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Why model streamflow?
Why model streamflow?
Anthropogenic climate warming acts largely at seasonal timescales resulting in changes in seasonal phases and amplitudes of air temperature and precipitation.
This can lead to changes in hydroclimate processes – seasonal shifts in peak runoff, evaporation, and soil moisture -- which can have impacts on water availability and security, freshwater biodiversity, and other ecosystem services.
Assessments of trends in seasonal variability in streamflow are needed to inform water management and adaptation strategies and policy under global change.
This shiny app was developed by undergraduate research assistant and university honors student Jake Riehle.
We have created a Shiny App allows users to interact with USGS streamflow data from 1965 to 2022 from over 1000 gages located across the north temperate region of the conterminous United States. The Shiny App depicts results from a Bayesian hierarchical model using Fourier harmonic functions developed with the following goals:
leverage the high temporal resolution of daily streamflow
robust to the inherent daily variability in streamflow time series
enable inferences about the spatiotemporal trends in seasonal river hydrographs
identify rivers undergoing similar changes in seasonal flow profiles -- shifts in flow event timing and magnitude -- to help understand large-scale patterns in shifting streamflow profiles.
Users of the app can explore changes in streamflow profiles across any gage and year used in our analysis. Specifically, we encourage uses to investigate the following:
Tab 1 illustrates semiannual and triannual harmonics of streamflow for any year and stream gage
Tab 2 depicts temporal changes in streamflow by overlaying multiple years of estimated streamflow profiles for a given stream with credible bands
Tab 3 compares streamflow profiles graphically for two time periods, early (1965 - 1989) and late (1999 - 2023), and the difference on each day, for a given stream
Tab 4 shows four clusters of rivers that are experiencing similar structural changes in seasonal streamflow. Clusters are based on six hyrdologic indices -- day of minimum flow, day of maximum flow, day of center, 10th percentile of daily flow, 90th percentile of daily flow, and minimum derivative of flow.
Tab 1
Tab 2
Tab 3
Tab 4
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