in situ monitoring of h and o stable isotopes in soil water reveals … · 2017-02-03 · for peer...

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In situ monitoring of H and O stable isotopes in soil water reveals ecohydrologic dynamics in managed soil systems

Journal: Ecohydrology

Manuscript ID ECO-16-0212.R1

Wiley - Manuscript type: Research Article

Date Submitted by the Author: 29-Jan-2017

Complete List of Authors: Oerter, Erik; Lawrence Livermore National Laboratory, Bowen, Gabriel; University of Utah, Geology and Geophysics

Keywords: isotope hydrology, membrane inlet, laser spectroscopy, ecohydrologic separation, soil water partitioning, irrigation, Technosol

John Wiley & Sons, Ltd

http://mc.manuscriptcentral.com/ecohydrology

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In situ monitoring of H and O stable isotopes in soil water reveals ecohydrologic dynamics in 1 managed soil systems 2

3 4

Erik J. Oerter1,2,3*, Gabriel Bowen1,2 5 6

1 Department of Geology and Geophysics, University of Utah, 115 South 1460 East, Salt Lake 7 City, UT 84112, USA. 8 2 Global Change and Sustainability Center, University of Utah, 257 South 1400 East, Salt Lake 9 City, UT 84112, USA. 10 3 Current address: Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 11 94550, USA. 12 13 14 * Corresponding Author email: [email protected] 15 16 17 Highlights 18 19 We develop a lightweight field deployable IRIS system for measuring in situ soil water δ2H and 20 δ18O values. 21 22 Seasonal soil water δ2H and δ18O values respond to precipitation and irrigation inputs. 23 24 Ecohydrologic separation between irrigation and precipitation, and soil and plant stem water can 25 occur in irrigated ecosystems. 26 27 It may be possible to couple water vapor probe measurements to that of extracted water to 28 characterize the isotopic composition of the various pools of water in soil. 29 30 31 Keywords 32 33 Isotope hydrology, membrane inlet, laser spectroscopy, irrigation, ecohydrologic separation, 34 Technosol, soil water partitioning 35 36 37 Abstract 38

39 The water cycle in urban and hydrologically-managed settings is subject to perturbations 40

that are dynamic on small spatial and temporal scales, the effects of which may be especially 41 profound in soils. We deploy a membrane inlet-based laser spectroscopy system in conjunction 42 with soil moisture sensors to monitor soil water dynamics and H and O stable isotope ratios (δ2H 43 and δ18O values) in a seasonally irrigated urban landscaped garden soil over the course of 9 44 months between the cessation of irrigation in the autumn and the onset of irrigation through the 45 summer. We find that soil water δ2H and δ18O values predominately reflect seasonal 46 precipitation and irrigation inputs. A comparison of total soil water by cryogenic extraction and 47

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mobile soil water measured by in situ water vapor probes, reveals that initial infiltration events 48 after long periods of soil drying (the autumn season in this case) emplace water into the soil 49 matrix that is not easily replaced by, or mixed with, successive pulses of infiltrating soil water. 50 Tree stem xylem water H and O stable isotope composition did not match that of available water 51 sources. These findings suggest that partitioning of soil water into mobile and immobile “pools” 52 and resulting ecohydrologic separation may occur in engineered and hydrologically-managed 53 soils and not be limited to natural settings. The laser spectroscopy method detailed here has 54 potential to yield insights in a variety of Critical Zone and vadose zone studies, potential that is 55 heightened by the simplicity and portability of the system. 56

57 58

1. Introduction 59 60 The use of natural variations in the stable isotopes of hydrogen and oxygen (2H and 18O) 61 in the water molecule as a tracer of water movement has been employed in a variety of natural 62 settings from watersheds to ecosystems (e.g. Kendall and McDonnell, 1998). Their use in soil 63 hydrology includes providing information on unsaturated zone infiltration and mixing (e.g. Gazis 64 and Feng, 2004; Mueller et al., 2014), quantifying the influence of evaporation on H and O stable 65 isotope profiles with soil depth (Barnes and Allison 1983; 1988), evapotranspiration partitioning 66 (e.g. Hsieh et al., 1998; Sutanto et al., 2014), estimating transit times for vadose waters (e.g. 67 Asano et al., 2002; Sprenger et al., 2016a), and spatio-temporal patterns of plant water use (e.g. 68 Dawson and Ehleringer, 1991; Evaristo et al., 2016). 69 In contrast to measurements of other soil hydrologic variables such as soil water content 70 that can be made repeatedly in situ via a sensor, H and O stable isotope values (δ2H and δ18O) 71 have until recently required removal of soil samples with intact soil water for laboratory analysis. 72 These approaches are inherently destructive to the soil system’s in-place integrity, preclude 73 repeated analysis through time in the same place, and are often prohibitively disruptive in urban 74 settings. Traditionally, removal of water from soil samples under vacuum distillation and 75 subsequent analysis of the liquid water has been the trusted method despite evidence that it is not 76 reproducible and is error-prone (Araguas-Araguas et al., 1995; Orlowski et al., 2015). The advent 77 of laser-based Isotope Ratio Infrared Spectroscopy (IRIS) allowed for the simultaneous analysis 78 of 2H and 18O in water vapor in equilibrium with soil water, though with destructive sampling 79 (Wassenaar et al., 2008). The coupling of IRIS with vapor-permeable membranes has enabled ex 80 situ measurements of δ2H and δ18O values in destructively sampled aliquots (Oerter et al., 2017), 81 as well as the in situ sampling and analysis of 2H and 18O in soil water vapor in field studies 82 (Volkmann and Weiler, 2014; Gaj et al., 2016). 83

Urban and managed land uses introduce perturbations to natural water cycling that are 84 spatially and temporally heterogeneous on scales from landscape to garden plot, and seasonal to 85 sub-daily (Fletcher et al., 2013). The introduction of water into soils via irrigation is a 86 predominant hydrological forcing in managed systems, and irrigation is often cyclical and of 87 durations and frequencies unlike those found naturally. After irrigation, the cycling of water back 88 to the atmosphere through evaporation and transpiration are altered by distinctive land uses and 89 land cover materials (Schirmer et al., 2013). Understanding the fluxes of water through 90 heterogeneous urban and managed soils and land cover schemes remains a challenge, but is of 91 increasing societal importance as water resources are under increasing and unpredictable 92 dynamic pressures from population increases and climate change (Niemczynowicz, 1999; 93 Ehleringer et al., 2016). Despite the prevalence of isotope-enabled hydrologic studies in a variety 94

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of natural settings, the use of H and O stable isotopes in water in hydrologically-managed 95 systems has been largely focused on studying water supply and transfers in cities (e.g. Good et 96 al., 2014; Jameel et al., 2016; Ehleringer et al., 2016). 97 In this study, we explore the use of an in situ membrane inlet IRIS system to measure δ2H 98 and δ18O values of soil water in a seasonally irrigated urban landscaped garden setting in 99 northern Utah (United States). We implement calibration approaches that explicitly include 100 temperature and water content, and implicitly include particle size effects. We demonstrate the 101 utility of this approach to measure soil depth profiles of δ2H and δ18O values of soil water at this 102 site over the course of nine months, spanning the end of irrigation in the fall, natural precipitation 103 inputs through the winter, and the onset of irrigation in the spring and early summer. We discuss 104 the insights that in situ measurements of soil water H and O stable isotope signatures can bring to 105 the unresolved notion of ecohydrologic partitioning of soil water into distinct mobile and 106 immobile components. 107 108 109 2. Study Location and Methods 110 111 2.1 Study location and field methods 112

