Mineral mapping in the Pyramid Lake basin: Hydrothermal alteration, chemical precipitates and geothermal energy potential

Remote Sensing of Environment 114 (2010) 2297–2304

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Remote Sensing of Environment j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / r s e

Mineral mapping in the Pyramid Lake basin: Hydrothermal alteration, chemical precipitates and geothermal energy potential Christopher Kratt a,⁎, Wendy M. Calvin b, Mark F. Coolbaugh b a b

Desert Research Institute, 2215 Raggio Parkway, Reno, NV 89512, United States Arthur Brant Laboratory for Exploration Geophysics and the Great Basin Center for Geothermal Energy, MS-172, University of Nevada Reno, Reno, NV 89557, United States

a r t i c l e

i n f o

Article history: Received 23 January 2009 Received in revised form 30 April 2010 Accepted 2 May 2010 Keywords: Geothermal Remote sensing Hyperspectral Pyramid Lake Walker Lane Nevada Tufa Evaporites

a b s t r a c t Geothermal resources exist on the Pyramid Lake Paiute Tribal Lands (PLPTL) in northwestern Nevada. We compiled numerous indicators of these resources into a geographic information system along with concurrent investigative results. This effort required acquisition and analysis of spaceborne multispectral and airborne hyperspectral remote sensing data for early-stage geothermal exploration. We identified minerals such as alunite, kaolinite, and montmorillonite through analysis of hyperspectral data indicating regions of hydrothermally altered rock associated with areas of geothermal potential. Tertiary volcanic and granitic rocks also contain these indicator minerals. Quaternary environments displayed gypsum-bearing evaporite crusts that we postulate were deposited by sulfate-rich thermal waters. Throughout the PLPTL, tufa towers and tufa shoreline deposits are extensively distributed as remnants of paleo-lake Lahontan. Based on measured spectra of calcium carbonate, we mapped tufa towers elucidating the strike direction of associated faults. Additionally, we correlated remotely-derived maps of shoreline tufa deposits with climate-related changes in lake level. Our mapping results helped guide detailed exploration efforts to areas with the most geothermal potential. © 2010 Elsevier Inc. All rights reserved.

1. Introduction High temperature springs and geothermal potential in the region surrounding Pyramid Lake, Nevada were noted as early as the 1960s, particularly near the Needles Rocks tufa formation (Garside & Schilling, 1979) (Fig. 1). Geothermal potential on the Pyramid Lake Paiute Tribal Lands (PLPTL) is considered to be high based on existing evidence of warm and hot springs, location of the lake along a major fault trend, and other known producing geothermal systems in the region along with the 3.6 MW San Emidio geothermal plant to the northeast of tribal lands. A detailed assessment of geothermal potential of the PLPTL was undertaken by the Great Basin Center for Geothermal Energy through the U. S. Department of Energy's GeoPowering the West program. We initiated the reconnaissance portion of phased exploration with acquisition of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spacecraft data. We also collected HyVista Corp. HyMap imaging spectroscopy data by an aerial survey, covering the PLPTL. Using these data and others, we assembled a geographic information system (GIS) database including 1) well and spring locations, 2) drill hole and well temperature-gradients, 3) magnetic and gravity data, 4) nighttime Landsat thermal imagery, 5) shallow temperature data, 6) earthquake locations, 7) Quaternary fault locations,

⁎ Corresponding author. E-mail address: [email protected] (C. Kratt). 0034-4257/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.rse.2010.05.006

8) topographic and aerial photographic base maps, and 9) hyperspectral imagery and derived mineral maps. Synthesis of these geothermal indicator data sets is provided by Coolbaugh et al. (2006). In this paper, we present detailed analysis of ASTER and HyMap data sets used in that study. The derived geothermal mineral indicator maps suggest promising sites for further exploration. 2. Geologic background The Pyramid Lake basin is located within the Walker Lane Belt (WLB) system of northwest-striking right-lateral faults that generally parallel the eastern side of the Sierra Nevada mountain range. The WLB presently accounts for 15–25% of the motion between the North American and Pacific Plates (Thatcher et al., 1999). Offset movement in the southern WLB is between 50 and 100 km and decreases to ∼20–30 km in the northern WLB where the study area is located. GPS-geodetic surveys (Kreemer et al., 2006) and structural evidence (Faulds et al., 2005) indicate that strain is partitioned into the Basin and Range from the northern WLB. Neotectonic faults on the Pyramid Lake reservation are characteristic of strain transfer relationships in the northern Walker Lane (Faulds et al., 2006). The northwest-striking, right-lateral Pyramid Lake fault (Fig. 1) extends southward more than 45 km and shows evidence of at least four different earthquake events in the past 15 ky (Briggs & Wesnousky, 2004). This fault accounts for 5–10 km of offset in the northern Walker Lane Belt (Faulds et al., 2005) as strain is transferred to N-NNE-striking normal faults to the north of Pyramid Lake (Faulds et al.,

