A linear inverse method to reconstruct paleo-topography
Landscape evolution provides insight into the tectonic and erosional processes that have shaped the topography observed today. However, in many cases, an estimate of an earlier topography is required to make first-order interpretations about volumes of sediment eroded or depths of fluvial incision,...
Main Author: | |
---|---|
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2019
|
Subjects: | |
Online Access: | https://discovery.ucl.ac.uk/id/eprint/10075342/1/Fox_2019_paleotopo.pdf https://discovery.ucl.ac.uk/id/eprint/10075342/ |
id |
ftucl:oai:eprints.ucl.ac.uk.OAI2:10075342 |
---|---|
record_format |
openpolar |
spelling |
ftucl:oai:eprints.ucl.ac.uk.OAI2:10075342 2023-12-24T10:17:09+01:00 A linear inverse method to reconstruct paleo-topography Fox, M 2019-07-15 text https://discovery.ucl.ac.uk/id/eprint/10075342/1/Fox_2019_paleotopo.pdf https://discovery.ucl.ac.uk/id/eprint/10075342/ eng eng https://discovery.ucl.ac.uk/id/eprint/10075342/1/Fox_2019_paleotopo.pdf https://discovery.ucl.ac.uk/id/eprint/10075342/ open Geomorphology , 337 pp. 151-164. (2019) Landscape evolution modeling Fluvial incision Grand Canyon Greenland Article 2019 ftucl 2023-11-27T13:07:37Z Landscape evolution provides insight into the tectonic and erosional processes that have shaped the topography observed today. However, in many cases, an estimate of an earlier topography is required to make first-order interpretations about volumes of sediment eroded or depths of fluvial incision, or to serve as an initial condition in landscape evolution models. This paper presents a means to reconstruct paleo-topography in two dimensions in areas that have experienced an increase in incision using available topographic remnants, or areas of low erosion rate. The approach is based on an analytical solution to the steady state stream power model in which a single elevation within the drainage network is a function of the integrated channel steepness and the normalized landscape response time, or χ, values. The branching structure of a drainage network provides redundant information that can be exploited to infer spatial variations in channel steepness and a base level parameter. A single elevation pixel can be written as a sum of channel steepness multiplied by Δχ values, and a set of elevation pixels can be combined as a system of equations. In order to improve efficiency, channel steepness is parameterized using pixels of constant values. By incorporating smoothness constraints on the channel steepness pixels using a Laplacian operator, a stable solution to the inverse problem can be obtained to infer the channel steepness values in space, a base level parameter and, in turn, paleo-topography. This approach is explored with examples from the Inyo Mountain Range, USA, Grand Canyon, USA and the Karrat Region in Western Greenland. Article in Journal/Newspaper Greenland University College London: UCL Discovery Greenland |
institution |
Open Polar |
collection |
University College London: UCL Discovery |
op_collection_id |
ftucl |
language |
English |
topic |
Landscape evolution modeling Fluvial incision Grand Canyon Greenland |
spellingShingle |
Landscape evolution modeling Fluvial incision Grand Canyon Greenland Fox, M A linear inverse method to reconstruct paleo-topography |
topic_facet |
Landscape evolution modeling Fluvial incision Grand Canyon Greenland |
description |
Landscape evolution provides insight into the tectonic and erosional processes that have shaped the topography observed today. However, in many cases, an estimate of an earlier topography is required to make first-order interpretations about volumes of sediment eroded or depths of fluvial incision, or to serve as an initial condition in landscape evolution models. This paper presents a means to reconstruct paleo-topography in two dimensions in areas that have experienced an increase in incision using available topographic remnants, or areas of low erosion rate. The approach is based on an analytical solution to the steady state stream power model in which a single elevation within the drainage network is a function of the integrated channel steepness and the normalized landscape response time, or χ, values. The branching structure of a drainage network provides redundant information that can be exploited to infer spatial variations in channel steepness and a base level parameter. A single elevation pixel can be written as a sum of channel steepness multiplied by Δχ values, and a set of elevation pixels can be combined as a system of equations. In order to improve efficiency, channel steepness is parameterized using pixels of constant values. By incorporating smoothness constraints on the channel steepness pixels using a Laplacian operator, a stable solution to the inverse problem can be obtained to infer the channel steepness values in space, a base level parameter and, in turn, paleo-topography. This approach is explored with examples from the Inyo Mountain Range, USA, Grand Canyon, USA and the Karrat Region in Western Greenland. |
format |
Article in Journal/Newspaper |
author |
Fox, M |
author_facet |
Fox, M |
author_sort |
Fox, M |
title |
A linear inverse method to reconstruct paleo-topography |
title_short |
A linear inverse method to reconstruct paleo-topography |
title_full |
A linear inverse method to reconstruct paleo-topography |
title_fullStr |
A linear inverse method to reconstruct paleo-topography |
title_full_unstemmed |
A linear inverse method to reconstruct paleo-topography |
title_sort |
linear inverse method to reconstruct paleo-topography |
publishDate |
2019 |
url |
https://discovery.ucl.ac.uk/id/eprint/10075342/1/Fox_2019_paleotopo.pdf https://discovery.ucl.ac.uk/id/eprint/10075342/ |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Greenland |
genre_facet |
Greenland |
op_source |
Geomorphology , 337 pp. 151-164. (2019) |
op_relation |
https://discovery.ucl.ac.uk/id/eprint/10075342/1/Fox_2019_paleotopo.pdf https://discovery.ucl.ac.uk/id/eprint/10075342/ |
op_rights |
open |
_version_ |
1786205093476958208 |