Collaborative Research: Framework: Software: NSCI : Computational and data innovation implementing a national community hydrologic modeling framework for scientific discovery
合作研究:框架:软件:NSCI:计算和数据创新实施国家社区水文建模框架以促进科学发现
基本信息
- 批准号:1835569
- 负责人:
- 金额:$ 34万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-10-01 至 2023-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This award supports the design and implementation of a software framework to simulate the movement of water at various scales. Understanding the movement and availability of water locally and across the country is of paramount importance to economic productivity and human health of our nation. Hydrologic scientists, are actively tackling these challenges using increasingly complex computational methods. However, modeling advances have not been easily translated to the broader community of scientists and professionals due to technical barriers to entry. This software platform draws from computer models and employs supercomputers capable of analyzing big data to provide unprecedented simulations of water movement over the continental US. Combining hydrologists and computer scientists the team behind the project envision a broad community of users who will have multiple ways to interact with the software framework. For the hydrologic scientist who is interested in generating their own scenarios the framework will facilitate direct interaction with the hydrologic models and the ability to generate simulations on the fly. Conversely, the framework will also provide a set of static output and a range of tools for a broader set of users who would like to evaluate hydrologic projections locally or extract model data for use in other analyses.Continental scale simulation of water flow through rivers, streams and groundwater is an identified grand challenge in hydrology. Decades of model development, combined with advances in solver technology and software engineering have enabled large-scale, high-resolution simulations of the hydrologic cycle over the US, yet substantial technical and communication challenges remain. With support from this award, an interdisciplinary team of computer scientists and hydrologists is developing a framework to leverage advances in computer science transforming simulation and data-driven discovery in the Hydrologic Sciences and beyond. This project is advancing the science behind these national scale hydrologic models, accelerating their capabilities and building novel interfaces for user interaction. The framework brings computational and domain science (hydrology) communities together to move more quickly from tools (models, big data, high-performance computing) to discoveries. It facilitates decadal, national scale simulations, which are an unprecedented resource for both the hydrologic community and the much broader community of people working in water dependent systems (e.g., biological system, energy and food production). These simulations will enable the community to address scientific questions about water availability and dynamics from the watershed to the national scale. Additionally, this framework is designed to facilitate multiple modes of interaction and engage a broad spectrum of users outside the hydrologic community. We will provide easy-to-access pre-processed datasets that can be visualized and plotted using built-in tools that will require no computer science or hydrology background. Recognizing that most hydrology training does not generally include High Performance Computing and data analytics or software engineering, this framework will provide a gateway for computationally enhanced hydrologic discovery. Additionally, for educators we will develop packaged videos and educational modules on different hydrologic systems geared towards K-12 classrooms.This award by the NSF Office of Advanced Cyberinfrastructure is jointly supported by the Cross-Cutting Activities Program of the Division of Earth Sciences within the NSF Directorate for Geosciences.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.
该奖项支持软件框架的设计和实施,以模拟各种尺度的水运动。了解当地和全国的水资源流动和可用性对我们国家的经济生产力和人类健康至关重要。水文科学家正在积极利用日益复杂的计算方法来应对这些挑战。然而,由于技术壁垒的进入,建模的进步并不容易转化为更广泛的科学家和专业人士社区。该软件平台借鉴了计算机模型,并采用能够分析大数据的超级计算机,以提供美国大陆水运动的前所未有的模拟。结合水文学家和计算机科学家,该项目背后的团队设想了一个广泛的用户社区,他们将有多种方式与软件框架进行交互。对于有兴趣生成自己的情景的水文科学家来说,该框架将促进与水文模型的直接交互以及实时生成模拟的能力。相反,该框架还将为更广泛的用户提供一套静态输出和一系列工具,这些用户希望在当地评估水文预测或提取模型数据用于其他分析。通过河流,溪流和地下水的水流的大陆尺度模拟是水文学中的一项重大挑战。几十年的模型开发,结合求解器技术和软件工程的进步,使美国的水文循环的大规模,高分辨率的模拟,但实质性的技术和通信挑战仍然存在。在该奖项的支持下,一个由计算机科学家和水文学家组成的跨学科团队正在开发一个框架,以利用计算机科学的进步来改变水文科学及其他领域的模拟和数据驱动的发现。该项目正在推进这些国家级水文模型背后的科学,加速其功能并为用户交互构建新颖的界面。该框架将计算和领域科学(水文学)社区聚集在一起,以更快地从工具(模型,大数据,高性能计算)转向发现。它促进了十年期的全国规模的模拟,这对于水文界和更广泛的在依赖水的系统中工作的人们来说是一种前所未有的资源(例如,生物系统、能源和粮食生产)。这些模拟将使社区能够解决从流域到全国范围的水资源可用性和动态的科学问题。此外,该框架旨在促进多种互动模式,并吸引水文界以外的广泛用户。我们将提供易于访问的预处理数据集,这些数据集可以使用内置工具进行可视化和绘制,不需要计算机科学或水文学背景。认识到大多数水文培训通常不包括高性能计算和数据分析或软件工程,该框架将为计算增强的水文发现提供一个网关。此外,本发明还对于教育工作者,我们将开发针对K-12教室的不同水文系统的打包视频和教育模块。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学术价值和更广泛的影响审查标准。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating Model‐Agnostic and Model‐Specific Configuration Steps in Applications of Large‐Domain Hydrologic Models
- DOI:10.1029/2021wr031753
- 发表时间:2021-12
- 期刊:
- 影响因子:5.4
- 作者:W. Knoben;M. Clark;J. Bales;Andrew R. Bennett;S. Gharari;C. Marsh;Bart Nijssen;A. Pietroniro;R. Spiteri;D. Tarboton;A. Wood
- 通讯作者:W. Knoben;M. Clark;J. Bales;Andrew R. Bennett;S. Gharari;C. Marsh;Bart Nijssen;A. Pietroniro;R. Spiteri;D. Tarboton;A. Wood
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David Tarboton其他文献
Intercomparison of the U.S. National Water Model with OpenET over the Bear River Basin, U.S.
