摘要
由于近年来气候变化和人类活动的双重影响,导致黄河水沙锐减,对未来变化趋势作出可靠判断十分必要。利用基于多种机器学习特征筛选的统计模型方法,采用潼关站实测径流量与输沙量、欧洲中期天气预报中心中尺度数据及不同气候变化路径的CO_(2)排放浓度下全球气候模式数据对未来水沙作了预测。结果表明,在rcp26情景下,潼关站未来10年、20年、50年的断面径流量为234.21亿m^(3)、227.52亿m^(3)、219.6亿m^(3),与2000—2016年平均径流量228.86亿m^(3)相比,径流量增加了约2.3%、-0.5%、4.0%;同期的断面输沙量预测结果为2.68亿t、3.44亿t、5.72亿t,与2000—2016年平均输沙量2.48亿t相比增加了约7.9%、38.4%、130.2%,表明黄河流域"水少沙多"的形势依然是未来较长一个时期的主要特征。
Due to the double impacts of climate changes and human activities in recent years,runoff and sediment transport in the Yellow have been reduced sharply,so it is necessary to make a reliable judgment on the future trends of these changes.Based on the method of feature selection and multiple regression analysis,this paper predicts the future runoff and sediment conditions of the river,using the sediment transport and runoff data measured at the Tongguan station,the mesoscale data from the European medium-range weather forecast center,and the global climate model data of CO_(2) emission concentrations along different climate change paths.The results show that under the scenario RCP26 in the next 10,20 and 50 years,the runoff at the Tongguan station will be 2.34×10^(10) m^(3),2.28×10^(10) m^(3) and 2.2×10^(10) m^(3) respectively,increased by 2.3%,-0.5%and-4.0%in comparison with the average of 2.29×10^(10) m^(3) over 2000-2016;the sediment discharge will be 2.68×10^(8) t,3.44×10^(8) t and 5.72×10^(8) t,increased by 7.9%,38.4%and 130.2%respectively against the 2000-2016 average of 2.48×10^(8) t.This indicates the less water and more sand feature of the Yellow basin will remain in place for quite a long period in the future.
作者
李雅娟
张宇
田颖琳
张青青
钟德钰
LI Yajuan;ZHANG Yu;TIAN Yinglin;ZHANG Qinqing;ZHONG Deyu(College of Water Resources and Hydropower,Qinghai University,Xining 810016;State Key Laboratory of Hydroscience and Engineering,Tsinghua University,Beijing 100084;State Key Laboratory of Plateau Ecology and Agriculture,Qinghai University,Xining 810016)
出处
《水力发电学报》
EI
CSCD
北大核心
2021年第5期99-109,共11页
Journal of Hydroelectric Engineering
基金
国家重点研发计划(2017YFC0404303)。
关键词
黄河
水沙预测
多元回归分析
数据驱动
Yellow River
runoff and sediment prediction
multiple regression analysis
data-driven
