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산간 계곡의 지하배수관 설치에 따른 벼 냉수피해 사례분석
심교문 ( Kyomoon Shim ),정명표 ( Myungpyo Jung ),김용석 ( Yongseok Kim ),최인태 ( Intae Choi ) 한국농림기상학회 2015 한국농림기상학회지 Vol.17 No.3
산간지역의 계곡 물길의 매립과 지하배수관의 설치에 따른 인근 논에서 벼 냉수해에 대한 민원이 제기되어 벼 냉수해와 지하배수관 설치의 연관성 유무을 파악하기 위해서 현장조사 및 분석을 실시하였다. 결론적으로 지하배수관 설치로 인하여 계곡물의 온도가 지하배수관 설치 전보다 0.5~4.5℃ 범위로 낮아진 것으로 분석되었고, 이 냉수를 농업용수로 관개한 하류쪽 논에서는 벼 냉수해가 발생할 가능성이 매우 높았을 것으로 판단되었다. 따라서, 적절한 수온상승 조치를 취하지 않으면 냉수해로 인하여 정상적인 수확이 불가능할 것으로 평가되었다. The complaint was filed for the cold water damage to rice in accordance with the installation of buried drain pipes in the mountainous areas of the valley. Field research was conducted in order to identify and analyze relevance of cold water damage to rice with underground drain pipe installation. In conclusion, water temperature was analyzed by 0.5 to 4.5℃ lower than before the installation of underground drain pipes, so the cold water damage to rice was likely to occur at the rice paddy field using cold water passing through the underground drain pipe. Therefore, the rice harvest was estimated to be impossible without appropriate measures of water temperature rise such as use of small unshaded warming basins, before water is applied to fields.
Kim, Hojung,Shim, Kyomoon International Journal of Agricultural and Biologic 2018 IJABE Vol.11 No.2
<P>Apples (Malus domestica) are one of the major fruits cultivated in South Korea and worldwide. To both sustain the productivity of apple trees and preserve the land, a land suitability assessment has been conducted. Two methods were used to analyze land suitability, a Most-Limiting Characteristic Method (MLCM) and an Analytic Hierarchy Process (AHP) with integrated soil and climate information based on the FAO classification framework. The most-limiting characteristic analysis showed that almost all areas were classified as marginally suitable (S3) or not suitable (N), which together accounted for 94.54% of the land in the Republic of Korea. On the contrary, AHP showed that S1 (34.1%) and S2 (44.17%) account for the majority of the land.</P>
정명표 ( Myungpyo Jung ),심교문 ( Kyomoon Shim ),김용석 ( Yongseok Kim ),최인태 ( Intae Choi ) 한국환경농학회 2015 한국환경농학회지 Vol.34 No.3
BACKGROUND: The growing season (GS) has been understood as a useful indicator for climate change due to high relationship with increasing temperature. Hear this study was conducted to examine changes in the thermal GS over South Korea from 1970 to 2013 based on daily mean air temperature for assessing the temporal and spatial variability in GS. METHODS AND RESULTS: Three GS parameters (starting date, ending date, and length) were determined at 19 stations throughout South Korea. The results show that the GS has been extended by 4.2 days/decade between 1970 and 2013 on average. The growing season start (GSS) has been advanced by 2.7 days/decade and the growing season end (GSE) has been delayed by 1.4 day/decade. Spatial variation in the GS parameters in Korea are shown. The GS parameters, especially GSS, of southeastern part of Korea have been changed more than that of northwestern part of Korea. The extension of GS may be more influenced on earlier onset in spring rather than later GSE. CONCLUSION: Under climate change scenarios, the GS will be more extended due to delayed GSE as well as advanced GSS. And These are more notable in the northeastern part of Korea.
BESS-Rice: A remote sensing derived and biophysical process-based rice productivity simulation model
Huang, Yan,Ryu, Youngryel,Jiang, Chongya,Kimm, Hyungsuk,Kim, Soyoun,Kang, Minseok,Shim, Kyomoon Elsevier 2018 Agricultural and forest meteorology Vol.256 No.-
<P><B>Abstract</B></P> <P>Conventional process-based crop simulation models and agro-land surface models require numerous forcing variables and input parameters. The regional application of these crop simulation models is complicated by factors concerning input data requirements and parameter uncertainty. In addition, the empirical remotely sensed regional scale crop yield estimation method does not enable growth process modeling. In this study, we developed a process-based rice yield estimation model by integrating an assimilate allocation module into the satellite remote sensing-derived and biophysical process-based Breathing Earth System Simulator (BESS). Normalized accumulated gross primary productivity ( <SUB> G P P n o r m - a c c u </SUB> ) was used as a scaler for growth development, and the relationships between <SUB> G P P n o r m - a c c u </SUB> and dry matter partitioning coefficients were determined from the eddy covariance and biometric measurements at the Cheorwon Rice paddy KoFlux site. Over 95% of the variation in the dry matter allocation coefficients of rice grain could be explained by <SUB> G P P n o r m - a c c u </SUB> . The dynamics of dry matter distribution among different rice components were simulated, and the annual grain yields were estimated. BESS-Rice simulated GPP and dry matter partitioning dynamics, and rice yields were evaluated against <I>in-situ</I> measurements at three paddy rice sites registered in KoFlux. The results showed that BESS-Rice performed well in terms of rice productivity estimation, with average root mean square error (RMSE) value of 2.2 g C m<SUP>−2</SUP> d<SUP>−1</SUP> (29.5%) and bias of –0.5 g C m<SUP>−2</SUP> d<SUP>−1</SUP> (–7.1%) for daily GPP, and an average RMSE value of 534.8 kg ha<SUP>−1</SUP> (7.7%) and bias of 242.1 kg ha<SUP>−1</SUP> (3.5%) for the annual yield, respectively. BESS-Rice is much simpler than conventional crop models and this helps to reduce the uncertainty related to the forcing variables and input parameters and can result in improved regional yield estimation. The process-based mechanism of BESS-Rice also enables an agronomic diagnosis to be made and the potential impacts of climate change on rice productivity to be investigated.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Developed a remote sensing derived and process-based rice model (BESS-Rice). </LI> <LI> Used normalized accumulated gross primary productivity to simulate C allocation. </LI> <LI> BESS-Rice performed well in GPP and rice yield estimation. </LI> </UL> </P>