HYDROLOGICAL PROCESSES
Hydrol. Process. 23, 2095–2101 (2009)
Published online 20 April 2009 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hyp.7326
A tale of two isotopes: differences in hydrograph separation for
a runoff event when using dD versus d18O
Steve W. Lyon,1 *
Sharon L. E. Desilets,2 and
Peter A. Troch2
1
Physical Geography and Quaternary
Geology, Stockholm University,
Stockholm, Sweden
2
University of Arizona, Hydrology and
Water Resources, Tucson, AZ, USA
*Correspondence to:
Steve W. Lyon, Physical Geography
and Quaternary Geology, Stockholm
University, 106 91 Stockholm,
Sweden.
E-mail: [email protected]
Abstract
It is often assumed that stable water isotopes (dD and d18 O) provide redundant
information for a given sample of water. In this note we illustrate that the choice of
isotope used may influence the resultant hydrograph separation. This is especially
true in light of the spatial and temporal variability in the isotopic composition
of rainfall water at the catchment scale. We present several possible hydrograph
separations based on both dD and d18 O observed in rainfall for a single runoff
event occurring in the southwest USA. This study demonstrates the potential
of using both stable water isotopes by showing that dD and d18 O may provide
unique information for catchment hydrologists. We also report on the utility of
new technology capable of simultaneous measurements of both dD and d18 O using
off-axis integrated cavity output spectroscopy (OA-ICOS) methods. This may be
of interest to catchment hydrologists seeking to incorporate this type of equipment
into their laboratory. Copyright  2009 John Wiley & Sons, Ltd.
Key Words
hydrograph separation; stable water isotopes; off-axis integrated
cavity output spectroscopy
Introduction
Received 14 October 2008
Accepted 10 March 2009
Copyright  2009 John Wiley & Sons, Ltd.
The use of stable water isotopes has become ubiquitous in catchment
hydrology. These naturally occurring tracers are popular because they allow
hydrologists to ‘label’ water. This provides a method to differentiate from
where spatially [e.g. transit time distribution modelling such as that presented
by Dinçer et al. (1970), Maloszewski and Zuber (1982), Pearce et al.
(1986), Kirchner et al. (2000), and McGuire and McDonnell (2006)] or
from when temporally [e.g. hydrograph separation such as that presented
by Sklash and Farvolden (1979), Pearce (1990), Burns (2002), Buttle and
McDonnell (2004)] stream water comes. Such estimates can help improve
our process understanding at the catchment scale (Ambroise, 1996; Burns,
2002; McGlynn et al., 2004).
Newly available gas analyzers based on off-axis integrated cavity output spectroscopy (OA-ICOS) lasers provide an alternative to conventional
isotope-ratio mass spectrometers (IRMS) for the stable isotopic analysis of
water samples (Lis et al., 2008). This OA-ICOS technique determines the
isotopic composition of a sample gas by tuning a narrow laser beam across
the linewidth of a characteristic absorption band for stable water isotopes
(typically, 2 H and 18 O) and integrating the resultant spectra in combination with Beer’s Law. In general, Beer’s Law relates the absorption of light
to the properties of the material through which the light travels. Here, the
light source is a laser, the material is a vapourized sample of water, and
the property of interest is the isotopic composition. High-reflectivity mirrors
are used in OA-ICOS to effectively trap the laser photons, causing them to
pass through the sample gas thousands of times. This significantly increases
the sensitivity of the method by increasing the laser path length to several
thousands of metres. OA-ICOS has several advantages compared to IRMS
(Kerstel et al., 2006; Lis et al., 2008). The capital cost is much lower, as
well as the operation costs per analysed sample. The simpler methodology
of OA-ICOS involves few moving parts and as such requires less expertise
for operation, maintenance, and repair. Smaller sample sizes and less sample preparation are necessary for OA-ICOS analysis. Finally, when used for
2095
S. W. LYON, S. L. E. DESILETS AND P. A. TROCH
stable isotopic measurements of waters, OA-ICOS measures υD and υ18 O directly and simultaneously on H2 O
molecules from a single injection, which is impossible
with conventional IRMS systems. This makes it possible
for hydrologists to obtain both υD and υ18 O for a water
sample.
