• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.991-993
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• 2003

The 4 sets of environmental variables dealing with meteorology, hydrology and physiography were analyzed to generate a spatial drought risk index of Phitsanulok province of Thailand. The analysis of K-mean and discriminant were applied to the set of the selective drought variables for grouping each of spatial variable set into 4 classes. The obtained 4 classes, based on group statistics, were thus recoded in the meaning of no risk, low risk, moderate risk, and high risk. The regression coefficient between recoded classes and a set of the selective environmental variables were then applied as spatial variable weighting on thematic dataset in GIS spatial analysis. The results showed that the weighting score of drought variable was highest in meteorological variable compared to other variables.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.4
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• pp.37-48
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• 2018

The extreme 2017 spring drought affected a large portion of central and western South Korea, and was one of the most climatologically driest spring seasons over the 1961-2016 period of record. This drought was characterized by exceptionally low precipitation, with total precipitation from January to June being 50% lower than the mean normal precipitation (1981-2010) over most of western South Korea. In this study, for the quantitative drought impact analysis, the widely-used Standardized Precipitation Index (SPI) and the statistical drought frequency are compared with observed meteorological characteristics and anomalies. According to the drought frequency analysis of monthly cumulative precipitation during January and May in 2017, Gyeonggi-do, Chungcheong-do, and Jeollanam-do areas showed more than drought frequency over 100 years. Gyeongsangnam-do area showed more than drought frequency over 200 years based on annual precipitation in 2017. The South Korean government (Ministry of Agriculture, Food and Rural Affairs (MAFRA) and Korea Rural Community Corporation (KRC)) have been operating a government-level drought monitoring system since 2016. Results from this study can be used to improve the drought monitoring applications of future drought events, as well as drought planning and preparedness in South Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.5
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• pp.477-484
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• 2021

Due to climate change, parts of Korea are experiencing large and small droughts every 2-3 years and extreme droughts every 7 years. Since most droughts occur mainly in areas where small water supply facilities in the tributaries or upstream are located, more research on technology for securing water in these areas is required. In this study, a drought evaluation using SPEI (Standardized Precipitation Evapotranspiration Index), SDI (Streamflow Drought Index), and WBDI (Water Budget-based Drought Index) was performed to investigate hydrological drought in the Mulrocheon watershed of Chuncheon, a vulnerable area in terms of water supply. As a result of calculating hydrological drought indices SPEI and SDI, examining each duration, it was confirmed that the common drought in 2014 did not recover and continued until 2015. In the hydrological drought index evaluation result by WBDI, a very severe drought condition was observed in the spring of 2015 following 2014, and that drought was the most severe at -1.94 in November 2017. As a result of deriving a SDF (Severity-Duration-Frequency) curve through frequency analysis by duration using the drought index calculated on a monthly basis from 2003 to 2019 (17 years), most droughts in the Mulrocheon watershed were found to have a return period of less than 10 years, but droughts that occurred in 2014, 2015, and 2019 were found to cover more than 20 years, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.253-264
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• 2011

Drought assessment is usually performed qualitatively and/or quantitatively after defining a drought from meteorological, agricultural, hydrological, and socioeconomic perspective. Most of the drought analyses focus on meteorological, agricultural, and hydrological droughts, whereas the socioeconomic drought evaluation has been not actively performed since it needs different aspects. In this study, after defining a socioeconomic drought applicable to assess droughts in Korea, we suggested Water Excess Deficiency Index (WEDI) as an useful tool to evaluate socioeconomic droughts, based on water demand condition and water supply condition. This study verified the validity of WEDI by comparing with other drought indices (SPI, PDSI) and historical drought condition in Gyeongsang-do in 2001. The results indicated that the WEDI can be used to assess regional droughts in a socioeconomic perspective.

• 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.54 no.11
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• pp.969-983
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• 2021

Evapotranspiration, one of the hydrometeorological components, is considered an important variable for water resource planning and management and is primarily used as input data for hydrological models such as water balance models. The FAO56 PM method has been recommended as a standard approach to estimate the reference evapotranspiration with relatively high accuracy. However, the FAO56 PM method is often challenging to apply because it requires considerable hydrometeorological variables. In this perspective, the Hargreaves equation has been widely adopted to estimate the reference evapotranspiration. In this study, a set of parameters of the Hargreaves equation was calibrated with relatively long-term data within a Bayesian framework. Statistical index (CC, RMSE, IoA) is used to validate the model. RMSE for monthly results reduced from 7.94 ~ 24.91 mm/month to 7.94 ~ 24.91 mm/month for the validation period. The results confirmed that the accuracy was significantly improved compared to the existing Hargreaves equation. Further, the evaporative demand drought index (EDDI) based on the evaporative demand (E₀) was proposed. To confirm the effectiveness of the EDDI, this study evaluated the estimated EDDI for the recent drought events from 2014 to 2015 and 2018, along with precipitation and SPI. As a result of the evaluation of the Han-river watershed in 2018, the weekly EDDI increased to more than 2 and it was confirmed that EDDI more effectively detects the onset of drought caused by heatwaves. EDDI can be used as a drought index, particularly for heatwave-driven flash drought monitoring and along with SPI.

