Abstract
: In this study, the prediction interval method was used in simple regression models to filter continuous river surface velocity microwave radar data. To evaluate the model performance, two data sets from monitoring stations with mild and steep channel slopes were used. A human–machine interface software program developed in LabVIEW was used to sample data from big continuous data for establishing the relationships between surface velocity and water level, two surface velocities, and their prediction intervals. Filtering by coupled relationships detected the most noise in the surface velocity and the original data, and the results for different cases were compared. The results were also compared with widely used modern smoothing methods. It was found that raw data cannot always be post–processed using these smoothing methods. Moreover, peaks become distorted. This study provides a method for filtering noise signals in continuous river surface velocity data without data contamination, which makes the surface velocity data more reliable and applicable for advanced studies, such as machine learning applications, and can be applied for the quality control of surface velocity data in the future.
Highlights
Continuous streamflow can be used to calibrate and verify hydraulic routing models
water level (WL), such as those observed in the morning and night of August difference with WL, such as those observed in the morning and night of August 77 and and the the afternoon afternoon of of August
Qualityof SV1 and SV2 are similar in the same period, both trends exhibiting little difference with WL, such as those observed in the morning and night of August 7 and the afternoon of
Summary
Continuous streamflow can be used to calibrate and verify hydraulic routing models. inherent limitations are associated with conventional discharge monitoring using rating curves directly estimated using the water level (WL) or free-surface slope; for example, the presence of backwater and flow unsteadiness. Several studies have used continuous surface velocity radar (SVR) for measuring river surface velocity (SV) combined with the index velocity method to obtain continuous discharge data. Several studies have used continuous surface velocity radar (SVR) for measuring river surface. 11, 764 velocity combined with the index velocity method to obtain continuous discharge data. Fukami et al [14] used SVR for et al [14] used SVR for continuous flow rate measurement during floods for three rivers in Japan. If SVR is the instrument used for computing continuous flow discharge, a method must be developed and assessed for filtering the noise in its signals. A WL radar gauge and two continuous SVRs for surface wave velocity were established to estimate discharge through the velocity index method.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
