[1] The shear layer at the top of a submerged canopy generates coherent vortices that control exchange between the canopy and the overflowing water. Unlike free shear layers, the vortices in a canopy shear layer do not grow continuously downstream but reach and maintain a finite scale determined by a balance between shear production and canopy dissipation. This balance defines the length scale of vortex penetration into the canopy, d e , and the region of rapid exchange between the canopy and overflow. Deeper within the canopy, transport is constrained by smaller turbulence scales. A two-box canopy model is proposed on the basis of the length scale d e . Using diffusivity and exchange rates defined in previous studies, the model predicts the timescale required to flush the canopy through vertical exchange over a range of canopy density and height. The predicted canopy retention times, which range from minutes to an hour, are consistent with canopy retention inferred from tracer observations in the field and comparable to retention times for some hyporheic regions. The timescale for vertical exchange, along with the in-canopy velocity, determines the minimum canopy length for which vertical exchange dominates water renewal. Shorter canopies renew interior water through longitudinal advection. Finally, canopy water retention influences longitudinal dispersion through a transient storage process. When vertical exchange controls canopy retention, the transient storage dispersion increases with canopy height. When longitudinal advection controls water renewal, dispersion increases with canopy patch length.

[1] Vegetation is ubiquitous in rivers, estuaries, and wetlands, strongly influencing water conveyance and mass transport. The plant canopy affects mean and turbulent flow structure, and thus both advection and dispersion. Accurate prediction for the transport of nutrients, microbes, dissolved oxygen and other scalars depends on our ability to quantify the impact of vegetation. In this paper, we focus on longitudinal dispersion, which traditionally has been modeled in vegetated channels by drawing analogy to rough boundary layers. This approach is inappropriate in many cases, as the vegetation provides a significant dead zone, which may trap scalars and augment dispersion. The dead zone process is not captured in the rough boundary model. This paper describes a new model for longitudinal dispersion in channels with submerged vegetation, and it validates the model with experimental observations.

Recent national focus on the value of increasing US supplies of indigenous renewable energy underscores the need for re-evaluating all alternatives, particularly those that are large and well distributed nationally. A panel was assembled in September 2005 to evaluate the technical and economic feasibility of geothermal becoming a major supplier of primary energy for US base-load generation capacity by 2050. Primary energy produced from both conventional hydrothermal and enhanced (or engineered) geothermal systems (EGS) was considered on a national scale. This paper summarizes the work of the panel which appears in complete form in a 2006 MIT report, 'The future of geothermal energy' parts 1 and 2.In the analysis, a comprehensive national assessment of US geothermal resources, evaluation of drilling and reservoir technologies and economic modelling was carried out. The methodologies employed to estimate geologic heat flow for a range of geothermal resources were utilized to provide detailed quantitative projections of the EGS resource base for the USA. Thirty years of field testing worldwide was evaluated to identify the remaining technology needs with respect to drilling and completing wells, stimulating EGS reservoirs and converting geothermal heat to electricity in surface power and energy recovery systems. Economic modelling was used to develop long-term projections of EGS in the USA for supplying electricity and thermal energy. Sensitivities to capital costs for drilling, stimulation and power plant construction, and financial factors, learning curve estimates, and uncertainties and risks were considered.

A numerical study was conducted to characterize the probability and intensity of storm surge hazards in Canada’s western Arctic. The utility of the European Centre for Medium-Range Weather Forecasts Reanalysis 5th Generation (ERA5) dataset to force numerical simulations of storm surges was explored. Fifty historical storm surge events that were captured on a tide gauge near Tuktoyaktuk, Northwest Territories, were simulated using a two-dimensional (depth-averaged) hydrodynamic model accounting for the influence of sea ice on air-sea momentum transfer. The extent of sea ice and the duration of the ice season has been reducing in the Arctic region, which may contribute to increasing risk from storm surge-driven hazards. Comparisons between winter storm events under present-day ice concentrations and future open-water scenarios revealed that the decline in ice cover has potential to result in storm surges that are up to three times higher. The numerical model was also used to hindcast a significant surge event that was not recorded by the tide gauge, but for which driftwood lines along the coast provided insights to the high-water marks. Compared to measurements at proximate meteorological stations, the ERA5 reanalysis dataset provided reasonable estimates of atmospheric pressure but did not accurately capture peak wind speeds during storm surge events. By adjusting the wind drag coefficients to compensate, reasonably accurate predictions of storm surges were attained for most of the simulated events. The extreme value probability distributions (i.e., return periods and values) of the storm surges were significantly altered when events absent from the tide gauge record were included in the frequency analysis, demonstrating the value of non-conventional data sources, such as driftwood line surveys, in supporting coastal hazard assessments in remote regions.