Sediment flux from a fjord during glacial periods, Isfjorden, Spitsbergen

Sediment has accumulated in Isfjorden, a deep fjord in Spitsbergen, at a rate of 1.7 km³/k.y. during the past 13 k.y. Between 200 ka and 13 ka the fjord was free of ice for 120 k.y. Assuming a similar sediment delivery rate during this ice-free time, 200 km³ of sediment would have accumulated in the fjord. An alternative calculation based on erosion rates suggests that 400 km³ could have been delivered to Isfjorden during this 120 k.y.Seismic studies have identified a 330 km³ package of sediment on the continental shelf and slope west of Isfjorden. This sediment is believed to have accumulated between 200 ka and 13 ka. Herein we argue that this is sediment that was originally deposited in the fjord, and that it was transferred to the shelf by glaciers in the 70 ka during which the fjord was occupied by ice. Calculations using a steady-state numerical model suggest that the sediment could have been moved in a deforming layer of subglacial till and in subglacial melt streams at rates of 7.6 × 10⁶ m³ a⁻¹ and 0.3 × 10⁶ m³ a⁻¹, respectively, resulting in a total flux of 7.9 × 10⁶ m³ a⁻¹. It is unlikely that much sediment was moved in a basal layer of dirty ice, as intense basal melting would have inhibited sediment entrainment.Of the time that glaciers occupied the fjord, 60% would have been required to evacuate the accumulated sediment. During the remaining time, the ice could have been deepening the fjord.     

Uncoupling of coupled flows in soil—a finite element method

Coupled flow of water, chemicals, heat and electrical potential in soil are of significance in a variety of circumstances. The problem is characterized by the coupling between different flows, i.e. a flow of one type driven by gradients of other types, and by the dual nature of certain flows, i.e. combined convection and conduction. Effective numerical solutions to the problem are challenged due to the coupling and the dual nature. In this paper, we first present a general expression that can be used to represent various types of coupled flows in soil. A finite element method is then proposed to solve the generalized coupled flows of convection-conduction pattern. The unknown vector is first decomposed into two parts, a convective part forming a hyperbolic system and a conductive part forming a parabolic system. At each time step, the hyperbolic system is solved analytically to give an initial solution. To solve the multi-dimensional hyperbolic system, we assume that a common eigenspace exists for the coefficient matrices, so that the system can be uncoupled by transforming the unknown vector to the common eigenspace. The uncoupled system is solved by the method of characteristics. Using the solution of the hyperbolic system as the initial condition, we then solve the parabolic system by a Galerkin finite element method for space discretization and a finite difference scheme for time stepping. The proposed technique can be used for solving multi-dimensional, transient, coupled or simultaneous flows of convection-conduction type. Application to a flow example shows that the technique indeed exhibits optimality in convergence and in stability.     

What controls dead-ice melting under different climate conditions? A discussion

In the geological record, hummocky dead-ice moraines represent the final product of the melt-out of dead-ice. Processes and rates of dead-ice melting in ice-cored moraines and at debris-covered glaciers are commonly believed to be governed by climate and debris-cover properties. Here, backwasting rates from 14 dead-ice areas are assessed in relation to mean annual air temperature, mean summer air temperature, mean annual precipitation, mean summer precipitation, and annual sum of positive degree days. The highest correlation was found between backwasting rate and mean annual air temperature. However, the correlation between melt rates and climate parameters is low, stressing that processes and topography play a major role in governing the rates of backwasting. The rates of backwasting from modern glacial environments should serve as input to de-icing models for ancient dead-ice areas in order to assess the mode and duration of deposition.A challenge for future explorations of dead-ice environments is to obtain long-term records of field-based monitoring of melt progression. Furthermore, many modern satellite-borne sensors have high potentials for recordings of multi-temporal Digital Elevation Models (DEMs) for detection and quantification of changes in dead-ice environments. In recent years, high-accuracy DEMs from airborne laser scanning altimetry (LiDAR) are emerging as an additional data source. However, time series of high-resolution aerial photographs remain essential for both visual inspection and high-resolution stereographic DEM production.     

Eddy Diffusion Coefficients of Suspended Particulate Matter: Effects of Wind Energy Transfer and Stratification

Gross sedimentation rates (GSR) have been measured using sediment traps placed at nine different levels above the bed (0·3, 0·5, 0·8, 1·0, 2·0, 4·0, 6·0, 8·0 and 10·0 m). The sediment traps were deployed for 1·25 years and recovered 28 times during the study period. Low average GSR values of 5·5 g m^-2 day^-1 were obtained at 10·0 m, and high average GSR values of 114·8 g m^-2 day^-1 were obtained at 0·3 m. An expression for the eddy diffusion coefficient of suspended particulate matter (K_s), based on the measured GSR is given. The expression has been used for modelling of K_s at the different trap levels above the bed. High values (≈42 cm² s^-1) of K_s were obtained at the upper traps, whereas low values (≈2 cm² s^-1) were obtained near the bed. Comparison between level of turbulent energy in terms of shear stress at the boundaries of the water column, i.e. from the wind and the bed flow, showed that wind energy exceeded that of the bed flow by a factor 16. At 5·0 m K_s was positively correlated (r=0·66) to the eddy diffusion coefficient of momentum (K_m) derived from the wind energy transfer to the water, giving an average β of 0·5 for K_s =βK_m. The density difference between surface and bottom waters has been designated a parameter of stratification, and is discussed in relation to variations of K_s and K_m .