A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments

The impact of climate change on future soil loss is commonly assessed with soil erosion models, which are suggested to be an important source of uncertainty. Here, we present a novel soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments. The model ensemble cons...

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Autores: Eekhout, Joris P.C., Millares-Valenzuela, Agustín, Martínez‐Salvador, Alberto, García‐Lorenzo, Rafael, Pérez-Cutillas, Pedro, Conesa García, Carmelo, de Vente, Joris
Tipo de documento: artigo
Estado:Versión aceptada para publicación
Data de publicação:2021
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositório:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/234592
Acesso em linha:http://hdl.handle.net/10261/234592
Access Level:Acceso aberto
Palavra-chave:Soil erosion
Climate change
Model ensemble
Process‐based
Model uncertainty
http://metadata.un.org/sdg/13
Take urgent action to combat climate change and its impacts
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spelling A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessmentsEekhout, Joris P.C.Millares-Valenzuela, AgustínMartínez‐Salvador, AlbertoGarcía‐Lorenzo, RafaelPérez-Cutillas, PedroConesa García, Carmelode Vente, JorisSoil erosionClimate changeModel ensembleProcess‐basedModel uncertaintyhttp://metadata.un.org/sdg/13Take urgent action to combat climate change and its impactsThe impact of climate change on future soil loss is commonly assessed with soil erosion models, which are suggested to be an important source of uncertainty. Here, we present a novel soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments. The model ensemble consists of five continuous process‐based soil erosion models that run at a daily time step (i.e., DHSVM, HSPF, INCA, MMF, SHETRAN). The models were implemented in the SPHY hydrological model and simulate detachment by raindrop impact, detachment by runoff, and immediate deposition. The soil erosion model ensemble was applied in a semiarid catchment in the southeast of Spain. We applied three future climate scenarios based on global mean temperature rise (+1.5, +2 and +3°C). Data from two contrasting regional climate models were used to assess how an increase and a decrease in projected extreme precipitation affect model uncertainty. Soil loss is projected to increase (up to 95%) and decrease (up to −30%) under climate change, mostly reflecting the change in extreme precipitation. Model uncertainty is found to increase with increasing slope, extreme precipitation and runoff, which reveals some inherent differences in model assumptions among the five models. Moreover, the model uncertainty increases in all climate change scenarios, independent of the projected change in annual precipitation and extreme precipitation. This stresses the importance to consider model uncertainty through model ensembles of climate, hydrology, and soil erosion in climate‐change impact assessments.This work has been financed by ERDF/Spanish Ministry of Science, Innovation and Universities—State Research Agency/Project CGL2017‐84625‐C2‐1‐R (CCAMICEM) and Project PID2019‐109381RB‐I00/AEI/10.13039/501100011033 (XTREME) both under the National Program for Research, Development and Innovation focused on the Societal ChallengesPeer reviewedWiley-BlackwellMinisterio de Ciencia, Innovación y Universidades (España)Agencia Estatal de Investigación (España)European CommissionEekhout, Joris P. C. [0000-0003-2097-696X]Millares-Valenzuela, Agustín [0000-0002-7120-7493]Martínez‐Salvador, Alberto [0000-0002-9113-3487]García‐Lorenzo, Rafael [0000-0002-4495-4944]Pérez-Cutillas, Pedro [0000-0003-1271-3895]Conesa García, Carmenlo [0000-0002-3818-5421]Vente, Joris de [0000-0001-7428-0621]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202120212021info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/234592reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019‐109381RB‐I00info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/CGL2017‐84625‐C2‐1‐Rhttps://doi.org/10.1002/ldr.3920Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2345922026-05-22T06:33:51Z
dc.title.none.fl_str_mv A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments
title A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments
spellingShingle A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments
Eekhout, Joris P.C.
Soil erosion
Climate change
Model ensemble
Process‐based
Model uncertainty
http://metadata.un.org/sdg/13
Take urgent action to combat climate change and its impacts
title_short A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments
title_full A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments
title_fullStr A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments
title_full_unstemmed A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments
title_sort A process‐based soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments
dc.creator.none.fl_str_mv Eekhout, Joris P.C.
Millares-Valenzuela, Agustín
Martínez‐Salvador, Alberto
García‐Lorenzo, Rafael
Pérez-Cutillas, Pedro
Conesa García, Carmelo
de Vente, Joris
author Eekhout, Joris P.C.
author_facet Eekhout, Joris P.C.
Millares-Valenzuela, Agustín
Martínez‐Salvador, Alberto
García‐Lorenzo, Rafael
Pérez-Cutillas, Pedro
Conesa García, Carmelo
de Vente, Joris
author_role author
author2 Millares-Valenzuela, Agustín
Martínez‐Salvador, Alberto
García‐Lorenzo, Rafael
Pérez-Cutillas, Pedro
Conesa García, Carmelo
de Vente, Joris
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia, Innovación y Universidades (España)
Agencia Estatal de Investigación (España)
European Commission
Eekhout, Joris P. C. [0000-0003-2097-696X]
Millares-Valenzuela, Agustín [0000-0002-7120-7493]
Martínez‐Salvador, Alberto [0000-0002-9113-3487]
García‐Lorenzo, Rafael [0000-0002-4495-4944]
Pérez-Cutillas, Pedro [0000-0003-1271-3895]
Conesa García, Carmenlo [0000-0002-3818-5421]
Vente, Joris de [0000-0001-7428-0621]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Soil erosion
Climate change
Model ensemble
Process‐based
Model uncertainty
http://metadata.un.org/sdg/13
Take urgent action to combat climate change and its impacts
topic Soil erosion
Climate change
Model ensemble
Process‐based
Model uncertainty
http://metadata.un.org/sdg/13
Take urgent action to combat climate change and its impacts
description The impact of climate change on future soil loss is commonly assessed with soil erosion models, which are suggested to be an important source of uncertainty. Here, we present a novel soil erosion model ensemble to assess model uncertainty in climate‐change impact assessments. The model ensemble consists of five continuous process‐based soil erosion models that run at a daily time step (i.e., DHSVM, HSPF, INCA, MMF, SHETRAN). The models were implemented in the SPHY hydrological model and simulate detachment by raindrop impact, detachment by runoff, and immediate deposition. The soil erosion model ensemble was applied in a semiarid catchment in the southeast of Spain. We applied three future climate scenarios based on global mean temperature rise (+1.5, +2 and +3°C). Data from two contrasting regional climate models were used to assess how an increase and a decrease in projected extreme precipitation affect model uncertainty. Soil loss is projected to increase (up to 95%) and decrease (up to −30%) under climate change, mostly reflecting the change in extreme precipitation. Model uncertainty is found to increase with increasing slope, extreme precipitation and runoff, which reveals some inherent differences in model assumptions among the five models. Moreover, the model uncertainty increases in all climate change scenarios, independent of the projected change in annual precipitation and extreme precipitation. This stresses the importance to consider model uncertainty through model ensembles of climate, hydrology, and soil erosion in climate‐change impact assessments.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/234592
url http://hdl.handle.net/10261/234592
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019‐109381RB‐I00
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/CGL2017‐84625‐C2‐1‐R
https://doi.org/10.1002/ldr.3920
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Wiley-Blackwell
publisher.none.fl_str_mv Wiley-Blackwell
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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