Stuart N. Lane

Bio: Stuart N. Lane is an academic researcher from University of Lausanne. The author has contributed to research in topics: Sediment & Glacier. The author has an hindex of 76, co-authored 337 publications receiving 15788 citations. Previous affiliations of Stuart N. Lane include Durham University & Loughborough University.

Estimation of erosion and deposition volumes in a large, gravel‐bed, braided river using synoptic remote sensing

Abstract: System-scale detection of erosion and deposition is crucial in order to assess the transferability of findings from scaled laboratory and small field studies to larger spatial scales. Increasingly, synoptic remote sensing has the potential to provide the necessary data. In this paper, we develop a methodology for channel change detection, coupled to the use of synoptic remote sensing, for erosion and deposition estimation, and apply it to a wide, braided, gravel-bed river. This is based upon construction of digital elevation models (DEMs) using digital photogrammetry, laser altimetry and image processing. DEMs of difference were constructed by subtracting DEM pairs, and a method for propagating error into the DEMs of difference was used under the assumption that each elevation in each surface contains error that is random, independent and Gaussian. Data were acquired for the braided Waimakariri River, South Island, New Zealand. The DEMs had a 1·0 m pixel resolution and covered an area of riverbed that is more than 1 km wide and 3·3 km long. Application of the method showed the need to use survey-specific estimates of point precision, as project design and manufacturer estimates of precision overestimate a priori point quality. This finding aside, the analysis showed that even after propagation of error it was possible to obtain high quality DEMs of difference for process estimation, over a spatial scale that has not previously been achieved. In particular, there was no difference in the ability to detect erosion and deposition. The estimates of volumes of change, despite being downgraded as compared with traditional cross-section survey in terms of point precision, produced more reliable erosion and deposition estimates as a result of the large improvement in spatial density that synoptic methods provide. Copyright © 2003 John Wiley & Sons, Ltd.

The science and practice of river restoration

Abstract: River restoration is one of the most prominent areas of applied water-resources science. From an initial focus on enhancing fish habitat or river appearance, primarily through structural modification of channel form, restoration has expanded to incorporate a wide variety of management activities designed to enhance river process and form. Restoration is conducted on headwater streams, large lowland rivers, and entire river networks in urban, agricultural, and less intensively human-altered environments. We critically examine how contemporary practitioners approach river restoration and challenges for implementing restoration, which include clearly identified objectives, holistic understanding of rivers as ecosystems, and the role of restoration as a social process. We also examine challenges for scientific understanding in river restoration. These include: how physical complexity supports biogeochemical function, stream metabolism, and stream ecosystem productivity; characterizing response curves of different river components; understanding sediment dynamics; and increasing appreciation of the importance of incorporating climate change considerations and resiliency into restoration planning. Finally, we examine changes in river restoration within the past decade, such as increasing use of stream mitigation banking; development of new tools and technologies; different types of process-based restoration; growing recognition of the importance of biological-physical feedbacks in rivers; increasing expectations of water quality improvements from restoration; and more effective communication between practitioners and river scientists.

Doing flood risk science differently: an experiment in radical scientific method

Abstract: In this paper, we describe an experiment in which the position of scientists with respect to flood risk management is fundamentally changed. Building on a review of three very different approaches to engaging the public in science, we contrast the normal way in which science is used in flood risk management in England and Wales with an experiment in which knowledge regarding flooding was co-produced. This illustrates a way of working with experts, both certified (academic natural and social scientists) and non-certified (local people affected by flooding), for whom flooding is a matter of concern, and where the event, flooding, is given agency in the experiment. We reveal a deep and distributed understanding of flood hydrology across all experts, certified and uncertified, involved in the experiment. This did not map onto the conventional dichotomy between ‘universal’ scientific expertise and ‘local’ lay expertise. By working with the event we harnessed, produced and negotiated a new and collective sense of knowledge, sufficient in our experiment to make a public intervention in flood risk management in our case-study location. The manner in which the academic scientists involved in the practice of their science were repositioned was radical as compared with normal scientific method. It was also radical for a more fundamental reason: the purpose of our experiment became as much about creating a new public capable of making a political intervention in a situation of impasse, as it was about producing the solution itself. The practice of knowledge generation, the science undertaken, worked with the hybridisation of science and politics rather than trying to extract science from it.

