• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.370-370
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• 2022

최근 우리나라는 수자원부존량 대비 수자원이용률이 16%에 불과하며 평상시 하천의 많은 가용수량이 이용되지 못하고 있는 실정이다. 현재 하천수 사용은 갈수와 가뭄시를 기준으로 허가 및 관리하고 있으며, 평상시 가용수량을 모니터링하여 하천유지유량, 하천수 사용, 환경대응 등 다양한 수요에 맞게 수량을 합리적으로 배분할 수 있는 수자원관리 체계 구축이 필요한 실정이다. 이에 본 연구에서는 대상지역인 금강유역의 하천수 사용 및 공급 상황을 파악하고 혼합(유역·하도) 물수지를 이용하여 실시간 가용수량 평가체계를 구축하였다. 실시간 가용수량 평가체계를 구축하기 위해서 유역의 수문상황과 기상전망(기온, 강우) 자료를 이용하여 장래기간의 강우조건(무강우, Ensemble Streamflow Prediction; ESP), 하천수 사용 및 공급계획(댐, 저수지 방류량 등) 시나리오 조건에 따른 예측기반 가용수량을 평가하였다. 대상 하천의 지류 유입량을 산정하기 위해서는 유역 물수지를 수행하고 하도 물수지를 통해 주요 지점별 하천관리유량과 가용수량을 산정한다. 또한, 유역(수계)간 물이동 및 하천수 사용 시설별 용·배수 체계를 고려하여 물수지 분석을 수행하였다. 이를 통해 산정된 각 취수시설별 유입량, 사용량, 회귀수량, 하천유지유량, 하천관리유량, 유량, 가용수량 등을 사용자가 쉽게 확인할 수 있도록 GIS와 테이블 기반으로 표출하였다. 본 평가체계를 활용하여 홍수통제소에서 수원(저수, 유수)별 가용수량을 다양한 수요에 맞게 적절하게 배분하고 조정할 수 있고 추후 가뭄 등 비상상황 발생 시 용수공급조정 및 연계운영계획에 반영될 수 있을 것으로 판단된다.

• Research in Plant Disease
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• v.21 no.2
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• pp.89-93
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• 2015

This study was carried out to develop the economic thresholds for the control of bacterial spot of red pepper. The correlation between diseased leaf rate and yield in field was Y=-0.724X+281.58, $R^2=0.78$, $r=-0.88^{**}$. The correlation between diseased leaf rate and yield loss in field was Y=0.813X+15.95, $R^2=0.78$, $r=0.88^*$.We found that control thresholds was below 30.3% diseased leaves rate per plant in field. The economic control thresholds for bacterial spot of red pepper was below 16.3%.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.307-307
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• 2011

ARF(Areal Reduction Factor, 면적우량감소계수)는 지점강우량을 면적 평균 강우량으로 변환하는 환산계수로 정의되며, 유역의 지형학적 특성과 강우의 공간적 분포특성을 반영한 유역단위의 ARF의 개발이 요구된다. 하지만 국내의 ARF는 대부분 한강유역을 대상으로 하고 있어 한강유역과 지형학적, 수문 기상학적 특징이 상이한 유역에 대하여 연구 결과를 적용하기는 많은 제약이 따를 것으로 판단된다. 따라서 본 연구에서는 남강댐 유역의 ARF를 산정하기 위해 7개의 강우관측소(산청, 삼가, 신안, 안의, 운봉, 태수, 함양)로부터 시강우자료(1990년~2010년)를 수집한 후 14개의 재현기간, 6개의 지속시간에 대한 지수형 ARF 회귀식을 산정하였다. 그 결과 남강댐 유역의 지수형 ARF 회귀식의 결정계수는 0.80~0.99로 높은 상관성을 나타내었다. 그리고 남강댐 유역의 ARF와 첨두홍수량의 관계를 분석하기 위해 남강댐 유역내의 산청유역을 대상으로 재현기간 100년, 지속시간 24시간에 대한 홍수량을 모의하였다. 그 결과 ARF의 적용 전 후의 첨두홍수량은 10% 이상 감소하는 것으로 나타났다. 따라서 남강댐 유역의 기상학적 특성을 고려한 첨두홍수량 산정을 위해서는 본 연구에서 제안한 ARF 회귀식이 유용할 것으로 판단된다.

• Research in Plant Disease
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• v.15 no.3
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• pp.175-182
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• 2009

We investigated the effect of the infection times and infection degrees at transplanting time of Zucchini yellow mosaic virus (ZYMV) on the growth and yield of cucumber plants at the semi-forcing and the retarding culture in 2007. When cucumber was inoculated with ZYMV at transplanting time, 15, 30, 45, 60, and 75 days after transplanting, vine length, internode length, number of leaf of the plants and marketable yield largely decreased as the cucumber infected earlier. The regression models were obtained between the disease incidence levels at 20 days after transplanting as the inoculation degrees and the marketable yield of cucumber: y = $9333.1e^{-0.0317x}$ ($R^2$ = 0.8946) at the semi-forcing culture and y = $14695e^{-0.0303x}$ ($R^2$ = 0.8735) at the retarding culture. And the cucumber yield loss regression models between the symptoms incidence days from the final harvesting time and the rates of yield decrease were expressed as y=1.0851x - 6.7067 ($R^2$ = 0.9567) at the semi-forcing culture andy=1.0439x + 2.1321 ($R^2$ = 0.9674) at the retarding culture.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2004.11a
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• pp.11-11
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• 2004

