Design and implement of hydrological data quality assessment system based on rules

Hydrological organizations take lots of time and energy on data quality assessment but with low efficiency. Poor quality data affects the performance of making decisions and even results in disasters in hydrological decision support system which plays a paramount role in flood controlling and drought resisting. It is a monotonous and exhausting task to achieve a reasonable, efficient, and objective quality assessment for hydrological volume data embraced with kinds of implicit and explicit domain defects or anomalies. This paper presents an overview of prioritized data quality dimensions in hydrology via the questionnaire, demonstrates a flexible and lightweight system framework for quality assessment, and employs a method to assess the data quality and cope with the defects or anomalies in hydrological database based on business rules. In our experiments, we choose some main quality dimensions (their default weight values are derived from the questionnaire, and also can be allocated by hydrologists), and get fused values based on the assessment model. Findings of exploratory laboratory experiments show that the assessment system can provide quality indicators to stakeholders to understand the data quality, and the assessment process demonstrates this quality assessment methodology is flexible and efficient.