• kelseylynnchauvin

AGU 2020 Poster: On-line Learning Activities concerning Hydrologic Droughts and Drying Rivers

Presented: December 8, 2020

Dr. Joann Mossa (University of Florida) and Dr. Hilary McMillan (San Diego State University) presented a poster at the AGU 2020 conference on their HydroLearn module, Hydrologic Droughts and Drying Rivers. The poster outlines concepts that are covered in the module that was a product of Hydrolearn’s Summer 2020 Hackathon.

This module begins with the basics of identifying drought types as well as drought magnitude, frequency, and duration. Afterward, the module examines a variety of drought indices used in different situations and applies real-world data to the calculation of drought metrics.

Next, the module uses streamflow data to examine flow regime and hydrologic droughts by using traditional daily flow, comparative before-after impact flow, and dimensionless flow duration curves. Students then learn strategies to communicate information about hydrologic droughts and drying rivers by adapting the climate or warming stripes method of Ed Hawkins, which uses color to convey trends in global warming, to create "streamflow stripes". This is allowing students to create streamflow heat maps or streamflow square strips to show trends and seasonal water deficits using monthly averages of streamflow over several decades. With the authentic, real-world application tools embedded in this module, students will gain the knowledge of how to approach the issue of hydraulic droughts and drying rivers, taking in consideration environmental and geographical factors.

Check out the poster here!

If you want to be a part of the HydroLearn community, check out our webpage for our upcoming summer 2021 Hackathon! Requests for applications will be announced soon.

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The HydroLearn project is supported by the National Science Foundation (NSF) under collaborative awards DUE-IUSE 17269651725989, and 1726667; I-Corps 1644493; TUES 1122898; and CCLI 0737073.  Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF. 

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