News
Hydroinformatics Blog - Advances in biogeochemical modeling and management of San Francisco Bay ecosystem
Posted Dec 7, 2023
San Francisco Bay (SFB) is a nutrient-enriched estuary that is at risk of experiencing adverse effects of nutrient enrichment as evidenced by harmful algal blooms. A numerical model is developed and validated for 6 water years to simulate hydrodynamics and biogeochemical processes in SFB. The model is employed to answer applied science questions related to nutrient transport and cycling and the effects of nutrients on water quality in SFB.
HYDROINFORMATICS BLOG - Hello to GroMoPo: Introducing a community Groundwater Model Portal
Posted Oct 9, 2023
Get familiar with GroMoPo - a community Groundwater Model Portal meant to help share and discover groundwater models.
Hydroinformatics Blog - FAIR and CARE Data Principles Assessment for Sustainable Water Resources Management on Reservation Lands
Posted Sep 13, 2023
Water resources management by Indigenous Peoples in the U.S. is a complex issue hindered by the lack of reliable and accessible high-quality databases. To address this challenge, we have initiated a research project to evaluate the availability of water-related databases for reservation lands in the U.S. The project focuses on the discoverability and reusability assessment of these databases in terms of both water quality and quantity variables with the goal of environmental justice for Indigenous communities.
Hydroinformatics Blog - A framework for conducting environmentally-responsible hydroinformatics research
Posted Jul 11, 2023
The Environmental Responsibility 5-R Framework provides researchers across disciplines with a valuable toolbox for critically evaluating and mitigating the environmental impacts of their work. This framework provides actionable methods to this end by providing resources for incorporating data and computational costs into their research recognition, refining research questions through open-source data platforms, and optimizing codes for minimal resource usage. With the 5-R Framework in practice, we believe that scientists can pursue environmentally responsible practices while leveraging the power of data science and informatics.
2023 CUAHSI Biennial
Posted Jun 22, 2023
2023 CUAHSI Biennial Recap
CUAHSI would like to thank everyone who participated in the 2023 Biennial Colloquium, held from June 11-14 at the Granlibakken Resort in Tahoe City, CA.
Hydroinformatics Blog - Classifying NHDPlus catchments based on drought propagation mechanism
Posted Jun 6, 2023
Understanding the driving mechanisms of droughts is critical for reducing and minimizing their impact. In this blog post, we employ a deep learning algorithm to predict the drought propagation mechanism over CONUS based hydrocliamte characteristics of NHDPlus catchments. We use HyRiver to retrieve and process the required input data including climate time series and catchment attributes and PyTorch Tabular to predict the drought propagation mechanisms.
Hydroinformatics Blog - A Case for Open Source-based Digital Water Systems
Posted May 10, 2023
Digital transformation stands to transform the operation and design of urban water networks. However, fundamental socio-technical knowledge gaps must be answered before these systems become commonplace. In this post, I make a case that open-source philosophy can help address some of these challenges and create accessible and equitable digital water technologies.
April e-Newsletter
Posted Apr 13, 2023
The CUAHSI April e-Newsletter came out today! Be sure to read on for more details about announcements, upcoming events and opportunities!
Hydroinformatics Blog - Monitor My Watershed Helps Lower Barriers for Real-time Data Sharing
Posted Jan 10, 2023
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
Hydroinformatics Blog - Arc Hydro’s WIM: A Machine Learning Framework for Wetland Identification
Posted Dec 7, 2022
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.