• The Journal of Engineering Geology
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• v.31 no.4
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• pp.631-646
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• 2021

Increasing incidences of landslides in Korea are endangering life and damaging property. To ascertain the cause of the rapid increase in landslides in 2020, this study analyzed the correlation between frequency of their occurrence and persistence of rainfall. The study area comprised seven areas in Gangwon-do, Gyeonggi-do, Gyeongsangnam-do, Gyeongsangbuk-do, Jeollanam-do, Jeollabuk-do, and Chungcheongnam-do. The used rainfall factors were monthly rainfall in June, July, and August, rainfall during the summer (June-August), rainfall during the monsoon season, and number of precipitation days during the summer and during the monsoon season. The effect of these factors on landslides was identified by comparing them with the occurrence of landslides in the year of increased landslide occurrence in each area. The results confirmed that not only rainfall but also the number of precipitation days during the monsoon season affect the occurrence of landslides. The rapid increase in landslide occurrence in 2020 was attributed to increases in both the number of precipitation days during the monsoon season and rainfall during the monsoon season in 2020. These results are expected to be used as basic data for future landslide warning standards that consider the effect of the persistence of rainfall.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.561-569
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• 2010

In this study, the impact of climate change on extreme drought events is investigated by comparing drought severity-area-duration curves under present and future climate. The depth-area-duration analysis for characterizing an extreme precipitation event provides a basis for analysing drought events when storm depth is replaced by an appropriate measure of drought severity. In our climate-change impact experiments, the future monthly precipitation time series is based on a KMA regional climate model which has a $27km{\times}27km$ spatial resolution, and the drought severity is computed using the standardized precipitation index. As a result, agricultural drought risk is likely to increase especially in short duration, while hydrologic drought risk will greatly increase in all durations. Such results indicate that a climate change vulnerability assessment for present water resources supply system is urgent.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.2
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• pp.47-61
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• 2000

Agroclimatic zoning was done for paddy rice culture in North Korea based on a simulation experiment. Daily weather data for the experiment were generated by 3 steps consisting of spatial interpolation based on topoclimatological relationships, zonal summarization of grid cell values, and conversion of monthly climate data to daily weather data. Regression models for monthly climatological temperature estimation were derived from a statistical procedure using monthly averages of 51 standard weather stations in South and North Korea (1981-1994) and their spatial variables such as latitude, altitude, distance from the coast, sloping angle, and aspect-dependent field of view (openness). Selected models (0.4 to 1.6$^{\circ}C$ RMSE) were applied to the generation of monthly temperature surface over the entire North Korean territory on 1 km$\times$l km grid spacing. Monthly precipitation data were prepared by a procedure described in Yun (2000). Solar radiation data for 27 North Korean stations were reproduced by applying a relationship found in South Korea ([Solar Radiation, MJ m$^{-2}$ day$^{-1}$ ] =0.344 + 0.4756 [Extraterrestrial Solar Irradiance) + 0.0299 [Openness toward south, 0 - 255) - 1.307 [Cloud amount, 0 - 10) - 0.01 [Relative humidity, %), $r^2$=0.92, RMSE = 0.95 ). Monthly solar irradiance data of 27 points calculated from the reproduced data set were converted to 1 km$\times$1 km grid data by inverse distance weighted interpolation. The grid cell values of monthly temperature, solar radiation, and precipitation were summed up to represent corresponding county, which will serve as a land unit for the growth simulation. Finally, we randomly generated daily maximum and minimum temperature, solar irradiance and precipitation data for 30 years from the monthly climatic data for each county based on a statistical method suggested by Pickering et a1. (1994). CERES-rice, a rice growth simulation model, was tuned to accommodate agronomic characteristics of major North Korean cultivars based on observed phenological and yield data at two sites in South Korea during 1995~1998. Daily weather data were fed into the model to simulate the crop status at 183 counties in North Korea for 30 years. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to score the suitability of the county for paddy rice culture.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.613-627
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• 2013

