Intermontane valley fills
type: CreativeWork
description: Sedimentary valley fills are a widespread characteristic of mountain belts around the world. They transiently store material over time spans ranging from thousands to millions of years and therefore play an important role in modulating the sediment flux from the orogen to the foreland and to oceanic depocenters. In most cases, their formation can be attributed to specific fluvial conditions, which are closely related to climatic and tectonic processes. Hence, valley-fill deposits constitute valuable archives that offer fundamental insight into landscape evolution, and their study may help to assess the impact of future climate change on sediment dynamics. In this thesis I analyzed intermontane valley-fill deposits to constrain different aspects of the climatic and tectonic history of mountain belts over multiple timescales. First, I developed a method to estimate the thickness distribution of valley fills using artificial neural networks (ANNs). Based on the assumption of geometrical similarity between exposed and buried parts of the landscape, this novel and highly automated technique allows reconstructing fill thickness and bedrock topography on the scale of catchments to entire mountain belts. Second, I used the new method for estimating the spatial distribution of post-glacial sediments that are stored in the entire European Alps. A comparison with data from exploratory drillings and from geophysical surveys revealed that the model reproduces the measurements with a root mean squared error (RMSE) of 70m and a coefficient of determination (R2) of 0.81. I used the derived sediment thickness estimates in combination with a model of the Last Glacial Maximum (LGM) icecap to infer the lithospheric response to deglaciation, erosion and deposition, and deduce their relative contribution to the present-day rock-uplift rate. For a range of different lithospheric and upper mantle-material properties, the results suggest that the long-wavelength uplift signal can be explain…
abstract: Sedimentary valley fills are a widespread characteristic of mountain belts around the world. They transiently store material over time spans ranging from thousands to millions of years and therefore play an important role in modulating the sediment flux from the orogen to the foreland and to oceanic depocenters. In most cases, their formation can be attributed to specific fluvial conditions, which are closely related to climatic and tectonic processes. Hence, valley-fill deposits constitute valuable archives that offer fundamental insight into landscape evolution, and their study may help to assess the impact of future climate change on sediment dynamics. In this thesis I analyzed intermontane valley-fill deposits to constrain different aspects of the climatic and tectonic history of mountain belts over multiple timescales. First, I developed a method to estimate the thickness distribution of valley fills using artificial neural networks (ANNs). Based on the assumption of geometrical similarity between exposed and buried parts of the landscape, this novel and highly automated technique allows reconstructing fill thickness and bedrock topography on the scale of catchments to entire mountain belts. Second, I used the new method for estimating the spatial distribution of post-glacial sediments that are stored in the entire European Alps. A comparison with data from exploratory drillings and from geophysical surveys revealed that the model reproduces the measurements with a root mean squared error (RMSE) of 70m and a coefficient of determination (R2) of 0.81. I used the derived sediment thickness estimates in combination with a model of the Last Glacial Maximum (LGM) icecap to infer the lithospheric response to deglaciation, erosion and deposition, and deduce their relative contribution to the present-day rock-uplift rate. For a range of different lithospheric and upper mantle-material properties, the results suggest that the long-wavelength uplift signal can be explain…
author: Mey, Jürgen
keywords: intermontane valley fill, sediment thickness, bedrock elevation, artificial neural networks, sediment volume, landscape evolution, glacial isostatic adjustment, isostatic uplift, LGM, Ice model, European Alps, outburst floods, glacial incision, Tibetan Plateau, Shyok River, cosmogenic nuclides, exposure age dating, ice dam, Karakoram, Namche Barwa, Yarlung-Tsangpo Gorge, burial dating, tectonic uplift, syntaxis, intermontane Talverfüllungen, Sedimentmächtigkeit, Grundgesteinshöhe, künstliche neurale Netzwerke, Sedimentvolumen, Landschaftsentwicklung, Glazialisostasie, isostatische Hebung, Eismodell, Europäische Alpen, Seeausbrüche, glaziale Einschneidung, Tibet Plateau, Shyok Fluss, kosmogene Nuklide, Expositionsaltersdatierung, Eisdamm, Karakorum, Yarlung-Tsangpo Schlucht, Verschüttungsaltersdatierung, tektonische Hebung, Syntaxe
date published: 2016-12-21
date modified: 2026-07-24T03:51:58Z
provider: Universität Potsdam - Diss
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Universität Potsdam