• Journal of Korea Water Resources Association
• /
• v.39 no.8 s.169
• /
• pp.691-702
• /
• 2006

This study introduced a method to evaluate the probability of a specific area to be affected by a drought of a given severity and shows Its potential for investigating agricultural drought characteristics. The method was applied to South Korea as a case study. The proposed procedure included Standardized Precipitation Index(SPI) time series, which were linearly transformed by the Empirical Orthogonal Functions(EOF) method. These EOFs were extended temporally with AutoRegressive Moving Average(ARMA) method and spatially with Kriging method. By performing these simulations, long time series of SPI can be simulated for each designed grid cell in whole area. The probability distribution functions of the area covered by a drought and the drought severity are then derived and combined to produce drought severity-area-frequency(SAF) curves.

• Journal of Korea Water Resources Association
• /
• v.51 no.spc
• /
• pp.1117-1126
• /
• 2018

Water supply system aims to meet the user's demand by securing water resources in a stable way. However, water supply failure sometimes happens because inflow decreases during drought period. Droughts induced by the lack of precipitation do not always lead to water supply failures. Thus, it is necessary to consider features of actual water shortage event when we evaluate a water supply risk. In this study, we developed a new drought index for drought management, i.e., Joint Drought Management Index (JDMI), using two water supply system performance indices such as reliability and vulnerability. Future data that were estimated from GCMs according to RCP 4.5 and 8.5 scenarios were used to estimate future water supply risk. After dividing the future period into three parts, the risk of water supply failure in the Nakdong River basin was analyzed using the JDMI. As a result, the risk was higher with the RCP 4.5 than the RCP 8.5. In case of RCP 4.5, W18 (Namgangdam) was identified as the most vulnerable area, whereas in case of RCP 8.5, W23 (Hyeongsangang) and W33 (Nakdonggangnamhae) were identified as the most vulnerable area.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.63 no.4
• /
• pp.1-12
• /
• 2021

Agricultural drought is a natural phenomenon that is not easy to observe and predict and is difficult to quantify. In South Korea, the amount of agricultural water used is large and the types of use are varied, so even if an agricultural drought occurs due to insufficient precipitation, the drought actually felt in the irrigated area is it can be temporally and spatially different. In order to interpret the general drought in the past, drought disasters were evaluated using single indicators such as drought damage area, precipitation shortage status, and drought index, and a comprehensive drought management system is needed through drought diagnosis survey. Therefore, we intend to conduct research on agricultural drought assessment and diagnosis using re-evaluation of agricultural facilities and irrigation water supply network due to changes in various conditions such as climate change, irrigation canal network, and evaluation of water supply capacity of agricultural facilities. In this study, agricultural drought diagnosis was conducted on two agricultural reservoirs located in Sangju, Gyeongsangbuk-do, with structural or non-structural evaluations to increase spatiotemporal water supply and efficiency in terms of water shortages. The results of the agricultural drought diagnosis evaluation can be used to identify irrigated areas and canal network vulnerable to drought and to prioritize drought response.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.63 no.3
• /
• pp.13-26
• /
• 2021

Recent drought events in the South Korea and the magnitude of drought losses indicate the continuing vulnerability of the agricultural drought. Various studies have been performed on drought hazard assessment at the regional scales, but until recently, drought management has been response oriented with little attention to mitigation and preparedness. A vulnerability assessment is introduced in order to preemptively respond to agricultural drought and to predict the occurrence of drought. This paper presents a method for spatial, Geographic Information Systems-based assessment of agricultural drought vulnerability in South Korea. It was hypothesized that the key 14 items that define agricultural drought vulnerability were meteorological, agricultural reservoir, social, and adaptability factors. Also, this study is to analyze agricultural drought vulnerability by comparing vulnerability assessment according to weighting method. The weight of the evaluation elements is expressed through the Analytic Hierarchy Process (AHP), which includes subjective elements such as surveys, and the Entropy method using attribute information of the evaluation items. The agricultural drought vulnerability map was created through development of a numerical weighting scheme to evaluate the drought potential of the classes within each factor. This vulnerability assessment is calculated the vulnerability index based on the weight, and analyze the vulnerable map from 2015 to 2019. The identification of agricultural drought vulnerability is an essential step in addressing the issue of drought vulnerability in the South Korea and can lead to mitigation-oriented drought management and supports government policymaking.

• Journal of Korea Water Resources Association
• /
• v.52 no.4
• /
• pp.279-289
• /
• 2019

Unlike other natural disasters, drought is a reoccurring and region-wide phenomenon after being triggered by a prolonged precipitation deficiency. Considering that remote sensing products provide consistent temporal and spatial measurements of precipitation, this study developed a remote sensing data-based drought outlook model. The meteorological drought was defined by the Standardized Precipitation Index (SPI) achieved from PERSIANN_CDR, TRMM 3B42 and GPM IMERG images. Bayesian networks were employed in this study to combine the historical drought information and dynamical prediction products in advance of drought outlook. Drought outlook was determined through a decision-making model considering the current drought condition and forecasted condition from the Bayesian networks. Drought outlook condition was classified by four states such as no drought, drought occurrence, drought persistence, and drought removal. The receiver operating characteristics (ROC) curve analysis were employed to measure the relative outlook performance with the dynamical prediction production, Multi-Model Ensemble (MME). The ROC analysis indicated that the proposed outlook model showed better performance than the MME, especially for drought occurrence and persistence of 2- and 3-month outlook.

