• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.579-587
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• 2010

The mid-range streamflow forecast was performed using NWP(Numerical Weather Prediction) provided by KMA. The NWP consists of RDAPS for 48-hour forecast and GDAPS for 240-hour forecast. To enhance the accuracy of the NWP, QPM to downscale the original NWP and Quantile Mapping to adjust the systematic biases were applied to the original NWP output. The applicability of the suggested streamflow prediction system which was verified in Geum River basin. In the system, the streamflow simulation was computed through the long-term continuous SSARR model with the rainfall prediction input transform to the format required by SSARR. The RQPM of the 2-day rainfall prediction results for the period of Jan. 1~Jun. 20, 2006, showed reasonable predictability that the total RQPM precipitation amounts to 89.7% of the observed precipitation. The streamflow forecast associated with 2-day RQPM followed the observed hydrograph pattern with high accuracy even though there occurred missing forecast and false alarm in some rainfall events. However, predictability decrease in downstream station, e.g. Gyuam was found because of the difficulties in parameter calibration of rainfall-runoff model for controlled streamflow and reliability deduction of rating curve at gauge station with large cross section area. The 10-day precipitation prediction using GQPM shows significantly underestimation for the peak and total amounts, which affects streamflow prediction clearly. The improvement of GDAPS forecast using post-processing seems to have limitation and there needs efforts of stabilization or reform for the original NWP.

• Journal of Environmental Impact Assessment
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• v.22 no.1
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• pp.39-50
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• 2013

Occurrence of landslides has been increasing due to extreme weather events(e.g. heavy rainfall, torrential rains) by climate change. Pyeongchang, Korea had seriously been damaged by landslides caused by a typhoon, Ewiniar in 2006. Moreover, the frequency and intensity of landslides are increasing in summer due to torrential rain. Therefore, risk assessment and adaptation measure is urgently needed to build resilience. To support landslide adaptation measures, this study predicted landslides occurrence using MaxEnt model and suggested susceptibility map of landslides. Precipitation data of RCP 8.5 Climate change scenarios were used to analyze an impact of increase in rainfall in the future. In 2050 and 2090, the probability of landslides occurrence was predicted to increase. These were due to an increase in heavy rainfall and cumulative rainfall. As a result of analysis, factors that has major impact on landslide appeared to be climate factors, prediction accuracy of the model was very high(92%). In the future Pyeongchang will have serious rainfall compare to 2006 and more intense landslides area expected to increase. This study will help to establish adaptation measure against landslides due to heavy rainfall.

• Atmosphere
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• v.26 no.1
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• pp.97-109
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• 2016

Heavy rainfall (over $80mm\;hr^{-1}$) system associated with unstable atmospheric conditions occurred over the Seoul metropolitan area on 27 July 2011. To investigate the heavy rainfall system, we used three-dimensional data from Korea Local Analysis and Prediction System (KLAPS) reanalysis data and analysed the structure of the precipitation system, kinematic characteristics, thermodynamic properties, and Meteorological condition. The existence of Upper-Level Jet (ULJ) and Low-Level Jet (LLJ) are accelerated the heavy rainfall. Convective cloud developed when a strong southwesterly LLJ and strong moisture convergence occurring around the time of the heavy rainfall is consistent with the results of previous studies on such continuous production. Environmental conditions included high equivalent potential temperature of over 355 K at low levels, and low equivalent potential temperature of under 330 K at middle levels, causing vertical instability. The tip of the band shaped precipitation system was made up of line-shaped convective systems (LSCSs) that caused flooding and landslides, and the LSCSs were continuously enhanced by merging between new cells and the pre-existing cell. Difference of wind direction between low and middle levels has also been considered an important factor favouring the occurrence of precipitation systems similar to LSCSs. Development of LSCs from the wind direction difference at heights of the severe precipitation occurrence area was also identified. This study can contribute to the identification of production and development mechanisms of heavy rainfall and can be used in applied research for prediction of severe weather.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1142-1146
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• 2009

A rainfall simulation and forecasting technique that can generate daily rainfall sequences conditional on multi-model ensemble GCMs is developed and applied to data in Korea for the major rainy season. The GCM forecasts are provided by APEC climate center. A Weather State Based Downscaling Model (WSDM) is used to map teleconnections from ocean-atmosphere data or key state variables from numerical integrations of Ocean-Atmosphere General Circulation Models to simulate daily sequences at multiple rain gauges. The method presented is general and is applied to the wet season which is JJA(June-July-August) data in Korea. The sequences of weather states identified by the EM algorithm are shown to correspond to dominant synoptic-scale features of rainfall generating mechanisms. Application of the methodology to seasonal rainfall forecasts using empirical teleconnections and GCM derived climate forecast are discussed.

