• 대한토목학회논문집
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• 제6권3호
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• pp.31-42
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• 1986

본(本) 연구(硏究)는 장래(將來) 예상(豫想)되는 유역내(流域內)의 수자원(水資源) 수요문제(需要問題)에 대처(對處)하여 수자원(水資源)의 기초(基礎)가 되는 강수(降水)를 공간적(空間的)으로 모의발생(模擬發生)(Simulation)하기 위한 모델을 개발(開發)한 것으로서, 유역(流域)의 중심(中心) 관측소(觀測所)인 기간관측소(基幹觀測所)와 그 주변의 준기간(準基幹) 관측소간(觀測所間)의 강수현상(降水現像)에 대(對)한 공간적(空間的) 확률구조(確率構造)로부터 준기간(準基幹) 관측소(觀測所)의 강수계열(降水系列)를 모의발생(模擬發生)하였다. 섬진강 유역(流域)을 대상(對象)으로 기간(基幹) 관측소(觀測所)로는 하동(河東)을 택(擇)하고 준기간(準基幹) 관측소(觀測所)로는 임실, 보성, 순창, 동복, 구례를 택(擇)하여 강수(降水)의 공간적(空間的) 모의발생(模擬發生) 모델을 검토(檢討)하였으며 얻어진 성과(成果)를 요약(要約)하면 다음과 같다. 1) 강수상태(降水狀態)의 공간적(空間的) 분리(分離)는 강수상태별(降水狀態別)(강수(降水)-강수계(降水系), 무강수(無降水)-강수계(降水系), 강수(降水)-무강수계(無降水系), 무강수(無降水)-무강수계(無降水系)) 발생확률(發生確率)이 안정(安定)된 값을 보여 공간적(空間的) 모의발생시(模擬發生時) 유효(有効)한 방법(方法)임을 알았다. 2) 기간(基幹) 관측소(觀測所)의 일강수계열(日降水系列)로부터 모의발생(模擬發生)한 준기간(準基幹) 관측소(觀測所)의 일강수계열(日降水系列)은 연평균(年平均) 강수량(降水量)의 경우(境遇) 관측치(觀測値)와 비슷한 결과(結果)를 보였으나, 하계(夏季)의 강수량(降水量)은 약간(若干) 과소(過少)하게 나타났다. 3) 준기간(準基幹) 관측소(觀測所)의 월강수량(月降水量)에 대한 Correlogram과 Power Spectrum은 관측표본(觀測標本)과 잘 맞고 있어 주기성(周期性)의 재현(再現)은 충분(充分)한 것으로 생각된다.

• 대기
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• 제24권2호
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• pp.159-171
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• 2014

This study investigated the temporal and spatial characteristics of summertime (June-August) precipitation over Korean peninsula, using Korea Meteorological Administration (KMA)is Automated Synoptic Observing System (ASOS) data for the period of 1973-2010 and Automatic Weather System (AWS) data for the period of 1998-2010.The authors looked through climatological features of the summertime precipitation, then examined the degree of locality of the precipitation, and probable precipitation amount and its return period of 100 years (i.e., an extreme precipitation event). The amount of monthly total precipitation showed increasing trends for all the summer months during the investigated 38-year period. In particular, the increasing trends were more significant for the months of July and August. The increasing trend of July was seen to be more attributable to the increase of precipitation intensity than that of frequency, while the increasing trend of August was seen to be played more importantly by the increase of the precipitation frequency. The e-folding distance, which is calculated using the correlation of the precipitation at the reference station with those at all other stations, revealed that it is August that has the highest locality of hourly precipitation, indicating higher potential of localized heavy rainfall in August compared to other summer months. More localized precipitation was observed over the western parts of the Korean peninsula where terrain is relatively smooth. Using the 38-years long series of maximum daily and hourly precipitation as input for FARD2006 (Frequency Analysis of Rainfall Data Program 2006), it was revealed that precipitation events with either 360 mm $day^{-1}$ or 80 mm $h^{-1}$ can occur with the return period of 100 years over the Korean Peninsula.

