Collaborative Research: Reading lithology from topography: How rock properties influence landscape form and evolution in the Guadalupe Mountains, TX and NM

合作研究：从地形中解读岩性：岩石特性如何影响德克萨斯州和新墨西哥州瓜达卢佩山脉的景观形态和演化

• 批准号: 1918351
• 负责人: Joel Johnson
• 金额: $ 31.97万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1918351&HistoricalAwards=false
• 关键词: Collaborative; Research; Reading; lithology; topography

The shape of landscapes partly depends on the physical properties of the bedrock that underlies them (e.g., how strong different rock types are in different places, how fractured the rocks are, and how easily particular rocks break down to make soil and sediment, also known as weathering). It should be possible to "read" rock properties from landscape form (topography), but we currently lack a quantitative relationship that can be used practically. For example, the likelihood of landslides depends on rock and soil properties. Past tectonic activity and the potential for future earthquakes along faults can also potentially be inferred from topography, but the effects of tectonics must be isolated from rock property controls on landscape form. Predicting land surface properties would also be beneficial for planning access to remote areas following natural disasters or during human conflicts. The researchers will develop teaching modules based on the Guadalupe Mountains to use in a dual enrollment (i.e., college credit for high school students) geoscience course taught through UT Austin that provides college credit to high school students across Texas. High school geoscience and environmental science teachers will be trained through intensive and fun field workshops to be taught in the Guadalupe Mountains.This project uses the Guadalupe Mountains in Texas and New Mexico as a natural laboratory to understand how rock properties can be inferred from topography. In addition to (a) using geographic information system analysis to relate meter-scale topographic data and digital geology maps, the researchers will also (b) make extensive field measurements of rock properties across this landscape, (c) determine long-term bedrock erosion rates by measuring cosmogenic radionuclide concentrations from rock samples, and (d) evaluate open-source computer models that predict how landscapes will evolve through time, and improve these models to better incorporate rock properties into their equations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

地貌的形状部分取决于其下方基岩的物理性质（例如，不同地方不同岩石类型的强度，岩石的断裂程度，以及特定岩石分解形成土壤和沉积物的难易程度，也被称为风化）。从地貌（地形）中“读出”岩石性质应该是可能的，但我们目前缺乏一种可以实际使用的定量关系。例如，滑坡的可能性取决于岩石和土壤的性质。过去的构造活动和未来沿断层发生地震的可能性也可能从地形中推断出来，但构造的影响必须与岩石性质对景观形态的控制分离开来。预测地表性质也有利于在自然灾害或人类冲突期间规划进入偏远地区的途径。研究人员将开发基于瓜达卢佩山脉的教学模块，用于德克萨斯大学奥斯汀分校（UT Austin）教授的双招生（即高中生的大学学分）地球科学课程，该课程为德克萨斯州的高中生提供大学学分。高中地球科学和环境科学教师将通过在瓜达卢佩山脉开设的密集而有趣的实地讲习班接受培训。该项目利用德克萨斯州和新墨西哥州的瓜达卢佩山脉作为自然实验室，了解如何从地形推断岩石属性。除了(a)使用地理信息系统分析来关联米尺度的地形数据和数字地质图之外，研究人员还将(b)对整个景观的岩石特性进行广泛的实地测量，(c)通过测量岩石样本中的宇宙生成放射性核素浓度来确定长期的基岩侵蚀率，以及(d)评估开源计算机模型，预测景观将如何随着时间的推移而演变。并改进这些模型，以便更好地将岩石特性纳入其方程中。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Building a bimodal landscape: bedrock lithology and bed thickness controls on the morphology of Last Chance Canyon, New Mexico, USA

构建双峰景观：美国新墨西哥州最后机会峡谷形态的基岩岩性和床厚控制

• DOI: 10.5194/esurf-11-995-2023
• 发表时间: 2023
• 期刊: Earth Surface Dynamics
• 影响因子: 3.4
• 作者: Anderson, Sam;Gasparini, Nicole;Johnson, Joel
• 通讯作者: Johnson, Joel