An Interval-Deviation Approach for hydrology and water quality model evaluation within an uncertainty framework

- This paper provides a substitute of model evaluation within uncertainty framework.
- The IDA incorporates both prediction uncertainty and measurement uncertainty.
- The IDA quantified the possible range of model performances.
- The proposed IDA was validated in a real application of SWAT and GLUE.

SummaryUncertainty assessment is becoming one of the main topics in hydrology and water resources. In this study, an Interval-Deviation Approach (IDA) was designed and incorporated into the process of model evaluation. The proposed IDA was validated in a real application of the Soil and Water Assessment Tool (SWAT) and Generalized Likelihood Uncertainty Estimation (GLUE) in the Three Gorges Reservoir Area (TGRA), China. Compared with the traditional point-to-point comparison between measured and predicted data, the main superiority of the IDA is its innovative theory that models should be evaluated by each absolute distance between the paired uncertainty intervals or probability distribution for each measured and predicted data. In addition, the IDA can be used to quantify the possible range of model performance in a real application of the SWAT. This proposed IDA can be useful for error form indicators and models by providing a substitute method to facilitate enhanced evaluation of watershed models within an uncertainty framework.

In this study, an Interval-Deviation Approach (IDA) was designed to calculate the error term for evaluating the hydrology and water quality (H/WQ) models when prediction or measurement uncertainty existed. The overall framework for IDA is designed as 'top-down' (beginning with the source of uncertainty). This proposed IDA can be extrapolated into other forms of indicators and mathematical models.