喀斯特流域枯季径流衰减系数与地表形态特征相关分析研究

薛显武; 陈 喜; 秦年秀; 赵旭升; 石 朋

doi:10.3969/j.issn.1001-4810.2011.01.007

喀斯特流域枯季径流衰减系数与地表形态特征相关分析研究

doi: 10.3969/j.issn.1001-4810.2011.01.007

1.
河海大学水文水资源与水利工程科学国家重点实验室；School of Civil Engineering and Environmental Sciences, University of Oklahoma, National Weather Center Suite 3630, Norman
2.
河海大学水文水资源与水利工程科学国家重点实验室
3.
珠江水利科学研究院

基金项目: 国家自然科学基金重点项目(40930635)、教育部科学技术研究重大项目(308012)、国家自然科技基金项目(50679025)及青年基金(41001011)资助

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出版历程
- 收稿日期: 2010-08-23
- 发布日期: 2011-03-25

Correlation analysis between low-flow recession coefficient and surface landform characteristics in karst basin

1.
State Key Lab of Hydrology-Water Resources and Hydraulic Engineering, Hohai University；School of Civil Engineering and Environ mental Sciences, University of Oklahoma, National Weather Center Suite 3600
2.
State Key Lab of Hydrology-Water Resources and Hydraulic Engineering, Hohai University
3.
Scientific Research Institute of Pearl River

摘要

摘要: 针对喀斯特流域地形、地貌对枯季径流的调蓄作用,选用乌江流域思南站以上19个水文站点枯季流量资料进行枯季径流衰减规律分析。根据枯季径流衰减曲线的拟合将枯季径流分为快速裂隙流和慢速裂隙流两段退水过程,并计算相应的衰减系数。通过对衰减系数与流域地表形态特征的单因素和多因素回归分析,确定影响衰减系数的主要影响因子为高程特征值和地形指数特征值,并建立两者与衰减系数的二元非线性回归方程(a1=0.781-0.266?ln(x)+0.633?ln(y),a2=0.061-0.016?ln(x)+0.044?ln(y)),其置信区间都大于99%,说明曲线整体拟合显著,为枯期径流衰减系数区域化分析及无/缺资料流域的水文模拟提供基础。
- 喀斯特流域 /
- 枯季径流 /
- 衰减系数
Abstract: In light of the storage and adjustment for runoff by topography and landform features in dry season, daily observed flow data during dry seasons from19 hydrology stations located up the Sinan station of the Wujiang River are analyzed to find out base flow recession law. According to the characteristics of low flow recession curve, the base flow is divided into two parts, fast fissure flow and slow fissure flow, and the corresponding recession coefficient is calculated. Based on the single factor and multi-factor regression analysis between the recession coefficient and the basin's landform features, elevation eigenvalue and topographic index eigenvalue are determined as the main factors affecting the recession coefficient. The dual non-linear regression equations are established with these two eigenvalues and the recession coefficient(a1=0.781-0.266?ln(x)+0.633?ln(y)and a2=0.061-0.016?ln(x)+0.044?ln(y)),their confidence intervals are greater than99%,so these two curves fit significantly and these equations can be used to regionalize the recession coefficients and to provide the basis for hydrological simulation in ungauged basins.
- karst basin /
- low-flow /
- recession coefficient

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