• Journal of Wetlands Research
• /
• v.18 no.4
• /
• pp.432-447
• /
• 2016

The increased frequency of drought and flood due to climate change was a global problem. In particular, drought was recognized as a serious environmental, ecological, social, and economic disaster. Therefore, it is necessary to study the measures to prevent it. In this study, we will estimate the meteorological drought index in the Han River Basin and analyze the impact of climate change on drought. The change of the meteorological drought occurrence due to climate change in the Han River separated by the common drought and severe drought was analyzed using the Representative Concentration Pathways (RCPs) scenarios provided by the Intergovernmental Panel on Climate Change (IPCC). The years 1973 - 2010 were selected for analysis in the current period. Using the scenario, we separated the future period (Target I: 2011 - 2039, Target II: 2040 - 2069, Target III : 2070 - 2099). The number of occurrences of less than -1.0 and -1.5 standard precipitation index were analyzed by SPI 3, 6, 12. Looking at the results, trends in rainfall in the Han River was expected to increase from the current figures, the occurrence of drought is predicted to decline in the future. However, the number of drought occurrence was analyzed to increase toward long-term drought. The number of severe drought occurrences was usually larger than the common drought estimated. Additional studies may be considered in addition to the agricultural drought, hydrological drought, socio-economic drought. This will be done by using efficient water management. The results can be used as a basis for future drought analysis of the Han River.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.34 no.6
• /
• pp.1787-1796
• /
• 2014

The main purpose of this study is to assess the sensitivity of meteorological drought indices in probabilistic perspective using Bayesian Network model. In other words, this study analyzed interrelationships between various drought indices and investigated the order of the incident. In this study, a Bayesian Network model was developed to evaluate meteorological drought characteristics by employing the percent of normal precipitation (PN) and Standardized Precipitation Index (SPI) with various time scales such as 30, 60, and 90 days. The sensitivity analysis was also performed for posterior probability of drought indices with various time scales. As a result, this study found out interdependent relationships among various drought indices and proposed the effective application method of SPI to drought monitoring.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.141-141
• /
• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

• Journal of Korea Water Resources Association
• /
• v.54 no.7
• /
• pp.523-534
• /
• 2021

Meteorological drought originates from a precipitation deficiency and propagates to agricultural and hydrological droughts through the hydrological cycle. Comparing with the meteorological drought, agricultural and hydrological droughts have more direct impacts on human society. Thus, understanding how meteorological drought evolves to agricultural and hydrological droughts is necessary for efficient drought preparedness and response. In this study, meteorological and hydrological droughts were defined based on the observed precipitation and the synthesized streamflow by the land surface model. The Bayesian network model was applied for probabilistic analysis of the propagation relationship between meteorological and hydrological droughts. The copula function was used to estimate the joint probability in the Bayesian network. The results indicated that the propagation probabilities from the moderate and extreme meteorological droughts were ranged from 0.41 to 0.63 and from 0.83 to 0.98, respectively. In addition, the propagation probabilities were highest in autumn (0.71 ~ 0.89) and lowest in winter (0.41 ~ 0.62). The propagation probability increases as the meteorological drought evolved from summer to autumn, and the severe hydrological drought could be prevented by appropriate mitigation during that time.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.80-83
• /
• 2008

Diverse researches using vegetation index have been carried out to monitor spring droughts that have frequently occurred since 2000. The strength of the drought monitoring using vegetation index lies in that it can reflect characteristics of satellite images: large area coverage, cyclicity, and promptness. However, vegetation index involve uncertainly caused by diverse factors that affect vegetation stress. In this study, multi-temporal vegetation index is compared with the most representative meteorological drought indices like PSDI, SPI. Based on the results from analyses, usability of vegetation index as a tool of drought analysis is proposed.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.12
• /
• pp.668-678
• /
• 2017

In this study, the hydrological and meteorological drought index with precipitation as a major factor were calculated, and various analyses of hydrological drought were conducted. The Modified Surface Water Supply Index (MSWSI) was applied to the hydrological drought index and Standardize Precipitation Index (SPI) was used to estimate the meteorological drought index. The target area for the estimation is the dam area among MSWSI categories. The 4001 basin with 43 years data from 1975 to 2017 was analyzed for the drought occurrence status and time series plotted with the monthly SPI and MSWSI. For the dam watershed based on the precipitation that has the role of a water supply in the hydrological cycle, correlation analysis of precipitation, dam inflow, and stream flow was performed by the monthly and moving average (2~9 months), and the correlation between meteorological and hydrological index by monthly and moving average (3, 6 months) was then calculated. The result of multifaced analysis of the hydrological drought index and meteorological drought index is believed to be useful in developing water policy.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.50 no.3
• /
• pp.3-15
• /
• 2008

