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Contrasting uncertainties in estimating floods and extreme low flow
  • Hadush Kidane Meresa,
  • Yongqiang Zhang
Hadush Kidane Meresa
Institute of Geographic Sciences and Natural Resources Research
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Yongqiang Zhang
Institute of Geographic Sciences and Natural Resources Research

Corresponding Author:[email protected]

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Abstract

Evaluation and quantification of possible sources of uncertainty and their influence on water resource planning and extreme management is very important for risk modeling and extreme hydrological management. The main objective of this research work is to combine statistical climate ensembles, multiple parameter sets for three conceptual hydrological model structure and five flood frequency distribution models to investigate the interplay among the associated uncertainty in flood and low flow modelling. Uncertainty in the modeling of extreme high flow frequency mainly comes from the quality of the input data, while in the modeling of low flow frequency, the main contributor to the total uncertainty is from model parameterization. This result is also confirmed by using the Analysis Of Variance Analysis (ANOVA) that considers additional information about the interaction impact of the main factors. The total uncertainty of QT90 (extreme peak flow quantile at 90-year return period) quantile shows the interaction of input data and extreme frequency models has significant influence on the total uncertainty. In contrast, in the QT10 (extreme low flow quantile at 10-year return period) estimation, the hydrological models and hydrological parameters have significant impact on the total uncertainty. This implies that the four factors and their interactions may cause significant risk in water resource management and flood and drought risk management, and neglecting of these four factors and their interaction in disaster risk management, water resource planning and evaluation of environmental impact assessment is not feasible and may lead to big risk.