Seasonal streamflow forecasting for fresh water reservoir management in the Netherlands: an assessment of multiple prediction systems

IF 3.1 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
R. Hurkmans, B. van den Hurk, M. Schmeits, F. Wetterhall, I. Pechlivanidis
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引用次数: 1

Abstract

For efficient management of the Dutch surface water reservoir Lake IJssel, (sub)seasonal forecasts of the water volumes going in and out of the reservoir are potentially of great interest. Here, streamflow forecasts were analyzed for the river Rhine at Lobith, which is partly routed through the river IJssel, the main influx into the reservoir. We analyzed seasonal forecast data sets derived from EFAS, E-HYPE and HTESSEL, which differ in their underlying hydrological formulation, but are all forced by meteorological forecasts from ECMWF SEAS5. We post-processed the streamflowforecasts using quantile mapping (QM) and analyzed several forecast quality metrics. Forecast performance was assessed based on the available reforecast period, as well as on individual summer seasons. QM increased forecast skill for nearly all metrics evaluated. Averaged over the reforecast period, forecasts were skillful for up to four months in spring, and early summer. Later in summer the skillful period deteriorated to 1-2 months. When investigating specific years with either low or high flow conditions, forecast skill increased with the extremity of the event. Although raw forecasts for both E-HYPE and EFAS were more skillful than HTESSEL, bias correction based on QM can significantly reduce the difference. In operational mode, the three forecast systems show comparable skill. In general, dry conditions can be forecasted with high success rates up to three months ahead, which is very promising for successful use of Rhine streamflow forecasts in downstream reservoir management.
荷兰淡水水库管理的季节性流量预测:多种预测系统的评估
为了有效地管理荷兰的伊塞尔湖地表水水库,对进出水库的水量进行(分)季节预报可能会引起极大的兴趣。在这里,对洛比斯的莱茵河的流量预测进行了分析,莱茵河部分流经伊塞尔河,而伊塞尔河是流入该水库的主要河流。我们分析了来自EFAS、E-HYPE和HTESSEL的季节预报数据集,它们的基础水文公式不同,但都受到来自ECMWF SEAS5的气象预报的影响。利用分位数映射(QM)对流量预测进行了后处理,并分析了几种预测质量指标。预报的效果是根据可获得的再预报期和个别夏季来评估的。QM提高了几乎所有评估指标的预测技能。在重新预测期间平均下来,在春季和初夏的四个月里,预测是熟练的。夏季后期,熟练期缩短为1-2个月。当调查具有低或高流量条件的特定年份时,预测技能随着事件的极端程度而提高。尽管E-HYPE和EFAS的原始预测都比HTESSEL更熟练,但基于QM的偏差校正可以显著减小差异。在运行模式下,这三种预报系统显示出相当的技能。一般来说,干旱状况可以提前三个月预测,成功率很高,这对于在下游水库管理中成功使用莱茵河流量预测是非常有希望的。
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来源期刊
Journal of Hydrometeorology
Journal of Hydrometeorology 地学-气象与大气科学
CiteScore
7.40
自引率
5.30%
发文量
116
审稿时长
4-8 weeks
期刊介绍: The Journal of Hydrometeorology (JHM) (ISSN: 1525-755X; eISSN: 1525-7541) publishes research on modeling, observing, and forecasting processes related to fluxes and storage of water and energy, including interactions with the boundary layer and lower atmosphere, and processes related to precipitation, radiation, and other meteorological inputs.
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