Effects of temporal resolution of input precipitation on the performance of hydrological forecasting

Effects of temporal resolution of input precipitation on the performance of hydrological forecasting
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输入降水时间分辨率对水文预报性能的影响

DOI:
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发表时间:
2011
期刊:
影响因子:
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通讯作者:
F. Pappenberger
F. Pappenberger
中科院分区:
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文献类型:
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作者:
F. Wetterhall;Y. He;H. Cloke;F. Pappenberger

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抽象的。洪水预测系统依赖于高质量的降水输入数据和预测来驱动水文模型。大部分降水量数据来自具有良好空间覆盖的逐日观测站。然而,一些洪水事件发生在亚日常的时间尺度上,洪水预测系统可以受益于使用在同一时间尺度上校准的模型。本研究比较了2006年10月1日至2009年12月31日期间ECMWF每小时预报的每小时站(HP)和每日站(DP)的降水数据。HP和DP数据集,然后被用来校准两个水文模型,LISFLOOD-RR和HBV,后者被用于洪水案例研究。在对交货期长达4天的预测进行评估时,HP的得分优于DP。然而,这并没有以同样的方式转化为水文建模,其中模型对两个数据集的模拟径流给出了相似的分数。洪水预报研究表明,两个数据集给出了相似的命中率,而HP数据集给出了小得多的误报率(FAR)。这表明,在水文模型的校准和启动中使用亚日降水量可以改善洪水预报。
Abstract. Flood prediction systems rely on good quality precipitation input data and forecasts to drive hydrological models. Most precipitation data comes from daily stations with a good spatial coverage. However, some flood events occur on sub-daily time scales and flood prediction systems could benefit from using models calibrated on the same time scale. This study compares precipitation data aggregated from hourly stations (HP) and data disaggregated from daily stations (DP) with 6-hourly forecasts from ECMWF over the time period 1 October 2006–31 December 2009. The HP and DP data sets were then used to calibrate two hydrological models, LISFLOOD-RR and HBV, and the latter was used in a flood case study. The HP scored better than the DP when evaluated against the forecast for lead times up to 4 days. However, this was not translated in the same way to the hydrological modelling, where the models gave similar scores for simulated runoff with the two datasets. The flood forecasting study showed that both datasets gave similar hit rates whereas the HP data set gave much smaller false alarm rates (FAR). This indicates that using sub-daily precipitation in the calibration and initiation of hydrological models can improve flood forecasting.
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DOI: 10.1111/j.1753-318x.2009.01056.x
发表时间: 2010
影响因子: 4.1
作者:
Nobert S
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DOI: 10.1002/met.194
发表时间: 2010
影响因子: 2.7
作者:
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