Because υD and υ18 O are related by the meteoric
water line (MWL) their information is generally considered redundant. However, where there is significant
deviation about the MWL in precipitation or terrestrial
water, the two can be used independently. This deviation, termed deuterium excess and quantified by the
d-parameter (Dansgaard, 1964), can come from a variety
of mechanisms, many of which are more common in dry
environments: secondary evaporation of raindrops below
the cloud base (Gat, 1996), precipitation from clouds with
water vapour supersaturated over ice (Jouzel and Merlivat, 1984), precipitation that originally evaporated from
different source waters, certain rainout slopes (depending on humidity and temperature), mixing of water from
different climates or seasons, and mixing with an evaporated body of water (e.g. lake, downstream) (Ingraham,
1998).
The main goal of this note is to exemplify the differences in hydrograph separation due to the use of υD
versus υ18 O. To demonstrate this in a catchment hydrology framework, we present several possible hydrograph
separations based on both υD and υ18 O levels observed
in rainfall for a single event occurring during the monsoon season of the southwest United States. We show
that υD and υ18 O may not necessarily provide redundant information for catchment hydrologists and that the
choice of isotope may influence hydrograph separation.
This is especially true in light of the spatial and temporal
variability in the isotopic composition of rainfall water
at the catchment scale. A secondary goal of this note is
to report on the associated cost and utility of relatively
newly available OA-ICOS equipment for measuring stable water isotopes. We provide this information as it may
be useful to researchers, considering the incorporation of
such newly available equipment into their research.
Upper Sabino Case Study
Lyon et al. (2008) used hydrometric and isotopic data
to characterize an extreme runoff event occurring on 30
July 2006 at the Upper Sabino research catchment located
northeast of downtown Tucson, AZ, USA (Figure 1). The
Upper Sabino research catchment occupies the uppermost elevations of the Santa Catalina Mountains and
has an elevation ranging from 2170 to 2790 m. The
catchment is covered primarily with pine and fir forest
due to the more humid climate found in this ‘sky island’
setting. Soils are typified by sandy loams of variable
depth ranging from greater than 1Ð5 m to less than 0Ð25 m
across the catchment. The extreme runoff event discussed
in the study by Lyon et al. (2008) resulted from the
fifth consecutive event in a sequence of extreme rainfall
events. The prior event delivered a total amount of
Copyright  2009 John Wiley & Sons, Ltd.
Figure 1. Observed rainfall and stream-flow response to the extreme
event occurring in the Upper Sabino research catchment. Isotopic values
for both υD and υ18 O observed in the stream samples (samples D filled
circles, piece-wise interpolation D light dotted line), and rainfall samples
at Mt. Lemmon (bulked D heavy solid line, samples D crosses) and at
Mt. Bigelow (bulked D heavy dashed line) are shown
rainfall of 78Ð6 mm across the catchment while the 30
July 2006 event delivered 26Ð1 mm resulting in a ratio
of total runoff depth and the total rainfall depth (runoff
ratio) of 0Ð72 (Lyon et al., 2008). The experimental
setup to monitor rainfall and runoff in this catchment
included a network of 20 tipping bucket rain gauges
spread across the catchment and a stream gauge with
automatic water sampler installed at the catchment outlet
allowing for multiple water samples to be collected in
response to rising (and falling) water levels. The reader
is referred to the study by Lyon et al. (2008) for a site
map and complete details on the experimental design and
catchment description.
In addition to the aforementioned instrumentation, two
rainfall sampling locations were instrumented at opposite ends of this 8Ð8 km2 , east–west oriented catchment. These locations were atop the highest (Mt.
Lemmon—west-most peak) and second highest (Mt.
Bigelow—east-most peak) peaks in the catchment. Both
sampling locations were equipped with automatic samplers designed to collect multiple samples of rain water
during individual rainfall events. Due to mechanical
error, the automatic sampler at the eastern most peak
(Mt. Bigelow) only provided a bulk sample of rain
water during the 30 July 2006 event, which was sampled within a few hours after the cessation of rainfall.
