Received: 2 April 2019 Accepted: 14 October 2019 DOI: 10.1002/hyp.13621

RESEARCH ARTICLE

Hydrogeology of desert springs in the Panamint Range, California, USA: Identifying the sources and amount of recharge that support spring flow

Carolyn L. Gleason1,2 | Marty D. Frisbee1 | Laura K. Rademacher3 | Donald W. Sada4 | Zachary P. Meyers1

1Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana 2Genesis Engineering and Redevelopment, Lodi, California 3Department of Geological and Environmental Sciences, University of the Pacific, Stockton, California 4Division of Hydrologic Sciences, Desert Research Institute, Reno, Nevada

Correspondence Marty D. Frisbee, Department of Earth, Abstract Atmospheric, and Planetary Sciences, Purdue Despite its location in the rain shadow of the southern Sierra Nevada, the Panamint University, 550 Stadium Mall Drive, West Lafayette, IN 47907. Range hosts a complex mountain groundwater system supporting numerous springs Email: [email protected] which have cultural, historical, and ecological importance. The sources of recharge

Funding information that support these quintessential desert springs remain poorly quantified since very Graduate Student Research Grant; Directorate little hydrogeological research has been completed in the Panamint Range. Here we for Geosciences, Grant/Award Numbers: 1516127, 1516698; Graduate Student address the following questions: (i) what is the primary source of recharge that sup- Research Grant ports springs in the Panamint Range (snowmelt or rainfall), (ii) where is the recharge occurring (mountain-block, mountain-front, or mountain-system) and (iii) how much recharge occurs in the Panamint Range? We answer questions (i) and (ii) using stable isotopes measured in spring waters and precipitation, and question (iii) using a chlo- ride mass-balance approach which is compared to a derivation of the Maxey–Eakin equation. Our dataset of the stable isotopic composition (δ18O and δ2H) of precipita- tion is short (1.5 years), but analyses on spring water samples indicate that high- elevation snowmelt is the dominant source of recharge for these springs, accounting for 57 (±9) to 79 (±12) percent of recharge. Recharge from rainfall is small but not insignificant. Mountain-block recharge is the dominant recharge mechanism. How- ever, two basin springs emerging along the western mountain-front of the Panamint Range in Panamint Valley appear to be supported by mountain-front and mountain- system recharge, while Tule Spring (a basin spring emerging at the terminus of the bajada on the eastern side of the Panamint Range) appears to be supported by mountain-front recharge. Calculated recharge rates range from 19 mm year−1 (eleva- tions < 1000 mrsl) to 388 mm year−1 (elevations > 1000 mrsl). The average annual recharge is approximately 91 mm year−1 (equivalent to 19.4 percent of total annual precipitation). We infer that the springs in the Panamint Range (and their associated ecosystems) are extremely vulnerable to changes in snow cover associated with cli- mate change. They are heavily dependent on snowmelt recharge from a relatively thin

Hydrological Processes. 2019;1–19. wileyonlinelibrary.com/journal/hyp © 2019 John Wiley & Sons, Ltd. 1 2 GLEASON ET AL.

annual snowpack. These findings have important implications for the vulnerability of desert springs worldwide.

KEYWORDS climate change, crenobiontic, Death Valley, Desert springs, mountain recharge, Panamint Range, snowmelt recharge, sources of recharge, spring vulnerability, stable isotopes

1 | INTRODUCTION were critical to the survival of early Native American Timbisha Sho- shone communities who would move from winter homes in the valleys The Panamint Range, located partially within Death Valley National to mountain homes during the spring, summer and fall (Crum, 2002; Park of California, consists of the Cottonwood Mountains, Panamint Wallace, 1980; White, 2006). These same springs were important Mountains (an informal name, but common usage; Belcher & sources of water for mining camps and mining activities which moved Sweetkind, 2010), and Owlshead Mountains. Our study was con- into the area in the late 1800s (Lingenfelter, 1986; Miller, 2008; ducted entirely in the central Panamint Mountains which we will refer White, 2006). Today, multiple studies have shown that the springs in to as the Panamint Range hereafter. The Panamint Range hosts the southern Great Basin are critical to aquatic ecosystem functioning numerous springs despite regional hyperaridity due to its location since they often provide the only surface water for bird, mammal, and within the rain shadow of the southern Sierra Nevada (Figure 1). For insect species (Chambers, Miller, & MacMahon, 2004; Hannah et al., context, the ratio of evaporation to precipitation is 90:1 (Hunt, Robin- 2007; Sada, Fleishman, & Murphy, 2005). For example, the springs son, Bowles, & Washburn, (1966)). While seasonal snowpacks in the emerging in the Panamint Range support nesting habitat for over southern Sierra Nevada can be greater than 4 m in thickness annually 70 species of birds (Wauer, 1964) and some of the springs support (Barbour, Berg, Kittel, & Kunz, 1991), snowpacks are typically much unique crenobiontic (obligate spring-dwelling) animals, namely thinner in the Panamint Range due to its location in the rain shadow. It springsnails such as P. Turbatrix (Hershler, Liu, & Howard, 2014; Her- is surprising that a mountain range that receives so little snow in com- shler & Sada, 2002; Sada & Pohlmann, 2007). Thus, a spatially compre- parison to the southern Sierra Nevada can support over 180 springs hensive quantification of the sources of groundwater recharge that (Figure 1). support these springs and the magnitude of recharge occurring in the Unfortunately, very little hydrogeological research has been con- Panamint Range will provide valuable information on the vulnerability ducted in the Panamint Range. The work of King and Bredehoeft of these springs to the effects of climate change and human alteration (1999) provides data on nine springs in the Panamint Range. As a con- (Frisbee, Phillips, White, Campbell, & Liu, 2013; Manning et al., 2012; sequence, the sources of recharge and magnitude of recharge Rademacher, Clark, Clow, & Hudson, 2005). supporting these springs remain poorly quantified. This creates a mul- Groundwater recharge has an explicit definition: it is water that tifaceted problem given the importance of desert springs in the region has infiltrated the soil and percolated into the fully saturated porous (and worldwide). The desert springs emerging in the Panamint Range media below the water table (Freeze & Cherry, 1979). In the American

FIGURE 1 Regional map showing the location of the Panamint Range and surrounding mountain ranges and spring locations (the red box in the inset shows the location of the study area relative to a basemap of the USA). Basins are labelled using abbreviations: BW, Badwater Basin and PV, Panamint Valley. Yellow Triangles represent precipitation collection sites. Information on the location of springs is sourced from the USGS National Hydrography Database (https://nhd. usgs.gov) GLEASON ET AL. 3

