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\begin{document}

\title{Suspended sediment monitoring in alluvial gullies: a laboratory and
field evaluation of available measurement techniques}



\author[1]{Nicholas Doriean}%
\author[2]{Andrew Brooks}%
\author[3]{Peter  Teasdale}%
\author[1]{David Welsh}%
\author[1]{William Bennett}%
\affil[1]{Griffith University }%
\affil[2]{Griffith University - Gold Coast Campus}%
\affil[3]{University of South Australia School of Natural and Built Environments}%


\vspace{-1em}



  
  \date{May 29, 2024}


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\selectlanguage{english}
\begin{abstract}
Gully erosion is a significant source of fine suspended sediment
(\textless{}63\selectlanguage{greek}µ\selectlanguage{english}m) and associated nutrient pollution to freshwater and
marine waterways. Researchers, government agencies, and monitoring
groups are currently using monitoring methods designed for streams and
rivers (e.g., autosamplers, rising stage samplers, and turbidity
loggers) to evaluate suspended sediment in gullies. This is potentially
problematic because gullies have unique hydrological and operational
challenges that differ to those of streams and rivers. Here we present a
laboratory and field-based assessment of the performance of common
suspended sediment monitoring techniques applied to gullies. We also
evaluate a recently-described method; the pumped active suspended
sediment (PASS) sampler, which has been modified for monitoring
suspended sediment in gully systems. Discrete autosampling provided data
at high temporal resolution, but had considerable uncertainty associated
with the poor collection efficiency (25 \selectlanguage{ngerman}± 10\%) of heavier sediment
particles (i.e., sand). Rising stage sampling, while robust and
cost-effective, suffered from large amounts of condensation under field
conditions (25-35\% of sampler volume), thereby diluting sample
concentrations and introducing additional measurement uncertainty. The
turbidity logger exhibited low uncertainty (\textless{} 10\%) when
calibrated with suspended sediment concentration data from physically
collected samples, however, this calibration approach needs to be
performed on a site-specific basis to overcome the error associated with
the impact of different particle size distributions on the turbidity
measurement. The modified PASS sampler proved to be a reliable and
representative measurement method for gully sediment water quality,
however, the time-integrated nature of the method limits its temporal
resolution compared to the other monitoring methods. We recommend
monitoring suspended sediment in alluvial gully systems using a
combination of complementary techniques (e.g., PASS and RS samplers) to
account for the limitations associated with individual methods.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


\section*{Introduction}

{\label{introduction}}

Gully erosion is globally recognised as a significant source of soil
loss and can directly influence the water quality of downstream aquatic
ecosystems by the presence of fine suspended sediment (\textless{}63 \selectlanguage{greek}µ\selectlanguage{english}m)
and suspended sand (63-2000 \selectlanguage{greek}µ\selectlanguage{english}m) (Vercruysse et al., 2017; Walling, 2006;
Walling et al., 2016). The impact to water quality from gully erosion
can vary depending on the particle size distribution and sediment yield.
For example, small gullies that form in recently tilled agricultural
land can affect local waterways (Capra et al., 2002), whereas larger
landscape-scale gullies can impact the water quality of connected
waterways for hundreds of kilometres downstream (e.g.,
\textgreater{}40\% of the sediment polluting the Great Barrier Reef
Marine Park, in the coastal waters of Northern Australia, is generated
by gully erosion that occurs hundreds of kilometres upstream) (Brooks et
al., 2013; Olley et al., 2013; Wilkinson et al., 2015).

Gullies are often formed by water flowing over land at a sufficient
velocity to incise the soil and form a deep exposed gap, typically in
areas with poor soil cohesion (Casal\selectlanguage{ngerman}í et al., 2009). Over time the area
of gullies expands due to active erosion caused by repeated flow events
associated with intense rainfall (Poesen et al., 2003). Gully erosion is
a natural process, however, the rate of erosion can drastically increase
as a consequence of anthropogenic land use change (e.g., installation of
roads and other infrastructure or through agricultural activities, such
as land clearing and livestock grazing) (Nyssen et al., 2002; Wilkinson
et al., 2018).

To date, suspended sediment monitoring in gullies has been conducted
using methods designed for rivers and streams (e.g., automated discrete
samplers (autosamplers), rising stage samplers (RS samplers), and
turbidity loggers) (Baker et al., 2016; Bartley et al., 2017; Caitcheon
et al., 2012; Nistor et al., 2005). However, gully systems present a
unique set of hydrological and operational challenges for which these
various sampling and measurement methods have not been thoroughly
evaluated. The method considered to be the most accurate for measuring
suspended sediment, flow-proportional manual sampling (Horowitz et al.,
2008; Perks, 2014), is often infeasible or unsafe to conduct in gully
systems due to the unpredictability of rainfall events, the remoteness
of many gully landscapes, and the instability of gully channels and
banks.

