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Video monitoring of in‐channel wood: From flux characterization and prediction to recommendations to equip stations
Earth Surface Processes and Landforms ( IF 3.3 ) Pub Date : 2021-01-15 , DOI: 10.1002/esp.5068
Zhi Zhang 1 , Hossein Ghaffarian 1 , Bruce MacVicar 2 , Lise Vaudor 1 , Aurélie Antonio 1 , Kristell Michel 1 , Hervé Piégay 1
Affiliation  

Wood flux (piece number per time interval) is a key parameter for understanding wood budgeting, determining the controlling factors, and managing flood risk in a river basin. Quantitative wood flux data is critically needed to improve the understanding of wood dynamics and estimate wood discharge in rivers. In this study, the streamside videography technique was applied to detect wood passage and measure instantaneous rates of wood transport. The goal was to better understand how wood flux responds to flood and wind events and then predict wood flux. In total, one exceptional wind and seven flood events were monitored on the Ain River, France, and around 24,000 wood pieces were detected visually. It is confirmed that, in general, there is a threshold of wood motion in the river equal to 60% of bankfull discharge. However, in a flood following a windy day, no obvious threshold for wood motion was observed, which confirms that wind is important for the preparation of wood for transport between floods. In two multi‐peak floods, around two‐thirds of the total amount of wood was delivered on the first peak, which confirms the importance of the time between floods for predicting wood fluxes. Moreover, we found an empirical relation between wood frequency and wood discharge, which is used to estimate the total wood amount produced by each of the floods. The data set is then used to develop a random forest regression model to predict wood frequency as a function of three input variables that are derived from the flow hydrograph. The model calculates the total wood volume either during day or night based on the video monitoring technique for the first time, which expands its utility for wood budgeting in a watershed. A one‐to‐one link is then established between the fraction of detected pieces of wood and the dimensionless parameter “passing time × frame rate”, which provides a general guideline for the design of monitoring stations.

中文翻译:

通道内木材的视频监控:从通量表征和预测到建议到装备站

木材通量(每个时间间隔的件数)是了解木材预算,确定控制因素以及管理流域洪水风险的关键参数。迫切需要定量的木材通量数据,以增进对木材动力学的了解并估算河流中的木材排放量。在这项研究中,河边摄像技术被用于检测木材通过并测量木材运输的瞬时速率。目的是更好地了解木材通量如何响应洪水和风灾事件,然后预测木材通量。总共在法国的艾因河上监测了一次特大风和七次洪水事件,目视检测到约24,000个木片。可以肯定的是,一般来说,河流中的木材运动阈值等于河岸满溢流量的60%。然而,在大风天过后的洪水中,没有观察到明显的木材运动阈值,这证明风对于在洪水之间运输的木材的制备很重要。在两次多峰洪灾中,约有三分之二的木材是在第一个高峰期交付的,这证实了两次洪灾之间的时间对于预测木材通量的重要性。此外,我们发现了木材频率与木材排放量之间的经验关系,该关系用于估算每次洪水产生的木材总量。然后,该数据集用于开发随机森林回归模型,以预测木材频率作为从流量水位图得出的三个输入变量的函数。该模型首次根据视频监控技术来计算白天或晚上的木材总体积,这扩大了它在分水岭上进行木材预算的效用。然后,在检测到的木材碎片与无量纲参数“通过时间×帧速率”,这为监控站的设计提供了一般指导。
更新日期:2021-01-15
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