The soil study site (“FASB”) is located on the University of Utah campus (40° 45' 59.92" 113 N, 111° 50' 53.89" W, 1436 m.a.s.l.) in a seasonally drip-irrigated ornamental garden. Mean 114 annual air temperature (MAAT) at the site is 11.6° C, and mean annual precipitation (MAP) is 115 393 mm (PRISM Climate Group, 2016). The soil was excavated to >50 cm depth and the soil 116 profile was described and logged following common pedological procedures (Soil Survey Staff, 117 1999; Schoeneberger et al., 2012). Bulk soil samples from 10 cm depth increments were taken 118 for particle size analysis and to provide material for calibration standards (discussed below). An 119 intact soil bulk density sample was taken by pounding a steel sleeve into undisturbed soil, 120 recovering the enclosed soil volume, and weighing it before and after oven drying at 105 C for 121 12 hr. 122

The soil can be classified as a Technosol (WRB, 2014) and does not display distinctive 123 signs of pedogenic development (such as illuvial horizonation) from long-term soil forming 124 processes, but instead possesses characteristics that reflect its history as “made land”. These 125 include a relatively homogeneous sandy-loam texture throughout the soil profile (56% sand, 35% 126 silt, 9% clay; determined by the hydrometer method (Gee and Bauder, 1986)), irregular rock 127 fragment content with depth, and no pedogenic soil structure. The soil surface was covered with 128 ~5 cm depth chipped-bark mulch with particle size of 2-10 cm. 129 Soil water vapor probes (described below) were installed in the walls of the soil 130 excavation carefully to avoid disruption of the intact soil texture. The installation technique 131 includes: 1) insertion of a thin-gauge sheet steel tool (knife or trowel) into the soil excavation 132 wall at the upper boundary of the intended installation depth, 2) careful excavation of a cavity 133 approximately 1 cm high by 5 cm wide by 10 cm deep into the soil excavation wall to 134 accommodate the probe immediately beneath the steel tool, 3) emplacement of the probe in the 135 cavity, and 4) careful withdrawal of the steel tool allowing overlying soil material to gently 136 envelope the probe. Soil water vapor probes were installed at the soil-mulch interface (0 cm 137 depth), at 5cm depth intervals in the upper 30cm of the soil, and every 10cm from 30 to 50cm 138 soil depth. Soil vapor probes were installed in a laterally staggered arrangement so that overlying 139 probes did not influence the vertical flow of soil water to underlying probes. The soil excavation 140

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cut face was roughened and the soil back fill material was carefully emplaced to both emulate 141 native soil texture and minimize the any preferential flow paths for surface water to infiltrate 142 along the excavation-backfill interface. 143

Dielectric permittivity soil water and temperature sensors (EC-TM; Decagon, USA) were 144 installed at 10, 20 and 50 cm depths near the soil water vapor probes. An air temperature and 145 humidity sensor (VP-3; Decagon, USA) was placed approximately 50 cm above the soil surface 146 nearby the soil excavation. Soil water vapor probe gas supply lines and sensor wires were routed 147 into a lidded plastic vault, which also housed a data logger (EM-50; Decagon, USA) recording 148 measurements from each sensor at 1 hr intervals. Precipitation amounts were measured by 149 tipping bucket rain gauge at a meteorological station 1.6 km from the FASB site 150 (http://data.iutahepscor.org/mdf/river_info/iUTAH_RedButte_OD/RB_GIRF_C/). Precipitation 151 samples were collected on a building rooftop ~200 m from the study site in an ongoing 152 monitoring effort, and precipitation δ2H and δ18O values used in this study were previously 153 reported in Jameel et al. (2016), with additional data reported in Supplementary Table 2. 154 On two occasions coinciding with soil water vapor sampling, soil material for vacuum 155 water extraction from 10, 25, and 50 cm depths was excavated by soil auger from within 2 m 156 lateral distance of the soil vapor probes. Triplicate soil samples from this material were collected 157 into 20 mL glass vials with polyseal caps, wrapped in parafilm, and stored under refrigeration 158 until vacuum extraction and IRIS analysis (detailed below). Irrigation water samples were 159 collected in October 2015, May 2016, and August 2016 into 20 mL glass vials with polyseal 160 caps, wrapped in parafilm, and stored under refrigeration until IRIS analysis. 161 Samples of stem material from a Prunus cerasifera tree approximately 5 m from the soil 162 site were collected at each sampling event starting in February 2016. Healthy, suberized stems of 163 10 to 15 mm diameter were collected in duplicate or triplicate (from different locations on the 164 tree), peeled of bark with a razor knife, stored in 20 mL glass vials with polyseal caps, wrapped 165 in parafilm, and stored under refrigeration until vacuum extraction and IRIS analysis. 166 167 2.2 Water vapor probe system 168 The water vapor probe analytical system is similar to that used by Oerter et al. (2017) to 169 measure δ2H and δ18O values of soil water in ex situ soil samples, and has been implemented in a 170 utility cart such that the system can be mobilized for portable operation in the field. Dry N2 gas is 171 supplied from a compressed gas tank regulated to 7 kPa and is carried through the system by 172 Excelon Bev-A-Line IV tubing composed of polyethylene liner with ethyl vinyl acetate shell 173 (6.35 mm outside diameter, 1.6 mm wall thickness; Thermoplastic Processes Corp., USA). The 174 N2 gas supply is split into primary and diluter flows after exiting the tank regulator. The primary 175 N2 stream is controlled to 60 standard cubic centimeters per minute (SCCM) flow rate and held 176 constant by a mass flow controller (MFC 1 in Fig. 1B; Sierra Instruments, USA). This primary 177 N2 flow is directed to each soil water vapor probe (Fig 1A), which is constructed of a 12 cm 178 length of gas permeable Accurrel PP V8/2HF polypropylene tubing (8.65 mm outside diameter, 179 1.55 mm wall thickness, 0.2 µm nominal porosity; Membrana GmbH, Germany) attached to 180 impermeable Bev-A-Line tubing that supplies dry N2 to one end of the water vapor probe. 181 Another length of Bev-A-Line tubing carries N2 and water vapor from the exhaust end of the 182 vapor probe and is joined by the diluter flow of N2 (regulated by an adjustable mass flow 183 controller, MFC 2 in Fig. 1B) before entering the CRDS instrument. The tubing lines connecting 184 the system to each water vapor probe are heated by electrical resistance cable to prevent 185 condensation, wrapped with polyethylene foam insulation, and temperature controlled to 40 C ± 186