Southwest, groundwater recharge occurring in the mountains contrib- the vulnerability of desert springs across the southern Great Basin utes significant amounts of water to surrounding basin aquifers from the Spring Mountains located west of Las Vegas, NV to Owens because precipitation is usually higher than evapotranspiration (ET) in Valley, CA. This research provides much-needed hydrogeological data the mountains, especially during the snowbound and snowmelt sea- that can be used to assess the vulnerability of these springs to climate sons (Bresciani et al., 2018; Wilson & Guan, 2004). In the basins, evap- change and other disturbances (Frisbee et al., 2013; Manning et al., oration commonly exceeds precipitation year-round, thus, the 2012; Rademacher et al., 2005). The results presented here have criti- likelihood of substantial recharge occurring in basins is negligible. This cal implications for other desert springs in the southern Great Basin is especially true for basins with climatic conditions similar to Death and are broadly applicable to desert springs globally. Valley (Figure 1) where the ratio of ET to precipitation exceeds 90:1. Substantial recharge can, however, occur when surface water flowing from the mountain block infiltrates alluvial sediments at and beyond 2 | STUDY AREA the mountain front. Therefore, it is important to evaluate recharge mechanisms as well as sources and magnitudes of recharge since 2.1 | Geology of the Panamint Range springs emerging in different parts of the landscape may depend on different recharge mechanisms. The public lands of the Panamint Range are managed by the Groundwater recharge in mountainous terrain commonly occurs U.S. National Parks Service (Death Valley National Park) and the via three different mechanisms (or a combination of these mecha- U.S. Bureau of Land Management (Ridgecrest office). The Panamint nisms): (i) mountain-block recharge (MBR), (ii) mountain-front recharge Range is a north/south trending mountain range located partially (MFR; Wilson & Guan, 2004; Bresciani et al., 2018) or (iii) the combi- within Death Valley National Park between Panamint Valley to the nation of MBR and MFR collectively known as mountain-system west and Badwater Basin to the east (Figure 1). It is a terrain of recharge (MSR; Wahi, Hogan, Ekwurzel, Baillie, & Eastoe, 2008; extreme elevation and climate, with numerous springs emerging Bresciani et al., 2018). MBR occurs at the highest elevations of the across elevations and geologic units (Figure 2). Its highest point, Tele- mountain block and supports groundwater circulating primarily within scope Peak (UTM: 11S, 491979 mE, 4002807 mN), reaches an eleva- the mountain block. This recharge, for example, supports springs or tion of 3366 m above sea level while the lowest point in the region seeps that emerge within the mountain block (Bresciani et al., 2018; (in North America) is Badwater at an elevation of 77 m below sea Manning & Solomon, 2003; Wilson & Guan, 2004). MFR occurs when level. Since elevations in the study area range from below sea level to surface water flows from the mountain block and recharges alluvial above sea level, we will use the terminology “meters relative to sea sediments located beyond the mountain front (Bresciani et al., 2018; level (mrsl)” throughout the manuscript. The elevation gradient in the Manning & Solomon, 2003). Springs emerging beyond the mountain Panamint Range is steep since the highest and lowest points are only front, on alluvial fans or bajadas, and/or at the terminus of alluvial fan separated by ~30 km of lateral distance, and this has important and bajadas are commonly supported by MFR. However, springs regional climatological consequences. which emerge at mountain-front faults or in the adjacent basin may The geology of the Panamint Range reflects its unique tectonic also be supported by MSR. history. The Panamint Range is located within a zone of extreme The perennial nature of many of the springs in the Panamint Cenozoic extension (Miller, 1987). The mountain block comprises pri- Range suggests that the springs must be dependent on substantial marily Proterozoic sedimentary rock with several phases of granitic annual recharge or that they are dependent on paleorecharge intrusive bodies that were emplaced between the Triassic period and (e.g. Pleistocene recharge). The latter requires substantial subsurface Miocene epoch (Workman, et al., 2016). Younger Cambrian and Ordo- storage and/or a hydraulic connection to a regional-flow system. The vician sedimentary rocks can be found on the flank of the eastern side paucity in precipitation across the rain shadow in the southern Great of the Panamint Range but are largely absent on the western flank Basin indicates that if substantial modern recharge is occurring, then it (Norton, 2011; Stewart, 1983). The range is cut by steep ephemeral must be occurring primarily in the mountains (Ajami, Troch, Maddock, channels draining to both Panamint Valley and Badwater Basin Meixner, & Eastoe, 2011). Here we address the following questions in (Figure 2). Flow from these streams recharges alluvium at the moun- this study. (i) What is/are the source(s) of groundwater recharge in the tain front. Panamint Range? Are springs recharged primarily by snowmelt or rain- fall? (ii) Where is the recharge occurring (mountain-block, mountain- front, or mountain-system)? (iii) How much recharge occurs in the 2.2 | Hydrogeology of the Panamint Range Panamint Range? We answer questions (i) and (ii) using stable isotopes of spring waters and precipitation. We answer question (iii) using a Mountain recharge is likely confined to the Noonday Formation, chloride mass-balance approach (Aishlin & McNamara, 2011; Frisbee Johnnie Formation, and Kingston Peak Formation which outcrop et al., 2013; Russell & Minor, 2002) which is compared to a derivation broadly across the crest and highest elevations of the Panamint Range of the Maxey–Eakin equation (Maxey & Eakin, 1949; Stephens & (Labotka & Albee, 1990; Norton, 2011; Workman, et al., 2016). Talus Umstot, 2019; Wilson & Guan, 2004). The Panamint Range study is a slopes with little vegetation and rocky slopes supporting sparse vege- small component of a larger research project, which seeks to quantify tation are widespread along the crest. Aquifers in the Panamint Range 4 GLEASON ET AL.

FIGURE 2 Map of the Panamint Range showing spring locations. The 1400 m contour line is shown in black

are most likely constrained to the Precambrian sedimentary strata groundwater within the mountain block. Chemical weathering of because the carbonate rocks prevalent in these units are thought to carbonate rocks may also enhance infiltration and subsequent have higher hydraulic conductivity than the intrusive bodies and recharge in the mountain-block. In comparison, the upper green- heavily metamorphosed rocks also present in the mountain block. We schist to lower amphibolite-grade metamorphism of the Precam- cannot provide ranges of hydraulic conductivities since very little brian rock likely limits hydraulic conductivity and deep circulation hydrogeological research has been completed in the study area. How- in these units (Miller, 1987). Faulting is widespread throughout the ever, our inference is supported by field observations noting that Panamint Range due to the rifting of the southern Great Basin many springs emerge at contacts between dolomitic units, such as the (Miller, 1987; Petterson, Prave, Wernicke, & Fallick, 2011; Work- Noonday and Beck Spring Dolomites, and formations associated with man, et al., 2016). These faults have variable depths and orienta- marine regression, such as the Johnnie Formation and the Kingston tions and can act either as barriers or conduits to groundwater Peak formation. flow within the mountain block depending on what water-bearing Chemical weathering in the carbonate units and faulting associ- units are intercepted by the faults, the spatial (lateral) and vertical ated with extensional forces have the potential to enhance the extent of the damage zone created by the faults, and the dissolu- porosity of these units and create highly connected flowpaths for tion and/or precipitation of calcite along the fault (Bense, Gleeson, GLEASON ET AL. 5

Loveless, Bour, & Scibek, 2013; Miller, 1987). Fault planes on the eastern flank of the mountain block dip 20–30 eastward toward Death Valley (Maxson, 1950; Miller, 1987).

2.3 | Climatology of the Panamint Range

Due to the remote and rugged nature of the terrain, there are no per- manent weather or SNOTEL stations in the Panamint Range. As a con- sequence, there are no continuous datasets of precipitation and temperature for the Panamint Range. However, as elevation increases, the amount of total annual precipitation increases, the amount of snow compared to rain increases, and the mean annual and mean daily temperatures decrease due to the orographic effect created by the extreme relief (Roe, 2005). The California Department of Water Resources lists the average rainfall as 8–10 cm year−1 along the west- ern Panamint Valley floor and less than 5 cm year−1 on the eastern Badwater Basin side of the range (Wauer, 1964). Average precipita- tion at the higher elevations of the Panamint Range can be estimated using precipitation models such as PRISM (PRISM, 2004). PRISM data indicate that the highest elevations of the Panamint Range receive an average annual precipitation rate of 486 mm year−1 (48.6 cm year−1). We use the PRISM estimated precipitation in the recharge analyses described in this article (see Section 3.4). Air temperatures and evaporation rates increase sharply with FIGURE 3 (a) Monthly environmental lapse rates (ELRs) created decreasing elevation in the Panamint Range. Figure (3a) shows using weather stations located across the Southern Great Basin for monthly environmental lapse rates (ELRs) for November, December, January (black circle), February (red circle), March (green circle), January, February and March using data obtained from meteorological November (purple circle), and December (blue). The red line indicates stations located across the southern Great Basin and monitored by the 1400 m contour. (b) same as (a) except for addition of spring water the National Climate Data Center (NCDC; see Table S1 in Supporting temperatures (blue squares) and ELR for July (yellow circle). Data were sourced from http://w2.weather.gov/climate/xmacis.php?wfo=vef Information for weather station locations and identification). These plots indicate that: (i) little, if any, snow falls at elevations less than 1350 mrsl, (ii) the majority of snow falls during December, January and February and (iii) snow can fall during November and March but Emigrant Pass at an elevation of 1225 mrsl, far from the expected only at elevations higher than 2000 mrsl. Although these ELR were recharge elevation. These data show average annual summer tempera- created across the southern Great Basin, it is likely that the evapora- tures between 17 and 34 C and winter temperatures between tion and sublimation losses are higher in the Panamint Range because 0 and 12 C. of its higher mean annual temperatures compared to the southern Data on evaporation and ET rates are lacking for the Panamint Sierra Nevada, the Argus Range, and possibly the Spring Mountains Range. However, Hunt, Robinson, Bowles, & Washburn (1966) state (DWR, 1964). Average summer temperatures in the greater Death Val- that pan evaporation rates in the basin equal 304.8 cm year−1 and can ley basin range from 30 to 46C while average winter temperatures exceed 393.7 cm year−1. During 1958–1961, a pan evaporation sta- range between 4 and 19C (Stachelski, 2013). Panamint Valley, how- tion was monitored near the Death Valley National Park Service Head- ever, is located at a higher elevation than Death Valley (Figure 2) and quarters. During the winter months of November, December, January, has correspondingly milder temperatures. According to the US February and March, an average evaporation of 71.5 cm was National Oceanic and Atmospheric Administration (NOAA) Climate recorded. This is in stark comparison to the 307.5 cm that was Data Online, the average annual summer temperatures from nearby recorded over the remainder of the year (Hunt, Robinson, Bowles, & Trona, CA (ID # GHCND:USC00049035; 11S, 464673 mE, 3957799 Washburn, 1966). In fact, the high evaporation rates result in an evap- mN; https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/sta- oration to precipitation ratio of 90:1. An evaporation “tub” was placed tions/GHCND:USC00049035/detail) range from 22 to 40C while the at 610 mrsl in Hanaupah Canyon and the data from this pan conform average annual winter temperatures range between 2 and 16C. The to the 90:1 ratio (Hunt, Robinson, Bowles, & Washburn, 1966). Thus, only data available within the Panamint Range itself is from a USAF precipitation which does reach the land surface at elevations less than WBAN Station (ID # 746190 99999; Superior Valley Gunnery Range; 1000 mrsl is likely lost to evaporation and does not recharge. 11S, 491025 mE, 4020556 mN) located in Wood Canyon near 6 GLEASON ET AL.

