| 基于水文模型与机器学习集合模拟的水沙变异归因定量识别——以黄河中游窟野河流域为例 |
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| 引用本文： | 鲍振鑫,张建云,王国庆,贺瑞敏,金君良,王婕,吴厚发.基于水文模型与机器学习集合模拟的水沙变异归因定量识别——以黄河中游窟野河流域为例[J].水科学进展,2021,32(4):485-496. |
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| 作者姓名： | 鲍振鑫 张建云 王国庆 贺瑞敏 金君良 王婕 吴厚发 |
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| 作者单位： | 1.南京水利科学研究院水文水资源与水利工程科学国家重点实验室, 江苏 南京 210029 |
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| 基金项目： | 国家重点研发计划资助项目2017YFA0605002国家自然科学基金资助项目41961124007 |
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| 摘 要： | 黄河水沙变化是当前流域水文与江河治理领域研究的前沿和热点问题。以黄土高原窟野河流域为典型研究对象，利用VIC水文模型和8种基于机器学习算法的输沙量模型，耦合构建流域水沙集合模拟技术，定量识别流域水沙演变特征与变异成因。结果表明:① 1960—2014年窟野河流域年气温和降水分别呈显著增加和不显著减少趋势，径流和输沙量都呈显著减少趋势，1980和1999年是流域产水产沙特性发生改变的重要转折点；②模拟月径流和输沙量的Nash-Sutcliffe效率系数和相关系数分别超过了0.6和0.7，适用于该流域水沙过程模拟；③与天然期1960—1979年相比，1980—2014年气候变化和人类活动对径流减少的贡献分别为24%~39%和61%~76%，对输沙量减少的贡献分别为15%~36%和64%~85%；④人类活动是窟野河流域水沙减少的主要原因，且随时间推移呈增大趋势。相关成果为流域水沙变异归因定量识别提供了新的技术方法，对促进黄河流域水资源开发利用和水沙治理具有重要的支撑作用。
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| 关 键 词： | 径流 泥沙 水文模型 机器学习 黄河流域 |
| 收稿时间： | 2020-09-14 |
Quantitative assessment of the attribution of runoff and sediment changes based on hydrologic model and machine learning: a case study of the Kuye River in the Middle Yellow River basin |
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| Affiliation: | 1.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China2.Research Center for Climate Change of MWR, Nanjing 210029, China |
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| Abstract: | The changes in runoff and sediment in the Yellow River is a hot issue in the field of hydrology and river management. The Kuye River located in the Loess Plateau was selected as a typical basin. Based on the observed hydro-meteorological data during 1960-2014, there was a statistically significant increasing trend in annual mean temperature, an insignificant decreasing trend in annual precipitation, and significant decreasing trends in annual runoff and sediment. 1980 and 1999 were two breakpoints of the relationships among runoff, sediment and climatic factors. The ensemble modelling framework of runoff and sediment was constructed by the VIC model and eight sediment models based on machine learning algorithm. The Nash-Sutcliffe efficiency coefficient and correlation coefficient for monthly runoff and sediment simulation were higher than 0.6 and 0.7, respectively, that denoted acceptable performance. Based on the comparison between the reconstructed natural runoff and sediment versus observed values, the attribution of runoff and sediment changes were quantitatively analyzed. The results indicated that the contributions of climate change and human activities to runoff reduction in 1980-2014 were 24%-39% and 61%-76% respectively, and the contributions to sediment reduction were 15%-36% and 64-85%, respectively, compared with that in the natural period from 1960 to 1979. Human activities are the main reason for the decreases in runoff and sediment in the Kuye River basin. The related results could not only improve an innovative methodology to understand the attribution of runoff and sediment changes, but also play an important supporting for the utilization of water resources and conservation of runoff and sediment in the Yellow River basin. |
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