted 15 June 2021
Available online 18 June 2021
0926-9851/© 2021 Elsevier B.V. All rights reserved.
H. Sana et al. Journal of Applied Geophysics 192 (2021) 104395

Sana et al., 2019b) can be attributed to a specific fault. The seismotec­

tonic map of the Kashmir basin is shown in Fig. 1.
So, to evaluate the seismic hazard in the Kashmir basin the active
fault detection and mapping is imperative especially when extensive
damage is reported in the basin from the historical earthquakes like the
1555 Kashmir earthquake ~M7.6 (Ambrasseys and Douglas, 2004) and
the 1885 Kashmir earthquake ~M6.3 (Ahmad et al., 2014). We identi­
fied few sites based on active tectonic geomorphological signatures
using high resolution digital elevation models (DEM) and the Google
Earth imagery in the macroseismic epicentral area of the 1885 Kashmir
earthquake (~M6.3) in the NW part of the Kashmir basin to look for the
active faults. After field verification, we used Electrical Resistivity To­
mography (ERT) to detect the active faults. We were able to detect an
active fault and named it as the NW Kashmir Fault.

2. Methodology

2.1. 2D and 3D electrical resistivity tomography (ERT)

For the determination of the lithological and structural conditions of

the investigated sites, we used DC resistivity measurements which
represent a quick and versatile geophysical surveying method. Among
the DC resistivity methods, the Electrical Resistivity Tomography (ERT)
is increasingly becoming popular in being used in detection of shallow
faults (E.g., Suzuki et al., 2000; Caputo et al., 2003; Wise et al., 2003;
Rizzo et al., 2004; Nguyen et al., 2007; Fazzito et al., 2009; Improta
et al., 2010; Anchuela et al., 2015; Blecha et al., 2018). In this study, we
carried out the ERT survey at an already identified and suspected fault
site based on the field work in the NW of the Kashmir basin. To obtain 2D
resistivity data points, we used the Wenner-Schlumberger (WS) array
with variable electrode spacings to get required resolution and depth
range, which can highlight both horizontal and vertical geological
structures. The WS configuration is also quite robust as far as the geo­
electrical noise is concerned (Loke, 2000; Zhou et al., 2002; Szalai and
Fig. 1. a: Seismotectonic map of the Kashmir basin and surroundings. MMT: Szarka, 2008; Szalai et al., 2009). Locations of the measured ERT pro­
Main Mantle Thrust, PT: Panjal Thrust, MBT: Main Boundary Thrust, B-BF: files were selected with respect to the anticipated positions of the main
Balakot-Bagh Fault, RT: Reasi Thrust, JF: Jhelum Fault, BF: Balapur Fault, DL:
tectonic features as well as to the later intended 3D processing of the
Drangbal Laridora Fault, HTS: Hazara Thrust System, KF: Kishtwar Fault, HKS:
data. Positions of the measured profiles were fixed using GNSS (GPS)
Hazara-Kashmir Syntaxis. Star shows the epicentral location of the 8 October
device and topographic profiles were obtained by using the laser range
2005 Kashmir earthquake (M7.6). b: Lithology map of the Kashmir basin.
Square shows the location of the Electrical Resistivity Tomography finder TruPulse360 (Trimble) and a prism.
(ERT) survey. The resistivity data were obtained by the ARES resistivity system (GF
Instruments ltd., Czech Republic) using a multi-electrode system of
relatively small fault, Balapur Fault (BF) is geologically mapped in the measurements with a high-power output (300 W and a current up to 2 A)
basin (Fig. 1). There have been some efforts to map the faults in the basin and an arbitrary number of connected electrodes. The measured re­
using remote sensing data (Alam et al., 2015; Sana and Nath, 2016a; sistivity data points were inverted using the Res2Dinv software (Loke
Shah and Malik, 2017) but those structures have not been geologically and Barker, 1996) and 2D electrical resistivity tomography (ERT) sec­
ascertained yet. Kashmir has a rich historical earthquake record (Ahmad tions were obtained. Before carrying out the inversion process, the data
et al., 2009; Sana et al., 2019a; Bilham, 2019) and a fairly good were checked for erroneous values or outliers and the damping factor
instrumental earthquake catalogue as well (Sana and Nath, 2017), but was increased (three-times over the default value) to suppress a possible
none of the significant earthquakes that have shaken the basin except value scatter. After the inversion, data were double-checked using RMS
the 8 October 2005 Kashmir earthquake of M7.6 (Avouac et al., 2006; error statistic and the maximum RMS error was found to be limited to

