Characterizing Ecologically Relevant Variations in Streamflow Regimes

TL;DRAbstract

Maintaining the ecological health of streams is vital for sustainable water resources management. Streamflow is a primary factor influencing the structure and function of ecological communities. A quantitative understanding of how stream biota respond to variation in streamflow is required for stream bioassessment. This dissertation focuses on quantifying relationships between streamflow regime and stream macroinvertebrate richness and composition. The contribution comprises statistical models that predict stream macroinvertebrate class from streamflow regime and predict streamflow regime from watershed attributes, and a tool that helps derive watershed attribute variables used in these models. The dissertation is a collection of three papers. In the first paper 12 variables were used to represent streamflow regime at 543 sites in the western US. Principal component analysis (PCA) and K-means clustering were used to obtain statistically independent factors and streamflow regime classes

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