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

机译:传统地表水流类型制图的准确性和可靠性:是时候提出一种表征河流物理生境的新方法了吗?

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摘要

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.
机译:提倡将地表水流类型(SFT)作为与生态相关的水力单元,通常从河岸上直观地绘制地图,以快速表征河流的物理栖息地。 SFT映射简单,无创且具有成本效益。但是,它在定性,主观和困扰方面也难以准确记录SFT单元的空间范围。通常缺乏对基本物理栖息地参数的定量验证,并且不能始终如一地区分SFT。在这里,我们使用在c的三个调查中收集的独立,水力和地形数据,明确调查了传统映射的SFT作为物理栖息地指标的准确性,可靠性和统计可分离性。英格兰沃里克郡箭河的50m距离。我们还探索了一种新颖的遥感方法的潜力,其中包括小型无人航空系统(sUAS)和动态结构摄影测量法(SfM),作为物理栖息地表征的替代方法。我们的主要发现表明,SFT映射精度变化很大,总体映射精度不超过74%。相似性分析(ANOSIM)测试的结果表明,所有SFT对之间都不存在强烈的差异。这使我们提出质疑,SFTs是否适合表征河流科学和管理应用中的自然栖息地。相比之下,sUAS-SfM方法可在微米尺度(空间尺度≤1m)上提供高分辨率,空间连续,空间明确的水深和点云粗糙度的定量测量。这样的数据可以快速,廉价地获取,并为在一定的时空范围内检查物理栖息地的异质性提供了新的机会。尽管需要持续改进sUAS-SfM方法,但我们建议该方法提供了一个机会,可以从广泛的中尺度物理生境分类(空间尺度10-100m)转向对连续水力的连续定量测量和实际上存在于微观尺度的地貌条件。

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