Table 1
Selected parameters of the ERT measurements.
Profile Site No. of Length Electrode Array Approx. Meas. std. Mean std. dev No. of RMS No. of Total
electrodes [m] spacing [m] type penetration dev limit measured [%] data limit filtered RMS
depth [m] [%] points [%] data points [%]

P1 Chaksari 63 252 4 WS 50 10 0,37 961 10 951 3,4

P1A Chaksari 63 63 1 WS 13 10 0,29 961 10 961 1,3
P2 Chaksari 63 126 2 WS 25 10 0,33 961 10 953 2,5
P3 Chaksari 63 315 5 WS 63 10 0,30 961 10 950 3,6
P4 Chaksari 63 315 5 WS 63 10 0,35 961 10 931 2,9
P5 Chaksari 63 315 5 WS 63 10 0,26 961 10 960 2,4
P6 Chaksari 63 315 5 WS 63 10 0,37 921 10 906 3,1
P7 Chaksari 63 315 5 WS 63 10 0,34 960 10 945 2,6
Delina Delina 63 63 1 WS 13 10 0,16 961 10 941 2,9

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H. Sana et al. Journal of Applied Geophysics 192 (2021) 104395

Fig. 2. Situation of the ERT profiles at Chaksari.

Fig. 4. The histogram of measured resistivity data used for the 3D inversion.
The data form a uniform distribution with no evident outliers.

we performed our survey in three consequent steps. At first, we

measured profiles P1 and P1A, across the expected fault in the trace of
the planned paleoseismological trenching investigation where an active
fault is supposed to run according to the geomorphological observations.
In the P1 profile the electrode spacing was kept 4 m with a total length of
the profile being 252 m. So, that the electric signal could penetrate
deeper (ca 50 m) into the lithology. While as, the P1A profile (length/
spacing = 63/1 m) was more detailed and focused on the anticipated
trenching site. Based on the interpretation of the ERT profiles, the actual
location of the fault and the potential paleoseismic trenching site was
confirmed. Afterwards, we measured profiles P2 – P6, to extend the
Fig. 3. Situation of the ERT profile at Delina site (red solid line). The Karewa information on geology and structures, derived from the trenching site,
outcrop faces to the NW. (For interpretation of the references to colour in this both laterally and to the depth. The profiles were obtained with respect
figure legend, the reader is referred to the web version of this article.) to the continuation of the expected fault zone laterally. Also, so that
there was a sufficient areal coverage and enough data to process the 3D
10%. The obtained filtered datasets were then reinverted. The maximum inversion. The maximum distance between the neighbouring profiles
value of the total RMS error of all yielded models did not exceed 4%. The was kept below 20 m. Finally, profile P7 was taken to extend and
acquired inverted data were transferred into Surfer software. Using confirm the information deduced from the profiles P1 to P6 (Fig. 2) at a
gridding and interpolating functions of Surfer, the dataset was finally farther distance (ca 400 m) from P1 profile and the potential trenching
exaggerated based on the measured topographic profiles and visualised site.
as 2D vertical resistivity sections. In addition, this program allowed At Delina site (Fig. 3), we did a testing ERT measurement, length of
further adjustments of the used unified resistivity scale. The selected the profile was kept 63 m with 1 m spacing following Wenner-
parameters of the measurements and of the final inverse models are Schlumberger electrode array. Here, a natural outcrop of Karewa for­
summarized in Table 1. mation reveals a normal fault named Delina fault, which vertically
Although the 3D inversion of resistivity profile data yields models displaces the sedimentary strata. Thus, we were able to directly compare
with lower resolution then a conventional inversion of 2D profiles, but the ERT results consisting of 2D resistivity section with the actual situ­
the 3D visualisation leads to a better understanding of coherence and ation in the outcrop (Fig. 9).
spatial relation of the individual anomalies. Therefore, the adjacent ERT The 3D inversion was carried out using the BERT software package
profiles (P1 to P6, Figs. 2 and 5) were collated into one dataset for a 3D by Günther et al. (2006) and Rücker et al. (2006). The software uses an
inversion. irregular triangulated mesh for the forward and inverse calculations.
The measured dataset was checked for reliability and data with very The BERT software offers a large modelling flexibility and topography
low measured values of voltage (less than 1 mV) or current (less than 1 adjustments based on the complete (and detailed) digital elevation
mA) were removed along with the few datapoints with very low re­ model, which is especially important in areas with highly varying
sistivity (lower than 18 Ωm). As a result, 19 out of 5730 datapoints were morphology. The necessary elevations of the adjacent terrain were
removed. The remaining data forms a uniform distribution histogram extracted from the 1 Arc-second global SRTM dataset (Farr et al., 2007).
(Fig. 4). In total, the dataset consisted of 5711 measurements and 384 The root mean square (RMS) error of the model after the final (11th)
individual electrode positions. iteration (Fig. 4) was 8.57%, which is a reasonably low error for the 3D
dataset.
3. Results and discussion The final 3D inverse model was exported into the ParaView software
package (version 5.7.0, open source), where a 3D cube was created,
We conducted our ERT survey at two sites in the Kashmir basin: which can be cut and rotated to visualize the appropriate parts of the
Chaksari and Delina in NW Kashmir (Figs. 2 and 3). At the Chaksari site, model. Thus, appropriate sections that display resistivity distribution in