• Environmental Engineering Research
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• v.22 no.2
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• pp.162-168
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• 2017

Rainfall is one of the most important phenomena of the natural system. In Bangladesh, agriculture largely depends on the intensity and variability of rainfall. Therefore, an early indication of possible rainfall can help to solve several problems related to agriculture, climate change and natural hazards like flood and drought. Rainfall forecasting could play a significant role in the planning and management of water resource systems also. In this study, univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to forecast monthly rainfall for twelve months lead-time for thirty rainfall stations of Bangladesh. The best SARIMA model was chosen based on the RMSE and normalized BIC criteria. A validation check for each station was performed on residual series. Residuals were found white noise at almost all stations. Besides, lack of fit test and normalized BIC confirms all the models were fitted satisfactorily. The predicted results from the selected models were compared with the observed data to determine prediction precision. We found that selected models predicted monthly rainfall with a reasonable accuracy. Therefore, year-long rainfall can be forecasted using these models.

• Korean Journal of Hydrosciences
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• v.3
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• pp.97-104
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• 1992

To design the minor structures in the small watersheds, it is required to calculate the peak discharge. For these calculations the simple peak flow prediction equations, the unit hydrograph method. the syntheic unit hydrograph methods or the runoff simulation models are adopted. To use these methods it is generally requried to know the amount and the distributions of the design rainfall; which are the uniform distribution, the trangular distribution, the trapezoidal distribution, or the Huff type distribution. In this study, the peak discharges are calculated by the different rainfall distributions and the results are compared.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.224-224
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• 2015

The East Asia monsoon is one of the most complex atmospheric phenomena caused by Land-Sea thermal contrast. It plays essential role in fulfilling the water needs of the region but also poses stern consequences in terms of flooding and droughts. This study analyzed the influence of Global Sea Surface Temperature Anomalies (SSTA) on occurrence of droughts in the East Asia monsoon region ($20^{\circ}N-50^{\circ}N$, $103^{\circ}E-149^{\circ}E$). Standardized Precipitation Index (SPI) was employed to characterize the droughts over the region using 30-year (1978-2007) gridded rainfall dataset at $0.5^{\circ}$ grid resolution. Due to high variability in intensity and spatial extent of monsoon rainfall the East Asia monsoon region was divided into the homogeneous rainfall zones using cluster analysis method. Seven zones were delineated that showed unique rainfall regimes over the region. The influence of SSTA was assessed by using lagged-correlation between global gridded SSTA ($0.2^{\circ}$ grid resolution) and SPI of each zone. Sea regions with potential influence on droughts in different zones were identified based on significant positive and negative correlation between SSTA and SPI with a lag period of 3-month. The results showed that SSTA have the potential to be used as predictor variables for prediction of droughts with a reasonable lead time. The findings of this study will assist to improve the drought prediction over the region.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.5
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• pp.813-821
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• 2000

The engineering of satellite communication systems at frequencies above 10GHz requires a method for estimating rain-caused outage probabilities on the earth-satellite path. A procedure for predicting a rain attenuation distribution from a point rainfall rate distribution is, therefore, needed. In order to predict rain attenuation on the satellite link, several prediction models such as ITU-R, Global, SAM, DAH model, have been developed and used at a particular propagation condition, they may not be appropriate to a propagation condition in Korean territory. In this paper, a new rain attenuation prediction method appropriate to a propagation condition in Korea is introduced. Based on the results from ETRI measurements, a new method has been derived for an empirical approach with an identification on the horizontal correction factor as in current ITU-R method, and the vertical correction factor has been suggested with decreasing power law as a function of rainfall rate. This proposed model uses the entire rainfall rate distribution as input to the model, while the ITU-R and DAH model approaches only use a single 0.01% annual rainfall rate and assume that the attenuation at other probability levels can be determined from that single point distribution. This new model was compared with several world-wide prediction models. Based on the analysis, we can easily know the importance of the model choice to predict rain attenuation for a particular location in the radio communication system design.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.448-451
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• 2005

This paper presents the methodology to analyze flow duration characteristics and performance prediction for small hydro power(SHP) plants and its application. The flow duration curvecan be decided by using monthly rainfall data at the most of the SHP sites with no useful hydrological data. It was proved that the monthly rainfall data can be characterized by using the cumulative density function of Weibull distribution and Thiessen method were adopted to decide flow duration curve at SHP plants. And, the performance prediction has been studied and development. One SHP plant was selected and performance characteristics was analyzed by using the developed technique. Primary design specfications such as design flowrate, plant capacity, operational rate and annual electricity production for the SHP plant were estimated. It was found that the methodology developed in this study can be a useful tool to predict the performance of SHP plants and candidate sites in Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.2 no.3
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• pp.43-56
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• 1982

A recursive algorithms for prediction of streamflows by Kalman filtering theory and Self-tuning predictor based on the state space description of the dynamic systems have been studied and the applicabilities of the algorithms to the rainfall-runoff processes have been investigated. For the representation of the dynamics of the processes, a low-order ARMA process has been taken as the linear discrete time system with white Gaussian disturbances. The state vector in the prediction model formulated by a random walk process. The model structures have been determined by a statistical analysis for residuals of the observed and predicted streamflows. For the verification of the prediction algorithms developed here, the observed historical data of the hourly rainfall and streamflows were used. The numerical studies shows that Kalman filtering theory has better performance than the Self-tuning predictor for system identification and prediction in rainfall-runoff processes.