• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.279-279
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• 2017

토양유실로 인해 발생된 토사는 강우 유출수와 함께 하류로 흘러들어 하천 및 호소의 탁수문제를 야기시킨다. 토양유실에 관한 현황을 파악하기 위해서는 유역 내 토지이용현황과 피복되어 있는 작물 등의 현황조사와 더불어 유역 내 발생되는 토양유실량에 대한 장기모니터링을 수행할 필요가 있다. 하지만 유역 내 발생되는 토양유실량에 대한 장기모니터링을 수행하기에는 많은 시간과 인력이 필요하므로 토양유실량 산정 및 유사거동특성을 계산하는 모형을 활용한 연구가 국내외 많은 연구자들에 의해 수행되고 있다. 토양유실량을 산정하는 모형 중 가장 많이 사용되고 있는 범용토양유실량산정공식(Universal Soil Loss Equation, USLE)은 5개의 인자를 사용하여 연평균 토양유실량을 산정한다. 국내의 경우 환경부에서 제정한 '표토의 침식 현황 조사에 관한 고시'에 표토침식현황을 조사하는 방법으로 USLE 공식을 사용한다. USLE 모형을 구성하는 인자 중 식생피복인자는 작물의 생육과정에 따른 변화를 고려하지 않고 작물에 대한 획일적인 값을 제시하고 있어 밭에서 발생되는 정확한 토양유실현황을 예측하는데 한계가 있다, 따라서 본 연구에서는 국내에서 사용하는 USLE 모형의 구성인자인 식생피복인자의 한계점을 인식하고 이를 유역별 월단위 인자값으로 산정하는 방법을 제시하기 위해 국내의 4대상 유역 중 대청호 유역, 소양호 유역, 주암호 유역, 임하호 유역을 선정하여 각 유역의 기후 및 지역특성을 고려한 식생피복인자를 제안하였다. 월단위 식생피복인자를 제안하기 위해 SWAT모형을 사용하여 일단위 식생피복인자를 출력하도록 모형을 구성하였으며, 구축된 인자의 지역적 한계를 보완하기 위해 4대강 유역에 대한 작물 재배일정을 조사하여 모형에 반영하여 모의하였다. 모의 결과 산정된 월단위 식생피복 인자는 모든 작물에 대해 작물이 파종되는 시점에서 수확되기까지 점차 감소하는 경향을 보였으며, 작물에 따라서 그리고 동일한 작물일지라도 유역에 따라 다소 차이가 있는 것으로 확인되었다. 따라서 본 연구를 통해 제안된 월단위 식생피복인자는 토양유실에 직접적인 영향을 주는 지표피복변화를 고려한 식생피복인자로써 정확한 토양유실량을 산정하는데 기여할 것으로 판단된다.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.721-732
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• 2017

With the increasing socio-economic importance of rice as a global staple food, several models have been developed for rice yield estimation by combining remote sensing data with carbon cycle modelling. In this study, we aimed to estimate rice yield in Korea using such an integrative model using satellite remote sensing data in combination with a biophysical crop growth model. Specifically, daily meteorological inputs derived from MODIS (Moderate Resolution imaging Spectroradiometer) and radar satellite products were used to run a light use efficiency based crop growth model, which is based on the MODIS gross primary production (GPP) algorithm. The modelled biomass was converted to rice yield using a harvest index model. We estimated rice yield from 2003 to 2014 at the county level and evaluated the modelled yield using the official rice yield and rice straw biomass statistics of Statistics Korea (KOSTAT). The estimated rice biomass, yield, and harvest index and their spatial distributions were investigated. Annual mean rice yield at the national level showed a good agreement with the yield statistics with the yield statistics, a mean error (ME) of +0.56% and a mean absolute error (MAE) of 5.73%. The estimated county level yield resulted in small ME (+0.10~+2.00%) and MAE (2.10~11.62%),respectively. Compared to the county-level yield statistics, the rice yield was over estimated in the counties in Gangwon province and under estimated in the urban and coastal counties in the south of Chungcheong province. Compared to the rice straw statistics, the estimated rice biomass showed similar error patterns with the yield estimates. The subpixel heterogeneity of the 1 km MODIS FPAR(Fraction of absorbed Photosynthetically Active Radiation) may have attributed to these errors. In addition, the growth and harvest index models can be further developed to take account of annually varying growth conditions and growth timings.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.4
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• pp.83-92
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• 2012

