摘要
选用8种概率分布函数,系统分析北江上游犁市和下游石角2站的水文极值流量。以极大似然法估计函数参数,采用K-S、A-D、ABS和AIC拟合优度方法选出变化环境前后最优分布函数。并对水文极值流量变化规律及其影响作了有益探讨。结果表明:1991年后流域下垫面植被减少是造成年最大流量显著上升的主要原因。犁市站极值流量厚尾分布拟合最好,石角站薄尾分布拟合最优,变化环境前后洪水频率最优分布线型基本一致,但流量增大造成分布参数改变已导致分布线型高水尾部特性变陡,相应设计流量偏大。用水文情势发生变化前估计的洪水重现期往往不能很好地描述变化后洪水频率特征。北江上游及时修建防洪水利工程对减轻中下游的防洪压力尤为重要。
We analyzed the statistical properties of hydrologic extreme flow for hydrologic stations of Lishi and Shijiao in Beijiang River using eight probability distribution functions. Estimate of parameters was performed using the maximum likelihood technique. Goodness-of-fit was done based on K-S, A-D, ABS and AIC for the optimal linear frequency distribution before and after environmental change. And the rules and effects of variability for hydrologic extreme flow was dis- cussed. The research results indicate that based on vegetation reduction in the basin, annual max- imum flow increased significantly in 1991, the hydrological conditions varied. Heavy tail distribu- tion at Lishi and light tail distribution at Shijiao were found to be the best fitting model. The opti- mal linear frequency distribution maintain consistency before and after environment change, but the impacts on fitting curve of flood series showed an overall performance as upper tail from "gen- tle" to" steep", and the designed flood magnitude will become larger. After changes in the hydro- logical regime, the flood return period estimated before the change is often unable to well describe the flood frequency characteristics after environmental changes. Construction of water conservancy projects in the upper reaches is vital to alleviate the pressure of flood on the middle and lower rea- ches of the river.
出处
《自然资源学报》
CSSCI
CSCD
北大核心
2012年第12期2102-2112,共11页
Journal of Natural Resources
基金
国家自然科学基金重点项目(50839005)
广东省科技厅项目(2010B050300010)
广东省水利科技创新项目(2009-39)
中英瑞气候变化适应项目广东气候变化风险评估及适应对策研究(ACCC/20100705-1)
国家重点基础研究发展计划(973)项目(2010CB428405)
广东省自然科学基金(S2011010001549)
关键词
频率分析
概率分布函数
极值流量
重现期
frequency analysis
probability distribution functions
stream flow extremes
return periods