Currently, the operational challenges associated with measuring water
quality in gullies are overcome using autonomous sampling or surrogate
measurement techniques (autosamplers, RS samplers, and turbidity
loggers) and remote sensing methods (time lapse cameras or light
detection and ranging (LiDAR) techniques) (Casalí et al., 2009; Castillo
et al., 2012). These methods are established monitoring techniques with
well understood capabilities and limitations (Table 1). Many of these
methods, however, are too expensive to implement over the large spatial
network of actively eroding gullies within a catchment (e.g.,
autosamplers and turbidity loggers), and others provide incomplete
information when deployed in isolation (e.g., RS samplers and time-lapse
cameras). To address this gap, our study includes the recently developed
Pumped Active Suspended Sediment (PASS) sampler; an automated,
time-integrated, and \emph{in situ} sampling device, as a low-cost
approach that could be used to monitor gully erosion over large spatial
scales (Doriean et al., 2019; Nunny 1985; Phillips et al., 2000). As
this work is primarily focussed on approaches that measure water quality
associated with suspended sediment (i.e., suspended sediment
concentration and particle size distribution) remote sensing techniques
(i.e., LiDAR) that are used to estimate soil loss using landscape scale
volumetric analysis will not be included in this evaluation.

Here we aim to systematically evaluate and compare the capabilities and
limitations of a variety of suspended sediment monitoring methods (i.e.,
autosampler, RS sampler, turbidity logger, and PASS sampler) when
applied to gully systems. The methods are compared under controlled
laboratory conditions and in the field to assess the relative ability of
each method to provide accurate measurements of suspended sediment
concentration and particle size distribution.

\section*{Methods}

{\label{methods}}

\subsection*{2.1 Modification of the PASS sampler to operate in ephemeral
waterways.}

{\label{modification-of-the-pass-sampler-to-operate-in-ephemeral-waterways.}}

The PASS sampler was originally designed for use in perennial waterways
(e.g., small permanently flowing streams and rivers) (Figure 1) (Doriean
et al., 2019). However, we propose that reconfiguration of the sampler
to operate in ephemerally flowing systems (e.g., gullies) will provide
an affordable alternative or complimentary monitoring method to those
currently used for the measurement of suspended sediment concentration
and particle size in ephemerally flowing systems, such as gullies.

The following modifications have been made to allow the use of the PASS
sampler in gully systems (Figure 1):

\begin{itemize}
\tightlist
\item
  The peristaltic pump has been placed before the settling column,
  rather than after it, to allow the sampler to be deployed dry. In its
  original design, the sampler needed to be filled with ambient water
  before deployment to ensure the peristaltic pump could generate enough
  vacuum to collect a sample.
\item
  A small coarse-sediment trap (or initial settling column) has been
  added at the intake of the pump to ensure larger particles (e.g., silt
  and sand) do not settle within the sampling tubing or damage the pump.
\item
  The main settling column outlet has been re-configured to include a
  vertical 4 mm inside diameter polypropylene tube with a 180 degree
  down-turn at the outlet to ensure water or debris cannot enter the
  sampler through the outlet (Figure 1).
\item
  A float switch has been added and placed at the same height as the
  sampler intake to ensure the pump only operates when water is flowing
  in the gully. The float switch requires the application of a timer
  (e.g., an hour meter or datalogger) linked to the PASS circuitry, or
  alternatively in tandem with a water level logger at the location of
  the sampler, to determine the sampling period and thereby the volume
  of water sampled.
\end{itemize}

\subsection*{2.2 Laboratory evaluation of gully monitoring
methods}

{\label{laboratory-evaluation-of-gully-monitoring-methods}}

Water quality conditions typical of a gully flow event, based on
previous observations at relevant field sites, were simulated in a
laboratory setting to evaluate the modifications made to the PASS
sampler design and to compare its performance with the other established
methods. A falling suspended sediment concentration trend (high
(\textasciitilde{}10,500 mg L\textsuperscript{-1}) to low (4,500 mg
L\textsuperscript{-1})) over a 6-hour period (typical of flow events in
the active gully used for the field evaluation of this study, determined
by preliminary field study data) was simulated using sediment sourced
from a gully at the field study site (median particle size of 29 \selectlanguage{greek}µ\selectlanguage{english}m). An
agitation vessel, similar in design to a churn splitter (20 L
cylindrical polypropylene container with four baffles (vertical strips
of aluminium, 0.5 cm thick and 3 cm wide, placed perpendicular to the
side wall, from the bottom to the top, of the vessel) (Ward et al.,
1990)) was used to create a turbulent flow of water during the
experiment (Figure 2).

