• Journal of Korea Water Resources Association
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• v.37 no.10
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• pp.813-822
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• 2004

This study quantifies and compares the drought return and duration characteristics by applying the Poisson process as well as based on by analyzing the observed data directly. The drought spatial distributions derived for the Gyunggi province are also compared. The monthly rainfall data are used to construct the SPI as a drought index. Especially, this study focuses on the evaluation of the Poisson process model when applying it to various data lengths such as in the spatial analysis 'of drought. Summarizing the results are as follows. (1) The Poisson process is found to be effective for the quantification of drought, especially when the data length is short. When applying the Poisson process, two neighboring sites are found insensitive to the data length to show similar drought characteristics, so the overall drought pattern becomes smoother than that derived directly from the observed data. (2) When the data length is very different site by site, the spatial analysis of drought based on a model application seems better than that based on the direct data analysis. This study also found more obvious spatial pattern of drought occurrence and duration when applying the Poisson process.

• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.351-359
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• 2016

This study was conducted to analyze the effect of climate change on the tree-ring growth of Pinus koraiensis in Korea. Annual tree-ring growth data of P. koraiensis collected by the $5^{th}$ National Forest Inventory were first organized to analyze yearly growth patterns of the species. When tree-ring growth data were analyzed through cluster analysis based on similarity of climatic conditions, five clusters were identified. Yearly growing degree days and standard precipitation index based on daily mean temperature and precipitation data from 1951 to 2010 were calculated by cluster. Using the information, yearly temperature effect index(TEI) and precipitation effect index(PEI) by cluster were estimated to analyze the effect of climatic conditions on the growth of the species. Tree-ring growth estimation equations by cluster were developed by using the product of yearly TEI and PEI as independent variable. The tree-ring growth estimation equations were applied to the climate change scenarios of RCP 4.5 and RCP 8.5 for predicting the changes in tree-ring growth by cluster of P. koraiensis from 2011 to 2100. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics of P. koraiensis and for predicting changes in tree-ring growth patterns caused by climate change.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.14-26
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• 2016

This study analyzed the correlation between the standardized precipitation index(SPI) and forest fire occurrences using monthly accumulative rainfall data since 1970 and regional fire occurrence data since 1991. To understand the relationship between the SPI and forest fire occurrences, the correlations among the SPI of nine main observatory weather stations including Seoul, number of fire occurrences, and log of fire occurrences were analyzed. We analyzed the correlation of SPI with fire occurrences in the 1990s and 2000s and found that in the 1990s, the SPI of 3 months showed high correlation in Gyeonggi, Gangwon, and Chungnam, while the SPI of 6 months showed high correlation in Chungbuk, and the SPI of 12 months showed high correlation in Gyeongnam, Gyenongbuk, Jeonnam, and Jeonbuk. In the 2000s, the SPI of 6 months showed high correlation with the fire frequency in Gyeonggi, Chungnam, Chungbuk, Jeonnam, and Jeonbuk, whereas the fire frequency in western Gangwon was highly correlated with the SPI of 3 months and, in eastern Gangwon, Gyeongnam, and Gyenongbuk, with the SPI of 1 month. In the 1990s, distinct differences in the drought condition between the SPI of 3 months and 12 months in the northern and southern regions of Korean Peninsula were found, whereas the differences in both the SPI of 1 month and 6 months were found in the Baekdudaegan region except western Gangwon since the 2000s. Therefore, this study suggests that we can develop a model to predict forest fire occurrences by applying the SPI of 1-month and 6-month data in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.69-78
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• 2006

The rainfall depth-area-duration analysis which is used to characterize precipitation extremes for specification of so-called design storms, provides a basis for evaluation of drought severity when storm depth is replaced by an appropriate measure of drought severity. So we propose a method for constructing drought severity-area-duration curves in this study. Monthly precipitation data over the whole Korea are used to compute SPI. Such SPIs are abstracted to several independent spatial components from EOF analysis. Using Kriging method, these spatial components are used to constitute grid-based SPI data set over the whole Korea including Jeju island with $6km{\times}6km$ resolution. After identifying main drought events, the drought severity-area-duration curves for these events over 32-year period of record are finally constructed. As a result, such curves show the similar shape with storm-based curves in the sense that the drought severity (or rainfall depth) is inversely proportional to drought area from the curves, but drought-based curves are different from storm-based curves in the sense that the drought severity decreasing rate with respect to drought area is much less than depth decreasing rate.

