EP33A-1056
Investigation of River Seismic Signal Induced by Sediment Transport and Water Flow: Controlled Dam Breaking Experiments

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Hsin Yu Chen1, Su Chin Chen1 and Wei-An Chao2, (1)National Chung Hsing University, Department of Soil and Water Conservation, Taichung, Taiwan, (2)Department of Geoscience, National Taiwan University, Taipei, Taiwan
Abstract:
Natural river’s bedload often hard to measure, which leads numerous uncertainties for us to predict the landscape evolution. However, the measurement of bedload flux has its certain importance to estimate the river hazard. Thus, we use seismometer to receive the seismic signal induced by bedload for partially fill the gap of field measurement capabilities.

Our research conducted a controlled dam breaking experiments at Landao River, Huisun Forest since it has advantage to well constraining the spatial and temporal variation of bedload transport. We set continuous bedload trap at downstream riverbed of dam to trap the transport bedload after dam breaking so as to analyze its grain size distribution and transport behavior. In the meantime we cooperate with two portable velocity seismometers (Guralp CMG6TD) along the river to explore the relationship between bedload transport and seismic signal.

Bedload trap was divided into three layers, bottom, middle, and top respectively. After the experiment, we analyzed the grain size and found out the median particle size from bottom to top is 88.664mm, 129.601mm, and 214.801mm individually. The median particle size of top layer is similar with the upstream riverbed before the experiment which median particle size is 230.683mm. This phenomena indicated that as the river flow become stronger after dam breaking, the sediment size will thereupon become larger, which meant the sediment from upstream will be carried down by the water flow and turned into bedload. Furthermore, we may tell apart the seismic signal induced by water flow and bedload by means of two different position seismometers. Eventually, we may estimate the probable error band of bedload quantity via accurately control of water depth, time-lapse photography, 3D LiDAR and other hydrology parameters.