빈번한 가뭄의 피해는 수자원의 양극화를 초래하고 있다. 국내에서는 2011년부터 2017년 사이에 국지적이고 주 기적인 이상 가뭄이 지속되어 10년 가뭄 빈도로 설계된 소규모 저수지의 저수율이 감소하였다. 이러한 저수율의 감소 는 수질을 떨어트릴 수 있고 이미 확보된 용수의 사용마저 제한할 수 있다. 따라서 가뭄에 대비하고 극복하기 위해서 는 수질관리와 가뭄 빈도의 재산정이 필요하다. 이 연구는 저수지에서 수질 변화의 원인인 잠재적 오염물질을 추정하고, 가뭄 기간 동안 저수지의 저수율 감소와 그에 따른 수질 변화를 검토한 것이다.

Currently in the drought evaluation, which is a supplier-oriented standard that applies storage rates of reservoirs, evaluation for users that use agricultural water is not done. Therefore, this study established drought evaluation items for drought evaluation based on farmers' judgement, conducted a survey on farmers and experts, compared and analyzed weighted value between two groups, and then classified the evaluation standards per each evaluation item. The agricultural drought evaluation items are 5 major items of water supply lapse rate, agricultural weather, agricultural irrigation facility, crop and soil, and 12 subsections for regional characteristics and opinions of consumers that use water to be reflected. The result of analyzing weighted value of farmers and experts' major items shows that farmers is agricultural irrigation facility(0.219), water supply lapse rate(0.211), agricultural weather(0.204), crop(0.183) and soil(0.183). Experts is agricultural weather(0.297), agricultural irrigation facility(0.202), water supply lapse rate(0.189), crop(0.162) and soil(0.150), which displays difference between the two groups. The agricultural drought criteria standards are established based on precedent studies and cases, and grades of evaluation items are 1st grade(extreme stage), 2nd grade(warning stage), 3rd grade(alert stage) and 4th grade(attention stage). The above analysis per each consumer-oriented agricultural drought evaluation item and the analysis on the standards of evaluation grades are expected to be used as a basic resource for establishing agriculture drought policy and selecting drought area in the future.

가뭄은 여러 가지 요인에 의해 복합적으로 발생하는 현상으로 자연적 원인과 인위적 원인으로 구분할 수 있다. 우리나라는 기후학적 특성상 여름철에 태평양 고기압의 발달 시기가 빠르거나 평년보다 강하면 장마 기간이 짧아져 자연적인 원인에 의해 가뭄이 발생한다. 가뭄은 발생과정과 피해 영향에 따라 기상학적, 농업적, 수문학적, 사회경제적 가뭄으로 구분할 수 있으며 직 ․ 간접적으로 다른 가뭄에 영향을 미친다. 가뭄의 종류가 기상학적 가뭄에서 농업적 가뭄 혹은 기상학적 가뭄에서 수문학적 가뭄으로 변화되는 현상을 가뭄 전이라 한다. 본 연구에서는 국내의 가뭄 전이 발생여부와 발생 패턴을 검토하기 위해 수문기상 정보를 이용하여 기상학적 가뭄에서 농업적 가뭄으로의 전이 관계를 분석하였다. 가뭄 전이 발생 현황 및 특성 분석을 위해 가뭄 발생의 유형을 5가지로 구분하였으며, 유형에 따라 가뭄 전이가 발생하지 않거나 최대 3개월까지 지체되는 것을 확인하였다. 향후 더 많은 가뭄 지표들과의 분석을 통해 가뭄 전이 관계를 일반화한다면 기상학적 가뭄 발생 시 농업적 가뭄 예측을 위한 인자로 활용할 수 있을 것으로 기대된다.

본 연구는 1985년부터 2015년까지 지속기간에 따른 청미천 유역의 가뭄을 분석하였다.가뭄의 정량적 평가를 위해 기상학적 가뭄지수와 수문학적 가뭄지수를 사용하였다. 기상학적 가뭄지수로는 강수량을 변수로 하는 SPI(Standarized Precipitation Index)와 강수량과 증발산량을 변수로 하는 SPEI(Standarized Precipitation Evapotranspiration Index)를 사용하였다. SWAT 모형의 모의를 통해 도출된 결과를 바탕으로 농업학적 가뭄지수 인 PDSI(Palmer Drought Severity Index)와 수문학적 가뭄지수인 SDI(Streamflow Drought Index)를 적용하였다. 산정 결과, 극한 및 평균 가뭄의 평균에서 2015년과 2014년이 가장 가뭄에 취약함이 확인되었다. 빈도분석에 따른 가뭄의 변동성은 서로 다른 형태를 보였다. 또한 상관분석에서 극 한 가뭄 및 평균 가뭄은 PDSI를 제외한 SPI, SPEI, SDI 가뭄지수간에는 높은 상관관계가 확인되었다.􀀁하지만 각 가뭄지수는 서로 다른 극한가뭄의 시기 및 강도를 보였다. 따라서 가뭄분석시 다양한 특성을 지닌 가뭄지수를 활용하는 것이 필요하다.

