Remote bed-level change and overwash observation with low-cost ultrasonic distance sensors

Shore & Beach Pub Date : 2021-06-09 DOI:10.34237/1008923
Ian R. B. Reeves, E. Goldstein, K. Anarde, L. Moore
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引用次数: 4

Abstract

Few datasets exist of high-frequency, in situ measurements of storm overwash, an essential mechanism for the subaerial maintenance of barrier islands and spits. Here we describe a new sensor platform for measuring bed-level change and estimating overwash inundation depths. Our MeOw (Measuring Overwash) stations consist of two ultrasonic distance sensors, a microprocessor board, and a camera and are capable of withstanding the impacts of large storm events, can be left unattended to collect data for months to years, and are relatively inexpensive. With the exception of the camera, the MeOw stations are built with all open-source hardware and software. Herein we provide complete instructions for manufacturing the MeOw stations and present observations from a single MeOw station for a three-month (2019) deployment on a frequently overwashed section of Smith Island, VA. The MeOw stations captured three large storm events over the course of the deployment (Hurricane Dorian, Tropical Storm Melissa, and a November nor’easter), as well as several high-tide events. Based on our interpretation of the raw data, bed-level changes occurred throughout the deployment from both storm and non-storm overwash, but were particularly large during Tropical Storm Melissa where initial accretion of approximately 0.15 m was followed by 0.77 m of erosion over three days. The maximum overwash inundation depth occurred during the nor’easter and measured approximately 0.83 m. The variability in bed level over the course of our experiment highlights the importance of in situ high frequency bed-level measurements for constraining overwash inundation depths. MeOw stations are ideally suited for measuring storm overwash — or any process that necessitates tracking bed and water level elevations at high frequency during harsh conditions.
低成本超声距离传感器远程床位变化及过洗观察
很少有高频率的数据集存在,风暴冲过的现场测量,一个重要的机制,对障壁岛和吐槽的地面维护。本文介绍了一种新的测量床面变化和估计过冲淹没深度的传感器平台。我们的MeOw(测量过冲)站由两个超声波距离传感器、一个微处理器板和一个摄像头组成,能够承受大风暴事件的影响,可以无人看管地收集数据数月至数年,而且价格相对便宜。除了摄像头之外,喵喵站的硬件和软件都是开源的。在此,我们提供了完整的制造MeOw站的说明,并提供了在弗吉尼亚州史密斯岛经常被淹没的部分部署的单个MeOw站的三个月(2019年)观测结果。MeOw站在部署过程中捕获了三次大型风暴事件(飓风多里安,热带风暴梅丽莎和11月的东北风),以及几次涨潮事件。根据我们对原始数据的解释,在整个部署过程中,由于风暴和非风暴冲积,床面都发生了变化,但在热带风暴梅丽莎期间,床面变化特别大,在三天的时间里,最初的冲积大约为0.15米,随后是0.77米的侵蚀。最大的过冲淹没深度发生在东北方,约为0.83米。在我们的实验过程中,床面变化突出了原位高频床面测量对限制过冲淹没深度的重要性。喵喵站非常适合测量风暴冲刷,或者任何需要在恶劣条件下高频跟踪河床和水位高度的过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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