A triplicate set of PASS sampler intakes were placed approximately 0.15
m above the bottom of the vessel. Sample inlets for discrete sample
collection, identical to the outlet of a churn splitter (Ward et al.,
1990), (6 mm ID polypropylene tube tapped through agitation vessel wall)
and the automatic sampler (Sigma\selectlanguage{ngerman}® 900) inlet were placed at the same
level as the PASS inlets to collect discrete samples. The discrete
automatic sampler was elevated (2 m) above its intake point to simulate
the configuration that would typically be used in the field. A turbidity
logger (Observator, NEP495 (measurement range 40-4000 nephelometric
turbidity units (NTU)) was placed at the same level as the sampler
inlets and programmed to record a turbidity measurement every
ten-minutes.

The RS sampler did not fit inside the agitation vessel, thus, a
substitute dataset using the discrete manual sample data (collected from
the isokinetic outlet) was generated to simulate the RS sampler data and
allow comparison with the other techniques. Laboratory test samples
collected using the discrete collection method and an RS sampler were
compared and found to be similar in suspended sediment concentration and
particle size distribution (\textless{} 2\% ± 1\% for both), which
provided confidence to rely on the discrete sample dataset to simulate
RS sample data. Flow event data gathered during a preliminary study,
from the gullies monitored at the field-test site show that there is
little hysteresis between suspended sediment concentration and water
level. Thus, the RS sample data was constructed based on time after
initial flow, estimating the peak stage to occur relatively early during
the simulated event (i.e., the peak water height of the simulated event
occurred 75-minutes into the 6-hour event).

To simulate the flow event, dry gully soil was weighed, suspended in a
small volume of rain water (collected from the laboratory roof) to aid
dispersion, and then diluted in rain water to a predetermined suspended
sediment concentration with a final volume of 15 L. The sediment was
kept in suspension using an overhead stirrer (OS40-S paddle stirrer)
operating at 500 rpm. The concentration was changed by exchanging the
water and sediment solution in the agitation vessel at 30-minute
intervals. Triplicate PASS samplers continuously sampled water from the
agitation vessel during the simulated flow event and repeat discrete
samples (three samples per method) were collected from the same vessel
using flow-proportional discrete sampling, simulated RS sampling and
discrete autosampling methods every 30 minutes (15-minutes after each
change in concentration).

\subsection*{2.3 Field evaluation of gully monitoring
methods}

{\label{field-evaluation-of-gully-monitoring-methods}}

The gullies monitored in this study were located at Crocodile Station in
North Queensland (15°40'08.4''S, 144°35'38.4''E), Australia, and drain
directly into the Laura River, which is connected to the coastal waters
of the northern Great Barrier Reef via the Normanby River (Olley et al.,
2013) (SI-1). The gullies are identified as alluvial gullies because
they are located in alluvial soils of the Laura River floodplain (Brooks
et al., 2013). Two gullies were studied to evaluate the accuracy and
limitations of the monitoring techniques for measuring suspended
sediment dynamics of gullies at different stages of erosion: an actively
eroding gully (gully-1) with high suspended sediment output consisting
of fine sediment (\textless{}63 \selectlanguage{greek}µ\selectlanguage{english}m) and some suspended sand (63-2000
\selectlanguage{greek}µ\selectlanguage{english}m); and a gully remediated in 2016 (gully-2) with relatively low
suspended sediment output dominated by fine sediment (\textless{}63 \selectlanguage{greek}µ\selectlanguage{english}m)
(SI-2). The suspended sediment particle size data used to describe the
suspended sediment characteristics of the test gullies was gathered in a
pilot study conducted at the study site.

