Although Sabo dams are an efficient method for river and basin management, traditional Sabo dams have a great impact on ecology and landscape. Moreover, such dams are hit and often damaged by great impulsive force when they block the debris flow. Therefore, alternative shapes for Sabo dam deserve thorough investigation. In this investigation, a curved dam was designed by changing the upstream-dam-surface geometric shape to reduce the impulsive force of the debris flow, with enhanced stability and reduced concrete mass being the anticipated outcomes. In this study, the flume and laboratory facilities simulated the impulsive force of the debris flow to the Sabo dams. Three geometric forms, including vertical, slanted and curved Sabo dams, were used to determine the impulsive force. Impulsive force theories of the debris flow were derived from the momentum equation and the Bernoulli equation. In these, the impulsive force was balanced by the friction force of the Sabo dam and the opposite force of the load cell behind the dam as it was hit by the debris flow. Positive correlations were found when comparing the experimental data with the theoretical results. These findings suggest that our impulsive force theory has predictive validity with regard to the experimental data. The results from both theory and experimental data clearly show that curved darns were sustained less force than the other darns under the same debris flow. This comparison demonstrates the importance of curved geometry for a well-designed Sabo dam. 相似文献
There is a pressing need to determine the relationships between driving variables and landscape transformations. Human activities shape landscapes and turn them into complex assemblages of highly diverse structures. Other factors, including climate and topography, also play significant roles in landscape transitions, and identifying the interactions among the variables is critical to environmental management. This study analyzed the configurations and spatial-temporal processes of landscape changes from 1998 to 2011 under different anthropogenic disturbances, identified the main variables that determine the landscape patterns and transitions, and quantified the relationships between pairs of driver sets. Landsat images of Baicheng and Tekes from 1998, 2006 and 2011 were used to classify landscapes by supervised classification. Redundancy analysis (RDA) and variation partitioning were performed to identify the main driving forces and to quantify the unique, shared, and total explained variation of the sets of variables. The results indicate that the proportions of otherwise identical landscapes in Baicheng and Tekes were very different. The area of the grassland in Tekes was much larger than that of the cropland; however, the differences between the grassland and cropland in Baicheng were not as pronounced. Much of the grassland in Tekes was located in an area that was near residents, whereas most of the grassland in Baicheng was far from residents. The slope, elevation, annual precipitation, annual temperature, and distance to the nearest resident were strong driving forces influencing the patterns and transitions of the landscapes. The results of the variation partitioning indicated complex interrelationships among all of the pairs of driver sets. All of the variable sets had significant explanatory roles, most of which had both unique and shared variations with the others. The results of this study can assist policy makers and planners in implementing sustainable landscape management and effective protection strategies. 相似文献