Collaborative Research: Steepland dynamics and steady-state forms resulting from debris flows

合作研究：泥石流造成的陡峭地带动力学和稳态形式

• 批准号: 1951274
• 负责人: Luke McGuire
• 金额: $ 31.54万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1951274&HistoricalAwards=false
• 关键词: Collaborative; Research; Steepland; dynamics; steady

Landscapes encode valuable information about tectonics and climate, as well as the frequency, size, and types of processes that shape them. Reliable extraction of this information, however, requires that we understand the relationships between the processes that transport sediment over the Earth’s surface and the landscapes that they create. The overarching goal of this project is to understand the role of debris flows in shaping steep landscapes. Debris flows are mixtures of mud, rocks, and other incidental debris (such as trees) that can travel at high speeds down valley networks. Their large size, rapid motion, and episodic behavior pose hazards to life and infrastructure. They also erode the valleys they travel through, contributing to the shape of steep landscapes. Debris flows are thought to be a dominant mechanism for transporting sediment and eroding bedrock in steep terrain, but we currently lack a mathematical framework to describe how landscapes respond to erosion by debris flows. In this project, the investigators will develop a model to predict how debris flows erode landscapes and apply this model to understand how changes in tectonics, climate, and land-use influence topography and the sediment volumes passed on to downstream rivers and reservoirs. The project will improve our ability to extract information about tectonics and climate from topographic data and will contribute to resolving a long-standing debate regarding the relative importance of debris flows and water-dominated flows in sculpting bedrock channel networks. This project will train one postdoctoral researcher, one PhD student, one MS student, and three undergraduate students. Two of the undergraduate students will be recruited through the University of Arizona ASEMS (Arizona’s Science Engineering and Math Scholars) program, which is designed to support underrepresented students in STEM fields. The investigators will also produce online community learning tools, lead in-person clinics that support students and researchers in using the model and analysis tools developed through the course of the project, and give guest lectures at a public high school.Debris flows are thought to be a primary driver of erosion in many steeplands but we currently lack a generalizable, mechanistic approach for quantifying debris flow erosion within landscape evolution models. As such, our ability to predict the dynamics of steeplands, including their geomorphic responses to tectonic, climatic, and anthropogenic forcing, is limited. This project will address three fundamental questions related to the geomorphic role of debris flow erosion: 1) How can we quantify erosion by episodic debris flows over geologic timescales?, 2) How does debris flow erosion influence the morphology of quasi-steady state landscapes?, and 3) How does debris flow erosion influence transient signals (e.g. knickpoints) propagating through the channel network? To address these questions, the investigators propose to analyze debris flow dominated landscapes in the Oregon Coast Range (OCR) and the San Gabriel Mountains (SGM), conduct a field campaign designed to relate changes in landscape morphology to tectonic forcing and environmental factors, and develop a novel landscape evolution model that incorporates debris flow erosion. The debris flow erosion model will employ process-based equations for debris flow motion that honor the discrete nature, transient flow dynamics, and limited mobility of debris flows that differentiates them from water-dominated flows. From this detailed picture of nonlocal debris-flow dynamics, the investigators will then calculate debris flow erosion within bedrock channels integrated over geologic time. The model will be validated through comparisons with topographic analyses of channel network properties and millennial-scale erosion rates in debris-flow-dominated valleys in the OCR and SGM. They will apply their process-based modeling approach in combination with data and observations from our study sites to derive a geomorphic transport law for debris flow erosion, quantify the impact of debris flow erosion on the form of steady state landscapes, and explore how debris flows influence the propagation of transient signals through the channel network.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.

景观编码有关构造和气候的宝贵信息，以及塑造它们的过程的频率，大小和类型。然而，可靠地提取这些信息需要我们了解在地球表面运输沉积物的过程与它们所创造的景观之间的关系。该项目的首要目标是了解泥石流在塑造陡峭景观中的作用。泥石流是泥浆、岩石和其他偶然碎片（如树木）的混合物，它们可以高速沿着山谷网络流动。它们的体积大、运动快和偶发行为对生命和基础设施构成危害。它们还侵蚀了所经过的山谷，形成了陡峭的地貌。泥石流被认为是在陡峭地形中运输沉积物和侵蚀基岩的主要机制，但我们目前缺乏一个数学框架来描述景观如何应对泥石流侵蚀。在这个项目中，研究人员将开发一个模型来预测泥石流如何侵蚀景观，并应用这个模型来了解构造，气候和土地利用的变化如何影响地形以及传递到下游河流和水库的沉积物量。该项目将提高我们从地形数据中提取有关构造和气候信息的能力，并将有助于解决关于泥石流和水流在塑造基岩水道网络中的相对重要性的长期争论。本项目将培养一名博士后研究员、一名博士生、一名硕士生和三名本科生。其中两名本科生将通过亚利桑那大学ASEMS（亚利桑那州科学工程和数学学者）计划招募，该计划旨在支持STEM领域代表性不足的学生。研究人员还将制作在线社区学习工具，领导面对面的诊所，支持学生和研究人员使用通过项目课程开发的模型和分析工具，并在公立高中进行客座讲座。泥石流被认为是许多陡坡侵蚀的主要驱动力，但我们目前缺乏一个可概括的，景观演变模型中量化泥石流侵蚀的机械方法。因此，我们的能力来预测动态的陡坡，包括其地貌的构造，气候和人为强迫的反应，是有限的。这个项目将解决与泥石流侵蚀的地貌作用有关的三个基本问题：1）我们如何量化地质时间尺度上的偶发泥石流的侵蚀？2)泥石流侵蚀如何影响准稳定状态地貌形态？3）泥石流侵蚀对沟道网络中传播的瞬态信号（如断点）有何影响？为了解决这些问题，研究人员建议分析泥石流占主导地位的景观在俄勒冈州海岸山脉（OCR）和圣盖博山脉（SGM），进行实地考察，旨在将景观形态的变化与构造强迫和环境因素，并开发一种新的景观演化模型，将泥石流侵蚀。泥石流侵蚀模型将采用基于过程的泥石流运动方程，该方程荣誉泥石流的离散性、瞬变流动动力学和有限流动性，这些特性将泥石流与水主导的流动区分开来。从这张非局部泥石流动力学的详细图片中，研究人员将计算地质时期内基岩通道内的泥石流侵蚀。该模型将通过与地形分析的通道网络属性和千年尺度的侵蚀速率在OCR和SGM的泥石流占主导地位的山谷进行比较验证。他们将应用基于过程的建模方法，结合我们研究点的数据和观测，推导泥石流侵蚀的地貌输运规律，量化泥石流侵蚀对稳态景观形态的影响，该奖项反映了NSF的法定使命，并被认为是值得支持的，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。

项目成果

A progressive flow-routing model for rapid assessment of debris-flow inundation

用于快速评估泥石流淹没的渐进式流程模型

• DOI: 10.1007/s10346-022-01890-y
• 发表时间: 2022
• 期刊: Landslides
• 影响因子: 6.7
• 作者: Gorr, Alexander N.;McGuire, Luke A.;Youberg, Ann M.;Rengers, Francis K.
• 通讯作者: Rengers, Francis K.