This study aims to develop a laboratory method for the traceability of a rainfall weighing gauge, including an evaluation of the measurement uncertainty. The adopted procedure is similar to the one used for the non-automatic weighing instruments. A static approach is followed to achieve the calibration deviation of the precipitation scale. The method used to evaluate the measurement uncertainty is based on a nonlinear mathematical model. The Monte Carlo method is used to calculate uncertainties and validate estimates following the conventional Guide to the Expression of Uncertainty in Measurement (GUM) approach. Measurement uncertainty contributions of input quantities to the mathematical model used to calculate rainfall also require specific calibration procedures. Results show the accuracy level achievable with rainfall weighing gauges commonly used as a reference for meteorological monitoring networks and data modelling.

This study examines the traceability and measurement uncertainty of in situ hydraulic calibration of flowmeters using clamp-on ultrasonic flowmeters as reference. The procedure compares the equipment readings with the reference ones. Measurement uncertainty evaluation uses Guide to the expression of Uncertainty in Measurement (GUM) formulation, considering the linearity conditions of the mathematical models applied. Experimental values are used to test the procedure and its suitability for actual cases where the expected accuracy needs to be achieved.

This paper aims to determine the instrumental measurement uncertainty of conductance transducers for maritime reduced-scale models developed in hydraulic experimental facilities. These transducers are used for the measurements of wave levels and their variations under a dynamic regime (being the measurement principle and method briefly described in the paper). Several metrological characterization methods are also presented, aiming to identify and quantify measurement uncertainty components, namely electrical stability, linearity, reversibility, repeatability, and thermal influence. The obtained results were applied in the evaluation of the transducer instrumental measurement uncertainty.

Biofilm is known to negatively affect the hydraulic performance of open channels by increasing friction and energy losses and, consequently, economic costs. This study proposes a method to accurately quantify the effect of flow reduction caused by biofouling in open channels. The approach is based on Manning’s equation, using the Monte Carlo Method for the propagation of input uncertainties. A case study concerning a trapezoidal concrete open channel of an agricultural irrigation network is presented, showing a relative expanded uncertainty (95% confidence level) of 10% for flow rates ranging from 1 m³·s⁻¹ to 50 m³·s⁻¹. Manning’s roughness coefficient was identified as the dominant contribution to the overall dispersion of flow rate values, being probabilistically modeled by a beta distribution using minimum, expected and maximum reference values. This information was used for conformity assessment of the studied open channel, considering flow reductions due to moderate and severe biofilm effects of 12.5% and 31.3%, respectively. The corresponding standard uncertainties (4.8% and 7.8%), the adopted confidence level (95%), tolerance upper limit (33%) and decision rule led to different conformity assessment outcomes. These results highlight the importance of accurate assessment of flow reduction due to biofouling for management entities.

Biofilm is known to negatively affect the hydraulic performance of open channels by increasing friction and energy losses and, consequently, economic costs. This study proposes a method to accurately quantify the effect of flow reduction caused by biofouling in open channels. The approach is based on Manning’s equation, using the Monte Carlo Method for the propagation of input uncertainties. A case study concerning a trapezoidal concrete open channel of an agricultural irrigation network is presented, showing a relative expanded uncertainty (95 % confidence level) of 10 % for flow rates ranging from 1 m3·s-1 and 50 m3·s-1. Manning’s roughness coefficient was identified as the dominant contribution to the overall dispersion of flow rate values, being probabilistically modelled by a beta distribution using minimum, expected and maximum reference values. This information was used for conformity assessment of the studied open channel, considering flow reductions due to moderate and severe biofilm effect of 12.5 % and 31.3 %, respectively. The corresponding standard uncertainties (4.8 % and 7.8 %), the adopted confidence level (95 %), tolerance upper limit (33 %) and decision rule, led to different conformity assessment outcomes. These results highlight the importance of accurate assessment of flow reduction due to biofouling for management entities.