Altogether, the sharp elevation gradient combined with the strong 3 | METHODS elevation dependencies between temperature and precipitation create conditions conducive to the sky island effect. As elevation increases, 3.1 | Spring sampling there are corresponding increases in precipitation and decreases in temperature that create stark ecotones (Coe, Finch, & Friggens, 2012; Springs were selected for this study to achieve a broad spatial distri- Gottfried, Gebow, Eskew, & Edminster, 2005; McCormack, Huang, & bution with respect to elevation, geologic setting, and climatic setting Knowles, 2009). In fact, the Panamint Range has every life zone in the across the Panamint Range (Figure 2). Samples of spring water were western U.S. except for the Arctic life zone (Wauer, 1964). Wauer collected for stable isotopic analyses during a single two-week field (1964) divided the Panamint Range into 8 ecological zones based on campaign in the Panamint Range from 23 May 2017 to 02 June 2017. predominant vegetation and landscape placement (e.g. alluvial fan vs. Water samples were collected at each spring using a portable peristal- hillslope vs. high mountain) and found that the number of bird species tic pump (Miller & Frisbee, 2018) and Masterflex silicon tubing. The and diversity of species changed as a function of ecological zone and tubing was placed in the spring orifice (where possible) and a 0.22 μm water availability. Thus, the relationship between ecological metrics polyethersulfone membrane Sterivex-GP pressure filter was attached such as species diversity and elevation are themselves expressions of to the other end of the tubing for filtering. Water was pumped directly the subtle feedbacks between hydrology and climatology that are into a collection vial after purging the tubing for 10 min. Most samples characteristic of other sky islands in the American Southwest. were collected directly from the spring orifice or source. Some spring emergences, however, were diffuse or their true emergences were inaccessible due to the extremely rugged terrain or presence of dense vegetation surrounding the spring emergence. In these cases, spring runs were sampled downstream of the spring emergence (these sam- ples are indicated in Table 1). In total, 18 springs were sampled during the field campaign; 7 of which were sampled downstream of their emergence point. Samples were stored unrefrigerated in the field in

TABLE 1 δ18O and δ2H values of Panamint range spring samples

UTM coordinates Date sampled Spring name Elevation (mrsl) zone 11 S (m E, mN) (mm/dd/yy) Temperature (C) δ2H(‰) δ18O(‰) Jail Spring 2434 491216, 4005046 5/24/2017 9.0 -101 -14.1 Thorndike Spring 2337 493294, 4009949 5/25/2017 9.8 -103 -14.2 Uppermost Spring 1633 496410, 4012068 5/31/2017 16.5 -95 -12.9 Apron Spring 1606 493581, 4017809 5/27/2017 17.7 -98 -13.2 High Noon Spring 1419 493756, 4018743 5/27/2017 17.3 -98 -13.3 Main Hanaupah Spring #2a 1265 496928, 4004586 5/28/2017 15.1 -100 -13.7 Main Hanaupah Spring #1a 1258 497013, 4004384 5/28/2017 20.5 -93 -12.5 Limekiln Spring 1223 486446, 3996617 6/1/2017 19.4 -99 -13.3 Unnamed Panamint spring Ca 1206 486503, 3996454 6/1/2017 16.5 -97 -13.4 Wilson Spring 1195 499326, 3993877 5/29/2017 20.4 -53 -7.7 South Hanaupah Spring #3a 1154 498063, 4004323 5/28/2017 16.1 -92 -12.4 Unnamed Panamint Spring E 963 484864, 3987455 5/26/2017 18.8 -94 -12.7 Unnamed Panamint Spring Fa 803 483892, 3987614 5/26/2017 19.4 -92 -12.5 Lower Warm Spring B 760 506108, 3980234 5/30/2017 34.4 -93 -12.7 Lower Warm Spring A 755 506301, 3980186 5/30/2017 34.3 -93 -12.4 Wheel Springb 748 499209, 4019868 5/26/2017 22.6 -61 -8.5 Post Office Springc 321 479772, 3988537 6/2/2017 18.7 -78 -8.8 Warm Sulphur Spring 318 480753, 3997248 6/1/2017 32.0 -95 -13.0 Tule Spring -77 510652, 4010962 3/14/2017 27.4 -103 -13.4 Poplar Spring A 1225 465797, 4097533 12/19/2016 17.7 -101 -14.0 Upper Emigrant Spring 1231 482674, 4031167 05/19/2016 19.8 -100 -13.5 aSprings that were sampled downstream of their true emergence (they were sampled in the springrun). bWheel spring was flagged for spectral contamination. cPost office spring shows evidence for evaporation. GLEASON ET AL. 7

2 ml glass vials with plastic screw-caps but samples were refrigerated them to published stable isotopic compositions of precipitation and once they were returned to the lab and were kept refrigerated until springs measured across the southern Great Basin. Three additional the time of analysis (the storage time was ~2 months). As part of the LMWLs were created from published data capturing the variability of decontamination protocol, a 50% ethanol (C2H5OH) solution was used precipitation and springs across the rain shadow of the southern Sierra to decontaminate the tubing, filters, shoes and clothes of the research Nevada: (i) a LMWL for Death Valley, CA was created using data com- team, and all equipment that came in contact with water between piled from Friedman, Smith, Johnson, and Moscati (2002), (ii) a LMWL each spring sampling site. Three additional springs (Tule Spring, Upper for Owens Valley, CA was created using data that was compiled from Emigrant Spring and Poplar Spring A) were sampled as part of the Friedman et al. (1992) and (iii) a LMWL was created for the Spring larger project on the southern Great Basin. Data from these three Mountains using data that was compiled from Ingraham and Taylor springs (sampled in May 2016–December 2016) are included in this (1991), Ingraham, Lyles, Jacobson, and Hess (1991) and Winograd, study because they emerge in/near the Panamint Range. Riggs, and Coplen (1998).