• Ecology and Resilient Infrastructure
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• v.5 no.3
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• pp.134-144
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• 2018

In this study, the historical drought in East Asia was analyzed with the Community Land Model (CLM) and CLM-Variable infiltration capacity (CLM-VIC). The observation dataset, Climate Research Unit (CRU), were also applied to check and estimate the historical drought for 1951 - 2010. The annual precipitation, temperature and evapotranspiration by CRU, CLM and CLM-VIC were investigated before estimating the meteorological drought index, which is the Standardized precipitation evapotranspiration index (SPEI). Three variables by observation and simulations have generally similar spatial pattern in East Asia even though there are some mere differences depending on the local area. These similar patterns are also founded in the results of SPEI by CRU, CLM and CLM-VIC. However, the similarity of SPEI becomes weaker as the drought severity goes severer from D1 to D4.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.225-225
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• 2015

Drought events usually evolve slowly in time and their impacts generally span a long period of time. This indicates that the sequence of drought is not completely random. The Hidden Markov Model (HMM) is a probabilistic model used to represent dependences between invisible hidden states which finally result in observations. Drought characteristics are dependent on the underlying generating mechanism, which can be well modelled by the HMM. This study employed a HMM with Gaussian emissions to fit the Standardized Precipitation Index (SPI) series and make multi-step prediction to check the drought characteristics in the future. To estimate the parameters of the HMM, we employed a Bayesian model computed via Markov Chain Monte Carlo (MCMC). Since the true number of hidden states is unknown, we fit the model with varying number of hidden states and used reversible jump to allow for transdimensional moves between models with different numbers of states. We applied the HMM to several stations SPI data in South Korea. The monthly SPI data from January 1973 to December 2012 was divided into two parts, the first 30-year SPI data (January 1973 to December 2002) was used for model calibration and the last 10-year SPI data (January 2003 to December 2012) for model validation. All the SPI data was preprocessed through the wavelet denoising and applied as the visible output in the HMM. Different lead time (T= 1, 3, 6, 12 months) forecasting performances were compared with conventional forecasting techniques (e.g., ANN and ARMA). Based on statistical evaluation performance, the HMM exhibited significant preferable results compared to conventional models with much larger forecasting skill score (about 0.3-0.6) and lower Root Mean Square Error (RMSE) values (about 0.5-0.9).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.541-549
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• 2010

While the number of rainy days is decreasing, the mean annual precipitation is increasing due to abnormal climate changes caused by the global warming in Korea. Owing to the biased-concentration of rainfall during specific short terms, not only flood but also drought becomes more and more serious. From the literature, it is easily found that previous studies about flood have been intensively conducted. However, previous studies about drought have been performed rarely. This study conducted the comparison between two representative drought indexes calculated from soil moisture and precipitation. Study area was Haenam-gun, Jeollanam-do in Korea. Soil Moisture Index(SMI) was calculated from soil moisture data while the Standardized Precipitation Index(SPI) and the Palmer Drought Severity Index(PDSI) were calculated from meteorological data. All monthly data utilized in this study were observed at the KoFlux Tower. After the comparative analysis, three indexes showed similar tendency. Therefore, it is thought that the drought index using soil moisture measured at the KoFlux Tower is reasonable, which is because the soil moisture is immediately affected by all the meteorological factors.

• Journal of Korea Water Resources Association
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• v.47 no.5
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• pp.435-446
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• 2014

Various drought indices developed from previous studies can not consider the inherent uncertainty of drought because they assess droughts using a pre-defined threshold. In this study, to consider inherent uncertainty embedded in monthly streamflow data, Hidden Markov Model (HMM) based drought index (HMDI) was proposed and then probabilistic assessment of hydrologic drought was performed using HMDI instead of using pre-defined threshold. Using monthly streamflow data (1966~2009) of Pyeongchang river and Upper Namhan river provided by Water Management Information System (WAMIS), applying the HMM after moving-averaging the data with 3, 6, 12 month windows, this study calculated the posterior probability of hidden state that becomes the HMDI. For verifying the method, this study compared the HMDI and Standardized Streamflow Index (SSI) which is one of drought indices using a pre-defined threshold. When using the SSI, only one value can be used as a criterion to determine the drought severity. However, the HMDI can classify the drought condition considering inherent uncertainty in observations and show the probability of each drought condition at a particular point in time. In addition, the comparison results based on actual drought events occurred near the basin indicated that the HMDI outperformed the SSI to represent the drought events.