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Çѱ¹¼öÀÚ¿øÇÐȸ / v.39, no.1, 2006³â, pp.79-88
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´ëûȣ »ó·ù ÇÏõ¿¡¼ °¿ì½Ã ÇÏõ ¼ö¿Â º¯µ¿ Ư¼º ¹× ¿¹Ãø ¸ðÇü °³¹ß
( River Water Temperature Variations at Upstream of Daecheong Lake During Rainfall Events and Development of Prediction Models ) |
| Á¤¼¼¿õ;¿ÀÁ¤±¹; ÃæºÏ´ëÇб³ ȯ°æ°øÇаú;ÃæºÏ´ëÇб³ ȯ°æ°øÇаú;
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| °¿ì½Ã Àú¼öÁö·Î À¯ÀÔÇϴ Ź¼öÀÇ ½Ã°ø°£ºÐÆ÷¸¦ ½Ç½Ã°£À¸·Î ¿¹ÃøÇϱâ À§Çؼ´Â ÇÏõ À¯ÀÔ¼ö ¼ö¿ÂÀÇ Á¤È®ÇÑ ¿¹ÃøÀÌ ÇÊ¿äÇÏ´Ù. º» ¿¬±¸¿¡¼´Â °¿ì½Ã ÇÏõ ¼ö¿ÂÀÇ º¯µ¿Æ¯¼ºÀ» Á¶»çÇϱâ À§ÇØ 2004³â È«¼ö±â µ¿¾È ´ëûȣ »ó·ù ÇÏõ¿¡¼ ÇÑ ½Ã°£ ´ÜÀ§ÀÇ ¿¬¼ÓÃøÁ¤À» ½Ç½ÃÇÏ¿´´Ù. °¿ì»ç»ó µ¿¾È ÇÏõ¼ö¿ÂÀº °¿ì Àü º¸´Ù ÃÖ´ë $5sim10^{circ}C$ Á¤µµ ÇϰÇÏ´Â °ÍÀ¸·Î ³ªÅ¸³µÀ¸¸ç, À̰ÍÀº Àú¼öÁö·Î À¯ÀÔÇÏ´Â ÇÏõ¼öÀÇ ¹Ðµµ¸¦ $1.2sim2.6$ tcg/$m^3$ ($0.12sim0.26%$) »ó½Â½ÃÄÑ ÁßÃþ ¹Ðµµ·ù¸¦ Çü¼ºÇÏ´Â ¿øÀÎÀ¸·Î ÀÛ¿ëÇß´Ù. ½ÇÃøÀڷḦ ÀÌ¿ëÇÏ¿© µÎ °¡Áö Á¾·ùÀÇ Åë°èÇü ¼ö¿Â ¿¹Ãø¸ðÇüÀÎ ·ÎÁö½ºÀû¸ðÇü(DLG)°ú ´ÙÁßȸ±Í¸ðÇü(DMR-1, DMR-2, DMR-3)À» °³¹ßÇÏ¿´´Ù. ¸ðµç ¸ðÇüµéÀÌ °¿ì-À¯Ãâ »ç»ó¿¡ µû¸¥ ÇÏõ ¼ö¿ÂÀÇ ±Þ°ÝÇÑ °ÇÏ Çö»óÀ» ºñ±³Àû Àß ¹¦»çÇÏ´Â °ÍÀ¸·Î ³ªÅ¸³µÀ¸³ª, ÀÏ Æò±Õ±â¿Â, À̽½Á¡ ¿Âµµ ±×¸®°í ÇÏõ À¯·®À» ¸ðÇüÀÇ µ¶¸³º¯¼ö·Î »ç¿ëÇÑ È¸±ÍÇü¸ðÇüÀÌ ´ë±â ±â¿Â°ú ÇÏõ ¼ö¿ÂÀÇ ·ÎÁö½ºÆ½ ÇÔ¼ö°ü°è¸¦ °¡Á¤ÇÑ DLG¸ðÇüº¸´Ù ¼ö¿Â¿¹Ãø ¼º´ÉÀÌ º¸´Ù ¿ì¼öÇÑ °ÍÀ¸·Î Æò°¡µÇ¾ú´Ù. |
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| An accurate prediction of inflow water temperature is essentially required for real-time simulation and analysis of rainfall-induced turbidity æïos in a reservoir. In this study, water temperature data were collected at every hour during the flood season of 2004 at the upstream of Daecheong Reservoir to justify its characteristics during rainfall event and model development. A significant drop of river water temperature by 5 to $10^{circ}C$ was observed during rainfall events, and resulted in the development of density flow regimes in the reservoir by elevating the inflow density by 1.2 to 2.6 kg/$m^3$ Two types of statistical river water temperature models, a logistic model(DLG) and regression models(DMR-1, DMR-2, DMR-3) were developed using the field data. All models are shown to reasonably replicate the effect of rainfall events on the water temperature drop, but the regression models that include average daily air temperature, dew point temperature, and river flow as independent variables showed better predictive performance than DLG model that uses a logistic function to determine the air to water relation. |
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| Ű¿öµå |
| ÇÏõ¼ö¿Â;ȸ±Í¸ðÇü;·ÎÁö½ºÆ½¸ðÇü;Àú¼öÁö ʼö;¹Ðµµ·ù;River Water Temperature;Regression models;Logistic model;Reservoir Turbidity Flow;Density flow; |
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Çѱ¹¼öÀÚ¿øÇÐȸ³í¹®Áý / v.39, no.1, 2006³â, pp.79-88
Çѱ¹¼öÀÚ¿øÇÐȸ
ISSN : 1226-6280
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO200612842600146)
¾ð¾î : Çѱ¹¾î |
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| ³í¹® Á¦°ø : KISTI Çѱ¹°úÇбâ¼úÁ¤º¸¿¬±¸¿ø |
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