2 Methodology
2.1 Experimental Design
For our experiment, we chose two well-studied (see e.g.(Orlowski et al.,
2016b, 2018b)) physico-chemically different soil types – a clayey loam
(LUFA 2.4) and a silty sand (LUFA 2.1) – from the German State Research
Institute for Agriculture (LUFA Speyer, 2015). For a detailed
description of the soil properties, the reader is referred to Orlowski
et al. (2018). Soils were sieved (2 mm) and oven-dried (48 h, 200°C). We
chose two experimental approaches to test the effect of different
pressure levels on the extracted soil water isotopic composition.
Experiment 1 aimed at sampling soil water along the pF curve and during
experiment 2 soil water was sampled sequentially at the highest pressure
level (15 bar) over 7 days. We further tested whether there is an
isotopic exchange between the ceramic plate water of the extractor and
the water to be extracted from the soil samples sitting on these ceramic
plates during extraction. Both experiments are based on spiking
approaches with two different waters of known isotopic composition (see
e.g.,(Orlowski et al., 2016b, 2018b)).
For the soil water extractions and the determination of water retention
curves, we used pressure extractors (Soilmoisture Equipment Corp., USA;
Figure 1). For errors associated with this method, the reader is
referred to Solone et al. (2012). Each pressure extractor cell contains
a porous ceramic plate covered on one side by a thin Neoprene diaphragm
sealed to the edges of the plate (Figure 1). Soil water is extracted via
air pressure under controlled conditions. Once air pressure inside the
pressure extractor cell is raised above atmospheric pressure, the higher
pressure inside the extractor forces excess water through the
microscopic pores in the ceramic plate. An internal screen between the
ceramic plate and a diaphragm further allows the extracted water to exit
the pressure plate cell via an outlet tube running through the plate,
which connects this water passage. However, the high pressure air will
not flow through the pores in the ceramic plate since the pores are
filled with water and the surface tension of the water, at the
gas-liquid interface at each of the pores, supports the pressure much
the same as a flexible rubber diaphragm (Soilmoisture, 2008). Thus, the
pressurized air will not isotopically interact with the soil water.
2.1.1 Experiment 1
The null hypothesis guiding experiment 1 was that soil water sampled
along the pF curve has the same isotopic composition over different pF
values, which also does not differ from the isotopic label used for
spiking the soils.
For rehydration, disturbed oven-dried soil was packed (silty sand: 105
g; clayey loam 121 g) into 100 mL open-bottom, stainless steel cylinders
(N=4 for each pF level). The bottom of the cylinders were covered with a
sterile polypropylene mesh to allow for water uptake but to prevent a
loss of soil material. Cylinders were placed in a water bath, filled
with distilled water (DIW) of known isotopic composition
(δ2H: −58.4±0.2‰, δ18O: −8.6±0.1‰).
The water bath was covered and sealed with a gas-tight lid to prevent
evaporation. Soils were left to saturate for two days. The ceramic
plates of the pressure extractors were likewise placed in a water bath
containing the same type of water and were also left to saturate for two
days (following the technical description by Soilmoisture (2008)).
Thielemann et al. (2019) showed that for spiking experiments with water
of known isotopic composition, 94% of the isotopic change is already
manifested after 1 day of equilibration. Afterwards, cylinders including
the saturated soils were placed in the pressure extractors and
increasing pressure levels were applied (pF: 1.4–4.2) (Appendix A). The
water being extracted at each pressure level was directed via an outlet
tube (consisting of Swagelok® fittings; Swagelok Company, Solon, OH, US)
into a sampling flask (Figure 1). Before applying the next pressure
level, ports and tubing were dried with compressed air and a new
sampling flask was attached to the outlet tube of the extractor. After
each pressure level, the amount of sampled water was determined and soil
samples were weighed. After two pressure stages (pF 3 and 4.2), eight
samples of each soil type were transferred into glass vials for
cryogenic vacuum extraction to remove any remaining water. Cryogenic
vacuum extraction was performed using the facility described in Orlowski
et al. (2013). Following Orlowski et al. (2018), clayey loam samples
were extracted for 240 min and silty sand soils for 45 min at a
temperature of 98°C and a baseline pressure of 0.1 Pa. After cryogenic
extraction, soils were oven-dried (24 h, 105°C) and weighed again with
no significant additional weight loss indicating that the water
extraction process was complete.
For isotope analysis, the extracted soil waters were filtered on 0.45 μm
disk filters, transferred to 2 mL amber glass vials covered by solid
silicone septa, and tightly sealed with Parafilm®.
2.1.2 Experiment 2
With experiment 2, we tested whether soil water collected sequentially
over a period of 7 days under the highest pressure level (15 bar) would
differ isotopically from the introduced isotopic label. Additionally, we
checked whether there is an isotopic exchange between the ceramic plate
water and the water to be extracted from the saturated soil samples.
