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分层型水库取水水温量纲分析及其影响因素研究
引用本文:郑铁刚,刘之平,孙双科,柳海涛,牛志攀,李广宁.分层型水库取水水温量纲分析及其影响因素研究[J].水利学报,2017,48(9):1030-1038.
作者姓名:郑铁刚  刘之平  孙双科  柳海涛  牛志攀  李广宁
作者单位:中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038,中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038,中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038,中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038,四川大学 水力学与山区河流开发保护国家重点实验室, 四川 成都 610065;中国三峡建设管理有限公司, 四川 成都 610023,中国水利水电科学研究院 流域水循环模拟与调控国家重点实验室, 北京 100038
基金项目:国家重点研发计划(2016YFC0401708);国家自然科学基金项目(51409181)
摘    要:水温分层作为影响库区水生生态系统的重要因素逐渐成为研究热点。影响下泄水温的主要因素包括:坝前水温梯度、取水水头、取水流量、取水口宽度、温跃层厚度、重力加速度等。通过量纲分析法,基于π定理尝试建立了溢流式分层取水下泄水温估算模型。采用SAS 9.3统计软件对实验数据进行了回归分析,提出了下泄水温估算方程,相关系数达到95.6%。研究结果表明,水温梯度项为下泄水温估算的最主要因素,其次为取水水头项,最后为流量项;随着坝前水温温跃层强度增大,下泄水温升高,且强度越大,对下泄水温的影响越显著;下泄水温随取水水头的增加而降低,下泄水温降低幅度明显小于取水水头变幅;当取水流量逐渐增大时,下泄水温逐渐升高,但取水流量大于临界值时,下泄水温转而表现出缓慢下降趋势;在本文研究范围内,估算方程可以用于较好地预测下泄水温,预测结果与实验数据的相关系数为99.4%。

关 键 词:水温分层  下泄水温  影响因素  估算模型  量纲分析法
收稿时间:2017/4/21 0:00:00

Dimensional analysis of water temperature withdrawn and influencing factors in thermal stratified reservoir
ZHENG Tiegang,LIU Zhiping,SUN Shuangke,LIU Haitao,NIU Zhipan and LI Guangning.Dimensional analysis of water temperature withdrawn and influencing factors in thermal stratified reservoir[J].Journal of Hydraulic Engineering,2017,48(9):1030-1038.
Authors:ZHENG Tiegang  LIU Zhiping  SUN Shuangke  LIU Haitao  NIU Zhipan and LI Guangning
Affiliation:Sate Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 10038, China,Sate Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 10038, China,Sate Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 10038, China,Sate Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 10038, China,Sate Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China;China Three Gorges Projects Development Co., Ltd., Chengdu 610023, China and Sate Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 10038, China
Abstract:Thermal stratification, as an important factor affecting the aquatic ecosystem, has becomes re-search hot topic gradually. Based on the analysis of some influencing factors,such as water temperature gra-dient, intake head and intake flow, an estimate model of water temperature withdrawn has been developed by using dimensional analysis. Besides of that, multiple regression analysis is performed by using SAS9.3, the quantitative relation between water temperature withdrawn and key factors is given, and show a good correlation with the measured data with a correlation coefficients of 0.956. The results show that water tem-perature gradient is the major factor affecting water temperature withdrawn, next is the intake head term, and the last is flow term. The water temperature will increase with the gradient in front of the dam increas-ing. The analyses also show that the bigger the temperature gradient,the more obviously the water tempera-ture withdrawn varied. It is also indicated that the water temperature will decrease with the intake head in-creasing,and the decrease is much smaller than the increase. Besides of that,with the intake flow increas-ing, the water temperature withdrawn becomes higher. However, while the intake flow is greater than criti-cal value, the water temperature shows a downward trend. A comparison between the predicted and the measured water temperature withdrawn is in close agreement with a correlation coefficient of 99.4%. The re-sults show that the model may be used to determine water temperature withdrawn with an acceptable accura-cy if the variables are within the following ranges.
Keywords:thermal stratification  water temperature withdrawn  influencing factor  estimate model  dimen-sional analysis method
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