Author(s): John Roadifer; Blair Greimann; Yantao Cui; Seth Gentzler; Brian Cluer; Joel Monschke; Derek B. Booth

Linked Author(s):

Keywords: Dam removal; Numerical modelling and analysis; Fine sediment erosion and transport; Suspended sediment concentration and turbidity; Empirical analysis

Abstract: Large quantities of fine sediment can be accumulated in reservoirs, and the potential impact of their downstream release is often a great concern if the dams are to be removed. Currently, there are no reliable numerical models to simulate the dynamics of the release of these fine sediments, mostly because their release following dam removal is often driven by a rapid erosional process not addressed by traditional sediment transport theory. However, precise quantification of fine sediment transport is rarely necessary to evaluate potential environmental impacts of alternative scenarios. Using the removal of Matilija Dam in southern California, USA, as an example, we quantify the likely magnitude of suspended sediment concentration and the duration of associated downstream impacts, two necessary (and most likely adequate) parameters for assessing alternatives. The analyses first estimate the general magnitude of suspended sediment concentration and duration of impacts based on field and experimental data; they then quantify the duration of impacts under both worst-case and reasonable assumptions according to the underlying physics and common sense. For rapid sediment release with fine-grained impoundment deposits, initial suspended sediment concentrations are likely to approach 10 6  mg/L, persisting for a few hours to no more than a couple of days. Suspended sediment concentrations are expected to decline approximately exponentially after the initial peak, reaching background levels within a few hours to a few days, provided that sufficient flow is available. The general method presented in the paper should be useful for stakeholders choosing amongst dam-removal alternatives for implementation under similar conditions.

DOI: https://doi.org/10.1080/15715124.2016.1247362

Year: 2017