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\begin{document}

\title{Investigating the effect of soil cracks on preferential flow using
ground-penetration radar surveys and infiltration experiment in karst,
Southwest China}



\author[1]{Fang Hou}%
\author[1]{Jinhua Cheng}%
\author[1]{Ning Guan}%
\affil[1]{Beijing Forestry University}%


\vspace{-1em}



  
  \date{May 26, 2024}


\begingroup
\let\center\flushleft
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\selectlanguage{english}
\begin{abstract}
Soil cracks significantly affect preferential flow; however, there are
some uncertainties associated with the effect of soil cracks on
preferential flow in karst areas in southwest China. In this study,
ground-penetrating radar (GPR) was applied to pedons to investigate the
soil crack properties (inclusion, width, and configuration). Blue dye
tracing experiments were designed, based on geophysical detection
results, to assess the influences of inclusions (sand grains and rock
fragments), crack width (1, 1.5, and 2 cm), and configuration (I-shape,
V-shape, and \selectlanguage{greek}Λ-\selectlanguage{english}shape) on the preferential flow. Our results indicated
that (1) GPR envelope can describe the configuration of isolated soil
cracks; (2) the Brilliant Blue FCF (C.I. Food Blue 2) infiltration rate
and depth were over 1.5 times slower and 1.2--3.8 times lower those of
water, respectively, during infiltration; (3) soil cracks can accelerate
infiltration and increase the maximum dye-penetration depth, cumulative
infiltration, and wetting front depth by at least an average of 5.2\%
and 63.2\%, respectively; and (4) the I- and \selectlanguage{greek}Λ-\selectlanguage{english}shaped soil crack
configurations contributed to preferential flow, while the flow was not
observed along the V-shaped configuration crack pore paths. The I-shaped
configurations, with a width of 1.5 cm, were filled with rock fragments
and had higher preferential flow ratios (18.2\%--52.3\%) and length
indexes (4.0\%--33.8\%) than those of other configurations. Inclusions,
crack widths, and configurations had significant influences on
preferential flow ( \emph{p} \textless{} 0.05). The influence of soil
crack properties on preferential flow cannot be neglected during
vegetation restoration and groundwater security processes in karst
areas.%
\end{abstract}%



\sloppy


\textbf{Investigating the effect of soil cracks on preferential flow
using ground-penetration radar surveys and infiltration experiment in
karst, Southwest China}

Fang Hou\textsuperscript{ID}, Jinhua Cheng, Ning Guan

Jinyun Forest Ecosystem Station, School of Soil and Water Conservation,
Beijing Forestry University, Beijing 100083, PR China

\textbf{Correspondence}

J. H. Cheng, Jinyun Forest Ecosystem Station, School of Soil and Water
Conservation, Beijing Forestry University, Beijing 100083, PR China

E-mail: jinhua\_cheng@126.com

\textbf{Declaration of Interest Statement}

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to
influence the work reported in this paper.

\textbf{Abstract:}Soil cracks significantly affect preferential flow;
however, there are some uncertainties associated with the effect of soil
cracks on preferential flow in karst areas in southwest China. In this
study, ground-penetrating radar (GPR) was applied to pedons to
investigate the soil crack properties (inclusion, width, and
configuration). Blue dye tracing experiments were designed, based on
geophysical detection results, to assess the influences of inclusions
(sand grains and rock fragments), crack width (1, 1.5, and 2 cm), and
configuration (I-shape, V-shape, and \selectlanguage{greek}Λ-\selectlanguage{english}shape) on the preferential flow.
Our results indicated that (1) GPR envelope can describe the
configuration of isolated soil cracks; (2) the Brilliant Blue FCF (C.I.
Food Blue 2) infiltration rate and depth were over 1.5 times slower and
1.2--3.8 times lower those of water, respectively, during infiltration;
(3) soil cracks can accelerate infiltration and increase the maximum
dye-penetration depth, cumulative infiltration, and wetting front depth
by at least an average of 5.2\% and 63.2\%, respectively; and (4) the I-
and \selectlanguage{greek}Λ-\selectlanguage{english}shaped soil crack configurations contributed to preferential flow,
while the flow was not observed along the V-shaped configuration crack
pore paths. The I-shaped configurations, with a width of 1.5 cm, were
filled with rock fragments and had higher preferential flow ratios
(18.2\%--52.3\%) and length indexes (4.0\%--33.8\%) than those of other
configurations. Inclusions, crack widths, and configurations had
significant influences on preferential flow (\emph{p} \textless{} 0.05).
The influence of soil crack properties on preferential flow cannot be
neglected during vegetation restoration and groundwater security
processes in karst areas.

