• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.867-872
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• 2005

This study introduces a method to evaluate the probability of a specific area to be affected by a drought of a given severity and shows its potential for investigating agricultural drought characteristics. The method is applied to Gyeonggi as a case study. The proposed procedure includes Standard Precipitation Index(SPI) time series, which are linearly transformed by the Empirical Orthogonal Functions(EOF) method, These EOFs are extended temporally with AutoRegressive Moving Average(ARMA) method and spatially with Kriging method. By performing these simulations, long time series of SPI can be simulated for each designed grid cell in whole Gyeonggi area. The probability distribution functions of the area covered by a drought and the drought severity are then derived and combined to produce drought severity-area-frequency(SAF) curves.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.729-735
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• 2023

The Moderate resolution Imaging Spectroradiometer (MODIS) is a multispectral sensor that has been actively researched in various fields using diverse land and atmospheric products. MODIS was first launched over 20 years ago, and the demand for novel sensors that can produce data comparable to that obtained using MODIS has continuously increased. In this study, land products obtained using the Visible Infrared Imaging Radiometer Suite (VIIRS) of the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite launched in 2011 were introduced, including land surface temperature and vegetation indices such as the normalized difference vegetation index and enhanced vegetation index. These land products were compared with existing data obtained using MODIS to verify their local applicability in South Korea. Based on spatiotemporal monitoring of an extreme drought period in South Korea and the application of VIIRS land products, our results indicate that VIIRS can effectively replace MODIS multispectral sensors for agricultural drought monitoring.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.57-70
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• 2017

In this study, we evaluated daily root zone soil moisture dynamics and agricultural drought using a near-surface soil moisture data assimilation scheme with Soil Moisture Active & Passive (SMAP, $3km{\times}3km$) soil moisture footprints under different hydro-climate conditions. Satellite-based LANDSAT and MODIS image footprints were converted to spatially-distributed soil moisture estimates based on the regression model, and the converted soil moisture distributions were used for assessing uncertainties and applicability of SMAP data at fields. In order to overcome drawbacks of the discontinuity of SMAP data at the spatio-temporal scales, the data assimilation was applied to SMAP for estimating daily soil moisture dynamics at the spatial domain. Then, daily soil moisture values were used to estimate weekly agricultural drought based on the Soil Moisture Deficit Index (SMDI). The Yongdam-dam and Soyan river-dam watersheds were selected for validating our proposed approach. As a results, the MODIS/SMAP soil moisture values were relatively overestimated compared to those of the TDR-based measurements and LANDSAT data. When we applied the data assimilation scheme to SMAP, uncertainties were highly reduced compared to the TDR measurements. The estimated daily root zone soil moisture dynamics and agricultural drought from SMAP showed the variability at the sptio-temporal scales indicating that soil moisture values are influenced by not only the precipitation, but also the land surface characteristics. These findings can be useful for establishing efficient water management plans in hydrology and agricultural drought.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.1-11
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• 2019

Remote sensing products have long been used to monitor and forecast natural disasters. Satellite-derived rainfall products are becoming more accurate as space and time resolution improve, and are widely used in areas where measurement is difficult because of the periodic accumulation of images in large areas. In the case of North Korea, there is a limit to the estimation of precipitation for unmeasured areas due to the limited accessibility and quality of statistical data. CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) is global satellite-derived rainfall data of 0.05 degree grid resolution. It has been available since 1981 from USAID (U.S. Agency for International Development), NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration). This study evaluates the applicability of CHIRPS rainfall products for South Korea and North Korea by comparing CHIRPS data with ground observation data, and analyzing temporal and spatial drought trends using the Standardized Precipitation Index (SPI), a meteorological drought index available through CHIRPS. The results indicate that the data set performed well in assessing drought years (1994, 2000, 2015 and 2017). Overall, this study concludes that CHIRPS is a valuable tool for using data to estimate precipitation and drought monitoring in Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4B
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• pp.203-211
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• 2012

