EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021
(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)
5/23/2019 | 9:45 AM - 10:00 AM | CALIFORNIA ENVIRONMENTAL FLOWS FRAMEWORK (CEFF) DECISION SUPPORT TOOLS II: PREDICTING FUNCTIONAL FLOW METRICS AT UNGAGED LOCATIONS | 250 CF
CALIFORNIA ENVIRONMENTAL FLOWS FRAMEWORK (CEFF) DECISION SUPPORT TOOLS II: PREDICTING FUNCTIONAL FLOW METRICS AT UNGAGED LOCATIONS
California’s environmental flows framework requires decision-support tools for statewide implementation. Given the paucity of active streamgaging sites, there is a particular need for a tool that provides information about stream segments that lack measured streamflow data. We describe the development of machine-learning models that predict expected natural Functional Flow Metrics (FFMs) using a combination of watershed physical features and time-varying weather data. FFMs were computed at two hundred sites with daily flow data spanning 5 to 65 years of record. Model performance was assessed using 1000 randomly selected combinations of calibration and validation data subsets. In general, FFMs representing magnitude were most successfully modeled, whereas FFMs for timing and duration were most difficult to model. We summarize the combinations of watershed physical features and climate that were most important predictors of FFMs. Finally, we illustrate how the models will be applied to the stream network to guide development of environmental flow criteria.
- Assessment
- Environmental Regulation
- Biodiversity
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Presenters/Authors
Daren Carlisle
(), U.S. Geological Survey, dcarlisle@usgs.gov;
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Ted Grantham
(), University of California, Berkeley, tgrantham@berkeley.edu;
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Belize Lane
(), Utah State University, belize.lane@usu.edu;
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