Uncertainty in flow and water quality measurement data: A case study in the Daning River watershed in the Three Gorges Reservoir region, China

Measurement data are used to calibrate and validate the effect of models. In this study, four types of uncertainty categories covering flow measurement, sample collection, sample preservation/storage and laboratory analysis were quantified for flow, sediment and water quality measurement data under best-, typical- and worst-case scenarios. The root mean square error propagation method was used to calculate the overall uncertainty. A case study was conducted in the Daning River with the Soil and Water Assessment Tool. Based on the results, the probable error range values of flow were lower than those of sediment and nutrients, indicating greater uncertainty in the sediment and total phosphorus results. It is also indicated that the uncertainty was smaller when the model outputs had a normal distribution. This research provides scientific data of measurement uncertainty in China, which can assist modelers in evaluating model performance by quantifying the “quality” of the response data.