| Summary: | 碩士 === 國立屏東科技大學 === 水土保持系所 === 96 === Toraji typhoon disembarked in the Hsiukuluan river of Hualien county in July 30, 2001 has caused severe disaster in Nangchingshui creek in Tashing village of Kuangfu township, Chienching creek in Chienching village of Wanjung township, Fengyi Suiyuanti in Fengyi town of Fenglin township, and Chialang creek in Hsinshe village of Fengpin township. After typhoon disaster, the government invested money and resource in planning overall administration of disaster zone, disaster prevention drills and evacuation route. Besides, the government also constructed all kind of control facilities to help the victims of the natural disaster rebuild their country.
This research has chosen Nangchingshui creek and Fengyi Suiyuanti watershed of the severest debris flow disaster zone as example. We collected sediment disaster data in Hualien among 1991 to 1998, and investigated field data of research areas to check the effect assessment of control facilities. On the other hand, we combined the measuring downstream scour data of control facilities with the existing domestic and foreign scour data and model to discuss and analyze the downstream scour form of control facilities. The results of this research are as follows:
1. The two creeks of this research deposited a lot of sediment after typhoon hazards, so the density of river-bed sediment could be looser than original river-bed sediment. That might cause sediment to scour easily by flood. We could calculate the flow velocity of creek-section by HEC-RAS and construct lateral control facilities in the rapid flow velocity of creek-section to adjust creek-slope and retard flow velocity. It could be proved that constructing groundsills was more effective to adjust creek-slope, retard flow velocity and slow the scour of river-bed down, but we could pay attention to the downstream scour of groundsills.
2. According to the 22 measured scour data in 2 research areas, we derived the models for maximum scour depth and length of groundsill conducting the parameters of , ( ), ( ), ( ) by multiple regression analysis.
The maximum scour depth of groundsill:
The maximum scour length of groundsill:
3. According to the 50 measured scour data in 7 domestic and foreign research areas, we derived the models for maximum scour depth and length of groundsill conducting the parameters of , ( ), ( ), ( ) by multiple regression analysis.
The maximum scour depth of groundsill:
The maximum scour length of groundsill:
4. This research showed that measuring scour data in single research area had same trend properties. But we merged all of measuring scour data in different research areas to analyze scour properties, it showed that all of measuring scour data was chaos and irregular. Causing this result might be every research area having their properties and can not merge all of data to analyze. Every research area might be having their scour trend line or scour model.
5. According to the 95 measured scour data in 8 domestic and foreign research areas, it showed that maximum scour depth( )and drop height( ) were positive correlation, maximum scour length( )and drop height( )were same positive correlation.
6. We put the measuring scour data in this research into the existing model. It showed that calculating scour depth by model of Lenzi et al. (2002) was similar to measuring scour data, but almost measuring and calculating scour depth were more different generally.
7. After verification and comparison, the scour depth model of this research or the existing scour depth model matched better than the model of scour length. Causing this result might measure maximum scour depth easier judgment than maximum scour length, and using the scour depth model of this research to calculate field scour depth could get more precise than the scour length model to calculate field scour length.
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