Recently, the occurrences of droughts have been increased because of global warming and climate change. Water resources that mostly rely on groundwater are particularly vulnerable to the impact of precipitation variation, one of the major elements of climate change, are very sensitive to changes in the seasonal distribution as well as the average annual change in the viewpoint of agricultural activity. In this study, the status of drought for the present and future on Jeju Island which entirely rely on groundwater using SPI and PDSI were analyzed considering regional distribution of crops in terms of land use and fluctuation of water demand. The results showed that the precipitation distribution in Jeju Island is changed in intensity as well as seasonal variation of extreme events and the amount increase of precipitation during the dry season in the spring and fall indicated that agricultural water demand and supply policies would be considered by regional characteristics, especially the western region with largest market garden crops. Regarding the simulated future drought, the drought would be mitigated in the SPI method because of considering total rainfall only excluding intensity variation, while more intensified in the PDSI because it considers the evapotranspiration as well as rainfall as time passed. Moreover, the drought in the northern and western regions is getting worse than in the southern region so that the establishment of regional customized policies for water supply in Jeju Island is needed.

Korean soybean variety Kwangan was transformed with coat protein (CP), helper component-proteinase (HC-Pro), and ABRE binding factor 3 (ABF3) genes using highly efficient soybean transformation system. Among these genes, CP and HC-Pro were transformed using RNAi technology. Transgenic plants with CP were confirmed for gene introduction and their expression using PCR, real-time PCR, RT-PCR, Southern blot, and Northern blot. To investigate the response of viral infection with CP, T1 plants were inoculated with SMV-infected leaves and confirmed the existence of mosaic symptom in both leaves and seeds. Two transgenic lines with CP were highly resistant to SMV with clear leaves and seeds while SMV-susceptible lines showed mosaic symptom with seed mottling. The transcript levels of T1 plants with CP were also determined by northern blot, suggesting that SMV-resistant T1 plants did not show viral RNA expression whereas SMV-susceptible T1 plants showed viral RNA expression. Currently, the response of viral infection with HC-Pro is investigating to produce SMV-resistant soybean transgenic plants, and the physiological experiment with ABF3 is also carrying out to produce drought-tolerant soybean transgenic plants.

본 연구에서는 전국 59개 지점의 3개월 SPI 자료를 가지고 EOF를 유도하고 아울러 그 공간적 특성을 분석하였다. 또한 EOF 해석에 의해 나타난 Coefficient Time Series를 다변량 시계열 모형에 적용하여 SPI 시계열을 자료기간 10,000년으로 확장하였고 전국적인 가뭄심도를 판단하기 위해 전국 평균 지수를 이용하여 재현기간별 최대심도를 결정하였다. 마지막으로 각 대권역의 댐 유효저수량과 농경지 면적을 이용하여 농업가뭄 대비능력을

The objectives of this study were to develop an evaluation method of regional vulnerability to agricultural drought and to classify the vulnerability patterns. In order to test the method, 24 city or county areas of Gyeonggi-do were chose. First, statistic data and digital maps referred for agricultural drought were defined, and the input data of 31 items were set up from 5 categories: land use factor, water resource factor, climate factor, topographic and soil factor, and agricultural production foundation factor. Second, for simplification of the factors, principal component analysis was carried out, and eventually 4 principal components which explain about 80.8% of total variance were extracted. Each of the principal components was explained into the vulnerability components of scale factor, geographical factor, weather factor and agricultural production foundation factor. Next, DVIP (Drought Vulnerability Index for Paddy), was calculated using factor scores from principal components. Last, by means of statistical cluster analysis on the DVIP, the study area was classified as 5 patterns from A to E. The cluster A corresponds to the area where the agricultural industry is insignificant and the agricultural foundation is little equipped, and the cluster B includes typical agricultural areas where the cultivation areas are large but irrigation facilities are still insufficient. As for the cluster C, the corresponding areas are vulnerable to the climate change, and the D cluster applies to the area with extensive forests and high elevation farmlands. The last cluster I indicates the areas where the farmlands are small but most of them are irrigated as much.

The objectives of this study are to develop an agricultural drought evaluation model based on administrative boundaries and to assist the effective drought-related decision-making of local governments. The model which was named ADEM(Administrative Drought Evaluation Model for Paddies) is designed to simulate daily water balance between available water quantities from various agricultural water facilities such as reservoirs, wells, pump stations, etc. and water requirements in paddies. And in order to numerically describe the agricultural drought severity, two indices were defined; One is ADFP(Agricultural Drought Frequency for Paddies) which is calculated with a frequency analysis of monthly water deficit, and the other is ADIP(Agricultural Drought Index for Paddies) with a scale of -4.2~+4.2. The developed model was applied to Yeoju district and showed good correspondence with the historical records of drought.