\textbf{KEYWORDS:}crack, configuration, preferential flow, karst,
ground-penetrating radar, Brilliant Blue FCF

\section*{1. INTRODUCTION}

{\label{introduction}}

Karst areas in southwest China, a humid monsoon region with distinct dry
and rainy seasons, are characterised by typical regional soil and
vegetation that distinguish them from other regions at the same latitude
(Peng et al., 2008). Carbonate-derived laterite is widely distributed in
karst areas with high clay contents, low permeabilities, and high
water-holding capacities (Waller and Wallender, 1993; Liu, et al., 2016;
2020). These soil features determine the calciphile and drought
endurance of local vegetation (Peng et al., 2008). Moreover, the complex
and unique topographical and geological conditions of karst areas lead
to water and nutrient loss (Wang et al., 2019). Given these
circumstances, the importance and specificity of these regions have
alarmed people about their ecological conditions.

Cracks are physical phenomena that exist in clayey and expansive soils
(Sima et al., 2014; Acharya et al., 2015). In karsts, the alternating
wet and dry conditions and the special dilation-shrinkage
characteristics of carbonate-derived laterite allow for soil cracks to
form with ease (Liao et al., 2000; Zhang et al., 2021). Additionally,
shallow subsurface cracks may be influenced by plant roots (Shem et al.,
2009; Zhu et al., 2020), burrowing fauna (Li et al., 2019), and
artificial factors (Mossadeghi-Bj\selectlanguage{ngerman}örklund et al., 2016; Tang et al.,
2016). For example, \emph{Eucalyptus robusta} can absorb approximately 9
t hm\selectlanguage{english}\textsuperscript{-2} year\selectlanguage{english}\textsuperscript{-1} of carbon dioxide
while releasing oxygen (Ghannoum et al., 2010; Teixeira et al., 2020);
further, rapid water absorption through its root systems result in soil
crevices and cracks (Shem et al., 2009).

Cracks can enhance water infiltration and induce preferential flows
(Zhang et al., 2014), making water one of the most important factors
limiting karst forest development (Zhang et al., 2018; Liu et al.,
2020). Preferential flow, generated by the rapid penetration of moisture
through soil pore channels, is a nonuniform and unstable water flow
(Bouma and De Laat, 1981; Sheng et al., 2014). Crack properties
including configuration, orientation, inclusion, angle, depth, and
volume can affect water distribution and preferential flow (Zhao et al.,
2014). For example, the configuration of a linear crack has a high
saturated hydraulic conductivity compared with other shapes and thus
develops preferential flow (Liu and She, 2020), whereas regular
rectangular crack networks made of steel sheets generate preferential
flow only under high-intensity precipitation or irrigation conditions
(Zhu et al., 2018). Inclusions within soil cracks are normally coarse
particles and rock fragments in karsts (Chen et al., 2011). Although
cracks and fissures in nature exist with complex combinations of
properties (Zhang et al., 2014; Zhu et al., 2020), the small-scale
control of the preferential flow of isolated cracks is critical for
water loss in soil-epikarst zones (Liu and She, 2020).

Preferential flow visibility is usually achieved by Brilliant Blue FCF
(C.I. Food Blue 2), which is a tracer that marks the area where stained
water flows (Bouma and De Laat, 1981; Hagedorn and Bundt, 2002) and
traces the flow paths to reveal soil profile characteristics (Hagedorn
and Bundt, 2002; Sheng et al., 2009). Recently, ground-penetrating radar
(GPR) has been successfully applied to karsts to reveal structural
information about the subsurface and transform invisible geological
features into trended signals (Estrada-Medina et al., 2010; Fernandes et
al., 2015), thereby providing more detailed information about soil
profiles. GPR can accurately locate soil cracks and identify crack
widths as low as 1--2 mm (Levatti et al., 2017). The combination of`
time-lapse GPR surveys and infiltration experiments has revealed
channelling soil water characteristics (Di Prima et al., 2022). However,
the combination of field-based GPR data and lab-based infiltration
experiments on crack properties has not been tested to generalise the
flow infiltration process.

To clarify whether soil cracks enhanced preferential flow and effected
infiltration processes, a case study approach was chosen. GPR was
applied to physically identify the natural soil cracks and place
``manmade cracks'' in transparent Plexiglas columns to observe
infiltration over time. This study aimed to i) identify the soil crack
properties through GPR envelopes with excavated pedons; ii) evaluate the
effects of crack inclusion, width, and configuration on infiltration
processes and preferential flow; and iii) discuss the preferential flow
characteristics caused by different cracks to further explore the
infiltration mechanism in karsts.

\section*{2. MATERIALS AND METHODS}

{\label{materials-and-methods}}

\subsection*{2.1 Study area}

{\label{study-area}}

This study was conducted at 102deg54\selectlanguage{english}'12\selectlanguage{english}" E and 23deg37\selectlanguage{english}'13\selectlanguage{english}" N and an altitude
of 1300--2500 m (Figure 1), in Jianshui County, Honghe Hani and Yi
Autonomous Prefecture, Yunnan Province, China. This region is a karst
graben basin with strong stratigraphic erosion since the Tertiary Period
(Cao, 2021). The red weathering crust of carbonate rocks, known as
carbonate laterite, is formed in tropical and subtropical environments
through a long weathering process that is unique to the karst graben
basin. The long-term average annual temperature of this area is 19.8 degC,
with most of the 805 mm mean annual precipitation occurring between May
and October. The summer/autumn wet season lasts from April through
September and provides approximately 70\%--90\% of the total annual
rainfall.

