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A framework for testing large-scale distributed soil erosion and sediment delivery models: Dealing with uncertainty in models and the observational data
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 4616602
Author(s) Batista, Pedro V. G.; Laceby, J. Patrick; Davies, Jessica; Carvalho, Teotônio S.; Tassinari, Diego; Silva, Marx L. N.; Curi, Nilton; Quinton, John N.
Author(s) at UniBasel Batista, Pedro
Year 2021
Title A framework for testing large-scale distributed soil erosion and sediment delivery models: Dealing with uncertainty in models and the observational data
Journal Environmental Modelling and Software
Volume 137
Pages / Article-Number 104961
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.
Publisher Elsevier
ISSN/ISBN 1364-8152 ; 1873-6726
edoc-URL https://edoc.unibas.ch/82018/
Full Text on edoc No
Digital Object Identifier DOI 10.1016/j.envsoft.2021.104961
ISI-Number WOS:000626525700002
Document type (ISI) Article
 
   

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