The evaluated monitoring techniques consisted of a Sigma\selectlanguage{ngerman}® 900
autosampler, a modified PASS sampler, a RS sampler array (six stages),
and an Observator® NEP495 turbidity logger). Instruments were deployed
in close proximity to each other in a straight section of channel
approximately 50 m and 110 m downstream from the head of gully 1 and 2
respectively. The autosampler was placed on the bank beside the channel
(elevated approximately 2 m above its intake) with the intake positioned
in the middle of the channel cross section, 0.2 m above the channel bed
with the inlet facing downstream (SI-3). A float switch, placed at the
intake, was used to initiate and halt sampling. A PASS sampler was also
placed at the midpoint of the channel affixed to a steel fencing post,
driven into the channel bed; the intake and float switch were placed
approximately 0.2 m above the channel bed. RS samplers were placed in a
line along the channel centre at various heights above the channel bed,
ranging from 0.2 to 0.45 m at 0.05 m intervals. The turbidity logger was
placed alongside the autosampler inlet. A level logger (In-situ® R100)
was placed at the midpoint of the channel directly on top of the bed,
fixed to the steel support for the rising stage samplers. A barometric
pressure logger (In-situ® baroTROLL) was placed nearby above maximum
flood elevation, to allow accurate calibration of the level logger. A
rain gauge (Hydrological Services tipping bucket rain gauges - 0.2
mm/tip with Hobo data logger) was also placed within the catchment area
of the gullies.

Once activated, the autosampler collected a sample of approximately 800
mL every ten minutes, whilst the PASS sampler continuously sampled until
the ambient water level dropped below the float switch. The turbidity
logger was programmed to record a measurement every 10-minutes whilst
deployed. The RS samplers collected a sample when the water level
covered the intake and caused a pressure difference in the sampler,
resulting in rapid filling of the sampler (Braatz, 1961)\{Braatz, 1961
\#362\}. Manual flow-proportional samples were collected using a DH-48
sampler using the equal discharge method when flow velocity and depth
were sufficient (\textgreater{}0.3 m sec\textsuperscript{-1} and
\textgreater{}0.17 m, respectively), or taken directly from the stream
with a sample bottle when flow velocity and depth was too low for
accurate use of the DH-48 sampler (Edwards et al., 1999).

\subsection*{2.4 Sample analysis and
statistics}

{\label{sample-analysis-and-statistics}}

Samples collected from the laboratory and field evaluations were
analysed for suspended sediment concentration using ASTM standard method
D 3977-97 and particle size distribution using laser diffraction
spectroscopy (Malvern Mastersizer 3000, Malvern Instruments). Discrete
samples from the autosampler were analysed as received, whilst the PASS
samples (composites of main settling column and intake sediment trap),
were placed in cold storage (4°C) for five days to settle, after which
they were decanted to 1 L and analysed. The supernatant was filtered
through a pre-weighed glass fibre filter (Whatman GF/F (0.7 \selectlanguage{greek}µ\selectlanguage{english}m)), to
account for the mass of any sediment that may have remained in
suspension. The time-weighted average (non-continuous) suspended
sediment concentration was determined by averaging the concentration of
multiple discrete samples, weighted by the time span between two
sequential samples. The PASS sampler continuously samples whilst in
operation, thus, the time-weighted average suspended sediment
concentration is calculated by weighting the total mass of suspended
sediment collected by time as a function of volume (Doriean et al.,
2019). Turbidity measurements were calibrated using the discrete samples
from the autosampler. A linear regression between turbidity and
suspended sediment concentration was used to convert NTU measurements
into suspended sediment concentration, when appropriate (Rasmussen et
al., 2009). Statistical analysis was conducted using GraphPad-Prism\selectlanguage{ngerman}®.
The sample data did not share similar standard deviations, thus, the
unpaired nonparametric Mann-Whitney t-test method was used to compare
differences between methods (p = 0.05).

\subsection*{2.5 Data quality and
uncertainty}

{\label{data-quality-and-uncertainty}}

The uncertainty of each measurement method must be considered when
evaluating their relative performance. The uncertainty assigned to a
particular technique was determined based on laboratory evaluations
conducted during this study and the scientific literature. If the
difference in suspended sediment concentration between two sampling
methods was equal to or less than the cumulative error associated with
those methods, the individual results were not considered significantly
different (Horowitz 2017). For example, manual sampling uncertainty is
typically \textasciitilde{}10\% of the sample suspended sediment
concentration (Sauer et al., 1992), whereas, the PASS sampler was
previously demonstrated to exhibit \textasciitilde{}6 to 17\%
uncertainty (Doriean et al., 2019). Cumulatively this suggests a sample
concentration difference range in the order of 16 to 27\%. Thus,
suspended sediment concentrations of samples collected by these methods
that differed within this uncertainty range were not likely to be
statistically different (Horowitz, 2017).