The \emph{E. robusta} forests in the experimental area are approximately
1.5 km\textsuperscript{2}, which cover the Nanpan River water system in
the upper reaches of the Pearl River and the middle and upper reaches of
the cross-border Red River Basin. Three study sites (2.8 m x 2.8 m each)
were selected for field tests and marked as Sites 1, 2, and 3. The bulk
density of the soil was approximately 1.2 g/cm\textsuperscript{3} and
the pH was 6.5. Table 1 details the physical and chemical properties of
the tested soil.

\subsection*{2.2 Experiment design}

{\label{experiment-design}}

\subsubsection*{2.2.1 GRP surveys and ground
truthing}

{\label{grp-surveys-and-ground-truthing}}

This study was divided into field survey and infiltration experiment
stages. The soil cracks and their properties were characterised in
accordance with the GPR lines and excavation of the soil pedons using an
embedded Linux GPR system (CAS-S500, IECAS, China) with a shielded
antenna of 500 MHz. Horizontal and vertical GPR lines were deployed in
accordance with crossed grid principles and with horizontal lines
parallel to contour lines. The GPR grid (2.8 m x 2.8 m) consisted of 15
horizontal (H1--H15) and vertical (V1--V15) parallel survey lines with
20 cm between them (Figure S1). The horizontal lines were oriented
downslope with a local 5deg slope. 90 radargrams (3 sites x 30 survey
lines) were collected over the study area, with data acquired from the
distance travelled by a survey wheel equipped with a position sensor.
The sampling frequency of the system was 25.6 Hz, and the wheel moved at
a uniform speed (scanning rate of 390.625 traces/s) in conformity with
the survey line. The time window was set at 40 \emph{ns} and, for each 3
m long survey transect, 258--276 traces and 38 time windows were
recorded. Based on the signal fluctuations appearing in the radargrams,
six pedons (three sites x two random pedons) were stochastically
excavated for verification (Figure S1). The length and depth of each pit
were 120 cm and 60--70 cm, respectively. Various soil crack shapes were
screened through the radargrams and pedons of the soil profile (Figure
2b).

\subsubsection*{2.2.2 Infiltration experiment
design}

{\label{infiltration-experiment-design}}

Preferential flow paths were simulated to account for the natural cracks
and pore structures of soils detected by GPR. Based on the
identification of crack configuration in the field which was defined as
``I'', ``V'', and ``\selectlanguage{greek}Λ\selectlanguage{english}'' morphologies, the infiltration experiments were
conducted to explore the effect of isolated cracks on water
infiltration. In addition, we found that soil cracks were filled with
sand grains or rock fragments of different grain sizes when excavating
the soil profile. It has been shown that inclusions (Yang et al., 2016;
Liu and She, 2020), width (Ou Yang, 2020), and configuration (Liu and
She, 2020) influence the infiltration process. For simplicity, soil
cracks are always assumed to resemble smooth parallel plates
(Tsakiroglou et al., 2012; Rouchier et al., 2012). Therefore, three
properties of different inclusions (sand grains and rock fragments),
crack widths (1, 1.5, and 2 cm), and configurations (I-shape, V-shape,
and \selectlanguage{greek}Λ-\selectlanguage{english}shape) for infiltration were simulated (Figure 2d and Table 2). A
soil column without cracks (CK) was used as the control. Based on these
properties, all experiments were divided into six groups (Figure 2d) in
which four soil columns (including CK) were conducted simultaneously,
with each experiment repeated three times.

Disturbed soil samples were collected in September 2021 from the upper
70 cm of pedons in layers. The tested soil was passed through a 2 mm
sieve, air-dried, thoroughly mixed, and hierarchically backfilled into
Plexiglas columns (20 cm \selectlanguage{ngerman}× 5cm × 60 cm, Figure 2c) to ensure that the
particle size composition of the backfilled soil was as consistent as
possible with the field site. For homogeneous soil columns, the
backfilled soil needed to be compacted, and the surface was roughened
every 5 cm before the next layer was added. The top layer was covered
with a metal mesh after backfilling soils of 50 cm to prevent water flow
impact on top soils. Different crack inclusions were replaced by sand
grains and rock fragments. The diameter of all sand grains was
approximately 2 mm, whereas the rock fragments ranged 2--5 mm. All these
debris (i.e. sand grains and rock fragments) was wrapped with 500-mesh
nylon netting to prevent soil particles from passing through and
blocking the paths (Figure 2c). From the field excavation of
representative sites and GPR large-scale detection, cracks are mainly
scattered approximately 10 cm from the surface. Therefore, the lab-based
experiments of cylindrical ``channel'' was placed in column when
backfilled to 30 cm from the upper edge of the column to simulate
various cracks.