• 대한토목학회논문집
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• 제14권3호
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• pp.509-521
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• 1994

본 연구는 간헐 수문과정인 일 강수계열의 모의발생 모델을 개발한 것으로서, 일 강수계열의 구조적 특성인 강수발생과정과 습윤일의 강수량과정을 고려하였다. 본 연구는 두편이 논문으로 구성되어 있으며, 연구(I)에서는 강수발생과정을 위하여 고대재생과정(ARP)을 이용하였으며, 건조 습윤계속기간 분포에 대해서는 TBD, TPD, TNBD, LSD의 4가지 이산형 확률분포를 적용하였다. 후속논문인 연구(II)에서는 강수발생과정으로 Markov 연쇄모델을 이용한다. 그리고 습윤일의 강수량 분포에 대해서는 Gamma 분포, Pearson Type-III 분포, Type-III 극치분포, 3모수 Weibull 분포의 4가지 연속형 확률분포를 적용하였다. 연구(I)에서는 낙동강 유역의 대구, 고령, 밀양, 영주 관측소 및 섬진강 유역의 하동, 순창, 구례 관측소의 일 강수계열 자료를 사용하였으며, 강수발생과정과 습윤일의 강수량과정을 조합하여 구성한 두가지의 일 강수계열 모의발생 모델 A-W, A-G 모델의 적용성을 확인하였다.

• 산업경영시스템학회지
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• 제33권3호
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• pp.162-168
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• 2010

Information is known to be a key element for the successful operation of a supply chain, which is required of the efficient ordering strategies and accurate predictions of demands. This study proposes a method to effectively utilize the meteorological forecast information in order to make decisions about ordering and prediction of demands by using the Taguchi experimental design. It is supposed that each echelon in a supply chain determines the order quantity with the prediction of precipitation in the next day based on probability forecast information. The precipitation event is predicted when the probability of the precipitation exceeds a chosen threshold. Accordingly, the choice of the threshold affect the performances of a supply chain. The Taguchi method is adopted to deduce a set of thresholds for echelons which is least sensitive to changes in environmental conditions, such as variability of demand distributions and production periods. A simulation of the beer distribution game was conducted to show that the set of thresholds found by the Taguchi method can reduce the cumulative chain cost, which consists of inventory and backlog costs.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2001년도 학술발표회 발표논문집
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• pp.314-318
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• 2001

The analysis of the spatial extent of flood inundation is important for flood mitigation. Geographic Information System (GIS) has advantage of analyzing spatial distributed data. Hydrologic Engineering Center's River Analsysis System(HEC-RAS) with HEC-GeoRAS was used to analyze flood inundation. HEC-GeoRAS, which is an ArcView GIS extension designed to process geospatial data for HEC-RAS, is a useful tool for storing, managing, analyzing, and displaying spatially distributed data. Rational formula and 24-hr duration probability precipitation data of Suwon meteorological station were used to estimate the flood runoff. And water profiles were calculated using the HEC-RAS model with HEC-GeoRAS. The flooded region is 8.24ha when 50-yr probability precipitation was applied and 8.8ha when 100-yr was applied to Bahlan study watershed which is located in Whasung county, Kyunggi province, having an area of $29.79km^{2}$.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2006년도 학술발표회 논문집
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• pp.51-56
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• 2006

Biases embedded in numerical weather precipitation forecasts by the RDAPS model was determined, quantified and corrected. The ultimate objective is to eventually enhance the reliability of reservoir operation by Korean Water Resources Corporation (KOWACO), which is based on precipitation-driven forecasts of stream flow. Statistical post-processing, so called MOS (Model Output Statistics) was applied to RDAPS to improve their performance. The Artificial Neural Nwetwork (ANN) model was applied for 4 cases of 'Probability of Precipitation (PoP) for wet and dry season' and 'Quantitative Precipitation Forecasts (QPF) for wet and dry season'. The reduction on the large systematic bias was especially remarkable. The performance of both networks may be improved by retraining, probably every month. In addition, it is expected that performance of the networks will improve once atmospheric profile data are incorporated in the analysis. The key to the optimal performance of ANN is to have a large data set relevant to the predictand variable. The more complex the process to be modeled by the ANN, the larger the data set needs to be.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.226-226
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• 2015

