Collaborative Research: From rock to regolith to rivers: weathering, grain size, and controls on soil production and fluvial incision

土壤是一种重要的资源，但控制土壤生产的过程还没有得到很好的理解。在以前的NSF资助的研究中收集的数据，沿着新的数据，将被用来更好地了解土壤是如何在不同的环境中产生的。土壤的深度可能与土壤的生产率和河流的侵蚀方式密切相关。河流和土壤的相互作用对河流基础设施和人类对森林砍伐或森林火灾等景观的影响具有实际影响。在不断变化的地球上，土壤的可持续性如何？本科生和研究生以及博士后学者将为该研究项目做出贡献。该团队还将使用3D打印机制作合成景观，用于为视力受损或患有自闭症谱系障碍的K-12学生提供服务。在卢基略临界区观测站的里奥布兰科流域，我们将绘制整个景观的表层土壤厚度，粒度和土壤化学的模式，并将其与新的土壤生产率和土壤颗粒停留时间联系起来。将使用Landlab建模工具包和最近发布的分析模型对理论山坡-渠道耦合进行建模，该模型预测作为气候和侵蚀速率函数的渠道沉积物粒度分布，控制土壤颗粒的停留时间。我们还将建立一个新的河流切割建模组件，以纳入沉积物负荷的影响，包括粒度，对基岩切割率。此外，来自里奥布兰科的数据将用于校准土地实验室模型。该奖项反映了NSF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。

Soil is a vital resource but processes controlling soil production are not well understood. Data collected in previously NSF-funded studies, along with new data, will be used to better understand how soil is produced in different environments. The depth of soil is likely closely linked to the soil production rate and how rivers erode. How rivers and soils interact has practical consequences for river infrastructure and human impacts on landscapes such as deforestation or forest fires. How sustainable is soil given a changing Earth? Undergraduate and graduate students and a post-doctoral scholar will contribute to this research project. The team will also use 3D printers to make synthetic landscapes to be used as part of outreach to K-12 students who are visually impaired or have Autism Spectrum Disorder.In the Rio Blanco watershed in the Luquillo Critical Zone Observatory, we will map patterns in surface soil thickness, grain size, and soil chemistry across the landscape and tie these to new rates of soil production and soil grain residence time. Theoretical hillslope-channel coupling will be modeled using the Landlab modeling toolkit and a recently published analytical model that predicts the grain size distribution of sediment fed to channels as a function of climate and erosion rate, which controls the residence time of soil particles. We will also build a new fluvial incision modeling component to incorporate the influence of sediment load, including grain size, on bedrock incision rates. Further, data from the Rio Blanco will be used to calibrate a Landlab model.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.