高质量高程数据和解释变量对通过最近排水沟以上高度绘制洪水淹没图的准确性的影响

F. Aristizabal, T. Chegini, Gregory Petrochenkov, F. Salas, J. Judge
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引用次数: 0

摘要

摘要鉴于美国地质调查局的三维高程计划(3DEP)提供了高质量、高空间分辨率的数字高程图(DEM),这些高程图主要由光探测和测距(lidar)传感器绘制,我们研究了这些不同空间分辨率的 DEM 对根据地形指数(即最近排水沟以上高度(HAND))绘制的洪水淹没图(FIM)范围质量的影响。我们发现,与使用国家水文数据集加高分辨率(NHDPlusHR)程序中的 DEM 相比,使用这些 DEM 提高了约 80% 的受分析流域的洪水淹没图范围质量。此外,我们还改变了 3DEP DEM 的空间分辨率(3、5、10、15 和 20 米),结果表明,不同分辨率对 FIM 范围质量的总体影响不大。然而,对 60 米和 90 米更高分辨率的进一步分析表明,FIM 技能明显下降,这突出表明了使用极高分辨率 DEM 的局限性。我们的实验表明,在更精细的分辨率下生成 HAND 和相关数据需要大量的计算时间。我们拟合了一个多线性回归模型,以帮助解释所采用的四项指标在流域尺度上的变化,并发现在我们的分析中,河流滞留系统上游缺乏水库洪水或淹没是一个重要因素。为了进行验证,我们使用了机构间洪水风险管理 (InFRM) 基础工程 (BLE) 制作的 FIM 范围以及德克萨斯州东部一个次区域的 100 年一遇和 500 年一遇的河水流量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of high-quality elevation data and explanatory variables on the accuracy of flood inundation mapping via Height Above Nearest Drainage
Abstract. Given the availability of high-quality and high-spatial-resolution digital elevation maps (DEMs) from the United States Geological Survey's 3D Elevation Program (3DEP), derived mostly from light detection and ranging (lidar) sensors, we examined the effects of these DEMs at various spatial resolutions on the quality of flood inundation map (FIM) extents derived from a terrain index known as Height Above Nearest Drainage (HAND). We found that using these DEMs improved the quality of resulting FIM extents at around 80 % of the catchments analyzed when compared to using DEMs from the National Hydrography Dataset Plus High Resolution (NHDPlusHR) program. Additionally, we varied the spatial resolution of the 3DEP DEMs at 3, 5, 10, 15, and 20 m (meters), and the results showed no significant overall effect on FIM extent quality across resolutions. However, further analysis at coarser resolutions of 60 and 90 m revealed a significant degradation in FIM skill, highlighting the limitations of using extremely coarse-resolution DEMs. Our experiments demonstrated a significant burden in terms of the computational time required to produce HAND and related data at finer resolutions. We fit a multiple linear regression model to help explain catchment-scale variations in the four metrics employed and found that the lack of reservoir flooding or inundation upstream of river retention systems was a significant factor in our analysis. For validation, we used Interagency Flood Risk Management (InFRM) Base Level Engineering (BLE)-produced FIM extents and streamflows at the 100- and 500-year event magnitudes in a sub-region in eastern Texas.
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