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1 C. The sampling lines are 2 m in length, thus allowing flexible connection to the vapor probe 187 lines emerging from the ground surface at the field site, while minimizing sample gas travel 188 distance and time. Excess water vapor and carrier N2 is vented to the atmosphere after the CRDS 189 pump system inducts a portion of the sample stream into the CRDS instrument (Fig. 1B). The 190 system is self-contained in a small all terrain utility cart (~60 kg total system weight) that is field 191 deployable by one person. At the FASB site, 120 volt line power was used for power supply, but 192 the system is also capable of being powered by a small (~1 kW, ~13 kg) gasoline powered 193 generator. 194

195 196 2.3 Field analytical methods 197

Before the first measurement of each soil water vapor probe during a measurement 198 session, dry N2 is used to pre-flush each probe for 2 minutes in order to remove any water films 199 accumulated inside the probe and lines since the previous measurement session. After pre-200 flushing, the CRDS analyzer is operated in continuous flow mode, and the measurement 201 sequence initiates with establishing a dry flow of N2 through the system by directly connecting 202 the supply N2 line to the CRDS inlet line, which creates water vapor mixing ratios ([H2O]) at the 203 CRDS of <1000 ppmV. The sampling lines are then connected to a water vapor probe installed 204 in the soil. When the supply of dry N2 passes through the gas permeable section of the water 205 vapor probe, water vapor that has crossed the tubing wall membrane due to the humidity gradient 206 between the wet soil and the dry N2 inside the probe is carried by the N2 stream through the 207 return tubing and into the CRDS system. The dilution N2 stream is controlled by MFC 2 and is 208 adjusted manually during each measurement session to achieve a measured water vapor mixing 209 ratio in the CRDS instrument of approximately 20,000 ppmV H2O. 210

A measurement duration of ~5 min is typically sufficient to achieve >2 min of stable 211 [H2O] and δ2H and δ18O measurements. The sampling lines are then disconnected from the soil 212 water vapor probe lines and shunted together to flush the remaining soil water vapor through the 213 system and reestablish low water vapor mixing ratios ([H2O]) at the CRDS of <1000 ppmV, 214 which takes ~2 min, thus allowing a measurement total cycle time of ~7 min. Values of δ2Hvap 215 and δ18Ovap were calculated by averaging 90 seconds of measurements collected at 1 Hz 216 frequency. Even though manufacturer data indicate that instrumental drift in the CRDS 217 instrument used here (L-2130i) has been nearly eliminated over the course of a ~6 hr analysis 218 session (Picarro Inc., 2016), instrument stability was monitored by repeated analysis of the same 219 samples at the beginning and end of the session, with no drift recorded. Rothfuss et al. (2013) 220 demonstrated that the Accurrel PP V8/2HF polypropylene tubing used for the water vapor probes 221 does not exert fractionation on either δ2Hvap or δ18Ovap isotope values of water. 222 223 2.4 Laboratory analytical methods 224 Soil and xylem water was extracted by distillation, and cryogenic collection in a pyrex 225 glass U-trap with boiling water for heat on the distillation side of the trap and liquid N2 cooling 226 on the collection side under vacuum (< 60 millitorr) until no additional water was recoverable 227 (verified by no further condensation inside the distillation apparatus; extraction time > 90 min.). 228 Extracted water samples were measured for δ2H and δ18O values using a Picarro L-2130i cavity 229 ring down water isotope analyzer following protocols described in Good et al., (2014), and the 230 data were screened with ChemCorrect software (Picarro, Inc.; Santa Clara, CA, USA) to identify 231 potential artefacts associated with spectroscopic interferences. Based on results from standard 232

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waters analyzed concurrently, analytical precision for these liquid water analyses is ±0.3‰ for 233 δ2H and ±0.03‰ for δ18O (± 1 S.D.). 234

Isotope values are reported in δ notation: δ = (Rsample / Rstandard – 1), where Rsample and 235 Rstandard are the 2H/1H or 18O/16O ratios for the sample and standard, respectively, and values are 236 reported in per mille (‰) by multiplying by 1000. Liquid and vapor H2O δ2H and δ18O values 237 are referenced to the Vienna Standard Mean Ocean Water (VSMOW) standard (Coplen, 1994). 238 We use Dansgaard’s (1964) “deuterium excess” parameter δ2H – 8 × δ18O to evaluate the degree 239 to which a sample has undergone evaporation, with lower deuterium excess values calculated 240 from liquid water δ values compared to the source water indicating more evaporation. 241 Soil water content sensors installed at the FASB site were calibrated in the laboratory by 242 utilizing soil material dried at 105 C overnight. A known quantity of water was added to the 243 dried soil, mixed well, soil water sensors were inserted into the wet soil, and 10 sensor readings 244 were collected from each probe. This procedure was repeated at water contents from 5 to 15.3% 245 water content (g g-1). The resulting linear calibration is: volumetric water content = (sensor 246 counts – 451.09)/1380.2. Calibrated volumetric water content (VWC) measurements from the 247 sensors were converted to gravimetric water content (g g-1) by dividing VWC by the bulk density 248 (1.68 g cm-3). Gravimetric water content (GWC) is reported throughout because the calibration 249 for the water vapor probe method uses standards created on the basis of GWC (see below). 250

The presence of CO2 in the analytical system carrier gas has been found to exert 251 confounding effects on measured δ2H and δ18O values of water vapor in CRDS instruments 252 (Gralher et al., 2016). In order to evaluate CO2 levels during sample and standard analyses, we 253 used the spectral line width variable “h2o_vy”, the value of which is related to carrier gas 254 composition, and which is available in the CRDS analyzer system diagnostic files (Gralher et al., 255 2016). We used h2o_vy values measured on silica sand-water samples prepared in the same way 256 as the calibration standards (that should have no CO2 beyond that which is incorporated into the 257 standard from atmosphere air, ~400 ppmV) for comparison to h2o_vy values measured on soil 258 samples and calibration standards. 259 260 2.5 Calibration of measured δ2H and δ18O values 261

Sub-equal amounts of each soil sample from all depth intervals were combined to create 262 aggregated “depth-composite” calibration standards for the water vapor probe and direct vapor 263 equilibration methods by adding water with known δ2H and δ18O values (AB-type: δ2H = -264 64.7‰ and δ18O = -9.62‰ (VSMOW); UT-type: δ2H = -122.8‰ and δ18O = -16.46‰ 265 (VSMOW), ±0.3‰ for δ2H and ±0.03‰ for δ18O (± 1 S.D.); to oven dried (105 C for > 12 hr) 266 soil material at 5%, 12%, 26% GWC (g water g-1 soil), n=6 calibration standards (3 GWC 267 contents × 2 water types). Water was distributed within each calibration standard evenly, the 268 water-soil mixtures were homogenized by physical mixing, and the saturation state inside each 269 standard bag or container was allowed to equilibrate overnight, thus ensuring even distribution of 270 water throughout the soil in the standard. Mixtures of pure silica sand (0.425 to 0.85 mm grain 271 size) and AB- and UT-type waters were prepared at 4%, 8%, 12% GWC, n=6 standards, in the 272 same way as mixtures made with FASB soil. The calibration standards were made in 473 mL 273 polyethylene containers with water vapor probes installed into the screw-top lids along with soil 274 temperature sensors. 275 Analyses of the calibration standards made from FASB soil with the water vapor probe 276 method at soil temperatures 0 to 35° C, and linear correlation modeling of the analytical results 277 with “nlme” package (Pinheiro et al., 2016) in R (R Core Team, 2016) yielded the following 278

