¶óÆæÆ®¦¢Ä«Æä¦¢ºí·Î±×¦¢´õº¸±â
¾ÆÄ«µ¥¹Ì Ȩ ¸í»çƯ°­ ´ëÇבּ¸½Ç޹æ Á¶°æ½Ç¹« µ¿¿µ»ó°­ÀÇ Çѱ¹ÀÇ ÀüÅëÁ¤¿ø ÇÐȸº° ³í¹®
ÇÐȸº° ³í¹®

Çѱ¹°Ç¼³°ü¸®ÇÐȸ
Çѱ¹°ÇÃà½Ã°øÇÐȸ
Çѱ¹µµ·ÎÇÐȸ
Çѱ¹»ý¹°È¯°æÁ¶ÀýÇÐȸ
Çѱ¹»ýÅÂÇÐȸ
Çѱ¹¼öÀÚ¿øÇÐȸ
Çѱ¹½Ä¹°ÇÐȸ
Çѱ¹½Ç³»µðÀÚÀÎÇÐȸ
Çѱ¹ÀÚ¿ø½Ä¹°ÇÐȸ
Çѱ¹ÀܵðÇÐȸ
Çѱ¹Á¶°æÇÐȸ
Çѱ¹Áö¹Ý°øÇÐȸ
Çѱ¹ÇÏõȣ¼öÇÐȸ
Çѱ¹È¯°æ»ý¹°ÇÐȸ
Çѱ¹È¯°æ»ýÅÂÇÐȸ

Çѱ¹¼öÀÚ¿øÇÐȸ / v.37, no.10, 2004³â, pp.813-822
Æ÷¾Æ¼Û°úÁ¤À» ÀÌ¿ëÇÑ °¡¹³ÀÇ °ø°£ºÐÆ÷ ºÐ¼®
( Analysis of Drought Spatial Distribution Using Poisson Process )
À¯Ã¶»ó;¾ÈÀçÇö;·ù¼Ò¶ó; °í·Á´ëÇб³ Åä¸ñȯ°æ°øÇаú;¼­°æ´ëÇб³ Åä¸ñ°øÇаú;Çѱ¹¼öÀÚ¿ø°ø»ç ¼öÀÚ¿ø¿¬±¸¼Ò ¼öÀÚ¿ø¿¬±¸ºÎ;
 