2096
Hydrol. Process. 23, 2095–2101 (2009)
DOI: 10.1002/hyp
SCIENTIFIC BRIEFING
Lyon et al. (2008) thus use a spatially uniform representation of temporally variable υ18 O values observed in the
rainfall at the western most location (Mt. Lemmon) to
perform a traditional two-component hydrograph separation (Sklash et al., 1976; Sklash and Farvolden, 1979;
Buttle and McDonnell, 2004) and a transfer function
hydrograph separation using TRANSEP (Weiler et al.,
2003) for the event (Table I, scenarios 1–3). Comparing rain water υ18 O values observed at Mt. Lemmon
and those observed in the bulk sample collected at Mt.
Bigelow, Lyon et al. (2008) note the spatial variability in rainwater υ18 O values across the catchment. The
precipitation falling in the eastern region of the catchment had a υ18 O value similar to that of pre-event
stream water (8Ð8 and 8Ð9‰ for Mt. Bigelow rain
water and pre-event stream water, respectively). The
total amounts of rainfall observed at Mt. Bigelow and
Mt. Lemmon for this event were 24Ð9 and 34Ð5 mm,
respectively, indicating slight bias in rainfall amount in
the vicinity of Mt. Lemmon compared to the catchment
wide average rainfall amount of 26Ð1 mm (Lyon et al.,
2008).
The observed spatial variability in precipitation υ18 O
values across the catchment likely influences the observed
stream υ18 O values for this event. The influence of water
coming from the eastern region of the catchment (25%
by area based on the structure of the stream network) is
effectively masked in the observed stream υ18 O values
as its υ18 O signature is not significantly different from
pre-event stream water. By assuming a spatially uniform,
temporally variable precipitation υ18 O value, the resultant
hydrograph separations emphasize the contribution of the
western 75% of the total catchment area. This may have
led to an under-estimation of the total amount of event
water represented in the hydrograph separations by Lyon
et al. (2008).
While they are typically assumed to provide redundant information, the use of multiple stable water isotopes (e.g. υD and υ18 O) may allow for a more unique
characterization of event water under such conditions.
To demonstrate this, we have obtained measures of
both υD and υ18 O by mass spectrometer at the Laboratory of Isotope Geochemistry at the University of
Arizona for the rainfall and runoff samples collected
for the study by Lyon et al. (2008). These measures
are compared to measures of υD and υ18 O determined
using OA-ICOS equipment to demonstrate the utility
of such equipment. These values are then used to perform several variations on the hydrograph separations
reported by Lyon et al. (2008) using both υD and
υ18 O.
Comparison of OA-ICOS and Mass
Spectrometry
Analytical procedure
The DLT-100 [Los Gatos Research (LGR), Inc., model
908-0008], an OA-ICOS liquid water isotope analyzer,
is operated in a temperature-controlled water chemistry
laboratory where it is coupled with an LC-PAL autosampler from CTC Analytics. Glass vials (2 ml capacity)
are filled with a 1 ml filtered (0Ð45 µm) sample and
Table I. Various hydrograph separations using the observed υ18 O and υD values for the extreme runoff event occurring on 30 July
2006 at the Upper Sabino research catchment reported by Lyon et al. (2008)
Scenario
Method
Rain data
% Event water
% Pre-event water
Temporal variable
Mt. Lemmon υ18 O
23
77
Temporal variable
Mt. Lemmon υ18 O
24
76
3
TRANSEP (Weiler et al., 2003) using
exponential distribution transport
transfer function
TRANSEP (Weiler et al., 2003) using
dispersion distribution transport
transfer function
Two-component
25
75
4
Two-component
22
78
5
Two-component
36
64
6
Two-component
26
74
7
Two-component
99
1
8
Two-component
66
34
9
Two-component
47
53
10
Two-component
31
69
11
Three-component
Temporal variable
Mt. Lemmon υ18 O
Temporal variable
Mt. Lemmon υD
Temporal bulk
Mt. Lemmon υ18 O
Temporal bulk
Mt. Lemmon υD
Temporal bulk
Mt. Bigelow υ18 O
Temporal bulk
Mt. Bigelow υD
Temporal bulk
Area-weighted
υ18 O
Temporal bulk
Area-weighted
υD
Temporal bulk
All data
54
46
1
2
Copyright  2009 John Wiley & Sons, Ltd.