3.2 | Precipitation sampling 3.3 | Recharge identification and partitioning

To collect precipitation in the Panamint Range, we deployed two pre- Two-component mixing models are commonly used to identify and cipitation collectors in 14 October 2017 using the design described in partition (separate) the sources of waters contributing to a stream or Earman, Campbell, Phillips, and Newman (2006) and Frisbee, Phillips, spring based on known endmembers (Frisbee et al., 2010; Genereux, Campbell, Hendrickx, and Engle (2010). One collector was placed near 1998; Liu, Williams, & Caine, 2004; Sklash & Farvolden, 1979; the Mahogany Flats Campground (2478 mrsl, 11S, 493858 mE, Winograd et al., 1998). The same model can be applied to quantify the 4009470 mN) and one was placed near Thorndike Campground (2262 sources of recharge assuming that all sources of recharge are known mrsl, 11S, 493513 mE, 4010232 mN). The locations of the precipita- and measured. In this case, rain and snowmelt are the two possible tion collectors were chosen because they are dirt-road accessible. sources of recharge. The set of equations that defines this model as Sample collection was further restricted by seasonal road closures and applied to spring recharge is shown below: poor driving conditions during snowmelt. Mineral oil was poured in 18 18 18 the reservoir of the collector to minimize the impact of evaporation δ Ospring = fsnowδ Osnow + frainδ Orain ð1Þ on isotopic fractionation (Earman et al., 2006; Friedman, Smith,

Gleason, Wardern, & Harris, 1992; Frisbee et al., 2010; Scholl, 2006). frain + fsnow = 1 and by rearranging frain =1− fsnow ð2Þ This collector type is suitable for rugged terrain in which the collector 18 18 18 18 must remain unchecked for months at a time (Earman et al., 2006; fsnow = δ Ospring −δ Orain = δ Osnow −δ Orain ð3Þ Friedman et al., 1992; Frisbee et al., 2010; Scholl, 2006). 18 Samples of precipitation were taken from the collectors and the where, δ Ospring is the stable composition of the spring, frain is the 18 collectors were reset on 12 March 2018, 18 May 2018 and fraction of recharge from rainfall, δ Orain is the stable isotopic compo-

18 September 2018. Precipitation samples were decanted and sepa- sition of rainfall, fsnow is the fraction of recharge from snow, and δ 18 18 rated from the mineral oil before they were stored in refrigerated 2 ml Osnow is the stable isotopic composition of snow. Although the δ O glass vials with screw-caps. One bulk snow sample was collected from of snow likely varies with elevation in the Panamint Range, we choose the remnant snowpack near Thorndike Campground on 12 March to separate springflow using seasonal endmembers (e.g. summer rain 2018. This snow sample was melted within a sealed, clean 1 L sam- and winter snow) because we do not have sufficient data to assess pling bottle and then decanted into a smaller vial. The δ18O and δ2Hof stable isotope lapse rates during the winter and summer nor their all spring and precipitation samples were measured by the University impact on the partitioning. An unintended consequence of this deci- of California Davis Stable Isotope Facility using a Los Gatos Research sion is that the fraction of rain may be lower than estimated since Laser Water Isotope Analyzer V2. The reported precision is 0.3 ‰ for low-elevation snow may be heavier than high-elevation snow. We do, 18 2 18 δ O and 2.0 ‰ for δ H (SIF, 2018). The accuracy of the analyses is however, assess this uncertainty by varying the δ Osnow from −17.2 0.11 ‰ for δ18O and 0.54 ‰ for δ2H (based on multiple [n = 11] ana- ‰ (representing the lowest value measured in our study) to −14.5 ‰ lyses of known standards). All stable isotopic values are reported rela- (representing the highest value measured in our study). We do not use tive to Vienna Standard Mean Ocean Water (VSMOW). volume-weighted average stable isotopic values for precipitation in A local meteoric water line (LMWL) was created for the Panamint the separation. Range using the δ18O and δ2H of precipitation that was collected in Uncertainties in the fractions of recharge from snow and rain this study. The springs of the Panamint Range were then compared to were calculated following the work of Genereux (1998) and Liu et al. the LMWL and the global meteoric water line (GMWL; Craig, 1961). (2004). We modify the uncertainty equation from Liu et al. (2004) to: Since our precipitation collection was short and we only sampled the springs in the Panamint Range once, we assessed the δ18O and δ2H values of the Panamint Range springs and the LMWL by comparing 8 GLEASON ET AL.

TABLE 2 δ18O and δ2H values from precipitation collectors at Mahogany Flats Campground (2478 mrsl) and Thorndike Campground (2262 mrsl), and a fresh snow sample from Thorndike Campground

Collection period Season Sample name δ2H(‰) δ18O(‰) 10/14/2017–03/12/2018 Winter 2017–18 Thorndike Collector −123 −16.6 10/14/2017–03/12/2018 Winter 2017–18 Mahogany Flats Collector −130 −17.2 10/14/2017–03/12/2018 Winter 2017–18 Thorndike Fresh Snow −124 −16.9 03/12/2018–05/18/2018 Spring 2018 Thorndike Collector −107 −14.9 03/12/2018–05/18/2018 Spring 2018 Mahogany Flats Collector −104 −14.5 05/18/2018–09/18/2018 Summer 2018 Thorndike Collector −47.9 −7.76 05/18/2018–09/18/2018 Summer 2018 Mahogany Flats Collector −49.2 −7.71

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi W hihihi 2 2 2 the spring emergence (Frisbee et al., 2013). Chloride/ fsnow frain −1 fsnow = − xWCsnow + − xWC + − xWCspr ðÞCrain Csnow ðÞCrain Csnow rain ðÞCrain Csnow bromide ratios were calculated for all springs and only those − − ð4Þ springs with a Cl /Br less than 200 were used to estimate recharge by the chloride mass-balance method. We chose a ratio of 200 since Davis, Whittemore, and Fabryka-Martin − − where, Wfsnow is the uncertainty in the fraction of snow and rain. (1998) reports a Cl /Br range of 80–160 for clean, shallow 18 Please note that Wfsnow =Wfrain.Csnow is the average δ O of the snow groundwater that only reflects chloride from precipitation. For the endmember (−16.0 ‰) and was calculated as the average of all snow springs with a Cl−/Br− <200 (n = 10), we use the chloride mass- samples taken from the collectors (n = 5; shown in blue in Table 2). balance approach developed in (Frisbee et al., 2013) where MBR is 18 −1 Crain is the average δ O of the rain endmember (−7.7 ‰) and was cal- in units of mm year : culated as the average of all rain samples taken from the collectors − Cl : (n = 2, Table 2). Wcsnow is the standard deviation of the snow samples MBR = Precip × P ð5Þ Cl− PR collected in the Panamint Range (1.2 ‰) and was calculated as the spring average standard deviation of the five snow samples shown in

Table 2. Wcrain is the standard deviation of the rain samples collected where, ClPrecip is the maximum chloride concentration in precipitation. in the Panamint Range (0.1 ‰) and was calculated as the average ACl− concentration for precipitation of 0.6 mg L−1 was reported by standard deviation of the two rain samples shown in Table 2. Wcspr is the National Atmospheric Deposition Program (NADP) for nearby Fur- the standard deviation of the spring samples. This is a difficult value to nace Creek. However, our measured Cl− concentrations in precipita- provide since we do not have repeat samples of individual springs. tion more closely match the Cl− concentration of 1.3 mg L−1 which Furthermore, the standard deviation of all the Panamint Range springs was reported for the Nevada Test Site by Tyler et al. (1996). We use is 1.8 ‰; this describes the spatial variability of the δ18O of springs the higher value of 1.3 mg L−1 since it likely represents an upper limit − and may not be meaningful in the context of uncertainty for individual on the expected Cl in regional precipitation. Clspring is equal to the springs. However, as suggested in Genereux (1998), there is flexibility measured chloride concentration of the spring water, and PPR is the in what value is used for this parameter. Therefore, we assume that average annual precipitation of the Panamint Range (mm year−1). The − Wcspr is equal to the analytical uncertainty (0.3 ‰). If Wcspr is runoff term for Cl was omitted from Equation (5) based on two increased to 1.0 ‰, then it results in an overall increase in uncertainty assumptions: (i) runoff is usually short lived prior to infiltration in the of 4–6%. mountain-block and therefore does not acquire a significant Cl− con- centration and (ii) the volume of snowmelt runoff during the snowmelt season is large such that Cl− from dry deposition is diluted in runoff. 3.4 | Methods used to calculate amounts of There is very little data available to assess the variability of the recharge PPR term because the Panamint Range is ungauged and there have been few studies in the Range. Hunt, Robinson, Bowles, & Washburn To estimate the amount of recharge occurring in the Panamint (1966) measured precipitation at Aguereberry Point located in the Range, we used a chloride mass-balance approach (Aishlin & McNa- northern Panamint Range (11 S, 495701 mE, 4023709 mN) at an ele- mara, 2011; Frisbee et al., 2013; Russell & Minor, 2002) vation of 1961 mrsl. They report that the annual precipitation at this and compared those calculations to a derivation of the Maxey– elevation is 381 mm year−1. Webb, Steiger, and Turner (1987) incor- Eakin equation (Wilson & Guan, 2004). The advantage of the rectly state that this precipitation was measured at the “top of the chloride mass-balance approach is that it is specific to each Panamint Range” (p. 479). For comparison, PRISM calculates an annual spring but is applicable only if chloride is not added to the precipitation total of 188 mm year−1 at Aguereberry Point. We chose groundwater flowpaths by bedrock weathering sources or in to use the annual precipitation of 486 mm year−1 reported using GLEASON ET AL. 9

