南宁市2018年取用水监测数据质量评价
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摘要
国家水资源监控能力建设项目取用水监控体系建设是落实最严格水资源管理信息化的关键。基于南宁市取用水监控体系2018年全年监测和2017年水资源公报年报等数据,采用对比分析和数据异常识别模型的方法,对不同行政区、行业,以及典型取水户的监测数据进行质量评价,并给出初步的数据修正思路。研究表明,不同行政区、时段、行业之间的数据质量各异,特别是不同行业之间的数据质量差异明显,灌区农业用水监测数据质量问题尤其突出。南宁市目前实际取水许可水量监控比例为85.23%,总用水量监控比例约为48.20%,南宁市取用水监控系统基本可为取水许可管理、用水量统计、水资源费核算等业务提供一定参考。
The construction of water monitoring system of National Water Resources Monitoring Capacity-Building Project is the key to implement the most stringent information-based water resources management. Based on the monitoring data of Nanning City in 2018, and annual report data of 2017 water resources bulletin, this paper evaluates the quality of monitoring data of different administrative regions, different industries and typical water intake users by using the method of comparative analysis and data anomaly recognition model, and gives a preliminary idea of data revision. The results show that the data quality of different administrative regions, different time periods and different industries is different. Especially, the data quality of different industries is obviously different. The quality problem of agricultural water monitoring data in irrigation area is particularly prominent. At present, the proportion of actual water intake permission monitoring in Nanning is 85.22%, and the proportion of total water consumption monitoring is about 48.19%. The water intake monitoring system in Nanning can basically provide some reference for business such as water intake permission management, water consumption statistics, water resources fee accounting and so on.
The construction of water monitoring system of National Water Resources Monitoring Capacity-Building Project is the key to implement the most stringent information-based water resources management. Based on the monitoring data of Nanning City in 2018, and annual report data of 2017 water resources bulletin, this paper evaluates the quality of monitoring data of different administrative regions, different industries and typical water intake users by using the method of comparative analysis and data anomaly recognition model, and gives a preliminary idea of data revision. The results show that the data quality of different administrative regions, different time periods and different industries is different. Especially, the data quality of different industries is obviously different. The quality problem of agricultural water monitoring data in irrigation area is particularly prominent. At present, the proportion of actual water intake permission monitoring in Nanning is 85.22%, and the proportion of total water consumption monitoring is about 48.19%. The water intake monitoring system in Nanning can basically provide some reference for business such as water intake permission management, water consumption statistics, water resources fee accounting and so on.
引文
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[2]蔡阳.国家水资源监控能力建设项目及其进展[J].水利信息化,2013(6):5-10.
[3]蒋云钟,万毅.水资源监控能力建设功能需求及实施策略[J].中国水利,2012(7):26-30.
[4]国务院.关于实行最严格水资源管理制度的意见[EB/OL].(2012-02-16)[2018-12-11].http://www.gov.cn/zwgk/2012-02/16/content_2067664.htm.
[5]于文静.《实行最严格水资源管理制度考核办法》解读[J].河南水利与南水北调,2013(6):33-33.
[6]李越.关于水资源监测数据的质量控制几点思考[J].监测与分析,2018(10):163-171.
[7]何南,谷军,吴晓雪,等.运用QC理论提高入库资源数据质量[J].大众科技,2015(6):15-16.
[8]方海泉,薛惠锋,万毅.关于国控监测点的取用水量预测仿真研究[J].计算机仿真,2016,33(10):437-440.
[9]张峰,薛惠锋,WANG Wei,等.水资源监测异常数据模态分解-支持向量机重构方法[J].农业机械学报,2017,48(11):316-323.
[10]熊明,梅军亚,杜耀东,等.水资源监测数据的质量控制[J].人民长江,2018,49(9):41-46.
[11]南宁市水利局.2017年南宁市水资源公报[M].南宁:南宁市水利局,2018:14-18.
[12]广西壮族自治区水利厅.2017年广西壮族自治区水资源公报[M].南宁:广西壮族自治区水利厅,2018:18-21.
[13]龙秋波,贾绍凤,汪党献.中国用水数据统计差异分析[J].资源科学,2016,38(2):248-254.