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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

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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. / Batista, Pedro V.G.; Laceby, J. Patrick; Davies, Jessica et al.
In: Environmental Modelling and Software, Vol. 137, 104961, 31.03.2021.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Batista, PVG, Laceby, JP, Davies, J, Carvalho, TS, Tassinari, D, Silva, MLN, Curi, N & Quinton, JN 2021, 'A framework for testing large-scale distributed soil erosion and sediment delivery models: Dealing with uncertainty in models and the observational data', Environmental Modelling and Software, vol. 137, 104961. https://doi.org/10.1016/j.envsoft.2021.104961

APA

Batista, P. V. G., Laceby, J. P., Davies, J., Carvalho, T. S., Tassinari, D., Silva, M. L. N., Curi, N., & Quinton, J. N. (2021). A framework for testing large-scale distributed soil erosion and sediment delivery models: Dealing with uncertainty in models and the observational data. Environmental Modelling and Software, 137, Article 104961. https://doi.org/10.1016/j.envsoft.2021.104961

Vancouver

Batista PVG, Laceby JP, Davies J, Carvalho TS, Tassinari D, Silva MLN et al. A framework for testing large-scale distributed soil erosion and sediment delivery models: Dealing with uncertainty in models and the observational data. Environmental Modelling and Software. 2021 Mar 31;137:104961. Epub 2021 Jan 8. doi: 10.1016/j.envsoft.2021.104961

Author

Batista, Pedro V.G. ; Laceby, J. Patrick ; Davies, Jessica et al. / A framework for testing large-scale distributed soil erosion and sediment delivery models : Dealing with uncertainty in models and the observational data. In: Environmental Modelling and Software. 2021 ; Vol. 137.

Bibtex

@article{bdc81d3ce17a46beb082ee5bd5026773,
title = "A framework for testing large-scale distributed soil erosion and sediment delivery models: Dealing with uncertainty in models and the observational data",
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.",
keywords = "GLUE, RUSLE, SEDD, Sediment fingerprinting, Sediment loads, Soil erosion models",
author = "Batista, {Pedro V.G.} and Laceby, {J. Patrick} and Jessica Davies and Carvalho, {Teot{\^o}nio S.} and Diego Tassinari and Silva, {Marx L.N.} and Nilton Curi and Quinton, {John N.}",
year = "2021",
month = mar,
day = "31",
doi = "10.1016/j.envsoft.2021.104961",
language = "English",
volume = "137",
journal = "Environmental Modelling and Software",
issn = "1364-8152",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - A framework for testing large-scale distributed soil erosion and sediment delivery models

T2 - Dealing with uncertainty in models and the observational data

AU - Batista, Pedro V.G.

AU - Laceby, J. Patrick

AU - Davies, Jessica

AU - Carvalho, Teotônio S.

AU - Tassinari, Diego

AU - Silva, Marx L.N.

AU - Curi, Nilton

AU - Quinton, John N.

PY - 2021/3/31

Y1 - 2021/3/31

N2 - 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.

AB - 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.

KW - GLUE

KW - RUSLE

KW - SEDD

KW - Sediment fingerprinting

KW - Sediment loads

KW - Soil erosion models

U2 - 10.1016/j.envsoft.2021.104961

DO - 10.1016/j.envsoft.2021.104961

M3 - Journal article

AN - SCOPUS:85099581886

VL - 137

JO - Environmental Modelling and Software

JF - Environmental Modelling and Software

SN - 1364-8152

M1 - 104961

ER -