Brilliant Blue FCF allows clear visualisation of the infiltration
process of non-uniform flow in the soil (Lipsius et al., 2006); as such,
a Brilliant Blue FCF dye volume of 5 L (4 g/L) was added to the Marriott
bottles to visualise the preferential flow paths. The volume of the dye
solution used corresponded to the amount of water collected in a 20 mm
rainfall event, considering more than 65\% of regional rainfall events
were for 20 mm during 2009--2018. Therefore, a constant pressure head of
20 mm was supplied using Marriott bottles (Figure 2c). For each
experimental group, four images (three variances and a control) were
taken with a digital camera (Canon EOS 60D, Canon, Japan) directly in
front of the soil column at 3, 5, 10, 20, 30, 50, 70, and 90 minutes
after the Brilliant Blue FCF dye solution was applied. The infiltration
continued until the wetting front penetrated the bottom of the column.
The dye infiltration depth and wetting front trajectory of each soil
column were recorded simultaneously using a ruler with millimetre
precision attached to the edge of the soil column. The infiltration rate
was determined by measuring change in water level in Marriott bottles
over time.

\subsection*{2.3 Data analysis}

{\label{data-analysis}}

\subsubsection*{2.3.1 GPR data processing}

{\label{gpr-data-processing}}

GPR data were processed following a conventional routine (Dal et al.,
2019; Guo et al., 2014) via Radar View V18.08 (Institute of Electronics,
Chinese Academy of Science, China) to enhance the signal-to-noise ratio,
which follows the sequence: 1) background filter wiped off antenna
reverberation; 2) time-zero correction calibrated the radar antenna
start time; 3) energy gained compensated energy attenuation with
propagation depth; 4) Hilbert filter removed high- and low-frequency;
and 5) DC-drift suppressed low-frequency noise and remedied average
amplitude. Finally, the high signal areas float compared to their
surroundings in the radargram, and were converted to average envelope
curves (Figure 2a). The envelopes can estimate the configuration of soil
cracks, and the abnormal signals, defined as cracks on the radargram,
were used to calculate the soil crack densities at the study site. Total
amplitude area (TotAra) is the area enclosed by the envelope curve and
the coordinate axis. Accumulative amplitude (Acum\textsubscript{a}) is
the accumulation of the amplitude at every 1 cm soil depth on the
envelope curve (The crack signal illustration method is shown in Figure
S2).

\subsubsection*{2.3.2 Image processing and data analysis of preferential
flow}

{\label{image-processing-and-data-analysis-of-preferential-flow}}

The captured images were cropped, and the threshold was adjusted using
Photoshop 2020 (Adobe Systems Inc., San Jose, CA) for further analysis.
The stained area was replaced with black (0) and the non-stained area
was replaced with white (255) via the colour replacement function.
Separation was then conducted using Image Pro Plus 6.0 (Media
Cybernetics Inc., Rockville, MD) to obtain only 0 and 255 dual-value
matrices after bitmap analyses were done.

Dye coverage (\emph{D\textsubscript{C}} ) is defined as the ratio of the
stained area to the total soil vertical profile, and the area was
measured using a matrix converted from pixel grids and was calculated as
follows:

, (1)

where \emph{D} is the number of matrix values of 0
and\emph{N\textsubscript{D}} is the number of matrix values of 255.

Many historians have argued that the matrix flow depth
(\emph{U\textsubscript{F}} ) is defined as the depth at which the
stained area ratio is greater than 80\% (Schaik, 2009; Bargues Tobella
et al., 2014). In contrast to preferential flow, water infiltration in
the matrix flow region is relatively uniform and continuous. Matrix flow
often leads to a delay in the preferential flow.

The preferential flow ratio (\emph{P\textsubscript{F}} ) is defined as
the ratio of the stained area of the preferential flow area to the
entire vertical profile; a high \emph{P\textsubscript{F}} value leads to
a high degree of preferential flow. This can be calculated as follows:

, (2)

where \emph{W} is the width of the Plexiglas column (\emph{W} = 20 cm)
and \emph{D\textsubscript{T}} is the total stained area of the soil
profile (cm\textsuperscript{2}).

The length index of preferential flow (\emph{L\textsubscript{i}} )
describes the heterogeneity of the dye penetration, which is higher in
the preferential flow region than in the matrix flow region. A high
\emph{L\textsubscript{i}} value leads to a high degree of preferential
flow. This can be calculated as follows:

, (3)

where \emph{n} is the number of vertical soil layers in the soil profile
(one pixel down along the vertical profile named one layer, the size of
which is determined by the number of pixels contained in the maximum
infiltration depth), and \emph{D\textsubscript{c(i+1)}}
and\emph{D\textsubscript{ci}} are the stained area ratios corresponding
to soil profile layer \emph{i} +1 and \emph{i} , respectively.

