A Regional Hydrologic Classification of Unregulated Rivers: Towards the Development of Natural Flow Regime Characterization and Environmental Flows in California

Abstract:

Alterations to flow regimes from regulation and climate change affect the biophysical functioning of rivers. Re-operating reservoirs to provide environmental flows - the quantity, quality, and timing of water to sustain natural river functions and species - is now widely applied in multi-objective water resources management. However, the absence of a quantitative, transferable framework for evaluating the relationships between hydrologic inputs, geomorphic functions, and ecological responses, remains a major limitation to setting environmental flows standards. This research addresses this gap by developing a hydrologic classification framework for the State of California that balances operational practicality with scientific defensibility. The framework organizes river reaches into: (1) natural flow classes based on (a) a classification model that clusters hydrologic indices calculated directly from unimpaired streamflow data, and (b) a regression model using a set of climatic, landscape, and local geomorphic controls over the flow regime, and (2) functional zones constrained by temporal (seasonal) ranges and hydrologic (average flow percentile-based) thresholds (e.g. summer low flows). The framework is then used to (1) identify major climatic, landscape, and local geomorphic controls over prototypical flow regime signatures, and (2) characterize key natural functions and processes expected of reaches of each flow class and functional zone during wet, dry, and normal water year types. Organizing hydrologic data in this manner provides a means of comparison and transferability of ecologically-significant hydrologic and geomorphic information across reaches of all major flow classes seen in California, both regulated and unregulated. Through this framework, transferable relationships between hydrologic and physiographic conditions, flow alteration, and ecological metrics can be developed and tested on the basis of data obtained from a limited set of study sites.