综合权重的可变模糊识别模型在水质动态评价中的应用

Application of variable fuzzy pattern recognition model with synthetic weight in the assessment of water quality dynamics

水质评价不仅要描述水体状态,还需要体现水体水质的变化过程。针对水质评价的模糊性、不确定性、时序性的特点,将可变模糊识别模型应用于水质动态评价,其中权重采用层次分析法和熵权法耦合确定,使其融合了原始水质数据信息与科研人员对科学问题的认识。在运用蒙特卡罗法分析指标不确定性对水质评价结果影响的基础上,运用所建模型进行逐月水质动态评价。以碧流河水库为例进行水质评价的结果表明,其水质在Ⅱ到Ⅲ类之间,各月间无显著变化;8月、9月的水质稍差,主要污染指标是总氮。

Water quality evaluation includes the description of water state and variation process of water quality.Due to the characteristics of water quality,such as fuzziness,uncertainty,and randomness,the variable pattern recognition model was applied to evaluate water quality dynamics.The weight was determined using the coupling analytic hierarchy process and entropy method,so the original water quality data and scientific research can be combined together.The Monte Carlo method was used to analyze the effects of index uncertainty on water quality evaluation,and the model was used to conduct monthly evaluation of water quality dynamics in the Biliu reservoir.The results showed that water quality in the Biliu reservoir is between level II and III,there are no significant changes between each month but water quality in August and September are worse,and the main pollution index is total nitrogen.