PRISM for Telescope Peak (see Section 2.3) since it is likely more rep- value of −93 ‰. The stable isotopic compositions of precipitation resentative of the amount of precipitation occurring along the crest of samples collected in the Panamint Range are reported in Table 2. the Panamint Range at elevations greater than 2500 mrsl. Equation (5) Snow samples (‘Winter 2017−18’ samples shown in Table 2) are ligh- was solved for all springs with Cl−/Br− <200 and then an average ter (more depleted) than spring waters and rainfall and are nearly iden- MBR was calculated from that group of springs. Jeton, Watkins, Lopes, tical to the snowpack sample collected in March 2018 (see ‘Snow near and Huntington (2005) report that PRISM estimates of precipitation Thorndike’ in Table 2). In comparison, the precipitation samples col- were within ±15% of the precipitation measured by the NWS and lected in May 2018 are comprised of late winter snow and early spring other agencies. Thus, we assume that annual precipitation at the rainfall and are isotopically heavier than the snow samples. Finally, the highest elevations in the Panamint Range likely varies between summer precipitation samples collected in September 2018 represent 413 and 559 mm year−1. only summer rain and are enriched in heavy isotopes. Since we only Maxey and Eakin (1949) provide an alternative calculation for have two sampling sites, there is insufficient data to quantify spatial MBR that is empirical in nature since it is based on an experimental variability or create an isotopic lapse rate. dataset from White River Basin, NV. The Maxey–Eakin method requires three steps: (i) divide a study area into distinct zones of mean annual precipitation (e.g. 30.5–38.1 cm, 38.1–50.8 cm, and so on), 4.2 | LMWL for the Panamint Range and (ii) apply a scaling factor to each precipitation band that accounts for comparison with regional LMWLs losses of water due to ET and surface runoff and (iii) sum the esti- mated recharge in each zone. It should be noted that the general form Figure 4 shows the relationship between the δ18Ovsδ2H composition of the Maxey–Eakin equation is used to calculate MFR, not MBR. of the Panamint spring waters. The spring samples are plotted against However, Wilson and Guan (2004) state that since the general form the GMWL (solid line in Figure 4) and the LMWL developed for the of the Maxey–Eakin equation accounts for losses due to direct runoff Panamint Range precipitation data (dash-dotted line in Figure 4). An and ET, we can assume that MFR equals MBR. Wilson and Guan additional LMWL derived from Friedman et al. (2002) based on precip- (2004) show that a power-law trend describes the relationship itation collected at Dante's View and Furnace Creek in Death Valley, between Maxey–Eakin estimated recharge for each precipitation zone CA is plotted for reference (Figure 4; see Table 3 for approximate and the midpoint of each precipitation zone. The equation, shown times of precipitation collection). The range of stable isotope values −1 below, is valid when Pm is less than 600 mm year : from Panamint precipitation collected the summer of 2018 (red box), –  winter of 2017 2018 (blue box), and late winter/early spring (purple −9 3:72 MBR =9× 10 × Pm ð6Þ box) are also included for reference. The majority of the spring water samples plot in the range of −14 to −12 ‰ for δ18O and −100 to −90 ‰ for δ2H, which indicates that winter snow and/or mixed −1 where, Pm is the mean annual precipitation (mm year ). This assump- tion is valid for the Panamint Range. Berger, Halford, Belcher, and Lico (2008) suggest that the Wilson and Guan approximation (Equation (6)) has one advantage over the original Maxey–Eakin method; it provides an estimate of recharge when Pm is less than 20.3 cm, albeit a small amount of recharge, whereas the scaling factor for the Maxey–Eakin method is assumed to be equal to zero (Maxey & Eakin, 1949). In addi- tion, Pohlmann, Campagna, Chapman, and Earman (1998) state that the Wilson and Guan approximation may be superior to the Maxey– Eakin method. They used stable isotopic techniques to show that sev- eral low-discharge springs in southern Nevada must be supported by recharge occurring in areas where Maxey–Eakin indicates that there is no recharge.

4 | RESULTS

4.1 | Stable isotope composition of springs

FIGURE 4 δ18 ‰ δ2 ‰ Results of the stable isotope analyses of the Panamint Range spring The O( ) and H( ) of springs in the Panamint Range. The red box represents the stable isotopic range of rain, the waters are reported in Table 1. The δ18O values in these spring waters blue box represents the stable isotopic range of winter snow, and the range from −14.2 ‰ to −7.7 ‰ with an average value of −12.6 ‰, purple box represents the stable isotopic range of late winter/early 2 while δ H values range from −104 ‰ to −53 ‰ with an average spring precipitation 10 GLEASON ET AL.

TABLE 3 Data used to create Owens valley (CA) LMWL LMWLs across the study area Sample location δ2H(‰) δ18O(‰) Time of sample collection Citation Lone Pine, CA −89 −12 October 1985 Friedman et al. (1992) Lone Pine, CA −60 −7 April 1986 Friedman et al. (1992) Lone Pine, CA −119 −16 October 1986 Friedman et al. (1992) Lone Pine, CA −30 −3 April 1987 Friedman et al. (1992) Inyokern, CA −106 −14 October 1986 Friedman et al. (1992) Inyokern, CA −37 −3 April 1987 Friedman et al. (1992) Bishop, CA −27 −4 Summer 1991 Friedman et al. (2002) Bishop, CA −107 −14 Winter 1992 Friedman et al. (2002) Bishop, CA −108 −13 Winter 1993 Friedman et al. (2002) Bishop, CA −109 −15 Winter 1994 Friedman et al. (2002) Death valley (CA) LMWL Dante's view −40 −5.7 Summer 1991 Friedman et al. (2002) Dante's view −103 −14.5 Winter 1991 Friedman et al. (2002) Dante's view −68 −8.2 Summer 1992 Friedman et al. (2002) Dante's view −97 −13.7 Winter 1992 Friedman et al. (2002) Dante's view −108 −14.1 Winter 1994 Friedman et al. (2002) Furnace creek −18 0 Summer 1991 Friedman et al. (2002) Furnace creek −75 −10 Winter 1991 Friedman et al. (2002) Furnace creek −69 −8 Summer 1992 Friedman et al. (2002) Furnace creek −71 −9 Winter 1992 Friedman et al. (2002) Furnace creek −51 −4 Winter 1994 Friedman et al. (2002) Spring mountains (NV) LMWL Not given −116 −16 Not given Ingraham et al. (1991) Not given −103 −14 Not given Ingraham et al. (1991) Not given −89 −12 Not given Ingraham et al. (1991) Not given −75 −10 Not given Ingraham et al. (1991) Not given −61 −8 Not given Ingraham et al. (1991) Not given −48 −6 Not given Ingraham et al. (1991) Not given −34 −4 Not given Ingraham et al. (1991 Not given −20 −2 Not given Ingraham et al. (1991) precipitation occurring in late winter/early spring may be primary Jaunat, Celle-Jeanton, Huneau, Dupuy, & Coustumer, 2013; sources of recharge for the springs. However, the amount of precipita- Winograd & Friedman, 1972). Post Office Spring shows strong evapo- tion collected over the winter was much greater than the amount col- ration effects as compared to two other basin springs, Warm Sulphur lected from March to May 2018 indicating that snow is more likely the Spring and Tule Spring, which do not appear to be heavily evaporated. primary source of recharge. The transition from winter precipitation to As a result, recharge estimates are not provided for Post Office Spring. spring precipitation (mixed snow and rain) is indicated by the shift to Wilson Spring plots near the red summer precipitation box in Figure 4 heavier isotopic compositions in spring. but it is not evaporated. The sample from Wheel Spring was flagged There are three outliers in the dataset: Post Office Spring, Wilson for spectral contamination by the analytical lab. This contamination is Spring and Wheel Spring. Post Office Spring emerges in the Panamint likely the result of residual 50% ethanol left in the sampling tube after Valley basin floor and flows through a meandering channel. We col- decontamination. As mentioned earlier, the tubing was lected the sample in a shallow pool in the channel and this sample is decontaminated after sampling at each spring by soaking the tubing in affected by evaporation. An evaporation line (see dotted line in ethanol. The tubing was then flushed prior to sampling at the next Figure 4) was created for Post Office Spring assuming that it evolved spring by pumping the water from the next spring through the tubing (fractionated) from an average snow composition (i.e. ‘Winter for 10 min. Wheel Spring has a very low discharge and we infer that 2017-18’ composition). This evaporation line has a slope approxi- the spectral contamination is likely due to incomplete flushing caused mately equal to 6 which is consistent with evaporation from an open by the longer time required to completely flush the tubing from the body of water (Coplen, 1993; Coplen, Herczeg, & Barnes, 2000; GLEASON ET AL. 11 low-discharge spring. Therefore, Wheel Spring is not included in Figure 5 shows the regional comparison of the stable isotopic Figure 4 and is omitted from further analyses. composition of the Panamint Range spring waters (excluding Wilson Spring and Post Office Spring) with the stable isotopic composition of other spring waters and LMWLs from across the southern Great Basin including Owens Valley, CA (light blue) and the Spring Mountains, NV (light green; see Table 3 for published data). Each region is plotted using coordinating colours that contrast them from the black Panamint spring dataset. The springs in Owens Valley, the southern Sierra Nevada, and the Inyo Mountains have the lightest stable isotopic com- position (Figure 5). Springs generally get isotopically heavier moving east from the Sierra Nevada and deeper into the rain shadow. Snow also tends to get isotopically heavier moving east from the Sierra Nevada (Table 3).

