基于灰色马尔可夫模型的区域地下水位动态预报

Dynamic forecast of regional groundwater level based on grey Markov chain model

摘要: 区域地下水位的变化受多种因素的影响，并且呈现高度的非线性特点。针对区域地下水位变化的随机波动性、高度非线性特征，把区域地下水位的变化变化过程视为随机变化过程，将灰色系统理论与离散状态的马尔可夫链相结合，并在状态划分过程中，采用均值–标准差分级法进行指标分级与状态划分，提出了区域地下水位变化过程预报的灰色马尔可夫动态预报模型。在实例分析中，把某灌区 14 a 的地下水位的变化资料划分成 5 种状态。预测分析结果表明，利用灰色马尔可夫动态预报模型进行区域地下水位的变化动态预报是可行的。

Abstract: The regional groundwater level is affected by several factors and highly nonlinear. Aiming at unstable change and highly nonlinear characteristics of the regional groundwater level, the grey Markov chain model is presented by means of combining the grey system theory with the dispersed Markov chain theory. The mean and standard deviations of information series are taken as the classification standard of precipitation states. The variance of the regional groundwater level for the past 14 years in the irrigating areas is classified into five classes according to the precipitation data. The predication results show that the model is feasible.