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首页> 外文期刊>Earth Surface Processes and Landforms: The journal of the British Geomorphological Research Group >Evaluating the performance of topobathymetric LiDAR to support multi-dimensional flow modelling in a gravel-bed mountain stream
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Evaluating the performance of topobathymetric LiDAR to support multi-dimensional flow modelling in a gravel-bed mountain stream

机译：评估塔皮达约激光器的性能，以支持砾石床山溪流中多维流动建模

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Stream biophysical processes are commonly studied using multi-dimensional numerical modelling that quantifies flow hydraulics from which parameters such as habitat suitability, stream carrying capacity, and bed mobility are derived. These analyses would benefit from accurate high-resolution stream bathymetries spanning tens of kilometres of channel, especially in small streams or where navigation is difficult. Traditional ground-based survey methods are limited by survey time, dense vegetation and stream access, and are usually only feasible for short reaches. Conversely, airborne topobathymetric LiDAR surveys may overcome these limitations, although limited research is available on how errors in LiDAR-derived digital elevation models (DEMs) might propagate through flow models. This study investigated the performance of LiDAR-derived topobathymetry in support of multi-dimensional flow modelling and ecohydraulics calculations in two gravel-bedded reaches (approximately 200 m long), one morphologically complex and one morphologically simple, and at the segment scale (32 km-long stream segment) along a 15 m-wide river in central Idaho, USA. We compared metre and sub-metre-resolution DEMs generated from RTK-GPS ground and Experimental Advanced Airborne Research LiDAR-B (EAARL-B) surveys and water depths, velocities, shear stresses, habitat suitability, and bed mobility modelled with two-dimensional (2D) hydraulic models supported by LiDAR and ground-surveyed DEMs. Residual statistics, bias (B), and standard deviation (SD) of the residuals between depth and velocity predicted from the model supported by LiDAR and ground-survey topobathymetries were up to -0.04 (B) and 0.09 m (SD) for depth and -0.09 (B) and 0.20 m s(-1)(SD) for velocity. The accuracy (B = 0.05 m), precision (SD = 0.09 m), and point density (1 point m(-2)) of the LiDAR topobathymetric survey (regardless of reach complexity) were sufficient to support 2D hydrodynamic modelling and derivative stream habitat and process analyses, because these statistics were comparable to those of model calibration with B = 0 m and SD = 0.04 m for water surface elevation and B = 0.05 m s(-1)and SD = 0.22 m s(-1)for velocity in our investigation. (c) 2020 John Wiley & Sons, Ltd.
机译：通常使用多维数值模型研究流生物物理过程，这些过程量化了流动液压的流动液压，从中得到了栖息地适用性，流携带能力和床移动性的参数。这些分析将受益于跨越几公里通道的准确高分辨率流浴，特别是在小型溪流中或导航难以。传统的基于地面调查方法受测量时间，密集植被和流程的限制，并且通常仅适用于短暂的地方。相反，Airborne Toodobathymetric LIDAR调查可能会克服这些限制，尽管有限的研究可以通过LIDAR推导的数字高度模型（DEM）的误差可以通过流量模型传播。本研究研究了激光雷达衍生的胸甲的性能，以支持两种砾石卧床（大约200米长），一个形态复杂，一个形态学简单，在段刻度（32公里） - 沿着美国爱达荷州地区的15米宽的河流。我们比较了从RTK-GPS地面和实验先进的空中研究LIDAR-B（EAARL-B）调查和水深，速度，剪切应力，栖息地适用性和用二维建模的仪表分辨率的DEM （2D）LIDAR和地面调查DEM支持的液压模型。从LIDAR和地面调查甲胸肉支持的模型预测的深度和速度之间的残留物之间的残留统计（B）和标准偏差（SD）高达-0.04（b）和0.09米（SD）深度和0.09米（SD） -0.09（b）和0.20ms（-1）（sd），用于速度。 LIDAR Topobathymetric测量的精度（B = 0.05米），精确度（SD = 0.09米）和点密度（无论达到复杂性的1点M（-2））足以支持2D流体动力学建模和衍生流栖息地和过程分析，因为这些统计数据与模型校准与B = 0 m的模型校准和水面升高的= 0.04 m相当，B = 0.05ms（-1）和SD = 0.22ms（-1），用于速度我们的调查。 （c）2020 John Wiley＆Sons，Ltd。

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