Identifying climate and human impact trends in streamflow: A case study in Uruguay.

NAVAS, R. - AALONSO, J. - GORGOGLIONE, A. - VERVOORT, R. W.

Resumen:

ABSTRACT.Land use change is an important driver of trends in streamflow. However, the effects are often difficult to disentangle from climate effects. The aim of this paper is to demonstrate that trends in streamflow can be identified by analysing residuals of rainfall-runoff simulations using a Generalized Additive Mixed Model. This assumes that the rainfall-runoff model removes the average climate forcing from streamflow. The case study involves the Santa Lucía river (Uruguay), the GR4J rainfall-runoff model, three nested catchments ranging from 690 to 4900 km 2 and 35 years of observations (1981?2016). Two exogenous variables were considered to influence the streamflow. Using satellite data, growth in forest cover was identified, while the growth in water licenses was obtained from the water authority. Depending on the catchment, effects of land use change differ, with the largest catchment most impacted by afforestation, while the middle size catchment was more influenced by the growth in water licenses.


Detalles Bibliográficos
2019
Statistical hydrology
Trend identification
Land use change
GR4J
Climate models
HYDROLOGY
Inglés
Instituto Nacional de Investigación Agropecuaria
AINFO
http://www.ainfo.inia.uy/consulta/busca?b=pc&id=60476&biblioteca=vazio&busca=60476&qFacets=60476
Acceso abierto
_version_ 1805580526618148864
author NAVAS, R.
author2 AALONSO, J.
GORGOGLIONE, A.
VERVOORT, R. W.
author2_role author
author
author
author_facet NAVAS, R.
AALONSO, J.
GORGOGLIONE, A.
VERVOORT, R. W.
author_role author
bitstream.checksum.fl_str_mv 5adbac31ab6ebbbbd3a5b4c46be6e262
bitstream.checksumAlgorithm.fl_str_mv MD5
bitstream.url.fl_str_mv https://redi.anii.org.uy/jspui/bitstream/20.500.12381/1131/1/sword-2022-10-20T22%3a28%3a16.original.xml
collection AINFO
dc.creator.none.fl_str_mv NAVAS, R.
AALONSO, J.
GORGOGLIONE, A.
VERVOORT, R. W.
dc.date.accessioned.none.fl_str_mv 2022-10-21T01:28:16Z
dc.date.available.none.fl_str_mv 2022-10-21T01:28:16Z
dc.date.issued.none.fl_str_mv 2019
dc.date.updated.none.fl_str_mv 2022-10-21T01:28:16Z
dc.description.abstract.none.fl_txt_mv ABSTRACT.Land use change is an important driver of trends in streamflow. However, the effects are often difficult to disentangle from climate effects. The aim of this paper is to demonstrate that trends in streamflow can be identified by analysing residuals of rainfall-runoff simulations using a Generalized Additive Mixed Model. This assumes that the rainfall-runoff model removes the average climate forcing from streamflow. The case study involves the Santa Lucía river (Uruguay), the GR4J rainfall-runoff model, three nested catchments ranging from 690 to 4900 km 2 and 35 years of observations (1981?2016). Two exogenous variables were considered to influence the streamflow. Using satellite data, growth in forest cover was identified, while the growth in water licenses was obtained from the water authority. Depending on the catchment, effects of land use change differ, with the largest catchment most impacted by afforestation, while the middle size catchment was more influenced by the growth in water licenses.
dc.identifier.none.fl_str_mv http://www.ainfo.inia.uy/consulta/busca?b=pc&id=60476&biblioteca=vazio&busca=60476&qFacets=60476
dc.language.iso.none.fl_str_mv en
eng
dc.rights.es.fl_str_mv Acceso abierto
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:AINFO
instname:Instituto Nacional de Investigación Agropecuaria
instacron:Instituto Nacional de Investigación Agropecuaria
dc.subject.none.fl_str_mv Statistical hydrology
Trend identification
Land use change
GR4J
Climate models
HYDROLOGY
dc.title.none.fl_str_mv Identifying climate and human impact trends in streamflow: A case study in Uruguay.
dc.type.none.fl_str_mv Article
PublishedVersion
info:eu-repo/semantics/article
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
