• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.457-467
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• 2022

Drought has strong local characteristics, an objective definition or standard that can define the progress or severity of drought is needed and to date, many drought-related studies are being conducted around the world. In this study, Standardized Precipitation Index (SPI), which is a representative meteorological drought index, was calculated, and the drought risk index (DRI) that can consider actual drought was applied to the target area, Uiryeong-gun, by applying the drought vulnerability index (DVI) and the drought hazard index (DHI). A method for practical drought evaluation that can establish a water supply system is presented in this study.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.171-182
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• 2014

The objective of this study is to evaluate the utilization of bivariate joint drought index in South Korea. In order to develop the bivariate joint drought index, in this study, Clayton copula was used to estimate the joint distribution function and the calibration method was employed for parameter estimation. Precipitation and soil moisture data were selected as input data of bivariate joint drought index for period of 1977~2012. The time series analysis, ROC (Receiver Operating Characteristic) analysis, spatial analysis were used to evaluate the bivariate joint drought index with SPI (Standardized Precipitation Index) and SSI (Standardized Soil moisture Index). As a result, SPI performed better for drought onset and SSI for drought demise. On the other hand the bivariate joint drought index captured both drought onset and demise very well. The ROC score of bivariate joint drought index was higher than that of SPI and SSI, and it also reflected the local drought situations. The bivariate joint drought index overcomes the limitations of existing drought indices and is useful for drought analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.735-742
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• 2019

Drought is a social phenomenon in which the degree of perception varies depending on the affected factors, and is defined as various relative concepts such as meteorological drought, hydrological drought, agricultural drought, and climatological drought. In this study, a comparative analysis of meteorological drought among variously defined droughts was conducted and the applicability of the drought index was examined by comparing the actual drought cases and the results of meteorological drought index analysis. In order to compare the drought index, we used standardized Precipitation Index (SPI), China-Z Index (CZI), Modified CZI (MCZI) and Z-Score Index Respectively. Four drought indices were used for the Taebaek and Sokcho areas. The drought index was analyzed using the meteorological data from 1986 to 2015 for a duration of 3 months. As a result of the analysis, the SPI drought index was analyzed to be highly reproducible for the case of drought with past limited water series. In the case of CZI and MCZI drought indices, the number of extreme dry occurrences is similar to that of the past cases, but the reproducibility is low for the actual drought years. In the case of ZSI drought index, it is analyzed that the number of occurrences and the comparison with the past cases are inferior in reproducibility. For the meteorological drought index using precipitation, it would be effective to use the SPI drought index with the highest reproducibility and the past drought case.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.619-629
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• 2023

Recent intensification of climate change has led to an increase in damages caused by droughts. Currently, in Korea, the Standardized Precipitation Index (SPI) is used as a criterion to classify the intensity of droughts. Based on the accumulated precipitation over the past six months (SPI-6), meteorological drought intensities are classified into four categories: concern, caution, alert, and severe. However, there is a limitation in classifying drought intensity solely based on precipitation. To overcome the limitations of the meteorological drought warning criteria based on SPI, this study collected emergency water supply damage data from the National Drought Information Portal (NDIP) to classify drought intensity. Factors of SPI, such as precipitation, and factors used to calculate evapotranspiration, such as temperature and humidity, were indexed using min-max normalization. Coefficients for each factor were determined based on the Genetic Algorithm (GA). The drought intensity based on emergency water supply was used as the dependent variable, and the coefficients of each meteorological factor determined by GA were used as coefficients to derive a new Drought Severity Classification Index (DSCI). After deriving the DSCI, cumulative distribution functions were used to present intensity stage classification boundaries. It is anticipated that using the proposed DSCI in this study will allow for more accurate drought intensity classification than the traditional SPI, supporting decision-making for disaster management personnel.

