首页> 外文会议>Hydroinformatics 2006 vol.2 >SNOWMELT FLOOD FREQUENCY ESTIMATION USING PHYSICALLY BASED MODEL COUPLED WITH WEATHER GENERATOR (WITH ESTIMATION'S UNCERTAINTY)
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SNOWMELT FLOOD FREQUENCY ESTIMATION USING PHYSICALLY BASED MODEL COUPLED WITH WEATHER GENERATOR (WITH ESTIMATION'S UNCERTAINTY)

机译:使用基于物理模型与天气生成器耦合的斯诺弗尔特洪水频率估计(估计的不确定性)

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摘要

A dynamic-stochastic model, which combines a physically based model of snowmelt runoff formation with a stochastic weather generator, has been proposed to estimate frequencies of extreme snowmelt floods. The physically based model describes snow accumulation and melt, soil freezing and thawing, vertical soil moisture transfer and infiltration, detention of melt water by the depressions at the catchment surface, overland and channel flow. The weather generator includes stochastic models that produce daily values of precipitation, air temperature, and air humidity during a whole year. Daily weather variables have been generated by Monte Carlo procedure and transposed to snowmelt flood discharges by the physically based model. The suitability of the dynamic-stochastic model has been demonstrated through its ability to reproduce frequencies of snowmelt flood peak discharges measured at the Seim river (the catchment area is 7460 km~2). Uncertainty of the calculated peak discharges of low probabilities has been assessed on the basis of Latin hypercube sampling.
机译:提出了一种动态随机模型,该模型将基于物理的融雪径流形成模型与随机天气生成器相结合,以估算极端融雪洪水的频率。基于物理的模型描述了积雪和融雪,土壤冻结和解冻,垂直土壤水分的转移和渗透,集水面凹陷处的融水滞留,陆上和河道流量。天气生成器包括随机模型,该模型可生成全年的每日降水,空气温度和空气湿度的日数值。每日天气变量已通过蒙特卡洛程序生成,并通过基于物理的模型转换为融雪洪水流量。通过再现Seim河(集水区为7460 km〜2)测得的融雪洪峰流量的频率,已经证明了动态随机模型的适用性。已根据拉丁文超立方体采样评估了计算出的低概率峰值排放的不确定性。

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