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sublacustrine springs, and paleo-shorelines where tufa forms a hard coating on surface materials that can be greater than 1 m in thickness. Sublacustrine tufa towers may indicate that structural control was aligned with identified faults (Benson, 1994; Hancock et al., 1999; Kratt et al., 2005). A series of structurally controlled tufa towers stand up to 90 m tall at the northern edge of Pyramid Lake where both spring and well waters can be found at boiling temperatures. Pyramid Rock, an island in the central part of the lake, is another tall tufa tower where a 97 °C spring issues from its base (Coolbaugh et al., 2006). Numerous other tufa towers, tens of meters tall, are found around the margins of the lake and adjacent basins, in addition to prolific tufa encrustations on paleo-shorelines. 3. Data sets and processing methods

Fig. 1. Shaded relief image shown with generalized geologic map modified from Bonham and Papke (1969) and approximate locations of other areas referenced in the text, dashed line is boundary of area imaged by the hyperspectral survey.

2006). The Olinghouse fault (Fig. 1) is a northeast-striking, left-lateral fault that can be traced for 25 km and has ruptured at least twice during the past 4 ky (Briggs & Wesnousky, 2005). Other, less active, predominantly N-NW-striking faults offset mostly east-dipping Tertiary basalts, rhyolite, lacustrine deposits, and limited metamorphic outcrops (Bonham & Papke, 1969). Association of the northern WLB with the Pyramid Lake basin promotes crustal dilation and deeper penetration of fluids along these steeply dipping faults (Faulds et al., 2005). This structural relationship enables increases in higher local heat flux and, therefore, increased potential for geothermal energy production (Faulds et al., 2005). Pyramid Lake is the largest of the few remaining vestiges of Pleistocene Lake Lahontan that once covered 22,500 km2 during its high stand at ∼13 ky (Adams & Wesnousky, 1999). The presence of Lake Lahontan gave rise to the prolific deposition of tufa in the region. These calcium-carbonate deposits are precipitated when calcium-rich spring waters mix with atmospherically derived CO2 dissolved in lake water (Coolbaugh et al., 2009). The mixing zone commonly occurs at

Due to the size of the PLPTL (∼1800 km2), we employed remote sensing data sets to provide a general survey of the area as well as direct field reconnaissance and mapping to the sites with the highest geothermal potential. The ASTER instrument on the NASA Terra satellite provides images in 14 wavelength channels from the optical to thermal infrared (Yamaguchi et al., 1998). Our analysis focused on the combination of visible/near-infrared (VNIR; 0.5–0.8 µm) and short-wave infrared (SWIR; 1.6–2.4 µm) channels. The three VNIR channels are acquired at a spatial resolution of 15 m/pixel spatial resolution and the six SWIR channels at 30 m/pixel. The VNIR and SWIR data were analyzed separately to provide initial surface cover and thematic maps. We used the AST-07 at-surface reflectance data product provided by the USGS Land Processes Distributed Archive Center, which provides on demand processing of ASTER high-level data products (http://asterweb.jpl.nasa.gov). We selected an ASTER scene from 6/04/04 for the similar seasonal coverage to that of the hyperspectral aerial survey described below. Eighty percent of the reservation was imaged by the ASTER scene, with minimal cloud cover. Past analysis has shown that simple color composites and band ratios can be used to refine targets for detailed analysis (e.g. Rowan & Mars, 2003). We applied decorrelation stretches (Gillespie et al., 1986) to various VNIR and SWIR band combinations to help identify areas of hydrothermally altered rock and tufa deposition. The HyMap sensor is an airborne imaging spectrometer flown by HyVista Corporation that measures radiance in 127 contiguous channels with 13–17 nm sampling intervals that span the 0.45–2.5 µm range. We acquired more than 2000 km2 of hyperspectral data over the PLPTL on Sept. 23, 2004 from an approximate altitude of 2500 m above ground level with spatial resolution of 5 m/pixel. Twenty-six overlapping flightlines were acquired, and each flightline was approximately 2.2 km wide by at least 60 km long. HyVista used in-house instrument calibration and atmospheric modeling routines to deliver calibrated atsurface reflectance data. For spectral analysis, we individually processed each flightline by masking the lake and then using statistical methods described by Green et al. (1988) to reduce spectral coherence and noise, as well as enhance identification of surface spectral endmembers. These methods follow those successfully used by others (e.g. Kratt et al., 2005; KennedyBowdoin et al., 2004; MacKnight et al., 2004; and Martini et al., 2003) to identify unique mineral signatures associated with geothermal systems. Data processing used algorithms found within the commercial software ENVI®, but relied on our previous experience analyzing this type of data to deliver high confidence map products. Unique spectral signatures identified in the airborne image data were corroborated with field and laboratory analyses. Due to variation in sun angle and flight direction, we processed each flightline separately. Our analytical methods relied on a series of principal component transforms that segregate noise and concentrate unique elements of the data cloud into low order components (Green et al., 1988). We visually inspected these “Minimum-Noise Fraction”

