Uncertainty exists widely in hydrological analysis, and this makes the process of uncertainty assessment very im- portant for making robust decisions. In this study, uncertainty sources in regional rainfall frequency ...Uncertainty exists widely in hydrological analysis, and this makes the process of uncertainty assessment very im- portant for making robust decisions. In this study, uncertainty sources in regional rainfall frequency analysis are identified for the first time. The numeral unite spread assessment pedigree （NUSAP） method is introduced and is first employed to quantify qual- itative uncertainty in regional rainfall frequency analysis. A pedigree matrix is particularly designed for regional rainfall frequency analysis, by which the qualitative uncertainty can be quantified. Finally, the qualitative and quantitative uncertainties are com- bined in an uncertainty diagnostic diagram, which makes the uncertainty evaluation results more intuitive. From the integrated diagnostic diagram, it can be determined that the uncertainty caused by the precipitation data is the smallest, and the uncertainty from different grouping methods is the largest. For the downstream sub-region, a generalized extreme value （GEV） distribution is better than a generalized logistic （GLO） distribution; for the south sub-region, a Pearson type III （PE3） distribution is the better choice; and for the north sub-region, GEV is more appropriate.展开更多
基金the National Natural Science Foundation of China，the Zhejiang Provincial Natural Science Foundation of China
文摘Uncertainty exists widely in hydrological analysis, and this makes the process of uncertainty assessment very im- portant for making robust decisions. In this study, uncertainty sources in regional rainfall frequency analysis are identified for the first time. The numeral unite spread assessment pedigree （NUSAP） method is introduced and is first employed to quantify qual- itative uncertainty in regional rainfall frequency analysis. A pedigree matrix is particularly designed for regional rainfall frequency analysis, by which the qualitative uncertainty can be quantified. Finally, the qualitative and quantitative uncertainties are com- bined in an uncertainty diagnostic diagram, which makes the uncertainty evaluation results more intuitive. From the integrated diagnostic diagram, it can be determined that the uncertainty caused by the precipitation data is the smallest, and the uncertainty from different grouping methods is the largest. For the downstream sub-region, a generalized extreme value （GEV） distribution is better than a generalized logistic （GLO） distribution; for the south sub-region, a Pearson type III （PE3） distribution is the better choice; and for the north sub-region, GEV is more appropriate.
