• 제목/요약/키워드: Rainfall Station

검색결과 403건 처리시간 0.037초

확률분포에 의한 지속기간 및 빈도별 가뭄우량 추정 (Estimation of Drought Rainfall According to Consecutive Duration and Return Period Using Probability Distribution)

  • 이순혁;맹승진;류경식
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2004년도 학술발표회
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    • pp.1103-1106
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    • 2004
  • The objective of this study is to induce the design drought rainfall by the methodology of L-moment including testing homogeneity, independence and outlier of the data of annual minimum monthly rainfall in 57 rainfall stations in Korea in terms of consecutive duration for 1, 2, 4, 6, 9 and 12 months. To select appropriate distribution of the data for annual minimum monthy rainfall by rainfall station, the distribution of generalized extreme value (GEV), generalized logistic (GLO) as well as that of generalized pareto (GPA) are applied and the appropriateness of the applied GEV, GLO, and GPA distribution is judged by L-moment ratio diagram and Kolmogorov-Smirnov (K-S) test. As for the annual minimum monthly rainfall measured by rainfall station and that stimulated by Monte Carlo techniques, the parameters of the appropriately selected GEV and GPA distributions are calculated by the methodology of L-moment and the design drought rainfall is induced. Through the comparative analysis of design drought rainfall induced by GEV and GPA distribution by rainfall station, the optimal design drought rainfall by rainfall station is provided.

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Appropriate identification of optimum number of hidden states for identification of extreme rainfall using Hidden Markov Model: Case study in Colombo, Sri Lanka

  • Chandrasekara, S.S.K.;Kwon, Hyun-Han
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2019년도 학술발표회
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    • pp.390-390
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    • 2019
  • Application of Hidden Markov Model (HMM) to the hydrological time series would be an innovative way to identify extreme rainfall events in a series. Even though the optimum number of hidden states can be identify based on maximizing the log-likelihood or minimizing Bayesian information criterion. However, occasionally value for the log-likelihood keep increasing with the state which gives false identification of the optimum hidden state. Therefore, this study attempts to identify optimum number of hidden states for Colombo station, Sri Lanka as fundamental approach to identify frequency and percentage of extreme rainfall events for the station. Colombo station consisted of daily rainfall values between 1961 and 2015. The representative station is located at the wet zone of Sri Lanka where the major rainfall season falls on May to September. Therefore, HMM was ran for the season of May to September between 1961 and 2015. Results showed more or less similar log-likelihood which could be identified as maximum for states between 4 to 7. Therefore, measure of central tendency (i.e. mean, median, mode, standard deviation, variance and auto-correlation) for observed and simulated daily rainfall series was carried to each state to identify optimum state which could give statistically compatible results. Further, the method was applied for the second major rainfall season (i.e. October to February) for the same station as a comparison.

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수문지역별 최적확률강우강도추정모형의 재정립 -영.호남 지역을 중심으로 - (Estimation Model for Optimum Probabilistic Rainfall Intensity on Hydrological Area - With Special Reference to Chonnam, Buk and Kyoungnam, Buk Area -)

  • 엄병헌;박종화;한국헌
    • 한국농공학회지
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    • 제38권2호
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    • pp.108-122
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    • 1996
  • This study was to introduced estimation model for optimum probabilistic rainfall intensity on hydrological area. Originally, probabilistic rainfall intensity formula have been characterized different coefficient of formula and model following watersheds. But recently in korea rainfall intensity formula does not use unionize applyment standard between administration and district. And mingle use planning formula with not assumption model. Following the number of year hydrological duration adjust areal index. But, with adjusting formula applyment was without systematic conduct. This study perceive the point as following : 1) Use method of excess probability of Iwai to calculate survey rainfall intensity value. 2) And, use method of least squares to calculate areal coefficient for a unit of 157 rain gauge station. And, use areal coefficient was introduced new probabilistic rainfall intensity formula for each rain gauge station. 3) And, use new probabilistic rainfall intensity formula to adjust a unit of fourteen duration-a unit of fifteen year probabilistic rainfall intensity. 4) The above survey value compared with adjustment value. And use three theory of error(absolute mean error, squares mean error, relative error ratio) to choice optimum probabilistic rainfall intensity formula for a unit of 157 rain gauge station.

