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  <titleInfo>
    <title>Assessment of the ungauge  rainfall forecasting using SDSM-GIS</title>
  </titleInfo>
  <name type="personal">
    <namePart>Nur Awatif Ahmad Shukri</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
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  <genre authority="marc">abstract or summary</genre>
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    <dateIssued encoding="marc">2019</dateIssued>
    <copyrightDate encoding="marc">2019</copyrightDate>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
    <extent>xi , 84 pages : illustrations ; 30 cm. + 1 CD-ROM</extent>
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  <abstract>An accuracy in the hydrological modelling will be effected when having limited data sources  especially  at  ungauged  areas.  Due  to  this  matter,  it  will  not  receiving  any significant attention especially on the potential hydrologic extremes.  Three of rainfall stations Pam Paya Pinang station, Paya Besar station and Kg. Sg. Soi acr oss Kuantan river were considered  in this research.  Thus, the objective was to analyses the accuracy of the long-term projected rainfall at ungauged rainfall station using integrated SDSM GIS model. The SDSM was used as a climate agent to predict the changes of the climate trend  in  ∆ 2030s  by  gauged  stations.  Five  predictors  were  selected  to  form  the  local climate  at  the  region  which  provided  by  NCEP  (validated)  and  CanESM2-RCP4.5 (projected). According to the statistical analyses, the SDSM was successfully  to produced reliable validated results with lesser % MAE (&lt;23%) and higher R (1.0). The projected rainfall was suspected to decrease 14% in ∆2030s. These findings then used to compare the accuracy of monthly  rainfall at ungauged station (Stn 2). The GIS-Kriging method being  as  an  interpolation  agent  to  treat  Stn  2.  Meanwhile,  the  next  objective  was  to estimate the accuracy of the forecasted monthly rainfall using Kriging-GIS interpolation. Comparing between ungauged and gauged stations, the small %MAE in the projected monthly results between gauged and ungauged stations as a proved the integrated SDSMGIS model can producing a reliable long-term rainfall generation at ungauged station(station  2).  Based  on  the  performance  GIS  interpolation,  for  the  result  its  historical rainfall  (JPS)  and  projected  rainfall  between  gauged  and  ungauged  stations  can  be accepted because the difference in percentage error of MAE is less than 30%. In July was recorded value with higher  error in MAE with 26.6% for historical rainfall. While the higher error for projected rainfall is 25.81% which happened in December.</abstract>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <note type="statement of responsibility">Nur Awatif Ahmad Shukri</note>
  <note>Faculty of Civil Engineering and Earth Resources</note>
  <note>Project Paper (Bachelors of Civil Engineering) -- Universiti Malaysia Pahang – 2019</note>
  <note>Includes bibliographical references</note>
  <subject authority="lcsh">
    <name type="corporate">
      <namePart>Faculty of Civil Engineering and Earth Resources</namePart>
    </name>
    <topic>Dissertations</topic>
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  <subject authority="lcsh">
    <topic>Universities and Colleges</topic>
    <topic>Dissertations</topic>
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  <subject authority="lcsh">
    <topic>Theses</topic>
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  <identifier type="isbn">THE0008298(Local)</identifier>
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    <recordCreationDate encoding="marc">191010</recordCreationDate>
    <recordChangeDate encoding="iso8601">20251125105401.0</recordChangeDate>
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      <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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