• Korean Journal of Soil Science and Fertilizer
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• v.32 no.2
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• pp.115-122
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• 1999

Investigation of nutrient movement in soil and soil water is necessary to clarify water purification functions and nutrient circulation within a forest ecosystem. In this study, seasonal changes in the nutrient content of soil and soil water was investigated in Korean white pine(Pinus koraiensis) and Japanese larch(Larix leptolepis) forest applied urea ($150kg\;ha^{-1}$). Soil pH was decreased rapidly in Japanese larch plot for a long period. On the other hand, soil pH was increased slightly in Korean white pine plot. T-C and T-N content were increased in both plots. In Japanes larch plot, exchangeable Ca and Mg contents were decreased remarkably than those in korean white pine plot while exchangeable K was increased rapidly after application. The effect of urea application on exchangeable K was not obvious compared to other cations. The pH, Ca, $NH_4-N$, $NO_3-N$, $SO_4-S$ and Cl concentrations in the sampled soil water at surface soil were increased only temporarily after fertilization, with the only exception of the decrease in pH of the soil water in Japanese larch plot. On the other hand, the peak value of K, Mg concentrations in the soil water was shown between 2 and 5 months after fertilization. The concentrations of Ca, $NO_3-N$, $SO_4-S$ and Cl returned to the values found before fertilization after about 1 month. Those of K, Mg, and $NO_3-N$ after 6-12 months.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.53-62
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• 2015

The water vapor including latent heat is the important component in an atmospheric circulation and in a monitoring of the Earth's climate changes, as well as in the weather forecast improvement. In this study, to establish the Algerian weighted mean temperature model, a linear regression method had been developed under 5 radiosonde observations for a total 24,694 profiles from 2004 to 2013. An weighted mean temperature is a key parameter in the processing of PWV from GNSS tropospheric delays. The result from the study has expected to provide an useful model to demonstrate the realization and utility of using the ground-based GNSS meteorology technique that will bring improvements in weather forecasting, climate monitoring in Algeria.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.199-199
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• 2017

Sustainable wheat production is of paramount importance for attaining/maintaining the food self-sufficiency status of the rapidly growing nation of Pakistan. However, the average wheat yield per unit area has been dwindling in recent years and the climate-induced variations in rainfall patterns and temperature regimes, during the wheat growth period, are believed to be the reason behind this decline. Crop growth simulation models are powerful tools capable of playing pivotal role in evaluating the climate change impacts on crop yield or productivity. This study was aimed to predict the plausible variations in the wheat yield for future climatic trends so that possible mitigation strategies could be explored. For this purpose, Aquacrop model v. 4.0 was employed to simulate the wheat yield under present and future climatology of the largest agricultural province of Punjab in Pakistan. The data related to crop phenology, management and yield were collected from the experimental plots to calibrate and validate the model. The future climate projections were statistically downscaled from five general circulation models (GCMs) and compared with the base line climate from 1980 to 2010. The model was fed with the projected climate to simulate the wheat yield based on the RCP (representative concentration pathways) 4.5 and 8.5. Under the worst, most likely future scenario of temperature rise and rainfall reduction, the crop yield decreased and water footprint, especially blue, increased, owing to the elevated irrigation demands due to accelerated evapotranspiration rates. The modeling results provided in this study are expected to provide a basic framework for devising policy responses to minimize the climate change impacts on wheat production in the area.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.619-629
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• 2002

Water in the atmosphere is circulated by reciprocal action of various factors in the climate system. Otherwise, any climate phenomenon could not occur of itself. Thus, we have tried to understand the climate change by analysis of the factors. In this study, the fuzzy theory which is useful to express inaccurate and approximate nature in the real world is used for forecasting precipitation influenced by the factors. Forecasting models used in this study are neuro-fuzzy system and a Markov chain and those are applied to precipitation forecasting of illinois. Various atmosphere circulation factors(like soil moisture and temperature) influencing the climate change are considered to forecast precipitation. As a forecasting result, it can be found that the considerations of the factors are helpful to increase the forecastibility of the models and the neuro-fuzzy system gives us relatively more accurate forecasts.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1057-1066
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• 2018

