Collaborative Research: An Inter-disciplinary Approach to Constraining Paleo-geomorphic Responses to the Eocene-Oligocene Hothouse to Icehouse Transition
合作研究:限制始新世-渐新世温室向冰室转变的古地貌响应的跨学科方法
基本信息
- 批准号:1844180
- 负责人:
- 金额:$ 11.35万
- 依托单位:
- 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:2019-07-01 至 2024-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Rivers are the arteries of the nation and are vital as sources of water and recreation, and avenues of commerce. They are also bellwethers for change in the landscape. However, a question of fundamental importance for national interest is how river systems respond to major environmental changes. Predicting how changes in environmental conditions affect river processes, such as flooding and erosion, is critical for water resource management. This project uses knowledge of the past as a key to better inform the present through examining ~35 million year old sediments from an ancient river network in western Nebraska and South Dakota to quantify how changes in precipitation, vegetation and temperature in the past caused changes in river discharge and flood magnitude. These data, integrated with hydraulic models, will improve our ability to predict how rivers flood, sediment is transported and catchments evolve. Results of this work will have far reaching implications for understanding, modeling and planning for changes to river systems in the future. Three key broader impacts of this study include: 1) support of graduate and undergraduate students to develop interdisciplinary expertise; 2) sharing of data, methods and results as teaching data-sets on open-access platforms; 3) science outreach modules for children to explore 3-dimensional rock outcrops and animations from computational models. The goal of the proposed research is to reconstruct the coevolution of paleoriver and ecosystems dynamics with environmental change in western North America during the Eocene-Oligocene transition (EOT), perhaps the largest climate state change of the last 65 million years. This will be accomplished by integrating geochemical records of paleoclimate, sedimentologic indicators of river transport and deposition, and hydraulic-geomorphic models. To achieve the project goals a team of geochemists, sedimentologists and hydraulic engineers will develop an integrated approach to understanding how rivers respond to environmental change. Success in this cross-disciplinary approach could provide a paradigm shift in utilizing modern and ancient terrestrial geologic archives to quantify environmental perturbations that manifest in the hydraulics, morphodynamics and regional ecosystem responses.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.
河流是国家的动脉,作为水和娱乐的来源以及商业途径至关重要。他们也是景观变化的铃铛。但是,对国家利益的根本重要性的问题是河流系统如何应对重大的环境变化。预测环境条件的变化如何影响河流过程,例如洪水和侵蚀,对于水资源管理至关重要。该项目以过去的知识为关键,通过检查内布拉斯加州西部和南达科他州的古河网络的约3500万年历史的沉积物来更好地告知现在,以量化过去的降水,植被和温度的变化如何导致河流排出和洪水量的变化。这些数据与液压模型集成在一起,将提高我们预测河流洪水,沉积物的运输和流域如何发展的能力。这项工作的结果将对未来的理解,建模和计划具有很大的影响。这项研究的三个主要广泛影响包括:1)支持研究生和本科生以发展跨学科专业知识; 2)在开放访问平台上共享数据,方法和结果作为教学数据集; 3)儿童科学外展模块探索计算模型的三维岩石露头和动画。拟议的研究的目的是重建西部北美西部北美环境变化的古代和生态系统动态的共同进化,这可能是过去6500万年的最大气候状态变化。这将通过整合古气候,河流运输和沉积的沉积学指标以及液压地球化模型的地球化学记录来实现。为了实现一个地球化学家团队的项目目标,沉积学家和液压工程师将开发一种综合方法来了解河流如何应对环境变化。在这种跨学科方法中的成功可能会在利用现代和古老的陆地地质档案库来量化环境扰动方面提供范式转变,这些档案表现出在液压,形态学和区域生态系统的响应中表现出来的。该奖项反映了NSF的法定任务,并通过评估了基金会的智力效果,并通过评估了基金会的范围。
项目成果
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Virginia Smith其他文献
Guardrail Baselines for Unlearning in LLMs
法学硕士遗忘的护栏基线
- DOI:
10.48550/arxiv.2403.03329 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Pratiksha Thaker;Yash Maurya;Virginia Smith - 通讯作者:
Virginia Smith
RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold
针对不正确合成数据的强化学习将 LLM 数学推理的效率提高了八倍
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Amrith Rajagopal Setlur;Saurabh Garg;Xinyang Geng;Naman Garg;Virginia Smith;Aviral Kumar - 通讯作者:
Aviral Kumar
Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients
Grass:使用结构化稀疏梯度计算高效的低内存 LLM 训练
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Aashiq Muhamed;Oscar Li;David Woodruff;Mona Diab;Virginia Smith - 通讯作者:
Virginia Smith
Is Support Set Diversity Necessary for Meta-Learning?
支持集多样性对于元学习是必要的吗?
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Amrith Rajagopal Setlur;Oscar Li;Virginia Smith - 通讯作者:
Virginia Smith
Temporal Soil Dynamics in Bioinfiltration Systems
生物渗透系统中的时态土壤动力学
- DOI:
10.1061/(asce)ir.1943-4774.0001617 - 发表时间:
2021 - 期刊:
- 影响因子:2.6
- 作者:
Christine Smith;R. Connolly;R. Ampomah;Amanda Hess;K. Sample;Virginia Smith - 通讯作者:
Virginia Smith
Virginia Smith的其他文献
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{{ truncateString('Virginia Smith', 18)}}的其他基金
Equipment: MRI: Track 2 Acquisition of a Hydraulic and Sediment Recirculation Flume to Advance Fundamental Research in Urban Stormwater and Fluvial Processes
设备: MRI:轨道 2 获取水力和沉积物再循环水槽,以推进城市雨水和河流过程的基础研究
- 批准号:
2320356 - 财政年份:2023
- 资助金额:
$ 11.35万 - 项目类别:
Standard Grant
CAREER: Foundations of Federated Multi-Task Learning
职业:联合多任务学习的基础
- 批准号:
2145670 - 财政年份:2022
- 资助金额:
$ 11.35万 - 项目类别:
Continuing Grant
Planning: SCC-PG: Smart, Sustainable, and Equitable Green Stormwater Systems in Urban Communities
规划:SCC-PG:城市社区智能、可持续和公平的绿色雨水系统
- 批准号:
2228035 - 财政年份:2022
- 资助金额:
$ 11.35万 - 项目类别:
Standard Grant
CAS- Climate: CDS&E: Facilitating Sustainable and Fair Transformation of GSI through AI
CAS-气候:CDS
- 批准号:
2152834 - 财政年份:2022
- 资助金额:
$ 11.35万 - 项目类别:
Standard Grant
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