News & Opportunities
The Monitor My Watershed Data Sharing Portal evolved from work by the CUAHSI community for managing environmental data with the Observations Data Model. Monitor My Watershed accepts real-time sensor data and other observation types and provides data visualization and connection with CUAHSI’s HIS. Adoption and use of Monitor My Watershed is growing rapidly partly due to the extensive training resources for DIY hardware
Arc Hydro’s Wetland Identification Model (WIM) is an automated framework for identifying wetlands using machine learning. Its baseline functionality infers wetland likelihood from geomorphologic indicators, but WIM can be configured and extended for your use case. WIM continues to be developed and improved as we gather feedback from users and collaborators in the wetland science community. Our goal is to build a tool that helps that community achieve its goal of better, faster, cheaper wetland mapping.
Collecting, managing and analyzing high temporal (sub-minute) resolution residential water use data is challenging due to lack of existing tools, yet doing so enables better understanding of water use behavior that can help improve urban water management and planning by allowing direct identification of water appliances characteristics. This month's entry to the Hydroinformatics Blog presents low-cost, open-source tools designed to facilitate collection and analysis of this type of data.
Models are an integral part of hydrologic research and investigation. Over the past few years, we have made efforts to develop and implement solutions that allow graduate students to use a research hydrological model as part of their coursework. This setup has allowed us to introduce graduate students to research hydrological models and to perform meaningful model experiments.
The latest NOAA National Water Model retrospective is a 42-year, >100 TB compendium of meteorological, land surface, and hydrologic states and fluxes across the Contiguous U.S. I've rounded up a handful of great example workflows for how to probe this rich data resource to help answer your looming scientific questions.
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International Research Experience for Students Summer 2023 - El Salvador
Now seeking MS and PhD students to conduct hydrological and sociocultural research in El Salvador.
Accurate snowpack property measurements are needed as ground truth for remotely sensed data, as input for hydrological models, as input to ecological models, and as data when making avalanche forecasts. This course provides hands-on training and experience with snow measurements, to help directly with snow measurement research objectives and for interpreting snow measurements collected by others.
I Hack Water is a collaborative space for exploring water issues. We invite you to join us in Cambridge, MA to explore innovative approaches for making water knowledge equitable and inclusive. This year focuses on water issues local to the greater Boston area.
The conference aims to bring together watershed scientists, stakeholders, and managers to share scientific advances and management strategies to sustain the country’s water resources, spanning streams, rivers, lakes, and estuaries. This year’s theme is “Adaptive watershed science and ecosystem management in a changing climate.” Presenters will include researchers from government, academic, nonprofit, and community organizations working to protect, restore, and manage water resources at local to national scales.