Climate change has been influenced on extreme precipitation events, which are major driving causes of flooding. Especially, most of extreme water-related disasters in Korea occur from floods induced by extreme precipitation events. However, future climate change scenarios simulated with Global Circulation Models (GCMs) or Reigonal Climate Models (RCMs) are limited to the application on medium and small size rivers and urban watersheds due to coarse spatial and temporal resolutions. Therefore, the current study introduces the state-of-the-art approaches and procedures of statistical downscaling techniques to resolve this limitation It is expected that the temporally downscaled data allows frequency analysis for the future precipitation and estimating the design precipitation for disaster prevention.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.327-340
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• 2015

General Circulation Models (GCMs) are the basic tool used for modelling climate. However, the spatio-temporal discrepancy between GCM and observed value, therefore, the models deliver output that are generally required calibration for applied studies. Which is generally done by Multi-Model Ensemble (MME) approach. Stochastic downscaling methods have been used extensively to generate long-term weather sequences from finite observed records. A primary objective of this study is to develop a forecasting scheme which is able to make use of a MME of different GCMs. This study employed a Nonstationary Hidden Markov Chain Model (NHMM) as a main tool for downscaling seasonal ensemble forecasts over 3 month period, providing daily forecasts. Our results showed that the proposed downscaling scheme can provide the skillful forecasts as inputs for hydrologic modeling, which in turn may improve water resources management. An application to the Nakdong watershed in South Korea illustrates how the proposed approach can lead to potentially reliable information for water resources management.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.116-124
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• 2016

In this paper, we propose digital exhibition contents for the aquarium, especially 'Gyeongpo Lagoon Ecological Museum'. We try to plan appropriate media contents that can be mixed with the aquarium storytelling. The aquarium must have special spaces that are not related with an exhibition directly but are necessary for survival of fishes such as a water circulation room. We design the special spaces using media contents and let visitors feel that the whole aquarium is in the ocean. First of all, we investigate the aquarium currently under construction. And then, we propose the appreciate media platforms and plan individual content. We suggest 3 types of media platforms, 3D water projection, interactive games utilizing Kinect, and a fog screen. Moreover, we produce 2D drawing concepts, 3D modeling images, and virtual exhibitions in virtual reality for the representation of the location in which those platforms are installed and the media contents we plan. The pre-visualization is helpful for the media platform construction and is used as a rough sketch to producing an animation shown in the exhibition.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.91-91
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• 2023

General circulation models(GCMs)은 여러 국가 기관들의 물리적 기후 모의 프로세스를 기반으로 과거 및 미래 기후변화의 영향을 정량화하기 위해 개발되었으며 현재 미래 기후변화를 예측하는데 가장 효과적인 도구이다. 그러나 GCMs에 내포된 여러 불확실성 요소 및 넓은 격자형식의 기후 데이터는 GCMs 기후 데이터를 사용한 지역적 기후 모의 시 주요 걸림돌로 인식되어지고 있다. 편의보정 방법은 GCMs을 사용한 지역적 기후 모의 시 기후 모의 성능을 향상시키기 위해 여러 연구에서 사용되어져 왔으나 다른 연구에서는 이러한 편의보정 방법의 문제점을 언급했다. 따라서 본 연구는 편의보정 방법이 GCMs 기후 모의 결과에 미치는 영향을 정량화하고 더 나아가 GCMs 기후 변수에 따른 유량 모의 결과에 미치는 영향을 분석했다. 연구대상지 과거 기간 기후 모의를 위해 coupled model intercomparison project(CMIP)6의 GCMs을 사용했으며, 미래 기후 모의를 위해 shared socioeconomic pathway(SSP) 시나리오를 사용했다. 편의보정 방법으로는 분위사상법을 사용했으며, 편의보정 전후 GCMs 기후 모의 성능평가를 위해 5개 평가 지표를 사용했다. 연구대상지 장기 유출 모의를 위해 storm water management model(SWMM)이 사용되었으며, 기후 입력 자료로는 일 단위 강수량, 최고 및 최저온도를 고려했다. 미래 기후 및 유량 모의 결과의 불확실성은 square root of error variance(SREV) 방법을 통해 정량화됐다. 결과적으로 과거 기간 GCMs 기후 및 유량 모의성능은 편의보정 전보다 편의보정 후에서 향상되었으며 특히, 강수 및 유량 모의 성능이 크게 향상되었다. 미래 기간의 경우 편의보정 후에서 기후 및 유량의 극값을 더 잘 반영함을 확인했다. 본 연구의 결과는 GCMs 기후 변수를 사용한 지역적 기후 및 유량 모의 시 편의보정 방법이 미치는 영향에 대한 구체적인 정보를 제공할 수 있다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.365-365
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• 2022