美国国家水模型与美国贝尔河盆地的 OpenET 之间的比对
- DOI:
10.1016/j.jhydrol.2025.132826 - 发表时间:
2025-08-01 - 期刊:
- 影响因子:6.300
- 作者:
Ayman Nassar;David Tarboton;Martha Anderson;Yun Yang;Joshua B. Fisher;Adam J. Purdy;Furqan Baig;Cenlin He;David Gochis;Forrest Melton;John Volk - 通讯作者:
John Volk
David Tarboton的其他文献
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{{ truncateString('David Tarboton', 18)}}的其他基金
EarthCube Data Capabilities: Collaborative Research: Integration of Reproducibility into Community CyberInfrastructure
EarthCube 数据功能:协作研究:将可重复性集成到社区网络基础设施中
- 批准号:
1928369 - 财政年份:2019
- 资助金额:
$ 34万 - 项目类别:
Standard Grant
Collaborative Research: SI2-SSI: Cyberinfrastructure for Advancing Hydrologic Knowledge through Collaborative Integration of Data Science, Modeling and Analysis
合作研究:SI2-SSI:通过数据科学、建模和分析的协作集成推进水文知识的网络基础设施
- 批准号:
1664061 - 财政年份:2017
- 资助金额:
$ 34万 - 项目类别:
Standard Grant
RAPID:Archiving and Enabling Community Access to Data from Recent US Hurricanes
RAPID:存档并允许社区访问最近美国飓风的数据
- 批准号:
1761673 - 财政年份:2017
- 资助金额:
$ 34万 - 项目类别:
Standard Grant
Collaborative Research: Improving Student Learning in Hydrology & Water Resources Engineering by Enabling the Development, Sharing and Interoperability of Active Learning Resou
合作研究:提高学生的水文学学习
- 批准号:
1725989 - 财政年份:2017
- 资助金额:
$ 34万 - 项目类别:
Standard Grant
EarthCube Building Blocks: Collaborative Proposal: GeoTrust: Improving Sharing and Reproducibility of Geoscience Applications
EarthCube 构建模块:协作提案:GeoTrust:提高地球科学应用的共享性和可重复性
- 批准号:
1639655 - 财政年份:2016
- 资助金额:
$ 34万 - 项目类别:
Standard Grant
Collaborative Research: SI2-SSI: An Interactive Software Infrastructure for Sustaining Collaborative Community Innovation in the Hydrologic Sciences
协作研究:SI2-SSI:用于维持水文科学领域协作社区创新的交互式软件基础设施
- 批准号:
1148453 - 财政年份:2012
- 资助金额:
$ 34万 - 项目类别:
Standard Grant
Collaborative Research: Development of Adaptable Web Modules to Stimulate Active Learning in Hydrology using Data and Model Simulations
协作研究:开发适应性网络模块,利用数据和模型模拟促进水文学主动学习
- 批准号:
1122812 - 财政年份:2011
- 资助金额:
$ 34万 - 项目类别:
Standard Grant
U.S.-New Zealand Cooperative Research: Spatially Distributed Hydrologic Models and Spatial Patterns
美国-新西兰合作研究:空间分布水文模型和空间模式
- 批准号:
9724720 - 财政年份:1997
- 资助金额:
$ 34万 - 项目类别:
Standard Grant
Geomorphological Processes, Scale and the Evolution of Fluvial Landforms
地貌过程、规模和河流地貌的演化
- 批准号:
9318977 - 财政年份:1994
- 资助金额:
$ 34万 - 项目类别:
Standard Grant
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