Extracting information on the spatial variability in erosion rate stored in detrital cooling age distributions in river sands

Abstract

Abstract.One of the main purposes of detrital thermochronology is to provide constraints on the regional-scale exhumation rate and its spatial variability in actively eroding mountain ranges. Procedures that use cooling age distributions coupled with hypsometry and thermal models have been developed in order to extract quantitative estimates of erosion rate and its spatial distribution, assuming steady state between tectonic uplift and erosion. This hypothesis precludes the use of these procedures to assess the likely transient response of mountain belts to changes in tectonic or climatic forcing. Other methods are based on an a priori knowledge of the in situ distribution of ages to interpret the detrital age distributions. In this paper, we describe a simple method that, using the observed detrital mineral age distributions collected along a river, allows us to extract information about the relative distribution of erosion rates in an eroding catchment without relying on a steady-state assumption, the value of thermal parameters or an a priori knowledge of in situ age distributions. The model is based on a relatively low number of parameters describing lithological variability among the various sub-catchments and their sizes and only uses the raw ages. The method we propose is tested against synthetic age distributions to demonstrate its accuracy and the optimum conditions for it use. In order to illustrate the method, we invert age distributions collected along the main trunk of the Tsangpo-Siang-Brahmaputra river system in the eastern Himalaya. From the inversion of the cooling age distributions we predict present-day erosion rates of the catchments along the Tsangpo-Siang-Brahmaputra river system, as well as some of its tributaries. We show that detrital age distributions contain dual information about present-day erosion rate, i.e., from the predicted distribution of surface ages within each catchment and from the relative contribution of any given catchment to the river distribution. The method additionally allows comparing modern erosion rates to long-term exhumation rates. We provide a simple implementation of the method in Python code within a Jupyter Notebook that includes the data used in this paper for illustration purposes.

The geologic interpretation of the detrital thermochronology record within a stratigraphic framework, with examples from the European Alps, Taiwan and the Himalayas

“…8, different sources are assumed to have the same mineral fertility, i.e., the same propensity to yield specific mineral grains when exposed to erosion. Most detrital thermochronology studies do assume negligible changes in mineral fertility (e.g., Malusà et al, 2009;Zhang et al, 2012;Glotzbach et al, 2013;Saylor et al, 2013;He et al, 2014;Braun et al, 2018). However, constant mineral fertility is rarely observed in real geologic settings, and the constant-fertility assumption of many studies, while understandable is generally untenable.…”

Source Region Geochemistry From Unmixing Downstream Sedimentary Elemental Compositions

“…The widely used stream power model, for example, predicts erosion rates using empirical relationships between slope angle, upstream area and erosion rate (see e.g., Howard & Kerby, 1983;Tucker & Whipple, 2002). Alternatively spatial patterns of erosion rate have be constrained using detrital geochronology (e.g., Avdeev et al, 2011;Braun et al, 2018;Fox, Leith, et al, 2015;Stock et al, 2006;Vermeesch, 2007). In Lipp et al (2020), the stream power model was used to predict erosion rates and hence composition of sediment downstream using Equation 1 for the same data set used here.…”

Response of Drainage Pattern and Basin Evolution to Tectonic and Climatic Changes Along the Dinarides-Hellenides Orogen

“…The basin gains or loses connectivity with the orogenic foreland (e.g., Aterno River in the Italian Apennines; see D 'Agostino et al, 2001;Geurts et al, 2018). In either case, the fluvial system exerts a first-order control on the position and magnitude of sedimentary supply within the basin (Whittaker et al, 2007) which can be used to infer patterns of hinterland erosion (Braun et al, 2018;Gemignani et al, 2018).…”