基于趋势及回归分析的珠三角城市群需水预测

发布时间：2019-05-10 03:30

【摘要】：对近10年珠三角城市群用水量进行了特征及结构分析,其中分析了总用水量和农业、工业、城镇公共、居民生活及生态环境用水量等与地区生产总值、年末人口数等参数的相关性,结果表明:与一般用水量随着经济与人口增长而增长的结论不同,近年来,珠三角地区城市总用水量与地区生产总值表现较强的负相关性,与年末人口数也呈一定程度负相关。基于相关性分析成果,构建基于经济、人口为自变量的二元回归模型及趋势模型,对城市群水资源需求进行了预测,并与常用的分项水量预测法进行对比,结果表明:趋势模型和二元回归模型预测精度良好,与实际值偏差在2%以内;趋势模型预测结果与实际值最为接近,二元回归模型预测结果偏小,而常用的分项水量预测法结果偏安全。相比分项水量预测法,趋势及二元回归预测方法具有较高精度和便利操作性,可供类似城市群需水预测研究参考。
[Abstract]:The characteristics and structure of water consumption in Pearl River Delta urban agglomeration in recent 10 years are analyzed, in which the total water consumption, agriculture, industry, urban public water consumption, residents' living and ecological environment water consumption and regional gross domestic product are analyzed. The correlation of population and other parameters at the end of the year shows that, different from the conclusion that the general water consumption increases with the economic and population growth, in recent years, the total urban water consumption in the Pearl River Delta region has shown a strong negative correlation with the regional gross domestic product (GDP). It is also negatively correlated with the population at the end of the year. Based on the results of correlation analysis, the binary regression model and trend model based on economy and population as independent variables are constructed, and the water resources demand of urban agglomeration is predicted and compared with the commonly used partial water quantity forecasting method. The results show that the prediction accuracy of the trend model and the binary regression model is good, and the deviation from the actual value is less than 2%. The prediction results of the trend model are the closest to the actual values, the prediction results of the binary regression model are small, and the results of the commonly used partial water quantity prediction method are safe. Compared with itemized water forecasting method, trend and binary regression forecasting method has high precision and convenient operation, which can be used as a reference for water demand prediction of similar urban agglomeration.
【作者单位】：广东省水利水电科学研究院;广东省水动力学应用研究重点实验室;河口水利技术国家地方联合工程实验室;
【基金】：广东省水利科技创新项目重点课题(2014-06) 广东省自然科学基金项目(2015A030313695)
【分类号】：TV213.4

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