• Journal of Korea Water Resources Association
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• v.50 no.12
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• pp.815-825
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• 2017

Groundwater management vulnerability was assessed using TOPSIS (Techniques for Order Performance by Similarity to Ideal Solution) for 21 administrative districts in Nakdong river basin. Ten indicators were selected for 21 administrative districts in the Nakdong river basin by collecting natural, human, and social data sets. The selected indicators were standardized using rescale method, and each indicator was weighted by considering the questionnaire of expert group. The results of the weights determination survey showed that the annual average groundwater level index was 0.157 and this is the highest value. The annual average precipitation index was 0.154 and the annual groundwater recharge index was 0.152. The lowest weighted index was 0.043 for population density. Finally, the result of assessment of groundwater management vulnerability showed that Sangju-si was the most vulnerable to groundwater management among 21 administrative districts in Nakdong river basin because the annual average precipitation, annual average groundwater recharge, and annual average groundwater use indicators were highly vulnerable. The second and the third vulnerable regions were Yecheon-gun and Haman-gun respectively. The assessment of groundwater management vulnerability for the five major river basins in Korea can be a essential basis for the establishment of groundwater management policy.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.119-136
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• 2012

The goal of this study is to apply the IPCC(Intergovernmental Panel on Climate Change) concept of vulnerability to climate change and verify the use of a combination of vulnerability index and fuzzy logic to flood vulnerability analysis and mapping in Seoul using GIS. In order to achieve this goal, this study identified indicators influencing floods based on literature review. We include indicators of exposure to climate(daily max rainfall, days of 80mm over), sensitivity(slope, geological, average DEM, impermeability layer, topography and drainage), and adaptive capacity(retarding basin and green-infra). Also, this research used fuzzy model for aggregating indicators, and utilized frequency ratio to decide fuzzy membership values. Results show that the number of days of precipitation above 80mm, the distance from river and impervious surface have comparatively strong influence on flood damage. Furthermore, when precipitation is over 269mm, areas with scare flood mitigation capacities, industrial land use, elevation of 16~20m, within 50m distance from rivers are quite vulnerable to floods. Yeongdeungpo-gu, Yongsan-gu, Mapo-gu include comparatively large vulnerable areas. This study improved previous flood vulnerability assessment methodology by adopting fuzzy model. Also, vulnerability map provides meaningful information for decision makers regarding priority areas for implementing flood mitigation policies.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.4
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• pp.73-82
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• 2013

The main objective of this study was to evaluate Representative Concentration Pathways (RCP) scenarios-based flood risk at a Si-Gun level. A bias correction using a quantile mapping method with the Generalized Extreme Value (GEV) distribution was performed to correct future precipitation data provided by the Korea Meteorological Administration (KMA). A series of proxy variables including CN80 (Number of days over 80 mm) and CX3h (Maximum precipitation during 3-hr) etc. were used to carry out flood risk assessment. Indicators were normalized by a Z-score method and weighted by factors estimated by principal component analysis (PCA). Flood risk evaluation was conducted for the four different time periods, i.e. 1990s, 2025s, 2055s, and 2085s, which correspond to 1976~2005, 2011~2040, 2041~2070, and 2071~2100. The average flood risk indices based on RCP4.5 scenario were 0.08, 0.16, 0.22, and 0.13 for the corresponding periods in the order of time, which increased steadily up to 2055s period and decreased. The average indices based on RCP8.5 scenario were 0.08, 0.23, 0.11, and 0.21, which decreased in the 2055s period and then increased again. Considering the average index during entire period of the future, RCP8.5 scenario resulted in greater risk than RCP4.5 scenario.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.91-107
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• 2018

It is required to monitor and assess the desertification in Tunisia, where the Sahara Desert, which is located in the southern part of Tunisia, is recently expanding northward. In this study, by using remote sensed data, land cover changes were examined, and the Normalized Difference Vegetation Index (NDVI), Topsoil Grain Size Index (TGSI) and Albedo are used to monitor and assess desertification in Tunisia. Decision Tree was constructed, and the frequencies and trends of each assessment indicator, desertification degree and land cover were identified. In addition, we analyzed the correlation between assessment indicators and precipitation. As a result, desertification is generally intensifying northward, especially in areas with high levels of desertification. Also, bivariate correlation analysis showed that Albedo, NDVI and TGSI were all highly correlated with precipitation. It indicates that changes in precipitation have also been shown to affect Tunisian desertification. In conclusion, this study has improved the usability of various methodologies considering the assessment indicators based on satellite imagery, Decision Tree, which is a method of evaluating them complexly, and trends of land cover change.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.211-211
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• 2020

The concept of virtual water has been largely applied in the study of regional, national, and global water flows with particular emphasis on water scarcity. Despite water traditionally being managed locally, certain global forces influence the local water resource scarcity/availability and hence virtual water exchanges worldwide. It is therefore of necessity that the significant forces be examined to understand the relationship between available water in a region and the variability and trends in environmental, social, and economic factors that are of utmost importance in the formulation of water resources management policies. This study therefore reviewed recent literature from 2003 - 2019 to determine the significant indicators of virtual water trade at different spatiotemporal levels. The study examined and compared the major approaches to virtual water trade flows accounting, and also identified and discussed policy implications and future research options concerning the analysis of virtual water trade. Available information has shown that virtual water trade is significantly influenced by economic (GDP, Demand-Supply of goods and services), geographical (Distance), institutional (population) and environmental (water availability, arable land, precipitation) factors. Reports further show that the selection of a given approach for virtual water trade flows accounting will depend on the scope of the study, the available datasets, and other research preferences. Accordingly, this study suggests that the adoption of multidisciplinary approaches to virtual water trade, taking into consideration the spatial and temporal variations in water resources availability and the complexity of environmental and socioeconomic factors will be pivotal for establishing the basis for the conservation of water resources worldwide.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.188-188
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• 2017