2097
Hydrol. Process. 23, 2095–2101 (2009)
DOI: 10.1002/hyp
S. W. LYON, S. L. E. DESILETS AND P. A. TROCH
sealed with a screw cap to prevent evaporation. A
5 Hamilton glass syringe draws 1Ð0 µl of sample to
inject into a heated port (¾70 ° C). For each injection,
the absorption spectra for each isotope are determined
20 times and averaged. Between injections, the sample chamber is flushed with air that has been drawn
through a desiccant column to remove water molecules.
To further eliminate memory effect between samples,
each sample is injected six times and the results of
the first three injections are discarded. Three standards
that isotopically bracket the sample values are run alternately with the samples. The standards were obtained
from LGR, Inc and the Laboratory of Isotope Geochemistry at the University of Arizona, where they
were calibrated with Standard Light Antarctic Precipitation (SLAP) and Vienna Standard Mean Ocean Water
(VSMOW). Results are calculated based on a rolling
calibration so that each sample is determined by the
three standards run closest in time to that of the sample.
Performance of the OA-ICOS equipment
We assessed the performance of the DLT-100 in two
ways. First, to evaluate accuracy, a subset (44 samples)
of all samples collected in connection with the field
campaigns of both Lyon et al. (2008) and Desilets et al.
(2008) were analysed for υD and υ18 O on both the DLT100 in our laboratory and by mass spectrometer at the
Laboratory of Isotope Geochemistry at the University of
Arizona [reported precision of 0Ð9 and 0Ð08‰(1 ) for
υD and υ18 O, respectively]. These samples were selected
to provide a wider range of isotope values than that
provided by the previously discussed event by Lyon et al.
(2008). The correlation coefficients between these two
methods for both isotopes are 0Ð995 and 0Ð977 for υD and
υ18 O, respectively. The 1 standard deviation of the
residuals between the determined values from the DLT100 and the mass spectrometer is 1Ð3 and 0Ð54‰for υD
and υ18 O, respectively. These values reflect the combined
precision from the two methods. Secondly, the precision
for the DLT-100 is determined by daily measurements
of a standard that is analysed as an unknown, i.e. the
calibration curve does not consider this point. The 1 standard deviation of determined values after running this
standard for more than 6 months is 0Ð37 and 0Ð12‰for
υD and υ18 O, respectively. This precision is 83% lower
in υD and 40% higher in υ18 O than that for the mass
spectrometer.
Hydrograph Separations
There are 10 stream samples, 4 Mt. Lemmon incremental
precipitation samples, and 1 Mt. Bigelow bulk precipitation sample corresponding to the event considered in
the study by Lyon et al. (2008). We can use the υD and
υ18 O measures to investigate possible representations of
event water for hydrograph separations other than those
reported by Lyon et al. (2008).
Copyright  2009 John Wiley & Sons, Ltd.
We can perform a traditional two-component hydrograph separation (e.g. Sklash et al., 1976; Sklash and
Farvolden, 1979; Buttle and McDonnell, 2004) using
a temporally variable representation of rainfall (event
water) based on the υD values of the Mt. Lemmon incremental precipitation samples (Table I, scenario 4). This
allows us to look at the influence of isotope selection
on hydrograph separation. To consider the influence of
spatial and temporal variability in the isotopic composition of rainfall, the two sampling locations need to
be made equivalent by creating a bulked representation
of the temporally variable rainfall υ18 O and υD values
measured at Mt. Lemmon (Table II). We use a rainfall
depth-weighted average of the individual sample isotopic
values to generate a representative bulk value for both
υ18 O and υD. Using these bulk representations of υD
and υ18 O at Mt. Lemmon and υD and υ18 O values of
the actual bulk sample collected at Mt. Bigelow, we can
perform four different two-component hydrograph separations treating each isotope and sampling location as
a spatially homogeneous, temporally constant representation of the event water component (Table I, scenarios
5–8).
Another possible representation of event water isotopic values can be achieved by creating an area-weighted
average of the bulk isotopic values from each sampling
location. This area weighting is based on the geomorphologic structure of the catchment’s stream network.
