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Karen R Ryberg, Ph.D.

Research Statistician for the Dakota Water Science Center

Expertise/Projects/Research Interests

  • Statistical analysis of hydrologic data, including parametric and nonparametric trend analysis and cluster analysis
  • Trend analysis for pesticide concentrations in surface water
  • Research related to the impact of climate variability on surface water
  • Data mining including automated data retrieval and analysis, outlier detection, and data cleaning
  • Machine learning
  • Graphical presentation of scientific data
  • R - Open Source Statistical Software
    • waterData package - Retrieval, analysis, and anomaly calculation of daily hydrologic time series data
    • seawaveQ package - A model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables
  • Associate Editor, Hydrological Sciences Journal
  • Course Coordinator and member of team teaching Statistical Methods for Environmental Data Analysis at USGS National Training Center


Ryberg, K.R., 2021, The role of the U.S. Geological Survey in monitoring North Dakota’s environmental conditions: North Dakota Climate Bulletin, v. 15, no. 1, p. 11–14,

Helsel, D.R., Hirsch, R.M., Ryberg, K.R., Archfield, S.A., and Gilroy, E.J., 2020, Statistical methods in water resources: U.S. Geological Survey Techniques and Methods, book 4, chapter A3, 458 p., [Supersedes USGS Techniques of Water-Resources Investigat