• Journal of Korean Society of Disaster and Security
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• v.14 no.1
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• pp.61-72
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• 2021

There is an increasing need for water supply plan using sustainable groundwater to resolve water shortage problem caused by drought due to climate change and artificial aquifer recharge has recently emerged as an alternative. This study deals with recharge potential assessment for artificial recharge system and quantitative assessment for securing stable water and efficient agricultural water supply adapt to drought finding optimal operating condition by numerical modeling to reflect recharge scenarios considering climate condition, target water intake, injection rate, and injection duration. In order to assess recharge potential of injection well, numerical simulation was performed to predict groundwater level changes in injection and observation well respect to injection scenarios (Case 1~4) for a given total injection rate (10,000 m³). The results indicate that groundwater levels for each case are maintained for 25~42 days and optimal injection rate is 50 m³/day for Case 3 resulted in groundwater level rise less than 1 m below surface. The results also show that influential area of groundwater level rise due to injection was estimated at 113.5 m and groundwater storage and elapsed time were respectively increased by 6 times and 4 times after installation of low permeable barrier. The proposed assessment method can be contributed to sustainable agricultural water supply and stable water security for drought adaptation.

• Journal of Korea Water Resources Association
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• v.55 no.2
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• pp.121-133
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• 2022

The drought resulting from insufficient rainfall compared to the amount in an ordinary year can significantly impact a broad area at the same time. Another feature of this disaster is hard to recognize its onset and disappearance. Therefore, a reliable and fast way of predicting both the suffering area and the amount of water shortage from the upcoming drought is a key issue to develop a countermeasure of the disaster. However, the available drought scenarios are about 50 events that have been observed in the past. Due to the limited number of events, it is difficult to predict the water shortage in a case where the pattern of a natural disaster is different from the one in the past. To overcome the limitation, in this study, we applied the four RCP climate change scenarios to the water balance model and the annual amount of water shortage from 360 drought events was estimated. In the following chapter, the deep neural network model was trained with the SPEI values from the RCP scenarios and the amount of water shortage as the input and output, respectively. The trained model in each sub-basin enables us to easily and reliably predict the water shortage with the SPEI values in the past and the predicted meteorological conditions in the upcoming season. It can be helpful for decision-makers to respond to future droughts before their onset.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.57-70
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• 2017

In this study, we evaluated daily root zone soil moisture dynamics and agricultural drought using a near-surface soil moisture data assimilation scheme with Soil Moisture Active & Passive (SMAP, $3km{\times}3km$) soil moisture footprints under different hydro-climate conditions. Satellite-based LANDSAT and MODIS image footprints were converted to spatially-distributed soil moisture estimates based on the regression model, and the converted soil moisture distributions were used for assessing uncertainties and applicability of SMAP data at fields. In order to overcome drawbacks of the discontinuity of SMAP data at the spatio-temporal scales, the data assimilation was applied to SMAP for estimating daily soil moisture dynamics at the spatial domain. Then, daily soil moisture values were used to estimate weekly agricultural drought based on the Soil Moisture Deficit Index (SMDI). The Yongdam-dam and Soyan river-dam watersheds were selected for validating our proposed approach. As a results, the MODIS/SMAP soil moisture values were relatively overestimated compared to those of the TDR-based measurements and LANDSAT data. When we applied the data assimilation scheme to SMAP, uncertainties were highly reduced compared to the TDR measurements. The estimated daily root zone soil moisture dynamics and agricultural drought from SMAP showed the variability at the sptio-temporal scales indicating that soil moisture values are influenced by not only the precipitation, but also the land surface characteristics. These findings can be useful for establishing efficient water management plans in hydrology and agricultural drought.

• Journal of Korean Society of Disaster and Security
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• v.9 no.2
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• pp.15-21
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• 2016

According to the disaster statistics issued by the Ministry of Public Safety and Security, traffic accidents, fire, collapses and others are classified into twenty-three (23) categories. In the past, disasters were mainly caused by the influence of nature, such as typhoon or drought. On the other hand, as society has become city-centered, social disasters' types, frequencies and scales are becoming more diversified and ever-increasing. However, there are no specific criteria and assessment methods that can measure degrees of social disasters-related risks objectively. Therefore, this study targeted traffic accidents, fire and collapses from major social disasters, utilized data that are related to occurrence rate, scale of casualties and scale of property loss in past eight years, and calculated the disaster risk index using the distance (Euclidean distance) between two points on the 3D spatial coordinates, in order to make the objective assessment by social disaster type possible. These results will enable the objective evaluation of risk index of major social disaster to be used as the foundational data when building the national disaster management system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.237-244
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• 1997

The goal of this research is to evaluate methodology that uses satellite data for the analysis of flood and drought damaged area. Land cover classification were performed using satellite data that were acquired at disaster periods and comparatively normal times. Damaged area was extracted by use of overlay analysis in land cover change and compared with the field survey results. The results show analysis of flood damaged area could be carried out with single scene acquired at adequate day, and are corresponded with field survey data very well. And also, some areas that had been missed in field survey were found. The suggested method proved to be more accurate and effective way for mapping inundated areas of floodplains than field survey that would be held a few month later. The results on the analysis of drought damaged area show that drained water could be detected just only in small area, and crop damaged area could not be verified in objective validity. Drought analysis by remote sensing was proved not to be adequate for practical use in this study.