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images for spatial coherence and subset to those deemed to be the strongest contributors to real-scene variance. After reducing dimensionality of the data set to twenty channels, we used random data cloud projections into n-dimensional space to identify pixels that appeared extreme and may have represented unique mineral surface components (Kruse et al., 1993). For context, we used a color-infrared composite while manually examining the full-range reflectance spectra of extreme pixels. This allowed immediate exclusion of vegetation, man-made objects, data artifacts, or other spectra that were not the primary focus of this study. Training areas were established for pixels the spectra of which visually matched library reference spectra (Fig. 2) of geothermal indicator minerals or that were recognized as possible mineral mixtures of interest. Spectra from these training areas were averaged to create high confidence end member training classes that were then used in a mixture-tuned, matched-filter (MTMF) (Boardman et al., 1995) processing routine applied to all flightlines. MTMF provided a gradational scale for every pixel in the scene where the similarity to the endmember training class was given a value from 0 (low) to 1 (high). Thresholding these similar images provided an initial map of mineral distribution. We identified potential high purity mineral areas and field checked using multiple site visits with a field spectrometer. Samples were collected and mineralogically characterized through spectral laboratory measurements as well as validated using X-ray diffraction analyses. After completing field observations, we adjusted MTMF thresholds so that

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final mineral maps would represent only those pixels with the best spectral matches to the target spectra. We created mineral maps of sulfates, phyllosilicates, alunite, kaolinite, montmorillonite/illite, chlorite, and calcium carbonate using the HyMap data. These maps were converted to vector products for the incorporation into the GIS database. By combining surface distribution of minerals with information available in the GIS database, we were able to consider mineral outcrops in their structural context, as they might relate to geothermal activity. 4. Results and analysis 4.1. ASTER Analysis of ASTER data using a decorrelation stretch algorithm called attention to several regions of altered rock (Fig. 3). A decorrelation stretch applied to bands 4, 6, and 9 (spectral ranges [µm] 1.60–1.70, 2.18–2.22, and 2.36–2.43) provided the most robust results for interpretation by rendering zones of altered rock bright red. This appearance was due to high reflectance in band 4 and lower reflectance in bands 6 and 9 where phylosillicates and alunite display strong absorption features. Three visually apparent areas of altered rock were located on the lower slopes of the Lake Range, Adobe Springs, and patches in the Hartford Hills formation of the Pah Rah Mountains. Two

Fig. 2. Example training area spectra compared with United States Geological Survey (USGS) library reference spectra (Clark et al., 2003) shown for the 2.0–2.45 µm region only. The Hymap and reference spectra shown above are resolved with 27 and 36 channels, respectively.

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Fig. 3. Decorrelation stretch image using ASTER bands 4, 6, and 9. Hydrothermally altered rocks appear red and were distinguished from vegetation, also appearing red, by using the false-color VNIR portion of the image.

anomalous zones identified with ASTER in the Lake Range corresponded to areas where kaolinite, montmorillonite/illite, and alunite were mapped with the HyMap data. Altered rock associated with a similar mineral assemblage near Adobe Springs also stands out in the transformed image. The southernmost anomaly within the Lake Range was related to the Big Basin silver prospect where mostly Miocene age volcanic rocks have been propylitically altered to chlorite (Bonham & Papke, 1969). The northern anomaly within the Lake Range was part of the same package of Miocene volcanic rocks and also showed less intense propylitic alteration. Vegetation in the decorrelation stretched image also appeared bright red but could be discerned from altered rock by comparison with the false-color VNIR portion of the image. All areas of altered ground that were identified by the ASTER data alerted us to where associated minerals were likely to be identified with hyperspectral data. Although it was possible to expand ASTER mineral mapping, ASTER spatial and spectral resolution limits the number of minerals and spatial detail that can be achieved, thus more detailed hyperspectral mineral mapping is discussed below. 4.2. HyMap Analysis of HyMap data, with its higher spatial and spectral resolutions, led to mapping of numerous individual outcrops and mineral exposures using endmember spectral characterizations (Fig. 4).

Fig. 4. Hyperspectral mineral maps of the entire study area.

These results were further validated with field and laboratory spectral measurements. Phyllosilicates, such as montmorillonite/illite and kaolinite, were the most spatially abundant. Kaolinite was distinguished by a secondary spectral absorption shoulder at 2.16 µm along with the stronger feature at 2.2 µm. Many of these same spectra had some hematitic component, and our final mapping results reflect a distribution of moderate to high purity clay content. We found several high purity alunite outcrops primarily due to strong absorption at 2.17 µm with a less obvious shoulder at 2.2 µm and absorption near 1.7 µm. Montmorillonite and illite were grouped together as a mineral class, however, because of similar spectral features within these data at 2.2 µm. This spectral ambiguity is common to many oxygen–hydrogen (OH) ion bearing phyllosilicates, so in this paper, montmorillonite and illite are placed into the class “montmorillonite/illite.” 4.2.1. Hydrothermally altered rock Previous studies have shown that the presence of sulfates and clays can be markers of hydrothermally altered rock within regions of known thermal activity (e.g. Dalton et al., 2005; Kratt et al., 2005, 2009; Vaughan et al., 2005; Vaughan & Calvin, 2005). Such alteration