In this study, to understand the May aridity condition of each region for the year of the worst drought on record in each duration (1-, 3-, 6-, 12-, 24 months), monthly climate data recorded from 1973 to 2006 at 53 climatological stations in South Korea were used to estimate the FAO Penman-Monteith reference potential evapotranspiration (RET). Monthly precipitation and RET were used to estimate P/RET as aridity index and variation index (VI) of P/RET, and these indexes are compared with SPI (Standard Precipitation Index). Fifty three climatological stations were grouped into 20 regions, so that May aridity conditions of 20 regions were studied. Furthermore, regional trend of May aridity index was studied by applying Mann-Kendall trend analysis, Spearman rank test, and Sen's slope estimator. The study results show that variation index (VI) of P/RET and SPI have close correlation. Throughout the country, as the duration is shorter, May aridity was more severe. In case of 3-month and 6-month duration, most of region show significant or non-significant decreasing trend of aridity index. However, no region show significant decreasing trend of aridity index in case of 12-month and 24-month duration.

• Journal of Soil and Groundwater Environment
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• v.26 no.3
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• pp.25-36
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• 2021

This study evaluated monthly, seasonal and altitudinal changes of oxygen and hydrogen isotope compositions of wet precipitation samples (n = 238) that were collected for last four years from 7 altitudes (from 265 to 1,500 m above sea level) in the Jeju Samdasoo watershed at the southeastern part of Jeju island, in order to examine the recharge characteristics of groundwater that is pumped out for the production of the Samdasoo drinking mineral water. Precipitation samples showed a clear seasonal change of O-H isotopic composition as follow, due to the different air masses and relative humidity: 𝛿D = 7.3𝛿¹⁸O + 11.3 (R² = 0.76) in the wet season (June to September), while 𝛿D = 7.9𝛿¹⁸O + 9.5 (R² = 0.91) in the dry season (October to May). In contrast, the stable isotope compositions of groundwater were nearly constant throughout the year and did not show a distinct monthly or seasonal change, implying the well-mixing of infiltrated water during and after its recharge. An altitudinal effect of the oxygen isotope compositions of precipitation was also remarkable with the decrease of -0.19‰ (R² = 0.91) with the elevation increase by 100 m. Based on the observed altitudinal change, the minimum altitude of groundwater recharge was estimated as 1,200 m above the sea level in the Jeju Samdasoo watershed.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.481-494
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• 2022

This study proposed a evaluation of the monthly vulnerable period for groundwater level management in the Miho stream watershed and a technique for evaluating the vulnerable period for future groundwater level management using LSTM. Observation data from groundwater level and precipitation observation stations in the Miho stream watershed were collected, LSTM was constructed, predicted values for precipitation and groundwater levels from 2020 to 2022 were calculated, and future groundwater management was evaluated when vulnerable. In order to evaluate the vulnerable period of groundwater level management, the correlation between groundwater level and precipitation was considered, and weights were calculated to consider changes caused by climate change. As a result of the evaluation, the Miho stream watershed showed high vulnerability to underground water management in February, March, and June, and especially near the Cheonan Susin observation well, the vulnerability index for groundwater level management is expected to deteriorate in the future. The results of this study are expected to contribute to the evaluation of the vulnerable period of groundwater level management and the derivation of preemptive countermeasures to the problem of groundwater resources in the basin by presenting future prediction techniques using LSTM.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.723-736
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• 2022

