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