• Title/Summary/Keyword: 호우규모

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Development of Domestic Rainwater Treatment System and its Application in the Field (소규모 빗물처리시설 개발 및 현장 적용성 평가 연구)

  • Pak, Gijung;Park, Minseung;Kim, Hwansuk;Lim, Yoonsoo;Kim, Sungpyo
    • Journal of Wetlands Research
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    • v.18 no.1
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    • pp.24-31
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    • 2016
  • The increase of impervious area in cities caused the unbalanced water cycle system and the accumulated various contaminants, which make troubles as introducing into watershed. In Korea, most of rainfall in a year precipitate in a summer season. This indicate that non-point source pollution control should be more important in summer and careful rainfall reuse strategy is necessary. Accordingly, the aim of this study is to monitor the characteristics of rainfall contaminants harvested in roofs and to develop the rainfall treatment system which are designed to fit well in a typical domestic household including rain garden. The rain garden consists of peatmoss, gravel and san to specially treat the initial rainfall contaminants. For this purpose, lab scale experiments with synthetic rainfall had been conducted to optimize the removal efficiency of TN, TP and CODcr. After lab scale experiments, field scale rainfall treatment system installed as a pilot scale in a field. This system has been monitored during June to July in 2015 in four time rainfall events as investigating the function of time, rainfall, and pollutant concentrations. As results, high loading of pollutants were introduced to the rainfall treatment system and its removal efficiency is increased as increase of pollutant concentrations. Since it is common that the mega-size of rainfall treatment system is not attractive in urban area, small scale rainfall treatment system is promising to treat the non-point source contaminants from cities. In addition, this small scale rainfall treatment system could have a potential to water resue system in islands, which usually suffer the shortage of water.

Case study on flood water level prediction accuracy of LSTM model according to condition of reference hydrological station combination (참조 수문관측소 구성 조건에 따른 LSTM 모형 홍수위예측 정확도 검토 사례 연구)

  • Lee, Seungho;Kim, Sooyoung;Jung, Jaewon;Yoon, Kwang Seok
    • Journal of Korea Water Resources Association
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    • v.56 no.12
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    • pp.981-992
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    • 2023
  • Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.

Analysis of Stability Indexes for Lightning by Using Upper Air Observation Data over South Korea (남한에서 낙뢰발생시 근접 고층기상관측 자료를 이용한 안정도 지수 분석)

  • Eom, Hyo-Sik;Suh, Myoung-Seok
    • Atmosphere
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    • v.20 no.4
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    • pp.467-482
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    • 2010
  • In this study, characteristics of various stability indexes (SI) and environmental parameters (EP) for the lightning are analysed by using 5 upper air observatories (Osan, Gwangju, Jeju, Pohang, and Baengnyeongdo) for the years 2002-2006 over South Korea. The analysed SI and EP are the lifted index, K-index, Showalter stability index, total precipitable water, mixing ratio, wind shear and temperature of lifting condensation level. The lightning data occurred on the range of -2 hr~+1 hr and within 100 km based on the launch time of rawinsonde and observing location are selected. In general, summer averaged temperature and mixing ratio of lower troposphere for the lightning cases are higher about 1 K and $1{\sim}2gkg^{-1}$ than no lightning cases, respectively. The Box-Whisker plot shows that the range of various SI and EP values for lightning and no lightning cases are well separated but overlapping of SI and EP values between lightning and no lightning are not a little. The optimized threshold values for the detection of lightning are determined objectively based on the highest Heidke skill socre (HSS), which is the most favorable validation parameter for the rare event, such as lightning, by using the simulation of SI and EP threshold values. Although the HSS is not high (0.15~0.30) and the number and values of selected SI and EP are dependent on geographic location, the new threshold values can be used as a supplementary tool for the detection or forecast of lightning over South Korea.

Climate Change Impact on Nonpoint Source Pollution in a Rural Small Watershed (기후변화에 따른 농촌 소유역에서의 비점오염 영향 분석)

  • Hwang, Sye-Woon;Jang, Tae-Il;Park, Seung-Woo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.8 no.4
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    • pp.209-221
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    • 2006
  • The purpose of this study is to analyze the effects of climate change on the nonpoint source pollution in a small watershed using a mid-range model. The study area is a basin in a rural area that covers 384 ha with a composition of 50% forest and 19% paddy. The hydrologic and water quality data were monitored from 1996 to 2004, and the feasibility of the GWLF (Generalized Watershed Loading function) model was examined in the agricultural small watershed using the data obtained from the study area. As one of the studies on climate change, KEI (Korea Environment Institute) has presented the monthly variation ratio of rainfall in Korea based on the climate change scenario for rainfall and temperature. These values and observed daily rainfall data of forty-one years from 1964 to 2004 in Suwon were used to generate daily weather data using the stochastic weather generator model (WGEN). Stream runoff was calibrated by the data of $1996{\sim}1999$ and was verified in $2002{\sim}2004$. The results were determination coeff, ($R^2$) of $0.70{\sim}0.91$ and root mean square error (RMSE) of $2.11{\sim}5.71$. Water quality simulation for SS, TN and TP showed $R^2$ values of 0.58, 0.47 and 0.62, respectively, The results for the impact of climate change on nonpoint source pollution show that if the factors of watershed are maintained as in the present circumstances, pollutant TN loads and TP would be expected to increase remarkably for the rainy season in the next fifty years.