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may be associated with geothermal systems or relic hydrothermal alteration caused by volcanic activity or contact metamorphism. Most of the outcrops discussed thus far are topographically high, unrelated to Holocene fault structures, and unlikely to be close to a near-surface water table. Therefore, we did not consider these regions as candidate geothermal resource zones but considered it important to validate our mineral identifications to establish detection thresholds in the data and have confidence in mapping results elsewhere on the PLPTL. Alternatively, we identified several high priority geothermal targets using the hyperspectral data. These included a large sulfate deposit (green) (Figs. 1, 4, and 5) in the Smoke Creek Desert and a smaller but intriguing sulfate outcrop near the Truckee River tufa towers at Astor Pass (light purple) and also west of the Smoke Creek Desert outcrop, as well as clay minerals mapped along the trend from Needles Rock to Astor Pass (Figs. 1, 4, and 5). Elsewhere in the study area, phyllosilicate and alunite outcrops generally were found to be associated with rock altered by hydrothermal fluids, contact metamorphism, and/or deuteric weathering processes (Fig. 4). Montmorillonite/illite clays were most abundant in the Pah Rah Mountains where Mesozoic granitic rocks are uncomformably underlying rhyolite of the Hartford Hill formation that hosts the Pyramid and Olinghouse mining districts (Bonham & Papke, 1969). The most spatially abundant areas of alunite we found were in the Tom Anderson Canyon area near the southern end of the lake, hosted by the same rhyolite (Figs. 1 and 4). Alunite and kaolinite also were mapped at the north end of the lake on the eastern side of the Virginia Mountains in the Adobe Springs area (Figs. 1 and 4). Miocene intermediate to mafic volcanics of the Pyramid Sequence at this location likely were altered by a similar granitic intrusion seen in other nearby mountain ranges. To the north of the lake, we identified abundant outcrops of montmorillonite/

Fig. 5. Hyperspectral color-infrared composite image, vegetation appears red. Gypsum crusts and tufa towers shown in relationship to thermal springs, Quaternary structures from the USGS Quaternary faults data base (2003), and shallow temperature measurements from Coolbaugh et al. (2006).

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illite and kaolinite in the Fox Range that bounds the eastern side of the Smoke Creek Desert (Figs. 1 and 4). Here, meta-sedimentary rocks of the Mesozoic Nightingale sequence likely were altered by intruding granodiorite associated with the Cottonwood gold district. An outcrop of montmorillonite/illite on the northeast tip of Marble Bluff also was part of the Nightingale Sequence (Figs. 1 and 4). On the western flanks of the Lake Range, typically at elevations below 1706 m, we mapped montmorillonite/illite and sometimes kaolinite in the Pyramid Sequence. Alunite was present with montmorillonite/illite around the Big Basin silver prospect in the west central part of the Lake Range (Figs. 1 and 4). Hydrothermal alteration in Big Basin and along the rest of the Lake Range is related to an intrusive diorite porphyry (Bonham & Papke, 1969). Directly to the north end of the lake in the Terraced Hills are Pliocene basalts that dip to the east and are dissected by high angle, west-dipping faults (Vice et al., 2007). Here, alteration has produced several kaolinite/halloysite outcrops with possible mixtures of other clays that cover between 50 and 150 m2 and were readily identified in the HyMap data (Figs. 1, 4, and 6). 4.2.2. Evaporites and chemical precipitates Evaporite deposits are widespread on playas throughout the Great Basin, including this study area. Many evaporite minerals display unique spectral features in the SWIR, although the presence of halite is not remotely mapped given a lack of spectral features (Crowley, 1991). Given the presence of molecular water (Hunt, 1977), gypsum has strong and diagnostic spectral features in the 2.0–2.5 µm region and we found gypsum in several regions. Gypsum can be concentrated at the surface by diffuse capillary evaporation of geothermal waters that are inherently rich in sulfur. The same mechanism can precipitate gypsum from non-geothermal waters that have re-mobilized sulfur from shale or lacustrine deposits. Gypsum crust in the Smoke Creek Desert trended NNE for more than 3000 m and showed a close correlation with young fault scarps (Fig. 5).

Fig. 6. Mineral maps in the Astor Pass area.

