• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.305-314
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• 2016

In this study, a quantitative assessment was carried out in order to identify the agricultural drought in time and space using the Terra MODIS remote sensing data for the agricultural drought. The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) were selected by MOD13A3 image which shows the changes in vegetation conditions. The land cover classification was made to show only vegetation excluding water and urbanized areas in order to collect the land information efficiently by Type1 of MCD12Q1 images. NDVI and EVI index calculated using land cover classification indicates the strong seasonal tendency. Therefore, standardized Vegetation Stress Index Anomaly (VSIA) of EVI were used to estimated the medium-scale regions in Korea during the extreme drought year 2001. In addition, the agricultural drought damages were investigated in the country's past, and it was calculated based on the Standardized Precipitation Index (SPI) using the data of the ground stations. The VSIA were compared with SPI based on historical drought in Korea and application for drought assessment was made by temporal and spatial correlation analysis to diagnose the properties of agricultural droughts in Korea.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.745-758
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• 2017

The copula-based models have been successfully applied to hydrological modeling including drought frequency analysis and time series modeling. However, uncertainty estimation associated with the parameters of these model is not often properly addressed. In these context, the main purposes of this study are to develop the Bayesian inference scheme for bivariate copula functions. The main applications considered are two-fold: First, this study developed and tested an approach to copula model parameter estimation within a Bayesian framework for drought frequency analysis. The proposed modeling scheme was shown to correctly estimate model parameters and detect the underlying dependence structure of the assumed copula functions in the synthetic dataset. The model was then used to estimate the joint return period of the recent 2013~2015 drought events in the Han River watershed. The joint return period of the drought duration and drought severity was above 100 years for many of stations. The results obtained in the validation process showed that the proposed model could effectively reproduce the underlying distribution of observed extreme rainfalls as well as explicitly account for parameter uncertainty in the bivariate drought frequency analysis.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.523-534
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• 2021

Meteorological drought originates from a precipitation deficiency and propagates to agricultural and hydrological droughts through the hydrological cycle. Comparing with the meteorological drought, agricultural and hydrological droughts have more direct impacts on human society. Thus, understanding how meteorological drought evolves to agricultural and hydrological droughts is necessary for efficient drought preparedness and response. In this study, meteorological and hydrological droughts were defined based on the observed precipitation and the synthesized streamflow by the land surface model. The Bayesian network model was applied for probabilistic analysis of the propagation relationship between meteorological and hydrological droughts. The copula function was used to estimate the joint probability in the Bayesian network. The results indicated that the propagation probabilities from the moderate and extreme meteorological droughts were ranged from 0.41 to 0.63 and from 0.83 to 0.98, respectively. In addition, the propagation probabilities were highest in autumn (0.71 ~ 0.89) and lowest in winter (0.41 ~ 0.62). The propagation probability increases as the meteorological drought evolved from summer to autumn, and the severe hydrological drought could be prevented by appropriate mitigation during that time.

• Journal of Ecology and Environment
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• v.33 no.1
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• pp.47-57
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• 2010

