Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling

dc.contributor.authorSetti, Sridharaen
dc.contributor.authorMaheswaran, Rathinasamyen
dc.contributor.authorSridhar, Venkataramanaen
dc.contributor.authorBarik, Kamal Kumaren
dc.contributor.authorMerz, Brunoen
dc.contributor.authorAgarwal, Ankiten
dc.contributor.departmentBiological Systems Engineeringen
dc.date.accessioned2020-11-30T12:49:53Zen
dc.date.available2020-11-30T12:49:53Zen
dc.date.issued2020-11-20en
dc.date.updated2020-11-26T14:08:33Zen
dc.description.abstractPrecipitation is essential for modeling the hydrologic behavior of watersheds. There exist multiple precipitation products of different sources and precision. We evaluate the influence of different precipitation product on model parameters and streamflow predictive uncertainty using a soil water assessment tool (SWAT) model for a forest dominated catchment in India. We used IMD (gridded rainfall dataset), TRMM (satellite product), bias-corrected TRMM (corrected satellite product) and NCEP-CFSR (reanalysis dataset) over a period from 1998&ndash;2012 for simulating streamflow. The precipitation analysis using statistical measures revealed that the TRMM and CFSR data slightly overestimate rainfall compared to the ground-based IMD data. However, the TRMM estimates improved, applying a bias correction. The Nash&ndash;Sutcliffe (and <inline-formula><math display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup></mrow></semantics></math></inline-formula>) values for TRMM, TRMMbias and CFSR, are 0.58 (0.62), 0.62 (0.63) and 0.52 (0.54), respectively at model calibrated with IMD data (Scenario A). The models of each precipitation product (Scenario B) yielded Nash&ndash;Sutcliffe (and <inline-formula><math display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup></mrow></semantics></math></inline-formula>) values 0.71 (0.76), 0.74 (0.78) and 0.76 (0.77) for TRMM, TRMMbias and CFSR datasets, respectively. Thus, the hydrological model-based evaluation revealed that the model calibration with individual rainfall data as input showed increased accuracy in the streamflow simulation. IMD and TRMM forced models to perform better in capturing the streamflow simulations than the CFSR reanalysis-driven model. Overall, our results showed that TRMM data after proper correction could be a good alternative for ground observations for driving hydrological models.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationSetti, S.; Maheswaran, R.; Sridhar, V.; Barik, K.K.; Merz, B.; Agarwal, A. Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling. Atmosphere 2020, 11, 1252.en
dc.identifier.doihttps://doi.org/10.3390/atmos11111252en
dc.identifier.orcidSridhar, Venkataramana [0000-0002-1003-2247]en
dc.identifier.urihttp://hdl.handle.net/10919/100963en
dc.identifier.volume11en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectparameter and prediction uncertaintyen
dc.subjectIMDen
dc.subjectTRMMen
dc.subjectCFSRen
dc.subjectNagavali River Basin Region (NRB)en
dc.titleInter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modelingen
dc.title.serialAtmosphereen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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