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The fault zone was about 18 vertical meters above the playa surface, and most of the outcrop seems to be in the hanging wall approximately 1.5 km from the playa's edge. Gypsum also forms in places along the playa edge and parallel to the outcrops along the fault zone. Several warm springs and wells with surface temperatures up to 49 °C are located between the fault zone and the playa. Geothermometer temperatures from the spring and well waters exceed 150 °C at depth (Coolbaugh et al., 2006). Discharge from these springs and nearby wells may be responsible for subsidence fissures that occur in the footwall. We propose that sulfate-rich geothermal waters are upwelling in the fault zone leaving behind gypsum crust following evaporation. Gypsum also was mapped on the western side of Lake Winnemucca, but field validation performed more than six months after the data were acquired did not find gypsum. At a different location, a discontiguous gypsum outcrop covering less than 41 m2 stood out near the Truckee River corridor adjacent to the base of the Truckee Range (Fig. 4). Field validation revealed that evaporite deposits were forming on horizontally bedded lacustrine deposits. A nearby 27 °C spring, also along the Truckee River, could originate from the same sulfate-rich waters that flow laterally after intersecting an impermeable layer in the lacustrine deposits, forming an evaporite crust at the outcrop. Again, the image spectra showed convincing matches to gypsum that were not supported by later field measurements. Tufa deposits were identified widely throughout much of the study area. They were commonly found from lake level up to about 1310 m elevation near the Lake Lahontan paleo high stand. Tufa outcrops included both shoreline deposits from past higher lake levels and structurally controlled deposits that may indicate present geothermal potential. Carbonate displays a strong and obvious absorption feature at 2.33 µm, but hyperspectral data cannot differentiate among formation mechanisms. In addition to mapping some of the obvious tufa towers on the reservation, we also were able to identify less apparent tufa towers. It was then easier to consider the relationship of sublacustrine tufa with other spatial data across the entire study area. Some structural inferences have been made previously based on distribution of tufa towers, such as at Needles Rocks. Another group of tufa towers is situated in an apparent range-front step-over approximately 1.2 km west of the large gypsum anomaly previously discussed (Figs. 4 and 5). Here, a Bouguer gravity anomaly suggests the presence of horse-tailing faults and a possible mini-graben in the subsurface underneath the gypsum outcrop and tufa locations. A temperature survey using 2 m deep auger-holes (Coolbaugh et al., 2006) outlined a shallow temperature anomaly with peak values near the tufa towers first identified with the remote sensing data. The shallow temperatures range from b16 °C in background areas to N22 °C near the tufa towers. One exploration model involves thermal waters rising within the 600 m step-over in the range-front fault to form hot springs and tufa towers during the time of Lake Lahontan (Coolbaugh et al., 2006). These same thermal waters likely are responsible for precipitation of gypsum crusts as they migrate directly down the hydrologic gradient from the tufa towers. Similarly, near Astor Pass northwest of Pyramid Lake (Figs. 4 and 6) another set of remotely identified tufa towers marks the intersection of two faults (Vice et al., 2007) that coincides with the presence of a shallow temperature anomaly outlined by a 2 m survey. Subsequent drilling of temperature gradient wells yielded temperatures as high as 94 °C within 70 m of the surface (Vice et al., 2007). In addition to the tufa outcrops previously discussed, we remotely mapped tufa towers and paleo-shoreline tufa throughout the study area in significantly more detail than reported by other authors (Fig. 4). The Nightingale sequence is the only formation in the study area with carbonate units, yet these rocks did not display a strong carbonate spectral response, possibly due to lack of purity or presence of mineral coatings. In contrast, tufa rocks displayed strong absorption at 2.33 µm that allows them to be readily identified with remote sensing data. Our first goal was to differentiate sublacustrine and shoreline tufa, but these two types of tufa are not spectrally distinct. Therefore, we made numerous field visits

