• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.123-123
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• 2019

최근 기후변화로 인해 중국, 한국, 일본, 몽골 등을 포함한 동아시아 지역은 태풍, 가뭄, 홍수와 같은 자연재해의 발생 빈도가 증가하고 있는 추세이다. 중국의 경우 2017년 극심한 가뭄으로 1,850만 (ha)의 농작물 피해가 발생하였으며, 몽골 또한 2017년 4월 이후 극심한 가뭄으로 사막화가 급속도로 진행되고 있다. 위성 기반의 강우 자료는 공간과 시간 해상도가 높아짐에 따라 지상관측소 강수량 자료의 대체 수단으로 이용되고 있다. 본 연구에서는 Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), Global Precipitation Climatology Centre (GPCC) 강우 위성 자료를 활용하여 기상학적 가뭄지수인 표준강수지수 (Standardized Precipitation Index, SPI)를 산정하였다. 시간 해상도는 월별 영상을 기준으로 2008년부터 2017년까지 지난 10년간의 데이터를 이용하였으며, 각각 격자가 다른 위성영상을 기존 기상관측소와 비교하였다. 피어슨 상관계수 (Pearson Correlation Coefficient, R)를 활용하여 강우 위성 영상과 지상관측소의 상관관계를 분석하고, 평균절대오차 (Mean Absolute Error, MAE), 평균제곱근오차 (Root Mean Square Error, RMSE)를 통해 통계적으로 정확도를 분석하였다. 인공위성 강수량 자료는 미계측 지역이 많은 곳이나 측정이 불가능한 지역에 효율성 측면에서 중요한 이점을 제공할 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.294-294
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• 2021

강우에 따른 수위예측은 수자원 관리 및 재해 예방에 있어 중요하다. 기존의 수문분석은 해당지역의 지형 데이터, 매개변수 최적화 등 수위예측 분석에 있어 어려움을 동반한다. 최근 AI(Artificial Intelligence) 기술의 발전에 따라, 수자원 분야에 AI 기술을 활용하는 연구가 수행되고 있다. 본 연구에서는 데이터 간의 관계를 포착할 수 있는 AI 기반의 기법을 이용하여 강우에 따른 수위예측을 실시하였다. 연구대상 유역으로는 과거 수문데이터가 풍부한 설마천 유역으로 선정하였다. AI 기법으로는 머신러닝 중 SVM (Support Vector Machine)과 Gradient boosting 기법을 이용하였으며, 딥러닝으로는 시계열 분석에 사용되는 RNN (Recurrent Neural Network) 중 LSTM (Long Short-Term Memory) 네트워크을 이용하여 수위 예측 분석을 수행하였다. 성능지표로는 수문분석에 주로 사용되는 상관계수와 NSE (Nash-Sutcliffe Efficiency)를 이용하였다. 분석결과 세 기법 모두 강우에 따른 수위예측을 우수하게 수행하였다. 이 중, LSTM 네트워크는 과거데이터를 이용한 보정기간이 늘어날수록 더욱 높은 성능을 보여주었다. 우리나라의 집중호우와 같은 긴급 재난이 우려되는 상황 시 수위예측은 빠른 판단을 요구한다. 비교적 간편한 데이터를 이용하여 수위예측이 가능한 AI 기반 기법을 적용할 시 위의 요구사항을 충족할 것이라 사료된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.148-148
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• 2022

Spatiotemporal precipitation data is one of the primary quantities in hydrological as well as climatological studies. Despite the fact that the estimation of these data has made considerable progress owing to advances in remote sensing, the discrepancy between satellite-derived precipitation product (SPP) data and observed data is still remarkable. This study aims to propose an effective deep learning model (DLM) for bias correction of SPPs. In which TRMM (The Tropical Rainfall Measuring Mission), CMORPH (CPC Morphing technique), and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) are three SPPs with a spatial resolution of 0.25o exploited for bias correction, and APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) data is used as a benchmark to evaluate the effectiveness of DLM. We selected the Mekong River Basin as a case study area because it is one of the largest watersheds in the world and spans many countries. The adjusted dataset has demonstrated an impressive performance of DLM in bias correction of SPPs in terms of both spatial and temporal evaluation. The findings of this study indicate that DLM can generate reliable estimates for the gridded satellite-based precipitation bias correction.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.12
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• pp.1922-1929
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• 2020

