• Korean Journal of Soil Science and Fertilizer
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• v.42 no.5
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• pp.348-354
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• 2009

We analyzed relationship soil distribution and climatic factors using temperature, precipitation and evapotranspiration maps in Jeju island. The whole area was divided into 5 groups - mesic high moisture region(group1), thermic high moisture region(group2), thermic balanced moisture region(group3), thermic short moisture region(group4), thermic very short moisture region(group5), by soil temperature and monthly moisture balances. By the sequence from group1 to group5, the occupation ratio of soils was increased in order of andisols, inceptisols, alfisols, ultisols in soil orders, and of black soils, very dark brown soils, dark brown soils in soil colors.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.283-290
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• 2015

This study was carried out a trend analysis for analyzing change of meteorological elements in the main producing areas of Chinese cabbage, radish, pepper, garlic and onion. As meteorological elements, we selected air temperature (maximum, minimum), precipitation and duration of sunshine. We used monthly data of meteorological elements obtained from the main producing areas of vegetables for 30 years from 1981 to 2010. Mann-Kendall test used for significance test of trend and Sen's estimator of slope for computing the variance of meteorological elements. The study results showed that air temperature tended to increase, but duration of sunshine tended to decrease in most regions.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.197-197
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• 2020

기후변화 연구의 주요 요소 중 하나는 온도, 강수량 및 증발과 같은 기후 요인의 변화를 연구하는 것이다. General Circulation Model(GCM)은 다양한 기후 요인의 변화를 연구하는 데 일반적으로 사용되고 있다. Coupled Model Intercomparison Project(CMIP)는 전 세계의 30여 개 이상의 기관에서 개발한 GCM의 모의 결과를 연구 및 공유하기 위해 개발되었다. 기후 연구에서 대표적으로 사용하고 있는 CMIP5의 GCM은 미래 시나리오인 Representative Concentration Pathway(RCP)를 기반으로 전망 기간의 기후요소를 예측한다. 현재 개발하고 있는 CMIP6의 미래 시나리오인 Shared Socioeconomic Pathways(SSP)는 인구, 경제개발, 생태계, 자원, 제도 및 사회적 요인에 대한 미래의 사회적, 경제적 변화에 따른 기후변화에 대한 대응을 포함하고 있으며, CMIP6의 미래 시나리오는 사회적 및 경제적 결합을 통해 기후변화에 대한 정책 영향에 대한 증진된 결과를 도출할 것으로 예측하고 있다. 따라서 본 연구는 CMIP5의 INM-CM4와 CMIP6의 INM-CM5를 사용하여 대한민국의 과거 기간(1970-2005)의 월 강수량에 대한 성능을 비교하였다. 격자형 자료인 GCM을 Inverse distance weight를 사용하여 대한민국 22개 관측소로 거리 보간을 수행하였으며, 편이보정 방법으로는 분위사상법(Quantile mapping) 방법 중 Smoothing Spline 방법을 사용하여 관측소와의 오차를 수정하였다. 산정된 강수량을 토대로 6개의 평가지표(NRMSE, Pbias, NSE, PRCP100, PRCP200, PRCP300)를 사용하여 GCM의 성능을 평가하여 INM-CM4와 INM-CM5의 성능을 비교하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.126-126
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• 2022

Climate change has continued to impact meteorological factors like rainfall in many countries including Nigeria. Thus, altering the rainfall patterns which subsequently affect the crop yield. Maize is an important cereal grown in northern Nigeria, along with sorghum, rice, and millet. Due to the challenge of water scarcity during the dry season, it has become critical to design appropriate strategies for planning, developing, and management of the limited available water resources to increase the maize yield. This study, therefore, determines the quantity of water required to produce maize from planting to harvesting and the impact of drought on maize during different growth stages in the region. Rainfall data from six rain gauge stations for a period of 36 years (1979-2014) was considered for the analysis. The standardized precipitation and evapotranspiration index (SPEI) is used to evaluate the severity of drought. Using the CROPWAT model, the evapotranspiration was calculated using the Penman-Monteith method, while the crop water requirements (CWRs) and irrigation scheduling for the maize crop was also determined. Irrigation was considered for 100% of critical soil moisture loss. At different phases of maize crop growth, the model predicted daily and monthly crop water requirements. The crop water requirement was found to be 319.0 mm and the irrigation requirement was 15.5 mm. The CROPWAT 8.0 model adequately estimated the yield reduction caused by water stress and climatic impacts, which makes this model appropriate for determining the crop water requirements, irrigation planning, and management.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.136-136
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• 2022

