Monitoring groundwater levels in Oasis Valley, NV, and evaluating potential drawdown during the North Bullfrog aquifer test

The Nature Conservancy (TNC) owns ecologically rich properties that include groundwater-dependent ecosystems (GDEs) in Oasis Valley, Nevada. AngloGold Ashanti has acquired the rights to several gold mines in Oasis Valley, including the North Bullfrog Project, where the company conducted two multiday aquifer tests in 2023 and 2024 to assess aquifer hydraulics and evaluate water level drawdown. In partnership with TNC, Desert Research Institute (DRI) monitored groundwater levels at sites within Oasis Valley to identify potential hydrologic impacts that could be attributed to the aquifer tests. Combined water level and water temperature sensors were installed and activated with a five-minute measurement frequency between August 30, 2023, and March 20, 2024, at the NC-GWE-OV-2 well (in Parker Ranch), OVU Lower ET Well (in the Atwood Preserve), and Crystal Spring. DRI also operates systems for monitoring meteorology at Colson Pond (in the Atwood Preserve) and diverted flow from Crystal Spring. Water level modeling was performed using SeriesSEE to assess whether drawdown was detected at the three monitoring points that can be attributed to groundwater pumping during aquifer testing. The water level modeling approach isolates pumping effects from environmental fluctuations (i.e., background water levels and barometric pressure). The modeling analysis indicates that no measurable drawdown can be attributed to the aquifer tests, which is likely due to a combination of aquifer conditions and testing parameters. It is recommended that monitoring continues at the three established stations and expands to other monitoring points in Oasis Valley to establish a baseline of natural variability to identify future impacts from pumping and to better understand groundwater interactions that may affect water availability at GDEs.

Methods
Transducer water level data were post-processed after each field trip. Quality control is performed through the Trainset program (https://trainset.geocene.com/). This program allows for the visualization and labeling of large sets of data. The data from each well were analyzed and labeled with different indicators, such as data offloads, adjusting periods (time soon after the sensor was first installed, when readings may be less accurate), dry (transducer out of the water), frozen (if sensor temperature drops to freezing), spikes, dips, wide dips (drop > 1.0 inch [2.5 cm], and then return to the original water level multiple hours later), steps (sudden increase or decrease to a new fairly constant water level), and flatlines. These labels help to identify different trends and possible erroneous data.