• Journal of Korea Water Resources Association
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• v.54 no.8
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• pp.577-587
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• 2021

Drought is generally considered to be a natural disaster caused by accumulated water shortages over a long period of time, taking months or years and slowly occurring. However, climate change has led to rapid changes in weather and environmental factors that directly affect agriculture, and extreme weather conditions have led to an increase in the frequency of rapidly developing droughts within weeks to months. This phenomenon is defined as 'Flash Drought', which is caused by an increase in surface temperature over a relatively short period of time and abnormally low and rapidly decreasing soil moisture. The detection and analysis of flash drought is essential because it has a significant impact on agriculture and natural ecosystems, and its impacts are associated with agricultural drought impacts. In South Korea, there is no clear definition of flash drought, so the purpose of this study is to identify and analyze its characteristics. In this study, flash drought detection condition was presented based on the satellite-derived drought index Evaporative Stress Index (ESI) from 2014 to 2018. ESI is used as an early warning indicator for rapidly-occurring flash drought a short period of time due to its similar relationship with reduced soil moisture content, lack of precipitation, increased evaporative demand due to low humidity, high temperature, and strong winds. The flash droughts were analyzed using hydrometeorological characteristics by comparing Standardized Precipitation Index (SPI), soil moisture, maximum temperature, relative humidity, wind speed, and precipitation. The correlation was analyzed based on the 8 weeks prior to the occurrence of the flash drought, and in most cases, a high correlation of 0.8(-0.8) or higher(lower) was expressed for ESI and SPI, soil moisture, and maximum temperature.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.143-147
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• 2000

This study was conducted to investigate suitable seeding rate under irrigation water-saving rice culture in ridge direct seeding on dry paddy during 1997~1998. Dongjinbyeo was seeded from 60 kg/ha to 120 kg/ha on silty loam condition. The number of irrigation from 3-leaf stage to complete drainage were 7.5 times and total amount of irrigation was 258.75 mm. The number of seedling stand rose with the increase of seeding rate, whereas the rate of seedling stand was decreased with the increase of it. Soil moisture tension was -2kPa at one day after stopped irrigation and lowered to -30kPa at five days after stopped irrigation. Leaf area index and shoot dry weight were increased with rising of seeding rate. Lodging index was increased with the rising of seeding rate, but lodging was not showed in field. Heading date, percent ripened grain and 1,000 grain weight had no difference with seeding rate, and number of spikelets per m$^2$ were highest at the rate of 100 kg/ha. Rice yield was increased by 9% at the seeding rate of 100 kg/ha and 4% at the rate of 80 kg/ha and 120 kg/ha compared with 60 kg/ha. Therefore, it was considered that appropriate seeding rate was 100 kg/ha under water-saving culture in ridge direct seeding on dry paddy.

• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.293-303
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• 2016

This study implemented a comparison of SPI characteristics in terms of quantitative and spatial analysis depending on four RCP scenarios. For this purpose, we compared quantitative characteristics of drought using standard precipitation index resulted from daily precipitation data reflecting future green gas concentration scenarios, and spatial distribution field of seasonal drought occurrence frequency and its duration, was analyzed to compare drought trends depending on the RCP scenarios. As a result, we found that SPI time series was quite different from each other and correlation coefficients were lower than 0.08. Depending on the RCP scenarios, spatial distribution results showed different trends in drought severity, frequency, and duration. The biggest reason of the difference is daily precipitation data based on the different greenhouse gas concentrations, but we could not find the effect of the concentration extent on drought occurrence projection. In addition, according to the results from this study, drought analysis results using single RCP scenario may have considerable uncertainty.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.105-105
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• 2018