Rainfall is an important input to hydrological models. The accuracy of hydrological studies for water resources and floods management depend primarily on the estimation of rainfall. Thailand is among the countries that have regularly affected by floods. Flood forecasting and warning are necessary to prevent or mitigate loss and damage. Merging near real time satellite-based precipitation estimation with relatively high spatial and temporal resolutions to ground gauged precipitation data could contribute to reducing uncertainty and increasing efficiency for flood forecasting application. This study tested the applicability of satellite-based rainfall for water resources management and flood forecasting. The objectives of the study are to assess uncertainty associated with satellite-based rainfall estimation, to perform bias correction for satellite-based rainfall products, and to evaluate the performance of the bias-corrected rainfall data for the prediction of flood events. This study was conducted using a case study of Thai catchments including the Chao Phraya, northeastern (Chi and Mun catchments), and the eastern catchments for the period of 2006-2015. Data used in the study included daily rainfall from ground gauges, telegauges, and near real time satellite-based rainfall products from TRMM, GSMaP and PERSIANN CCS. Uncertainty in satellite-based precipitation estimation was assessed using a set of indicators describing the capability to detect rainfall event and efficiency to capture rainfall pattern and amount. The results suggested that TRMM, GSMaP and PERSIANN CCS are potentially able to improve flood forecast especially after the process of bias correction. Recommendations for further study include extending the scope of the study from regional to national level, testing the model at finer spatial and temporal resolutions and assessing other bias correction methods.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.305-305
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• 2022

A better approach for assessing meteorological drought occurrences is increasingly important in mitigating and adapting to the impacts of climate change, as well as strategies for developing early warning systems. The present study defines meteorological droughts as a period with an abnormal precipitation deficit based on monthly precipitation data of 18 gauging stations for the Han River watershed in the past (1974-2015). This study utilizes a Bayesian parameter estimation approach to analyze the effects of climate change on future drought (2025-2065) in the Han River Basin using the Coupled Model Intercomparison Project Phase 6 (CMIP6) with four bias-corrected general circulation models (GCMs) under the Shared Socioeconomic Pathway (SSP)2-4.5 scenario. Given that drought is defined by several dependent variables, the evaluation of this phenomenon should be based on multivariate analysis. Two main characteristics of drought (severity and duration) were extracted from precipitation anomalies in the past and near-future periods using the copula function. Three parameters of the Archimedean family copulas, Frank, Clayton, and Gumbel copula, were selected to fit with drought severity and duration. The results reveal that the lower parts and middle of the Han River basin have faced severe drought conditions in the near future. Also, the bivariate analysis using copula showed that, according to both indicators, the study area would experience droughts with greater severity and duration in the future as compared with the historical period.

• Journal of Korea Water Resources Association
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• v.32 no.2
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• pp.111-120
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• 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 The Korean Society of Agricultural Engineers
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• v.62 no.2
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• pp.63-73
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• 2020

Drought is considered as a devastating hazard that causes serious agricultural, ecological and socio-economic impacts worldwide. Fundamentally, the drought can be defined as temporarily different levels of inadequate precipitation, soil moisture, and water supply relative to the long-term average conditions. From no unified definition of droughts, droughts have been divided into different severity level, i.e., moderate drought, severe drought, extreme drought and exceptional drought. The drought severity classification defined the ranges for each indicator for each dryness level. Because the ranges of the various indicators often don't coincide, the final drought category tends to be based on what the majority of the indicators show and on local observations. Evaporative Stress Index (ESI), a satellite-based drought index using the ratio of potential and actual evaporation, is being used as a index of the droughts occurring rapidly in a short period of time from studies showing a more sensitive and fast response to drought compared to Standardized Precipitation Index (SPI), and Palmer Drought Severity Index (PDSI). However, ESI is difficult to provide an objective drought assessment because it does not have clear drought severity classification criteria. In this study, U.S. Drought Monitor (USDM), the standard for drought determination used in the United States, was applied to ESI, and the Percentile method was used to classify drought categories by severity. Regarding the actual 2017 drought event in South Korea, we compare the spatial distribution of drought area and understand the USDM-based ESI by comparing the results of Standardized Groundwater level Index (SGI) and drought impact information. These results demonstrated that the USDM-based ESI could be an effective tool to provide objective drought conditions to inform management decisions for drought policy.

• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.336-341
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• 2016

The object of this study was to classify the local types in relation to regional differences using Height-DBH growth of Pinus densiflora in Korea. The regional types were clustered according to Getis-Ord's $G_i$ among Local indicators of spatial association (LISA) by characteristics of spatial distribution which were calculated the residual of sample plots by fitting Height-DBH growth model using Weibull growth equation. Accordingly, Pinus densiflora were classified 3 groups, It indicated that annual precipitation had one of the biggest impacts among the considered site and climate factors. This results can become the standard for regional management of Pinus densiflora forests.