• Journal of Korea Water Resources Association
• /
• v.34 no.5
• /
• pp.533-542
• /
• 2001

In order to establish drought policy, the estimation of drought period for each drought situation should be preceded. Non-linear Water Balance Model(NWBM) and palmer Drought Severity Index (PDSI) can be used for analysis of drought period. As a water balance method considering moisture transfer between land surface and atmosphere, NWBM can be used to estimate transition time between dry and wet period induced by stochastic fluctuations. PDSI is also water balance method to show drought severity comparing actual precipitation with climatically appropriate precipitation based on precipitation and potential evapotranspiration. In this study, the drought periods are estimated using NWBM and PDSI for the Han River Basin. The drought periods according to the soil moisture estimated by NWBS and the drought periods according to drought severity index estimated by PDSI show similar trend. The estimated drought period from extreme drought to wet condition for the Han River Basin is about 3years.

• Journal of Wetlands Research
• /
• v.12 no.1
• /
• pp.51-61
• /
• 2010

Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, it is important to understand the spatial-temporal features of rainfall. In this study, RADAR rainfall was used to calculate gridded areal rainfall which reflects the spatial-temporal variability. In addition, Kalman-filter method, a stochastical technique, was used to combine ground rainfall network with RADAR rainfall network to calculate areal rainfall. Thiessen polygon method, Inverse distance weighting method, and Kriging method were used for calculating areal rainfall, and the calculated data was compared with adjusted areal RADAR rainfall measured using the Kalman-filter method. The result showed that RADAR rainfall adjusted with Kalman-filter method well-reproduced the distribution of raw RADAR rainfall which has a similar spatial distribution as the actual rainfall distribution. The adjusted RADAR rainfall also showed a similar rainfall volume as the volume shown in rain gauge data. Anseong-Cheon basin was used as a study area and the RADAR rainfall adjusted with Kalman-filter method was applied in $Vflo^{TM}$ model, a physical-based distributed model, and ModClark model, a semi-distributed model. As a result, $Vflo^{TM}$ model simulated peak time and peak value similar to that of observed hydrograph. ModClark model showed good results for total runoff volume. However, for verifying the parameter, $Vflo^{TM}$ model showed better reproduction of observed hydrograph than ModClark model. These results confirmed that flood runoff simulation is applicable in domestic settings(in South Korea) if highly accurate areal rainfall is calculated by combining gauge rainfall and RADAR rainfall data and the simulation is performed in link to the distributed hydrological model.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2007.05a
• /
• pp.774-779
• /
• 2007

