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My 30-Year Struggle with the Rosgen Stream Classification - Can We Reduce the Struggle? 

Bob Siegfried
RES
Richmond VA

Authors:  Bob Siegfried

After 30 years of using the Rosgen Stream Classification, I find it a great communication tool.  However, I still find myself struggling with the metrics in the classification chart.  Experienced practitioners often determine Rosgen stream types without a bankfull call, width/depth ratio, entrenchment ratio, or sinuosity.  We don’t “let the numbers confuse us”.  Yet, less experienced practitioners might struggle, finding it difficult to understand why their field measurements do not provide a clear stream type.

To help resolve some of the struggles, I looked at what makes a classification system effective.  For stream type, an effective classification tool should be built around four defining goals and the question that those goals answer:

  • Tying classification metrics to underlying processes

    • What drives stream formation?

  • Ensuring metrics are objective and measurable

    • Can we measure the drivers effectively?

  • Minimizing overlap and ambiguity between classes

    • Can we put streams in well-defined classes?

  • Allowing for flexibility without loss of rigor

    • Can we accommodate natural variation without degrading the utility of classification?

 I review the original Rosgen Stream Classification against these defining goals, identifying significant concerns.  Processes are often inferred in the narrative description of stream types (i.e. bedforms, vegetation) but not part of the classification flowchart.  Metrics are often subjective with low repeatability.  Field measurements can often result in overlapping classifications or ambiguous results. 

I propose to enhance the Rosgen Stream Classification by tying the classification to the underlying processes driving channel form: Gravity (slope): Energy Dissipation (bedform), and Vegetation (wood, floodplain vegetation, living roots).  By incorporating these processes more directly into the classification, the explanatory and predictive power of the classification increases.  These enhancements also reduce reliance on subjective metrics, which create discrepancies among practitioners. 

Regionalization of the original Rosgen Stream Classification would greatly improve the utility of the classification method, reflecting regional characteristics like precipitation pattern, vegetation, and geology.

About Bob Siegfried
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