North Korea is one of the vulnerable countries facing the threat of a drought, so that it is unavoidable to experience fatal damage when drought is occurred, and it is necessary to improve the drought response capability of water resources systems. However, it is still difficult to find research efforts for drought characteristics and drought management in North Korea. This study is to quantify drought duration and magnitude and to analyze drought characteristics in North Korea. In order to quantitatively identify historical drought conditions and to evaluate their variability, drought indices are commonly used. In this study, drought indices including dry-day index, deciles of normal precipitation, Phillips drought index, standardized precipitation index and Palmer drought severity index are calculated and compared monthly using the weather data for the twenty one meteorological stations in North Korea. The indices compared with the drought damage records that have reported from 1990 to present to understand how the indices can explain the drought. A comparative study was also conducted to evaluate the relative severity of the significant droughts occurred during 2000 and 2001 which were reported as the worst drought in North Korea. Drought indices calculated from this study demonstrated that those can be the effective tools in quantitatively evaluating drought severity and measures of drought. Thus it is recommended the distributed trend of drought be considered when the plan or measures for drought in North Korea are established.

• Journal of Environmental Science International
• /
• v.31 no.2
• /
• pp.117-129
• /
• 2022

In this study, we investigated the characteristics of the meteorological and environmental conditions for a cloud seeding experiment over the Korean peninsula and estimated the available days for the same. The conditions of available days appropriate for a cloud seeding experiment were classified according to four purposes: water resources, drought relief, forest fire prevention, and air quality improvement. The average number of available days for a cloud seeding experiment were 91.27 (water resources), 45.93-51.11 (drought relief), 40.28-46.00 (forest fire prevention), and 42.19-44.60 days/year (air quality improvement). If six experiments were carried out per available day for a cloud seeding experiment, the number of times cloud seeding experiments could be conducted per year in a continuously operating system were estimated as 547.62 (water resources), 275.58-306.66 (drought relief), 241.68-276.00 (forest fire prevention), and 253.14-267.60 times/year (air quality improvement). From this result, it was possible to determine the appropriate meteorological and environmental conditions and statistically estimate the available days for a cloud seeding experiment. The data on the available days for a cloud seeding experiment might be useful for preparing and performing such an experiment.

• Journal of Korea Water Resources Association
• /
• v.49 no.10
• /
• pp.877-885
• /
• 2016

In this study, the Standard Precipitation Index(SPI), meteorological drought index, was used to evaluate the temporal and spatial assessment of drought forecasting results for all cross Korea. For the drought forecasting, the Multi Layer Perceptron-Artificial Neural Network (MLP-ANN) was selected and the drought forecasting was performed according to different forecasting lead time for SPI (3) and SPI (6). The precipitation data observed in 59 gaging stations of Korea Meteorological Adminstration (KMA) from 1976~2015. For the performance evaluation of the drought forecasting, the binary classification confusion matrix, such as evaluating the status of drought occurrence based on threshold, was constituted. Then Receiver Operating Characteristics (ROC) score and F score according to conditional probability are computed. As a result of ROC analysis on forecasting performance, drought forecasting performance, of applying the MLP-ANN model, shows satisfactory forecasting results. Consequently, two-month and five-month leading forecasts were possible for SPI (3) and SPI (6), respectively.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2018.05a
• /
• pp.158-158
• /
• 2018

Drought is a recurrent natural hazard in Bangladesh. It has significant impacts on agriculture, environment, and society. Well-timed information on the onset, extent, intensity, duration, and impacts of drought can mitigate the potential drought-related losses. Thus, drought characteristics need to be explained in terms of frequency, severity, and duration. This paper aims to characterize the spatial and temporal pattern of meteorological drought using EDI and illustrated drought severity over Bangladesh. Twenty-seven (27) station-based daily rainfall data for the study period of 1981-2015 were used to calculate the EDI values over Bangladesh. The evaluation of EDI is conducted for 4 sub-regions over the country to confirm the historical drought record-developed at the regional scale. The finding shows that on average, the frequency of severe to extreme drought is approximately 0.7 events per year. As a result of the regional analysis, most of the recorded historical drought events were successfully detected during the study period. Additionally, the seasonal analysis showed that the extreme droughts were frequently hit in northwestern, middle portion of the eastern and small portion of central parts of Bangladesh during the Kharif(wet) and Rabi(dry) seasons. The severe drought was affected recurrently in the central and northern regions of the country during all cropping seasons. The study also points out that the northern, south-western and central regions in Bangladesh are comparatively vulnerable to both extreme and severe drought event. The study showed that EDI would be a useful tool to identify the drought-prone area and time and potentially applicable to the climate change-induced drought evolution monitoring at regional to the national level in Bangladesh. The outcome of the present study can be used in taking anticipatory strategies to mitigate the drought damages on agricultural production as well as human sufferings in drought-prone areas of Bangladesh.