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.630-634
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• 2004

현재까지 대부분의 유출 모형들은 우리나라 농업지역에 내한 적용에 있어 많은 수정이 요구되고, 그에 따른 모의 결과 또한 불확실성을 내포하고 있으며, 이의 원인중 상당수는 농업지역에서 발생하는 관개와 회귀에 따른 것이라 찰 수 있다. 특히 농업지역에서의 유출 및 물사용에 대한 정확한 계측이 제대로 이루어지고 있지 못하기 때문에, 그에 따른 정확한 수자원 평가가 어려운 현실이다. 이에 본 논문에서는 본 연구진에서 기 개발한 순물소모량 산정방법과 회귀 관계식으로 보청천 유역의 회귀특성을 규명하고자 하였으며, 본 연구에서 사용한 모형은 SWAT모형의 농업용수 관개 기능을 보완한 SWAT-AGRIMANAGEMENT모형을 개발 이용하였다. 유역규모에서의 농업용수 사용에 따른 하천유량의 변화 및 유역내 회귀관계를 파악할 수 있었으며, 기존에 주로 관개지구 단위에서의 회귀수량 조사 결과 및 가정에 의하여 사용되던 농업용수 회귀율에 대한 보다 의미있는 기준을 제시할 수 있을 것으로 기대된다.

• Journal of Korean Society of Disaster and Security
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• v.13 no.3
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• pp.15-28
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• 2020

Hydrological data is very important in understanding the hydrological process and identifying its characteristics to protect human life and property from natural disasters. In particular, hydrological analysis are often performed assuming that hydrological data are stationary. However, recently climate change has raised the issue of climate stationary, and it is necessary to analyze the nonstationary of the climate. In this study, a method to analyze the stationarity of hydrological data was examined using the annual precipitation of 37 meteorological stations with long - term record data. Therefore, in this study, the stationary was determined by analyzing the persistence, trend, and stability using annual precipitation. Overall results showed that a trend was observed in 4 out of 37 stations, stable was investigated at 15 stations, and persistence was shown at 4 stations. In the stationary analysis using the annual precipitation data, 25 stations (67% of 37 stations) were nonstationary.

• Water for future
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• v.26 no.1
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• pp.51-62
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• 1993

The most significant factor in estimating annual runoff must be the precipitation. But in the previous study, the watershed area instead of precitation was included as an independent variable in regression model in the process of checking accurate data. The criterion of accurate data was the runoff ratio in the range of 20% to 100%. In this study the valid range of evapotranspiration was adopted as a criterion of accurate data and the same data were reexamined. It came up with following model which has a high coefficient of determination and conforms to hydrologic theory. R=-518.25+0.8834P where, R: runoff depth(mm) P: precipitation(mm) This regression model was found to be stable by cross-validation and is proposed as annual runoff estimation model applicable to ungaged small and medium watersheds in Korea.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.699-708
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• 2017

The present study was to develop an approach for predicting soybean yield using a crop growth simulation model at the regional level where the detailed and site-specific information on cultivation management practices is not easily accessible for model input. CROPGRO-Soybean model included in Decision Support System for Agrotechnology Transfer (DSSAT) was employed for this study, and Illinois which is a major soybean production region of USA was selected as a study region. As a first step to predict soybean yield of Illinois using CROPGRO-Soybean model, genetic coefficients representative for each soybean maturity group (MG I~VI) were estimated through sowing date experiments using domestic and foreign cultivars with diverse maturity in Seoul National University Farm ($37.27^{\circ}N$, $126.99^{\circ}E$) for two years. The model using the representative genetic coefficients simulated the developmental stages of cultivars within each maturity group fairly well. Soybean yields for the grids of $10km{\times}10km$ in Illinois state were simulated from 2,000 to 2,011 with weather data under 18 simulation conditions including the combinations of three maturity groups, three seeding dates and two irrigation regimes. Planting dates and maturity groups were assigned differently to the three sub-regions divided longitudinally. The yearly state yields that were estimated by averaging all the grid yields simulated under non-irrigated and fully-Irrigated conditions showed a big difference from the statistical yields and did not explain the annual trend of yield increase due to the improved cultivation technologies. Using the grain yield data of 9 agricultural districts in Illinois observed and estimated from the simulated grid yield under 18 simulation conditions, a multiple regression model was constructed to estimate soybean yield at agricultural district level. In this model a year variable was also added to reflect the yearly yield trend. This model explained the yearly and district yield variation fairly well with a determination coefficients of $R^2=0.61$ (n = 108). Yearly state yields which were calculated by weighting the model-estimated yearly average agricultural district yield by the cultivation area of each agricultural district showed very close correspondence ($R^2=0.80$) to the yearly statistical state yields. Furthermore, the model predicted state yield fairly well in 2012 in which data were not used for the model construction and severe yield reduction was recorded due to drought.

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.441-446
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• 2000