The quantification of pebble shape has been of interest to geomorphologists for decades. Several authors developed parameters to describe pebble shapes from their images. The extraction of this information from images involves two steps: the segmentation of pebble contours and the application of a computational geometry algorithm to estimate shape parameters. When images are taken in the field, unavoidable shadows might hinder the possibility of using automatic segmentation methods. This paper introduces a new method for automatic segmentation of pebbles that improves segmentation accuracy in the presence of shadows. The method is based on the Canny edge detection algorithm which uses a double thresholding process to provide a classification of the strength of the detected edges. The proposed method applies this algorithm with an ensemble of thresholding values, estimating, for each pixel, the probability of being an edge. The resulting pebble contours were analysed using two computational geometry algorithms to obtain shape parameters. The algorithm was calibrated on a sample of five pebbles and then validated on a sample of 1696 pebbles. Its accuracy has been estimated by comparing the resulting shape parameters with those obtained using reference software, which was used as ground truth (GT). The proposed segmentation method was capable of accurately segmenting around 91% of the sample with a relative error for roundness of −1.7% and −0.4%; for elongation of −0.2% and −0.3% and for circularity of 0.2% and 0.1%, when shape parameters were computed using the algorithms of Zheng or Roussillon, respectively. The method could therefore be used to segment images of pebbles collected in the field with low contrast and shadowing, providing comparable accuracy with ‘manual’ segmentation, while removing operator bias.

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The increase in economic activities, population and rural electrification has significantly increased the energy demand in most of the developing nations. This demand has to be supplied from various sources, preferably renewable, among which hydropower is expected to be one of the major contributors. Though developed nations have already harnessed most of their hydropower potential, developing nations are still struggling in project identification and capacity assessment, mainly due to lack of data and difficulties of access. We present and test an assessment framework, developed for data scarce regions, to identify optimal location and installed capacity of multiple run-of-river hydropower projects within a river basin. The developed framework consists of two components: the first component is a hydrological model for flow duration curves, the second component is a so-called hydropower model. Flow duration curves are obtained using an existing probabilistic hydrological model which derives the probability distribution of streamflow as a function of few topographic and climatic parameters. A novel optimization procedure is developed, where viable hydropower projects are identified minimizing their specific cost, which depends mainly on discharge, head and length of conduit system. We tested the assessment framework in the West Rapti basin (Nepal). The application showed that the total potential of this basin maybe achieved with 79 different projects with capacity ranging from 1 to 17 MW. The framework was developed using open languages and software and can therefore be freely used after request to the corresponding author.

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Sediment transport in rivers is a complex process whose understanding is still partial. Each sediment particle can be characterized by its size, shape or distance it travelled from its entrance into the river network to its actual position on the river bed. A number of field techniques have been developed to estimate sediment source locations. This research investigates the possibility of using sediment morphometry as a proxy for travel distance. Recent studies on sediment attrition claim the existence of a “universal” relation between particles’ mass loss and specific shape indices. In order to test this hypothesis, we identified a small basin with localized sources of arenites and metabasalts, which we treated as tracers. We identified lithology as a major control on the absolute attrition speed, while downstream trends in shape changes are controlled by sediment production at basin scale.@en