To understand day-to-day fluctuations in soil moisture content in Seoul, I simulated daily soil moisture content from 1908 to 2009 using long-term climatic precipitation and temperature data collected at the Surface Synoptic Meteorological Station in Seoul for the last 98 years with a hydrological simulation model, BROOK. The output data set from the BROOK model allowed me to examine day-to-day fluctuations and the severity and duration of droughts in the Seoul area. Although the soil moisture content is highly dependent on the occurrence of precipitation, the pattern of changes in daily soil moisture content was clearly quite different from that of precipitation. Generally, there were several phases in the dynamics of daily soil moisture content. The period from mid-May to late June can be categorized as the initial period of decreasing soil moisture content. With the initiation of the monsoon season in late June, soil moisture content sharply increases until mid-July. From the termination of the rainy season in mid-July, daily soil moisture content decreases again. Highly stochastic events of typhoons from late June to October bring large amount of rain to the Korean peninsula, culminating in late August, and increase the soil moisture content again from late August to early September. From early September until early October, another sharp decrease in soil moisture content was observed. The period from early October to mid-May of the next year can be categorized as a recharging period when soil moisture content shows an increasing trend. It is interesting to note that no statistically significant increase in mean annual soil moisture content in Seoul, Korea was observed over the last 98 years. By simulating daily soil moisture content, I was also able to reconstruct drought phenomena to understand the severity and duration of droughts in Seoul area. During the period from 1908 to 2009, droughts in the years 1913, 1979, 1939, and 2006 were categorized as 'severe' and those in 1988 and 1982 were categorized as 'extreme'. This information provides ecologists with further potential to interpret natural phenomenon, including tree growth and the decline of tree species in Korea.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.583-595
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• 2002

The purposes of this study are to perform the management and monitoring of droughts for Mokpo area via the monthly Palmer index(PDSI), the data is obtained from the Mokpo meteorological station, and the used data are in the period of 1906 to 1999. Monthly Palmer index is classified into 7 stochastic classes and its dynamic change of monthly transition probability estimated by Markov chain is investigated. We also estimate the steady state probability of the classified PDSI. The 4th class shows the highest frequency of 49.6% out of 7 classes and the 7th class which is the most extreme drought show that a stochastic transition probability is more or less larger than an empirical one. Also, we found that the monthly steady state probability could be used for the forecasting of changing pattern of drought magnitude for the study area.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.4
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• pp.73-82
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• 2018

In this study, we assessed meteorological and agricultural drought based on the SPI(Standardized Precipitation Index), SMP(Soil Moisture Percentile), and SMDI(Soil Moisture Deficit Index) indices using satellite-based TRMM(Tropical Rainfall Measuring Mission)/GPM(Global Precipitation Measurement) images at the province of Chungcheongbuk-do. The long-term(2000-2015) TRMM/GPM precipitation data were used to estimate the SPI values. Then, we estimated the spatially-/temporally-distributed soil moisture values based on the near-surface soil moisture data assimilation scheme using the TRMM/GPM and MODIS(MODerate resolution Imaging Spectroradiometer) images. Overall, the SPI value was significantly affected by the precipitation at the study region, while both the precipitation and land surface condition have influences on the SMP and SMDI values. But the SMP index showed the relatively extreme wet/dry conditions compared to SPI and SMDI, because SMP only calculates the percentage of current wetness condition without considering the impacts of past wetness condition. Considering that different drought indices have their own advantages and disadvantages, the SMDI index could be useful for evaluating agricultural drought and establishing efficient water management plans.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.602-602
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• 2015

