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  <titleInfo>
    <title>Heuristic relation between point rainfall and meteorological factors</title>
  </titleInfo>
  <name type="personal">
    <namePart>Chalinee Prajakthum</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Prida Thimakorn</namePart>
    <role>
      <roleTerm type="text">Chairperson</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Hoshi, Kiyoshi</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Huynh, Ngoc Phien</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>Self--support</namePart>
    <role>
      <roleTerm type="text">Scholarship Donor</roleTerm>
    </role>
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  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">th</placeTerm>
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    <place>
      <placeTerm type="text">Bangkok</placeTerm>
    </place>
    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>1983</dateIssued>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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    <extent>119 p.</extent>
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  <abstract>The point-rainfall calibrating and forecasting models are developed and applied for Khonkhan station by using the empirical GMDH (Group Method of Data Handling) model. It is considered as a semi-causal model in a deterministic sense , though the actual times of occurance are defined as a day  or duration of day , it emphasizes on magnitude at that actual time than to  predict in a probabilistic sense in tension probability of occurance or in a stochastic sense with emphasis on the probability of the sequences of events. The causal input variables are acquired by other meteorological  parameters at the same station, The accuracy of the model performance on calibration and forecasting is tested by applying them to perform rainfall  calibration for daily , 5 , 6 , and 7 days and rainfall forecasting for those duration 5, 6 and 7 days during the years 1970-1980. The accuracy of the model performance depends mainly upon, i) rainfall condition: such as distribution, fluctuation and variation etc. ii) the relationship between rainfall and each meteorological input variables, and iii) the numerical technique applied to solve the problems. The accuracy of the models are  evaluated by means of root mean square error, percentage of error and coefficient of correlation. The analysis of the model signified the acceptable performance of the model in calibration of those duration 5 ,  6, and 7 days. In case of daily calibration the insignificant results are due to the rather wider fluctuation. That is the coefficients of variation are more than 1.0 . The basic heuristics considered in this study  and also limitation of the empirical models impose difficulties in forecasting the nonstationary phenomena of rainfall. </abstract>
  <note>A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Engineering and Technology</note>
  <note>Thesis (M.Eng.) - Asian Institute of Technology, 1983</note>
  <subject authority="lcsh">
    <topic>Rain and rainfall</topic>
  </subject>
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    <titleInfo>
      <title>Thesis ; no. WA-84-15</title>
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      <namePart>Asian Institute of Technology.</namePart>
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  <identifier type="uri">http://203.159.5.9/ait-thesis/detail.php?q=B21031</identifier>
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    <url displayLabel="Full-Text">http://203.159.5.9/ait-thesis/detail.php?q=B21031</url>
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