around basin margins to determine if tufa outcrops were sublacustrine or shoreline in origin. Where the genesis of some towers was less obvious, we inspected the base for evidence of preexisting non-carbonate rock under a tufa coating. We relied upon these field observations to separate the remote sensing carbonate maps into shoreline and sublacustrine tufa. In some cases, the latter may be related to upwelling geothermal fluids as discussed previously. Our next goal was to quantify the distribution of shoreline tufa with respect to elevation, slope, and aspect to help better understand and predict where shoreline tufa occurs elsewhere in the Lahontan basin. We used a 10 m digital elevation model combined with the hyperspectral shoreline tufa map for GIS analysis. We correlated shoreline tufa distribution with significant historic lake levels. For example, Fig. 7 shows that the greatest amount of shoreline tufa relative to the total land area is greatest between 1180 and 1185 m. This elevation corresponds to the Mud Lake (Lake Winnemucca) slough sill. When Pyramid Lake reached ∼1183 m, lake level remained relatively stable while water spilled over the sill until it filled Lake Winnemucca to the same level (Benson, 1994). While Lake Winnemucca was filling, shoreline tufa in the Pyramid basin had the opportunity to proliferate. Slopes that average b5%, where tufa was mapped at this same elevation interval, also may be a contributing factor to strong tufa development. Some of the most abundant shoreline tufa outcrops occur at several different intervals and may suggest periods of climate stability that maintained relatively static lake-level elevations. An alternative explanation or contributing factor may be that slopes on which shoreline tufa occur at elevations up to 1195 m are less than 10%. Another possible correlation may exist near 1308 m where Lake Lahontan began spilling over the Adrian Valley sill into the Walker Lake basin. There is a slight increase in the amount of shoreline tufa at this elevation and a decrease in slope, relative to the adjacent elevation ranges (Fig. 7). This relationship could be associated with tufa development on a terrace that was forming while the Walker Lake basin was being filled. There are two other significant sills at ∼ 1208 m and ∼ 1265 m but no apparent correlation with tufa distribution exists. The average slope on which shoreline tufa occurs at a particular elevation band generally increases with increasing elevation without necessarily showing a corresponding decrease in shoreline tufa. Fig. 7 also reveals that shoreline tufa development is most prolific on more southerly facing aspects. This distribution pattern may be explained by the inverse relationship of calcium-carbonate solubility and temperature. Rocks on more south-facing paleo-shorelines aspects would be subject to increased solar heat loading and therefore possess greater potential for calcite precipitation. 4.3. Correlations with geothermal energy potential The ability to detect hydrothermally altered rock, evaporates, and chemical precipitates with remote sensing made it possible to develop models of geothermal fluid flow from which information on temperatures and possible locations of underlying geothermal reservoirs was derived. Advanced argillic alteration minerals, such as kaolinite and alunite, commonly form at or near the surface above upwelling plumes of geothermal waters (Henley, 1985). The presence of kaolinite and alunite indicates acidic conditions which are made possible by boiling geothermal groundwater at depth. Steam generated by boiling tends to be acidic because of preferential partitioning of volatile solutes such as H2S and HCl into the vapor phase (Robb, 2005). Ascendancy of those gases to the near-surface environment leads to cooling and subsequent condensation, oxidation, and mixing with shallow groundwater to form acidic, “steam-heated” groundwater which alters bedrock to produce kaolinite and alunite (Henley, 1985). Therefore, the existence of kaolinite and alunite can imply existence of relatively high-temperature waters at depth (≥100 °C). Because the ascending gases are less dense than water, they tend to rise vertically; and thus advanced argillic alteration (kaolinite and alunite) tends to lie proximally above thermal upwelling zones.

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Fig. 7. Spatial distribution of shoreline tufa with respect to elevation and slope (top), and aspect (bottom).

Detection of evaporates and chemical precipitates with remote sensing can help complete a model of possible geothermal fluid flow in the subsurface. The unboiled fraction of geothermal groundwater, because of its higher temperature compared to most groundwater, is normally less dense and more buoyant, and thus tends to rise to the top of the groundwater table, where it can flow laterally long distances until the groundwater table intercepts the surface, at which point a hot spring can form. At these points, evaporite minerals (e.g. gypsum) and chemical precipitates (e.g. calcium carbonate in the form of tufa towers) are respectively produced by evaporation of thermal fluids or interaction of these fluids with lake waters. Bearing these relationships in mind, it is possible to use the relative locations of evaporates and chemical precipitates plus advanced argillic alteration to vector in towards a possible high-temperature upwelling source of geothermal fluids, which is most likely to lie proximal to, but underneath, advanced argillic alteration but also upgradient along the groundwater potentiometric surface from the evaporates and chemical precipitates. Examples of this relationship in Nevada include proximally located advanced argillic alteration and distally located silica sinter (chemical precipitate) at Steamboat Springs, Nevada (White et al., 1964) and proximally located advanced argillic alteration and distally located thermal springs and sulfate evaporites at Dixie Meadows, Nevada (Kennedy-Bowdoin et al., 2004).

One possible example on the PLPT reservation of geothermally linked occurrences of clay minerals and chemical precipitates occurs at Astor Pass (Fig. 6). Steam-heated groundwater could have produced some of the kaolinite-type clays detected in the Terraced Hills, and unboiled geothermal groundwater could have traveled laterally on top of the groundwater table to form chemical precipitates (carbonate tufa towers) further to the south near Astor Pass and Needle Rocks. A new Department of Energy research grant is making it possible to explore this possibility further, and more detailed temperature surveys and related exploration work are now in progress. 5. Summary and conclusions We used more than 1800 km2 of 5 m resolution hyperspectral data to focus geothermal exploration on the Pyramid Lake Paiute reservation in northwestern Nevada. Geothermal-indicator mineral maps helped elucidate structural controls and structural orientation or were found to be in close association with thermal springs. This study helped guide geothermal exploration on the PLPTR with regional-scale mineral mapping that focused subsequent exploration efforts. Minerals identified and mapped included alunite, carbonate rocks, gypsum, kaolinite/ halloysite, and montmorillonite/illite. After an initial round of field validation, we modified mineral maps accordingly and integrated these