\section*{3. RESULTS}

{\label{results}}

\subsection*{3.1 Soil profile
characteristics}

{\label{soil-profile-characteristics}}

The general characteristics of soil pedons are illustrated based on
pedon 1 (Figure 2b). At 0--10 cm soil depth, the soil was dark red with
numerous wormholes found due to the high organic matter content of the
surface layer. Cracks began to appear below 10 cm, with a few soil
profiles showing various crack configurations. For instance, pedon 1
contained a V-shaped crack at 18--21 cm and an I-shaped crack at
approximately 19--33 cm, while most of the profiles contained more
I-shaped cracks. Pedon 1 consisted of four genetic horizons, delineated
as A (0--8 cm), B1 (8--21 cm), B2 (21--54 cm), and BC (54--60 cm)
(Figure 2b), which were classified as loamy skeletal, mixed,
super-active, or mesic, respectively (Soil Survey Staff, 1999).

This experiment applied GPR technology to physically probe soil cracks
and identify natural crack configurations before the infiltration
experiment was unfolded. High-signal areas floating on the radargrams
were identified, and the envelopes were calculated as the average crack
coverage amplitude (Table 3). Soil cracks existed or did not result in
different envelopes. The envelope of non-crack profiles had no
substantial fluctuation with reflection wave conduction, while the
profile with cracks showed more signal fluctuations at 0.3--0.6 m. The
extracted crack signal parameters TotAr\textsubscript{a},
Max\textsubscript{a}, Min\textsubscript{a}, and
Acum\textsubscript{a}support the phenomenon (Table 3). Furthermore, the
amplitude fluctuation of the I-shaped crack was less marked than that of
the V- and \selectlanguage{greek}Λ-\selectlanguage{english}shaped cracks (Figure S3). Thus, the different soil crack
configurations, as determined by GPR and excavation, could provide
practical support for conducting infiltration experiments. Notably,
geophysical methods cannot directly explain all the properties of soil
cracks. Whether the crack width, inclusion, and signal fluctuations
corresponded to each other based on the raw data remains unclear.

\subsection*{3.2 Comparison between Brilliant Blue FCF solution and water
transport}

{\label{comparison-between-brilliant-blue-fcf-solution-and-water-transport}}

Figure 3 shows the infiltration trajectories with time, showing that the
Brilliant Blue FCF solution penetrates faster than water. The difference
between water and dye penetration was observed at the beginning of
infiltration, as early as 3 min. In the VR1.5 treatment (Figure 3c), the
matrix flow was notably dominant throughout the infiltration process,
and no preferential flow occurred. This phenomenon indicates that water
was probably not transported down V-shaped cracks (Figure 3b). The
matrix flow dominated before 30 min, while preferential flow dominated
later in the IR1.5 and \selectlanguage{greek}Λ\selectlanguage{english}R1.5 treatments (Figure 3a--b).

The dye-stained and wetting areas show a linear fit with the primary
function, in which the \emph{R} \textsuperscript{2} values were all
above 0.8 (Figure 4). Regarding the I-shaped crack filled with rock
fragments, slight variabilities were found between Brilliant Blue FCF
solution and water when the dye-stained area was less than 21\%, at
which point the former infiltrated marginally faster than the latter;
however, these differences gradually became more potent after the
turning point, indicating that there was a lag in the effects of the
Brilliant Blue FCF solution compared to water (Figure 3--4). Comparison
with the I-shaped crack showed that the retardation on the solution
infiltration in the \selectlanguage{greek}Λ-\selectlanguage{english}shaped crack appeared later, around a dye-stained
area ratio of 24\%--27\%. This result may explain, at least in part,
that the retardation on the Brilliant Blue FCF with time was influenced
by the crack configuration, and the flow pathways of the Brilliant Blue
FCF were not fully representative of water infiltration paths.

\subsection*{3.3 Effect of crack properties on infiltration and
preferential
flow}

{\label{effect-of-crack-properties-on-infiltration-and-preferential-flow}}

The effects of the crack properties (inclusion, crack width, and
configuration) on the infiltration rate, maximum dye-penetration depth,
cumulative infiltration, and wetting advancing rate are shown in Figure
5--7. Generally, a noticeable trend in the infiltration rate was
observed, which could be divided into a sharp decline and a steady
decline for all treatments. The turning point occurred at approximately
40 min, after which, the infiltration rate reached a relatively smooth
decline for all treatments (Figure 5a, 6a, and 7a). The maximum dye
penetration depth and cumulative infiltration increased at a slower rate
with time after 40 min (Figure 5b--c, 6b--c, and 7b--c).

