A Comparison of Different Methods for Rainfall Imputation: A Galician Case Study

With the ultimate goal of developing models that involve the use of environmental variables, a GIS-based application is being developed that is circumscribed to the region of Galicia (Spain). Ten-minute data of six meteorological variables were collected from 150 stations of the MeteoGalicia network...

Full description

Saved in:
Bibliographic Details
Published in:Applied sciences 2023-11, Vol.13 (22), p.12260
Main Authors: Vidal-Paz, José, Rodríguez-Gómez, Benigno Antonio, Orosa, José A.
Format: Article
Language:English
Subjects:
Altitude
Autumn
Case studies
Coasts
Comparative analysis
Discriminant analysis
Geographic information systems
imputation
Methods
Missing data
Mountains
Precipitation
Rain
Rain and rainfall
rainfall
Time series
Winter
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c363t-17e8f7549fe404dcfc247f870c4e3c53d84b76bed9fe612b7695783a0aaca4923
container_end_page
container_issue 22
container_start_page 12260
container_title Applied sciences
container_volume 13
creator Vidal-Paz, José
Rodríguez-Gómez, Benigno Antonio
Orosa, José A.
description With the ultimate goal of developing models that involve the use of environmental variables, a GIS-based application is being developed that is circumscribed to the region of Galicia (Spain). Ten-minute data of six meteorological variables were collected from 150 stations of the MeteoGalicia network over a period of 18 years, but the time series data are not complete. In order to estimate missing rainfall data, four imputation methods were evaluated in this study: missForest, MICE, Amelia II, and inverse distance weighting (IDW). Crossvalidation results show that the precipitation is out of phase in the different stations due to their geographical locations, and the imputation can be improved with a displacement of the time series; on the other hand, the missForest method provided better results in the imputation of this meteorological variable than the MICE, Amelia, or IDW.
doi_str_mv 10.3390/app132212260
format article
fullrecord <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_644a71cf27c046c08f6333aab4133d79</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A774316924</galeid><doaj_id>oai_doaj_org_article_644a71cf27c046c08f6333aab4133d79</doaj_id><sourcerecordid>A774316924</sourcerecordid><originalsourceid>FETCH-LOGICAL-c363t-17e8f7549fe404dcfc247f870c4e3c53d84b76bed9fe612b7695783a0aaca4923</originalsourceid><addsrcrecordid>eNpNUU1LQzEQfIiCot78AQGvVpNsmrx4K_WroCh-nMM2L9GU9uWZpIf-e6MVcS-7DDPDsNM0J4yeA2h6gcPAgHPGuaQ7zQGnSo5AMLX7795vjnNe0DqaQcvoQfM0IdO4GjCFHHsSPbkK3rvk-kIeXPmIXSY-JvKMofe4XJLZalgXLCH2l2RCbnEZbMCeTDE78lLW3eao2avE7I5_92HzdnP9Or0b3T_ezqaT-5EFCWXElGu9GgvtnaCis95yoXyrqBUO7Bi6VsyVnLuuEiTj9dZj1QJSRItCczhsZlvfLuLCDCmsMG1MxGB-gJjeDaYS7NIZKQQqZj1XlgppaeslACDOBQPolK5ep1uvIcXPtcvFLOI69TW-4a3mWo0Z_2adb1nvWE3rP2JJNYzFzq2Cjb3zoeITpQQwqbmogrOtwKaYc3L-Lyaj5rsz878z-AIvv4bE</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2892975129</pqid></control><display><type>article</type><title>A Comparison of Different Methods for Rainfall Imputation: A Galician Case Study</title><source>ProQuest - Publicly Available Content Database</source><creator>Vidal-Paz, José ; Rodríguez-Gómez, Benigno Antonio ; Orosa, José A.</creator><creatorcontrib>Vidal-Paz, José ; Rodríguez-Gómez, Benigno Antonio ; Orosa, José A.</creatorcontrib><description>With the ultimate goal of developing models that involve the use of environmental variables, a GIS-based application is being developed that is circumscribed to the region of Galicia (Spain). Ten-minute data of six meteorological variables were collected from 150 stations of the MeteoGalicia network over a period of 18 years, but the time series data are not complete. In order to estimate missing rainfall data, four imputation methods were evaluated in this study: missForest, MICE, Amelia II, and inverse distance weighting (IDW). Crossvalidation results show that the precipitation is out of phase in the different stations due to their geographical locations, and the imputation can be improved with a displacement of the time series; on the other hand, the missForest method provided better results in the imputation of this meteorological variable than the MICE, Amelia, or IDW.