Workshop on Critical Timescales of Hydrologic Transport: A comparative study of response-time, travel-time, and information-flow timescales in focal watersheds from data and predictive models
Dates: May 22-24, 2019
Location: UC Berkeley
REGISTRATION: This workshop is full and seats are no longer available.
Please contact Zexuan Xu (firstname.lastname@example.org) to be placed on the wait list.
Admitted participants will be notified via email with instructions for attendance if a set becomes available.
All workshop and travel costs will be fully funded for the selected participants.
This workshop will bring together data scientists and watershed hydrologists at the Berkeley Institute for Data Science, May 22-24, 2019. Participants will include:
- Students and postdocs with strong data science and computing skills, looking to learn more about how to apply those skills to real-world hydrologic problems;
- Researchers trained in hydrology looking to learn new techniques for working with large hydrologic datasets and performing causal inference; and
- Anyone interested in gaining new skills and putting these skills to work toward solutions of an important research problem in hydrology.
This workshop will be part training, part hackathon, and will be focused on applying multiple time-series analysis techniques, hydrologic modeling, and isotope tracer approaches to understand fundamental controls on the timescales over which water moves through watersheds to generate streamflow.
We are trying to compile a database relevant to understanding how watersheds respond to precipitation and climatic factors, which will enable us to produce better forecasts of streamflow. In this workshop, we will work with data to try to understand what is often one of the greatest uncertainties in forecasting: the timescales over which watersheds respond to perturbation. We will work with data from two watersheds (HJ Andrews, Oregon, and East River, Colorado) that are currently a focus for the development of predictive models and have extensive data records from sensor networks and isotope studies. This workshop will be part training, part networking, and part hackathon, with a presentation of findings and discoveries at the end. For committed participants, there will also be opportunities to participate in journal papers that will emerge from the work done here. As an immediate short-term incentive, there will be monetary prizes associated with the hackathon.
Laurel is an assistant professor of earth systems science at the University of California, Berkeley, where she runs the Environmental Systems Dynamics Laboratory. Previously, she was a research ecologist and research hydrologist with the USGS in Reston, VA. Laurel’s research uses a variety of tools to identify the feedback processes driving environmental systems at the landscape scale. These tools include field and laboratory work, simulation modeling, and data-driven analysis using increasingly available environmental data from sensor networks and remote sensing platforms. Much of this work focuses on how water interacts with physical (e.g., sediment) and biological (e.g., plants) components of the environment, often in nonlinear ways that lead to thresholds, sudden shifts between alternate stable states, or chaotic behavior. Understanding these type of interactions enables anticipatory planning and improves the efficiency and effectiveness of restoration efforts. Her work has influenced restoration efforts in in the Everglades, with ongoing work focusing on the Chesapeake Bay and the Wax Lake Delta, part of the greater Mississippi River delta complex. Laurel earned her PhD from the University of Colorado at Boulder and also trained at Washington University in St. Louis.
At UC Berkeley, Zexuan Xu was a hydrology postdoctoral researcher working with the Clean Energy Research Center for Water-Energy Technologies (CERC-WET) and the Climate & Ecosystem Sciences Division (CESD) at Lawrence Berkeley National Laboratory (LBNL). Before joining Berkeley Lab, Zexuan received his PhD degree in hydrology and groundwater modeling at Florida State University (FSU). His PhD dissertation is “Data analysis and numerical modeling of seawater intrusion through conduit network in a coastal karst aquifer." As a hydrological modeler, Zexuan is proficient in several watershed and regional scale models for simulating hydrological processes in both subsurface and surface domains. He also has experience in downscaling of global and regional climate models on LBNL’s NERSC supercomputer system. His research focused on assessing the accuracy of these models compared to observational data, developing statistical corrections, and providing these inputs to hydrologic models and water resource studies.