Quantifying the influence of sediment source area sampling on detrital thermochronometer data

Tuesday, 16 December 2014: 3:10 PM
David Michael Whipp Jr, University of Helsinki, Helsinki, Finland, Todd Alan Ehlers, University of Tübingen, Tübingen, Germany, Isabelle Coutand, Dalhousie University, Halifax, NS, Canada and Bodo Bookhagen, University of Potsdam, Potsdam, Germany
Detrital thermochronology offers a unique advantage over traditional bedrock thermochronology because of its sensitivity to sediment production and transportation to sample sites. In mountainous regions, modern fluvial sediment is often collected and dated to determine the past (105 to >107 year) exhumation history of the upstream drainage area. Though potentially powerful, the interpretation of detrital thermochronometer data derived from modern fluvial sediment is challenging because of spatial and temporal variations in sediment production and transport, and target mineral concentrations. Thermochronometer age prediction models provide a quantitative basis for data interpretation, but it can be difficult to separate variations in catchment bedrock ages from the effects of variable basin denudation and sediment transport.

We present two examples of quantitative data interpretation using detrital thermochronometer data from the Himalaya, focusing on the influence of spatial and temporal variations in basin denudation on predicted age distributions. We combine age predictions from the 3D thermokinematic numerical model Pecube with simple models for sediment sampling in the upstream drainage basin area to assess the influence of variations in sediment production by different geomorphic processes or scaled by topographic metrics. We first consider a small catchment from the central Himalaya where bedrock landsliding appears to have affected the observed muscovite 40Ar/39Ar age distributions. Using a simple model of random landsliding with a power-law landslide frequency-area relationship we find that the sediment residence time in the catchment has a major influence on predicted age distributions. In the second case, we compare observed detrital apatite fission-track age distributions from 16 catchments in the Bhutan Himalaya to ages predicted using Pecube and scaled by various topographic metrics. Preliminary results suggest that predicted age distributions scaled by the rock uplift rate in Pecube are statistically equivalent to the observed age distributions for ~75% of the catchments, but may improve when scaled by local relief or specific stream power weighted by satellite-derived precipitation. Ongoing work is exploring the effect of scaling by other topographic metrics.