Flood Generation Mechanisms and Potential Drivers of Flood in Wabi-Shebele River Basin, Ethiopia

Fraol Abebe Wudineh, S. Moges, B. Kidanewold
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引用次数: 1

Abstract

Flood is a natural process generated by the interaction of various driving factors. Flood peak flows, flood frequency at different return periods, and potential driving forces are analyzed in this study. The peak flow of six gauging stations, with a catchment area ranging from 169 - 124,108 km 2 and sufficient observed streamflow data, was selected to develop threshold (3 rd quartile) magnitude and frequency (POTF) that occurred over ten years of records. Sixteen Potential climatic, watershed and human driving factors of floods in the study area were identified and analyzed with GIS, Pearson’s correlation, and Principal Correlation Analysis (PCA) to select the most influential factors. Eight of them (MAR, DA, BE, VS, sand, forest AGR, PD) are identified as the most significant variables in the flood formation of the basin. Moreover, mean annual rainfall (MAR), drainage area (DA), and lack of forest cover are explored as the principal driving factors for flood peak discharge in Wabi-Shebele River Basin. Fi-nally, the study resulted in regression equations that helped plan and design different infrastructure works in the basin as ungauged catchment empirical equations to compute Q MPF , Q 5 , Q 10 , Q 50 , and Q 100 using influential climate, watershed, and human driving factors. The results of these empirical equations are also statistically accepted with a high significance correlation (R 2 > 0.9).
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埃塞俄比亚Wabi-Shebele河流域洪水发生机制及潜在驱动因素
洪水是多种驱动因素相互作用产生的自然过程。分析了洪峰流量、不同回潮期洪峰频次及潜在驱动力。选取集水区面积为169 ~ 124,108 km²的6个测量站的峰值流量,建立了10年记录的阈值(第3四分位数)震级和频率(POTF)。利用GIS、Pearson’s correlation和主相关分析法(Principal correlation Analysis, PCA)对研究区洪水的16个潜在气候、流域和人为驱动因子进行了识别和分析。其中8个变量(MAR、DA、BE、VS、sand、forest AGR、PD)是影响流域洪水形成的最显著变量。此外,还探讨了年平均降雨量(MAR)、流域面积(DA)和森林覆盖缺失是瓦比-谢贝勒河流域洪峰流量的主要驱动因素。最后,研究得出回归方程,帮助规划和设计流域内不同的基础设施工程,作为未测量的流域经验方程,计算qmpf、q5、q10、q50和q100,并使用有影响的气候、流域和人为驱动因素。这些经验方程的结果在统计上也被接受,具有高度显著相关(r2 > 0.9)。
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