Accurate prediction of the hydrographs of outburst floods induced by landslide dam overtopping failure is necessary for hazard prevention and mitigation. In this study, flume model tests on the breaching of landslide ...Accurate prediction of the hydrographs of outburst floods induced by landslide dam overtopping failure is necessary for hazard prevention and mitigation. In this study, flume model tests on the breaching of landslide dams were conducted. Unconsolidated soil materials with wide grain size distributions were used to construct the dam. The effects of different upstream inflow discharges and downstream bed soil erosion on the outburst peak discharge were investigated. Experimental results reveal that the whole hydrodynamic process of landslide dam breaching can be divided into three stages as defined by clear inflection points and peak discharges. The larger the inflow discharge, the shorter the time it takes to reach the peak discharge, and the larger the outburst flood peak discharge. The scale of the outburst floods was found to be amplified by the presence of an erodible bed located downstream of the landslide dam. This amplification decreases with the increase of upstream inflow. In addition, the results show that the existence of an erodible bed increases the density of the outburst flow, increasing its probability of transforming from a sediment flow to a debris flow.展开更多
The estimation of underwater features of channel bed surfaces without the use of bathymetric sensors results in very high levels of uncertainty. A revised approach enabling an automatic extraction of the wet areas to ...The estimation of underwater features of channel bed surfaces without the use of bathymetric sensors results in very high levels of uncertainty. A revised approach enabling an automatic extraction of the wet areas to create more accurate and detailed Digital Terrain Models (DTMs) is here presented. LiDAR-derived elevations of dry surfaces, water depths of wetted areas derived from aerial photos and a predictive depth-colour relationship were adopted. This methodology was applied at two different reaches of a northeastern Italian gravel-bed river (Tagliamento) before and after two flood events occurred in November and December 2010. In-channel dGPS survey points were performed taking different depth levels and different colour scales of the river bed. More than 10,473 control points were acquired, 1107 in 2010 and 9366 in 2011 respectively. A regression model that calculates channel depths using the correct intensity of three colour bands (RGB) was implemented. LiDAR and water depth points were merged and interpolated into DTMs which features an average error, for the wet areas, of ±14 cm. The different number of calibration points obtained for 2010 and 2011 showed that the bathymetric error is also sensitive to the number of acquired calibration points. The morphological evolution calculated through a difference of DTMs shows a prevalence of deposition and erosion areas into the wet areas.展开更多
基金the financial support from the National Natural Science Foundation of China (Grant No. 41731283)the Key Research Program of Frontier Sciences, Chinese Academy of Sciences (CAS) (Grant No. QYZDB-SSW-DQC010)the Youth Innovation Promotion Association, Chinese Academy of Sciences (CAS)
文摘Accurate prediction of the hydrographs of outburst floods induced by landslide dam overtopping failure is necessary for hazard prevention and mitigation. In this study, flume model tests on the breaching of landslide dams were conducted. Unconsolidated soil materials with wide grain size distributions were used to construct the dam. The effects of different upstream inflow discharges and downstream bed soil erosion on the outburst peak discharge were investigated. Experimental results reveal that the whole hydrodynamic process of landslide dam breaching can be divided into three stages as defined by clear inflection points and peak discharges. The larger the inflow discharge, the shorter the time it takes to reach the peak discharge, and the larger the outburst flood peak discharge. The scale of the outburst floods was found to be amplified by the presence of an erodible bed located downstream of the landslide dam. This amplification decreases with the increase of upstream inflow. In addition, the results show that the existence of an erodible bed increases the density of the outburst flow, increasing its probability of transforming from a sediment flow to a debris flow.
文摘The estimation of underwater features of channel bed surfaces without the use of bathymetric sensors results in very high levels of uncertainty. A revised approach enabling an automatic extraction of the wet areas to create more accurate and detailed Digital Terrain Models (DTMs) is here presented. LiDAR-derived elevations of dry surfaces, water depths of wetted areas derived from aerial photos and a predictive depth-colour relationship were adopted. This methodology was applied at two different reaches of a northeastern Italian gravel-bed river (Tagliamento) before and after two flood events occurred in November and December 2010. In-channel dGPS survey points were performed taking different depth levels and different colour scales of the river bed. More than 10,473 control points were acquired, 1107 in 2010 and 9366 in 2011 respectively. A regression model that calculates channel depths using the correct intensity of three colour bands (RGB) was implemented. LiDAR and water depth points were merged and interpolated into DTMs which features an average error, for the wet areas, of ±14 cm. The different number of calibration points obtained for 2010 and 2011 showed that the bathymetric error is also sensitive to the number of acquired calibration points. The morphological evolution calculated through a difference of DTMs shows a prevalence of deposition and erosion areas into the wet areas.
