• Journal of Korea Water Resources Association
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• v.35 no.4 s.129
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• pp.397-410
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• 2002

In order to quantitatively identify historical drought conditions and to evaluate their variability, drought indices commonly used. The calculation method for the drought index based on the principal hydrological factors, such as precipitation and reservoir storage, can estimate the duration and intensity of a drought. In this study the Palmer-type formula for drought index is derived for the Nakdong River basin by analyzing the monthly rainfall and meteorological data at 21 stations. The Palmer Drought Severity Index(PDSI) is used for dry land sectors to evaluate the meteorological anomaly in terms of an index which permits time and space comparisons of drought severity. The Surface Water Supply Index(SWSI) is devised for the use in conjunction with the Palmer index to provide an objective indicator of water supply conditions in Nakdong River basin. The SWSI was designed to quantify surface water supply capability of a watershed which depends on river and reservoir water The Standardized Precipitation Index(SPI) is evaluated for various time periods of 1 to 12 months in Nakdong River basin. For the purpose of comparison between drought indices correlation coefficient was calculated between indices and appropriate SPI time period was selected as 10 months for Nakdong River basin. A comparative study is made to evaluate the relative severity of the significant droughts occurred in Nakdong River basin since 1976. It turned out that $'94{\sim}'97$ drought was the worst drought in it's severity. It is found that drought indices are very useful tools in quantitatively evaluating the severity of a drought over a river basin.

• Journal of Korea Water Resources Association
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• v.47 no.11
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• pp.1039-1050
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• 2014

The goal of this study is to demonstrate the diversity of model performance for various climatic elements and indicators. We evaluated the skills of the most advanced 17 General Circulation Models (GCMs) i.e., CMIP5 (Climate Model Inter-comparison project, phase 5) climate models in reproducing retrospective climatology from 1950 to 2000 over the Southeast US for the key climatic elements important in the hydrological and agricultural perspectives (i.e., precipitation, maximum and minimum temperature, and wind speed). The biases of raw CMIP5 GCMs were estimated for 16 different climatic indicators that imply mean climatology, temporal variability, extreme frequency, etc. using a grid-based observational dataset as reference. Based on the error (RMSE) and correlation (R) of GCM outputs, the error-based GCM ranks were assigned on average over the indicators. Overall, the GCMs showed much better accuracy in representing mean climatology of temperature comparing to other elements whereas few GCM showed acceptable skills for precipitation. It was also found that the model skills and ranks would be substantially different by the climatic elements, error statistics applied for evaluation, and indicators as well. This study presents significance of GCM uncertainty and the needs of considering rational strategies for climate model evaluation and selection.

• Journal of Environmental Impact Assessment
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• v.20 no.6
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• pp.891-905
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• 2011

Climate vulnerability index is usually defined as a function of the climate exposure, sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature, and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed, and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability, implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend, suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.17-28
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• 2017

A recent increase in extreme weather events and flash floods associated with the enhanced climate variability results in an increase in climate-related disasters. For these reasons, various studies based on a high resolution weather radar system have been carried out. The weather radar can provide estimates of precipitation in real-time over a wide area, while ground-based rain gauges only provides a point estimate in space. Weather radar is thus capable of identifying changes in rainfall structure as it moves through an ungauged basin. However, the advantage of the weather radar rainfall estimates has been limited by a variety of sources of uncertainty in the radar reflectivity process, including systematic and random errors. In this study, we developed an ensemble radar rainfall estimation scheme using the multivariate copula method. The results presented in this study confirmed that the proposed ensemble technique can effectively reproduce the rainfall statistics such as mean, variance and skewness (more importantly the extremes) as well as the spatio-temporal structure of rainfall fields.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1219-1228
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• 2015

The Fixed Area ARFs (Area Reduction Factors) method has limitations in providing exact information about spatial distribution due to the lack of enough density of rain gauge stations. In this study the storm-centered ARF was evaluated between frontal and typhoon storm events utilizing radar precipitation. In estimating storm-centered ARFs, in order to consider the horizontal advection, direction, and spatial distribution of rain cells, the rotational angle of rainfall of each rainfall event and the optimum areal rainfall within the spatial rain cell envelope was taken into account. Compared with the frontal storm, the ARF of typhoon storm shows narrow range of variability. It is noted that the ARFs of frontal storm increases with the rainfall duration, but those of typhoon storm shows opposite pattern. As a result the typhoon ARFs appear greater than frontal ARFs for 1~3 hours of duration, but less for more than 6 hours of duration.

• Journal of Korea Water Resources Association
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• v.37 no.4
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• pp.305-314
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• 2004

Climate change mainly due to the increase of green house gases cause different patterns of water cycle within the basin. However, it is common that current planning and management practices do not consider the effect of the climate change. So, this study evaluated the effect of climate change on the water circulation within the watershed. This study used several GCM simulations for the double $CO_2$condition for the generation of temperature and rainfall series using the Markov chain. Daily runoff series for 100 years were generated using a rainfall-runoff model. As results. annual temperature increase by ＋3.2 ∼＋4.6$^{\circ}C$, annual precipitation change －7 ∼ ＋8 %, annual runoff change －14 ∼ ＋7 %, and potential evapotranspiration amount change ＋3 ∼＋4 % for the change of 1 $^{\circ}C$ are found to be expected depending on GCM simulations. Even though the simulation results are very dependent on the GCM predictions considered, overall variability of runoff is expected to become higher than the current state.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.1
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• pp.112-117
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• 2012

