Toward Predictive Stream Channel Design

A professional practice of stream restoration links restoration objectives and actions via predictive relations connecting the project site to its watershed via the supply of water, sediment, and nutrients. At present, most stream channel design is based on analogy: a template is sought in a nearby or idealized channel that the designer judges to be suitable. But if a disturbed stream is adjusting to changes in essential controlling factors, an appropriate template will not exist, a predicament is commonly encountered in practice. More critically, an analogy approach cannot provide true prediction because it provides no basis for linking cause and effect in a logically complete and testable framework. At best, the design can be tested after the fact for its ability to transport the supplied sediment with the available flow. The alternative approach explicitly incorporates the essential drivers - the supply of water and sediment - in the design process. The tools available for an explicit, predictive design process have advanced in recent years, particularly in terms of the treatment of mixed grain sizes and ready implementation of hydraulic flow and sediment routing. Yet particular challenges remain. Forecasts of sediment supply and its uncertainty remain difficult and time consuming. Improved guidance for selecting a design discharge requires explicit connections between the physical and ecological components of the project. Methods for incorporating uncertainty in channel design are overly simplistic. This talk outlines recent advances in the logic and tools for predictive stream channel design and examines challenges in its development and implementation. A primary challenge for those engaged in research is developing a closer understanding of the problems faced by those engaged in restoration practice. Some design problems will be addressed via improved predictive tools spun off from research. Other design problems will be resolved by the clever specification of project objectives that effectively account for uncertainty and acceptable risk. Advances in restoration practice will require close collaboration through which research results find their way into practice and practice helps define the most pressing research priorities.