Armoring and Embedding Processes in Sediment Impact Analysis Methods (SIAM)
SIAM evaluates trends in stream morphology under management scenarios (including changes to flow regime, land use, morphological adjustments, and in channel modifications). SIAM uses sediment continuity and channel response concepts to link basin-wide processes and predict impacts from sediment movement through a system.
This proposal seeks to further develop SIAM for reaches undergoing changes in substrate composition. Accurately predicting armoring or fining of reaches assists in evaluating habitat destruction, morphological threats to infrastructure, and impairment of riparian lands.
SIAM can handle larger watersheds, more tributaries, and evaluate more management scenarios in shorter time frames than current technology. This research extends sediment analysis capabilities where quantitative analysis may not have been possible before. Results can provide input to habitat models that depend on characterizing the bed composition.
Need and Benefit
Qualitative models of channel evolution and watershed response describe the expected behavior of streams without providing engineering design parameters. Models capable of quantitatively analyzing river morphology problems rely on mobile boundary sediment routing techniques run over a simulated time period. While mobile boundary numerical models serve an important role, SIAM addresses several shortcomings:
* Modeling Effort: Mobile boundary models require high expertise and large amounts of time to generate results. SIAM provides an intermediate analysis effort to either stand alone or narrow the focus for more intensive studies. Using SIAM to identify critical areas requiring a full mobile boundary model further reduces cost. The low modeling effort in SIAM reduces the time and cost of a sediment study.
* Connection to Watershed Processes: SIAM links sediment impacts to the watershed processes creating problems. Mobile boundary models lump catchment processes into boundary conditions. A standard sediment budget cannot project impacts throughout a network. A SIAM model identifies causes of problems in addition to quantifying symptoms.
* Prescriptive Results: SIAM provides design guidance for the steps necessary to restore sediment equilibrium within a stream network. SIAM functions as a network-wide design as well as analysis tool. While mobile boundary models can evaluate the impact from a proposed design alternative, they cannot provide parameters to generate alternatives. Existing empirical and theoretical methods operate on single reaches in isolation.
* Multiple Scenarios: The short setup time and small computational burden allows quick formulation and evaluation of many management scenarios. Scenarios may range from changing the flow regime to altering land management practices to in stream structures. SIAM provides additional design guidance at each step to further suggest courses of action. Current technology can only evaluate a handful of alternatives within a reasonable time frame.
* Risk Analysis: The low computation burden allows risk analysis using a Monte Carlo approach with many traces of different statistically probable inputs. Risk analysis provides an estimate of the confidence in modeling result to provide a more informed evaluation of sediment outcomes. The computation time of a numerical model prevents statistical risk analysis.
* Large Project Scale: The modeling effort for large river networks prohibits applying numerical models. Efforts are limited to the main stem or a few large branches and neglect tributary impacts or sources. The SIAM framework can easily accommodate drainage networks spanning areas over several thousand square miles.
SIAM uses a trend analysis procedure rather than computing a series of discrete states and cannot readily adopt the grain sorting methods used in mobile boundary models. As a new class of sediment model, grain sorting routines have not yet been developed within the analysis framework or in the literature. Without this capability, SIAM could overestimate scour predictions (resulting in excessive mitigation effort or inefficient flow regimes to address sediment concerns). On the aggradation side, SIAM could overpredict the burying or embedding of fine material within gravel habitat necessary for fish breeding and survival. Inaccurate predictions may restrict the ability of Reclamation to deliver water.
Developing a module to incorporate grain sorting will extend the capability of the SIAM model to provide accurate predictions of sedimentation problems in watersheds with Reclamation projects. It will enable the development of basin wide sediment analysis and management. The SIAM tool can assist in evaluating reservoir sedimentation.
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This information was last updated on April 28, 2015
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