U.S. Stream Classification System

An effort to organize the nation’s 2.6 million stream reaches into groups of similar physical properties.

Background and Purpose

Stream environments are dynamic systems whose structure and function are governed by processes operating at micro-habitats to basin scales. Predicting stream biophysical responses to human disturbances, such as hydropower development, as well as mitigating the effects of disturbances, are both complex and challenging problems. Typically, every stream is viewed as unique and appropriate management and mitigation actions are handled on an individual basis. Furthermore, reference streams (or case studies) are many times used to guide mitigation and restoration actions. Hence, finding the most suitable reference streams would benefit from tools that provide structured approaches to identifying appropriate systems. Partitioning stream ecosystems into functional components helps reduce some of the complexity of understanding stream responses to disturbance and restoring impaired components. Furthermore, classifying streams into groups of similar biophysical types provides a template to understand and generalize stream responses to disturbance and assist in determining best mitigation practices. Finally, these classes provide a multi-level criteria for selecting reference streams and case studies.

What is the U.S. Stream Classification System?

Example of hydrologic classes mapped to stream reaches. Fifteen hydrologic classes developed using hierarchical Bayesian mixture modeling approach for stream gaging stations (McManamay et al. 2014). A predictive model was developed and used to extrapolate these classes to stream reaches in the CONUS.

The U.S. Stream Classification System (USSCS) is an effort to group 2.6 million stream reaches of the Conterminous United States into a layered typology of stream types. The USSCS is based on classifying streams within five layers: 1) Hydrology, 2) Size, 3) Gradient, 4) Temperature, and 5) Valley Confinement. Developing the classification generally followed six guiding principles:

  • Stream-reach resolution: Classification was developed using the NHDPlus V2 medium resolution
  • Empirically-driven: Empirical observations (e.g., stream gages, remote sensing, and other sources were used to create classes directly or indirectly through modeling.
  • Physically-based classes: Partitioning classes was based on physical variation (not biological discriminatory power) and scientific consensus surrounding thresholds found in literature.
  • Layered: A layered approach (e.g., hydrology, size, temperature, etc) provides a multi-dimensional perspective of stream environments that are easier to understand.
  • Least-disturbed condition: The reference or least-disturbance condition of streams is very important to guide mitigation, as these conditions approximate a reference or baseline. The layered approach provides the flexibility to add disturbance “layers” to other classes.
  • Spatially contiguous and comprehensive: The effort is comprehensive (i.e., cover the entire CONUS) and be spatially contiguous (i.e., seamlessly cover all stream reaches), and not be limited to points on a map.

Use the Stream Classification Web App

The Stream Classification Web App provides a platform for stakeholders, regulators, and the hydropower industry to explore, visualize, and query stream classes. Suppose you might want to find a suitable reference stream? Or understand what type of stream ecosystem you are studying? The app can help you do that. First, the app provides users an ability to conduct an inventory of hydrologic regimes, thermal regimes, size, gradient, and valley geomorphology of rivers within a region or basin. In doing so, the streams can be used to identify ideal environmental conditions. Second, the app can be used to search for reference streams or case studies meeting search criteria. Thus, the app is expected to increase the effectiveness of the hydropower regulatory process by creating an objective and data-rich means to address meaningful mitigation actions.

User Tutorials

Data and Publications

Coming soon.