짐바브웨는 식량부족을 격어 오고 있으며, 이는 기후변화에 따른 수자원의 부족, 인구증가, 개발 및 환경보전 등으로 인하여 앞으로는 더욱 심화될 것으로 보인다. 3가지 배출시나리오 (A2, A1B, B1)에 대한 13개의 GCM 기후자료로부터 상세화한 기후예측값과 AquaCrop 작물모형을 이용하여 기후변화가 짐바브웨의 주곡인 옥수수의 수확량에 미치는 영향과 모형예측값의 불확실성을 분석하였다. 작물생육환경이 잘 유지된다고 가정하고 옥수수 잠재생산량을 모의한 결과 기준년도 (1970s)에 비해 2020s, 2050s and 2090s 년대에 평균 (범위) 8 % (6-9 %), 14 % (10-15 %) 및 16 % (11-17 %) 증가할 것으로 예측되었다. 같은 기간에 대한 물의 생산성은 평균 (범위) 7 % (4-13 %), 13 % (6-30 %) 및 15% (6-23 %) 증가할 것으로 예측되었다. 기온의 꾸준한 상승과 대기중 이산화탄소 농도 증가로 인한 시비효과로 인하여 미래에는 옥수수 단위 생산량과 물의 생산성이 증가할 것으로 예측되었으며 증가 범위를 보면 모형간의 변동성이 상당히 큰 것을 알 수 있었다. 본 연구결과는 기후변화가 짐바브웨의 옥수수 생산량에 미치는 영향과 변동성을 제시하므로서 장기적인 식량계획의 기초자료로 이용될 수 있을 것이다.

• Journal of Korean Society of Forest Science
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• v.90 no.2
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• pp.176-183
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• 2001

Loblolly pine (Pinus taeda L.) is the most economically important timber producing species in the southern United States. Much attention has been given to predicting diameter distributions for the solution of multiple-product yield estimates. The three-parameter Weibull diameter distribution yield prediction systems were developed for loblolly pine plantations. A parameter recovery procedure for the Weibull distribution function based on four percentile equations was applied to develop diameter distribution yield prediction models. Four percentiles (0th, 25th, 50th, 95th) of the cumulative diameter distribution were predicted as a function of quadratic mean diameter. Individual tree height prediction equations were developed for the calculation of yields by diameter class. By using individual tree content prediction equations, expected yield by diameter class can be computed. To reduce rounding-off errors, the Weibull cumulative upper bound limit difference procedure applied in this study shows slightly better results compared with upper and lower bound procedure applied in the past studies. To evaluate this system, the predicted diameter distributions were tested against the observed diameter distributions using the Kolmogorov-Smirnov two sample test at the ${\alpha}$=0.05 level to check if any significant differences existed. Statistically, no significant differences were detected based on the data from 516 evaluation data sets. This diameter distribution yield prediction system will be useful in loblolly pine stand structure modeling, in updating forest inventories, and in evaluating investment opportunities.

• Journal of Korean Society of Forest Science
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• v.89 no.3
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• pp.335-341
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• 2000

In this study, the multiobjective linear programming (MOLP) formulation was built to solve for the optimal forest management planning considering carbon sequestration and timber production simultaneously. The formulation was applied to a case study problem to investigate the trends of the optimal forest harvest schedules as the function of preference of forest management for carbon sequestration and timber production. The study site was Mt. Kari area in Hongchun. The formulation includes several site-specific constraints for non-declining yields, upper and lower bounds of cut volume and area for timber, ending inventory conditions, etc.. According to the changes of weight combinations for timber production and carbon sequestration, the joint production possibilities curve was proposed as the option for management choice.

• Korean Journal of Environmental Agriculture
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• v.31 no.4
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• pp.318-327
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• 2012

BACKGROUND: For Non-Point Source(NPS) loads reduction, pollutant loads need to be quantified for major farming methods. The objective of this study was to evaluate impacts of farming methods on NPS pollutant loads from a paddy rice field during the growing season. METHODS AND RESULTS: The height of drainage outlet, amount of fertilizer, irrigation water quality were considered as farming factors for scenarios development. The control was derived from conventional farming methods and four different scenarios were developed based combination of farming factors. A field scale model, CREAMS-PADDY(Chemicals, Runoff, and Erosion from Agricultural Management Systems for PADDY), was used to calculate pollutant nutrient loads. The data collected from an experimental plot located downstream of the Idong reservoir were used for model calibration and validation. The simulation results agreed well with observed values during the calibration and validation periods. The calibrated model was used to evaluate farming scenarios in terms of NPS loads. Pollutant loads for T-N, T-P were reduced by 5~62%, 8~37% with increasing the height of drainage outlet from 100 mm of 100 mm, respectively. When amount of fertilizer was changed from standard to conventional, T-N, T-P pollutant loads were reduced by 0~22%, 0~24%. Irrigation water quality below water criteria IV of reservoir increased T-N of 9~65%, T-P of 9~47% in comparison with conventional. CONCLUSION(S): The results indicated that applying increased the height of drainage after midsummer drainage, standard fertilization level during non-rainy seasons, irrigation water quality below water criteria IV of reservoir were effective farming methods to reduce NPS pollutant loads from paddy in Korea.

