Past Events:

California Water Data Consortium May 2023 Data for Lunch

May 23 2023
The California Water Data Consortium is proud to host a presentation Machine Learning for Rivers: How Data Science Can Inform Water Mgmt.

Data for Lunch Series

This event is part of the Consortium’s Data for Lunch series, which provides an opportunity to learn about innovative water data-related projects.

Date: May 23rd from 12:00 – 1:00 pm, with additional Q&A from 1-1:30pm

Presenters: Kirk Klausmeyer, Director of Data Science for The Nature Conservancy’s California Program and Laura Read, Head of Product Strategy for HydroForecast at Upstream Tech

Meeting Agenda

  • Welcome and introduction (10 mins)
  • Presentation (30 mins)
  • Facilitated discussion (15 mins)
  • Additional Q&A time (30 mins)

Presentation Title: Machine Learning for Rivers: How Data Science Can Inform Water Management in California

Presentation Recording:


Presentation Summary

Water management in California is plagued by missing data. Typical questions include:

  • How much water should naturally be flowing in this stream?
  • How much water is actually flowing in this stream?

Stream gages only cover about 10% of rivers in the state, and 70% of watersheds have no active gages and no history of gages. But with recent advances in data science and machine learning, we will soon be able to answer these questions for most rivers in California. In this talk we will present the results of our machine learning pipeline that converts monthly precipitation and temperature data into natural or unimpaired stream flow predictions for >95% of the rivers in California. These data are currently available on We will also present some initial results from our efforts to predict both unimpaired and impaired (actual) flows at the daily time-step from 2000 to the present. The presentation will conclude with a Q&A session where the audience can interact with the speakers to explore the implications of predicting river flows with machine learning.


Kirk Klausmeyer is the Director of Data Science for The Nature Conservancy’s California Program. In his 18 years at the Conservancy, Kirk has made significant contributions to California’s environmental conservation efforts. He has built a machine learning data pipeline to predict natural flows in all the rivers in the state, mapped groundwater dependent ecosystems to inform groundwater management, and analyzed satellite and drone data to track habitat for migratory birds. Kirk has authored/co-authored 17 publications in peer-reviewed journals while working at the Conservancy. Kirk graduated Suma Cum Laude with a B.A. in environmental studies and economics from Dartmouth College and has an M.A. in environmental planning from UC Berkeley. Kirk also loves anything to do with Mars and hopes to visit it someday.

Laura Read is a water resources engineer with 10 years of experience in hydrologic modeling, forecasting, and decision tools. She has a PhD from Tufts University and a M.S.E. from the University of Texas at Austin both in Environmental and Water Resources Engineering. At Upstream Tech she is Head of Product Strategy for HydroForecast, where she leads the technical direction and strategy based on industry and customer feedback. Her passions are learning and thinking on how data can be used for creating a sustainable future for all living things. Outside of work, Laura plays tennis, jams on the drums and spends summer days in her garden.

Learn about future events by subscribing to the California Water Data Consortium’s listserve here.

Available Materials:

  • Natural-Flows-Database_Data4Lunch.pdf
  • 2023-05-23-CA-Open-Data-Consortium-Read_LK-presentation-1.pdf