• Journal of Korean Society of Environmental Engineers
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• v.39 no.12
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• pp.723-732
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• 2017

As the development of ICT technology, in order to solve the problem of scattered water information's availability, WINS(Water management Information Networking System) by the Ministry of Land, Infrastructure and Transport was established and has been operated since 2004. However, there has been a disadvantage of providing specialized and limited information to the water resources sector mainly and a lack of active sharing of information because of no compulsory provision of information sharing between participants. In order to solve these problems, this paper carried out system development study, to do this, the status of domestic water information was surveyed and domestic and overseas related systems were compared and analyzed. The latest ICT technology was used to realize the contents as screen, and the user interface definition was created to present a role model of integrated water management through maximizing visualization by combining GIS and realtime data and providing space-time integrated information. These prior studies reached to actual construction of the ICT-based integrated management system for water information by K-water. This system is in service to the public installed in the water information portal, "MyWater".

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.211-216
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• 2016

Worldwide casualties caused by earthquakes, floods, fire or other disaster has been increasing. So many researchers are being actively done technical studies to ensure golden-time. In this paper if a disaster occurs, use the IoT technologies in order to secure golden-time and transmits the message after to find the user of the accident area first. When the previous job is finished, gradually finds a user of the surrounding area and transmits the message. For national emergency information, OPEN API of Korea Meteorological Administration was used. To collect detailed information on a relevant area in real time, this study established the system that connects and integrates Crowd Sensing technology with BLE (Bluetooth Low Energy) Beacon technology. Up to now, the CBS based on base station has been applied. However, this study designed and mapped DB in the integration of Beacon based user positioning and national administrative address system in order to estimate local users. In this experiment, the accuracy and speed of information dif6fusion algorithm were measured with a rise in the number of users. The experiments were conducted in a manner that increases the number of users by one thousand and was measured the accuracy and speed of the message spread transfer algorithm. Finally, became operational in less than one second in 20,000 users, it was confirmed that the notification message is sent.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.381-381
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• 2017

수자원 분야에 대한 기후변화의 영향은 홍수, 가뭄 등 극치 수문사상의 증가와 변동성 확대를 초래하는 것으로 알려져 있으며, 이에 따라 예년에 비해 발생빈도 및 심도가 증가한 가뭄에 대한 모니터링 및 피해경감을 위해 정부에서는 국민안전처를 비롯한 관계기관 합동으로 생활 공업 농업용수 등 분야별 가뭄정보를 제공하고 있다. 국토교통부와 환경부는 생활 및 공업용수 분야의 가뭄정보 제공을 위해 광역 지방 상수도를 이용하는 급수 지역과 마을상수도, 소규모급수시설 등 미급수지역의 용수수급 정보를 분석하여 가뭄 분석정보를 제공 중에 있다. 하지만, 미급수지역에 대한 가뭄 예?경보는 기준이 되는 수원정보의 부재로 기상 가뭄지수인 SPI6를 이용하여 정보를 생산하고 있다. 기상학적 가뭄 상황과 물부족에 의한 체감 가뭄은 차이가 있으며, 미급수 지역의 경우 지하수를 주 수원으로 사용하는 지역이 대부분으로 기상학적 가뭄지수인 SPI6를 이용한 가뭄정보로 실제 물수급 상황을 반영하기는 부족한 실정이다. 따라서 본 연구에서는 미급수지역의 주요 수원인 지하수의 수위 상황을 반영한 가뭄모니터링 기법을 개발하고자 하였으며, 가용량 분석이 현실적으로 어려운 지하수의 특성을 고려하여 수위 거동의 통계적 분석을 통해 가뭄을 모니터링 할 수 있는 방법으로 접근하였다. 국가지하수관측소 중 관측기간이 10년 이상이고 강우와의 상관성이 높은 관측소들을 선정한 후, 일수위 관측자료를 월별로 분리하여 1월~12월 각 월에 대해 핵밀도 함수 추정기법(kernel densitiy estimation)을 적용하여 월별 지하수위 분포 특성을 도출하였다. 각 관측소별 관측수위 분포에 대해 백분위수(percentile)를 이용하여, 25%~100% 사이는 정상, 10%~25% 사이는 주의단계, 5%~10% 사이는 심한가뭄, 5% 이하는 매우심함으로 가뭄의 단계를 구분하였다. 각 백분위수에 해당하는 수위 값은 추정된 Kernel Density와 Quantile Function을 이용하여 산정하였고, 최근 10일 평균수위를 현재의 수위로 설정하여 가뭄의 정도를 분류하였다. 분석된 결과는 관측소를 기점으로 역거리가중법(inverse distance weighting)을 통해 공간 분포를 시켰으며, 수문학적, 지질학적 동질성을 반영하기 위하여 유역도 및 수문지질도를 중첩한 공간연산을 통해 전국 지하수 가뭄상태를 나타내는 지하수위 등급분포도를 작성하였다. 실제 가뭄상황과의 상관성을 분석하기 위해 언론기사를 통해 확인된 가뭄시기와 백문위수 25%이하로 분석된 지하수 가뭄시기를 ROC(receiver operation characteristics) 분석을 통해 비교 검증하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.213-213
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• 2020