4.3 | Sources and fractions of recharge

The calculated fractions of recharge from snow and rainfall (and asso- ciated uncertainties) are listed in Table 4. The uncertainties shown in Table 4 represent the uncertainty calculated based on the assumed stable isotopic composition of our endmembers. Springs in the Pan- FIGURE 5 Comparison of the δ18O(‰) and δ2H(‰) of springs amint Range have a strong dependence on seasonal snowpack (with and local meteoric water lines (LMWLs) across the rain shadow of the the exception of Wilson Spring). Snow conservatively accounts for southern Sierra Nevada. The light blue triangles represent springs in between 57 (±9) and 79 (±12)% of recharge to the Panamint Range Owens Valley and the blue line is the LMWL for Owens Valley, the springs. The overall average fraction of snow in recharge is 67 ± 7%, light green triangles represent springs in the Spring Mountains and the except for Wilson Spring (less than 1 %). Wilson Spring (δ18O=−7.7 green line is the LMWL for the Spring Mountains, and the grey circles ‰ represent the springs in the Panamint Range and the grey line is the ) appears to be recharged almost exclusively from rainfall and has LMWL for the Panamint Range δ18O values consistent with rainfall (δ18O=−7.7 ‰). The relationship

TABLE 4 Sources of recharge and partitioning of recharge

Spring name Fraction of recharge from snow (%) Fraction of recharge from rain (%) Uncertainty (%)

Thorndike Spring 79 21 12 Jail Spring 77 23 12 Main Hanaupah Spring #2 72 28 11 Limekiln Spring 68 32 10 Apron Spring 67 33 10 High Noon Spring 68 32 10 Unnamed Panamint Spring C 68 32 10 Warm Sulphur Spring 64 36 10 Uppermost Spring 62 38 10 Unnamed Panamint Spring E 61 39 9 Lower Warm Spring B 60 40 9 Lower Warm Spring A 57 43 9 Main Hanaupah Spring #1 58 42 9 South Hanaupah Spring #3 57 43 9 Unnamed Panamint Spring F 58 42 9 Wilson Spring 1 99 4 Poplar Spring A 76 24 12 Tule Spring 70 30 11 Upper Emigrant Spring 69 31 11

Note. Wilson Spring (grey shading) is not included in the calculation of the average, minimum and maximum recharge. Uncertainty is estimated in percent. 12 GLEASON ET AL.

4.4 | Amounts of recharge

Estimates of MBR based on the chloride mass-balance method range from 12 mm year−1 (at an elevation of 800 mrsl) to 388 mm year−1 (at an elevation of 2434 mrsl; Figure 7). The average MBR is 91 mm year−1 using the chloride mass-balance method (Table 5). The elevation dependency found by creating a simple linear regression to the data presented in Figure 7 is described by: MBR (mm year−1) = 0.10 xz(m) – 67.8, R2 = 0.81 and p-value < .05 (where, z(m) equals the ele- vation of the spring emergence in meters). In comparison, 89 mm year−1 of MBR is estimated using the Wilson & Guan deriva- – FIGURE 6 Relationship between the estimated fraction of tion of the Maxey Eakin equation. The difference between the two recharge sourced from snow and mean elevation of spring emergence methods is small, however Wilson and Guan (2004) state that the relative to sea level. The blue dots represent the fraction of recharge Maxey and Eakin (1949) model is most applicable to the area it which 18 sourced from snow assuming that the δ O of snow is equal to −16.0 it was developed (i.e. it is empirical and site-specific). Thus, the chlo- ‰ (the average snow composition of this study). The red dashes ride mass-balance may provide the most realistic estimates of MBR in represent the fraction of recharge sourced from snow assuming that the Panamint Range. the δ18O of snow is equal to—17.2 ‰ (assumed to be either fresh snow or snow at elevations >3000 mrsl if the stable isotopic lapse rate is approximately −2.0 ‰ km−1). The green dashes represent the fraction of recharge sourced from snow assuming that the δ18Oof 5 | DISCUSSION OF RESULTS snow is equal to −14.5 ‰ (assumed to be late season snowpack or snow at elevations <2000 mrsl if the stable isotopic lapse rate is Springs emerging in the Panamint Range are recharged primarily by approximately −2.0‰ km−1) snowmelt although the fraction of recharge sourced from rainfall is not insignificant. For context, Winograd et al. (1998) reported that rainfall accounted for a third of the total annual precipitation in the Spring Mountains of NV but only provided about 10 percent of the recharge. Our estimates of the fraction of recharge sourced from snow are likely too low since using fresh snow (and even seasonally integrated snow) as an endmember can underestimate the true frac- tion of recharge from snow. The stable isotopic composition of snow changes within the snowpack due to sublimation and partial melting, and the isotopic composition of snowmelt changes prior to recharge due to evaporation and mixing in the soil zone (Beria et al., 2018; Earman et al., 2006 ; Frisbee et al., 2010). These processes tend to leave snowmelt recharge isotopically heavier and sometimes slightly evaporated compared to fresh snow (Earman et al., 2006; Frisbee et al., 2010). If the isotopic composition of snow becomes heavier, then snowmelt recharge should plot closer to the springs in Figure 4, and the estimated fraction of recharge sourced from snow should increase. For example, suppose that the snow endmember becomes 2 ‰ heavier (this value was chosen based on the snow evolution line − FIGURE 7 Relationship between the estimated MBR (mm year 1) observed in Frisbee et al., 2010), then the “evolved snow” endmember and elevation of spring emergence accounts for 75 (±15) to 104 (±20) percent of spring discharge. The stable isotopic composition of snow likely decreases with increasing elevation, thus the proportion of recharge from rain may between elevation and the fraction of recharge from snow is weak again be too large since low-elevation snow may have a higher 2 18 (Figure 6; fs = 0.0085 x z(m) + 55.7, R = .38, p-value < .001, where z δ O. We do not have sufficient field data to assess the stable isotopic (m) equals the elevation of the spring emergence), but in general, the lapse rate, however if we assume a reasonable lapse rate of −2 ‰ fraction of recharge from snow increases with increasing elevation. km−1 (Poage & Chamberlain, 2001), then we can vary the stable isoto- pic composition of fresh snow accordingly from −16.0 ‰ (used in our model and collected between 2200 and 2500 mrsl). Our snow samples ranged from −17.2 to −14.5 ‰ and this largely conforms to the assumed lapse rate. Table 6 shows the uncertainty associated with GLEASON ET AL. 13

