Abstract Mudrocks are highly heterogeneous in a range of physical and chemical properties, including: porosity and permeability, fissility, colour, particle composition, size, orientation, carbon loading, degree of compaction, and diagenetic overprint. It is therefore important that the maximum information be extracted as efficiently and completely as possible. This can be accomplished through high-resolution analysis of polished thin sections by scanning electron microscopy (SEM), with the collection of large-area images and X-ray elemental map montages, and the application of targeted particle analysis. A workflow model, based on these techniques, for the digitization of mudrocks is presented herein. A range of the data that can be collected and the variety of analyses that can be achieved are also illustrated. Data collection is discussed in terms of inherent problems with acquisition, storage, transfer and manipulation, which can be time-consuming and non-trivial. Similar information and resolutions can be achieved through other techniques, such as QEMSCAN and infra-red (IR)/Raman spectroscopic mapping. These can be seen as complementary to the workflow described herein.

Abstract The availability of historical streamflow data of the desired length is often limited and, in these situations, the ability to synthetically generate statistically significant datasets becomes important. We previously developed a highly efficient stochastic modelling approach for the synthetic generation of daily streamflow sequences using the systematic combination of a hidden Markov model with the generalized Pareto distribution (the HMM-GP model). Daily streamflow sequences provide limited information on various significant small duration flooding events exceeding the peak over threshold values, but these are averaged out in the daily datasets. These small duration intense flooding events are often capable of causing significant damage and are important in conducting thorough flood risk management and flood risk assessment studies. This paper presents upgrades to our HMM-GP stochastic modelling approach and examines its efficiency in simulating streamflow at a temporal resolution of 15 minutes. The potential of the HMM-GP model in simulating a synthetic 15-minute streamflow series is investigated by comparing various statistical characteristics (e.g. percentiles, the probability density distribution and the autocorrelation function) of the observed streamflow records with 100 synthetically simulated streamflow time series. The proposed modelling schematics are robustly validated across case studies in four UK rivers (the Don, Nith, Dee and Tweed).

Abstract Natural stone is an important material used for buildings, walls and monuments. However, when used outdoors, it is subject to damage by the effects of weathering. Inspired by the experiments carried out by Friedrich Pfaff, a German geologist and professor of mineralogy at the University of Erlangen, Germany, in the 1870s, Archibald Geikie became interested in the subject of rock weathering and came up with the idea of using gravestones as a means of monitoring weathering in stone used for building. This work, apparently carried out in cemeteries in Edinburgh as a sideline to his normal fieldwork activities, was described in 1880 in a communication read to the Royal Society of Edinburgh. It represents the first comprehensive scientific study of rock weathering published in English, and the methodology Geikie developed for his study formed the basis for modern studies of rock weathering using gravestones.