取用水监测点的水量计算与变化趋势分析

加强取用水监测是实施最严格水资源管理制度的重要举措.为了更有效地利用大量的取用水在线监测数据,需要对获取的监测数据进行预处理.本文首先提出应用中位数法与曲线拟合相结合的方法对取用水监测数据进行异常值检测,再用曲线拟合方法对异常值进行校正;其次,根据校正后得到的数据进行两个方面的分析,一方面是计算监测点的年取水量,另一方面是应用集成经验模态分解方法分析监测点的日取水量变化趋势;最后,以M市的16个自来水厂2016年取用水在线监测数据为例进行实证分析,结果表明,本文提出的中位数法与曲线拟合相结合的方法能够有效地检测异常值,进而再用曲线拟合方法能够更好地对异常值校正.根据校正后得到的数据进行分析发现81%的监测点年取水量相对2011年水利普查数据有所增加,个别监测点超出许可取水量较多,75%的监测点从春季到冬季日取水量变化为先增后减的抛物线趋势.

Calculation of water quantity and analysis of variation trend of the water intake monitoring point

It was an important measure for the strictest water resources management system to strengthen the monitoring of water intake. In order to make more effective use of a large number of online monitoring data of water intake, we need to pre-process the raw data. In this paper, first of all, the outliers of the water intake monitoring data were detected by the method of combining median and curve fitting, and the curve fitting method was used to correct the outliers. And then, two aspects analysis of the data which obtained by correction were analyzed, on the one hand the annual water intake quantity of monitoring points were calculated, while on the other the variation trend of daily water intake quantity of monitoring points were analyzed by the ensemble empirical mode decomposition (EEMD). At last, taking the online monitoring data of water intake of 16 water supply companies of M city in 2016 as an example, the results show that the method of combining median and curve fitting proposed in this paper can effectively detect the outliers, furthermore, the curve fitting method can better be used to correct the outliers. According to the data which obtained by correction, we found that 81% of the annual water intake quantity of monitoring points are increased compared with the data of China census for water in 2011, individual monitoring points exceed the permitted water quantity of the water abstraction licence more, 75% of daily water intake quantity of the monitoring points follows a parabolic curve first ascended and then descended from spring to winter.