DATA-DRIVEN APPROACH TO OBSERVING THE ELUSIVE ERODIBILITY COEFFICIENT

The development of computer-based fluvial landscape evolution models has provided copious insights into how drainage systems respond to tectonics, sediment load, climate change, and landscape. Relatively simple, yet powerful equations are used in these models to predict stream bedrock incision. However, these equations come at a cost: the introduction of parameters not grounded in field observations. Most notably, the erodibility coefficient is often used. Here we present a data-driven approach to estimate the erodibility of a landscape. We show that we can predict erodibility from the landsurface in landscape evolution models. We also are testing this method on natural landscapes.