• Journal of Biosystems Engineering
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• v.30 no.6 s.113
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• pp.360-365
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• 2005

Precision agriculture attempts to improve cropping efficiency by variable application of crop treatments such as fertilizers and pesticides, within field on a point-by-point basis. Therefore, a more complete understanding of the relationships between yield and soil properties is of critical importance in precision agriculture. In this study, the functional relationships between measured soil properties and rice yield were investigated. A supervised back-propagation neural network model was employed to relate soil chemical properties and rice yields on a point-by point basis, within individual site-years. As a results, a positive correlation was found between practical yields and predicted yields in 1999, 2000, 2001, and 2002 are 0.916, 0.879, 0.800 and 0.789, respectively. The results showed that significant overfitting for yields with only the soil chemical properties occurred so that more of environmental factors, such as climatological data, variety, cultivation method etc., would be required to predict the yield more accurately.

• Journal of Korean Society of Forest Science
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• v.88 no.2
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• pp.273-281
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• 1999

In this study, linear programming (LP) was applied to solving for optimal harvesting schedules of multiple-use forest management in Mt. Kari area managed by Chunchun National Forest Station. Associated with the geographic characteristics, the study area was classified into 4 large management units or watersheds and simultaneously applied were the site-specific levels of management constraints : nondeclining yield, initial cut for existing stands, % cut area, the volume of soil erosion, timber production and carbon storage, ending inventory condition and % area species selection for regeneration. The problem was formulated using both Model I and Model II techniques. In this paper, the formulations are presented and the results of the optimal solutions are discussed for comparison purposes.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.333-339
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• 2015

A thermal time-based phenology model of Kimchi cabbage was developed by using the field observed growth and temperature data for the purpose of accurately predicting heading and harvest dates among diverse cropping systems. In this model the lifecycle of Kimchi cabbage was separated into the growth stage and the heading stage, while the growth amount of each stage was calculated by optimal mathematical functions describing the response curves for different temperature regimes. The parameter for individual functions were derived from the 2012-2014 crop status report collected from seven farms with different cropping systems located in major Kimchi cabbage production area of South Korea (i.e., alpine Gangwon Province for the summer cultivation and coastal plains in Jeonnam Province for the autumn cultivation). For the model validation, we used an independent data set consisting of local temperature data restored by a geospatial correction scheme and observed harvest dates from 17 farms. The results showed that the root mean square error averaged across the location and time period (2012-2014) was 5.3 days for the harvest date. This model is expected to enhance the utilization of the Korea Meteorological Administration's daily temperature data in issuing agrometeorological forecasts for developmental stages of Kimchi cabbage grown widely in South Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.68-78
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• 2020

Crop models have been used to predict vegetable crop yield, which would have a considerable economic impact on consumers as well as producers. A small number of models have been developed to estimate growth and yield of vegetables due to limited availability of growth observation data in high-quality. In this study, we aimed to analyze the protocols designed for collection of the observation data for major vegetable crops including cabbage, radish, garlic, onion and pepper. We also designed the protocols suitable for development and verification of a vegetable crop growth model. In particular, different measures were proposed to improve the existing protocol used by Statistics Korea (KOSTAT) and Rural Development Administration (RDA), which would enhance reliability of parameter estimation for the crop model. It would be advantageous to select sampling sites in areas where reliable weather observation data can be obtained because crop models quantify the response of crop growth to given weather conditions. It is recommended to choose multiple sampling sites where climate conditions would differ. It is crucial to collect time series data for comparison between observed and simulated crop growth and yield. A crop model can be developed to predict actual yield rather than attainable yield using data for crop damage caused by diseases and pests as well as weather anomalies. A bigdata platform where the observation data are to be shared would facilitate the development of crop models for vegetable crops.