Mapping Groundwater in the Snowy Range Annette Hein, Dr. Andrew Parsekian, Ryan Armstrong, Dr. Steve Holbrook, Andrea Creighton

Introduction Project goal: produce groundwater map in an alpine drainage Importance: monitoring, hydrologic studies Approach: airborne resistivity mapping and nuclear magnetic resonance (NMR) point soundings Using public domain data for base map, surface water, and geology. Not ideal from a pure science perspective, but good from a practical perspective.

Location Location: Southern Wyoming, Snowy Range. Landmarks: Medicine Bow Peak, Centennial, Highway 130, Libby Creek, Nash Fork, North Fork Little Laramie River. Scale 1:100,000

Methods: Resistivity Around 12 square miles of resistivity data was collected through the Airborne Transient ElectroMagnetic (SkyTEM) survey. Advantage: it covers a large area. Disadvantage: it is not a direct measurement of water content.

Methods: Nuclear Magnetic Resonance Four point soundings were collected using nuclear magnetic resonance (NMR) Advantage: this is the only geophysics method that directly measures water content Disadvantage: each measurement applies to only one point.

Geologic Setting -Metamorphic rocks—quartzite, schist, slate, phyllite, greenstone -Nash Fork Shear Zones -Vertical dips -Quaternary cover -TEM measurement area -Each NMR site in a different formation.

Vertical Structure of Groundwater The NMR shows water at shallow levels (between 5-10 m) and water at deeper levels (~40 m). This is consistent at all 4 sites and suggests good depths to study the TEM data. Dashed line is depth above which the profile is reliable.

TEM data overview The TEM data cube starts at the surface and goes down more than 100 m. This slice is a layer with the base 6 m below the surface (following topography). We want to take this map of resistivity at 6 m and turn it into a map of groundwater. The first thing to notice is that the data has such a wide range, it’s hard to see much subtle variation. We can begin by taking a log of the data to bring out patterns.

TEM data overview Even with a log transform, the major information displayed here is that the Quaternary geology is much more conductive than the bedrock, and that different bedrock formations have various resistivities. That’s great, but it doesn’t say much about groundwater. We want to highlight the anomalies within a particular geological setting.

TEM data processing This map attempts to compare “apples to apples” by comparing each point only with others in the same formation (bedrock or Quaternary). The log of the resistivity data was taken to produce a more normal distribution. SkyTEM points were selected by formation, and the mean log(resistivity) and standard deviation value was found for that formation. Points were then standardized by subtracting the mean and dividing by the standard deviation. A negative number means more conductive than the mean for that formation, and a positive number means less conductive than the mean for that formation. Note: this map CANNOT answer any questions about how formations compare to each other, because this processing took that information OUT. So now we have anomalies—how do we interpret them? We need to know whether water will show up as resistive or conductive.

Can we predict water from resistivity? Define “Conductive” points to be those with a standardized level less than 0, and “Resistive” points to be those with a standardized level greater than 0. Assume at 6 m depth, the presence of groundwater is controlled chiefly by nearby surface water Choose a search distance of 100 m, the approximate radius of each TEM measurement. Check whether water shows up as an anomaly Check whether anomalies tend to be water

Sometimes, yes! We notice that three formations (Lookout Schist, Nash Marble, and Anderson Phyllite) have greater than 50% probability that a wet point will be conductive AND that a conductive point will be wet. This first probability is fairly different from those in the general population. This supports the assumption that we can use resistivity in these formations to predict water at a greater depth.

How wet is “wet”? Groundwater –around 14% near surface. Recall—peak of 7% at a depth of approximately 40 m. The groundwater is in the neighborhood of 14% for the sounding at a conductive point in Xa, which is reasonable for a fractured bedrock aquifer. Recall that we also see a groundwater peak of around 7% at a depth of approximately 40 m. This suggests that depth would be a good place to generate a “groundwater map” for the formations where that is possible

Creating the groundwater map We assume that the glacial till doesn’t extend down this far (120 feet). We say everything resistive is dry. We say everything conductive is wet, and probably around 5% water content. There’s a better than 50% chance that the points mapped in blue really are groundwater. More than half the groundwater has probably been mapped as blue. No, I didn’t say it was definitive!

Interpreting the groundwater map The very most conductive (assumed to be wettest) points are close to the surface water. The presence of conductive conduits between the lakes makes it appear that the lakes are interconnected through the water table at this level.

Questions? And as imagination bodies forth The forms of things unknown, the poet's pen geophysicist Turns them to shapes and gives to airy nothing A local habitation and a name. -A Midsummer Night’s Dream

Bedrock Resistivity We see that different bedrock formations have different resistivities and respond differently to weathering. Therefore, they could respond differently to the addition of water. Also, water may have different resistivities for different formations because resistivity is controlled by dissolved ions in the water.

Sometimes, yes! Xl 57% 84% Xn 72% 63% Xa 65% 81% Q 790 50% 55% 25% 45% Formation # Points Within 100 m of Stream or Lake (WET) Percent of ALL pts that are CONDUCTIVE Percent of WET points that are CONDUCTIVE Percent of CONDUCTIVE pts that are WET Percent of ALL pts that are RESISTIVE Percent of WET pts that are RESISTIVE Percent of RESISTIVE pts that are WET Q 790 50% 55% 25% 45% 21% Xm 109 48% 61% 40% 52% 39% 23% Xl 67 46% 57% 84% 54% 43% 56% Xn 76 72% 63% 28% Xa 54 65% 81% 35% 53% Xr 21 49% 62% 42% 51% 38% Xt 17 12% Xf 64 67% 33% 22% NFSZ1 227 26% NFSZ2 2 100% 2% 58% 0% NFSZ3 41 66% 34% 13% NFSZ4 47 19% 11% We notice that three formations (Lookout Schist, Nash Marble, and Anderson Phyllite) have greater than 50% probability that a wet point will be conductive AND that a conductive point will be wet. This first probability is fairly different from those in the general population. This supports the assumption that we can use resistivity in these formations to predict water at a greater depth.

NMR data processing This is so pretty!! But it doesn’t seem to make a difference to the inversion—Why not?? I feel like it should