• 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.E
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• pp.47-58
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• 1990

Abstract A regionalized daily streamflow model using a modified retention parameter in the SCS method was developed to predict the daily streamflow of a natural series for Korean watersheds. Model verification showed that it is possible to use the model for extending short period records in a gaged watershed or for predicting daily streamflow in any ungaged watershed, with reasonable accuracy by simply inputing the name of the watershed boundary, the watershed size, the latitude and longitude of the watershed, and the daily areal rainfall.

• Journal of Korean Society of Disaster and Security
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• v.8 no.1
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• pp.21-27
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• 2015

Recent researches show that climate change has impact on the rainfall process at different temporal and spatial scales. The present paper is focused on climate change impact on sub-daily rainfall quantile of Han River basin in South Korea. Climate change simulation outputs from ECHO-G GCM under the A2 scenario were used to estimate daily extreme rainfall. Sub-daily extreme rainfall was estimated using the scale invariance concept. In order to assess sub-daily extreme rainfall from climate change simulation outputs, precipitation time series were generated based on NSRPM (Neyman-Scott Rectangular Pulse Model) and modified using the ratio of rainfall over projection periods to historical one. Sub-daily extreme rainfall was then estimated from those series. It was found that sub-daily extreme rainfall in the future displayed increasing or decreasing trends for estimation methods and different periods.

• Water for future
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• v.10 no.1
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• pp.79-94
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• 1977

This study is aimed at the establishment and examination of stochastic model to simulate Run-length and Run-sum of daily rainfall and streamflow. In the analysis, daily rainfall records in major cities (Seoul, Kangnung, Taegu, Kwangju, Busan, and Cheju) and daily streamflow records of Major rivers (Han, Nakdong and Geum River) were used. Also, the fitness of daily rainfall and streamflow to Weibull and one parameter exponential distribution was tested by Chi-square and Kolmogorov-Smirnov test, from which it was found that daily rainfall and streamflow generally fit well to exponential type distribution function. The Run-length and Run-sum were simulated by the Weibull Model (WBL Model), one parameter exponential model (EXP-1 Model) based on the Nonte Carlo technique. In this result, Run-length of rainfall was fitted for one parameter exponential model and Run-length of streamflow was fitted for Weibull model. And Run-sum of rainfall and streamflow were fit comparatively for regression model. Hereby, statistical charactristics of Simulation data were sinilar to historical data.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.943-947
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• 2005

This study was intended to interpose an objection about the analysis of rainfall spatial distribution without a proper standard, and offer the improved approach using 1,he geostatistical analysis method to analyze it. For this, spatially distributed daily rainfall data sets were collected for 41 weather stations in study area, and variogram and correlation analysis were conducted. In the results of correlation analysis, it was found that the longer distance between the stations reduces the correlation of the rainfall data, and maltes the characteristics of the rainfall spatial distribution. The variogram analysis shows that correlation range was less than 50 km for the 17 daily rainfall data sets of total 91 sets. It says that it involves some rike, to determine the application method for rainfall spatial distribution without some qualifications, hence the Application standards of the Rainfall Spatial Distribution Analysis Technique, were essential and that was contingent on characteristics of rainfall and landscape.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2223-2235
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• 2013

This study aimed to understand temporal and spatial trends of rainfall characteristics in South and North Korea. Daily rainfall observed at the 65 stations in South Korea between 1963 and 2010 and the 27 stations in North Korea between 1973 and 2010 were analyzed. Rainfall Indicators for amount, extremes, frequency of rainfall were defined. Province-based indicators in the recent 10 years (i.e., between 2001 and 2010) were compared to those in the past (i.e., between 1963/1973 and 2000 for South/North Korea). In the recent 10 years, all the indicators except for the number of wet days (NWD) and 200-yr frequency rainfall (Freq200) increased in South Korea and all the indicators except for the annual mean daily rainfall over wet days (SDII) and annual total rainfall amount (TotalDR) decreased in North Korea. Furthermore, we performed the Mann-Kendall trend test based on the annual indicators. In some stations, decreasing trends in the past and increasing trends in the recent 10 years were found, and such opposite trends between two periods suggest he limitation in predicting and analyzing the rainfall characteristics based on the average. Results from this study can be used in analyzing the impact of climate change and preparing adaptation strategies for the water resources management.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.135-135
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• 2021