</description><identifier>ISSN: 2076-3417</identifier><identifier>EISSN: 2076-3417</identifier><identifier>DOI: 10.3390/app132212260</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Altitude ; Autumn ; Case studies ; Coasts ; Comparative analysis ; Discriminant analysis ; Geographic information systems ; imputation ; Methods ; Missing data ; Mountains ; Precipitation ; Rain ; Rain and rainfall ; rainfall ; Time series ; Winter</subject><ispartof>Applied sciences, 2023-11, Vol.13 (22), p.12260</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c363t-17e8f7549fe404dcfc247f870c4e3c53d84b76bed9fe612b7695783a0aaca4923</cites><orcidid>0000-0002-7012-9518 ; 0000-0002-8384-908X ; 0000-0002-0424-5764</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2892975129/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2892975129?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25752,27923,27924,37011,44589,74897</link.rule.ids></links><search><creatorcontrib>Vidal-Paz, José</creatorcontrib><creatorcontrib>Rodríguez-Gómez, Benigno Antonio</creatorcontrib><creatorcontrib>Orosa, José A.</creatorcontrib><title>A Comparison of Different Methods for Rainfall Imputation: A Galician Case Study</title><title>Applied sciences</title><description>With the ultimate goal of developing models that involve the use of environmental variables, a GIS-based application is being developed that is circumscribed to the region of Galicia (Spain). Ten-minute data of six meteorological variables were collected from 150 stations of the MeteoGalicia network over a period of 18 years, but the time series data are not complete. In order to estimate missing rainfall data, four imputation methods were evaluated in this study: missForest, MICE, Amelia II, and inverse distance weighting (IDW). Crossvalidation results show that the precipitation is out of phase in the different stations due to their geographical locations, and the imputation can be improved with a displacement of the time series; on the other hand, the missForest method provided better results in the imputation of this meteorological variable than the MICE, Amelia, or IDW.</description><subject>Altitude</subject><subject>Autumn</subject><subject>Case studies</subject><subject>Coasts</subject><subject>Comparative analysis</subject><subject>Discriminant analysis</subject><subject>Geographic information systems</subject><subject>imputation</subject><subject>Methods</subject><subject>Missing data</subject><subject>Mountains</subject><subject>Precipitation</subject><subject>Rain</subject><subject>Rain and rainfall</subject><subject>rainfall</subject><subject>Time series</subject><subject>Winter</subject><issn>2076-3417</issn><issn>2076-3417</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1LQzEQfIiCot78AQGvVpNsmrx4K_WroCh-nMM2L9GU9uWZpIf-e6MVcS-7DDPDsNM0J4yeA2h6gcPAgHPGuaQ7zQGnSo5AMLX7795vjnNe0DqaQcvoQfM0IdO4GjCFHHsSPbkK3rvk-kIeXPmIXSY-JvKMofe4XJLZalgXLCH2l2RCbnEZbMCeTDE78lLW3eao2avE7I5_92HzdnP9Or0b3T_ezqaT-5EFCWXElGu9GgvtnaCis95yoXyrqBUO7Bi6VsyVnLuuEiTj9dZj1QJSRItCczhsZlvfLuLCDCmsMG1MxGB-gJjeDaYS7NIZKQQqZj1XlgppaeslACDOBQPolK5ep1uvIcXPtcvFLOI69TW-4a3mWo0Z_2adb1nvWE3rP2JJNYzFzq2Cjb3zoeITpQQwqbmogrOtwKaYc3L-Lyaj5rsz878z-AIvv4bE</recordid><startdate>20231101</startdate><enddate>20231101</enddate><creator>Vidal-Paz, José</creator><creator>Rodríguez-Gómez, Benigno Antonio</creator><creator>Orosa, José A.