This study investigates the possibility of coupling empirical mode decomposition (EMD) for runoff prediction from machine learning (ML) models. Here, support vector regression (SVR) and convolutional neural network (CNN) were considered for ML algorithms. Precipitation (P), minimum temperature (Tmin), maximum temperature (Tmax) and their intrinsic mode functions (IMF) values were used for input variables at a monthly scale from Jan. 1973 to Dec. 2020 in the Grand river basin, Canada. The support vector machine-recursive feature elimination (SVM-RFE) technique was applied for finding the best combination of predictors among input variables. The results show that the proposed method outperformed the individual performance of SVR and CNN during the training and testing periods in the study area. According to the correlation coefficient (R), the EMD-SVR model outperformed the EMD-CNN model in both training and testing even though the CNN indicated a better performance than the SVR before using IMF values. The EMD-SVR model showed higher improvement in R value (38.7%) than that from the EMD-CNN model (7.1%). It should be noted that the coupled models of EMD-SVR and EMD-CNN represented much higher accuracy in runoff prediction with respect to the considered evaluation indicators, including root mean square error (RMSE) and R values.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.525-536
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• 2014

In this study, a method to assess and monitor hydrological drought using remote sensing was investigated for use in regions with limited observation data, and was applied to the Upper Namhangang basin in South Korea, which was seriously affected by the 2008-2009 drought. Drought information may be obtained more easily from meteorological data based on water balance than hydrological data that are hard to estimate. Air temperature data at 2 m above ground level (AGL) were estimated using remotely sensed data, evapotranspiration was estimated from the air temperature, and the correlations between precipitation minus evapotranspiration (P-PET) and streamflow percentiles were examined. Land Surface Temperature data with $1{\times}1km$ spatial resolution as well as Atmospheric Profile data with $5{\times}5km$ spatial resolution from MODIS sensor on board Aqua satellite were used to estimate monthly maximum and minimum air temperature in South Korea. Evapotranspiration was estimated from the maximum and minimum air temperature using the Hargreaves method and the estimates were compared to existing data of the University of Montana based on Penman-Monteith method showing smaller coefficient of determination values but smaller error values. Precipitation was obtained from TRMM monthly rainfall data, and the correlations of 1-, 3-, 6-, and 12-month P-PET percentiles with streamflow percentiles were analyzed for the Upper Namhan-gang basin in South Korea. The 1-month P-PET percentile during JJA (r = 0.89, tau = 0.71) and SON (r = 0.63, tau = 0.47) in the Upper Namhan-gang basin are highly correlated with the streamflow percentile with 95% confidence level. Since the effect of precipitation in the basin is especially high, the correlation between evapotranspiration percentile and streamflow percentile is positive. These results indicate that remote sensing-based P-PET estimates can be used for the assessment and monitoring of hydrological drought. The high spatial resolution estimates can be used in the decision-making process to minimize the adverse impacts of hydrological drought and to establish differentiated measures coping with drought.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.1
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• pp.17-28
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• 2007

This study was conducted to analyze the optimum heading period according to the recent climatic change for improvement of rice yield and grain quality in the Yeongnam area. We analyzed climatic elements including daily mean air temperature, daily range of air temperature, sunshine hours, and amount of precipitation from 1996 to 2005 in comparison with those of the 1971 to 2000 normal. Daily mean air temperature and amount of precipitation in the recent 10 years increased, but daily range of air temperature and sunshine hours decreased in comparison with the norm. Also, monthly mean air temperature was lowered remarkably in July and August. The monthly amount of precipitation largely increased in August and September. The daily range of air temperature and sunshine hours were greatly decreased from August to October, Possible cultivation periods for rice in the recent 10 years ranged from 171 days in Boughwa to 228 days in Busan and was expanded about $1{\sim}13$ days in comparison with the normal. Optimum heading date by local regions for the maximum climatic yield potential was estimated as July 31 at Bonghwa to September 7 at Busan, Masan, and Tongyeong in the recent 10 years. There was a wide difference in optimum heading date according to local legions of the Yeongnam area. Compared to the normal, optimum heading date in the recent 10 years was delayed about I~8 days in most local regions except Bonghwa, Mungyeong, and Yeongdeok. These results suggested that it is necessary to develop late maturity rice cultivars for producing high yield and quality rice grain due to the recent climatic change. Moreover, it is still more important to select the most suitable cultivation period appropriate to the changed climate of each local region in Yeongnam area.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.547-559
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• 2014

