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Evaluation of satellite and reanalysis estimates of surface and root-zone soil moisture in croplands of Jiangsu Province, China

hal.structure.identifierSouthwest University [Chongqing]
dc.contributor.authorFAN, Lei
hal.structure.identifierUniversity of Chinese Academy of Sciences [Beijing] [UCAS]
hal.structure.identifierChinese Academy of Sciences [Beijing] [CAS]
dc.contributor.authorXING, Zanpin
hal.structure.identifierTechnologie campus Gent - KU Leuven [KU Leuven]
dc.contributor.authorLANNOY, Gabrielle De
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorFRAPPART, Frédéric
hal.structure.identifierHelmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research [UFZ]
hal.structure.identifierLeipzig University / Universität Leipzig
dc.contributor.authorPENG, Jian
hal.structure.identifierChinese Academy of Sciences [Beijing] [CAS]
dc.contributor.authorZENG, Jiangyuan
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLI, Xiaojun
hal.structure.identifierTsinghua University [Beijing] [THU]
dc.contributor.authorYANG, Kun
hal.structure.identifierChinese Academy of Sciences [Beijing] [CAS]
dc.contributor.authorZHAO, Tianjie
hal.structure.identifierChinese Academy of Sciences [Beijing] [CAS]
dc.contributor.authorSHI, Jiancheng
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
hal.structure.identifierWuhan University [China]
dc.contributor.authorMA, Hongliang
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorWANG, Mengjia
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorLIU, Xiangzhuo
hal.structure.identifierYancheng Institute of Technology [YIT]
dc.contributor.authorYI, Chuanxiang
hal.structure.identifierSouthwest University [Chongqing]
dc.contributor.authorMA, Mingguo
hal.structure.identifierSouthwest University [Chongqing]
dc.contributor.authorTANG, Xuguang
hal.structure.identifierChinese Academy of Sciences [Beijing] [CAS]
dc.contributor.authorWEN, Jianguang
hal.structure.identifierSun Yat-sen University [Guangzhou] [SYSU]
dc.contributor.authorCHEN, Xiuzhi
hal.structure.identifierNanjing University of Information Science and Technology [NUIST]
dc.contributor.authorWANG, Chong
hal.structure.identifierNanjing University of Information Science and Technology [NUIST]
dc.contributor.authorWANG, Lingxiao
hal.structure.identifierNanjing University of Information Science and Technology [NUIST]
dc.contributor.authorWANG, Guojie
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorJ.-P., Wigneron
dc.date.accessioned2024-04-08T11:43:56Z
dc.date.available2024-04-08T11:43:56Z
dc.date.issued2022-12
dc.identifier.issn0034-4257
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195129
dc.description.abstractEnHigh-quality and long-term surface soil moisture (SSM) and root-zone soil moisture (RZSM) data are critical for agricultural water management of Jiangsu province, which is a major agricultural province in China. However, few studies assessed the accuracy of SSM and RZSM datasets in croplands of Jiangsu province. The study addressed this gap by firstly using observations from ninety-one sites to assess thirteen satellite and model-based SSM products (Advanced Scatterometer (ASCAT), European Space Agency Climate Change Initiative (ESA CCI) Combined/Passive/Active, Soil Moisture and Ocean Salinity in version IC (SMOS-IC), Land Parameter Retrieval Model (LPRM) Advanced Microwave Scanning Radiometer 2 (AMSR2), Soil Moisture Active Passive (SMAP)-Multi-Temporal Dual-channel Algorithm (MTDCA)/Level 3 (L3)/Level 4 (L4)/SMAP-INRAE-BORDEAUX (IB)/ Multi-channel Collaborative Algorithm (MCCA), the fifth generation of the land component of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5-Land), and the Noah land surface model driven by Global Land Data Assimilation System (GLDAS-Noah)), and four RZSM products (ERA5-Land, GLDAS-Noah, SMAP-L4 and ESA CCI (retrieved using ESA CCI Combined SSM coupled with an exponential filter)). We also inter-compared time-invariant and time-variant Triple Collocation Analysis (TCA)-based R with in situ-based R calculated using SSM anomalies. Various evaluation strategies were compared using different groups of available sites and temporal samplings. Our results showed that the model-based and combined SSM products (i.e., ERA5-Land, SMAP-L4, ESA CCI Combined/Passive/Active, GLDAS-Noah, ASCAT) performed better than the other SSM products and ERA5-Land, SMAP-L4 and ESA CCI RZSM generally performed better than the GLDAS-Noah RZSM product with higher R. Similar performance rankings were observed among time-invariant and time-variant TCA-R and in situ-based R, in which the TCA-R values for all SSM datasets were higher than the in situ-based R as the representativeness errors of the in situ measurements may bias in situ-based R. The accuracy of the ESA CCI, GLDAS-Noah and ERA5-Land SSM products was expected to be enhanced by considering the water effect and high uncertainties were observed for MTDCA and SMAP-MCCA SSM over dense vegetation periods and regions. Also, it is important to select appropriate evaluation strategies to conduct the SSM and RZSM evaluations according to the situation as the available sites and temporal samplings may bias the evalu-ation results.
dc.language.isoen
dc.publisherElsevier
dc.subject.enJiangsu province
dc.subject.enMicrowave remote sensing
dc.subject.enReanalysis datasets
dc.subject.enSurface soil moisture
dc.subject.enRoot-zone soil moisture
dc.subject.enEvaluation strategies
dc.subject.enInter-comparison
dc.subject.enTriple collocation
dc.title.enEvaluation of satellite and reanalysis estimates of surface and root-zone soil moisture in croplands of Jiangsu Province, China
dc.typeArticle de revue
dc.identifier.doi10.1016/j.rse.2022.113283
dc.subject.halSciences de l'environnement
bordeaux.journalRemote Sensing of Environment
bordeaux.page113283
bordeaux.volume282
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-04111618
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04111618v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing%20of%20Environment&rft.date=2022-12&rft.volume=282&rft.spage=113283&rft.epage=113283&rft.eissn=0034-4257&rft.issn=0034-4257&rft.au=FAN,%20Lei&XING,%20Zanpin&LANNOY,%20Gabrielle%20De&FRAPPART,%20Fr%C3%A9d%C3%A9ric&PENG,%20Jian&rft.genre=article


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