A framework for testing large-scale distributed soil erosion and sediment delivery models: Dealing with uncertainty in models and the observational data. (March 2021) - Batista, Pedro V.G.; Laceby, J. Patrick; Davies, Jessica; Carvalho, Teotônio S.; Tassinari, Diego; Silva, Marx L.N.; Curi, Nilton; Quinton, John N.
Abstract: Evaluating distributed soil erosion models is challenging because of the uncertainty in models and measurements of system responses. Here, we present an approach to evaluate soil erosion and sediment delivery models, which incorporates sediment source fingerprinting and sediment-rating curve uncertainty into model testing. We applied the Generalized Likelihood Uncertainty Estimation (GLUE) methodology to the Sediment Delivery Distributed model (SEDD) for a large catchment in Southeast Brazil. The model was not rejected, as 23.4% of model realizations were considered behavioral. Fingerprinting results and SEDD simulations showed a partial agreement regarding the identification of the main sediment sources in the catchment. However, grid-based estimates of soil erosion and sediment delivery rates were highly uncertain, which restricted the model's usefulness for quantifying sediment dynamics. Although our results are case-specific, similar levels of error might be expected in erosion models elsewhere. The representation of such errors should be standard practice. Highlights: GLUE was applied to an erosion and sediment delivery model. Models were conditioned according to sediment load measurements. Behavioral simulations were tested against sediment fingerprinting apportionments. Forcing and testing data were highly uncertain, as well as model outputs. Better observational data is needed to reject non-behavioral models.