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기후변화 시나리오를 고려한 제주도 확률강우량 산정 (Estimation of Design Rainfall Based on Climate Change Scenario in Jeju Island)

  • 이준호;양성기;정우열;양원석
    • 한국환경과학회지
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    • 제24권4호
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    • pp.383-391
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    • 2015
  • As occurrence of gradually increasing extreme temperature events in Jeju Island, a hybrid downscaling technique that simultaneously applies by dynamical method and statistical method has implemented on design rainfall in order to reduce flood damages from severe storms and typhoons.As a result of computation, Case 1 shows a strong tendency to excessively compute rainfall, which is continuously increasing. While Case 2 showed similar trend as Case 1, low design rainfall has computed by rainfall in A1B scenario. Based on the design rainfall computation method mainly used in Preventive Disaster System through Pre-disaster Effect Examination System and Basic Plan for River of Jeju Island which are considering climatic change for selecting 50-year and 100-year frequencies. Case 3 selecting for Jeju rain gage station and Case 1 for Seogwipo rain gage station. The results were different for each rain gage station because of difference in rainfall characteristics according to recent climatic change, and the risk of currently known design rainfall can be increased in near future.

Rainfall Trend Detection Using Non Parametric Test in the Yom River Basin, Thailand

  • Mama, Ruetaitip;Bidorn, Butsawan;Namsai, Matharit;Jung, Kwansue
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2017년도 학술발표회
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    • pp.424-424
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    • 2017
  • Several studies of the world have analyzed the regional rainfall trends in large data sets. However, it reported that the long-term behavior of rainfall was different on spatial and temporal scales. The objective of this study is to determine the local trends of rainfall indices in the Yom River Basin, Thailand. The rainfall indices consist of the annual total precipitation (PRCTPOP), number of heavy rainfall days ($R_{10}$), number of very heavy rainfall days ($R_{20}$), consecutive of dry days (CDD), consecutive of wet days (CWD), daily maximum rainfall ($R_{x1}$), five-days maximum rainfall ($R_{x5}$), and total of annual rainy day ($R_{annual}$). The rainfall data from twelve hydrological stations during the period 1965-2015 were used to analysis rainfall trend. The Mann-Kendall test, which is non-parametric test was adopted to detect trend at 95 percent confident level. The results of these data were found that there is only one station an increasing significantly trend in PRCTPOP index. CWD, which the index is expresses longest annual wet days, was exhibited significant negative trend in three locations. Meanwhile, the significant positive trend of CDD that represents longest annual dry spell was exhibited four locations. Three out of thirteen stations had significant decreasing trend in $R_{annual}$ index. In contrast, there is a station statistically significant increasing trend. The analysis of $R_{x1}$ was showed a station significant decreasing trend at located in the middle of basin, while the $R_{x5}$ of the most locations an insignificant decreasing trend. The heavy rainfall index indicated significant decreasing trend in two rainfall stations, whereas was not notice the increase or decrease trends in very heavy rainfall index. The results of this study suggest that the trend signal in the Yom River Basin in the half twentieth century showed the decreasing tendency in both of intensity and frequency of rainfall.

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마산지방 확률강우강도식의 유도 (Derivation of Probable Rainfall Intensity Formula at Masan District)

  • 김지홍;배덕효
    • 한국습지학회지
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    • 제2권1호
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    • pp.49-58
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    • 2000
  • The frequency analysis of annual maximum rainfall data and the derivation of probable rainfall intensity formula at Masan station are performed in this study. Based on the eight different rainfall duration data from 10 minutes to 24 hours, eight types of probability distribution (Gamma, Lognormal, Log-Pearson type III, GEV, Gumbel, Log-Gumbel, Weibull, and Wakeby distributions), three types of parameter estimation scheme (moment, maximum likelihood and probability weighted methods) and three types of goodness-of-fit test (${\chi}^2$, Kolmogorov-Smirnov and Cramer von Mises tests) were considered to find an appropriate probability distribution at Masan station. The Lognormal-2 distribution was selected and the probable rainfall intensity formula was derived by regression analysis. The derived formula can be used for estimating rainfall quantiles of the Masan vicinity areas with convenience and reliability in practice.

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빗물펌프장에 설치된 인공습지의 비점오염원 저감효율 연구 (A Study of Non-point Source Reduction Efficiency by Constructed Wetland installed in Flood Pumping Station)

  • 천석영;김지태;이일국;장순웅
    • 환경영향평가
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    • 제23권1호
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    • pp.67-74
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    • 2014
  • The aim of this study was evaluated the effects of total rainfall, rainfall intensity and antecedent dry days and identify the correlation analysis with the EMC removal efficiency, in order to provide an understanding of the operation and maintenance factors of constructed wetland in flood pumping station. This study was conducted total of 20 monitoring in a catchment(326.2 ha) of constructed wetland in Ga-un flood pumping station located at the downstream of the Wang-suk stream. The determined EMC removal efficiencies were $36.04{\pm}9.45%$ for BOD, $38.50{\pm}13.50%$ for $COD_{Mn}$, $34.34{\pm}13.05%$ for TN and $34.22{\pm}14.27%$ for TP, respectively. These results showed that the pollutants concentration and EMC were reduced while passing through the constructed wetland. In the correlation analysis, the highly correlations with EMC removal efficiency of BOD and $COD_{Mn}$ were observed for total rainfall and rainfall intensity (P<0.05). However, the correlations were not found with TN and TP for rainfall variables.

