| 基于相关指标的裂隙岩体渗透系数估算模型研究 |
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| 引用本文： | 王玮,钱家忠,马雷,王德健,马海春,赵卫东.基于相关指标的裂隙岩体渗透系数估算模型研究[J].水文地质工程地质,2021,48(3):82-89. |
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| 作者姓名： | 王玮 钱家忠 马雷 王德健 马海春 赵卫东 |
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| 作者单位： | 合肥工业大学资源与环境工程学院，安徽 合肥 230009 |
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| 基金项目： | 国家自然科学基金项目（41831289；41772250；41972278） |
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| 摘 要： | 掌握岩体的渗透性是精细化描述一个地区水文地质特征的重要工作。渗透系数是表征岩体渗透性的重要指标，研究渗透系数估算模型对于实际工程应用具有重要意义。在现有的渗透系数估算模型中，单因子模型忽略了其他因素对该地区渗透系数的综合影响，复合因子模型存在参数选取不够灵活、部分参数较难获取等问题。基于公开数据，分类整理和对比分析了影响裂隙岩体渗透性的正、负相关参数，提出一种拟合效果好、参数选取灵活的渗透系数估算模型——PNC（Positive and Negative Correlation）模型。研究结果表明:在研究区一，PNC模型的拟合效果（可决系数R2=0.964和R2=0.801）优于HC模型的拟合效果（R2=0.905和R2=0.563）；在研究区二，PNC模型的拟合效果（R2=0.959）优于RMP模型的拟合效果（R2=0.927）；在研究区三，PNC模型的拟合效果（R2=0.94～0.99）优于ZRF模型的拟合效果（R2=0.92～0.99）。利用纳什效率系数（Nash-Sutcliffe Coefficient，NSE）进行模型误差分析，7组数据中有5组数据的误差系数在0.95以上。这说明PNC模型具有便利性和可靠性，可以为实际工程估算和验证渗透系数提供一定的参考。
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| 关 键 词： | 渗透系数 正、负相关指标 估算模型 裂隙岩体 |
| 收稿时间： | 2020-06-14 |
A model for estimating hydraulic conductivity of fractured rock mass based on correlation indexes |
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| Affiliation: | School of Resources and Environmental Engineering, Hefei University of Technology, Hefei, Anhui 230009, China |
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| Abstract: | Mastering hydraulic conductivity of rock mass is an important way to precisely describe hydrogeological characteristics of a certain region. Hydraulic conductivity is a significant indicator to reflect the rock mass’ permeability. The studies of hydraulic conductivity estimation models have important implications for the development of actual engineering. In the existing estimation models of hydraulic conductivity, the single-factor model cannot take into consideration of the comprehensive influence of various factors on hydraulic conductivity in the area, and the parameters selection of the multi-factor model lacks the flexibility and its application is limited when some parameters are difficult to be obtained, etc. The classification and comparative analyses of the positive and negative correlation parameters are conducted based on public data. We propose a set of high-fitting hydraulic conductivity estimation models, which are the PNC (Positive and negative correlation) model. The research results show that the fitting result of the PNC model (R2=0.964 and R2=0.801) is superior to that of the HC model (R2=0.905 and R2=0.563) in No. 1 study area. In No. 2 study area, the fitting result of the PNC model (R2=0.959) is superior to that of the RMP model (R2=0.927). In No. 3 study area, the fitting result of the PNC model (R2=0.94 to 0.99) is also better than that of the ZRF model (R2=0.92 to 0.99). By using Nash-Sutcliffe coefficient (NSE) to carry out the error analyses of the model, it is found that the error coefficients of 5 in 7 sets of data are above 0.95. It further illustrates the convenience and reliability of the PNC model, which can provide a certain reference for estimating and verifying hydraulic conductivity in actual engineering. |
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