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水力发电学报 ›› 2019, Vol. 38 ›› Issue (3): 65-74.doi: 10.11660/slfdxb.20190307

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基于径流和积雪资料的水文模型多目标率定

  

  • 出版日期:2019-03-25 发布日期:2019-03-25

Multi-objective optimization of hydrological model based on runoff and snow data

  • Online:2019-03-25 Published:2019-03-25

摘要: 以雅鲁藏布江奴下水文站以上流域作为研究区,采用HBV水文模型(Hydrologiska Byr?ns Vattenbalansavdelning model)对研究区域的积雪和径流进行模拟。提出了一种同时考虑径流、雪深和积雪覆盖面积的多目标优化方法对水文模型的参数进行率定,并同仅考虑径流和雪深的率定结果进行了对比。结果表明,率定时仅考虑径流和雪深时,HBV模型能较好地模拟研究区的径流过程,但对雪深变化过程的模拟效果欠佳;率定时增加积雪覆盖面积目标函数后,模型能精确判断流域积雪覆盖情况,径流的模拟效率系数也有所提升,表明同时基于径流、积雪覆盖面积和雪深数据的HBV水文模型可以更好地预测和模拟研究区积雪和径流变化。

关键词: 水文模型, 径流模拟, 积雪模拟, 多目标率定

Abstract: This study applies the Hydrologiska Byr?ns Vattenbalansavdelning (HBV) model to simulations of snow and runoff processes in the upper Yalung Zangbu River over its basin above the Nuxia gauging station. We develop a multi-objective optimization method considering river runoff, snow depth, and snow coverage to calibrate the model’s parameters; and compare the simulation results with those considering only river runoff and snow depth. The results show that the HBV model based on measurements of runoff and snow depth simulates the runoff quite well, but its simulations of snow depth are poor. Adding snow coverage to the model calibration can improve the simulation accuracy of snow coverage significantly, and also improves efficiency coefficient of river runoff. Thus, changes in snow and runoff in the study area can be better predicted by this HBV model that is calibrated against the measurements of river runoff, snow coverage, and snow depth.

Key words: hydrological model, runoff simulation, snow simulation, multi-objective calibration

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