The Assessment of Hydrologic- and Flood-Induced Land Deformation in Data-Sparse Regions Using GRACE/GRACE-FO Data Assimilation

dc.contributor.authorTangdamrongsub, Nattachet
dc.contributor.authorŠprlák, Michal
dc.date.accessioned2021-09-06T10:00:24Z
dc.date.available2021-09-06T10:00:24Z
dc.date.issued2021
dc.description.abstract-translatedThe vertical motion of the Earth’s surface is dominated by the hydrologic cycle on a seasonal scale. Accurate land deformation measurements can provide constructive insight into the regional geophysical process. Although the Global Positioning System (GPS) delivers relatively accurate measurements, GPS networks are not uniformly distributed across the globe, posing a challenge to obtaining accurate deformation information in data-sparse regions, e.g., Central South-East Asia (CSEA). Model simulations and gravity data (from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO)) have been successfully used to improve the spatial coverage. While combining model estimates and GRACE/GRACE-FO data via the GRACE/GRACE-FO data assimilation (DA) framework can potentially improve the accuracy and resolution of deformation estimates, the approach has rarely been considered or investigated thus far. This study assesses the performance of vertical displacement estimates from GRACE/GRACE-FO, the PCRaster Global Water Balance (PCR-GLOBWB) hydrology model, and the GRACE/GRACE-FO DA approach (assimilating GRACE/GRACE-FO into PCR-GLOBWB) in CSEA, where measurements from six GPS sites are available for validation. The results show that GRACE/GRACE-FO, PCRGLOBWB, and GRACE/GRACE-FO DA accurately capture regional-scale hydrologic- and flood induced vertical displacements, with the correlation value and RMS reduction relative to GPS measurements up to 0.89 and 53%, respectively. The analyses also confirm the GRACE/GRACE-FO DA’s effectiveness in providing vertical displacement estimates consistent with GRACE/GRACE-FO data while maintaining high-spatial details of the PCR-GLOBWB model, highlighting the benefits of GRACE/GRACE-FO DA in data-sparse regions.en
dc.format18 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationTANGDAMRONGSUB, N., ŠPRLÁK, M. The Assessment of Hydrologic- and Flood-Induced Land Deformation in Data-Sparse Regions Using GRACE/GRACE-FO Data Assimilation. Remote Sensing, 2021, roč. 13, č. 2, s. 1-18. ISSN 2072-4292.cs
dc.identifier.document-number611549700001
dc.identifier.doi10.3390/rs13020235
dc.identifier.issn2072-4292
dc.identifier.obd43931541
dc.identifier.uri2-s2.0-85099224482
dc.identifier.urihttp://hdl.handle.net/11025/45044
dc.language.isoenen
dc.project.IDLO1506/PUNTIS - Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnostcs
dc.publisherMDPIen
dc.relation.ispartofseriesRemote Sensingen
dc.rights© MDPIen
dc.rights.accessopenAccessen
dc.subject.translatedGRACEen
dc.subject.translatedGRACE-FOen
dc.subject.translateddata assimilationen
dc.subject.translatedvertical displacementen
dc.subject.translatedGPSen
dc.subject.translatedMODISen
dc.subject.translatedflooden
dc.subject.translatedCentral South-East Asiaen
dc.titleThe Assessment of Hydrologic- and Flood-Induced Land Deformation in Data-Sparse Regions Using GRACE/GRACE-FO Data Assimilationen
dc.typečlánekcs
dc.typearticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

Files