• Magazine of the Korean Society of Agricultural Engineers
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• v.41 no.5
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• pp.43-52
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• 1999

In an effort to identify quantitatively historical drought conditions, and to evaluate their temporal and spatial variability , two commonly used drougth indices, the standardized precipitation index, SPI by Mckee and the Palmer drought severity index. PDSI were calculated from 54 meteorological stations, SPI was evaluated for different time scales, 3 to 48 months. As the compjtational spans for SPI increase from 3 to 48 months the frequency and intensity of drought decrease, but the duration of drought increase. When monthly and ten-day PDSIs were compared, the frequency and duratin of drought were almost equal and the intensity of drought differ slightly. The three month SPI has the advatage to detect the drought resulting from short-term shortage of rainfall, while PDSI had the advantage to detect the state of drought resulting from cumulated shortage of rainfall. The period-frequency spectrum analyses at Kangnung statino showed that the maximum value of relative frequency was 24.4% when the period was 5.2months, and the 6month SPI has most similar trends to PDSI.

• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1249-1263
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• 2013

In order to minimize the damages caused by long-term drought, appropriate drought management plans of the basin should be established with the drought forecasting technology. Further, in order to build reasonable adaptive measurement for future drought, the duration and severity of drought must be predicted quantitatively in advance. Thus, this study, attempts to forecast drought in Korea by using an Artificial Neural Network Model, and drought index, which are the representative statistical approach most frequently used for hydrological time series forecasting. SPI (Standardized Precipitation Index) for major weather stations in Korea, estimated using observed historical precipitation, was used as input variables to the MLP (Multi Layer Perceptron) Neural Network model. Data set from 1976 to 2000 was selected as the training period for the parameter calibration and data from 2001 to 2010 was set as the validation period for the drought forecast. The optimal model for drought forecast determined by training process was applied to drought forecast using SPI (3), SPI (6) and SPI (12) over different forecasting lead time (1 to 6 months). Drought forecast with SPI (3) shows good result only in case of 1 month forecast lead time, SPI (6) shows good accordance with observed data for 1-3 months forecast lead time and SPI (12) shows relatively good results in case of up to 1~5 months forecast lead time. The analysis of this study shows that SPI (3) can be used for only 1-month short-term drought forecast. SPI (6) and SPI (12) have advantage over long-term drought forecast for 3~5 months lead time.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.105-115
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• 2019

For 159 administrative areas, SPI(Standardized Precipitation Index), ARDI(Agricultural Reservoir Drought Index) and ARDIs(Agricultural Reservoir Drought Index Simulated) were developed and applied to analyze the characteristics of agricultural drought index and agricultural droughts. In order to identify hydrometeorological characteristics of agricultural droughts, SPI, ARDI and ARDIs were calculated nationwide, and the applicability was compared and examined. SPI and ARDI showed significant differences in time and depth of drought in both spatial and temporal. ARDI and ARDIs showed similar tendency of change, and ARDIs were considered to be more representative of agricultural drought characteristics. The results of this study suggest that agricultural drought is a problem to be solved in the medium and long term rather than short term due to various forms of development, complexity of development, and difficulty in forecasting. Therefore, it is concluded that a preliminary and systematic approach is needed in consideration of meteorological, hydrological and hydrometeorological characteristics rather than a fragmentary approach, and that an agricultural drought index is needed to quantitatively evaluate agricultural drought.

• Journal of Soil and Groundwater Environment
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• v.27 no.5
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• pp.1-9
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• 2022

A correlation analysis was performed to investigate differences in the response of surface water and groundwater to drought using the Standardized Precipitation Index (SPI). Water level data of 20 agricultural reservoirs, 4 dams, 2 rivers, and 8 groundwater observation wells were used for the analysis. SPI was calculated using precipitation data measured at a nearby meteorological station. The water storage of reservoirs and dams decreased significantly as they responded sensitively to the drought from 2014 to 2016, showing high correlation with SPI of the relatively long accumulation period (AP). The responses of rivers varied greatly depending on the presence of an upstream dam. The water level in rivers connected to an upstream dam was predominantly influenced by the dam discharge, resulting in very weak correlation with SPI. On the contrary, the rivers without dam exhibited a sharp water level rise in response to precipitation, showing higher correlation with SPI of a short-term AP. Unlike dams and reservoirs, the responses of groundwater levels to precipitation were very short-lived, and they did not show high correlation with SPI during the long-term drought. In drought years, the rise of groundwater level in the rainy season was small, and the lowered water level in the dry season did not proceed any further and was maintained at almost the same as that of other normal years. Conclusively, it is confirmed that groundwater is likely to persist longer than surface water even in the long-term drought years.

• 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.