description ABSTRACT.Land use change is an important driver of trends in streamflow. However, the effects are often difficult to disentangle from climate effects. The aim of this paper is to demonstrate that trends in streamflow can be identified by analysing residuals of rainfall-runoff simulations using a Generalized Additive Mixed Model. This assumes that the rainfall-runoff model removes the average climate forcing from streamflow. The case study involves the Santa Lucía river (Uruguay), the GR4J rainfall-runoff model, three nested catchments ranging from 690 to 4900 km 2 and 35 years of observations (1981?2016). Two exogenous variables were considered to influence the streamflow. Using satellite data, growth in forest cover was identified, while the growth in water licenses was obtained from the water authority. Depending on the catchment, effects of land use change differ, with the largest catchment most impacted by afforestation, while the middle size catchment was more influenced by the growth in water licenses.
eu_rights_str_mv openAccess
format article
id INIAOAI_131fe73560f5099d9ae26afbd46ec023
instacron_str Instituto Nacional de Investigación Agropecuaria
institution Instituto Nacional de Investigación Agropecuaria
instname_str Instituto Nacional de Investigación Agropecuaria
language eng
language_invalid_str_mv en
network_acronym_str INIAOAI
network_name_str AINFO
oai_identifier_str oai:redi.anii.org.uy:20.500.12381/1131
publishDate 2019
reponame_str AINFO
repository.mail.fl_str_mv lorrego@inia.org.uy
repository.name.fl_str_mv AINFO - Instituto Nacional de Investigación Agropecuaria
repository_id_str
rights_invalid_str_mv Acceso abierto
spelling 2022-10-21T01:28:16Z2022-10-21T01:28:16Z20192022-10-21T01:28:16Zhttp://www.ainfo.inia.uy/consulta/busca?b=pc&id=60476&biblioteca=vazio&busca=60476&qFacets=60476ABSTRACT.Land use change is an important driver of trends in streamflow. However, the effects are often difficult to disentangle from climate effects. The aim of this paper is to demonstrate that trends in streamflow can be identified by analysing residuals of rainfall-runoff simulations using a Generalized Additive Mixed Model. This assumes that the rainfall-runoff model removes the average climate forcing from streamflow. The case study involves the Santa Lucía river (Uruguay), the GR4J rainfall-runoff model, three nested catchments ranging from 690 to 4900 km 2 and 35 years of observations (1981?2016). Two exogenous variables were considered to influence the streamflow. Using satellite data, growth in forest cover was identified, while the growth in water licenses was obtained from the water authority. Depending on the catchment, effects of land use change differ, with the largest catchment most impacted by afforestation, while the middle size catchment was more influenced by the growth in water licenses.https://hdl.handle.net/20.500.12381/1131enenginfo:eu-repo/semantics/openAccessAcceso abiertoStatistical hydrologyTrend identificationLand use changeGR4JClimate modelsHYDROLOGYIdentifying climate and human impact trends in streamflow: A case study in Uruguay.ArticlePublishedVersioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:AINFOinstname:Instituto Nacional de Investigación Agropecuariainstacron:Instituto Nacional de Investigación AgropecuariaNAVAS, R.AALONSO, J.GORGOGLIONE, A.VERVOORT, R. W.SWORDsword-2022-10-20T22:28:16.original.xmlOriginal SWORD entry documentapplication/octet-stream2181https://redi.anii.org.uy/jspui/bitstream/20.500.12381/1131/1/sword-2022-10-20T22%3a28%3a16.original.xml5adbac31ab6ebbbbd3a5b4c46be6e262MD5120.500.12381/11312022-10-20 22:28:17.452oai:redi.anii.org.uy:20.500.12381/1131Gobiernohttp://inia.uyhttps://redi.anii.org.uy/oai/requestlorrego@inia.org.uyUruguayopendoar:2022-10-21T01:28:17AINFO - Instituto Nacional de Investigación Agropecuariafalse
spellingShingle Identifying climate and human impact trends in streamflow: A case study in Uruguay.
NAVAS, R.
Statistical hydrology
Trend identification
Land use change
GR4J
Climate models
HYDROLOGY
status_str publishedVersion
title Identifying climate and human impact trends in streamflow: A case study in Uruguay.
title_full Identifying climate and human impact trends in streamflow: A case study in Uruguay.
title_fullStr Identifying climate and human impact trends in streamflow: A case study in Uruguay.
title_full_unstemmed Identifying climate and human impact trends in streamflow: A case study in Uruguay.
title_short Identifying climate and human impact trends in streamflow: A case study in Uruguay.
title_sort Identifying climate and human impact trends in streamflow: A case study in Uruguay.
topic Statistical hydrology
Trend identification
Land use change
GR4J
Climate models
HYDROLOGY
url http://www.ainfo.inia.uy/consulta/busca?b=pc&id=60476&biblioteca=vazio&busca=60476&qFacets=60476