CGSpaceA Repository of Agricultural Research Outputs
    View Item 
    •   CGSpace Home
    • International Water Management Institute (IWMI)
    • IWMI Journal Articles
    • View Item
       
    • CGSpace Home
    • International Water Management Institute (IWMI)
    • IWMI Journal Articles
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka

    Thumbnail
    
    Authors
    Yoshimoto, Shuhei
    Amarnath, Giriraj
    Date
    2017
    Language
    en
    Type
    Journal Article
    Review status
    Peer Review
    Accessibility
    Open Access
    Metadata
    Show full item record
    Share
    Citation
    Yoshimoto, Shuhei; Amarnath, Giriraj. 2017. Applications of satellite-based rainfall estimates in flood inundation modeling: a case study in Mundeni Aru River Basin, Sri Lanka. Remote Sensing, 9(10):1-16. doi: 10.3390/rs9100998
    Permanent link to cite or share this item: http://hdl.handle.net/10568/89283
    DOI: http://dx.doi.org/10.3390/rs9100998
    Abstract/Description
    The performance of Satellite Rainfall Estimate (SRE) products applied to flood inundation modelling was tested for the Mundeni Aru River Basin in eastern Sri Lanka. Three SREs (PERSIANN, TRMM, and GSMaP) were tested, with the Rainfall-Runoff-Inundation (RRI) model used as the flood inundation model. All the SREs were found to be suitable for applying to the RRI model. The simulations created by applying the SREs were generally accurate, although there were some discrepancies in discharge due to differing precipitation volumes. The volumes of precipitation of the SREs tended to be smaller than those of the gauged data, but using a scale factor to correct this improved the simulations. In particular, the SRE, i.e., the GSMaP yielding the best simulation that correlated most closely with the flood inundation extent from the satellite data, was considered the most appropriate to apply to the model calculation. The application procedures and suggestions shown in this study could help authorities to make better-informed decisions when giving early flood warnings and making rapid flood forecasts, especially in areas where in-situ observations are limited.
    CGIAR Affiliations
    Climate Change, Agriculture and Food Security; Water, Land and Ecosystems
    AGROVOC Keywords
    SATELLITE OBSERVATION; RAINFALL PATTERNS; FLOODING; MONITORING; RAINFALL-RUNOFF RELATIONSHIPS; MODELS; RIVER BASINS; PRECIPITATION; FORECASTING; CASE STUDIES
    Regions
    ASIA; SOUTH ASIA
    Collections
    • CCAFS Journal Articles [811]
    • IWMI Journal Articles [1929]

    AboutSend Feedback
     

    My Account

    LoginRegister

    Browse

    All of CGSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesBy AGROVOC keywordBy ILRI subjectBy CPWF subjectBy CCAFS subjectBy CIFOR subjectBy IWMI subjectBy RegionBy CountryBy SubregionBy CRP subjectBy River basinBy Output typeBy CTA subjectBy WLE subjectBy Bioversity subjectBy CIAT subjectBy CIP subjectBy animal breedBy CGIAR System subjectThis CollectionBy Issue DateAuthorsTitlesBy AGROVOC keywordBy ILRI subjectBy CPWF subjectBy CCAFS subjectBy CIFOR subjectBy IWMI subjectBy RegionBy CountryBy SubregionBy CRP subjectBy River basinBy Output typeBy CTA subjectBy WLE subjectBy Bioversity subjectBy CIAT subjectBy CIP subjectBy animal breedBy CGIAR System subject

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    AboutSend Feedback