\subsubsection*{3.3.1 Crack inclusion}

{\label{crack-inclusion}}

Regarding the influence of inclusions, the infiltration rate was faster
by 18.8\% on average when filled with rock fragments than when filled
with sand grains (Figure 5a), and the existence of cracks increased the
dye-penetration depth, cumulative infiltration, and wetting front depth
by at least 5.2\%, 63.2\%, and 4.4\% (Figure 5b--d). These results were
apparent in the IR2, IS2, \selectlanguage{greek}Λ\selectlanguage{english}R1.5, and \selectlanguage{greek}Λ\selectlanguage{english}S1.5 treatments, indicating that
cracks filled with rock fragments enhanced the infiltration capacity of
the soil. The \selectlanguage{greek}Λ\selectlanguage{english}R1.5 treatment had a notably higher dye penetration
depth, cumulative infiltration, and wetting front depth at the end of
infiltration (Figure 5b--d). For example, the 70-min wetting front depth
of the \selectlanguage{greek}Λ\selectlanguage{english}R1.5 treatment was 46.5 mm, whereas that of the \selectlanguage{greek}Λ\selectlanguage{english}S1.5 treatment
decreased by 17.0 \% (Figure 5d). Similarly, the maximum dye-penetration
depth and cumulative infiltration decreased by 14.9\% and 4.4\%,
respectively (Figure 5b--c).

\subsubsection*{3.3.2 Crack width}

{\label{crack-width}}

The volumes corresponding to the three crack widths were 8.0, 17.5, and
31.5 cm\textsuperscript{3}, respectively. Regarding crack widths,
significant differences (\emph{p} \textless{}0.05) were identified in
the infiltration rates among the three treatments with different crack
widths (Figure 8b). After the infiltration reached relative stability,
the infiltration rate was faster for the 1.5-cm width crack (Figure 6a).
The maximum dye-penetration depth, cumulative infiltration, and wetting
advancing rate were the highest when the crack width was 1.5 cm (Figure
6b--d), and there was a significant difference (\emph{p}
\textless{}0.05) in the maximum dye-penetration depth with the 1.5-cm
width crack (Figure 8b). Our experimental results indicate the existence
of a certain optimal crack width between 1 and 2 cm, which allowed the
infiltration rate to be maximised. After the crack volume reached a
value range of 8.0--31.5 cm\textsuperscript{3}, moisture was more
inclined to be stored in the crack than to infiltrate downward.

\subsubsection*{3.3.3 Crack configuration}

{\label{crack-configuration}}

Regarding the configuration, the chart shows that the \selectlanguage{greek}Λ\selectlanguage{english}R1.5 treatment
had a substantially higher penetration rate than other configurations,
ranging from 54\% to 120\% higher than other two configurations (Figure
7a). The maximum dye-penetration depth and cumulative infiltration of
the \selectlanguage{greek}Λ-\selectlanguage{english}shaped configuration increased steadily at the beginning of
infiltration, crossing the line for the I-shaped configuration at
approximately 50 min (Figure 7b and 7c). When infiltration proceeded to
a certain process, the \selectlanguage{greek}Λ-\selectlanguage{english}shaped configuration increased the rate of
liquid passage, but the effect on the wetting advancing rate was not
obvious. The wetting front depth nearly overlapped between the three
crack configurations, with variations ranging from 0.03\% to 38.39\%
(Figure 7d). Significant differences (\emph{p} \textless{}0.05) were
observed between the IR1.5 and \selectlanguage{greek}Λ\selectlanguage{english}R1.5 treatments, but there were no
significant differences (\emph{p} \textless{}0.05) between these and the
VR1.5 treatment (Figure 8c).

\subsection*{3. 4 Contribution of crack properties to preferential
flow}

{\label{contribution-of-crack-properties-to-preferential-flow}}

The I- and \selectlanguage{greek}Λ-\selectlanguage{english}shaped treatments, filled with rock fragments, generated
preferential flow, whereas the V-shape was not sensitive to preferential
flow (Table 2). Thus, the analysis of dye coverage and preferential flow
indices was displayed only for IR1, IR1.5, IR2, and \selectlanguage{greek}Λ\selectlanguage{english}R1, \selectlanguage{greek}Λ\selectlanguage{english}R1.5, and \selectlanguage{greek}Λ\selectlanguage{english}R2
treatments.

Figure 9 illustrates the turning range of the preferential flow ratio
with increasing crack width for the same configuration and inclusion.
The experiment proved that the preferential flow extensively slowed down
the decline in dye coverage and remained steady in the IR1.5 and \selectlanguage{greek}Λ\selectlanguage{english}R2
treatments (Figure 9b and 9f). For example, the percentage of
preferential flow dye coverage in the IR1.5 treatment ranged from 60.7\%
at 15 cm to 14.4\% at 20 cm, while in the \selectlanguage{greek}Λ\selectlanguage{english}R1.5 treatment, it ranged
from 75.9\% at 14 cm to 7.5\% at 17 cm. The variations indicated more
preferential pathways in the \selectlanguage{greek}Λ\selectlanguage{english}R1.5. However, a rebound point at a soil
depth of 15 cm was observed in the IR2 treatment, in which the
morphology of the stained end appeared radially orbicular (Figure 9c).
This demonstrates the configuration has a greater effect on preferential
flow and a wider linear crack filled with rock fragments likely leads to
a lateral flow at the end of the crack.

