Collaborative Research: Framework: Software: NSCI : Computational and data innovation implementing a national community hydrologic modeling framework for scientific discovery

Project: Research

Project Details

Description

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.

StatusFinished
Effective start/end date1/10/1830/09/23

Funding

  • National Science Foundation: $700,000.00

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