EAR-PF Dynamics from drones: using high-resolution repeat topography and grain size to differentiate between physically-based models of debris creation and debris flow initiation

Katherine R. Barnhart博士获得美国国家科学基金会EAR博士后奖学金，在科罗拉多大学和堪萨斯大学开展研究和教育计划。该项目旨在评估引发泥石流的机制。泥石流是由滑坡产生的泥土和岩石的含水泥浆，在陡峭的地形中迅速流过河道，对人类生命、基础设施和财产造成危害。为了让公众受益，这个项目的结果将包括一个景观演变模型，其中包括负责碎片补给的过程，以及负责实际泥石流开始的过程。该模型将改进泥石流易发地区的预测和风险评估。对于该项目的教育部分，Barnhart博士将开发一门大四-本科生和一年级研究生课程，重点是应用于地球科学的科学哲学，并对一个好的研究问题的成分进行调查。泥石流是最危险和最常见的自然灾害之一；一旦在陡峭的地区开始，泥石流可以继续在浅地形上移动，极大地扩大了危险，经常摧毁房屋和覆盖街道的泥浆，而清除这些泥浆的成本很高。与先决条件（如土壤湿度）和外部强迫（如地表水动力应力）有关的泥石流模型为从机制上理解和预测自然泥石流提供了机会。然而，泥石流易发地区陡峭而困难的地形妨碍了对起爆带的观察，这反过来又阻碍了将碎屑补给和泥石流起爆归因于特定机制。该项目将采用新颖的方法——包括基于无人机的摄影——在泥石流起源地的陡峭地形内进行观测。这些图像将绘制出地形和沉积物特征图，这将限制以下方面的数值模型：(1)泥石流事件之间流入河道的物质的数量和大小分布，(2)泥石流发生的时间和(3)泥石流发生的机制。

Dr. Katherine R. Barnhart has been granted an NSF EAR Postdoctoral Fellowship to carry out research and education plans at the University of Colorado and University of Kansas. The project seeks to assess the mechanisms responsible for initiating debris flows - water-laden slurries of soil and rock from landslides - that move rapidly through channels in steep landscapes and present hazards to human life, infrastructure and property. To benefit the public, the outcomes of this project will include a landscape evolution model incorporating processes responsible for the recharge of debris, and processes responsible for the actual debris flow initiation. This model will improve predictions and risk assessment in debris flow prone areas. For the education component of this project, Dr. Barnhart will develop a senior-undergraduate and first-year graduate student course focused on the philosophy of science as applied to the geosciences and an investigation into the ingredients of a good research question.Debris flows are among the most dangerous and frequent natural hazards; once initiated in a steep region, a debris flow can continue to travel over shallow terrain, greatly extending the hazard, frequently destroying houses and covering streets with mud, which is costly to remove. Models for debris flows that relate antecedent conditions (e.g., soil moisture) and external forcing (e.g., surface hydrodynamic stresses) provide an opportunity for mechanistic understanding and prediction of natural debris flows. However, the steep and difficult terrain in debris flow prone regions precludes the observation of initiation zones which, in turn, prevents attribution of debris recharge and flow initiation to specific mechanisms. The project will employ novel methods -including drone-based photography- to make observations within the steep terrain in debris-flow initiation zones. Maps of topography and sediment characteristics will be made from these images which will constrain numerical models for (1) the amount and size distribution of material delivered to the channel between debris flow events, (2) the timing and (3) mechanisms of debris flow initiation.