The complex climate system regarding human actions is well represented through global climate models (GCMs). The output from GCMs provides useful information about the rate and magnitude of future climate change. Especially, the temperature variable is most reliable among other GCM outputs. However, hydrological variables (e.g. precipitation) from GCM outputs for future climate change contain too high uncertainty to use in practice. Therefore, we propose a method that simulates temperature variable with increasing in a certain level (e.g. 0.5oC or 1.0oC increase) as a global warming scenario from observed data. In addition, a hydrometeorological variable can be simulated employing block-wise sampling technique associated with the temperature simulation. The proposed method was tested for assessing the future change of the seasonal precipitation in South Korea under global warming scenario. The results illustrate that the proposed method is a good alternative to levy the variation of hydrological variables under global warming condition.

• 한국농공학회논문집
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• 제54권6호
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• pp.39-44
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• 2012

Water supply capacity and operational capability in agricultural reservoirs are expressed differently in the limited storage due to seasonal and local variation of precipitation. Since agricultural water supply and demand basically assumes the uncertainty of hydrological phenomena, it is necessary to improve probabilistic approach for potential risk assessment of water supply capacity in reservoir for enhanced operational storage management. Here, it was introduced the irrigation vulnerability characteristic curves to represent the water supply capacity corresponding to probability distribution of the water demand from the paddy field and water supply in agricultural reservoir. Irrigation vulnerability probability was formulated using reliability analysis method based on water supply and demand probability distribution. The lower duration of irrigation vulnerability probability defined as the time period requiring intensive water management, and it will be considered to assessment tools as a risk mitigated water supply planning in decision making with a limited reservoir storage.

• 한국농공학회논문집
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• 제58권3호
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• pp.57-69
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• 2016

In this study, we analyzed the extreme rainfall distribution scenarios based on probable rainfall calculation and applying various time distribution models over the landslide high risk zones in urban areas. We used observed rainfall data form total 71 ASOS (Automated Synoptic Observing System) station and AWS (Automatic Weather Station) in KMA (Korea Meteorological Administration), and we analyzed the linear trends for 1-hr and 24-hr annual maximum rainfall series using simple linear regression method, which are identified their increasing trends with slopes of 0.035 and 0.660 during 1961-2014, respectively. The Gumbel distribution was applied to obtain the return period and probability precipitation for each duration. The IDF (Intensity-Duration-Frequency) curves for landslide high risk zones were derived by applying integrated probability precipitation intensity equation. Results from IDF analysis indicate that the probability precipitation varies from 31.4~38.3 % for 1 hr duration, and 33.0~47.9 % for 24 hr duration. It also showed different results for each area. The $Huff-4^{th}$ Quartile method as well as Mononobe distribution were selected as the rainfall distribution scenarios of landslide high risk zones. The results of this study can be used to provide boundary conditions for slope collapse analysis, to analyze sediment disaster risk, and to use as input data for risk prediction of debris flow.

• 대기
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• 제30권2호
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• pp.141-154
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• 2020

Seasonal forecast is growing in demand, as it provides valuable information for decision making and potential to reduce impact on weather events. This study examines how operational climate prediction systems can be reliable, producing the probability forecast in seasonal scale. A reliability diagram was used, which is a tool for the reliability by comparing probabilities with the corresponding observed frequency. It is proposed for a method grading scales of 1-5 based on the reliability diagram to quantify the reliability. Probabilities are derived from ensemble members using hindcast data. The analysis is focused on skill for 2 m temperature and precipitation from climate prediction systems in KMA, UKMO, and ECMWF, NCEP and JMA. Five categorizations are found depending on variables, seasons and regions. The probability forecast for 2 m temperature can be relied on while that for precipitation is reliable only in few regions. The probabilistic skill in KMA and UKMO is comparable with ECMWF, and the reliabilities tend to increase as the ensemble size and hindcast period increasing.