摘要
水文模拟精度优劣与参与水文过程的多源不确定性相关,且其累积效应将会造成预测不确定性进一步扩大。因此,以黄河源区为例,利用极大似然不确定性估计法(GLUE)识别新安江模型有效参数组,通过耦合CMIP5下4种气候模式、3种气候变化情景、8种有效参数组,揭示了各源不确定性对流域径流量和蓄水量预测的影响,并采用方差分析方法(ANOVA)量化分离了其对月尺度流域径流量和蓄水量预测不确定性的相对贡献。结果表明,利用统计降尺度模型(SDSM)获得的降水量、最低和最高气温数据可较好的应用于研究区,其相关系数R^(2)均大于0.70,且均方根误差R_(RMSE)小于30%;参数和GCMs不确定性对流域径流量的影响占主导地位,前者对流域蓄水量的相对贡献高达0.98,且多源不确定性之间交互作用对汛前和汛后的贡献大于非汛期。研究结果对于流域防洪减灾、降低水文模拟过程认知不确定性具有重要意义。
The accuracy of the hydrological simulation is closely related to the multi-source uncertainty involved in the hydrological process,and its cumulative effect inevitably leads to further expansion of hydrological prediction uncertainty.Therefore,this paper takes the source region of the Yellow River as the research object and uses the maximum likelihood uncertainty estimation method(GLUE)to effectively identify the"same effect"parameter group of the Xin'anjiang model.By coupling four future climate models,three climate change scenario data,and eight"different parameters and same effect"parameter sets under CMIP5,the impact of source uncertainty on watershed runoff and water storage was explored.Finally,the analysis of variance(ANOVA)method was used to quantitatively separate the relative contributions of each source uncertainty to monthly scale watershed runoff and water storage.The results show that the precipitation,minimum and maximum temperature data obtained using the SDSM downscaling model can be better applied to the Yellow River basin,with correlation coefficients(R^(2))greater than 0.70 and root mean square error(R_(RMSE))less than 30%.The uncertainty of parameters and GCMs dominates the impact on watershed runoff,with the former contributing up to 0.98 relative to watershed water storage,and the interaction between multi-source uncertainties contributes more to pre-flood and post-flood than to non-flood period.The research results are of great significance for flood control and disaster reduction in river basins,as well as for reducing cognitive uncertainty in hydrological simulation processes.
作者
殷晖
白福青
YIN Hui;BAI Fu-qing(College of Civil Engineeringand Architecture,Zhejiang University of Water Resources and Electric Power,Hangzhou 310018,China)
出处
《水电能源科学》
北大核心
2024年第2期18-22,共5页
Water Resources and Power
基金
浙江省水利厅重点课题(RB2115)
浙江水利水电学院课题(SWHZX202003)。
关键词
多源不确定性
径流
蓄水量
水文模型
黄河上游
multi-source uncertainty
runoff
water storage
hydrologic model
Upper Reaches of Yellow River