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H. Sana et al. Journal of Applied Geophysics 192 (2021) 104395

Fig. 5. ERT profiles P1 to P6 at Chaksari site. A generalized valley axis is indicated by a dash-and-dot line.

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H. Sana et al. Journal of Applied Geophysics 192 (2021) 104395

Fig. 6. Integrated ERT profile P1 + P3 displays an overall picture of the main valley situation (with approximately symmetrical overlap) and shows the subsurface
structures of both valley banks. Interpreted fault strands are indicated by dashed lines and indexed. A detailed P1A profile (performed in the line of the P1 profile)
shows a situation along the paleoseismological trench excavated. The position of the trench is also marked.

Fig. 7. Showing ERT profile P7 at Chaksari site and its comparison with profile P1. Dashed lines indicate possible fault strands (with indexes) and the offset layers.
Dashed blue circle marks the position of fluvial deposits (flD) confirmed in natural outcrops. Dotted red curve indicates a repeated structure – a vertically displaced
(subsided) Karewas along dip-slip. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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H. Sana et al. Journal of Applied Geophysics 192 (2021) 104395

Fig. 8. Trench along the P1 profile, confirmed the normal faulting infered from the ERT interpretation. a) a view from NE; b) Eastern wall photomosaic with
highlighted fault strands and offset layers.

Fig. 9. ERT investigation of the Delina fault – a) showing the

fault across the Karewa formation; b) ERT profile at Delina site
with an indication of the main Delina fault (“Df”) and possible
secondary fault strand (“f?”). A vertical displacement of the
individual layers is also indicated. A certain discrepancy within
varying resistivity values of deeper layers is very likely caused
by a rapid decrease of the resolution with the depth compared
to the shallower near-surface layers. The apparent difference in
the dip of the fault in the photograph and the ERT section is
caused due to the angular (focal) distortion of the camera lense
while taking the photograph.

the 3D space were visualised and interpreted. ERT section across the main valley having a length of 360 m. The section
is perpendicular to the main valley and it approximately symmetrically
3.1. 2D data interpretation overlaps both rivulet banks and thus provides a broader insight into the
subsurface lithology of the Karewas. A detailed P1A profile (performed
The results of the ERT profiles from P1 to P6 at Chaksari site are in the trace of the P1 profile) shows a situation along the excavated
shown in Fig. 5. A dip-slip offset of the lithological units (e.g. between paleoseismological trench (Fig. 6).
100 and 120 m in the P1 profile) can be clearly seen. The normal fault The exact offset of the layers found in the P1 profile was also found in
was confirmed by digging a trench at the site (Fig. 8) along the P1/P1A the P7 profile situated ca. 400 m south-eastwards of the P1 profile (see
profiles (trench position is indicated in Fig. 6). The profiles from P2 to P6 Fig. 2). The locations of the possible fault strands are indicated by
were taken to extend the information laterally obtained from P1 and comparing the P1 and P7 profiles as shown in Fig. 7. It clearly indicates
P1A profiles which was confirmed in the trench and to provide sufficient continuity of the fault strands between the profiles.
areal coverage and enough data for the 3D interpretation. Fig. 6 in­ At Delina site, the fault is already visible along a road cut. We did an
troduces an integration of the profiles P1 and P3 which represents an ERT profile across this fault, named it Delina fault and compared the

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H. Sana et al. Journal of Applied Geophysics 192 (2021) 104395

Fig. 10. A map view a) and a perspective view b) of the 3D

inverted resistivity data. The white lines in the map view (a)
represents the course of the individual profiles, and as the
white dots in the perspective view (b) map positions of indi­
vidual electrodes. The coordinates used are the WS84/UTM
zone 43 N. The interpreted fault system is depicted with black
lines (solid line shows the fault verified by trenching, broken
line marks interpreted older fault, dash-dot lines marks
younger interpreted fault strands cross-cutting the older ones.