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relationships between δ2H and δ18O values of water vapor (δ2Hvap and δ18Ovap) and that of liquid 279 water (δ2Hliq and δ18Oliq), temperature (TEMP, as degrees C), and gravimetric water content 280 (GWC, as g water g-1 soil): 281 282 δ2Hliq = 120.128 − 1.255×TEMP + 0.008×TEMP2 + 1.138×δ2Hvap (1a) 283 284 δ18Oliq = 9.954 – 0.163×TEMP + 0.002×TEMP2 + 13.386×GWC + 1.051×δ18Ovap (1b) 285 286 All predictors in Eqns. 1a and 1b are significant to p < 0.001, except TEMP2 with p < 0.1 for δ2H 287 and p < 0.05 for δ18O (n=43). The inclusion of the second-order temperature term in the 288 calibration equations is justified even with reduced statistical significance because the 289 equilibrium fractionation between water and vapor has a second-order form with respect to 290 temperature. GWC is not included in the calibration for δ2H because the data indicated no 291 significant correlation between water content and δ2Hvap values in the FASB soil matrix (Fig. 2). 292 When Eqns. 1a and 1b are applied to the δvap measurements made by the water vapor 293 probe method to predict δliq values of the calibration standards, the residuals (model - actual) are 294 distributed normally (average 0‰ ±2.4‰ (1 S.D.)) for δ2Hliq, and almost normally with a very 295 small negative bias for δ18Oliq (average of -0.07‰ ±0.48‰ (1 S.D.)) (Supp. Fig. 1). We therefore 296 estimate the analytical uncertainty of measurements with the water vapor probe method to be 297 ±2.4‰ for δ2Hliq and ±0.48‰ for δ18Oliq. 298 299 300 3. Results 301 302 3.1 Effects of soil temperature, water content and soil texture on H and O vapor values 303 In order to assess the effects of soil water content and texture (clay content) on measured 304 δ2H and δ18O values of water vapor (δ2Hvap and δ18Ovap) with the soil water vapor probe method, 305 a comparison experiment between silica sand and FASB soil was made. The δ2Hvap and δ18Ovap 306 values measured at -10 to 35 C in these sand-water mixtures are shown in Figure 2. The 307 dependence of δvap values on temperature mimics, but does not fully follow relationships 308 expected from thermodynamic equilibrium (i.e. Majoube, 1971; Merlivat and Nief, 1967). δ2Hvap 309 values are offset towards higher values in both silica sand and FASB soil material by ~10 to 310 20‰ at the lowest temperatures, an effect that diminishes to almost 0‰ as temperature increases 311 to 35 C (Fig. 2). A similar offset from equilibrium towards higher values exists for δ18Ovap 312 values, but is ~1‰, much less than that of δ2Hvap, and is nearly constant with increasing 313 temperature. 314

When comparing measured δvap values from the silica sand and FASB standards across 315 the water freezing threshold of 0 C, effects related to the soil matrix become apparent (Fig. 2). In 316 the case of silica sand, equilibrium ice-vapor fractionation appears to be controlling the measured 317 δvap values at soil-water temperatures below freezing. At the solid-liquid transition at 0 C, the 318 predicted change to liquid-vapor equilibrium fractionation results in a discontinuity in measured 319 δvap values, and liquid-vapor equilibrium fractionation appears to control the values up to 35C 320 (Fig. 2). In contrast, soil-water mixtures made with FASB soil material do not exhibit the 321 predicted discontinuity in equilibrium fractionation at 0 C, and instead display measured δvap 322 values that are similar to that predicted by liquid-vapor equilibrium regardless of temperature 323

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(Fig. 2). For both silica sand and FASB soil standards there is more variability in δvap values at 324 temperatures below 0 C than there is above 0 C (Fig. 2). 325 326 327 3.2 Soil water contents through time 328 Soil volumetric water content (VWC) was generally highest in the upper 20cm of the soil 329 profile throughout the study period, with values of ~15% in between precipitation and irrigation 330 events that raised VWC to as high as ~20% (Fig. 3). VWC at 50 cm depth was always less than 331 the upper soil with values of 12% between wetting events that resulted in VWC maxima of 332 ~15% at 50 cm. Seasonally, the period of lowest VWC during the study period occurred after the 333 last irrigation event of the fall season on 26 Oct 2015, and small precipitation events during this 334 time infiltrated only the upper 20cm of the soil (Fig. 3). The first significant precipitation event 335 of the winter season occurred on 20 Dec 2015 as snow and infiltrated throughout the soil profile 336 to reset VWC to wetter conditions. These higher VWC values continued for the remainder of the 337 study period (Fig. 3). Spring season rains in mid-April 2016 marked a return to wetter conditions 338 in the upper 10 cm of the soil, compared to the winter when VWC values throughout the upper 339 20cm of the soil were similar. The onset of irrigation in late May 2016 imparted a distinct cyclic 340 signal to VWC, with high VWC values in the upper 20 cm, and a muted VWC response at 50 cm 341 soil depth (Fig. 3). 342 343 344 3.3 Soil and xylem water δ2H and δ18O values 345 When calibration Eqns. 1a and 1b are applied to δvap measurements made from water 346 vapor probes installed at the study site using water content and soil temperatures interpolated 347 from the sensors at depths nearest to each water vapor probe, the depth profiles of δ2Hliq and 348 δ18Oliq values shown in Fig. 3 and Supplementary Table 1 are calculated. 349 Evaluation of the spectral line width variable “h2o_vy” as an indicator of the presence of 350 elevated levels of CO2 in the analytical system carrier gas was used to evaluate whether a 351 correction to δ2Hliq and δ18Oliq values was necessary. In mixtures of N2-CO2 the presence of CO2 352 does not begin to exert effects on δ2H and δ18O values that are larger than the precision of the 353 vapor probe measurement method (ca. ±2.4 ‰ for δ2Hliq and ±0.5 ‰ for δ18Oliq) until CO2 354 mixing ratios ≥ 0.5% (5,000 ppmV), and then only in high-clay and organic-rich soils (Gralher et 355 al., 2016). Values of h2o_vy ~0.45 are normal for standards made with silica sand and water 356 (which should have no CO2 content beyond ~400 ppmV contributed by the atmosphere) at a 357 variety of water content levels analyzed with the same instrument and analytical system as used 358 in this study. In comparison, no soil sample or calibration standard made with field soil displayed 359 h2o_vy values greater than ~0.5. Therefore, based on the similarity of h2o_vy values from silica 360 sand-water standards and that measured on soil samples and calibration standards made with 361 FASB soil, and very little variability in h2o_vy values with soil depth or through time, no CO2 362 correction was applied to δ2Hliq and δ18Oliq values. 363 The δ2Hliq and δ18Oliq values in soil water at the study site, in precipitation collected 364 nearby on the University of Utah campus (Jameel et al., 2016), and in three samples of irrigation 365 water at the site are shown in Fig. 4 and in Supplementary Tables 1 and 2. Water infiltrating into 366 the soil at the study site is sourced from either precipitation or irrigation, both of which plot 367 along the local meteoric water line with a slope of 7.45 (LMWL: δ2H = 7.45 × δ18O - 1.66). 368