• Journal of Wetlands Research
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• v.13 no.1
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• pp.1-11
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• 2011

A chronic drought stress has been imposed during non-rainy season(from winter to spring) since 1990s. We faced the most significant water crisis in 2001, and the drought was characterized by sultry weather and severe drought on a national scale. It has been widely acknowledged that the drought related damage is 2-3 times serious than floods. In the list of the world's largest natural disaster compiled by NOAA, 4 of the top 5 disasters are droughts. And according to the analysis from the NDMC report, the drought has the highest annual average damage among all the disasters. There was a very serious impact on the economic such as rising consumer price during the 2001 spring drought in Korea. There has been flood prevention measures implemented at national-level but for mitigation of droughts, there are only plans aimed at emergency (short-term) restoration rather than the comprehensive preventive measures. In addition, there is a lack of a clear set of indicators to express drought situation objectively, and therefore it is important and urgent to begin a systematic study. In this study, a nonstationary downscaling model using RCM based climate change scenario was first applied to simulate precipitation, and the simulated precipitation data was used to derive Standardized Precipitation Index (SPI). The SPI under climate change was used to evaluate the spatio-temporal variability of drought through principal component analysis at three different time scales which are 2015, 2045 and 2075. It was found that spatio-temporal variability is likely to modulate with climate change.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.198-207
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• 2013

This study was to examine the effects of risk characteristic and risk perception on risk severity of natural disaster. The findings showed that the risk severity of natural disaster were classified into geographical disaster, storm and flood damage, drought damage. Typhoon among storm and flood damage showed high scores on risk severity of natural disaster. Moreover participants showed high scores on unfamiliar, undiscoverable, and unknown by scientific knowledge among risk characteristic of natural disaster. Second, risk characteristic was significantly correlated to risk perception. Third, risk characteristic influenced positively on risk severity of natural disaster. Especially, risk characteristic had great effect on storm and flood damage among natural disaster. Fourth, risk perception influenced positively on risk severity of natural disaster. Especially, risk perception had great effect on storm and flood damage among natural disaster.

• Journal of Appropriate Technology
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• v.5 no.2
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• pp.118-125
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• 2019

Climate change is one part of 17 Sustainable Development Goals (SDGs). According to the Fifth Assessment Report by the Inter- governmental Panel on Climate Change(IPCC) published in 2014, global warming is caused by greenhouse gas (GHG) emissions. The most important GHG is carbon dioxide (CO₂), which is released by the burning of fossil fuels and, to a lesser extent, by land use practices, followed by nitrous oxide and methane. IPCC predicts that global temperatures will rise 3.7℃ and sea level will rise 0.63 m by 2099 in the case of no strong restraint. According to the report, we can expect a massive species extinctions, changes in storm and drought cycles, altered ocean circulation, and redistribution of vegetation by global warming. However, climate changes, especially global warming, are the largest potential threat to human health and the source of a number of diseases globally. If climate changes are continued uncontrolled, human health will be adversely affected by the accelerating climate change and the natural disaster induced by climate change. It means we will face more serious conditions of injury, disease, and death related to natural disasters such as flood, drought, heat waves, malnutrition, more allergy, air pollution and climate change related infections related to morbidity and mortality. This review emphasizes on the relationship between global climate changes and human health and provides some suggestions for improvement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1117-1123
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• 2014

Water is a necessary condition of plants, animals and human. The state of the water shortage, that drought is globally one of the most feared disasters. This study was calculated target standardized precipitation index with unit of region for judgment and preparation of drought in consideration of the regional characteristics. First of all, Standardized Precipitation Index (3) were calculated by monthly rainfall data from rainfall data more than 30 years of 88 stations. Parametric frequency and nonparametric frequency using boundary kernel density function were analysed using annual minimum data that were extracted from calculated SPI (3). Also, Target return period sets up 30 year and target SPI analysed unit of region using thiessen by result of nonparametric frequency. Analyzed result, Drought was entirely different from severity and frequency by region. This study results will contribute to a national water resources plan and disaster prevention measures with data foundation for judgment and preparation of drought in korea.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.119-131
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• 2010

Drought is one of disaster causing factors to produce severe damage in the World because drought is destroyed to the ecosystem as well as to make difficult the economy of the drought area. This study, using Palmer Drought Severity Index carries out correlation analysis with sea surface temperatures. Comparative analysis carries out by calculated Palmer Drought Severity Index and past drought occurrence year. Result of comparative analysis, PDSI indexes were in accord with the past drought. Cluster analysis for correlation analysis carries out using precipitation and temperature that is input datas palmer drought severity index, and the result of cluster analysis was classified as 6. Also, principal component carries out using result of cluster analysis. 14 principal component analyze out through principal component analysis. Using analyzed 14 principal component carries out correlation analysis with sea surface temperature that is delay time from 0month until 11month. Correlation analysis carries out sea surface temperatures and calculated cycle component of the low frequency through Wavelet Transform analysis form principal component. Result of correlation analysis, yang(+) correlation is bigger than yin(-) correlation. It is possible to check similar correlation statistically the area of sea surface temperature with sea surface temperature in the Pacific. Forecasting possibility of the future drought make propose using sea surface temperature.