A HYDROGEOCHEMICAL ANALYSIS OF SPRINGS IN THE SANDIA AND MANZANO MOUNTAINS, NEW MEXICO

Springs are an important water resource both for anthropogenic use and support of ecosystems in the arid Southwest. During times of drought, the sustainability of these groundwater systems is a major concern for effective water resource management. During 2017-2019, several springs were visited in the Sandia and Manzano mountains of north-central New Mexico to perform an inventory of the springs and the surrounding environment. This work is part of an ongoing collaboration between students and faculty at UNM and the US Forest Service (Cibola National Forest).

We collected water samples for water quality analysis (major ions and stable isotopes), and field water quality parameters such as pH, total dissolved solids (TDS), dissolved oxygen (DO), and discharge. We analysed monthly precipitation samples from a collection site near the springs in the Sandia mountains. We also analyzed snowpack samples from 2019. Spring samples primarily consist of calcium bicarbonate and calcium magnesium chloride sulfate waters. Trends in solute distribution are interpreted to reflect different water-rock interactions along groundwater flow paths. Regional aquifers include the Madera Group (chiefly carbonates) as well as several sandstone aquifers. Fault structures also play a role in controlling spring occurrence. Our results show two distinct trends between spring waters that are interpreted to have undergone silicate weathering and those undergoing carbonate dissolution. Carbonate dissolution occurs in waters traveling through the Madera Group aquifer system while silicate weathering occurs as waters travel through faults within the Sandia granite. Stable isotope analyses show that winter snowpack is the primary recharge mechanism of the majority of these waters.

In addition to data collection and analyses, we have made major efforts in compiling all datasets into a regional database (Springs Stewardship Database) to preserve valuable information, make the data accessible to others, and provide important baselines for future comparison.