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results with other spatial data in a GIS. Mineral associations with young fault scarps, temperature anomalies, and warm springs suggest that a large area of gypsum evaporite crust in the northern part of the study area had formed from evaporation of sulfur-rich upwelling geothermal fluids. We mapped both apparent and subtle tufa towers and related them to structural controls and shallow temperature anomalies, identifying regions of high potential for geothermal activity. It was not possible to spectrally differentiate shoreline and sublacustrine tufa; after field observations, however, we created separate maps for each type of tufa from remote sensing data. The scale and detail of tufa mapping exceed any similar previously documented effort in the Lahontan basin. We also quantified distribution of shoreline tufa with respect to elevation, slope, and aspect and identified some correlations with paleo-shoreline history. Quantification of the spatial distribution of shoreline tufa in the Pyramid Lake basin may help geologists recognize anomalous tufa distribution trends elsewhere in the Lahontan Basin. Such tufa anomalies may have structural or geothermal implications. Our results provide examples of how altered rock and certain chemical precipitates were used as geothermal exploration guides. Moreover, due to their spectral characteristics, attention was called to these features in remote sensing data sets, whereas in the field they may appear nondescript without close inspection. Acknowledgements We foremost wish to express our appreciation to John Jackson, Donna Noel, and the Pyramid Lake Paiute Tribe for allowing this research to happen and for facilitating our field exploration. We also appreciate Shuman Moore and Mack Shelor of High Desert GeoCulture LLC, whose vision of geothermal exploration and development has made it possible to meld research with exploration to produce optimal results. References Adams, K. D., & Wesnousky, S. G. (1999). Isostatic rebound, active faulting, and potential geomorphic effects in the Lahontan Basin, Nevada and California. GSA Bulletin, 111(12), 1739−1756. Benson, L. (1994). Carbonate deposition, Pyramid Lake subbasin, Nevada: 1. Sequence of formation and elevational distribution of carbonate deposits (tufas). Paleogeography, Paleoclimatology, Paleoecology, 109(1), 55−87. Boardman, J. W., Kruse, F. A., & Green, R. O. (1995). Mapping target signatures via partial unmixing of AVIRIS data. Proceedings of the Fifth JPL Airborne Earth Science Workshop, 95-1 (1). (pp. 23−26): JPL Publication. Bonham, H. F., & Papke, K. G. (1969). Geology and mineral deposits of Washoe and Storey Counties.Nevada: Nevada Bureau of Mines and Geology Bulletin, 70 139 pp. Briggs, R. W., & Wesnousky, S. G. (2004). Late Pleistocene fault slip rate, earthquake recurrence, and recency slip along the Pyramid Lake fault zone, northern Walker Lane, United States. Journal of Geophysical Research, 109, 16. Briggs, R. W., & Wesnousky, S. G. (2005). Late Pleistocene and Holocene paleoearthquake activity of the Olinghouse Fault Zone, Nevada. Bulletin of the Seismological Society of America, 95(4), 1301−1313. Crowley, J. K. (1991). Visible and near-infrared (0.4–2.5 μm) reflectance spectra of playa evaporite minerals. Journal of Geophysical Research, 96(B10), 16,231−16,240. Coolbaugh, M. F., Faulds, J. E., Kratt, C., Oppliger, G. L., Shevenell, L., Calvin, W. M., et al. (2006). Geothermal potential of the Pyramid Lake Paiute Reservation, Nevada, USA: Evidence of previously unrecognized moderate-temperature (150–170 °C) geothermal systems.Geothermal Resources Council Transactions, 20, 59−67 Available on line at http://www.unr.edu/Geothermal/meetings_pres.html Coolbaugh, M. F., Lechler, P., Sladek, C., & Kratt, C. (2009). Carbonate tufa columns as exploration guides for geothermal systems in the Great Basin. Geothermal Resources Council Transactions, 33, 361−366. Clark, R. N., Swayze, G. A., Wise, R., Livo, K. E., Hoefen, T. M., Kokaly, R. F., et al. (2003). USGS Digital Spectral Library splib05a. USGS Open File Report, 03-395. Dalton, J. B., Bove, D. J., & Mladinich, C. S. (2005). Remote sensing characterization of the Animas River watershed, southwestern Colorado, by AVIRIS imaging spectroscopy.

