• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.883-893
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• 2023

While South Korea's dependence on imported grains is very high, droughts impacts from exporting countries have been overlooked. Using the Evaporative Stress Index (ESI), this study globally analyzed frequency, extent, and long-term trends of agricultural droughts and their relation to natural oscillations and global crop prices. Results showed that global-scale correlations were found between ESI and soil moisture anomalies, and they were particularly strong in crop cultivation areas. The high correlations in crop cultivation areas imply a strong land-atmosphere coupling, which can lead to relatively large yield losses with a minor soil moisture deficits. ESI showed a clear decreasing trend in crop cultivation areas from 1991 to 2022, and this trend may continue due to global warming. The sharp increases in the grain prices in 2012 and 2022 were likely related to increased drought areas in major grain-exporting countries, and they seemed to elevate South Korea's producer price index. This study suggests the need for drought risk management for grain-exporting countries to reduce socioeconomic impacts in South Korea.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.931-946
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• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.

• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.163-174
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• 2017

This study developed the prototype of the system and implemented its main functions, which is the intelligent integrated agricultural water management information system and service (IaWAMISS). The developed system was designed to be able to collect, process and analyze the agricultural water information of spatially dispersed reservoirs in whole country and spatial geographic information distributed in various systems of other organizations. The system, IaWAMISS, is also possible to provide the reproduced information services in each reservoir and space units, such as agricultural water demand and supply analysis and drought prediction, to the people, experts, and policy makers. This study defined the 6 step modules to develop the system, which are to design the components of intelligent integrated information system, to derive the utilization contents of existing systems, to design the new development elements for IaWAMISS, to design the reservoir information system can be used by managers of city and county, to designate the monitoring reservoirs managed by city and county, and finally to prepare the sharing system between organizations with the existing information systems. In order to implement the prototype of the system, this study shows the results for three important functions of the system: spatial integration of reservoirs' information, data link integration between the existing systems, and intelligent analysis program development to assist decision support for agricultural water management. For the spatial integration with the reservoir water information of the Korea Rural Community Corporation, this study get IaWAMISS to receive the real-time reservoir storage information from the measurement facility installed in the municipal management reservoir. The data link integration connecting databases of the existing systems, was implemented by integrating the meteorological information of the Korea Meteorological Administration with IaWAMISS, so that the rainfall forecast data could be derived and used. For the implementation of the intelligent analysis program, this study also showed the results of analysis and prediction of agricultural water demand and supply amount, estimation of Palmer drought index, analysis of flood risk area in typhoon course region, and analysis of the storage status of reservoirs related to each storm. This study confirmed the possibility and efficiency of an useful system development through the prototype design and implementation of IaWAMISS. By solving the preliminary 6 step modules presented in this study, it is possible not only to efficiently manage water by spatial unit, but also to provide the service of information and to enhance the relevant policy and national understanding to the people.

• Journal of Microbiology and Biotechnology
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• v.34 no.6
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• pp.1239-1248
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• 2024

Peatlands are marginal agricultural lands due to highly acidic soil conditions and poor drainage systems. Drought stress is a big problem in peatlands as it can affect plants through poor root development, so technological innovations are needed to increase the productivity and sustainability of upland rice on peatlands. Rhizobacteria can overcome the effects of drought stress by altering root morphology, regulating stress-responsive genes, and producing exopolysaccharides and indole acetic acid (IAA). This study aimed to determine the ability of rhizobacteria in upland rice to produce exopolysaccharides and IAA, identify potential isolates using molecular markers, and prove the effect of rhizobacteria on viability and vigor index in upland rice. Rhizobacterial isolates were grown on yeast extract mannitol broth (YEMB) medium for exopolysaccharides production testing and Nutrient Broth (NB)+L-tryptophan medium for IAA production testing. The selected isolates identify using sequence 16S rRNA. The variables observed in testing the effect of rhizobacteria were germination ability, vigour index, and growth uniformity. EPS-1 isolate is the best production of exopolysaccharides (41.6 mg/ml) and IAA (60.83 ppm). The isolate EPS-1 was identified as Klebsiella variicola using 16S rRNA sequencing and phylogenetic analysis. The isolate EPS-1 can increase the viability and vigor of upland rice seeds. K. variicola is more adaptive and has several functional properties that can be developed as a potential bioagent or biofertilizer to improve soil nutrition, moisture and enhance plant growth. The use of rhizobacteria can reduce dependence on the use of synthetic materials with sustainable agriculture.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.839-852
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• 2018

The purpose of this study is to predict monthly agricultural reservoir storage by developing weather data-based Multiple Linear Regression Model (MLRM) with precipitation, maximum temperature, minimum temperature, average temperature, and average wind speed. Using Naïve-Bayes classification, total 1,559 nationwide reservoirs were classified into 30 clusters based on geomorphological specification (effective storage volume, irrigation area, watershed area, latitude, longitude and frequency of drought). For each cluster, the monthly MLRM was derived using 13 years (2002~2014) meteorological data by KMA (Korea Meteorological Administration) and reservoir storage rate data by KRC (Korea Rural Community). The MLRM for reservoir storage rate showed the determination coefficient ($R^2$) of 0.76, Nash-Sutcliffe efficiency (NSE) of 0.73, and root mean square error (RMSE) of 8.33% respectively. The MLRM was evaluated for 2 years (2015~2016) using 3 months weather forecast data of GloSea5 (GS5) by KMA. The Reservoir Drought Index (RDI) that was represented by present and normal year reservoir storage rate showed that the ROC (Receiver Operating Characteristics) average hit rate was 0.80 using observed data and 0.73 using GS5 data in the MLRM. Using the results of this study, future reservoir storage rates can be predicted and used as decision-making data on stable future agricultural water supply.