In water resources management, rainfall prediction with high accuracy is still one of controversial issues particularly in countries facing heavy rainfall during wet seasons in the monsoon climate. The aim of this study is to develop an artificial neural network (ANN) for predicting future six months of rainfall data (from April to September 2020) from daily meteorological data (from 1971 to 2019) such as rainfall, temperature, wind speed, and humidity at Seoul, Korea. After normalizing these data, they were trained by using a multilayer perceptron (MLP) as a class of the feedforward ANN with 15,000 neurons. The results show that the proposed method can analyze the relation between meteorological datasets properly and predict rainfall data for future six months in 2020, with an overall accuracy over almost 70% and a root mean square error of 0.0098. This study demonstrates the possibility and potential of MLP's applications to predict future daily rainfall patterns, essential for managing flood risks and protecting water resources.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.617-625
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• 1999

Global warming has begun since the industrial revolution and it is getting worse recently. Even though the increase of greenhouse gases such as $CO_2$ is thought to be the main cause for global warming, its impact on global climate has not been revealed clearly in rather quantitative manners. However, researches using General Circulation Models(GCMs) has shown the accumulation of greenhouse gases increases the global mean temperature, which in turn impacts on the global water circulation pattern. This changes in global water circulation pattern result in abnormal and more frequent meteorological events such as severe floods and droughts, generally more severe than the normal ones, which are now common around the world and is referred as a indirect proof of global warming. Korean peninsula also cannot be an exception and have had several extremes recently. The main objective of this research is to analyze the impact of global warming on the change of flood and drought frequency. Based on the assumption that now is a point in a continuously changing climate due to global warming, we analyzed the observed daily rainfall data to find out how the increase of annual rainfall amount affects the distribution of daily rainfall. Obviously, the more the annual rainfall depth, the more frequency of much daily rainfall, and vice versa. However, the analysis of the 17 points data of Keum river basin in Korea shows that especially the number of days of under 10mm or over 50mm daily rainfall depth is highly correlated with the amount of annual rainfall depth, not the number of dry days with their correlation coefficients quite high around 0.8 to 0.9.

• Journal of Korean Society on Water Environment
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• v.26 no.4
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• pp.648-653
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• 2010

Discharged pollution load for the management of Total Maximum Daily Loads (TMDLs) is calculated on the basis of rainfall data for reference year. Rainfall has an influence on discharged pollution load in unit watershed with combined sewer system. This study reviewed the status of discharged pollution load and rainfall conditions. We also investigated rainfall effects on discharged pollution load by analyzing change of the load in accordance with increase of rainfall. The change ratio of discharged pollution load was 18.6% while inflow load only 5.8% for 5 years from 2004 to 2008 in Daejeon district. The greatest rainfall and rain days were over 2 times than the least during the period. This change in rainfall could have great effect on discharged pollution load. The analysis showed that discharged pollution load increased 2.1 times in case rainfall increased 2 times and 1.2 times in case rain days increased 2 times. Rainfall effects, therefore, should be considered to make resonable evaluation of discharged pollution load in the assessment of annual performances.

• Journal of the Korean Statistical Society
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• v.35 no.4
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• pp.355-376
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• 2006

To identify whether the sequence of observations follows a chain dependent process and whether the chain dependent or repeated observations follow stationary process or not, alternative procedures are suggested in this paper. These test procedures are formulated on the basis of logistic regression model under the likelihood ratio test criterion and applied to the daily rainfall occurrence data of Bangladesh for selected stations. These test procedures indicate that the daily rainfall occurrences follow a chain dependent process, and the different types of transition probabilities and overall transition probabilities of Markov chain for the occurrences of rainfall follow a stationary process in the Mymensingh and Rajshahi areas, and non-stationary process in the Chittagong, Faridpur and Satkhira areas.