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Çѱ¹¼öÀÚ¿øÇÐȸ / v.36, no.2, 2003³â, pp.315-324
ÇѰ­À¯¿ªÀÇ È®·ü°¥¼ö·® ÃßÁ¤±â¹ý ºñ±³¿¬±¸
( A Comparative Study on Lowflow Quantiles Estimation in Han River Basin )
±è°æ´ö;±èµ·¼ö;ÇãÁØÇà;±è±ÔÈ£; Çѱ¹½Ã¼³¾ÈÀü±â¼ú°ø´Ü Áø´Ü2º»ºÎ ´ïÇ׸¸½Ç;°Ç¼³±³ÅëºÎ ¿¹»ê´ã´ç°ü;¿¬¼¼´ëÇб³ »çȸȯ°æ½Ã½ºÅÛ°øÇкÎ;Çѱ¹°Ç¼³±â¼ú¿¬±¸¿ø ¼öÀÚ¿øÈ¯°æºÎ;
 
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ÇÏõÀ¯ÁöÀ¯·® ¼³Á¤¿¡ ÃÖ¼ÒÇÑÀÇ ±âÁØÀÌ µÇ´Â °¥¼ö·®À» °áÁ¤Çϱâ À§ÇÏ¿© ÇÏõÀ¯·® ÀڷḦ °ËÅäÇϰí È®·ü°¥¼ö·®À» ÃßÁ¤ÇÏ¿´´Ù. È®·ü°¥¼ö·®Àº ¸ð¼öÀû ¹æ¹ý°ú ºñ¸ð¼öÀû ¹æ¹ýÀ» »ç¿ëÇÏ¿© »êÁ¤ÇÏ¿´À¸¸ç, Monte Carlo ¸ðÀǽÇÇèÀ» ÅëÇÏ¿© ºñ±³¡¤ºÐ¼®ÇÏ¿´´Ù. ÇѰ­À¯¿ª 13°³ ÁöÁ¡ÀÇ °¥¼ö·®¿¡ ´ëÇÑ ºóµµ ÇØ¼®À» ½Ç½ÃÇÑ °á°ú, À¯¿ª Àüü¿¡ ´ëÇÑ È®·üºÐÆ÷ ÇüÀº 3°¡Áö ºÐÆ÷Çü, Áï 2¸ð¼ö gamma, 2¸ð¼ö lognormal, ±×¸®°í 2¸ð¼ö Weibull ºÐÆ÷°¡ ÇѰ­ ÀüÁöÁ¡ÀÇ ÁÖ¿ä ºÐÆ÷ÇüÀ¸·Î ³ªÅ¸³µ´Ù. ¸ðÁý´Ü°ú °°Àº È®·üºÐÆ÷ÇüÀÇ »ó´ëÆíÀÇ¿Í »ó´ëÆò±ÕÁ¦°ö±Ù¿ÀÂ÷°¡ °¡Àå ÀÛ°Ô ³ªÅ¸³µÀ¸¸ç, ³»»ð¹ü À§¿¡¼­ ºñ¸ð¼öÀû ¹æ¹ýÀÌ Åë°èÀû °Åµ¿Æ¯¼º(»ó´ëÆíÀÇ¿Í »ó´ëÆò±ÕÁ¦°ö±Ù¿ÀÂ÷)ÀÌ ÁÁÀº °ÍÀ¸·Î ³ªÅ¸³µ´Ù. RRMSE¿¡ À־ ºñ¸ð¼öÀû ¹æ¹ýÁß¿¡¼­ PM ±â¹ýÀÌ °¡Àå ÀÛ°Ô ³ªÅ¸³µÀ¸¸ç, SJ ±â¹ýÀÌ ºñ¸ð¼öÀû ¹æ¹ý °¡¿îµ¥ °¡Àå Å©°Ô ³ªÅ¸³µ´Ù.
Stream flow data was analyzed for determining the lowflow which is the standard for river maintenance flow. Lowflow quantiles were estimated based on the parametric and nonparametric methods and two methods were compared by Monte Carlo simulation study. As the results of the parametric method, three probability distributions such as gamma-2, lognormal-2 and Weibull-2, are selected as appropriate models for stream flow data of 13 stations in Han River Basins. According to simulation results, relative bias (RBIAS) and relative root mean square error (RRMSE) of the lowflow quantiles are the smallest when the applied and population models are the same. The fame statistical properties from the nonparametric models are good within the interpolation range. Among 7 bandwidth selectors used in this study, the RRMSEs of the Park and Marron method (PM) are the smallest while those of the Shoaler and Jones method (SJ) are the largest.
 
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È®·ü°¥¼ö·®;¸ð¼öÀû ¹æ¹ý;ºñ¸ð¼öÀû ¹æ¹ý;Monte Carlo ¸ðÀǽÇÇè;»ó´ëÆíÀÇ;»ó´ëÆò±ÕÁ¦°ö±Ù¿ÀÂ÷;lowflow quantile;parametric method;nonparametic;method;Monte Carlo simulation;relative bias;relative;root mean square error;
 
Çѱ¹¼öÀÚ¿øÇÐȸ³í¹®Áý / v.36, no.2, 2003³â, pp.315-324
Çѱ¹¼öÀÚ¿øÇÐȸ
ISSN : 1226-6280
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO200311921618049)
¾ð¾î : Çѱ¹¾î
³í¹® Á¦°ø : KISTI Çѱ¹°úÇбâ¼úÁ¤º¸¿¬±¸¿ø
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ȸ»ç¼Ò°³ ±¤°í¾È³» ÀÌ¿ë¾à°ü °³ÀÎÁ¤º¸Ãë±Þ¹æÄ§ Ã¥ÀÓÀÇ ÇѰè¿Í ¹ýÀû°íÁö À̸ÞÀÏÁÖ¼Ò ¹«´Ü¼öÁý °ÅºÎ °í°´¼¾ÅÍ
   

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