Once drought occurs, it results in the extensive affected area and considerable socio-economic damages. Thus, it is necessary to assess drought risk and to prepare its counterplans. In this study, using various observation data on meteorological and socio-economical factors, drought risk was evaluated in South Korea. To quantify drought risk, Drought Hazard Index (DHI) was calculated based on the occurrence probability of drought, and Drought Vulnerability Index (DVI) was computed to reflect socio-economic consequences of drought. Drought Risk Index (DRI) was finally suggested by combining DHI and DVI. These indices were used to assess drought risk for different administrative districts of South Korea. The overall results show that the highest drought risk area was Jeolla Province where agricultural practice is concentrated. The drought risk map proposed in this study reflects regional characteristics, thus it could be utilized as a basic data for the establishment of drought preventive measures.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.236-239
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• 2009

우리나라는 계절적으로 편중된 강우특성 때문에 가용 수자원이 충분하지 않고 최근엔 빈번하게 발생하는 이상기후현상과 국지성기후로 인해 가뭄의 빈도 및 강도가 증대되고 있어 기후변화에 적응할 수 있는 농촌용수 물관리 대책과 가뭄대응능력 개선의 필요성이 요구되고 있다. 이러한 가뭄의 관리를 위해서는 시간적인 가뭄의 발생과 공간적인 가뭄의 분포를 파악하여 적절한 가뭄평가 수단을 통한 가뭄대책 수립기준을 설정하고 이에 대한 대책방안을 마련하여 각 지역별 특성에 맞는 가뭄대책을 수립해야 한다. 따라서 본 연구에서는 농업가뭄을 극복하고 농촌수자원의 안정적 확보와 효율적인 이용을 위해서 농업가뭄 상황을 분석하고 평가할 수 있으며 농업가뭄대책의 수립과 시행을 뒷받침할 수 있는 Web 및 GIS 기반농업가뭄관리시스템을 제안하고자 한다. 기존의 개발된 토양수분지수(Soil Moisture Index, SMI)와 저수지가뭄지수(Reservoir Drought Index, RDI)를 통합한 통합농업가뭄지수(Integrated Agricultural Drought Index, IADI)을 이용하여 다양한 시나리오를 통해 가뭄의 여러 가지 패턴에 따른 지역별 농업가뭄의 위험과 예측 피해를 설명하고, 가뭄관리에 필요한 정보를 단계적으로 제공함으로써 실제 물 관리 및 가뭄대책 업무에 반영하고 적절한 대응책을 수립하는데 기초자료가 될 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.364-364
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• 2019

최근 전세계적으로 기후변화로 인한 국내외 가뭄에 대한 피해 및 발생 빈도가 점차 증가하고 있으며, 우리나라의 경우 2000년대 이후 가뭄 주기가 점점 짧아져 2013년 이후 매년 가뭄이 발생하고 있다. 북한은 자연재해에 취약한 국가이며 특히 가뭄으로 인한 식량난 문제가 대두되고 있지만, 북한의 제한적인 정보로 인해 북한 지역에서의 가뭄의 발생과 피해 정보는 한정적이고, 활용할 수 있는 자료의 경우 외국 기관의 정보에 의존하는 실정이다. 향후 농업부문에 대한 대북한 지원과 통일 후를 대비한 농업정책의 수립을 위하여 북한의 가뭄에 대하여 독자적으로 신속한 정보를 취득, 분석할 수 있는 능력을 확보하는 것이 필요하다. 위성영상을 이용한 원격탐사 기술은 접근이 용이하지 못한 지역의 주기적인 관측이 가능하며, 동일한 정확도로 기상자료의 획득이 가능하다. Vegetation Drought Response Index (VegDRI)는 위성영상기반의 가뭄지수인 정규식생지수(Nomalized Difference Vegetation Index, NDVI), 기상학적 가뭄지수를 활용한 기후적 요소, 토지피복 및 생태지역 등의 생물물리학적 요소를 활용한 가뭄지표이다. 본 연구에서는 MODerate resolution Imaging Spectroradiometer (MODIS) 위성의 MOD13Q1 영상자료의 NDVI (2001~2018년)를 이용하였으며, 북한의 기상자료를 이용한 표준강수지수 (Standardized Precipitation Index, SPI)와 파머가뭄심도지수 (Palmer Drought Severity Index, PDSI), 그리고 북한 지역의 토지피복 및 생태지역 등의 요소들을 활용한 VegDRI를 통하여 북한의 가뭄 시기에 따른 시도별 가뭄 특성에 대하여 분석하고자 한다.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.6
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• pp.1-8
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• 2016

