The Accuracy and Reliability of Traditional Surface Flow Type Mapping: Is It Time for A New Method of Characterising Physical River Habitat?

Surface flow types (SFT) are advocated as ecologically relevant hydraulic units, often mapped visually from the bankside to characterise rapidly the physical habitat of rivers. SFT mapping is simple, non-invasive and cost-efficient. However, it is also qualitative, subjective and plagued by difficulties in recording accurately the spatial extent of SFT units. Quantitative validation of the underlying physical habitat parameters is often lacking, and does not consistently differentiate between SFTs. Here, we investigate explicitly the accuracy, reliability and statistical separability of traditionally mapped SFTs as indicators of physical habitat, using independent, hydraulic and topographic data collected during three surveys of a c. 50m reach of the River Arrow, Warwickshire, England. We also explore the potential of a novel remote sensing approach, comprising a small unmanned aerial system (sUAS) and Structure-from-Motion photogrammetry (SfM), as an alternative method of physical habitat characterisation. Our key findings indicate that SFT mapping accuracy is highly variable, with overall mapping accuracy not exceeding 74%. Results from analysis of similarity (ANOSIM) tests found that strong differences did not exist between all SFT pairs. This leads us to question the suitability of SFTs for characterising physical habitat for river science and management applications. In contrast, the sUAS-SfM approach provided high resolution, spatially continuous, spatially explicit, quantitative measurements of water depth and point cloud roughness at the microscale (spatial scales ≤1m). Such data are acquired rapidly, inexpensively, and provide new opportunities for examining the heterogeneity of physical habitat over a range of spatial and temporal scales. Whilst continued refinement of the sUAS-SfM approach is required, we propose that this method offers an opportunity to move away from broad, mesoscale classifications of physical habitat (spatial scales 10-100m), and towards continuous, quantitative measurements of the continuum of hydraulic and geomorphic conditions which actually exists at the microscale.

Strategic Management Simulation as a Blended Learning Dimension: Campus Based Students’ Perspectives

Although business simulations are widely used in management education, there is no consensus about how to optimise their application. Our research explores the use of business simulations as a dimension of a blended learning pedagogic approach for undergraduate business education. Accepting that few best-practice prescriptive models for the design and implementation of simulations in this context have been presented, and that there is little empirical evidence for the claims made by proponents of such models, we address the lacuna by considering business student perspectives on the use of simulations. We then intersect available data with espoused positive outcomes made by the authors of a prescriptive model. We find the model to be essentially robust and offer evidence to support this position. In so doing we provide one of the few empirically based studies to support claims made by proponents of simulations in business education. The research should prove valuable for those with an academic interest in the use of simulations, either as a blended learning dimension or as a stand-alone business education activity. Further, the findings contribute to the academic debate surrounding the use and efficacy of simulation-based training [SBT] within business and management education.