Thus, a different rehydration and extraction approach was used. This
time, soil samples (N=30 per soil type, 2 per time step) were rehydrated
in the same manner as for experiment 1 but with “Lauretana” water (LW,
commercial sparkling water; δ2H: −64.6±0.6‰,
δ18O: −9.8±0.1‰) and the ceramic plates of the
pressure extractors were rehydrated with the same distilled water as in
experiment 1. Both waters differ isotopically. Mean water content of the
clayey loam samples after rehydration was 44.2±1.2 Vol-% and for the
silty sand samples 25.5±0.6 Vol-%. For water extraction, the highest
pressure level (15 bar) was directly applied to the pressure extractors
and a sequential soil water extraction was performed. Therefore, water
was sampled after 10-80 min (every 10 min), 105, 115, 125, 150, 180, 240
min, 1 day, 2, 5 and 7 days. After pressure extraction, cryogenic vacuum
extraction was performed on all soil samples (as in experiment 1). We
further crushed the ceramic plates used for this experiment and
cryogenically extracted the bound water (in the same manner as the
clayey loam). Pre- and post-extraction (pressure extractor and cryogenic
vacuum extraction) weights and oven-drying weights of soil samples were
determined. There was no significant additional weight loss after
oven-drying of the cryogenically extracted soil samples (mean±SD weight
loss for the clayey loam and silty sand samples, respectively:
0.07±0.03g, 0.03±0.02g).
2.2 Isotope analysis
δ2H and δ18O compositions of
extracted soil water samples were measured at the Institute for
Landscape Ecology and Resources Management (Justus Liebig University
Giessen, DE) on a L2130-i isotope analyzer (Picarro Inc., US). The
accuracy of the isotope analyses was ±0.2/±0.8‰ for
δ18O/δ2H (determined via repeated
measurements of the same sample). All isotope ratios are reported in per
mil (‰) relative to Vienna Standard Mean OceanWater
(VSMOW) (δ2H or
δ18O=(Rsample/Rstandard-1) x 1000
‰), where R is the isotope ratio of the sample and the known reference
(i.e., VSMOW) (Craig, 1961). In-house standards, were run as samples to
allow the results to be reported against VSMOW (Nelson, 2000). Isotope
data of soil water extracts were checked for spectral interferences
(caused by potentially co-extracted organics such as methanol or
ethanol) using ChemCorrect™. This software attempts to identify
contaminations in water samples both through fitting to a known library
of spectral features, and by examining changes in baseline, slope,
line-broadening and residual noise of the spectra (West et al., 2011).
Further information about this approach is available from the
manufacturer (Picarro, 2010). No sample was found to be contaminated by
organics.
2.3 Statistical Analysis and
Evaluation
We used R for statistical analyses (R version 3.6.3; R Core Team
(2014)). All data were tested for normality using the Shapiro-Wilk test.
Homoscedasticity was tested using either the Levene’s test for normally
distributed data or the Fligner-Killeen test for non-normally
distributed data. Cluster analysis based on the furthest neighbor
approach using the Euclidean distance as measure was performed in order
to identify outliers. This method is more robust for non-normally
distributed data. Depending on the type of data (normally distributed
and homoscedastic), either Kruskal-Wallis rank sum tests or Analyses of
Variances (ANOVAs) were applied and posthoc tests (e.g., Tukey-HSD tests
(equality of variances) or Dunnett-T3 tests (non-equality of variances))
were run to determine which groups were significantly different
(p≤0.05). Dual isotope (δ18O vs.
δ2H) graphical representation was used to compare
water extracts from different pF levels (experiment 1) and times of
extraction (experiment 2). Statistically significant (p≤0.05) linear
regressions were added to dual isotope plots as well as the Global
Meteoric Water Line (GMWL:
δ2H=8.2×δ18O+11.3‰, as defined by
Rozanski et al. (1993)).
Many models for fitting the SWRCs have been proposed (Leong and
Rahardjo, 1997). We used the well accepted and widely applied van
Genuchten model (Eq. 1) (van Genuchten, 1980) to fit water retention
curves to our measured soil water retention data of the two soil types:
\(S=\frac{\theta-\theta r}{\text{θs}-\theta r}=\left(1+{(\alpha h)}^{n}\right)^{-m}\)\(m=1-\frac{1}{n}\) [Eq. 1]
where S is effective saturation (dimensionless), θ is the soil
moisture content (Vol., %), while θ s andθ r are the saturated and residual soil water
content (Vol., %), respectively. h denotes the soil water
potential or pressure head (hPa, also written as cm
(H2O)), α is the scaling parameter which
reciprocal can be rated as the air entry pressure
(cm−1), m and n are dimensionless
parameters related to the curve shape. Best fit parameters (α ,m and n ) were estimated for the van Genuchten model of
SWRC using “SWRC Fit” (SWRC Fit, 2020) and checked against literature
values from Carsel and Parrish (1988). It is, however, well known that
the SWRC relationship may vary substantially even for the same soil
texture class due to the variation in fitting parameter (α ) and
pore size distribution parameter (n ) (Tuller and Or, 2005). To
measure the goodness of fit between the measured and the predicted data,
coefficients of determination (R2) were obtained for
each dataset.