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Figure 4 also shows the δ2Hliq and δ18Oliq values of stem xylem water from a Prunus 369 cerasifera tree approximately 5 m from the soil study site, all of which lie below and/or to the 370 right of the LMWL. Stem xylem water prior to leaf formation has the highest δ values of stem 371 water in the study period (“winter xylem” in Fig. 4) and may be a result of stagnant xylem water 372 that has undergone some evaporation through the winter. Leaves on the tree were beginning to 373 form in April and had fully formed by late May, and xylem water after leaf formation (“growing 374 xylem” in Fig. 4) has lower δ values than the winter xylem. We interpret this shift to lower δ 375 values during the growing season to reflect the flushing of preexisting winter xylem water that 376 had undergone fractionation while stagnant in the xylem (Phillips and Ehleringer, 1995; 377 Ellsworth and Sternberg, 2015). 378

379 3.4 Comparison of in situ soil water vapor δ2H and δ18O value with vacuum extracted soil waters 380 In Fig. 5, soil water δ2Hliq and δ18Oliq values from water vapor probe measurements in 381 February and April 2016 are compared to δ2Hliq and δ18Oliq values of vacuum-extracted water 382 from soil samples taken from within ~2 m distance of the vapor probes on the same dates. For 383 the 28 Feb 2016 samples, the difference (Root Mean Squared Error, RMSE) between δ2Hliq and 384 δ18Oliq values measured by water vapor probe and vacuum extraction is 5.7‰ for δ2H and 1.09‰ 385 for δ18O (Fig. 5). For the 7 Apr 2016 samples, the RMSE difference is 19.2‰ for δ2H and 1.62‰ 386 for δ18O. The reason for the higher difference at 25 cm in the April samples is not known. 387 Comparing the rest of the soil depths (excluding the large influence of the 25 cm sample, 388 especially for δ2H values), the RMSE difference is 8.3‰ for δ2H and 0.48‰ for δ18O (Fig. 5). 389 The dual isotope plot in Fig. 6 compares δ2Hliq and δ18Oliq values during the February and 390 April 2016 sampling events of vacuum-extracted soil water and that from in situ soil water vapor 391 probes from 10 cm and deeper to that of irrigation water and local precipitation (LMWL). Soil 392 water values from 10 cm and deeper where chosen for this comparison to reflect soil water that 393 has not been evaporated or has not mixed with preexisting evaporated water (see Section 4.4, 394 Fig. 7). A least squares regression through the soil water vapor probe data from 10 cm and 395 deeper yields a slope of the relationship between δ2Hliq and δ18Oliq values of 7.20 (R2 = 0.95, n = 396 17), which is very similar to the LMWL slope of 7.45 (Jameel et al., 2016), though the vapor 397 measurements are systematically offset above the LMWL in δ2H values by about 1.9 ‰ (Fig. 6). 398 In contrast, the regression slope between vacuum extracted δ2Hliq and δ18Oliq values measured on 399 soil water samples below 5 cm depth is 8.05 (R2 = 0.99, n = 18), and is offset below the LMWL 400 in δ2H values by about -3.9 ‰ (Fig. 6). 401 402 4. Discussion 403 404 4.1 Effects of temperature, water content and soil matrix on δ2Hvap and δ18Ovap values 405

The lack of the predicted discontinuity in equilibrium fractionation at 0 C, and thus 406 measured δvap values, from the FASB soil-water standards across the water freezing threshold of 407 0 C (Fig. 2) suggests that liquid water may persist in the frozen FASB soils below 0 C, and that 408 vapor measurements may reflect equilibration with this water rather than ice. The location and 409 nature of this liquid water in otherwise “frozen” soil may be controlled by osmotic effects 410 (Brooks et al., 2011) associated with dissolved solutes transferred to the introduced water by the 411 soil matrix. These δvap measurements on “frozen” soils demonstrate that the water vapor probe 412 method developed here may be useful in the investigation of soils at temperatures below 0 C that 413 pose significant challenges to sampling and monitoring, such as in permafrost and alpine 414

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climates. Analytical precision will be lower below 0 C though, as indicated by the increased 415 variability in measured δvap values on both silica sand and FASB soil standards (Fig. 2). The 416 sensitivity of the water vapor probe method to coexisting pools of water in soil (frozen and liquid 417 water in the above example) suggests that if there is further heterogeneity within the soil water 418 (e.g. frozen and liquid fractions are different in source or history) the measurement may be 419 biased toward the liquid fraction. The systematic difference in δ values measured by the vapor 420 probes and vacuum extraction (Figure 6) is further evidence that each method may be measuring 421 separate and distinct “pools” of soil water. 422 In addition to factors related to solid- and liquid-water vapor equilibrium, the probe 423 measurements may be affected by liquid-vapor equilibrium fractionation effects that are related 424 to the soil particle surface-water interface. These effects include water isotopologue organization 425 and partitioning at interfaces with organic material adsorbed to soil particle surfaces (Chen et al., 426 2016;), or around cations adsorbed to the clay particle surfaces (Oerter et al., 2014), or by the 427 soil mineral particles themselves (Gaj et al., 2017). The equilibrium fractionation factor between 428 liquid water adsorbed to particles and vapor in soils may be smaller than that of free liquid and 429 vapor, as shown by laboratory experiments with mesoporous silica-water systems (Lin and 430 Horita, 2016). All of these can lead to soil water vapor isotope values that do not reflect the bulk 431 soil water values modified by standard equilibrium fractionation. The magnitude of particle-432 water effects is predicted to be greatest in soils with low soil water contents and decrease with 433 increasing water content. Indeed, our calibration study with FASB soil shows a strong 434 relationship between non-equilibrium effects and GWC, where there are strong offsets towards 435 higher δ18Ovap values at 5% GWC, but not at 12% or 20% GWC (Fig. 2). Though these effects 436 may be present, the use of site-specific soil material to create calibration standards at a range of 437 GWC should allow correction for them during conversion of δ18Ovap measurements to calibrated 438 δ18Oliq values using Eqns. 1a and 1b. 439 Further complications may arise from considerations about the relative “availability” of 440 vapor to reach the vapor probe, which are related most immediately to vapor diffusion that is 441 controlled primarily by porosity and permeability within the soil. This case may exist in soil 442 water considered to be “immobile” (i.e. water held in micropores or adsorbed to soil particles) vs 443 “mobile” (i.e. free draining or macropore-held water), where the vapor probe method may be 444 biased towards the water that can most readily come to isotopic equilibrium with vapor 445 (presumably the “mobile” water). 446 447 4.2 Soil water δ2H and δ18O dynamics 448 Repeated in situ sampling of the soil water vapor through time at the study site reveals 449 that: 1) soil water δ values below ~20 cm generally reflect those of the infiltrating precipitation 450 or irrigation that preceded each sampling event, and 2) soil water δ values trend from higher 451 values in the fall season, toward lower values in the winter, and return to higher values in the 452 spring season, mirroring seasonal trends in the δ values of precipitation before the onset of 453 irrigation in the spring. 454 In the case of the period from the end of irrigation in the fall season until the first 455 snowfall and snowmelt in the winter (October to early December, Fig. 3A), soil water content at 456 all soil depths decreases throughout this time period (with only a brief, small increase in the 457 shallow soil from a small precipitation event in mid-November). The soil water δ2Hliq and δ18Oliq 458 values at 50 cm depth are set by the last irrigation event of the season in late October, and show a 459 change towards higher values at all soil depths as the soil dries out. This trend to higher δ values 460