Objective: The present study aimed to survey seasonal changes in reproductive performance of local cows receiving artificial insemination (AI) in the Pursat province of Cambodia, a tropical country, to investigate if ambient conditions affect the reproductive performance of cows as to better understand the major problems regarding cattle production. Methods: The number of cows receiving AI, resultant number of calving, and calving rate were analyzed for those receiving the first AI from 2016 to 2017. The year was divided into three seasons: cool/dry (from November to February), hot/dry (from March to June), and wet (from July to October), based on the maximal temperature and rainfall in Pursat, to analyze the relationship between ambient conditions and the reproductive performance of cows. Body condition scores (BCS) and feeding schemes were also analyzed in these seasons. Results: The number of cows receiving AI was significantly higher in the cool/dry season than the wet season. The number of calving and calving rate were significantly higher in cows receiving AI in the cool/dry season compared with the hot/dry and wet seasons. The cows showed higher BCSs in the cool/dry season compared to the hot/dry and wet seasons probably due to the seasonal changes in the feeding schemes: these cows grazed on wild grasses in the cool/dry season but fed with a limited amount of grasses and straw in the hot/dry and wet seasons. Conclusion: The present study suggests that the low number of cows receiving AI, low number of calving, and low calving rate could be mainly due to poor body condition as a result of the poor feeding schemes during the hot/dry and wet seasons. The improvement of body condition by the refinement of feeding schemes may contribute to an increase in the reproductive performance in cows during the hot/dry and wet seasons in Cambodia.

• Journal of agriculture & life science
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• v.45 no.5
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• pp.97-103
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• 2011

The purpose of this study was to analyze the pollutant reduction effect for non-irrigated crop land by nonpoint source pollution control. For a field scale monitoring, 6 plots (5m width and 22m length) and 3 sediment traps were installed. At the outlet of each plot, the stage gauges were installed for runoff monitoring. For a rainfall monitoring, tipping bucket rain gage was installed within the experiment site. Through the artificial irrigation, runoff from the plots were monitored. The SS, TOC, T-N, T-P, COD, NTU of sampled water were analyzed by standard methods. The SS, TOC, T-N, T-P, COD, NTU concentration of initial runoff were 15.00, 1.54, 5.27, 0.07, 4.72, 0.45mg/L, respectively. Four hours later than the initial runoff, the concentration was changed to 1.00, 0.94, 4.06, 0.01, 0.60, 0.33 mg/L, respectively. As a result of artificial irrigation, three out of four sediment traps were filled with runoff water from the experimental plots. One sediment trap was not filled with runoff water because the artificial irrigation was not supplied for two experimental plots. The stage of sediment traps were gradually lowered. However, the water quality didn't showed a decrease trend as the stage went down because the suspended solid was not equally collected during the water sampling.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1131-1141
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• 2021

In this study, the artificial neural network model is applied for real-time dam inflow prediction and then evaluated for the prediction lead times (1, 3, 6 hr) in dam basins in Korea. For the training and testing the model, hourly precipitation and inflow are used as input data according to average annual inflow. The results show that the model performance for up to 6 hour is acceptable because the NSE is 0.57 to 0.79 or higher. Totally, the predictive performance of the model in dry seasons is weaker than the performance in wet seasons, and this difference in performance increases in the larger basin. For the 6 hour prediction lead time, the model performance changes as the sequence length increases. These changes are significant for the dry season with increasing sequence length compared to the wet season. Also, with increasing the sequence length, the prediction performance of the model improved during the dry season. Comparison of observed and predicted hydrographs for flood events showed that although the shape of the prediction hydrograph is similar to the observed hydrograph, the peak flow tends to be underestimated and the peak time is delayed depending on the prediction lead time.

• Journal of the Korean Geotechnical Society
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• v.30 no.6
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• pp.23-39
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• 2014

