中文摘要：

为了提高MODFLOW中模型计算的精确度,减少不收敛情况的发生,通过建立数值模型算例,分析了不同解算器对计算精度的影响差异、主要参数值的设定对计算精度产生的影响以及收敛指标与迭代次数的定量关系。结果表明,PCG、SAMG和GMG计算精度较高,WHS和SOR计算精度较低。PCG算法中,低收敛指标使得计算精度有所提高,但稳定性却明显降低;计算精度对PCG算法中的阻尼因子的敏感性比对SIP算法中的加速因子敏感性低,二者的减小均导致计算精度降低;SIP算法中,计算过程中的迭代次数、运行时间与水头变化的收敛指标值呈明显的反比关系。当收敛指标设定小于一定值时,迭代次数和收敛指标的对数值呈现明显的线性关系。

英文摘要：

To increase the accuracy in a practical modeling process and avoid the misconvergence in MODFLOW, this paper analyzes different accuracy caused by different solvers and the major parameters by building a numerical model example. The relationship between the convergence criterion and the iteration times is also evaluated quantitatively. The results show that PCG, SAMG and GMG have a higher accuracy, while WHS and SOR have a lower accuracy. The low head change criterion increases the calculation accuracy, while its stability decreases. The sensibility of calculation accuracy caused by the damping factors in PCG is lower than that caused by the accelerated variable in SIP. It is found that the head change criterion, the iteration times and the running time are significantly inversely proportional in SIP. After the convergence criterion is less than a certain value, the iteration times and the logarithm of convergence criterion show an obvious linear relationship.