• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1851-1860
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• 2013

The Standardized Precipitation Index (SPI) is widely applied to evaluate for meteorological droughts. However, the SPI is limited to capture a drought event with a short duration, expecially shorter than one month. In this study, we proposed a daily SPI (DSPI) as a way to overcome the limitation of the monthly SPI for drought monitoring. In order to objectively assess the ability of the drought reproduction of the DSPI, we performed a receiver operating characteristic (ROC) analysis using the quantified drought records from official reports, newspapers, etc. The results of ROC analysis showed that the DSPI has an ability to reproduce short-term drought compared with other indices. It also showed that the main cause of historical droughts was the shortage of rainfall accumulated during the time period less than 90 days compared with the rainfall of normal years.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.65-73
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• 2017

This study analyzed the peak drought severity and drought duration of the Cheongmicheon watershed from 1985 to 2015 to assess the lag time of peak drought severity between several drought indices. Standardized Precipitation Index (SPI) based on precipitation and Standardized Precipitation Evapotranspiration Index (SPEI) based on precipitation and evapotranspiration were applied as meteorological drought indices. Streamflow Drought Index (SDI) based on runoff data was applied as hydrological drought index. In case of SDI, we used Soil and Water Assessment Tool (SWAT) model for simulation of daily runoff data. As a result, the time of peak drought severity of SDI occurred after the occurrence of SPI and SPEI. The lag time for the peak drought severity, on average, between SDI and SPI was 0.59 months while SDI and SPEI was 0.79 months. As compared with SDI, the maximum delay was 2 months for both SPI and SPEI. This study results also shows that even though the rainfall events were able to cope with meteorological droughts, they were not always available to solve the hydrological droughts in the same time.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.195-207
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• 2024

This study selected major drought events that occurred in the Jeonnam region from 1991 to 2023, examining both meteorological and hydrological drought occurrence mechanisms. The daily drought index was calculated using rainfall and dam storage as input data, and the drought propagation characteristics from meteorological drought to hydrological drought were analyzed. The characteristics of the 2022-23 drought, which recently occurred in the Jeonnam region and caused serious damage, were evaluated. Compared to historical droughts, the duration of the hydrological drought for 2022-2023 lasted 334 days, the second longest after 2017-2018, the drought severity was evaluated as the most severe at -1.76. As a result of a linked analysis of SPI (StandQardized Precipitation Index), and SRSI (Standardized Reservoir Storage Index), it is possible to suggest a proactive utilization for SPI(6) to respond to hydrological drought. Furthermore, by confirming the similarity between SRSI and SPI(12) in long-term drought monitoring, the applicability of SPI(12) to hydrological drought monitoring in ungauged basins was also confirmed. Through this study, it was confirmed that the long-term dryness that occurs during the summer rainy season can transition into a serious level of hydrological drought. Therefore, for preemptive drought response, it is necessary to use real-time monitoring results of various drought indices and understand the propagation phenomenon from meteorological-agricultural-hydrological drought to secure a sufficient drought response period.

• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.1
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• pp.112-117
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• 2012

The Revised Universal Soil Loss Equation (RUSLE) is a revision of the Universal Soil Loss Equation (USLE). However, changes for each factor of the USLE have been made in RUSLE which can be used to compute soil loss on areas only where significant overland flow occurs. RUSLE which requires standardized methods to satisfy new data requirements estimates soil movement at a particular site by utilizing the same factorial approach employed by the USLE. The rainfall erosivity in the RUSLE expressed through the R-factor to quantify the effect of raindrop impact and to reflect the amount and rate of runoff likely is associated with the rain. Calculating the R-factor value in the RUSLE equation to predict the related soil loss may be possible to analyse the variability of rainfall erosivity with long time-series of concerned rainfall data. However, daily time step models cannot return proper estimates when run on other specific rainfall patters such as storm and daily cumulative precipitation. Therefore, it is desirable that cross-checking is carried out amongst different time-aggregations typical rainfall event may cause error in estimating the potential soil loss in definite conditions.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.126-126
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• 2022

Climate change has continued to impact meteorological factors like rainfall in many countries including Nigeria. Thus, altering the rainfall patterns which subsequently affect the crop yield. Maize is an important cereal grown in northern Nigeria, along with sorghum, rice, and millet. Due to the challenge of water scarcity during the dry season, it has become critical to design appropriate strategies for planning, developing, and management of the limited available water resources to increase the maize yield. This study, therefore, determines the quantity of water required to produce maize from planting to harvesting and the impact of drought on maize during different growth stages in the region. Rainfall data from six rain gauge stations for a period of 36 years (1979-2014) was considered for the analysis. The standardized precipitation and evapotranspiration index (SPEI) is used to evaluate the severity of drought. Using the CROPWAT model, the evapotranspiration was calculated using the Penman-Monteith method, while the crop water requirements (CWRs) and irrigation scheduling for the maize crop was also determined. Irrigation was considered for 100% of critical soil moisture loss. At different phases of maize crop growth, the model predicted daily and monthly crop water requirements. The crop water requirement was found to be 319.0 mm and the irrigation requirement was 15.5 mm. The CROPWAT 8.0 model adequately estimated the yield reduction caused by water stress and climatic impacts, which makes this model appropriate for determining the crop water requirements, irrigation planning, and management.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.168-168
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• 2020