TABLE 5 Data used to estimate groundwater recharge. Data in yellow shaded cells have Cl−/Br− greater than 200

Spring Name Elevation (m) Cl− (mg L−1)Br− (mg L−1)Cl−/Br− Recharge (mm year−1) Jail Spring 2434 3.28 0.024 137 193 High Noon Spring 1419 21.5 0.171 126 29 Main Hanaupah Spring #2* 1265 1.63 0.011 148 388 Poplar Spring A 1225 23.9 0.17 141 26 Limekiln Spring 1223 8.35 0.075 111 76 Unnamed Panamint Spring C* 1206 7.57 0.042 180 83 Wilson Spring 1195 11.7 0.078 150 54 Unnamed Panamint Spring E 963 30.9 0.2 155 20 Unnamed Panamint Spring F* 803 32.5 0.19 171 19 Lower Warm Spring A 755 25.9 0.13 199 24 Apron Spring 1606 18.3 0.07 261 35 Lower Warm Spring B 760 25.8 0.11 235 24 Thorndike Spring 2337 7.44 0.005 1488 – Uppermost Spring 1633 12.9 0.005 2580 – Main Hanaupah Spring #1* 1258 6.95 0.005 1390 – Upper Emigrant Spring 1231 38.8 0.005 7760 – South Hanaupah Spring #3* 1154 6.7 0.005 1340 – Post Office Spring 321 1520 2.21 688 – Warm Sulphur Spring 318 873 1.3 687 – Tule Spring -77 998 0.14 6931 –

Note. Thorndike Spring, Uppermost Spring, Main Hanaupah Spring # 1, Upper Emigrant Spring, and South Hanaupah Spring # 3 springs which have high Cl−/Br− due to Br− concentrations which were non-detects, so Br− was set equal to ½ the detection limit. Post Office Spring and Warm Sulfur Spring are interacting with evaporites in the emergence. Tule Spring is mixing with basin brines. The springs with high Cl−/Br− ratios were not used to calculate the average groundwater recharge.

TABLE 6 Uncertainty in Partitioning Spring Name fs (%) fr (%) Unc. (%) fs (%) fr (%) Unc. (%) of recharge; where fs is the fraction of Jail Spring 0.67 0.33 9 0.94 0.06 17 snow, fr is the fraction of rain, and Unc is uncertainty in percent Thorndike Spring 0.69 0.31 9 0.96 0.04 18 Unnamed Panamint Spring E 0.53 0.47 7 0.74 0.26 14 Unnamed Panamint Spring F 0.51 0.49 7 0.71 0.29 13 Wheel Spring 0.08 0.92 3 0.11 0.89 5 Apron Spring 0.58 0.42 8 0.81 0.19 15 Main Hanaupah Spring #2 0.63 0.37 9 0.88 0.12 16 Main Hanaupah Spring #1 0.51 0.49 7 0.71 0.29 13 South Hanaupah Spring #3 0.49 0.51 7 0.69 0.31 13 Wilson Spring 0.00 1.00 3 0.01 0.99 5 Lower Warm Spring A 0.50 0.50 7 0.69 0.31 13 Lower Warm Spring B 0.52 0.48 7 0.73 0.27 14 Uppermost Spring 0.54 0.46 8 0.76 0.24 14 Limekiln Spring 0.59 0.41 8 0.83 0.17 15 Unnamed Panamint Spring C 0.60 0.40 8 0.83 0.17 15 Warm Sulphur Spring 0.56 0.44 8 0.78 0.22 15

Note. The partitioning shown in the white column was created assuming that the δ18O of snow equals −17.2 ‰ and the δ18O of snow equals −7.7 ‰. The partitioning shown in the grey column was created assuming that the δ18O of snow equals −14.5 ‰ and the δ18O of snow equals −7.7 ‰. These values represent the lowest and highest the δ18O of snow, respectively, measured in the study. 14 GLEASON ET AL.

FIGURE 8 Map of National Land Cover Database (NLCD) land cover classes

changing the δ18O of snow to indirectly account for variability in the the mountain block (Figure 8). Groundwater is warmed due to heat δ18O of snow with elevation. The fraction of recharge from snow exchange processes after it recharges and circulates in the subsurface. decreases (and uncertainty decreases) by changing the δ18O of snow Heat transport in groundwater systems is governed by conduction to −17.2 ‰. In comparison, the fraction of snow increases (and uncer- and convection. In steep, mountainous terrain where topography- tainty increases) by changing the δ18O of snow to −14.5 ‰. We con- driven flow and deep circulation can occur, heat transport is primarily sider our estimated recharge fractions from snow using a δ18Oof facilitated by forced convection; circulation that is driven by recharge −16.0 ‰ to be minimum (conservative) estimates because it is at high elevations and discharge at lower elevations (Anderson, 2005; extremely challenging to obtain the true stable isotopic composition Saar, 2011). The effects of heat conduction from the surface are often of recharge in mountainous terrain. assumed to be negligible in mountainous terrain where the aquifer is Comparing spring water temperatures to seasonal environmental deeper than 10 m (Anderson, 2005; Manga & Kirchner, 2004). lapse rates provides insight into sources of recharge and subsequent Environmental lapse rates bounding the months of the western depths of circulation. The topographic relief and temperature gradient snow season of November, December, January, February and March are steep in the Panamint Range affecting local environmental lapse strongly indicate that snowfall is unlikely at elevations less than 1400 rates and the elevation zone where recharge is most likely to occur in mrsl and that the majority of snow occurs during December and GLEASON ET AL. 15

the elevated temperature of Lower Warm Spring A and Lower Warm Spring B. The elevation range over which recharge can potentially occur in the Panamint Range spans from the rain/snow transition elevation of ~1966 mrsl to the highest point in the range, Telescope Peak, at 3366 mrsl. Recharge is enhanced at the highest elevations since they are not densely vegetated (Figure 8). The sub-alpine zone (2287–2896 mrsl; Wauer, 1964) contains grassy montane meadows with Limber pine (Pinus flexilis). Bristlecone pine (Pinus longaeva) grow at higher ele- vations (2896–3201 mrsl; Wauer, 1964) and the very highest eleva- tions are rocky with little to no vegetation cover. Talus fields are