</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-7012-9518</orcidid><orcidid>https://orcid.org/0000-0002-8384-908X</orcidid><orcidid>https://orcid.org/0000-0002-0424-5764</orcidid></search><sort><creationdate>20231101</creationdate><title>A Comparison of Different Methods for Rainfall Imputation: A Galician Case Study</title><author>Vidal-Paz, José ; Rodríguez-Gómez, Benigno Antonio ; Orosa, José A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c363t-17e8f7549fe404dcfc247f870c4e3c53d84b76bed9fe612b7695783a0aaca4923</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Altitude</topic><topic>Autumn</topic><topic>Case studies</topic><topic>Coasts</topic><topic>Comparative analysis</topic><topic>Discriminant analysis</topic><topic>Geographic information systems</topic><topic>imputation</topic><topic>Methods</topic><topic>Missing data</topic><topic>Mountains</topic><topic>Precipitation</topic><topic>Rain</topic><topic>Rain and rainfall</topic><topic>rainfall</topic><topic>Time series</topic><topic>Winter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Vidal-Paz, José</creatorcontrib><creatorcontrib>Rodríguez-Gómez, Benigno Antonio</creatorcontrib><creatorcontrib>Orosa, José A.</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest - Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Applied sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Vidal-Paz, José</au><au>Rodríguez-Gómez, Benigno Antonio</au><au>Orosa, José A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Comparison of Different Methods for Rainfall Imputation: A Galician Case Study</atitle><jtitle>Applied sciences</jtitle><date>2023-11-01</date><risdate>2023</risdate><volume>13</volume><issue>22</issue><spage>12260</spage><pages>12260-</pages><issn>2076-3417</issn><eissn>2076-3417</eissn><abstract>With the ultimate goal of developing models that involve the use of environmental variables, a GIS-based application is being developed that is circumscribed to the region of Galicia (Spain). Ten-minute data of six meteorological variables were collected from 150 stations of the MeteoGalicia network over a period of 18 years, but the time series data are not complete. In order to estimate missing rainfall data, four imputation methods were evaluated in this study: missForest, MICE, Amelia II, and inverse distance weighting (IDW). Crossvalidation results show that the precipitation is out of phase in the different stations due to their geographical locations, and the imputation can be improved with a displacement of the time series; on the other hand, the missForest method provided better results in the imputation of this meteorological variable than the MICE, Amelia, or IDW.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/app132212260</doi><orcidid>https://orcid.org/0000-0002-7012-9518</orcidid><orcidid>https://orcid.org/0000-0002-8384-908X</orcidid><orcidid>https://orcid.org/0000-0002-0424-5764</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2076-3417
ispartof Applied sciences, 2023-11, Vol.13 (22), p.12260
issn 2076-3417
2076-3417
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_644a71cf27c046c08f6333aab4133d79
source ProQuest - Publicly Available Content Database
subjects Altitude
Autumn
Case studies
Coasts
Comparative analysis
Discriminant analysis
Geographic information systems
imputation
Methods
Missing data
Mountains
Precipitation
Rain
Rain and rainfall
rainfall
Time series
Winter
title A Comparison of Different Methods for Rainfall Imputation: A Galician Case Study
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T11%3A02%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Comparison%20of%20Different%20Methods%20for%20Rainfall%20Imputation:%20A%20Galician%20Case%20Study&rft.jtitle=Applied%20sciences&rft.au=Vidal-Paz,%20Jos%C3%A9&rft.date=2023-11-01&rft.volume=13&rft.issue=22&rft.spage=12260&rft.pages=12260-&rft.issn=2076-3417&rft.eissn=2076-3417&rft_id=info:doi/10.3390/app132212260&rft_dat=%3Cgale_doaj_%3EA774316924%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c363t-17e8f7549fe404dcfc247f870c4e3c53d84b76bed9fe612b7695783a0aaca4923%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2892975129&rft_id=info:pmid/&rft_galeid=A774316924&rfr_iscdi=true