• Journal of Korea Water Resources Association
• /
• v.54 no.11
• /
• pp.925-932
• /
• 2021

A drought-flood abrupt alternation event is an overlapping extreme event that is harder to cope with than a single event of drought and flood. It is also expected to have a significant adverse impact on ecosystems as well as industries and agriculture. However, there has not yet been a comprehensive study that characterizes the drought-flood abrupt alternation events in Korea. Therefore, this study employed a standard weighted average precipitation (SWAP) index, which is efficient to analyze not only individual events of drought and flood but also the drought-flood abrupt alternation events considering various time scales. The SWAP standardized the weighted average precipitation (WAP) by adding temporal weights to the precipitation. The SWAP indices were calculated for middle-sized watersheds of the Han River basin using the area average precipitation during 1966 and 2018. The severity K was calculated to represent the relative regional severity considering normal rainfalls, and used to characterize the drought-flood abrupt alternation in the study areas. The results indicated that 20 of the 30 middle-sized watersheds in the Han River basin were confirmed to increase the severity of drought-flood abrupt alternation over time. Considering the frequency and severity of drought-flood abrupt alternation events in each watershed, vulnerable areas and dangerous areas due to drought-flood abrupt alternation were identified, for example, the Upstream Namhan River (#1001).

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.37 no.4
• /
• pp.669-680
• /
• 2017

This study evaluated the consistency of the standard flow to forecast low-flow based on various drought indices. The data used in this study were streamflow data at the Gurye2 station located in the Seomjin River and the Angang station located in the Hyeongsan River, as well as rainfall data of nearby weather stations (Namwon and Pohang). Using streamflow data, the streamflow accumulation drought index (SADI) was developed in this study to represent the hydrological drought condition. For SADI calculations, the threshold of drought was determined by a Change-Point analysis of the flow pattern and a reduction factor was estimated based on the kernel density function. Standardized runoff index (SRI) and standardized precipitation index (SPI) were also calculated to compared with the SADI. SRI and SPI were calculated for the 30-, 90-, 180-, and 270-day period and then an ROC curve analysis was performed to determine the appropriate time-period which has the highest consistency with the standard flow. The result of ROC curve analysis indicated that for the Seomjin River-Gurye2 station SADI_C3, SRI30, SADI_C1, SADI_C2, and SPI90 were confirmed in oder of having high consistency with standard flow under the attention stage and for the Hyeongsan River-Angang station, SADI_C3, SADI_C1, SPI270, SRI30, and SADI_C2 have order of high consistency with standard flow under the attention stage.

• Journal of Korea Water Resources Association
• /
• v.51 no.10
• /
• pp.875-886
• /
• 2018

This study evaluated drought severity by bivariate frequency analysis using drought magnitude and precipitation deficit. A drought event was defined by Standardized Precipitation Index (SPI) and the precipitation deficit was estimated using reference precipitation corresponding to the SPI -1. In previous studies, drought magnitude and duration were used for bivariate frequency analysis. However, since these two variables have a largely linear relationship, extensibility of drought information is not great compared to the univariate frequency analysis for each variable. In the case of drought in 2015, return periods of 'drought magnitude-precipitation deficit' in the Seoul, Yangpyeong, and Chungju indicated severe drought over 300 years. However, the result of 'drought magnitude-duration' showed a significant difference by evaluating the return period of about 10, 50, and 50 years. Although a drought including the rainy season was seriously lacking in precipitation, drought magnitude did not adequately represent the severity of the absolute lack of precipitation. This showed that there is a limit to expressing the actual severity of drought. The results of frequency analysis for 'drought magnitude-precipitation deficit' include the absolute deficit of precipitation information, so which could consider being a useful indicator to cope with drought.

• Journal of Korea Water Resources Association
• /
• v.32 no.2
• /
• pp.111-120
• /
• 1999

The relationship between EI Nino-Southern Oscillation(ENSO) and drought in Korea is investigated using the cross correlation analysis. In this paper, Palmer Drought Severity Index(PDSI) is used as an index of drought and nine ENSO indicators are used. To obtain PDSI for Korea, the PDSI equation is derived using monthly precipitation and temperature in Korea. In addition, ENSO composite percentile analyses for PDSI, precipitation and streamflow in Korea are performed to verify the results of the cross correlation. Results of the cross correlation show that the link between drought in Korea and ENSO is statistically significant with 6% of the variance in PDSI for Korea explained by ENSO. The PDSI is negatively correlated with the equatorial Pacific Sea Surface Temperature and the Sea Level Pressure(SLP) at Darwin leading by about 16 months. However, the relationship of the PDSI with the Southern Oscillation Index and the SLP at Tahiti is positive correlation. The ENSO composite percentile analyses show that drought, precipitation and streamflow in Korea are associated with ENSO during 6 months from December of the ENSO ending year

• Journal of Korea Water Resources Association
• /
• v.56 no.8
• /
• pp.509-520
• /
• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.