水文模型的不确定性量化

P. Vallam, X.S. Qin, J.J. Yu
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引用次数: 8

摘要

采用广义似然不确定性估计(GLUE),即一种简化的贝叶斯方法来确定水文模型中的参数不确定性。对加拿大库特尼流域夏季水流进行了初步分析,模拟了典型的不确定性分析程序。SLURP是一种健壮的水文模型。结果证明了GLUE方法与SLURP水文模型结合应用的可行性,随后分析了参数的后验概率分布。该技术的性能通过检查2年的流量预测间隔得到验证,从而为流域提供有效的未来水文预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uncertainty Quantification of Hydrologic Model

Generalized Likelihood Uncertainty Estimation (GLUE), a simplified Bayesian method, was adopted to determine the parametric uncertainty in hydrological modeling. A preliminary analysis of the summer flows of the Kootenay Watershed, Canada, was modeled to portray a typical uncertainty analysis procedure. SLURP, a robust hydrologic model was chosen for this procedure. The results demonstrated the viability of applying the GLUE method in conjunction with the SLURP hydrological model, following which the posterior probability distributions of the parameters was analyzed. The performance of this technique was verified by examining the flows’ prediction intervals for a period of 2 years, enabling valid future hydrological forecasting for the watershed.

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