That is, rain falling in the vicinity of Mt. Bigelow is
likely to influence the stream network draining approximately 25% of the catchment while rain falling near
Mt. Lemmon is likely to influence about 75% of the
catchment area. We can perform a two-component hydrograph separation using a weighted mixture of the bulk
values for each sampling locations where the values
observed at Mt. Lemmon are weighted 75% and the
values at Mt. Bigelow are weighted 25% (Table I, scenarios 9–10). A final hydrograph separation considered
in this study is a three-component hydrograph separation (e.g. Ogunkoya and Jenkins, 1993). For a threecomponent separation, we treat the bulk rainfall at Mt.
Lemmon as the first component, the bulk rainfall at
Mt. Bigelow as the second component, and the preevent stream water as the third component (Table I,
scenario 11). Three-component hydrograph separation
requires the use of two chemical tracers and, thus, uses
the bulk values of both υD and υ18 O at both sampling
locations.
Table II. Temporal bulked υD and υ18 O values for both rainfall monitoring locations (Mt. Lemmon and Mt. Bigelow) and
pre-event stream-flow samples
Mt. Lemmon rainfall
Mt. Bigelow rainfall
Stream pre-event
2098
υD
υ18 O
46
54
59
8Ð0
8Ð8
8Ð9
Hydrol. Process. 23, 2095–2101 (2009)
DOI: 10.1002/hyp
SCIENTIFIC BRIEFING
Discussion
Variations in hydrograph separations using dD
versus d18 O
For the event considered in this study, the choice of
using either υD or υ18 O to represent the rainfall isotopic
signal (event water) directly influences the hydrograph
separation (Table I). This is largely due to the independent variations in sampled precipitation values of υD and
υ18 O in space. Wright (2001) observed 5 years of isotopic precipitation patterns in the Catalina Mountains near
the study site and calculated summer and winter MWLs.
The summer MWL has a shallow slope (6Ð8) compared
with the global MWL, due to the typically warm and dry
condensation conditions for monsoon storms in the southwestern United States. The series of storms from which
the event presented in this study arises produced precipitation that was isotopically varied (Figure 1). This reflects
the influence of multiple moisture sources responsible for
generating the rainfall in this region.
In spite of this variability, all of the precipitation in
these sequential days of rainfall plot left (above) the summer MWL of Wright (2001) (analysis not shown). This
indicates that below-cloud evaporation does not influence
this particular event. Rather, these values may reflect the
cooler condensation conditions of the night-time precipitation and the influence of tropical moisture from the Gulf
of California, which is likely during monsoon season in
the southwestern United States. This influence may by
dampened in other regions such as more humid settings
where precipitation is derived from more uniform sources
and distributed via frontal systems. Unlike the precipitation, the isotopic composition of stream-flow samples
collected prior to this rainfall event fall along the summer MWL of Wright (2001). The differences observed in
υD and υ18 O in sampled precipitation are thus not likely
attributed to enrichment of samples after collection as
samples were stored in oil-covered bottles and removed
from the field site within a few hours of collection.
Depending on choice of stable water isotope in combination with different hydrograph separation methods,
there are many possible event/pre-event water compositions estimated for this runoff event. Hydrograph separations based on the rainfall samples collected only at
the Mt. Lemmon sampling location estimate that the
majority of water in the runoff hydrograph is pre-event
water (Table III). When using the samples from only the
Mt. Bigelow sampling location, however, the majority of
water in the hydrograph is estimated to be event water.
The spatial variability of the isotopic composition in rainwater precludes accurate hydrograph separation based on
precipitation samples collected at one point in the catchment during this rainfall event. This is similar to findings
of previous studies, which highlight the need for capturing the spatial variability rainfall isotopic signature (e.g.
Brown et al., 1999; Shanley et al., 2002). Temporal variability in isotope values within the event considered has
a smaller influence on the hydrograph separation than the
spatial variability for the event considered (Table III).
Copyright  2009 John Wiley & Sons, Ltd.
Comparing the bulked representation to the temporally
variable representation of event water isotopic composition, the hydrograph separations are fairly similar. This
comparison is available only for the precipitation observations at Mt. Lemmon. This small influence of temporal
variations of hydrograph separation differs slightly from
the influence reported by McDonnell et al. (1990) and
may be due to the extreme nature of this event (total
duration of rainfall was only 180 min).