FIGURE 9 Temperatures of the Panamint Range springs are expansive and have little vegetation cover while most high-elevation plotted relative to the average local geothermal gradient. The blue rock outcrops are highly fractured. Our field observations indicate that circles represent mountain-block (MBR) and mountain-front (MFR) strong storms develop over the Panamint Range in the spring and fall springs, the yellow squares represent the basin springs emerging in and this may increase the potential for infiltration and recharge during Panamint Valley (Post Office Spring and Warm Sulphur Spring [Warm these rain events. The potential for recharge from rainfall may also be Sulfur Spring plots closer to the Warm Springs because it emerges enhanced during these seasons since evaporation rates are still rela- along a mountain-front fault and does not mix with MFR]), and the red diamonds represent the two anomalous springs (Lower Warm Spring tively low. However, rocky slopes located along the crest and montane A and Lower Warm Spring B). The surface temperature is assumed to meadows tend to have sparse vegetation but likely decreased infiltra- be equal to the temperature of the highest elevation spring (Jail tion rates. Therefore, we infer that the fraction of recharge from rain- Spring) and the average local geothermal gradient is equal to fall is likely small except for perhaps focused recharge along the talus 35.2Ckm−1 slopes. Springs emerging in the mid- to high-elevations of the Panamint January (Figure 3a). PRISM calculates 299 mm year−1 near Telescope Range are recharged by MBR. These springs primarily emerge at geo- Peak during the months of November, December, January, February logic contacts within the mountain block. By definition, this eliminates and March as compared to 169 mm year−1 for the remainder of the the possibility of MFR and MSR since these springs emerge well year when the effects of ET are also the highest. The temperatures of upgradient of the mountain front. Estimated MBR is quite variable all but two spring waters plot between the ELR for December (the col- across the mid-elevations of the Panamint Range, but in general, MBR dest month) and July (the hottest month) indicating that springs are increases with elevation of spring emergence (Table 5). MBR ranges receiving recharge consistent with cooler conditions (Figure 3b). After from 19 to 24 mm year−1 at elevations less than 1000 mrsl, while at recharge, the groundwater warms slightly as it circulates within the elevations greater than 1000 mrsl but less than 2000 mrsl, MBR mountain block (Figure 3b). The temperatures of springs in the Pan- ranges from 26 to 388 mm year−1. MBR ranges from 85 to amint Range, however, plot to the left of the line describing the geo- 193 mm year−1 at elevations greater than 2000 mrsl. We infer that thermal gradient (Figure 9); they are cooler than the geothermal MFR and MSR also support springs in the Panamint Range. The Pan- gradient. The surface temperature in Figure 9 is assumed to be equal amint Range is fault-bounded such that alluvial fans are short on the to the temperature of Jail Spring, one of the highest elevation springs. west side of the range and large alluvial fans coalesce into bajadas on The average geothermal gradient of the Panamint Range is the east. Warm Sulfur Spring and Post Office Spring both emerge on 35.2 ± 1.7Ckm−1 (Coolbaugh et al., 2005). Thus, we infer that the the western side of the Range. Warm Sulfur Spring emerges at a position of the MBR & MFR springs in Figure 9 (blue circles) represents mountain-front fault and is supported by MSR. Post Office Spring groundwater flowpaths which have not equilibrated with the local emerges at a fault at the terminus of the Pleasant Canyon alluvial fan, geothermal gradient (see Figure 1 of Saar, 2011). All of the MBR & thus this spring is supported by MFR on the alluvial fan and MSR at MFR springs in Figure 9 conform to a trendline described by: T the fault (Figure 2). Tule Spring emerges at the transition from the (C) = −0.0068 x z(m) + 26.6; where z(m) is elevation in mrsl, R2 = .88, bajada draining Hanaupah Canyon and Badwater Basin on the east p-value < .001 at 95% confidence. The two anomalous springs, Lower (Figure 2) and is supported by MFR. Tule Spring is surprisingly isotopi- Warm Spring A and Lower Warm Spring B, were sampled at their cally light for a basin spring (Table 1) and has a stable isotopic compo- source, which is located along a deep fault. The groundwater sition comparable to the headwater springs of Hanaupah Canyon flowpaths that support these two warm springs have circulated deeper (Main Hanaupah Spring # 2). Warm Sulphur Spring receives 58 percent in the mountain-block, but still have not reached equilibrium with the of its recharge from snow, yet this spring emerges over 2134 m below geothermal gradient. All of the springs in the Panamint Range are low- the snowline. Therefore, there must be some groundwater connectiv- volume, low-discharge type springs having cold (9C) to warm (34.4C) ity through the mountain block to these springs consistent with MSR. temperatures, thus we infer that the effects of gravitational potential We do not see evidence for enhanced evaporation at these springs. energy (Manga & Kirchner, 2004) are also negligible. Bedinger and Adjacent basins (Badwater and Panamint Valley) typically receive less Harrill (2012) also inferred that deep circulation was responsible for than 6 cm year−1 of precipitation per year compared to the high 16 GLEASON ET AL. elevations of the mountains, which can receive over 40 cm year−1. springs and will continue to affect other desert springs and their Thus, these three basin springs are dependent on recharge and runoff unique aquatic ecosystems. occurring in the mountain block since very little, if any, recharge Reductions in recharge are also expected in the scenario where occurs in the basin. more rain and less snow falls on the mountainous systems of the western U.S. (Easterling et al., 2017; Knowles, Dettinger, & Cayan, 2006). It is extremely unlikely that groundwater recharge will 6 | CONCLUSIONS remain stable or actually increase in this scenario (Niraula et al., 2017). The water balance of mountainous systems is hypsometric This study was conducted to identify the sources of recharge for meaning that components of the water balance are elevation springs in the Panamint Range, Death Valley, CA. Specifically, the fol- dependent. Goulden et al. (2012) discuss the hypsometric nature of lowing questions were addressed: (i) what is the source of recharge the water balance in the Upper Kings River basin located in the that supports springs in the Panamint Range (is recharge sourced pri- southern Sierra Nevada. In their work, the difference (P-ET) marily from snow or rain), (ii) where is the recharge occurring (moun- between precipitation (P) and modelled ET increases with increasing tain-block, mountain-front or mountain-system) and (iii) how much elevation above ~2500 m (see Figure 8 of Goulden et al., 2012). recharge occurs in the Panamint Range? With respect to question (i), This implies that there is more effective precipitation (P-ET) avail- the comparison between δ18O and δ2H values of the spring waters able at higher elevations and that this water must be partitioned with precipitation collected on the Panamint Range indicates that the between surface runoff and groundwater recharge. The amount of springs are predominantly recharged by high-elevation winter precipi- effective precipitation at high elevations is critically important tation (snowmelt) rather than summer rain, although the fraction of because, in a warming climate, vegetation is expected to expand recharge sourced from rainfall is not insignificant. The fraction of upslope to higher elevations, which have been largely vegetation- recharge derived from snow ranges from 56 to 79 percent, although free since the Last Glacial Maximum. When this occurs, P-ET will this is a conservative estimate. With respect to question (ii), springs decrease implying that less water is available for groundwater emerging in the mountain block are recharged by MBR, while basin recharge, and that recharge will occur over a potentially smaller springs are recharged by MFR (Tule Spring), MSR (Warm Sulphur area. These scenarios do not bode well for the springs of the Pan- Spring), and a combination of MFR and MSR (Post Office Spring). Tule amint Range. Spring has an isotopic composition similar to the high-elevation The vulnerability of desert springs to climate change in the study springs in Hanaupah Canyon and is supported by recharge from snow- area and worldwide is controlled by their recharge source, recharge melt (70%). Warm Sulphur Spring receives 64% of its recharge from rate, aquifer volume, and aquifer response time. The dependence of snow, yet it emerges over 2134 m below the snowline. Finally, with the Panamint Range springs on recharge from a relatively small (thin) respect to question (iii), we estimate that the Panamint Range receives seasonal snowpack and inferred shallow circulation depths increases between 12 (at an elevation of 800 mrsl) and 388 mm year−1 (at an their vulnerability to the effects of climate change in the western elevation of 2434 mrsl) of MBR or on average 91 ± 117 mm year−1 of U.S. In fact, during the field campaign we discovered that several recharge. This is equivalent to ~19.4% of total annual precipitation. springs were dry which had been previously sampled by Don Sada in Springs in the Panamint Range are supported primarily by the late 1990s and early 2000s, and by King and Bredehoeft (1999). recharge from high-elevation snow with much smaller contributions of Changes in recharge will ultimately impact groundwater flowpath dis- rain. The importance of snowmelt recharge cannot be overemphasized tributions, mean residence times of springs, and geochemical pro- given the location in the hyperarid rain shadow of the southern Sierra cesses. These changes, in extension, will affect the permanence and Nevada. The springs emerging in the Panamint Range depend on a ecosystem integrity of other springs in the Panamint Range in the source of recharge that is extremely susceptible to climate change. future. Quantifying these fundamental relationships will improve our Mote and Sharp (2016) and Mote, Li, Lettenmaier, Xiao, and Engel understanding of the processes and metrics, which define the perma- (2018) mapped changes in snow water equivalent (SWE) at 669 snow nence or vulnerability of desert springs in the U.S. and worldwide, course stations located across the western U.S. While they did not especially those springs reliant on snowmelt recharge. include SWE data from the Panamint Range or adjacent mountain ranges, their data show substantial changes in SWE in the nearby ACKNOWLEDGMENTS Sierra Nevada and in mountains along the Mogollon Rim in Arizona Funding for this research was provided by the National Science Foun- where the SWE has decreased by as much as 80%. Given its location dation Grant EAR 1516127 and 1516698. Additional support for Car- in the rain shadow of the southern Sierra Nevada, we expect similar, olyn Gleason's fieldwork was provided by the Hydrologists Helping perhaps more severe, impacts to SWE in the Panamint Range. If this is Others (H20) and Darrell Leap Hydrogeology graduate student true, then reductions in SWE and reductions in the duration of snow research grants through the Department of Earth, Atmospheric and cover of the magnitude documented in the Sierra Nevada and Mogo- Planetary Sciences at Purdue University. We thank Josh Hoines, llon Rim will severely impact the springs of the Panamint Range. 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