actual offset in the field with the ERT profiles which is shown between cross-cut and displaced by the second, NWN-ESE, system (dash-dot
20 and 30 m of the profile. The fault is shown as a dashed line in the lines).
Fig. 9 and the actual situation in the field is shown in Fig. 10. We propose that this detected shallow normal fault system is shallow
and secondary, while the main system is suspected to be buried
3.2. 3D data interpretation (thrust?). This proposal is made considering the indications of uplift­
ment and folding of the Karewa sediments near the survey sites. The 3D
The interpretation of the 3D resistivity model was focused on map­ interpretation of the dataset clearly shows the advantages of the 3D
ping of the fault zones. In general, the fault zones can be mapped in two model over the 2D profiles, especially in the tectonically complex ter­
ways. First, as conductive zones due to increased degree of weathering rains. Although, the 3D model does not offer the same level of details as
within the fractured zone and a higher water permeability bearing dis­ its 2D counterpart, the spatial relations of the geological structures
solved ions (e.g. Blecha et al., 2018). And, second, as discontinuities in cannot be easily inferred from the individual resistivity profiles.
the resistivity distribution on both sides of the fault if the displacement
along the fault is significant. This way, the individual fault strands were 4. Conclusion
interpreted in the 3D resistivity model in this study (Fig. 10).
The fault zone can be traced as a zone of decreased resistivity (re­ The Electrical Resistivity Tomography (ERT) was used to detect the
sistivities lower than 50 Ωm) mainly in the depth range of 20 m below active faults in the intermountain basin of Kashmir in the NW Himalaya.
the surface in the centre of the investigated area. The fault zone corre­ The Kashmir basin is sandwiched between the Pir Panjal range and
sponds well to the local topography of the terrain (Fig. 10). Neverthe­ Greater Himalayas to the SE and NW, respectively. The ERT survey was
less, the inverted model is detailed enough that it not only enables carried out at two prospective sites in the NW of the basin, Chaksari and
interpretation of the fault zones but also of individual fault strands. Delina. The later site had an already identified fault visible along the
The interpretation of fault strands shows two orthogonal systems of road-cut passing through Delina. The Wenner-Schlumberger array
fault strands, shown as dashed lines and dash-dot lines in Fig. 10. The configuration was used with different electrode spacing to obtain 2D
first fault system is oriented in the NE-SW direction whereas the second resistivity data. The obtained 2D resistivity data was later collated and
one generally follows the NWN-ESE direction. Due to superposition and inverted to develop a 3D model. A 3D map and perspective view of the
cross-cutting of these fault strands it can be inferred that they form two Chaksari study site were then derived from the inverse 3D model. We
sets of fault strands. The NE-SW system (dashed lines) is older as it is were able to detect two secondary active normal faults at both survey

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Acknowledgments DC resistivity data incorporating topography – I. Modelling. Geophys. J. Int. 166,
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First author is grateful to Institute of Rock Structure and Mechanics, Himalaya. Geosci. Lett. 6 (1), 5.
CAS for Long Term Conceptual Development Research Organization Sana, H., Nath, S.K., 2016a. In and around the Hazara-Kashmir dyntaxis: s seismoteconic
and seismic hazard perspective. J. Indian Geophys. Union 20 (5), 496–505.
grant (Grant no: RVO:67985891). First author is also thankful to the Sana, H., Nath, S.K., 2016b. Liquefaction potential analysis of the Kashmir valley
Director Institute of Rock Structure and Mechanics, CAS for the annual alluvium, NW Himalaya. Soil Dyn. Earthq. Eng. 85, 11–18.
research grant (No.617) which made the field trips for this study Sana, H., Nath, S.K., 2017. Seismic source zoning and maximum credible earthquake
prognosis of the greater Kashmir territory, NW Himalaya. J. Seismol. 21 (2),
possible. We are also grateful to Gulzar Ahmad (Sr.) and Gulzar Ahmad 411–424. https://doi.org/10.1007/s10950-016-9608-2.
(Jr.) and the team for their generous help throughout our fieldtrip in Sana, H., Bhat, F.A., Sana, S., 2019a. The ancient temples of Kashmir turned from marvel
Kashmir especially at the Chaksari site. The first author is grateful to to ruin by earthquakes? A case study of the pattan twin temples (AD 883–902).
Seismol. Res. Lett. 90 (1), 358–365.
Thomas Rockwell for discussions on the tectonic geomorphology of the
Sana, H., Nath, S.K., Gujral, K.S., 2019b. Site response analysis of the Kashmir valley
survey sites in the Kashmir basin. We are also grateful to the anonymous during the 8 October 2005 Kashmir earthquake (Mw 7.6) using a geotechnical
reviewers for their comments. Their comments helped in improving the dataset. Bull. Eng. Geol. Environ. 78 (4), 2551–2563.
Schiffman, C., Bali, B.S., Szeliga, W., Bilham, R., 2013. Seismic slip deficit in the Kashmir
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