Accurate streamflow and discharge/inflow data are critical to water resources professionals, as hydrologists, engineers, and hydropower managers rely on these data for their analyses and decision making. However, streamflow and discharge/inflow data are generally measured indirectly and are subject to multiple types of errors, which can have significant impacts on engineering decisions and consequently, public safety.
Robust data screening techniques are required to identify and correct streamflow errors. Although there are many methods that can be used to screen these data, individual users are left to choose which methods should be used. Furthermore, the scientific literature has provided little guidance to users performing data screening.
This project addresses this shortfall by creating a reference guide for data screening methods. The main objectives of this project are to review/describe/classify data screening methods, identify easily applicable and robust techniques, develop a reference guide to assist users in the selection of data screening methods, and identify emerging techniques for discharge/inflow data screening. The project consists of a literature review, an interview process, and a conceptual evaluation of the methods that were found in the literature review and interview process.
Keywords: Data screening, Discharge, Inflow, Streamflow, Error, Correction, Literature Review, Interview