改进加权马尔科夫链模型在喀什地区承压含水层参数动态识别中的应用研究

承压含水层的估算对于地下水开发利用的合理规划十分重要。而承压含水层参数识别对于含水层水量参数估算至关重要。结合改进加权马尔科夫链模型,以喀什为研究实例,对该地区承压含水层参数进行动态识别,从置信区间分析结果可看出,喀什地区承压含水层参数的变幅为7.93 m^2/min,而承压含水层参数μ的变幅为0.048,从不同置信度下的变幅结果可看出,相比于传统模型,改进加权马尔科夫链模型提高了参数识别收敛效率和计算精度。计算结果的可靠性程度较高。研究成果对于喀什地区含水层水量估算具有重要的参考价值。

Application of Improved Weighted Markov Chain Model to Dynamic Identification of Confined Aquifer Parameters in Kashi Region

The estimation of confined aquifers is important for the rational planning of groundwater development and utilization. The identification of confined aquifer parameters is essential for the estimation of aquifer water parameters. Combined with the improved weighted Markov chain model and Kashgar as an example, the parameters of confined aquifers in this area are dynamically identified. From the results of confidence interval analysis, it can be seen that the variation of confined aquifer parameters in Kashgar is 7.93 m^2/min, and the variation of the confined aquifer parameter μ is 0.048. It can be seen from the variation results under different confidence that the improved weighted Markov chain model improves the parameter identification convergence efficiency and calculation accuracy compared with the traditional model. The reliability of the calculation results is high. The research results have important reference value for the estimation of aquifer water quantity in Kashgar.