Assessment of Uncertainty in the Spatial Distribution of Rainfall Using Geostochastic Simulation

被引:3
作者
Seo, Youngmin [1 ]
Kim, Sungwon [1 ]
Singh, Vijay P. [2 ,3 ]
机构
[1] Dongyang Univ, Dept Railrd & Civil Engn, Yeongju 750711, South Korea
[2] Texas A&M Univ, Dept Biol & Agr Engn, College Stn, TX 77843 USA
[3] Texas A&M Univ, Dept Civil & Environm Engn, College Stn, TX 77843 USA
关键词
Sequential Gaussian simulation; Turning bands method; Uncertainty assessment; Circulant embedding method; Geostochastic simulation; Rainfall spatial distribution; VARIABILITY; ALGORITHM; MODELS; FIELDS; RADAR;
D O I
10.1061/(ASCE)HE.1943-5584.0000882
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The uncertainty in the spatial rainfall distribution and basin mean rainfall for flood discharge estimation has not been considered in hydrologic practice. The geostochastic simulation has potential for the assessment of uncertainty of the spatial rainfall distribution and basin mean rainfall. This study compares three geostochastic simulation methods, including the circulant embedding method (CEM), the sequential Gaussian simulation (SGS), and the turning bands method (TBM), for assessing the uncertainty in the spatial distribution of rainfall. These methods are found to be comparable in terms of spatial standard deviation, coefficient of variation, interquartile range, overall range, and the distribution of basin mean rainfall. Further, the estimates of basin mean rainfall by these methods are almost similar to those by conventional spatial interpolation methods. However, CEM and TBM are found to be superior to SGS in the simulation performance based on mean error (ME), mean percentage error (MPE), mean absolute error (MAE), and root-mean-square error (RMSE). The geostochastic simulation methods have potential for flood risk assessment.
引用
收藏
页码:978 / 992
页数:15
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