Urban fluvial flood modelling using a two‐dimensional diffusion‐wave treatment, part 1: mesh resolution effects

Abstract: High-resolution data obtained from airborne remote sensing is increasing opportunities for representation of small-scale structural elements (e.g. walls, buildings) in complex floodplain systems using two-dimensional (2D) models of flood inundation. At the same time, 2D inundation models have been devel-oped and shown to provide good predictions of flood inundation extent, with respect to both full solution of the depth-averaged Navier-Stokes equations and simplified diffusion wave models. However, these models have yet to be applied extensively to urban areas. This paper applies a 2D raster-based diffusion wave model to determine patterns of fluvial flood inundation in urban areas using high-resolution topog-raphic data. The aim of this paper is to explore the effects of spatial resolution upon estimated inundation extent and flow routing process. This is important as the complexity of urban surfaces is such that chang-ing data resolution may have a major effect upon surface representation and hence flow routing. Similarly, few applications to date have explicitly considered the timing of the inundation process. The model assumes that the prime source of the flood is fluvial: pluvial floods and floods associated with urban drainage systems are not addressed. The topographic data are based upon airborne laser altimetry (Li-DAR) obtained for the City of York, U.K. A series of image processing steps are used to pre-prepare the topographic data. A one-dimensional hydraulic model of the Ouse from Skelton (upstream of the city) through to Naburn Weir (downstream of the city) is used to provide estimates of flux from the river to the floodplain for a major flood inundation event (estimated to have a return period of greater than 100 years) in November 2000. Validation data were available in the form of inundation patterns obtained using aerial photography at a point on the falling limb of the flood event. Model response shows that even relatively small changes in model resolution have considerable effects on the predicted inundation extent and the timing of flood inundation. Timing sensitivity would be expected given the relatively poor representation of inertial processes in a diffusion wave model. Compared with previous work, sensitivity to inundation extent is more surprising and is associated with three connected effects: (1) the smoothing effect of mesh coarsening upon input topographical data; (2) poorer representation of both cell blockage and surface routing processes as the mesh is coarsened, where the flow routing is especially complex; and (3) the ef-fects of (1) and (2) upon water levels and velocities which in turn determine which parts of the floodplain the flow can actually travel to. The combined effects of wetting and roughness parameters can compen-sate in part for a coarser mesh resolution. However, the coarser the resolution, the poorer the ability to control the inundation process as these parameters not only affect the speed but also the direction of wet-ting. Thus, high resolution data will need to be coupled to more sophisticated representation of the inun-dation process in order to obtain effective predictions of flood inundation extent. This is explored in a companion paper.

Developments in monitoring and modelling small‐scale river bed topography

Abstract: Recent research in fluvial geomorphology has emphasized the spatially distributed feedbacks amongst river channel topography, flow hydraulics and sediment transport. Although understanding of the behaviour of dynamic river channels has been increased markedly through detailed within-channel process studies, less attention has been given to the accurate monitoring and terrain modelling of river channel form using three-dimensional measurements. However, such information is useful in two distinct senses. Firstly, it is one of the necessary boundary conditions for a physically based, deterministic modelling approach in which three-dimensional topography and river discharge drive within-channel flow hydraulics and ultimately spatial patterns of erosion and deposition and therefore channel change. Secondly, research has shown that an alternative means of estimating the medium-term bedload transport rate can be based upon monitoring spatial patterns of erosion and deposition within the river channel. This paper presents a detailed assessment of the distributed monitoring and terrain modelling of river bed topography using a technique that combines rigorous analytical photogrammetry with rapid ground survey. The availability of increasingly sophisticated terrain modelling packages developed for civil engineering application allows the representation of topographic information as a landform surface. Intercomparison of landform surfaces allows visualization and quantification of spatial patterns of erosion and deposition. A detailed assessment is undertaken of the quality of the morphological information acquired. This allow some general comments to be made concerning the use of more traditional methods to monitor and represent small-scale river channel morphology.

Remote Sensing And Image Interpretation

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Position paper: Characterising performance of environmental models

Abstract: In order to use environmental models effectively for management and decision-making, it is vital to establish an appropriate level of confidence in their performance. This paper reviews techniques available across various fields for characterising the performance of environmental models with focus on numerical, graphical and qualitative methods. General classes of direct value comparison, coupling real and modelled values, preserving data patterns, indirect metrics based on parameter values, and data transformations are discussed. In practice environmental modelling requires the use and implementation of workflows that combine several methods, tailored to the model purpose and dependent upon the data and information available. A five-step procedure for performance evaluation of models is suggested, with the key elements including: (i) (re)assessment of the model's aim, scale and scope; (ii) characterisation of the data for calibration and testing; (iii) visual and other analysis to detect under- or non-modelled behaviour and to gain an overview of overall performance; (iv) selection of basic performance criteria; and (v) consideration of more advanced methods to handle problems such as systematic divergence between modelled and observed values.