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We are working to incorporate environmental DNA (eDNA) data into the Nonindigenous Aquatic Species (NAS) database, which houses over 570,000 records of nonindigenous species nationally, and already is used by a broad user-base of managers and researchers regularly for invasive species monitoring. eDNA studies have allowed for the identification and biosurveillance of numerous invasive and threatened species in managed ecosystems. Managers need such information for their decision-making efforts, and therefore require that such data be produced and reported in a standardized fashion to improve confidence in the results. As we work to gain community consensus on such standards, we are finalizing the process for submitting...
The purpose of this study is to understand how the USGS is using decision support, learning from successes and pitfalls in order to help streamline the design and development process across all levels of USGS scientific tool creation and outreach. What should researchers consider before diving into tool design and development? Our goal is to provide a synthesis of lessons learned and best practices across the spectrum of USGS decision support efforts to a) provide guidance to future efforts and b) identify knowledge gaps and opportunities for knowledge transfer and integration. Principal Investigator : Amanda E Cravens Co-Investigator : Nicole M Herman-Mercer, Amanda Stoltz
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Wildfires affect streams and rivers when they burn vegetation and scorch the ground. This makes floods more likely to happen and reduces water quality. Public managers, first responders, fire scientists, and hydrologists need timely information before and after a fire to plan for floods and water treatment. This project will create a method to combine national fire databases with the StreamStats water web mapping application to help stakeholders make informed decisions. When the project is finished, people will be able to use StreamStats to estimate post-wildfire peak flows in streams and rivers for most of the United States (where data is available). There will also be tools that allow users to trace upstream and...
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Autonomous Underwater Vehicles (AUVs) are instruments that collect water-quality, depth, and other data in waterbodies. They produce complex and massive datasets. There is currently no standard method to store, organize, process, quality-check, analyze, or visualize this data. The Waterbody Rapid Assessment Tool (WaterRAT) is aPython application that processes and displays water-quality data with interactive two-dimensional and three-dimensional figures, but it runs offline with few capabilities and for just one study site. This project will transition WaterRAT to an online application that the public can easily use to view all AUV data. A database of all AUV datasets will be developed to improve accessibility,...
Artificial Intelligence (AI) is revolutionizing ecology and conservation by enabling species recognition from photos and videos. Our project evaluates the capacity to expand AI for individual fish recognition for population assessment. The success of this effort would facilitate fisheries analysis at an unprecedented scale by engaging anglers and citizen scientists in imagery collection.This project is one of the first attempts to apply AI towards fish population assessment with citizen science. Principal Investigator : Nathaniel P Hitt Co-Investigator : Natalya I Rapstine, Mona (Contractor) Arami, Jeff T Falgout, Benjamin Letcher, Nicholas Polys Cooperator/Partner : Sophia Liu, Fraser Hayes, Ky Wildermuth, Bryan...
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A unique opportunity for USGS to collaborate with IRIS-PASSCAL (the national seismic instrument facility) has presented itself to develop a geophysical data archive format that follows FAIR principles. IRIS-PASSCAL is extending facility to include magnetotelluric (MT) instruments prescribing the need for them to archive collected MT data by extending their existing protocol. Concurrently, Congress has mandated the USGS to collect nationwide MT data (5000 stations) which will all need to be archived under FAIR principles. In collaboration with IRIS-PASSCAL, we propose to develop a generalized HDF5 format for archiving MT data which can easily be extended to other geophysical data in the future. This project will...
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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 examples detailing how those resources and services are being used across the USGS. Developing a platform that allows cloud users to contribute to the available documentation and provides a location to consolidate information relevant to operating in the USGS cloud will help to decrease duplication of efforts across projects that share...
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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, particularly in areas where there are no observations. The pilot dataset will be accessible to the public via an interactive map and Web-based query service. The pilot dataset, USGS software used to produce it, and a publication on the processing methods will be generated. This work represents a substantial addition to USGS data services...
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Understanding and anticipating change in dynamic Earth systems is vital for societal adaptation and welfare. USGS possesses the multidisciplinary capabilities to anticipate Earth systems change, yet our work is often bound within a single discipline and/or Mission Area. The proposed work breaks new ground in moving USGS towards an interdisciplinary predictive modeling framework. We are initially leveraging three research elements that cross the Land Resources and Water Mission Areas in an attempt to “close the loop” in modeling interactions among water, land use, and climate. Using the Delaware River Basin as a proof-of-concept, we are modeling 1) historical and future landscapes (~1850 to 2100), 2) evapotranspiration...
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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 their data. Recently, USGS launched an instance of Pangeo—a community platform for Big Data geoscience—as a tool for internally hosting and executing these notebooks. Few examples exist on how to use Pangeo and no formal documentation exists for USGS scientists to use Pangeo. We will create and curate examples of using Jupyter Notebooks...
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In the mid-1800s, tile-drains were installed in poorly-drained soils of topographic lows as water management to protect cropland during wet conditions; consequently, estimations of tile-drain location have been based on soil series. Most tile drains are in the Midwest, however each state has farms with tile and tile-drain density has increased in the last decade. Where tile drains quickly remove water from fields, groundwater and stream water interaction can change, affecting water availability and flooding. Nutrients and sediment can quickly travel to streams thru tile, contributing to harmful algal blooms and hypoxia in large water bodies. Tile drains are below the soil surface, about 1 m deep, but their location...
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Rangeland ecosystems are one of the largest single providers of agro-ecological services in the U.S. The plant growth of these rangelands helps determine the amount of forage available for our livestock and for wildlife, as well as information about fire likelihood and restoration opportunities. However, every spring, ranchers and other rangeland managers face the same difficult challenge —trying to approximate how much and where grass will be available during the upcoming growing season. This project represents an innovative grassland productivity forecasting tool, named “Grass-Cast”, which we are developing for the US Southwest to help managers and producers in the region reduce this economically important source...
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Many coastal areas are experiencing departures from normal conditions due to changing land use and climate patterns, including increased frequency, severity, or duration of floods and droughts, in some cases combinations of the two. To address these issues, the U.S. Geological Survey developed the Coastal Salinity Index (CSI) to identify and communicate fluctuating salinity conditions due to such disturbance events through quantitative analyses of long-term salinity records. This project aims to make the CSI broadly useful as a monitoring, forecasting, and decision-making tool, extending the platform to enable real-time reporting of disturbance events as they unfold and covering a larger user base than what existing...