Crop damages due to agricultural drought has been increased in recent years. In Korea, water resources are limited indicating that proper management plans against agricultural drought are required for better water-use efficiency in agriculture. In this study, irrigation intervals and amounts for various crops and soil physical properties (sandy and silt loams) were estimated using the IWMM model. Five different crops (soybean, radish, potato, barley and maize) at the Bangdong-ri site in Chuncheon were selected to test the IWMM model. IWMM assessed agricultural drought conditions using the soil moisture deficit index (SMDI), and irrigation intervals and amounts were determined based on the degree of agricultural drought (SMDI). Additionally, we tested the effects of surface irrigation and sprinkler irrigation methods and various irrigation intervals of 2, 3, 5 and 7 days. In our findings, the irrigation intervals of 5 and 7 days showed the minimum rrigation amounts than others. When we considered that the intervals of 3 or 5 days are usually preferred to fields, the interval of 5 days was determined in our study. The estimated irrigation amounts for different crops were shown as maize > radish > barley > soybean > potato, respectively. The irrigation amounts for maize and barley were highly affected by soil properties, but other crops have less differences. Also, small differences in irrigation amounts were shown between the surface and sprinkler irrigation methods. These might be due to the lack of consideration of water loss (e.g., evapotranspiration, infiltration, etc.) in IWMM indicating model structural uncertainties. Thus, possible water loss (e.g., evapotranspiration, infiltration) need to be considered in application to fields. Overall, IWMM performed well in determining the irrigation intervals and amounts based on the degree of agricultural drought conditions (SMDI). Thus, the IWMM model can be useful for efficient agricultural water resources management in regions at where available water resources are limited.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.61-74
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• 2019

In this study, the SPI (Standardized Precipitation Index) of meteorological drought and SDI (Streamflow Drought Index) of hydrological drought for 1, 3, 6, 9, and 12 months duration were estimated to analyse the characteristics of drought using rainfall and dam inflow data for Chungju dam ($6,661.8km^2$) with 31 years (1986-2016) and Boryeong dam ($163.6km^2$) watershed with 19 years (1998-2016) respectively. Using the estimated SPI and SDI, the drought forecasting was conducted using seasonal autoregressive integrated moving average (SARIMA) model for the 5 durations. For 2016 drought, the SARIMA had a good results for 3 and 6 months. For the 3 months SARIMA forecasting of SPI and SDI, the correlation coefficient of SPI3, SPI6, SPI12, SDI1, and SDI6 at Chungju Dam showed 0.960, 0.990, 0.999, 0.868, and 0.846, respectively. Also, for same duration forecasting of SPI and SDI at Boryeong Dam, the correlation coefficient of SPI3, SPI6, SDI3, SDI6, and SDI12 showed 0.999, 0.994, 0.999, 0.880, and 0.992, respectively. The SARIMA model showed the possibility to provide the future short-term SPI meteorological drought and the resulting SDI hydrological drought.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.6
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• pp.434-444
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• 2013

In order to evaluate drought risk at upland according to climate change scenario (RCP8.5), we have carried out the simulation using agricultural water balance estimation model, called AFKAE0.5, at 66 weather station sites in 2020, 2046, 2050, 2084, and 2090. Total Drought Risk Index between the first month (f) and last month (l) (TDRI(f/l)) and maximum continuous drought risk index (MCDRI(f/l)) were defined as the index for analyzing pattern and strength of drought simulated by the model. Based on distribution maps of MCDRI (1/12), drought strength was predicted to be most severe in 2084 for all regions. Some regions showed severe risk of drought meaning over 20 days of MCDRI (1/12) in the other years, while MCDRI (1/12) in other regions did not reach 5 days. Even though maximum value of TDRI (1/12) in 2090 was greater than in 2050, more severe drought risk in 2050 than in 2090 was predicted based on MCDRI (4/6). It implies that drought risk should be assessed for each crop with its own growing season.