Overall, the preferential flow ratio increased with increasing crack
width, similar to the length index of the preferential flow. Generally,
the preferential flow ratio and matrix flow depth showed opposite
trends; however, this was not always the case (Table 4). Treatment with
IR1.5, however, did not match the above regularity. The nonuniformity
and spatial variability of the linear crack was more distinct, which led
to an obvious preferential flow phenomenon. The response of the \selectlanguage{greek}Λ-\selectlanguage{english}shaped
crack to the preferential flow with time lagged. For instance, the depth
of matrix flow for I-shape was 0.9\%--33.3\% lower than that for
\selectlanguage{greek}Λ-\selectlanguage{english}shape; however, the length index of preferential flow was higher by
3.9\%--11.4\% (Table 4).

\section*{4. DISCUSSION}

{\label{discussion}}

\subsection*{4.1 Effect of crack properties on preferential
flow}

{\label{effect-of-crack-properties-on-preferential-flow}}

During the infiltration event, the infiltration rate of Brilliant Blue
FCF was over 1.5 times slower and the infiltration depth was 1.2--3.8
times lower than those of water, which may be attributed to the fact
that the viscosity of water was different from that of Brilliant Blue
FCF. A similar phenomenon was observed by Liu and She (2020a), who
showed that a large organic molecule size and nonlinear adsorption
behaviour within the soil matrix led to slow migration rates. This may
be due to the retardation caused by the reaction between Brilliant Blue
FCF and Ca\textsuperscript{2+} in carbonate laterite areas (Flury and
Fl\selectlanguage{ngerman}ühler 1995; Nobles et al., 2010). Therefore, using Brilliant Blue FCF
as a staining tracer, the infiltration depth in the soil profile may not
be the true water infiltration depth. The results of this experiment can
be used as a basis for calibration in future field tests.

Soil cracks showed undulated reflections and individual features,
whereas CK showed a more continuous interface, as derived from the
envelope curves (Figure S3). Moreover, the morphological characteristics
in the vertical direction of the I-shaped cracks showed a smaller
envelope reflection amplitude than those of the other shapes. Cracks are
always filled with sand grains or rock fragments, which had a
significant role in providing high-amplitude reflections (Han et al.,
2016; Dal et al., 2019\emph{)} . Although the co-offset results only
distinguished the envelope curves of different crack configurations, the
soil cracks always had different widths and inclusions as well
(Tsakiroglou et al., 2012; Yang et al., 2016), where the radar
reflections provided by could not be distinguished.

The volume proportion of ``manmade cracks'' occupied approximately
0.16\%, 0.35\%, and 0.63\%, corresponding to the 1-, 1.5-, and 2-cm
cracks, respectively, as shown in the infiltration experiments. Although
the volume of cracks was less than 1\%, the existence of cracks
considerably accelerated the water infiltration rate, while the
infiltration rate, maximum dye-penetration depth, cumulative
infiltration, and wetting advancing rate of CK were lower than those of
other treatments containing cracks. Cracks provide channels or pores for
fluid flow, even though only the I- and \selectlanguage{greek}Λ-\selectlanguage{english}shaped cracks produce
preferential flow. Our findings did not concur with those of Liu and She
(2020a), who suggested that crack volume is not a good predictive
parameter for infiltration characteristics. However, Yang (2020)
concluded that the crack volume is an important indicator of the initial
infiltration rate, and that they are positively correlated.

Preferential flow was observed only in the I- and \selectlanguage{greek}Λ-\selectlanguage{english}shaped treatments,
along the crack pore paths. These results are consistent with those of
Liu and She (2020a) and Yang et al. (2016), who demonstrated that cracks
influence preferential flow. Liu and She (2020a) showed that I-shaped
cracks retained more water than V-shaped or non-cracks, in which
preferential flow was the dominant flow type. Yang et al. (2016)
revealed that the orientation of subsurface flow varied in accordance
with the connectivity of the cracks or underlying structure, which
resulted in lateral flows and deep percolation occupying approximately
32\%--36\% of the total rainfall.

\subsection*{4.2 Necessity of combining geophysical surveys and column
experiments}

{\label{necessity-of-combining-geophysical-surveys-and-column-experiments}}

GPR was successfully applied in karst topography to reveal structural
information about the subsurface and achieve the transformation of
invisible geological features into trended signals (Estrada-Medina et
al., 2010; Fernandes et al., 2015), thus providing more detailed
information about soil profiles (Busch et al., 2013). This geophysical
technique retrieves information with the advantages of low-cost,
efficiency, and less labour-intensive. We explored the distribution and
characteristics of soil cracks on a large scale in the field, and
verified the configuration by GPR. On the one hand, geophysical surveys
provide a reference for the crack properties before the simulation
experiments. The column experiments were conducted based on the results
of GPR and excavations and visualise the flow infiltration process (Liu
et al., 2020a). On the other hand, it provides a new insight for
interpreting isolated cracks from radar signals. The combination of GPR
with field observations and column experiments has shown great potential
for investigate the effect of isolated soil cracks on preferential flow.

