--> Numerical Model Predictions of Intrinsically Generated Fluvial Terraces and Comparison to Climate-Change Expectations

AAPG Annual Convention and Exhibition

Datapages, Inc.Print this page

Numerical Model Predictions of Intrinsically Generated Fluvial Terraces and Comparison to Climate-Change Expectations

Abstract

Terraces eroded in sediment (cut-fill) and bedrock (strath) preserve a geomorphic record of river activity. River terraces are often thought to form when a river switches from a period of low vertical incision rates and valley widening to high vertical incision rates and terrace abandonment. Consequently, terraces are frequently interpreted to reflect landscape response to changing external drivers, including tectonics, sea-level, and most commonly, climate. In contrast, unsteady lateral migration in meandering rivers may generate river terraces even under constant vertical incision and without changes in external forcing. To explore this latter mechanism, we use a numerical model and an automated terrace detection algorithm to simulate landscape evolution by a vertically incising, meandering river and isolate the age and geometric fingerprints of intrinsically generated river terraces. Simulations indicate that terraces form for a wide range of lateral and vertical incision rates. Terrace formation is limited by a characteristic timescale for relief generation, and once this is surpassed the time interval between terraces increases in time due to re-working of previously visited areas. Surprisingly, intrinsically generated terraces are commonly paired and longitudinally extensive—attributes that are thought to be diagnostic of climate change. Evolving spatial differences in bank strength between bedrock and sediment reduce terrace formation frequency and length, and can explain sub-linear terrace margins at valley boundaries. Comparison of model predictions to natural river terraces indicates that long terraces are the most unique indicators of pulses of vertical incision, and may contain the imprint of past climate change on landscapes.