\section*{Results and Discussion}

{\label{results-and-discussion}}

\subsection*{3.1 Comparison of laboratory evaluation of gully suspended
sediment monitoring
methods}

{\label{comparison-of-laboratory-evaluation-of-gully-suspended-sediment-monitoring-methods}}

The laboratory evaluation of the various monitoring methods
(flow-proportional discrete manual sampling, simulated RS sampler, PASS
sampler, autosampler, and turbidity logger) demonstrated the
capabilities and limitations of the methods to provide representative
measurements of suspended sediment concentration and particle size
distribution (Table 2, Figure 3, SI-4) as discussed in relevant sections
below. The scientific literature considers discrete manual, isokinetic
depth and width integrated, sampling to be the most representative field
sample collection method (Horowitz et al., 2008; Perks, 2014; Ward et
al., 1990). For this reason, we argue that assessment of sampler
performance under laboratory conditions should be made by comparison to
the discrete manual sampling results. The flow-proportional discrete
manual samples collected during the laboratory evaluation are comparable
to what would be collected using isokinetic manual sampling techniques
in the field (Ward et al., 1990).

3.1.1 Autosampler

The time-weighted average suspended sediment concentration of the
samples collected using the autosampler underestimated the manual
discrete sample time-weighted average suspended sediment concentration
by 38\% and was also lower than the other tested methods (Table 2). The
coarser sediment fraction (100-2000 \selectlanguage{greek}µ\selectlanguage{english}m) was also underrepresented in the
samples collected by the autosampler (Figure 3, Table 2). This is due to
increased head pressure and slower sampling velocity as a result of the
elevation difference between the autosampler and its sample intake.
Thus, heavier particles (i.e., sand) were under-represented in the
samples collected with the autosampler (Bent et al., 2003; Clark et al.,
2009; Fowler et al., 2009). These samples also had different suspended
sediment concentrations and particle size distribution to comparable
samples collected by the other methods (Figure 3). The finer fraction of
sediment (the 10\textsuperscript{th} percentile
(\emph{d\textsubscript{10}} ) of the particle size distribution) within
the samples, collected using the autosampler, appears to be similar to
the discrete sample sediment \emph{d\textsubscript{10}} , however, the
two datasets were significantly different (Table 2). Additionally, the
median sediment particle size (\emph{d\textsubscript{50}} ) and
90\textsuperscript{th} percentile (\emph{d\textsubscript{90}} ) of
samples collected using the autosampler were generally close to half or
less of those sediments collected by the other methods (Table 2). These
data indicate that unless an autosampler can be configured so that the
level of its intake is close to that of the sampling unit there will
likely be under-representation of larger suspended sediment particles
(\textgreater{}100 \selectlanguage{greek}µ\selectlanguage{english}m) and therefore also the suspended sediment
concentration in the collected samples. This limitation suggests that
suspended sediment data collected using an autosampler from a gully with
high channel banks should be corrected using comparable data from a more
representative method (e.g., manual sampling).

3.1.2 Rising stage sampler

The time-weighted average suspended sediment concentration derived from
RS sampler data was biased to a higher sediment concentration (32\%)
compared to the time-weighted average suspended sediment concentration
of the manually collected samples (Table 2). This bias was expected as
samples were not collected after the simulated peak stage (i.e., 75
mins). The particle size distribution was not significantly different to
the discrete manual sample data, as previously discussed in the methods,
and it was also similar to the PASS sample data (Table 2, Figure 3).

The RS sampler provides representative individual sample data, however,
the often rapid sampling rate due to gullies having a fast rising stage
and lack of falling stage data will likely result in an overestimation
of suspended sediment concentration and a potentially unrepresentative
PSD for a flow event (Garc\selectlanguage{ngerman}ía\selectlanguage{english}-Comendador et al., 2017; Shellberg et al.,
2013). However, we note that this laboratory simulation represents only
one type of hydrograph that may occur in gully systems, so the
suitability of the RS sampling approach should be considered on a
case-by-case basis using available data on the relationship of suspended
sediment concentration and flow at a particular field site.

3.1.3 PASS sampler

The time-weighted average suspended sediment concentration of the
samples collected using both discrete and PASS sampling methods differed
by only 9\% +- 5\% (Table 2). The suspended sediment concentration of the
sample water expelled (i.e., water not retained) by the PASS sampler was
150 mg/L, which is equivalent to the sampler retaining 98.5 +- 1\% of the
total sediment sampled. The modifications made to the PASS sampler,
therefore, have not hindered its ability to collect a representative
sample of time-weighted average suspended sediment concentration and
particle size distribution.

