This paper reports on a laboratory study that aims to reproduce a tidal channel network, in order to enhance the understanding of the morphodynamic evolution of the channel characteristics as the network expands and finally reaches equilibrium. A high-resolution laser system scanned the bed topography at different time steps creating multiple digital elevation models of the channel network. Two hundred and seventy individual channel segments are analyzed and cross-correlated in terms of their width, depth and length.The laboratory results show positive linear correlations between depth and width as well as between length and width of channel segments of the network configuration at final equilibrium. In a downstream direction, channels appear to widen more than they deepen, indirectly a sign that discharge has a stronger control on channel width than on depth. In contrast to fluvial drainage networks that commonly display fractal and scale-invariant behavior, the geometric properties of the experimental tidal creek network shows scale dependence. Channel attributes exhibit consistent patterns of exponentially decreasing abundance, with increasing creek length, depth and width. The nature of the observed exponential distributions within creek attributes (width, depth, length) allows for statistical predictability of relative creek attribute dimensions downstream and through time.

Deployment of floating solar photovoltaic installations (floatovoltaics) is advancing, with various designs beginning to appear in a range of marine environments. Insight from freshwater floatovoltaics is not readily transferable offshore, and so lessons from other marine energy infrastructure are used to highlight how the marine environment may impact floatovoltaics, how the floatovoltaics impact the environment (both positively and negatively) and the likely societal response. It becomes clear that research to understand the environmental and societal implications of floating solar in the marine environment must proceed in parallel with investigations of the technical and economic feasibility.

The search for, and extraction of, hydrocarbons in carbonate rocks demands a thorough understanding of their depositional anatomy. The complexity of carbonate systems, however, hinders detailed direct characterization of their volumetric heterogeneity. Information with which to construct a reservoir model must therefore be based on information gathered from wells or outcrops transecting the sequence of interest. Most (particularly exploration wells) are vertical, presenting a problem for geostatistical modeling. While understanding vertical stratal stacking is straightforward, it is difficult to obtain lateral facies information. Though in some situations outcrop surfaces, seismic data, and horizontal wells may somewhat mitigate this bias, the likelihood remains that the lateral dimension of a buried system will be vastly undersampled with respect to the vertical. However, through the principle of Walther's Law (Walther 1894) or due to the geometry of basinward-inclined beds, comparable facies frequencies and transition probabilities may link vertical and lateral stratal arrangements, the implication being that a reservoir model, competent at least in terms of transition statistics, could be built against information harvested down-core. Taking an interpreted outcrop panel from Lewis Canyon (Albian, Pecos River, Texas), we use Markov-chains to first ascertain that vertical and lateral stratal ordering is nonrandom. Second, we show lithofacies transition probabilities in the outcrop as being interchangeable between the vertical and lateral directions. The work concludes by demonstrating the utility of an existing 3-D Markov random field simulation to volumetrically model the Lewis Canyon outcrop on the basis of vertical facies transition tendencies. Statistical interrogation of the 3-D model output reveals the simulation to contain realistic facies associations compared to the outcrop. This suggests that the reconstruction process, based on Markov chains, produces a useful representation of 3-D heterogeneity in this Lower Cretaceous carbonate succession. Markov random field simulation might provide an important tool for prediction and simulation of subsurface carbonate reservoirs.

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