ÃÊ ·Ï
º» ¿¬±¸¿¡¼­´Â °æ±âµµ Áö¿ªÀ» Áß½ÉÀ¸·Î °üÃøÀÚ·á·Î ºÎÅÍ ¾Æ¿ï·¯ Æ÷¾Æ¼Û °úÁ¤À» Àû¿ëÇÏ¿© °¡¹³ÀÇ ÀçÇö ¹× Áö¼ÓƯ¼ºÀ» Á¤·®È­ÇÏ°í ±× °ø°£ºÐÆ÷¸¦ ºñ±³ ºÐ¼®ÇØ º¸¾Ò´Ù. º» ¿¬±¸¿¡¼­´Â °üÃøµÈ ¿ù °­¼ö·® ÀڷḦ °¡¹³Áö¼öÀÎ SPI·Î º¯È¯ÇÏ¿© ºÐ¼®¿¡ ÀÌ¿ëÇÏ¿´´Ù. ƯÈ÷, °¡¹³ÀÇ °ø°£ºÐÆ÷ Ư¼º ÆÄ¾ÇÀ» À§ÇØ °üÃø±æÀ̰¡ ¼­·Î ´Ù¸¥ ÀÚ·á¿¡ Æ÷¾Æ¼Û °úÁ¤À» Àû¿ëÇÏ´Â °æ¿ìÀÇ Àå¤ý´ÜÁ¡ µîÀ» ÆÄ¾ÇÇØ º¸°íÀÚ ÇÏ¿´´Ù. º» ¿¬±¸ÀÇ °á°ú¸¦ ¿ä¾àÇÏ¸é ´ÙÀ½°ú °°´Ù. (1) Æ÷¾Æ¼Û °úÁ¤À» ÀÌ¿ëÇÑ °¡¹³ÀÇ Á¤·®È­´Â ƯÈ÷ °üÃø±â·ÏÀÌ ÂªÀº °æ¿ì¿¡ À¯¸®ÇÑ °ÍÀ¸·Î ³ªÅ¸³µ´Ù. °ø°£ÀûÀ¸·Î °¡±î¿î À§Ä¡¿¡ ÀÖ´Â µÎ ÁöÁ¡ÀÇ Æ¯¼ºÀÌ °üÃø±â·ÏÀÇ ±æÀÌ¿¡ ´ú ¹Î°¨ÇØ Áü¿¡ µû¶ó ÀüüÀûÀ¸·Î À¯»çÇÑ Æ¯¼ºÀ» ³ªÅ¸³¿À» È®ÀÎÇÒ ¼ö ÀÖ¾ú´Ù. (2) ÁöÁ¡º° °üÃø±â·ÏÀÇ ±æÀ̰¡ Å©°Ô ´Ù¸¥ °æ¿ì ¸ðÇü¿¡ ÀÇÇÑ °¡¹³ÀÇ °ø°£Àû Ư¼º ÆÄ¾ÇÀÌ ´Ü¼øÈ÷ °üÃøÀڷḦ ÀÌ¿ëÇÑ °æ¿ì¿¡ ºñÇØ ¿ì¿ùÇÒ ¼ö ÀÖ´Ù. º» ¿¬±¸ÀÇ °æ¿ì¿¡ À־µµ ¸ðÇüÀ» ÀÌ¿ëÇÑ °æ¿ì °¡¹³ÀÇ °ø°£ºÐÆ÷°¡ °üÃøÀ» Á÷Á¢ ºÐ¼®ÇÏ¿© ¾òÀº °¡¹³ÀÇ °ø°£ºÐÆ÷º¸´Ù ¶Ñ·ÇÇÏ°Ô ³ªÅ¸³²À» È®ÀÎÇÒ ¼ö ÀÖ¾ú´Ù.
This study quantifies and compares the drought return and duration characteristics by applying the Poisson process as well as based on by analyzing the observed data directly. The drought spatial distributions derived for the Gyunggi province are also compared. The monthly rainfall data are used to construct the SPI as a drought index. Especially, this study focuses on the evaluation of the Poisson process model when applying it to various data lengths such as in the spatial analysis 'of drought. Summarizing the results are as follows. (1) The Poisson process is found to be effective for the quantification of drought, especially when the data length is short. When applying the Poisson process, two neighboring sites are found insensitive to the data length to show similar drought characteristics, so the overall drought pattern becomes smoother than that derived directly from the observed data. (2) When the data length is very different site by site, the spatial analysis of drought based on a model application seems better than that based on the direct data analysis. This study also found more obvious spatial pattern of drought occurrence and duration when applying the Poisson process.
 
Ű¿öµå
Ç¥Áذ­¼öÁö¼ö;°¡¹³;ÀçÇöƯ¼º;Áö¼ÓƯ¼º;Æ÷¾Æ¼Û °úÁ¤;°ø°£ºÐÆ÷;Standardized Precipitation Index;Drought;Return;Duration;Poisson process;spatial distribution;
 
Çѱ¹¼öÀÚ¿øÇÐȸ³í¹®Áý / v.37, no.10, 2004³â, pp.813-822
Çѱ¹¼öÀÚ¿øÇÐȸ
ISSN : 1226-6280
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO200411922948738)
¾ð¾î : Çѱ¹¾î
³í¹® Á¦°ø : KISTI Çѱ¹°úÇбâ¼úÁ¤º¸¿¬±¸¿ø
¸ñ·Ïº¸±â
ȸ»ç¼Ò°³ ±¤°í¾È³» ÀÌ¿ë¾à°ü °³ÀÎÁ¤º¸Ãë±Þ¹æÄ§ Ã¥ÀÓÀÇ ÇѰè¿Í ¹ýÀû°íÁö À̸ÞÀÏÁÖ¼Ò ¹«´Ü¼öÁý °ÅºÎ °í°´¼¾ÅÍ
   

ÇÏÀ§¹è³ÊÀ̵¿