\section*{5. CONCLUSIONS}

{\label{conclusions}}

In this study, field GPR physical imaging techniques and infiltration
experiments were applied to investigate the effects of crack properties
on preferential flow paths. Many soil cracks filled with fine fragments
were present in karst. By evaluating the influence of crack inclusion
(sand grains and rock fragments), crack width (1, 1.5, and 2 cm), and
configuration (I-shape, V-shape, and \selectlanguage{greek}Λ-\selectlanguage{english}shape) on infiltration, we found
that isolated soil cracks could enhance preferential flow with some
properties.

The isolated soil cracks accelerated the infiltration process supported
by infiltration rate, maximum dye-penetration depth, cumulative
infiltration, and wetting advancing rate. These indicators reached a
relatively stable increase or decrease in infiltration over time until
the 40\textsuperscript{th} min. The transport depth of Brilliant Blue
FCF was 1.2--3.8 times slower and the infiltration rate was over 1.5
times slower than that of water during the entire infiltration process.
The retardation of the Brilliant Blue FCF necessitates calibration when
applied to field infiltration tests.

The inclusions, crack width, and configuration significantly affected
the preferential flow indices (\emph{p} \textless{} 0.05), of which the
configuration has a greater effect on preferential flow. Only I-shape
and \selectlanguage{greek}Λ-\selectlanguage{english}shape of the soil cracks filled with rock fragments generated
preferential flow. The effect of linear cracks on preferential flow in
the field cannot be ignored.

The configuration of isolated soil cracks can be identified by GPR
envelopes. The GPR envelope can be used to directly reflect the possible
occurrence of preferential flow during rainfall conditions in crack
soils.

Our research proved that isolated cracks control preferential flow and
relationships between envelopes and preferential flow indices in crack
soils. These findings offer new insights for underground hydrological
processes and vegetation restoration in karst areas. Further research
should be directed towards the future development of a combination of
complex crack structures at large scales.

\section*{ACKNOWLEDGMENTS}

{\label{acknowledgments}}

This research was financially supported by The National Natural Science
Foundation of China (32071839). The authors thank Ning Guan and Zhiming
Niu for helping with the field work, and American Journal Experts for
English language editing.

\section*{CONFLICT OF INTEREST
STATEMENT}

{\label{conflict-of-interest-statement}}

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to
influence the work reported in this paper.

\section*{DATA AVAILABILITY STATEMENT}

{\label{data-availability-statement}}

The data that support the findings of this study are available from the
corresponding author upon reasonable request.

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\textbf{Figures caption:}

\textbf{FIGURE 1} Location of research area and the three study sites in
Jianshui County, Yunnan Province, China.

\textbf{FIGURE 2} Main steps of infiltration experiment: (a)
identification of envelope curves on radargram; (b) soil profile at
pedon 1 (yellow dotted lines represent the boundary between horizons,
white dashed boxes represent cracks found during excavation); (c)
Plexiglas columns for experiment and text device; and (d) experimental
groups to be performed.

\textbf{FIGURE 3} Infiltration process over time in different treatments
(only IR1.5, \selectlanguage{greek}Λ\selectlanguage{english}R1.5, and VR1.5 treatments are shown here), with blue
lines indicating dye traces, yellow lines indicating moisture wetting
front traces, and red dotted regions indicating that the preferential
flow occurred after 40 minutes.

\textbf{FIGURE 4} Comparison of dye-stained and wetting areas for I- and
\selectlanguage{greek}Λ-\selectlanguage{english}shaped cracks filled with rock fragment treatment (the wetting area
was wetted by water, excluding the area wetted by Brilliant Blue FCF
solution). The shaded part after the fitted line represented the 95\%
confidence interval.

\textbf{FIGURE 5} Effect of crack inclusion (only CK, IR2, \selectlanguage{greek}Λ\selectlanguage{english}R1.5, \selectlanguage{greek}Λ\selectlanguage{english}S1.5,
and IS2 treatments are shown here).

\textbf{FIGURE 6} Effect of crack width (the crack width is the average
of tests).

\textbf{FIGURE 7} Effect of CK, IR1.5, VR1.5, and \selectlanguage{greek}Λ\selectlanguage{english}R1.5 treatments crack
configurations.

\textbf{FIGURE 8} Effect of crack inclusion (a), crack width (b), and
crack configuration (c) on the mean infiltration rate, dye-penetration
depth, cumulative information, and wetting front depth. Different
lowercase letters indicate significant differences between treatments
at\emph{p} \textless{}0.05 (e.g. a, b, and c indicate significant
differences; a and ab indicate no significant differences). The error
bars indicate the standard deviation of 3--4 replicates.

\textbf{FIGURE 9} Dye coverage of soil vertical profiles and stained
area ratio for the I- and \selectlanguage{greek}Λ-\selectlanguage{english}shaped configurations filled with rock
fragment are shown here.\selectlanguage{english}
\begin{figure}[H]
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