• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.743-748
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• 2005

김남원 등(2004a, b)에 의해 개발된 SWAT-MODFLOW 모형은 SWAT 모형과 MODFLOW 모형의 Recharge Package와 River Package를 직렬로 연결한 모형이다. 그러나 MODFLOW 모형에는 지하수 흐름방정식의 해석에 관련된 Package를 제외하더라도 Well, Drain, Evapotranspiration 등의 Package가 더 있어 대수층으로부터의 우물의 함양과 배출, 배수관을 통한 지하수의 배출, 지하수의 증발산으로 인한 손실 등을 수행할 수 있다. MODFLOW 모형의 Well Package는 SWAT 모형에서 대수층의 물이동, Drain Package는 SWAT 모형의 토관배수, Evapotranspiration Package는 SWAT 모형의 얕은 대수층에서의 증발산과 밀접한 관계가 있다. 본 연구에서는 이들 세 개의 Package를 SWAT 모형과 완전 연동시킴으로써 사용자가 좀 더 다양한 조건에 대하여 SWAT-MODFLOW 결합모형을 적용할 수 있도록 기능을 향상시켰다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.2
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• pp.62-72
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• 2017

Spatio-temporal projection of evapotranspiration over croplands would be useful for assessment of climate change impact and development of adaptation strategies in agriculture. Potential evapotranspiration (PET) and dryness index (DI) during rice growing seasons were calculated using climate change scenario data provided by the National Institute of Meteorological Research (NIMR). A data processing tool for gridded climate data files, readGrADSWrapper, was used to calculate PET and DI during the current (1986-2005) and future (2006-2100) periods. Scripts were written to implement the formulas of PET and DI in R, which is an open source statistical data analysis tool. Evapotranspiration in rice fields ($PET_{Rice}$) was also determined using R scripts. The Spatio-temporal patterns of PET differed by regions in Korean Peninsula under current and future climate conditions. Overall, PET and $PET_{Rice}$ tended to increase throughout the $21^{st}$ century. Those results suggested that region-specific water resource managements would be needed to minimize the risk of water loss in the regions where considerable increases in PET would occur under the future climate conditions. For example, a number of provinces classified as a humid region were projected to become a sub-humid region in the future. The Spatio-temporal assessment of water resources based on PET and DI would help the development of climate change adaptation strategies for rice production in the 21st century. In addition, the studies on climate change impact would be facilitated using specialized data tools, e.g., readGrADSWrapper, for geospatial analysis of climate data.