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Water Resources Management

Erschienen in:

18.04.2021

Contrasting Uncertainties in Estimating Floods and Low Flow Extremes

verfasst von: Hadush Meresa, Yongqiang Zhang

Erschienen in: Water Resources Management | Ausgabe 6/2021

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Abstract

Evaluation of possible sources of uncertainty and their influence on water resource planning and extreme hydrological characteristics are very important for extreme risk reduction and management. The main objective is to identify and holistically address the uncertainty propagation from the input data to the frequency of hydrological extremes. This novel uncertainty estimation framework has four stages that comprise hydrological models, hydrological parameter sets, and frequency distribution types. The influence of uncertainty on the simulated flow is not uniform across all the selected eight catchments due to different flow regimes and runoff generation mechanisms. The result shows that uncertainty in peak flow frequency simulation mainly comes from the input data quality. Whereas, in the low flow frequency, the main contributor to the total uncertainty is model parameterization. The total uncertainty in the estimation 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. In contrast, the hydrological models and hydrological parameters have a substantial impact on the QT10 (extreme low flow quantile at 10-year return period) estimation. This implies that the four factors and their interactions may cause significant risk in water resource management and flood and drought risk management. Therefore, neglecting these factors in disaster risk management, water resource planning, and evaluation of environmental impact assessment is not feasible and may lead to significant impact.

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Titel: Contrasting Uncertainties in Estimating Floods and Low Flow Extremes
verfasst von: Hadush Meresa
Yongqiang Zhang
Publikationsdatum: 18.04.2021
Verlag: Springer Netherlands
Erschienen in: Water Resources Management / Ausgabe 6/2021
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI: https://doi.org/10.1007/s11269-021-02809-3

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