The Revised Universal Soil Loss Equation (RUSLE) is a revision of the Universal Soil Loss Equation (USLE). However, changes for each factor of the USLE have been made in RUSLE which can be used to compute soil loss on areas only where significant overland flow occurs. RUSLE which requires standardized methods to satisfy new data requirements estimates soil movement at a particular site by utilizing the same factorial approach employed by the USLE. The rainfall erosivity in the RUSLE expressed through the R-factor to quantify the effect of raindrop impact and to reflect the amount and rate of runoff likely is associated with the rain. Calculating the R-factor value in the RUSLE equation to predict the related soil loss may be possible to analyse the variability of rainfall erosivity with long time-series of concerned rainfall data. However, daily time step models cannot return proper estimates when run on other specific rainfall patters such as storm and daily cumulative precipitation. Therefore, it is desirable that cross-checking is carried out amongst different time-aggregations typical rainfall event may cause error in estimating the potential soil loss in definite conditions.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1174-1177
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• 2008

이상기후기간동안 유역의 수문 변화는 강수변화와 기온변화 등 복합적인 상관관계에 의하여 나타난다. 우리나라 지역의 최근 강수변화는 연 강수량의 증가 추세를 보이나 기온 또한 상승하므로 강수효율의 연변화, 월변화 및 지역 변화특성의 분석이 필요하다. 본 연구에서는 강수변화와 기온변화의 상관관계로 나타나는 월강수량을 월 증발량으로 나눈 P-E비 즉 강수효율을 분석하였다. 이상기후기간과 평년에 대한 강수효율 분석 결과 강수량의 영향이 지배적이고 기온이 강수효율에 미치는 영향은 미미하다 하겠다. 일반적으로 연 강수효율은 엘리뇨>평년>라니냐기간 순으로 나타난다. 이러한 일반적 특성과 달리 도시화된 서울과 인천지역의 연강수효율은 기후에 따른 차이를 발견할 수 없으나 연 강수효율과 달리 월 강수효율변화는 매우 큼을 보였다. 고도 200m 이상인 점과 섬이라는 지역 특성으로 인하여 울릉도는 평년>라니냐>엘리뇨라는 타 지역과 상반된 강수효율 분포를 보였다. 남부지역으로 갈수록 엘리뇨해의 강수효율이 높은 것으로 보아 엘리뇨의 영향을 더 많이 받는 지역은 북부지역 보다는 남부지역 이라는 것을 알 수 있다. 엘니뇨해의 7, 8월의 강수효율이 높게 나타났으며 이는 엘니뇨해의 7, 8월의 강수량이 많다는 것을 의미한다. 또한 엘리뇨 기간 9, 10월 강수 효율은 평년에 비하여 낮게 나타났다. 라니냐해의 강수효율 분포를 살펴보면 6, 9월에 강수효율이 높게 나타났으며 11, 12월 강수효율이 평년에 비하여 낮게 나타났다. 서울, 강릉, 울릉, 부산, 광주, 여수, 제주지역의 강수효율이 타 지역에 비해 높게 나타났다. 서울, 부산, 광주 지역은 고도의 도시화로 인해, 강릉, 울릉도, 여수, 제주 지역은 해양과 인접한 지형적 특성 때문이라 판단된다. 강수효율 또한 강수량이 집중되는 5월부터 8월까지 증가하는 것으로 나타났다. 나머지 달은 대부분 감소하는 것으로 분석되었다.

• Journal of Soil and Groundwater Environment
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• v.7 no.3
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• pp.45-59
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• 2002

This study is objected to demonstrate the spatial variability of the ground-water recharge by classifying the types of ground-water hydrographs and assessing the recharge ratio(the ratio of the rise of ground-water level to cumulative precipitation) of each type using the National Ground-water Monitoring network data. A total of 5 types were identified by factor analysis on the ground-water hydrographs nationwide. The recharge ratio of each type were estimated to be 6.5% (TYPE I), 4.1 % (TYPE II), 9.2%(TYPE III), 5.8 %(TYPE IV), 15.3 %(TYPE V) in the confidence level of 95.44% and 6% variation was estimated site by site even in the same type. The recharges of Han, Nakdong, Keum, Youngsan·Seomjin river basins were estimated as 10.0 %, 6.1 %, 8.3 %. and 6.6 % respectively. These results were consistent with the results of the existing baseflow method.

• Journal of Ecology and Environment
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• v.38 no.1
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• pp.95-107
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• 2015

Because an ecological community consists of diverse species that vary nonlinearly with environmental variability, its dynamics are complex and difficult to analyze. To investigate temporal variations of benthic macroinvertebrate community, we used the community data that were collected at the sampling site in Baenae Stream near Busan, Korea, which is a clean stream with minimum pollution, from July 2006 to July 2013. First, we used a self-organizing map (SOM) to heuristically derive the states that characterizes the biotic condition of the benthic macroinvertebrate communities in forms of time series data. Next, we applied the hidden Markov model (HMM) to fine-tune the states objectively and to obtain the transition probabilities between the states and the emission probabilities that show the connection of the states with observable events such as the number of species, the diversity measured by Shannon entropy, and the biological water quality index (BMWP). While the number of species apparently addressed the state of the community, the diversity reflected the state changes after the HMM training along with seasonal variations in cyclic manners. The BMWP showed clear characterization of events that correspond to the different states based on the emission probabilities. The environmental factors such as temperature and precipitation also indicated the seasonal and cyclic changes according to the HMM. Though the usage of the HMM alone can guarantee the convergence of the training or the precision of the derived states based on field data in this study, the derivation of the states by the SOM that followed the fine-tuning by the HMM well elucidated the states of the community and could serve as an alternative reference system to reveal the ecological structures in stream communities.