优化最近排水口以上高度参数,以便在北卡罗来纳州快速绘制洪水地图

Colin A. Richardson, R. Beighley
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摘要

地表水洪水对许多基础设施系统都有重大危害。例如,住宅、商业和工业物业、水和废水处理设施、私人饮用水井、雨水系统或交通网络通常会受到洪水事件的影响(即在损坏或功能性方面)。对于大规模的洪灾事件,了解恢复资源的优先次序可能具有挑战性。为了帮助整个北卡罗来纳州的社区管理洪水灾害响应,需要近实时的全州范围快速洪水测绘方法。在这项研究中,最近排水口以上高度 (HAND) 概念与国家水模型河流排水量相结合,实现了北卡罗来纳州全境的快速洪水测绘。该建模系统使用 USGS 阶段-排泄关系和 FEMA 100 年洪水地图进行校准。校准过程最终提供了与现有数据集最匹配的空间分布式河道粗糙度值。结果表明,洪水测绘系统经过校准后,可合理估算河段(或相应的水面高程)和地表水范围。将 HAND 与威克县和全州的联邦紧急事务管理局危险地图进行比较后发现,两者的吻合度分别为 80.1% 和 76.3%。对于不一致的地点,洪水范围往往被高估,而不是低估,这在识别可能受影响的基础设施系统方面是可取的。未来的研究将侧重于开发转移关系,以估算缺乏校准所需数据的地点的河道粗糙度值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing Height Above Nearest Drainage parameters to enable rapid flood mapping in North Carolina
Surface water flooding represents a significant hazard for many infrastructure systems. For example, residential, commercial, and industrial properties, water and wastewater treatment facilities, private drinking water wells, stormwater systems, or transportation networks are often impacted (i.e., in terms of damage or functionality) by flooding events. For large scale events, knowing where to prioritize recovery resources can be challenging. To help communities throughout North Carolina manage flood disaster responses, near real-time state-wide rapid flood mapping methods are needed. In this study, Height Above Nearest Drainage (HAND) concepts are combined with National Water Model river discharges to enable rapid flood mapping throughout North Carolina. The modeling system is calibrated using USGS stage-discharge relationships and FEMA 100-year flood maps. The calibration process ultimately provides spatially distributed channel roughness values to best match the available datasets. Results show that the flood mapping system, when calibrated, provides reasonable estimates of both river stage (or corresponding water surface elevations) and surface water extents. Comparing HAND to FEMA hazard maps both in Wake County and state-wide shows an agreement of 80.1% and 76.3%, respectively. For the non-agreement locations, flood extents tend to be overestimated as compared to underestimated, which is preferred in the context of identifying potentially impacted infrastructure systems. Future research will focus on developing transfer relationships to estimate channel roughness values for locations that lack the data needed for calibration.
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