灰色拓扑模型在海州湾人工鱼礁区水质预测的应用

Application of grey topological prediction model in water quality prediction of artificial reef area in Haizhou Bay

  • 摘要: 该研究分别采用残差修正的 GM (1,1) 模型和灰色拓扑预测方法对2007—2017年春 (5月)、秋 (10月) 海州湾人工鱼礁区的溶解氧 (DO)、化学需氧量 (COD)、生化需氧量 (BOD5) 及溶解无机氮 (DIN) 4个指标的监测数据建立水质预测模型并选择精度较高的模型预测2018—2022年的水质变化趋势,最终利用2018年的调查数据对预测结果进行检验。结果表明,灰色拓扑模型相较于残差修正的GM (1,1) 模型针对水质数据具有更好的预测精度,预测结果与2018年的调查结果较吻合,可信度较高;预测结果显示,DO和COD在2018—2022年能够保持良好的水质状态,可见人工鱼礁建设对海域水环境状况具有一定的修复作用,但BOD5和DIN存在一定的超标风险;针对灰色拓扑模型的改进仍具有很大的研究空间,有待进一步挖掘。

     

    Abstract: In this study, we applied residual modified GM (1,1) model and grey topological prediction method to establish water quality prediction models based on the monitoring data of dissolved oxygen (DO), chemical oxygen demand (COD), biochemical oxygen demand (BOD5) and dissolved inorganic nitrogen (DIN) of the artificial reef area in Haizhou Bay in spring (May) and autumn (October) of 2007−2017. Then we selected the model with higher accuracy to predict the variation trend of water concentration during 2018−2022. Finally, we verified the forecast results with the meaured data of 2018. The results indicate that the grey topological model has better prediction accuracy for water quality data than the residual correction GM (1,1). The predicted results are consistent with the actual values in 2018, so the model is reliable. According to the prediction results, the DO and COD can maintain good values in 2018−2022. It is shown that the construction of artificial reef has a certain restoration effect on the water environment of the sea area, but BOD5 and DIN have a risk of exceeding the standard; and  improvement of grey topology model should be further explored.

     

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