The particle size distribution statistics
(i.e.,\emph{d\textsubscript{10}, d\textsubscript{50}, and
d\textsubscript{90}} ) of the suspended sediment collected using the
PASS and discrete sampling methods reveal generally good agreement
between the two methods (Table 2). The distribution of fine particles
\textless{} 10 \selectlanguage{greek}µ\selectlanguage{english}m were almost identical, whereas distributions of larger
(heavier) particles differed with increasing size (Figure 3). This
difference is likely due to the heterogeneity in sand particles in
suspension within the agitation vessel during the test. The continuous
collection of sediment by the PASS sampler should more accurately
incorporate this heterogeneity into the final measurement compared to
discrete sampling, which likely explains the difference in the coarser
sediment particle size fractions collected by the PASS and discrete
sampling methods (Figure 3).

Overall, our data suggests that the PASS sampler is capable of
collecting a time-integrated sediment sample that is comparable in
suspended sediment concentration and particle size distribution to that
collected by isokinetic manual sampling approaches, under controlled
laboratory conditions.

3.1.4 Turbidity Logger

Turbidity measurements and discrete sample suspended sediment
concentrations had a strong linear relationship (R\textsuperscript{2} =
0.97), indicating that a predictive relationship between turbidity and
suspended sediment could be used to estimate SSC from turbidity data
(SI-5). Simulated RS sampler sample suspended sediment concentrations
also had a strong linear relationship with turbidity
(R\textsuperscript{2} = 0.94), however, this was only for three paired
measurements, which is not sufficient to derive a predictive
relationship between turbidity and suspended sediment concentration
(Rasmussen et al., 2009). Suspended sediment concentrations of the
samples collected with the autosampler showed a more variable
relationship with turbidity measurements (R\textsuperscript{2} = 0.87)
(SI-5). The time-weighted average suspended sediment concentration
derived from turbidity data corrected with manually collected discrete
samples compared well to the PASS (within 11\%) and RS samples (within
26\%) (SI-4). These results suggest the turbidity logger may be a good
surrogate for the other monitoring methods provided a significant
relationship between suspended sediment concentration and turbidity can
be obtained under field conditions.

\subsection*{3.2 Field evaluation of gully monitoring
methods}

{\label{field-evaluation-of-gully-monitoring-methods-1}}

The two gullies at the field site were investigated over two wet seasons
(2017/2018 and 2018/2019). During this time several flow events of
different intensities were monitored (SI-6). Due to the remote locations
of gullies used in this study, samples were often only able to be
retrieved after multiple flow events had occurred, rather than after
individual flow events. As such, there were only a limited number of
single flow events that could be used to directly compare the
performance of the various monitoring methods.

3.2.1 Autosampler

The autosampler collected samples in gully-2 with suspended sediment
concentrations and particle size distributions that were similar to the
other methods. The lack of suspended sand in gully-2 (commonly less than
2\% by sample volume) meant that samples were representative despite the
sampling unit being elevated (\textgreater{}1.5 m) relative to the
intake (Table 3 and Figure 4). In contrast, samples collected using the
autosampler from gully-1 had similar characteristics to those observed
in the laboratory test, where suspended sediment concentration and
particle size distribution were different to the PASS and RS samples
when a relatively large amount of suspended sand was present
(\textgreater{}20\%) (Table 3). For example, during a short and intense
flow event during the Jan-18 to Feb-18 sampling period in gully-1,
samples collected by the autosampler underestimated the time-weighted
average suspended sediment concentration by \textasciitilde{}30\%
compared to the PASS sampler (Table 3, SI-6). Conversely, flow events
that had relatively lower proportions of suspended sand
(\textless{}10\%) compared well to PASS sampler and RS sampler
estimates. These differences in sample suspended sediment concentration
and particle size distribution are consistent with observations from the
laboratory test where the autosampler was unable to collect
representative samples of the coarser sediment fractions due to the
vertical displacement between the sampler position and its inlet.
Additionally, the autosampler had several operational issues (e.g.,
insect infestation, sample intake blockages, and programming
malfunctions) that limited the number of samples it collected in these
specific field settings.

3.2.2 Rising Stage Sampler

The remote location of the study site meant the RS sampler arrays (i.e.,
six samplers) were only collected three times during the study period.
This highlights the challenge of gaining sufficient samples for more
than a small number of flow events from a gully using this method
compared to the autosampler and PASS sampler, which can sample multiple
flow events per deployment.