최근 나타나는 지구온난화와 이상기후로 인해 가뭄과 홍수피해 같은 자연재해 발생 빈도가 높아졌고, 하천에서는 오염된 수질과 수생태계 복원 및 수변공간 조성, 수자원 관리 등의 목적으로 수질환경 개선사업이 진행되고 있다. 수질환경 측면에서 하천에서 발생하는 가장 큰 문제점으로는 녹조 즉, 남조류의 발생을 예로 들 수 있다. 본 연구에서는 최근 보 개방을 통하여 수질개선 효과가 나타나고 있는 금강을 대상으로 세종보, 공주보, 백제보 구간에 대하여 주요 수질인자에 대한 상관관계 분석을 수행하였다. 특히 남조류 세포수와 주요 하천 수질인자를 Pearson's correlation analysis를 이용하여 상관관계를 분석하였고, 보 위치별 남조류 세포수를 종속변수로 하고, 상관도가 높은 수질인자를 독립변수로 하는 다중회귀식을 도출하여 금강 내 주요 하천 수질인자의 농도에 따른 남조류 세포수 관계를 규명하고자 하였다. 분석기간은 2012년 1월부터 2019년 12월까지 보 건설 이후 시점으로 선정하였고, 월 평균 남조류 개체수가 조류경보제 발령기준 관심단계이상에 해당하는 금강수계의 3개 보에 대하여 남조류 세포수와 수질에 영향을 끼치는 인자인 강수량, (수온)W·T, (수소이온농도)pH, (용존산소)DO, (생물화학적산소요구량)BOD, (화학적산소요구량)COD, (부유물질량)SS, (총질소)TN, (총인)TP, (클로로필-a)Chl-a, (전기전도도)EC, (질산성질소)NO₃-N, (암모니아성 질소)NH₃-N, (인산염 인)PO₄-P, (용존총질소)DTN, (용존총인)DTP, (총유기탄소)TOC 와의 상관관계를 분석하였다. 분석 결과 측정 지점별 남조류 세포수와 상관관계가 있는 인자는 서로 상이했지만 (수온)W·T과 pH의 경우 모든 지점에서 남조류 세포수와 양의 상관관계가 나타났다. 세종보는 W·T(0.383, P<0.01), pH(0.391, P<0.05)의 양의 상관계수를 나타냈고, 공주보에서는 (수온)W·T(0.436, P<0.05), pH(0.412, P<0.05)의 양의 상관관계를 나타냈다. 백제보에서는 (수온)W·T(0.415, P<0.01), pH(0.221, P<0.01)의 양의 상관성을 나타냈다. 남조류 세포수와 수질인자 간의 상관관계 분석에 따라 통계적으로 유의한 인자 중 (수온)W·T과 pH에 영향을 받는 영양염류와 퇴적물에 대한 후속 연구가 필요할 것으로 사료되며, 연구를 통해 제시된 남조류 세포수 다중회귀식은 주요 수질인자 농도에 따라 발생 가능한 남조류세포수를 예측하여 금강의 수질 관리에 활용될 수 있을 것으로 기대된다.

• Journal of Korea Water Resources Association
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• v.47 no.4
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• pp.371-384
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• 2014

This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship ($Z=303R^{0.72}$) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.75-89
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• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.311-323
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• 2023

In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.