The objective of this study is to evaluate the performance of the complementary relationship-based evapotranspiration models, namely, advection-aridity (AA) model of Brutsaert and Stricker and the CRAE model of Morton for estimating actual evapotranspiration. Both models were applied to the Bokhacheon middle-upper watershed, and their estimates were evaluated against the water balance estimate. The calculation was made on a daily basis and comparison was made on monthly and annual bases. For comparison, the water balance estimates were not obtained from the observed precipitation and streamflow data but were based on the simulated data by using integrated watershed model, SWAT-K which is the revised version of SWAT. The reason not to directly use the observed data for water balance estimate is that the credible record period is not sufficient and the streamflow has been altered due to water use and release. Overall, the results showed that both AA model and CRAE model with their original parameters overestimate annual and monthly evapotranspiration, and the large difference between the complementary relationship-based approach and the water balance approach occurs especially for the dry season from Nov. to Mar. It was found out that the parameters, particularly for the advection related parameter, must be recalibrated to accurately produce monthly and annual regional evapotranspiration for this study area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.445-458
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• 2010

The effects of geographical and climatic factors on annual and monthly pan and Penman evaporation were analyzed. 52 climatological stations were selected and trend analyses were performed. Furthermore, cluster analysis and multiple linear regression analysis were performed to understand the effects of geographical and climatic factors on pan and Penman evaporation. Based on stepwise multiple linear regression analysis, annual pan evaporation is proved to be mainly controlled by urbanization as geographical factor, and annual pan evaporation is also controlled by temperature, relative humidity, wind speed, and solar radiation as climatic factor. Especially wind speed is considered to be most significant climatic factor which affects pan evaporation. Meanwhile, Penman evaporation is not affected by geographical factors but it is affected by climate factors such as temperature, relative humidity, wind speed, and solar radiation except precipitation. Furthermore, the study results show that only proximity to coast affects pan evaporation trend on July; however, geographical and climatic factors do not affect pan evaporation trends in annual basis and monthly basis (January, April, and October). On the other hand, Penman evaporation trends were not affected by geographical factors in annual and monthly basises.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.1
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• pp.1-8
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• 2013

This study was conducted to compare the local climate conditions and growth periods for the apple (Malus domestica 'Borkh') orchards at different altitudes (330, 500, and 670 m) in Jangsu-Gun, Korea. Observation data for the growth period show that the monthly mean air temperatures at the 'Hongro' apple orchard sites decrease with height at the rate of 1.0 to $3.0^{\circ}C$/100 m. The monthly minimum temperatures in April (blooming period for 'Hongro' apple) were 4.3, 2.9, and $0.4^{\circ}C$ at 330, 500, and 670 m, respectively. The monthly mean temperatures in September (i.e., the coloration and maturation period) were 20.6, 18.7, and $14.5^{\circ}C$, respectively. The annual precipitation range varied from 1,234 to 1,439 mm, which tended to increase with height. The heavy rainfall occurred in summer (June to August) and amounted to 827-933 mm. No significant differences in the duration of sunshine were observed amongst the orchards at three different altitudes. The earliest bud break was observed at the 330 m altitude (18 March 2009), which was 4 and 11 days earlier in comparison to those at 500 and 670 m, respectively. The time of full bloom at 330 m was 12 days ahead of that at 670 m. The optimal maturation of fruit (based on skin redness > 80%) was observed between 7 and 10 September at 330 m, 15 and 18 September at 500 m, and 21 and 23 September at 670 m.