基于无人机摄影测量的全流域FEWS选址估算

Taegyun Kim, Jae-Kook Park, S. Hwang, Taesam Lee
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引用次数: 0

摘要

对于小型河流和水库,通常采用洪水预警系统(FEWS)来应对突发性洪水事件,而突发性洪水事件的影响由于环境和气候的同质化变化而增强。目前,FEWS需要安装水位计,通常安装在桥上。这是FEWS的一个限制,因为可能存在比桥梁更脆弱的地区。因此,为了分析整个目标流域的洪水风险,提出了一种安装FEWS的程序。首先,分析基于无人机(UAV)的摄影测量信息,预选洪水易发区域;其次,对预选地区进行包括地面测量在内的进一步调查。最后,利用无人机摄影测量信息估算洪水量,发布FEWS预警级别。为此,选择Malgol水库作为当前研究区域,Malgol水库是一个洪水高风险级别的水库,包含居民区。通过对无人机摄影测量信息的分析,确定了11个洪水易发点。然后,在11个点中选取洪水量最低的洪水点作为最脆弱点;该段位于Malgol水库泄洪道下游464 m处。根据最脆弱路段的路堤,可发出全流域FEWS预警警报。这保证了整个流域包括水库及其下游地区的安全。该方法利用整个流域的无人机摄影测量信息,并考虑整个洪水易发断面,克服了目前基于桥梁水位分析的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Whole Watershed-based Estimation of FEWS Installation Site Using UAV Photogrammetry
For small rivers and reservoirs, a flood early warning system (FEWS) is generally used to prepare for sudden flood events whose impact is augmented from homonized environment and climate change. Currently, a FEWS requires the installation of a water gauge, typically on a bridge. This is a limitation of the FEWS owing to the possibility of existence of areas that are more vulnerable than the bridge. Therefore, to analyze the flood risk over the entire target basin, a procedure to install a FEWS was proposed. First, unmanned aerial vehicle (UAV)-based photogrammetry information is analyzed to preselect flood-prone areas. Second, further investigation including the ground surveying is followed for the preselected areas. Finally, the flood amount is estimated and the UAV photogrammetry information for issuing the alarm levels of the FEWS. For this purpose, Malgol Reservoir, a reservoir with high-risk level from floods, containing residential areas was selected as the current study area. Eleven flood-prone points were identified by analyzing the UAV photogrammetry information. Then, the flooding point with the lowest flood volume among the 11 points was selected as the most vulnerable point; this section was located at 464 m from the Malgol Reservoir spillway in the downstream direction. The warning alarm for the basin-wide FEWS could be issued according to the embankment of the most vulnerable section. This ensured the safety over the entire basin including the reservoir and its downstream area. The proposed procedure can overcome the limitations of the current bridge water level-based analysis by employing UAV-photogrammetry information of the entire basin and considering the entire flood-prone cross-sections.
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