IDF 곡선은 전통적으로 지점에서의 과거 관측 강우량 시계열 자료를 수집하여 작성하여 왔으며, 이때 과거 강우량 자료는 정상성을 지니고 있고 미래를 대변한다는 가정을 전제로 한다. 그러나 이미 많은 연구자들에 의해 기후변화가 전구적으로 발생하고 있으며 우리나라에서도 더 이상 기후변화의 사실여부는 이제 더이상 논란 꺼리가 아니다. 특히, 기후변화의 영향을 직접적으로 받을 수밖에 없는 수자원 분야에서는 1990년대부터 잦은 홍수와 가뭄의 반복으로 곤란을 겪고 있다. 특히, 우리나라는 협소한 국토면적과 과다한 인구로 토지나 수자원 등 국토자원 이용의 강도가 다른 나라에 비하여 현저하게 높기 때문에 지구온난화에 따른 기후변화와 같은 약간의 기후변동으로도 심각한 문제가 발생할 가능성이 내포되어 있다. 특히, 기후변화는 유역 규모의 강우 발생 패턴과 강우량의 증가 및 감소에 영향을 미치게 되며 이로 인해 강우 시계열 자료는 비정상성과 경향성을 지니게 된다. 그러나 지금까지는 IDF 곡선의 작성시 강우의 경향성을 무시해 왔다. 본 연구에서는 기후변화가 IDF 곡선에 미치는 영향을 분석하기 위하여 GCM 기후변화 시나리오를 이용하여 IDF 곡선을 작성하였다. 이를 위하여 먼저, YONU CGCM의 제한실험과 점증실험을 실시하여 전구적 규모의 기후변화 시나리오를 작성하였으며, 통계학적 축소기법과 추계학적 일기발생기법을 이용하여 대상지점의 일 수문기상 시계열을 모의하였다. 그리고 BLRP(Bartlett Lewis Rectangular Pulse) 모형과 분해(koutsoyiannis, 2000) 기법을 이용하여 모의된 일 강우 자료를 시자료로 분해하였으며 이를 이용하여 IDF 곡선을 작성하였다. 그 결과, 기후변화 시 지속기간별 재현기간별 강우량이 현재에 크게 비해 증가됨을 확인할 수 있었다.으며 여러명이 동시에 서버에 접속을 하기 때문에 컴퓨터에 부하가 많이 걸리는 모델링이나 복잡한 분석은 실시하기 어려우며, 대용량 데이터를 전송할 수 있는 대역폭이 확보 되어야 한다. 또한, Internet 환경으로 개발을 해야되기 때문에 데스크탑용 GIS에 비해 개발속도가 느리며 개발 초기비용이 많이 들게 된다. 하지만, 네트워크 기술의 발달과 모바일과의 연계 등으로 이러한 약점을 극복할 수 있을 것으로 판단된다. 따라서 본 논문에서는 인터넷 GIS를 이용하여 홍수재해 정보를 검색, 처리, 분석, 예경보할 수 있는 홍수방재정보 시스템을 구축토록 하였다.비해 초음파 감시하 치골상부 방광천자가 정확하고 안전한 채뇨법으로 권장되어야 한다고 생각한다.應裝置) 및 운용(運用)에 별다른 어려움이 없고, 내열성(耐熱性)이 강(强)하므로 쉬운 조건하(條件下)에서 경제적(經濟的)으로 공업적(工業的) 이용(利用)에 유리(有利)하다고 판단(判斷)되어진다.reatinine은 함량이 적었다. 관능검사결과(官能檢査結果) 자가소화(自家消化)시킨 크릴간장은 효소(酵素)처리한 것이나 재래식 콩간장에 비하여 품질 면에서 손색이 없고 저장성(貯藏性)이 좋은 크릴간장을 제조(製造)할 수 있다는 결론을 얻었다.이 있음을 확인할 수 있었다.에 착안하여 침전시 슬러지층과 상등액의 온도차를 측정하여 대사열량의 발생량을 측정하고 슬러지의 활성을 측정할 수 있는 방법을 개발하였다.enin과 Rhaponticin의 작용(作用)에 의(依)한 것이며, 이는 한의학(韓醫學) 방제(方劑) 원리(原理)인 군신좌사(君臣佐使) 이론(理論)에서 군약(君藥)이 주증(主症)에 주(主)로 작용(作用)하는 약물(藥物)이라는 것을 밝혀주는 것이라고 사료(思料)된다.일전 $13.447\;{\mu}g/hr/g$, 섭취 7일중 $8.123

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.6 no.3
• /
• pp.63-74
• /
• 1986

A methodology for the probabilistic determination of active storage capacity of an impounding reservoir is proposed with due considerations to the durations and return periods of the low flow series at the reservoir site. For more reliable probabilistic analysis the best-fit stochastic generation model of Monte Carlo type was first selected for the generation of monthly flow series, the models tested being the Month Carlo Model based on the month-by-month flow series (Monte Carlo-A Type), Monte Carlo Model based on the standardized sequential monthly flow series (Monte Carlo-B Type), and the Thomas-Fiering Model. Monte Carlo-B Model was final1y selected and synthetic monthly flows of 200 years at Hong Cheon dam site were generated. With so generated 200 years' monthly flows partial duration series of low flows were developed for various durations. Each low flow series was further processed by a nonsequential mass analysis for specified draft rates. This mass analysis furnished the storage-draft-recurrence interval relationship which gives the reservoir storage requirement for a specified water demand from the reservoir during a drought of given return period. Illustrations are given on the application of these results in analyzing the water supply capacity of a particlar reservoir, existing or proposed.

• Journal of Korea Water Resources Association
• /
• v.49 no.2
• /
• pp.155-164
• /
• 2016

Algal blooms not only destroy fish habitats but also diminish biological diversity of ecosystem which results into water quality deterioration of 4 major rivers in South Korea. The relationship between algal bloom and environmental factors had been analyzed through the cross-correlation function between concentration of chlorophyll a and other environmental factors. However, time series of cross-correlations can be affected by the stochastic structure such auto-correlated feature of other controllers. In order to remove external effect in the correlation analysis, the pre-whitening procedure was implemented into the cross correlation analysis. The modeling process is consisted of a series of procedure (e.g., model identification, parameter estimation, and diagnostic checking of selected models). This study provides the exclusive correlation relationship between algae concentration and other environmental factors. The difference between the conventional correlation using raw data and that of pre-whitened series was discussed. The process implemented in this paper is useful not only to identify exclusive environmental variables to model Chl-a concentration but also in further extensive application to configure causality in the environment.

