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Potential application of hydrological ensemble prediction in forecasting floods and its components over the Yarlung Zangbo River basin, China

机译:中国水文集合预测水文集合预测亚隆Zangbo River河流域的洪水及其组件的潜在应用

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In recent year, floods becomes a serious issue in the Tibetan Plateau?(TP) due to climate change. Many studies have shown that ensemble flood forecasting based on numerical weather predictions can provide an early warning with extended lead time. However, the role of hydrological ensemble prediction in forecasting flood volume and its components over the Yarlung Zangbo River?(YZR) basin, China, has not been investigated. This study adopts the variable infiltration capacity?(VIC) model to forecast the annual maximum floods and annual first floods in the YZR based on precipitation and the maximum and minimum temperature from the European Centre for Medium-Range Weather Forecasts?(ECMWF). N simulations are proposed to account for parameter uncertainty in VIC. Results show that when trade-offs between multiple objectives are significant, N simulations are recommended for better simulation and forecasting. This is why better results are obtained for the Nugesha and Yangcun stations. Our ensemble flood forecasting system can skillfully predict the maximum floods with a lead time of more than 10 d and can predict about 7 d ahead for meltwater-related components. The accuracy of forecasts for the first floods is inferior, with a lead time of only 5 d. The base-flow components for the first floods are insensitive to lead time, except at the Nuxia station, whilst for the maximum floods an obvious deterioration in performance with lead time can be recognized. The meltwater-induced surface runoff is the most poorly captured component by the forecast system, and the well-predicted rainfall-related components are the major contributor to good performance. The performance in 7 d accumulated flood volumes is better than the peak flows.
机译:近年来,由于气候变化,洪水成为藏高原的严重问题?(TP)。许多研究表明,基于数值天气预报的集合洪水预测可以提供延长的交换时间的预警。然而,水文集合预测在yarlung Zangbo河上的预测洪水和其组件中的作用?(yzr)盆地,尚未调查。本研究采用可变渗透能力?(VIC)模型,以预测基于欧洲中距离预测中心的降水量和最高温度的yzr年度最大洪水和年度第一洪水?(ECMWF)。建议拟模拟以解释VIC中的参数不确定性。结果表明,当多个目标之间的权衡很大时,建议使用n仿真以进行更好的仿真和预测。这就是为什么为纽金斯和阳春站获得了更好的结果。我们的集合洪水预测系统可以巧妙地预测最大洪水超过10天,可以预测熔水与熔丙特水有关的组成部分。第一次洪水预测的准确性是较差的,其优惠时间仅为5天。第一洪水的碱流量分量对诺卡利亚站之外的发出时间不敏感,而在最大洪水中,可以识别出现铅的性能明显劣化。熔融诱导的表面径流是预测系统最糟糕的组成部分,良好预测的降雨相关组件是良好性能的主要贡献者。 7 D累计洪水卷中的性能优于峰值流量。

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