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is evidence that the soil is drying by evaporation and not by drainage, which would also be 461 evident in GWC content data showing downward movement of water in the soil column. This 462 evaporative drying trend continues until mid-December, resulting in the lowest soil water 463 contents of the study period (Fig. 3). 464 The effect of infiltrating snowmelt in the soil is evident in late January, when GWC 465 contents are higher than during the preceding fall season and δ values have changed to the lowest 466 of the study period (Fig. 3B). These low soil water δ values at all soil depths below 10 cm are 467 derived from snow (with δ2Hliq and δ18Oliq values of -141.2‰ and -18.44‰ respectively) and 468 resulting melt and infiltration. Evaporative enrichment appears to be minor and confined to the 469 upper 10 cm of the soil (Fig. 3B). Low soil water δ values continue through the end of February 470 2016, though the lack of precipitation after mid-February is evident in the greater evaporative 471 enrichment (higher δ values) at 10 cm and above (Fig. 3B). The Feb 2016 sampling event 472 occurred after a prolonged period (>60 days) of multiple snowfall events and resulting recharge 473 of soil water at 50 cm depth from snowmelt infiltration (Fig. 3) and presumably very little 474 evaporative and transpirative loss due to cold temperatures and inactive plant growth. 475

The water vapor probes may be measuring a distinct portion of the total soil water (i.e. 476 the “mobile” soil water that is able to equilibrate with vapor accessible to the vapor probe) that 477 has different isotopic composition from bulk soil water. In contrast, vacuum extracted soil water 478 is typically thought to represent the total soil water if extractions are run to completion (all of the 479 water is extracted from the soil sample (Orlowski et al., 2015)). In this way it may be possible to 480 differentiate between various “pools” of soil water by using the soil water vapor probe 481 measurements in conjunction with vacuum extraction and analyses of the total soil water. 482

Comparison of water vapor probe measurements with vacuum extracted water indicates 483 that the snowmelt infiltration resulted in a complete “reset” of the soil water δ values to reflect 484 that of the infiltrating snowmelt (Fig. 3A and 3B), as evidenced by the similarity between vapor 485 measurements and extracted water δ values for the Feb 2016 samples (Fig. 5). Infiltration of 486 spring season precipitation with increasing δ values through the season is reflected in a shift 487 toward higher soil water δ values throughout the soil profiles when measured in March and April 488 2016 (Fig. 3C). At that time the soil water measured by vapor probes had δ values (Fig 3C) that 489 were different than the extracted water samples by up to 19.2‰ for δ2H and 1.62‰ for δ18O 490 (Fig. 5). The different δ values generated by the two measurement methods could be explained 491 by spatial heterogeneity in the soil water conditions, and therefore sampling in different locations 492 yields differing soil water δ values. However, such a spatially-fine heterogeneity is unlikely 493 because of the general similarity and close spacing of the sampling sites, and the uniformity of 494 the Technosol soil material throughout the area. 495

Different δ values generated by the two measurement methods could indicate that the soil 496 water in April consisted of two distinct components: an immobile pool (that comprises some 497 fraction of the total soil water yielded by vacuum extraction), and a more mobile soil water pool 498 comprised of infiltrating precipitation (measured by vapor probe measurements). The differing δ 499 values resulting from the two measurement methods could indicate that the immobile water may 500 have only been partially replaced by, or mixed with the mobile water since the winter, and only 501 at depths less than 25 cm. Deep soil water at 50 cm depth continued to be dominated by 502 wintertime precipitation with lower δ values than the following spring precipitation events. It is 503 interesting that this deeper soil water from snowmelt events ~4 months prior (that infiltrated very 504 dry soil) persists in a relatively undisturbed state despite numerous successive precipitation and 505 infiltration events involving isotopically distinct water. Previous work (Geris et al., 2015; 506

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Sprenger et al., 2015) in climates and soils different than the present study also found that soil 507 water sampled in summer showed evidence of the preceding winter’s infiltration water in the 508 form of lower δ values of extracted water as compared to lysimeter- or direct equilibration-509 sampled (mobile) soil water. These results suggest that water that initially fills pores in dry soil 510 (which may of a very small pore size) does not readily mix or equilibrate via diffusion with other 511 “pools” of soil water even after several months’ time (Brooks et al., 2010). 512 Reactivation of the irrigation system in late May 2016 does not result in a shift in deep 513 soil water δ values to reflect the irrigation water δ values, but rather the deep (≥40 cm) soil water 514 δ values for the June through August 2016 sampling events remain similar to those in March and 515 April 2016 (Fig. 3C and 3D), especially in the case of δ18Oliq values. This stationarity in soil 516 water δ18Oliq profiles below 15 cm depth is despite a marked decrease in the δ18Oliq values of the 517 largest source of input water to the soil (irrigation), which has a δ18Oliq value of -16.4‰ in May 518 2016. These distinct patterns in soil water H and O isotope depth profiles through time suggest 519 that the FASB soil seems to have two hydrological systems that are somewhat decoupled: the 520 upper soil above 10 or 15 cm depth where soil water evaporation effects (see below) and 521 irrigation infiltration lead to high variability in soil moisture and isotopic composition, and a 522 lower soil below about 20 cm that is connected to the upper soil only during seasonal snowmelt 523 infiltration. 524 525 4.3 Evaporation of soil water restricted by mulch surface cover 526 A comparison of soil water from different soil depths to local precipitation and irrigation 527 water (Fig. 4) shows that the slope of the relationship between δ2Hliq and δ18Oliq values is similar 528 to that of precipitation at soil depths greater than 15 cm. Soil depth profiles of deuterium excess 529 values compared to that of precipitation and irrigation (Fig. 7) suggests that the influence of soil 530 water evaporation is most prevalent in the upper 10 cm of the soil. While there is some shift in 531 deuterium excess values below 15cm soil depth for the Oct – Dec samples when the soil was 532 driest (Fig. 7) that is likely due to diffusion in response to evaporative removal of water in the 533 upper soil, the similarity between soil water, and precipitation and irrigation deuterium excess 534 values indicates that soil water from greater than 15 cm depth is not influenced by evaporation to 535 a large degree. The shallow depth of soil water evaporation at this site is in contrast to studies 536 from similar climates that show a much larger evaporative influence on soil water δ values to 537 ~50 cm soil depth (Breecker et al., 2008; Sprenger et al., 2016b; Oerter et al., 2016). 538 It is likely that the major control on restricting soil water evaporation in this studied soil 539 is the presence of the chipped bark mulch layer covering the soil surface (e.g. Hillel, 1982). The 540 mulch layer minimizes evaporation of water from the soil surface in several ways: 1) by creating 541 a buffer between the high water content of the soil surface and the comparatively lower humidity 542 of the overlying atmosphere and through which diffusive transport of water vapor is minimized 543 (e.g. Allison et al., 1983), 2) by preventing turbulent mixing with the atmosphere and resulting 544 advective removal of water vapor from the soil surface and upper soil (e.g. Craig and Gordon, 545 1965), and 3) insulating the soil from solar heating and warm air temperatures (e.g. Barnes and 546 Allison, 1984). 547 548 4.4 Tree water use and ecohydrologic separation in Technosols 549 Previous work has shown that most plants do not isotopically fractionate the water they 550 take up through the roots or move through xylem tissue (White et al., 1985; Dawson and 551 Ehleringer, 1991; Roden and Ehleringer, 1999). Therefore xylem water H and/or O isotopic 552

