Abstract
River discharge data are critical to elaborating on engineering projects and water resources management. Discharge data must be precise and collected with good temporal resolution. To elaborate on a more accurate database, this paper aims to quantify the uncertainty generated while applying Bayesian inference through the GLUE and DREAM methods. Both methods were used to estimate hydraulic parameters and compare between them with Manning’s equation. Throughout the statistical analysis, the uncertainties in the application of the models are used to determine the parameters of Manning’s roughness coefficient and bed slope. The validation was made via a comparison of the calculated maximum and minimum discharges, and the observed flow available at HidroWeb. In conclusion, both methods estimated the hydraulic parameters well, but a higher relative deviation was seen in the intervals with smaller calculated discharges; DREAM appears to be more accurate than GLUE, once the relative deviation in GLUE became greater.
Highlights
IntroductionMonitoring river discharge is important to the maintenance of the environment and water planning
Monitoring river discharge is important to the maintenance of the environment and water planning.Such data are necessary to elaborate engineering projects aiming to guarantee water availability to the public, as well as industrial and agricultural supply
The first one presents the results for GLUE, and the second one is for DREAM
Summary
Monitoring river discharge is important to the maintenance of the environment and water planning Such data are necessary to elaborate engineering projects aiming to guarantee water availability to the public, as well as industrial and agricultural supply. Doppler Current Profiler (ADCP), Acoustic Doppler Velocimeter (ADV), mechanical current meters, drones, and others [1]. Even though these ways of measuring the flow can lead to results with high resolution, this equipment is expensive and may require a professional to deal with the situation in the field and during post-processing [2]. There is physical risk to the professional handling of this equipment during flooding [1,3,4]
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