This study is to evaluate the drought-related bigdata characteristics published from South Korean by developing crawler. The 5 years (2013 ~ 2017) drought-related posted articles were collected from Korean internet search engine 'NAVER' which contains 13 main and 81 local daily newspapers. During the 5 years period, total 40,219 news articles including 'drought' word were found using crawler. To filter the homonyms liken drought to soccer goal drought in sports, money drought economics, and policy drought in politics often used in South Korea, the quality control was processed and 47.8 % articles were filtered. After, the 20,999 (52.2 %) drought news articles of this study were classified into four categories of water deficit (WD), water security and support (WSS), economic damage and impact (EDI), and environmental and sanitation impact (ESI) with 27, 15, 13, and 18 drought-related keywords in each category. The WD, WSS, EDI, and ESI occupied 41.4 %, 34.5 %, 14.8 %, and 9.3 % respectively. The drought articles were mostly posted in June 2015 and June 2017 with 22.7 % (15,097) and 15.9 % (10,619) respectively. The drought news articles were spatiotemporally compared with SPI (Standardized Precipitation Index) and RDI (Reservoir Drought Index) were calculated. They were classified into administration boundaries of 8 main cities and 9 provinces in South Korea because the drought response works based on local government unit. The space-time clustering between news articles (WD, WSS, EDI, and ESI) and indices (SPI and RDI) were tried how much they have correlation each other. The spatiotemporal clusters detection was applied using SaTScan software (Kulldorff, 2015). The retrospective and prospective cluster analyses were conducted for past and present time to understand how much they are intensive in clusters. The news articles of WD, WSS and EDI had strong clusters in provinces, and ESI in cities.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.328-328
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• 2023

표준강수지수(Standardized Precipitation Index, SPI)는 강수량 변동의 정도를 표준화하여 나타낸 지수로, 가뭄 평가에 적용되고 있다. 일반적으로 SPI를 산정할 때는 월 단위의 시간 척도를 적용하며, 장기간의 가뭄에 대해 평가한다. 그러나 시간 척도가 길어질수록 가뭄 발생 후 가뭄을 감지하는 데 걸리는 시간이 더 길어지기 때문에 대처가 더욱 어려워진다. 또한, 기후변화로 인해 가뭄 빈도가 증가하고, 그 정도가 더욱 심화되면서 일 단위의 적용이 필요해지고 있다. 본 연구는 한반도 남부지역을 대상으로 일 단위의 SPI 적용을 위한 최소 시간 척도를 조사하였다. 대상 지역을 강원권, 수도권, 부울경, 대경권, 호남권, 충청권의 총 6개 지역으로 분리하여, 각 지역별, 계절별 최소 시간 척도를 조사하였다. SPI 산정을 위해 후보 분포형으로 Gumbel, Gamma, GEV, Loglogistic, Lognormal, Weibull을 적용하였으며, 시간 척도는 5일부터 365일까지 총 10개로 설정하였다. 본 연구에선 크게 적합도 검정과 정규성 검정으로 진행하였다. 적합도 검정에서는 Chi-square test를 적용하였으며, 이때 일 단위의 짧은 시간 척도를 적용할 경우 누가 강수 시계열의 값이 0으로, 0값이 시계열에 포함되면 SPI의 정확도가 떨어지는 문제가 발생하는데, 이를 보완하기 위해 누가 강수 시계열의 0값을 고려하였다. 마지막으로 각 후보 분포형을 적용하여 산정된 SPI가 표준정규분포에 합당한지를 검증하기 위해 Anderson-Darling test를 수행하였다. 결과적으로 대부분의 지역에서는 봄과 여름의 경우 최소 15일 정도의 시간 척도까지는 적용할 수 있을 것으로 판단되며, 겨울의 경우는 최소 30일 정도의 시간 척도를 적용해야 함을 확인하였다. 지역별로 차이가 크진 않지만, 이러한 연구 결과를 참고하여 각 지역별로 더 나은 가뭄 대책을 마련할 수 있을 것으로 기대된다.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.107-119
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• 2020

This study analyzed past drought characteristics based on the observed rainfall data and performed a long-term outlook for future extreme droughts using Representative Concentration Pathways 8.5 (RCP 8.5) climate change scenarios. Standardized Precipitation Index (SPI) used duration of 1, 3, 6, 9 and 12 months, a meteorological drought index, was applied for quantitative drought analysis. A single long-term time series was constructed by combining daily rainfall observation data and RCP scenario. The constructed data was used as SPI input factors for each different duration. For the analysis of meteorological drought observed relatively long-term since 1954 in Korea, 12 rainfall stations were selected and applied 10 general circulation models (GCM) at the same point. In order to analyze drought characteristics according to climate change, trend analysis and clustering were performed. For non-stationary frequency analysis using sampling technique, we adopted the technique DEMC that combines Bayesian-based differential evolution ("DE") and Markov chain Monte Carlo ("MCMC"). A non-stationary drought frequency analysis was used to derive Severity-Duration-Frequency (SDF) curves for the 12 locations. A quantitative outlook for future droughts was carried out by deriving SDF curves with long-term hydrologic data assuming non-stationarity, and by quantitatively identifying potential drought risks. As a result of performing cluster analysis to identify the spatial characteristics, it was analyzed that there is a high risk of drought in the future in Jeonju, Gwangju, Yeosun, Mokpo, and Chupyeongryeong except Jeju corresponding to Zone 1-2, 2, and 3-2. They could be efficiently utilized in future drought management policies.