Assessing different sources of uncertainty in hydrological projections of high and low flows: case study for Omerli Basin, Istanbul, Turkey
Assessing different sources of uncertainty in hydrological projections of high and low flows: case study for Omerli Basin, Istanbul, Turkey
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评估高流量和低流量水文预测中不确定性的不同来源：土耳其伊斯坦布尔奥梅尔利盆地案例研究
DOI：
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发表时间：
2017
影响因子：
3
通讯作者：
A. Yılmaz
中科院分区：
文献类型：
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作者：
Batuhan Engin;Ismail Yücel;A. Yılmaz
本研究探讨了水文模式参数化和集合区域气候模式（RCM）输入的预测变化的高，低流量的不确定性贡献的评估。利用水文学Byråns Vattenbalansavdelning（HBV）模式和基于4个目标函数的25个最佳拟合参数集，利用15个全球环流模式（GCM）/RCM组合和2个偏差修正（变化因子（CF）和平均偏差修正（BC））的气候预测集合生成参考期和未来期的径流序列。通过季节性指数的计算，对高流量发生的时间进行了评估。结果表明，与水文模式参数化的贡献相比，集合气候模式的水文模式输入对高流量预测变化的不确定性贡献更大。然而，不确定性的贡献是相反的低流量，特别是CF方法。CF和BC都增加了高流量和低流量的总平均方差。高流量发生时间的变化通过RCMs是大于水文模型参数的变化，没有统计降尺度。CF提供了比BC更准确的时间，它显示了洪水季节性的最明显的变化。
This study investigates the assessment of uncertainty contribution in projected changes of high and low flows from parameterization of a hydrological model and inputs of ensemble regional climate models (RCM). An ensemble of climate projections including 15 global circulation model (GCM)/RCM combinations and two bias corrections (change factor (CF) and bias correction in mean (BC)) was used to generate streamflow series for a reference and future period using the Hydrologiska Byråns Vattenbalansavdelning (HBV) model with the 25 best-fit parameter sets based on four objective functions. The occurrence time of high flows is also assessed through seasonality index calculation. Results indicated that the inputs of hydrological model from ensemble climate models accounts for greater contribution to the uncertainty related to projected changes in high flows comparing to the contribution from hydrological model parameterization. However, the uncertainty contribution is opposite for low flows, particularly for CF method. Both CF and BC increases the total mean variance of high and low flows. The variability in the occurrence time of high flows through RCMs is greater than the variability resulted from hydrological model parameters with and without statistical downscaling. The CF provides more accurate timing than BC and it shows the most pronounced changes in flood seasonality.