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composition can be compared to that of the various water sources (including soil water H and O 553 isotope depth profiles) to determine water use patterns in space and time. In this study, the most 554 likely sources to supply water for transpiration in the Prunus cerasifera tree at the study site are 555 irrigation, or precipitation during times of non-irrigation. When plotted in dual isotope space (i.e. 556 Fig. 4) xylem water should coincide with either source, or lie in between sources if the tree is 557 using some combination of source waters. 558 In Figure 4, Prunus cerasifera xylem water isotopic values do not match precipitation 559 (LMWL) or irrigation water, and instead are most similar to soil water from 0 cm (soil/mulch 560 interface) to 5 cm soil depth. This finding is surprising because it seems very unlikely that a ~5 561 m tall tree is rooted at, and using soil water primarily from, such a shallow depth. In a study of 562 tree water use in an urban setting, Bijoor et al. (2012) found a similar pattern of xylem water H 563 and O isotope values that lie below and to the right of the LMWL on a dual isotope plot, and 564 interpreted those results to indicate that the trees were using shallow soil water (<30 cm soil 565 depth). If a similar interpretation is advanced for our study system, the high-resolution soil water 566 isotope profile data constrain the source of water more precisely to the top 5 cm. Bijoor et al. 567 (2012) also found evidence that some irrigated trees were using groundwater despite the 568 presence of irrigation water in the soil. Groundwater in the vicinity of our study site has δ2H and 569 δ18O values of -118.8 (± 1.2) ‰ and -15.6 (± 0.2) ‰ (Hall et al., 2016), which overlaps with the 570 LMWL (Fig. 4). Therefore, we conclude that groundwater is not a likely water source for Prunus 571 cerasifera at our study site. While we cannot completely exclude a residual isotopically-enriched 572 signal from winter time fractionation of stem water while in the xylem which persists into the 573 growing season (Phillips and Ehleringer, 1995; Ellsworth and Sternberg, 2015), this is unlikely 574 because it appears that winter water is completely flushed from the xylem after leaf emergence in 575 the spring time (Fig. 4). In sum, it appears that Prunus is linked primarily to the upper soil 576 hydrologic system. 577 In this soil system, the contrasting isotopic signatures generated from the vapor probe and 578 vacuum extracted methods after initial snowmelt infiltration, compared to results that did not 579 differ as much after repeated infiltration events (see Section 4.2) suggests that a physical 580 separation of soil water pools occurred in this study system. This observation of soil water 581 partitioning into distinct pools in the Technosol studied here is similar to results from natural 582 soils (e.g. Brooks et al., 2010; Goldsmith et al., 2012), and suggests that soil water partitioning 583 may result from soil material properties such as particle size and not to characteristics resulting 584 from natural soil development (e.g. development of soil structure and characteristic pore-size 585 distributions, organic material accumulation, etc). Indeed, studies using modeling and sand 586 column experiments have found that particle size controls how antecedent water is displaced by 587 subsequent water infiltration, with significant fractions (up to 30%) of old water remaining in the 588 experimental pore space even after multiple successive infiltration events (Gouet-Kaplan et al., 589 2011; Gouet-Kaplan et al., 2012; Kapetas et al., 2014). These areas of persistently older water, 590 would be the immobile component in the mobile-immobile water paradigm. If the antecedent 591 water had an isotopic composition distinct from successive events (as did winter water in this 592 study), the antecedent water would still be detectable in the soil even after infiltration of later 593 waters, but only by extraction of the recalcitrant immobile water from the soil matrix, which we 594 have shown (Fig. 5). Therefore, the sensitivity of the water vapor probe method to yield 595 measurements of mobile soil water, or perhaps distinct “pools” of soil water that have not yet 596 equilibrated or mixed with the “whole” soil water suggests that it may be possible to couple 597

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water vapor probe measurements to that of extracted water to characterize the isotopic 598 composition of the various pools of water in soil in ways that have not been possible until now. 599 600 5. Conclusions 601 602

In this study we present a versatile analytical approach to non-destructive in situ 603 monitoring of soil water δ2H and δ18O values that is field deployable by a single person. We 604 demonstrate the system’s utility and efficacy in an urban landscaped garden setting in which 605 repeated measurements reveal seasonal soil water H and O stable isotope dynamics. We find that 606 soil water δ2H and δ18O values predominately reflect seasonal precipitation and irrigation inputs, 607 but that initial infiltration events after long periods of soil drying (the fall season in this case) 608 emplace water into the soil matrix that is not easily replaced by, or mix with successive pulses of 609 infiltrating soil water. Tree stem xylem water was isotopically distinct from the various water 610 sources, and a combination of the available water sources cannot explain the observed xylem 611 water composition. These findings are in agreement with studies from a variety of naturally 612 formed soils in a range of climates, which suggests that partitioning of soil water into mobile and 613 immobile “pools” may be somewhat universal and ultimately an intrinsic property of soils. When 614 the continuum of soil water mobility states are combined with related physico-chemical effects 615 that can alter the isotopic composition of soil water in the various soil microenvironments, it may 616 offer some progress towards explaining the mechanisms behind ecohydrologic separation. 617

The plot-scale at which soil water flux measurements can be made with this approach 618 make it especially suitable for application to urban, managed, and otherwise novel ecosystems 619 that have large heterogeneity in land use, land cover, and irrigation inputs at small spatial scales. 620 Beyond managed settings, the approach also has potential to yield insights in a variety of Critical 621 Zone and vadose system studies, potential that is heightened by the simplicity of the system, its 622 portability and robustness, and low cost to deploy. 623 624 Acknowledgements 625 626 We appreciate the field assistance of John Walker of the University of Utah facilities 627 staff. All data is publicly available on line from the iUTAH Modeling and Data Federation 628 at data.iutahepscor.org/mdf. This research was supported by NSF EPSCoR grant IIA 1208732 629 awarded to Utah State University as part of the State of Utah Research Infrastructure 630 Improvement Award. Constructive comments by Matthias Sprenger and three anonymous 631 reviewers helped to improve this paper. 632 633 634 References 635 636 Allison, G.B., Barnes, C.J., Hughes, M.W., 1983. The Distribution of Deuterium and O-18 in 637

