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      Uncertainty estimation of the SURR model parameters and input data for the Imjin River basin using the GLUE method

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      https://www.riss.kr/link?id=A107513454

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      <P>This study investigated the flow simulation uncertainty caused by the model parameters and input data for the Imjin River basin using the generalized likelihood uncertainty estimation (GLUE) method and the Sejong University rainfall-runoff (SURR) model for four events during 2007, 2008, 2009 and 2010. Based on the nonsystematic errors caused by the rainfall interpolation process, the input uncertainty was estimated and compared with the model parameter uncertainty for the regions with different data information situations. The reasons for the high or low uncertainty of the model parameters and input were also analyzed. Two indices were used to examine the uncertainty of the streamflow simulation: the ratio of the number of observations falling inside the uncertainty interval (p - factor) and the width of the uncertainty interval (r - factor). The results indicated that the uncertainty of the streamflow simulation of the northern area (Gunnam station) was significantly higher than that of the southern areas (Jeonkok and Jeogseong stations) for both model parameter and input uncertainty. In the southern areas, the parameter uncertainty was higher than the input uncertainty. However, the northern area exhibited the opposite trend, with the former being lower than the latter. Additionally, the uncertainty was also shown in the time of the hydrograph. The uncertainty at the peak flow was higher than that at the beginning or the end of each event.</P>
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      <P>This study investigated the flow simulation uncertainty caused by the model parameters and input data for the Imjin River basin using the generalized likelihood uncertainty estimation (GLUE) method and the Sejong University rainfall-runoff (S...

      <P>This study investigated the flow simulation uncertainty caused by the model parameters and input data for the Imjin River basin using the generalized likelihood uncertainty estimation (GLUE) method and the Sejong University rainfall-runoff (SURR) model for four events during 2007, 2008, 2009 and 2010. Based on the nonsystematic errors caused by the rainfall interpolation process, the input uncertainty was estimated and compared with the model parameter uncertainty for the regions with different data information situations. The reasons for the high or low uncertainty of the model parameters and input were also analyzed. Two indices were used to examine the uncertainty of the streamflow simulation: the ratio of the number of observations falling inside the uncertainty interval (p - factor) and the width of the uncertainty interval (r - factor). The results indicated that the uncertainty of the streamflow simulation of the northern area (Gunnam station) was significantly higher than that of the southern areas (Jeonkok and Jeogseong stations) for both model parameter and input uncertainty. In the southern areas, the parameter uncertainty was higher than the input uncertainty. However, the northern area exhibited the opposite trend, with the former being lower than the latter. Additionally, the uncertainty was also shown in the time of the hydrograph. The uncertainty at the peak flow was higher than that at the beginning or the end of each event.</P>

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