The influence of isotope selection (υD vs υ18 O) on
hydrograph separation is especially pronounced looking
at the range of separations based on the bulk Mt. Bigelow
samples. If we assume this one sample collected in space
and time is representative of all rainfall in the catchment
during the event, there is a difference of 33% in the
event water estimate when comparing the separation
made using υD and υ18 O. This is due for the most
part to the similarity in the υ18 O composition for the
bulk rainfall sample collected at Mt. Bigelow to that of
the pre-event water sample (Figure 1). In this case, the
use of both stable water isotopes to separate the event
hydrograph helps identify the ‘unrealistic’ conclusion
reached solely using the υ18 O composition for the bulk
rainfall sample at Mt. Bigelow. With information on both
stable water isotopes and some basic investigation of
catchment characteristics (e.g. soil or land cover), one
could disqualify such an extreme hydrograph separation
(99% event water) based on a single point observation of
precipitation composition. However, it would be difficult
to reach this opinion without considering separation
based on both stable water isotopes and some spatially
distributed samples of rainfall isotopic composition.
There is obviously a need to capture the spatial variability of precipitation isotopic composition using distributed sampling locations of rainfall to obtain accurate
hydrograph separation. This has been pointed out by previous catchment scale research (e.g. Dansgaard, 1964;
Ingraham, 1998; McGuire et al., 2005). In addition, the
temporal variability of rainfall isotopic composition may
have a significant impact on the resultant hydrograph
separation (McDonnell et al., 1990). This note highlights that, under conditions where there is significant
isotopic deviation about the MWL in precipitation or terrestrial water samples, such as those present in monsoonal
Table III. Summary statistics of the hydrograph separations given
in Table I
Grouping
All
Mt. Lemmon
Mt. Bigelow
Temporal
bulk
Temporal
variable
υ18 O
υD
2099
Scenarios
Average
% event
water
Average
% pre-event
water
Standard
deviation
%
1–11
1–6
7–8
5–6
41
26
83
24
59
74
17
76
24
5
23
2
3–4
31
69
7
1–3, 5, 7, 9
4, 6, 8, 10
42
36
58
64
29
20
Hydrol. Process. 23, 2095–2101 (2009)
DOI: 10.1002/hyp
S. W. LYON, S. L. E. DESILETS AND P. A. TROCH
southwestern United States, there is also a need to
confirm that independent differences in υD and υ18 O
are not influencing the hydrograph separation or other
tracer studies.
Recommendations on increased representation of spatial and temporal isotopic variability in rainfall are not
necessarily new; however, they are now becoming more
achievable with the introduction of new technology such
as equipment using OA-ICOS techniques. Such equipment brings down analysis cost per sample. In addition,
these new OA-ICOS techniques allow for the simultaneous measurement of both υD and υ18 O for a given
water sample. As demonstrated in this study, having
information on both stable water isotopes may not prove
redundant under certain conditions.
We are compelled to finish this note by providing some
estimates of costs associated with using this new technology to measure both stable-water isotopes compared with
traditional methods. Of course, the costs we report here
are specific to our experience and setup, but they should
provide some general guidelines for researchers considering the purchase of new equipment using OA-ICOS
technology for use in catchment hydrology studies. At
the time the samples reported in this study were analysed, the price to obtain both υD and υ18 O from a single
water sample was 36 U.S. dollars (USD) using IRMS.
For our lab to maintain OA-ICOS technology to analyse
stable water isotopes in-house, we estimate an analysis
cost covering all general overheads associated with the
machine of 8 USD per sample to obtain both υD and
υ18 O. This price does not include the cost of hiring a
new operator for processing samples and running the
equipment. The cost of hiring an operator brings our inhouse estimate to about 13 USD per sample. This gives
an estimated, in-house cost of using OA-ICOS, which is
about 36% of the cost to analyse samples using IRMS.
While these numbers are specific to our experience running a DLT-100 from Los Gatos Research, Inc., we would
like make clear that other equipment is available to measure stable water isotope composition of natural waters
[e.g. the Wavelength-Scanned Cavity Ring Down Spectroscopy (WS-CRDS) Analyzer for Isotopic Water Liquid
from Picarro, Inc.].
Acknowledgements
The authors would like to thank two anonymous reviewers for thoughtful and thorough reviews which allowed
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