미계측 지역에서 토석류 유발강우의 산정을 위한 레이더 강우의 활용에 대한 연구 (A Study on Use of Radar Rainfall for Rainfall-Triggered Mud-Debris Flows at an Ungauged Site)

  • 전환돈;이지호;김수전
    • 한국물환경학회지
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    • 제32권3호
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    • pp.310-317
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    • 2016
  • It has been a big problem to estimate rainfall for the studies of mud-debris flows because the estimated rainfall from the nearest AWS (Automatic Weather Station) can tend to be quite inaccurate at individual sites. This study attempts to improve this problem through accurate rainfall depth estimation by applying an artificial neural network with radar rainfall data. For this, three models were made according to utilizing methodologies of rainfall data. The first model uses the nearest rainfall, observing the site from an ungauged site. The second uses only radar rainfall data and the third model integrates the above two models using both radar and observed rainfall at the sites around the ungauged site. This methodology was applied to the metropolitan area in Korea. It appeared as though the third model improved rainfall estimations by the largest margin. Therefore, the proposed methodology can be applied to forecast mud-debris flows in ungageed sites.

제주지방(濟州地方)의 확률강우강도식(確率降雨强度式) 유도(誘導) (Derivation of Probable Rainfall-Intensity Formula in the Cheju Districts)

  • 김철순;임병대;김운중;표영평
    • 대한토목학회논문집
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    • 제13권2호
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    • pp.183-190
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    • 1993
  • 강우현상은 지역별로 그 특성이 다르고, 장기간을 관측하여 보면 강우특성도 전에 비해서 많이 변화하므로 보다 정확한 배수계획의 수립이나 수공구조물계획을 위해서는 그 지역의 최근의 관측자료까지 포함한 강우특성을 연구하여 적용하는 것이 바람직하다. 따라서 제주지방의 주요 우량관측소(제주시, 서귀포, 성산포)의 최근 20년간(年間)의 자기우량기록지에서 연최대(年最大) 강우량만을 골라서 우량지속기간별로 실측우량을 발췌하였으며, 강우강도식은 일반적으로 많이 사용하고 있는 Talbot형(型), Sherman형(型), Japanese형(型)에다 새로운 Semi-log형(型)을 추가해서 제주지방의 지역별 최적확률 강우강도식을 유도해 본 결과 제주시는 확률년이 3년(年)~5년(年)에는 Japanese형(型), 그 외는 Talbot형(型)이고, 서귀포는 Sherman형(型), 성산포는 Talbot형(型)으로 나타났다.

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Optimize rainfall prediction utilize multivariate time series, seasonal adjustment and Stacked Long short term memory

  • Nguyen, Thi Huong;Kwon, Yoon Jeong;Yoo, Je-Ho;Kwon, Hyun-Han
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2021년도 학술발표회
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    • pp.373-373
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    • 2021
  • Rainfall forecasting is an important issue that is applied in many areas, such as agriculture, flood warning, and water resources management. In this context, this study proposed a statistical and machine learning-based forecasting model for monthly rainfall. The Bayesian Gaussian process was chosen to optimize the hyperparameters of the Stacked Long Short-term memory (SLSTM) model. The proposed SLSTM model was applied for predicting monthly precipitation of Seoul station, South Korea. Data were retrieved from the Korea Meteorological Administration (KMA) in the period between 1960 and 2019. Four schemes were examined in this study: (i) prediction with only rainfall; (ii) with deseasonalized rainfall; (iii) with rainfall and minimum temperature; (iv) with deseasonalized rainfall and minimum temperature. The error of predicted rainfall based on the root mean squared error (RMSE), 16-17 mm, is relatively small compared with the average monthly rainfall at Seoul station is 117mm. The results showed scheme (iv) gives the best prediction result. Therefore, this approach is more straightforward than the hydrological and hydraulic models, which request much more input data. The result indicated that a deep learning network could be applied successfully in the hydrology field. Overall, the proposed method is promising, given a good solution for rainfall prediction.

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