2017년 이상기후 보고서에 따르면, 지난해 장마기간(6월 24일~7월 29일) 동안 전국 평균 강수량은 291.7mm로 평년(356.1mm)의 81%에 그쳤고, 7월 전국 평균기온은 $26.4^{\circ}C$로 평년($24.5^{\circ}C$) 보다 $1.9^{\circ}C$ 높았으며, 폭염일수는 평년대비 1.5배 많았음을 보고했다. 이러한 극심한 기후변화는 유역환경에 영향을 미쳐 미래 수자원 계획과 관리에 어려움을 가중시킬 것으로 예상된다. 이에 본 연구에서는 금강유역($9,865km^2$)을 대상으로 SWAT(Soil and Water Assessment Tool)모형과 RCP(Representative Concentration Pathway) 기후변화 시나리오를 이용하여 극한 기후변화 사상에 따른 수문 수질 거동을 평가하고자 하였다. 유역의 물수지 분석을 위해 금강 유역을 표준단위유역으로 구분 하였고, 기상자료와 다목적댐 2개(대청댐, 용담댐)과 다기능 보 3개(공주보, 백제보, 세종보)의 운영 자료와 국가 수자원관리 종합 정보 시스템(WAMIS)에서 관측 및 관리하고 있는 수문, 기상 자료를 수집하였다. SWAT 모형의 신뢰성 있는 수문 및 수질 보정을 위해 금강 소유역 내 위치하는 다목적 댐 2개 및 다기능 보 3개의 실측 방류랑을 이용하여 댐 운영모의를 하였으며, 댐 운영 자료와 수질 자료를 이용하여 모형의 검정 및 보정(2000~2015)을 실시하였다. 미래 극한 기후변화 사상을 모의하기 위해 기후변화 시나리오는 APCC의 26개 CMIP5 GCM 자료 중 RCP 8.5 시나리오를 활용했으며, 극한 기후 시나리오 선정을 위해 STARDEX에서 제시한 강우관련 극한지수를 이용했다. 선정된 홍수 및 가뭄 시나리오에 대해 Historical기간(1976~2005)과 미래기간(2006~2099)을 설정하여 미래 극한 기후변화 사상에 따른 금강유역의 수문 및 수질의 거동을 평가하였다.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.329-340
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• 2021

Purpose: In this paper, using artificial neural network algorithm, the Korean Peninsula was analyzed for drought vulnerable areas by predicting weather data changes. Method: Monthly cumulative precipitation data were utilized for research areas considering the specific nature areas, and weather data prediction through artificial neural network algorithm was carried out using statistical program R. The predicted data were applied to the Standardized Precipitation Index (SPI) to analyze drought vulnerable areas in the Korean Peninsula. Result: In this paper, the correlation coefficient values between real and predicted data are found to be 0.043879 higher on average than the regression results, using artificial neural network algorithms. Conclusion: The results of the research are expected to be used as basic research materials for responding to drought.

• Journal of the Korean earth science society
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• v.41 no.2
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• pp.129-136
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• 2020

Drought is an environmental disaster typically defined as an unusual deficiency of water supply over an extended period. Satellite remote sensing provides an alternative approach to monitoring drought over large areas. In this study, we monitored drought patterns over about 30 years (1985-2015), using satellite imagery of Lake Soyang, Gangwondo, South Korea. Landsat images were classified using ISODATA, maximum likelihood analysis, and an artificial neural network to derive the lake area. In addition, the relationship between areas of Lake Soyang and the Standardized Precipitation Index (SPI) was analyzed. The results showed that the artificial neural network was a better method for determining the area of the lake. Based on the relationship between the SPI value and changes in area, the R² value was 0.52. This means that the area of the lake varied depending on SPI value. This study was able to detect and monitor drought conditions in the Lake Soyang area. The results of this study are used in the development of a regional drought monitoring program.