GSA Connects 2021 in Portland, Oregon

Paper No. 127-14
Presentation Time: 2:30 PM-6:30 PM


GRAMBLING, Tyler1, JESSUP, Micah J.2, NEWELL, Dennis L.3, METHNER, Katharina4, MULCH, Andreas5, HUGHES, Cameron A.2 and SHAW, Colin6, (1)Department of Earth and Planetary Sciences, University of Tennessee, 1621 Cumberland Ave, 602 Strong Hall, Knoxville, TN 37996, (2)Department of Earth and Planetary Sciences, University of Tennessee, 1621 Cumberland Ave, 602 Strong Hall, Knoxville, TN 37996-1526, (3)Department of Geology, Utah State University, 4505 Old Main Hill, Logan, UT 84322, (4)Stanford University Department of Geological Sciences, 473 Via Ortega, Stanford, CA 94305-4121, (5)Institute of Geosciences, Goethe University Frankfurt, Altenhoeferallee 1, Frankfurt am Main, 60438, Germany, (6)Department of Earth Sciences, Montana State University, P.O. Box 173480, Bozeman, MT 59717

Reconstructions of altitude in the orogenic record have implications for landscape evolution in tectonically active areas, the interplay of climate and tectonics, and aid in reconstructing geodynamic processes. Stable isotope paleoaltimetry capitalizes on the mass-dependent fractionation of oxygen and hydrogen isotopes during rainout as moisture ascends an orographic front. Variability of precipitation, evaporation, and recycling patterns as moisture moves across a mountain belt indicate that these assumptions must be regionally verified to avoid erroneous interpretations of the altitude effect on oxygen and hydrogen isotope ratios. This requires corroboration that hydrogen (δ2H) and oxygen (δ18O) stable isotope values in surface waters correlate with their mean catchment elevation before applying a lapse rate to historic isotope proxies used to reconstruct paleoelevation. Additionally, multiple lapse rates based on empirical, thermodynamic, and climate model-based variations in stable isotope ratios provide competing approaches to reconstructing paleoelevation. While prior work established the best practice for the southern Peruvian Andes and Altiplano Plateau, we aim to verify this approach within the Cordillera Blanca as this region is heavily glaciated, represents the highest elevations in Peru, and sees variations in rainfall that may result in deviation from behavior observed elsewhere in the Peruvian Andes. Here, we use published lapse rates to model recharge elevation from modern surface and thermal spring waters in order to examine their accuracy and verify the best approach for this region. These modeled elevations are referenced against known hypsometric mean elevation for catchments in the Cordilleras Blanca and Negra that are feeding the headwaters of the Rio Santa. We demonstrate that elevations approximated from non-linear lapse rates closely reflect the mean elevation of local catchments and the upper Rio Santa watershed. This approach most reliably reproduces catchment elevation and verifies that non-linear lapse rates are the most appropriate means of reconstructing paleoelevation for this region.