Based on the results of the laboratory evaluation, samples collected
using the RS sampler were expected to be more representative of actual
suspended sediment concentrations compared to samples collected by the
autosampler. This was valid for most samples, however, under the field
conditions prevailing at the study site some of the RS samplers were
observed to accumulate large quantities of water (between 25-35\% of the
1 L sampler volume) due to condensation. This phenomenon was
unpredictable and resulted in suspended sediment samples being diluted
by unknown amounts of water, thus potentially introducing significant
error to the calculated SSC. Condensation in RS samplers has been noted
in previous studies (Edwards et al., 1999), however, these comparatively
large accumulations of condensate are likely caused by the high ambient
daytime air temperatures and relative humidity, followed by cooler night
time temperatures (a change of \textasciitilde{}18\selectlanguage{ngerman}°C), at the study
site. This is likely to be an issue at many sites located in tropical
regions and should be considered when designing monitoring programs in
such places.

Unfortunately, upon return to a remote site following a flow event,
there is no way of knowing which, if any, or to what degree individual
samples collected by the RS samplers were affected by condensation.
Considering this, it is best to interpret the RS sample suspended
sediment concentration data with approximately 25-30\% uncertainty. The
RS samples had suspended sediment concentrations and particle size
distributions in the range of the autosampler and PASS sampler samples
(Table 3, Figure 4), although it is possible some of the suspended
sediment concentrations could be outside of that range if condensation
is considered. RS samples demonstrated the variability in particle size
distribution under different water depth conditions well. For example,
during a flow event in gully-1, the particle size distribution shifted
between being dominated by finer and coarser particle as the water level
increased (e.g., sample \emph{d\textsubscript{50}}
and\emph{d\textsubscript{90}} ranged between 6.24 to 11.8 and 59.9 to
116, respectively) (SI-7). This ability to obtain information on
suspended sediment particle size dynamics is a strength of the RS
sampler approach.

Overall, suspended sediment concentration (provided the sampler is not
compromised by condensation) and sediment particle size data of the RS
samples compared well with the PASS sampler in both gully types. The
development of a falling stage sampler has been recently reported,
although no assessment of its limitations or capabilities has been done
to date (DPI, 2017). Such a sampler could address a major limitation of
using RS samplers for monitoring sediment transport processes in
gullies.

3.2.3 PASS sampler

The particle size distribution of the samples collected from gully-2 by
the autosampler, RS sampler, and PASS sampler were all very similar for
all flow events (Table 3 and Figure 4). The average particle size
distribution of the samples collected by the autosampler and PASS
sampler were often within the uncertainty of their respective particle
size distribution statistics (\emph{d\textsubscript{10},
d\textsubscript{50}, d\textsubscript{90}} ) (Table 3). This data
confirms the observations of the laboratory test in that the PASS
sampler is collecting a sample comparable to the other methods for both
time-weighted average suspended sediment concentration and particle size
distribution of fine suspended sediment (\textless{} 63 \selectlanguage{greek}µ\selectlanguage{english}m).

The PASS sampler, RS sampler, and autosampler data did not agree as well
for samples collected from gully-1, where the higher percentage of
suspended sand present during flows resulted in more variable suspended
sediment concentrations and particle size distributions (Table 3, Figure
4). Despite this, the range of time-weighted average suspended sediment
concentrations of PASS samples compared relatively well with the other
methods for flow events with less suspended sand (e.g., flow events
sampled between November 2017 and January 2018) (Table 3). The particle
size distribution of coarser sediment (i.e.,
the\emph{d\textsubscript{90}} ) measured for the PASS samples were
typically more than double those measured on the RS and autosampler
samples, which indicates that the latter methods likely
under-represented the coarser suspended sediment fraction in gully-1.
The time-weighted average design of the PASS sampler means it cannot
provide information on suspended sediment dynamics during a flow event.
However, the PASS sampler is well-suited for investigating long-term
trends in suspended sediment concentration and particle size
distribution (e.g., several wet seasons), and for assessing the
effectiveness of gully remediation works. Comparison of the laboratory
and field data of the PASS sampler to the autosampler and RS sampler
shows the method provides the most representative time-integrated
suspended sediment data of the three methods and because the PASS
sampler data was most consistent with manually collected samples.

3.2.4 Turbidity Logger

The turbidity logger can provide a high frequency of suspended sediment
concentration measurements over extended time periods (e.g., months),
provided there are sufficient comparable physical samples collected to
ensure accurate calibration of the method (Rasmussen et al., 2009).
There were some instances, at gully-2, where turbidity measurements
could have been corrected to suspended sediment concentration
measurements, using samples collected by the autosampler
(R\textsuperscript{2} \textgreater{} 0.83 (SI-8)). However, this
characteristic was not reflected in the measurements collected from
gully-1, where the relationship between the autosampler sample suspended
sediment concentrations and the turbidity logger measurements was poor
(R\textsuperscript{2}=0.17 (SI-8)).