가뭄에 대한 정의와 구분이 다양하게 존재하나 일반적으로 기상학적 가뭄으로부터 농업적 가뭄, 수문학적 가뭄, 사회경제학적 가뭄으로 전이되므로 강수량의 부족이 가뭄의 첫 번째 원인인 것은 자명하다. 최근까지 여러 가지 기상학적 가뭄지수가 개발되어 다양한 목적으로 세계 곳곳에서 활용되고 있으나, 그 중 적용사례가 가장 많은 것은 표준강수지수 (SPI; Standardized Precipitation Index)이다. 월단위로 계산되어지는 SPI는 우리나라와 같이 강수의 변동성이 큰 지역에서는 그 활용성이 떨어지는 경우가 있어 최근에는 일 단위 SPI를 산정하여 활용하는 경우도 있다. 그러나, 일단위 SPI는 가뭄기간 동안 가뭄단계가 'Extreme drought'에서 'Moderate drought'로 약해질 경우 가뭄 지속기간이 가장 긴 'Moderate drought' 단계에서 가뭄피해 및 체감하는 고통이 가장 클수 있어, 가뭄에 대응하거나 대국민 가뭄정보 전달에 한계가 있다. 가뭄에 대응하거나 가뭄정보 전달을 위해서는 가뭄이 지속되는 동안 가뭄단계가 높아질 필요성이 있다. 이에 본 연구에서는 가뭄사상의 특성 중 가뭄의 강도(Intensity)와 지속기간(Duration)의 특성을 모두 포함하는 가뭄의 심도(Severity)를 활용하여 기상학적 가뭄을 평가하였다. 일단위 SPI 값(강도)을 가뭄기간동안 누적하여 일단위 가뭄심도(SPI-S)를 산정하고 이를 통해 가뭄단계를 제안하였다. 또한 다양한 SPI 대상기간에 대해 최솟값을 취하는 Blended SPI에 대해서도 같은 방법으로 가뭄심도(SPIB-S)를 산정하고 가뭄단계를 적용하였다. 2001년, 2008-2009년, 2012년 가뭄사례에 적용한 결과 SPI-S(or SPIB-S)는 가뭄기간동안 단계적인 가뭄단계의 상승으로 당시의 가뭄상황을 잘 나타내었다. 이는 SPI-S(or SPIB-S)가 단계적인 가뭄대비와 대응 지수로 가뭄피해 경감에 활용도가 높을 것으로 판단되며, 가뭄상황을 지역민들에게 단계적, 일관적으로 전달할 수 있어 가뭄극복을 위한 시민참여를 유도하기에 유리할 것이다.

• 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 Grassland and Forage Science
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• v.42 no.1
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• pp.1-9
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• 2022

This study was carried out to compare the DMY (dry matter yield) of IRG (Italian ryegrass) in the southern coastal regions of Korea due to seasonal climate scenarios such as the Kaul-Changma (late monsoon) in autumn, extreme winter cold, and drought in the next spring. The IRG data (n = 203) were collected from various Reports for Collaborative Research Program to Develop New Cultivars of Summer Crops in Jeju, 203 Namwon, and Yeungam from the Rural Development Administration - (en DASH). In order to define the seasonal climate scenarios, climate variables including temperature, humidity, wind, sunshine were used by collected from the Korean Meteorological Administration. The discriminant analysis based on 5% significance level was performed to distinguish normal and abnormal climate scenarios. Furthermore, the DMY comparison was simulated based on the information of sample distribution of IRG. As a result, in the southern coastal regions, only the impact of next spring drought on DMY of IRG was critical. Although the severe winter cold was clearly classified from the normal, there was no difference in DMY. Thus, the DMY comparison was simulated only for the next spring drought. Under the yield comparison simulation, DMY (kg/ha) in the normal and drought was 14,743.83 and 12,707.97 respectively. It implies that the expected damage caused by the spring drought was about 2,000 kg/ha. Furthermore, the predicted DMY of spring drought was wider and slower than that of normal, indicating on high variability. This study is meaningful in confirming the predictive DMY damage and its possibility by spring drought for IRG via statistical simulation considering seasonal climate scenarios.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.5
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• pp.961-969
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• 2017

Today, the world is experiencing a variety of natural disasters due to the extreme weather. Drought that occurred throughout Southeast Asia from February to May 2016 is also a form of abnormal climate. As a result of this drought, five countries, including Cambodia, Thailand, Vietnam, Laos and Myanmar, faced food shortages, food shortages, as well as rice yields for export. In this study, remote sensing technique was applied to the vicinity of Tonlé Sap, the largest lake in Southeast Asia, to quantitatively analyze the damage caused by drought. As a result, the change of land cover caused a drastic decrease in the water system (132.582㎢) and greenery (706.937㎢) in February 2016, and the reduced water system and greenery changed to dry land and paddy field. It was also found that the temperature rise of 6℃ ~ 8 ℃ compared to the previous year due to the drought from February to April 2016 due to the change of the surface temperature. And it was found that the function of the lake was deteriorated in April due to continuous drought.