Collaborative Research: CMG --Quantifying Tectonic and Geomorphic Interpretations of Thermochronometer Data with Inverse Problem Theory

合作研究：CMG——用反问题理论量化测温仪数据的构造和地貌解释

• 批准号: 0724656
• 负责人: Christopher Poulsen
• 金额: $ 48.6万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0724656&HistoricalAwards=false
• 关键词: Collaborative; Research; CMG; Quantifying; Tectonic

The grandeur of mountain topography has for millennia captured the attention of poets, artists, and scientists. How plate tectonic processes of mountain building and mountain erosion by surface processes interact to produce topography over millions of years is now at the forefront of Earth science research. A fundamental question that arises when studying the evolution of mountains is: what did the past topography of mountain ranges look like? This question has proven very difficult to answer. Recent developments in both computer modeling of mountain building and erosional processes, and developments in geochemistry have made progress in reconstructing paleotopography. Advances in new geochemical techniques and mathematics (inverse problem theory) now allow a means of testing computer model predictions with geochemical (thermochronometer) data from rocks exposed at the Earth's surface today. These data record the cooling history of rocks as they are exhumed to the surface by erosion and faulting. This interdisciplinary project is addressing questions and hypotheses that are fundamental to quantifying the evolution of mountain topography including: (1) How can geologically meaningful interpretations of tectonic and geomorphic processes influencing mountain topography be improved from an integration of thermochronometer data, computer modeling, and mathematics? (2) How sensitive are thermochronometer data to different mountain building and erosional processes and how can sampling strategies be optimized to improve interpretations? and (3) What is the magnitude and rate of topographic change that can be resolved from mathematical inversion of thermochronometer data? To address these questions, this project investigates the forward and inverse problems of mountain topographic evolution with a comprehensive model. Coupled 3D thermal, hydrologic, and kinematic computer models are under development in addition to a surface process model accounting for glacial, fluvial, and hillslope erosional processes. The coupled model is used to explore the sensitivity of thermochronometer data to different processes and mathematically invert a dense network of new and existing thermochronometer samples from the southern Coast Mountains, B.C., for the regional paleotopography. Field work is in progress for the collection of additional data. Several novel mathematical techniques are also under development. In particular, a low pass filter technique and a regularized iterative method are being used to solve the notoriously ill-posed backward parabolic equation and large scale, nonlinear inverse heat transport equation. These problems are by nature interdisciplinary and in the forefront of predicting and interpreting thermochronometer data and mountain topography.

几千年来，雄伟的山脉地形一直吸引着诗人、艺术家和科学家的注意力。 造山的板块构造过程和地表过程造成的山体侵蚀如何相互作用，在数百万年的时间里产生地形，现在已成为地球科学研究的前沿。研究山脉演化时出现的一个基本问题是：山脉过去的地形是什么样的？事实证明这个问题很难回答。造山和侵蚀过程计算机模型的最新发展以及地球化学的发展在重建古地貌方面取得了进展。新地球化学技术和数学（反问题理论）的进步现在允许使用当今地球表面暴露的岩石的地球化学（温度计）数据来测试计算机模型预测。这些数据记录了岩石因侵蚀和断层而被挖掘到地表时的冷却历史。这个跨学科项目正在解决对量化山地地形演变至关重要的问题和假设，包括：（1）如何通过整合热天文台数据、计算机建模和数学来改进对影响山地地形的构造和地貌过程的具有地质意义的解释？ (2) 温度计数据对不同的造山和侵蚀过程有多敏感，如何优化采样策略以改善解释？ (3) 从测温仪数据的数学反演中可以解析出地形变化的幅度和速率是多少？ 为了解决这些问题，本项目通过综合模型研究山地地形演化的正向和逆向问题。除了考虑冰川、河流和山坡侵蚀过程的地表过程模型之外，耦合的 3D 热、水文和运动学计算机模型也正在开发中。该耦合模型用于探索热计数据对不同过程的敏感性，并以数学方式反演来自不列颠哥伦比亚省南部海岸山脉的新的和现有的热计样本的密集网络，以用于区域古地形。收集额外数据的现场工作正在进行中。几种新颖的数学技术也正在开发中。 In particular, a low pass filter technique and a regularized iterative method are being used to solve the notoriously ill-posed backward parabolic equation and large scale, nonlinear inverse heat transport equation. 这些问题本质上是跨学科的，并且处于预测和解释热计数据和山地地形的前沿。