• Journal of Climate Change Research
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• v.6 no.1
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• pp.55-60
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• 2015

Agro-Meteorological Information Service (AMIS) network has been established since 2001 by Rural Development Administration (RDA) in Korea, and has provided access to current and historical weather data with useful information for agricultural activities. AMIS network includes 158 automated weather stations located mostly in farm region, with planning to increase by 200 stations until 2017. Agrometeorological information is disseminated via the web site (http://weather.rda.go.kr) to growers, researchers, and extension service officials. Our services will give enhanced information from observation data (temperature, precipitation, etc.) to application information, such as drought index, agro-climatic map, and early warning service. AMIS network of RDA will help the implementation of an early warning service for weather risk management.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.29-39
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• 2017

In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

• Journal of Korean Society of Rural Planning
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• v.22 no.2
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• pp.121-129
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• 2016

A disaster can be defined in many ways based on perspectives, in addition, its types are able to classify differently by various standards. Considering the different perspectives, the disaster can be occurred by natural phenomenon that is like typhoon, earthquake, flood, and drought, and by the accident that is like collapse of facilities, traffic accidents, and environmental pollution, etc. Into the modern society, moreover, the disaster includes the damages by diffusion of epidemic and infectious disease in domestic animals. The disaster was defined by natural and man-made hazards in the past. As societies grew with changes of paradigm, social factors have been included in the concept of the disaster according to new types unexpected by new disease and scientific technology. Change the concept of social disasters, Ministry of Public Safety and Security (MPSS) has provided the regional safety index, which measures the safety level of a local government. However, this regional safety index has some limitation to use because this index provides the information for city unit which is a unit of administrative districts of urban. Since these administrative districts units are on a different level with urban and rural areas, the regional safety index provided by MPSS is not be able to direct apply to the rural areas. The purpose of this study is to determine the regional safety index targeting rural areas. To estimate the safety index, we was used for 3 indicators of the MPSS, a fire, a crime, and an infectious disease which are evaluable the regional safety index using an accessibility analysis. For determining the regional safety index using accessibility from community centers to public facilities, the safety index of fire, crime, and infectious disease used access time to fire station, police office, and medical facility, respectively. An integrated Cheongju, targeting areas in this study, is mixed region with urban and rural areas. The results of regional safety index about urban and rural areas, the safety index in rural area is relatively higher than in the urban. Neverthless the investment would be needed to improve the safety in the rural areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1883-1886
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• 2010

농업가뭄은 강수의 부족으로 인하여 농업용 저수지의 저수량 저하로 농작물 생육 및 수확량의 직접적인 영향을 미치는 것으로, 농업가뭄평가는 강수량뿐만 아니라 작물의 생육시기별 필요수량과 용수공급능력을 모두 고려할 수 있어야 한다. 농업가뭄관리의 주요 대상인 논벼는 기본적으로 수원공과 관개지역 사이의 물수지를 판단함으로써 농업가뭄의 위험을 정의할 수 있다. 본 연구에서는 가뭄관리가 필요한 농업용 저수지 관개지구의 농업가뭄 평가를 위해 논 물수지 분석 모형과 저수지 물수지 분석 모형을 구성하고, 용수수급해석의 결과로부터 가뭄의 크기를 객관화하고 가뭄의 단계를 평가할 수 있도록 빈도개념을 적용한 저수지가뭄지수 (Reservoir Drought Index, RDI)를 이용하여 농업가뭄을 분석 평가하였다. 또한 농업용 저수지의 저수량 모의치와 실시간 저수위를 이용하여 경험적으로 농업용 저수지의 유입량을 자동으로 보정하여 장기적으로 최적화할 수 있는 방안을 제시하였으며, 과거 유효강수량을 시기별로 나누어 빈도분석을 통해 농업가뭄대응을 위한 가뭄 기상시나리오를 사용하여 향후 가뭄의 여러 가지 패턴에 따른 농업가뭄을 전망하였다. 이러한 다양한 시나리오를 통해 실제 물 관리 및 가뭄대책 업무에 반영하고 농업가뭄대응책 수립 및 농업수자원관리의 의사결정을 수립하는데 기초자료가 될 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.183-183
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• 2019

최근 지구온난화에 따른 기후변화로 폭염, 가뭄, 홍수 등 기상 재해의 발생빈도가 상승하고 있으며, 강우 집중도와 변동성이 증가함에 따라 2010년 이후 2014년을 제외한 현재까지 지속적인 농업가뭄의 발생으로 연속적인 가뭄 피해를 겪고 있다. 근대적 수리시설의 발달과 선제적 가뭄대책 등으로 가뭄대응력은 향상되어 피해 수준은 과거에 비해 상대적으로 적은 편이나 정량적인 가뭄피해 평가의 기준이나 피해 평가 사례가 미흡하다. 일반적으로 기상학적 가뭄은 표준강수지수(Standardized Precipitation Index, SPI)를 활용하고 있으며, 농업적 가뭄은 농촌수자원의 주요한 용수공급시설인 농업용 저수지의 용수공급능력과 관개지역의 필요수량을 평가하여 시기별로 부족 수량을 산정하고 가뭄강도를 정량화함으로써 농업가뭄 상황을 평가할 수 있다. 본 연구에서는 기상학적 가뭄 지수인 SPI와 농업용 저수지의 용수공급능력, 농업적 가뭄 피해 지역의 관련 자료 등을 수집하여 농업 가뭄의 직접 피해를 중심으로 기상학적 가뭄 정도에 따른 농업적 가뭄 피해에 대한 상관성을 살펴보고자 한다.