The lack of a relationship between turbidity and SSC at gully-1 was
likely due to the higher proportion of sand at this site. The turbidity
measurement method is based on the detection of light intensity,
originally emitted from the instrument, refracted from a particle back
to the instrument detector. A study by Rasmussen et al. (2009) found the
presence of fine to very coarse sand (125-2000 \selectlanguage{greek}µ\selectlanguage{english}m) can often a
negatively bias turbidity measurements because the larger particles do
not reflect light in a manner that is consistent with that used to
calibrate the instrument (Rasmussen et al., 2009). This measurement
characteristic often leads to an underestimation of the
turbidity-suspended sediment concentration relationship (Bent et al.,
2003; Clark et al., 2009; Fowler et al., 2009).

Without site-specific calibration, turbidity measurements are unlikely
to be suitable for even semi-quantitative investigations of suspended
sediment dynamics in gully systems. This is evidenced by the lack of
significant difference between the turbidity measurements of the loggers
located in the two studied gullies (SI-9), despite very different
suspended sediment concentration ranges and PSDs (Table 3; Figure 4).
For example, the mean turbidity of gully-1 (1250 (\selectlanguage{ngerman}± 1173) NTU) and
gully-2 (1501 (± 994) NTU), for the 2017/2018 wet season, were not
significantly different, yet the SSCs measured by the other methods
differed by \textasciitilde{}4 to 7-fold between these gullies (Table
3). This emphasises the importance of collecting representative
suspended sediment concentration samples in-order to calibrate the
turbidity measurement to a surrogate suspended sediment concentration.
Turbidity measurements alone do not provide useful information and thus
should only be relied upon as a complimentary addition to other
monitoring methods (e.g., RS or PASS samplers).

3.2.5 Comparison to manual sampling

The collection of manual samples from gullies is often difficult due to
the remote location of the sites, safety concerns, and the
unpredictability of flow events. However, samples were able to be
collected from a single flow event in gully-1. Seven samples were
manually collected during this event using a DH-48 sampler, and one
time-integrated sample was collected over the same period by a PASS
sampler deployed in the gully. There was little difference between
average particle size distributions (Table 4, Figure 5) and the
time-weighted average suspended sediment concentrations of the manually
collected samples (6067 mg L\textsuperscript{-1}) and PASS sample (6082
mg L\textsuperscript{-1}), respectively. While these data are
preliminary, it further supports the ability of the PASS sampler to
collect representative samples of time-weighted average suspended
sediment concentration and particle size distribution in challenging
field settings.

\section*{Conclusion}

{\label{conclusion}}

This study shows that no individual suspended sediment monitoring method
is suitable for providing the necessary data to understand sediment
transport dynamics in a flowing gully. Rather, the application of a
combination of complimentary methods is necessary to reliably provide
representative data from these challenging aquatic environments. For
example, autosamplers provide multiple samples over a flow event but
fail to sample coarser particles accurately; the calibration of samples
collected by autosamplers with the time-integrated data from a PASS
sampler, which does sample coarser particles relatively accurately,
would result in a more reliable dataset than the use of either method
alone. Other configurations could be used to improve the spatial scale
of monitoring effort, for example, low cost methods (i.e., PASS and RS
samplers) could be deployed at various locations throughout a network of
gullies, whereas multiple methods (i.e., PASS and RS samplers, turbidity
logger, and an autosampler) would be deployed at the gully network
outlet.

The modified PASS sampler performed well in both laboratory and field
trials. The modification of the PASS sampler to operate in gullies is a
good example of how existing techniques can be customised to operate in
the harsh environments typical of gully systems. We aim to further
modify the PASS sampler by interfacing a flow meter and pump controller
so that its sample rate can be matched to stream velocity, thus allowing
the collection of a flow proportional (i.e., isokinetic) sample. Further
comparisons using the PASS sampler and other methods in different
gullies with varied suspended sediment dynamics are required to confirm
its validity as an automated sampling method for gully systems.

\section*{Acknowledgments}

{\label{acknowledgments}}

The authors acknowledge the traditional owners of the country this study
was conducted on. We thank the Laura Ranger group for their support
throughout the field monitoring component of this study, we would not
have half the information we do now without their help. We also thank
William Higham and Michael Goddard for the opportunity to collaborate
with them on the site. Much gratitude to John Spencer for his technical
expertise and for the long hours of fieldwork and data processing.
Thanks also to the assistance of Emily Looke.

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