In this study, monthly precipitation forecasting models that can predict up to 12 months in advance were constructed for the Geum River basin, and two statistical techniques, multiple linear regression (MLR) and artificial neural network (ANN), were applied to the model construction. As predictor candidates, a total of 47 climate indices were used, including 39 global climate patterns provided by the National Oceanic and Atmospheric Administration (NOAA) and 8 meteorological factors for the basin. Forecast models were constructed by using climate indices with high correlation by analyzing the teleconnection between the monthly precipitation and each climate index for the past 40 years based on the forecast month. In the goodness-of-fit test results for the average value of forecasts of each month for 1991 to 2021, the MLR models showed -3.3 to -0.1% for the percent bias (PBIAS), 0.45 to 0.50 for the Nash-Sutcliffe efficiency (NSE), and 0.69 to 0.70 for the Pearson correlation coefficient (r), whereas, the ANN models showed PBIAS -5.0~+0.5%, NSE 0.35~0.47, and r 0.64~0.70. The mean values predicted by the MLR models were found to be closer to the observation than the ANN models. The probability of including observations within the forecast range for each month was 57.5 to 83.6% (average 72.9%) for the MLR models, and 71.5 to 88.7% (average 81.1%) for the ANN models, indicating that the ANN models showed better results. The tercile probability by month was 25.9 to 41.9% (average 34.6%) for the MLR models, and 30.3 to 39.1% (average 34.7%) for the ANN models. Both models showed long-term predictability of monthly precipitation with an average of 33.3% or more in tercile probability. In conclusion, the difference in predictability between the two models was found to be relatively small. However, when judging from the hit rate for the prediction range or the tercile probability, the monthly deviation for predictability was found to be relatively small for the ANN models.

• Ecology and Resilient Infrastructure
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• v.2 no.3
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• pp.198-205
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• 2015

Impacts of climate change on aquatic ecosystems range from changes in physiological processes of aquatic organisms to species distribution. In this study, MaxEnt that has high prediction power without nonoccurrence data was used to simulate fish distribution changes in the Geum river watershed according to climate change. The fish distribution in 2050 and 2100 was predicted with RCP 8.5 climate change scenario using fish occurrence data (a total of 47 species, including 17 endemic species) from 2007 to 2009 at 134 survey points and 9 environmental variables (monthly lowest, highest and average air temperature, monthly precipitation, monthly lowest, highest and average water temperature, altitude and slope). The fitness of MaxEnt modeling was successful with the area under the relative operating characteristic curve (AUC) of 0.798, and environmental variables that showed a high level of prediction were as follows: altitude, monthly average precipitation and monthly lowest water temperature. As climate change proceeds until 2100, the probability of occurrence for Odontobutis interrupta and Acheilognathus yamatsuatea (endemic species) decreases whereas the probability of occurrence for Microphysogobio yaluensis and Lepomis macrochirus (exotic species) increases. In particular, five fish species (Gnathopogon strigatus, Misgurnus mizolepis, Erythroculter erythropterus, A. yamatsuatea and A. koreensis) were expected to become extinct in the Geum river watershed in 2100. In addition, the species rich area was expected to move to the northern part of the Geum river watershed. These findings suggest that water temperature increase caused by climate change may disturb the aquatic ecosystem of Geum river watershed significantly.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.15-17
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• 2001

북한 지역은 산이 많아, 농경지의 많은 부분이 경사지에 이루어져 있다. 경사지는 특성상 토양 유실이 일어나기 쉬운 조건에 있다. 북한 지역에서 토양 유실은 농경지 황폐화의 주된 원인이고, 농업 생산성 감퇴의 한 원인으로 지적되고 있다. 특히 경사지 밭에서 강수에 의한 토양 유실이 심각한 것으로 알려져 있다(류, 2000).(중략)

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.191-198
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• 2010

Assessing seasonality of precipitation is necessarily required to establish future plans and policies for water resources management. In this regard, a main objective of the study is to introduce an effective approach for assessing the seasonality of the precipitation and evaluate the seasonality through the proposed one. We have used circular statistics to characterize the seasonality on the precipitation in Korea. The circular statistics allow us to effectively assess changes in timing of the seasonality in detail. It was found that peak time on monthly rainfall occurred between end of June and early July in southern coastal area while the timing was delayed in northern part of Korea because of monsoon moving in from south to north. In case of annual daily peak precipitation, spatio-temporal variation of the peak time was increased. It is mainly because of geophysical effects, frequency and paths of typhoons. Finally, temporal variations on the timing of the peak seasons were evaluated through circular statistics by 30-year moving average data. The peak season in the Northen part of Korea (e.g. Seoul and Gangrung) has been moved back from early July to end of July while the peak season has been moved up from middle of July to early July in the Southern part of Korea (e.g. Busan and Mokpo). It seems that changes in seasonality are mostly modulated by variability in the east-asia monsoon system.