权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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

基本信息

批准号：
1918459
负责人：
Nicole Gasparini
金额：
$ 19.66万
依托单位：
Tulane University
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 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1918459&HistoricalAwards=false
关键词：
Collaborative Research Reading lithology topography

项目摘要

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.

景观的形状部分取决于它们下面的基岩的物理性质（例如，不同的岩石类型在不同的地方有多坚固，岩石有多破碎，以及特定的岩石有多容易分解成土壤和沉积物，也称为风化）。从地貌形态（地形）中“读取”岩石属性应该是可能的，但我们目前缺乏一种可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。过去的构造活动和潜在的未来地震沿着断层也可以从地形推断，但构造的影响必须从岩石属性控制景观形式。预测地表特性也将有利于规划自然灾害后或人类冲突期间进入偏远地区的机会。研究人员将开发基于瓜达卢佩山脉的教学模块，用于双招生（即，为高中生提供大学学分）通过德州大学奥斯汀分校教授的地球科学课程，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密集和有趣的实地讲习班接受培训，讲习班将在瓜达卢佩山脉授课。该项目将德克萨斯州和新墨西哥州的瓜达卢佩山脉作为天然实验室，以了解如何从地形推断岩石性质。除了（a）使用地理信息系统分析将米级地形数据和数字地质图联系起来之外，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成因放射性核素浓度来确定长期基岩侵蚀率，以及（d）评估预测景观如何随时间演变的开源计算机模型，该奖项反映了NSF的法定使命，并被认为值得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来支持。