摘要

Influenced by combined effects of climate change and human activities, groundwater system shows varieties of uncertain properties, such as stochastic, fuzzy, gray, unascertained and chaotic characteristics. Based on shortages of distributed parameter model and lumped parameter model in groundwater level prediction, considering current researches of time series application with set pair analysis, groundwater level prediction model was established with set pair analysis based on rules of maximum similarity forecast (SPA-MSF). On the basis of theory of similarity forecast, maximum connection degree is used to measure the similarities among historical samples of groundwater level quantitatively with time series consistency analysis. Steps of modeling and solving a five-element connection degree model for groundwater level prediction was applied in monthly and inter-annual depth forecast at Shandanqiao observation well, Zhangye Heihe River basin. The results indicated that goodness of fit and trend between predictive value and measured value were optimal. Besides, the SPA-MSF model was proved to be of high prediction accuracy and better generalization with posterior variance test.

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