Dry Soils .2. Experimental. Journal of Hydrology, 64(1-4): 377-397. 638 Asano, Y., Uchida, T., Ohte, N., 2002. Residence times and flow paths of water in steep 639

unchannelled catchments, Tanakami, Japan. Journal of Hydrology, 261(1): 173-192. 640 Barnes, C.J., Allison, G.B., 1983. The Distribution of Deuterium and O-18 in Dry Soils .1. 641

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Roden, J.S., Ehleringer, J.R., 1999. Hydrogen and oxygen isotope ratios of tree-ring cellulose 743 for riparian trees grown long-term under hydroponically controlled environments. 744 Oecologia, 121(4): 467-477. 745

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Schoeneberger, P.J., Wysocki, D.A., Benham, E.C., Soil Survey Staff, 2012. Field book for 751 describing and sampling soils, Version 3.0. Natural Resources Conservation Service, 752 National Soil Survey Center, Lincoln, NE. 753

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Sprenger, M., Herbstritt, B., Weiler, M., 2015. Established methods and new opportunities 757 for pore water stable isotope analysis. Hydrological Processes, 29(25): 5174-5192. 758

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778

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779 780 781 FIGURE CAPTIONS 782 783 Figure 1. Schematic drawings of: (A) subsurface portion of soil water vapor probe; (B) layout of 784 the water vapor probe analytical system, arrows indicate carrier gas (N2) flow direction; (C) field 785 installation of water vapor system and soil water content and temperature sensors in the wall of 786 the soil excavation, shown at four depths only for diagrammatic clarity. 787 788 789 Figure 2. Comparison of δvapor values measured with the water vapor probe (circles) at varying 790 temperatures with that calculated to be in equilibrium with the water used to make each standard 791 (dashed lines) using the relations of Majoube (1971) and Merlivat and Nief (1967), for silica 792 sand-water (top) and FASB soil-water (bottom) standards. 793 794 795 Figure 3. Comparison of gravimetric soil water content (left), precipitation events (center) and 796 soil δ2Hliq and δ18Oliq depth profiles (right). Precipitation events were recorded at a nearby station 797 (http://data.iutahepscor.org/mdf/river_info/iUTAH_RedButte_OD/RB_GIRF_C/). Precipitation 798 and irrigation δ2Hliq and δ18Oliq values (grey bars on right panels) correspond to events denoted 799 as A*-D* in center panel (data shown in Supp. Table 2). Shaded areas in left panel represent 800 time periods when the irrigation system was active. Water content data from 20cm soil depth 801 ceased in mid-June 2016 due to a failed sensor. 802 803 804 Figure 4. Soil water δ2H and δ18O values measured by in situ water vapor probes compared to 805 that of local precipitation, (LMWL = Local Meteoric Water Line), irrigation, ground water, and 806 Prunus cerasifera xylem water samples. Dashed line denotes linear regression of soil water at 0 807 cm depth (soil interface with mulch) (R2 = 0.86, n = 12). LMWL data from Jameel et al. (2016), 808 ground water data from Hall et al. (2016). 809 810 811 Figure 5. Comparison of soil water δ2H and δ18O values measured by water vapor probe to that 812 extracted under vacuum. Vacuum extracted data are plotted as the average δ values of three soil 813 sample replicates from each depth (n = 18 total); the range of variability for the three vacuum 814 extracted sample replicates and the analytical uncertainty of the measurements of the extracted 815 liquid waters is smaller than the plotted marker symbols, and is ±2.4‰ for δ2Hliq and ±0.48‰ for 816 δ18Oliq for the water vapor probe method. 817 818 819 Figure 6. Comparison of δ2Hliq and δ18Oliq values of soil water during the February and April 820 2016 sampling events measured by vacuum extraction and in situ water vapor probes from 10 cm 821 and deeper, irrigation water from throughout the study period, and the Local Meteoric Water 822 Line (LMWL). LMWL data from Jameel et al., (2016). 823 824

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825 Figure 7. Comparison of deuterium excess values for soil water from all sampling events in this 826 study with deuterium excess values in irrigation and precipitation. This figure also shows that 827 soil water is not fully reset isotopically until after the January sampling after the infiltration of 828 the winter season’s first snow melt. 829 830 831 832 833 834 835 836

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Figure 1. Schematic drawings of: (A) subsurface portion of soil water vapor probe; (B) layout of the water vapor probe analytical system, arrows indicate carrier gas (N2) flow direction; (C) field installation of water vapor system and soil water content and temperature sensors in the wall of the soil excavation, shown at

four depths only for diagrammatic clarity.

163x98mm (300 x 300 DPI)

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Figure 2. Comparison of δvapor values measured with the water vapor probe (circles) at varying

temperatures with that calculated to be in equilibrium with the water used to make each standard (dashed

lines) using the relations of Majoube (1971) and Merlivat and Nief (1967), for silica sand-water (top) and

FASB soil-water (bottom) standards.

156x146mm (300 x 300 DPI)

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Figure 3. Comparison of gravimetric soil water content (left), precipitation events (center) and soil δ2Hliq

and δ18Oliq depth profiles (right). Precipitation events were recorded at a nearby station

(http://data.iutahepscor.org/mdf/river_info/iUTAH_RedButte_OD/RB_GIRF_C/). Precipitation and irrigation

δ2Hliq and δ18Oliq values (grey bars on right panels) correspond to events denoted as A*-D* in center

panel (data shown in Supp. Table 2). Shaded areas in left panel represent time periods when the irrigation

system was active. Water content data from 20cm soil depth ceased in mid-June 2016 due to a failed

sensor.

190x241mm (300 x 300 DPI)

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Figure 4. Soil water δ2H and δ18O values measured by in situ water vapor probes compared to that of local precipitation, (LMWL = Local Meteoric Water Line), irrigation, ground water, and Prunus cerasifera xylem

water samples. Dashed line denotes linear regression of soil water at 0 cm depth (soil interface with mulch) (R2 = 0.86, n = 12). LMWL data from Jameel et al. (2016), ground water data from Hall et al. (2016).

118x114mm (300 x 300 DPI)

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Figure 5. Comparison of soil water δ2H and δ18O values measured by water vapor probe to that extracted under vacuum. Vacuum extracted data are plotted as the average δ values of three soil sample replicates from each depth (n = 18 total); the range of variability for the three vacuum extracted sample replicates

and the analytical uncertainty of the measurements of the extracted liquid waters is smaller than the plotted marker symbols, and is ±2.4‰ for δ2Hliq and ±0.48‰ for δ18Oliq for the water vapor probe method.

135x66mm (300 x 300 DPI)

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Figure 6. Comparison of δ2Hliq and δ18Oliq values of soil water during the February and April 2016 sampling events measured by vacuum extraction and in situ water vapor probes from 10 cm and deeper, irrigation water from throughout the study period, and the Local Meteoric Water Line (LMWL). LMWL data

from Jameel et al., (2016).

148x143mm (300 x 300 DPI)

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Figure 7. Comparison of deuterium excess values for soil water from all sampling events in this study with deuterium excess values in irrigation and precipitation. This figure also shows that soil water is not fully

reset isotopically until after the January sampling after the infiltration of the winter season’s first snow melt.

144x142mm (300 x 300 DPI)

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in situ monitoring of h and o stable isotopes in soil water reveals … · 2017-02-03 · for peer...

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