All Funded Projects

The proposed work will create a seamless pilot dataset of continuous basin characteristics (for example upstream average precipitation, elevation, or dominant land cover type) for the conterminous United States. Basin characteristic data are necessary for training or parameterizing statistical, machine learning, and physical models, and for making predictions across the landscape...

The cloud offers new and exciting opportunities for USGS employees to leverage computing resources and services that can quickly improve their workflows and reduce expenditures typically associated with establishing a comparable environment with physical infrastructure. However, due to the novelty of access to and use of the cloud environment, there is limited documentation and shared...

Increasingly, USGS scientists seek to share and collaborate while working on data and code. Furthermore, these scientists often require advanced computing resources. Jupyter Notebooks are one such tool for creating these workflows. The files are interactive, code “notebooks” which allow users to combine code and text in one document, enabling scientists to share the stories held within...

Rangeland systems are some of our nation’s largest providers of agro-ecological services, sustaining plant productivity that is highly variable across seasons and years. Although the ability to predict the upcoming growing season’s rangeland productivity would have enormous economic and management value – such as for making decisions about cattle stocking rates, fire, restoration, and...

Computational models are important tools that aid process understanding, hypothesis testing, and data interpretation. The ability to easily couple models from various domains such as, surface-water and groundwater, to form integrated models will aid studies in water resources. This project investigates the use of the Community Surface Dynamics Modeling System (CSDMS) Modeling Framework...

FAIR is an international set of principles for improving the findability, accessibility, interoperability, and reusability of research data and other digital products. The PIs for this CDI project planned and hosted a workshop of USGS data stakeholders, data professionals, and managers of USGS data systems from across the Bureau’s Mission Areas. Workshop participants shared case studies...

The goal of this project was to maximize the value of expensive animal tagging data. We developed an interactive web application to help scientists understand patterns in their own tagging datasets and to help scientists, funders and agencies communicate tagging data to decision-makers and to the general public. Interactive visualizations have emerged recently as a valuable tool for...

Sinkholes present hazards to humans due to subsidence and by focusing contaminated surface water runoff into groundwater. Sinkholes create instability in the foundations of buildings, roads and other infrastructure, resulting in damage and in some cases loss of life, but may also play an important role as vernal pools in some ecosystems. This project created a prototype nationwide...

Environmental DNA (eDNA) testing allows for high sensitivity monitoring efforts of cryptic species in large, remote systems and is performed by investigating water and soil samples for sloughed DNA. Having access to eDNA datasets across multiple taxa and ecosystems is necessary for improved coordination among researchers and management. Additionally, quality control protocols are needed...

Geochronological data provide essential information necessary for understanding the timing of geologic processes and events, as well as quantifying rates and timescales key to geologic mapping, mineral and energy resource and hazard assessments. The USGS’s National Geochronological Database (NGDB) contains over 30,000 radiometric ages, but no formal update has occurred in over 20 years...

We developed an Internet of Things (IoT) prototype and associated cloud infrastructure for camera-based data collection and initial processing of river streamflow using the cloud (fig. 1). This pilot successfully created a hardware and cloud infrastructure to collect and upload video from a camera gage at San Pedro Creek in San Antonio, Texas. Using a ThingLogix Foundry instance in the...

Advances in information technology now provide large volume, high-frequency data collection which may improve real-time biosurveillance and forecasting. But, big data streams present challenges for data management and timely analysis. As a first step in creating a data science pipeline for translating large datasets into meaningful interpretations, we created a cloud-hosted PostgreSQL...