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1. Identity statement
Reference TypeJournal Article
Sitemtc-m16b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier6qtX3pFwXQZGivnK2Y/THSKL
Repositorysid.inpe.br/mtc-m17@80/2008/04.10.19.04   (restricted access)
Last Update2008:04.10.19.04.17 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m17@80/2008/04.10.19.04.19
Metadata Last Update2018:06.05.03.30.39 (UTC) administrator
Secondary KeyINPE--PRE/
DOI10.1016/j.jhydrol.2008.02.008
ISSN0022-1694
Citation KeyRavinesSchmMigoRenn:2008:CaRiGr
TitleA joint model for rainfall-runoff: The case of Rio Grande Basin
Year2008
MonthMay
Access Date2024, Apr. 28
Secondary TypePRE PI
Number of Files1
Size558 KiB
2. Context
Author1 Ravines, Romy Rodríguez
2 Schmidt, Alexandra Mello
3 Migon, Helio dos Santos
4 Rennó, Camilo Daleles
Group1 DPI-OBT-INPE-MCT-BR
Affiliation1 Universidade Federal do Rio de Janeiro
2 Universidade Federal do Rio de Janeiro
3 Universidade Federal do Rio de Janeiro
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 romy@dme.ufrj.br
2 alex@im.ufrj.br
3 migon@im.ufrj.br
4 camilo@dpi.inpe.br
e-Mail Addresscamilo@dpi.inpe.br
JournalJournal of Hydrology
Volume353
Number1-2
Pages189-200
ProgressePrint update
Secondary MarkA
History (UTC)2008-04-14 16:36:13 :: camilo@dpi.inpe.br -> banon ::
2008-04-14 16:41:36 :: banon -> camilo@dpi.inpe.br ::
2008-06-19 13:48:31 :: camilo@dpi.inpe.br -> marciana ::
2008-12-15 15:40:16 :: marciana -> administrator ::
2010-05-11 02:43:16 :: administrator -> marciana ::
2011-05-20 20:28:16 :: marciana -> administrator ::
2018-06-05 03:30:39 :: administrator -> simone :: 2008
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsBayesian paradigm
Dynamic Models
Transfer functions
Spatio-Temporal
Spatial change of support
AbstractWe present an analysis of runoff and rainfall data from Rio Grande, a basin located in the northeast of Brazil. The main challenges we face here are: (i) to model runoff and rainfall jointly, taking into account their different spatial units, (ii) to use stochastic models where all the parameters have physical interpretations, and (iii) to model these processes in their original scale, without assuming any transformation to attain normality of these variables. The intrinsically uncertain nature of these hydrological processes makes Bayesian analysis natural in this field. Our approach is based on dynamic models. The effect of rainfall on runoff is modeled through a transfer function, whereas the amount of rainfall is obtained after fitting a spatio-temporal model and dealing with the change of support problem. Besides the computational effort to implement the proposed models, some methodological novelties are also implemented. The data consist of monthly series from January 1984 to September 2004, at a runoff station and nine rainfall stations irregularly located in a drainage area of 37522.48 km2. Model assessment, spatial interpolation and temporal predictions were part of our analysis. The results show that our approach is a promising tool for rainfall-runoff analysis.
AreaSRE
ArrangementA joint model...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target FileHYDROL16097_offprint.pdf
User Groupadministrator
banon
camilo@dpi.inpe.br
marciana
Visibilityshown
Archiving Policydenypublisher denyfinaldraft24
Read Permissiondeny from all and allow from 150.163
5. Allied materials
Previous Editionsid.inpe.br/mtc-m17@80/2007/09.28.19.36
Next Higher Units8JMKD3MGPCW/3EQCCU5
DisseminationWEBSCI; PORTALCAPES.
Host Collectionlcp.inpe.br/ignes/2004/02.12.18.39
cptec.inpe.br/walmeida/2003/04.25.17.12
6. Notes
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7. Description control
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