A Study on Process Optimization for CSOs Application of Horizontal Flow Filtration Technology (수평흐름식 여과기술의 CSOs 적용을 위한 공정 최적화 연구)

  • Kim, Jae-Hak;Yang, Jeong-Ha;Lee, Young-Shin
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.2
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    • pp.56-63
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    • 2018
  • The management of Combined Sewer Overflows(CSOs) and Separated Sewer Overflows(SSOs) discharge directly to the effluent system in an untreated state, which occurs when the facility capacity is exceeded due to heavy rain, has become an important issue in recent years as the heavy rain becomes a regular phenomenon. Despite the continuous development of filtration technology, targeting densely populated urban areas, CSOs are rarely applied. Therefore, this study was carried out to optimize the process to apply CSOs in a pilot-scale horizontal flow filtration system with a rope-type synthetic fiber. The research was carried out in two steps: a preliminary study using artificial samples and a field study using sewage. In the preliminary study using an artificial sample, head loss of the filter media itself was analyzed to be approximately 1.1cm, and the head loss was increased by approximately 0.1cm as the linear velocity was increased by 10m/hr. In addition, the SS removal efficiency was stable at 81.4%, the filtration duration was maintained for more than 6 hours, and the average recovery rate of 98% was obtained by air backwashing only. In the on-site evaluation using sewage, the filtration duration was approximately 2 hours and the average removal efficiency of 83.9% was obtained when belt screen (over 450 mesh) was applied as a pre-treatment process to prevent the premature clogging of filter media. To apply the filtration process to CSOs and SSOs, it was concluded that the combination with the pre-treatment process was important to reinforce the hydraulic dimension for the stable maintain of operation period, rather than efficiency. Compared to the dry season, the quality of incoming sewage was lower in the rainy season, which was attributed to the characteristics of the drainage area with higher sanitary sewerage. In addition, the difference in removal efficiency according to the influent quality of the wet season and dry season was small.

Evaluation of Temperature and Precipitation over CORDEX-EA Phase 2 Domain using Regional Climate Model HadGEM3-RA (HadGEM3-RA 지역기후모델을 이용한 CORDEX 동아시아 2단계 지역의 기온과 강수 모의 평가)

  • Byon, Jae-Young;Kim, Tae-Jun;Kim, Jin-Uk;Kim, Do-Hyun
    • Journal of the Korean earth science society
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    • v.43 no.3
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    • pp.367-385
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    • 2022
  • This study evaluates the temperature and precipitation results in East Asia simulated from the Hadley Centre Global Environmental Model version 3 regional climate model (HadGEM3-RA) developed by the UK Met Office. The HadGEM3-RA is conducted in the Coordinated Regional climate Downscaling Experiment-East Asia (CORDEX-EA) Phase II domain for 15 year (2000-2014). The spatial distribution of rainbands produced from the HadGEM3-RA by the summer monsoon is in good agreement with the Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of water resources (APRODITE) data over the East Asia. But, precipitation amount is overestimated in Southeast Asia and underestimated over the Korean Peninsula. In particular, the simulated summer rainfall and APRODITE data show the least correlation coefficient and the maximum value of root mean square error in South Korea. Prediction of temperature in Southeast Asia shows underestimation with a maximum error during winter season, while it appears the largest underestimation in South Korea during spring season. In order to evaluate local predictability, the time series of temperature and precipitation compared to the ASOS data of the Seoul Meteorological Station is similar to the spatial average verification results in which the summer precipitation and winter temperature underestimate. Especially, the underestimation of the rainfall increases when the amounts of precipitation increase in summer. The winter temperature tends to underestimate at low temperature, while it overestimates at high temperature. The results of the extreme climate index comparison show that heat wave is overestimated and heavy rainfall is underestimated. The HadGEM3-RA simulated with a horizontal resolution of 25 km shows limitations in the prediction of mesoscale convective system and topographic precipitation. This study indicates that improvement of initial data, horizontal resolution, and physical process are necessary to improve predictability of regional climate model.