Catchment-scale, high-resolution, hydraulic models and habitat maps – a salmonid's perspective

IF 4.6 Q2 ENVIRONMENTAL SCIENCES Journal of ecohydraulics Pub Date : 2020-07-31 DOI:10.1080/24705357.2020.1768600
A. O'Sullivan, Bernhard Wegscheider, J. Helminen, Joseph G. Cormier, T. Linnansaari, Dale A. Wilson, R. A. Curry
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引用次数: 24

Abstract

Abstract The advent of remotely-sensed high-resolution imagery has led to the development of methods to map river bathymetry. In this study, we utilized high-resolution imagery to map river depth and quantify hydraulic habitats at the catchment scale (>1000 km2) during low flows. Using 0.3-m airborne multi-spectral imagery (resampled to 0.5 m), we mapped contiguous river depth (124 km) within a well-established Atlantic Salmon (Salmo salar) and Brook Trout (Salvelinus fontinalis) river – The Little Southwest Miramichi, New Brunswick. We built image-derived depth maps with and without field data calibration. The model without field calibration data (flow resistance equation‐based imaging of river depths) accurately described river depths (R 2 = 72.7; RMSE = 0.167 m; n = 762); however, it overestimated shallow depths. The field-calibrated model removed shallow depth errors (R 2 = 76.4; RMSE = 0.155 m; n = 762). We mapped velocity using a relationship between river geometry and discharge, and coalesced the field-calibrated depth and velocity maps to create Froude and Reynolds number maps. Finally, we performed an unsupervised classification model to delineate the hydraulically relevant habitat units for salmonids. This approach provides an unprecedented view of catchment-scale hydraulic habitats that will advance both hydrological process research and river resources management.
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流域尺度,高分辨率,水力模型和栖息地地图-鲑鱼的视角
遥感高分辨率影像的出现,促进了河流水深测量方法的发展。在本研究中,我们利用高分辨率图像绘制了河流深度图,并量化了低流量期间流域尺度(>1000 km2)的水力栖息地。利用0.3米的机载多光谱图像(重新采样至0.5米),我们绘制了一条成熟的大西洋鲑鱼(Salmo salar)和布鲁克鳟鱼(Salvelinus fontinalis)河流的连续河流深度(124公里),该河流位于新不伦瑞克省的小西南米拉米奇。我们在有和没有现场数据校准的情况下建立了图像衍生的深度图。没有现场校准数据的模型(基于流阻方程的河流深度成像)准确地描述了河流深度(r2 = 72.7;RMSE = 0.167 m;n = 762);然而,它高估了浅层深度。现场标定模型消除了浅层深度误差(r2 = 76.4;RMSE = 0.155 m;n = 762)。我们利用河流几何形状和流量之间的关系绘制流速图,并将现场校准的深度和流速图结合起来,生成弗劳德和雷诺数图。最后,我们执行了一个无监督分类模型来描绘鲑鱼的水力相关栖息地单位。这种方法为流域尺度的水力栖息地提供了前所未有的视角,将促进水文过程研究和河流资源管理。
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