Analysis of interaction between lake water and groundwater in beach of Maowusu Lake Basin
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摘要: 湖水与地下水交互作用对于水资源合理开发与利用有着重要意义。基于温度示踪的原理，采用解析法、数值法2种方法，分析了湖床底部埋深0~0.4 m湖水与浅层地下水交互关系，并与水动力学方法进行了对比。结果表明，2018年5月20日至28日，湖水与地下水之间的垂向渗流速度为2×10-7~1×10-6 m/s，且在埋深0.4 m时大于埋深0.2 m处。降水会对解析法的结果造成一定影响，0.4 m处受到降雨影响表现为一定的滞后性。无降雨干扰情况下，数值法与水动力学方法估算结果较为吻合，且3种方法的计算结果处于同一数量级。同时，湖床沉积物体积热容和孔隙度2种参数对计算结果影响较大。在半干旱地区湖水与地下水交互研究中，数据较完备时，数值模拟法是更好的选择。
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关键词:
- 湖水与地下水交互作用 /
- 温度示踪法 /
- VFLUX2 /
- VS2DH /
- 毛乌素湖盆滩地
Abstract: The interaction between lake water and groundwater is of great significance to the rational development and utilization of water resources. In this paper, based on temperature tracer principle, two methods including of the analytical method and numerical simulation method are used to comprehensively study the interaction between lake water and groundwater with a buried depth of 0-0.4 meters at the lake bed in the beach of Maowusu Lake Basin. In addition, compared with the result by hydrodynamic method. The results show that from May 20 to 28, 2018, the vertical seepage velocity between lake water and groundwater is 2×10-7-1×10-6 m/s, and the seepage velocity at the buried depth is 0.4 m is greater than that at the buried depth of 0.2 m. Precipitation have a certain impact on the results of analytic method, and there is a certain lag in the seepage velocity at the buried depth of 0.4 m. Without less rainfall interference, the results of numerical method and hydrodynamic method are of good agreement, furthermore the results of the three methods are in the same order of magnitude. At the same time, the volume heat capacity and porosity of lake bed sediments have great influence on the results. In the study of interaction between lake water and groundwater in semi-arid areas, numerical simulation is much better choice when the monitoring data are collected completely. -
图 1 湖床温度监测剖面示意图
Figure 1. Schematic diagram of temperature monitoring section of the lake bed
图 3 识别期不同深度模拟温度与实测温度对比
Figure 3. Comparison of simulated temperature and measured temperature at different depths in identification period
图 6 不同湖床深度垂向渗流速度变化
Figure 6. Variation of vertical seepage velocity at different lake bed depths
图 7 数值法(VS2DH)不同月份垂向渗流速度
Figure 7. Vertical seepage velocity in different months by VS2DH numerical method
图 9 湖床深度0.2 m处参数敏感性分析
Figure 9. Sensitivity analysis of 0.2 m lake bed depth parameters
图 10 湖床深度0.4 m处参数敏感性分析
Figure 10. Sensitivity analysis of 0.4 m lake bed depth parameters
图 11 湖床深度0.2 m处参数敏感性分析
Figure 11. Sensitivity analysis of 0.2 m lake bed depth parameters
图 12 湖床深度0.4 m处参数敏感性分析
Figure 12. Sensitivity analysis of 0.4 m lake bed depth parameter
图 13 数值法、解析法与水动力学法垂向渗流速度计算对比
Figure 13. Comparison of numerical method, analytical method and hydrodynamic vertical seepage velocity calculation
表 1 模型识别期的水力学参数
Table 1. Hydraulic parameters model of identification period
参数名 KZZ/ Khh Khh/ (m·s-1) 给水度 孔隙度/% 残余含水率 α/(1· m-1) n 粉砂 1 6.55×10-7 0.1 0.39 0.029 0.057 1.553 细砂 1 5.78×10-6 0.15 0.38 0.029 0.04 8.61 注：Khh为垂向渗透系数；α与进气值有关；n为曲线形状参数 
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表 2 模型识别的热力学参数
Table 2. Thermodynamic parameters of model identification period
参数名 α1 αt Cs/(J·m-3) λmr/(W·m-1·℃-1) λms/(W·m-1·℃-1) Cw/(J·m-3) 粉砂 0.095 0.009 5 2 500 000 0.38 2 4 200 000 细砂 0.095 0.009 5 1 800 000 0.4 1.5 4 200 000 注：λmr为残余含水率下的热通量；λms是饱和含水率下的热通量；Cs为沉积物体积热容；Cw为水体积热容
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表 3 识别期不同深度温度模拟值与实测值误差分析
Table 3. Error snalysis of simulated and measured temperature at different depths in identification period
指标 深度/m 0.15 0.35 0.65 0.85 RE 0.015 5 0.029 9 0.065 9 0.050 8 RMSE/℃ 1.352 8 1.044 9 1.262 9 0.905 1 RE.相对误差；RMSE.均方根误差，下同
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表 4 验证期不同深度温度模拟值与实测值误差分析
Table 4. Error analysis of simulated and measured temperature at different depths in verification period
指标 深度/m 0.15 0.25 0.65 0.85 RE 0.054 6 0.049 1 0.020 1 0.022 2 RMSE/℃ 1.799 3 1.686 2 1.338 5 1.075 6
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