An artificial rainwater reservoir installed in urban areas for recycling rainwater is an eco-friendly facility for reducing storm water effluence. However, in order to recycle the rainwater directly, the artificial rainwater reservoir requires an auxiliary system that can remove non-point source pollutants included in the initial rainfall of urban area. Therefore, the conventional soil filtration technology is adopted to capture non-point source pollutants in an economical and efficient way in the purification system of artificial rainwater reservoirs. In order to satisfy such a demand, clogging characteristics of the sand filter layers with different grain-size distributions were studied with real non-point source pollutants. For this, a series of lab-scale chamber tests were conducted to make a prediction model for removal of non-point source pollutants, based on the clogging theory. The laboratory chamber experiments were carried out by permeating two types of artificially contaminated water through five different types of sand filter layers with different grain-size distributions. The two artificial contaminated waters were made by fine marine-clay particles and real non-point source pollutants collected from motorcar roads of Seoul, Korea. In the laboratory chamber experiments, the concentrations of the artificial contaminated water were measured in terms of TSS (Total Suspended Solids) and COD (Chemical Oxygen Demand) and compared with each other to evaluate the performance of sand filter layers. In addition, the accumulated weight of pollutant particles clogged in the sand filter layers was estimated. This paper suggests a prediction model for removal of non-point source pollutants with theoretical consideration of the physical characteristics such as the grain-size distribution and composition, and change in the hydraulic conductivity and porosity of sand filter layers. The lumped parameter ${\theta}$ related with the clogging property was estimated by comparing the accumulated weight of pollutant particles obtained from the laboratory chamber experiments and calculated from the prediction model based on the clogging theory. It is found that the lumped parameter ${\theta}$ has a significant influence on the amount of the pollutant particles clogged in the pores of sand filter layers. In conclusion, according to the clogging prediction model, a double-sand-filter layer consisting of two separate layers: the upper sand-filter layer with the effective particle size of 1.49 mm and the lower sand-filter layer with the effective particle size of 0.93 mm, is proposed as the optimum system for removing non-point source pollutants in the field-sized artificial rainwater reservoir.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.1
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• pp.15-29
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• 2020

Recently, the incidence of flooding in Korea has decreased by the measures by central and local governments, however the scale of damage is increasing due to the improvement of living standard. One of the causes of such flood damage is natural causes such as rainfall exceeding the planned frequency of flood control under climate change. In addition, there are artificial causes such as encroachment of river spaces and management problems in upstream basins without consideration of downstream damage potential by regional development flood. In this study, in order to reduce the inundation damage caused by flooding of river, the situation at the time of inundation damage was reproduced by the detailed topographic data and 2D numerical model. Therefore, the effect of preparing various disaster prevention measures for the lowland was simulated in advance so that quantitative evaluation could be achieved. The target area is Taehwa river basin, where flooding was caused by the flooding of river waters caused by typhoon Chaba in October 2016. As a result of rainfall-discharge and two-dimensional analysis, the simulation results agree with the observed in terms of flood depth, flood arrival time and flooded area. This study examined the applicability of hydraulic analysis on river using two-dimensional inundation model, by applying detailed topographic data and it is expected to contribute to establish of disaster prevention measures.

• Journal of the Korean Geosynthetics Society
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• v.14 no.4
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• pp.79-86
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• 2015

Korean territories has formed about 70% of mountainous areas that have acidified serious level to average pH 4-5. There are a number of abandoned metal mines about 1,000 in Korea. However, mine tailings and waste rock included heavy metals are exposed to long-term environment without prevention facility or treatment system. Thus, ongoing management and monitoring of soil environment are required. Most of abandoned mine scattered in forest areas of slopes. Soil erosion due to continuous rainfall in the slopy areas can cause the secondary pollution by the influence eutrophication of water system and the productivity loss of the plant. Therefore, this study would like to estimate pH leaching rate by artificial rainfall using waste neutralization-agent in lysimeter. Moreover, the potentially of secondary pollution related to precipitation is figured out through the experiments, and the optimal planting methods would examinate after neutralizing treatment in soil. Experiments composed three kinds of lysimeter; lysimeter 1 had filled only acidic soil, lysimeter 2 had neutralized soil, and lysimeter 3 had planting plants after neutralized soil. In the results, lysimeter 2 showed the lowest pH leaching, and there is not specific relativity with pH leaching of the seasonal characteristics.

• Research in Plant Disease
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• v.20 no.3
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• pp.196-200
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• 2014

This study was carried out to determine the effect of mixing with paraffin oil on rainfastness of mancozeb on citrus fruits and assay the improvement of control effect of mancozeb against citrus melanose by mixing with paraffin oil. In artificial rainfall condition (7.2 mm/hr), the attached contents of mancozeb on detached fruits were the most in treatment of mancozeb 0.2% + paraffin oil 0.1% as the contents was $7.43{\mu}g/cm^2$ after treatment of rainfall for 10 hr. In open field condition, the contents of attached mancozeb on fruits were significantly more in treatment of mancozeb 0.2% + paraffin oil 0.1% or 0.25% than the other treatments 1, 15 and 25 days after treatment 2009 and 2010 seasons. The disease incidence was significantly lower in treatment of mancozeb 0.2% + paraffin oil 0.1% or 0.25% than treatment of mancozeb 0.2% only 2009, 2010 and 2011 seasons. Based on this study, it was suggested that the control effect of mancozeb against citrus melanose can be improved by mixing with paraffin oil.