August 1 - Submit Abstract to CUAHSI Organized Sessions at 2018 AGU Fall Meeting
AGU Fall Meeting
December 10 - 14, 2018 in Washington, D.C.
Abstracts are now being accepted for AGU's 2018 Fall Meeting! The abstract deadline is Wednesday, August 1, 2018 at 11:59 p.m. EDT.
We encourage you to submit your novel research to a session CUAHSI has organized. Continue reading below.
The sustainability of food, energy, and water resources is threatened by increasing population and climate change. The availability, management, and use of these resources are at the heart of human-nature interactions, which are intertwined with the ability of the food-energy-water (FEW) nexus system to meet societal demands while protecting ecosystem services. The resilience of this nexus system is complex, involving interconnections and interdependencies among global changes, socioeconomic pressures, governance policies, regional interventions, and human behaviors. It is therefore imperative to build interdisciplinary capability in data synthesis, cyberinfrastructure, and modeling frameworks to understand, predict, and support multi-scale decisions impacting FEW nexus sustainability. This session highlights challenges and recent progress from a diversity of interdisciplinary approaches to address FEW nexus issues.
Groundwater is a key component of the global water cycle. Groundwater controls baseflow and may affect terrestrial – atmospheric coupling through control of soil moisture, and, as such, must be included in terrestrial hydrologic and Earth-systems models. However, because of the differing temporal scales at which ground- and surface-water operate, and because water movement over the land surface is two-dimensional, whereas groundwater flows through a heterogeneous three-dimensional matrix, coupling these processes in hydrologic models is a major challenge. We seek papers and posters that offer novel approaches, including case studies, for coupling groundwater and surface water in terrestrial hydrologic and Earth systems models, especially at regional to continental scales.
H106: Research, Development and Evaluation of the National Water Model and Facilitation of Community Involvement
The NOAA National Weather Service, Office of Water Prediction, is leading development of the National Water Model (NWM). The NWM represents transformative cyberinfrastructure by providing a platform for community hydrologic model development. At its ultimate build-out, the NWM will include operational capabilities for forecasting the full suite of water budget variables at a continental scale, providing insight into floods, droughts, water quality and water supply. The development of the NWM provides natural collaborative opportunities for federal agencies involved in water prediction and the research and academic communities in both hydrologic and atmospheric sciences. Continental-scale hydrologic prediction represents a new frontier at the nexus of atmospheric and hydrologic modeling, with important connections to remote sensing, data assimilation, anthropogenic effects, big data, decision support, calibration and parameter estimation, machine learning, model testing and evaluation. This session seeks presentations or posters on any of these topics, facilitation of collaborations and enhancing community involvement.
ED060: Virtual Community Platforms and Tools for FAIR Data Management Planning: Supporting Your Research and Training the Next Generation
Currently, data management plan (DMP) usage is mostly limited to research proposals. Clear training, easy-to-access and use tools, and consistent policies are needed to help scientists develop DMPs and manage data more broadly and across multiple phases of scientific projects. In an effort to train current and future generations of scientists, virtual community platforms and training resources are being developed to provide services and support to ensure that DMPs are embedded in the scientific research lifecycle. Well-developed, executable, and machine-actionable DMPs can ultimately assist data to be Findable, Accessible, Interoperable, and Reusable (FAIR). We encourage submissions, especially case studies, describing training, policies, infrastructural activities, tools and platforms that leverage and help fulfill DMPs and that enable the scientific community to make their data FAIR.
Using real data can improve learning outcomes for students and the non-scientific public alike. In particular, data-driven curriculum can help students gain a better understanding of challenges in conducting research such as data scarcity and understanding metadata. The development of community cyberinfrastructure has lowered the barriers to data-driven education for many of the Earth Sciences. In this session, we solicit presentations describing place-based, data-driven learning exercises and their learning outcomes, in both classroom and community learning settings.
For more information, including how to submit an abstract, click here.