강우에 따른 유역 내 유출량은 수문순환에서 중요한 요소 중 하나이며, 과거부터 강우-유출 모델링을 위한 여러 물리적 수문모형들이 개발되어왔다. 또한 최근 딥러닝 기술을 기반으로한 강우-유출 모델링 접근 방식이 유효함을 입증하는 여러 연구가 수행됨에 따라 딥러닝을 기반으로한 유출량 모의 연구도 활발히 진행되고 있다. 따라서 본 연구에서는 물리적 수문모형인 SWAT(Soil Water Assessment Tool)과 딥러닝 기법 중 하나인 LSTM(Long Short-Term Memory)을 사용하여 연구대상지 유출량을 모의했으며, 두 모형에 의해 모의 된 유출량의 극값을 비교 분석했다. 연구대상지로는 영산강 유역을 선정했으며, 영산강 유역의 과거 기간의 기후 변수 모의를 위해 CMIP(Coupled Model Intercomparison Project)6 GCM(General Circulation Model)을 사용했다. GCM을 사용하여 모의 된 기후 변수들은 영산강 유역 내 기상관측소의 과거 기간 관측 값을 기반으로 분위사상법을 사용하여 편이보정 됐다. GCM에 의해 모의 된 기후 변수 및 SWAT, LSTM에 의해 모의 된 유출량은 각각 영산강 유역 내 기상관측소 및 수위관측소의 관측 값을 기반으로 재현성을 평가했다. SWAT 및 LSTM을 사용하여 모의 된 유출량의 극값은 GEV(General Extreme Value) 분포를 사용하여 추정하였다. 결과적으로 GCM의 기후 변수 모의 성능은 과거 기간 관측 값과 비교했을 때 편이보정 후에서 상당히 향상되었다. 유출량 모의 결과의 경우 과거 기간 유출량의 관측 값과 비교했을 때 LSTM의 모의 유출량이 SWAT보다 과거 기간 유출량을 보다 근접하게 모의했으며, 극값 모의 성능의 경우 또한 LSTM이 SWAT보다 높은 성능을 보였다.

• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1235-1247
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• 2013

This study is to evaluate the climate change impact on future storage behavior of Chungju dam($2,750{\times}10^6m^3$) and the regulation dam($30{\times}10^6m^3$) using SWAT(Soil Water Assessment Tool) model. Using 9 years data (2002~2010), the SWAT was calibrated and validated for streamflow at three locations with 0.73 average Nash-Sutcliffe model Efficiency (NSE) and for two reservoir water levels with 0.86 NSE respectively. For future evaluation, the HadCM3 of GCMs (General Circulation Models) data by scenarios of SRES (Special Report on Emission Scenarios) A2 and B1 of the IPCC (Intergovernmental Panel on Climate Change) were adopted. The monthly temperature and precipitation data (2007~2099) were spatially corrected using 30 years (1977~2006, baseline period) of ground measured data through bias-correction, and temporally downscaled by Change Factor (CF) statistical method. For two periods; 2040s (2031~2050), 2080s (2071~2099), the future annual temperature were predicted to change $+0.9^{\circ}C$ in 2040s and $+4.0^{\circ}C$ in 2080s, and annual precipitation increased 9.6% in 2040s and 20.7% in 2080s respectively. The future watershed evapotranspiration increased up to 15.3% and the soil moisture decreased maximum 2.8% compared to baseline (2002~2010) condition. Under the future dam release condition of 9 years average (2002~2010) for each dam, the yearly dam inflow increased maximum 21.1% for most period except autumn. By the decrease of dam inflow in future autumn, the future dam storage could not recover to the full water level at the end of the year by the present dam release pattern. For the future flood and drought years, the temporal variation of dam storage became more unstable as it needs careful downward and upward management of dam storage respectively. Thus it is necessary to adjust the dam release pattern for climate change adaptation.