U.S. Geological Survey Scientific Investigations Report 2004–5203 (pp. 49). http:// pubs.usgs.gov/sir/2004/5203/ Faulds, J. E., Coolbaugh, M. F., Vice, G. S., & Edwards, M. L. (2006). Characterizing structural controls of geothermal fields in the Northwestern Great Basin: A progress report. Geothermal Resources Council Transactions, 30, 69−76. Faulds, J. E., Henry, C. D., & Hinz, N. H. (2005). Kinematics of the northern Walker Lane; an incipient transform fault along the Pacific-North American Plate boundary. Geology, 33(6), 505−508. Garside, L. J., & Schilling, J. H. (1979). Thermal waters of Nevada.Nevada Bureau of Mines and Geology Bulletin, 91 163 pp. Gillespie, A. R., Kahle, A. B., & Walker, R. E. (1986). Color enhancement of highly correlated images. I. Decorrelation and HIS contrast stretches. Remote Sensing of Environment, 20, 209−235. Green, A. A., Berman, M., Switzer, P., & Craig, M. (1988). A transformation for ordering multispectral data in terms of image quality with implications for noise removal. IEEE Transactions on Geoscience and Remote Sensing, 26(1), 65−74. Hancock, P. L., Chalmers, R. M. L., Altunel, E., & Cakir, Z. (1999). Travitonics: Using travertines in active fault studies. Journal of Structural Geology, 21, 903−916. Henley, R. W. (1985). The geothermal framework for epithermal deposits. In B. R. Berger & P.M. Bethke (Eds.), Geology and geochemistry of epithermal systems: Reviews in Economic Geology, Vol. 2. (pp. 1−24)Chelsea, MI: Society of Economic Geologists. Hunt, G. (1977). Spectral signatures of particulate minerals in the visible and near infrared. Geophysics, 42(3), 501−513. Kennedy-Bowdoin, T., Silver, E. A., Martini, B. A., & Pickles, W. L. (2004). Geothermal prospecting using hyperspectral imaging and field observations, Dixie Meadows, Nevada. Geothermal Resources Council Transactions, 28, 19−22. Kratt, C., Calvin, W. M., & Coolbaugh, M. F. (2005). Geothermal exploration with HyMap hyperspectral data at Brady-Desert Peak, Nevada. Remote Sensing of Environment, 104, 313−324. Kratt, C., Coolbaugh, M. F., Peppin, B., & Sladek, C. (2009). Identification of a new blind geothermal system with hyperspectral remote sensing and shallow temperature measurements at Columbus Salt Marsh, Esmeralda County, Nevada. Geothermal Resources Council Transactions, 33, 481−485. Kreemer, C., Blewitt, G., & Hammond, H. C. (2006). Using geodesy to explore correlations between crustal deformation characteristics and geothermal resources. Geothermal Resources Council Transactions, 30, 441−446. Kruse, F. A., Letkoff, A. B., Boardman, J. W., Heidbrecht, K. B., Shapiro, A. T., Barloon, J. P., et al. (1993). The Spectral Image Processing System (SIPS) — Interactive visualization and analysis of imaging spectrometer data. Remote Sensing of Environment, 44, 145−163. MacKnight, R. B., Martini, B. A., Silver, E. A., Pickles, W. L., & Kennedy-Bowdoin, T. (2004). Remote sensing analysis of structural and geothermal potential in the Humboldt Block, NV. International Geoscience and Remote Sensing Symposium Proceedings, September 20–24. Martini, B. A., Silver, E. A., Pickles, W. L., & Cocks, P. A. (2003). Hyperspectral mineral mapping in support of geothermal exploration: Examples from Long Valley Caldera, CA and Dixie Valley, NV, USA. Proceedings, Annual Meeting, Morelia, Mexico, Oct. 12–15, 2002Geothermal Resources Council Transactions, Vol. 27. (pp. 657−662). Robb, L. J. (2005). Introduction to ore-forming processes. Blackwell Science Ltd. Rowan, L. C., & Mars, J. C. (2003). Lithologic mapping in the Mountain Pass, California area using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Remote Sensing of Environment, 84, 350−366. Thatcher, W., Foulger, G. R., Julian, B. R., Svarc, J., Quilty, E., & Bawden, G. W. (1999). Present-day deformation across the Basin and Range province, western United States. Science, 283, 1714−1718. U.S. Geological Survey (2003). Quaternary fault and fold database of the United States. U.S. Geological Survey Open-File Report 03-417 http://earthquake.usgs.gov/regional/ qfaults/ Vaughan, R. G., & Calvin, W. M. (2005). Mapping weathering and alteration minerals in the Comstock and Geiger Grade areas using visible to thermal infrared airborne remote sensing data. In H. N. Rhoden, R. C. Steininger & P.G. Vikre (Eds.), Geological Society of Nevada Symposium 2005. Reno: Window to the World. Vaughan, R. G., Hook, S. J., Calvin, W. M., & Taranik, J. V. (2005). Surface mineral mapping at Steamboat Springs, Nevada with multi-wavelength thermal infrared images. Remote Sensing of Environment, ASTER Special Issue, 99(1–2), 140−158. Vice, G. S., Faulds, J. E., Ehni, W. J., & Coolbaugh, M. F. (2007). Structural controls of a blind geothermal system in the northern Pyramid Lake area, northwestern Nevada. Geothermal Resources Council Transactions, 31, 133−137. White, D., Thompson, G., & Sandberg, C. (1964). Rocks, structure, and geologic history of Steamboat Springs thermal area, Washoe County, Nevada. United States Geological Survey Professional Paper 458-B 63 pp. Yamaguchi, Y., Kahle, A. B., Tsu, H., Kawakami, T., & Pneil, M. (1998). Overview of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). IEEE Transactions on Geosciences and Remote Sensing, 36(4), 1062−1071.