• Journal of Korean Society on Water Environment
• /
• v.28 no.1
• /
• pp.38-49
• /
• 2012

In this study, we analyze statistical characteristics of influent water quality in Daejeon waste water treatment plant and apply a stochastic model for data generation. In the analysis, the influent water quality data from year 2003 to 2008, except for year 2006, are used. Among water quality variables, we find strong correlations between BOD and T-N; T-N and T-P; BOD and T-P; $COD_{Mn}$ and T-P; and BOD and $COD_{Mn}$. We also find that different water quality variables follow different theoretical probability distribution functions, which also depends on whether the seasonal cycle is removed. Finally, we generate the influent water quality data using the multi-season 1st Markov model (Thomas-Fiering model). With model parameters calibrated for the period 2003~2005, the generated data for 2007~2008 are well compared with observed data showing good agreement in general. BOD and T-N are underestimated by the stochastic model. This is mainly due to the statistical difference in observed data itself between two periods of 2003~2005 and 2007~2008. Therefore, we expect the stochastic model can be applied with more confidence in the case that the data follows stationary pattern.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.10 no.1
• /
• pp.81-88
• /
• 2010

The analysis and synthesis of various types of hydrologic variables such as precipitation, surface runoff, and discharge are usually required in planning and management of water resources. These hydrologic variables are mostly represented using stochastic models. One of which is the autoregressive model, that gives promising results in time series modeling. This study is an application of this model, which aimed to determine the AR model that best represents the historical monthly streamflow of the two gauging stations, namely Andong Dam and Imha Dam, both located in the upper Nakdong River Basin. AR(3) model was found to be the best model for both gauging stations. Parameters of the determined order of AR model ($\phi_1$, $\phi_2$ and $\phi_3$) were also estimated. Using several diagnostic tests, the efficiency of the determined AR(3) model was tested. These tests indicated the accuracy of the determined AR(3) model.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.1B
• /
• pp.21-27
• /
• 2011

When execute runoff forecasting, can not remove perfectly uncertainty of forecasting results. But, reduce uncertainty by various techniques analysis. This study applied various forecasting techniques for runoff prediction's accuracy elevation in Gongju basin. statics techniques is ESP, Period Average & Moving average, Exponential Smoothing, Winters, Auto regressive moving average process. Authoritativeness estimation with results of runoff forecasting by each techniques used MAE (Mean Absolute Error), RMSE (Root Mean Squared Error), RRMSE (Relative Root Mean Squared Error), Mean Absolute Percentage Error (MAPE), TIC (Theil Inequality Coefficient). Result that use MAE, RMSE, RRMSE, MAPE, TIC and confirm improvement effect of runoff forecasting, ESP techniques than the others displayed the best result.

• Water for future
• /
• v.21 no.1
• /
• pp.77-86
• /
• 1988

The main objective of this paper is to study the application of runs to the analysis of hydrologic data. The stochastic structure of annual hydrologic data is investigated using the statistical properties of run-length for various truncation levels. Observed relative frequencies of run-length at each station are copared with the calculated and approched to the calculated. Also, it can be shown to estimate the durations of wet and dry years by the probabilities of run-length for a given truncation level. Annual precipitation data were obtained from the stations where have relatively long records, and stream flow data were generated by Markov model. The results of hypothesis test with run-lengths show independence of annual hydrologic series and Markov model can be applied to generate annual stream flow at Hyunpung, Waekwan and Gyuam.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.16 no.5
• /
• pp.29-39
• /
• 2012

The main objective is to predict the future degradation and maintenance budget for a suspension bridge system. Bayesian inference is applied to find the posterior probability density function of the source parameters (damage indices and serviceability), given ten years of maintenance data. The posterior distribution of the parameters is sampled using a Markov chain Monte Carlo method. The simulated risk prediction for decreased serviceability conditions are posterior distributions based on prior distribution and likelihood of data updated from annual maintenance tasks. Compared with conventional linear prediction model, the proposed quadratic model provides highly improved convergence and closeness to measured data in terms of serviceability, risky factors, and maintenance budget for bridge components, which allows forecasting a future performance and financial management of complex infrastructures based on the proposed quadratic stochastic regression model.